Annotation of imach/src/imach.c, revision 1.271
1.271 ! brouard 1: /* $Id: imach.c,v 1.270 2017/05/24 05:45:29 brouard Exp $
1.126 brouard 2: $State: Exp $
1.163 brouard 3: $Log: imach.c,v $
1.271 ! brouard 4: Revision 1.270 2017/05/24 05:45:29 brouard
! 5: *** empty log message ***
! 6:
1.270 brouard 7: Revision 1.269 2017/05/23 08:39:25 brouard
8: Summary: Code into subroutine, cleanings
9:
1.269 brouard 10: Revision 1.268 2017/05/18 20:09:32 brouard
11: Summary: backprojection and confidence intervals of backprevalence
12:
1.268 brouard 13: Revision 1.267 2017/05/13 10:25:05 brouard
14: Summary: temporary save for backprojection
15:
1.267 brouard 16: Revision 1.266 2017/05/13 07:26:12 brouard
17: Summary: Version 0.99r13 (improvements and bugs fixed)
18:
1.266 brouard 19: Revision 1.265 2017/04/26 16:22:11 brouard
20: Summary: imach 0.99r13 Some bugs fixed
21:
1.265 brouard 22: Revision 1.264 2017/04/26 06:01:29 brouard
23: Summary: Labels in graphs
24:
1.264 brouard 25: Revision 1.263 2017/04/24 15:23:15 brouard
26: Summary: to save
27:
1.263 brouard 28: Revision 1.262 2017/04/18 16:48:12 brouard
29: *** empty log message ***
30:
1.262 brouard 31: Revision 1.261 2017/04/05 10:14:09 brouard
32: Summary: Bug in E_ as well as in T_ fixed nres-1 vs k1-1
33:
1.261 brouard 34: Revision 1.260 2017/04/04 17:46:59 brouard
35: Summary: Gnuplot indexations fixed (humm)
36:
1.260 brouard 37: Revision 1.259 2017/04/04 13:01:16 brouard
38: Summary: Some errors to warnings only if date of death is unknown but status is death we could set to pi3
39:
1.259 brouard 40: Revision 1.258 2017/04/03 10:17:47 brouard
41: Summary: Version 0.99r12
42:
43: Some cleanings, conformed with updated documentation.
44:
1.258 brouard 45: Revision 1.257 2017/03/29 16:53:30 brouard
46: Summary: Temp
47:
1.257 brouard 48: Revision 1.256 2017/03/27 05:50:23 brouard
49: Summary: Temporary
50:
1.256 brouard 51: Revision 1.255 2017/03/08 16:02:28 brouard
52: Summary: IMaCh version 0.99r10 bugs in gnuplot fixed
53:
1.255 brouard 54: Revision 1.254 2017/03/08 07:13:00 brouard
55: Summary: Fixing data parameter line
56:
1.254 brouard 57: Revision 1.253 2016/12/15 11:59:41 brouard
58: Summary: 0.99 in progress
59:
1.253 brouard 60: Revision 1.252 2016/09/15 21:15:37 brouard
61: *** empty log message ***
62:
1.252 brouard 63: Revision 1.251 2016/09/15 15:01:13 brouard
64: Summary: not working
65:
1.251 brouard 66: Revision 1.250 2016/09/08 16:07:27 brouard
67: Summary: continue
68:
1.250 brouard 69: Revision 1.249 2016/09/07 17:14:18 brouard
70: Summary: Starting values from frequencies
71:
1.249 brouard 72: Revision 1.248 2016/09/07 14:10:18 brouard
73: *** empty log message ***
74:
1.248 brouard 75: Revision 1.247 2016/09/02 11:11:21 brouard
76: *** empty log message ***
77:
1.247 brouard 78: Revision 1.246 2016/09/02 08:49:22 brouard
79: *** empty log message ***
80:
1.246 brouard 81: Revision 1.245 2016/09/02 07:25:01 brouard
82: *** empty log message ***
83:
1.245 brouard 84: Revision 1.244 2016/09/02 07:17:34 brouard
85: *** empty log message ***
86:
1.244 brouard 87: Revision 1.243 2016/09/02 06:45:35 brouard
88: *** empty log message ***
89:
1.243 brouard 90: Revision 1.242 2016/08/30 15:01:20 brouard
91: Summary: Fixing a lots
92:
1.242 brouard 93: Revision 1.241 2016/08/29 17:17:25 brouard
94: Summary: gnuplot problem in Back projection to fix
95:
1.241 brouard 96: Revision 1.240 2016/08/29 07:53:18 brouard
97: Summary: Better
98:
1.240 brouard 99: Revision 1.239 2016/08/26 15:51:03 brouard
100: Summary: Improvement in Powell output in order to copy and paste
101:
102: Author:
103:
1.239 brouard 104: Revision 1.238 2016/08/26 14:23:35 brouard
105: Summary: Starting tests of 0.99
106:
1.238 brouard 107: Revision 1.237 2016/08/26 09:20:19 brouard
108: Summary: to valgrind
109:
1.237 brouard 110: Revision 1.236 2016/08/25 10:50:18 brouard
111: *** empty log message ***
112:
1.236 brouard 113: Revision 1.235 2016/08/25 06:59:23 brouard
114: *** empty log message ***
115:
1.235 brouard 116: Revision 1.234 2016/08/23 16:51:20 brouard
117: *** empty log message ***
118:
1.234 brouard 119: Revision 1.233 2016/08/23 07:40:50 brouard
120: Summary: not working
121:
1.233 brouard 122: Revision 1.232 2016/08/22 14:20:21 brouard
123: Summary: not working
124:
1.232 brouard 125: Revision 1.231 2016/08/22 07:17:15 brouard
126: Summary: not working
127:
1.231 brouard 128: Revision 1.230 2016/08/22 06:55:53 brouard
129: Summary: Not working
130:
1.230 brouard 131: Revision 1.229 2016/07/23 09:45:53 brouard
132: Summary: Completing for func too
133:
1.229 brouard 134: Revision 1.228 2016/07/22 17:45:30 brouard
135: Summary: Fixing some arrays, still debugging
136:
1.227 brouard 137: Revision 1.226 2016/07/12 18:42:34 brouard
138: Summary: temp
139:
1.226 brouard 140: Revision 1.225 2016/07/12 08:40:03 brouard
141: Summary: saving but not running
142:
1.225 brouard 143: Revision 1.224 2016/07/01 13:16:01 brouard
144: Summary: Fixes
145:
1.224 brouard 146: Revision 1.223 2016/02/19 09:23:35 brouard
147: Summary: temporary
148:
1.223 brouard 149: Revision 1.222 2016/02/17 08:14:50 brouard
150: Summary: Probably last 0.98 stable version 0.98r6
151:
1.222 brouard 152: Revision 1.221 2016/02/15 23:35:36 brouard
153: Summary: minor bug
154:
1.220 brouard 155: Revision 1.219 2016/02/15 00:48:12 brouard
156: *** empty log message ***
157:
1.219 brouard 158: Revision 1.218 2016/02/12 11:29:23 brouard
159: Summary: 0.99 Back projections
160:
1.218 brouard 161: Revision 1.217 2015/12/23 17:18:31 brouard
162: Summary: Experimental backcast
163:
1.217 brouard 164: Revision 1.216 2015/12/18 17:32:11 brouard
165: Summary: 0.98r4 Warning and status=-2
166:
167: Version 0.98r4 is now:
168: - displaying an error when status is -1, date of interview unknown and date of death known;
169: - permitting a status -2 when the vital status is unknown at a known date of right truncation.
170: Older changes concerning s=-2, dating from 2005 have been supersed.
171:
1.216 brouard 172: Revision 1.215 2015/12/16 08:52:24 brouard
173: Summary: 0.98r4 working
174:
1.215 brouard 175: Revision 1.214 2015/12/16 06:57:54 brouard
176: Summary: temporary not working
177:
1.214 brouard 178: Revision 1.213 2015/12/11 18:22:17 brouard
179: Summary: 0.98r4
180:
1.213 brouard 181: Revision 1.212 2015/11/21 12:47:24 brouard
182: Summary: minor typo
183:
1.212 brouard 184: Revision 1.211 2015/11/21 12:41:11 brouard
185: Summary: 0.98r3 with some graph of projected cross-sectional
186:
187: Author: Nicolas Brouard
188:
1.211 brouard 189: Revision 1.210 2015/11/18 17:41:20 brouard
1.252 brouard 190: Summary: Start working on projected prevalences Revision 1.209 2015/11/17 22:12:03 brouard
1.210 brouard 191: Summary: Adding ftolpl parameter
192: Author: N Brouard
193:
194: We had difficulties to get smoothed confidence intervals. It was due
195: to the period prevalence which wasn't computed accurately. The inner
196: parameter ftolpl is now an outer parameter of the .imach parameter
197: file after estepm. If ftolpl is small 1.e-4 and estepm too,
198: computation are long.
199:
1.209 brouard 200: Revision 1.208 2015/11/17 14:31:57 brouard
201: Summary: temporary
202:
1.208 brouard 203: Revision 1.207 2015/10/27 17:36:57 brouard
204: *** empty log message ***
205:
1.207 brouard 206: Revision 1.206 2015/10/24 07:14:11 brouard
207: *** empty log message ***
208:
1.206 brouard 209: Revision 1.205 2015/10/23 15:50:53 brouard
210: Summary: 0.98r3 some clarification for graphs on likelihood contributions
211:
1.205 brouard 212: Revision 1.204 2015/10/01 16:20:26 brouard
213: Summary: Some new graphs of contribution to likelihood
214:
1.204 brouard 215: Revision 1.203 2015/09/30 17:45:14 brouard
216: Summary: looking at better estimation of the hessian
217:
218: Also a better criteria for convergence to the period prevalence And
219: therefore adding the number of years needed to converge. (The
220: prevalence in any alive state shold sum to one
221:
1.203 brouard 222: Revision 1.202 2015/09/22 19:45:16 brouard
223: Summary: Adding some overall graph on contribution to likelihood. Might change
224:
1.202 brouard 225: Revision 1.201 2015/09/15 17:34:58 brouard
226: Summary: 0.98r0
227:
228: - Some new graphs like suvival functions
229: - Some bugs fixed like model=1+age+V2.
230:
1.201 brouard 231: Revision 1.200 2015/09/09 16:53:55 brouard
232: Summary: Big bug thanks to Flavia
233:
234: Even model=1+age+V2. did not work anymore
235:
1.200 brouard 236: Revision 1.199 2015/09/07 14:09:23 brouard
237: Summary: 0.98q6 changing default small png format for graph to vectorized svg.
238:
1.199 brouard 239: Revision 1.198 2015/09/03 07:14:39 brouard
240: Summary: 0.98q5 Flavia
241:
1.198 brouard 242: Revision 1.197 2015/09/01 18:24:39 brouard
243: *** empty log message ***
244:
1.197 brouard 245: Revision 1.196 2015/08/18 23:17:52 brouard
246: Summary: 0.98q5
247:
1.196 brouard 248: Revision 1.195 2015/08/18 16:28:39 brouard
249: Summary: Adding a hack for testing purpose
250:
251: After reading the title, ftol and model lines, if the comment line has
252: a q, starting with #q, the answer at the end of the run is quit. It
253: permits to run test files in batch with ctest. The former workaround was
254: $ echo q | imach foo.imach
255:
1.195 brouard 256: Revision 1.194 2015/08/18 13:32:00 brouard
257: Summary: Adding error when the covariance matrix doesn't contain the exact number of lines required by the model line.
258:
1.194 brouard 259: Revision 1.193 2015/08/04 07:17:42 brouard
260: Summary: 0.98q4
261:
1.193 brouard 262: Revision 1.192 2015/07/16 16:49:02 brouard
263: Summary: Fixing some outputs
264:
1.192 brouard 265: Revision 1.191 2015/07/14 10:00:33 brouard
266: Summary: Some fixes
267:
1.191 brouard 268: Revision 1.190 2015/05/05 08:51:13 brouard
269: Summary: Adding digits in output parameters (7 digits instead of 6)
270:
271: Fix 1+age+.
272:
1.190 brouard 273: Revision 1.189 2015/04/30 14:45:16 brouard
274: Summary: 0.98q2
275:
1.189 brouard 276: Revision 1.188 2015/04/30 08:27:53 brouard
277: *** empty log message ***
278:
1.188 brouard 279: Revision 1.187 2015/04/29 09:11:15 brouard
280: *** empty log message ***
281:
1.187 brouard 282: Revision 1.186 2015/04/23 12:01:52 brouard
283: Summary: V1*age is working now, version 0.98q1
284:
285: Some codes had been disabled in order to simplify and Vn*age was
286: working in the optimization phase, ie, giving correct MLE parameters,
287: but, as usual, outputs were not correct and program core dumped.
288:
1.186 brouard 289: Revision 1.185 2015/03/11 13:26:42 brouard
290: Summary: Inclusion of compile and links command line for Intel Compiler
291:
1.185 brouard 292: Revision 1.184 2015/03/11 11:52:39 brouard
293: Summary: Back from Windows 8. Intel Compiler
294:
1.184 brouard 295: Revision 1.183 2015/03/10 20:34:32 brouard
296: Summary: 0.98q0, trying with directest, mnbrak fixed
297:
298: We use directest instead of original Powell test; probably no
299: incidence on the results, but better justifications;
300: We fixed Numerical Recipes mnbrak routine which was wrong and gave
301: wrong results.
302:
1.183 brouard 303: Revision 1.182 2015/02/12 08:19:57 brouard
304: Summary: Trying to keep directest which seems simpler and more general
305: Author: Nicolas Brouard
306:
1.182 brouard 307: Revision 1.181 2015/02/11 23:22:24 brouard
308: Summary: Comments on Powell added
309:
310: Author:
311:
1.181 brouard 312: Revision 1.180 2015/02/11 17:33:45 brouard
313: Summary: Finishing move from main to function (hpijx and prevalence_limit)
314:
1.180 brouard 315: Revision 1.179 2015/01/04 09:57:06 brouard
316: Summary: back to OS/X
317:
1.179 brouard 318: Revision 1.178 2015/01/04 09:35:48 brouard
319: *** empty log message ***
320:
1.178 brouard 321: Revision 1.177 2015/01/03 18:40:56 brouard
322: Summary: Still testing ilc32 on OSX
323:
1.177 brouard 324: Revision 1.176 2015/01/03 16:45:04 brouard
325: *** empty log message ***
326:
1.176 brouard 327: Revision 1.175 2015/01/03 16:33:42 brouard
328: *** empty log message ***
329:
1.175 brouard 330: Revision 1.174 2015/01/03 16:15:49 brouard
331: Summary: Still in cross-compilation
332:
1.174 brouard 333: Revision 1.173 2015/01/03 12:06:26 brouard
334: Summary: trying to detect cross-compilation
335:
1.173 brouard 336: Revision 1.172 2014/12/27 12:07:47 brouard
337: Summary: Back from Visual Studio and Intel, options for compiling for Windows XP
338:
1.172 brouard 339: Revision 1.171 2014/12/23 13:26:59 brouard
340: Summary: Back from Visual C
341:
342: Still problem with utsname.h on Windows
343:
1.171 brouard 344: Revision 1.170 2014/12/23 11:17:12 brouard
345: Summary: Cleaning some \%% back to %%
346:
347: The escape was mandatory for a specific compiler (which one?), but too many warnings.
348:
1.170 brouard 349: Revision 1.169 2014/12/22 23:08:31 brouard
350: Summary: 0.98p
351:
352: Outputs some informations on compiler used, OS etc. Testing on different platforms.
353:
1.169 brouard 354: Revision 1.168 2014/12/22 15:17:42 brouard
1.170 brouard 355: Summary: update
1.169 brouard 356:
1.168 brouard 357: Revision 1.167 2014/12/22 13:50:56 brouard
358: Summary: Testing uname and compiler version and if compiled 32 or 64
359:
360: Testing on Linux 64
361:
1.167 brouard 362: Revision 1.166 2014/12/22 11:40:47 brouard
363: *** empty log message ***
364:
1.166 brouard 365: Revision 1.165 2014/12/16 11:20:36 brouard
366: Summary: After compiling on Visual C
367:
368: * imach.c (Module): Merging 1.61 to 1.162
369:
1.165 brouard 370: Revision 1.164 2014/12/16 10:52:11 brouard
371: Summary: Merging with Visual C after suppressing some warnings for unused variables. Also fixing Saito's bug 0.98Xn
372:
373: * imach.c (Module): Merging 1.61 to 1.162
374:
1.164 brouard 375: Revision 1.163 2014/12/16 10:30:11 brouard
376: * imach.c (Module): Merging 1.61 to 1.162
377:
1.163 brouard 378: Revision 1.162 2014/09/25 11:43:39 brouard
379: Summary: temporary backup 0.99!
380:
1.162 brouard 381: Revision 1.1 2014/09/16 11:06:58 brouard
382: Summary: With some code (wrong) for nlopt
383:
384: Author:
385:
386: Revision 1.161 2014/09/15 20:41:41 brouard
387: Summary: Problem with macro SQR on Intel compiler
388:
1.161 brouard 389: Revision 1.160 2014/09/02 09:24:05 brouard
390: *** empty log message ***
391:
1.160 brouard 392: Revision 1.159 2014/09/01 10:34:10 brouard
393: Summary: WIN32
394: Author: Brouard
395:
1.159 brouard 396: Revision 1.158 2014/08/27 17:11:51 brouard
397: *** empty log message ***
398:
1.158 brouard 399: Revision 1.157 2014/08/27 16:26:55 brouard
400: Summary: Preparing windows Visual studio version
401: Author: Brouard
402:
403: In order to compile on Visual studio, time.h is now correct and time_t
404: and tm struct should be used. difftime should be used but sometimes I
405: just make the differences in raw time format (time(&now).
406: Trying to suppress #ifdef LINUX
407: Add xdg-open for __linux in order to open default browser.
408:
1.157 brouard 409: Revision 1.156 2014/08/25 20:10:10 brouard
410: *** empty log message ***
411:
1.156 brouard 412: Revision 1.155 2014/08/25 18:32:34 brouard
413: Summary: New compile, minor changes
414: Author: Brouard
415:
1.155 brouard 416: Revision 1.154 2014/06/20 17:32:08 brouard
417: Summary: Outputs now all graphs of convergence to period prevalence
418:
1.154 brouard 419: Revision 1.153 2014/06/20 16:45:46 brouard
420: Summary: If 3 live state, convergence to period prevalence on same graph
421: Author: Brouard
422:
1.153 brouard 423: Revision 1.152 2014/06/18 17:54:09 brouard
424: Summary: open browser, use gnuplot on same dir than imach if not found in the path
425:
1.152 brouard 426: Revision 1.151 2014/06/18 16:43:30 brouard
427: *** empty log message ***
428:
1.151 brouard 429: Revision 1.150 2014/06/18 16:42:35 brouard
430: Summary: If gnuplot is not in the path try on same directory than imach binary (OSX)
431: Author: brouard
432:
1.150 brouard 433: Revision 1.149 2014/06/18 15:51:14 brouard
434: Summary: Some fixes in parameter files errors
435: Author: Nicolas Brouard
436:
1.149 brouard 437: Revision 1.148 2014/06/17 17:38:48 brouard
438: Summary: Nothing new
439: Author: Brouard
440:
441: Just a new packaging for OS/X version 0.98nS
442:
1.148 brouard 443: Revision 1.147 2014/06/16 10:33:11 brouard
444: *** empty log message ***
445:
1.147 brouard 446: Revision 1.146 2014/06/16 10:20:28 brouard
447: Summary: Merge
448: Author: Brouard
449:
450: Merge, before building revised version.
451:
1.146 brouard 452: Revision 1.145 2014/06/10 21:23:15 brouard
453: Summary: Debugging with valgrind
454: Author: Nicolas Brouard
455:
456: Lot of changes in order to output the results with some covariates
457: After the Edimburgh REVES conference 2014, it seems mandatory to
458: improve the code.
459: No more memory valgrind error but a lot has to be done in order to
460: continue the work of splitting the code into subroutines.
461: Also, decodemodel has been improved. Tricode is still not
462: optimal. nbcode should be improved. Documentation has been added in
463: the source code.
464:
1.144 brouard 465: Revision 1.143 2014/01/26 09:45:38 brouard
466: Summary: Version 0.98nR (to be improved, but gives same optimization results as 0.98k. Nice, promising
467:
468: * imach.c (Module): Trying to merge old staffs together while being at Tokyo. Not tested...
469: (Module): Version 0.98nR Running ok, but output format still only works for three covariates.
470:
1.143 brouard 471: Revision 1.142 2014/01/26 03:57:36 brouard
472: Summary: gnuplot changed plot w l 1 has to be changed to plot w l lt 2
473:
474: * imach.c (Module): Trying to merge old staffs together while being at Tokyo. Not tested...
475:
1.142 brouard 476: Revision 1.141 2014/01/26 02:42:01 brouard
477: * imach.c (Module): Trying to merge old staffs together while being at Tokyo. Not tested...
478:
1.141 brouard 479: Revision 1.140 2011/09/02 10:37:54 brouard
480: Summary: times.h is ok with mingw32 now.
481:
1.140 brouard 482: Revision 1.139 2010/06/14 07:50:17 brouard
483: After the theft of my laptop, I probably lost some lines of codes which were not uploaded to the CVS tree.
484: I remember having already fixed agemin agemax which are pointers now but not cvs saved.
485:
1.139 brouard 486: Revision 1.138 2010/04/30 18:19:40 brouard
487: *** empty log message ***
488:
1.138 brouard 489: Revision 1.137 2010/04/29 18:11:38 brouard
490: (Module): Checking covariates for more complex models
491: than V1+V2. A lot of change to be done. Unstable.
492:
1.137 brouard 493: Revision 1.136 2010/04/26 20:30:53 brouard
494: (Module): merging some libgsl code. Fixing computation
495: of likelione (using inter/intrapolation if mle = 0) in order to
496: get same likelihood as if mle=1.
497: Some cleaning of code and comments added.
498:
1.136 brouard 499: Revision 1.135 2009/10/29 15:33:14 brouard
500: (Module): Now imach stops if date of birth, at least year of birth, is not given. Some cleaning of the code.
501:
1.135 brouard 502: Revision 1.134 2009/10/29 13:18:53 brouard
503: (Module): Now imach stops if date of birth, at least year of birth, is not given. Some cleaning of the code.
504:
1.134 brouard 505: Revision 1.133 2009/07/06 10:21:25 brouard
506: just nforces
507:
1.133 brouard 508: Revision 1.132 2009/07/06 08:22:05 brouard
509: Many tings
510:
1.132 brouard 511: Revision 1.131 2009/06/20 16:22:47 brouard
512: Some dimensions resccaled
513:
1.131 brouard 514: Revision 1.130 2009/05/26 06:44:34 brouard
515: (Module): Max Covariate is now set to 20 instead of 8. A
516: lot of cleaning with variables initialized to 0. Trying to make
517: V2+V3*age+V1+V4 strb=V3*age+V1+V4 working better.
518:
1.130 brouard 519: Revision 1.129 2007/08/31 13:49:27 lievre
520: Modification of the way of exiting when the covariate is not binary in order to see on the window the error message before exiting
521:
1.129 lievre 522: Revision 1.128 2006/06/30 13:02:05 brouard
523: (Module): Clarifications on computing e.j
524:
1.128 brouard 525: Revision 1.127 2006/04/28 18:11:50 brouard
526: (Module): Yes the sum of survivors was wrong since
527: imach-114 because nhstepm was no more computed in the age
528: loop. Now we define nhstepma in the age loop.
529: (Module): In order to speed up (in case of numerous covariates) we
530: compute health expectancies (without variances) in a first step
531: and then all the health expectancies with variances or standard
532: deviation (needs data from the Hessian matrices) which slows the
533: computation.
534: In the future we should be able to stop the program is only health
535: expectancies and graph are needed without standard deviations.
536:
1.127 brouard 537: Revision 1.126 2006/04/28 17:23:28 brouard
538: (Module): Yes the sum of survivors was wrong since
539: imach-114 because nhstepm was no more computed in the age
540: loop. Now we define nhstepma in the age loop.
541: Version 0.98h
542:
1.126 brouard 543: Revision 1.125 2006/04/04 15:20:31 lievre
544: Errors in calculation of health expectancies. Age was not initialized.
545: Forecasting file added.
546:
547: Revision 1.124 2006/03/22 17:13:53 lievre
548: Parameters are printed with %lf instead of %f (more numbers after the comma).
549: The log-likelihood is printed in the log file
550:
551: Revision 1.123 2006/03/20 10:52:43 brouard
552: * imach.c (Module): <title> changed, corresponds to .htm file
553: name. <head> headers where missing.
554:
555: * imach.c (Module): Weights can have a decimal point as for
556: English (a comma might work with a correct LC_NUMERIC environment,
557: otherwise the weight is truncated).
558: Modification of warning when the covariates values are not 0 or
559: 1.
560: Version 0.98g
561:
562: Revision 1.122 2006/03/20 09:45:41 brouard
563: (Module): Weights can have a decimal point as for
564: English (a comma might work with a correct LC_NUMERIC environment,
565: otherwise the weight is truncated).
566: Modification of warning when the covariates values are not 0 or
567: 1.
568: Version 0.98g
569:
570: Revision 1.121 2006/03/16 17:45:01 lievre
571: * imach.c (Module): Comments concerning covariates added
572:
573: * imach.c (Module): refinements in the computation of lli if
574: status=-2 in order to have more reliable computation if stepm is
575: not 1 month. Version 0.98f
576:
577: Revision 1.120 2006/03/16 15:10:38 lievre
578: (Module): refinements in the computation of lli if
579: status=-2 in order to have more reliable computation if stepm is
580: not 1 month. Version 0.98f
581:
582: Revision 1.119 2006/03/15 17:42:26 brouard
583: (Module): Bug if status = -2, the loglikelihood was
584: computed as likelihood omitting the logarithm. Version O.98e
585:
586: Revision 1.118 2006/03/14 18:20:07 brouard
587: (Module): varevsij Comments added explaining the second
588: table of variances if popbased=1 .
589: (Module): Covariances of eij, ekl added, graphs fixed, new html link.
590: (Module): Function pstamp added
591: (Module): Version 0.98d
592:
593: Revision 1.117 2006/03/14 17:16:22 brouard
594: (Module): varevsij Comments added explaining the second
595: table of variances if popbased=1 .
596: (Module): Covariances of eij, ekl added, graphs fixed, new html link.
597: (Module): Function pstamp added
598: (Module): Version 0.98d
599:
600: Revision 1.116 2006/03/06 10:29:27 brouard
601: (Module): Variance-covariance wrong links and
602: varian-covariance of ej. is needed (Saito).
603:
604: Revision 1.115 2006/02/27 12:17:45 brouard
605: (Module): One freematrix added in mlikeli! 0.98c
606:
607: Revision 1.114 2006/02/26 12:57:58 brouard
608: (Module): Some improvements in processing parameter
609: filename with strsep.
610:
611: Revision 1.113 2006/02/24 14:20:24 brouard
612: (Module): Memory leaks checks with valgrind and:
613: datafile was not closed, some imatrix were not freed and on matrix
614: allocation too.
615:
616: Revision 1.112 2006/01/30 09:55:26 brouard
617: (Module): Back to gnuplot.exe instead of wgnuplot.exe
618:
619: Revision 1.111 2006/01/25 20:38:18 brouard
620: (Module): Lots of cleaning and bugs added (Gompertz)
621: (Module): Comments can be added in data file. Missing date values
622: can be a simple dot '.'.
623:
624: Revision 1.110 2006/01/25 00:51:50 brouard
625: (Module): Lots of cleaning and bugs added (Gompertz)
626:
627: Revision 1.109 2006/01/24 19:37:15 brouard
628: (Module): Comments (lines starting with a #) are allowed in data.
629:
630: Revision 1.108 2006/01/19 18:05:42 lievre
631: Gnuplot problem appeared...
632: To be fixed
633:
634: Revision 1.107 2006/01/19 16:20:37 brouard
635: Test existence of gnuplot in imach path
636:
637: Revision 1.106 2006/01/19 13:24:36 brouard
638: Some cleaning and links added in html output
639:
640: Revision 1.105 2006/01/05 20:23:19 lievre
641: *** empty log message ***
642:
643: Revision 1.104 2005/09/30 16:11:43 lievre
644: (Module): sump fixed, loop imx fixed, and simplifications.
645: (Module): If the status is missing at the last wave but we know
646: that the person is alive, then we can code his/her status as -2
647: (instead of missing=-1 in earlier versions) and his/her
648: contributions to the likelihood is 1 - Prob of dying from last
649: health status (= 1-p13= p11+p12 in the easiest case of somebody in
650: the healthy state at last known wave). Version is 0.98
651:
652: Revision 1.103 2005/09/30 15:54:49 lievre
653: (Module): sump fixed, loop imx fixed, and simplifications.
654:
655: Revision 1.102 2004/09/15 17:31:30 brouard
656: Add the possibility to read data file including tab characters.
657:
658: Revision 1.101 2004/09/15 10:38:38 brouard
659: Fix on curr_time
660:
661: Revision 1.100 2004/07/12 18:29:06 brouard
662: Add version for Mac OS X. Just define UNIX in Makefile
663:
664: Revision 1.99 2004/06/05 08:57:40 brouard
665: *** empty log message ***
666:
667: Revision 1.98 2004/05/16 15:05:56 brouard
668: New version 0.97 . First attempt to estimate force of mortality
669: directly from the data i.e. without the need of knowing the health
670: state at each age, but using a Gompertz model: log u =a + b*age .
671: This is the basic analysis of mortality and should be done before any
672: other analysis, in order to test if the mortality estimated from the
673: cross-longitudinal survey is different from the mortality estimated
674: from other sources like vital statistic data.
675:
676: The same imach parameter file can be used but the option for mle should be -3.
677:
1.133 brouard 678: Agnès, who wrote this part of the code, tried to keep most of the
1.126 brouard 679: former routines in order to include the new code within the former code.
680:
681: The output is very simple: only an estimate of the intercept and of
682: the slope with 95% confident intervals.
683:
684: Current limitations:
685: A) Even if you enter covariates, i.e. with the
686: model= V1+V2 equation for example, the programm does only estimate a unique global model without covariates.
687: B) There is no computation of Life Expectancy nor Life Table.
688:
689: Revision 1.97 2004/02/20 13:25:42 lievre
690: Version 0.96d. Population forecasting command line is (temporarily)
691: suppressed.
692:
693: Revision 1.96 2003/07/15 15:38:55 brouard
694: * imach.c (Repository): Errors in subdirf, 2, 3 while printing tmpout is
695: rewritten within the same printf. Workaround: many printfs.
696:
697: Revision 1.95 2003/07/08 07:54:34 brouard
698: * imach.c (Repository):
699: (Repository): Using imachwizard code to output a more meaningful covariance
700: matrix (cov(a12,c31) instead of numbers.
701:
702: Revision 1.94 2003/06/27 13:00:02 brouard
703: Just cleaning
704:
705: Revision 1.93 2003/06/25 16:33:55 brouard
706: (Module): On windows (cygwin) function asctime_r doesn't
707: exist so I changed back to asctime which exists.
708: (Module): Version 0.96b
709:
710: Revision 1.92 2003/06/25 16:30:45 brouard
711: (Module): On windows (cygwin) function asctime_r doesn't
712: exist so I changed back to asctime which exists.
713:
714: Revision 1.91 2003/06/25 15:30:29 brouard
715: * imach.c (Repository): Duplicated warning errors corrected.
716: (Repository): Elapsed time after each iteration is now output. It
717: helps to forecast when convergence will be reached. Elapsed time
718: is stamped in powell. We created a new html file for the graphs
719: concerning matrix of covariance. It has extension -cov.htm.
720:
721: Revision 1.90 2003/06/24 12:34:15 brouard
722: (Module): Some bugs corrected for windows. Also, when
723: mle=-1 a template is output in file "or"mypar.txt with the design
724: of the covariance matrix to be input.
725:
726: Revision 1.89 2003/06/24 12:30:52 brouard
727: (Module): Some bugs corrected for windows. Also, when
728: mle=-1 a template is output in file "or"mypar.txt with the design
729: of the covariance matrix to be input.
730:
731: Revision 1.88 2003/06/23 17:54:56 brouard
732: * 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.
733:
734: Revision 1.87 2003/06/18 12:26:01 brouard
735: Version 0.96
736:
737: Revision 1.86 2003/06/17 20:04:08 brouard
738: (Module): Change position of html and gnuplot routines and added
739: routine fileappend.
740:
741: Revision 1.85 2003/06/17 13:12:43 brouard
742: * imach.c (Repository): Check when date of death was earlier that
743: current date of interview. It may happen when the death was just
744: prior to the death. In this case, dh was negative and likelihood
745: was wrong (infinity). We still send an "Error" but patch by
746: assuming that the date of death was just one stepm after the
747: interview.
748: (Repository): Because some people have very long ID (first column)
749: we changed int to long in num[] and we added a new lvector for
750: memory allocation. But we also truncated to 8 characters (left
751: truncation)
752: (Repository): No more line truncation errors.
753:
754: Revision 1.84 2003/06/13 21:44:43 brouard
755: * imach.c (Repository): Replace "freqsummary" at a correct
756: place. It differs from routine "prevalence" which may be called
757: many times. Probs is memory consuming and must be used with
758: parcimony.
759: Version 0.95a3 (should output exactly the same maximization than 0.8a2)
760:
761: Revision 1.83 2003/06/10 13:39:11 lievre
762: *** empty log message ***
763:
764: Revision 1.82 2003/06/05 15:57:20 brouard
765: Add log in imach.c and fullversion number is now printed.
766:
767: */
768: /*
769: Interpolated Markov Chain
770:
771: Short summary of the programme:
772:
1.227 brouard 773: This program computes Healthy Life Expectancies or State-specific
774: (if states aren't health statuses) Expectancies from
775: cross-longitudinal data. Cross-longitudinal data consist in:
776:
777: -1- a first survey ("cross") where individuals from different ages
778: are interviewed on their health status or degree of disability (in
779: the case of a health survey which is our main interest)
780:
781: -2- at least a second wave of interviews ("longitudinal") which
782: measure each change (if any) in individual health status. Health
783: expectancies are computed from the time spent in each health state
784: according to a model. More health states you consider, more time is
785: necessary to reach the Maximum Likelihood of the parameters involved
786: in the model. The simplest model is the multinomial logistic model
787: where pij is the probability to be observed in state j at the second
788: wave conditional to be observed in state i at the first
789: wave. Therefore the model is: log(pij/pii)= aij + bij*age+ cij*sex +
790: etc , where 'age' is age and 'sex' is a covariate. If you want to
791: have a more complex model than "constant and age", you should modify
792: the program where the markup *Covariates have to be included here
793: again* invites you to do it. More covariates you add, slower the
1.126 brouard 794: convergence.
795:
796: The advantage of this computer programme, compared to a simple
797: multinomial logistic model, is clear when the delay between waves is not
798: identical for each individual. Also, if a individual missed an
799: intermediate interview, the information is lost, but taken into
800: account using an interpolation or extrapolation.
801:
802: hPijx is the probability to be observed in state i at age x+h
803: conditional to the observed state i at age x. The delay 'h' can be
804: split into an exact number (nh*stepm) of unobserved intermediate
805: states. This elementary transition (by month, quarter,
806: semester or year) is modelled as a multinomial logistic. The hPx
807: matrix is simply the matrix product of nh*stepm elementary matrices
808: and the contribution of each individual to the likelihood is simply
809: hPijx.
810:
811: Also this programme outputs the covariance matrix of the parameters but also
1.218 brouard 812: of the life expectancies. It also computes the period (stable) prevalence.
813:
814: Back prevalence and projections:
1.227 brouard 815:
816: - back_prevalence_limit(double *p, double **bprlim, double ageminpar,
817: double agemaxpar, double ftolpl, int *ncvyearp, double
818: dateprev1,double dateprev2, int firstpass, int lastpass, int
819: mobilavproj)
820:
821: Computes the back prevalence limit for any combination of
822: covariate values k at any age between ageminpar and agemaxpar and
823: returns it in **bprlim. In the loops,
824:
825: - **bprevalim(**bprlim, ***mobaverage, nlstate, *p, age, **oldm,
826: **savm, **dnewm, **doldm, **dsavm, ftolpl, ncvyearp, k);
827:
828: - hBijx Back Probability to be in state i at age x-h being in j at x
1.218 brouard 829: Computes for any combination of covariates k and any age between bage and fage
830: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
831: oldm=oldms;savm=savms;
1.227 brouard 832:
1.267 brouard 833: - hbxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k, nres);
1.218 brouard 834: Computes the transition matrix starting at age 'age' over
835: 'nhstepm*hstepm*stepm' months (i.e. until
836: age (in years) age+nhstepm*hstepm*stepm/12) by multiplying
1.227 brouard 837: nhstepm*hstepm matrices.
838:
839: Returns p3mat[i][j][h] after calling
840: p3mat[i][j][h]=matprod2(newm,
841: bmij(pmmij,cov,ncovmodel,x,nlstate,prevacurrent, dnewm, doldm,
842: dsavm,ij),\ 1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath,
843: oldm);
1.226 brouard 844:
845: Important routines
846:
847: - func (or funcone), computes logit (pij) distinguishing
848: o fixed variables (single or product dummies or quantitative);
849: o varying variables by:
850: (1) wave (single, product dummies, quantitative),
851: (2) by age (can be month) age (done), age*age (done), age*Vn where Vn can be:
852: % fixed dummy (treated) or quantitative (not done because time-consuming);
853: % varying dummy (not done) or quantitative (not done);
854: - Tricode which tests the modality of dummy variables (in order to warn with wrong or empty modalities)
855: and returns the number of efficient covariates cptcoveff and modalities nbcode[Tvar[k]][1]= 0 and nbcode[Tvar[k]][2]= 1 usually.
856: - printinghtml which outputs results like life expectancy in and from a state for a combination of modalities of dummy variables
857: o There are 2*cptcoveff combinations of (0,1) for cptcoveff variables. Outputting only combinations with people, éliminating 1 1 if
858: race White (0 0), Black vs White (1 0), Hispanic (0 1) and 1 1 being meaningless.
1.218 brouard 859:
1.226 brouard 860:
861:
1.133 brouard 862: Authors: Nicolas Brouard (brouard@ined.fr) and Agnès Lièvre (lievre@ined.fr).
863: Institut national d'études démographiques, Paris.
1.126 brouard 864: This software have been partly granted by Euro-REVES, a concerted action
865: from the European Union.
866: It is copyrighted identically to a GNU software product, ie programme and
867: software can be distributed freely for non commercial use. Latest version
868: can be accessed at http://euroreves.ined.fr/imach .
869:
870: Help to debug: LD_PRELOAD=/usr/local/lib/libnjamd.so ./imach foo.imach
871: or better on gdb : set env LD_PRELOAD=/usr/local/lib/libnjamd.so
872:
873: **********************************************************************/
874: /*
875: main
876: read parameterfile
877: read datafile
878: concatwav
879: freqsummary
880: if (mle >= 1)
881: mlikeli
882: print results files
883: if mle==1
884: computes hessian
885: read end of parameter file: agemin, agemax, bage, fage, estepm
886: begin-prev-date,...
887: open gnuplot file
888: open html file
1.145 brouard 889: period (stable) prevalence | pl_nom 1-1 2-2 etc by covariate
890: for age prevalim() | #****** V1=0 V2=1 V3=1 V4=0 ******
891: | 65 1 0 2 1 3 1 4 0 0.96326 0.03674
892: freexexit2 possible for memory heap.
893:
894: h Pij x | pij_nom ficrestpij
895: # Cov Agex agex+h hpijx with i,j= 1-1 1-2 1-3 2-1 2-2 2-3
896: 1 85 85 1.00000 0.00000 0.00000 0.00000 1.00000 0.00000
897: 1 85 86 0.68299 0.22291 0.09410 0.71093 0.00000 0.28907
898:
899: 1 65 99 0.00364 0.00322 0.99314 0.00350 0.00310 0.99340
900: 1 65 100 0.00214 0.00204 0.99581 0.00206 0.00196 0.99597
901: variance of p one-step probabilities varprob | prob_nom ficresprob #One-step probabilities and stand. devi in ()
902: Standard deviation of one-step probabilities | probcor_nom ficresprobcor #One-step probabilities and correlation matrix
903: Matrix of variance covariance of one-step probabilities | probcov_nom ficresprobcov #One-step probabilities and covariance matrix
904:
1.126 brouard 905: forecasting if prevfcast==1 prevforecast call prevalence()
906: health expectancies
907: Variance-covariance of DFLE
908: prevalence()
909: movingaverage()
910: varevsij()
911: if popbased==1 varevsij(,popbased)
912: total life expectancies
913: Variance of period (stable) prevalence
914: end
915: */
916:
1.187 brouard 917: /* #define DEBUG */
918: /* #define DEBUGBRENT */
1.203 brouard 919: /* #define DEBUGLINMIN */
920: /* #define DEBUGHESS */
921: #define DEBUGHESSIJ
1.224 brouard 922: /* #define LINMINORIGINAL /\* Don't use loop on scale in linmin (accepting nan) *\/ */
1.165 brouard 923: #define POWELL /* Instead of NLOPT */
1.224 brouard 924: #define POWELLNOF3INFF1TEST /* Skip test */
1.186 brouard 925: /* #define POWELLORIGINAL /\* Don't use Directest to decide new direction but original Powell test *\/ */
926: /* #define MNBRAKORIGINAL /\* Don't use mnbrak fix *\/ */
1.126 brouard 927:
928: #include <math.h>
929: #include <stdio.h>
930: #include <stdlib.h>
931: #include <string.h>
1.226 brouard 932: #include <ctype.h>
1.159 brouard 933:
934: #ifdef _WIN32
935: #include <io.h>
1.172 brouard 936: #include <windows.h>
937: #include <tchar.h>
1.159 brouard 938: #else
1.126 brouard 939: #include <unistd.h>
1.159 brouard 940: #endif
1.126 brouard 941:
942: #include <limits.h>
943: #include <sys/types.h>
1.171 brouard 944:
945: #if defined(__GNUC__)
946: #include <sys/utsname.h> /* Doesn't work on Windows */
947: #endif
948:
1.126 brouard 949: #include <sys/stat.h>
950: #include <errno.h>
1.159 brouard 951: /* extern int errno; */
1.126 brouard 952:
1.157 brouard 953: /* #ifdef LINUX */
954: /* #include <time.h> */
955: /* #include "timeval.h" */
956: /* #else */
957: /* #include <sys/time.h> */
958: /* #endif */
959:
1.126 brouard 960: #include <time.h>
961:
1.136 brouard 962: #ifdef GSL
963: #include <gsl/gsl_errno.h>
964: #include <gsl/gsl_multimin.h>
965: #endif
966:
1.167 brouard 967:
1.162 brouard 968: #ifdef NLOPT
969: #include <nlopt.h>
970: typedef struct {
971: double (* function)(double [] );
972: } myfunc_data ;
973: #endif
974:
1.126 brouard 975: /* #include <libintl.h> */
976: /* #define _(String) gettext (String) */
977:
1.251 brouard 978: #define MAXLINE 2048 /* Was 256 and 1024. Overflow with 312 with 2 states and 4 covariates. Should be ok */
1.126 brouard 979:
980: #define GNUPLOTPROGRAM "gnuplot"
981: /*#define GNUPLOTPROGRAM "..\\gp37mgw\\wgnuplot"*/
982: #define FILENAMELENGTH 132
983:
984: #define GLOCK_ERROR_NOPATH -1 /* empty path */
985: #define GLOCK_ERROR_GETCWD -2 /* cannot get cwd */
986:
1.144 brouard 987: #define MAXPARM 128 /**< Maximum number of parameters for the optimization */
988: #define NPARMAX 64 /**< (nlstate+ndeath-1)*nlstate*ncovmodel */
1.126 brouard 989:
990: #define NINTERVMAX 8
1.144 brouard 991: #define NLSTATEMAX 8 /**< Maximum number of live states (for func) */
992: #define NDEATHMAX 8 /**< Maximum number of dead states (for func) */
993: #define NCOVMAX 20 /**< Maximum number of covariates, including generated covariates V1*V2 */
1.197 brouard 994: #define codtabm(h,k) (1 & (h-1) >> (k-1))+1
1.211 brouard 995: /*#define decodtabm(h,k,cptcoveff)= (h <= (1<<cptcoveff)?(((h-1) >> (k-1)) & 1) +1 : -1)*/
996: #define decodtabm(h,k,cptcoveff) (((h-1) >> (k-1)) & 1) +1
1.126 brouard 997: #define MAXN 20000
1.144 brouard 998: #define YEARM 12. /**< Number of months per year */
1.218 brouard 999: /* #define AGESUP 130 */
1000: #define AGESUP 150
1.268 brouard 1001: #define AGEINF 0
1.218 brouard 1002: #define AGEMARGE 25 /* Marge for agemin and agemax for(iage=agemin-AGEMARGE; iage <= agemax+3+AGEMARGE; iage++) */
1.126 brouard 1003: #define AGEBASE 40
1.194 brouard 1004: #define AGEOVERFLOW 1.e20
1.164 brouard 1005: #define AGEGOMP 10 /**< Minimal age for Gompertz adjustment */
1.157 brouard 1006: #ifdef _WIN32
1007: #define DIRSEPARATOR '\\'
1008: #define CHARSEPARATOR "\\"
1009: #define ODIRSEPARATOR '/'
1010: #else
1.126 brouard 1011: #define DIRSEPARATOR '/'
1012: #define CHARSEPARATOR "/"
1013: #define ODIRSEPARATOR '\\'
1014: #endif
1015:
1.271 ! brouard 1016: /* $Id: imach.c,v 1.270 2017/05/24 05:45:29 brouard Exp $ */
1.126 brouard 1017: /* $State: Exp $ */
1.196 brouard 1018: #include "version.h"
1019: char version[]=__IMACH_VERSION__;
1.224 brouard 1020: 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";
1.271 ! brouard 1021: char fullversion[]="$Revision: 1.270 $ $Date: 2017/05/24 05:45:29 $";
1.126 brouard 1022: char strstart[80];
1023: char optionfilext[10], optionfilefiname[FILENAMELENGTH];
1.130 brouard 1024: int erreur=0, nberr=0, nbwarn=0; /* Error number, number of errors number of warnings */
1.187 brouard 1025: int nagesqr=0, nforce=0; /* nagesqr=1 if model is including age*age, number of forces */
1.145 brouard 1026: /* Number of covariates model=V2+V1+ V3*age+V2*V4 */
1027: int cptcovn=0; /**< cptcovn number of covariates added in the model (excepting constant and age and age*product) */
1028: int cptcovt=0; /**< cptcovt number of covariates added in the model (excepting constant and age) */
1.225 brouard 1029: int cptcovs=0; /**< cptcovs number of simple covariates in the model V2+V1 =2 */
1030: int cptcovsnq=0; /**< cptcovsnq number of simple covariates in the model but non quantitative V2+V1 =2 */
1.145 brouard 1031: int cptcovage=0; /**< Number of covariates with age: V3*age only =1 */
1032: int cptcovprodnoage=0; /**< Number of covariate products without age */
1033: int cptcoveff=0; /* Total number of covariates to vary for printing results */
1.233 brouard 1034: int ncovf=0; /* Total number of effective fixed covariates (dummy or quantitative) in the model */
1035: int ncovv=0; /* Total number of effective (wave) varying covariates (dummy or quantitative) in the model */
1.232 brouard 1036: int ncova=0; /* Total number of effective (wave and stepm) varying with age covariates (dummy of quantitative) in the model */
1.234 brouard 1037: int nsd=0; /**< Total number of single dummy variables (output) */
1038: int nsq=0; /**< Total number of single quantitative variables (output) */
1.232 brouard 1039: int ncoveff=0; /* Total number of effective fixed dummy covariates in the model */
1.225 brouard 1040: int nqfveff=0; /**< nqfveff Number of Quantitative Fixed Variables Effective */
1.224 brouard 1041: int ntveff=0; /**< ntveff number of effective time varying variables */
1042: int nqtveff=0; /**< ntqveff number of effective time varying quantitative variables */
1.145 brouard 1043: int cptcov=0; /* Working variable */
1.218 brouard 1044: int ncovcombmax=NCOVMAX; /* Maximum calculated number of covariate combination = pow(2, cptcoveff) */
1.126 brouard 1045: int npar=NPARMAX;
1046: int nlstate=2; /* Number of live states */
1047: int ndeath=1; /* Number of dead states */
1.130 brouard 1048: int ncovmodel=0, ncovcol=0; /* Total number of covariables including constant a12*1 +b12*x ncovmodel=2 */
1.223 brouard 1049: int nqv=0, ntv=0, nqtv=0; /* Total number of quantitative variables, time variable (dummy), quantitative and time variable */
1.126 brouard 1050: int popbased=0;
1051:
1052: int *wav; /* Number of waves for this individuual 0 is possible */
1.130 brouard 1053: int maxwav=0; /* Maxim number of waves */
1054: int jmin=0, jmax=0; /* min, max spacing between 2 waves */
1055: int ijmin=0, ijmax=0; /* Individuals having jmin and jmax */
1056: int gipmx=0, gsw=0; /* Global variables on the number of contributions
1.126 brouard 1057: to the likelihood and the sum of weights (done by funcone)*/
1.130 brouard 1058: int mle=1, weightopt=0;
1.126 brouard 1059: int **mw; /* mw[mi][i] is number of the mi wave for this individual */
1060: int **dh; /* dh[mi][i] is number of steps between mi,mi+1 for this individual */
1061: int **bh; /* bh[mi][i] is the bias (+ or -) for this individual if the delay between
1062: * wave mi and wave mi+1 is not an exact multiple of stepm. */
1.162 brouard 1063: int countcallfunc=0; /* Count the number of calls to func */
1.230 brouard 1064: int selected(int kvar); /* Is covariate kvar selected for printing results */
1065:
1.130 brouard 1066: double jmean=1; /* Mean space between 2 waves */
1.145 brouard 1067: double **matprod2(); /* test */
1.126 brouard 1068: double **oldm, **newm, **savm; /* Working pointers to matrices */
1069: double **oldms, **newms, **savms; /* Fixed working pointers to matrices */
1.218 brouard 1070: double **ddnewms, **ddoldms, **ddsavms; /* for freeing later */
1071:
1.136 brouard 1072: /*FILE *fic ; */ /* Used in readdata only */
1.217 brouard 1073: FILE *ficpar, *ficparo,*ficres, *ficresp, *ficresphtm, *ficresphtmfr, *ficrespl, *ficresplb,*ficrespij, *ficrespijb, *ficrest,*ficresf, *ficresfb,*ficrespop;
1.126 brouard 1074: FILE *ficlog, *ficrespow;
1.130 brouard 1075: int globpr=0; /* Global variable for printing or not */
1.126 brouard 1076: double fretone; /* Only one call to likelihood */
1.130 brouard 1077: long ipmx=0; /* Number of contributions */
1.126 brouard 1078: double sw; /* Sum of weights */
1079: char filerespow[FILENAMELENGTH];
1080: char fileresilk[FILENAMELENGTH]; /* File of individual contributions to the likelihood */
1081: FILE *ficresilk;
1082: FILE *ficgp,*ficresprob,*ficpop, *ficresprobcov, *ficresprobcor;
1083: FILE *ficresprobmorprev;
1084: FILE *fichtm, *fichtmcov; /* Html File */
1085: FILE *ficreseij;
1086: char filerese[FILENAMELENGTH];
1087: FILE *ficresstdeij;
1088: char fileresstde[FILENAMELENGTH];
1089: FILE *ficrescveij;
1090: char filerescve[FILENAMELENGTH];
1091: FILE *ficresvij;
1092: char fileresv[FILENAMELENGTH];
1.269 brouard 1093:
1.126 brouard 1094: char title[MAXLINE];
1.234 brouard 1095: char model[MAXLINE]; /**< The model line */
1.217 brouard 1096: char optionfile[FILENAMELENGTH], datafile[FILENAMELENGTH], filerespl[FILENAMELENGTH], fileresplb[FILENAMELENGTH];
1.126 brouard 1097: char plotcmd[FILENAMELENGTH], pplotcmd[FILENAMELENGTH];
1098: char tmpout[FILENAMELENGTH], tmpout2[FILENAMELENGTH];
1099: char command[FILENAMELENGTH];
1100: int outcmd=0;
1101:
1.217 brouard 1102: char fileres[FILENAMELENGTH], filerespij[FILENAMELENGTH], filerespijb[FILENAMELENGTH], filereso[FILENAMELENGTH], rfileres[FILENAMELENGTH];
1.202 brouard 1103: char fileresu[FILENAMELENGTH]; /* fileres without r in front */
1.126 brouard 1104: char filelog[FILENAMELENGTH]; /* Log file */
1105: char filerest[FILENAMELENGTH];
1106: char fileregp[FILENAMELENGTH];
1107: char popfile[FILENAMELENGTH];
1108:
1109: char optionfilegnuplot[FILENAMELENGTH], optionfilehtm[FILENAMELENGTH], optionfilehtmcov[FILENAMELENGTH] ;
1110:
1.157 brouard 1111: /* struct timeval start_time, end_time, curr_time, last_time, forecast_time; */
1112: /* struct timezone tzp; */
1113: /* extern int gettimeofday(); */
1114: struct tm tml, *gmtime(), *localtime();
1115:
1116: extern time_t time();
1117:
1118: struct tm start_time, end_time, curr_time, last_time, forecast_time;
1119: time_t rstart_time, rend_time, rcurr_time, rlast_time, rforecast_time; /* raw time */
1120: struct tm tm;
1121:
1.126 brouard 1122: char strcurr[80], strfor[80];
1123:
1124: char *endptr;
1125: long lval;
1126: double dval;
1127:
1128: #define NR_END 1
1129: #define FREE_ARG char*
1130: #define FTOL 1.0e-10
1131:
1132: #define NRANSI
1.240 brouard 1133: #define ITMAX 200
1134: #define ITPOWMAX 20 /* This is now multiplied by the number of parameters */
1.126 brouard 1135:
1136: #define TOL 2.0e-4
1137:
1138: #define CGOLD 0.3819660
1139: #define ZEPS 1.0e-10
1140: #define SHFT(a,b,c,d) (a)=(b);(b)=(c);(c)=(d);
1141:
1142: #define GOLD 1.618034
1143: #define GLIMIT 100.0
1144: #define TINY 1.0e-20
1145:
1146: static double maxarg1,maxarg2;
1147: #define FMAX(a,b) (maxarg1=(a),maxarg2=(b),(maxarg1)>(maxarg2)? (maxarg1):(maxarg2))
1148: #define FMIN(a,b) (maxarg1=(a),maxarg2=(b),(maxarg1)<(maxarg2)? (maxarg1):(maxarg2))
1149:
1150: #define SIGN(a,b) ((b)>0.0 ? fabs(a) : -fabs(a))
1151: #define rint(a) floor(a+0.5)
1.166 brouard 1152: /* http://www.thphys.uni-heidelberg.de/~robbers/cmbeasy/doc/html/myutils_8h-source.html */
1.183 brouard 1153: #define mytinydouble 1.0e-16
1.166 brouard 1154: /* #define DEQUAL(a,b) (fabs((a)-(b))<mytinydouble) */
1155: /* http://www.thphys.uni-heidelberg.de/~robbers/cmbeasy/doc/html/mynrutils_8h-source.html */
1156: /* static double dsqrarg; */
1157: /* #define DSQR(a) (DEQUAL((dsqrarg=(a)),0.0) ? 0.0 : dsqrarg*dsqrarg) */
1.126 brouard 1158: static double sqrarg;
1159: #define SQR(a) ((sqrarg=(a)) == 0.0 ? 0.0 :sqrarg*sqrarg)
1160: #define SWAP(a,b) {temp=(a);(a)=(b);(b)=temp;}
1161: int agegomp= AGEGOMP;
1162:
1163: int imx;
1164: int stepm=1;
1165: /* Stepm, step in month: minimum step interpolation*/
1166:
1167: int estepm;
1168: /* Estepm, step in month to interpolate survival function in order to approximate Life Expectancy*/
1169:
1170: int m,nb;
1171: long *num;
1.197 brouard 1172: int firstpass=0, lastpass=4,*cod, *cens;
1.192 brouard 1173: int *ncodemax; /* ncodemax[j]= Number of modalities of the j th
1174: covariate for which somebody answered excluding
1175: undefined. Usually 2: 0 and 1. */
1176: int *ncodemaxwundef; /* ncodemax[j]= Number of modalities of the j th
1177: covariate for which somebody answered including
1178: undefined. Usually 3: -1, 0 and 1. */
1.126 brouard 1179: double **agev,*moisnais, *annais, *moisdc, *andc,**mint, **anint;
1.218 brouard 1180: double **pmmij, ***probs; /* Global pointer */
1.219 brouard 1181: double ***mobaverage, ***mobaverages; /* New global variable */
1.126 brouard 1182: double *ageexmed,*agecens;
1183: double dateintmean=0;
1184:
1185: double *weight;
1186: int **s; /* Status */
1.141 brouard 1187: double *agedc;
1.145 brouard 1188: double **covar; /**< covar[j,i], value of jth covariate for individual i,
1.141 brouard 1189: * covar=matrix(0,NCOVMAX,1,n);
1.187 brouard 1190: * cov[Tage[kk]+2]=covar[Tvar[Tage[kk]]][i]*age; */
1.268 brouard 1191: double **coqvar; /* Fixed quantitative covariate nqv */
1192: double ***cotvar; /* Time varying covariate ntv */
1.225 brouard 1193: double ***cotqvar; /* Time varying quantitative covariate itqv */
1.141 brouard 1194: double idx;
1195: int **nbcode, *Tvar; /**< model=V2 => Tvar[1]= 2 */
1.234 brouard 1196: /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1197: /*k 1 2 3 4 5 6 7 8 9 */
1198: /*Tvar[k]= 5 4 3 6 5 2 7 1 1 */
1199: /* Tndvar[k] 1 2 3 4 5 */
1200: /*TDvar 4 3 6 7 1 */ /* For outputs only; combination of dummies fixed or varying */
1201: /* Tns[k] 1 2 2 4 5 */ /* Number of single cova */
1202: /* TvarsD[k] 1 2 3 */ /* Number of single dummy cova */
1203: /* TvarsDind 2 3 9 */ /* position K of single dummy cova */
1204: /* TvarsQ[k] 1 2 */ /* Number of single quantitative cova */
1205: /* TvarsQind 1 6 */ /* position K of single quantitative cova */
1206: /* Tprod[i]=k 4 7 */
1207: /* Tage[i]=k 5 8 */
1208: /* */
1209: /* Type */
1210: /* V 1 2 3 4 5 */
1211: /* F F V V V */
1212: /* D Q D D Q */
1213: /* */
1214: int *TvarsD;
1215: int *TvarsDind;
1216: int *TvarsQ;
1217: int *TvarsQind;
1218:
1.235 brouard 1219: #define MAXRESULTLINES 10
1220: int nresult=0;
1.258 brouard 1221: int parameterline=0; /* # of the parameter (type) line */
1.235 brouard 1222: int TKresult[MAXRESULTLINES];
1.237 brouard 1223: int Tresult[MAXRESULTLINES][NCOVMAX];/* For dummy variable , value (output) */
1224: int Tinvresult[MAXRESULTLINES][NCOVMAX];/* For dummy variable , value (output) */
1.235 brouard 1225: int Tvresult[MAXRESULTLINES][NCOVMAX]; /* For dummy variable , variable # (output) */
1226: double Tqresult[MAXRESULTLINES][NCOVMAX]; /* For quantitative variable , value (output) */
1.237 brouard 1227: double Tqinvresult[MAXRESULTLINES][NCOVMAX]; /* For quantitative variable , value (output) */
1.235 brouard 1228: int Tvqresult[MAXRESULTLINES][NCOVMAX]; /* For quantitative variable , variable # (output) */
1229:
1.234 brouard 1230: /* 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 1231: 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 */
1232: 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 */
1233: 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 */
1234: int *TvarVind; /**< TvarVind[1]=1, TvarVind[2]=2 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1235: 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 */
1236: 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 1237: int *TvarFD; /**< TvarFD[1]=V1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1238: int *TvarFDind; /* TvarFDind[1]=9 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1239: int *TvarFQ; /* TvarFQ[1]=V2 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1240: int *TvarFQind; /* TvarFQind[1]=6 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1241: int *TvarVD; /* TvarVD[1]=V5 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1242: int *TvarVDind; /* TvarVDind[1]=1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1243: 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 */
1244: 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 */
1245:
1.230 brouard 1246: int *Tvarsel; /**< Selected covariates for output */
1247: double *Tvalsel; /**< Selected modality value of covariate for output */
1.226 brouard 1248: int *Typevar; /**< 0 for simple covariate (dummy, quantitative, fixed or varying), 1 for age product, 2 for product */
1.227 brouard 1249: int *Fixed; /** Fixed[k] 0=fixed, 1 varying, 2 fixed with age product, 3 varying with age product */
1250: 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 1251: int *DummyV; /** Dummy[v] 0=dummy (0 1), 1 quantitative */
1252: int *FixedV; /** FixedV[v] 0 fixed, 1 varying */
1.197 brouard 1253: int *Tage;
1.227 brouard 1254: int anyvaryingduminmodel=0; /**< Any varying dummy in Model=1 yes, 0 no, to avoid a loop on waves in freq */
1.228 brouard 1255: 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 1256: 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*/
1257: 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 1258: int *Ndum; /** Freq of modality (tricode */
1.200 brouard 1259: /* int **codtab;*/ /**< codtab=imatrix(1,100,1,10); */
1.227 brouard 1260: int **Tvard;
1261: int *Tprod;/**< Gives the k position of the k1 product */
1.238 brouard 1262: /* Tprod[k1=1]=3(=V1*V4) for V2+V1+V1*V4+age*V3 */
1.227 brouard 1263: int *Tposprod; /**< Gives the k1 product from the k position */
1.238 brouard 1264: /* if V2+V1+V1*V4+age*V3+V3*V2 TProd[k1=2]=5 (V3*V2) */
1265: /* Tposprod[k]=k1 , Tposprod[3]=1, Tposprod[5(V3*V2)]=2 (2nd product without age) */
1.227 brouard 1266: int cptcovprod, *Tvaraff, *invalidvarcomb;
1.126 brouard 1267: double *lsurv, *lpop, *tpop;
1268:
1.231 brouard 1269: #define FD 1; /* Fixed dummy covariate */
1270: #define FQ 2; /* Fixed quantitative covariate */
1271: #define FP 3; /* Fixed product covariate */
1272: #define FPDD 7; /* Fixed product dummy*dummy covariate */
1273: #define FPDQ 8; /* Fixed product dummy*quantitative covariate */
1274: #define FPQQ 9; /* Fixed product quantitative*quantitative covariate */
1275: #define VD 10; /* Varying dummy covariate */
1276: #define VQ 11; /* Varying quantitative covariate */
1277: #define VP 12; /* Varying product covariate */
1278: #define VPDD 13; /* Varying product dummy*dummy covariate */
1279: #define VPDQ 14; /* Varying product dummy*quantitative covariate */
1280: #define VPQQ 15; /* Varying product quantitative*quantitative covariate */
1281: #define APFD 16; /* Age product * fixed dummy covariate */
1282: #define APFQ 17; /* Age product * fixed quantitative covariate */
1283: #define APVD 18; /* Age product * varying dummy covariate */
1284: #define APVQ 19; /* Age product * varying quantitative covariate */
1285:
1286: #define FTYPE 1; /* Fixed covariate */
1287: #define VTYPE 2; /* Varying covariate (loop in wave) */
1288: #define ATYPE 2; /* Age product covariate (loop in dh within wave)*/
1289:
1290: struct kmodel{
1291: int maintype; /* main type */
1292: int subtype; /* subtype */
1293: };
1294: struct kmodel modell[NCOVMAX];
1295:
1.143 brouard 1296: double ftol=FTOL; /**< Tolerance for computing Max Likelihood */
1297: double ftolhess; /**< Tolerance for computing hessian */
1.126 brouard 1298:
1299: /**************** split *************************/
1300: static int split( char *path, char *dirc, char *name, char *ext, char *finame )
1301: {
1302: /* From a file name with (full) path (either Unix or Windows) we extract the directory (dirc)
1303: the name of the file (name), its extension only (ext) and its first part of the name (finame)
1304: */
1305: char *ss; /* pointer */
1.186 brouard 1306: int l1=0, l2=0; /* length counters */
1.126 brouard 1307:
1308: l1 = strlen(path ); /* length of path */
1309: if ( l1 == 0 ) return( GLOCK_ERROR_NOPATH );
1310: ss= strrchr( path, DIRSEPARATOR ); /* find last / */
1311: if ( ss == NULL ) { /* no directory, so determine current directory */
1312: strcpy( name, path ); /* we got the fullname name because no directory */
1313: /*if(strrchr(path, ODIRSEPARATOR )==NULL)
1314: printf("Warning you should use %s as a separator\n",DIRSEPARATOR);*/
1315: /* get current working directory */
1316: /* extern char* getcwd ( char *buf , int len);*/
1.184 brouard 1317: #ifdef WIN32
1318: if (_getcwd( dirc, FILENAME_MAX ) == NULL ) {
1319: #else
1320: if (getcwd(dirc, FILENAME_MAX) == NULL) {
1321: #endif
1.126 brouard 1322: return( GLOCK_ERROR_GETCWD );
1323: }
1324: /* got dirc from getcwd*/
1325: printf(" DIRC = %s \n",dirc);
1.205 brouard 1326: } else { /* strip directory from path */
1.126 brouard 1327: ss++; /* after this, the filename */
1328: l2 = strlen( ss ); /* length of filename */
1329: if ( l2 == 0 ) return( GLOCK_ERROR_NOPATH );
1330: strcpy( name, ss ); /* save file name */
1331: strncpy( dirc, path, l1 - l2 ); /* now the directory */
1.186 brouard 1332: dirc[l1-l2] = '\0'; /* add zero */
1.126 brouard 1333: printf(" DIRC2 = %s \n",dirc);
1334: }
1335: /* We add a separator at the end of dirc if not exists */
1336: l1 = strlen( dirc ); /* length of directory */
1337: if( dirc[l1-1] != DIRSEPARATOR ){
1338: dirc[l1] = DIRSEPARATOR;
1339: dirc[l1+1] = 0;
1340: printf(" DIRC3 = %s \n",dirc);
1341: }
1342: ss = strrchr( name, '.' ); /* find last / */
1343: if (ss >0){
1344: ss++;
1345: strcpy(ext,ss); /* save extension */
1346: l1= strlen( name);
1347: l2= strlen(ss)+1;
1348: strncpy( finame, name, l1-l2);
1349: finame[l1-l2]= 0;
1350: }
1351:
1352: return( 0 ); /* we're done */
1353: }
1354:
1355:
1356: /******************************************/
1357:
1358: void replace_back_to_slash(char *s, char*t)
1359: {
1360: int i;
1361: int lg=0;
1362: i=0;
1363: lg=strlen(t);
1364: for(i=0; i<= lg; i++) {
1365: (s[i] = t[i]);
1366: if (t[i]== '\\') s[i]='/';
1367: }
1368: }
1369:
1.132 brouard 1370: char *trimbb(char *out, char *in)
1.137 brouard 1371: { /* Trim multiple blanks in line but keeps first blanks if line starts with blanks */
1.132 brouard 1372: char *s;
1373: s=out;
1374: while (*in != '\0'){
1.137 brouard 1375: while( *in == ' ' && *(in+1) == ' '){ /* && *(in+1) != '\0'){*/
1.132 brouard 1376: in++;
1377: }
1378: *out++ = *in++;
1379: }
1380: *out='\0';
1381: return s;
1382: }
1383:
1.187 brouard 1384: /* char *substrchaine(char *out, char *in, char *chain) */
1385: /* { */
1386: /* /\* Substract chain 'chain' from 'in', return and output 'out' *\/ */
1387: /* char *s, *t; */
1388: /* t=in;s=out; */
1389: /* while ((*in != *chain) && (*in != '\0')){ */
1390: /* *out++ = *in++; */
1391: /* } */
1392:
1393: /* /\* *in matches *chain *\/ */
1394: /* while ((*in++ == *chain++) && (*in != '\0')){ */
1395: /* printf("*in = %c, *out= %c *chain= %c \n", *in, *out, *chain); */
1396: /* } */
1397: /* in--; chain--; */
1398: /* while ( (*in != '\0')){ */
1399: /* printf("Bef *in = %c, *out= %c *chain= %c \n", *in, *out, *chain); */
1400: /* *out++ = *in++; */
1401: /* printf("Aft *in = %c, *out= %c *chain= %c \n", *in, *out, *chain); */
1402: /* } */
1403: /* *out='\0'; */
1404: /* out=s; */
1405: /* return out; */
1406: /* } */
1407: char *substrchaine(char *out, char *in, char *chain)
1408: {
1409: /* Substract chain 'chain' from 'in', return and output 'out' */
1410: /* in="V1+V1*age+age*age+V2", chain="age*age" */
1411:
1412: char *strloc;
1413:
1414: strcpy (out, in);
1415: strloc = strstr(out, chain); /* strloc points to out at age*age+V2 */
1416: printf("Bef strloc=%s chain=%s out=%s \n", strloc, chain, out);
1417: if(strloc != NULL){
1418: /* will affect out */ /* strloc+strlenc(chain)=+V2 */ /* Will also work in Unicode */
1419: memmove(strloc,strloc+strlen(chain), strlen(strloc+strlen(chain))+1);
1420: /* strcpy (strloc, strloc +strlen(chain));*/
1421: }
1422: printf("Aft strloc=%s chain=%s in=%s out=%s \n", strloc, chain, in, out);
1423: return out;
1424: }
1425:
1426:
1.145 brouard 1427: char *cutl(char *blocc, char *alocc, char *in, char occ)
1428: {
1.187 brouard 1429: /* cuts string in into blocc and alocc where blocc ends before FIRST occurence of char 'occ'
1.145 brouard 1430: and alocc starts after first occurence of char 'occ' : ex cutv(blocc,alocc,"abcdef2ghi2j",'2')
1.187 brouard 1431: gives blocc="abcdef" and alocc="ghi2j".
1.145 brouard 1432: If occ is not found blocc is null and alocc is equal to in. Returns blocc
1433: */
1.160 brouard 1434: char *s, *t;
1.145 brouard 1435: t=in;s=in;
1436: while ((*in != occ) && (*in != '\0')){
1437: *alocc++ = *in++;
1438: }
1439: if( *in == occ){
1440: *(alocc)='\0';
1441: s=++in;
1442: }
1443:
1444: if (s == t) {/* occ not found */
1445: *(alocc-(in-s))='\0';
1446: in=s;
1447: }
1448: while ( *in != '\0'){
1449: *blocc++ = *in++;
1450: }
1451:
1452: *blocc='\0';
1453: return t;
1454: }
1.137 brouard 1455: char *cutv(char *blocc, char *alocc, char *in, char occ)
1456: {
1.187 brouard 1457: /* cuts string in into blocc and alocc where blocc ends before LAST occurence of char 'occ'
1.137 brouard 1458: and alocc starts after last occurence of char 'occ' : ex cutv(blocc,alocc,"abcdef2ghi2j",'2')
1459: gives blocc="abcdef2ghi" and alocc="j".
1460: If occ is not found blocc is null and alocc is equal to in. Returns alocc
1461: */
1462: char *s, *t;
1463: t=in;s=in;
1464: while (*in != '\0'){
1465: while( *in == occ){
1466: *blocc++ = *in++;
1467: s=in;
1468: }
1469: *blocc++ = *in++;
1470: }
1471: if (s == t) /* occ not found */
1472: *(blocc-(in-s))='\0';
1473: else
1474: *(blocc-(in-s)-1)='\0';
1475: in=s;
1476: while ( *in != '\0'){
1477: *alocc++ = *in++;
1478: }
1479:
1480: *alocc='\0';
1481: return s;
1482: }
1483:
1.126 brouard 1484: int nbocc(char *s, char occ)
1485: {
1486: int i,j=0;
1487: int lg=20;
1488: i=0;
1489: lg=strlen(s);
1490: for(i=0; i<= lg; i++) {
1.234 brouard 1491: if (s[i] == occ ) j++;
1.126 brouard 1492: }
1493: return j;
1494: }
1495:
1.137 brouard 1496: /* void cutv(char *u,char *v, char*t, char occ) */
1497: /* { */
1498: /* /\* cuts string t into u and v where u ends before last occurence of char 'occ' */
1499: /* and v starts after last occurence of char 'occ' : ex cutv(u,v,"abcdef2ghi2j",'2') */
1500: /* gives u="abcdef2ghi" and v="j" *\/ */
1501: /* int i,lg,j,p=0; */
1502: /* i=0; */
1503: /* lg=strlen(t); */
1504: /* for(j=0; j<=lg-1; j++) { */
1505: /* if((t[j]!= occ) && (t[j+1]== occ)) p=j+1; */
1506: /* } */
1.126 brouard 1507:
1.137 brouard 1508: /* for(j=0; j<p; j++) { */
1509: /* (u[j] = t[j]); */
1510: /* } */
1511: /* u[p]='\0'; */
1.126 brouard 1512:
1.137 brouard 1513: /* for(j=0; j<= lg; j++) { */
1514: /* if (j>=(p+1))(v[j-p-1] = t[j]); */
1515: /* } */
1516: /* } */
1.126 brouard 1517:
1.160 brouard 1518: #ifdef _WIN32
1519: char * strsep(char **pp, const char *delim)
1520: {
1521: char *p, *q;
1522:
1523: if ((p = *pp) == NULL)
1524: return 0;
1525: if ((q = strpbrk (p, delim)) != NULL)
1526: {
1527: *pp = q + 1;
1528: *q = '\0';
1529: }
1530: else
1531: *pp = 0;
1532: return p;
1533: }
1534: #endif
1535:
1.126 brouard 1536: /********************** nrerror ********************/
1537:
1538: void nrerror(char error_text[])
1539: {
1540: fprintf(stderr,"ERREUR ...\n");
1541: fprintf(stderr,"%s\n",error_text);
1542: exit(EXIT_FAILURE);
1543: }
1544: /*********************** vector *******************/
1545: double *vector(int nl, int nh)
1546: {
1547: double *v;
1548: v=(double *) malloc((size_t)((nh-nl+1+NR_END)*sizeof(double)));
1549: if (!v) nrerror("allocation failure in vector");
1550: return v-nl+NR_END;
1551: }
1552:
1553: /************************ free vector ******************/
1554: void free_vector(double*v, int nl, int nh)
1555: {
1556: free((FREE_ARG)(v+nl-NR_END));
1557: }
1558:
1559: /************************ivector *******************************/
1560: int *ivector(long nl,long nh)
1561: {
1562: int *v;
1563: v=(int *) malloc((size_t)((nh-nl+1+NR_END)*sizeof(int)));
1564: if (!v) nrerror("allocation failure in ivector");
1565: return v-nl+NR_END;
1566: }
1567:
1568: /******************free ivector **************************/
1569: void free_ivector(int *v, long nl, long nh)
1570: {
1571: free((FREE_ARG)(v+nl-NR_END));
1572: }
1573:
1574: /************************lvector *******************************/
1575: long *lvector(long nl,long nh)
1576: {
1577: long *v;
1578: v=(long *) malloc((size_t)((nh-nl+1+NR_END)*sizeof(long)));
1579: if (!v) nrerror("allocation failure in ivector");
1580: return v-nl+NR_END;
1581: }
1582:
1583: /******************free lvector **************************/
1584: void free_lvector(long *v, long nl, long nh)
1585: {
1586: free((FREE_ARG)(v+nl-NR_END));
1587: }
1588:
1589: /******************* imatrix *******************************/
1590: int **imatrix(long nrl, long nrh, long ncl, long nch)
1591: /* allocate a int matrix with subscript range m[nrl..nrh][ncl..nch] */
1592: {
1593: long i, nrow=nrh-nrl+1,ncol=nch-ncl+1;
1594: int **m;
1595:
1596: /* allocate pointers to rows */
1597: m=(int **) malloc((size_t)((nrow+NR_END)*sizeof(int*)));
1598: if (!m) nrerror("allocation failure 1 in matrix()");
1599: m += NR_END;
1600: m -= nrl;
1601:
1602:
1603: /* allocate rows and set pointers to them */
1604: m[nrl]=(int *) malloc((size_t)((nrow*ncol+NR_END)*sizeof(int)));
1605: if (!m[nrl]) nrerror("allocation failure 2 in matrix()");
1606: m[nrl] += NR_END;
1607: m[nrl] -= ncl;
1608:
1609: for(i=nrl+1;i<=nrh;i++) m[i]=m[i-1]+ncol;
1610:
1611: /* return pointer to array of pointers to rows */
1612: return m;
1613: }
1614:
1615: /****************** free_imatrix *************************/
1616: void free_imatrix(m,nrl,nrh,ncl,nch)
1617: int **m;
1618: long nch,ncl,nrh,nrl;
1619: /* free an int matrix allocated by imatrix() */
1620: {
1621: free((FREE_ARG) (m[nrl]+ncl-NR_END));
1622: free((FREE_ARG) (m+nrl-NR_END));
1623: }
1624:
1625: /******************* matrix *******************************/
1626: double **matrix(long nrl, long nrh, long ncl, long nch)
1627: {
1628: long i, nrow=nrh-nrl+1, ncol=nch-ncl+1;
1629: double **m;
1630:
1631: m=(double **) malloc((size_t)((nrow+NR_END)*sizeof(double*)));
1632: if (!m) nrerror("allocation failure 1 in matrix()");
1633: m += NR_END;
1634: m -= nrl;
1635:
1636: m[nrl]=(double *) malloc((size_t)((nrow*ncol+NR_END)*sizeof(double)));
1637: if (!m[nrl]) nrerror("allocation failure 2 in matrix()");
1638: m[nrl] += NR_END;
1639: m[nrl] -= ncl;
1640:
1641: for (i=nrl+1; i<=nrh; i++) m[i]=m[i-1]+ncol;
1642: return m;
1.145 brouard 1643: /* print *(*(m+1)+70) or print m[1][70]; print m+1 or print &(m[1]) or &(m[1][0])
1644: m[i] = address of ith row of the table. &(m[i]) is its value which is another adress
1645: that of m[i][0]. In order to get the value p m[i][0] but it is unitialized.
1.126 brouard 1646: */
1647: }
1648:
1649: /*************************free matrix ************************/
1650: void free_matrix(double **m, long nrl, long nrh, long ncl, long nch)
1651: {
1652: free((FREE_ARG)(m[nrl]+ncl-NR_END));
1653: free((FREE_ARG)(m+nrl-NR_END));
1654: }
1655:
1656: /******************* ma3x *******************************/
1657: double ***ma3x(long nrl, long nrh, long ncl, long nch, long nll, long nlh)
1658: {
1659: long i, j, nrow=nrh-nrl+1, ncol=nch-ncl+1, nlay=nlh-nll+1;
1660: double ***m;
1661:
1662: m=(double ***) malloc((size_t)((nrow+NR_END)*sizeof(double*)));
1663: if (!m) nrerror("allocation failure 1 in matrix()");
1664: m += NR_END;
1665: m -= nrl;
1666:
1667: m[nrl]=(double **) malloc((size_t)((nrow*ncol+NR_END)*sizeof(double)));
1668: if (!m[nrl]) nrerror("allocation failure 2 in matrix()");
1669: m[nrl] += NR_END;
1670: m[nrl] -= ncl;
1671:
1672: for (i=nrl+1; i<=nrh; i++) m[i]=m[i-1]+ncol;
1673:
1674: m[nrl][ncl]=(double *) malloc((size_t)((nrow*ncol*nlay+NR_END)*sizeof(double)));
1675: if (!m[nrl][ncl]) nrerror("allocation failure 3 in matrix()");
1676: m[nrl][ncl] += NR_END;
1677: m[nrl][ncl] -= nll;
1678: for (j=ncl+1; j<=nch; j++)
1679: m[nrl][j]=m[nrl][j-1]+nlay;
1680:
1681: for (i=nrl+1; i<=nrh; i++) {
1682: m[i][ncl]=m[i-1l][ncl]+ncol*nlay;
1683: for (j=ncl+1; j<=nch; j++)
1684: m[i][j]=m[i][j-1]+nlay;
1685: }
1686: return m;
1687: /* gdb: p *(m+1) <=> p m[1] and p (m+1) <=> p (m+1) <=> p &(m[1])
1688: &(m[i][j][k]) <=> *((*(m+i) + j)+k)
1689: */
1690: }
1691:
1692: /*************************free ma3x ************************/
1693: void free_ma3x(double ***m, long nrl, long nrh, long ncl, long nch,long nll, long nlh)
1694: {
1695: free((FREE_ARG)(m[nrl][ncl]+ nll-NR_END));
1696: free((FREE_ARG)(m[nrl]+ncl-NR_END));
1697: free((FREE_ARG)(m+nrl-NR_END));
1698: }
1699:
1700: /*************** function subdirf ***********/
1701: char *subdirf(char fileres[])
1702: {
1703: /* Caution optionfilefiname is hidden */
1704: strcpy(tmpout,optionfilefiname);
1705: strcat(tmpout,"/"); /* Add to the right */
1706: strcat(tmpout,fileres);
1707: return tmpout;
1708: }
1709:
1710: /*************** function subdirf2 ***********/
1711: char *subdirf2(char fileres[], char *preop)
1712: {
1713:
1714: /* Caution optionfilefiname is hidden */
1715: strcpy(tmpout,optionfilefiname);
1716: strcat(tmpout,"/");
1717: strcat(tmpout,preop);
1718: strcat(tmpout,fileres);
1719: return tmpout;
1720: }
1721:
1722: /*************** function subdirf3 ***********/
1723: char *subdirf3(char fileres[], char *preop, char *preop2)
1724: {
1725:
1726: /* Caution optionfilefiname is hidden */
1727: strcpy(tmpout,optionfilefiname);
1728: strcat(tmpout,"/");
1729: strcat(tmpout,preop);
1730: strcat(tmpout,preop2);
1731: strcat(tmpout,fileres);
1732: return tmpout;
1733: }
1.213 brouard 1734:
1735: /*************** function subdirfext ***********/
1736: char *subdirfext(char fileres[], char *preop, char *postop)
1737: {
1738:
1739: strcpy(tmpout,preop);
1740: strcat(tmpout,fileres);
1741: strcat(tmpout,postop);
1742: return tmpout;
1743: }
1.126 brouard 1744:
1.213 brouard 1745: /*************** function subdirfext3 ***********/
1746: char *subdirfext3(char fileres[], char *preop, char *postop)
1747: {
1748:
1749: /* Caution optionfilefiname is hidden */
1750: strcpy(tmpout,optionfilefiname);
1751: strcat(tmpout,"/");
1752: strcat(tmpout,preop);
1753: strcat(tmpout,fileres);
1754: strcat(tmpout,postop);
1755: return tmpout;
1756: }
1757:
1.162 brouard 1758: char *asc_diff_time(long time_sec, char ascdiff[])
1759: {
1760: long sec_left, days, hours, minutes;
1761: days = (time_sec) / (60*60*24);
1762: sec_left = (time_sec) % (60*60*24);
1763: hours = (sec_left) / (60*60) ;
1764: sec_left = (sec_left) %(60*60);
1765: minutes = (sec_left) /60;
1766: sec_left = (sec_left) % (60);
1767: sprintf(ascdiff,"%ld day(s) %ld hour(s) %ld minute(s) %ld second(s)",days, hours, minutes, sec_left);
1768: return ascdiff;
1769: }
1770:
1.126 brouard 1771: /***************** f1dim *************************/
1772: extern int ncom;
1773: extern double *pcom,*xicom;
1774: extern double (*nrfunc)(double []);
1775:
1776: double f1dim(double x)
1777: {
1778: int j;
1779: double f;
1780: double *xt;
1781:
1782: xt=vector(1,ncom);
1783: for (j=1;j<=ncom;j++) xt[j]=pcom[j]+x*xicom[j];
1784: f=(*nrfunc)(xt);
1785: free_vector(xt,1,ncom);
1786: return f;
1787: }
1788:
1789: /*****************brent *************************/
1790: double brent(double ax, double bx, double cx, double (*f)(double), double tol, double *xmin)
1.187 brouard 1791: {
1792: /* Given a function f, and given a bracketing triplet of abscissas ax, bx, cx (such that bx is
1793: * between ax and cx, and f(bx) is less than both f(ax) and f(cx) ), this routine isolates
1794: * the minimum to a fractional precision of about tol using Brent’s method. The abscissa of
1795: * the minimum is returned as xmin, and the minimum function value is returned as brent , the
1796: * returned function value.
1797: */
1.126 brouard 1798: int iter;
1799: double a,b,d,etemp;
1.159 brouard 1800: double fu=0,fv,fw,fx;
1.164 brouard 1801: double ftemp=0.;
1.126 brouard 1802: double p,q,r,tol1,tol2,u,v,w,x,xm;
1803: double e=0.0;
1804:
1805: a=(ax < cx ? ax : cx);
1806: b=(ax > cx ? ax : cx);
1807: x=w=v=bx;
1808: fw=fv=fx=(*f)(x);
1809: for (iter=1;iter<=ITMAX;iter++) {
1810: xm=0.5*(a+b);
1811: tol2=2.0*(tol1=tol*fabs(x)+ZEPS);
1812: /* if (2.0*fabs(fp-(*fret)) <= ftol*(fabs(fp)+fabs(*fret)))*/
1813: printf(".");fflush(stdout);
1814: fprintf(ficlog,".");fflush(ficlog);
1.162 brouard 1815: #ifdef DEBUGBRENT
1.126 brouard 1816: 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);
1817: 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);
1818: /* if ((fabs(x-xm) <= (tol2-0.5*(b-a)))||(2.0*fabs(fu-ftemp) <= ftol*1.e-2*(fabs(fu)+fabs(ftemp)))) { */
1819: #endif
1820: if (fabs(x-xm) <= (tol2-0.5*(b-a))){
1821: *xmin=x;
1822: return fx;
1823: }
1824: ftemp=fu;
1825: if (fabs(e) > tol1) {
1826: r=(x-w)*(fx-fv);
1827: q=(x-v)*(fx-fw);
1828: p=(x-v)*q-(x-w)*r;
1829: q=2.0*(q-r);
1830: if (q > 0.0) p = -p;
1831: q=fabs(q);
1832: etemp=e;
1833: e=d;
1834: if (fabs(p) >= fabs(0.5*q*etemp) || p <= q*(a-x) || p >= q*(b-x))
1.224 brouard 1835: d=CGOLD*(e=(x >= xm ? a-x : b-x));
1.126 brouard 1836: else {
1.224 brouard 1837: d=p/q;
1838: u=x+d;
1839: if (u-a < tol2 || b-u < tol2)
1840: d=SIGN(tol1,xm-x);
1.126 brouard 1841: }
1842: } else {
1843: d=CGOLD*(e=(x >= xm ? a-x : b-x));
1844: }
1845: u=(fabs(d) >= tol1 ? x+d : x+SIGN(tol1,d));
1846: fu=(*f)(u);
1847: if (fu <= fx) {
1848: if (u >= x) a=x; else b=x;
1849: SHFT(v,w,x,u)
1.183 brouard 1850: SHFT(fv,fw,fx,fu)
1851: } else {
1852: if (u < x) a=u; else b=u;
1853: if (fu <= fw || w == x) {
1.224 brouard 1854: v=w;
1855: w=u;
1856: fv=fw;
1857: fw=fu;
1.183 brouard 1858: } else if (fu <= fv || v == x || v == w) {
1.224 brouard 1859: v=u;
1860: fv=fu;
1.183 brouard 1861: }
1862: }
1.126 brouard 1863: }
1864: nrerror("Too many iterations in brent");
1865: *xmin=x;
1866: return fx;
1867: }
1868:
1869: /****************** mnbrak ***********************/
1870:
1871: void mnbrak(double *ax, double *bx, double *cx, double *fa, double *fb, double *fc,
1872: double (*func)(double))
1.183 brouard 1873: { /* Given a function func , and given distinct initial points ax and bx , this routine searches in
1874: the downhill direction (defined by the function as evaluated at the initial points) and returns
1875: new points ax , bx , cx that bracket a minimum of the function. Also returned are the function
1876: values at the three points, fa, fb , and fc such that fa > fb and fb < fc.
1877: */
1.126 brouard 1878: double ulim,u,r,q, dum;
1879: double fu;
1.187 brouard 1880:
1881: double scale=10.;
1882: int iterscale=0;
1883:
1884: *fa=(*func)(*ax); /* xta[j]=pcom[j]+(*ax)*xicom[j]; fa=f(xta[j])*/
1885: *fb=(*func)(*bx); /* xtb[j]=pcom[j]+(*bx)*xicom[j]; fb=f(xtb[j]) */
1886:
1887:
1888: /* while(*fb != *fb){ /\* *ax should be ok, reducing distance to *ax *\/ */
1889: /* printf("Warning mnbrak *fb = %lf, *bx=%lf *ax=%lf *fa==%lf iter=%d\n",*fb, *bx, *ax, *fa, iterscale++); */
1890: /* *bx = *ax - (*ax - *bx)/scale; */
1891: /* *fb=(*func)(*bx); /\* xtb[j]=pcom[j]+(*bx)*xicom[j]; fb=f(xtb[j]) *\/ */
1892: /* } */
1893:
1.126 brouard 1894: if (*fb > *fa) {
1895: SHFT(dum,*ax,*bx,dum)
1.183 brouard 1896: SHFT(dum,*fb,*fa,dum)
1897: }
1.126 brouard 1898: *cx=(*bx)+GOLD*(*bx-*ax);
1899: *fc=(*func)(*cx);
1.183 brouard 1900: #ifdef DEBUG
1.224 brouard 1901: printf("mnbrak0 a=%lf *fa=%lf, b=%lf *fb=%lf, c=%lf *fc=%lf\n",*ax,*fa,*bx,*fb,*cx, *fc);
1902: 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 1903: #endif
1.224 brouard 1904: 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 1905: r=(*bx-*ax)*(*fb-*fc);
1.224 brouard 1906: q=(*bx-*cx)*(*fb-*fa); /* What if fa=inf */
1.126 brouard 1907: u=(*bx)-((*bx-*cx)*q-(*bx-*ax)*r)/
1.183 brouard 1908: (2.0*SIGN(FMAX(fabs(q-r),TINY),q-r)); /* Minimum abscissa of a parabolic estimated from (a,fa), (b,fb) and (c,fc). */
1909: ulim=(*bx)+GLIMIT*(*cx-*bx); /* Maximum abscissa where function should be evaluated */
1910: if ((*bx-u)*(u-*cx) > 0.0) { /* if u_p is between b and c */
1.126 brouard 1911: fu=(*func)(u);
1.163 brouard 1912: #ifdef DEBUG
1913: /* f(x)=A(x-u)**2+f(u) */
1914: double A, fparabu;
1915: A= (*fb - *fa)/(*bx-*ax)/(*bx+*ax-2*u);
1916: fparabu= *fa - A*(*ax-u)*(*ax-u);
1.224 brouard 1917: 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);
1918: 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 1919: /* And thus,it can be that fu > *fc even if fparabu < *fc */
1920: /* mnbrak (*ax=7.666299858533, *fa=299039.693133272231), (*bx=8.595447774979, *fb=298976.598289369489),
1921: (*cx=10.098840694817, *fc=298946.631474258087), (*u=9.852501168332, fu=298948.773013752128, fparabu=298945.434711494134) */
1922: /* In that case, there is no bracket in the output! Routine is wrong with many consequences.*/
1.163 brouard 1923: #endif
1.184 brouard 1924: #ifdef MNBRAKORIGINAL
1.183 brouard 1925: #else
1.191 brouard 1926: /* if (fu > *fc) { */
1927: /* #ifdef DEBUG */
1928: /* printf("mnbrak4 fu > fc \n"); */
1929: /* fprintf(ficlog, "mnbrak4 fu > fc\n"); */
1930: /* #endif */
1931: /* /\* 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 *\\/ *\/ */
1932: /* /\* SHFT(*fa,*fc,fu,*fc) /\\* (b, u, c) is a bracket while test fb > fc will be fu > fc will exit *\\/ *\/ */
1933: /* dum=u; /\* Shifting c and u *\/ */
1934: /* u = *cx; */
1935: /* *cx = dum; */
1936: /* dum = fu; */
1937: /* fu = *fc; */
1938: /* *fc =dum; */
1939: /* } else { /\* end *\/ */
1940: /* #ifdef DEBUG */
1941: /* printf("mnbrak3 fu < fc \n"); */
1942: /* fprintf(ficlog, "mnbrak3 fu < fc\n"); */
1943: /* #endif */
1944: /* dum=u; /\* Shifting c and u *\/ */
1945: /* u = *cx; */
1946: /* *cx = dum; */
1947: /* dum = fu; */
1948: /* fu = *fc; */
1949: /* *fc =dum; */
1950: /* } */
1.224 brouard 1951: #ifdef DEBUGMNBRAK
1952: double A, fparabu;
1953: A= (*fb - *fa)/(*bx-*ax)/(*bx+*ax-2*u);
1954: fparabu= *fa - A*(*ax-u)*(*ax-u);
1955: 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);
1956: 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 1957: #endif
1.191 brouard 1958: dum=u; /* Shifting c and u */
1959: u = *cx;
1960: *cx = dum;
1961: dum = fu;
1962: fu = *fc;
1963: *fc =dum;
1.183 brouard 1964: #endif
1.162 brouard 1965: } else if ((*cx-u)*(u-ulim) > 0.0) { /* u is after c but before ulim */
1.183 brouard 1966: #ifdef DEBUG
1.224 brouard 1967: printf("\nmnbrak2 u=%lf after c=%lf but before ulim\n",u,*cx);
1968: fprintf(ficlog,"\nmnbrak2 u=%lf after c=%lf but before ulim\n",u,*cx);
1.183 brouard 1969: #endif
1.126 brouard 1970: fu=(*func)(u);
1971: if (fu < *fc) {
1.183 brouard 1972: #ifdef DEBUG
1.224 brouard 1973: printf("\nmnbrak2 u=%lf after c=%lf but before ulim=%lf AND fu=%lf < %lf=fc\n",u,*cx,ulim,fu, *fc);
1974: fprintf(ficlog,"\nmnbrak2 u=%lf after c=%lf but before ulim=%lf AND fu=%lf < %lf=fc\n",u,*cx,ulim,fu, *fc);
1975: #endif
1976: SHFT(*bx,*cx,u,*cx+GOLD*(*cx-*bx))
1977: SHFT(*fb,*fc,fu,(*func)(u))
1978: #ifdef DEBUG
1979: printf("\nmnbrak2 shift GOLD c=%lf",*cx+GOLD*(*cx-*bx));
1.183 brouard 1980: #endif
1981: }
1.162 brouard 1982: } else if ((u-ulim)*(ulim-*cx) >= 0.0) { /* u outside ulim (verifying that ulim is beyond c) */
1.183 brouard 1983: #ifdef DEBUG
1.224 brouard 1984: printf("\nmnbrak2 u=%lf outside ulim=%lf (verifying that ulim is beyond c=%lf)\n",u,ulim,*cx);
1985: fprintf(ficlog,"\nmnbrak2 u=%lf outside ulim=%lf (verifying that ulim is beyond c=%lf)\n",u,ulim,*cx);
1.183 brouard 1986: #endif
1.126 brouard 1987: u=ulim;
1988: fu=(*func)(u);
1.183 brouard 1989: } else { /* u could be left to b (if r > q parabola has a maximum) */
1990: #ifdef DEBUG
1.224 brouard 1991: printf("\nmnbrak2 u=%lf could be left to b=%lf (if r=%lf > q=%lf parabola has a maximum)\n",u,*bx,r,q);
1992: 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 1993: #endif
1.126 brouard 1994: u=(*cx)+GOLD*(*cx-*bx);
1995: fu=(*func)(u);
1.224 brouard 1996: #ifdef DEBUG
1997: printf("\nmnbrak2 new u=%lf fu=%lf shifted gold left from c=%lf and b=%lf \n",u,fu,*cx,*bx);
1998: fprintf(ficlog,"\nmnbrak2 new u=%lf fu=%lf shifted gold left from c=%lf and b=%lf \n",u,fu,*cx,*bx);
1999: #endif
1.183 brouard 2000: } /* end tests */
1.126 brouard 2001: SHFT(*ax,*bx,*cx,u)
1.183 brouard 2002: SHFT(*fa,*fb,*fc,fu)
2003: #ifdef DEBUG
1.224 brouard 2004: printf("\nmnbrak2 shift (*ax=%.12f, *fa=%.12lf), (*bx=%.12f, *fb=%.12lf), (*cx=%.12f, *fc=%.12lf)\n",*ax,*fa,*bx,*fb,*cx,*fc);
2005: 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 2006: #endif
2007: } /* 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 2008: }
2009:
2010: /*************** linmin ************************/
1.162 brouard 2011: /* Given an n -dimensional point p[1..n] and an n -dimensional direction xi[1..n] , moves and
2012: resets p to where the function func(p) takes on a minimum along the direction xi from p ,
2013: and replaces xi by the actual vector displacement that p was moved. Also returns as fret
2014: the value of func at the returned location p . This is actually all accomplished by calling the
2015: routines mnbrak and brent .*/
1.126 brouard 2016: int ncom;
2017: double *pcom,*xicom;
2018: double (*nrfunc)(double []);
2019:
1.224 brouard 2020: #ifdef LINMINORIGINAL
1.126 brouard 2021: void linmin(double p[], double xi[], int n, double *fret,double (*func)(double []))
1.224 brouard 2022: #else
2023: void linmin(double p[], double xi[], int n, double *fret,double (*func)(double []), int *flat)
2024: #endif
1.126 brouard 2025: {
2026: double brent(double ax, double bx, double cx,
2027: double (*f)(double), double tol, double *xmin);
2028: double f1dim(double x);
2029: void mnbrak(double *ax, double *bx, double *cx, double *fa, double *fb,
2030: double *fc, double (*func)(double));
2031: int j;
2032: double xx,xmin,bx,ax;
2033: double fx,fb,fa;
1.187 brouard 2034:
1.203 brouard 2035: #ifdef LINMINORIGINAL
2036: #else
2037: double scale=10., axs, xxs; /* Scale added for infinity */
2038: #endif
2039:
1.126 brouard 2040: ncom=n;
2041: pcom=vector(1,n);
2042: xicom=vector(1,n);
2043: nrfunc=func;
2044: for (j=1;j<=n;j++) {
2045: pcom[j]=p[j];
1.202 brouard 2046: xicom[j]=xi[j]; /* Former scale xi[j] of currrent direction i */
1.126 brouard 2047: }
1.187 brouard 2048:
1.203 brouard 2049: #ifdef LINMINORIGINAL
2050: xx=1.;
2051: #else
2052: axs=0.0;
2053: xxs=1.;
2054: do{
2055: xx= xxs;
2056: #endif
1.187 brouard 2057: ax=0.;
2058: mnbrak(&ax,&xx,&bx,&fa,&fx,&fb,f1dim); /* Outputs: xtx[j]=pcom[j]+(*xx)*xicom[j]; fx=f(xtx[j]) */
2059: /* brackets with inputs ax=0 and xx=1, but points, pcom=p, and directions values, xicom=xi, are sent via f1dim(x) */
2060: /* 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)) */
2061: /* Outputs: fa=f(p(j)) and fx=f(p(j) + xxs * xi(j) ) and f(bx)= f(p(j)+ bx* xi(j)) */
2062: /* Given input ax=axs and xx=xxs, xx might be too far from ax to get a finite f(xx) */
2063: /* Searches on line, outputs (ax, xx, bx) such that fx < min(fa and fb) */
2064: /* 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 2065: #ifdef LINMINORIGINAL
2066: #else
2067: if (fx != fx){
1.224 brouard 2068: xxs=xxs/scale; /* Trying a smaller xx, closer to initial ax=0 */
2069: printf("|");
2070: fprintf(ficlog,"|");
1.203 brouard 2071: #ifdef DEBUGLINMIN
1.224 brouard 2072: 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 2073: #endif
2074: }
1.224 brouard 2075: }while(fx != fx && xxs > 1.e-5);
1.203 brouard 2076: #endif
2077:
1.191 brouard 2078: #ifdef DEBUGLINMIN
2079: 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 2080: 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 2081: #endif
1.224 brouard 2082: #ifdef LINMINORIGINAL
2083: #else
2084: if(fb == fx){ /* Flat function in the direction */
2085: xmin=xx;
2086: *flat=1;
2087: }else{
2088: *flat=0;
2089: #endif
2090: /*Flat mnbrak2 shift (*ax=0.000000000000, *fa=51626.272983130431), (*bx=-1.618034000000, *fb=51590.149499362531), (*cx=-4.236068025156, *fc=51590.149499362531) */
1.187 brouard 2091: *fret=brent(ax,xx,bx,f1dim,TOL,&xmin); /* Giving a bracketting triplet (ax, xx, bx), find a minimum, xmin, according to f1dim, *fret(xmin),*/
2092: /* fa = f(p[j] + ax * xi[j]), fx = f(p[j] + xx * xi[j]), fb = f(p[j] + bx * xi[j]) */
2093: /* fmin = f(p[j] + xmin * xi[j]) */
2094: /* P+lambda n in that direction (lambdamin), with TOL between abscisses */
2095: /* f1dim(xmin): for (j=1;j<=ncom;j++) xt[j]=pcom[j]+xmin*xicom[j]; */
1.126 brouard 2096: #ifdef DEBUG
1.224 brouard 2097: 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);
2098: 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);
2099: #endif
2100: #ifdef LINMINORIGINAL
2101: #else
2102: }
1.126 brouard 2103: #endif
1.191 brouard 2104: #ifdef DEBUGLINMIN
2105: printf("linmin end ");
1.202 brouard 2106: fprintf(ficlog,"linmin end ");
1.191 brouard 2107: #endif
1.126 brouard 2108: for (j=1;j<=n;j++) {
1.203 brouard 2109: #ifdef LINMINORIGINAL
2110: xi[j] *= xmin;
2111: #else
2112: #ifdef DEBUGLINMIN
2113: if(xxs <1.0)
2114: printf(" before xi[%d]=%12.8f", j,xi[j]);
2115: #endif
2116: 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) */
2117: #ifdef DEBUGLINMIN
2118: if(xxs <1.0)
2119: 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 );
2120: #endif
2121: #endif
1.187 brouard 2122: p[j] += xi[j]; /* Parameters values are updated accordingly */
1.126 brouard 2123: }
1.191 brouard 2124: #ifdef DEBUGLINMIN
1.203 brouard 2125: printf("\n");
1.191 brouard 2126: printf("Comparing last *frec(xmin=%12.8f)=%12.8f from Brent and frec(0.)=%12.8f \n", xmin, *fret, (*func)(p));
1.202 brouard 2127: 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 2128: for (j=1;j<=n;j++) {
1.202 brouard 2129: printf(" xi[%d]= %14.10f p[%d]= %12.7f",j,xi[j],j,p[j]);
2130: fprintf(ficlog," xi[%d]= %14.10f p[%d]= %12.7f",j,xi[j],j,p[j]);
2131: if(j % ncovmodel == 0){
1.191 brouard 2132: printf("\n");
1.202 brouard 2133: fprintf(ficlog,"\n");
2134: }
1.191 brouard 2135: }
1.203 brouard 2136: #else
1.191 brouard 2137: #endif
1.126 brouard 2138: free_vector(xicom,1,n);
2139: free_vector(pcom,1,n);
2140: }
2141:
2142:
2143: /*************** powell ************************/
1.162 brouard 2144: /*
2145: Minimization of a function func of n variables. Input consists of an initial starting point
2146: p[1..n] ; an initial matrix xi[1..n][1..n] , whose columns contain the initial set of di-
2147: rections (usually the n unit vectors); and ftol , the fractional tolerance in the function value
2148: such that failure to decrease by more than this amount on one iteration signals doneness. On
2149: output, p is set to the best point found, xi is the then-current direction set, fret is the returned
2150: function value at p , and iter is the number of iterations taken. The routine linmin is used.
2151: */
1.224 brouard 2152: #ifdef LINMINORIGINAL
2153: #else
2154: int *flatdir; /* Function is vanishing in that direction */
1.225 brouard 2155: int flat=0, flatd=0; /* Function is vanishing in that direction */
1.224 brouard 2156: #endif
1.126 brouard 2157: void powell(double p[], double **xi, int n, double ftol, int *iter, double *fret,
2158: double (*func)(double []))
2159: {
1.224 brouard 2160: #ifdef LINMINORIGINAL
2161: void linmin(double p[], double xi[], int n, double *fret,
1.126 brouard 2162: double (*func)(double []));
1.224 brouard 2163: #else
1.241 brouard 2164: void linmin(double p[], double xi[], int n, double *fret,
2165: double (*func)(double []),int *flat);
1.224 brouard 2166: #endif
1.239 brouard 2167: int i,ibig,j,jk,k;
1.126 brouard 2168: double del,t,*pt,*ptt,*xit;
1.181 brouard 2169: double directest;
1.126 brouard 2170: double fp,fptt;
2171: double *xits;
2172: int niterf, itmp;
1.224 brouard 2173: #ifdef LINMINORIGINAL
2174: #else
2175:
2176: flatdir=ivector(1,n);
2177: for (j=1;j<=n;j++) flatdir[j]=0;
2178: #endif
1.126 brouard 2179:
2180: pt=vector(1,n);
2181: ptt=vector(1,n);
2182: xit=vector(1,n);
2183: xits=vector(1,n);
2184: *fret=(*func)(p);
2185: for (j=1;j<=n;j++) pt[j]=p[j];
1.202 brouard 2186: rcurr_time = time(NULL);
1.126 brouard 2187: for (*iter=1;;++(*iter)) {
1.187 brouard 2188: fp=(*fret); /* From former iteration or initial value */
1.126 brouard 2189: ibig=0;
2190: del=0.0;
1.157 brouard 2191: rlast_time=rcurr_time;
2192: /* (void) gettimeofday(&curr_time,&tzp); */
2193: rcurr_time = time(NULL);
2194: curr_time = *localtime(&rcurr_time);
2195: printf("\nPowell iter=%d -2*LL=%.12f %ld sec. %ld sec.",*iter,*fret, rcurr_time-rlast_time, rcurr_time-rstart_time);fflush(stdout);
2196: fprintf(ficlog,"\nPowell iter=%d -2*LL=%.12f %ld sec. %ld sec.",*iter,*fret,rcurr_time-rlast_time, rcurr_time-rstart_time); fflush(ficlog);
2197: /* fprintf(ficrespow,"%d %.12f %ld",*iter,*fret,curr_time.tm_sec-start_time.tm_sec); */
1.192 brouard 2198: for (i=1;i<=n;i++) {
1.126 brouard 2199: fprintf(ficrespow," %.12lf", p[i]);
2200: }
1.239 brouard 2201: fprintf(ficrespow,"\n");fflush(ficrespow);
2202: printf("\n#model= 1 + age ");
2203: fprintf(ficlog,"\n#model= 1 + age ");
2204: if(nagesqr==1){
1.241 brouard 2205: printf(" + age*age ");
2206: fprintf(ficlog," + age*age ");
1.239 brouard 2207: }
2208: for(j=1;j <=ncovmodel-2;j++){
2209: if(Typevar[j]==0) {
2210: printf(" + V%d ",Tvar[j]);
2211: fprintf(ficlog," + V%d ",Tvar[j]);
2212: }else if(Typevar[j]==1) {
2213: printf(" + V%d*age ",Tvar[j]);
2214: fprintf(ficlog," + V%d*age ",Tvar[j]);
2215: }else if(Typevar[j]==2) {
2216: printf(" + V%d*V%d ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
2217: fprintf(ficlog," + V%d*V%d ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
2218: }
2219: }
1.126 brouard 2220: printf("\n");
1.239 brouard 2221: /* printf("12 47.0114589 0.0154322 33.2424412 0.3279905 2.3731903 */
2222: /* 13 -21.5392400 0.1118147 1.2680506 1.2973408 -1.0663662 */
1.126 brouard 2223: fprintf(ficlog,"\n");
1.239 brouard 2224: for(i=1,jk=1; i <=nlstate; i++){
2225: for(k=1; k <=(nlstate+ndeath); k++){
2226: if (k != i) {
2227: printf("%d%d ",i,k);
2228: fprintf(ficlog,"%d%d ",i,k);
2229: for(j=1; j <=ncovmodel; j++){
2230: printf("%12.7f ",p[jk]);
2231: fprintf(ficlog,"%12.7f ",p[jk]);
2232: jk++;
2233: }
2234: printf("\n");
2235: fprintf(ficlog,"\n");
2236: }
2237: }
2238: }
1.241 brouard 2239: if(*iter <=3 && *iter >1){
1.157 brouard 2240: tml = *localtime(&rcurr_time);
2241: strcpy(strcurr,asctime(&tml));
2242: rforecast_time=rcurr_time;
1.126 brouard 2243: itmp = strlen(strcurr);
2244: if(strcurr[itmp-1]=='\n') /* Windows outputs with a new line */
1.241 brouard 2245: strcurr[itmp-1]='\0';
1.162 brouard 2246: printf("\nConsidering the time needed for the last iteration #%d: %ld seconds,\n",*iter,rcurr_time-rlast_time);
1.157 brouard 2247: fprintf(ficlog,"\nConsidering the time needed for this last iteration #%d: %ld seconds,\n",*iter,rcurr_time-rlast_time);
1.126 brouard 2248: for(niterf=10;niterf<=30;niterf+=10){
1.241 brouard 2249: rforecast_time=rcurr_time+(niterf-*iter)*(rcurr_time-rlast_time);
2250: forecast_time = *localtime(&rforecast_time);
2251: strcpy(strfor,asctime(&forecast_time));
2252: itmp = strlen(strfor);
2253: if(strfor[itmp-1]=='\n')
2254: strfor[itmp-1]='\0';
2255: 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);
2256: 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 2257: }
2258: }
1.187 brouard 2259: for (i=1;i<=n;i++) { /* For each direction i */
2260: for (j=1;j<=n;j++) xit[j]=xi[j][i]; /* Directions stored from previous iteration with previous scales */
1.126 brouard 2261: fptt=(*fret);
2262: #ifdef DEBUG
1.203 brouard 2263: printf("fret=%lf, %lf, %lf \n", *fret, *fret, *fret);
2264: fprintf(ficlog, "fret=%lf, %lf, %lf \n", *fret, *fret, *fret);
1.126 brouard 2265: #endif
1.203 brouard 2266: printf("%d",i);fflush(stdout); /* print direction (parameter) i */
1.126 brouard 2267: fprintf(ficlog,"%d",i);fflush(ficlog);
1.224 brouard 2268: #ifdef LINMINORIGINAL
1.188 brouard 2269: linmin(p,xit,n,fret,func); /* Point p[n]. xit[n] has been loaded for direction i as input.*/
1.224 brouard 2270: #else
2271: linmin(p,xit,n,fret,func,&flat); /* Point p[n]. xit[n] has been loaded for direction i as input.*/
2272: flatdir[i]=flat; /* Function is vanishing in that direction i */
2273: #endif
2274: /* Outputs are fret(new point p) p is updated and xit rescaled */
1.188 brouard 2275: if (fabs(fptt-(*fret)) > del) { /* We are keeping the max gain on each of the n directions */
1.224 brouard 2276: /* because that direction will be replaced unless the gain del is small */
2277: /* in comparison with the 'probable' gain, mu^2, with the last average direction. */
2278: /* Unless the n directions are conjugate some gain in the determinant may be obtained */
2279: /* with the new direction. */
2280: del=fabs(fptt-(*fret));
2281: ibig=i;
1.126 brouard 2282: }
2283: #ifdef DEBUG
2284: printf("%d %.12e",i,(*fret));
2285: fprintf(ficlog,"%d %.12e",i,(*fret));
2286: for (j=1;j<=n;j++) {
1.224 brouard 2287: xits[j]=FMAX(fabs(p[j]-pt[j]),1.e-5);
2288: printf(" x(%d)=%.12e",j,xit[j]);
2289: fprintf(ficlog," x(%d)=%.12e",j,xit[j]);
1.126 brouard 2290: }
2291: for(j=1;j<=n;j++) {
1.225 brouard 2292: printf(" p(%d)=%.12e",j,p[j]);
2293: fprintf(ficlog," p(%d)=%.12e",j,p[j]);
1.126 brouard 2294: }
2295: printf("\n");
2296: fprintf(ficlog,"\n");
2297: #endif
1.187 brouard 2298: } /* end loop on each direction i */
2299: /* Convergence test will use last linmin estimation (fret) and compare former iteration (fp) */
1.188 brouard 2300: /* But p and xit have been updated at the end of linmin, *fret corresponds to new p, xit */
1.187 brouard 2301: /* New value of last point Pn is not computed, P(n-1) */
1.224 brouard 2302: for(j=1;j<=n;j++) {
1.225 brouard 2303: if(flatdir[j] >0){
2304: printf(" p(%d)=%lf flat=%d ",j,p[j],flatdir[j]);
2305: fprintf(ficlog," p(%d)=%lf flat=%d ",j,p[j],flatdir[j]);
2306: }
2307: /* printf("\n"); */
2308: /* fprintf(ficlog,"\n"); */
2309: }
1.243 brouard 2310: /* if (2.0*fabs(fp-(*fret)) <= ftol*(fabs(fp)+fabs(*fret))) { /\* Did we reach enough precision? *\/ */
2311: if (2.0*fabs(fp-(*fret)) <= ftol) { /* Did we reach enough precision? */
1.188 brouard 2312: /* We could compare with a chi^2. chisquare(0.95,ddl=1)=3.84 */
2313: /* By adding age*age in a model, the new -2LL should be lower and the difference follows a */
2314: /* a chisquare statistics with 1 degree. To be significant at the 95% level, it should have */
2315: /* decreased of more than 3.84 */
2316: /* By adding age*age and V1*age the gain (-2LL) should be more than 5.99 (ddl=2) */
2317: /* By using V1+V2+V3, the gain should be 7.82, compared with basic 1+age. */
2318: /* By adding 10 parameters more the gain should be 18.31 */
1.224 brouard 2319:
1.188 brouard 2320: /* Starting the program with initial values given by a former maximization will simply change */
2321: /* the scales of the directions and the directions, because the are reset to canonical directions */
2322: /* Thus the first calls to linmin will give new points and better maximizations until fp-(*fret) is */
2323: /* under the tolerance value. If the tolerance is very small 1.e-9, it could last long. */
1.126 brouard 2324: #ifdef DEBUG
2325: int k[2],l;
2326: k[0]=1;
2327: k[1]=-1;
2328: printf("Max: %.12e",(*func)(p));
2329: fprintf(ficlog,"Max: %.12e",(*func)(p));
2330: for (j=1;j<=n;j++) {
2331: printf(" %.12e",p[j]);
2332: fprintf(ficlog," %.12e",p[j]);
2333: }
2334: printf("\n");
2335: fprintf(ficlog,"\n");
2336: for(l=0;l<=1;l++) {
2337: for (j=1;j<=n;j++) {
2338: ptt[j]=p[j]+(p[j]-pt[j])*k[l];
2339: printf("l=%d j=%d ptt=%.12e, xits=%.12e, p=%.12e, xit=%.12e", l,j,ptt[j],xits[j],p[j],xit[j]);
2340: fprintf(ficlog,"l=%d j=%d ptt=%.12e, xits=%.12e, p=%.12e, xit=%.12e", l,j,ptt[j],xits[j],p[j],xit[j]);
2341: }
2342: printf("func(ptt)=%.12e, deriv=%.12e\n",(*func)(ptt),(ptt[j]-p[j])/((*func)(ptt)-(*func)(p)));
2343: fprintf(ficlog,"func(ptt)=%.12e, deriv=%.12e\n",(*func)(ptt),(ptt[j]-p[j])/((*func)(ptt)-(*func)(p)));
2344: }
2345: #endif
2346:
1.224 brouard 2347: #ifdef LINMINORIGINAL
2348: #else
2349: free_ivector(flatdir,1,n);
2350: #endif
1.126 brouard 2351: free_vector(xit,1,n);
2352: free_vector(xits,1,n);
2353: free_vector(ptt,1,n);
2354: free_vector(pt,1,n);
2355: return;
1.192 brouard 2356: } /* enough precision */
1.240 brouard 2357: if (*iter == ITMAX*n) nrerror("powell exceeding maximum iterations.");
1.181 brouard 2358: for (j=1;j<=n;j++) { /* Computes the extrapolated point P_0 + 2 (P_n-P_0) */
1.126 brouard 2359: ptt[j]=2.0*p[j]-pt[j];
2360: xit[j]=p[j]-pt[j];
2361: pt[j]=p[j];
2362: }
1.181 brouard 2363: fptt=(*func)(ptt); /* f_3 */
1.224 brouard 2364: #ifdef NODIRECTIONCHANGEDUNTILNITER /* No change in drections until some iterations are done */
2365: if (*iter <=4) {
1.225 brouard 2366: #else
2367: #endif
1.224 brouard 2368: #ifdef POWELLNOF3INFF1TEST /* skips test F3 <F1 */
1.192 brouard 2369: #else
1.161 brouard 2370: if (fptt < fp) { /* If extrapolated point is better, decide if we keep that new direction or not */
1.192 brouard 2371: #endif
1.162 brouard 2372: /* (x1 f1=fp), (x2 f2=*fret), (x3 f3=fptt), (xm fm) */
1.161 brouard 2373: /* From x1 (P0) distance of x2 is at h and x3 is 2h */
1.162 brouard 2374: /* Let f"(x2) be the 2nd derivative equal everywhere. */
2375: /* Then the parabolic through (x1,f1), (x2,f2) and (x3,f3) */
2376: /* will reach at f3 = fm + h^2/2 f"m ; f" = (f1 -2f2 +f3 ) / h**2 */
1.224 brouard 2377: /* Conditional for using this new direction is that mu^2 = (f1-2f2+f3)^2 /2 < del or directest <0 */
2378: /* also lamda^2=(f1-f2)^2/mu² is a parasite solution of powell */
2379: /* For powell, inclusion of this average direction is only if t(del)<0 or del inbetween mu^2 and lambda^2 */
1.161 brouard 2380: /* t=2.0*(fp-2.0*(*fret)+fptt)*SQR(fp-(*fret)-del)-del*SQR(fp-fptt); */
1.224 brouard 2381: /* Even if f3 <f1, directest can be negative and t >0 */
2382: /* mu² and del² are equal when f3=f1 */
2383: /* f3 < f1 : mu² < del <= lambda^2 both test are equivalent */
2384: /* f3 < f1 : mu² < lambda^2 < del then directtest is negative and powell t is positive */
2385: /* f3 > f1 : lambda² < mu^2 < del then t is negative and directest >0 */
2386: /* f3 > f1 : lambda² < del < mu^2 then t is positive and directest >0 */
1.183 brouard 2387: #ifdef NRCORIGINAL
2388: t=2.0*(fp-2.0*(*fret)+fptt)*SQR(fp-(*fret)-del)- del*SQR(fp-fptt); /* Original Numerical Recipes in C*/
2389: #else
2390: 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 2391: t= t- del*SQR(fp-fptt);
1.183 brouard 2392: #endif
1.202 brouard 2393: directest = fp-2.0*(*fret)+fptt - 2.0 * del; /* If delta was big enough we change it for a new direction */
1.161 brouard 2394: #ifdef DEBUG
1.181 brouard 2395: 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);
2396: 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 2397: printf("t3= %.12lf, t4= %.12lf, t3*= %.12lf, t4*= %.12lf\n",SQR(fp-(*fret)-del),SQR(fp-fptt),
2398: (fp-(*fret)-del)*(fp-(*fret)-del),(fp-fptt)*(fp-fptt));
2399: fprintf(ficlog,"t3= %.12lf, t4= %.12lf, t3*= %.12lf, t4*= %.12lf\n",SQR(fp-(*fret)-del),SQR(fp-fptt),
2400: (fp-(*fret)-del)*(fp-(*fret)-del),(fp-fptt)*(fp-fptt));
2401: 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);
2402: 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);
2403: #endif
1.183 brouard 2404: #ifdef POWELLORIGINAL
2405: if (t < 0.0) { /* Then we use it for new direction */
2406: #else
1.182 brouard 2407: if (directest*t < 0.0) { /* Contradiction between both tests */
1.224 brouard 2408: 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 2409: 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 2410: 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 2411: fprintf(ficlog,"f1-2f2+f3= %.12lf, f1-f2-del= %.12lf, f1-f3= %.12lf\n",fp-2.0*(*fret)+fptt, fp -(*fret) -del, fp-fptt);
2412: }
1.181 brouard 2413: if (directest < 0.0) { /* Then we use it for new direction */
2414: #endif
1.191 brouard 2415: #ifdef DEBUGLINMIN
1.234 brouard 2416: printf("Before linmin in direction P%d-P0\n",n);
2417: for (j=1;j<=n;j++) {
2418: printf(" Before xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
2419: fprintf(ficlog," Before xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
2420: if(j % ncovmodel == 0){
2421: printf("\n");
2422: fprintf(ficlog,"\n");
2423: }
2424: }
1.224 brouard 2425: #endif
2426: #ifdef LINMINORIGINAL
1.234 brouard 2427: linmin(p,xit,n,fret,func); /* computes minimum on the extrapolated direction: changes p and rescales xit.*/
1.224 brouard 2428: #else
1.234 brouard 2429: linmin(p,xit,n,fret,func,&flat); /* computes minimum on the extrapolated direction: changes p and rescales xit.*/
2430: flatdir[i]=flat; /* Function is vanishing in that direction i */
1.191 brouard 2431: #endif
1.234 brouard 2432:
1.191 brouard 2433: #ifdef DEBUGLINMIN
1.234 brouard 2434: for (j=1;j<=n;j++) {
2435: printf("After xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
2436: fprintf(ficlog,"After xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
2437: if(j % ncovmodel == 0){
2438: printf("\n");
2439: fprintf(ficlog,"\n");
2440: }
2441: }
1.224 brouard 2442: #endif
1.234 brouard 2443: for (j=1;j<=n;j++) {
2444: xi[j][ibig]=xi[j][n]; /* Replace direction with biggest decrease by last direction n */
2445: xi[j][n]=xit[j]; /* and this nth direction by the by the average p_0 p_n */
2446: }
1.224 brouard 2447: #ifdef LINMINORIGINAL
2448: #else
1.234 brouard 2449: for (j=1, flatd=0;j<=n;j++) {
2450: if(flatdir[j]>0)
2451: flatd++;
2452: }
2453: if(flatd >0){
1.255 brouard 2454: printf("%d flat directions: ",flatd);
2455: fprintf(ficlog,"%d flat directions :",flatd);
1.234 brouard 2456: for (j=1;j<=n;j++) {
2457: if(flatdir[j]>0){
2458: printf("%d ",j);
2459: fprintf(ficlog,"%d ",j);
2460: }
2461: }
2462: printf("\n");
2463: fprintf(ficlog,"\n");
2464: }
1.191 brouard 2465: #endif
1.234 brouard 2466: printf("Gaining to use new average direction of P0 P%d instead of biggest increase direction %d :\n",n,ibig);
2467: fprintf(ficlog,"Gaining to use new average direction of P0 P%d instead of biggest increase direction %d :\n",n,ibig);
2468:
1.126 brouard 2469: #ifdef DEBUG
1.234 brouard 2470: printf("Direction changed last moved %d in place of ibig=%d, new last is the average:\n",n,ibig);
2471: fprintf(ficlog,"Direction changed last moved %d in place of ibig=%d, new last is the average:\n",n,ibig);
2472: for(j=1;j<=n;j++){
2473: printf(" %lf",xit[j]);
2474: fprintf(ficlog," %lf",xit[j]);
2475: }
2476: printf("\n");
2477: fprintf(ficlog,"\n");
1.126 brouard 2478: #endif
1.192 brouard 2479: } /* end of t or directest negative */
1.224 brouard 2480: #ifdef POWELLNOF3INFF1TEST
1.192 brouard 2481: #else
1.234 brouard 2482: } /* end if (fptt < fp) */
1.192 brouard 2483: #endif
1.225 brouard 2484: #ifdef NODIRECTIONCHANGEDUNTILNITER /* No change in drections until some iterations are done */
1.234 brouard 2485: } /*NODIRECTIONCHANGEDUNTILNITER No change in drections until some iterations are done */
1.225 brouard 2486: #else
1.224 brouard 2487: #endif
1.234 brouard 2488: } /* loop iteration */
1.126 brouard 2489: }
1.234 brouard 2490:
1.126 brouard 2491: /**** Prevalence limit (stable or period prevalence) ****************/
1.234 brouard 2492:
1.235 brouard 2493: 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 2494: {
1.235 brouard 2495: /* Computes the prevalence limit in each live state at age x and for covariate combination ij
2496: (and selected quantitative values in nres)
2497: by left multiplying the unit
1.234 brouard 2498: matrix by transitions matrix until convergence is reached with precision ftolpl */
1.206 brouard 2499: /* Wx= Wx-1 Px-1= Wx-2 Px-2 Px-1 = Wx-n Px-n ... Px-2 Px-1 I */
2500: /* Wx is row vector: population in state 1, population in state 2, population dead */
2501: /* or prevalence in state 1, prevalence in state 2, 0 */
2502: /* newm is the matrix after multiplications, its rows are identical at a factor */
2503: /* Initial matrix pimij */
2504: /* {0.85204250825084937, 0.13044499163996345, 0.017512500109187184, */
2505: /* 0.090851990222114765, 0.88271245433047185, 0.026435555447413338, */
2506: /* 0, 0 , 1} */
2507: /*
2508: * and after some iteration: */
2509: /* {0.45504275246439968, 0.42731458730878791, 0.11764266022681241, */
2510: /* 0.45201005341706885, 0.42865420071559901, 0.11933574586733192, */
2511: /* 0, 0 , 1} */
2512: /* And prevalence by suppressing the deaths are close to identical rows in prlim: */
2513: /* {0.51571254859325999, 0.4842874514067399, */
2514: /* 0.51326036147820708, 0.48673963852179264} */
2515: /* If we start from prlim again, prlim tends to a constant matrix */
1.234 brouard 2516:
1.126 brouard 2517: int i, ii,j,k;
1.209 brouard 2518: double *min, *max, *meandiff, maxmax,sumnew=0.;
1.145 brouard 2519: /* double **matprod2(); */ /* test */
1.218 brouard 2520: double **out, cov[NCOVMAX+1], **pmij(); /* **pmmij is a global variable feeded with oldms etc */
1.126 brouard 2521: double **newm;
1.209 brouard 2522: double agefin, delaymax=200. ; /* 100 Max number of years to converge */
1.203 brouard 2523: int ncvloop=0;
1.169 brouard 2524:
1.209 brouard 2525: min=vector(1,nlstate);
2526: max=vector(1,nlstate);
2527: meandiff=vector(1,nlstate);
2528:
1.218 brouard 2529: /* Starting with matrix unity */
1.126 brouard 2530: for (ii=1;ii<=nlstate+ndeath;ii++)
2531: for (j=1;j<=nlstate+ndeath;j++){
2532: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
2533: }
1.169 brouard 2534:
2535: cov[1]=1.;
2536:
2537: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
1.202 brouard 2538: /* Start at agefin= age, computes the matrix of passage and loops decreasing agefin until convergence is reached */
1.126 brouard 2539: for(agefin=age-stepm/YEARM; agefin>=age-delaymax; agefin=agefin-stepm/YEARM){
1.202 brouard 2540: ncvloop++;
1.126 brouard 2541: newm=savm;
2542: /* Covariates have to be included here again */
1.138 brouard 2543: cov[2]=agefin;
1.187 brouard 2544: if(nagesqr==1)
2545: cov[3]= agefin*agefin;;
1.234 brouard 2546: for (k=1; k<=nsd;k++) { /* For single dummy covariates only */
2547: /* Here comes the value of the covariate 'ij' after renumbering k with single dummy covariates */
2548: cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,k)];
1.235 brouard 2549: /* 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 2550: }
2551: for (k=1; k<=nsq;k++) { /* For single varying covariates only */
2552: /* Here comes the value of quantitative after renumbering k with single quantitative covariates */
1.235 brouard 2553: cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k];
2554: /* 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 2555: }
1.237 brouard 2556: for (k=1; k<=cptcovage;k++){ /* For product with age */
1.234 brouard 2557: if(Dummy[Tvar[Tage[k]]]){
2558: cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2];
2559: } else{
1.235 brouard 2560: cov[2+nagesqr+Tage[k]]=Tqresult[nres][k];
1.234 brouard 2561: }
1.235 brouard 2562: /* 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 2563: }
1.237 brouard 2564: for (k=1; k<=cptcovprod;k++){ /* For product without age */
1.235 brouard 2565: /* 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 2566: if(Dummy[Tvard[k][1]==0]){
2567: if(Dummy[Tvard[k][2]==0]){
2568: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)];
2569: }else{
2570: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * Tqresult[nres][k];
2571: }
2572: }else{
2573: if(Dummy[Tvard[k][2]==0]){
2574: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][2]][codtabm(ij,k)] * Tqinvresult[nres][Tvard[k][1]];
2575: }else{
2576: cov[2+nagesqr+Tprod[k]]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]];
2577: }
2578: }
1.234 brouard 2579: }
1.138 brouard 2580: /*printf("ij=%d cptcovprod=%d tvar=%d ", ij, cptcovprod, Tvar[1]);*/
2581: /*printf("ij=%d cov[3]=%lf cov[4]=%lf \n",ij, cov[3],cov[4]);*/
2582: /*printf("ij=%d cov[3]=%lf \n",ij, cov[3]);*/
1.145 brouard 2583: /* savm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
2584: /* out=matprod2(newm, pmij(pmmij,cov,ncovmodel,x,nlstate),1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); /\* Bug Valgrind *\/ */
1.218 brouard 2585: /* age and covariate values of ij are in 'cov' */
1.142 brouard 2586: out=matprod2(newm, pmij(pmmij,cov,ncovmodel,x,nlstate),1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); /* Bug Valgrind */
1.138 brouard 2587:
1.126 brouard 2588: savm=oldm;
2589: oldm=newm;
1.209 brouard 2590:
2591: for(j=1; j<=nlstate; j++){
2592: max[j]=0.;
2593: min[j]=1.;
2594: }
2595: for(i=1;i<=nlstate;i++){
2596: sumnew=0;
2597: for(k=1; k<=ndeath; k++) sumnew+=newm[i][nlstate+k];
2598: for(j=1; j<=nlstate; j++){
2599: prlim[i][j]= newm[i][j]/(1-sumnew);
2600: max[j]=FMAX(max[j],prlim[i][j]);
2601: min[j]=FMIN(min[j],prlim[i][j]);
2602: }
2603: }
2604:
1.126 brouard 2605: maxmax=0.;
1.209 brouard 2606: for(j=1; j<=nlstate; j++){
2607: meandiff[j]=(max[j]-min[j])/(max[j]+min[j])*2.; /* mean difference for each column */
2608: maxmax=FMAX(maxmax,meandiff[j]);
2609: /* 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 2610: } /* j loop */
1.203 brouard 2611: *ncvyear= (int)age- (int)agefin;
1.208 brouard 2612: /* 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 2613: if(maxmax < ftolpl){
1.209 brouard 2614: /* printf("maxmax=%lf ncvloop=%ld, age=%d, agefin=%d ncvyear=%d \n", maxmax, ncvloop, (int)age, (int)agefin, *ncvyear); */
2615: free_vector(min,1,nlstate);
2616: free_vector(max,1,nlstate);
2617: free_vector(meandiff,1,nlstate);
1.126 brouard 2618: return prlim;
2619: }
1.169 brouard 2620: } /* age loop */
1.208 brouard 2621: /* After some age loop it doesn't converge */
1.209 brouard 2622: 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 2623: 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 2624: /* 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); */
2625: free_vector(min,1,nlstate);
2626: free_vector(max,1,nlstate);
2627: free_vector(meandiff,1,nlstate);
1.208 brouard 2628:
1.169 brouard 2629: return prlim; /* should not reach here */
1.126 brouard 2630: }
2631:
1.217 brouard 2632:
2633: /**** Back Prevalence limit (stable or period prevalence) ****************/
2634:
1.218 brouard 2635: /* 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) */
2636: /* 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 2637: double **bprevalim(double **bprlim, double ***prevacurrent, int nlstate, double x[], double age, double ftolpl, int *ncvyear, int ij, int nres)
1.217 brouard 2638: {
1.264 brouard 2639: /* 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 2640: matrix by transitions matrix until convergence is reached with precision ftolpl */
2641: /* Wx= Wx-1 Px-1= Wx-2 Px-2 Px-1 = Wx-n Px-n ... Px-2 Px-1 I */
2642: /* Wx is row vector: population in state 1, population in state 2, population dead */
2643: /* or prevalence in state 1, prevalence in state 2, 0 */
2644: /* newm is the matrix after multiplications, its rows are identical at a factor */
2645: /* Initial matrix pimij */
2646: /* {0.85204250825084937, 0.13044499163996345, 0.017512500109187184, */
2647: /* 0.090851990222114765, 0.88271245433047185, 0.026435555447413338, */
2648: /* 0, 0 , 1} */
2649: /*
2650: * and after some iteration: */
2651: /* {0.45504275246439968, 0.42731458730878791, 0.11764266022681241, */
2652: /* 0.45201005341706885, 0.42865420071559901, 0.11933574586733192, */
2653: /* 0, 0 , 1} */
2654: /* And prevalence by suppressing the deaths are close to identical rows in prlim: */
2655: /* {0.51571254859325999, 0.4842874514067399, */
2656: /* 0.51326036147820708, 0.48673963852179264} */
2657: /* If we start from prlim again, prlim tends to a constant matrix */
2658:
2659: int i, ii,j,k;
1.247 brouard 2660: int first=0;
1.217 brouard 2661: double *min, *max, *meandiff, maxmax,sumnew=0.;
2662: /* double **matprod2(); */ /* test */
2663: double **out, cov[NCOVMAX+1], **bmij();
2664: double **newm;
1.218 brouard 2665: double **dnewm, **doldm, **dsavm; /* for use */
2666: double **oldm, **savm; /* for use */
2667:
1.217 brouard 2668: double agefin, delaymax=200. ; /* 100 Max number of years to converge */
2669: int ncvloop=0;
2670:
2671: min=vector(1,nlstate);
2672: max=vector(1,nlstate);
2673: meandiff=vector(1,nlstate);
2674:
1.266 brouard 2675: dnewm=ddnewms; doldm=ddoldms; dsavm=ddsavms;
2676: oldm=oldms; savm=savms;
2677:
2678: /* Starting with matrix unity */
2679: for (ii=1;ii<=nlstate+ndeath;ii++)
2680: for (j=1;j<=nlstate+ndeath;j++){
1.217 brouard 2681: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
2682: }
2683:
2684: cov[1]=1.;
2685:
2686: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
2687: /* Start at agefin= age, computes the matrix of passage and loops decreasing agefin until convergence is reached */
1.218 brouard 2688: /* for(agefin=age+stepm/YEARM; agefin<=age+delaymax; agefin=agefin+stepm/YEARM){ /\* A changer en age *\/ */
2689: for(agefin=age; agefin<AGESUP; agefin=agefin+stepm/YEARM){ /* A changer en age */
1.217 brouard 2690: ncvloop++;
1.218 brouard 2691: newm=savm; /* oldm should be kept from previous iteration or unity at start */
2692: /* newm points to the allocated table savm passed by the function it can be written, savm could be reallocated */
1.217 brouard 2693: /* Covariates have to be included here again */
2694: cov[2]=agefin;
2695: if(nagesqr==1)
2696: cov[3]= agefin*agefin;;
1.242 brouard 2697: for (k=1; k<=nsd;k++) { /* For single dummy covariates only */
2698: /* Here comes the value of the covariate 'ij' after renumbering k with single dummy covariates */
2699: cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,k)];
1.264 brouard 2700: /* 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 2701: }
2702: /* for (k=1; k<=cptcovn;k++) { */
2703: /* /\* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,Tvar[k])]; *\/ */
2704: /* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,k)]; */
2705: /* /\* 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])]); *\/ */
2706: /* } */
2707: for (k=1; k<=nsq;k++) { /* For single varying covariates only */
2708: /* Here comes the value of quantitative after renumbering k with single quantitative covariates */
2709: cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k];
2710: /* 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]); */
2711: }
2712: /* for (k=1; k<=cptcovage;k++) cov[2+nagesqr+Tage[k]]=nbcode[Tvar[k]][codtabm(ij,k)]*cov[2]; */
2713: /* for (k=1; k<=cptcovprod;k++) /\* Useless *\/ */
2714: /* /\* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])]; *\/ */
2715: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)]; */
2716: for (k=1; k<=cptcovage;k++){ /* For product with age */
2717: if(Dummy[Tvar[Tage[k]]]){
2718: cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2];
2719: } else{
2720: cov[2+nagesqr+Tage[k]]=Tqresult[nres][k];
2721: }
2722: /* 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]); */
2723: }
2724: for (k=1; k<=cptcovprod;k++){ /* For product without age */
2725: /* 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]); */
2726: if(Dummy[Tvard[k][1]==0]){
2727: if(Dummy[Tvard[k][2]==0]){
2728: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)];
2729: }else{
2730: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * Tqresult[nres][k];
2731: }
2732: }else{
2733: if(Dummy[Tvard[k][2]==0]){
2734: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][2]][codtabm(ij,k)] * Tqinvresult[nres][Tvard[k][1]];
2735: }else{
2736: cov[2+nagesqr+Tprod[k]]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]];
2737: }
2738: }
1.217 brouard 2739: }
2740:
2741: /*printf("ij=%d cptcovprod=%d tvar=%d ", ij, cptcovprod, Tvar[1]);*/
2742: /*printf("ij=%d cov[3]=%lf cov[4]=%lf \n",ij, cov[3],cov[4]);*/
2743: /*printf("ij=%d cov[3]=%lf \n",ij, cov[3]);*/
2744: /* savm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
2745: /* out=matprod2(newm, pmij(pmmij,cov,ncovmodel,x,nlstate),1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); /\* Bug Valgrind *\/ */
1.218 brouard 2746: /* ij should be linked to the correct index of cov */
2747: /* age and covariate values ij are in 'cov', but we need to pass
2748: * ij for the observed prevalence at age and status and covariate
2749: * number: prevacurrent[(int)agefin][ii][ij]
2750: */
2751: /* 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 *\/ */
2752: /* 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 *\/ */
2753: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, bmij(pmmij,cov,ncovmodel,x,nlstate,prevacurrent,ij)); /* Bug Valgrind */
1.268 brouard 2754: /* if((int)age == 86 || (int)age == 87){ */
1.266 brouard 2755: /* printf(" Backward prevalim age=%d agefin=%d \n", (int) age, (int) agefin); */
2756: /* for(i=1; i<=nlstate+ndeath; i++) { */
2757: /* printf("%d newm= ",i); */
2758: /* for(j=1;j<=nlstate+ndeath;j++) { */
2759: /* printf("%f ",newm[i][j]); */
2760: /* } */
2761: /* printf("oldm * "); */
2762: /* for(j=1;j<=nlstate+ndeath;j++) { */
2763: /* printf("%f ",oldm[i][j]); */
2764: /* } */
1.268 brouard 2765: /* printf(" bmmij "); */
1.266 brouard 2766: /* for(j=1;j<=nlstate+ndeath;j++) { */
2767: /* printf("%f ",pmmij[i][j]); */
2768: /* } */
2769: /* printf("\n"); */
2770: /* } */
2771: /* } */
1.217 brouard 2772: savm=oldm;
2773: oldm=newm;
1.266 brouard 2774:
1.217 brouard 2775: for(j=1; j<=nlstate; j++){
2776: max[j]=0.;
2777: min[j]=1.;
2778: }
2779: for(j=1; j<=nlstate; j++){
2780: for(i=1;i<=nlstate;i++){
1.234 brouard 2781: /* bprlim[i][j]= newm[i][j]/(1-sumnew); */
2782: bprlim[i][j]= newm[i][j];
2783: max[i]=FMAX(max[i],bprlim[i][j]); /* Max in line */
2784: min[i]=FMIN(min[i],bprlim[i][j]);
1.217 brouard 2785: }
2786: }
1.218 brouard 2787:
1.217 brouard 2788: maxmax=0.;
2789: for(i=1; i<=nlstate; i++){
2790: meandiff[i]=(max[i]-min[i])/(max[i]+min[i])*2.; /* mean difference for each column */
2791: maxmax=FMAX(maxmax,meandiff[i]);
2792: /* printf("Back age= %d meandiff[%d]=%f, agefin=%d max[%d]=%f min[%d]=%f maxmax=%f\n", (int)age, i, meandiff[i],(int)agefin, i, max[i], i, min[i],maxmax); */
1.268 brouard 2793: } /* i loop */
1.217 brouard 2794: *ncvyear= -( (int)age- (int)agefin);
1.268 brouard 2795: /* printf("Back maxmax=%lf ncvloop=%d, age=%d, agefin=%d ncvyear=%d \n", maxmax, ncvloop, (int)age, (int)agefin, *ncvyear); */
1.217 brouard 2796: if(maxmax < ftolpl){
1.220 brouard 2797: /* printf("OK Back maxmax=%lf ncvloop=%d, age=%d, agefin=%d ncvyear=%d \n", maxmax, ncvloop, (int)age, (int)agefin, *ncvyear); */
1.217 brouard 2798: free_vector(min,1,nlstate);
2799: free_vector(max,1,nlstate);
2800: free_vector(meandiff,1,nlstate);
2801: return bprlim;
2802: }
2803: } /* age loop */
2804: /* After some age loop it doesn't converge */
1.247 brouard 2805: if(first){
2806: first=1;
2807: 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\
2808: 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);
2809: }
2810: 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 2811: 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);
2812: /* 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); */
2813: free_vector(min,1,nlstate);
2814: free_vector(max,1,nlstate);
2815: free_vector(meandiff,1,nlstate);
2816:
2817: return bprlim; /* should not reach here */
2818: }
2819:
1.126 brouard 2820: /*************** transition probabilities ***************/
2821:
2822: double **pmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate )
2823: {
1.138 brouard 2824: /* According to parameters values stored in x and the covariate's values stored in cov,
1.266 brouard 2825: computes the probability to be observed in state j (after stepm years) being in state i by appying the
1.138 brouard 2826: model to the ncovmodel covariates (including constant and age).
2827: lnpijopii=ln(pij/pii)= aij+bij*age+cij*v1+dij*v2+... = sum_nc=1^ncovmodel xij(nc)*cov[nc]
2828: and, according on how parameters are entered, the position of the coefficient xij(nc) of the
2829: ncth covariate in the global vector x is given by the formula:
2830: j<i nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel
2831: j>=i nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel
2832: Computes ln(pij/pii) (lnpijopii), deduces pij/pii by exponentiation,
2833: sums on j different of i to get 1-pii/pii, deduces pii, and then all pij.
1.266 brouard 2834: Outputs ps[i][j] or probability to be observed in j being in i according to
1.138 brouard 2835: the values of the covariates cov[nc] and corresponding parameter values x[nc+shiftij]
1.266 brouard 2836: Sum on j ps[i][j] should equal to 1.
1.138 brouard 2837: */
2838: double s1, lnpijopii;
1.126 brouard 2839: /*double t34;*/
1.164 brouard 2840: int i,j, nc, ii, jj;
1.126 brouard 2841:
1.223 brouard 2842: for(i=1; i<= nlstate; i++){
2843: for(j=1; j<i;j++){
2844: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
2845: /*lnpijopii += param[i][j][nc]*cov[nc];*/
2846: lnpijopii += x[nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel]*cov[nc];
2847: /* printf("Int j<i s1=%.17e, lnpijopii=%.17e\n",s1,lnpijopii); */
2848: }
2849: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
2850: /* printf("s1=%.17e, lnpijopii=%.17e\n",s1,lnpijopii); */
2851: }
2852: for(j=i+1; j<=nlstate+ndeath;j++){
2853: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
2854: /*lnpijopii += x[(i-1)*nlstate*ncovmodel+(j-2)*ncovmodel+nc+(i-1)*(ndeath-1)*ncovmodel]*cov[nc];*/
2855: lnpijopii += x[nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel]*cov[nc];
2856: /* printf("Int j>i s1=%.17e, lnpijopii=%.17e %lx %lx\n",s1,lnpijopii,s1,lnpijopii); */
2857: }
2858: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
2859: }
2860: }
1.218 brouard 2861:
1.223 brouard 2862: for(i=1; i<= nlstate; i++){
2863: s1=0;
2864: for(j=1; j<i; j++){
2865: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
2866: /*printf("debug1 %d %d ps=%lf exp(ps)=%lf s1+=%lf\n",i,j,ps[i][j],exp(ps[i][j]),s1); */
2867: }
2868: for(j=i+1; j<=nlstate+ndeath; j++){
2869: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
2870: /*printf("debug2 %d %d ps=%lf exp(ps)=%lf s1+=%lf\n",i,j,ps[i][j],exp(ps[i][j]),s1); */
2871: }
2872: /* s1= sum_{j<>i} pij/pii=(1-pii)/pii and thus pii is known from s1 */
2873: ps[i][i]=1./(s1+1.);
2874: /* Computing other pijs */
2875: for(j=1; j<i; j++)
2876: ps[i][j]= exp(ps[i][j])*ps[i][i];
2877: for(j=i+1; j<=nlstate+ndeath; j++)
2878: ps[i][j]= exp(ps[i][j])*ps[i][i];
2879: /* ps[i][nlstate+1]=1.-s1- ps[i][i];*/ /* Sum should be 1 */
2880: } /* end i */
1.218 brouard 2881:
1.223 brouard 2882: for(ii=nlstate+1; ii<= nlstate+ndeath; ii++){
2883: for(jj=1; jj<= nlstate+ndeath; jj++){
2884: ps[ii][jj]=0;
2885: ps[ii][ii]=1;
2886: }
2887: }
1.218 brouard 2888:
2889:
1.223 brouard 2890: /* for(ii=1; ii<= nlstate+ndeath; ii++){ */
2891: /* for(jj=1; jj<= nlstate+ndeath; jj++){ */
2892: /* printf(" pmij ps[%d][%d]=%lf ",ii,jj,ps[ii][jj]); */
2893: /* } */
2894: /* printf("\n "); */
2895: /* } */
2896: /* printf("\n ");printf("%lf ",cov[2]);*/
2897: /*
2898: for(i=1; i<= npar; i++) printf("%f ",x[i]);
1.218 brouard 2899: goto end;*/
1.266 brouard 2900: return ps; /* Pointer is unchanged since its call */
1.126 brouard 2901: }
2902:
1.218 brouard 2903: /*************** backward transition probabilities ***************/
2904:
2905: /* 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 ) */
2906: /* double **bmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate, double ***prevacurrent, double ***dnewm, double **doldm, double **dsavm, int ij ) */
2907: double **bmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate, double ***prevacurrent, int ij )
2908: {
1.266 brouard 2909: /* Computes the backward probability at age agefin and covariate combination ij. In fact cov is already filled and x too.
2910: * Call to pmij(cov and x), call to cross prevalence, sums and inverses, left multiply, and returns in **ps as well as **bmij.
1.222 brouard 2911: */
1.218 brouard 2912: int i, ii, j,k;
1.222 brouard 2913:
2914: double **out, **pmij();
2915: double sumnew=0.;
1.218 brouard 2916: double agefin;
1.268 brouard 2917: double k3=0.; /* constant of the w_x diagonal matrixe (in order for B to sum to 1 even for death state) */
1.222 brouard 2918: double **dnewm, **dsavm, **doldm;
2919: double **bbmij;
2920:
1.218 brouard 2921: doldm=ddoldms; /* global pointers */
1.222 brouard 2922: dnewm=ddnewms;
2923: dsavm=ddsavms;
2924:
2925: agefin=cov[2];
1.268 brouard 2926: /* Bx = Diag(w_x) P_x Diag(Sum_i w^i_x p^ij_x */
1.222 brouard 2927: /* bmij *//* age is cov[2], ij is included in cov, but we need for
1.266 brouard 2928: the observed prevalence (with this covariate ij) at beginning of transition */
2929: /* dsavm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
1.268 brouard 2930:
2931: /* P_x */
1.266 brouard 2932: pmmij=pmij(pmmij,cov,ncovmodel,x,nlstate); /*This is forward probability from agefin to agefin + stepm */
1.268 brouard 2933: /* outputs pmmij which is a stochastic matrix in row */
2934:
2935: /* Diag(w_x) */
2936: /* Problem with prevacurrent which can be zero */
2937: sumnew=0.;
1.269 brouard 2938: /*for (ii=1;ii<=nlstate+ndeath;ii++){*/
1.268 brouard 2939: for (ii=1;ii<=nlstate;ii++){ /* Only on live states */
1.269 brouard 2940: /* printf(" agefin=%d, ii=%d, ij=%d, prev=%f\n",(int)agefin,ii, ij, prevacurrent[(int)agefin][ii][ij]); */
1.268 brouard 2941: sumnew+=prevacurrent[(int)agefin][ii][ij];
2942: }
2943: if(sumnew >0.01){ /* At least some value in the prevalence */
2944: for (ii=1;ii<=nlstate+ndeath;ii++){
2945: for (j=1;j<=nlstate+ndeath;j++)
1.269 brouard 2946: doldm[ii][j]=(ii==j ? prevacurrent[(int)agefin][ii][ij]/sumnew : 0.0);
1.268 brouard 2947: }
2948: }else{
2949: for (ii=1;ii<=nlstate+ndeath;ii++){
2950: for (j=1;j<=nlstate+ndeath;j++)
2951: doldm[ii][j]=(ii==j ? 1./nlstate : 0.0);
2952: }
2953: /* if(sumnew <0.9){ */
2954: /* printf("Problem internal bmij B: sum on i wi <0.9: j=%d, sum_i wi=%lf,agefin=%d\n",j,sumnew, (int)agefin); */
2955: /* } */
2956: }
2957: k3=0.0; /* We put the last diagonal to 0 */
2958: for (ii=nlstate+1;ii<=nlstate+ndeath;ii++){
2959: doldm[ii][ii]= k3;
2960: }
2961: /* End doldm, At the end doldm is diag[(w_i)] */
2962:
2963: /* left Product of this diag matrix by pmmij=Px (dnewm=dsavm*doldm) */
2964: bbmij=matprod2(dnewm, doldm,1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, pmmij); /* Bug Valgrind */
2965:
2966: /* Diag(Sum_i w^i_x p^ij_x */
2967: /* w1 p11 + w2 p21 only on live states N1./N..*N11/N1. + N2./N..*N21/N2.=(N11+N21)/N..=N.1/N.. */
1.222 brouard 2968: for (j=1;j<=nlstate+ndeath;j++){
1.268 brouard 2969: sumnew=0.;
1.222 brouard 2970: for (ii=1;ii<=nlstate;ii++){
1.266 brouard 2971: /* sumnew+=dsavm[ii][j]*prevacurrent[(int)agefin][ii][ij]; */
1.268 brouard 2972: sumnew+=pmmij[ii][j]*doldm[ii][ii]; /* Yes prevalence at beginning of transition */
1.222 brouard 2973: } /* sumnew is (N11+N21)/N..= N.1/N.. = sum on i of w_i pij */
1.268 brouard 2974: for (ii=1;ii<=nlstate+ndeath;ii++){
1.222 brouard 2975: /* if(agefin >= agemaxpar && agefin <= agemaxpar+stepm/YEARM){ */
1.268 brouard 2976: /* dsavm[ii][j]=(ii==j ? 1./sumnew : 0.0); */
1.222 brouard 2977: /* }else if(agefin >= agemaxpar+stepm/YEARM){ */
1.268 brouard 2978: /* dsavm[ii][j]=(ii==j ? 1./sumnew : 0.0); */
1.222 brouard 2979: /* }else */
1.268 brouard 2980: dsavm[ii][j]=(ii==j ? 1./sumnew : 0.0);
2981: } /*End ii */
2982: } /* End j, At the end dsavm is diag[1/(w_1p1i+w_2 p2i)] for ALL states even if the sum is only for live states */
2983:
2984: ps=matprod2(ps, dnewm,1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, dsavm); /* Bug Valgrind */
2985: /* ps is now diag[w_i] * Px * diag [1/(w_1p1i+w_2 p2i)] */
1.222 brouard 2986: /* end bmij */
1.266 brouard 2987: return ps; /*pointer is unchanged */
1.218 brouard 2988: }
1.217 brouard 2989: /*************** transition probabilities ***************/
2990:
1.218 brouard 2991: double **bpmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate )
1.217 brouard 2992: {
2993: /* According to parameters values stored in x and the covariate's values stored in cov,
2994: computes the probability to be observed in state j being in state i by appying the
2995: model to the ncovmodel covariates (including constant and age).
2996: lnpijopii=ln(pij/pii)= aij+bij*age+cij*v1+dij*v2+... = sum_nc=1^ncovmodel xij(nc)*cov[nc]
2997: and, according on how parameters are entered, the position of the coefficient xij(nc) of the
2998: ncth covariate in the global vector x is given by the formula:
2999: j<i nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel
3000: j>=i nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel
3001: Computes ln(pij/pii) (lnpijopii), deduces pij/pii by exponentiation,
3002: sums on j different of i to get 1-pii/pii, deduces pii, and then all pij.
3003: Outputs ps[i][j] the probability to be observed in j being in j according to
3004: the values of the covariates cov[nc] and corresponding parameter values x[nc+shiftij]
3005: */
3006: double s1, lnpijopii;
3007: /*double t34;*/
3008: int i,j, nc, ii, jj;
3009:
1.234 brouard 3010: for(i=1; i<= nlstate; i++){
3011: for(j=1; j<i;j++){
3012: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
3013: /*lnpijopii += param[i][j][nc]*cov[nc];*/
3014: lnpijopii += x[nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel]*cov[nc];
3015: /* printf("Int j<i s1=%.17e, lnpijopii=%.17e\n",s1,lnpijopii); */
3016: }
3017: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
3018: /* printf("s1=%.17e, lnpijopii=%.17e\n",s1,lnpijopii); */
3019: }
3020: for(j=i+1; j<=nlstate+ndeath;j++){
3021: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
3022: /*lnpijopii += x[(i-1)*nlstate*ncovmodel+(j-2)*ncovmodel+nc+(i-1)*(ndeath-1)*ncovmodel]*cov[nc];*/
3023: lnpijopii += x[nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel]*cov[nc];
3024: /* printf("Int j>i s1=%.17e, lnpijopii=%.17e %lx %lx\n",s1,lnpijopii,s1,lnpijopii); */
3025: }
3026: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
3027: }
3028: }
3029:
3030: for(i=1; i<= nlstate; i++){
3031: s1=0;
3032: for(j=1; j<i; j++){
3033: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
3034: /*printf("debug1 %d %d ps=%lf exp(ps)=%lf s1+=%lf\n",i,j,ps[i][j],exp(ps[i][j]),s1); */
3035: }
3036: for(j=i+1; j<=nlstate+ndeath; j++){
3037: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
3038: /*printf("debug2 %d %d ps=%lf exp(ps)=%lf s1+=%lf\n",i,j,ps[i][j],exp(ps[i][j]),s1); */
3039: }
3040: /* s1= sum_{j<>i} pij/pii=(1-pii)/pii and thus pii is known from s1 */
3041: ps[i][i]=1./(s1+1.);
3042: /* Computing other pijs */
3043: for(j=1; j<i; j++)
3044: ps[i][j]= exp(ps[i][j])*ps[i][i];
3045: for(j=i+1; j<=nlstate+ndeath; j++)
3046: ps[i][j]= exp(ps[i][j])*ps[i][i];
3047: /* ps[i][nlstate+1]=1.-s1- ps[i][i];*/ /* Sum should be 1 */
3048: } /* end i */
3049:
3050: for(ii=nlstate+1; ii<= nlstate+ndeath; ii++){
3051: for(jj=1; jj<= nlstate+ndeath; jj++){
3052: ps[ii][jj]=0;
3053: ps[ii][ii]=1;
3054: }
3055: }
3056: /* Added for backcast */ /* Transposed matrix too */
3057: for(jj=1; jj<= nlstate+ndeath; jj++){
3058: s1=0.;
3059: for(ii=1; ii<= nlstate+ndeath; ii++){
3060: s1+=ps[ii][jj];
3061: }
3062: for(ii=1; ii<= nlstate; ii++){
3063: ps[ii][jj]=ps[ii][jj]/s1;
3064: }
3065: }
3066: /* Transposition */
3067: for(jj=1; jj<= nlstate+ndeath; jj++){
3068: for(ii=jj; ii<= nlstate+ndeath; ii++){
3069: s1=ps[ii][jj];
3070: ps[ii][jj]=ps[jj][ii];
3071: ps[jj][ii]=s1;
3072: }
3073: }
3074: /* for(ii=1; ii<= nlstate+ndeath; ii++){ */
3075: /* for(jj=1; jj<= nlstate+ndeath; jj++){ */
3076: /* printf(" pmij ps[%d][%d]=%lf ",ii,jj,ps[ii][jj]); */
3077: /* } */
3078: /* printf("\n "); */
3079: /* } */
3080: /* printf("\n ");printf("%lf ",cov[2]);*/
3081: /*
3082: for(i=1; i<= npar; i++) printf("%f ",x[i]);
3083: goto end;*/
3084: return ps;
1.217 brouard 3085: }
3086:
3087:
1.126 brouard 3088: /**************** Product of 2 matrices ******************/
3089:
1.145 brouard 3090: double **matprod2(double **out, double **in,int nrl, int nrh, int ncl, int nch, int ncolol, int ncoloh, double **b)
1.126 brouard 3091: {
3092: /* Computes the matrix product of in(1,nrh-nrl+1)(1,nch-ncl+1) times
3093: b(1,nch-ncl+1)(1,ncoloh-ncolol+1) into out(...) */
3094: /* in, b, out are matrice of pointers which should have been initialized
3095: before: only the contents of out is modified. The function returns
3096: a pointer to pointers identical to out */
1.145 brouard 3097: int i, j, k;
1.126 brouard 3098: for(i=nrl; i<= nrh; i++)
1.145 brouard 3099: for(k=ncolol; k<=ncoloh; k++){
3100: out[i][k]=0.;
3101: for(j=ncl; j<=nch; j++)
3102: out[i][k] +=in[i][j]*b[j][k];
3103: }
1.126 brouard 3104: return out;
3105: }
3106:
3107:
3108: /************* Higher Matrix Product ***************/
3109:
1.235 brouard 3110: 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 3111: {
1.218 brouard 3112: /* Computes the transition matrix starting at age 'age' and combination of covariate values corresponding to ij over
1.126 brouard 3113: 'nhstepm*hstepm*stepm' months (i.e. until
3114: age (in years) age+nhstepm*hstepm*stepm/12) by multiplying
3115: nhstepm*hstepm matrices.
3116: Output is stored in matrix po[i][j][h] for h every 'hstepm' step
3117: (typically every 2 years instead of every month which is too big
3118: for the memory).
3119: Model is determined by parameters x and covariates have to be
3120: included manually here.
3121:
3122: */
3123:
3124: int i, j, d, h, k;
1.131 brouard 3125: double **out, cov[NCOVMAX+1];
1.126 brouard 3126: double **newm;
1.187 brouard 3127: double agexact;
1.214 brouard 3128: double agebegin, ageend;
1.126 brouard 3129:
3130: /* Hstepm could be zero and should return the unit matrix */
3131: for (i=1;i<=nlstate+ndeath;i++)
3132: for (j=1;j<=nlstate+ndeath;j++){
3133: oldm[i][j]=(i==j ? 1.0 : 0.0);
3134: po[i][j][0]=(i==j ? 1.0 : 0.0);
3135: }
3136: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
3137: for(h=1; h <=nhstepm; h++){
3138: for(d=1; d <=hstepm; d++){
3139: newm=savm;
3140: /* Covariates have to be included here again */
3141: cov[1]=1.;
1.214 brouard 3142: agexact=age+((h-1)*hstepm + (d-1))*stepm/YEARM; /* age just before transition */
1.187 brouard 3143: cov[2]=agexact;
3144: if(nagesqr==1)
1.227 brouard 3145: cov[3]= agexact*agexact;
1.235 brouard 3146: for (k=1; k<=nsd;k++) { /* For single dummy covariates only */
3147: /* Here comes the value of the covariate 'ij' after renumbering k with single dummy covariates */
3148: cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,k)];
3149: /* 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)); */
3150: }
3151: for (k=1; k<=nsq;k++) { /* For single varying covariates only */
3152: /* Here comes the value of quantitative after renumbering k with single quantitative covariates */
3153: cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k];
3154: /* 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]); */
3155: }
3156: for (k=1; k<=cptcovage;k++){
3157: if(Dummy[Tvar[Tage[k]]]){
3158: cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2];
3159: } else{
3160: cov[2+nagesqr+Tage[k]]=Tqresult[nres][k];
3161: }
3162: /* 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]); */
3163: }
3164: for (k=1; k<=cptcovprod;k++){ /* */
3165: /* 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]); */
3166: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)];
3167: }
3168: /* for (k=1; k<=cptcovn;k++) */
3169: /* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,k)]; */
3170: /* for (k=1; k<=cptcovage;k++) /\* Should start at cptcovn+1 *\/ */
3171: /* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2]; */
3172: /* for (k=1; k<=cptcovprod;k++) /\* Useless because included in cptcovn *\/ */
3173: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)]*nbcode[Tvard[k][2]][codtabm(ij,k)]; */
1.227 brouard 3174:
3175:
1.126 brouard 3176: /*printf("hxi cptcov=%d cptcode=%d\n",cptcov,cptcode);*/
3177: /*printf("h=%d d=%d age=%f cov=%f\n",h,d,age,cov[2]);*/
1.218 brouard 3178: /* right multiplication of oldm by the current matrix */
1.126 brouard 3179: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath,
3180: pmij(pmmij,cov,ncovmodel,x,nlstate));
1.217 brouard 3181: /* if((int)age == 70){ */
3182: /* printf(" Forward hpxij age=%d agexact=%f d=%d nhstepm=%d hstepm=%d\n", (int) age, agexact, d, nhstepm, hstepm); */
3183: /* for(i=1; i<=nlstate+ndeath; i++) { */
3184: /* printf("%d pmmij ",i); */
3185: /* for(j=1;j<=nlstate+ndeath;j++) { */
3186: /* printf("%f ",pmmij[i][j]); */
3187: /* } */
3188: /* printf(" oldm "); */
3189: /* for(j=1;j<=nlstate+ndeath;j++) { */
3190: /* printf("%f ",oldm[i][j]); */
3191: /* } */
3192: /* printf("\n"); */
3193: /* } */
3194: /* } */
1.126 brouard 3195: savm=oldm;
3196: oldm=newm;
3197: }
3198: for(i=1; i<=nlstate+ndeath; i++)
3199: for(j=1;j<=nlstate+ndeath;j++) {
1.267 brouard 3200: po[i][j][h]=newm[i][j];
3201: /*if(h==nhstepm) printf("po[%d][%d][%d]=%f ",i,j,h,po[i][j][h]);*/
1.126 brouard 3202: }
1.128 brouard 3203: /*printf("h=%d ",h);*/
1.126 brouard 3204: } /* end h */
1.267 brouard 3205: /* printf("\n H=%d \n",h); */
1.126 brouard 3206: return po;
3207: }
3208:
1.217 brouard 3209: /************* Higher Back Matrix Product ***************/
1.218 brouard 3210: /* double ***hbxij(double ***po, int nhstepm, double age, int hstepm, double *x, double ***prevacurrent, int nlstate, int stepm, double **oldm, double **savm, double **dnewm, double **doldm, double **dsavm, int ij ) */
1.267 brouard 3211: double ***hbxij(double ***po, int nhstepm, double age, int hstepm, double *x, double ***prevacurrent, int nlstate, int stepm, int ij, int nres )
1.217 brouard 3212: {
1.266 brouard 3213: /* For a combination of dummy covariate ij, computes the transition matrix starting at age 'age' over
1.217 brouard 3214: 'nhstepm*hstepm*stepm' months (i.e. until
1.218 brouard 3215: age (in years) age+nhstepm*hstepm*stepm/12) by multiplying
3216: nhstepm*hstepm matrices.
3217: Output is stored in matrix po[i][j][h] for h every 'hstepm' step
3218: (typically every 2 years instead of every month which is too big
1.217 brouard 3219: for the memory).
1.218 brouard 3220: Model is determined by parameters x and covariates have to be
1.266 brouard 3221: included manually here. Then we use a call to bmij(x and cov)
3222: The addresss of po (p3mat allocated to the dimension of nhstepm) should be stored for output
1.222 brouard 3223: */
1.217 brouard 3224:
3225: int i, j, d, h, k;
1.266 brouard 3226: double **out, cov[NCOVMAX+1], **bmij();
3227: double **newm, ***newmm;
1.217 brouard 3228: double agexact;
3229: double agebegin, ageend;
1.222 brouard 3230: double **oldm, **savm;
1.217 brouard 3231:
1.266 brouard 3232: newmm=po; /* To be saved */
3233: oldm=oldms;savm=savms; /* Global pointers */
1.217 brouard 3234: /* Hstepm could be zero and should return the unit matrix */
3235: for (i=1;i<=nlstate+ndeath;i++)
3236: for (j=1;j<=nlstate+ndeath;j++){
3237: oldm[i][j]=(i==j ? 1.0 : 0.0);
3238: po[i][j][0]=(i==j ? 1.0 : 0.0);
3239: }
3240: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
3241: for(h=1; h <=nhstepm; h++){
3242: for(d=1; d <=hstepm; d++){
3243: newm=savm;
3244: /* Covariates have to be included here again */
3245: cov[1]=1.;
1.271 ! brouard 3246: agexact=age-( (h-1)*hstepm + (d) )*stepm/YEARM; /* age just before transition, d or d-1? */
1.217 brouard 3247: /* agexact=age+((h-1)*hstepm + (d-1))*stepm/YEARM; /\* age just before transition *\/ */
3248: cov[2]=agexact;
3249: if(nagesqr==1)
1.222 brouard 3250: cov[3]= agexact*agexact;
1.266 brouard 3251: for (k=1; k<=cptcovn;k++){
3252: /* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,k)]; */
3253: /* /\* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,Tvar[k])]; *\/ */
3254: cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,k)];
3255: /* printf("hbxij Dummy agexact=%.0f combi=%d k=%d TvarsD[%d]=V%d TvarsDind[%d]=%d nbcode=%d cov[%d]=%lf codtabm(%d,Tvar[%d])=%d \n",agexact,ij,k, k, TvarsD[k],k,TvarsDind[k],nbcode[TvarsD[k]][codtabm(ij,k)],2+nagesqr+TvarsDind[k],cov[2+nagesqr+TvarsDind[k]], ij, k, codtabm(ij,k)); */
3256: }
1.267 brouard 3257: for (k=1; k<=nsq;k++) { /* For single varying covariates only */
3258: /* Here comes the value of quantitative after renumbering k with single quantitative covariates */
3259: cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k];
3260: /* 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]); */
3261: }
3262: for (k=1; k<=cptcovage;k++){ /* Should start at cptcovn+1 */
3263: if(Dummy[Tvar[Tage[k]]]){
3264: cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2];
3265: } else{
3266: cov[2+nagesqr+Tage[k]]=Tqresult[nres][k];
3267: }
3268: /* printf("hBxij Age combi=%d k=%d Tage[%d]=V%d Tqresult[%d][%d]=%f\n",ij,k,k,Tage[k],nres,k,Tqresult[nres][k]); */
3269: }
3270: for (k=1; k<=cptcovprod;k++){ /* Useless because included in cptcovn */
1.222 brouard 3271: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)]*nbcode[Tvard[k][2]][codtabm(ij,k)];
1.267 brouard 3272: }
1.217 brouard 3273: /*printf("hxi cptcov=%d cptcode=%d\n",cptcov,cptcode);*/
3274: /*printf("h=%d d=%d age=%f cov=%f\n",h,d,age,cov[2]);*/
1.267 brouard 3275:
1.218 brouard 3276: /* Careful transposed matrix */
1.266 brouard 3277: /* age is in cov[2], prevacurrent at beginning of transition. */
1.218 brouard 3278: /* out=matprod2(newm, bmij(pmmij,cov,ncovmodel,x,nlstate,prevacurrent, dnewm, doldm, dsavm,ij),\ */
1.222 brouard 3279: /* 1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); */
1.218 brouard 3280: out=matprod2(newm, bmij(pmmij,cov,ncovmodel,x,nlstate,prevacurrent,ij),\
1.222 brouard 3281: 1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm);
1.217 brouard 3282: /* if((int)age == 70){ */
3283: /* printf(" Backward hbxij age=%d agexact=%f d=%d nhstepm=%d hstepm=%d\n", (int) age, agexact, d, nhstepm, hstepm); */
3284: /* for(i=1; i<=nlstate+ndeath; i++) { */
3285: /* printf("%d pmmij ",i); */
3286: /* for(j=1;j<=nlstate+ndeath;j++) { */
3287: /* printf("%f ",pmmij[i][j]); */
3288: /* } */
3289: /* printf(" oldm "); */
3290: /* for(j=1;j<=nlstate+ndeath;j++) { */
3291: /* printf("%f ",oldm[i][j]); */
3292: /* } */
3293: /* printf("\n"); */
3294: /* } */
3295: /* } */
3296: savm=oldm;
3297: oldm=newm;
3298: }
3299: for(i=1; i<=nlstate+ndeath; i++)
3300: for(j=1;j<=nlstate+ndeath;j++) {
1.222 brouard 3301: po[i][j][h]=newm[i][j];
1.268 brouard 3302: /* if(h==nhstepm) */
3303: /* printf("po[%d][%d][%d]=%f ",i,j,h,po[i][j][h]); */
1.217 brouard 3304: }
1.268 brouard 3305: /* printf("h=%d %.1f ",h, agexact); */
1.217 brouard 3306: } /* end h */
1.268 brouard 3307: /* printf("\n H=%d nhs=%d \n",h, nhstepm); */
1.217 brouard 3308: return po;
3309: }
3310:
3311:
1.162 brouard 3312: #ifdef NLOPT
3313: double myfunc(unsigned n, const double *p1, double *grad, void *pd){
3314: double fret;
3315: double *xt;
3316: int j;
3317: myfunc_data *d2 = (myfunc_data *) pd;
3318: /* xt = (p1-1); */
3319: xt=vector(1,n);
3320: for (j=1;j<=n;j++) xt[j]=p1[j-1]; /* xt[1]=p1[0] */
3321:
3322: fret=(d2->function)(xt); /* p xt[1]@8 is fine */
3323: /* fret=(*func)(xt); /\* p xt[1]@8 is fine *\/ */
3324: printf("Function = %.12lf ",fret);
3325: for (j=1;j<=n;j++) printf(" %d %.8lf", j, xt[j]);
3326: printf("\n");
3327: free_vector(xt,1,n);
3328: return fret;
3329: }
3330: #endif
1.126 brouard 3331:
3332: /*************** log-likelihood *************/
3333: double func( double *x)
3334: {
1.226 brouard 3335: int i, ii, j, k, mi, d, kk;
3336: int ioffset=0;
3337: double l, ll[NLSTATEMAX+1], cov[NCOVMAX+1];
3338: double **out;
3339: double lli; /* Individual log likelihood */
3340: int s1, s2;
1.228 brouard 3341: 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 3342: double bbh, survp;
3343: long ipmx;
3344: double agexact;
3345: /*extern weight */
3346: /* We are differentiating ll according to initial status */
3347: /* for (i=1;i<=npar;i++) printf("%f ", x[i]);*/
3348: /*for(i=1;i<imx;i++)
3349: printf(" %d\n",s[4][i]);
3350: */
1.162 brouard 3351:
1.226 brouard 3352: ++countcallfunc;
1.162 brouard 3353:
1.226 brouard 3354: cov[1]=1.;
1.126 brouard 3355:
1.226 brouard 3356: for(k=1; k<=nlstate; k++) ll[k]=0.;
1.224 brouard 3357: ioffset=0;
1.226 brouard 3358: if(mle==1){
3359: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
3360: /* Computes the values of the ncovmodel covariates of the model
3361: depending if the covariates are fixed or varying (age dependent) and stores them in cov[]
3362: Then computes with function pmij which return a matrix p[i][j] giving the elementary probability
3363: to be observed in j being in i according to the model.
3364: */
1.243 brouard 3365: ioffset=2+nagesqr ;
1.233 brouard 3366: /* Fixed */
1.234 brouard 3367: for (k=1; k<=ncovf;k++){ /* Simple and product fixed covariates without age* products */
3368: 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)*/
3369: }
1.226 brouard 3370: /* In model V2+V1*V4+age*V3+V3*V2 Tvar[1] is V2, Tvar[2=V1*V4]
3371: is 6, Tvar[3=age*V3] should not be computed because of age Tvar[4=V3*V2]
3372: has been calculated etc */
3373: /* For an individual i, wav[i] gives the number of effective waves */
3374: /* We compute the contribution to Likelihood of each effective transition
3375: mw[mi][i] is real wave of the mi th effectve wave */
3376: /* Then statuses are computed at each begin and end of an effective wave s1=s[ mw[mi][i] ][i];
3377: s2=s[mw[mi+1][i]][i];
3378: And the iv th varying covariate is the cotvar[mw[mi+1][i]][iv][i]
3379: But if the variable is not in the model TTvar[iv] is the real variable effective in the model:
3380: meaning that decodemodel should be used cotvar[mw[mi+1][i]][TTvar[iv]][i]
3381: */
3382: for(mi=1; mi<= wav[i]-1; mi++){
1.234 brouard 3383: for(k=1; k <= ncovv ; k++){ /* Varying covariates (single and product but no age )*/
1.242 brouard 3384: /* cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]][i]; */
3385: cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]-ncovcol-nqv][i];
1.234 brouard 3386: }
3387: for (ii=1;ii<=nlstate+ndeath;ii++)
3388: for (j=1;j<=nlstate+ndeath;j++){
3389: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
3390: savm[ii][j]=(ii==j ? 1.0 : 0.0);
3391: }
3392: for(d=0; d<dh[mi][i]; d++){
3393: newm=savm;
3394: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
3395: cov[2]=agexact;
3396: if(nagesqr==1)
3397: cov[3]= agexact*agexact; /* Should be changed here */
3398: for (kk=1; kk<=cptcovage;kk++) {
1.242 brouard 3399: if(!FixedV[Tvar[Tage[kk]]])
1.234 brouard 3400: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact; /* Tage[kk] gives the data-covariate associated with age */
1.242 brouard 3401: else
3402: cov[Tage[kk]+2+nagesqr]=cotvar[mw[mi][i]][Tvar[Tage[kk]]-ncovcol-nqv][i]*agexact;
1.234 brouard 3403: }
3404: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
3405: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
3406: savm=oldm;
3407: oldm=newm;
3408: } /* end mult */
3409:
3410: /*lli=log(out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]);*/ /* Original formula */
3411: /* But now since version 0.9 we anticipate for bias at large stepm.
3412: * If stepm is larger than one month (smallest stepm) and if the exact delay
3413: * (in months) between two waves is not a multiple of stepm, we rounded to
3414: * the nearest (and in case of equal distance, to the lowest) interval but now
3415: * we keep into memory the bias bh[mi][i] and also the previous matrix product
3416: * (i.e to dh[mi][i]-1) saved in 'savm'. Then we inter(extra)polate the
3417: * probability in order to take into account the bias as a fraction of the way
1.231 brouard 3418: * from savm to out if bh is negative or even beyond if bh is positive. bh varies
3419: * -stepm/2 to stepm/2 .
3420: * For stepm=1 the results are the same as for previous versions of Imach.
3421: * For stepm > 1 the results are less biased than in previous versions.
3422: */
1.234 brouard 3423: s1=s[mw[mi][i]][i];
3424: s2=s[mw[mi+1][i]][i];
3425: bbh=(double)bh[mi][i]/(double)stepm;
3426: /* bias bh is positive if real duration
3427: * is higher than the multiple of stepm and negative otherwise.
3428: */
3429: /* lli= (savm[s1][s2]>1.e-8 ?(1.+bbh)*log(out[s1][s2])- bbh*log(savm[s1][s2]):log((1.+bbh)*out[s1][s2]));*/
3430: if( s2 > nlstate){
3431: /* i.e. if s2 is a death state and if the date of death is known
3432: then the contribution to the likelihood is the probability to
3433: die between last step unit time and current step unit time,
3434: which is also equal to probability to die before dh
3435: minus probability to die before dh-stepm .
3436: In version up to 0.92 likelihood was computed
3437: as if date of death was unknown. Death was treated as any other
3438: health state: the date of the interview describes the actual state
3439: and not the date of a change in health state. The former idea was
3440: to consider that at each interview the state was recorded
3441: (healthy, disable or death) and IMaCh was corrected; but when we
3442: introduced the exact date of death then we should have modified
3443: the contribution of an exact death to the likelihood. This new
3444: contribution is smaller and very dependent of the step unit
3445: stepm. It is no more the probability to die between last interview
3446: and month of death but the probability to survive from last
3447: interview up to one month before death multiplied by the
3448: probability to die within a month. Thanks to Chris
3449: Jackson for correcting this bug. Former versions increased
3450: mortality artificially. The bad side is that we add another loop
3451: which slows down the processing. The difference can be up to 10%
3452: lower mortality.
3453: */
3454: /* If, at the beginning of the maximization mostly, the
3455: cumulative probability or probability to be dead is
3456: constant (ie = 1) over time d, the difference is equal to
3457: 0. out[s1][3] = savm[s1][3]: probability, being at state
3458: s1 at precedent wave, to be dead a month before current
3459: wave is equal to probability, being at state s1 at
3460: precedent wave, to be dead at mont of the current
3461: wave. Then the observed probability (that this person died)
3462: is null according to current estimated parameter. In fact,
3463: it should be very low but not zero otherwise the log go to
3464: infinity.
3465: */
1.183 brouard 3466: /* #ifdef INFINITYORIGINAL */
3467: /* lli=log(out[s1][s2] - savm[s1][s2]); */
3468: /* #else */
3469: /* if ((out[s1][s2] - savm[s1][s2]) < mytinydouble) */
3470: /* lli=log(mytinydouble); */
3471: /* else */
3472: /* lli=log(out[s1][s2] - savm[s1][s2]); */
3473: /* #endif */
1.226 brouard 3474: lli=log(out[s1][s2] - savm[s1][s2]);
1.216 brouard 3475:
1.226 brouard 3476: } else if ( s2==-1 ) { /* alive */
3477: for (j=1,survp=0. ; j<=nlstate; j++)
3478: survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j];
3479: /*survp += out[s1][j]; */
3480: lli= log(survp);
3481: }
3482: else if (s2==-4) {
3483: for (j=3,survp=0. ; j<=nlstate; j++)
3484: survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j];
3485: lli= log(survp);
3486: }
3487: else if (s2==-5) {
3488: for (j=1,survp=0. ; j<=2; j++)
3489: survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j];
3490: lli= log(survp);
3491: }
3492: else{
3493: lli= log((1.+bbh)*out[s1][s2]- bbh*savm[s1][s2]); /* linear interpolation */
3494: /* 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 */
3495: }
3496: /*lli=(1.+bbh)*log(out[s1][s2])- bbh*log(savm[s1][s2]);*/
3497: /*if(lli ==000.0)*/
3498: /*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); */
3499: ipmx +=1;
3500: sw += weight[i];
3501: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
3502: /* if (lli < log(mytinydouble)){ */
3503: /* 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); */
3504: /* 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]); */
3505: /* } */
3506: } /* end of wave */
3507: } /* end of individual */
3508: } else if(mle==2){
3509: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
3510: for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i];
3511: for(mi=1; mi<= wav[i]-1; mi++){
3512: for (ii=1;ii<=nlstate+ndeath;ii++)
3513: for (j=1;j<=nlstate+ndeath;j++){
3514: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
3515: savm[ii][j]=(ii==j ? 1.0 : 0.0);
3516: }
3517: for(d=0; d<=dh[mi][i]; d++){
3518: newm=savm;
3519: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
3520: cov[2]=agexact;
3521: if(nagesqr==1)
3522: cov[3]= agexact*agexact;
3523: for (kk=1; kk<=cptcovage;kk++) {
3524: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
3525: }
3526: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
3527: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
3528: savm=oldm;
3529: oldm=newm;
3530: } /* end mult */
3531:
3532: s1=s[mw[mi][i]][i];
3533: s2=s[mw[mi+1][i]][i];
3534: bbh=(double)bh[mi][i]/(double)stepm;
3535: 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 */
3536: ipmx +=1;
3537: sw += weight[i];
3538: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
3539: } /* end of wave */
3540: } /* end of individual */
3541: } else if(mle==3){ /* exponential inter-extrapolation */
3542: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
3543: for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i];
3544: for(mi=1; mi<= wav[i]-1; mi++){
3545: for (ii=1;ii<=nlstate+ndeath;ii++)
3546: for (j=1;j<=nlstate+ndeath;j++){
3547: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
3548: savm[ii][j]=(ii==j ? 1.0 : 0.0);
3549: }
3550: for(d=0; d<dh[mi][i]; d++){
3551: newm=savm;
3552: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
3553: cov[2]=agexact;
3554: if(nagesqr==1)
3555: cov[3]= agexact*agexact;
3556: for (kk=1; kk<=cptcovage;kk++) {
3557: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
3558: }
3559: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
3560: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
3561: savm=oldm;
3562: oldm=newm;
3563: } /* end mult */
3564:
3565: s1=s[mw[mi][i]][i];
3566: s2=s[mw[mi+1][i]][i];
3567: bbh=(double)bh[mi][i]/(double)stepm;
3568: 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 */
3569: ipmx +=1;
3570: sw += weight[i];
3571: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
3572: } /* end of wave */
3573: } /* end of individual */
3574: }else if (mle==4){ /* ml=4 no inter-extrapolation */
3575: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
3576: for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i];
3577: for(mi=1; mi<= wav[i]-1; mi++){
3578: for (ii=1;ii<=nlstate+ndeath;ii++)
3579: for (j=1;j<=nlstate+ndeath;j++){
3580: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
3581: savm[ii][j]=(ii==j ? 1.0 : 0.0);
3582: }
3583: for(d=0; d<dh[mi][i]; d++){
3584: newm=savm;
3585: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
3586: cov[2]=agexact;
3587: if(nagesqr==1)
3588: cov[3]= agexact*agexact;
3589: for (kk=1; kk<=cptcovage;kk++) {
3590: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
3591: }
1.126 brouard 3592:
1.226 brouard 3593: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
3594: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
3595: savm=oldm;
3596: oldm=newm;
3597: } /* end mult */
3598:
3599: s1=s[mw[mi][i]][i];
3600: s2=s[mw[mi+1][i]][i];
3601: if( s2 > nlstate){
3602: lli=log(out[s1][s2] - savm[s1][s2]);
3603: } else if ( s2==-1 ) { /* alive */
3604: for (j=1,survp=0. ; j<=nlstate; j++)
3605: survp += out[s1][j];
3606: lli= log(survp);
3607: }else{
3608: lli=log(out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]); /* Original formula */
3609: }
3610: ipmx +=1;
3611: sw += weight[i];
3612: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
1.126 brouard 3613: /* 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 3614: } /* end of wave */
3615: } /* end of individual */
3616: }else{ /* ml=5 no inter-extrapolation no jackson =0.8a */
3617: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
3618: for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i];
3619: for(mi=1; mi<= wav[i]-1; mi++){
3620: for (ii=1;ii<=nlstate+ndeath;ii++)
3621: for (j=1;j<=nlstate+ndeath;j++){
3622: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
3623: savm[ii][j]=(ii==j ? 1.0 : 0.0);
3624: }
3625: for(d=0; d<dh[mi][i]; d++){
3626: newm=savm;
3627: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
3628: cov[2]=agexact;
3629: if(nagesqr==1)
3630: cov[3]= agexact*agexact;
3631: for (kk=1; kk<=cptcovage;kk++) {
3632: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
3633: }
1.126 brouard 3634:
1.226 brouard 3635: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
3636: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
3637: savm=oldm;
3638: oldm=newm;
3639: } /* end mult */
3640:
3641: s1=s[mw[mi][i]][i];
3642: s2=s[mw[mi+1][i]][i];
3643: lli=log(out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]); /* Original formula */
3644: ipmx +=1;
3645: sw += weight[i];
3646: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
3647: /*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]);*/
3648: } /* end of wave */
3649: } /* end of individual */
3650: } /* End of if */
3651: for(k=1,l=0.; k<=nlstate; k++) l += ll[k];
3652: /* printf("l1=%f l2=%f ",ll[1],ll[2]); */
3653: l= l*ipmx/sw; /* To get the same order of magnitude as if weight=1 for every body */
3654: return -l;
1.126 brouard 3655: }
3656:
3657: /*************** log-likelihood *************/
3658: double funcone( double *x)
3659: {
1.228 brouard 3660: /* Same as func but slower because of a lot of printf and if */
1.126 brouard 3661: int i, ii, j, k, mi, d, kk;
1.228 brouard 3662: int ioffset=0;
1.131 brouard 3663: double l, ll[NLSTATEMAX+1], cov[NCOVMAX+1];
1.126 brouard 3664: double **out;
3665: double lli; /* Individual log likelihood */
3666: double llt;
3667: int s1, s2;
1.228 brouard 3668: int iv=0, iqv=0, itv=0, iqtv=0 ; /* Index of varying covariate, fixed quantitative cov, time varying covariate, quantitative time varying covariate */
3669:
1.126 brouard 3670: double bbh, survp;
1.187 brouard 3671: double agexact;
1.214 brouard 3672: double agebegin, ageend;
1.126 brouard 3673: /*extern weight */
3674: /* We are differentiating ll according to initial status */
3675: /* for (i=1;i<=npar;i++) printf("%f ", x[i]);*/
3676: /*for(i=1;i<imx;i++)
3677: printf(" %d\n",s[4][i]);
3678: */
3679: cov[1]=1.;
3680:
3681: for(k=1; k<=nlstate; k++) ll[k]=0.;
1.224 brouard 3682: ioffset=0;
3683: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
1.243 brouard 3684: /* ioffset=2+nagesqr+cptcovage; */
3685: ioffset=2+nagesqr;
1.232 brouard 3686: /* Fixed */
1.224 brouard 3687: /* for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i]; */
1.232 brouard 3688: /* for (k=1; k<=ncoveff;k++){ /\* Simple and product fixed Dummy covariates without age* products *\/ */
3689: for (k=1; k<=ncovf;k++){ /* Simple and product fixed covariates without age* products */
3690: 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)*/
3691: /* cov[ioffset+TvarFind[1]]=covar[Tvar[TvarFind[1]]][i]; */
3692: /* cov[2+6]=covar[Tvar[6]][i]; */
3693: /* cov[2+6]=covar[2][i]; V2 */
3694: /* cov[TvarFind[2]]=covar[Tvar[TvarFind[2]]][i]; */
3695: /* cov[2+7]=covar[Tvar[7]][i]; */
3696: /* cov[2+7]=covar[7][i]; V7=V1*V2 */
3697: /* cov[TvarFind[3]]=covar[Tvar[TvarFind[3]]][i]; */
3698: /* cov[2+9]=covar[Tvar[9]][i]; */
3699: /* cov[2+9]=covar[1][i]; V1 */
1.225 brouard 3700: }
1.232 brouard 3701: /* for (k=1; k<=nqfveff;k++){ /\* Simple and product fixed Quantitative covariates without age* products *\/ */
3702: /* 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?)*\/ */
3703: /* } */
1.231 brouard 3704: /* for(iqv=1; iqv <= nqfveff; iqv++){ /\* Quantitative fixed covariates *\/ */
3705: /* cov[++ioffset]=coqvar[Tvar[iqv]][i]; /\* Only V2 k=6 and V1*V2 7 *\/ */
3706: /* } */
1.225 brouard 3707:
1.233 brouard 3708:
3709: for(mi=1; mi<= wav[i]-1; mi++){ /* Varying with waves */
1.232 brouard 3710: /* Wave varying (but not age varying) */
3711: for(k=1; k <= ncovv ; k++){ /* Varying covariates (single and product but no age )*/
1.242 brouard 3712: /* cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]][i]; */
3713: cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]-ncovcol-nqv][i];
3714: }
1.232 brouard 3715: /* for(itv=1; itv <= ntveff; itv++){ /\* Varying dummy covariates (single??)*\/ */
1.242 brouard 3716: /* iv= Tvar[Tmodelind[ioffset-2-nagesqr-cptcovage+itv]]-ncovcol-nqv; /\* Counting the # varying covariate from 1 to ntveff *\/ */
3717: /* cov[ioffset+iv]=cotvar[mw[mi][i]][iv][i]; */
3718: /* k=ioffset-2-nagesqr-cptcovage+itv; /\* position in simple model *\/ */
3719: /* cov[ioffset+itv]=cotvar[mw[mi][i]][TmodelInvind[itv]][i]; */
3720: /* 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 3721: /* for(iqtv=1; iqtv <= nqtveff; iqtv++){ /\* Varying quantitatives covariates *\/ */
1.242 brouard 3722: /* iv=TmodelInvQind[iqtv]; /\* Counting the # varying covariate from 1 to ntveff *\/ */
3723: /* /\* 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]); *\/ */
3724: /* cov[ioffset+ntveff+iqtv]=cotqvar[mw[mi][i]][TmodelInvQind[iqtv]][i]; */
1.232 brouard 3725: /* } */
1.126 brouard 3726: for (ii=1;ii<=nlstate+ndeath;ii++)
1.242 brouard 3727: for (j=1;j<=nlstate+ndeath;j++){
3728: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
3729: savm[ii][j]=(ii==j ? 1.0 : 0.0);
3730: }
1.214 brouard 3731:
3732: agebegin=agev[mw[mi][i]][i]; /* Age at beginning of effective wave */
3733: ageend=agev[mw[mi][i]][i] + (dh[mi][i])*stepm/YEARM; /* Age at end of effective wave and at the end of transition */
3734: for(d=0; d<dh[mi][i]; d++){ /* Delay between two effective waves */
1.247 brouard 3735: /* for(d=0; d<=0; d++){ /\* Delay between two effective waves Only one matrix to speed up*\/ */
1.242 brouard 3736: /*dh[m][i] or dh[mw[mi][i]][i] is the delay between two effective waves m=mw[mi][i]
3737: and mw[mi+1][i]. dh depends on stepm.*/
3738: newm=savm;
1.247 brouard 3739: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM; /* Here d is needed */
1.242 brouard 3740: cov[2]=agexact;
3741: if(nagesqr==1)
3742: cov[3]= agexact*agexact;
3743: for (kk=1; kk<=cptcovage;kk++) {
3744: if(!FixedV[Tvar[Tage[kk]]])
3745: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
3746: else
3747: cov[Tage[kk]+2+nagesqr]=cotvar[mw[mi][i]][Tvar[Tage[kk]]-ncovcol-nqv][i]*agexact;
3748: }
3749: /* printf("i=%d,mi=%d,d=%d,mw[mi][i]=%d\n",i, mi,d,mw[mi][i]); */
3750: /* savm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
3751: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
3752: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
3753: /* out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath, */
3754: /* 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate)); */
3755: savm=oldm;
3756: oldm=newm;
1.126 brouard 3757: } /* end mult */
3758:
3759: s1=s[mw[mi][i]][i];
3760: s2=s[mw[mi+1][i]][i];
1.217 brouard 3761: /* if(s2==-1){ */
1.268 brouard 3762: /* printf(" ERROR s1=%d, s2=%d i=%d \n", s1, s2, i); */
1.217 brouard 3763: /* /\* exit(1); *\/ */
3764: /* } */
1.126 brouard 3765: bbh=(double)bh[mi][i]/(double)stepm;
3766: /* bias is positive if real duration
3767: * is higher than the multiple of stepm and negative otherwise.
3768: */
3769: if( s2 > nlstate && (mle <5) ){ /* Jackson */
1.242 brouard 3770: lli=log(out[s1][s2] - savm[s1][s2]);
1.216 brouard 3771: } else if ( s2==-1 ) { /* alive */
1.242 brouard 3772: for (j=1,survp=0. ; j<=nlstate; j++)
3773: survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j];
3774: lli= log(survp);
1.126 brouard 3775: }else if (mle==1){
1.242 brouard 3776: lli= log((1.+bbh)*out[s1][s2]- bbh*savm[s1][s2]); /* linear interpolation */
1.126 brouard 3777: } else if(mle==2){
1.242 brouard 3778: 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 3779: } else if(mle==3){ /* exponential inter-extrapolation */
1.242 brouard 3780: 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 3781: } else if (mle==4){ /* mle=4 no inter-extrapolation */
1.242 brouard 3782: lli=log(out[s1][s2]); /* Original formula */
1.136 brouard 3783: } else{ /* mle=0 back to 1 */
1.242 brouard 3784: lli= log((1.+bbh)*out[s1][s2]- bbh*savm[s1][s2]); /* linear interpolation */
3785: /*lli=log(out[s1][s2]); */ /* Original formula */
1.126 brouard 3786: } /* End of if */
3787: ipmx +=1;
3788: sw += weight[i];
3789: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
1.132 brouard 3790: /*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 3791: if(globpr){
1.246 brouard 3792: fprintf(ficresilk,"%09ld %6.1f %6.1f %6d %2d %2d %2d %2d %3d %15.6f %8.4f %8.3f\
1.126 brouard 3793: %11.6f %11.6f %11.6f ", \
1.242 brouard 3794: num[i], agebegin, ageend, i,s1,s2,mi,mw[mi][i],dh[mi][i],exp(lli),weight[i],weight[i]*gipmx/gsw,
1.268 brouard 3795: 2*weight[i]*lli,(s2==-1? -1: out[s1][s2]),(s2==-1? -1: savm[s1][s2]));
1.242 brouard 3796: for(k=1,llt=0.,l=0.; k<=nlstate; k++){
3797: llt +=ll[k]*gipmx/gsw;
3798: fprintf(ficresilk," %10.6f",-ll[k]*gipmx/gsw);
3799: }
3800: fprintf(ficresilk," %10.6f\n", -llt);
1.126 brouard 3801: }
1.232 brouard 3802: } /* end of wave */
3803: } /* end of individual */
3804: for(k=1,l=0.; k<=nlstate; k++) l += ll[k];
3805: /* printf("l1=%f l2=%f ",ll[1],ll[2]); */
3806: l= l*ipmx/sw; /* To get the same order of magnitude as if weight=1 for every body */
3807: if(globpr==0){ /* First time we count the contributions and weights */
3808: gipmx=ipmx;
3809: gsw=sw;
3810: }
3811: return -l;
1.126 brouard 3812: }
3813:
3814:
3815: /*************** function likelione ***********/
3816: void likelione(FILE *ficres,double p[], int npar, int nlstate, int *globpri, long *ipmx, double *sw, double *fretone, double (*funcone)(double []))
3817: {
3818: /* This routine should help understanding what is done with
3819: the selection of individuals/waves and
3820: to check the exact contribution to the likelihood.
3821: Plotting could be done.
3822: */
3823: int k;
3824:
3825: if(*globpri !=0){ /* Just counts and sums, no printings */
1.201 brouard 3826: strcpy(fileresilk,"ILK_");
1.202 brouard 3827: strcat(fileresilk,fileresu);
1.126 brouard 3828: if((ficresilk=fopen(fileresilk,"w"))==NULL) {
3829: printf("Problem with resultfile: %s\n", fileresilk);
3830: fprintf(ficlog,"Problem with resultfile: %s\n", fileresilk);
3831: }
1.214 brouard 3832: 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");
3833: fprintf(ficresilk, "#num_i ageb agend i s1 s2 mi mw dh likeli weight %%weight 2wlli out sav ");
1.126 brouard 3834: /* i,s1,s2,mi,mw[mi][i],dh[mi][i],exp(lli),weight[i],2*weight[i]*lli,out[s1][s2],savm[s1][s2]); */
3835: for(k=1; k<=nlstate; k++)
3836: fprintf(ficresilk," -2*gipw/gsw*weight*ll[%d]++",k);
3837: fprintf(ficresilk," -2*gipw/gsw*weight*ll(total)\n");
3838: }
3839:
3840: *fretone=(*funcone)(p);
3841: if(*globpri !=0){
3842: fclose(ficresilk);
1.205 brouard 3843: if (mle ==0)
3844: fprintf(fichtm,"\n<br>File of contributions to the likelihood computed with initial parameters and mle = %d.",mle);
3845: else if(mle >=1)
3846: fprintf(fichtm,"\n<br>File of contributions to the likelihood computed with optimized parameters mle = %d.",mle);
3847: 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 3848:
1.208 brouard 3849:
3850: for (k=1; k<= nlstate ; k++) {
1.211 brouard 3851: 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 3852: <img src=\"%s-p%dj.png\">",k,k,subdirf2(optionfilefiname,"ILK_"),k,subdirf2(optionfilefiname,"ILK_"),k,subdirf2(optionfilefiname,"ILK_"),k);
3853: }
1.207 brouard 3854: 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 3855: <img src=\"%s-ori.png\">",subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"));
1.207 brouard 3856: fprintf(fichtm,"<br>- and by state of destination <a href=\"%s-dest.png\">%s-dest.png</a><br> \
1.204 brouard 3857: <img src=\"%s-dest.png\">",subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"));
1.207 brouard 3858: fflush(fichtm);
1.205 brouard 3859: }
1.126 brouard 3860: return;
3861: }
3862:
3863:
3864: /*********** Maximum Likelihood Estimation ***************/
3865:
3866: void mlikeli(FILE *ficres,double p[], int npar, int ncovmodel, int nlstate, double ftol, double (*func)(double []))
3867: {
1.165 brouard 3868: int i,j, iter=0;
1.126 brouard 3869: double **xi;
3870: double fret;
3871: double fretone; /* Only one call to likelihood */
3872: /* char filerespow[FILENAMELENGTH];*/
1.162 brouard 3873:
3874: #ifdef NLOPT
3875: int creturn;
3876: nlopt_opt opt;
3877: /* double lb[9] = { -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL }; /\* lower bounds *\/ */
3878: double *lb;
3879: double minf; /* the minimum objective value, upon return */
3880: double * p1; /* Shifted parameters from 0 instead of 1 */
3881: myfunc_data dinst, *d = &dinst;
3882: #endif
3883:
3884:
1.126 brouard 3885: xi=matrix(1,npar,1,npar);
3886: for (i=1;i<=npar;i++)
3887: for (j=1;j<=npar;j++)
3888: xi[i][j]=(i==j ? 1.0 : 0.0);
3889: printf("Powell\n"); fprintf(ficlog,"Powell\n");
1.201 brouard 3890: strcpy(filerespow,"POW_");
1.126 brouard 3891: strcat(filerespow,fileres);
3892: if((ficrespow=fopen(filerespow,"w"))==NULL) {
3893: printf("Problem with resultfile: %s\n", filerespow);
3894: fprintf(ficlog,"Problem with resultfile: %s\n", filerespow);
3895: }
3896: fprintf(ficrespow,"# Powell\n# iter -2*LL");
3897: for (i=1;i<=nlstate;i++)
3898: for(j=1;j<=nlstate+ndeath;j++)
3899: if(j!=i)fprintf(ficrespow," p%1d%1d",i,j);
3900: fprintf(ficrespow,"\n");
1.162 brouard 3901: #ifdef POWELL
1.126 brouard 3902: powell(p,xi,npar,ftol,&iter,&fret,func);
1.162 brouard 3903: #endif
1.126 brouard 3904:
1.162 brouard 3905: #ifdef NLOPT
3906: #ifdef NEWUOA
3907: opt = nlopt_create(NLOPT_LN_NEWUOA,npar);
3908: #else
3909: opt = nlopt_create(NLOPT_LN_BOBYQA,npar);
3910: #endif
3911: lb=vector(0,npar-1);
3912: for (i=0;i<npar;i++) lb[i]= -HUGE_VAL;
3913: nlopt_set_lower_bounds(opt, lb);
3914: nlopt_set_initial_step1(opt, 0.1);
3915:
3916: p1= (p+1); /* p *(p+1)@8 and p *(p1)@8 are equal p1[0]=p[1] */
3917: d->function = func;
3918: printf(" Func %.12lf \n",myfunc(npar,p1,NULL,d));
3919: nlopt_set_min_objective(opt, myfunc, d);
3920: nlopt_set_xtol_rel(opt, ftol);
3921: if ((creturn=nlopt_optimize(opt, p1, &minf)) < 0) {
3922: printf("nlopt failed! %d\n",creturn);
3923: }
3924: else {
3925: printf("found minimum after %d evaluations (NLOPT=%d)\n", countcallfunc ,NLOPT);
3926: printf("found minimum at f(%g,%g) = %0.10g\n", p[0], p[1], minf);
3927: iter=1; /* not equal */
3928: }
3929: nlopt_destroy(opt);
3930: #endif
1.126 brouard 3931: free_matrix(xi,1,npar,1,npar);
3932: fclose(ficrespow);
1.203 brouard 3933: printf("\n#Number of iterations & function calls = %d & %d, -2 Log likelihood = %.12f\n",iter, countcallfunc,func(p));
3934: fprintf(ficlog,"\n#Number of iterations & function calls = %d & %d, -2 Log likelihood = %.12f\n",iter, countcallfunc,func(p));
1.180 brouard 3935: fprintf(ficres,"#Number of iterations & function calls = %d & %d, -2 Log likelihood = %.12f\n",iter, countcallfunc,func(p));
1.126 brouard 3936:
3937: }
3938:
3939: /**** Computes Hessian and covariance matrix ***/
1.203 brouard 3940: void hesscov(double **matcov, double **hess, double p[], int npar, double delti[], double ftolhess, double (*func)(double []))
1.126 brouard 3941: {
3942: double **a,**y,*x,pd;
1.203 brouard 3943: /* double **hess; */
1.164 brouard 3944: int i, j;
1.126 brouard 3945: int *indx;
3946:
3947: double hessii(double p[], double delta, int theta, double delti[],double (*func)(double []),int npar);
1.203 brouard 3948: double hessij(double p[], double **hess, double delti[], int i, int j,double (*func)(double []),int npar);
1.126 brouard 3949: void lubksb(double **a, int npar, int *indx, double b[]) ;
3950: void ludcmp(double **a, int npar, int *indx, double *d) ;
3951: double gompertz(double p[]);
1.203 brouard 3952: /* hess=matrix(1,npar,1,npar); */
1.126 brouard 3953:
3954: printf("\nCalculation of the hessian matrix. Wait...\n");
3955: fprintf(ficlog,"\nCalculation of the hessian matrix. Wait...\n");
3956: for (i=1;i<=npar;i++){
1.203 brouard 3957: printf("%d-",i);fflush(stdout);
3958: fprintf(ficlog,"%d-",i);fflush(ficlog);
1.126 brouard 3959:
3960: hess[i][i]=hessii(p,ftolhess,i,delti,func,npar);
3961:
3962: /* printf(" %f ",p[i]);
3963: printf(" %lf %lf %lf",hess[i][i],ftolhess,delti[i]);*/
3964: }
3965:
3966: for (i=1;i<=npar;i++) {
3967: for (j=1;j<=npar;j++) {
3968: if (j>i) {
1.203 brouard 3969: printf(".%d-%d",i,j);fflush(stdout);
3970: fprintf(ficlog,".%d-%d",i,j);fflush(ficlog);
3971: hess[i][j]=hessij(p,hess, delti,i,j,func,npar);
1.126 brouard 3972:
3973: hess[j][i]=hess[i][j];
3974: /*printf(" %lf ",hess[i][j]);*/
3975: }
3976: }
3977: }
3978: printf("\n");
3979: fprintf(ficlog,"\n");
3980:
3981: printf("\nInverting the hessian to get the covariance matrix. Wait...\n");
3982: fprintf(ficlog,"\nInverting the hessian to get the covariance matrix. Wait...\n");
3983:
3984: a=matrix(1,npar,1,npar);
3985: y=matrix(1,npar,1,npar);
3986: x=vector(1,npar);
3987: indx=ivector(1,npar);
3988: for (i=1;i<=npar;i++)
3989: for (j=1;j<=npar;j++) a[i][j]=hess[i][j];
3990: ludcmp(a,npar,indx,&pd);
3991:
3992: for (j=1;j<=npar;j++) {
3993: for (i=1;i<=npar;i++) x[i]=0;
3994: x[j]=1;
3995: lubksb(a,npar,indx,x);
3996: for (i=1;i<=npar;i++){
3997: matcov[i][j]=x[i];
3998: }
3999: }
4000:
4001: printf("\n#Hessian matrix#\n");
4002: fprintf(ficlog,"\n#Hessian matrix#\n");
4003: for (i=1;i<=npar;i++) {
4004: for (j=1;j<=npar;j++) {
1.203 brouard 4005: printf("%.6e ",hess[i][j]);
4006: fprintf(ficlog,"%.6e ",hess[i][j]);
1.126 brouard 4007: }
4008: printf("\n");
4009: fprintf(ficlog,"\n");
4010: }
4011:
1.203 brouard 4012: /* printf("\n#Covariance matrix#\n"); */
4013: /* fprintf(ficlog,"\n#Covariance matrix#\n"); */
4014: /* for (i=1;i<=npar;i++) { */
4015: /* for (j=1;j<=npar;j++) { */
4016: /* printf("%.6e ",matcov[i][j]); */
4017: /* fprintf(ficlog,"%.6e ",matcov[i][j]); */
4018: /* } */
4019: /* printf("\n"); */
4020: /* fprintf(ficlog,"\n"); */
4021: /* } */
4022:
1.126 brouard 4023: /* Recompute Inverse */
1.203 brouard 4024: /* for (i=1;i<=npar;i++) */
4025: /* for (j=1;j<=npar;j++) a[i][j]=matcov[i][j]; */
4026: /* ludcmp(a,npar,indx,&pd); */
4027:
4028: /* printf("\n#Hessian matrix recomputed#\n"); */
4029:
4030: /* for (j=1;j<=npar;j++) { */
4031: /* for (i=1;i<=npar;i++) x[i]=0; */
4032: /* x[j]=1; */
4033: /* lubksb(a,npar,indx,x); */
4034: /* for (i=1;i<=npar;i++){ */
4035: /* y[i][j]=x[i]; */
4036: /* printf("%.3e ",y[i][j]); */
4037: /* fprintf(ficlog,"%.3e ",y[i][j]); */
4038: /* } */
4039: /* printf("\n"); */
4040: /* fprintf(ficlog,"\n"); */
4041: /* } */
4042:
4043: /* Verifying the inverse matrix */
4044: #ifdef DEBUGHESS
4045: y=matprod2(y,hess,1,npar,1,npar,1,npar,matcov);
1.126 brouard 4046:
1.203 brouard 4047: printf("\n#Verification: multiplying the matrix of covariance by the Hessian matrix, should be unity:#\n");
4048: fprintf(ficlog,"\n#Verification: multiplying the matrix of covariance by the Hessian matrix. Should be unity:#\n");
1.126 brouard 4049:
4050: for (j=1;j<=npar;j++) {
4051: for (i=1;i<=npar;i++){
1.203 brouard 4052: printf("%.2f ",y[i][j]);
4053: fprintf(ficlog,"%.2f ",y[i][j]);
1.126 brouard 4054: }
4055: printf("\n");
4056: fprintf(ficlog,"\n");
4057: }
1.203 brouard 4058: #endif
1.126 brouard 4059:
4060: free_matrix(a,1,npar,1,npar);
4061: free_matrix(y,1,npar,1,npar);
4062: free_vector(x,1,npar);
4063: free_ivector(indx,1,npar);
1.203 brouard 4064: /* free_matrix(hess,1,npar,1,npar); */
1.126 brouard 4065:
4066:
4067: }
4068:
4069: /*************** hessian matrix ****************/
4070: double hessii(double x[], double delta, int theta, double delti[], double (*func)(double []), int npar)
1.203 brouard 4071: { /* Around values of x, computes the function func and returns the scales delti and hessian */
1.126 brouard 4072: int i;
4073: int l=1, lmax=20;
1.203 brouard 4074: double k1,k2, res, fx;
1.132 brouard 4075: double p2[MAXPARM+1]; /* identical to x */
1.126 brouard 4076: double delt=0.0001, delts, nkhi=10.,nkhif=1., khi=1.e-4;
4077: int k=0,kmax=10;
4078: double l1;
4079:
4080: fx=func(x);
4081: for (i=1;i<=npar;i++) p2[i]=x[i];
1.145 brouard 4082: for(l=0 ; l <=lmax; l++){ /* Enlarging the zone around the Maximum */
1.126 brouard 4083: l1=pow(10,l);
4084: delts=delt;
4085: for(k=1 ; k <kmax; k=k+1){
4086: delt = delta*(l1*k);
4087: p2[theta]=x[theta] +delt;
1.145 brouard 4088: k1=func(p2)-fx; /* Might be negative if too close to the theoretical maximum */
1.126 brouard 4089: p2[theta]=x[theta]-delt;
4090: k2=func(p2)-fx;
4091: /*res= (k1-2.0*fx+k2)/delt/delt; */
1.203 brouard 4092: res= (k1+k2)/delt/delt/2.; /* Divided by 2 because L and not 2*L */
1.126 brouard 4093:
1.203 brouard 4094: #ifdef DEBUGHESSII
1.126 brouard 4095: 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);
4096: 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);
4097: #endif
4098: /*if(fabs(k1-2.0*fx+k2) <1.e-13){ */
4099: if((k1 <khi/nkhi/2.) || (k2 <khi/nkhi/2.)){
4100: k=kmax;
4101: }
4102: else if((k1 >khi/nkhif) || (k2 >khi/nkhif)){ /* Keeps lastvalue before 3.84/2 KHI2 5% 1d.f. */
1.164 brouard 4103: k=kmax; l=lmax*10;
1.126 brouard 4104: }
4105: else if((k1 >khi/nkhi) || (k2 >khi/nkhi)){
4106: delts=delt;
4107: }
1.203 brouard 4108: } /* End loop k */
1.126 brouard 4109: }
4110: delti[theta]=delts;
4111: return res;
4112:
4113: }
4114:
1.203 brouard 4115: double hessij( double x[], double **hess, double delti[], int thetai,int thetaj,double (*func)(double []),int npar)
1.126 brouard 4116: {
4117: int i;
1.164 brouard 4118: int l=1, lmax=20;
1.126 brouard 4119: double k1,k2,k3,k4,res,fx;
1.132 brouard 4120: double p2[MAXPARM+1];
1.203 brouard 4121: int k, kmax=1;
4122: double v1, v2, cv12, lc1, lc2;
1.208 brouard 4123:
4124: int firstime=0;
1.203 brouard 4125:
1.126 brouard 4126: fx=func(x);
1.203 brouard 4127: for (k=1; k<=kmax; k=k+10) {
1.126 brouard 4128: for (i=1;i<=npar;i++) p2[i]=x[i];
1.203 brouard 4129: p2[thetai]=x[thetai]+delti[thetai]*k;
4130: p2[thetaj]=x[thetaj]+delti[thetaj]*k;
1.126 brouard 4131: k1=func(p2)-fx;
4132:
1.203 brouard 4133: p2[thetai]=x[thetai]+delti[thetai]*k;
4134: p2[thetaj]=x[thetaj]-delti[thetaj]*k;
1.126 brouard 4135: k2=func(p2)-fx;
4136:
1.203 brouard 4137: p2[thetai]=x[thetai]-delti[thetai]*k;
4138: p2[thetaj]=x[thetaj]+delti[thetaj]*k;
1.126 brouard 4139: k3=func(p2)-fx;
4140:
1.203 brouard 4141: p2[thetai]=x[thetai]-delti[thetai]*k;
4142: p2[thetaj]=x[thetaj]-delti[thetaj]*k;
1.126 brouard 4143: k4=func(p2)-fx;
1.203 brouard 4144: res=(k1-k2-k3+k4)/4.0/delti[thetai]/k/delti[thetaj]/k/2.; /* Because of L not 2*L */
4145: if(k1*k2*k3*k4 <0.){
1.208 brouard 4146: firstime=1;
1.203 brouard 4147: kmax=kmax+10;
1.208 brouard 4148: }
4149: if(kmax >=10 || firstime ==1){
1.246 brouard 4150: 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);
4151: 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 4152: 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);
4153: 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);
4154: }
4155: #ifdef DEBUGHESSIJ
4156: v1=hess[thetai][thetai];
4157: v2=hess[thetaj][thetaj];
4158: cv12=res;
4159: /* Computing eigen value of Hessian matrix */
4160: lc1=((v1+v2)+sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
4161: lc2=((v1+v2)-sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
4162: if ((lc2 <0) || (lc1 <0) ){
4163: printf("Warning: sub Hessian matrix '%d%d' does not have positive eigen values \n",thetai,thetaj);
4164: fprintf(ficlog, "Warning: sub Hessian matrix '%d%d' does not have positive eigen values \n",thetai,thetaj);
4165: 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);
4166: 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);
4167: }
1.126 brouard 4168: #endif
4169: }
4170: return res;
4171: }
4172:
1.203 brouard 4173: /* Not done yet: Was supposed to fix if not exactly at the maximum */
4174: /* double hessij( double x[], double delti[], int thetai,int thetaj,double (*func)(double []),int npar) */
4175: /* { */
4176: /* int i; */
4177: /* int l=1, lmax=20; */
4178: /* double k1,k2,k3,k4,res,fx; */
4179: /* double p2[MAXPARM+1]; */
4180: /* double delt=0.0001, delts, nkhi=10.,nkhif=1., khi=1.e-4; */
4181: /* int k=0,kmax=10; */
4182: /* double l1; */
4183:
4184: /* fx=func(x); */
4185: /* for(l=0 ; l <=lmax; l++){ /\* Enlarging the zone around the Maximum *\/ */
4186: /* l1=pow(10,l); */
4187: /* delts=delt; */
4188: /* for(k=1 ; k <kmax; k=k+1){ */
4189: /* delt = delti*(l1*k); */
4190: /* for (i=1;i<=npar;i++) p2[i]=x[i]; */
4191: /* p2[thetai]=x[thetai]+delti[thetai]/k; */
4192: /* p2[thetaj]=x[thetaj]+delti[thetaj]/k; */
4193: /* k1=func(p2)-fx; */
4194:
4195: /* p2[thetai]=x[thetai]+delti[thetai]/k; */
4196: /* p2[thetaj]=x[thetaj]-delti[thetaj]/k; */
4197: /* k2=func(p2)-fx; */
4198:
4199: /* p2[thetai]=x[thetai]-delti[thetai]/k; */
4200: /* p2[thetaj]=x[thetaj]+delti[thetaj]/k; */
4201: /* k3=func(p2)-fx; */
4202:
4203: /* p2[thetai]=x[thetai]-delti[thetai]/k; */
4204: /* p2[thetaj]=x[thetaj]-delti[thetaj]/k; */
4205: /* k4=func(p2)-fx; */
4206: /* res=(k1-k2-k3+k4)/4.0/delti[thetai]*k/delti[thetaj]*k/2.; /\* Because of L not 2*L *\/ */
4207: /* #ifdef DEBUGHESSIJ */
4208: /* 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); */
4209: /* 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); */
4210: /* #endif */
4211: /* if((k1 <khi/nkhi/2.) || (k2 <khi/nkhi/2.)|| (k4 <khi/nkhi/2.)|| (k4 <khi/nkhi/2.)){ */
4212: /* k=kmax; */
4213: /* } */
4214: /* else if((k1 >khi/nkhif) || (k2 >khi/nkhif) || (k4 >khi/nkhif) || (k4 >khi/nkhif)){ /\* Keeps lastvalue before 3.84/2 KHI2 5% 1d.f. *\/ */
4215: /* k=kmax; l=lmax*10; */
4216: /* } */
4217: /* else if((k1 >khi/nkhi) || (k2 >khi/nkhi)){ */
4218: /* delts=delt; */
4219: /* } */
4220: /* } /\* End loop k *\/ */
4221: /* } */
4222: /* delti[theta]=delts; */
4223: /* return res; */
4224: /* } */
4225:
4226:
1.126 brouard 4227: /************** Inverse of matrix **************/
4228: void ludcmp(double **a, int n, int *indx, double *d)
4229: {
4230: int i,imax,j,k;
4231: double big,dum,sum,temp;
4232: double *vv;
4233:
4234: vv=vector(1,n);
4235: *d=1.0;
4236: for (i=1;i<=n;i++) {
4237: big=0.0;
4238: for (j=1;j<=n;j++)
4239: if ((temp=fabs(a[i][j])) > big) big=temp;
1.256 brouard 4240: if (big == 0.0){
4241: printf(" Singular Hessian matrix at row %d:\n",i);
4242: for (j=1;j<=n;j++) {
4243: printf(" a[%d][%d]=%f,",i,j,a[i][j]);
4244: fprintf(ficlog," a[%d][%d]=%f,",i,j,a[i][j]);
4245: }
4246: fflush(ficlog);
4247: fclose(ficlog);
4248: nrerror("Singular matrix in routine ludcmp");
4249: }
1.126 brouard 4250: vv[i]=1.0/big;
4251: }
4252: for (j=1;j<=n;j++) {
4253: for (i=1;i<j;i++) {
4254: sum=a[i][j];
4255: for (k=1;k<i;k++) sum -= a[i][k]*a[k][j];
4256: a[i][j]=sum;
4257: }
4258: big=0.0;
4259: for (i=j;i<=n;i++) {
4260: sum=a[i][j];
4261: for (k=1;k<j;k++)
4262: sum -= a[i][k]*a[k][j];
4263: a[i][j]=sum;
4264: if ( (dum=vv[i]*fabs(sum)) >= big) {
4265: big=dum;
4266: imax=i;
4267: }
4268: }
4269: if (j != imax) {
4270: for (k=1;k<=n;k++) {
4271: dum=a[imax][k];
4272: a[imax][k]=a[j][k];
4273: a[j][k]=dum;
4274: }
4275: *d = -(*d);
4276: vv[imax]=vv[j];
4277: }
4278: indx[j]=imax;
4279: if (a[j][j] == 0.0) a[j][j]=TINY;
4280: if (j != n) {
4281: dum=1.0/(a[j][j]);
4282: for (i=j+1;i<=n;i++) a[i][j] *= dum;
4283: }
4284: }
4285: free_vector(vv,1,n); /* Doesn't work */
4286: ;
4287: }
4288:
4289: void lubksb(double **a, int n, int *indx, double b[])
4290: {
4291: int i,ii=0,ip,j;
4292: double sum;
4293:
4294: for (i=1;i<=n;i++) {
4295: ip=indx[i];
4296: sum=b[ip];
4297: b[ip]=b[i];
4298: if (ii)
4299: for (j=ii;j<=i-1;j++) sum -= a[i][j]*b[j];
4300: else if (sum) ii=i;
4301: b[i]=sum;
4302: }
4303: for (i=n;i>=1;i--) {
4304: sum=b[i];
4305: for (j=i+1;j<=n;j++) sum -= a[i][j]*b[j];
4306: b[i]=sum/a[i][i];
4307: }
4308: }
4309:
4310: void pstamp(FILE *fichier)
4311: {
1.196 brouard 4312: fprintf(fichier,"# %s.%s\n#IMaCh version %s, %s\n#%s\n# %s", optionfilefiname,optionfilext,version,copyright, fullversion, strstart);
1.126 brouard 4313: }
4314:
1.253 brouard 4315:
4316:
1.126 brouard 4317: /************ Frequencies ********************/
1.251 brouard 4318: void freqsummary(char fileres[], double p[], double pstart[], int iagemin, int iagemax, int **s, double **agev, int nlstate, int imx, \
1.226 brouard 4319: int *Tvaraff, int *invalidvarcomb, int **nbcode, int *ncodemax,double **mint,double **anint, char strstart[], \
4320: int firstpass, int lastpass, int stepm, int weightopt, char model[])
1.250 brouard 4321: { /* Some frequencies as well as proposing some starting values */
1.226 brouard 4322:
1.265 brouard 4323: int i, m, jk, j1, bool, z1,j, nj, nl, k, iv, jj=0, s1=1, s2=1;
1.226 brouard 4324: int iind=0, iage=0;
4325: int mi; /* Effective wave */
4326: int first;
4327: double ***freq; /* Frequencies */
1.268 brouard 4328: double *x, *y, a=0.,b=0.,r=1., sa=0., sb=0.; /* for regression, y=b+m*x and r is the correlation coefficient */
4329: int no=0, linreg(int ifi, int ila, int *no, const double x[], const double y[], double* a, double* b, double* r, double* sa, double * sb);
1.226 brouard 4330: double *meanq;
4331: double **meanqt;
4332: double *pp, **prop, *posprop, *pospropt;
4333: double pos=0., posproptt=0., pospropta=0., k2, dateintsum=0,k2cpt=0;
4334: char fileresp[FILENAMELENGTH], fileresphtm[FILENAMELENGTH], fileresphtmfr[FILENAMELENGTH];
4335: double agebegin, ageend;
4336:
4337: pp=vector(1,nlstate);
1.251 brouard 4338: prop=matrix(1,nlstate,iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.226 brouard 4339: posprop=vector(1,nlstate); /* Counting the number of transition starting from a live state per age */
4340: pospropt=vector(1,nlstate); /* Counting the number of transition starting from a live state */
4341: /* prop=matrix(1,nlstate,iagemin,iagemax+3); */
4342: meanq=vector(1,nqfveff); /* Number of Quantitative Fixed Variables Effective */
4343: meanqt=matrix(1,lastpass,1,nqtveff);
4344: strcpy(fileresp,"P_");
4345: strcat(fileresp,fileresu);
4346: /*strcat(fileresphtm,fileresu);*/
4347: if((ficresp=fopen(fileresp,"w"))==NULL) {
4348: printf("Problem with prevalence resultfile: %s\n", fileresp);
4349: fprintf(ficlog,"Problem with prevalence resultfile: %s\n", fileresp);
4350: exit(0);
4351: }
1.240 brouard 4352:
1.226 brouard 4353: strcpy(fileresphtm,subdirfext(optionfilefiname,"PHTM_",".htm"));
4354: if((ficresphtm=fopen(fileresphtm,"w"))==NULL) {
4355: printf("Problem with prevalence HTM resultfile '%s' with errno='%s'\n",fileresphtm,strerror(errno));
4356: fprintf(ficlog,"Problem with prevalence HTM resultfile '%s' with errno='%s'\n",fileresphtm,strerror(errno));
4357: fflush(ficlog);
4358: exit(70);
4359: }
4360: else{
4361: fprintf(ficresphtm,"<html><head>\n<title>IMaCh PHTM_ %s</title></head>\n <body><font size=\"2\">%s <br> %s</font> \
1.240 brouard 4362: <hr size=\"2\" color=\"#EC5E5E\"> \n \
1.214 brouard 4363: Title=%s <br>Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s<br>\n",\
1.226 brouard 4364: fileresphtm,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model);
4365: }
1.237 brouard 4366: 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 4367:
1.226 brouard 4368: strcpy(fileresphtmfr,subdirfext(optionfilefiname,"PHTMFR_",".htm"));
4369: if((ficresphtmfr=fopen(fileresphtmfr,"w"))==NULL) {
4370: printf("Problem with frequency table HTM resultfile '%s' with errno='%s'\n",fileresphtmfr,strerror(errno));
4371: fprintf(ficlog,"Problem with frequency table HTM resultfile '%s' with errno='%s'\n",fileresphtmfr,strerror(errno));
4372: fflush(ficlog);
4373: exit(70);
1.240 brouard 4374: } else{
1.226 brouard 4375: 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 4376: <hr size=\"2\" color=\"#EC5E5E\"> \n \
1.214 brouard 4377: Title=%s <br>Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s<br>\n",\
1.226 brouard 4378: fileresphtmfr,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model);
4379: }
1.240 brouard 4380: 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);
4381:
1.253 brouard 4382: y= vector(iagemin-AGEMARGE,iagemax+4+AGEMARGE);
4383: x= vector(iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.251 brouard 4384: freq= ma3x(-5,nlstate+ndeath,-5,nlstate+ndeath,iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.226 brouard 4385: j1=0;
1.126 brouard 4386:
1.227 brouard 4387: /* j=ncoveff; /\* Only fixed dummy covariates *\/ */
4388: j=cptcoveff; /* Only dummy covariates of the model */
1.226 brouard 4389: if (cptcovn<1) {j=1;ncodemax[1]=1;}
1.240 brouard 4390:
4391:
1.226 brouard 4392: /* Detects if a combination j1 is empty: for a multinomial variable like 3 education levels:
4393: reference=low_education V1=0,V2=0
4394: med_educ V1=1 V2=0,
4395: high_educ V1=0 V2=1
4396: Then V1=1 and V2=1 is a noisy combination that we want to exclude for the list 2**cptcoveff
4397: */
1.249 brouard 4398: dateintsum=0;
4399: k2cpt=0;
4400:
1.253 brouard 4401: if(cptcoveff == 0 )
1.265 brouard 4402: nl=1; /* Constant and age model only */
1.253 brouard 4403: else
4404: nl=2;
1.265 brouard 4405:
4406: /* if a constant only model, one pass to compute frequency tables and to write it on ficresp */
4407: /* Loop on nj=1 or 2 if dummy covariates j!=0
4408: * Loop on j1(1 to 2**cptcoveff) covariate combination
4409: * freq[s1][s2][iage] =0.
4410: * Loop on iind
4411: * ++freq[s1][s2][iage] weighted
4412: * end iind
4413: * if covariate and j!0
4414: * headers Variable on one line
4415: * endif cov j!=0
4416: * header of frequency table by age
4417: * Loop on age
4418: * pp[s1]+=freq[s1][s2][iage] weighted
4419: * pos+=freq[s1][s2][iage] weighted
4420: * Loop on s1 initial state
4421: * fprintf(ficresp
4422: * end s1
4423: * end age
4424: * if j!=0 computes starting values
4425: * end compute starting values
4426: * end j1
4427: * end nl
4428: */
1.253 brouard 4429: for (nj = 1; nj <= nl; nj++){ /* nj= 1 constant model, nl number of loops. */
4430: if(nj==1)
4431: j=0; /* First pass for the constant */
1.265 brouard 4432: else{
1.253 brouard 4433: j=cptcoveff; /* Other passes for the covariate values */
1.265 brouard 4434: }
1.251 brouard 4435: first=1;
1.265 brouard 4436: for (j1 = 1; j1 <= (int) pow(2,j); j1++){ /* Loop on all covariates combination of the model, excluding quantitatives, V4=0, V3=0 for example, fixed or varying covariates */
1.251 brouard 4437: posproptt=0.;
4438: /*printf("cptcoveff=%d Tvaraff=%d", cptcoveff,Tvaraff[1]);
4439: scanf("%d", i);*/
4440: for (i=-5; i<=nlstate+ndeath; i++)
1.265 brouard 4441: for (s2=-5; s2<=nlstate+ndeath; s2++)
1.251 brouard 4442: for(m=iagemin; m <= iagemax+3; m++)
1.265 brouard 4443: freq[i][s2][m]=0;
1.251 brouard 4444:
4445: for (i=1; i<=nlstate; i++) {
1.240 brouard 4446: for(m=iagemin; m <= iagemax+3; m++)
1.251 brouard 4447: prop[i][m]=0;
4448: posprop[i]=0;
4449: pospropt[i]=0;
4450: }
4451: /* for (z1=1; z1<= nqfveff; z1++) { */
4452: /* meanq[z1]+=0.; */
4453: /* for(m=1;m<=lastpass;m++){ */
4454: /* meanqt[m][z1]=0.; */
4455: /* } */
4456: /* } */
4457:
4458: /* dateintsum=0; */
4459: /* k2cpt=0; */
4460:
1.265 brouard 4461: /* For that combination of covariates j1 (V4=1 V3=0 for example), we count and print the frequencies in one pass */
1.251 brouard 4462: for (iind=1; iind<=imx; iind++) { /* For each individual iind */
4463: bool=1;
4464: if(j !=0){
4465: if(anyvaryingduminmodel==0){ /* If All fixed covariates */
4466: if (cptcoveff >0) { /* Filter is here: Must be looked at for model=V1+V2+V3+V4 */
4467: /* for (z1=1; z1<= nqfveff; z1++) { */
4468: /* meanq[z1]+=coqvar[Tvar[z1]][iind]; /\* Computes mean of quantitative with selected filter *\/ */
4469: /* } */
4470: for (z1=1; z1<=cptcoveff; z1++) { /* loops on covariates in the model */
4471: /* if(Tvaraff[z1] ==-20){ */
4472: /* /\* sumnew+=cotvar[mw[mi][iind]][z1][iind]; *\/ */
4473: /* }else if(Tvaraff[z1] ==-10){ */
4474: /* /\* sumnew+=coqvar[z1][iind]; *\/ */
4475: /* }else */
4476: if (covar[Tvaraff[z1]][iind]!= nbcode[Tvaraff[z1]][codtabm(j1,z1)]){ /* for combination j1 of covariates */
1.265 brouard 4477: /* Tests if the value of the covariate z1 for this individual iind responded to combination j1 (V4=1 V3=0) */
1.251 brouard 4478: bool=0; /* bool should be equal to 1 to be selected, one covariate value failed */
4479: /* 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",
4480: bool,i,z1, z1, Tvaraff[z1],i,covar[Tvaraff[z1]][i],j1,z1,codtabm(j1,z1),
4481: j1,z1,nbcode[Tvaraff[z1]][codtabm(j1,z1)],j1);*/
4482: /* For j1=7 in V1+V2+V3+V4 = 0 1 1 0 and codtabm(7,3)=1 and nbcde[3][?]=1*/
4483: } /* Onlyf fixed */
4484: } /* end z1 */
4485: } /* cptcovn > 0 */
4486: } /* end any */
4487: }/* end j==0 */
1.265 brouard 4488: if (bool==1){ /* We selected an individual iind satisfying combination j1 (V4=1 V3=0) or all fixed covariates */
1.251 brouard 4489: /* for(m=firstpass; m<=lastpass; m++){ */
4490: for(mi=1; mi<wav[iind];mi++){ /* For that wave */
4491: m=mw[mi][iind];
4492: if(j!=0){
4493: if(anyvaryingduminmodel==1){ /* Some are varying covariates */
4494: for (z1=1; z1<=cptcoveff; z1++) {
4495: if( Fixed[Tmodelind[z1]]==1){
4496: iv= Tvar[Tmodelind[z1]]-ncovcol-nqv;
4497: if (cotvar[m][iv][iind]!= nbcode[Tvaraff[z1]][codtabm(j1,z1)]) /* iv=1 to ntv, right modality. If covariate's
4498: value is -1, we don't select. It differs from the
4499: constant and age model which counts them. */
4500: bool=0; /* not selected */
4501: }else if( Fixed[Tmodelind[z1]]== 0) { /* fixed */
4502: if (covar[Tvaraff[z1]][iind]!= nbcode[Tvaraff[z1]][codtabm(j1,z1)]) {
4503: bool=0;
4504: }
4505: }
4506: }
4507: }/* Some are varying covariates, we tried to speed up if all fixed covariates in the model, avoiding waves loop */
4508: } /* end j==0 */
4509: /* bool =0 we keep that guy which corresponds to the combination of dummy values */
4510: if(bool==1){
4511: /* dh[m][iind] or dh[mw[mi][iind]][iind] is the delay between two effective (mi) waves m=mw[mi][iind]
4512: and mw[mi+1][iind]. dh depends on stepm. */
4513: agebegin=agev[m][iind]; /* Age at beginning of wave before transition*/
4514: ageend=agev[m][iind]+(dh[m][iind])*stepm/YEARM; /* Age at end of wave and transition */
4515: if(m >=firstpass && m <=lastpass){
4516: k2=anint[m][iind]+(mint[m][iind]/12.);
4517: /*if ((k2>=dateprev1) && (k2<=dateprev2)) {*/
4518: if(agev[m][iind]==0) agev[m][iind]=iagemax+1; /* All ages equal to 0 are in iagemax+1 */
4519: if(agev[m][iind]==1) agev[m][iind]=iagemax+2; /* All ages equal to 1 are in iagemax+2 */
4520: if (s[m][iind]>0 && s[m][iind]<=nlstate) /* If status at wave m is known and a live state */
4521: prop[s[m][iind]][(int)agev[m][iind]] += weight[iind]; /* At age of beginning of transition, where status is known */
4522: if (m<lastpass) {
4523: /* if(s[m][iind]==4 && s[m+1][iind]==4) */
4524: /* 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]); */
4525: if(s[m][iind]==-1)
4526: 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.));
4527: freq[s[m][iind]][s[m+1][iind]][(int)agev[m][iind]] += weight[iind]; /* At age of beginning of transition, where status is known */
4528: /* if((int)agev[m][iind] == 55) */
4529: /* printf("j=%d, j1=%d Age %d, iind=%d, num=%09ld m=%d\n",j,j1,(int)agev[m][iind],iind, num[iind],m); */
4530: /* freq[s[m][iind]][s[m+1][iind]][(int)((agebegin+ageend)/2.)] += weight[iind]; */
4531: 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 4532: }
1.251 brouard 4533: } /* end if between passes */
4534: if ((agev[m][iind]>1) && (agev[m][iind]< (iagemax+3)) && (anint[m][iind]!=9999) && (mint[m][iind]!=99) && (j==0)) {
4535: dateintsum=dateintsum+k2; /* on all covariates ?*/
4536: k2cpt++;
4537: /* printf("iind=%ld dateintmean = %lf dateintsum=%lf k2cpt=%lf k2=%lf\n",iind, dateintsum/k2cpt, dateintsum,k2cpt, k2); */
1.234 brouard 4538: }
1.251 brouard 4539: }else{
4540: bool=1;
4541: }/* end bool 2 */
4542: } /* end m */
4543: } /* end bool */
4544: } /* end iind = 1 to imx */
4545: /* prop[s][age] is feeded for any initial and valid live state as well as
4546: freq[s1][s2][age] at single age of beginning the transition, for a combination j1 */
4547:
4548:
4549: /* fprintf(ficresp, "#Count between %.lf/%.lf/%.lf and %.lf/%.lf/%.lf\n",jprev1, mprev1,anprev1,jprev2, mprev2,anprev2);*/
1.265 brouard 4550: if(cptcoveff==0 && nj==1) /* no covariate and first pass */
4551: pstamp(ficresp);
1.251 brouard 4552: if (cptcoveff>0 && j!=0){
1.265 brouard 4553: pstamp(ficresp);
1.251 brouard 4554: printf( "\n#********** Variable ");
4555: fprintf(ficresp, "\n#********** Variable ");
4556: fprintf(ficresphtm, "\n<br/><br/><h3>********** Variable ");
4557: fprintf(ficresphtmfr, "\n<br/><br/><h3>********** Variable ");
4558: fprintf(ficlog, "\n#********** Variable ");
4559: for (z1=1; z1<=cptcoveff; z1++){
4560: if(!FixedV[Tvaraff[z1]]){
4561: printf( "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4562: fprintf(ficresp, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4563: fprintf(ficresphtm, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4564: fprintf(ficresphtmfr, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4565: fprintf(ficlog, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
1.250 brouard 4566: }else{
1.251 brouard 4567: printf( "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4568: fprintf(ficresp, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4569: fprintf(ficresphtm, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4570: fprintf(ficresphtmfr, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4571: fprintf(ficlog, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4572: }
4573: }
4574: printf( "**********\n#");
4575: fprintf(ficresp, "**********\n#");
4576: fprintf(ficresphtm, "**********</h3>\n");
4577: fprintf(ficresphtmfr, "**********</h3>\n");
4578: fprintf(ficlog, "**********\n");
4579: }
4580: fprintf(ficresphtm,"<table style=\"text-align:center; border: 1px solid\">");
1.265 brouard 4581: if((cptcoveff==0 && nj==1)|| nj==2 ) /* no covariate and first pass */
4582: fprintf(ficresp, " Age");
4583: if(nj==2) for (z1=1; z1<=cptcoveff; z1++) fprintf(ficresp, " V%d=%d",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
1.251 brouard 4584: for(i=1; i<=nlstate;i++) {
1.265 brouard 4585: if((cptcoveff==0 && nj==1)|| nj==2 ) fprintf(ficresp," Prev(%d) N(%d) N ",i,i);
1.251 brouard 4586: fprintf(ficresphtm, "<th>Age</th><th>Prev(%d)</th><th>N(%d)</th><th>N</th>",i,i);
4587: }
1.265 brouard 4588: if((cptcoveff==0 && nj==1)|| nj==2 ) fprintf(ficresp, "\n");
1.251 brouard 4589: fprintf(ficresphtm, "\n");
4590:
4591: /* Header of frequency table by age */
4592: fprintf(ficresphtmfr,"<table style=\"text-align:center; border: 1px solid\">");
4593: fprintf(ficresphtmfr,"<th>Age</th> ");
1.265 brouard 4594: for(s2=-1; s2 <=nlstate+ndeath; s2++){
1.251 brouard 4595: for(m=-1; m <=nlstate+ndeath; m++){
1.265 brouard 4596: if(s2!=0 && m!=0)
4597: fprintf(ficresphtmfr,"<th>%d%d</th> ",s2,m);
1.240 brouard 4598: }
1.226 brouard 4599: }
1.251 brouard 4600: fprintf(ficresphtmfr, "\n");
4601:
4602: /* For each age */
4603: for(iage=iagemin; iage <= iagemax+3; iage++){
4604: fprintf(ficresphtm,"<tr>");
4605: if(iage==iagemax+1){
4606: fprintf(ficlog,"1");
4607: fprintf(ficresphtmfr,"<tr><th>0</th> ");
4608: }else if(iage==iagemax+2){
4609: fprintf(ficlog,"0");
4610: fprintf(ficresphtmfr,"<tr><th>Unknown</th> ");
4611: }else if(iage==iagemax+3){
4612: fprintf(ficlog,"Total");
4613: fprintf(ficresphtmfr,"<tr><th>Total</th> ");
4614: }else{
1.240 brouard 4615: if(first==1){
1.251 brouard 4616: first=0;
4617: printf("See log file for details...\n");
4618: }
4619: fprintf(ficresphtmfr,"<tr><th>%d</th> ",iage);
4620: fprintf(ficlog,"Age %d", iage);
4621: }
1.265 brouard 4622: for(s1=1; s1 <=nlstate ; s1++){
4623: for(m=-1, pp[s1]=0; m <=nlstate+ndeath ; m++)
4624: pp[s1] += freq[s1][m][iage];
1.251 brouard 4625: }
1.265 brouard 4626: for(s1=1; s1 <=nlstate ; s1++){
1.251 brouard 4627: for(m=-1, pos=0; m <=0 ; m++)
1.265 brouard 4628: pos += freq[s1][m][iage];
4629: if(pp[s1]>=1.e-10){
1.251 brouard 4630: if(first==1){
1.265 brouard 4631: printf(" %d.=%.0f loss[%d]=%.1f%%",s1,pp[s1],s1,100*pos/pp[s1]);
1.251 brouard 4632: }
1.265 brouard 4633: fprintf(ficlog," %d.=%.0f loss[%d]=%.1f%%",s1,pp[s1],s1,100*pos/pp[s1]);
1.251 brouard 4634: }else{
4635: if(first==1)
1.265 brouard 4636: printf(" %d.=%.0f loss[%d]=NaNQ%%",s1,pp[s1],s1);
4637: fprintf(ficlog," %d.=%.0f loss[%d]=NaNQ%%",s1,pp[s1],s1);
1.240 brouard 4638: }
4639: }
4640:
1.265 brouard 4641: for(s1=1; s1 <=nlstate ; s1++){
4642: /* posprop[s1]=0; */
4643: for(m=0, pp[s1]=0; m <=nlstate+ndeath; m++)/* Summing on all ages */
4644: pp[s1] += freq[s1][m][iage];
4645: } /* pp[s1] is the total number of transitions starting from state s1 and any ending status until this age */
4646:
4647: for(s1=1,pos=0, pospropta=0.; s1 <=nlstate ; s1++){
4648: pos += pp[s1]; /* pos is the total number of transitions until this age */
4649: posprop[s1] += prop[s1][iage]; /* prop is the number of transitions from a live state
4650: from s1 at age iage prop[s[m][iind]][(int)agev[m][iind]] += weight[iind] */
4651: pospropta += prop[s1][iage]; /* prop is the number of transitions from a live state
4652: from s1 at age iage prop[s[m][iind]][(int)agev[m][iind]] += weight[iind] */
4653: }
4654:
4655: /* Writing ficresp */
4656: if(cptcoveff==0 && nj==1){ /* no covariate and first pass */
4657: if( iage <= iagemax){
4658: fprintf(ficresp," %d",iage);
4659: }
4660: }else if( nj==2){
4661: if( iage <= iagemax){
4662: fprintf(ficresp," %d",iage);
4663: for (z1=1; z1<=cptcoveff; z1++) fprintf(ficresp, " %d %d",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4664: }
1.240 brouard 4665: }
1.265 brouard 4666: for(s1=1; s1 <=nlstate ; s1++){
1.240 brouard 4667: if(pos>=1.e-5){
1.251 brouard 4668: if(first==1)
1.265 brouard 4669: printf(" %d.=%.0f prev[%d]=%.1f%%",s1,pp[s1],s1,100*pp[s1]/pos);
4670: fprintf(ficlog," %d.=%.0f prev[%d]=%.1f%%",s1,pp[s1],s1,100*pp[s1]/pos);
1.251 brouard 4671: }else{
4672: if(first==1)
1.265 brouard 4673: printf(" %d.=%.0f prev[%d]=NaNQ%%",s1,pp[s1],s1);
4674: fprintf(ficlog," %d.=%.0f prev[%d]=NaNQ%%",s1,pp[s1],s1);
1.251 brouard 4675: }
4676: if( iage <= iagemax){
4677: if(pos>=1.e-5){
1.265 brouard 4678: if(cptcoveff==0 && nj==1){ /* no covariate and first pass */
4679: fprintf(ficresp," %.5f %.0f %.0f",prop[s1][iage]/pospropta, prop[s1][iage],pospropta);
4680: }else if( nj==2){
4681: fprintf(ficresp," %.5f %.0f %.0f",prop[s1][iage]/pospropta, prop[s1][iage],pospropta);
4682: }
4683: fprintf(ficresphtm,"<th>%d</th><td>%.5f</td><td>%.0f</td><td>%.0f</td>",iage,prop[s1][iage]/pospropta, prop[s1][iage],pospropta);
4684: /*probs[iage][s1][j1]= pp[s1]/pos;*/
4685: /*printf("\niage=%d s1=%d j1=%d %.5f %.0f %.0f %f",iage,s1,j1,pp[s1]/pos, pp[s1],pos,probs[iage][s1][j1]);*/
4686: } else{
4687: if((cptcoveff==0 && nj==1)|| nj==2 ) fprintf(ficresp," NaNq %.0f %.0f",prop[s1][iage],pospropta);
4688: fprintf(ficresphtm,"<th>%d</th><td>NaNq</td><td>%.0f</td><td>%.0f</td>",iage, prop[s1][iage],pospropta);
1.251 brouard 4689: }
1.240 brouard 4690: }
1.265 brouard 4691: pospropt[s1] +=posprop[s1];
4692: } /* end loop s1 */
1.251 brouard 4693: /* pospropt=0.; */
1.265 brouard 4694: for(s1=-1; s1 <=nlstate+ndeath; s1++){
1.251 brouard 4695: for(m=-1; m <=nlstate+ndeath; m++){
1.265 brouard 4696: if(freq[s1][m][iage] !=0 ) { /* minimizing output */
1.251 brouard 4697: if(first==1){
1.265 brouard 4698: printf(" %d%d=%.0f",s1,m,freq[s1][m][iage]);
1.251 brouard 4699: }
1.265 brouard 4700: /* printf(" %d%d=%.0f",s1,m,freq[s1][m][iage]); */
4701: fprintf(ficlog," %d%d=%.0f",s1,m,freq[s1][m][iage]);
1.251 brouard 4702: }
1.265 brouard 4703: if(s1!=0 && m!=0)
4704: fprintf(ficresphtmfr,"<td>%.0f</td> ",freq[s1][m][iage]);
1.240 brouard 4705: }
1.265 brouard 4706: } /* end loop s1 */
1.251 brouard 4707: posproptt=0.;
1.265 brouard 4708: for(s1=1; s1 <=nlstate; s1++){
4709: posproptt += pospropt[s1];
1.251 brouard 4710: }
4711: fprintf(ficresphtmfr,"</tr>\n ");
1.265 brouard 4712: fprintf(ficresphtm,"</tr>\n");
4713: if((cptcoveff==0 && nj==1)|| nj==2 ) {
4714: if(iage <= iagemax)
4715: fprintf(ficresp,"\n");
1.240 brouard 4716: }
1.251 brouard 4717: if(first==1)
4718: printf("Others in log...\n");
4719: fprintf(ficlog,"\n");
4720: } /* end loop age iage */
1.265 brouard 4721:
1.251 brouard 4722: fprintf(ficresphtm,"<tr><th>Tot</th>");
1.265 brouard 4723: for(s1=1; s1 <=nlstate ; s1++){
1.251 brouard 4724: if(posproptt < 1.e-5){
1.265 brouard 4725: fprintf(ficresphtm,"<td>Nanq</td><td>%.0f</td><td>%.0f</td>",pospropt[s1],posproptt);
1.251 brouard 4726: }else{
1.265 brouard 4727: fprintf(ficresphtm,"<td>%.5f</td><td>%.0f</td><td>%.0f</td>",pospropt[s1]/posproptt,pospropt[s1],posproptt);
1.240 brouard 4728: }
1.226 brouard 4729: }
1.251 brouard 4730: fprintf(ficresphtm,"</tr>\n");
4731: fprintf(ficresphtm,"</table>\n");
4732: fprintf(ficresphtmfr,"</table>\n");
1.226 brouard 4733: if(posproptt < 1.e-5){
1.251 brouard 4734: fprintf(ficresphtm,"\n <p><b> This combination (%d) is not valid and no result will be produced</b></p>",j1);
4735: fprintf(ficresphtmfr,"\n <p><b> This combination (%d) is not valid and no result will be produced</b></p>",j1);
1.260 brouard 4736: fprintf(ficlog,"# This combination (%d) is not valid and no result will be produced\n",j1);
4737: printf("# This combination (%d) is not valid and no result will be produced\n",j1);
1.251 brouard 4738: invalidvarcomb[j1]=1;
1.226 brouard 4739: }else{
1.251 brouard 4740: fprintf(ficresphtm,"\n <p> This combination (%d) is valid and result will be produced.</p>",j1);
4741: invalidvarcomb[j1]=0;
1.226 brouard 4742: }
1.251 brouard 4743: fprintf(ficresphtmfr,"</table>\n");
4744: fprintf(ficlog,"\n");
4745: if(j!=0){
4746: printf("#Freqsummary: Starting values for combination j1=%d:\n", j1);
1.265 brouard 4747: for(i=1,s1=1; i <=nlstate; i++){
1.251 brouard 4748: for(k=1; k <=(nlstate+ndeath); k++){
4749: if (k != i) {
1.265 brouard 4750: for(jj=1; jj <=ncovmodel; jj++){ /* For counting s1 */
1.253 brouard 4751: if(jj==1){ /* Constant case (in fact cste + age) */
1.251 brouard 4752: if(j1==1){ /* All dummy covariates to zero */
4753: freq[i][k][iagemax+4]=freq[i][k][iagemax+3]; /* Stores case 0 0 0 */
4754: freq[i][i][iagemax+4]=freq[i][i][iagemax+3]; /* Stores case 0 0 0 */
1.252 brouard 4755: printf("%d%d ",i,k);
4756: fprintf(ficlog,"%d%d ",i,k);
1.265 brouard 4757: printf("%12.7f ln(%.0f/%.0f)= %f, OR=%f sd=%f \n",p[s1],freq[i][k][iagemax+3],freq[i][i][iagemax+3], log(freq[i][k][iagemax+3]/freq[i][i][iagemax+3]),freq[i][k][iagemax+3]/freq[i][i][iagemax+3], sqrt(1/freq[i][k][iagemax+3]+1/freq[i][i][iagemax+3]));
4758: fprintf(ficlog,"%12.7f ln(%.0f/%.0f)= %12.7f \n",p[s1],freq[i][k][iagemax+3],freq[i][i][iagemax+3], log(freq[i][k][iagemax+3]/freq[i][i][iagemax+3]));
4759: pstart[s1]= log(freq[i][k][iagemax+3]/freq[i][i][iagemax+3]);
1.251 brouard 4760: }
1.253 brouard 4761: }else if((j1==1) && (jj==2 || nagesqr==1)){ /* age or age*age parameter without covariate V4*age (to be done later) */
4762: for(iage=iagemin; iage <= iagemax+3; iage++){
4763: x[iage]= (double)iage;
4764: y[iage]= log(freq[i][k][iage]/freq[i][i][iage]);
1.265 brouard 4765: /* printf("i=%d, k=%d, s1=%d, j1=%d, jj=%d, y[%d]=%f\n",i,k,s1,j1,jj, iage, y[iage]); */
1.253 brouard 4766: }
1.268 brouard 4767: /* Some are not finite, but linreg will ignore these ages */
4768: no=0;
1.253 brouard 4769: linreg(iagemin,iagemax,&no,x,y,&a,&b,&r, &sa, &sb ); /* y= a+b*x with standard errors */
1.265 brouard 4770: pstart[s1]=b;
4771: pstart[s1-1]=a;
1.252 brouard 4772: }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 */
4773: 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]);
4774: printf("j1=%d, jj=%d, (log(j1-1.)/log(2.))+1=%f, TvarsDind[(int)(log(j1-1.)/log(2.))+1]=%d\n",j1, jj,(log(j1-1.)/log(2.))+1,TvarsDind[(int)(log(j1-1.)/log(2.))+1]);
1.265 brouard 4775: pstart[s1]= log((freq[i][k][iagemax+3]/freq[i][i][iagemax+3])/(freq[i][k][iagemax+4]/freq[i][i][iagemax+4]));
1.252 brouard 4776: printf("%d%d ",i,k);
4777: fprintf(ficlog,"%d%d ",i,k);
1.265 brouard 4778: printf("s1=%d,i=%d,k=%d,p[%d]=%12.7f ln((%.0f/%.0f)/(%.0f/%.0f))= %f, OR=%f sd=%f \n",s1,i,k,s1,p[s1],freq[i][k][iagemax+3],freq[i][i][iagemax+3],freq[i][k][iagemax+4],freq[i][i][iagemax+4], log((freq[i][k][iagemax+3]/freq[i][i][iagemax+3])/(freq[i][k][iagemax+4]/freq[i][i][iagemax+4])),(freq[i][k][iagemax+3]/freq[i][i][iagemax+3])/(freq[i][k][iagemax+4]/freq[i][i][iagemax+4]), sqrt(1/freq[i][k][iagemax+3]+1/freq[i][i][iagemax+3]+1/freq[i][k][iagemax+4]+1/freq[i][i][iagemax+4]));
1.251 brouard 4779: }else{ /* Other cases, like quantitative fixed or varying covariates */
4780: ;
4781: }
4782: /* printf("%12.7f )", param[i][jj][k]); */
4783: /* fprintf(ficlog,"%12.7f )", param[i][jj][k]); */
1.265 brouard 4784: s1++;
1.251 brouard 4785: } /* end jj */
4786: } /* end k!= i */
4787: } /* end k */
1.265 brouard 4788: } /* end i, s1 */
1.251 brouard 4789: } /* end j !=0 */
4790: } /* end selected combination of covariate j1 */
4791: if(j==0){ /* We can estimate starting values from the occurences in each case */
4792: printf("#Freqsummary: Starting values for the constants:\n");
4793: fprintf(ficlog,"\n");
1.265 brouard 4794: for(i=1,s1=1; i <=nlstate; i++){
1.251 brouard 4795: for(k=1; k <=(nlstate+ndeath); k++){
4796: if (k != i) {
4797: printf("%d%d ",i,k);
4798: fprintf(ficlog,"%d%d ",i,k);
4799: for(jj=1; jj <=ncovmodel; jj++){
1.265 brouard 4800: pstart[s1]=p[s1]; /* Setting pstart to p values by default */
1.253 brouard 4801: if(jj==1){ /* Age has to be done */
1.265 brouard 4802: pstart[s1]= log(freq[i][k][iagemax+3]/freq[i][i][iagemax+3]);
4803: printf("%12.7f ln(%.0f/%.0f)= %12.7f ",p[s1],freq[i][k][iagemax+3],freq[i][i][iagemax+3], log(freq[i][k][iagemax+3]/freq[i][i][iagemax+3]));
4804: fprintf(ficlog,"%12.7f ln(%.0f/%.0f)= %12.7f ",p[s1],freq[i][k][iagemax+3],freq[i][i][iagemax+3], log(freq[i][k][iagemax+3]/freq[i][i][iagemax+3]));
1.251 brouard 4805: }
4806: /* printf("%12.7f )", param[i][jj][k]); */
4807: /* fprintf(ficlog,"%12.7f )", param[i][jj][k]); */
1.265 brouard 4808: s1++;
1.250 brouard 4809: }
1.251 brouard 4810: printf("\n");
4811: fprintf(ficlog,"\n");
1.250 brouard 4812: }
4813: }
4814: }
1.251 brouard 4815: printf("#Freqsummary\n");
4816: fprintf(ficlog,"\n");
1.265 brouard 4817: for(s1=-1; s1 <=nlstate+ndeath; s1++){
4818: for(s2=-1; s2 <=nlstate+ndeath; s2++){
4819: /* param[i]|j][k]= freq[s1][s2][iagemax+3] */
4820: printf(" %d%d=%.0f",s1,s2,freq[s1][s2][iagemax+3]);
4821: fprintf(ficlog," %d%d=%.0f",s1,s2,freq[s1][s2][iagemax+3]);
4822: /* if(freq[s1][s2][iage] !=0 ) { /\* minimizing output *\/ */
4823: /* printf(" %d%d=%.0f",s1,s2,freq[s1][s2][iagemax+3]); */
4824: /* fprintf(ficlog," %d%d=%.0f",s1,s2,freq[s1][s2][iagemax+3]); */
1.251 brouard 4825: /* } */
4826: }
1.265 brouard 4827: } /* end loop s1 */
1.251 brouard 4828:
4829: printf("\n");
4830: fprintf(ficlog,"\n");
4831: } /* end j=0 */
1.249 brouard 4832: } /* end j */
1.252 brouard 4833:
1.253 brouard 4834: if(mle == -2){ /* We want to use these values as starting values */
1.252 brouard 4835: for(i=1, jk=1; i <=nlstate; i++){
4836: for(j=1; j <=nlstate+ndeath; j++){
4837: if(j!=i){
4838: /*ca[0]= k+'a'-1;ca[1]='\0';*/
4839: printf("%1d%1d",i,j);
4840: fprintf(ficparo,"%1d%1d",i,j);
4841: for(k=1; k<=ncovmodel;k++){
4842: /* printf(" %lf",param[i][j][k]); */
4843: /* fprintf(ficparo," %lf",param[i][j][k]); */
4844: p[jk]=pstart[jk];
4845: printf(" %f ",pstart[jk]);
4846: fprintf(ficparo," %f ",pstart[jk]);
4847: jk++;
4848: }
4849: printf("\n");
4850: fprintf(ficparo,"\n");
4851: }
4852: }
4853: }
4854: } /* end mle=-2 */
1.226 brouard 4855: dateintmean=dateintsum/k2cpt;
1.240 brouard 4856:
1.226 brouard 4857: fclose(ficresp);
4858: fclose(ficresphtm);
4859: fclose(ficresphtmfr);
4860: free_vector(meanq,1,nqfveff);
4861: free_matrix(meanqt,1,lastpass,1,nqtveff);
1.253 brouard 4862: free_vector(x, iagemin-AGEMARGE, iagemax+4+AGEMARGE);
4863: free_vector(y, iagemin-AGEMARGE, iagemax+4+AGEMARGE);
1.251 brouard 4864: free_ma3x(freq,-5,nlstate+ndeath,-5,nlstate+ndeath, iagemin-AGEMARGE, iagemax+4+AGEMARGE);
1.226 brouard 4865: free_vector(pospropt,1,nlstate);
4866: free_vector(posprop,1,nlstate);
1.251 brouard 4867: free_matrix(prop,1,nlstate,iagemin-AGEMARGE, iagemax+4+AGEMARGE);
1.226 brouard 4868: free_vector(pp,1,nlstate);
4869: /* End of freqsummary */
4870: }
1.126 brouard 4871:
1.268 brouard 4872: /* Simple linear regression */
4873: int linreg(int ifi, int ila, int *no, const double x[], const double y[], double* a, double* b, double* r, double* sa, double * sb) {
4874:
4875: /* y=a+bx regression */
4876: double sumx = 0.0; /* sum of x */
4877: double sumx2 = 0.0; /* sum of x**2 */
4878: double sumxy = 0.0; /* sum of x * y */
4879: double sumy = 0.0; /* sum of y */
4880: double sumy2 = 0.0; /* sum of y**2 */
4881: double sume2 = 0.0; /* sum of square or residuals */
4882: double yhat;
4883:
4884: double denom=0;
4885: int i;
4886: int ne=*no;
4887:
4888: for ( i=ifi, ne=0;i<=ila;i++) {
4889: if(!isfinite(x[i]) || !isfinite(y[i])){
4890: /* printf(" x[%d]=%f, y[%d]=%f\n",i,x[i],i,y[i]); */
4891: continue;
4892: }
4893: ne=ne+1;
4894: sumx += x[i];
4895: sumx2 += x[i]*x[i];
4896: sumxy += x[i] * y[i];
4897: sumy += y[i];
4898: sumy2 += y[i]*y[i];
4899: denom = (ne * sumx2 - sumx*sumx);
4900: /* 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); */
4901: }
4902:
4903: denom = (ne * sumx2 - sumx*sumx);
4904: if (denom == 0) {
4905: // vertical, slope m is infinity
4906: *b = INFINITY;
4907: *a = 0;
4908: if (r) *r = 0;
4909: return 1;
4910: }
4911:
4912: *b = (ne * sumxy - sumx * sumy) / denom;
4913: *a = (sumy * sumx2 - sumx * sumxy) / denom;
4914: if (r!=NULL) {
4915: *r = (sumxy - sumx * sumy / ne) / /* compute correlation coeff */
4916: sqrt((sumx2 - sumx*sumx/ne) *
4917: (sumy2 - sumy*sumy/ne));
4918: }
4919: *no=ne;
4920: for ( i=ifi, ne=0;i<=ila;i++) {
4921: if(!isfinite(x[i]) || !isfinite(y[i])){
4922: /* printf(" x[%d]=%f, y[%d]=%f\n",i,x[i],i,y[i]); */
4923: continue;
4924: }
4925: ne=ne+1;
4926: yhat = y[i] - *a -*b* x[i];
4927: sume2 += yhat * yhat ;
4928:
4929: denom = (ne * sumx2 - sumx*sumx);
4930: /* 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); */
4931: }
4932: *sb = sqrt(sume2/(double)(ne-2)/(sumx2 - sumx * sumx /(double)ne));
4933: *sa= *sb * sqrt(sumx2/ne);
4934:
4935: return 0;
4936: }
4937:
1.126 brouard 4938: /************ Prevalence ********************/
1.227 brouard 4939: 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)
4940: {
4941: /* Compute observed prevalence between dateprev1 and dateprev2 by counting the number of people
4942: in each health status at the date of interview (if between dateprev1 and dateprev2).
4943: We still use firstpass and lastpass as another selection.
4944: */
1.126 brouard 4945:
1.227 brouard 4946: int i, m, jk, j1, bool, z1,j, iv;
4947: int mi; /* Effective wave */
4948: int iage;
4949: double agebegin, ageend;
4950:
4951: double **prop;
4952: double posprop;
4953: double y2; /* in fractional years */
4954: int iagemin, iagemax;
4955: int first; /** to stop verbosity which is redirected to log file */
4956:
4957: iagemin= (int) agemin;
4958: iagemax= (int) agemax;
4959: /*pp=vector(1,nlstate);*/
1.251 brouard 4960: prop=matrix(1,nlstate,iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.227 brouard 4961: /* freq=ma3x(-1,nlstate+ndeath,-1,nlstate+ndeath,iagemin,iagemax+3);*/
4962: j1=0;
1.222 brouard 4963:
1.227 brouard 4964: /*j=cptcoveff;*/
4965: if (cptcovn<1) {j=1;ncodemax[1]=1;}
1.222 brouard 4966:
1.227 brouard 4967: first=1;
4968: for(j1=1; j1<= (int) pow(2,cptcoveff);j1++){ /* For each combination of covariate */
4969: for (i=1; i<=nlstate; i++)
1.251 brouard 4970: for(iage=iagemin-AGEMARGE; iage <= iagemax+4+AGEMARGE; iage++)
1.227 brouard 4971: prop[i][iage]=0.0;
4972: printf("Prevalence combination of varying and fixed dummies %d\n",j1);
4973: /* fprintf(ficlog," V%d=%d ",Tvaraff[j1],nbcode[Tvaraff[j1]][codtabm(k,j1)]); */
4974: fprintf(ficlog,"Prevalence combination of varying and fixed dummies %d\n",j1);
4975:
4976: for (i=1; i<=imx; i++) { /* Each individual */
4977: bool=1;
4978: /* for(m=firstpass; m<=lastpass; m++){/\* Other selection (we can limit to certain interviews*\/ */
4979: for(mi=1; mi<wav[i];mi++){ /* For this wave too look where individual can be counted V4=0 V3=0 */
4980: m=mw[mi][i];
4981: /* Tmodelind[z1]=k is the position of the varying covariate in the model, but which # within 1 to ntv? */
4982: /* Tvar[Tmodelind[z1]] is the n of Vn; n-ncovcol-nqv is the first time varying covariate or iv */
4983: for (z1=1; z1<=cptcoveff; z1++){
4984: if( Fixed[Tmodelind[z1]]==1){
4985: iv= Tvar[Tmodelind[z1]]-ncovcol-nqv;
4986: if (cotvar[m][iv][i]!= nbcode[Tvaraff[z1]][codtabm(j1,z1)]) /* iv=1 to ntv, right modality */
4987: bool=0;
4988: }else if( Fixed[Tmodelind[z1]]== 0) /* fixed */
4989: if (covar[Tvaraff[z1]][i]!= nbcode[Tvaraff[z1]][codtabm(j1,z1)]) {
4990: bool=0;
4991: }
4992: }
4993: if(bool==1){ /* Otherwise we skip that wave/person */
4994: agebegin=agev[m][i]; /* Age at beginning of wave before transition*/
4995: /* ageend=agev[m][i]+(dh[m][i])*stepm/YEARM; /\* Age at end of wave and transition *\/ */
4996: if(m >=firstpass && m <=lastpass){
4997: y2=anint[m][i]+(mint[m][i]/12.); /* Fractional date in year */
4998: if ((y2>=dateprev1) && (y2<=dateprev2)) { /* Here is the main selection (fractional years) */
4999: if(agev[m][i]==0) agev[m][i]=iagemax+1;
5000: if(agev[m][i]==1) agev[m][i]=iagemax+2;
1.251 brouard 5001: if((int)agev[m][i] <iagemin-AGEMARGE || (int)agev[m][i] >iagemax+4+AGEMARGE){
1.227 brouard 5002: 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);
5003: exit(1);
5004: }
5005: if (s[m][i]>0 && s[m][i]<=nlstate) {
5006: /*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]]);*/
5007: prop[s[m][i]][(int)agev[m][i]] += weight[i];/* At age of beginning of transition, where status is known */
5008: prop[s[m][i]][iagemax+3] += weight[i];
5009: } /* end valid statuses */
5010: } /* end selection of dates */
5011: } /* end selection of waves */
5012: } /* end bool */
5013: } /* end wave */
5014: } /* end individual */
5015: for(i=iagemin; i <= iagemax+3; i++){
5016: for(jk=1,posprop=0; jk <=nlstate ; jk++) {
5017: posprop += prop[jk][i];
5018: }
5019:
5020: for(jk=1; jk <=nlstate ; jk++){
5021: if( i <= iagemax){
5022: if(posprop>=1.e-5){
5023: probs[i][jk][j1]= prop[jk][i]/posprop;
5024: } else{
5025: if(first==1){
5026: first=0;
1.266 brouard 5027: printf("Warning Observed prevalence doesn't sum to 1 for state %d: probs[%d][%d][%d]=%lf because of lack of cases\nSee others in log file...\n",jk,i,jk, j1,probs[i][jk][j1]);
5028: fprintf(ficlog,"Warning Observed prevalence doesn't sum to 1 for state %d: probs[%d][%d][%d]=%lf because of lack of cases\nSee others in log file...\n",jk,i,jk, j1,probs[i][jk][j1]);
5029: }else{
5030: fprintf(ficlog,"Warning Observed prevalence doesn't sum to 1 for state %d: probs[%d][%d][%d]=%lf because of lack of cases\nSee others in log file...\n",jk,i,jk, j1,probs[i][jk][j1]);
1.227 brouard 5031: }
5032: }
5033: }
5034: }/* end jk */
5035: }/* end i */
1.222 brouard 5036: /*} *//* end i1 */
1.227 brouard 5037: } /* end j1 */
1.222 brouard 5038:
1.227 brouard 5039: /* free_ma3x(freq,-1,nlstate+ndeath,-1,nlstate+ndeath, iagemin, iagemax+3);*/
5040: /*free_vector(pp,1,nlstate);*/
1.251 brouard 5041: free_matrix(prop,1,nlstate, iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.227 brouard 5042: } /* End of prevalence */
1.126 brouard 5043:
5044: /************* Waves Concatenation ***************/
5045:
5046: 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)
5047: {
5048: /* Concatenates waves: wav[i] is the number of effective (useful waves) of individual i.
5049: Death is a valid wave (if date is known).
5050: mw[mi][i] is the mi (mi=1 to wav[i]) effective wave of individual i
5051: dh[m][i] or dh[mw[mi][i]][i] is the delay between two effective waves m=mw[mi][i]
5052: and mw[mi+1][i]. dh depends on stepm.
1.227 brouard 5053: */
1.126 brouard 5054:
1.224 brouard 5055: int i=0, mi=0, m=0, mli=0;
1.126 brouard 5056: /* int j, k=0,jk, ju, jl,jmin=1e+5, jmax=-1;
5057: double sum=0., jmean=0.;*/
1.224 brouard 5058: int first=0, firstwo=0, firsthree=0, firstfour=0, firstfiv=0;
1.126 brouard 5059: int j, k=0,jk, ju, jl;
5060: double sum=0.;
5061: first=0;
1.214 brouard 5062: firstwo=0;
1.217 brouard 5063: firsthree=0;
1.218 brouard 5064: firstfour=0;
1.164 brouard 5065: jmin=100000;
1.126 brouard 5066: jmax=-1;
5067: jmean=0.;
1.224 brouard 5068:
5069: /* Treating live states */
1.214 brouard 5070: for(i=1; i<=imx; i++){ /* For simple cases and if state is death */
1.224 brouard 5071: mi=0; /* First valid wave */
1.227 brouard 5072: mli=0; /* Last valid wave */
1.126 brouard 5073: m=firstpass;
1.214 brouard 5074: while(s[m][i] <= nlstate){ /* a live state */
1.227 brouard 5075: 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 */
5076: mli=m-1;/* mw[++mi][i]=m-1; */
5077: }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 */
5078: mw[++mi][i]=m;
5079: mli=m;
1.224 brouard 5080: } /* else might be a useless wave -1 and mi is not incremented and mw[mi] not updated */
5081: if(m < lastpass){ /* m < lastpass, standard case */
1.227 brouard 5082: m++; /* mi gives the "effective" current wave, m the current wave, go to next wave by incrementing m */
1.216 brouard 5083: }
1.227 brouard 5084: else{ /* m >= lastpass, eventual special issue with warning */
1.224 brouard 5085: #ifdef UNKNOWNSTATUSNOTCONTRIBUTING
1.227 brouard 5086: break;
1.224 brouard 5087: #else
1.227 brouard 5088: if(s[m][i]==-1 && (int) andc[i] == 9999 && (int)anint[m][i] != 9999){
5089: if(firsthree == 0){
1.262 brouard 5090: 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 5091: firsthree=1;
5092: }
1.262 brouard 5093: 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 5094: mw[++mi][i]=m;
5095: mli=m;
5096: }
5097: if(s[m][i]==-2){ /* Vital status is really unknown */
5098: nbwarn++;
5099: if((int)anint[m][i] == 9999){ /* Has the vital status really been verified? */
5100: 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);
5101: 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);
5102: }
5103: break;
5104: }
5105: break;
1.224 brouard 5106: #endif
1.227 brouard 5107: }/* End m >= lastpass */
1.126 brouard 5108: }/* end while */
1.224 brouard 5109:
1.227 brouard 5110: /* 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 5111: /* After last pass */
1.224 brouard 5112: /* Treating death states */
1.214 brouard 5113: if (s[m][i] > nlstate){ /* In a death state */
1.227 brouard 5114: /* if( mint[m][i]==mdc[m][i] && anint[m][i]==andc[m][i]){ /\* same date of death and date of interview *\/ */
5115: /* } */
1.126 brouard 5116: mi++; /* Death is another wave */
5117: /* if(mi==0) never been interviewed correctly before death */
1.227 brouard 5118: /* Only death is a correct wave */
1.126 brouard 5119: mw[mi][i]=m;
1.257 brouard 5120: } /* else not in a death state */
1.224 brouard 5121: #ifndef DISPATCHINGKNOWNDEATHAFTERLASTWAVE
1.257 brouard 5122: else if ((int) andc[i] != 9999) { /* Date of death is known */
1.218 brouard 5123: if ((int)anint[m][i]!= 9999) { /* date of last interview is known */
1.227 brouard 5124: 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 */
5125: nbwarn++;
5126: if(firstfiv==0){
5127: 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 );
5128: firstfiv=1;
5129: }else{
5130: 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 );
5131: }
5132: }else{ /* Death occured afer last wave potential bias */
5133: nberr++;
5134: if(firstwo==0){
1.257 brouard 5135: 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 5136: firstwo=1;
5137: }
1.257 brouard 5138: 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 5139: }
1.257 brouard 5140: }else{ /* if date of interview is unknown */
1.227 brouard 5141: /* death is known but not confirmed by death status at any wave */
5142: if(firstfour==0){
5143: 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 );
5144: firstfour=1;
5145: }
5146: 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 5147: }
1.224 brouard 5148: } /* end if date of death is known */
5149: #endif
5150: wav[i]=mi; /* mi should be the last effective wave (or mli) */
5151: /* wav[i]=mw[mi][i]; */
1.126 brouard 5152: if(mi==0){
5153: nbwarn++;
5154: if(first==0){
1.227 brouard 5155: printf("Warning! No valid information for individual %ld line=%d (skipped) and may be others, see log file\n",num[i],i);
5156: first=1;
1.126 brouard 5157: }
5158: if(first==1){
1.227 brouard 5159: fprintf(ficlog,"Warning! No valid information for individual %ld line=%d (skipped)\n",num[i],i);
1.126 brouard 5160: }
5161: } /* end mi==0 */
5162: } /* End individuals */
1.214 brouard 5163: /* wav and mw are no more changed */
1.223 brouard 5164:
1.214 brouard 5165:
1.126 brouard 5166: for(i=1; i<=imx; i++){
5167: for(mi=1; mi<wav[i];mi++){
5168: if (stepm <=0)
1.227 brouard 5169: dh[mi][i]=1;
1.126 brouard 5170: else{
1.260 brouard 5171: if (s[mw[mi+1][i]][i] > nlstate) { /* A death, but what if date is unknown? */
1.227 brouard 5172: if (agedc[i] < 2*AGESUP) {
5173: j= rint(agedc[i]*12-agev[mw[mi][i]][i]*12);
5174: if(j==0) j=1; /* Survives at least one month after exam */
5175: else if(j<0){
5176: nberr++;
5177: 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]);
5178: j=1; /* Temporary Dangerous patch */
5179: 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);
5180: 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]);
5181: 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);
5182: }
5183: k=k+1;
5184: if (j >= jmax){
5185: jmax=j;
5186: ijmax=i;
5187: }
5188: if (j <= jmin){
5189: jmin=j;
5190: ijmin=i;
5191: }
5192: sum=sum+j;
5193: /*if (j<0) printf("j=%d num=%d \n",j,i);*/
5194: /* printf("%d %d %d %d\n", s[mw[mi][i]][i] ,s[mw[mi+1][i]][i],j,i);*/
5195: }
5196: }
5197: else{
5198: j= rint( (agev[mw[mi+1][i]][i]*12 - agev[mw[mi][i]][i]*12));
1.126 brouard 5199: /* 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 5200:
1.227 brouard 5201: k=k+1;
5202: if (j >= jmax) {
5203: jmax=j;
5204: ijmax=i;
5205: }
5206: else if (j <= jmin){
5207: jmin=j;
5208: ijmin=i;
5209: }
5210: /* if (j<10) printf("j=%d jmin=%d num=%d ",j,jmin,i); */
5211: /*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]);*/
5212: if(j<0){
5213: nberr++;
5214: 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]);
5215: 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]);
5216: }
5217: sum=sum+j;
5218: }
5219: jk= j/stepm;
5220: jl= j -jk*stepm;
5221: ju= j -(jk+1)*stepm;
5222: if(mle <=1){ /* only if we use a the linear-interpoloation pseudo-likelihood */
5223: if(jl==0){
5224: dh[mi][i]=jk;
5225: bh[mi][i]=0;
5226: }else{ /* We want a negative bias in order to only have interpolation ie
5227: * to avoid the price of an extra matrix product in likelihood */
5228: dh[mi][i]=jk+1;
5229: bh[mi][i]=ju;
5230: }
5231: }else{
5232: if(jl <= -ju){
5233: dh[mi][i]=jk;
5234: bh[mi][i]=jl; /* bias is positive if real duration
5235: * is higher than the multiple of stepm and negative otherwise.
5236: */
5237: }
5238: else{
5239: dh[mi][i]=jk+1;
5240: bh[mi][i]=ju;
5241: }
5242: if(dh[mi][i]==0){
5243: dh[mi][i]=1; /* At least one step */
5244: bh[mi][i]=ju; /* At least one step */
5245: /* 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);*/
5246: }
5247: } /* end if mle */
1.126 brouard 5248: }
5249: } /* end wave */
5250: }
5251: jmean=sum/k;
5252: 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 5253: 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 5254: }
1.126 brouard 5255:
5256: /*********** Tricode ****************************/
1.220 brouard 5257: void tricode(int *cptcov, int *Tvar, int **nbcode, int imx, int *Ndum)
1.242 brouard 5258: {
5259: /**< Uses cptcovn+2*cptcovprod as the number of covariates */
5260: /* Tvar[i]=atoi(stre); find 'n' in Vn and stores in Tvar. If model=V2+V1 Tvar[1]=2 and Tvar[2]=1
5261: * Boring subroutine which should only output nbcode[Tvar[j]][k]
5262: * Tvar[5] in V2+V1+V3*age+V2*V4 is 4 (V4) even it is a time varying or quantitative variable
5263: * nbcode[Tvar[5]][1]= nbcode[4][1]=0, nbcode[4][2]=1 (usually);
5264: */
1.130 brouard 5265:
1.242 brouard 5266: int ij=1, k=0, j=0, i=0, maxncov=NCOVMAX;
5267: int modmaxcovj=0; /* Modality max of covariates j */
5268: int cptcode=0; /* Modality max of covariates j */
5269: int modmincovj=0; /* Modality min of covariates j */
1.145 brouard 5270:
5271:
1.242 brouard 5272: /* cptcoveff=0; */
5273: /* *cptcov=0; */
1.126 brouard 5274:
1.242 brouard 5275: for (k=1; k <= maxncov; k++) ncodemax[k]=0; /* Horrible constant again replaced by NCOVMAX */
1.126 brouard 5276:
1.242 brouard 5277: /* Loop on covariates without age and products and no quantitative variable */
5278: /* for (j=1; j<=(cptcovs); j++) { /\* From model V1 + V2*age+ V3 + V3*V4 keeps V1 + V3 = 2 only *\/ */
5279: for (k=1; k<=cptcovt; k++) { /* From model V1 + V2*age + V3 + V3*V4 keeps V1 + V3 = 2 only */
5280: for (j=-1; (j < maxncov); j++) Ndum[j]=0;
5281: if(Dummy[k]==0 && Typevar[k] !=1){ /* Dummy covariate and not age product */
5282: switch(Fixed[k]) {
5283: case 0: /* Testing on fixed dummy covariate, simple or product of fixed */
5284: 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*/
5285: ij=(int)(covar[Tvar[k]][i]);
5286: /* ij=0 or 1 or -1. Value of the covariate Tvar[j] for individual i
5287: * If product of Vn*Vm, still boolean *:
5288: * If it was coded 1, 2, 3, 4 should be splitted into 3 boolean variables
5289: * 1 => 0 0 0, 2 => 0 0 1, 3 => 0 1 1, 4=1 0 0 */
5290: /* Finds for covariate j, n=Tvar[j] of Vn . ij is the
5291: modality of the nth covariate of individual i. */
5292: if (ij > modmaxcovj)
5293: modmaxcovj=ij;
5294: else if (ij < modmincovj)
5295: modmincovj=ij;
5296: if ((ij < -1) && (ij > NCOVMAX)){
5297: printf( "Error: minimal is less than -1 or maximal is bigger than %d. Exiting. \n", NCOVMAX );
5298: exit(1);
5299: }else
5300: Ndum[ij]++; /*counts and stores the occurence of this modality 0, 1, -1*/
5301: /* If coded 1, 2, 3 , counts the number of 1 Ndum[1], number of 2, Ndum[2], etc */
5302: /*printf("i=%d ij=%d Ndum[ij]=%d imx=%d",i,ij,Ndum[ij],imx);*/
5303: /* getting the maximum value of the modality of the covariate
5304: (should be 0 or 1 now) Tvar[j]. If V=sex and male is coded 0 and
5305: female ies 1, then modmaxcovj=1.
5306: */
5307: } /* end for loop on individuals i */
5308: printf(" Minimal and maximal values of %d th (fixed) covariate V%d: min=%d max=%d \n", k, Tvar[k], modmincovj, modmaxcovj);
5309: fprintf(ficlog," Minimal and maximal values of %d th (fixed) covariate V%d: min=%d max=%d \n", k, Tvar[k], modmincovj, modmaxcovj);
5310: cptcode=modmaxcovj;
5311: /* Ndum[0] = frequency of 0 for model-covariate j, Ndum[1] frequency of 1 etc. */
5312: /*for (i=0; i<=cptcode; i++) {*/
5313: for (j=modmincovj; j<=modmaxcovj; j++) { /* j=-1 ? 0 and 1*//* For each value j of the modality of model-cov k */
5314: printf("Frequencies of (fixed) covariate %d ie V%d with value %d: %d\n", k, Tvar[k], j, Ndum[j]);
5315: fprintf(ficlog, "Frequencies of (fixed) covariate %d ie V%d with value %d: %d\n", k, Tvar[k], j, Ndum[j]);
5316: if( Ndum[j] != 0 ){ /* Counts if nobody answered modality j ie empty modality, we skip it and reorder */
5317: if( j != -1){
5318: ncodemax[k]++; /* ncodemax[k]= Number of modalities of the k th
5319: covariate for which somebody answered excluding
5320: undefined. Usually 2: 0 and 1. */
5321: }
5322: ncodemaxwundef[k]++; /* ncodemax[j]= Number of modalities of the k th
5323: covariate for which somebody answered including
5324: undefined. Usually 3: -1, 0 and 1. */
5325: } /* In fact ncodemax[k]=2 (dichotom. variables only) but it could be more for
5326: * historical reasons: 3 if coded 1, 2, 3 and 4 and Ndum[2]=0 */
5327: } /* Ndum[-1] number of undefined modalities */
1.231 brouard 5328:
1.242 brouard 5329: /* j is a covariate, n=Tvar[j] of Vn; Fills nbcode */
5330: /* For covariate j, modalities could be 1, 2, 3, 4, 5, 6, 7. */
5331: /* If Ndum[1]=0, Ndum[2]=0, Ndum[3]= 635, Ndum[4]=0, Ndum[5]=0, Ndum[6]=27, Ndum[7]=125; */
5332: /* modmincovj=3; modmaxcovj = 7; */
5333: /* There are only 3 modalities non empty 3, 6, 7 (or 2 if 27 is too few) : ncodemax[j]=3; */
5334: /* which will be coded 0, 1, 2 which in binary on 2=3-1 digits are 0=00 1=01, 2=10; */
5335: /* defining two dummy variables: variables V1_1 and V1_2.*/
5336: /* nbcode[Tvar[j]][ij]=k; */
5337: /* nbcode[Tvar[j]][1]=0; */
5338: /* nbcode[Tvar[j]][2]=1; */
5339: /* nbcode[Tvar[j]][3]=2; */
5340: /* To be continued (not working yet). */
5341: ij=0; /* ij is similar to i but can jump over null modalities */
5342: 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*/
5343: if (Ndum[i] == 0) { /* If nobody responded to this modality k */
5344: break;
5345: }
5346: ij++;
5347: 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*/
5348: cptcode = ij; /* New max modality for covar j */
5349: } /* end of loop on modality i=-1 to 1 or more */
5350: break;
5351: case 1: /* Testing on varying covariate, could be simple and
5352: * should look at waves or product of fixed *
5353: * varying. No time to test -1, assuming 0 and 1 only */
5354: ij=0;
5355: for(i=0; i<=1;i++){
5356: nbcode[Tvar[k]][++ij]=i;
5357: }
5358: break;
5359: default:
5360: break;
5361: } /* end switch */
5362: } /* end dummy test */
5363:
5364: /* for (k=0; k<= cptcode; k++) { /\* k=-1 ? k=0 to 1 *\//\* Could be 1 to 4 *\//\* cptcode=modmaxcovj *\/ */
5365: /* /\*recode from 0 *\/ */
5366: /* k is a modality. If we have model=V1+V1*sex */
5367: /* then: nbcode[1][1]=0 ; nbcode[1][2]=1; nbcode[2][1]=0 ; nbcode[2][2]=1; */
5368: /* But if some modality were not used, it is recoded from 0 to a newer modmaxcovj=cptcode *\/ */
5369: /* } */
5370: /* /\* cptcode = ij; *\/ /\* New max modality for covar j *\/ */
5371: /* if (ij > ncodemax[j]) { */
5372: /* printf( " Error ij=%d > ncodemax[%d]=%d\n", ij, j, ncodemax[j]); */
5373: /* fprintf(ficlog, " Error ij=%d > ncodemax[%d]=%d\n", ij, j, ncodemax[j]); */
5374: /* break; */
5375: /* } */
5376: /* } /\* end of loop on modality k *\/ */
5377: } /* end of loop on model-covariate j. nbcode[Tvarj][1]=0 and nbcode[Tvarj][2]=1 sets the value of covariate j*/
5378:
5379: for (k=-1; k< maxncov; k++) Ndum[k]=0;
5380: /* Look at fixed dummy (single or product) covariates to check empty modalities */
5381: for (i=1; i<=ncovmodel-2-nagesqr; i++) { /* -2, cste and age and eventually age*age */
5382: /* Listing of all covariables in statement model to see if some covariates appear twice. For example, V1 appears twice in V1+V1*V2.*/
5383: 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 */
5384: 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 */
5385: /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, {2, 1, 1, 1, 2, 1, 1, 0, 0} */
5386: } /* V4+V3+V5, Ndum[1]@5={0, 0, 1, 1, 1} */
5387:
5388: ij=0;
5389: /* for (i=0; i<= maxncov-1; i++) { /\* modmaxcovj is unknown here. Only Ndum[2(V2),3(age*V3), 5(V3*V2) 6(V1*V4) *\/ */
5390: for (k=1; k<= cptcovt; k++) { /* modmaxcovj is unknown here. Only Ndum[2(V2),3(age*V3), 5(V3*V2) 6(V1*V4) */
5391: /*printf("Ndum[%d]=%d\n",i, Ndum[i]);*/
5392: /* if((Ndum[i]!=0) && (i<=ncovcol)){ /\* Tvar[i] <= ncovmodel ? *\/ */
5393: if(Ndum[Tvar[k]]!=0 && Dummy[k] == 0 && Typevar[k]==0){ /* Only Dummy and non empty in the model */
5394: /* If product not in single variable we don't print results */
5395: /*printf("diff Ndum[%d]=%d\n",i, Ndum[i]);*/
5396: ++ij;/* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, */
5397: 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*/
5398: Tmodelind[ij]=k; /* Tmodelind: index in model of dummies Tmodelind[1]=2 V4: pos=2; V3: pos=3, V1=9 {2, 3, 9, ?, ?,} */
5399: 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 */
5400: if(Fixed[k]!=0)
5401: anyvaryingduminmodel=1;
5402: /* }else if((Ndum[i]!=0) && (i<=ncovcol+nqv)){ */
5403: /* Tvaraff[++ij]=-10; /\* Dont'n know how to treat quantitative variables yet *\/ */
5404: /* }else if((Ndum[i]!=0) && (i<=ncovcol+nqv+ntv)){ */
5405: /* Tvaraff[++ij]=i; /\*For printing (unclear) *\/ */
5406: /* }else if((Ndum[i]!=0) && (i<=ncovcol+nqv+ntv+nqtv)){ */
5407: /* Tvaraff[++ij]=-20; /\* Dont'n know how to treat quantitative variables yet *\/ */
5408: }
5409: } /* Tvaraff[1]@5 {3, 4, -20, 0, 0} Very strange */
5410: /* ij--; */
5411: /* cptcoveff=ij; /\*Number of total covariates*\/ */
5412: *cptcov=ij; /*Number of total real effective covariates: effective
5413: * because they can be excluded from the model and real
5414: * if in the model but excluded because missing values, but how to get k from ij?*/
5415: for(j=ij+1; j<= cptcovt; j++){
5416: Tvaraff[j]=0;
5417: Tmodelind[j]=0;
5418: }
5419: for(j=ntveff+1; j<= cptcovt; j++){
5420: TmodelInvind[j]=0;
5421: }
5422: /* To be sorted */
5423: ;
5424: }
1.126 brouard 5425:
1.145 brouard 5426:
1.126 brouard 5427: /*********** Health Expectancies ****************/
5428:
1.235 brouard 5429: 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 5430:
5431: {
5432: /* Health expectancies, no variances */
1.164 brouard 5433: int i, j, nhstepm, hstepm, h, nstepm;
1.126 brouard 5434: int nhstepma, nstepma; /* Decreasing with age */
5435: double age, agelim, hf;
5436: double ***p3mat;
5437: double eip;
5438:
1.238 brouard 5439: /* pstamp(ficreseij); */
1.126 brouard 5440: fprintf(ficreseij,"# (a) Life expectancies by health status at initial age and (b) health expectancies by health status at initial age\n");
5441: fprintf(ficreseij,"# Age");
5442: for(i=1; i<=nlstate;i++){
5443: for(j=1; j<=nlstate;j++){
5444: fprintf(ficreseij," e%1d%1d ",i,j);
5445: }
5446: fprintf(ficreseij," e%1d. ",i);
5447: }
5448: fprintf(ficreseij,"\n");
5449:
5450:
5451: if(estepm < stepm){
5452: printf ("Problem %d lower than %d\n",estepm, stepm);
5453: }
5454: else hstepm=estepm;
5455: /* We compute the life expectancy from trapezoids spaced every estepm months
5456: * This is mainly to measure the difference between two models: for example
5457: * if stepm=24 months pijx are given only every 2 years and by summing them
5458: * we are calculating an estimate of the Life Expectancy assuming a linear
5459: * progression in between and thus overestimating or underestimating according
5460: * to the curvature of the survival function. If, for the same date, we
5461: * estimate the model with stepm=1 month, we can keep estepm to 24 months
5462: * to compare the new estimate of Life expectancy with the same linear
5463: * hypothesis. A more precise result, taking into account a more precise
5464: * curvature will be obtained if estepm is as small as stepm. */
5465:
5466: /* For example we decided to compute the life expectancy with the smallest unit */
5467: /* hstepm beeing the number of stepms, if hstepm=1 the length of hstepm is stepm.
5468: nhstepm is the number of hstepm from age to agelim
5469: nstepm is the number of stepm from age to agelin.
1.270 brouard 5470: Look at hpijx to understand the reason which relies in memory size consideration
1.126 brouard 5471: and note for a fixed period like estepm months */
5472: /* We decided (b) to get a life expectancy respecting the most precise curvature of the
5473: survival function given by stepm (the optimization length). Unfortunately it
5474: means that if the survival funtion is printed only each two years of age and if
5475: you sum them up and add 1 year (area under the trapezoids) you won't get the same
5476: results. So we changed our mind and took the option of the best precision.
5477: */
5478: hstepm=hstepm/stepm; /* Typically in stepm units, if stepm=6 & estepm=24 , = 24/6 months = 4 */
5479:
5480: agelim=AGESUP;
5481: /* If stepm=6 months */
5482: /* Computed by stepm unit matrices, product of hstepm matrices, stored
5483: in an array of nhstepm length: nhstepm=10, hstepm=4, stepm=6 months */
5484:
5485: /* nhstepm age range expressed in number of stepm */
5486: nstepm=(int) rint((agelim-bage)*YEARM/stepm); /* Biggest nstepm */
5487: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
5488: /* if (stepm >= YEARM) hstepm=1;*/
5489: nhstepm = nstepm/hstepm;/* Expressed in hstepm, typically nhstepm=40/4=10 */
5490: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
5491:
5492: for (age=bage; age<=fage; age ++){
5493: nstepma=(int) rint((agelim-bage)*YEARM/stepm); /* Biggest nstepm */
5494: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
5495: /* if (stepm >= YEARM) hstepm=1;*/
5496: nhstepma = nstepma/hstepm;/* Expressed in hstepm, typically nhstepma=40/4=10 */
5497:
5498: /* If stepm=6 months */
5499: /* Computed by stepm unit matrices, product of hstepma matrices, stored
5500: in an array of nhstepma length: nhstepma=10, hstepm=4, stepm=6 months */
5501:
1.235 brouard 5502: hpxij(p3mat,nhstepma,age,hstepm,x,nlstate,stepm,oldm, savm, cij, nres);
1.126 brouard 5503:
5504: hf=hstepm*stepm/YEARM; /* Duration of hstepm expressed in year unit. */
5505:
5506: printf("%d|",(int)age);fflush(stdout);
5507: fprintf(ficlog,"%d|",(int)age);fflush(ficlog);
5508:
5509: /* Computing expectancies */
5510: for(i=1; i<=nlstate;i++)
5511: for(j=1; j<=nlstate;j++)
5512: for (h=0, eij[i][j][(int)age]=0; h<=nhstepm-1; h++){
5513: eij[i][j][(int)age] += (p3mat[i][j][h]+p3mat[i][j][h+1])/2.0*hf;
5514:
5515: /* 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]);*/
5516:
5517: }
5518:
5519: fprintf(ficreseij,"%3.0f",age );
5520: for(i=1; i<=nlstate;i++){
5521: eip=0;
5522: for(j=1; j<=nlstate;j++){
5523: eip +=eij[i][j][(int)age];
5524: fprintf(ficreseij,"%9.4f", eij[i][j][(int)age] );
5525: }
5526: fprintf(ficreseij,"%9.4f", eip );
5527: }
5528: fprintf(ficreseij,"\n");
5529:
5530: }
5531: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
5532: printf("\n");
5533: fprintf(ficlog,"\n");
5534:
5535: }
5536:
1.235 brouard 5537: 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 5538:
5539: {
5540: /* Covariances of health expectancies eij and of total life expectancies according
1.222 brouard 5541: to initial status i, ei. .
1.126 brouard 5542: */
5543: int i, j, nhstepm, hstepm, h, nstepm, k, cptj, cptj2, i2, j2, ij, ji;
5544: int nhstepma, nstepma; /* Decreasing with age */
5545: double age, agelim, hf;
5546: double ***p3matp, ***p3matm, ***varhe;
5547: double **dnewm,**doldm;
5548: double *xp, *xm;
5549: double **gp, **gm;
5550: double ***gradg, ***trgradg;
5551: int theta;
5552:
5553: double eip, vip;
5554:
5555: varhe=ma3x(1,nlstate*nlstate,1,nlstate*nlstate,(int) bage, (int) fage);
5556: xp=vector(1,npar);
5557: xm=vector(1,npar);
5558: dnewm=matrix(1,nlstate*nlstate,1,npar);
5559: doldm=matrix(1,nlstate*nlstate,1,nlstate*nlstate);
5560:
5561: pstamp(ficresstdeij);
5562: fprintf(ficresstdeij,"# Health expectancies with standard errors\n");
5563: fprintf(ficresstdeij,"# Age");
5564: for(i=1; i<=nlstate;i++){
5565: for(j=1; j<=nlstate;j++)
5566: fprintf(ficresstdeij," e%1d%1d (SE)",i,j);
5567: fprintf(ficresstdeij," e%1d. ",i);
5568: }
5569: fprintf(ficresstdeij,"\n");
5570:
5571: pstamp(ficrescveij);
5572: fprintf(ficrescveij,"# Subdiagonal matrix of covariances of health expectancies by age: cov(eij,ekl)\n");
5573: fprintf(ficrescveij,"# Age");
5574: for(i=1; i<=nlstate;i++)
5575: for(j=1; j<=nlstate;j++){
5576: cptj= (j-1)*nlstate+i;
5577: for(i2=1; i2<=nlstate;i2++)
5578: for(j2=1; j2<=nlstate;j2++){
5579: cptj2= (j2-1)*nlstate+i2;
5580: if(cptj2 <= cptj)
5581: fprintf(ficrescveij," %1d%1d,%1d%1d",i,j,i2,j2);
5582: }
5583: }
5584: fprintf(ficrescveij,"\n");
5585:
5586: if(estepm < stepm){
5587: printf ("Problem %d lower than %d\n",estepm, stepm);
5588: }
5589: else hstepm=estepm;
5590: /* We compute the life expectancy from trapezoids spaced every estepm months
5591: * This is mainly to measure the difference between two models: for example
5592: * if stepm=24 months pijx are given only every 2 years and by summing them
5593: * we are calculating an estimate of the Life Expectancy assuming a linear
5594: * progression in between and thus overestimating or underestimating according
5595: * to the curvature of the survival function. If, for the same date, we
5596: * estimate the model with stepm=1 month, we can keep estepm to 24 months
5597: * to compare the new estimate of Life expectancy with the same linear
5598: * hypothesis. A more precise result, taking into account a more precise
5599: * curvature will be obtained if estepm is as small as stepm. */
5600:
5601: /* For example we decided to compute the life expectancy with the smallest unit */
5602: /* hstepm beeing the number of stepms, if hstepm=1 the length of hstepm is stepm.
5603: nhstepm is the number of hstepm from age to agelim
5604: nstepm is the number of stepm from age to agelin.
5605: Look at hpijx to understand the reason of that which relies in memory size
5606: and note for a fixed period like estepm months */
5607: /* We decided (b) to get a life expectancy respecting the most precise curvature of the
5608: survival function given by stepm (the optimization length). Unfortunately it
5609: means that if the survival funtion is printed only each two years of age and if
5610: you sum them up and add 1 year (area under the trapezoids) you won't get the same
5611: results. So we changed our mind and took the option of the best precision.
5612: */
5613: hstepm=hstepm/stepm; /* Typically in stepm units, if stepm=6 & estepm=24 , = 24/6 months = 4 */
5614:
5615: /* If stepm=6 months */
5616: /* nhstepm age range expressed in number of stepm */
5617: agelim=AGESUP;
5618: nstepm=(int) rint((agelim-bage)*YEARM/stepm);
5619: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
5620: /* if (stepm >= YEARM) hstepm=1;*/
5621: nhstepm = nstepm/hstepm;/* Expressed in hstepm, typically nhstepm=40/4=10 */
5622:
5623: p3matp=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
5624: p3matm=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
5625: gradg=ma3x(0,nhstepm,1,npar,1,nlstate*nlstate);
5626: trgradg =ma3x(0,nhstepm,1,nlstate*nlstate,1,npar);
5627: gp=matrix(0,nhstepm,1,nlstate*nlstate);
5628: gm=matrix(0,nhstepm,1,nlstate*nlstate);
5629:
5630: for (age=bage; age<=fage; age ++){
5631: nstepma=(int) rint((agelim-bage)*YEARM/stepm); /* Biggest nstepm */
5632: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
5633: /* if (stepm >= YEARM) hstepm=1;*/
5634: nhstepma = nstepma/hstepm;/* Expressed in hstepm, typically nhstepma=40/4=10 */
1.218 brouard 5635:
1.126 brouard 5636: /* If stepm=6 months */
5637: /* Computed by stepm unit matrices, product of hstepma matrices, stored
5638: in an array of nhstepma length: nhstepma=10, hstepm=4, stepm=6 months */
5639:
5640: hf=hstepm*stepm/YEARM; /* Duration of hstepm expressed in year unit. */
1.218 brouard 5641:
1.126 brouard 5642: /* Computing Variances of health expectancies */
5643: /* Gradient is computed with plus gp and minus gm. Code is duplicated in order to
5644: decrease memory allocation */
5645: for(theta=1; theta <=npar; theta++){
5646: for(i=1; i<=npar; i++){
1.222 brouard 5647: xp[i] = x[i] + (i==theta ?delti[theta]:0);
5648: xm[i] = x[i] - (i==theta ?delti[theta]:0);
1.126 brouard 5649: }
1.235 brouard 5650: hpxij(p3matp,nhstepm,age,hstepm,xp,nlstate,stepm,oldm,savm, cij, nres);
5651: hpxij(p3matm,nhstepm,age,hstepm,xm,nlstate,stepm,oldm,savm, cij, nres);
1.218 brouard 5652:
1.126 brouard 5653: for(j=1; j<= nlstate; j++){
1.222 brouard 5654: for(i=1; i<=nlstate; i++){
5655: for(h=0; h<=nhstepm-1; h++){
5656: gp[h][(j-1)*nlstate + i] = (p3matp[i][j][h]+p3matp[i][j][h+1])/2.;
5657: gm[h][(j-1)*nlstate + i] = (p3matm[i][j][h]+p3matm[i][j][h+1])/2.;
5658: }
5659: }
1.126 brouard 5660: }
1.218 brouard 5661:
1.126 brouard 5662: for(ij=1; ij<= nlstate*nlstate; ij++)
1.222 brouard 5663: for(h=0; h<=nhstepm-1; h++){
5664: gradg[h][theta][ij]= (gp[h][ij]-gm[h][ij])/2./delti[theta];
5665: }
1.126 brouard 5666: }/* End theta */
5667:
5668:
5669: for(h=0; h<=nhstepm-1; h++)
5670: for(j=1; j<=nlstate*nlstate;j++)
1.222 brouard 5671: for(theta=1; theta <=npar; theta++)
5672: trgradg[h][j][theta]=gradg[h][theta][j];
1.126 brouard 5673:
1.218 brouard 5674:
1.222 brouard 5675: for(ij=1;ij<=nlstate*nlstate;ij++)
1.126 brouard 5676: for(ji=1;ji<=nlstate*nlstate;ji++)
1.222 brouard 5677: varhe[ij][ji][(int)age] =0.;
1.218 brouard 5678:
1.222 brouard 5679: printf("%d|",(int)age);fflush(stdout);
5680: fprintf(ficlog,"%d|",(int)age);fflush(ficlog);
5681: for(h=0;h<=nhstepm-1;h++){
1.126 brouard 5682: for(k=0;k<=nhstepm-1;k++){
1.222 brouard 5683: matprod2(dnewm,trgradg[h],1,nlstate*nlstate,1,npar,1,npar,matcov);
5684: matprod2(doldm,dnewm,1,nlstate*nlstate,1,npar,1,nlstate*nlstate,gradg[k]);
5685: for(ij=1;ij<=nlstate*nlstate;ij++)
5686: for(ji=1;ji<=nlstate*nlstate;ji++)
5687: varhe[ij][ji][(int)age] += doldm[ij][ji]*hf*hf;
1.126 brouard 5688: }
5689: }
1.218 brouard 5690:
1.126 brouard 5691: /* Computing expectancies */
1.235 brouard 5692: hpxij(p3matm,nhstepm,age,hstepm,x,nlstate,stepm,oldm, savm, cij,nres);
1.126 brouard 5693: for(i=1; i<=nlstate;i++)
5694: for(j=1; j<=nlstate;j++)
1.222 brouard 5695: for (h=0, eij[i][j][(int)age]=0; h<=nhstepm-1; h++){
5696: eij[i][j][(int)age] += (p3matm[i][j][h]+p3matm[i][j][h+1])/2.0*hf;
1.218 brouard 5697:
1.222 brouard 5698: /* 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 5699:
1.222 brouard 5700: }
1.269 brouard 5701:
5702: /* Standard deviation of expectancies ij */
1.126 brouard 5703: fprintf(ficresstdeij,"%3.0f",age );
5704: for(i=1; i<=nlstate;i++){
5705: eip=0.;
5706: vip=0.;
5707: for(j=1; j<=nlstate;j++){
1.222 brouard 5708: eip += eij[i][j][(int)age];
5709: for(k=1; k<=nlstate;k++) /* Sum on j and k of cov(eij,eik) */
5710: vip += varhe[(j-1)*nlstate+i][(k-1)*nlstate+i][(int)age];
5711: 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 5712: }
5713: fprintf(ficresstdeij," %9.4f (%.4f)", eip, sqrt(vip));
5714: }
5715: fprintf(ficresstdeij,"\n");
1.218 brouard 5716:
1.269 brouard 5717: /* Variance of expectancies ij */
1.126 brouard 5718: fprintf(ficrescveij,"%3.0f",age );
5719: for(i=1; i<=nlstate;i++)
5720: for(j=1; j<=nlstate;j++){
1.222 brouard 5721: cptj= (j-1)*nlstate+i;
5722: for(i2=1; i2<=nlstate;i2++)
5723: for(j2=1; j2<=nlstate;j2++){
5724: cptj2= (j2-1)*nlstate+i2;
5725: if(cptj2 <= cptj)
5726: fprintf(ficrescveij," %.4f", varhe[cptj][cptj2][(int)age]);
5727: }
1.126 brouard 5728: }
5729: fprintf(ficrescveij,"\n");
1.218 brouard 5730:
1.126 brouard 5731: }
5732: free_matrix(gm,0,nhstepm,1,nlstate*nlstate);
5733: free_matrix(gp,0,nhstepm,1,nlstate*nlstate);
5734: free_ma3x(gradg,0,nhstepm,1,npar,1,nlstate*nlstate);
5735: free_ma3x(trgradg,0,nhstepm,1,nlstate*nlstate,1,npar);
5736: free_ma3x(p3matm,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
5737: free_ma3x(p3matp,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
5738: printf("\n");
5739: fprintf(ficlog,"\n");
1.218 brouard 5740:
1.126 brouard 5741: free_vector(xm,1,npar);
5742: free_vector(xp,1,npar);
5743: free_matrix(dnewm,1,nlstate*nlstate,1,npar);
5744: free_matrix(doldm,1,nlstate*nlstate,1,nlstate*nlstate);
5745: free_ma3x(varhe,1,nlstate*nlstate,1,nlstate*nlstate,(int) bage, (int)fage);
5746: }
1.218 brouard 5747:
1.126 brouard 5748: /************ Variance ******************/
1.235 brouard 5749: 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 5750: {
5751: /* Variance of health expectancies */
5752: /* double **prevalim(double **prlim, int nlstate, double *xp, double age, double **oldm, double ** savm,double ftolpl);*/
5753: /* double **newm;*/
5754: /* int movingaverage(double ***probs, double bage,double fage, double ***mobaverage, int mobilav)*/
5755:
5756: /* int movingaverage(); */
5757: double **dnewm,**doldm;
5758: double **dnewmp,**doldmp;
5759: int i, j, nhstepm, hstepm, h, nstepm ;
5760: int k;
5761: double *xp;
5762: double **gp, **gm; /* for var eij */
5763: double ***gradg, ***trgradg; /*for var eij */
5764: double **gradgp, **trgradgp; /* for var p point j */
5765: double *gpp, *gmp; /* for var p point j */
5766: double **varppt; /* for var p point j nlstate to nlstate+ndeath */
5767: double ***p3mat;
5768: double age,agelim, hf;
5769: /* double ***mobaverage; */
5770: int theta;
5771: char digit[4];
5772: char digitp[25];
5773:
5774: char fileresprobmorprev[FILENAMELENGTH];
5775:
5776: if(popbased==1){
5777: if(mobilav!=0)
5778: strcpy(digitp,"-POPULBASED-MOBILAV_");
5779: else strcpy(digitp,"-POPULBASED-NOMOBIL_");
5780: }
5781: else
5782: strcpy(digitp,"-STABLBASED_");
1.126 brouard 5783:
1.218 brouard 5784: /* if (mobilav!=0) { */
5785: /* mobaverage= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
5786: /* if (movingaverage(probs, bage, fage, mobaverage,mobilav)!=0){ */
5787: /* fprintf(ficlog," Error in movingaverage mobilav=%d\n",mobilav); */
5788: /* printf(" Error in movingaverage mobilav=%d\n",mobilav); */
5789: /* } */
5790: /* } */
5791:
5792: strcpy(fileresprobmorprev,"PRMORPREV-");
5793: sprintf(digit,"%-d",ij);
5794: /*printf("DIGIT=%s, ij=%d ijr=%-d|\n",digit, ij,ij);*/
5795: strcat(fileresprobmorprev,digit); /* Tvar to be done */
5796: strcat(fileresprobmorprev,digitp); /* Popbased or not, mobilav or not */
5797: strcat(fileresprobmorprev,fileresu);
5798: if((ficresprobmorprev=fopen(fileresprobmorprev,"w"))==NULL) {
5799: printf("Problem with resultfile: %s\n", fileresprobmorprev);
5800: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprobmorprev);
5801: }
5802: printf("Computing total mortality p.j=w1*p1j+w2*p2j+..: result on file '%s' \n",fileresprobmorprev);
5803: fprintf(ficlog,"Computing total mortality p.j=w1*p1j+w2*p2j+..: result on file '%s' \n",fileresprobmorprev);
5804: pstamp(ficresprobmorprev);
5805: 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 5806: fprintf(ficresprobmorprev,"# Selected quantitative variables and dummies");
5807: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
5808: fprintf(ficresprobmorprev," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
5809: }
5810: for(j=1;j<=cptcoveff;j++)
5811: fprintf(ficresprobmorprev,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(ij,j)]);
5812: fprintf(ficresprobmorprev,"\n");
5813:
1.218 brouard 5814: fprintf(ficresprobmorprev,"# Age cov=%-d",ij);
5815: for(j=nlstate+1; j<=(nlstate+ndeath);j++){
5816: fprintf(ficresprobmorprev," p.%-d SE",j);
5817: for(i=1; i<=nlstate;i++)
5818: fprintf(ficresprobmorprev," w%1d p%-d%-d",i,i,j);
5819: }
5820: fprintf(ficresprobmorprev,"\n");
5821:
5822: fprintf(ficgp,"\n# Routine varevsij");
5823: fprintf(ficgp,"\nunset title \n");
5824: /* fprintf(fichtm, "#Local time at start: %s", strstart);*/
5825: 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");
5826: fprintf(fichtm,"\n<br>%s <br>\n",digitp);
5827: /* } */
5828: varppt = matrix(nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
5829: pstamp(ficresvij);
5830: fprintf(ficresvij,"# Variance and covariance of health expectancies e.j \n# (weighted average of eij where weights are ");
5831: if(popbased==1)
5832: 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);
5833: else
5834: fprintf(ficresvij,"the age specific period (stable) prevalences in each health state \n");
5835: fprintf(ficresvij,"# Age");
5836: for(i=1; i<=nlstate;i++)
5837: for(j=1; j<=nlstate;j++)
5838: fprintf(ficresvij," Cov(e.%1d, e.%1d)",i,j);
5839: fprintf(ficresvij,"\n");
5840:
5841: xp=vector(1,npar);
5842: dnewm=matrix(1,nlstate,1,npar);
5843: doldm=matrix(1,nlstate,1,nlstate);
5844: dnewmp= matrix(nlstate+1,nlstate+ndeath,1,npar);
5845: doldmp= matrix(nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
5846:
5847: gradgp=matrix(1,npar,nlstate+1,nlstate+ndeath);
5848: gpp=vector(nlstate+1,nlstate+ndeath);
5849: gmp=vector(nlstate+1,nlstate+ndeath);
5850: trgradgp =matrix(nlstate+1,nlstate+ndeath,1,npar); /* mu or p point j*/
1.126 brouard 5851:
1.218 brouard 5852: if(estepm < stepm){
5853: printf ("Problem %d lower than %d\n",estepm, stepm);
5854: }
5855: else hstepm=estepm;
5856: /* For example we decided to compute the life expectancy with the smallest unit */
5857: /* hstepm beeing the number of stepms, if hstepm=1 the length of hstepm is stepm.
5858: nhstepm is the number of hstepm from age to agelim
5859: nstepm is the number of stepm from age to agelim.
5860: Look at function hpijx to understand why because of memory size limitations,
5861: we decided (b) to get a life expectancy respecting the most precise curvature of the
5862: survival function given by stepm (the optimization length). Unfortunately it
5863: means that if the survival funtion is printed every two years of age and if
5864: you sum them up and add 1 year (area under the trapezoids) you won't get the same
5865: results. So we changed our mind and took the option of the best precision.
5866: */
5867: hstepm=hstepm/stepm; /* Typically in stepm units, if stepm=6 & estepm=24 , = 24/6 months = 4 */
5868: agelim = AGESUP;
5869: for (age=bage; age<=fage; age ++){ /* If stepm=6 months */
5870: nstepm=(int) rint((agelim-age)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
5871: nhstepm = nstepm/hstepm;/* Expressed in hstepm, typically nhstepm=40/4=10 */
5872: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
5873: gradg=ma3x(0,nhstepm,1,npar,1,nlstate);
5874: gp=matrix(0,nhstepm,1,nlstate);
5875: gm=matrix(0,nhstepm,1,nlstate);
5876:
5877:
5878: for(theta=1; theta <=npar; theta++){
5879: for(i=1; i<=npar; i++){ /* Computes gradient x + delta*/
5880: xp[i] = x[i] + (i==theta ?delti[theta]:0);
5881: }
5882:
1.242 brouard 5883: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij, nres);
1.218 brouard 5884:
5885: if (popbased==1) {
5886: if(mobilav ==0){
5887: for(i=1; i<=nlstate;i++)
5888: prlim[i][i]=probs[(int)age][i][ij];
5889: }else{ /* mobilav */
5890: for(i=1; i<=nlstate;i++)
5891: prlim[i][i]=mobaverage[(int)age][i][ij];
5892: }
5893: }
5894:
1.235 brouard 5895: 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 5896: for(j=1; j<= nlstate; j++){
5897: for(h=0; h<=nhstepm; h++){
5898: for(i=1, gp[h][j]=0.;i<=nlstate;i++)
5899: gp[h][j] += prlim[i][i]*p3mat[i][j][h];
5900: }
5901: }
5902: /* Next for computing probability of death (h=1 means
5903: computed over hstepm matrices product = hstepm*stepm months)
5904: as a weighted average of prlim.
5905: */
5906: for(j=nlstate+1;j<=nlstate+ndeath;j++){
5907: for(i=1,gpp[j]=0.; i<= nlstate; i++)
5908: gpp[j] += prlim[i][i]*p3mat[i][j][1];
5909: }
5910: /* end probability of death */
5911:
5912: for(i=1; i<=npar; i++) /* Computes gradient x - delta */
5913: xp[i] = x[i] - (i==theta ?delti[theta]:0);
5914:
1.242 brouard 5915: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp, ij, nres);
1.218 brouard 5916:
5917: if (popbased==1) {
5918: if(mobilav ==0){
5919: for(i=1; i<=nlstate;i++)
5920: prlim[i][i]=probs[(int)age][i][ij];
5921: }else{ /* mobilav */
5922: for(i=1; i<=nlstate;i++)
5923: prlim[i][i]=mobaverage[(int)age][i][ij];
5924: }
5925: }
5926:
1.235 brouard 5927: hpxij(p3mat,nhstepm,age,hstepm,xp,nlstate,stepm,oldm,savm, ij,nres);
1.218 brouard 5928:
5929: for(j=1; j<= nlstate; j++){ /* Sum of wi * eij = e.j */
5930: for(h=0; h<=nhstepm; h++){
5931: for(i=1, gm[h][j]=0.;i<=nlstate;i++)
5932: gm[h][j] += prlim[i][i]*p3mat[i][j][h];
5933: }
5934: }
5935: /* This for computing probability of death (h=1 means
5936: computed over hstepm matrices product = hstepm*stepm months)
5937: as a weighted average of prlim.
5938: */
5939: for(j=nlstate+1;j<=nlstate+ndeath;j++){
5940: for(i=1,gmp[j]=0.; i<= nlstate; i++)
5941: gmp[j] += prlim[i][i]*p3mat[i][j][1];
5942: }
5943: /* end probability of death */
5944:
5945: for(j=1; j<= nlstate; j++) /* vareij */
5946: for(h=0; h<=nhstepm; h++){
5947: gradg[h][theta][j]= (gp[h][j]-gm[h][j])/2./delti[theta];
5948: }
5949:
5950: for(j=nlstate+1; j<= nlstate+ndeath; j++){ /* var mu */
5951: gradgp[theta][j]= (gpp[j]-gmp[j])/2./delti[theta];
5952: }
5953:
5954: } /* End theta */
5955:
5956: trgradg =ma3x(0,nhstepm,1,nlstate,1,npar); /* veij */
5957:
5958: for(h=0; h<=nhstepm; h++) /* veij */
5959: for(j=1; j<=nlstate;j++)
5960: for(theta=1; theta <=npar; theta++)
5961: trgradg[h][j][theta]=gradg[h][theta][j];
5962:
5963: for(j=nlstate+1; j<=nlstate+ndeath;j++) /* mu */
5964: for(theta=1; theta <=npar; theta++)
5965: trgradgp[j][theta]=gradgp[theta][j];
5966:
5967:
5968: hf=hstepm*stepm/YEARM; /* Duration of hstepm expressed in year unit. */
5969: for(i=1;i<=nlstate;i++)
5970: for(j=1;j<=nlstate;j++)
5971: vareij[i][j][(int)age] =0.;
5972:
5973: for(h=0;h<=nhstepm;h++){
5974: for(k=0;k<=nhstepm;k++){
5975: matprod2(dnewm,trgradg[h],1,nlstate,1,npar,1,npar,matcov);
5976: matprod2(doldm,dnewm,1,nlstate,1,npar,1,nlstate,gradg[k]);
5977: for(i=1;i<=nlstate;i++)
5978: for(j=1;j<=nlstate;j++)
5979: vareij[i][j][(int)age] += doldm[i][j]*hf*hf;
5980: }
5981: }
5982:
5983: /* pptj */
5984: matprod2(dnewmp,trgradgp,nlstate+1,nlstate+ndeath,1,npar,1,npar,matcov);
5985: matprod2(doldmp,dnewmp,nlstate+1,nlstate+ndeath,1,npar,nlstate+1,nlstate+ndeath,gradgp);
5986: for(j=nlstate+1;j<=nlstate+ndeath;j++)
5987: for(i=nlstate+1;i<=nlstate+ndeath;i++)
5988: varppt[j][i]=doldmp[j][i];
5989: /* end ppptj */
5990: /* x centered again */
5991:
1.242 brouard 5992: prevalim(prlim,nlstate,x,age,oldm,savm,ftolpl,ncvyearp,ij, nres);
1.218 brouard 5993:
5994: if (popbased==1) {
5995: if(mobilav ==0){
5996: for(i=1; i<=nlstate;i++)
5997: prlim[i][i]=probs[(int)age][i][ij];
5998: }else{ /* mobilav */
5999: for(i=1; i<=nlstate;i++)
6000: prlim[i][i]=mobaverage[(int)age][i][ij];
6001: }
6002: }
6003:
6004: /* This for computing probability of death (h=1 means
6005: computed over hstepm (estepm) matrices product = hstepm*stepm months)
6006: as a weighted average of prlim.
6007: */
1.235 brouard 6008: hpxij(p3mat,nhstepm,age,hstepm,x,nlstate,stepm,oldm,savm, ij, nres);
1.218 brouard 6009: for(j=nlstate+1;j<=nlstate+ndeath;j++){
6010: for(i=1,gmp[j]=0.;i<= nlstate; i++)
6011: gmp[j] += prlim[i][i]*p3mat[i][j][1];
6012: }
6013: /* end probability of death */
6014:
6015: fprintf(ficresprobmorprev,"%3d %d ",(int) age, ij);
6016: for(j=nlstate+1; j<=(nlstate+ndeath);j++){
6017: fprintf(ficresprobmorprev," %11.3e %11.3e",gmp[j], sqrt(varppt[j][j]));
6018: for(i=1; i<=nlstate;i++){
6019: fprintf(ficresprobmorprev," %11.3e %11.3e ",prlim[i][i],p3mat[i][j][1]);
6020: }
6021: }
6022: fprintf(ficresprobmorprev,"\n");
6023:
6024: fprintf(ficresvij,"%.0f ",age );
6025: for(i=1; i<=nlstate;i++)
6026: for(j=1; j<=nlstate;j++){
6027: fprintf(ficresvij," %.4f", vareij[i][j][(int)age]);
6028: }
6029: fprintf(ficresvij,"\n");
6030: free_matrix(gp,0,nhstepm,1,nlstate);
6031: free_matrix(gm,0,nhstepm,1,nlstate);
6032: free_ma3x(gradg,0,nhstepm,1,npar,1,nlstate);
6033: free_ma3x(trgradg,0,nhstepm,1,nlstate,1,npar);
6034: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
6035: } /* End age */
6036: free_vector(gpp,nlstate+1,nlstate+ndeath);
6037: free_vector(gmp,nlstate+1,nlstate+ndeath);
6038: free_matrix(gradgp,1,npar,nlstate+1,nlstate+ndeath);
6039: free_matrix(trgradgp,nlstate+1,nlstate+ndeath,1,npar); /* mu or p point j*/
6040: /* fprintf(ficgp,"\nunset parametric;unset label; set ter png small size 320, 240"); */
6041: fprintf(ficgp,"\nunset parametric;unset label; set ter svg size 640, 480");
6042: /* for(j=nlstate+1; j<= nlstate+ndeath; j++){ *//* Only the first actually */
6043: fprintf(ficgp,"\n set log y; unset log x;set xlabel \"Age\"; set ylabel \"Force of mortality (year-1)\";");
6044: fprintf(ficgp,"\nset out \"%s%s.svg\";",subdirf3(optionfilefiname,"VARMUPTJGR-",digitp),digit);
6045: /* fprintf(ficgp,"\n plot \"%s\" u 1:($3*%6.3f) not w l 1 ",fileresprobmorprev,YEARM/estepm); */
6046: /* fprintf(ficgp,"\n replot \"%s\" u 1:(($3+1.96*$4)*%6.3f) t \"95\%% interval\" w l 2 ",fileresprobmorprev,YEARM/estepm); */
6047: /* fprintf(ficgp,"\n replot \"%s\" u 1:(($3-1.96*$4)*%6.3f) not w l 2 ",fileresprobmorprev,YEARM/estepm); */
6048: fprintf(ficgp,"\n plot \"%s\" u 1:($3) not w l lt 1 ",subdirf(fileresprobmorprev));
6049: fprintf(ficgp,"\n replot \"%s\" u 1:(($3+1.96*$4)) t \"95%% interval\" w l lt 2 ",subdirf(fileresprobmorprev));
6050: fprintf(ficgp,"\n replot \"%s\" u 1:(($3-1.96*$4)) not w l lt 2 ",subdirf(fileresprobmorprev));
6051: fprintf(fichtm,"\n<br> File (multiple files are possible if covariates are present): <A href=\"%s\">%s</a>\n",subdirf(fileresprobmorprev),subdirf(fileresprobmorprev));
6052: 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);
6053: /* 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 6054: */
1.218 brouard 6055: /* fprintf(ficgp,"\nset out \"varmuptjgr%s%s%s.svg\";replot;",digitp,optionfilefiname,digit); */
6056: fprintf(ficgp,"\nset out;\nset out \"%s%s.svg\";replot;set out;\n",subdirf3(optionfilefiname,"VARMUPTJGR-",digitp),digit);
1.126 brouard 6057:
1.218 brouard 6058: free_vector(xp,1,npar);
6059: free_matrix(doldm,1,nlstate,1,nlstate);
6060: free_matrix(dnewm,1,nlstate,1,npar);
6061: free_matrix(doldmp,nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
6062: free_matrix(dnewmp,nlstate+1,nlstate+ndeath,1,npar);
6063: free_matrix(varppt,nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
6064: /* if (mobilav!=0) free_ma3x(mobaverage,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
6065: fclose(ficresprobmorprev);
6066: fflush(ficgp);
6067: fflush(fichtm);
6068: } /* end varevsij */
1.126 brouard 6069:
6070: /************ Variance of prevlim ******************/
1.269 brouard 6071: void varprevlim(char fileresvpl[], FILE *ficresvpl, double **varpl, double **matcov, double x[], double delti[], int nlstate, int stepm, double bage, double fage, double **oldm, double **savm, double **prlim, double ftolpl, int *ncvyearp, int ij, char strstart[], int nres)
1.126 brouard 6072: {
1.205 brouard 6073: /* Variance of prevalence limit for each state ij using current parameters x[] and estimates of neighbourhood give by delti*/
1.126 brouard 6074: /* double **prevalim(double **prlim, int nlstate, double *xp, double age, double **oldm, double **savm,double ftolpl);*/
1.164 brouard 6075:
1.268 brouard 6076: double **dnewmpar,**doldm;
1.126 brouard 6077: int i, j, nhstepm, hstepm;
6078: double *xp;
6079: double *gp, *gm;
6080: double **gradg, **trgradg;
1.208 brouard 6081: double **mgm, **mgp;
1.126 brouard 6082: double age,agelim;
6083: int theta;
6084:
6085: pstamp(ficresvpl);
6086: fprintf(ficresvpl,"# Standard deviation of period (stable) prevalences \n");
1.241 brouard 6087: fprintf(ficresvpl,"# Age ");
6088: if(nresult >=1)
6089: fprintf(ficresvpl," Result# ");
1.126 brouard 6090: for(i=1; i<=nlstate;i++)
6091: fprintf(ficresvpl," %1d-%1d",i,i);
6092: fprintf(ficresvpl,"\n");
6093:
6094: xp=vector(1,npar);
1.268 brouard 6095: dnewmpar=matrix(1,nlstate,1,npar);
1.126 brouard 6096: doldm=matrix(1,nlstate,1,nlstate);
6097:
6098: hstepm=1*YEARM; /* Every year of age */
6099: hstepm=hstepm/stepm; /* Typically in stepm units, if j= 2 years, = 2/6 months = 4 */
6100: agelim = AGESUP;
6101: for (age=bage; age<=fage; age ++){ /* If stepm=6 months */
6102: nhstepm=(int) rint((agelim-age)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
6103: if (stepm >= YEARM) hstepm=1;
6104: nhstepm = nhstepm/hstepm; /* Typically 40/4=10 */
6105: gradg=matrix(1,npar,1,nlstate);
1.208 brouard 6106: mgp=matrix(1,npar,1,nlstate);
6107: mgm=matrix(1,npar,1,nlstate);
1.126 brouard 6108: gp=vector(1,nlstate);
6109: gm=vector(1,nlstate);
6110:
6111: for(theta=1; theta <=npar; theta++){
6112: for(i=1; i<=npar; i++){ /* Computes gradient */
6113: xp[i] = x[i] + (i==theta ?delti[theta]:0);
6114: }
1.209 brouard 6115: if((int)age==79 ||(int)age== 80 ||(int)age== 81 )
1.235 brouard 6116: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres);
1.209 brouard 6117: else
1.235 brouard 6118: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres);
1.208 brouard 6119: for(i=1;i<=nlstate;i++){
1.126 brouard 6120: gp[i] = prlim[i][i];
1.208 brouard 6121: mgp[theta][i] = prlim[i][i];
6122: }
1.126 brouard 6123: for(i=1; i<=npar; i++) /* Computes gradient */
6124: xp[i] = x[i] - (i==theta ?delti[theta]:0);
1.209 brouard 6125: if((int)age==79 ||(int)age== 80 ||(int)age== 81 )
1.235 brouard 6126: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres);
1.209 brouard 6127: else
1.235 brouard 6128: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres);
1.208 brouard 6129: for(i=1;i<=nlstate;i++){
1.126 brouard 6130: gm[i] = prlim[i][i];
1.208 brouard 6131: mgm[theta][i] = prlim[i][i];
6132: }
1.126 brouard 6133: for(i=1;i<=nlstate;i++)
6134: gradg[theta][i]= (gp[i]-gm[i])/2./delti[theta];
1.209 brouard 6135: /* gradg[theta][2]= -gradg[theta][1]; */ /* For testing if nlstate=2 */
1.126 brouard 6136: } /* End theta */
6137:
6138: trgradg =matrix(1,nlstate,1,npar);
6139:
6140: for(j=1; j<=nlstate;j++)
6141: for(theta=1; theta <=npar; theta++)
6142: trgradg[j][theta]=gradg[theta][j];
1.209 brouard 6143: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
6144: /* printf("\nmgm mgp %d ",(int)age); */
6145: /* for(j=1; j<=nlstate;j++){ */
6146: /* printf(" %d ",j); */
6147: /* for(theta=1; theta <=npar; theta++) */
6148: /* printf(" %d %lf %lf",theta,mgm[theta][j],mgp[theta][j]); */
6149: /* printf("\n "); */
6150: /* } */
6151: /* } */
6152: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
6153: /* printf("\n gradg %d ",(int)age); */
6154: /* for(j=1; j<=nlstate;j++){ */
6155: /* printf("%d ",j); */
6156: /* for(theta=1; theta <=npar; theta++) */
6157: /* printf("%d %lf ",theta,gradg[theta][j]); */
6158: /* printf("\n "); */
6159: /* } */
6160: /* } */
1.126 brouard 6161:
6162: for(i=1;i<=nlstate;i++)
6163: varpl[i][(int)age] =0.;
1.209 brouard 6164: if((int)age==79 ||(int)age== 80 ||(int)age== 81){
1.268 brouard 6165: matprod2(dnewmpar,trgradg,1,nlstate,1,npar,1,npar,matcov);
6166: matprod2(doldm,dnewmpar,1,nlstate,1,npar,1,nlstate,gradg);
1.205 brouard 6167: }else{
1.268 brouard 6168: matprod2(dnewmpar,trgradg,1,nlstate,1,npar,1,npar,matcov);
6169: matprod2(doldm,dnewmpar,1,nlstate,1,npar,1,nlstate,gradg);
1.205 brouard 6170: }
1.126 brouard 6171: for(i=1;i<=nlstate;i++)
6172: varpl[i][(int)age] = doldm[i][i]; /* Covariances are useless */
6173:
6174: fprintf(ficresvpl,"%.0f ",age );
1.241 brouard 6175: if(nresult >=1)
6176: fprintf(ficresvpl,"%d ",nres );
1.126 brouard 6177: for(i=1; i<=nlstate;i++)
6178: fprintf(ficresvpl," %.5f (%.5f)",prlim[i][i],sqrt(varpl[i][(int)age]));
6179: fprintf(ficresvpl,"\n");
6180: free_vector(gp,1,nlstate);
6181: free_vector(gm,1,nlstate);
1.208 brouard 6182: free_matrix(mgm,1,npar,1,nlstate);
6183: free_matrix(mgp,1,npar,1,nlstate);
1.126 brouard 6184: free_matrix(gradg,1,npar,1,nlstate);
6185: free_matrix(trgradg,1,nlstate,1,npar);
6186: } /* End age */
6187:
6188: free_vector(xp,1,npar);
6189: free_matrix(doldm,1,nlstate,1,npar);
1.268 brouard 6190: free_matrix(dnewmpar,1,nlstate,1,nlstate);
6191:
6192: }
6193:
6194:
6195: /************ Variance of backprevalence limit ******************/
1.269 brouard 6196: void varbrevlim(char fileresvbl[], FILE *ficresvbl, double **varbpl, double **matcov, double x[], double delti[], int nlstate, int stepm, double bage, double fage, double **oldm, double **savm, double **bprlim, double ftolpl, int mobilavproj, int *ncvyearp, int ij, char strstart[], int nres)
1.268 brouard 6197: {
6198: /* Variance of backward prevalence limit for each state ij using current parameters x[] and estimates of neighbourhood give by delti*/
6199: /* double **prevalim(double **prlim, int nlstate, double *xp, double age, double **oldm, double **savm,double ftolpl);*/
6200:
6201: double **dnewmpar,**doldm;
6202: int i, j, nhstepm, hstepm;
6203: double *xp;
6204: double *gp, *gm;
6205: double **gradg, **trgradg;
6206: double **mgm, **mgp;
6207: double age,agelim;
6208: int theta;
6209:
6210: pstamp(ficresvbl);
6211: fprintf(ficresvbl,"# Standard deviation of back (stable) prevalences \n");
6212: fprintf(ficresvbl,"# Age ");
6213: if(nresult >=1)
6214: fprintf(ficresvbl," Result# ");
6215: for(i=1; i<=nlstate;i++)
6216: fprintf(ficresvbl," %1d-%1d",i,i);
6217: fprintf(ficresvbl,"\n");
6218:
6219: xp=vector(1,npar);
6220: dnewmpar=matrix(1,nlstate,1,npar);
6221: doldm=matrix(1,nlstate,1,nlstate);
6222:
6223: hstepm=1*YEARM; /* Every year of age */
6224: hstepm=hstepm/stepm; /* Typically in stepm units, if j= 2 years, = 2/6 months = 4 */
6225: agelim = AGEINF;
6226: for (age=fage; age>=bage; age --){ /* If stepm=6 months */
6227: nhstepm=(int) rint((age-agelim)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
6228: if (stepm >= YEARM) hstepm=1;
6229: nhstepm = nhstepm/hstepm; /* Typically 40/4=10 */
6230: gradg=matrix(1,npar,1,nlstate);
6231: mgp=matrix(1,npar,1,nlstate);
6232: mgm=matrix(1,npar,1,nlstate);
6233: gp=vector(1,nlstate);
6234: gm=vector(1,nlstate);
6235:
6236: for(theta=1; theta <=npar; theta++){
6237: for(i=1; i<=npar; i++){ /* Computes gradient */
6238: xp[i] = x[i] + (i==theta ?delti[theta]:0);
6239: }
6240: if(mobilavproj > 0 )
6241: bprevalim(bprlim, mobaverage,nlstate,xp,age,ftolpl,ncvyearp,ij,nres);
6242: else
6243: bprevalim(bprlim, mobaverage,nlstate,xp,age,ftolpl,ncvyearp,ij,nres);
6244: for(i=1;i<=nlstate;i++){
6245: gp[i] = bprlim[i][i];
6246: mgp[theta][i] = bprlim[i][i];
6247: }
6248: for(i=1; i<=npar; i++) /* Computes gradient */
6249: xp[i] = x[i] - (i==theta ?delti[theta]:0);
6250: if(mobilavproj > 0 )
6251: bprevalim(bprlim, mobaverage,nlstate,xp,age,ftolpl,ncvyearp,ij,nres);
6252: else
6253: bprevalim(bprlim, mobaverage,nlstate,xp,age,ftolpl,ncvyearp,ij,nres);
6254: for(i=1;i<=nlstate;i++){
6255: gm[i] = bprlim[i][i];
6256: mgm[theta][i] = bprlim[i][i];
6257: }
6258: for(i=1;i<=nlstate;i++)
6259: gradg[theta][i]= (gp[i]-gm[i])/2./delti[theta];
6260: /* gradg[theta][2]= -gradg[theta][1]; */ /* For testing if nlstate=2 */
6261: } /* End theta */
6262:
6263: trgradg =matrix(1,nlstate,1,npar);
6264:
6265: for(j=1; j<=nlstate;j++)
6266: for(theta=1; theta <=npar; theta++)
6267: trgradg[j][theta]=gradg[theta][j];
6268: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
6269: /* printf("\nmgm mgp %d ",(int)age); */
6270: /* for(j=1; j<=nlstate;j++){ */
6271: /* printf(" %d ",j); */
6272: /* for(theta=1; theta <=npar; theta++) */
6273: /* printf(" %d %lf %lf",theta,mgm[theta][j],mgp[theta][j]); */
6274: /* printf("\n "); */
6275: /* } */
6276: /* } */
6277: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
6278: /* printf("\n gradg %d ",(int)age); */
6279: /* for(j=1; j<=nlstate;j++){ */
6280: /* printf("%d ",j); */
6281: /* for(theta=1; theta <=npar; theta++) */
6282: /* printf("%d %lf ",theta,gradg[theta][j]); */
6283: /* printf("\n "); */
6284: /* } */
6285: /* } */
6286:
6287: for(i=1;i<=nlstate;i++)
6288: varbpl[i][(int)age] =0.;
6289: if((int)age==79 ||(int)age== 80 ||(int)age== 81){
6290: matprod2(dnewmpar,trgradg,1,nlstate,1,npar,1,npar,matcov);
6291: matprod2(doldm,dnewmpar,1,nlstate,1,npar,1,nlstate,gradg);
6292: }else{
6293: matprod2(dnewmpar,trgradg,1,nlstate,1,npar,1,npar,matcov);
6294: matprod2(doldm,dnewmpar,1,nlstate,1,npar,1,nlstate,gradg);
6295: }
6296: for(i=1;i<=nlstate;i++)
6297: varbpl[i][(int)age] = doldm[i][i]; /* Covariances are useless */
6298:
6299: fprintf(ficresvbl,"%.0f ",age );
6300: if(nresult >=1)
6301: fprintf(ficresvbl,"%d ",nres );
6302: for(i=1; i<=nlstate;i++)
6303: fprintf(ficresvbl," %.5f (%.5f)",bprlim[i][i],sqrt(varbpl[i][(int)age]));
6304: fprintf(ficresvbl,"\n");
6305: free_vector(gp,1,nlstate);
6306: free_vector(gm,1,nlstate);
6307: free_matrix(mgm,1,npar,1,nlstate);
6308: free_matrix(mgp,1,npar,1,nlstate);
6309: free_matrix(gradg,1,npar,1,nlstate);
6310: free_matrix(trgradg,1,nlstate,1,npar);
6311: } /* End age */
6312:
6313: free_vector(xp,1,npar);
6314: free_matrix(doldm,1,nlstate,1,npar);
6315: free_matrix(dnewmpar,1,nlstate,1,nlstate);
1.126 brouard 6316:
6317: }
6318:
6319: /************ Variance of one-step probabilities ******************/
6320: 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 6321: {
6322: int i, j=0, k1, l1, tj;
6323: int k2, l2, j1, z1;
6324: int k=0, l;
6325: int first=1, first1, first2;
6326: double cv12, mu1, mu2, lc1, lc2, v12, v21, v11, v22,v1,v2, c12, tnalp;
6327: double **dnewm,**doldm;
6328: double *xp;
6329: double *gp, *gm;
6330: double **gradg, **trgradg;
6331: double **mu;
6332: double age, cov[NCOVMAX+1];
6333: double std=2.0; /* Number of standard deviation wide of confidence ellipsoids */
6334: int theta;
6335: char fileresprob[FILENAMELENGTH];
6336: char fileresprobcov[FILENAMELENGTH];
6337: char fileresprobcor[FILENAMELENGTH];
6338: double ***varpij;
6339:
6340: strcpy(fileresprob,"PROB_");
6341: strcat(fileresprob,fileres);
6342: if((ficresprob=fopen(fileresprob,"w"))==NULL) {
6343: printf("Problem with resultfile: %s\n", fileresprob);
6344: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprob);
6345: }
6346: strcpy(fileresprobcov,"PROBCOV_");
6347: strcat(fileresprobcov,fileresu);
6348: if((ficresprobcov=fopen(fileresprobcov,"w"))==NULL) {
6349: printf("Problem with resultfile: %s\n", fileresprobcov);
6350: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprobcov);
6351: }
6352: strcpy(fileresprobcor,"PROBCOR_");
6353: strcat(fileresprobcor,fileresu);
6354: if((ficresprobcor=fopen(fileresprobcor,"w"))==NULL) {
6355: printf("Problem with resultfile: %s\n", fileresprobcor);
6356: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprobcor);
6357: }
6358: printf("Computing standard deviation of one-step probabilities: result on file '%s' \n",fileresprob);
6359: fprintf(ficlog,"Computing standard deviation of one-step probabilities: result on file '%s' \n",fileresprob);
6360: printf("Computing matrix of variance covariance of one-step probabilities: result on file '%s' \n",fileresprobcov);
6361: fprintf(ficlog,"Computing matrix of variance covariance of one-step probabilities: result on file '%s' \n",fileresprobcov);
6362: printf("and correlation matrix of one-step probabilities: result on file '%s' \n",fileresprobcor);
6363: fprintf(ficlog,"and correlation matrix of one-step probabilities: result on file '%s' \n",fileresprobcor);
6364: pstamp(ficresprob);
6365: fprintf(ficresprob,"#One-step probabilities and stand. devi in ()\n");
6366: fprintf(ficresprob,"# Age");
6367: pstamp(ficresprobcov);
6368: fprintf(ficresprobcov,"#One-step probabilities and covariance matrix\n");
6369: fprintf(ficresprobcov,"# Age");
6370: pstamp(ficresprobcor);
6371: fprintf(ficresprobcor,"#One-step probabilities and correlation matrix\n");
6372: fprintf(ficresprobcor,"# Age");
1.126 brouard 6373:
6374:
1.222 brouard 6375: for(i=1; i<=nlstate;i++)
6376: for(j=1; j<=(nlstate+ndeath);j++){
6377: fprintf(ficresprob," p%1d-%1d (SE)",i,j);
6378: fprintf(ficresprobcov," p%1d-%1d ",i,j);
6379: fprintf(ficresprobcor," p%1d-%1d ",i,j);
6380: }
6381: /* fprintf(ficresprob,"\n");
6382: fprintf(ficresprobcov,"\n");
6383: fprintf(ficresprobcor,"\n");
6384: */
6385: xp=vector(1,npar);
6386: dnewm=matrix(1,(nlstate)*(nlstate+ndeath),1,npar);
6387: doldm=matrix(1,(nlstate)*(nlstate+ndeath),1,(nlstate)*(nlstate+ndeath));
6388: mu=matrix(1,(nlstate)*(nlstate+ndeath), (int) bage, (int)fage);
6389: varpij=ma3x(1,nlstate*(nlstate+ndeath),1,nlstate*(nlstate+ndeath),(int) bage, (int) fage);
6390: first=1;
6391: fprintf(ficgp,"\n# Routine varprob");
6392: fprintf(fichtm,"\n<li><h4> Computing and drawing one step probabilities with their confidence intervals</h4></li>\n");
6393: fprintf(fichtm,"\n");
6394:
1.266 brouard 6395: fprintf(fichtm,"\n<li><h4> <a href=\"%s\">Matrix of variance-covariance of one-step probabilities (drawings)</a></h4> this page is important in order to visualize confidence intervals and especially correlation between disability and recovery, or more generally, way in and way back. %s</li>\n",optionfilehtmcov,optionfilehtmcov);
1.222 brouard 6396: 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);
6397: fprintf(fichtmcov,"\nEllipsoids of confidence centered on point (p<inf>ij</inf>, p<inf>kl</inf>) are estimated \
1.126 brouard 6398: and drawn. It helps understanding how is the covariance between two incidences.\
6399: They are expressed in year<sup>-1</sup> in order to be less dependent of stepm.<br>\n");
1.222 brouard 6400: 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 6401: It can be understood this way: if pij and pkl where uncorrelated the (2x2) matrix of covariance \
6402: would have been (1/(var pij), 0 , 0, 1/(var pkl)), and the confidence interval would be 2 \
6403: standard deviations wide on each axis. <br>\
6404: Now, if both incidences are correlated (usual case) we diagonalised the inverse of the covariance matrix\
6405: and made the appropriate rotation to look at the uncorrelated principal directions.<br>\
6406: To be simple, these graphs help to understand the significativity of each parameter in relation to a second other one.<br> \n");
6407:
1.222 brouard 6408: cov[1]=1;
6409: /* tj=cptcoveff; */
1.225 brouard 6410: tj = (int) pow(2,cptcoveff);
1.222 brouard 6411: if (cptcovn<1) {tj=1;ncodemax[1]=1;}
6412: j1=0;
1.224 brouard 6413: for(j1=1; j1<=tj;j1++){ /* For each valid combination of covariates or only once*/
1.222 brouard 6414: if (cptcovn>0) {
6415: fprintf(ficresprob, "\n#********** Variable ");
1.225 brouard 6416: for (z1=1; z1<=cptcoveff; z1++) fprintf(ficresprob, "V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
1.222 brouard 6417: fprintf(ficresprob, "**********\n#\n");
6418: fprintf(ficresprobcov, "\n#********** Variable ");
1.225 brouard 6419: for (z1=1; z1<=cptcoveff; z1++) fprintf(ficresprobcov, "V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
1.222 brouard 6420: fprintf(ficresprobcov, "**********\n#\n");
1.220 brouard 6421:
1.222 brouard 6422: fprintf(ficgp, "\n#********** Variable ");
1.225 brouard 6423: for (z1=1; z1<=cptcoveff; z1++) fprintf(ficgp, " V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
1.222 brouard 6424: fprintf(ficgp, "**********\n#\n");
1.220 brouard 6425:
6426:
1.222 brouard 6427: fprintf(fichtmcov, "\n<hr size=\"2\" color=\"#EC5E5E\">********** Variable ");
1.225 brouard 6428: for (z1=1; z1<=cptcoveff; z1++) fprintf(fichtm, "V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
1.222 brouard 6429: fprintf(fichtmcov, "**********\n<hr size=\"2\" color=\"#EC5E5E\">");
1.220 brouard 6430:
1.222 brouard 6431: fprintf(ficresprobcor, "\n#********** Variable ");
1.225 brouard 6432: for (z1=1; z1<=cptcoveff; z1++) fprintf(ficresprobcor, "V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
1.222 brouard 6433: fprintf(ficresprobcor, "**********\n#");
6434: if(invalidvarcomb[j1]){
6435: fprintf(ficgp,"\n#Combination (%d) ignored because no cases \n",j1);
6436: fprintf(fichtmcov,"\n<h3>Combination (%d) ignored because no cases </h3>\n",j1);
6437: continue;
6438: }
6439: }
6440: gradg=matrix(1,npar,1,(nlstate)*(nlstate+ndeath));
6441: trgradg=matrix(1,(nlstate)*(nlstate+ndeath),1,npar);
6442: gp=vector(1,(nlstate)*(nlstate+ndeath));
6443: gm=vector(1,(nlstate)*(nlstate+ndeath));
6444: for (age=bage; age<=fage; age ++){
6445: cov[2]=age;
6446: if(nagesqr==1)
6447: cov[3]= age*age;
6448: for (k=1; k<=cptcovn;k++) {
6449: cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(j1,k)];
6450: /*cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(j1,Tvar[k])];*//* j1 1 2 3 4
6451: * 1 1 1 1 1
6452: * 2 2 1 1 1
6453: * 3 1 2 1 1
6454: */
6455: /* nbcode[1][1]=0 nbcode[1][2]=1;*/
6456: }
6457: /* for (k=1; k<=cptcovage;k++) cov[2+Tage[k]]=cov[2+Tage[k]]*cov[2]; */
6458: for (k=1; k<=cptcovage;k++) cov[2+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2];
6459: for (k=1; k<=cptcovprod;k++)
6460: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)]*nbcode[Tvard[k][2]][codtabm(ij,k)];
1.220 brouard 6461:
6462:
1.222 brouard 6463: for(theta=1; theta <=npar; theta++){
6464: for(i=1; i<=npar; i++)
6465: xp[i] = x[i] + (i==theta ?delti[theta]:(double)0);
1.220 brouard 6466:
1.222 brouard 6467: pmij(pmmij,cov,ncovmodel,xp,nlstate);
1.220 brouard 6468:
1.222 brouard 6469: k=0;
6470: for(i=1; i<= (nlstate); i++){
6471: for(j=1; j<=(nlstate+ndeath);j++){
6472: k=k+1;
6473: gp[k]=pmmij[i][j];
6474: }
6475: }
1.220 brouard 6476:
1.222 brouard 6477: for(i=1; i<=npar; i++)
6478: xp[i] = x[i] - (i==theta ?delti[theta]:(double)0);
1.220 brouard 6479:
1.222 brouard 6480: pmij(pmmij,cov,ncovmodel,xp,nlstate);
6481: k=0;
6482: for(i=1; i<=(nlstate); i++){
6483: for(j=1; j<=(nlstate+ndeath);j++){
6484: k=k+1;
6485: gm[k]=pmmij[i][j];
6486: }
6487: }
1.220 brouard 6488:
1.222 brouard 6489: for(i=1; i<= (nlstate)*(nlstate+ndeath); i++)
6490: gradg[theta][i]=(gp[i]-gm[i])/(double)2./delti[theta];
6491: }
1.126 brouard 6492:
1.222 brouard 6493: for(j=1; j<=(nlstate)*(nlstate+ndeath);j++)
6494: for(theta=1; theta <=npar; theta++)
6495: trgradg[j][theta]=gradg[theta][j];
1.220 brouard 6496:
1.222 brouard 6497: matprod2(dnewm,trgradg,1,(nlstate)*(nlstate+ndeath),1,npar,1,npar,matcov);
6498: matprod2(doldm,dnewm,1,(nlstate)*(nlstate+ndeath),1,npar,1,(nlstate)*(nlstate+ndeath),gradg);
1.220 brouard 6499:
1.222 brouard 6500: pmij(pmmij,cov,ncovmodel,x,nlstate);
1.220 brouard 6501:
1.222 brouard 6502: k=0;
6503: for(i=1; i<=(nlstate); i++){
6504: for(j=1; j<=(nlstate+ndeath);j++){
6505: k=k+1;
6506: mu[k][(int) age]=pmmij[i][j];
6507: }
6508: }
6509: for(i=1;i<=(nlstate)*(nlstate+ndeath);i++)
6510: for(j=1;j<=(nlstate)*(nlstate+ndeath);j++)
6511: varpij[i][j][(int)age] = doldm[i][j];
1.220 brouard 6512:
1.222 brouard 6513: /*printf("\n%d ",(int)age);
6514: for (i=1; i<=(nlstate)*(nlstate+ndeath);i++){
6515: printf("%e [%e ;%e] ",gm[i],gm[i]-2*sqrt(doldm[i][i]),gm[i]+2*sqrt(doldm[i][i]));
6516: fprintf(ficlog,"%e [%e ;%e] ",gm[i],gm[i]-2*sqrt(doldm[i][i]),gm[i]+2*sqrt(doldm[i][i]));
6517: }*/
1.220 brouard 6518:
1.222 brouard 6519: fprintf(ficresprob,"\n%d ",(int)age);
6520: fprintf(ficresprobcov,"\n%d ",(int)age);
6521: fprintf(ficresprobcor,"\n%d ",(int)age);
1.220 brouard 6522:
1.222 brouard 6523: for (i=1; i<=(nlstate)*(nlstate+ndeath);i++)
6524: fprintf(ficresprob,"%11.3e (%11.3e) ",mu[i][(int) age],sqrt(varpij[i][i][(int)age]));
6525: for (i=1; i<=(nlstate)*(nlstate+ndeath);i++){
6526: fprintf(ficresprobcov,"%11.3e ",mu[i][(int) age]);
6527: fprintf(ficresprobcor,"%11.3e ",mu[i][(int) age]);
6528: }
6529: i=0;
6530: for (k=1; k<=(nlstate);k++){
6531: for (l=1; l<=(nlstate+ndeath);l++){
6532: i++;
6533: fprintf(ficresprobcov,"\n%d %d-%d",(int)age,k,l);
6534: fprintf(ficresprobcor,"\n%d %d-%d",(int)age,k,l);
6535: for (j=1; j<=i;j++){
6536: /* printf(" k=%d l=%d i=%d j=%d\n",k,l,i,j);fflush(stdout); */
6537: fprintf(ficresprobcov," %11.3e",varpij[i][j][(int)age]);
6538: fprintf(ficresprobcor," %11.3e",varpij[i][j][(int) age]/sqrt(varpij[i][i][(int) age])/sqrt(varpij[j][j][(int)age]));
6539: }
6540: }
6541: }/* end of loop for state */
6542: } /* end of loop for age */
6543: free_vector(gp,1,(nlstate+ndeath)*(nlstate+ndeath));
6544: free_vector(gm,1,(nlstate+ndeath)*(nlstate+ndeath));
6545: free_matrix(trgradg,1,(nlstate+ndeath)*(nlstate+ndeath),1,npar);
6546: free_matrix(gradg,1,(nlstate+ndeath)*(nlstate+ndeath),1,npar);
6547:
6548: /* Confidence intervalle of pij */
6549: /*
6550: fprintf(ficgp,"\nunset parametric;unset label");
6551: fprintf(ficgp,"\nset log y;unset log x; set xlabel \"Age\";set ylabel \"probability (year-1)\"");
6552: fprintf(ficgp,"\nset ter png small\nset size 0.65,0.65");
6553: 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);
6554: fprintf(fichtm,"\n<br><img src=\"pijgr%s.png\"> ",optionfilefiname);
6555: fprintf(ficgp,"\nset out \"pijgr%s.png\"",optionfilefiname);
6556: fprintf(ficgp,"\nplot \"%s\" every :::%d::%d u 1:2 \"\%%lf",k1,k2,xfilevarprob);
6557: */
6558:
6559: /* Drawing ellipsoids of confidence of two variables p(k1-l1,k2-l2)*/
6560: first1=1;first2=2;
6561: for (k2=1; k2<=(nlstate);k2++){
6562: for (l2=1; l2<=(nlstate+ndeath);l2++){
6563: if(l2==k2) continue;
6564: j=(k2-1)*(nlstate+ndeath)+l2;
6565: for (k1=1; k1<=(nlstate);k1++){
6566: for (l1=1; l1<=(nlstate+ndeath);l1++){
6567: if(l1==k1) continue;
6568: i=(k1-1)*(nlstate+ndeath)+l1;
6569: if(i<=j) continue;
6570: for (age=bage; age<=fage; age ++){
6571: if ((int)age %5==0){
6572: v1=varpij[i][i][(int)age]/stepm*YEARM/stepm*YEARM;
6573: v2=varpij[j][j][(int)age]/stepm*YEARM/stepm*YEARM;
6574: cv12=varpij[i][j][(int)age]/stepm*YEARM/stepm*YEARM;
6575: mu1=mu[i][(int) age]/stepm*YEARM ;
6576: mu2=mu[j][(int) age]/stepm*YEARM;
6577: c12=cv12/sqrt(v1*v2);
6578: /* Computing eigen value of matrix of covariance */
6579: lc1=((v1+v2)+sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
6580: lc2=((v1+v2)-sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
6581: if ((lc2 <0) || (lc1 <0) ){
6582: if(first2==1){
6583: first1=0;
6584: 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);
6585: }
6586: 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);
6587: /* lc1=fabs(lc1); */ /* If we want to have them positive */
6588: /* lc2=fabs(lc2); */
6589: }
1.220 brouard 6590:
1.222 brouard 6591: /* Eigen vectors */
6592: v11=(1./sqrt(1+(v1-lc1)*(v1-lc1)/cv12/cv12));
6593: /*v21=sqrt(1.-v11*v11); *//* error */
6594: v21=(lc1-v1)/cv12*v11;
6595: v12=-v21;
6596: v22=v11;
6597: tnalp=v21/v11;
6598: if(first1==1){
6599: first1=0;
6600: 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);
6601: }
6602: 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);
6603: /*printf(fignu*/
6604: /* mu1+ v11*lc1*cost + v12*lc2*sin(t) */
6605: /* mu2+ v21*lc1*cost + v22*lc2*sin(t) */
6606: if(first==1){
6607: first=0;
6608: fprintf(ficgp,"\n# Ellipsoids of confidence\n#\n");
6609: fprintf(ficgp,"\nset parametric;unset label");
6610: 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);
6611: fprintf(ficgp,"\nset ter svg size 640, 480");
1.266 brouard 6612: fprintf(fichtmcov,"\n<p><br>Ellipsoids of confidence cov(p%1d%1d,p%1d%1d) expressed in year<sup>-1</sup>\
1.220 brouard 6613: :<a href=\"%s_%d%1d%1d-%1d%1d.svg\"> \
1.201 brouard 6614: %s_%d%1d%1d-%1d%1d.svg</A>, ",k1,l1,k2,l2,\
1.222 brouard 6615: subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2, \
6616: subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
6617: fprintf(fichtmcov,"\n<br><img src=\"%s_%d%1d%1d-%1d%1d.svg\"> ",subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
6618: fprintf(fichtmcov,"\n<br> Correlation at age %d (%.3f),",(int) age, c12);
6619: fprintf(ficgp,"\nset out \"%s_%d%1d%1d-%1d%1d.svg\"",subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
6620: fprintf(ficgp,"\nset label \"%d\" at %11.3e,%11.3e center",(int) age, mu1,mu2);
6621: fprintf(ficgp,"\n# Age %d, p%1d%1d - p%1d%1d",(int) age, k1,l1,k2,l2);
6622: fprintf(ficgp,"\nplot [-pi:pi] %11.3e+ %.3f*(%11.3e*%11.3e*cos(t)+%11.3e*%11.3e*sin(t)), %11.3e +%.3f*(%11.3e*%11.3e*cos(t)+%11.3e*%11.3e*sin(t)) not", \
1.266 brouard 6623: mu1,std,v11,sqrt(lc1),v12,sqrt(fabs(lc2)), \
6624: mu2,std,v21,sqrt(lc1),v22,sqrt(fabs(lc2))); /* For gnuplot only */
1.222 brouard 6625: }else{
6626: first=0;
6627: fprintf(fichtmcov," %d (%.3f),",(int) age, c12);
6628: fprintf(ficgp,"\n# Age %d, p%1d%1d - p%1d%1d",(int) age, k1,l1,k2,l2);
6629: fprintf(ficgp,"\nset label \"%d\" at %11.3e,%11.3e center",(int) age, mu1,mu2);
6630: fprintf(ficgp,"\nreplot %11.3e+ %.3f*(%11.3e*%11.3e*cos(t)+%11.3e*%11.3e*sin(t)), %11.3e +%.3f*(%11.3e*%11.3e*cos(t)+%11.3e*%11.3e*sin(t)) not", \
1.266 brouard 6631: mu1,std,v11,sqrt(lc1),v12,sqrt(fabs(lc2)), \
6632: mu2,std,v21,sqrt(lc1),v22,sqrt(fabs(lc2)));
1.222 brouard 6633: }/* if first */
6634: } /* age mod 5 */
6635: } /* end loop age */
6636: fprintf(ficgp,"\nset out;\nset out \"%s_%d%1d%1d-%1d%1d.svg\";replot;set out;",subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
6637: first=1;
6638: } /*l12 */
6639: } /* k12 */
6640: } /*l1 */
6641: }/* k1 */
6642: } /* loop on combination of covariates j1 */
6643: free_ma3x(varpij,1,nlstate,1,nlstate+ndeath,(int) bage, (int)fage);
6644: free_matrix(mu,1,(nlstate+ndeath)*(nlstate+ndeath),(int) bage, (int)fage);
6645: free_matrix(doldm,1,(nlstate)*(nlstate+ndeath),1,(nlstate)*(nlstate+ndeath));
6646: free_matrix(dnewm,1,(nlstate)*(nlstate+ndeath),1,npar);
6647: free_vector(xp,1,npar);
6648: fclose(ficresprob);
6649: fclose(ficresprobcov);
6650: fclose(ficresprobcor);
6651: fflush(ficgp);
6652: fflush(fichtmcov);
6653: }
1.126 brouard 6654:
6655:
6656: /******************* Printing html file ***********/
1.201 brouard 6657: void printinghtml(char fileresu[], char title[], char datafile[], int firstpass, \
1.126 brouard 6658: int lastpass, int stepm, int weightopt, char model[],\
6659: int imx,int jmin, int jmax, double jmeanint,char rfileres[],\
1.258 brouard 6660: int popforecast, int mobilav, int prevfcast, int mobilavproj, int backcast, int estepm , \
1.213 brouard 6661: double jprev1, double mprev1,double anprev1, double dateprev1, \
6662: double jprev2, double mprev2,double anprev2, double dateprev2){
1.237 brouard 6663: int jj1, k1, i1, cpt, k4, nres;
1.126 brouard 6664:
6665: fprintf(fichtm,"<ul><li><a href='#firstorder'>Result files (first order: no variance)</a>\n \
6666: <li><a href='#secondorder'>Result files (second order (variance)</a>\n \
6667: </ul>");
1.237 brouard 6668: fprintf(fichtm,"<ul><li> model=1+age+%s\n \
6669: </ul>", model);
1.214 brouard 6670: fprintf(fichtm,"<ul><li><h4><a name='firstorder'>Result files (first order: no variance)</a></h4>\n");
6671: 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",
6672: jprev1, mprev1,anprev1,jprev2, mprev2,anprev2,subdirfext3(optionfilefiname,"PHTMFR_",".htm"),subdirfext3(optionfilefiname,"PHTMFR_",".htm"));
6673: 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 6674: jprev1, mprev1,anprev1,jprev2, mprev2,anprev2,subdirfext3(optionfilefiname,"PHTM_",".htm"),subdirfext3(optionfilefiname,"PHTM_",".htm"));
6675: fprintf(fichtm,", <a href=\"%s\">%s</a> (text file) <br>\n",subdirf2(fileresu,"P_"),subdirf2(fileresu,"P_"));
1.126 brouard 6676: fprintf(fichtm,"\
6677: - Estimated transition probabilities over %d (stepm) months: <a href=\"%s\">%s</a><br>\n ",
1.201 brouard 6678: stepm,subdirf2(fileresu,"PIJ_"),subdirf2(fileresu,"PIJ_"));
1.126 brouard 6679: fprintf(fichtm,"\
1.217 brouard 6680: - Estimated back transition probabilities over %d (stepm) months: <a href=\"%s\">%s</a><br>\n ",
6681: stepm,subdirf2(fileresu,"PIJB_"),subdirf2(fileresu,"PIJB_"));
6682: fprintf(fichtm,"\
1.126 brouard 6683: - Period (stable) prevalence in each health state: <a href=\"%s\">%s</a> <br>\n",
1.201 brouard 6684: subdirf2(fileresu,"PL_"),subdirf2(fileresu,"PL_"));
1.126 brouard 6685: fprintf(fichtm,"\
1.217 brouard 6686: - Period (stable) back prevalence in each health state: <a href=\"%s\">%s</a> <br>\n",
6687: subdirf2(fileresu,"PLB_"),subdirf2(fileresu,"PLB_"));
6688: fprintf(fichtm,"\
1.211 brouard 6689: - (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 6690: <a href=\"%s\">%s</a> <br>\n",
1.201 brouard 6691: estepm,subdirf2(fileresu,"E_"),subdirf2(fileresu,"E_"));
1.211 brouard 6692: if(prevfcast==1){
6693: fprintf(fichtm,"\
6694: - Prevalence projections by age and states: \
1.201 brouard 6695: <a href=\"%s\">%s</a> <br>\n</li>", subdirf2(fileresu,"F_"),subdirf2(fileresu,"F_"));
1.211 brouard 6696: }
1.126 brouard 6697:
6698:
1.225 brouard 6699: m=pow(2,cptcoveff);
1.222 brouard 6700: if (cptcovn < 1) {m=1;ncodemax[1]=1;}
1.126 brouard 6701:
1.264 brouard 6702: fprintf(fichtm," \n<ul><li><b>Graphs</b></li><p>");
6703:
6704: jj1=0;
6705:
6706: fprintf(fichtm," \n<ul>");
6707: for(nres=1; nres <= nresult; nres++) /* For each resultline */
6708: for(k1=1; k1<=m;k1++){ /* For each combination of covariate */
6709: if(m != 1 && TKresult[nres]!= k1)
6710: continue;
6711: jj1++;
6712: if (cptcovn > 0) {
6713: fprintf(fichtm,"\n<li><a size=\"1\" color=\"#EC5E5E\" href=\"#rescov");
6714: for (cpt=1; cpt<=cptcoveff;cpt++){
6715: fprintf(fichtm,"_V%d=%d_",Tvresult[nres][cpt],(int)Tresult[nres][cpt]);
6716: }
6717: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
6718: fprintf(fichtm,"_V%d=%f_",Tvqresult[nres][k4],Tqresult[nres][k4]);
6719: }
6720: fprintf(fichtm,"\">");
6721:
6722: /* if(nqfveff+nqtveff 0) */ /* Test to be done */
6723: fprintf(fichtm,"************ Results for covariates");
6724: for (cpt=1; cpt<=cptcoveff;cpt++){
6725: fprintf(fichtm," V%d=%d ",Tvresult[nres][cpt],(int)Tresult[nres][cpt]);
6726: }
6727: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
6728: fprintf(fichtm," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
6729: }
6730: if(invalidvarcomb[k1]){
6731: fprintf(fichtm," Warning Combination (%d) ignored because no cases ",k1);
6732: continue;
6733: }
6734: fprintf(fichtm,"</a></li>");
6735: } /* cptcovn >0 */
6736: }
6737: fprintf(fichtm," \n</ul>");
6738:
1.222 brouard 6739: jj1=0;
1.237 brouard 6740:
6741: for(nres=1; nres <= nresult; nres++) /* For each resultline */
1.241 brouard 6742: for(k1=1; k1<=m;k1++){ /* For each combination of covariate */
1.253 brouard 6743: if(m != 1 && TKresult[nres]!= k1)
1.237 brouard 6744: continue;
1.220 brouard 6745:
1.222 brouard 6746: /* for(i1=1; i1<=ncodemax[k1];i1++){ */
6747: jj1++;
6748: if (cptcovn > 0) {
1.264 brouard 6749: fprintf(fichtm,"\n<p><a name=\"rescov");
6750: for (cpt=1; cpt<=cptcoveff;cpt++){
6751: fprintf(fichtm,"_V%d=%d_",Tvresult[nres][cpt],(int)Tresult[nres][cpt]);
6752: }
6753: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
6754: fprintf(fichtm,"_V%d=%f_",Tvqresult[nres][k4],Tqresult[nres][k4]);
6755: }
6756: fprintf(fichtm,"\"</a>");
6757:
1.222 brouard 6758: fprintf(fichtm,"<hr size=\"2\" color=\"#EC5E5E\">************ Results for covariates");
1.225 brouard 6759: for (cpt=1; cpt<=cptcoveff;cpt++){
1.237 brouard 6760: fprintf(fichtm," V%d=%d ",Tvresult[nres][cpt],(int)Tresult[nres][cpt]);
6761: printf(" V%d=%d ",Tvresult[nres][cpt],Tresult[nres][cpt]);fflush(stdout);
6762: /* fprintf(fichtm," V%d=%d ",Tvaraff[cpt],nbcode[Tvaraff[cpt]][codtabm(jj1,cpt)]); */
6763: /* printf(" V%d=%d ",Tvaraff[cpt],nbcode[Tvaraff[cpt]][codtabm(jj1,cpt)]);fflush(stdout); */
1.222 brouard 6764: }
1.237 brouard 6765: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
6766: fprintf(fichtm," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
6767: printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);fflush(stdout);
6768: }
6769:
1.230 brouard 6770: /* if(nqfveff+nqtveff 0) */ /* Test to be done */
1.222 brouard 6771: fprintf(fichtm," ************\n<hr size=\"2\" color=\"#EC5E5E\">");
6772: if(invalidvarcomb[k1]){
6773: fprintf(fichtm,"\n<h3>Combination (%d) ignored because no cases </h3>\n",k1);
6774: printf("\nCombination (%d) ignored because no cases \n",k1);
6775: continue;
6776: }
6777: }
6778: /* aij, bij */
1.259 brouard 6779: 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 6780: <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 6781: /* Pij */
1.241 brouard 6782: 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> \
6783: <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 6784: /* Quasi-incidences */
6785: 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 6786: before but expressed in per year i.e. quasi incidences if stepm is small and probabilities too, \
1.211 brouard 6787: 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 6788: 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> \
6789: <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 6790: /* Survival functions (period) in state j */
6791: for(cpt=1; cpt<=nlstate;cpt++){
1.241 brouard 6792: 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> \
6793: <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 6794: }
6795: /* State specific survival functions (period) */
6796: for(cpt=1; cpt<=nlstate;cpt++){
6797: fprintf(fichtm,"<br>\n- Survival functions from state %d in each live state and total.\
1.220 brouard 6798: Or probability to survive in various states (1 to %d) being in state %d at different ages. \
1.241 brouard 6799: <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 6800: }
6801: /* Period (stable) prevalence in each health state */
6802: for(cpt=1; cpt<=nlstate;cpt++){
1.264 brouard 6803: 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> \
6804: <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 6805: }
6806: if(backcast==1){
6807: /* Period (stable) back prevalence in each health state */
6808: for(cpt=1; cpt<=nlstate;cpt++){
1.264 brouard 6809: 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 6810: <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 6811: }
1.217 brouard 6812: }
1.222 brouard 6813: if(prevfcast==1){
6814: /* Projection of prevalence up to period (stable) prevalence in each health state */
6815: for(cpt=1; cpt<=nlstate;cpt++){
1.268 brouard 6816: 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 an observed weighted state (from 1 to %d). <a href=\"%s_%d-%d-%d.svg\">%s_%d-%d-%d.svg</a><br> \
1.258 brouard 6817: <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 6818: }
6819: }
1.268 brouard 6820: if(backcast==1){
6821: /* Back projection of prevalence up to stable (mixed) back-prevalence in each health state */
6822: for(cpt=1; cpt<=nlstate;cpt++){
6823: fprintf(fichtm,"<br>\n- Back projection of cross-sectional prevalence (estimated with cases observed from %.1f to %.1f and mobil_average=%d) up to stable (mixed) back prevalence in state %d. Or probability to have been in an state %d, knowing that the person was in either state (1 or %d) with weights corresponding to observed prevalence at different ages. <a href=\"%s_%d-%d-%d.svg\">%s_%d-%d-%d.svg</a><br> \
6824: <img src=\"%s_%d-%d-%d.svg\">", dateprev1, dateprev2, mobilavproj, cpt, cpt, nlstate, subdirf2(optionfilefiname,"PROJB_"),cpt,k1,nres,subdirf2(optionfilefiname,"PROJB_"),cpt,k1,nres,subdirf2(optionfilefiname,"PROJB_"),cpt,k1,nres);
6825: }
6826: }
1.220 brouard 6827:
1.222 brouard 6828: for(cpt=1; cpt<=nlstate;cpt++) {
1.241 brouard 6829: 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> \
6830: <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 6831: }
6832: /* } /\* end i1 *\/ */
6833: }/* End k1 */
6834: fprintf(fichtm,"</ul>");
1.126 brouard 6835:
1.222 brouard 6836: fprintf(fichtm,"\
1.126 brouard 6837: \n<br><li><h4> <a name='secondorder'>Result files (second order: variances)</a></h4>\n\
1.193 brouard 6838: - Parameter file with estimated parameters and covariance matrix: <a href=\"%s\">%s</a> <br> \
1.203 brouard 6839: - 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 6840: But because parameters are usually highly correlated (a higher incidence of disability \
6841: and a higher incidence of recovery can give very close observed transition) it might \
6842: be very useful to look not only at linear confidence intervals estimated from the \
6843: variances but at the covariance matrix. And instead of looking at the estimated coefficients \
6844: (parameters) of the logistic regression, it might be more meaningful to visualize the \
6845: covariance matrix of the one-step probabilities. \
6846: See page 'Matrix of variance-covariance of one-step probabilities' below. \n", rfileres,rfileres);
1.126 brouard 6847:
1.222 brouard 6848: fprintf(fichtm," - Standard deviation of one-step probabilities: <a href=\"%s\">%s</a> <br>\n",
6849: subdirf2(fileresu,"PROB_"),subdirf2(fileresu,"PROB_"));
6850: fprintf(fichtm,"\
1.126 brouard 6851: - Variance-covariance of one-step probabilities: <a href=\"%s\">%s</a> <br>\n",
1.222 brouard 6852: subdirf2(fileresu,"PROBCOV_"),subdirf2(fileresu,"PROBCOV_"));
1.126 brouard 6853:
1.222 brouard 6854: fprintf(fichtm,"\
1.126 brouard 6855: - Correlation matrix of one-step probabilities: <a href=\"%s\">%s</a> <br>\n",
1.222 brouard 6856: subdirf2(fileresu,"PROBCOR_"),subdirf2(fileresu,"PROBCOR_"));
6857: fprintf(fichtm,"\
1.126 brouard 6858: - 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): \
6859: <a href=\"%s\">%s</a> <br>\n</li>",
1.201 brouard 6860: estepm,subdirf2(fileresu,"CVE_"),subdirf2(fileresu,"CVE_"));
1.222 brouard 6861: fprintf(fichtm,"\
1.126 brouard 6862: - (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): \
6863: <a href=\"%s\">%s</a> <br>\n</li>",
1.201 brouard 6864: estepm,subdirf2(fileresu,"STDE_"),subdirf2(fileresu,"STDE_"));
1.222 brouard 6865: fprintf(fichtm,"\
1.128 brouard 6866: - 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 6867: estepm, subdirf2(fileresu,"V_"),subdirf2(fileresu,"V_"));
6868: fprintf(fichtm,"\
1.128 brouard 6869: - 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 6870: estepm, subdirf2(fileresu,"T_"),subdirf2(fileresu,"T_"));
6871: fprintf(fichtm,"\
1.126 brouard 6872: - Standard deviation of period (stable) prevalences: <a href=\"%s\">%s</a> <br>\n",\
1.222 brouard 6873: subdirf2(fileresu,"VPL_"),subdirf2(fileresu,"VPL_"));
1.126 brouard 6874:
6875: /* if(popforecast==1) fprintf(fichtm,"\n */
6876: /* - Prevalences forecasting: <a href=\"f%s\">f%s</a> <br>\n */
6877: /* - Population forecasting (if popforecast=1): <a href=\"pop%s\">pop%s</a> <br>\n */
6878: /* <br>",fileres,fileres,fileres,fileres); */
6879: /* else */
6880: /* 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 6881: fflush(fichtm);
6882: fprintf(fichtm," <ul><li><b>Graphs</b></li><p>");
1.126 brouard 6883:
1.225 brouard 6884: m=pow(2,cptcoveff);
1.222 brouard 6885: if (cptcovn < 1) {m=1;ncodemax[1]=1;}
1.126 brouard 6886:
1.222 brouard 6887: jj1=0;
1.237 brouard 6888:
1.241 brouard 6889: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.222 brouard 6890: for(k1=1; k1<=m;k1++){
1.253 brouard 6891: if(m != 1 && TKresult[nres]!= k1)
1.237 brouard 6892: continue;
1.222 brouard 6893: /* for(i1=1; i1<=ncodemax[k1];i1++){ */
6894: jj1++;
1.126 brouard 6895: if (cptcovn > 0) {
6896: fprintf(fichtm,"<hr size=\"2\" color=\"#EC5E5E\">************ Results for covariates");
1.225 brouard 6897: for (cpt=1; cpt<=cptcoveff;cpt++) /**< cptcoveff number of variables */
1.237 brouard 6898: fprintf(fichtm," V%d=%d ",Tvresult[nres][cpt],Tresult[nres][cpt]);
6899: /* fprintf(fichtm," V%d=%d ",Tvaraff[cpt],nbcode[Tvaraff[cpt]][codtabm(jj1,cpt)]); */
6900: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
6901: fprintf(fichtm," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
6902: }
6903:
1.126 brouard 6904: fprintf(fichtm," ************\n<hr size=\"2\" color=\"#EC5E5E\">");
1.220 brouard 6905:
1.222 brouard 6906: if(invalidvarcomb[k1]){
6907: fprintf(fichtm,"\n<h4>Combination (%d) ignored because no cases </h4>\n",k1);
6908: continue;
6909: }
1.126 brouard 6910: }
6911: for(cpt=1; cpt<=nlstate;cpt++) {
1.258 brouard 6912: fprintf(fichtm,"\n<br>- Observed (cross-sectional with mov_average=%d) and period (incidence based) \
1.241 brouard 6913: 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 6914: <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 6915: }
6916: fprintf(fichtm,"\n<br>- Total life expectancy by age and \
1.128 brouard 6917: health expectancies in states (1) and (2). If popbased=1 the smooth (due to the model) \
6918: true period expectancies (those weighted with period prevalences are also\
6919: drawn in addition to the population based expectancies computed using\
1.241 brouard 6920: observed and cahotic prevalences: <a href=\"%s_%d-%d.svg\">%s_%d-%d.svg</a>\n<br>\
6921: <img src=\"%s_%d-%d.svg\">",subdirf2(optionfilefiname,"E_"),k1,nres,subdirf2(optionfilefiname,"E_"),k1,nres,subdirf2(optionfilefiname,"E_"),k1,nres);
1.222 brouard 6922: /* } /\* end i1 *\/ */
6923: }/* End k1 */
1.241 brouard 6924: }/* End nres */
1.222 brouard 6925: fprintf(fichtm,"</ul>");
6926: fflush(fichtm);
1.126 brouard 6927: }
6928:
6929: /******************* Gnuplot file **************/
1.270 brouard 6930: void printinggnuplot(char fileresu[], char optionfilefiname[], double ageminpar, double agemaxpar, double bage, double fage , int prevfcast, int backcast, char pathc[], double p[], int offyear, int offbyear){
1.126 brouard 6931:
6932: char dirfileres[132],optfileres[132];
1.264 brouard 6933: char gplotcondition[132], gplotlabel[132];
1.237 brouard 6934: 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 6935: int lv=0, vlv=0, kl=0;
1.130 brouard 6936: int ng=0;
1.201 brouard 6937: int vpopbased;
1.223 brouard 6938: int ioffset; /* variable offset for columns */
1.270 brouard 6939: int iyearc=1; /* variable column for year of projection */
6940: int iagec=1; /* variable column for age of projection */
1.235 brouard 6941: int nres=0; /* Index of resultline */
1.266 brouard 6942: int istart=1; /* For starting graphs in projections */
1.219 brouard 6943:
1.126 brouard 6944: /* if((ficgp=fopen(optionfilegnuplot,"a"))==NULL) { */
6945: /* printf("Problem with file %s",optionfilegnuplot); */
6946: /* fprintf(ficlog,"Problem with file %s",optionfilegnuplot); */
6947: /* } */
6948:
6949: /*#ifdef windows */
6950: fprintf(ficgp,"cd \"%s\" \n",pathc);
1.223 brouard 6951: /*#endif */
1.225 brouard 6952: m=pow(2,cptcoveff);
1.126 brouard 6953:
1.202 brouard 6954: /* Contribution to likelihood */
6955: /* Plot the probability implied in the likelihood */
1.223 brouard 6956: fprintf(ficgp,"\n# Contributions to the Likelihood, mle >=1. For mle=4 no interpolation, pure matrix products.\n#\n");
6957: fprintf(ficgp,"\n set log y; unset log x;set xlabel \"Age\"; set ylabel \"Likelihood (-2Log(L))\";");
6958: /* fprintf(ficgp,"\nset ter svg size 640, 480"); */ /* Too big for svg */
6959: fprintf(ficgp,"\nset ter pngcairo size 640, 480");
1.204 brouard 6960: /* nice for mle=4 plot by number of matrix products.
1.202 brouard 6961: replot "rrtest1/toto.txt" u 2:($4 == 1 && $5==2 ? $9 : 1/0):5 t "p12" with point lc 1 */
6962: /* replot exp(p1+p2*x)/(1+exp(p1+p2*x)+exp(p3+p4*x)+exp(p5+p6*x)) t "p12(x)" */
1.223 brouard 6963: /* fprintf(ficgp,"\nset out \"%s.svg\";",subdirf2(optionfilefiname,"ILK_")); */
6964: fprintf(ficgp,"\nset out \"%s-dest.png\";",subdirf2(optionfilefiname,"ILK_"));
6965: 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));
6966: fprintf(ficgp,"\nset out \"%s-ori.png\";",subdirf2(optionfilefiname,"ILK_"));
6967: 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));
6968: for (i=1; i<= nlstate ; i ++) {
6969: fprintf(ficgp,"\nset out \"%s-p%dj.png\";set ylabel \"Probability for each individual/wave\";",subdirf2(optionfilefiname,"ILK_"),i);
6970: fprintf(ficgp,"unset log;\n# plot weighted, mean weight should have point size of 0.5\n plot \"%s\"",subdirf(fileresilk));
6971: 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);
6972: for (j=2; j<= nlstate+ndeath ; j ++) {
6973: 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);
6974: }
6975: fprintf(ficgp,";\nset out; unset ylabel;\n");
6976: }
6977: /* 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 */
6978: /* fprintf(ficgp,"\nset log y;plot \"%s\" u 2:(-$11):3 t \"All sample, all transitions\" with dots lc variable",subdirf(fileresilk)); */
6979: /* fprintf(ficgp,"\nreplot \"%s\" u 2:($3 <= 3 ? -$11 : 1/0):3 t \"First 3 individuals\" with line lc variable", subdirf(fileresilk)); */
6980: fprintf(ficgp,"\nset out;unset log\n");
6981: /* fprintf(ficgp,"\nset out \"%s.svg\"; replot; set out; # bug gnuplot",subdirf2(optionfilefiname,"ILK_")); */
1.202 brouard 6982:
1.126 brouard 6983: strcpy(dirfileres,optionfilefiname);
6984: strcpy(optfileres,"vpl");
1.223 brouard 6985: /* 1eme*/
1.238 brouard 6986: for (cpt=1; cpt<= nlstate ; cpt ++){ /* For each live state */
6987: for (k1=1; k1<= m ; k1 ++){ /* For each valid combination of covariate */
1.236 brouard 6988: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.238 brouard 6989: /* plot [100000000000000000000:-100000000000000000000] "mysbiaspar/vplrmysbiaspar.txt to check */
1.253 brouard 6990: if(m != 1 && TKresult[nres]!= k1)
1.238 brouard 6991: continue;
6992: /* We are interested in selected combination by the resultline */
1.246 brouard 6993: /* printf("\n# 1st: Period (stable) prevalence with CI: 'VPL_' files and live state =%d ", cpt); */
1.238 brouard 6994: fprintf(ficgp,"\n# 1st: Period (stable) prevalence with CI: 'VPL_' files and live state =%d ", cpt);
1.264 brouard 6995: strcpy(gplotlabel,"(");
1.238 brouard 6996: for (k=1; k<=cptcoveff; k++){ /* For each covariate k get corresponding value lv for combination k1 */
6997: lv= decodtabm(k1,k,cptcoveff); /* Should be the value of the covariate corresponding to k1 combination */
6998: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
6999: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7000: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7001: vlv= nbcode[Tvaraff[k]][lv]; /* vlv is the value of the covariate lv, 0 or 1 */
7002: /* For each combination of covariate k1 (V1=1, V3=0), we printed the current covariate k and its value vlv */
1.246 brouard 7003: /* printf(" V%d=%d ",Tvaraff[k],vlv); */
1.238 brouard 7004: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 7005: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.238 brouard 7006: }
7007: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
1.246 brouard 7008: /* printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
1.238 brouard 7009: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7010: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
7011: }
7012: strcpy(gplotlabel+strlen(gplotlabel),")");
1.246 brouard 7013: /* printf("\n#\n"); */
1.238 brouard 7014: fprintf(ficgp,"\n#\n");
7015: if(invalidvarcomb[k1]){
1.260 brouard 7016: /*k1=k1-1;*/ /* To be checked */
1.238 brouard 7017: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7018: continue;
7019: }
1.235 brouard 7020:
1.241 brouard 7021: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"V_"),cpt,k1,nres);
7022: fprintf(ficgp,"\n#set out \"V_%s_%d-%d-%d.svg\" \n",optionfilefiname,cpt,k1,nres);
1.264 brouard 7023: 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 7024: 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);
7025: /* 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); */
7026: /* k1-1 error should be nres-1*/
1.238 brouard 7027: for (i=1; i<= nlstate ; i ++) {
7028: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
7029: else fprintf(ficgp," %%*lf (%%*lf)");
7030: }
1.260 brouard 7031: 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 7032: for (i=1; i<= nlstate ; i ++) {
7033: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
7034: else fprintf(ficgp," %%*lf (%%*lf)");
7035: }
1.260 brouard 7036: fprintf(ficgp,"\" t\"95%% CI\" w l lt 1,\"%s\" every :::%d::%d u 1:($2==%d ? $3-1.96*$4 : 1/0) \"%%lf %%lf",subdirf2(fileresu,"VPL_"),nres-1,nres-1,nres);
1.238 brouard 7037: for (i=1; i<= nlstate ; i ++) {
7038: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
7039: else fprintf(ficgp," %%*lf (%%*lf)");
7040: }
1.265 brouard 7041: /* fprintf(ficgp,"\" t\"\" w l lt 1,\"%s\" every :::%d::%d u 1:($%d) t\"Observed prevalence\" w l lt 2",subdirf2(fileresu,"P_"),k1-1,k1-1,2+4*(cpt-1)); */
7042:
7043: fprintf(ficgp,"\" t\"\" w l lt 1,\"%s\" u 1:((",subdirf2(fileresu,"P_"));
7044: if(cptcoveff ==0){
1.271 ! brouard 7045: fprintf(ficgp,"$%d)) t 'Observed prevalence in state %d' with line lt 3", 2+3*(cpt-1), cpt );
1.265 brouard 7046: }else{
7047: kl=0;
7048: for (k=1; k<=cptcoveff; k++){ /* For each combination of covariate */
7049: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate value corresponding to k1 combination and kth covariate */
7050: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7051: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7052: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7053: vlv= nbcode[Tvaraff[k]][lv];
7054: kl++;
7055: /* 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 *\/ */
7056: /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */
7057: /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */
7058: /* '' u 6:(($1==1 && $2==0 && $3==2 && $4==0)? $9/(1.-$15) : 1/0):($5==2000? 3:2) t 'p.1' with line lc variable*/
7059: if(k==cptcoveff){
7060: fprintf(ficgp,"$%d==%d && $%d==%d)? $%d : 1/0) t 'Observed prevalence in state %d' w l lt 2",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][lv], \
7061: 2+cptcoveff*2+3*(cpt-1), cpt ); /* 4 or 6 ?*/
7062: }else{
7063: fprintf(ficgp,"$%d==%d && $%d==%d && ",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][lv]);
7064: kl++;
7065: }
7066: } /* end covariate */
7067: } /* end if no covariate */
7068:
1.238 brouard 7069: if(backcast==1){ /* We need to get the corresponding values of the covariates involved in this combination k1 */
7070: /* fprintf(ficgp,",\"%s\" every :::%d::%d u 1:($%d) t\"Backward stable prevalence\" w l lt 3",subdirf2(fileresu,"PLB_"),k1-1,k1-1,1+cpt); */
1.242 brouard 7071: fprintf(ficgp,",\"%s\" u 1:((",subdirf2(fileresu,"PLB_")); /* Age is in 1, nres in 2 to be fixed */
1.238 brouard 7072: if(cptcoveff ==0){
1.245 brouard 7073: fprintf(ficgp,"$%d)) t 'Backward prevalence in state %d' with line lt 3", 2+(cpt-1), cpt );
1.238 brouard 7074: }else{
7075: kl=0;
7076: for (k=1; k<=cptcoveff; k++){ /* For each combination of covariate */
7077: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate value corresponding to k1 combination and kth covariate */
7078: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7079: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7080: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7081: vlv= nbcode[Tvaraff[k]][lv];
1.223 brouard 7082: kl++;
1.238 brouard 7083: /* 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 *\/ */
7084: /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */
7085: /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */
7086: /* '' u 6:(($1==1 && $2==0 && $3==2 && $4==0)? $9/(1.-$15) : 1/0):($5==2000? 3:2) t 'p.1' with line lc variable*/
7087: if(k==cptcoveff){
1.245 brouard 7088: fprintf(ficgp,"$%d==%d && $%d==%d)? $%d : 1/0) t 'Backward prevalence in state %d' w l lt 3",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][lv], \
1.242 brouard 7089: 2+cptcoveff*2+(cpt-1), cpt ); /* 4 or 6 ?*/
1.238 brouard 7090: }else{
7091: fprintf(ficgp,"$%d==%d && $%d==%d && ",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][lv]);
7092: kl++;
7093: }
7094: } /* end covariate */
7095: } /* end if no covariate */
1.268 brouard 7096: if(backcast == 1){
7097: fprintf(ficgp,", \"%s\" every :::%d::%d u 1:($2==%d ? $3:1/0) \"%%lf %%lf",subdirf2(fileresu,"VBL_"),nres-1,nres-1,nres);
7098: /* k1-1 error should be nres-1*/
7099: for (i=1; i<= nlstate ; i ++) {
7100: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
7101: else fprintf(ficgp," %%*lf (%%*lf)");
7102: }
1.271 ! brouard 7103: fprintf(ficgp,"\" t\"Backward (stable) prevalence\" w l lt 6 dt 3,\"%s\" every :::%d::%d u 1:($2==%d ? $3+1.96*$4 : 1/0) \"%%lf %%lf",subdirf2(fileresu,"VBL_"),nres-1,nres-1,nres);
1.268 brouard 7104: for (i=1; i<= nlstate ; i ++) {
7105: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
7106: else fprintf(ficgp," %%*lf (%%*lf)");
7107: }
1.271 ! brouard 7108: fprintf(ficgp,"\" t\"95%% CI\" w l lt 6,\"%s\" every :::%d::%d u 1:($2==%d ? $3-1.96*$4 : 1/0) \"%%lf %%lf",subdirf2(fileresu,"VBL_"),nres-1,nres-1,nres);
1.268 brouard 7109: for (i=1; i<= nlstate ; i ++) {
7110: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
7111: else fprintf(ficgp," %%*lf (%%*lf)");
7112: }
1.271 ! brouard 7113: fprintf(ficgp,"\" t\"\" w l lt 6");
1.268 brouard 7114: } /* end if backprojcast */
1.238 brouard 7115: } /* end if backcast */
1.264 brouard 7116: fprintf(ficgp,"\nset out ;unset label;\n");
1.238 brouard 7117: } /* nres */
1.201 brouard 7118: } /* k1 */
7119: } /* cpt */
1.235 brouard 7120:
7121:
1.126 brouard 7122: /*2 eme*/
1.238 brouard 7123: for (k1=1; k1<= m ; k1 ++){
7124: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 7125: if(m != 1 && TKresult[nres]!= k1)
1.238 brouard 7126: continue;
7127: fprintf(ficgp,"\n# 2nd: Total life expectancy with CI: 't' files ");
1.264 brouard 7128: strcpy(gplotlabel,"(");
1.238 brouard 7129: for (k=1; k<=cptcoveff; k++){ /* For each covariate and each value */
1.225 brouard 7130: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate number corresponding to k1 combination */
1.223 brouard 7131: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7132: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7133: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7134: vlv= nbcode[Tvaraff[k]][lv];
7135: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 7136: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.211 brouard 7137: }
1.237 brouard 7138: /* for(k=1; k <= ncovds; k++){ */
1.236 brouard 7139: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
1.238 brouard 7140: printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.236 brouard 7141: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7142: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.238 brouard 7143: }
1.264 brouard 7144: strcpy(gplotlabel+strlen(gplotlabel),")");
1.211 brouard 7145: fprintf(ficgp,"\n#\n");
1.223 brouard 7146: if(invalidvarcomb[k1]){
7147: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7148: continue;
7149: }
1.219 brouard 7150:
1.241 brouard 7151: fprintf(ficgp,"\nset out \"%s_%d-%d.svg\" \n",subdirf2(optionfilefiname,"E_"),k1,nres);
1.238 brouard 7152: for(vpopbased=0; vpopbased <= popbased; vpopbased++){ /* Done for vpopbased=0 and vpopbased=1 if popbased==1*/
1.264 brouard 7153: fprintf(ficgp,"\nset label \"popbased %d %s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",vpopbased,gplotlabel);
7154: if(vpopbased==0){
1.238 brouard 7155: fprintf(ficgp,"set ylabel \"Years\" \nset ter svg size 640, 480\nplot [%.f:%.f] ",ageminpar,fage);
1.264 brouard 7156: }else
1.238 brouard 7157: fprintf(ficgp,"\nreplot ");
7158: for (i=1; i<= nlstate+1 ; i ++) {
7159: k=2*i;
1.261 brouard 7160: 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 7161: for (j=1; j<= nlstate+1 ; j ++) {
7162: if (j==i) fprintf(ficgp," %%lf (%%lf)");
7163: else fprintf(ficgp," %%*lf (%%*lf)");
7164: }
7165: if (i== 1) fprintf(ficgp,"\" t\"TLE\" w l lt %d, \\\n",i);
7166: else fprintf(ficgp,"\" t\"LE in state (%d)\" w l lt %d, \\\n",i-1,i+1);
1.261 brouard 7167: 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 7168: for (j=1; j<= nlstate+1 ; j ++) {
7169: if (j==i) fprintf(ficgp," %%lf (%%lf)");
7170: else fprintf(ficgp," %%*lf (%%*lf)");
7171: }
7172: fprintf(ficgp,"\" t\"\" w l lt 0,");
1.261 brouard 7173: 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 7174: for (j=1; j<= nlstate+1 ; j ++) {
7175: if (j==i) fprintf(ficgp," %%lf (%%lf)");
7176: else fprintf(ficgp," %%*lf (%%*lf)");
7177: }
7178: if (i== (nlstate+1)) fprintf(ficgp,"\" t\"\" w l lt 0");
7179: else fprintf(ficgp,"\" t\"\" w l lt 0,\\\n");
7180: } /* state */
7181: } /* vpopbased */
1.264 brouard 7182: 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 7183: } /* end nres */
7184: } /* k1 end 2 eme*/
7185:
7186:
7187: /*3eme*/
7188: for (k1=1; k1<= m ; k1 ++){
7189: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 7190: if(m != 1 && TKresult[nres]!= k1)
1.238 brouard 7191: continue;
7192:
7193: for (cpt=1; cpt<= nlstate ; cpt ++) {
1.261 brouard 7194: fprintf(ficgp,"\n\n# 3d: Life expectancy with EXP_ files: combination=%d state=%d",k1, cpt);
1.264 brouard 7195: strcpy(gplotlabel,"(");
1.238 brouard 7196: for (k=1; k<=cptcoveff; k++){ /* For each covariate and each value */
7197: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate number corresponding to k1 combination */
7198: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7199: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7200: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7201: vlv= nbcode[Tvaraff[k]][lv];
7202: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 7203: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.238 brouard 7204: }
7205: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7206: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7207: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.238 brouard 7208: }
1.264 brouard 7209: strcpy(gplotlabel+strlen(gplotlabel),")");
1.238 brouard 7210: fprintf(ficgp,"\n#\n");
7211: if(invalidvarcomb[k1]){
7212: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7213: continue;
7214: }
7215:
7216: /* k=2+nlstate*(2*cpt-2); */
7217: k=2+(nlstate+1)*(cpt-1);
1.241 brouard 7218: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"EXP_"),cpt,k1,nres);
1.264 brouard 7219: fprintf(ficgp,"set label \"%s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",gplotlabel);
1.238 brouard 7220: fprintf(ficgp,"set ter svg size 640, 480\n\
1.261 brouard 7221: 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 7222: /*fprintf(ficgp,",\"e%s\" every :::%d::%d u 1:($%d-2*$%d) \"\%%lf ",fileres,k1-1,k1-1,k,k+1);
7223: for (i=1; i<= nlstate*2 ; i ++) fprintf(ficgp,"\%%lf (\%%lf) ");
7224: fprintf(ficgp,"\" t \"e%d1\" w l",cpt);
7225: fprintf(ficgp,",\"e%s\" every :::%d::%d u 1:($%d+2*$%d) \"\%%lf ",fileres,k1-1,k1-1,k,k+1);
7226: for (i=1; i<= nlstate*2 ; i ++) fprintf(ficgp,"\%%lf (\%%lf) ");
7227: fprintf(ficgp,"\" t \"e%d1\" w l",cpt);
1.219 brouard 7228:
1.238 brouard 7229: */
7230: for (i=1; i< nlstate ; i ++) {
1.261 brouard 7231: 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 7232: /* 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 7233:
1.238 brouard 7234: }
1.261 brouard 7235: 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 7236: }
1.264 brouard 7237: fprintf(ficgp,"\nunset label;\n");
1.238 brouard 7238: } /* end nres */
7239: } /* end kl 3eme */
1.126 brouard 7240:
1.223 brouard 7241: /* 4eme */
1.201 brouard 7242: /* Survival functions (period) from state i in state j by initial state i */
1.238 brouard 7243: for (k1=1; k1<=m; k1++){ /* For each covariate and each value */
7244: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 7245: if(m != 1 && TKresult[nres]!= k1)
1.223 brouard 7246: continue;
1.238 brouard 7247: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state cpt*/
1.264 brouard 7248: strcpy(gplotlabel,"(");
1.238 brouard 7249: fprintf(ficgp,"\n#\n#\n# Survival functions in state j : 'LIJ_' files, cov=%d state=%d",k1, cpt);
7250: for (k=1; k<=cptcoveff; k++){ /* For each covariate and each value */
7251: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate number corresponding to k1 combination */
7252: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7253: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7254: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7255: vlv= nbcode[Tvaraff[k]][lv];
7256: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 7257: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.238 brouard 7258: }
7259: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7260: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7261: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.238 brouard 7262: }
1.264 brouard 7263: strcpy(gplotlabel+strlen(gplotlabel),")");
1.238 brouard 7264: fprintf(ficgp,"\n#\n");
7265: if(invalidvarcomb[k1]){
7266: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7267: continue;
1.223 brouard 7268: }
1.238 brouard 7269:
1.241 brouard 7270: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"LIJ_"),cpt,k1,nres);
1.264 brouard 7271: 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 7272: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability to be alive\" \n\
7273: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
7274: k=3;
7275: for (i=1; i<= nlstate ; i ++){
7276: if(i==1){
7277: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJ_"));
7278: }else{
7279: fprintf(ficgp,", '' ");
7280: }
7281: l=(nlstate+ndeath)*(i-1)+1;
7282: fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d/($%d",k1,k+l+(cpt-1),k+l);
7283: for (j=2; j<= nlstate+ndeath ; j ++)
7284: fprintf(ficgp,"+$%d",k+l+j-1);
7285: fprintf(ficgp,")) t \"l(%d,%d)\" w l",i,cpt);
7286: } /* nlstate */
1.264 brouard 7287: fprintf(ficgp,"\nset out; unset label;\n");
1.238 brouard 7288: } /* end cpt state*/
7289: } /* end nres */
7290: } /* end covariate k1 */
7291:
1.220 brouard 7292: /* 5eme */
1.201 brouard 7293: /* Survival functions (period) from state i in state j by final state j */
1.238 brouard 7294: for (k1=1; k1<= m ; k1++){ /* For each covariate combination if any */
7295: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 7296: if(m != 1 && TKresult[nres]!= k1)
1.227 brouard 7297: continue;
1.238 brouard 7298: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each inital state */
1.264 brouard 7299: strcpy(gplotlabel,"(");
1.238 brouard 7300: 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);
7301: for (k=1; k<=cptcoveff; k++){ /* For each covariate and each value */
7302: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate number corresponding to k1 combination */
7303: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7304: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7305: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7306: vlv= nbcode[Tvaraff[k]][lv];
7307: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 7308: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.238 brouard 7309: }
7310: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7311: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7312: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.238 brouard 7313: }
1.264 brouard 7314: strcpy(gplotlabel+strlen(gplotlabel),")");
1.238 brouard 7315: fprintf(ficgp,"\n#\n");
7316: if(invalidvarcomb[k1]){
7317: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7318: continue;
7319: }
1.227 brouard 7320:
1.241 brouard 7321: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"LIJT_"),cpt,k1,nres);
1.264 brouard 7322: 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 7323: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability to be alive\" \n\
7324: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
7325: k=3;
7326: for (j=1; j<= nlstate ; j ++){ /* Lived in state j */
7327: if(j==1)
7328: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJ_"));
7329: else
7330: fprintf(ficgp,", '' ");
7331: l=(nlstate+ndeath)*(cpt-1) +j;
7332: fprintf(ficgp," u (($1==%d && (floor($2)%%5 == 0)) ? ($3):1/0):($%d",k1,k+l);
7333: /* for (i=2; i<= nlstate+ndeath ; i ++) */
7334: /* fprintf(ficgp,"+$%d",k+l+i-1); */
7335: fprintf(ficgp,") t \"l(%d,%d)\" w l",cpt,j);
7336: } /* nlstate */
7337: fprintf(ficgp,", '' ");
7338: fprintf(ficgp," u (($1==%d && (floor($2)%%5 == 0)) ? ($3):1/0):(",k1);
7339: for (j=1; j<= nlstate ; j ++){ /* Lived in state j */
7340: l=(nlstate+ndeath)*(cpt-1) +j;
7341: if(j < nlstate)
7342: fprintf(ficgp,"$%d +",k+l);
7343: else
7344: fprintf(ficgp,"$%d) t\"l(%d,.)\" w l",k+l,cpt);
7345: }
1.264 brouard 7346: fprintf(ficgp,"\nset out; unset label;\n");
1.238 brouard 7347: } /* end cpt state*/
7348: } /* end covariate */
7349: } /* end nres */
1.227 brouard 7350:
1.220 brouard 7351: /* 6eme */
1.202 brouard 7352: /* CV preval stable (period) for each covariate */
1.237 brouard 7353: for (k1=1; k1<= m ; k1 ++) /* For each covariate combination if any */
7354: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 7355: if(m != 1 && TKresult[nres]!= k1)
1.237 brouard 7356: continue;
1.255 brouard 7357: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state of arrival */
1.264 brouard 7358: strcpy(gplotlabel,"(");
1.211 brouard 7359: fprintf(ficgp,"\n#\n#\n#CV preval stable (period): 'pij' files, covariatecombination#=%d state=%d",k1, cpt);
1.225 brouard 7360: for (k=1; k<=cptcoveff; k++){ /* For each covariate and each value */
1.227 brouard 7361: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate number corresponding to k1 combination */
7362: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7363: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7364: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7365: vlv= nbcode[Tvaraff[k]][lv];
7366: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 7367: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.211 brouard 7368: }
1.237 brouard 7369: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7370: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7371: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.237 brouard 7372: }
1.264 brouard 7373: strcpy(gplotlabel+strlen(gplotlabel),")");
1.211 brouard 7374: fprintf(ficgp,"\n#\n");
1.223 brouard 7375: if(invalidvarcomb[k1]){
1.227 brouard 7376: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7377: continue;
1.223 brouard 7378: }
1.227 brouard 7379:
1.241 brouard 7380: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"P_"),cpt,k1,nres);
1.264 brouard 7381: 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 7382: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability\" \n\
1.238 brouard 7383: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
1.211 brouard 7384: k=3; /* Offset */
1.255 brouard 7385: for (i=1; i<= nlstate ; i ++){ /* State of origin */
1.227 brouard 7386: if(i==1)
7387: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJ_"));
7388: else
7389: fprintf(ficgp,", '' ");
1.255 brouard 7390: l=(nlstate+ndeath)*(i-1)+1; /* 1, 1+ nlstate+ndeath, 1+2*(nlstate+ndeath) */
1.227 brouard 7391: fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d/($%d",k1,k+l+(cpt-1),k+l);
7392: for (j=2; j<= nlstate ; j ++)
7393: fprintf(ficgp,"+$%d",k+l+j-1);
7394: fprintf(ficgp,")) t \"prev(%d,%d)\" w l",i,cpt);
1.153 brouard 7395: } /* nlstate */
1.264 brouard 7396: fprintf(ficgp,"\nset out; unset label;\n");
1.153 brouard 7397: } /* end cpt state*/
7398: } /* end covariate */
1.227 brouard 7399:
7400:
1.220 brouard 7401: /* 7eme */
1.218 brouard 7402: if(backcast == 1){
1.217 brouard 7403: /* CV back preval stable (period) for each covariate */
1.237 brouard 7404: for (k1=1; k1<= m ; k1 ++) /* For each covariate combination if any */
7405: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 7406: if(m != 1 && TKresult[nres]!= k1)
1.237 brouard 7407: continue;
1.268 brouard 7408: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life origin state */
1.264 brouard 7409: strcpy(gplotlabel,"(");
7410: fprintf(ficgp,"\n#\n#\n#CV Back preval stable (period): 'pijb' files, covariatecombination#=%d state=%d",k1, cpt);
1.227 brouard 7411: for (k=1; k<=cptcoveff; k++){ /* For each covariate and each value */
7412: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate number corresponding to k1 combination */
7413: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7414: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
1.223 brouard 7415: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
1.227 brouard 7416: vlv= nbcode[Tvaraff[k]][lv];
7417: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 7418: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.227 brouard 7419: }
1.237 brouard 7420: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7421: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7422: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.237 brouard 7423: }
1.264 brouard 7424: strcpy(gplotlabel+strlen(gplotlabel),")");
1.227 brouard 7425: fprintf(ficgp,"\n#\n");
7426: if(invalidvarcomb[k1]){
7427: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7428: continue;
7429: }
7430:
1.241 brouard 7431: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"PB_"),cpt,k1,nres);
1.268 brouard 7432: fprintf(ficgp,"set label \"Origin alive state %d %s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",cpt,gplotlabel);
1.227 brouard 7433: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability\" \n\
1.238 brouard 7434: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
1.227 brouard 7435: k=3; /* Offset */
1.268 brouard 7436: for (i=1; i<= nlstate ; i ++){ /* State of arrival */
1.227 brouard 7437: if(i==1)
7438: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJB_"));
7439: else
7440: fprintf(ficgp,", '' ");
7441: /* l=(nlstate+ndeath)*(i-1)+1; */
1.255 brouard 7442: l=(nlstate+ndeath)*(cpt-1)+1; /* fixed for i; cpt=1 1, cpt=2 1+ nlstate+ndeath, 1+2*(nlstate+ndeath) */
1.227 brouard 7443: /* fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d/($%d",k1,k+l+(cpt-1),k+l); /\* a vérifier *\/ */
7444: /* 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 7445: fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d",k1,k+l+i-1); /* To be verified */
1.227 brouard 7446: /* for (j=2; j<= nlstate ; j ++) */
7447: /* fprintf(ficgp,"+$%d",k+l+j-1); */
7448: /* /\* fprintf(ficgp,"+$%d",k+l+j-1); *\/ */
1.268 brouard 7449: fprintf(ficgp,") t \"bprev(%d,%d)\" w l",cpt,i);
1.227 brouard 7450: } /* nlstate */
1.264 brouard 7451: fprintf(ficgp,"\nset out; unset label;\n");
1.218 brouard 7452: } /* end cpt state*/
7453: } /* end covariate */
7454: } /* End if backcast */
7455:
1.223 brouard 7456: /* 8eme */
1.218 brouard 7457: if(prevfcast==1){
7458: /* Projection from cross-sectional to stable (period) for each covariate */
7459:
1.237 brouard 7460: for (k1=1; k1<= m ; k1 ++) /* For each covariate combination if any */
7461: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 7462: if(m != 1 && TKresult[nres]!= k1)
1.237 brouard 7463: continue;
1.211 brouard 7464: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state */
1.264 brouard 7465: strcpy(gplotlabel,"(");
1.227 brouard 7466: fprintf(ficgp,"\n#\n#\n#Projection of prevalence to stable (period): 'PROJ_' files, covariatecombination#=%d state=%d",k1, cpt);
7467: for (k=1; k<=cptcoveff; k++){ /* For each correspondig covariate value */
7468: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate value corresponding to k1 combination and kth covariate */
7469: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7470: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7471: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7472: vlv= nbcode[Tvaraff[k]][lv];
7473: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 7474: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.227 brouard 7475: }
1.237 brouard 7476: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7477: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7478: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.237 brouard 7479: }
1.264 brouard 7480: strcpy(gplotlabel+strlen(gplotlabel),")");
1.227 brouard 7481: fprintf(ficgp,"\n#\n");
7482: if(invalidvarcomb[k1]){
7483: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7484: continue;
7485: }
7486:
7487: fprintf(ficgp,"# hpijx=probability over h years, hp.jx is weighted by observed prev\n ");
1.241 brouard 7488: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"PROJ_"),cpt,k1,nres);
1.264 brouard 7489: 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 7490: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Prevalence\" \n\
1.238 brouard 7491: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
1.266 brouard 7492:
7493: /* for (i=1; i<= nlstate+1 ; i ++){ /\* nlstate +1 p11 p21 p.1 *\/ */
7494: istart=nlstate+1; /* Could be one if by state, but nlstate+1 is w.i projection only */
7495: /*istart=1;*/ /* Could be one if by state, but nlstate+1 is w.i projection only */
7496: for (i=istart; i<= nlstate+1 ; i ++){ /* nlstate +1 p11 p21 p.1 */
1.227 brouard 7497: /*# V1 = 1 V2 = 0 yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
7498: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
7499: /*# yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
7500: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
1.266 brouard 7501: if(i==istart){
1.227 brouard 7502: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"F_"));
7503: }else{
7504: fprintf(ficgp,",\\\n '' ");
7505: }
7506: if(cptcoveff ==0){ /* No covariate */
7507: ioffset=2; /* Age is in 2 */
7508: /*# yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/
7509: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */
7510: /*# V1 = 1 yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/
7511: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */
7512: fprintf(ficgp," u %d:(", ioffset);
1.266 brouard 7513: if(i==nlstate+1){
1.270 brouard 7514: fprintf(ficgp," $%d/(1.-$%d)):1 t 'pw.%d' with line lc variable ", \
1.266 brouard 7515: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,cpt );
7516: fprintf(ficgp,",\\\n '' ");
7517: fprintf(ficgp," u %d:(",ioffset);
1.270 brouard 7518: fprintf(ficgp," (($1-$2) == %d ) ? $%d/(1.-$%d) : 1/0):1 with labels center not ", \
1.266 brouard 7519: offyear, \
1.268 brouard 7520: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate );
1.266 brouard 7521: }else
1.227 brouard 7522: fprintf(ficgp," $%d/(1.-$%d)) t 'p%d%d' with line ", \
7523: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,i,cpt );
7524: }else{ /* more than 2 covariates */
1.270 brouard 7525: ioffset=2*cptcoveff+2; /* Age is in 4 or 6 or etc.*/
7526: /*# V1 = 1 V2 = 0 yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
7527: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
7528: iyearc=ioffset-1;
7529: iagec=ioffset;
1.227 brouard 7530: fprintf(ficgp," u %d:(",ioffset);
7531: kl=0;
7532: strcpy(gplotcondition,"(");
7533: for (k=1; k<=cptcoveff; k++){ /* For each covariate writing the chain of conditions */
7534: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate value corresponding to combination k1 and covariate k */
7535: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7536: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7537: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7538: vlv= nbcode[Tvaraff[k]][lv]; /* Value of the modality of Tvaraff[k] */
7539: kl++;
7540: sprintf(gplotcondition+strlen(gplotcondition),"$%d==%d && $%d==%d " ,kl,Tvaraff[k], kl+1, nbcode[Tvaraff[k]][lv]);
7541: kl++;
7542: if(k <cptcoveff && cptcoveff>1)
7543: sprintf(gplotcondition+strlen(gplotcondition)," && ");
7544: }
7545: strcpy(gplotcondition+strlen(gplotcondition),")");
7546: /* 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 *\/ */
7547: /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */
7548: /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */
7549: /* '' 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*/
7550: if(i==nlstate+1){
1.270 brouard 7551: fprintf(ficgp,"%s ? $%d/(1.-$%d) : 1/0):%d t 'p.%d' with line lc variable", gplotcondition, \
7552: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,iyearc, cpt );
1.266 brouard 7553: fprintf(ficgp,",\\\n '' ");
1.270 brouard 7554: fprintf(ficgp," u %d:(",iagec);
7555: fprintf(ficgp,"%s && (($%d-$%d) == %d ) ? $%d/(1.-$%d) : 1/0):%d with labels center not ", gplotcondition, \
7556: iyearc, iagec, offyear, \
7557: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate, iyearc );
1.266 brouard 7558: /* '' u 6:(($1==1 && $2==0 && $3==2 && $4==0) && (($5-$6) == 1947) ? $10/(1.-$22) : 1/0):5 with labels center boxed not*/
1.227 brouard 7559: }else{
7560: fprintf(ficgp,"%s ? $%d/(1.-$%d) : 1/0) t 'p%d%d' with line ", gplotcondition, \
7561: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset +1+(i-1)+(nlstate+1)*nlstate,i,cpt );
7562: }
7563: } /* end if covariate */
7564: } /* nlstate */
1.264 brouard 7565: fprintf(ficgp,"\nset out; unset label;\n");
1.223 brouard 7566: } /* end cpt state*/
7567: } /* end covariate */
7568: } /* End if prevfcast */
1.227 brouard 7569:
1.268 brouard 7570: if(backcast==1){
7571: /* Back projection from cross-sectional to stable (mixed) for each covariate */
7572:
7573: for (k1=1; k1<= m ; k1 ++) /* For each covariate combination if any */
7574: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
7575: if(m != 1 && TKresult[nres]!= k1)
7576: continue;
7577: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state */
7578: strcpy(gplotlabel,"(");
7579: fprintf(ficgp,"\n#\n#\n#Back projection of prevalence to stable (mixed) back prevalence: 'BPROJ_' files, covariatecombination#=%d originstate=%d",k1, cpt);
7580: for (k=1; k<=cptcoveff; k++){ /* For each correspondig covariate value */
7581: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate value corresponding to k1 combination and kth covariate */
7582: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7583: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7584: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7585: vlv= nbcode[Tvaraff[k]][lv];
7586: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
7587: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
7588: }
7589: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7590: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
7591: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
7592: }
7593: strcpy(gplotlabel+strlen(gplotlabel),")");
7594: fprintf(ficgp,"\n#\n");
7595: if(invalidvarcomb[k1]){
7596: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7597: continue;
7598: }
7599:
7600: fprintf(ficgp,"# hbijx=backprobability over h years, hb.jx is weighted by observed prev at destination state\n ");
7601: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"PROJB_"),cpt,k1,nres);
7602: fprintf(ficgp,"set label \"Origin alive state %d %s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",cpt,gplotlabel);
7603: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Prevalence\" \n\
7604: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
7605:
7606: /* for (i=1; i<= nlstate+1 ; i ++){ /\* nlstate +1 p11 p21 p.1 *\/ */
7607: istart=nlstate+1; /* Could be one if by state, but nlstate+1 is w.i projection only */
7608: /*istart=1;*/ /* Could be one if by state, but nlstate+1 is w.i projection only */
7609: for (i=istart; i<= nlstate+1 ; i ++){ /* nlstate +1 p11 p21 p.1 */
7610: /*# V1 = 1 V2 = 0 yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
7611: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
7612: /*# yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
7613: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
7614: if(i==istart){
7615: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"FB_"));
7616: }else{
7617: fprintf(ficgp,",\\\n '' ");
7618: }
7619: if(cptcoveff ==0){ /* No covariate */
7620: ioffset=2; /* Age is in 2 */
7621: /*# yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/
7622: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */
7623: /*# V1 = 1 yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/
7624: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */
7625: fprintf(ficgp," u %d:(", ioffset);
7626: if(i==nlstate+1){
1.270 brouard 7627: fprintf(ficgp," $%d/(1.-$%d)):1 t 'bw%d' with line lc variable ", \
1.268 brouard 7628: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,cpt );
7629: fprintf(ficgp,",\\\n '' ");
7630: fprintf(ficgp," u %d:(",ioffset);
1.270 brouard 7631: fprintf(ficgp," (($1-$2) == %d ) ? $%d : 1/0):1 with labels center not ", \
1.268 brouard 7632: offbyear, \
7633: ioffset+(cpt-1)*(nlstate+1)+1+(i-1) );
7634: }else
7635: fprintf(ficgp," $%d/(1.-$%d)) t 'b%d%d' with line ", \
7636: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,cpt,i );
7637: }else{ /* more than 2 covariates */
1.270 brouard 7638: ioffset=2*cptcoveff+2; /* Age is in 4 or 6 or etc.*/
7639: /*# V1 = 1 V2 = 0 yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
7640: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
7641: iyearc=ioffset-1;
7642: iagec=ioffset;
1.268 brouard 7643: fprintf(ficgp," u %d:(",ioffset);
7644: kl=0;
7645: strcpy(gplotcondition,"(");
7646: for (k=1; k<=cptcoveff; k++){ /* For each covariate writing the chain of conditions */
7647: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate value corresponding to combination k1 and covariate k */
7648: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7649: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7650: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7651: vlv= nbcode[Tvaraff[k]][lv]; /* Value of the modality of Tvaraff[k] */
7652: kl++;
7653: sprintf(gplotcondition+strlen(gplotcondition),"$%d==%d && $%d==%d " ,kl,Tvaraff[k], kl+1, nbcode[Tvaraff[k]][lv]);
7654: kl++;
7655: if(k <cptcoveff && cptcoveff>1)
7656: sprintf(gplotcondition+strlen(gplotcondition)," && ");
7657: }
7658: strcpy(gplotcondition+strlen(gplotcondition),")");
7659: /* 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 *\/ */
7660: /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */
7661: /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */
7662: /* '' 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*/
7663: if(i==nlstate+1){
1.270 brouard 7664: fprintf(ficgp,"%s ? $%d : 1/0):%d t 'bw%d' with line lc variable", gplotcondition, \
7665: ioffset+(cpt-1)*(nlstate+1)+1+(i-1),iyearc,cpt );
1.268 brouard 7666: fprintf(ficgp,",\\\n '' ");
1.270 brouard 7667: fprintf(ficgp," u %d:(",iagec);
1.268 brouard 7668: /* fprintf(ficgp,"%s && (($5-$6) == %d ) ? $%d/(1.-$%d) : 1/0):5 with labels center not ", gplotcondition, \ */
1.270 brouard 7669: fprintf(ficgp,"%s && (($%d-$%d) == %d ) ? $%d : 1/0):%d with labels center not ", gplotcondition, \
7670: iyearc,iagec,offbyear, \
7671: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), iyearc );
1.268 brouard 7672: /* '' u 6:(($1==1 && $2==0 && $3==2 && $4==0) && (($5-$6) == 1947) ? $10/(1.-$22) : 1/0):5 with labels center boxed not*/
7673: }else{
7674: /* fprintf(ficgp,"%s ? $%d/(1.-$%d) : 1/0) t 'p%d%d' with line ", gplotcondition, \ */
7675: fprintf(ficgp,"%s ? $%d : 1/0) t 'b%d%d' with line ", gplotcondition, \
7676: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), cpt,i );
7677: }
7678: } /* end if covariate */
7679: } /* nlstate */
7680: fprintf(ficgp,"\nset out; unset label;\n");
7681: } /* end cpt state*/
7682: } /* end covariate */
7683: } /* End if backcast */
7684:
1.227 brouard 7685:
1.238 brouard 7686: /* 9eme writing MLE parameters */
7687: fprintf(ficgp,"\n##############\n#9eme MLE estimated parameters\n#############\n");
1.126 brouard 7688: for(i=1,jk=1; i <=nlstate; i++){
1.187 brouard 7689: fprintf(ficgp,"# initial state %d\n",i);
1.126 brouard 7690: for(k=1; k <=(nlstate+ndeath); k++){
7691: if (k != i) {
1.227 brouard 7692: fprintf(ficgp,"# current state %d\n",k);
7693: for(j=1; j <=ncovmodel; j++){
7694: fprintf(ficgp,"p%d=%f; ",jk,p[jk]);
7695: jk++;
7696: }
7697: fprintf(ficgp,"\n");
1.126 brouard 7698: }
7699: }
1.223 brouard 7700: }
1.187 brouard 7701: fprintf(ficgp,"##############\n#\n");
1.227 brouard 7702:
1.145 brouard 7703: /*goto avoid;*/
1.238 brouard 7704: /* 10eme Graphics of probabilities or incidences using written MLE parameters */
7705: fprintf(ficgp,"\n##############\n#10eme Graphics of probabilities or incidences\n#############\n");
1.187 brouard 7706: fprintf(ficgp,"# logi(p12/p11)=a12+b12*age+c12age*age+d12*V1+e12*V1*age\n");
7707: fprintf(ficgp,"# logi(p12/p11)=p1 +p2*age +p3*age*age+ p4*V1+ p5*V1*age\n");
7708: fprintf(ficgp,"# logi(p13/p11)=a13+b13*age+c13age*age+d13*V1+e13*V1*age\n");
7709: fprintf(ficgp,"# logi(p13/p11)=p6 +p7*age +p8*age*age+ p9*V1+ p10*V1*age\n");
7710: fprintf(ficgp,"# p12+p13+p14+p11=1=p11(1+exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)\n");
7711: fprintf(ficgp,"# +exp(a13+b13*age+c13age*age+d13*V1+e13*V1*age)+...)\n");
7712: fprintf(ficgp,"# p11=1/(1+exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)\n");
7713: fprintf(ficgp,"# +exp(a13+b13*age+c13age*age+d13*V1+e13*V1*age)+...)\n");
7714: fprintf(ficgp,"# p12=exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)/\n");
7715: fprintf(ficgp,"# (1+exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)\n");
7716: fprintf(ficgp,"# +exp(a13+b13*age+c13age*age+d13*V1+e13*V1*age))\n");
7717: fprintf(ficgp,"# +exp(a14+b14*age+c14age*age+d14*V1+e14*V1*age)+...)\n");
7718: fprintf(ficgp,"#\n");
1.223 brouard 7719: for(ng=1; ng<=3;ng++){ /* Number of graphics: first is logit, 2nd is probabilities, third is incidences per year*/
1.238 brouard 7720: fprintf(ficgp,"#Number of graphics: first is logit, 2nd is probabilities, third is incidences per year\n");
1.237 brouard 7721: fprintf(ficgp,"#model=%s \n",model);
1.238 brouard 7722: fprintf(ficgp,"# Type of graphic ng=%d\n",ng);
1.264 brouard 7723: fprintf(ficgp,"# k1=1 to 2^%d=%d\n",cptcoveff,m);/* to be checked */
7724: for(k1=1; k1 <=m; k1++) /* For each combination of covariate */
1.237 brouard 7725: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.264 brouard 7726: if(m != 1 && TKresult[nres]!= k1)
1.237 brouard 7727: continue;
1.264 brouard 7728: fprintf(ficgp,"\n\n# Combination of dummy k1=%d which is ",k1);
7729: strcpy(gplotlabel,"(");
7730: sprintf(gplotlabel+strlen(gplotlabel)," Dummy combination %d ",k1);
7731: for (k=1; k<=cptcoveff; k++){ /* For each correspondig covariate value */
7732: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate value corresponding to k1 combination and kth covariate */
7733: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7734: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7735: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7736: vlv= nbcode[Tvaraff[k]][lv];
7737: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
7738: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
7739: }
1.237 brouard 7740: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7741: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7742: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.237 brouard 7743: }
1.264 brouard 7744: strcpy(gplotlabel+strlen(gplotlabel),")");
1.237 brouard 7745: fprintf(ficgp,"\n#\n");
1.264 brouard 7746: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" ",subdirf2(optionfilefiname,"PE_"),k1,ng,nres);
7747: fprintf(ficgp,"\nset label \"%s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",gplotlabel);
1.223 brouard 7748: fprintf(ficgp,"\nset ter svg size 640, 480 ");
7749: if (ng==1){
7750: fprintf(ficgp,"\nset ylabel \"Value of the logit of the model\"\n"); /* exp(a12+b12*x) could be nice */
7751: fprintf(ficgp,"\nunset log y");
7752: }else if (ng==2){
7753: fprintf(ficgp,"\nset ylabel \"Probability\"\n");
7754: fprintf(ficgp,"\nset log y");
7755: }else if (ng==3){
7756: fprintf(ficgp,"\nset ylabel \"Quasi-incidence per year\"\n");
7757: fprintf(ficgp,"\nset log y");
7758: }else
7759: fprintf(ficgp,"\nunset title ");
7760: fprintf(ficgp,"\nplot [%.f:%.f] ",ageminpar,agemaxpar);
7761: i=1;
7762: for(k2=1; k2<=nlstate; k2++) {
7763: k3=i;
7764: for(k=1; k<=(nlstate+ndeath); k++) {
7765: if (k != k2){
7766: switch( ng) {
7767: case 1:
7768: if(nagesqr==0)
7769: fprintf(ficgp," p%d+p%d*x",i,i+1);
7770: else /* nagesqr =1 */
7771: fprintf(ficgp," p%d+p%d*x+p%d*x*x",i,i+1,i+1+nagesqr);
7772: break;
7773: case 2: /* ng=2 */
7774: if(nagesqr==0)
7775: fprintf(ficgp," exp(p%d+p%d*x",i,i+1);
7776: else /* nagesqr =1 */
7777: fprintf(ficgp," exp(p%d+p%d*x+p%d*x*x",i,i+1,i+1+nagesqr);
7778: break;
7779: case 3:
7780: if(nagesqr==0)
7781: fprintf(ficgp," %f*exp(p%d+p%d*x",YEARM/stepm,i,i+1);
7782: else /* nagesqr =1 */
7783: fprintf(ficgp," %f*exp(p%d+p%d*x+p%d*x*x",YEARM/stepm,i,i+1,i+1+nagesqr);
7784: break;
7785: }
7786: ij=1;/* To be checked else nbcode[0][0] wrong */
1.237 brouard 7787: ijp=1; /* product no age */
7788: /* for(j=3; j <=ncovmodel-nagesqr; j++) { */
7789: for(j=1; j <=cptcovt; j++) { /* For each covariate of the simplified model */
1.223 brouard 7790: /* printf("Tage[%d]=%d, j=%d\n", ij, Tage[ij], j); */
1.268 brouard 7791: if(cptcovage >0){ /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, 2 V5 and V1 */
7792: if(j==Tage[ij]) { /* Product by age To be looked at!!*/
7793: if(ij <=cptcovage) { /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, 2 V5 and V1 */
7794: if(DummyV[j]==0){
7795: fprintf(ficgp,"+p%d*%d*x",i+j+2+nagesqr-1,Tinvresult[nres][Tvar[j]]);;
7796: }else{ /* quantitative */
7797: fprintf(ficgp,"+p%d*%f*x",i+j+2+nagesqr-1,Tqinvresult[nres][Tvar[j]]); /* Tqinvresult in decoderesult */
7798: /* fprintf(ficgp,"+p%d*%d*x",i+j+nagesqr-1,nbcode[Tvar[j-2]][codtabm(k1,Tvar[j-2])]); */
7799: }
7800: ij++;
1.237 brouard 7801: }
1.268 brouard 7802: }
7803: }else if(cptcovprod >0){
7804: if(j==Tprod[ijp]) { /* */
7805: /* printf("Tprod[%d]=%d, j=%d\n", ij, Tprod[ijp], j); */
7806: if(ijp <=cptcovprod) { /* Product */
7807: if(DummyV[Tvard[ijp][1]]==0){/* Vn is dummy */
7808: if(DummyV[Tvard[ijp][2]]==0){/* Vn and Vm are dummy */
7809: /* 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)]); */
7810: fprintf(ficgp,"+p%d*%d*%d",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tinvresult[nres][Tvard[ijp][2]]);
7811: }else{ /* Vn is dummy and Vm is quanti */
7812: /* fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,nbcode[Tvard[ijp][1]][codtabm(k1,j)],Tqinvresult[nres][Tvard[ijp][2]]); */
7813: fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]);
7814: }
7815: }else{ /* Vn*Vm Vn is quanti */
7816: if(DummyV[Tvard[ijp][2]]==0){
7817: fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][2]],Tqinvresult[nres][Tvard[ijp][1]]);
7818: }else{ /* Both quanti */
7819: fprintf(ficgp,"+p%d*%f*%f",i+j+2+nagesqr-1,Tqinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]);
7820: }
1.237 brouard 7821: }
1.268 brouard 7822: ijp++;
1.237 brouard 7823: }
1.268 brouard 7824: } /* end Tprod */
1.237 brouard 7825: } else{ /* simple covariate */
1.264 brouard 7826: /* fprintf(ficgp,"+p%d*%d",i+j+2+nagesqr-1,nbcode[Tvar[j]][codtabm(k1,j)]); /\* Valgrind bug nbcode *\/ */
1.237 brouard 7827: if(Dummy[j]==0){
7828: fprintf(ficgp,"+p%d*%d",i+j+2+nagesqr-1,Tinvresult[nres][Tvar[j]]); /* */
7829: }else{ /* quantitative */
7830: fprintf(ficgp,"+p%d*%f",i+j+2+nagesqr-1,Tqinvresult[nres][Tvar[j]]); /* */
1.264 brouard 7831: /* fprintf(ficgp,"+p%d*%d*x",i+j+nagesqr-1,nbcode[Tvar[j-2]][codtabm(k1,Tvar[j-2])]); */
1.223 brouard 7832: }
1.237 brouard 7833: } /* end simple */
7834: } /* end j */
1.223 brouard 7835: }else{
7836: i=i-ncovmodel;
7837: if(ng !=1 ) /* For logit formula of log p11 is more difficult to get */
7838: fprintf(ficgp," (1.");
7839: }
1.227 brouard 7840:
1.223 brouard 7841: if(ng != 1){
7842: fprintf(ficgp,")/(1");
1.227 brouard 7843:
1.264 brouard 7844: for(cpt=1; cpt <=nlstate; cpt++){
1.223 brouard 7845: if(nagesqr==0)
1.264 brouard 7846: fprintf(ficgp,"+exp(p%d+p%d*x",k3+(cpt-1)*ncovmodel,k3+(cpt-1)*ncovmodel+1);
1.223 brouard 7847: else /* nagesqr =1 */
1.264 brouard 7848: 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 7849:
1.223 brouard 7850: ij=1;
7851: for(j=3; j <=ncovmodel-nagesqr; j++){
1.268 brouard 7852: if(cptcovage >0){
7853: if((j-2)==Tage[ij]) { /* Bug valgrind */
7854: if(ij <=cptcovage) { /* Bug valgrind */
7855: fprintf(ficgp,"+p%d*%d*x",k3+(cpt-1)*ncovmodel+1+j-2+nagesqr,nbcode[Tvar[j-2]][codtabm(k1,j-2)]);
7856: /* fprintf(ficgp,"+p%d*%d*x",k3+(cpt-1)*ncovmodel+1+j-2+nagesqr,nbcode[Tvar[j-2]][codtabm(k1,Tvar[j-2])]); */
7857: ij++;
7858: }
7859: }
7860: }else
7861: 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 7862: }
7863: fprintf(ficgp,")");
7864: }
7865: fprintf(ficgp,")");
7866: if(ng ==2)
7867: fprintf(ficgp," t \"p%d%d\" ", k2,k);
7868: else /* ng= 3 */
7869: fprintf(ficgp," t \"i%d%d\" ", k2,k);
7870: }else{ /* end ng <> 1 */
7871: if( k !=k2) /* logit p11 is hard to draw */
7872: fprintf(ficgp," t \"logit(p%d%d)\" ", k2,k);
7873: }
7874: if ((k+k2)!= (nlstate*2+ndeath) && ng != 1)
7875: fprintf(ficgp,",");
7876: if (ng == 1 && k!=k2 && (k+k2)!= (nlstate*2+ndeath))
7877: fprintf(ficgp,",");
7878: i=i+ncovmodel;
7879: } /* end k */
7880: } /* end k2 */
1.264 brouard 7881: fprintf(ficgp,"\n set out; unset label;\n");
7882: } /* end k1 */
1.223 brouard 7883: } /* end ng */
7884: /* avoid: */
7885: fflush(ficgp);
1.126 brouard 7886: } /* end gnuplot */
7887:
7888:
7889: /*************** Moving average **************/
1.219 brouard 7890: /* int movingaverage(double ***probs, double bage, double fage, double ***mobaverage, int mobilav, double bageout, double fageout){ */
1.222 brouard 7891: int movingaverage(double ***probs, double bage, double fage, double ***mobaverage, int mobilav){
1.218 brouard 7892:
1.222 brouard 7893: int i, cpt, cptcod;
7894: int modcovmax =1;
7895: int mobilavrange, mob;
7896: int iage=0;
7897:
1.266 brouard 7898: double sum=0., sumr=0.;
1.222 brouard 7899: double age;
1.266 brouard 7900: double *sumnewp, *sumnewm, *sumnewmr;
7901: double *agemingood, *agemaxgood;
7902: double *agemingoodr, *agemaxgoodr;
1.222 brouard 7903:
7904:
1.225 brouard 7905: /* modcovmax=2*cptcoveff;/\* Max number of modalities. We suppose */
1.222 brouard 7906: /* a covariate has 2 modalities, should be equal to ncovcombmax *\/ */
7907:
7908: sumnewp = vector(1,ncovcombmax);
7909: sumnewm = vector(1,ncovcombmax);
1.266 brouard 7910: sumnewmr = vector(1,ncovcombmax);
1.222 brouard 7911: agemingood = vector(1,ncovcombmax);
1.266 brouard 7912: agemingoodr = vector(1,ncovcombmax);
1.222 brouard 7913: agemaxgood = vector(1,ncovcombmax);
1.266 brouard 7914: agemaxgoodr = vector(1,ncovcombmax);
1.222 brouard 7915:
7916: for (cptcod=1;cptcod<=ncovcombmax;cptcod++){
1.266 brouard 7917: sumnewm[cptcod]=0.; sumnewmr[cptcod]=0.;
1.222 brouard 7918: sumnewp[cptcod]=0.;
1.266 brouard 7919: agemingood[cptcod]=0, agemingoodr[cptcod]=0;
7920: agemaxgood[cptcod]=0, agemaxgoodr[cptcod]=0;
1.222 brouard 7921: }
7922: if (cptcovn<1) ncovcombmax=1; /* At least 1 pass */
7923:
1.266 brouard 7924: if(mobilav==-1 || mobilav==1||mobilav ==3 ||mobilav==5 ||mobilav== 7){
7925: if(mobilav==1 || mobilav==-1) mobilavrange=5; /* default */
1.222 brouard 7926: else mobilavrange=mobilav;
7927: for (age=bage; age<=fage; age++)
7928: for (i=1; i<=nlstate;i++)
7929: for (cptcod=1;cptcod<=ncovcombmax;cptcod++)
7930: mobaverage[(int)age][i][cptcod]=probs[(int)age][i][cptcod];
7931: /* We keep the original values on the extreme ages bage, fage and for
7932: fage+1 and bage-1 we use a 3 terms moving average; for fage+2 bage+2
7933: we use a 5 terms etc. until the borders are no more concerned.
7934: */
7935: for (mob=3;mob <=mobilavrange;mob=mob+2){
7936: for (age=bage+(mob-1)/2; age<=fage-(mob-1)/2; age++){
1.266 brouard 7937: for (cptcod=1;cptcod<=ncovcombmax;cptcod++){
7938: sumnewm[cptcod]=0.;
7939: for (i=1; i<=nlstate;i++){
1.222 brouard 7940: mobaverage[(int)age][i][cptcod] =probs[(int)age][i][cptcod];
7941: for (cpt=1;cpt<=(mob-1)/2;cpt++){
7942: mobaverage[(int)age][i][cptcod] +=probs[(int)age-cpt][i][cptcod];
7943: mobaverage[(int)age][i][cptcod] +=probs[(int)age+cpt][i][cptcod];
7944: }
7945: mobaverage[(int)age][i][cptcod]=mobaverage[(int)age][i][cptcod]/mob;
1.266 brouard 7946: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
7947: } /* end i */
7948: if(sumnewm[cptcod] >1.e-3) mobaverage[(int)age][i][cptcod]=mobaverage[(int)age][i][cptcod]/sumnewm[cptcod]; /* Rescaling to sum one */
7949: } /* end cptcod */
1.222 brouard 7950: }/* end age */
7951: }/* end mob */
1.266 brouard 7952: }else{
7953: printf("Error internal in movingaverage, mobilav=%d.\n",mobilav);
1.222 brouard 7954: return -1;
1.266 brouard 7955: }
7956:
7957: for (cptcod=1;cptcod<=ncovcombmax;cptcod++){ /* for each combination */
1.222 brouard 7958: /* for (age=bage+(mob-1)/2; age<=fage-(mob-1)/2; age++){ */
7959: if(invalidvarcomb[cptcod]){
7960: printf("\nCombination (%d) ignored because no cases \n",cptcod);
7961: continue;
7962: }
1.219 brouard 7963:
1.266 brouard 7964: for (age=fage-(mob-1)/2; age>=bage+(mob-1)/2; age--){ /*looking for the youngest and oldest good age */
7965: sumnewm[cptcod]=0.;
7966: sumnewmr[cptcod]=0.;
7967: for (i=1; i<=nlstate;i++){
7968: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
7969: sumnewmr[cptcod]+=probs[(int)age][i][cptcod];
7970: }
7971: if(fabs(sumnewmr[cptcod] - 1.) <= 1.e-3) { /* good without smoothing */
7972: agemingoodr[cptcod]=age;
7973: }
7974: if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
7975: agemingood[cptcod]=age;
7976: }
7977: } /* age */
7978: for (age=bage+(mob-1)/2; age<=fage-(mob-1)/2; age++){ /*looking for the youngest and oldest good age */
1.222 brouard 7979: sumnewm[cptcod]=0.;
1.266 brouard 7980: sumnewmr[cptcod]=0.;
1.222 brouard 7981: for (i=1; i<=nlstate;i++){
7982: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
1.266 brouard 7983: sumnewmr[cptcod]+=probs[(int)age][i][cptcod];
7984: }
7985: if(fabs(sumnewmr[cptcod] - 1.) <= 1.e-3) { /* good without smoothing */
7986: agemaxgoodr[cptcod]=age;
1.222 brouard 7987: }
7988: if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
1.266 brouard 7989: agemaxgood[cptcod]=age;
7990: }
7991: } /* age */
7992: /* Thus we have agemingood and agemaxgood as well as goodr for raw (preobs) */
7993: /* but they will change */
7994: for (age=fage-(mob-1)/2; age>=bage; age--){/* From oldest to youngest, filling up to the youngest */
7995: sumnewm[cptcod]=0.;
7996: sumnewmr[cptcod]=0.;
7997: for (i=1; i<=nlstate;i++){
7998: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
7999: sumnewmr[cptcod]+=probs[(int)age][i][cptcod];
8000: }
8001: if(mobilav==-1){ /* Forcing raw ages if good else agemingood */
8002: if(fabs(sumnewmr[cptcod] - 1.) <= 1.e-3) { /* good without smoothing */
8003: agemaxgoodr[cptcod]=age; /* age min */
8004: for (i=1; i<=nlstate;i++)
8005: mobaverage[(int)age][i][cptcod]=probs[(int)age][i][cptcod];
8006: }else{ /* bad we change the value with the values of good ages */
8007: for (i=1; i<=nlstate;i++){
8008: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemaxgoodr[cptcod]][i][cptcod];
8009: } /* i */
8010: } /* end bad */
8011: }else{
8012: if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
8013: agemaxgood[cptcod]=age;
8014: }else{ /* bad we change the value with the values of good ages */
8015: for (i=1; i<=nlstate;i++){
8016: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemaxgood[cptcod]][i][cptcod];
8017: } /* i */
8018: } /* end bad */
8019: }/* end else */
8020: sum=0.;sumr=0.;
8021: for (i=1; i<=nlstate;i++){
8022: sum+=mobaverage[(int)age][i][cptcod];
8023: sumr+=probs[(int)age][i][cptcod];
8024: }
8025: if(fabs(sum - 1.) > 1.e-3) { /* bad */
1.268 brouard 8026: printf("Moving average A1: For this combination of covariate cptcod=%d, we can't get a smoothed prevalence which sums to one (%f) at any descending age! age=%d, could you increase bage=%d\n",cptcod,sumr, (int)age, (int)bage);
1.266 brouard 8027: } /* end bad */
8028: /* else{ /\* We found some ages summing to one, we will smooth the oldest *\/ */
8029: if(fabs(sumr - 1.) > 1.e-3) { /* bad */
1.268 brouard 8030: printf("Moving average A2: For this combination of covariate cptcod=%d, the raw prevalence doesn't sums to one (%f) even with smoothed values at young ages! age=%d, could you increase bage=%d\n",cptcod,sumr, (int)age, (int)bage);
1.222 brouard 8031: } /* end bad */
8032: }/* age */
1.266 brouard 8033:
8034: for (age=bage+(mob-1)/2; age<=fage; age++){/* From youngest, finding the oldest wrong */
1.222 brouard 8035: sumnewm[cptcod]=0.;
1.266 brouard 8036: sumnewmr[cptcod]=0.;
1.222 brouard 8037: for (i=1; i<=nlstate;i++){
8038: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
1.266 brouard 8039: sumnewmr[cptcod]+=probs[(int)age][i][cptcod];
8040: }
8041: if(mobilav==-1){ /* Forcing raw ages if good else agemingood */
8042: if(fabs(sumnewmr[cptcod] - 1.) <= 1.e-3) { /* good */
8043: agemingoodr[cptcod]=age;
8044: for (i=1; i<=nlstate;i++)
8045: mobaverage[(int)age][i][cptcod]=probs[(int)age][i][cptcod];
8046: }else{ /* bad we change the value with the values of good ages */
8047: for (i=1; i<=nlstate;i++){
8048: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemingoodr[cptcod]][i][cptcod];
8049: } /* i */
8050: } /* end bad */
8051: }else{
8052: if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
8053: agemingood[cptcod]=age;
8054: }else{ /* bad */
8055: for (i=1; i<=nlstate;i++){
8056: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemingood[cptcod]][i][cptcod];
8057: } /* i */
8058: } /* end bad */
8059: }/* end else */
8060: sum=0.;sumr=0.;
8061: for (i=1; i<=nlstate;i++){
8062: sum+=mobaverage[(int)age][i][cptcod];
8063: sumr+=mobaverage[(int)age][i][cptcod];
1.222 brouard 8064: }
1.266 brouard 8065: if(fabs(sum - 1.) > 1.e-3) { /* bad */
1.268 brouard 8066: printf("Moving average B1: For this combination of covariate cptcod=%d, we can't get a smoothed prevalence which sums to one (%f) at any descending age! age=%d, could you decrease fage=%d?\n",cptcod, sum, (int) age, (int)fage);
1.266 brouard 8067: } /* end bad */
8068: /* else{ /\* We found some ages summing to one, we will smooth the oldest *\/ */
8069: if(fabs(sumr - 1.) > 1.e-3) { /* bad */
1.268 brouard 8070: printf("Moving average B2: For this combination of covariate cptcod=%d, the raw prevalence doesn't sums to one (%f) even with smoothed values at young ages! age=%d, could you increase fage=%d\n",cptcod,sumr, (int)age, (int)fage);
1.222 brouard 8071: } /* end bad */
8072: }/* age */
1.266 brouard 8073:
1.222 brouard 8074:
8075: for (age=bage; age<=fage; age++){
1.235 brouard 8076: /* printf("%d %d ", cptcod, (int)age); */
1.222 brouard 8077: sumnewp[cptcod]=0.;
8078: sumnewm[cptcod]=0.;
8079: for (i=1; i<=nlstate;i++){
8080: sumnewp[cptcod]+=probs[(int)age][i][cptcod];
8081: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
8082: /* printf("%.4f %.4f ",probs[(int)age][i][cptcod], mobaverage[(int)age][i][cptcod]); */
8083: }
8084: /* printf("%.4f %.4f \n",sumnewp[cptcod], sumnewm[cptcod]); */
8085: }
8086: /* printf("\n"); */
8087: /* } */
1.266 brouard 8088:
1.222 brouard 8089: /* brutal averaging */
1.266 brouard 8090: /* for (i=1; i<=nlstate;i++){ */
8091: /* for (age=1; age<=bage; age++){ */
8092: /* mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemingood[cptcod]][i][cptcod]; */
8093: /* /\* printf("age=%d i=%d cptcod=%d mobaverage=%.4f \n",(int)age,i, cptcod, mobaverage[(int)age][i][cptcod]); *\/ */
8094: /* } */
8095: /* for (age=fage; age<=AGESUP; age++){ */
8096: /* mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemaxgood[cptcod]][i][cptcod]; */
8097: /* /\* printf("age=%d i=%d cptcod=%d mobaverage=%.4f \n",(int)age,i, cptcod, mobaverage[(int)age][i][cptcod]); *\/ */
8098: /* } */
8099: /* } /\* end i status *\/ */
8100: /* for (i=nlstate+1; i<=nlstate+ndeath;i++){ */
8101: /* for (age=1; age<=AGESUP; age++){ */
8102: /* /\*printf("i=%d, age=%d, cptcod=%d\n",i, (int)age, cptcod);*\/ */
8103: /* mobaverage[(int)age][i][cptcod]=0.; */
8104: /* } */
8105: /* } */
1.222 brouard 8106: }/* end cptcod */
1.266 brouard 8107: free_vector(agemaxgoodr,1, ncovcombmax);
8108: free_vector(agemaxgood,1, ncovcombmax);
8109: free_vector(agemingood,1, ncovcombmax);
8110: free_vector(agemingoodr,1, ncovcombmax);
8111: free_vector(sumnewmr,1, ncovcombmax);
1.222 brouard 8112: free_vector(sumnewm,1, ncovcombmax);
8113: free_vector(sumnewp,1, ncovcombmax);
8114: return 0;
8115: }/* End movingaverage */
1.218 brouard 8116:
1.126 brouard 8117:
8118: /************** Forecasting ******************/
1.269 brouard 8119: void prevforecast(char fileres[], double anproj1, double mproj1, double jproj1, double ageminpar, double agemax, double dateprev1, double dateprev2, int mobilav, double ***prev, double bage, double fage, int firstpass, int lastpass, double anproj2, double p[], int cptcoveff){
1.126 brouard 8120: /* proj1, year, month, day of starting projection
8121: agemin, agemax range of age
8122: dateprev1 dateprev2 range of dates during which prevalence is computed
8123: anproj2 year of en of projection (same day and month as proj1).
8124: */
1.267 brouard 8125: int yearp, stepsize, hstepm, nhstepm, j, k, cptcod, i, h, i1, k4, nres=0;
1.126 brouard 8126: double agec; /* generic age */
8127: double agelim, ppij, yp,yp1,yp2,jprojmean,mprojmean,anprojmean;
8128: double *popeffectif,*popcount;
8129: double ***p3mat;
1.218 brouard 8130: /* double ***mobaverage; */
1.126 brouard 8131: char fileresf[FILENAMELENGTH];
8132:
8133: agelim=AGESUP;
1.211 brouard 8134: /* Compute observed prevalence between dateprev1 and dateprev2 by counting the number of people
8135: in each health status at the date of interview (if between dateprev1 and dateprev2).
8136: We still use firstpass and lastpass as another selection.
8137: */
1.214 brouard 8138: /* freqsummary(fileres, agemin, agemax, s, agev, nlstate, imx,Tvaraff,nbcode, ncodemax,mint,anint,strstart,\ */
8139: /* firstpass, lastpass, stepm, weightopt, model); */
1.126 brouard 8140:
1.201 brouard 8141: strcpy(fileresf,"F_");
8142: strcat(fileresf,fileresu);
1.126 brouard 8143: if((ficresf=fopen(fileresf,"w"))==NULL) {
8144: printf("Problem with forecast resultfile: %s\n", fileresf);
8145: fprintf(ficlog,"Problem with forecast resultfile: %s\n", fileresf);
8146: }
1.235 brouard 8147: printf("\nComputing forecasting: result on file '%s', please wait... \n", fileresf);
8148: fprintf(ficlog,"\nComputing forecasting: result on file '%s', please wait... \n", fileresf);
1.126 brouard 8149:
1.225 brouard 8150: if (cptcoveff==0) ncodemax[cptcoveff]=1;
1.126 brouard 8151:
8152:
8153: stepsize=(int) (stepm+YEARM-1)/YEARM;
8154: if (stepm<=12) stepsize=1;
8155: if(estepm < stepm){
8156: printf ("Problem %d lower than %d\n",estepm, stepm);
8157: }
1.270 brouard 8158: else{
8159: hstepm=estepm;
8160: }
8161: if(estepm > stepm){ /* Yes every two year */
8162: stepsize=2;
8163: }
1.126 brouard 8164:
8165: hstepm=hstepm/stepm;
8166: yp1=modf(dateintmean,&yp);/* extracts integral of datemean in yp and
8167: fractional in yp1 */
8168: anprojmean=yp;
8169: yp2=modf((yp1*12),&yp);
8170: mprojmean=yp;
8171: yp1=modf((yp2*30.5),&yp);
8172: jprojmean=yp;
8173: if(jprojmean==0) jprojmean=1;
8174: if(mprojmean==0) jprojmean=1;
8175:
1.227 brouard 8176: i1=pow(2,cptcoveff);
1.126 brouard 8177: if (cptcovn < 1){i1=1;}
8178:
8179: fprintf(ficresf,"# Mean day of interviews %.lf/%.lf/%.lf (%.2f) between %.2f and %.2f \n",jprojmean,mprojmean,anprojmean,dateintmean,dateprev1,dateprev2);
8180:
8181: fprintf(ficresf,"#****** Routine prevforecast **\n");
1.227 brouard 8182:
1.126 brouard 8183: /* if (h==(int)(YEARM*yearp)){ */
1.235 brouard 8184: for(nres=1; nres <= nresult; nres++) /* For each resultline */
8185: for(k=1; k<=i1;k++){
1.253 brouard 8186: if(i1 != 1 && TKresult[nres]!= k)
1.235 brouard 8187: continue;
1.227 brouard 8188: if(invalidvarcomb[k]){
8189: printf("\nCombination (%d) projection ignored because no cases \n",k);
8190: continue;
8191: }
8192: fprintf(ficresf,"\n#****** hpijx=probability over h years, hp.jx is weighted by observed prev \n#");
8193: for(j=1;j<=cptcoveff;j++) {
8194: fprintf(ficresf," V%d (=) %d",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
8195: }
1.235 brouard 8196: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
1.238 brouard 8197: fprintf(ficresf," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.235 brouard 8198: }
1.227 brouard 8199: fprintf(ficresf," yearproj age");
8200: for(j=1; j<=nlstate+ndeath;j++){
8201: for(i=1; i<=nlstate;i++)
8202: fprintf(ficresf," p%d%d",i,j);
8203: fprintf(ficresf," wp.%d",j);
8204: }
8205: for (yearp=0; yearp<=(anproj2-anproj1);yearp +=stepsize) {
8206: fprintf(ficresf,"\n");
8207: fprintf(ficresf,"\n# Forecasting at date %.lf/%.lf/%.lf ",jproj1,mproj1,anproj1+yearp);
1.270 brouard 8208: /* for (agec=fage; agec>=(ageminpar-1); agec--){ */
8209: for (agec=fage; agec>=(bage); agec--){
1.227 brouard 8210: nhstepm=(int) rint((agelim-agec)*YEARM/stepm);
8211: nhstepm = nhstepm/hstepm;
8212: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
8213: oldm=oldms;savm=savms;
1.268 brouard 8214: /* We compute pii at age agec over nhstepm);*/
1.235 brouard 8215: hpxij(p3mat,nhstepm,agec,hstepm,p,nlstate,stepm,oldm,savm, k,nres);
1.268 brouard 8216: /* Then we print p3mat for h corresponding to the right agec+h*stepms=yearp */
1.227 brouard 8217: for (h=0; h<=nhstepm; h++){
8218: if (h*hstepm/YEARM*stepm ==yearp) {
1.268 brouard 8219: break;
8220: }
8221: }
8222: fprintf(ficresf,"\n");
8223: for(j=1;j<=cptcoveff;j++)
8224: fprintf(ficresf,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
8225: fprintf(ficresf,"%.f %.f ",anproj1+yearp,agec+h*hstepm/YEARM*stepm);
8226:
8227: for(j=1; j<=nlstate+ndeath;j++) {
8228: ppij=0.;
8229: for(i=1; i<=nlstate;i++) {
8230: /* if (mobilav>=1) */
1.269 brouard 8231: ppij=ppij+p3mat[i][j][h]*prev[(int)agec][i][k];
1.268 brouard 8232: /* else { */ /* even if mobilav==-1 we use mobaverage */
8233: /* ppij=ppij+p3mat[i][j][h]*probs[(int)(agec)][i][k]; */
8234: /* } */
8235: fprintf(ficresf," %.3f", p3mat[i][j][h]);
8236: } /* end i */
8237: fprintf(ficresf," %.3f", ppij);
8238: }/* end j */
1.227 brouard 8239: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
8240: } /* end agec */
1.266 brouard 8241: /* diffyear=(int) anproj1+yearp-ageminpar-1; */
8242: /*printf("Prevforecast %d+%d-%d=diffyear=%d\n",(int) anproj1, (int)yearp,(int)ageminpar,(int) anproj1-(int)ageminpar);*/
1.227 brouard 8243: } /* end yearp */
8244: } /* end k */
1.219 brouard 8245:
1.126 brouard 8246: fclose(ficresf);
1.215 brouard 8247: printf("End of Computing forecasting \n");
8248: fprintf(ficlog,"End of Computing forecasting\n");
8249:
1.126 brouard 8250: }
8251:
1.269 brouard 8252: /************** Back Forecasting ******************/
8253: void prevbackforecast(char fileres[], double ***prevacurrent, double anback1, double mback1, double jback1, double ageminpar, double agemax, double dateprev1, double dateprev2, int mobilav, double bage, double fage, int firstpass, int lastpass, double anback2, double p[], int cptcoveff){
1.267 brouard 8254: /* back1, year, month, day of starting backection
8255: agemin, agemax range of age
8256: dateprev1 dateprev2 range of dates during which prevalence is computed
1.269 brouard 8257: anback2 year of end of backprojection (same day and month as back1).
8258: prevacurrent and prev are prevalences.
1.267 brouard 8259: */
8260: int yearp, stepsize, hstepm, nhstepm, j, k, cptcod, i, h, i1, k4, nres=0;
8261: double agec; /* generic age */
1.268 brouard 8262: double agelim, ppij, ppi, yp,yp1,yp2,jprojmean,mprojmean,anprojmean;
1.267 brouard 8263: double *popeffectif,*popcount;
8264: double ***p3mat;
8265: /* double ***mobaverage; */
8266: char fileresfb[FILENAMELENGTH];
8267:
1.268 brouard 8268: agelim=AGEINF;
1.267 brouard 8269: /* Compute observed prevalence between dateprev1 and dateprev2 by counting the number of people
8270: in each health status at the date of interview (if between dateprev1 and dateprev2).
8271: We still use firstpass and lastpass as another selection.
8272: */
8273: /* freqsummary(fileres, agemin, agemax, s, agev, nlstate, imx,Tvaraff,nbcode, ncodemax,mint,anint,strstart,\ */
8274: /* firstpass, lastpass, stepm, weightopt, model); */
8275:
8276: /*Do we need to compute prevalence again?*/
8277:
8278: /* prevalence(probs, ageminpar, agemax, s, agev, nlstate, imx, Tvar, nbcode, ncodemax, mint, anint, dateprev1, dateprev2, firstpass, lastpass); */
8279:
8280: strcpy(fileresfb,"FB_");
8281: strcat(fileresfb,fileresu);
8282: if((ficresfb=fopen(fileresfb,"w"))==NULL) {
8283: printf("Problem with back forecast resultfile: %s\n", fileresfb);
8284: fprintf(ficlog,"Problem with back forecast resultfile: %s\n", fileresfb);
8285: }
8286: printf("\nComputing back forecasting: result on file '%s', please wait... \n", fileresfb);
8287: fprintf(ficlog,"\nComputing back forecasting: result on file '%s', please wait... \n", fileresfb);
8288:
8289: if (cptcoveff==0) ncodemax[cptcoveff]=1;
8290:
8291:
8292: stepsize=(int) (stepm+YEARM-1)/YEARM;
8293: if (stepm<=12) stepsize=1;
8294: if(estepm < stepm){
8295: printf ("Problem %d lower than %d\n",estepm, stepm);
8296: }
1.270 brouard 8297: else{
8298: hstepm=estepm;
8299: }
8300: if(estepm >= stepm){ /* Yes every two year */
8301: stepsize=2;
8302: }
1.267 brouard 8303:
8304: hstepm=hstepm/stepm;
8305: yp1=modf(dateintmean,&yp);/* extracts integral of datemean in yp and
8306: fractional in yp1 */
8307: anprojmean=yp;
8308: yp2=modf((yp1*12),&yp);
8309: mprojmean=yp;
8310: yp1=modf((yp2*30.5),&yp);
8311: jprojmean=yp;
8312: if(jprojmean==0) jprojmean=1;
8313: if(mprojmean==0) jprojmean=1;
8314:
8315: i1=pow(2,cptcoveff);
8316: if (cptcovn < 1){i1=1;}
8317:
8318: fprintf(ficresfb,"# Mean day of interviews %.lf/%.lf/%.lf (%.2f) between %.2f and %.2f \n",jprojmean,mprojmean,anprojmean,dateintmean,dateprev1,dateprev2);
1.268 brouard 8319: printf("# Mean day of interviews %.lf/%.lf/%.lf (%.2f) between %.2f and %.2f \n",jprojmean,mprojmean,anprojmean,dateintmean,dateprev1,dateprev2);
1.267 brouard 8320:
8321: fprintf(ficresfb,"#****** Routine prevbackforecast **\n");
8322:
8323: for(nres=1; nres <= nresult; nres++) /* For each resultline */
8324: for(k=1; k<=i1;k++){
8325: if(i1 != 1 && TKresult[nres]!= k)
8326: continue;
8327: if(invalidvarcomb[k]){
8328: printf("\nCombination (%d) projection ignored because no cases \n",k);
8329: continue;
8330: }
1.268 brouard 8331: fprintf(ficresfb,"\n#****** hbijx=probability over h years, hb.jx is weighted by observed prev \n#");
1.267 brouard 8332: for(j=1;j<=cptcoveff;j++) {
8333: fprintf(ficresfb," V%d (=) %d",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
8334: }
8335: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
8336: fprintf(ficresf," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
8337: }
8338: fprintf(ficresfb," yearbproj age");
8339: for(j=1; j<=nlstate+ndeath;j++){
8340: for(i=1; i<=nlstate;i++)
1.268 brouard 8341: fprintf(ficresfb," b%d%d",i,j);
8342: fprintf(ficresfb," b.%d",j);
1.267 brouard 8343: }
8344: for (yearp=0; yearp>=(anback2-anback1);yearp -=stepsize) {
8345: /* for (yearp=0; yearp<=(anproj2-anproj1);yearp +=stepsize) { */
8346: fprintf(ficresfb,"\n");
8347: fprintf(ficresfb,"\n# Back Forecasting at date %.lf/%.lf/%.lf ",jback1,mback1,anback1+yearp);
1.271 ! brouard 8348: printf("\n# Back Forecasting at date %.lf/%.lf/%.lf ",jback1,mback1,anback1+yearp);
1.270 brouard 8349: /* for (agec=bage; agec<=agemax-1; agec++){ /\* testing *\/ */
8350: for (agec=bage; agec<=fage; agec++){ /* testing */
1.268 brouard 8351: /* We compute bij at age agec over nhstepm, nhstepm decreases when agec increases because of agemax;*/
1.271 ! brouard 8352: nhstepm=(int) (agec-agelim) *YEARM/stepm;/* nhstepm=(int) rint((agec-agelim)*YEARM/stepm);*/
1.267 brouard 8353: nhstepm = nhstepm/hstepm;
8354: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
8355: oldm=oldms;savm=savms;
1.268 brouard 8356: /* computes hbxij at age agec over 1 to nhstepm */
1.271 ! brouard 8357: /* printf("####prevbackforecast debug agec=%.2f nhstepm=%d\n",agec, nhstepm);fflush(stdout); */
1.267 brouard 8358: hbxij(p3mat,nhstepm,agec,hstepm,p,prevacurrent,nlstate,stepm, k, nres);
1.268 brouard 8359: /* hpxij(p3mat,nhstepm,agec,hstepm,p, nlstate,stepm,oldm,savm, k,nres); */
8360: /* Then we print p3mat for h corresponding to the right agec+h*stepms=yearp */
8361: /* printf(" agec=%.2f\n",agec);fflush(stdout); */
1.267 brouard 8362: for (h=0; h<=nhstepm; h++){
1.268 brouard 8363: if (h*hstepm/YEARM*stepm ==-yearp) {
8364: break;
8365: }
8366: }
8367: fprintf(ficresfb,"\n");
8368: for(j=1;j<=cptcoveff;j++)
8369: fprintf(ficresfb,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
8370: fprintf(ficresfb,"%.f %.f ",anback1+yearp,agec-h*hstepm/YEARM*stepm);
8371: for(i=1; i<=nlstate+ndeath;i++) {
8372: ppij=0.;ppi=0.;
8373: for(j=1; j<=nlstate;j++) {
8374: /* if (mobilav==1) */
1.269 brouard 8375: ppij=ppij+p3mat[i][j][h]*prevacurrent[(int)agec][j][k];
8376: ppi=ppi+prevacurrent[(int)agec][j][k];
8377: /* ppij=ppij+p3mat[i][j][h]*mobaverage[(int)agec][j][k]; */
8378: /* ppi=ppi+mobaverage[(int)agec][j][k]; */
1.267 brouard 8379: /* else { */
8380: /* ppij=ppij+p3mat[i][j][h]*probs[(int)(agec)][i][k]; */
8381: /* } */
1.268 brouard 8382: fprintf(ficresfb," %.3f", p3mat[i][j][h]);
8383: } /* end j */
8384: if(ppi <0.99){
8385: printf("Error in prevbackforecast, prevalence doesn't sum to 1 for state %d: %3f\n",i, ppi);
8386: fprintf(ficlog,"Error in prevbackforecast, prevalence doesn't sum to 1 for state %d: %3f\n",i, ppi);
8387: }
8388: fprintf(ficresfb," %.3f", ppij);
8389: }/* end j */
1.267 brouard 8390: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
8391: } /* end agec */
8392: } /* end yearp */
8393: } /* end k */
1.217 brouard 8394:
1.267 brouard 8395: /* if (mobilav!=0) free_ma3x(mobaverage,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
1.217 brouard 8396:
1.267 brouard 8397: fclose(ficresfb);
8398: printf("End of Computing Back forecasting \n");
8399: fprintf(ficlog,"End of Computing Back forecasting\n");
1.218 brouard 8400:
1.267 brouard 8401: }
1.217 brouard 8402:
1.269 brouard 8403: /* Variance of prevalence limit: varprlim */
8404: void varprlim(char fileresu[], int nresult, double ***prevacurrent, int mobilavproj, double bage, double fage, double **prlim, int *ncvyearp, double ftolpl, double p[], double **matcov, double *delti, int stepm, int cptcoveff){
8405: /*------- Variance of period (stable) prevalence------*/
8406:
8407: char fileresvpl[FILENAMELENGTH];
8408: FILE *ficresvpl;
8409: double **oldm, **savm;
8410: double **varpl; /* Variances of prevalence limits by age */
8411: int i1, k, nres, j ;
8412:
8413: strcpy(fileresvpl,"VPL_");
8414: strcat(fileresvpl,fileresu);
8415: if((ficresvpl=fopen(fileresvpl,"w"))==NULL) {
8416: printf("Problem with variance of period (stable) prevalence resultfile: %s\n", fileresvpl);
8417: exit(0);
8418: }
8419: printf("Computing Variance-covariance of period (stable) prevalence: file '%s' ...", fileresvpl);fflush(stdout);
8420: fprintf(ficlog, "Computing Variance-covariance of period (stable) prevalence: file '%s' ...", fileresvpl);fflush(ficlog);
8421:
8422: /*for(cptcov=1,k=0;cptcov<=i1;cptcov++){
8423: for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){*/
8424:
8425: i1=pow(2,cptcoveff);
8426: if (cptcovn < 1){i1=1;}
8427:
8428: for(nres=1; nres <= nresult; nres++) /* For each resultline */
8429: for(k=1; k<=i1;k++){
8430: if(i1 != 1 && TKresult[nres]!= k)
8431: continue;
8432: fprintf(ficresvpl,"\n#****** ");
8433: printf("\n#****** ");
8434: fprintf(ficlog,"\n#****** ");
8435: for(j=1;j<=cptcoveff;j++) {
8436: fprintf(ficresvpl,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
8437: fprintf(ficlog,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
8438: printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
8439: }
8440: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
8441: printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
8442: fprintf(ficresvpl," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
8443: fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
8444: }
8445: fprintf(ficresvpl,"******\n");
8446: printf("******\n");
8447: fprintf(ficlog,"******\n");
8448:
8449: varpl=matrix(1,nlstate,(int) bage, (int) fage);
8450: oldm=oldms;savm=savms;
8451: varprevlim(fileresvpl, ficresvpl, varpl, matcov, p, delti, nlstate, stepm, (int) bage, (int) fage, oldm, savm, prlim, ftolpl, ncvyearp, k, strstart, nres);
8452: free_matrix(varpl,1,nlstate,(int) bage, (int)fage);
8453: /*}*/
8454: }
8455:
8456: fclose(ficresvpl);
8457: printf("done variance-covariance of period prevalence\n");fflush(stdout);
8458: fprintf(ficlog,"done variance-covariance of period prevalence\n");fflush(ficlog);
8459:
8460: }
8461: /* Variance of back prevalence: varbprlim */
8462: void varbprlim(char fileresu[], int nresult, double ***prevacurrent, int mobilavproj, double bage, double fage, double **bprlim, int *ncvyearp, double ftolpl, double p[], double **matcov, double *delti, int stepm, int cptcoveff){
8463: /*------- Variance of back (stable) prevalence------*/
8464:
8465: char fileresvbl[FILENAMELENGTH];
8466: FILE *ficresvbl;
8467:
8468: double **oldm, **savm;
8469: double **varbpl; /* Variances of back prevalence limits by age */
8470: int i1, k, nres, j ;
8471:
8472: strcpy(fileresvbl,"VBL_");
8473: strcat(fileresvbl,fileresu);
8474: if((ficresvbl=fopen(fileresvbl,"w"))==NULL) {
8475: printf("Problem with variance of back (stable) prevalence resultfile: %s\n", fileresvbl);
8476: exit(0);
8477: }
8478: printf("Computing Variance-covariance of back (stable) prevalence: file '%s' ...", fileresvbl);fflush(stdout);
8479: fprintf(ficlog, "Computing Variance-covariance of back (stable) prevalence: file '%s' ...", fileresvbl);fflush(ficlog);
8480:
8481:
8482: i1=pow(2,cptcoveff);
8483: if (cptcovn < 1){i1=1;}
8484:
8485: for(nres=1; nres <= nresult; nres++) /* For each resultline */
8486: for(k=1; k<=i1;k++){
8487: if(i1 != 1 && TKresult[nres]!= k)
8488: continue;
8489: fprintf(ficresvbl,"\n#****** ");
8490: printf("\n#****** ");
8491: fprintf(ficlog,"\n#****** ");
8492: for(j=1;j<=cptcoveff;j++) {
8493: fprintf(ficresvbl,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
8494: fprintf(ficlog,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
8495: printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
8496: }
8497: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
8498: printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
8499: fprintf(ficresvbl," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
8500: fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
8501: }
8502: fprintf(ficresvbl,"******\n");
8503: printf("******\n");
8504: fprintf(ficlog,"******\n");
8505:
8506: varbpl=matrix(1,nlstate,(int) bage, (int) fage);
8507: oldm=oldms;savm=savms;
8508:
8509: varbrevlim(fileresvbl, ficresvbl, varbpl, matcov, p, delti, nlstate, stepm, (int) bage, (int) fage, oldm, savm, bprlim, ftolpl, mobilavproj, ncvyearp, k, strstart, nres);
8510: free_matrix(varbpl,1,nlstate,(int) bage, (int)fage);
8511: /*}*/
8512: }
8513:
8514: fclose(ficresvbl);
8515: printf("done variance-covariance of back prevalence\n");fflush(stdout);
8516: fprintf(ficlog,"done variance-covariance of back prevalence\n");fflush(ficlog);
8517:
8518: } /* End of varbprlim */
8519:
1.126 brouard 8520: /************** Forecasting *****not tested NB*************/
1.227 brouard 8521: /* 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 8522:
1.227 brouard 8523: /* int cpt, stepsize, hstepm, nhstepm, j,k,c, cptcod, i,h; */
8524: /* int *popage; */
8525: /* double calagedatem, agelim, kk1, kk2; */
8526: /* double *popeffectif,*popcount; */
8527: /* double ***p3mat,***tabpop,***tabpopprev; */
8528: /* /\* double ***mobaverage; *\/ */
8529: /* char filerespop[FILENAMELENGTH]; */
1.126 brouard 8530:
1.227 brouard 8531: /* tabpop= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
8532: /* tabpopprev= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
8533: /* agelim=AGESUP; */
8534: /* calagedatem=(anpyram+mpyram/12.+jpyram/365.-dateintmean)*YEARM; */
1.126 brouard 8535:
1.227 brouard 8536: /* prevalence(probs, ageminpar, agemax, s, agev, nlstate, imx, Tvar, nbcode, ncodemax, mint, anint, dateprev1, dateprev2, firstpass, lastpass); */
1.126 brouard 8537:
8538:
1.227 brouard 8539: /* strcpy(filerespop,"POP_"); */
8540: /* strcat(filerespop,fileresu); */
8541: /* if((ficrespop=fopen(filerespop,"w"))==NULL) { */
8542: /* printf("Problem with forecast resultfile: %s\n", filerespop); */
8543: /* fprintf(ficlog,"Problem with forecast resultfile: %s\n", filerespop); */
8544: /* } */
8545: /* printf("Computing forecasting: result on file '%s' \n", filerespop); */
8546: /* fprintf(ficlog,"Computing forecasting: result on file '%s' \n", filerespop); */
1.126 brouard 8547:
1.227 brouard 8548: /* if (cptcoveff==0) ncodemax[cptcoveff]=1; */
1.126 brouard 8549:
1.227 brouard 8550: /* /\* if (mobilav!=0) { *\/ */
8551: /* /\* mobaverage= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); *\/ */
8552: /* /\* if (movingaverage(probs, ageminpar, fage, mobaverage,mobilav)!=0){ *\/ */
8553: /* /\* fprintf(ficlog," Error in movingaverage mobilav=%d\n",mobilav); *\/ */
8554: /* /\* printf(" Error in movingaverage mobilav=%d\n",mobilav); *\/ */
8555: /* /\* } *\/ */
8556: /* /\* } *\/ */
1.126 brouard 8557:
1.227 brouard 8558: /* stepsize=(int) (stepm+YEARM-1)/YEARM; */
8559: /* if (stepm<=12) stepsize=1; */
1.126 brouard 8560:
1.227 brouard 8561: /* agelim=AGESUP; */
1.126 brouard 8562:
1.227 brouard 8563: /* hstepm=1; */
8564: /* hstepm=hstepm/stepm; */
1.218 brouard 8565:
1.227 brouard 8566: /* if (popforecast==1) { */
8567: /* if((ficpop=fopen(popfile,"r"))==NULL) { */
8568: /* printf("Problem with population file : %s\n",popfile);exit(0); */
8569: /* fprintf(ficlog,"Problem with population file : %s\n",popfile);exit(0); */
8570: /* } */
8571: /* popage=ivector(0,AGESUP); */
8572: /* popeffectif=vector(0,AGESUP); */
8573: /* popcount=vector(0,AGESUP); */
1.126 brouard 8574:
1.227 brouard 8575: /* i=1; */
8576: /* while ((c=fscanf(ficpop,"%d %lf\n",&popage[i],&popcount[i])) != EOF) i=i+1; */
1.218 brouard 8577:
1.227 brouard 8578: /* imx=i; */
8579: /* for (i=1; i<imx;i++) popeffectif[popage[i]]=popcount[i]; */
8580: /* } */
1.218 brouard 8581:
1.227 brouard 8582: /* for(cptcov=1,k=0;cptcov<=i2;cptcov++){ */
8583: /* for(cptcod=1;cptcod<=ncodemax[cptcoveff];cptcod++){ */
8584: /* k=k+1; */
8585: /* fprintf(ficrespop,"\n#******"); */
8586: /* for(j=1;j<=cptcoveff;j++) { */
8587: /* fprintf(ficrespop," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]); */
8588: /* } */
8589: /* fprintf(ficrespop,"******\n"); */
8590: /* fprintf(ficrespop,"# Age"); */
8591: /* for(j=1; j<=nlstate+ndeath;j++) fprintf(ficrespop," P.%d",j); */
8592: /* if (popforecast==1) fprintf(ficrespop," [Population]"); */
1.126 brouard 8593:
1.227 brouard 8594: /* for (cpt=0; cpt<=0;cpt++) { */
8595: /* fprintf(ficrespop,"\n\n# Forecasting at date %.lf/%.lf/%.lf ",jpyram,mpyram,anpyram+cpt); */
1.126 brouard 8596:
1.227 brouard 8597: /* for (agedeb=(fage-((int)calagedatem %12/12.)); agedeb>=(ageminpar-((int)calagedatem %12)/12.); agedeb--){ */
8598: /* nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); */
8599: /* nhstepm = nhstepm/hstepm; */
1.126 brouard 8600:
1.227 brouard 8601: /* p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
8602: /* oldm=oldms;savm=savms; */
8603: /* hpxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k); */
1.218 brouard 8604:
1.227 brouard 8605: /* for (h=0; h<=nhstepm; h++){ */
8606: /* if (h==(int) (calagedatem+YEARM*cpt)) { */
8607: /* fprintf(ficrespop,"\n %3.f ",agedeb+h*hstepm/YEARM*stepm); */
8608: /* } */
8609: /* for(j=1; j<=nlstate+ndeath;j++) { */
8610: /* kk1=0.;kk2=0; */
8611: /* for(i=1; i<=nlstate;i++) { */
8612: /* if (mobilav==1) */
8613: /* kk1=kk1+p3mat[i][j][h]*mobaverage[(int)agedeb+1][i][cptcod]; */
8614: /* else { */
8615: /* kk1=kk1+p3mat[i][j][h]*probs[(int)(agedeb+1)][i][cptcod]; */
8616: /* } */
8617: /* } */
8618: /* if (h==(int)(calagedatem+12*cpt)){ */
8619: /* tabpop[(int)(agedeb)][j][cptcod]=kk1; */
8620: /* /\*fprintf(ficrespop," %.3f", kk1); */
8621: /* if (popforecast==1) fprintf(ficrespop," [%.f]", kk1*popeffectif[(int)agedeb+1]);*\/ */
8622: /* } */
8623: /* } */
8624: /* for(i=1; i<=nlstate;i++){ */
8625: /* kk1=0.; */
8626: /* for(j=1; j<=nlstate;j++){ */
8627: /* kk1= kk1+tabpop[(int)(agedeb)][j][cptcod]; */
8628: /* } */
8629: /* tabpopprev[(int)(agedeb)][i][cptcod]=tabpop[(int)(agedeb)][i][cptcod]/kk1*popeffectif[(int)(agedeb+(calagedatem+12*cpt)*hstepm/YEARM*stepm-1)]; */
8630: /* } */
1.218 brouard 8631:
1.227 brouard 8632: /* if (h==(int)(calagedatem+12*cpt)) */
8633: /* for(j=1; j<=nlstate;j++) */
8634: /* fprintf(ficrespop," %15.2f",tabpopprev[(int)(agedeb+1)][j][cptcod]); */
8635: /* } */
8636: /* free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
8637: /* } */
8638: /* } */
1.218 brouard 8639:
1.227 brouard 8640: /* /\******\/ */
1.218 brouard 8641:
1.227 brouard 8642: /* for (cpt=1; cpt<=(anpyram1-anpyram);cpt++) { */
8643: /* fprintf(ficrespop,"\n\n# Forecasting at date %.lf/%.lf/%.lf ",jpyram,mpyram,anpyram+cpt); */
8644: /* for (agedeb=(fage-((int)calagedatem %12/12.)); agedeb>=(ageminpar-((int)calagedatem %12)/12.); agedeb--){ */
8645: /* nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); */
8646: /* nhstepm = nhstepm/hstepm; */
1.126 brouard 8647:
1.227 brouard 8648: /* p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
8649: /* oldm=oldms;savm=savms; */
8650: /* hpxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k); */
8651: /* for (h=0; h<=nhstepm; h++){ */
8652: /* if (h==(int) (calagedatem+YEARM*cpt)) { */
8653: /* fprintf(ficresf,"\n %3.f ",agedeb+h*hstepm/YEARM*stepm); */
8654: /* } */
8655: /* for(j=1; j<=nlstate+ndeath;j++) { */
8656: /* kk1=0.;kk2=0; */
8657: /* for(i=1; i<=nlstate;i++) { */
8658: /* kk1=kk1+p3mat[i][j][h]*tabpopprev[(int)agedeb+1][i][cptcod]; */
8659: /* } */
8660: /* if (h==(int)(calagedatem+12*cpt)) fprintf(ficresf," %15.2f", kk1); */
8661: /* } */
8662: /* } */
8663: /* free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
8664: /* } */
8665: /* } */
8666: /* } */
8667: /* } */
1.218 brouard 8668:
1.227 brouard 8669: /* /\* if (mobilav!=0) free_ma3x(mobaverage,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); *\/ */
1.218 brouard 8670:
1.227 brouard 8671: /* if (popforecast==1) { */
8672: /* free_ivector(popage,0,AGESUP); */
8673: /* free_vector(popeffectif,0,AGESUP); */
8674: /* free_vector(popcount,0,AGESUP); */
8675: /* } */
8676: /* free_ma3x(tabpop,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
8677: /* free_ma3x(tabpopprev,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
8678: /* fclose(ficrespop); */
8679: /* } /\* End of popforecast *\/ */
1.218 brouard 8680:
1.126 brouard 8681: int fileappend(FILE *fichier, char *optionfich)
8682: {
8683: if((fichier=fopen(optionfich,"a"))==NULL) {
8684: printf("Problem with file: %s\n", optionfich);
8685: fprintf(ficlog,"Problem with file: %s\n", optionfich);
8686: return (0);
8687: }
8688: fflush(fichier);
8689: return (1);
8690: }
8691:
8692:
8693: /**************** function prwizard **********************/
8694: void prwizard(int ncovmodel, int nlstate, int ndeath, char model[], FILE *ficparo)
8695: {
8696:
8697: /* Wizard to print covariance matrix template */
8698:
1.164 brouard 8699: char ca[32], cb[32];
8700: int i,j, k, li, lj, lk, ll, jj, npar, itimes;
1.126 brouard 8701: int numlinepar;
8702:
8703: printf("# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
8704: fprintf(ficparo,"# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
8705: for(i=1; i <=nlstate; i++){
8706: jj=0;
8707: for(j=1; j <=nlstate+ndeath; j++){
8708: if(j==i) continue;
8709: jj++;
8710: /*ca[0]= k+'a'-1;ca[1]='\0';*/
8711: printf("%1d%1d",i,j);
8712: fprintf(ficparo,"%1d%1d",i,j);
8713: for(k=1; k<=ncovmodel;k++){
8714: /* printf(" %lf",param[i][j][k]); */
8715: /* fprintf(ficparo," %lf",param[i][j][k]); */
8716: printf(" 0.");
8717: fprintf(ficparo," 0.");
8718: }
8719: printf("\n");
8720: fprintf(ficparo,"\n");
8721: }
8722: }
8723: printf("# Scales (for hessian or gradient estimation)\n");
8724: fprintf(ficparo,"# Scales (for hessian or gradient estimation)\n");
8725: npar= (nlstate+ndeath-1)*nlstate*ncovmodel; /* Number of parameters*/
8726: for(i=1; i <=nlstate; i++){
8727: jj=0;
8728: for(j=1; j <=nlstate+ndeath; j++){
8729: if(j==i) continue;
8730: jj++;
8731: fprintf(ficparo,"%1d%1d",i,j);
8732: printf("%1d%1d",i,j);
8733: fflush(stdout);
8734: for(k=1; k<=ncovmodel;k++){
8735: /* printf(" %le",delti3[i][j][k]); */
8736: /* fprintf(ficparo," %le",delti3[i][j][k]); */
8737: printf(" 0.");
8738: fprintf(ficparo," 0.");
8739: }
8740: numlinepar++;
8741: printf("\n");
8742: fprintf(ficparo,"\n");
8743: }
8744: }
8745: printf("# Covariance matrix\n");
8746: /* # 121 Var(a12)\n\ */
8747: /* # 122 Cov(b12,a12) Var(b12)\n\ */
8748: /* # 131 Cov(a13,a12) Cov(a13,b12, Var(a13)\n\ */
8749: /* # 132 Cov(b13,a12) Cov(b13,b12, Cov(b13,a13) Var(b13)\n\ */
8750: /* # 212 Cov(a21,a12) Cov(a21,b12, Cov(a21,a13) Cov(a21,b13) Var(a21)\n\ */
8751: /* # 212 Cov(b21,a12) Cov(b21,b12, Cov(b21,a13) Cov(b21,b13) Cov(b21,a21) Var(b21)\n\ */
8752: /* # 232 Cov(a23,a12) Cov(a23,b12, Cov(a23,a13) Cov(a23,b13) Cov(a23,a21) Cov(a23,b21) Var(a23)\n\ */
8753: /* # 232 Cov(b23,a12) Cov(b23,b12) ... Var (b23)\n" */
8754: fflush(stdout);
8755: fprintf(ficparo,"# Covariance matrix\n");
8756: /* # 121 Var(a12)\n\ */
8757: /* # 122 Cov(b12,a12) Var(b12)\n\ */
8758: /* # ...\n\ */
8759: /* # 232 Cov(b23,a12) Cov(b23,b12) ... Var (b23)\n" */
8760:
8761: for(itimes=1;itimes<=2;itimes++){
8762: jj=0;
8763: for(i=1; i <=nlstate; i++){
8764: for(j=1; j <=nlstate+ndeath; j++){
8765: if(j==i) continue;
8766: for(k=1; k<=ncovmodel;k++){
8767: jj++;
8768: ca[0]= k+'a'-1;ca[1]='\0';
8769: if(itimes==1){
8770: printf("#%1d%1d%d",i,j,k);
8771: fprintf(ficparo,"#%1d%1d%d",i,j,k);
8772: }else{
8773: printf("%1d%1d%d",i,j,k);
8774: fprintf(ficparo,"%1d%1d%d",i,j,k);
8775: /* printf(" %.5le",matcov[i][j]); */
8776: }
8777: ll=0;
8778: for(li=1;li <=nlstate; li++){
8779: for(lj=1;lj <=nlstate+ndeath; lj++){
8780: if(lj==li) continue;
8781: for(lk=1;lk<=ncovmodel;lk++){
8782: ll++;
8783: if(ll<=jj){
8784: cb[0]= lk +'a'-1;cb[1]='\0';
8785: if(ll<jj){
8786: if(itimes==1){
8787: printf(" Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
8788: fprintf(ficparo," Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
8789: }else{
8790: printf(" 0.");
8791: fprintf(ficparo," 0.");
8792: }
8793: }else{
8794: if(itimes==1){
8795: printf(" Var(%s%1d%1d)",ca,i,j);
8796: fprintf(ficparo," Var(%s%1d%1d)",ca,i,j);
8797: }else{
8798: printf(" 0.");
8799: fprintf(ficparo," 0.");
8800: }
8801: }
8802: }
8803: } /* end lk */
8804: } /* end lj */
8805: } /* end li */
8806: printf("\n");
8807: fprintf(ficparo,"\n");
8808: numlinepar++;
8809: } /* end k*/
8810: } /*end j */
8811: } /* end i */
8812: } /* end itimes */
8813:
8814: } /* end of prwizard */
8815: /******************* Gompertz Likelihood ******************************/
8816: double gompertz(double x[])
8817: {
8818: double A,B,L=0.0,sump=0.,num=0.;
8819: int i,n=0; /* n is the size of the sample */
8820:
1.220 brouard 8821: for (i=1;i<=imx ; i++) {
1.126 brouard 8822: sump=sump+weight[i];
8823: /* sump=sump+1;*/
8824: num=num+1;
8825: }
8826:
8827:
8828: /* for (i=0; i<=imx; i++)
8829: 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]);*/
8830:
8831: for (i=1;i<=imx ; i++)
8832: {
8833: if (cens[i] == 1 && wav[i]>1)
8834: A=-x[1]/(x[2])*(exp(x[2]*(agecens[i]-agegomp))-exp(x[2]*(ageexmed[i]-agegomp)));
8835:
8836: if (cens[i] == 0 && wav[i]>1)
8837: A=-x[1]/(x[2])*(exp(x[2]*(agedc[i]-agegomp))-exp(x[2]*(ageexmed[i]-agegomp)))
8838: +log(x[1]/YEARM)+x[2]*(agedc[i]-agegomp)+log(YEARM);
8839:
8840: /*if (wav[i] > 1 && agecens[i] > 15) {*/ /* ??? */
8841: if (wav[i] > 1 ) { /* ??? */
8842: L=L+A*weight[i];
8843: /* 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]);*/
8844: }
8845: }
8846:
8847: /*printf("x1=%2.9f x2=%2.9f x3=%2.9f L=%f\n",x[1],x[2],x[3],L);*/
8848:
8849: return -2*L*num/sump;
8850: }
8851:
1.136 brouard 8852: #ifdef GSL
8853: /******************* Gompertz_f Likelihood ******************************/
8854: double gompertz_f(const gsl_vector *v, void *params)
8855: {
8856: double A,B,LL=0.0,sump=0.,num=0.;
8857: double *x= (double *) v->data;
8858: int i,n=0; /* n is the size of the sample */
8859:
8860: for (i=0;i<=imx-1 ; i++) {
8861: sump=sump+weight[i];
8862: /* sump=sump+1;*/
8863: num=num+1;
8864: }
8865:
8866:
8867: /* for (i=0; i<=imx; i++)
8868: 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]);*/
8869: printf("x[0]=%lf x[1]=%lf\n",x[0],x[1]);
8870: for (i=1;i<=imx ; i++)
8871: {
8872: if (cens[i] == 1 && wav[i]>1)
8873: A=-x[0]/(x[1])*(exp(x[1]*(agecens[i]-agegomp))-exp(x[1]*(ageexmed[i]-agegomp)));
8874:
8875: if (cens[i] == 0 && wav[i]>1)
8876: A=-x[0]/(x[1])*(exp(x[1]*(agedc[i]-agegomp))-exp(x[1]*(ageexmed[i]-agegomp)))
8877: +log(x[0]/YEARM)+x[1]*(agedc[i]-agegomp)+log(YEARM);
8878:
8879: /*if (wav[i] > 1 && agecens[i] > 15) {*/ /* ??? */
8880: if (wav[i] > 1 ) { /* ??? */
8881: LL=LL+A*weight[i];
8882: /* 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]);*/
8883: }
8884: }
8885:
8886: /*printf("x1=%2.9f x2=%2.9f x3=%2.9f L=%f\n",x[1],x[2],x[3],L);*/
8887: printf("x[0]=%lf x[1]=%lf -2*LL*num/sump=%lf\n",x[0],x[1],-2*LL*num/sump);
8888:
8889: return -2*LL*num/sump;
8890: }
8891: #endif
8892:
1.126 brouard 8893: /******************* Printing html file ***********/
1.201 brouard 8894: void printinghtmlmort(char fileresu[], char title[], char datafile[], int firstpass, \
1.126 brouard 8895: int lastpass, int stepm, int weightopt, char model[],\
8896: int imx, double p[],double **matcov,double agemortsup){
8897: int i,k;
8898:
8899: fprintf(fichtm,"<ul><li><h4>Result files </h4>\n Force of mortality. Parameters of the Gompertz fit (with confidence interval in brackets):<br>");
8900: fprintf(fichtm," mu(age) =%lf*exp(%lf*(age-%d)) per year<br><br>",p[1],p[2],agegomp);
8901: for (i=1;i<=2;i++)
8902: 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 8903: fprintf(fichtm,"<br><br><img src=\"graphmort.svg\">");
1.126 brouard 8904: fprintf(fichtm,"</ul>");
8905:
8906: fprintf(fichtm,"<ul><li><h4>Life table</h4>\n <br>");
8907:
8908: 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>");
8909:
8910: for (k=agegomp;k<(agemortsup-2);k++)
8911: 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]);
8912:
8913:
8914: fflush(fichtm);
8915: }
8916:
8917: /******************* Gnuplot file **************/
1.201 brouard 8918: void printinggnuplotmort(char fileresu[], char optionfilefiname[], double ageminpar, double agemaxpar, double fage , char pathc[], double p[]){
1.126 brouard 8919:
8920: char dirfileres[132],optfileres[132];
1.164 brouard 8921:
1.126 brouard 8922: int ng;
8923:
8924:
8925: /*#ifdef windows */
8926: fprintf(ficgp,"cd \"%s\" \n",pathc);
8927: /*#endif */
8928:
8929:
8930: strcpy(dirfileres,optionfilefiname);
8931: strcpy(optfileres,"vpl");
1.199 brouard 8932: fprintf(ficgp,"set out \"graphmort.svg\"\n ");
1.126 brouard 8933: fprintf(ficgp,"set xlabel \"Age\"\n set ylabel \"Force of mortality (per year)\" \n ");
1.199 brouard 8934: fprintf(ficgp, "set ter svg size 640, 480\n set log y\n");
1.145 brouard 8935: /* fprintf(ficgp, "set size 0.65,0.65\n"); */
1.126 brouard 8936: fprintf(ficgp,"plot [%d:100] %lf*exp(%lf*(x-%d))",agegomp,p[1],p[2],agegomp);
8937:
8938: }
8939:
1.136 brouard 8940: int readdata(char datafile[], int firstobs, int lastobs, int *imax)
8941: {
1.126 brouard 8942:
1.136 brouard 8943: /*-------- data file ----------*/
8944: FILE *fic;
8945: char dummy[]=" ";
1.240 brouard 8946: int i=0, j=0, n=0, iv=0, v;
1.223 brouard 8947: int lstra;
1.136 brouard 8948: int linei, month, year,iout;
8949: char line[MAXLINE], linetmp[MAXLINE];
1.164 brouard 8950: char stra[MAXLINE], strb[MAXLINE];
1.136 brouard 8951: char *stratrunc;
1.223 brouard 8952:
1.240 brouard 8953: DummyV=ivector(1,NCOVMAX); /* 1 to 3 */
8954: FixedV=ivector(1,NCOVMAX); /* 1 to 3 */
1.126 brouard 8955:
1.240 brouard 8956: for(v=1; v <=ncovcol;v++){
8957: DummyV[v]=0;
8958: FixedV[v]=0;
8959: }
8960: for(v=ncovcol+1; v <=ncovcol+nqv;v++){
8961: DummyV[v]=1;
8962: FixedV[v]=0;
8963: }
8964: for(v=ncovcol+nqv+1; v <=ncovcol+nqv+ntv;v++){
8965: DummyV[v]=0;
8966: FixedV[v]=1;
8967: }
8968: for(v=ncovcol+nqv+ntv+1; v <=ncovcol+nqv+ntv+nqtv;v++){
8969: DummyV[v]=1;
8970: FixedV[v]=1;
8971: }
8972: for(v=1; v <=ncovcol+nqv+ntv+nqtv;v++){
8973: printf("Covariate type in the data: V%d, DummyV(V%d)=%d, FixedV(V%d)=%d\n",v,v,DummyV[v],v,FixedV[v]);
8974: 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]);
8975: }
1.126 brouard 8976:
1.136 brouard 8977: if((fic=fopen(datafile,"r"))==NULL) {
1.218 brouard 8978: printf("Problem while opening datafile: %s with errno='%s'\n", datafile,strerror(errno));fflush(stdout);
8979: fprintf(ficlog,"Problem while opening datafile: %s with errno='%s'\n", datafile,strerror(errno));fflush(ficlog);return 1;
1.136 brouard 8980: }
1.126 brouard 8981:
1.136 brouard 8982: i=1;
8983: linei=0;
8984: while ((fgets(line, MAXLINE, fic) != NULL) &&((i >= firstobs) && (i <=lastobs))) {
8985: linei=linei+1;
8986: for(j=strlen(line); j>=0;j--){ /* Untabifies line */
8987: if(line[j] == '\t')
8988: line[j] = ' ';
8989: }
8990: for(j=strlen(line)-1; (line[j]==' ')||(line[j]==10)||(line[j]==13);j--){
8991: ;
8992: };
8993: line[j+1]=0; /* Trims blanks at end of line */
8994: if(line[0]=='#'){
8995: fprintf(ficlog,"Comment line\n%s\n",line);
8996: printf("Comment line\n%s\n",line);
8997: continue;
8998: }
8999: trimbb(linetmp,line); /* Trims multiple blanks in line */
1.164 brouard 9000: strcpy(line, linetmp);
1.223 brouard 9001:
9002: /* Loops on waves */
9003: for (j=maxwav;j>=1;j--){
9004: for (iv=nqtv;iv>=1;iv--){ /* Loop on time varying quantitative variables */
1.238 brouard 9005: cutv(stra, strb, line, ' ');
9006: if(strb[0]=='.') { /* Missing value */
9007: lval=-1;
9008: cotqvar[j][iv][i]=-1; /* 0.0/0.0 */
9009: cotvar[j][ntv+iv][i]=-1; /* For performance reasons */
9010: if(isalpha(strb[1])) { /* .m or .d Really Missing value */
9011: 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);
9012: 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);
9013: return 1;
9014: }
9015: }else{
9016: errno=0;
9017: /* what_kind_of_number(strb); */
9018: dval=strtod(strb,&endptr);
9019: /* if( strb[0]=='\0' || (*endptr != '\0')){ */
9020: /* if(strb != endptr && *endptr == '\0') */
9021: /* dval=dlval; */
9022: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN)) */
9023: if( strb[0]=='\0' || (*endptr != '\0')){
9024: 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);
9025: 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);
9026: return 1;
9027: }
9028: cotqvar[j][iv][i]=dval;
9029: cotvar[j][ntv+iv][i]=dval;
9030: }
9031: strcpy(line,stra);
1.223 brouard 9032: }/* end loop ntqv */
1.225 brouard 9033:
1.223 brouard 9034: for (iv=ntv;iv>=1;iv--){ /* Loop on time varying dummies */
1.238 brouard 9035: cutv(stra, strb, line, ' ');
9036: if(strb[0]=='.') { /* Missing value */
9037: lval=-1;
9038: }else{
9039: errno=0;
9040: lval=strtol(strb,&endptr,10);
9041: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN))*/
9042: if( strb[0]=='\0' || (*endptr != '\0')){
9043: 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);
9044: 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);
9045: return 1;
9046: }
9047: }
9048: if(lval <-1 || lval >1){
9049: printf("Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.223 brouard 9050: Should be a value of %d(nth) covariate (0 should be the value for the reference and 1\n \
9051: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.238 brouard 9052: For example, for multinomial values like 1, 2 and 3,\n \
9053: build V1=0 V2=0 for the reference value (1),\n \
9054: V1=1 V2=0 for (2) \n \
1.223 brouard 9055: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.238 brouard 9056: output of IMaCh is often meaningless.\n \
1.223 brouard 9057: Exiting.\n",lval,linei, i,line,j);
1.238 brouard 9058: fprintf(ficlog,"Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.223 brouard 9059: Should be a value of %d(nth) covariate (0 should be the value for the reference and 1\n \
9060: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.238 brouard 9061: For example, for multinomial values like 1, 2 and 3,\n \
9062: build V1=0 V2=0 for the reference value (1),\n \
9063: V1=1 V2=0 for (2) \n \
1.223 brouard 9064: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.238 brouard 9065: output of IMaCh is often meaningless.\n \
1.223 brouard 9066: Exiting.\n",lval,linei, i,line,j);fflush(ficlog);
1.238 brouard 9067: return 1;
9068: }
9069: cotvar[j][iv][i]=(double)(lval);
9070: strcpy(line,stra);
1.223 brouard 9071: }/* end loop ntv */
1.225 brouard 9072:
1.223 brouard 9073: /* Statuses at wave */
1.137 brouard 9074: cutv(stra, strb, line, ' ');
1.223 brouard 9075: if(strb[0]=='.') { /* Missing value */
1.238 brouard 9076: lval=-1;
1.136 brouard 9077: }else{
1.238 brouard 9078: errno=0;
9079: lval=strtol(strb,&endptr,10);
9080: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN))*/
9081: if( strb[0]=='\0' || (*endptr != '\0')){
9082: 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);
9083: 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);
9084: return 1;
9085: }
1.136 brouard 9086: }
1.225 brouard 9087:
1.136 brouard 9088: s[j][i]=lval;
1.225 brouard 9089:
1.223 brouard 9090: /* Date of Interview */
1.136 brouard 9091: strcpy(line,stra);
9092: cutv(stra, strb,line,' ');
1.169 brouard 9093: if( (iout=sscanf(strb,"%d/%d",&month, &year)) != 0){
1.136 brouard 9094: }
1.169 brouard 9095: else if( (iout=sscanf(strb,"%s.",dummy)) != 0){
1.225 brouard 9096: month=99;
9097: year=9999;
1.136 brouard 9098: }else{
1.225 brouard 9099: 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);
9100: 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);
9101: return 1;
1.136 brouard 9102: }
9103: anint[j][i]= (double) year;
9104: mint[j][i]= (double)month;
9105: strcpy(line,stra);
1.223 brouard 9106: } /* End loop on waves */
1.225 brouard 9107:
1.223 brouard 9108: /* Date of death */
1.136 brouard 9109: cutv(stra, strb,line,' ');
1.169 brouard 9110: if( (iout=sscanf(strb,"%d/%d",&month, &year)) != 0){
1.136 brouard 9111: }
1.169 brouard 9112: else if( (iout=sscanf(strb,"%s.",dummy)) != 0){
1.136 brouard 9113: month=99;
9114: year=9999;
9115: }else{
1.141 brouard 9116: 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 9117: 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);
9118: return 1;
1.136 brouard 9119: }
9120: andc[i]=(double) year;
9121: moisdc[i]=(double) month;
9122: strcpy(line,stra);
9123:
1.223 brouard 9124: /* Date of birth */
1.136 brouard 9125: cutv(stra, strb,line,' ');
1.169 brouard 9126: if( (iout=sscanf(strb,"%d/%d",&month, &year)) != 0){
1.136 brouard 9127: }
1.169 brouard 9128: else if( (iout=sscanf(strb,"%s.", dummy)) != 0){
1.136 brouard 9129: month=99;
9130: year=9999;
9131: }else{
1.141 brouard 9132: 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);
9133: 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 9134: return 1;
1.136 brouard 9135: }
9136: if (year==9999) {
1.141 brouard 9137: 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);
9138: 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 9139: return 1;
9140:
1.136 brouard 9141: }
9142: annais[i]=(double)(year);
9143: moisnais[i]=(double)(month);
9144: strcpy(line,stra);
1.225 brouard 9145:
1.223 brouard 9146: /* Sample weight */
1.136 brouard 9147: cutv(stra, strb,line,' ');
9148: errno=0;
9149: dval=strtod(strb,&endptr);
9150: if( strb[0]=='\0' || (*endptr != '\0')){
1.141 brouard 9151: printf("Error reading data around '%f' at line number %d, \"%s\" for individual %d\nShould be a weight. Exiting.\n",dval, i,line,linei);
9152: 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 9153: fflush(ficlog);
9154: return 1;
9155: }
9156: weight[i]=dval;
9157: strcpy(line,stra);
1.225 brouard 9158:
1.223 brouard 9159: for (iv=nqv;iv>=1;iv--){ /* Loop on fixed quantitative variables */
9160: cutv(stra, strb, line, ' ');
9161: if(strb[0]=='.') { /* Missing value */
1.225 brouard 9162: lval=-1;
1.223 brouard 9163: }else{
1.225 brouard 9164: errno=0;
9165: /* what_kind_of_number(strb); */
9166: dval=strtod(strb,&endptr);
9167: /* if(strb != endptr && *endptr == '\0') */
9168: /* dval=dlval; */
9169: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN)) */
9170: if( strb[0]=='\0' || (*endptr != '\0')){
9171: 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);
9172: 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);
9173: return 1;
9174: }
9175: coqvar[iv][i]=dval;
1.226 brouard 9176: covar[ncovcol+iv][i]=dval; /* including qvar in standard covar for performance reasons */
1.223 brouard 9177: }
9178: strcpy(line,stra);
9179: }/* end loop nqv */
1.136 brouard 9180:
1.223 brouard 9181: /* Covariate values */
1.136 brouard 9182: for (j=ncovcol;j>=1;j--){
9183: cutv(stra, strb,line,' ');
1.223 brouard 9184: if(strb[0]=='.') { /* Missing covariate value */
1.225 brouard 9185: lval=-1;
1.136 brouard 9186: }else{
1.225 brouard 9187: errno=0;
9188: lval=strtol(strb,&endptr,10);
9189: if( strb[0]=='\0' || (*endptr != '\0')){
9190: 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);
9191: 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);
9192: return 1;
9193: }
1.136 brouard 9194: }
9195: if(lval <-1 || lval >1){
1.225 brouard 9196: printf("Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.136 brouard 9197: Should be a value of %d(nth) covariate (0 should be the value for the reference and 1\n \
9198: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.225 brouard 9199: For example, for multinomial values like 1, 2 and 3,\n \
9200: build V1=0 V2=0 for the reference value (1),\n \
9201: V1=1 V2=0 for (2) \n \
1.136 brouard 9202: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.225 brouard 9203: output of IMaCh is often meaningless.\n \
1.136 brouard 9204: Exiting.\n",lval,linei, i,line,j);
1.225 brouard 9205: fprintf(ficlog,"Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.136 brouard 9206: Should be a value of %d(nth) covariate (0 should be the value for the reference and 1\n \
9207: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.225 brouard 9208: For example, for multinomial values like 1, 2 and 3,\n \
9209: build V1=0 V2=0 for the reference value (1),\n \
9210: V1=1 V2=0 for (2) \n \
1.136 brouard 9211: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.225 brouard 9212: output of IMaCh is often meaningless.\n \
1.136 brouard 9213: Exiting.\n",lval,linei, i,line,j);fflush(ficlog);
1.225 brouard 9214: return 1;
1.136 brouard 9215: }
9216: covar[j][i]=(double)(lval);
9217: strcpy(line,stra);
9218: }
9219: lstra=strlen(stra);
1.225 brouard 9220:
1.136 brouard 9221: if(lstra > 9){ /* More than 2**32 or max of what printf can write with %ld */
9222: stratrunc = &(stra[lstra-9]);
9223: num[i]=atol(stratrunc);
9224: }
9225: else
9226: num[i]=atol(stra);
9227: /*if((s[2][i]==2) && (s[3][i]==-1)&&(s[4][i]==9)){
9228: 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;}*/
9229:
9230: i=i+1;
9231: } /* End loop reading data */
1.225 brouard 9232:
1.136 brouard 9233: *imax=i-1; /* Number of individuals */
9234: fclose(fic);
1.225 brouard 9235:
1.136 brouard 9236: return (0);
1.164 brouard 9237: /* endread: */
1.225 brouard 9238: printf("Exiting readdata: ");
9239: fclose(fic);
9240: return (1);
1.223 brouard 9241: }
1.126 brouard 9242:
1.234 brouard 9243: void removefirstspace(char **stri){/*, char stro[]) {*/
1.230 brouard 9244: char *p1 = *stri, *p2 = *stri;
1.235 brouard 9245: while (*p2 == ' ')
1.234 brouard 9246: p2++;
9247: /* while ((*p1++ = *p2++) !=0) */
9248: /* ; */
9249: /* do */
9250: /* while (*p2 == ' ') */
9251: /* p2++; */
9252: /* while (*p1++ == *p2++); */
9253: *stri=p2;
1.145 brouard 9254: }
9255:
1.235 brouard 9256: int decoderesult ( char resultline[], int nres)
1.230 brouard 9257: /**< This routine decode one result line and returns the combination # of dummy covariates only **/
9258: {
1.235 brouard 9259: int j=0, k=0, k1=0, k2=0, k3=0, k4=0, match=0, k2q=0, k3q=0, k4q=0;
1.230 brouard 9260: char resultsav[MAXLINE];
1.234 brouard 9261: int resultmodel[MAXLINE];
9262: int modelresult[MAXLINE];
1.230 brouard 9263: char stra[80], strb[80], strc[80], strd[80],stre[80];
9264:
1.234 brouard 9265: removefirstspace(&resultline);
1.233 brouard 9266: printf("decoderesult:%s\n",resultline);
1.230 brouard 9267:
9268: if (strstr(resultline,"v") !=0){
9269: printf("Error. 'v' must be in upper case 'V' result: %s ",resultline);
9270: fprintf(ficlog,"Error. 'v' must be in upper case result: %s ",resultline);fflush(ficlog);
9271: return 1;
9272: }
9273: trimbb(resultsav, resultline);
9274: if (strlen(resultsav) >1){
9275: j=nbocc(resultsav,'='); /**< j=Number of covariate values'=' */
9276: }
1.253 brouard 9277: if(j == 0){ /* Resultline but no = */
9278: TKresult[nres]=0; /* Combination for the nresult and the model */
9279: return (0);
9280: }
9281:
1.234 brouard 9282: if( j != cptcovs ){ /* Be careful if a variable is in a product but not single */
9283: 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);
9284: 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);
9285: }
9286: for(k=1; k<=j;k++){ /* Loop on any covariate of the result line */
9287: if(nbocc(resultsav,'=') >1){
9288: cutl(stra,strb,resultsav,' '); /* keeps in strb after the first ' '
9289: resultsav= V4=1 V5=25.1 V3=0 strb=V3=0 stra= V4=1 V5=25.1 */
9290: cutl(strc,strd,strb,'='); /* strb:V4=1 strc=1 strd=V4 */
9291: }else
9292: cutl(strc,strd,resultsav,'=');
1.230 brouard 9293: Tvalsel[k]=atof(strc); /* 1 */
1.234 brouard 9294:
1.230 brouard 9295: cutl(strc,stre,strd,'V'); /* strd='V4' strc=4 stre='V' */;
9296: Tvarsel[k]=atoi(strc);
9297: /* Typevarsel[k]=1; /\* 1 for age product *\/ */
9298: /* cptcovsel++; */
9299: if (nbocc(stra,'=') >0)
9300: strcpy(resultsav,stra); /* and analyzes it */
9301: }
1.235 brouard 9302: /* Checking for missing or useless values in comparison of current model needs */
1.236 brouard 9303: for(k1=1; k1<= cptcovt ;k1++){ /* model line V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
9304: if(Typevar[k1]==0){ /* Single covariate in model */
1.234 brouard 9305: match=0;
1.236 brouard 9306: for(k2=1; k2 <=j;k2++){/* result line V4=1 V5=24.1 V3=1 V2=8 V1=0 */
1.237 brouard 9307: if(Tvar[k1]==Tvarsel[k2]) {/* Tvar[1]=5 == Tvarsel[2]=5 */
1.236 brouard 9308: modelresult[k2]=k1;/* modelresult[2]=1 modelresult[1]=2 modelresult[3]=3 modelresult[6]=4 modelresult[9]=5 */
1.234 brouard 9309: match=1;
9310: break;
9311: }
9312: }
9313: if(match == 0){
9314: printf("Error in result line: %d value missing; result: %s, model=%s\n",k1, resultline, model);
9315: }
9316: }
9317: }
1.235 brouard 9318: /* Checking for missing or useless values in comparison of current model needs */
9319: for(k2=1; k2 <=j;k2++){ /* result line V4=1 V5=24.1 V3=1 V2=8 V1=0 */
1.234 brouard 9320: match=0;
1.235 brouard 9321: for(k1=1; k1<= cptcovt ;k1++){ /* model line V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
9322: if(Typevar[k1]==0){ /* Single */
1.237 brouard 9323: if(Tvar[k1]==Tvarsel[k2]) { /* Tvar[2]=4 == Tvarsel[1]=4 */
1.235 brouard 9324: resultmodel[k1]=k2; /* resultmodel[2]=1 resultmodel[1]=2 resultmodel[3]=3 resultmodel[6]=4 resultmodel[9]=5 */
1.234 brouard 9325: ++match;
9326: }
9327: }
9328: }
9329: if(match == 0){
9330: printf("Error in result line: %d value missing; result: %s, model=%s\n",k1, resultline, model);
9331: }else if(match > 1){
9332: printf("Error in result line: %d doubled; result: %s, model=%s\n",k2, resultline, model);
9333: }
9334: }
1.235 brouard 9335:
1.234 brouard 9336: /* We need to deduce which combination number is chosen and save quantitative values */
1.235 brouard 9337: /* model line V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
9338: /* result line V4=1 V5=25.1 V3=0 V2=8 V1=1 */
9339: /* should give a combination of dummy V4=1, V3=0, V1=1 => V4*2**(0) + V3*2**(1) + V1*2**(2) = 5 + (1offset) = 6*/
9340: /* result line V4=1 V5=24.1 V3=1 V2=8 V1=0 */
9341: /* should give a combination of dummy V4=1, V3=1, V1=0 => V4*2**(0) + V3*2**(1) + V1*2**(2) = 3 + (1offset) = 4*/
9342: /* 1 0 0 0 */
9343: /* 2 1 0 0 */
9344: /* 3 0 1 0 */
9345: /* 4 1 1 0 */ /* V4=1, V3=1, V1=0 */
9346: /* 5 0 0 1 */
9347: /* 6 1 0 1 */ /* V4=1, V3=0, V1=1 */
9348: /* 7 0 1 1 */
9349: /* 8 1 1 1 */
1.237 brouard 9350: /* V(Tvresult)=Tresult V4=1 V3=0 V1=1 Tresult[nres=1][2]=0 */
9351: /* V(Tvqresult)=Tqresult V5=25.1 V2=8 Tqresult[nres=1][1]=25.1 */
9352: /* V5*age V5 known which value for nres? */
9353: /* Tqinvresult[2]=8 Tqinvresult[1]=25.1 */
1.235 brouard 9354: for(k1=1, k=0, k4=0, k4q=0; k1 <=cptcovt;k1++){ /* model line */
9355: if( Dummy[k1]==0 && Typevar[k1]==0 ){ /* Single dummy */
1.237 brouard 9356: k3= resultmodel[k1]; /* resultmodel[2(V4)] = 1=k3 */
1.235 brouard 9357: k2=(int)Tvarsel[k3]; /* Tvarsel[resultmodel[2]]= Tvarsel[1] = 4=k2 */
9358: k+=Tvalsel[k3]*pow(2,k4); /* Tvalsel[1]=1 */
1.237 brouard 9359: Tresult[nres][k4+1]=Tvalsel[k3];/* Tresult[nres][1]=1(V4=1) Tresult[nres][2]=0(V3=0) */
9360: Tvresult[nres][k4+1]=(int)Tvarsel[k3];/* Tvresult[nres][1]=4 Tvresult[nres][3]=1 */
9361: Tinvresult[nres][(int)Tvarsel[k3]]=Tvalsel[k3]; /* Tinvresult[nres][4]=1 */
1.235 brouard 9362: printf("Decoderesult Dummy k=%d, V(k2=V%d)= Tvalsel[%d]=%d, 2**(%d)\n",k, k2, k3, (int)Tvalsel[k3], k4);
9363: k4++;;
9364: } else if( Dummy[k1]==1 && Typevar[k1]==0 ){ /* Single quantitative */
9365: k3q= resultmodel[k1]; /* resultmodel[2] = 1=k3 */
9366: k2q=(int)Tvarsel[k3q]; /* Tvarsel[resultmodel[2]]= Tvarsel[1] = 4=k2 */
1.237 brouard 9367: Tqresult[nres][k4q+1]=Tvalsel[k3q]; /* Tqresult[nres][1]=25.1 */
9368: Tvqresult[nres][k4q+1]=(int)Tvarsel[k3q]; /* Tvqresult[nres][1]=5 */
9369: Tqinvresult[nres][(int)Tvarsel[k3q]]=Tvalsel[k3q]; /* Tqinvresult[nres][5]=25.1 */
1.235 brouard 9370: printf("Decoderesult Quantitative nres=%d, V(k2q=V%d)= Tvalsel[%d]=%d, Tvarsel[%d]=%f\n",nres, k2q, k3q, Tvarsel[k3q], k3q, Tvalsel[k3q]);
9371: k4q++;;
9372: }
9373: }
1.234 brouard 9374:
1.235 brouard 9375: TKresult[nres]=++k; /* Combination for the nresult and the model */
1.230 brouard 9376: return (0);
9377: }
1.235 brouard 9378:
1.230 brouard 9379: int decodemodel( char model[], int lastobs)
9380: /**< This routine decodes the model and returns:
1.224 brouard 9381: * Model V1+V2+V3+V8+V7*V8+V5*V6+V8*age+V3*age+age*age
9382: * - nagesqr = 1 if age*age in the model, otherwise 0.
9383: * - cptcovt total number of covariates of the model nbocc(+)+1 = 8 excepting constant and age and age*age
9384: * - cptcovn or number of covariates k of the models excluding age*products =6 and age*age
9385: * - cptcovage number of covariates with age*products =2
9386: * - cptcovs number of simple covariates
9387: * - 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
9388: * which is a new column after the 9 (ncovcol) variables.
9389: * - if k is a product Vn*Vm covar[k][i] is filled with correct values for each individual
9390: * - Tprod[l] gives the kth covariates of the product Vn*Vm l=1 to cptcovprod-cptcovage
9391: * Tprod[1]@2 {5, 6}: position of first product V7*V8 is 5, and second V5*V6 is 6.
9392: * - Tvard[k] p Tvard[1][1]@4 {7, 8, 5, 6} for V7*V8 and V5*V6 .
9393: */
1.136 brouard 9394: {
1.238 brouard 9395: int i, j, k, ks, v;
1.227 brouard 9396: int j1, k1, k2, k3, k4;
1.136 brouard 9397: char modelsav[80];
1.145 brouard 9398: char stra[80], strb[80], strc[80], strd[80],stre[80];
1.187 brouard 9399: char *strpt;
1.136 brouard 9400:
1.145 brouard 9401: /*removespace(model);*/
1.136 brouard 9402: if (strlen(model) >1){ /* If there is at least 1 covariate */
1.145 brouard 9403: j=0, j1=0, k1=0, k2=-1, ks=0, cptcovn=0;
1.137 brouard 9404: if (strstr(model,"AGE") !=0){
1.192 brouard 9405: printf("Error. AGE must be in lower case 'age' model=1+age+%s. ",model);
9406: fprintf(ficlog,"Error. AGE must be in lower case model=1+age+%s. ",model);fflush(ficlog);
1.136 brouard 9407: return 1;
9408: }
1.141 brouard 9409: if (strstr(model,"v") !=0){
9410: printf("Error. 'v' must be in upper case 'V' model=%s ",model);
9411: fprintf(ficlog,"Error. 'v' must be in upper case model=%s ",model);fflush(ficlog);
9412: return 1;
9413: }
1.187 brouard 9414: strcpy(modelsav,model);
9415: if ((strpt=strstr(model,"age*age")) !=0){
9416: printf(" strpt=%s, model=%s\n",strpt, model);
9417: if(strpt != model){
1.234 brouard 9418: printf("Error in model: 'model=%s'; 'age*age' should in first place before other covariates\n \
1.192 brouard 9419: 'model=1+age+age*age+V1.' or 'model=1+age+age*age+V1+V1*age.', please swap as well as \n \
1.187 brouard 9420: corresponding column of parameters.\n",model);
1.234 brouard 9421: fprintf(ficlog,"Error in model: 'model=%s'; 'age*age' should in first place before other covariates\n \
1.192 brouard 9422: 'model=1+age+age*age+V1.' or 'model=1+age+age*age+V1+V1*age.', please swap as well as \n \
1.187 brouard 9423: corresponding column of parameters.\n",model); fflush(ficlog);
1.234 brouard 9424: return 1;
1.225 brouard 9425: }
1.187 brouard 9426: nagesqr=1;
9427: if (strstr(model,"+age*age") !=0)
1.234 brouard 9428: substrchaine(modelsav, model, "+age*age");
1.187 brouard 9429: else if (strstr(model,"age*age+") !=0)
1.234 brouard 9430: substrchaine(modelsav, model, "age*age+");
1.187 brouard 9431: else
1.234 brouard 9432: substrchaine(modelsav, model, "age*age");
1.187 brouard 9433: }else
9434: nagesqr=0;
9435: if (strlen(modelsav) >1){
9436: j=nbocc(modelsav,'+'); /**< j=Number of '+' */
9437: j1=nbocc(modelsav,'*'); /**< j1=Number of '*' */
1.224 brouard 9438: cptcovs=j+1-j1; /**< Number of simple covariates V1+V1*age+V3 +V3*V4+age*age=> V1 + V3 =5-3=2 */
1.187 brouard 9439: cptcovt= j+1; /* Number of total covariates in the model, not including
1.225 brouard 9440: * cst, age and age*age
9441: * V1+V1*age+ V3 + V3*V4+age*age=> 3+1=4*/
9442: /* including age products which are counted in cptcovage.
9443: * but the covariates which are products must be treated
9444: * separately: ncovn=4- 2=2 (V1+V3). */
1.187 brouard 9445: cptcovprod=j1; /**< Number of products V1*V2 +v3*age = 2 */
9446: cptcovprodnoage=0; /**< Number of covariate products without age: V3*V4 =1 */
1.225 brouard 9447:
9448:
1.187 brouard 9449: /* Design
9450: * V1 V2 V3 V4 V5 V6 V7 V8 V9 Weight
9451: * < ncovcol=8 >
9452: * Model V2 + V1 + V3*age + V3 + V5*V6 + V7*V8 + V8*age + V8
9453: * k= 1 2 3 4 5 6 7 8
9454: * cptcovn number of covariates (not including constant and age ) = # of + plus 1 = 7+1=8
9455: * covar[k,i], value of kth covariate if not including age for individual i:
1.224 brouard 9456: * covar[1][i]= (V1), covar[4][i]=(V4), covar[8][i]=(V8)
9457: * Tvar[k] # of the kth covariate: Tvar[1]=2 Tvar[2]=1 Tvar[4]=3 Tvar[8]=8
1.187 brouard 9458: * if multiplied by age: V3*age Tvar[3=V3*age]=3 (V3) Tvar[7]=8 and
9459: * Tage[++cptcovage]=k
9460: * if products, new covar are created after ncovcol with k1
9461: * Tvar[k]=ncovcol+k1; # of the kth covariate product: Tvar[5]=ncovcol+1=10 Tvar[6]=ncovcol+1=11
9462: * Tprod[k1]=k; Tprod[1]=5 Tprod[2]= 6; gives the position of the k1th product
9463: * 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
9464: * Tvar[cptcovn+k2]=Tvard[k1][1];Tvar[cptcovn+k2+1]=Tvard[k1][2];
9465: * Tvar[8+1]=5;Tvar[8+2]=6;Tvar[8+3]=7;Tvar[8+4]=8 inverted
9466: * V1 V2 V3 V4 V5 V6 V7 V8 V9 V10 V11
9467: * < ncovcol=8 >
9468: * Model V2 + V1 + V3*age + V3 + V5*V6 + V7*V8 + V8*age + V8 d1 d1 d2 d2
9469: * k= 1 2 3 4 5 6 7 8 9 10 11 12
9470: * Tvar[k]= 2 1 3 3 10 11 8 8 5 6 7 8
9471: * p Tvar[1]@12={2, 1, 3, 3, 11, 10, 8, 8, 7, 8, 5, 6}
9472: * p Tprod[1]@2={ 6, 5}
9473: *p Tvard[1][1]@4= {7, 8, 5, 6}
9474: * covar[k][i]= V2 V1 ? V3 V5*V6? V7*V8? ? V8
9475: * cov[Tage[kk]+2]=covar[Tvar[Tage[kk]]][i]*cov[2];
9476: *How to reorganize?
9477: * Model V1 + V2 + V3 + V8 + V5*V6 + V7*V8 + V3*age + V8*age
9478: * Tvars {2, 1, 3, 3, 11, 10, 8, 8, 7, 8, 5, 6}
9479: * {2, 1, 4, 8, 5, 6, 3, 7}
9480: * Struct []
9481: */
1.225 brouard 9482:
1.187 brouard 9483: /* This loop fills the array Tvar from the string 'model'.*/
9484: /* j is the number of + signs in the model V1+V2+V3 j=2 i=3 to 1 */
9485: /* modelsav=V2+V1+V4+age*V3 strb=age*V3 stra=V2+V1+V4 */
9486: /* k=4 (age*V3) Tvar[k=4]= 3 (from V3) Tage[cptcovage=1]=4 */
9487: /* k=3 V4 Tvar[k=3]= 4 (from V4) */
9488: /* k=2 V1 Tvar[k=2]= 1 (from V1) */
9489: /* k=1 Tvar[1]=2 (from V2) */
9490: /* k=5 Tvar[5] */
9491: /* for (k=1; k<=cptcovn;k++) { */
1.198 brouard 9492: /* cov[2+k]=nbcode[Tvar[k]][codtabm(ij,Tvar[k])]; */
1.187 brouard 9493: /* } */
1.198 brouard 9494: /* for (k=1; k<=cptcovage;k++) cov[2+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,Tvar[Tage[k])]]*cov[2]; */
1.187 brouard 9495: /*
9496: * Treating invertedly V2+V1+V3*age+V2*V4 is as if written V2*V4 +V3*age + V1 + V2 */
1.227 brouard 9497: for(k=cptcovt; k>=1;k--){ /**< Number of covariates not including constant and age, neither age*age*/
9498: Tvar[k]=0; Tprod[k]=0; Tposprod[k]=0;
9499: }
1.187 brouard 9500: cptcovage=0;
9501: for(k=1; k<=cptcovt;k++){ /* Loop on total covariates of the model */
1.234 brouard 9502: cutl(stra,strb,modelsav,'+'); /* keeps in strb after the first '+'
1.225 brouard 9503: modelsav==V2+V1+V4+V3*age strb=V3*age stra=V2+V1+V4 */
1.234 brouard 9504: if (nbocc(modelsav,'+')==0) strcpy(strb,modelsav); /* and analyzes it */
9505: /* printf("i=%d a=%s b=%s sav=%s\n",i, stra,strb,modelsav);*/
9506: /*scanf("%d",i);*/
9507: if (strchr(strb,'*')) { /**< Model includes a product V2+V1+V4+V3*age strb=V3*age */
9508: cutl(strc,strd,strb,'*'); /**< strd*strc Vm*Vn: strb=V3*age(input) strc=age strd=V3 ; V3*V2 strc=V2, strd=V3 */
9509: if (strcmp(strc,"age")==0) { /**< Model includes age: Vn*age */
9510: /* covar is not filled and then is empty */
9511: cptcovprod--;
9512: cutl(stre,strb,strd,'V'); /* strd=V3(input): stre="3" */
9513: Tvar[k]=atoi(stre); /* V2+V1+V4+V3*age Tvar[4]=3 ; V1+V2*age Tvar[2]=2; V1+V1*age Tvar[2]=1 */
9514: Typevar[k]=1; /* 1 for age product */
9515: cptcovage++; /* Sums the number of covariates which include age as a product */
9516: Tage[cptcovage]=k; /* Tvar[4]=3, Tage[1] = 4 or V1+V1*age Tvar[2]=1, Tage[1]=2 */
9517: /*printf("stre=%s ", stre);*/
9518: } else if (strcmp(strd,"age")==0) { /* or age*Vn */
9519: cptcovprod--;
9520: cutl(stre,strb,strc,'V');
9521: Tvar[k]=atoi(stre);
9522: Typevar[k]=1; /* 1 for age product */
9523: cptcovage++;
9524: Tage[cptcovage]=k;
9525: } else { /* Age is not in the model product V2+V1+V1*V4+V3*age+V3*V2 strb=V3*V2*/
9526: /* loops on k1=1 (V3*V2) and k1=2 V4*V3 */
9527: cptcovn++;
9528: cptcovprodnoage++;k1++;
9529: cutl(stre,strb,strc,'V'); /* strc= Vn, stre is n; strb=V3*V2 stre=3 strc=*/
9530: Tvar[k]=ncovcol+nqv+ntv+nqtv+k1; /* For model-covariate k tells which data-covariate to use but
9531: because this model-covariate is a construction we invent a new column
9532: which is after existing variables ncovcol+nqv+ntv+nqtv + k1
9533: If already ncovcol=4 and model=V2+V1+V1*V4+age*V3+V3*V2
9534: Tvar[3=V1*V4]=4+1 Tvar[5=V3*V2]=4 + 2= 6, etc */
9535: Typevar[k]=2; /* 2 for double fixed dummy covariates */
9536: cutl(strc,strb,strd,'V'); /* strd was Vm, strc is m */
9537: Tprod[k1]=k; /* Tprod[1]=3(=V1*V4) for V2+V1+V1*V4+age*V3+V3*V2 */
9538: Tposprod[k]=k1; /* Tpsprod[3]=1, Tposprod[2]=5 */
9539: Tvard[k1][1] =atoi(strc); /* m 1 for V1*/
9540: Tvard[k1][2] =atoi(stre); /* n 4 for V4*/
9541: k2=k2+2; /* k2 is initialize to -1, We want to store the n and m in Vn*Vm at the end of Tvar */
9542: /* Tvar[cptcovt+k2]=Tvard[k1][1]; /\* Tvar[(cptcovt=4+k2=1)=5]= 1 (V1) *\/ */
9543: /* Tvar[cptcovt+k2+1]=Tvard[k1][2]; /\* Tvar[(cptcovt=4+(k2=1)+1)=6]= 4 (V4) *\/ */
1.225 brouard 9544: /*ncovcol=4 and model=V2+V1+V1*V4+age*V3+V3*V2, Tvar[3]=5, Tvar[4]=6, cptcovt=5 */
1.234 brouard 9545: /* 1 2 3 4 5 | Tvar[5+1)=1, Tvar[7]=2 */
9546: for (i=1; i<=lastobs;i++){
9547: /* Computes the new covariate which is a product of
9548: covar[n][i]* covar[m][i] and stores it at ncovol+k1 May not be defined */
9549: covar[ncovcol+k1][i]=covar[atoi(stre)][i]*covar[atoi(strc)][i];
9550: }
9551: } /* End age is not in the model */
9552: } /* End if model includes a product */
9553: else { /* no more sum */
9554: /*printf("d=%s c=%s b=%s\n", strd,strc,strb);*/
9555: /* scanf("%d",i);*/
9556: cutl(strd,strc,strb,'V');
9557: ks++; /**< Number of simple covariates dummy or quantitative, fixe or varying */
9558: cptcovn++; /** V4+V3+V5: V4 and V3 timevarying dummy covariates, V5 timevarying quantitative */
9559: Tvar[k]=atoi(strd);
9560: Typevar[k]=0; /* 0 for simple covariates */
9561: }
9562: strcpy(modelsav,stra); /* modelsav=V2+V1+V4 stra=V2+V1+V4 */
1.223 brouard 9563: /*printf("a=%s b=%s sav=%s\n", stra,strb,modelsav);
1.225 brouard 9564: scanf("%d",i);*/
1.187 brouard 9565: } /* end of loop + on total covariates */
9566: } /* end if strlen(modelsave == 0) age*age might exist */
9567: } /* end if strlen(model == 0) */
1.136 brouard 9568:
9569: /*The number n of Vn is stored in Tvar. cptcovage =number of age covariate. Tage gives the position of age. cptcovprod= number of products.
9570: If model=V1+V1*age then Tvar[1]=1 Tvar[2]=1 cptcovage=1 Tage[1]=2 cptcovprod=0*/
1.225 brouard 9571:
1.136 brouard 9572: /* printf("tvar1=%d tvar2=%d tvar3=%d cptcovage=%d Tage=%d",Tvar[1],Tvar[2],Tvar[3],cptcovage,Tage[1]);
1.225 brouard 9573: printf("cptcovprod=%d ", cptcovprod);
9574: fprintf(ficlog,"cptcovprod=%d ", cptcovprod);
9575: scanf("%d ",i);*/
9576:
9577:
1.230 brouard 9578: /* Until here, decodemodel knows only the grammar (simple, product, age*) of the model but not what kind
9579: of variable (dummy vs quantitative, fixed vs time varying) is behind. But we know the # of each. */
1.226 brouard 9580: /* ncovcol= 1, nqv=1 | ntv=2, nqtv= 1 = 5 possible variables data: 2 fixed 3, varying
9581: model= V5 + V4 +V3 + V4*V3 + V5*age + V2 + V1*V2 + V1*age + V5*age, V1 is not used saving its place
9582: k = 1 2 3 4 5 6 7 8 9
9583: Tvar[k]= 5 4 3 1+1+2+1+1=6 5 2 7 1 5
9584: Typevar[k]= 0 0 0 2 1 0 2 1 1
1.227 brouard 9585: Fixed[k] 1 1 1 1 3 0 0 or 2 2 3
9586: Dummy[k] 1 0 0 0 3 1 1 2 3
9587: Tmodelind[combination of covar]=k;
1.225 brouard 9588: */
9589: /* Dispatching between quantitative and time varying covariates */
1.226 brouard 9590: /* If Tvar[k] >ncovcol it is a product */
1.225 brouard 9591: /* 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 9592: /* Computing effective variables, ie used by the model, that is from the cptcovt variables */
1.227 brouard 9593: printf("Model=%s\n\
9594: Typevar: 0 for simple covariate (dummy, quantitative, fixed or varying), 1 for age product, 2 for product \n\
9595: Fixed[k] 0=fixed (product or simple), 1 varying, 2 fixed with age product, 3 varying with age product \n\
9596: 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);
9597: fprintf(ficlog,"Model=%s\n\
9598: Typevar: 0 for simple covariate (dummy, quantitative, fixed or varying), 1 for age product, 2 for product \n\
9599: Fixed[k] 0=fixed (product or simple), 1 varying, 2 fixed with age product, 3 varying with age product \n\
9600: 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 9601: for(k=1;k<=cptcovt; k++){ Fixed[k]=0; Dummy[k]=0;}
1.234 brouard 9602: 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 */
9603: if (Tvar[k] <=ncovcol && Typevar[k]==0 ){ /* Simple fixed dummy (<=ncovcol) covariates */
1.227 brouard 9604: Fixed[k]= 0;
9605: Dummy[k]= 0;
1.225 brouard 9606: ncoveff++;
1.232 brouard 9607: ncovf++;
1.234 brouard 9608: nsd++;
9609: modell[k].maintype= FTYPE;
9610: TvarsD[nsd]=Tvar[k];
9611: TvarsDind[nsd]=k;
9612: TvarF[ncovf]=Tvar[k];
9613: TvarFind[ncovf]=k;
9614: TvarFD[ncoveff]=Tvar[k]; /* TvarFD[1]=V1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
9615: TvarFDind[ncoveff]=k; /* TvarFDind[1]=9 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
9616: }else if( Tvar[k] <=ncovcol && Typevar[k]==2){ /* Product of fixed dummy (<=ncovcol) covariates */
9617: Fixed[k]= 0;
9618: Dummy[k]= 0;
9619: ncoveff++;
9620: ncovf++;
9621: modell[k].maintype= FTYPE;
9622: TvarF[ncovf]=Tvar[k];
9623: TvarFind[ncovf]=k;
1.230 brouard 9624: TvarFD[ncoveff]=Tvar[k]; /* TvarFD[1]=V1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1.231 brouard 9625: TvarFDind[ncoveff]=k; /* TvarFDind[1]=9 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1.240 brouard 9626: }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 9627: Fixed[k]= 0;
9628: Dummy[k]= 1;
1.230 brouard 9629: nqfveff++;
1.234 brouard 9630: modell[k].maintype= FTYPE;
9631: modell[k].subtype= FQ;
9632: nsq++;
9633: TvarsQ[nsq]=Tvar[k];
9634: TvarsQind[nsq]=k;
1.232 brouard 9635: ncovf++;
1.234 brouard 9636: TvarF[ncovf]=Tvar[k];
9637: TvarFind[ncovf]=k;
1.231 brouard 9638: 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 9639: 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 9640: }else if( Tvar[k] <=ncovcol+nqv+ntv && Typevar[k]==0){/* Only simple time varying dummy variables */
1.227 brouard 9641: Fixed[k]= 1;
9642: Dummy[k]= 0;
1.225 brouard 9643: ntveff++; /* Only simple time varying dummy variable */
1.234 brouard 9644: modell[k].maintype= VTYPE;
9645: modell[k].subtype= VD;
9646: nsd++;
9647: TvarsD[nsd]=Tvar[k];
9648: TvarsDind[nsd]=k;
9649: ncovv++; /* Only simple time varying variables */
9650: TvarV[ncovv]=Tvar[k];
1.242 brouard 9651: 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 9652: 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 */
9653: 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 9654: 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);
9655: printf("Quasi TmodelInvind[%d]=%d\n",k,Tvar[k]- ncovcol-nqv);
1.231 brouard 9656: }else if( Tvar[k] <=ncovcol+nqv+ntv+nqtv && Typevar[k]==0){ /* Only simple time varying quantitative variable V5*/
1.234 brouard 9657: Fixed[k]= 1;
9658: Dummy[k]= 1;
9659: nqtveff++;
9660: modell[k].maintype= VTYPE;
9661: modell[k].subtype= VQ;
9662: ncovv++; /* Only simple time varying variables */
9663: nsq++;
9664: TvarsQ[nsq]=Tvar[k];
9665: TvarsQind[nsq]=k;
9666: TvarV[ncovv]=Tvar[k];
1.242 brouard 9667: 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 9668: 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 */
9669: 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 9670: TmodelInvQind[nqtveff]=Tvar[k]- ncovcol-nqv-ntv;/* Only simple time varying quantitative variable */
9671: /* Tmodeliqind[k]=nqtveff;/\* Only simple time varying quantitative variable *\/ */
9672: 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 9673: printf("Quasi TmodelInvQind[%d]=%d\n",k,Tvar[k]- ncovcol-nqv-ntv);
1.227 brouard 9674: }else if (Typevar[k] == 1) { /* product with age */
1.234 brouard 9675: ncova++;
9676: TvarA[ncova]=Tvar[k];
9677: TvarAind[ncova]=k;
1.231 brouard 9678: if (Tvar[k] <=ncovcol ){ /* Product age with fixed dummy covariatee */
1.240 brouard 9679: Fixed[k]= 2;
9680: Dummy[k]= 2;
9681: modell[k].maintype= ATYPE;
9682: modell[k].subtype= APFD;
9683: /* ncoveff++; */
1.227 brouard 9684: }else if( Tvar[k] <=ncovcol+nqv) { /* Remind that product Vn*Vm are added in k*/
1.240 brouard 9685: Fixed[k]= 2;
9686: Dummy[k]= 3;
9687: modell[k].maintype= ATYPE;
9688: modell[k].subtype= APFQ; /* Product age * fixed quantitative */
9689: /* nqfveff++; /\* Only simple fixed quantitative variable *\/ */
1.227 brouard 9690: }else if( Tvar[k] <=ncovcol+nqv+ntv ){
1.240 brouard 9691: Fixed[k]= 3;
9692: Dummy[k]= 2;
9693: modell[k].maintype= ATYPE;
9694: modell[k].subtype= APVD; /* Product age * varying dummy */
9695: /* ntveff++; /\* Only simple time varying dummy variable *\/ */
1.227 brouard 9696: }else if( Tvar[k] <=ncovcol+nqv+ntv+nqtv){
1.240 brouard 9697: Fixed[k]= 3;
9698: Dummy[k]= 3;
9699: modell[k].maintype= ATYPE;
9700: modell[k].subtype= APVQ; /* Product age * varying quantitative */
9701: /* nqtveff++;/\* Only simple time varying quantitative variable *\/ */
1.227 brouard 9702: }
9703: }else if (Typevar[k] == 2) { /* product without age */
9704: k1=Tposprod[k];
9705: if(Tvard[k1][1] <=ncovcol){
1.240 brouard 9706: if(Tvard[k1][2] <=ncovcol){
9707: Fixed[k]= 1;
9708: Dummy[k]= 0;
9709: modell[k].maintype= FTYPE;
9710: modell[k].subtype= FPDD; /* Product fixed dummy * fixed dummy */
9711: ncovf++; /* Fixed variables without age */
9712: TvarF[ncovf]=Tvar[k];
9713: TvarFind[ncovf]=k;
9714: }else if(Tvard[k1][2] <=ncovcol+nqv){
9715: Fixed[k]= 0; /* or 2 ?*/
9716: Dummy[k]= 1;
9717: modell[k].maintype= FTYPE;
9718: modell[k].subtype= FPDQ; /* Product fixed dummy * fixed quantitative */
9719: ncovf++; /* Varying variables without age */
9720: TvarF[ncovf]=Tvar[k];
9721: TvarFind[ncovf]=k;
9722: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){
9723: Fixed[k]= 1;
9724: Dummy[k]= 0;
9725: modell[k].maintype= VTYPE;
9726: modell[k].subtype= VPDD; /* Product fixed dummy * varying dummy */
9727: ncovv++; /* Varying variables without age */
9728: TvarV[ncovv]=Tvar[k];
9729: TvarVind[ncovv]=k;
9730: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){
9731: Fixed[k]= 1;
9732: Dummy[k]= 1;
9733: modell[k].maintype= VTYPE;
9734: modell[k].subtype= VPDQ; /* Product fixed dummy * varying quantitative */
9735: ncovv++; /* Varying variables without age */
9736: TvarV[ncovv]=Tvar[k];
9737: TvarVind[ncovv]=k;
9738: }
1.227 brouard 9739: }else if(Tvard[k1][1] <=ncovcol+nqv){
1.240 brouard 9740: if(Tvard[k1][2] <=ncovcol){
9741: Fixed[k]= 0; /* or 2 ?*/
9742: Dummy[k]= 1;
9743: modell[k].maintype= FTYPE;
9744: modell[k].subtype= FPDQ; /* Product fixed quantitative * fixed dummy */
9745: ncovf++; /* Fixed variables without age */
9746: TvarF[ncovf]=Tvar[k];
9747: TvarFind[ncovf]=k;
9748: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){
9749: Fixed[k]= 1;
9750: Dummy[k]= 1;
9751: modell[k].maintype= VTYPE;
9752: modell[k].subtype= VPDQ; /* Product fixed quantitative * varying dummy */
9753: ncovv++; /* Varying variables without age */
9754: TvarV[ncovv]=Tvar[k];
9755: TvarVind[ncovv]=k;
9756: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){
9757: Fixed[k]= 1;
9758: Dummy[k]= 1;
9759: modell[k].maintype= VTYPE;
9760: modell[k].subtype= VPQQ; /* Product fixed quantitative * varying quantitative */
9761: ncovv++; /* Varying variables without age */
9762: TvarV[ncovv]=Tvar[k];
9763: TvarVind[ncovv]=k;
9764: ncovv++; /* Varying variables without age */
9765: TvarV[ncovv]=Tvar[k];
9766: TvarVind[ncovv]=k;
9767: }
1.227 brouard 9768: }else if(Tvard[k1][1] <=ncovcol+nqv+ntv){
1.240 brouard 9769: if(Tvard[k1][2] <=ncovcol){
9770: Fixed[k]= 1;
9771: Dummy[k]= 1;
9772: modell[k].maintype= VTYPE;
9773: modell[k].subtype= VPDD; /* Product time varying dummy * fixed dummy */
9774: ncovv++; /* Varying variables without age */
9775: TvarV[ncovv]=Tvar[k];
9776: TvarVind[ncovv]=k;
9777: }else if(Tvard[k1][2] <=ncovcol+nqv){
9778: Fixed[k]= 1;
9779: Dummy[k]= 1;
9780: modell[k].maintype= VTYPE;
9781: modell[k].subtype= VPDQ; /* Product time varying dummy * fixed quantitative */
9782: ncovv++; /* Varying variables without age */
9783: TvarV[ncovv]=Tvar[k];
9784: TvarVind[ncovv]=k;
9785: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){
9786: Fixed[k]= 1;
9787: Dummy[k]= 0;
9788: modell[k].maintype= VTYPE;
9789: modell[k].subtype= VPDD; /* Product time varying dummy * time varying dummy */
9790: ncovv++; /* Varying variables without age */
9791: TvarV[ncovv]=Tvar[k];
9792: TvarVind[ncovv]=k;
9793: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){
9794: Fixed[k]= 1;
9795: Dummy[k]= 1;
9796: modell[k].maintype= VTYPE;
9797: modell[k].subtype= VPDQ; /* Product time varying dummy * time varying quantitative */
9798: ncovv++; /* Varying variables without age */
9799: TvarV[ncovv]=Tvar[k];
9800: TvarVind[ncovv]=k;
9801: }
1.227 brouard 9802: }else if(Tvard[k1][1] <=ncovcol+nqv+ntv+nqtv){
1.240 brouard 9803: if(Tvard[k1][2] <=ncovcol){
9804: Fixed[k]= 1;
9805: Dummy[k]= 1;
9806: modell[k].maintype= VTYPE;
9807: modell[k].subtype= VPDQ; /* Product time varying quantitative * fixed dummy */
9808: ncovv++; /* Varying variables without age */
9809: TvarV[ncovv]=Tvar[k];
9810: TvarVind[ncovv]=k;
9811: }else if(Tvard[k1][2] <=ncovcol+nqv){
9812: Fixed[k]= 1;
9813: Dummy[k]= 1;
9814: modell[k].maintype= VTYPE;
9815: modell[k].subtype= VPQQ; /* Product time varying quantitative * fixed quantitative */
9816: ncovv++; /* Varying variables without age */
9817: TvarV[ncovv]=Tvar[k];
9818: TvarVind[ncovv]=k;
9819: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){
9820: Fixed[k]= 1;
9821: Dummy[k]= 1;
9822: modell[k].maintype= VTYPE;
9823: modell[k].subtype= VPDQ; /* Product time varying quantitative * time varying dummy */
9824: ncovv++; /* Varying variables without age */
9825: TvarV[ncovv]=Tvar[k];
9826: TvarVind[ncovv]=k;
9827: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){
9828: Fixed[k]= 1;
9829: Dummy[k]= 1;
9830: modell[k].maintype= VTYPE;
9831: modell[k].subtype= VPQQ; /* Product time varying quantitative * time varying quantitative */
9832: ncovv++; /* Varying variables without age */
9833: TvarV[ncovv]=Tvar[k];
9834: TvarVind[ncovv]=k;
9835: }
1.227 brouard 9836: }else{
1.240 brouard 9837: printf("Error unknown type of covariate: Tvard[%d][1]=%d,Tvard[%d][2]=%d\n",k1,Tvard[k1][1],k1,Tvard[k1][2]);
9838: fprintf(ficlog,"Error unknown type of covariate: Tvard[%d][1]=%d,Tvard[%d][2]=%d\n",k1,Tvard[k1][1],k1,Tvard[k1][2]);
9839: } /*end k1*/
1.225 brouard 9840: }else{
1.226 brouard 9841: printf("Error, current version can't treat for performance reasons, Tvar[%d]=%d, Typevar[%d]=%d\n", k, Tvar[k], k, Typevar[k]);
9842: 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 9843: }
1.227 brouard 9844: 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 9845: printf(" modell[%d].maintype=%d, modell[%d].subtype=%d\n",k,modell[k].maintype,k,modell[k].subtype);
1.227 brouard 9846: 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]);
9847: }
9848: /* Searching for doublons in the model */
9849: for(k1=1; k1<= cptcovt;k1++){
9850: for(k2=1; k2 <k1;k2++){
9851: if((Typevar[k1]==Typevar[k2]) && (Fixed[Tvar[k1]]==Fixed[Tvar[k2]]) && (Dummy[Tvar[k1]]==Dummy[Tvar[k2]] )){
1.234 brouard 9852: if((Typevar[k1] == 0 || Typevar[k1] == 1)){ /* Simple or age product */
9853: if(Tvar[k1]==Tvar[k2]){
9854: 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]]);
9855: 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);
9856: return(1);
9857: }
9858: }else if (Typevar[k1] ==2){
9859: k3=Tposprod[k1];
9860: k4=Tposprod[k2];
9861: 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])) ){
9862: 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]]);
9863: 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);
9864: return(1);
9865: }
9866: }
1.227 brouard 9867: }
9868: }
1.225 brouard 9869: }
9870: printf("ncoveff=%d, nqfveff=%d, ntveff=%d, nqtveff=%d, cptcovn=%d\n",ncoveff,nqfveff,ntveff,nqtveff,cptcovn);
9871: fprintf(ficlog,"ncoveff=%d, nqfveff=%d, ntveff=%d, nqtveff=%d, cptcovn=%d\n",ncoveff,nqfveff,ntveff,nqtveff,cptcovn);
1.234 brouard 9872: printf("ncovf=%d, ncovv=%d, ncova=%d, nsd=%d, nsq=%d\n",ncovf,ncovv,ncova,nsd,nsq);
9873: fprintf(ficlog,"ncovf=%d, ncovv=%d, ncova=%d, nsd=%d, nsq=%d\n",ncovf,ncovv,ncova,nsd, nsq);
1.137 brouard 9874: return (0); /* with covar[new additional covariate if product] and Tage if age */
1.164 brouard 9875: /*endread:*/
1.225 brouard 9876: printf("Exiting decodemodel: ");
9877: return (1);
1.136 brouard 9878: }
9879:
1.169 brouard 9880: int calandcheckages(int imx, int maxwav, double *agemin, double *agemax, int *nberr, int *nbwarn )
1.248 brouard 9881: {/* Check ages at death */
1.136 brouard 9882: int i, m;
1.218 brouard 9883: int firstone=0;
9884:
1.136 brouard 9885: for (i=1; i<=imx; i++) {
9886: for(m=2; (m<= maxwav); m++) {
9887: if (((int)mint[m][i]== 99) && (s[m][i] <= nlstate)){
9888: anint[m][i]=9999;
1.216 brouard 9889: if (s[m][i] != -2) /* Keeping initial status of unknown vital status */
9890: s[m][i]=-1;
1.136 brouard 9891: }
9892: if((int)moisdc[i]==99 && (int)andc[i]==9999 && s[m][i]>nlstate){
1.260 brouard 9893: *nberr = *nberr + 1;
1.218 brouard 9894: if(firstone == 0){
9895: firstone=1;
1.260 brouard 9896: 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 9897: }
1.262 brouard 9898: 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 9899: s[m][i]=-1; /* Droping the death status */
1.136 brouard 9900: }
9901: if((int)moisdc[i]==99 && (int)andc[i]!=9999 && s[m][i]>nlstate){
1.169 brouard 9902: (*nberr)++;
1.259 brouard 9903: 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 9904: 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 9905: s[m][i]=-2; /* We prefer to skip it (and to skip it in version 0.8a1 too */
1.136 brouard 9906: }
9907: }
9908: }
9909:
9910: for (i=1; i<=imx; i++) {
9911: agedc[i]=(moisdc[i]/12.+andc[i])-(moisnais[i]/12.+annais[i]);
9912: for(m=firstpass; (m<= lastpass); m++){
1.214 brouard 9913: 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 9914: if (s[m][i] >= nlstate+1) {
1.169 brouard 9915: if(agedc[i]>0){
9916: if((int)moisdc[i]!=99 && (int)andc[i]!=9999){
1.136 brouard 9917: agev[m][i]=agedc[i];
1.214 brouard 9918: /*if(moisdc[i]==99 && andc[i]==9999) s[m][i]=-1;*/
1.169 brouard 9919: }else {
1.136 brouard 9920: if ((int)andc[i]!=9999){
9921: nbwarn++;
9922: printf("Warning negative age at death: %ld line:%d\n",num[i],i);
9923: fprintf(ficlog,"Warning negative age at death: %ld line:%d\n",num[i],i);
9924: agev[m][i]=-1;
9925: }
9926: }
1.169 brouard 9927: } /* agedc > 0 */
1.214 brouard 9928: } /* end if */
1.136 brouard 9929: else if(s[m][i] !=9){ /* Standard case, age in fractional
9930: years but with the precision of a month */
9931: agev[m][i]=(mint[m][i]/12.+1./24.+anint[m][i])-(moisnais[i]/12.+1./24.+annais[i]);
9932: if((int)mint[m][i]==99 || (int)anint[m][i]==9999)
9933: agev[m][i]=1;
9934: else if(agev[m][i] < *agemin){
9935: *agemin=agev[m][i];
9936: printf(" Min anint[%d][%d]=%.2f annais[%d]=%.2f, agemin=%.2f\n",m,i,anint[m][i], i,annais[i], *agemin);
9937: }
9938: else if(agev[m][i] >*agemax){
9939: *agemax=agev[m][i];
1.156 brouard 9940: /* printf(" Max anint[%d][%d]=%.0f annais[%d]=%.0f, agemax=%.2f\n",m,i,anint[m][i], i,annais[i], *agemax);*/
1.136 brouard 9941: }
9942: /*agev[m][i]=anint[m][i]-annais[i];*/
9943: /* agev[m][i] = age[i]+2*m;*/
1.214 brouard 9944: } /* en if 9*/
1.136 brouard 9945: else { /* =9 */
1.214 brouard 9946: /* printf("Debug num[%d]=%ld s[%d][%d]=%d\n",i,num[i], m,i, s[m][i]); */
1.136 brouard 9947: agev[m][i]=1;
9948: s[m][i]=-1;
9949: }
9950: }
1.214 brouard 9951: else if(s[m][i]==0) /*= 0 Unknown */
1.136 brouard 9952: agev[m][i]=1;
1.214 brouard 9953: else{
9954: printf("Warning, num[%d]=%ld, s[%d][%d]=%d\n", i, num[i], m, i,s[m][i]);
9955: fprintf(ficlog, "Warning, num[%d]=%ld, s[%d][%d]=%d\n", i, num[i], m, i,s[m][i]);
9956: agev[m][i]=0;
9957: }
9958: } /* End for lastpass */
9959: }
1.136 brouard 9960:
9961: for (i=1; i<=imx; i++) {
9962: for(m=firstpass; (m<=lastpass); m++){
9963: if (s[m][i] > (nlstate+ndeath)) {
1.169 brouard 9964: (*nberr)++;
1.136 brouard 9965: 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);
9966: 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);
9967: return 1;
9968: }
9969: }
9970: }
9971:
9972: /*for (i=1; i<=imx; i++){
9973: for (m=firstpass; (m<lastpass); m++){
9974: printf("%ld %d %.lf %d %d\n", num[i],(covar[1][i]),agev[m][i],s[m][i],s[m+1][i]);
9975: }
9976:
9977: }*/
9978:
9979:
1.139 brouard 9980: printf("Total number of individuals= %d, Agemin = %.2f, Agemax= %.2f\n\n", imx, *agemin, *agemax);
9981: fprintf(ficlog,"Total number of individuals= %d, Agemin = %.2f, Agemax= %.2f\n\n", imx, *agemin, *agemax);
1.136 brouard 9982:
9983: return (0);
1.164 brouard 9984: /* endread:*/
1.136 brouard 9985: printf("Exiting calandcheckages: ");
9986: return (1);
9987: }
9988:
1.172 brouard 9989: #if defined(_MSC_VER)
9990: /*printf("Visual C++ compiler: %s \n;", _MSC_FULL_VER);*/
9991: /*fprintf(ficlog, "Visual C++ compiler: %s \n;", _MSC_FULL_VER);*/
9992: //#include "stdafx.h"
9993: //#include <stdio.h>
9994: //#include <tchar.h>
9995: //#include <windows.h>
9996: //#include <iostream>
9997: typedef BOOL(WINAPI *LPFN_ISWOW64PROCESS) (HANDLE, PBOOL);
9998:
9999: LPFN_ISWOW64PROCESS fnIsWow64Process;
10000:
10001: BOOL IsWow64()
10002: {
10003: BOOL bIsWow64 = FALSE;
10004:
10005: //typedef BOOL (APIENTRY *LPFN_ISWOW64PROCESS)
10006: // (HANDLE, PBOOL);
10007:
10008: //LPFN_ISWOW64PROCESS fnIsWow64Process;
10009:
10010: HMODULE module = GetModuleHandle(_T("kernel32"));
10011: const char funcName[] = "IsWow64Process";
10012: fnIsWow64Process = (LPFN_ISWOW64PROCESS)
10013: GetProcAddress(module, funcName);
10014:
10015: if (NULL != fnIsWow64Process)
10016: {
10017: if (!fnIsWow64Process(GetCurrentProcess(),
10018: &bIsWow64))
10019: //throw std::exception("Unknown error");
10020: printf("Unknown error\n");
10021: }
10022: return bIsWow64 != FALSE;
10023: }
10024: #endif
1.177 brouard 10025:
1.191 brouard 10026: void syscompilerinfo(int logged)
1.167 brouard 10027: {
10028: /* #include "syscompilerinfo.h"*/
1.185 brouard 10029: /* command line Intel compiler 32bit windows, XP compatible:*/
10030: /* /GS /W3 /Gy
10031: /Zc:wchar_t /Zi /O2 /Fd"Release\vc120.pdb" /D "WIN32" /D "NDEBUG" /D
10032: "_CONSOLE" /D "_LIB" /D "_USING_V110_SDK71_" /D "_UNICODE" /D
10033: "UNICODE" /Qipo /Zc:forScope /Gd /Oi /MT /Fa"Release\" /EHsc /nologo
1.186 brouard 10034: /Fo"Release\" /Qprof-dir "Release\" /Fp"Release\IMaCh.pch"
10035: */
10036: /* 64 bits */
1.185 brouard 10037: /*
10038: /GS /W3 /Gy
10039: /Zc:wchar_t /Zi /O2 /Fd"x64\Release\vc120.pdb" /D "WIN32" /D "NDEBUG"
10040: /D "_CONSOLE" /D "_LIB" /D "_UNICODE" /D "UNICODE" /Qipo /Zc:forScope
10041: /Oi /MD /Fa"x64\Release\" /EHsc /nologo /Fo"x64\Release\" /Qprof-dir
10042: "x64\Release\" /Fp"x64\Release\IMaCh.pch" */
10043: /* Optimization are useless and O3 is slower than O2 */
10044: /*
10045: /GS /W3 /Gy /Zc:wchar_t /Zi /O3 /Fd"x64\Release\vc120.pdb" /D "WIN32"
10046: /D "NDEBUG" /D "_CONSOLE" /D "_LIB" /D "_UNICODE" /D "UNICODE" /Qipo
10047: /Zc:forScope /Oi /MD /Fa"x64\Release\" /EHsc /nologo /Qparallel
10048: /Fo"x64\Release\" /Qprof-dir "x64\Release\" /Fp"x64\Release\IMaCh.pch"
10049: */
1.186 brouard 10050: /* Link is */ /* /OUT:"visual studio
1.185 brouard 10051: 2013\Projects\IMaCh\Release\IMaCh.exe" /MANIFEST /NXCOMPAT
10052: /PDB:"visual studio
10053: 2013\Projects\IMaCh\Release\IMaCh.pdb" /DYNAMICBASE
10054: "kernel32.lib" "user32.lib" "gdi32.lib" "winspool.lib"
10055: "comdlg32.lib" "advapi32.lib" "shell32.lib" "ole32.lib"
10056: "oleaut32.lib" "uuid.lib" "odbc32.lib" "odbccp32.lib"
10057: /MACHINE:X86 /OPT:REF /SAFESEH /INCREMENTAL:NO
10058: /SUBSYSTEM:CONSOLE",5.01" /MANIFESTUAC:"level='asInvoker'
10059: uiAccess='false'"
10060: /ManifestFile:"Release\IMaCh.exe.intermediate.manifest" /OPT:ICF
10061: /NOLOGO /TLBID:1
10062: */
1.177 brouard 10063: #if defined __INTEL_COMPILER
1.178 brouard 10064: #if defined(__GNUC__)
10065: struct utsname sysInfo; /* For Intel on Linux and OS/X */
10066: #endif
1.177 brouard 10067: #elif defined(__GNUC__)
1.179 brouard 10068: #ifndef __APPLE__
1.174 brouard 10069: #include <gnu/libc-version.h> /* Only on gnu */
1.179 brouard 10070: #endif
1.177 brouard 10071: struct utsname sysInfo;
1.178 brouard 10072: int cross = CROSS;
10073: if (cross){
10074: printf("Cross-");
1.191 brouard 10075: if(logged) fprintf(ficlog, "Cross-");
1.178 brouard 10076: }
1.174 brouard 10077: #endif
10078:
1.171 brouard 10079: #include <stdint.h>
1.178 brouard 10080:
1.191 brouard 10081: printf("Compiled with:");if(logged)fprintf(ficlog,"Compiled with:");
1.169 brouard 10082: #if defined(__clang__)
1.191 brouard 10083: printf(" Clang/LLVM");if(logged)fprintf(ficlog," Clang/LLVM"); /* Clang/LLVM. ---------------------------------------------- */
1.169 brouard 10084: #endif
10085: #if defined(__ICC) || defined(__INTEL_COMPILER)
1.191 brouard 10086: printf(" Intel ICC/ICPC");if(logged)fprintf(ficlog," Intel ICC/ICPC");/* Intel ICC/ICPC. ------------------------------------------ */
1.169 brouard 10087: #endif
10088: #if defined(__GNUC__) || defined(__GNUG__)
1.191 brouard 10089: printf(" GNU GCC/G++");if(logged)fprintf(ficlog," GNU GCC/G++");/* GNU GCC/G++. --------------------------------------------- */
1.169 brouard 10090: #endif
10091: #if defined(__HP_cc) || defined(__HP_aCC)
1.191 brouard 10092: printf(" Hewlett-Packard C/aC++");if(logged)fprintf(fcilog," Hewlett-Packard C/aC++"); /* Hewlett-Packard C/aC++. ---------------------------------- */
1.169 brouard 10093: #endif
10094: #if defined(__IBMC__) || defined(__IBMCPP__)
1.191 brouard 10095: printf(" IBM XL C/C++"); if(logged) fprintf(ficlog," IBM XL C/C++");/* IBM XL C/C++. -------------------------------------------- */
1.169 brouard 10096: #endif
10097: #if defined(_MSC_VER)
1.191 brouard 10098: printf(" Microsoft Visual Studio");if(logged)fprintf(ficlog," Microsoft Visual Studio");/* Microsoft Visual Studio. --------------------------------- */
1.169 brouard 10099: #endif
10100: #if defined(__PGI)
1.191 brouard 10101: printf(" Portland Group PGCC/PGCPP");if(logged) fprintf(ficlog," Portland Group PGCC/PGCPP");/* Portland Group PGCC/PGCPP. ------------------------------- */
1.169 brouard 10102: #endif
10103: #if defined(__SUNPRO_C) || defined(__SUNPRO_CC)
1.191 brouard 10104: printf(" Oracle Solaris Studio");if(logged)fprintf(ficlog," Oracle Solaris Studio\n");/* Oracle Solaris Studio. ----------------------------------- */
1.167 brouard 10105: #endif
1.191 brouard 10106: printf(" for "); if (logged) fprintf(ficlog, " for ");
1.169 brouard 10107:
1.167 brouard 10108: // http://stackoverflow.com/questions/4605842/how-to-identify-platform-compiler-from-preprocessor-macros
10109: #ifdef _WIN32 // note the underscore: without it, it's not msdn official!
10110: // Windows (x64 and x86)
1.191 brouard 10111: printf("Windows (x64 and x86) ");if(logged) fprintf(ficlog,"Windows (x64 and x86) ");
1.167 brouard 10112: #elif __unix__ // all unices, not all compilers
10113: // Unix
1.191 brouard 10114: printf("Unix ");if(logged) fprintf(ficlog,"Unix ");
1.167 brouard 10115: #elif __linux__
10116: // linux
1.191 brouard 10117: printf("linux ");if(logged) fprintf(ficlog,"linux ");
1.167 brouard 10118: #elif __APPLE__
1.174 brouard 10119: // Mac OS, not sure if this is covered by __posix__ and/or __unix__ though..
1.191 brouard 10120: printf("Mac OS ");if(logged) fprintf(ficlog,"Mac OS ");
1.167 brouard 10121: #endif
10122:
10123: /* __MINGW32__ */
10124: /* __CYGWIN__ */
10125: /* __MINGW64__ */
10126: // http://msdn.microsoft.com/en-us/library/b0084kay.aspx
10127: /* _MSC_VER //the Visual C++ compiler is 17.00.51106.1, the _MSC_VER macro evaluates to 1700. Type cl /? */
10128: /* _MSC_FULL_VER //the Visual C++ compiler is 15.00.20706.01, the _MSC_FULL_VER macro evaluates to 150020706 */
10129: /* _WIN64 // Defined for applications for Win64. */
10130: /* _M_X64 // Defined for compilations that target x64 processors. */
10131: /* _DEBUG // Defined when you compile with /LDd, /MDd, and /MTd. */
1.171 brouard 10132:
1.167 brouard 10133: #if UINTPTR_MAX == 0xffffffff
1.191 brouard 10134: printf(" 32-bit"); if(logged) fprintf(ficlog," 32-bit");/* 32-bit */
1.167 brouard 10135: #elif UINTPTR_MAX == 0xffffffffffffffff
1.191 brouard 10136: printf(" 64-bit"); if(logged) fprintf(ficlog," 64-bit");/* 64-bit */
1.167 brouard 10137: #else
1.191 brouard 10138: printf(" wtf-bit"); if(logged) fprintf(ficlog," wtf-bit");/* wtf */
1.167 brouard 10139: #endif
10140:
1.169 brouard 10141: #if defined(__GNUC__)
10142: # if defined(__GNUC_PATCHLEVEL__)
10143: # define __GNUC_VERSION__ (__GNUC__ * 10000 \
10144: + __GNUC_MINOR__ * 100 \
10145: + __GNUC_PATCHLEVEL__)
10146: # else
10147: # define __GNUC_VERSION__ (__GNUC__ * 10000 \
10148: + __GNUC_MINOR__ * 100)
10149: # endif
1.174 brouard 10150: printf(" using GNU C version %d.\n", __GNUC_VERSION__);
1.191 brouard 10151: if(logged) fprintf(ficlog, " using GNU C version %d.\n", __GNUC_VERSION__);
1.176 brouard 10152:
10153: if (uname(&sysInfo) != -1) {
10154: printf("Running on: %s %s %s %s %s\n",sysInfo.sysname, sysInfo.nodename, sysInfo.release, sysInfo.version, sysInfo.machine);
1.191 brouard 10155: 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 10156: }
10157: else
10158: perror("uname() error");
1.179 brouard 10159: //#ifndef __INTEL_COMPILER
10160: #if !defined (__INTEL_COMPILER) && !defined(__APPLE__)
1.174 brouard 10161: printf("GNU libc version: %s\n", gnu_get_libc_version());
1.191 brouard 10162: if(logged) fprintf(ficlog,"GNU libc version: %s\n", gnu_get_libc_version());
1.177 brouard 10163: #endif
1.169 brouard 10164: #endif
1.172 brouard 10165:
10166: // void main()
10167: // {
1.169 brouard 10168: #if defined(_MSC_VER)
1.174 brouard 10169: if (IsWow64()){
1.191 brouard 10170: printf("\nThe program (probably compiled for 32bit) is running under WOW64 (64bit) emulation.\n");
10171: if (logged) fprintf(ficlog, "\nThe program (probably compiled for 32bit) is running under WOW64 (64bit) emulation.\n");
1.174 brouard 10172: }
10173: else{
1.191 brouard 10174: printf("\nThe program is not running under WOW64 (i.e probably on a 64bit Windows).\n");
10175: if (logged) fprintf(ficlog, "\nThe programm is not running under WOW64 (i.e probably on a 64bit Windows).\n");
1.174 brouard 10176: }
1.172 brouard 10177: // printf("\nPress Enter to continue...");
10178: // getchar();
10179: // }
10180:
1.169 brouard 10181: #endif
10182:
1.167 brouard 10183:
1.219 brouard 10184: }
1.136 brouard 10185:
1.219 brouard 10186: int prevalence_limit(double *p, double **prlim, double ageminpar, double agemaxpar, double ftolpl, int *ncvyearp){
1.180 brouard 10187: /*--------------- Prevalence limit (period or stable prevalence) --------------*/
1.235 brouard 10188: int i, j, k, i1, k4=0, nres=0 ;
1.202 brouard 10189: /* double ftolpl = 1.e-10; */
1.180 brouard 10190: double age, agebase, agelim;
1.203 brouard 10191: double tot;
1.180 brouard 10192:
1.202 brouard 10193: strcpy(filerespl,"PL_");
10194: strcat(filerespl,fileresu);
10195: if((ficrespl=fopen(filerespl,"w"))==NULL) {
10196: printf("Problem with period (stable) prevalence resultfile: %s\n", filerespl);return 1;
10197: fprintf(ficlog,"Problem with period (stable) prevalence resultfile: %s\n", filerespl);return 1;
10198: }
1.227 brouard 10199: printf("\nComputing period (stable) prevalence: result on file '%s' \n", filerespl);
10200: fprintf(ficlog,"\nComputing period (stable) prevalence: result on file '%s' \n", filerespl);
1.202 brouard 10201: pstamp(ficrespl);
1.203 brouard 10202: fprintf(ficrespl,"# Period (stable) prevalence. Precision given by ftolpl=%g \n", ftolpl);
1.202 brouard 10203: fprintf(ficrespl,"#Age ");
10204: for(i=1; i<=nlstate;i++) fprintf(ficrespl,"%d-%d ",i,i);
10205: fprintf(ficrespl,"\n");
1.180 brouard 10206:
1.219 brouard 10207: /* prlim=matrix(1,nlstate,1,nlstate);*/ /* back in main */
1.180 brouard 10208:
1.219 brouard 10209: agebase=ageminpar;
10210: agelim=agemaxpar;
1.180 brouard 10211:
1.227 brouard 10212: /* i1=pow(2,ncoveff); */
1.234 brouard 10213: i1=pow(2,cptcoveff); /* Number of combination of dummy covariates */
1.219 brouard 10214: if (cptcovn < 1){i1=1;}
1.180 brouard 10215:
1.238 brouard 10216: for(k=1; k<=i1;k++){ /* For each combination k of dummy covariates in the model */
10217: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 10218: if(i1 != 1 && TKresult[nres]!= k)
1.238 brouard 10219: continue;
1.235 brouard 10220:
1.238 brouard 10221: /* for(cptcov=1,k=0;cptcov<=i1;cptcov++){ */
10222: /* for(cptcov=1,k=0;cptcov<=1;cptcov++){ */
10223: //for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){
10224: /* k=k+1; */
10225: /* to clean */
10226: //printf("cptcov=%d cptcod=%d codtab=%d\n",cptcov, cptcod,codtabm(cptcod,cptcov));
10227: fprintf(ficrespl,"#******");
10228: printf("#******");
10229: fprintf(ficlog,"#******");
10230: for(j=1;j<=cptcoveff ;j++) {/* all covariates */
10231: fprintf(ficrespl," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]); /* Here problem for varying dummy*/
10232: printf(" V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10233: fprintf(ficlog," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10234: }
10235: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
10236: printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
10237: fprintf(ficrespl," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
10238: fprintf(ficlog," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
10239: }
10240: fprintf(ficrespl,"******\n");
10241: printf("******\n");
10242: fprintf(ficlog,"******\n");
10243: if(invalidvarcomb[k]){
10244: printf("\nCombination (%d) ignored because no case \n",k);
10245: fprintf(ficrespl,"#Combination (%d) ignored because no case \n",k);
10246: fprintf(ficlog,"\nCombination (%d) ignored because no case \n",k);
10247: continue;
10248: }
1.219 brouard 10249:
1.238 brouard 10250: fprintf(ficrespl,"#Age ");
10251: for(j=1;j<=cptcoveff;j++) {
10252: fprintf(ficrespl,"V%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10253: }
10254: for(i=1; i<=nlstate;i++) fprintf(ficrespl," %d-%d ",i,i);
10255: fprintf(ficrespl,"Total Years_to_converge\n");
1.227 brouard 10256:
1.238 brouard 10257: for (age=agebase; age<=agelim; age++){
10258: /* for (age=agebase; age<=agebase; age++){ */
10259: prevalim(prlim, nlstate, p, age, oldm, savm, ftolpl, ncvyearp, k, nres);
10260: fprintf(ficrespl,"%.0f ",age );
10261: for(j=1;j<=cptcoveff;j++)
10262: fprintf(ficrespl,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10263: tot=0.;
10264: for(i=1; i<=nlstate;i++){
10265: tot += prlim[i][i];
10266: fprintf(ficrespl," %.5f", prlim[i][i]);
10267: }
10268: fprintf(ficrespl," %.3f %d\n", tot, *ncvyearp);
10269: } /* Age */
10270: /* was end of cptcod */
10271: } /* cptcov */
10272: } /* nres */
1.219 brouard 10273: return 0;
1.180 brouard 10274: }
10275:
1.218 brouard 10276: 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){
10277: /*--------------- Back Prevalence limit (period or stable prevalence) --------------*/
10278:
10279: /* Computes the back prevalence limit for any combination of covariate values
10280: * at any age between ageminpar and agemaxpar
10281: */
1.235 brouard 10282: int i, j, k, i1, nres=0 ;
1.217 brouard 10283: /* double ftolpl = 1.e-10; */
10284: double age, agebase, agelim;
10285: double tot;
1.218 brouard 10286: /* double ***mobaverage; */
10287: /* double **dnewm, **doldm, **dsavm; /\* for use *\/ */
1.217 brouard 10288:
10289: strcpy(fileresplb,"PLB_");
10290: strcat(fileresplb,fileresu);
10291: if((ficresplb=fopen(fileresplb,"w"))==NULL) {
10292: printf("Problem with period (stable) back prevalence resultfile: %s\n", fileresplb);return 1;
10293: fprintf(ficlog,"Problem with period (stable) back prevalence resultfile: %s\n", fileresplb);return 1;
10294: }
10295: printf("Computing period (stable) back prevalence: result on file '%s' \n", fileresplb);
10296: fprintf(ficlog,"Computing period (stable) back prevalence: result on file '%s' \n", fileresplb);
10297: pstamp(ficresplb);
10298: fprintf(ficresplb,"# Period (stable) back prevalence. Precision given by ftolpl=%g \n", ftolpl);
10299: fprintf(ficresplb,"#Age ");
10300: for(i=1; i<=nlstate;i++) fprintf(ficresplb,"%d-%d ",i,i);
10301: fprintf(ficresplb,"\n");
10302:
1.218 brouard 10303:
10304: /* prlim=matrix(1,nlstate,1,nlstate);*/ /* back in main */
10305:
10306: agebase=ageminpar;
10307: agelim=agemaxpar;
10308:
10309:
1.227 brouard 10310: i1=pow(2,cptcoveff);
1.218 brouard 10311: if (cptcovn < 1){i1=1;}
1.227 brouard 10312:
1.238 brouard 10313: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
10314: for(k=1; k<=i1;k++){ /* For any combination of dummy covariates, fixed and varying */
1.253 brouard 10315: if(i1 != 1 && TKresult[nres]!= k)
1.238 brouard 10316: continue;
10317: //printf("cptcov=%d cptcod=%d codtab=%d\n",cptcov, cptcod,codtabm(cptcod,cptcov));
10318: fprintf(ficresplb,"#******");
10319: printf("#******");
10320: fprintf(ficlog,"#******");
10321: for(j=1;j<=cptcoveff ;j++) {/* all covariates */
10322: fprintf(ficresplb," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10323: printf(" V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10324: fprintf(ficlog," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10325: }
10326: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
10327: printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
10328: fprintf(ficresplb," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
10329: fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
10330: }
10331: fprintf(ficresplb,"******\n");
10332: printf("******\n");
10333: fprintf(ficlog,"******\n");
10334: if(invalidvarcomb[k]){
10335: printf("\nCombination (%d) ignored because no cases \n",k);
10336: fprintf(ficresplb,"#Combination (%d) ignored because no cases \n",k);
10337: fprintf(ficlog,"\nCombination (%d) ignored because no cases \n",k);
10338: continue;
10339: }
1.218 brouard 10340:
1.238 brouard 10341: fprintf(ficresplb,"#Age ");
10342: for(j=1;j<=cptcoveff;j++) {
10343: fprintf(ficresplb,"V%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10344: }
10345: for(i=1; i<=nlstate;i++) fprintf(ficresplb," %d-%d ",i,i);
10346: fprintf(ficresplb,"Total Years_to_converge\n");
1.218 brouard 10347:
10348:
1.238 brouard 10349: for (age=agebase; age<=agelim; age++){
10350: /* for (age=agebase; age<=agebase; age++){ */
10351: if(mobilavproj > 0){
10352: /* bprevalim(bprlim, mobaverage, nlstate, p, age, ageminpar, agemaxpar, oldm, savm, doldm, dsavm, ftolpl, ncvyearp, k); */
10353: /* bprevalim(bprlim, mobaverage, nlstate, p, age, oldm, savm, dnewm, doldm, dsavm, ftolpl, ncvyearp, k); */
1.242 brouard 10354: bprevalim(bprlim, mobaverage, nlstate, p, age, ftolpl, ncvyearp, k, nres);
1.238 brouard 10355: }else if (mobilavproj == 0){
10356: 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);
10357: 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);
10358: exit(1);
10359: }else{
10360: /* bprevalim(bprlim, probs, nlstate, p, age, oldm, savm, dnewm, doldm, dsavm, ftolpl, ncvyearp, k); */
1.242 brouard 10361: bprevalim(bprlim, probs, nlstate, p, age, ftolpl, ncvyearp, k,nres);
1.266 brouard 10362: /* printf("TOTOT\n"); */
10363: /* exit(1); */
1.238 brouard 10364: }
10365: fprintf(ficresplb,"%.0f ",age );
10366: for(j=1;j<=cptcoveff;j++)
10367: fprintf(ficresplb,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10368: tot=0.;
10369: for(i=1; i<=nlstate;i++){
10370: tot += bprlim[i][i];
10371: fprintf(ficresplb," %.5f", bprlim[i][i]);
10372: }
10373: fprintf(ficresplb," %.3f %d\n", tot, *ncvyearp);
10374: } /* Age */
10375: /* was end of cptcod */
1.255 brouard 10376: /*fprintf(ficresplb,"\n");*/ /* Seems to be necessary for gnuplot only if two result lines and no covariate. */
1.238 brouard 10377: } /* end of any combination */
10378: } /* end of nres */
1.218 brouard 10379: /* hBijx(p, bage, fage); */
10380: /* fclose(ficrespijb); */
10381:
10382: return 0;
1.217 brouard 10383: }
1.218 brouard 10384:
1.180 brouard 10385: int hPijx(double *p, int bage, int fage){
10386: /*------------- h Pij x at various ages ------------*/
10387:
10388: int stepsize;
10389: int agelim;
10390: int hstepm;
10391: int nhstepm;
1.235 brouard 10392: int h, i, i1, j, k, k4, nres=0;
1.180 brouard 10393:
10394: double agedeb;
10395: double ***p3mat;
10396:
1.201 brouard 10397: strcpy(filerespij,"PIJ_"); strcat(filerespij,fileresu);
1.180 brouard 10398: if((ficrespij=fopen(filerespij,"w"))==NULL) {
10399: printf("Problem with Pij resultfile: %s\n", filerespij); return 1;
10400: fprintf(ficlog,"Problem with Pij resultfile: %s\n", filerespij); return 1;
10401: }
10402: printf("Computing pij: result on file '%s' \n", filerespij);
10403: fprintf(ficlog,"Computing pij: result on file '%s' \n", filerespij);
10404:
10405: stepsize=(int) (stepm+YEARM-1)/YEARM;
10406: /*if (stepm<=24) stepsize=2;*/
10407:
10408: agelim=AGESUP;
10409: hstepm=stepsize*YEARM; /* Every year of age */
10410: hstepm=hstepm/stepm; /* Typically 2 years, = 2/6 months = 4 */
1.218 brouard 10411:
1.180 brouard 10412: /* hstepm=1; aff par mois*/
10413: pstamp(ficrespij);
10414: fprintf(ficrespij,"#****** h Pij x Probability to be in state j at age x+h being in i at x ");
1.227 brouard 10415: i1= pow(2,cptcoveff);
1.218 brouard 10416: /* for(cptcov=1,k=0;cptcov<=i1;cptcov++){ */
10417: /* /\*for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){*\/ */
10418: /* k=k+1; */
1.235 brouard 10419: for(nres=1; nres <= nresult; nres++) /* For each resultline */
10420: for(k=1; k<=i1;k++){
1.253 brouard 10421: if(i1 != 1 && TKresult[nres]!= k)
1.235 brouard 10422: continue;
1.183 brouard 10423: fprintf(ficrespij,"\n#****** ");
1.227 brouard 10424: for(j=1;j<=cptcoveff;j++)
1.198 brouard 10425: fprintf(ficrespij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
1.235 brouard 10426: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
10427: printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
10428: fprintf(ficrespij," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
10429: }
1.183 brouard 10430: fprintf(ficrespij,"******\n");
10431:
10432: for (agedeb=fage; agedeb>=bage; agedeb--){ /* If stepm=6 months */
10433: nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
10434: nhstepm = nhstepm/hstepm; /* Typically 40/4=10 */
10435:
10436: /* nhstepm=nhstepm*YEARM; aff par mois*/
1.180 brouard 10437:
1.183 brouard 10438: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
10439: oldm=oldms;savm=savms;
1.235 brouard 10440: hpxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k, nres);
1.183 brouard 10441: fprintf(ficrespij,"# Cov Agex agex+h hpijx with i,j=");
10442: for(i=1; i<=nlstate;i++)
10443: for(j=1; j<=nlstate+ndeath;j++)
10444: fprintf(ficrespij," %1d-%1d",i,j);
10445: fprintf(ficrespij,"\n");
10446: for (h=0; h<=nhstepm; h++){
10447: /*agedebphstep = agedeb + h*hstepm/YEARM*stepm;*/
10448: fprintf(ficrespij,"%d %3.f %3.f",k, agedeb, agedeb + h*hstepm/YEARM*stepm );
1.180 brouard 10449: for(i=1; i<=nlstate;i++)
10450: for(j=1; j<=nlstate+ndeath;j++)
1.183 brouard 10451: fprintf(ficrespij," %.5f", p3mat[i][j][h]);
1.180 brouard 10452: fprintf(ficrespij,"\n");
10453: }
1.183 brouard 10454: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
10455: fprintf(ficrespij,"\n");
10456: }
1.180 brouard 10457: /*}*/
10458: }
1.218 brouard 10459: return 0;
1.180 brouard 10460: }
1.218 brouard 10461:
10462: int hBijx(double *p, int bage, int fage, double ***prevacurrent){
1.217 brouard 10463: /*------------- h Bij x at various ages ------------*/
10464:
10465: int stepsize;
1.218 brouard 10466: /* int agelim; */
10467: int ageminl;
1.217 brouard 10468: int hstepm;
10469: int nhstepm;
1.238 brouard 10470: int h, i, i1, j, k, nres;
1.218 brouard 10471:
1.217 brouard 10472: double agedeb;
10473: double ***p3mat;
1.218 brouard 10474:
10475: strcpy(filerespijb,"PIJB_"); strcat(filerespijb,fileresu);
10476: if((ficrespijb=fopen(filerespijb,"w"))==NULL) {
10477: printf("Problem with Pij back resultfile: %s\n", filerespijb); return 1;
10478: fprintf(ficlog,"Problem with Pij back resultfile: %s\n", filerespijb); return 1;
10479: }
10480: printf("Computing pij back: result on file '%s' \n", filerespijb);
10481: fprintf(ficlog,"Computing pij back: result on file '%s' \n", filerespijb);
10482:
10483: stepsize=(int) (stepm+YEARM-1)/YEARM;
10484: /*if (stepm<=24) stepsize=2;*/
1.217 brouard 10485:
1.218 brouard 10486: /* agelim=AGESUP; */
10487: ageminl=30;
10488: hstepm=stepsize*YEARM; /* Every year of age */
10489: hstepm=hstepm/stepm; /* Typically 2 years, = 2/6 months = 4 */
10490:
10491: /* hstepm=1; aff par mois*/
10492: pstamp(ficrespijb);
1.255 brouard 10493: 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 10494: i1= pow(2,cptcoveff);
1.218 brouard 10495: /* for(cptcov=1,k=0;cptcov<=i1;cptcov++){ */
10496: /* /\*for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){*\/ */
10497: /* k=k+1; */
1.238 brouard 10498: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
10499: for(k=1; k<=i1;k++){ /* For any combination of dummy covariates, fixed and varying */
1.253 brouard 10500: if(i1 != 1 && TKresult[nres]!= k)
1.238 brouard 10501: continue;
10502: fprintf(ficrespijb,"\n#****** ");
10503: for(j=1;j<=cptcoveff;j++)
10504: fprintf(ficrespijb,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10505: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
10506: fprintf(ficrespijb," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
10507: }
10508: fprintf(ficrespijb,"******\n");
1.264 brouard 10509: if(invalidvarcomb[k]){ /* Is it necessary here? */
1.238 brouard 10510: fprintf(ficrespijb,"\n#Combination (%d) ignored because no cases \n",k);
10511: continue;
10512: }
10513:
10514: /* for (agedeb=fage; agedeb>=bage; agedeb--){ /\* If stepm=6 months *\/ */
10515: for (agedeb=bage; agedeb<=fage; agedeb++){ /* If stepm=6 months and estepm=24 (2 years) */
10516: /* nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); /\* Typically 20 years = 20*12/6=40 *\/ */
10517: nhstepm=(int) rint((agedeb-ageminl)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
10518: nhstepm = nhstepm/hstepm; /* Typically 40/4=10, because estepm=24 stepm=6 => hstepm=24/6=4 */
10519:
10520: /* nhstepm=nhstepm*YEARM; aff par mois*/
10521:
1.266 brouard 10522: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); /* We can't have it at an upper level because of nhstepm */
10523: /* and memory limitations if stepm is small */
10524:
1.238 brouard 10525: /* oldm=oldms;savm=savms; */
10526: /* hbxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k); */
1.267 brouard 10527: hbxij(p3mat,nhstepm,agedeb,hstepm,p,prevacurrent,nlstate,stepm, k, nres);
1.238 brouard 10528: /* hbxij(p3mat,nhstepm,agedeb,hstepm,p,prevacurrent,nlstate,stepm,oldm,savm, dnewm, doldm, dsavm, k); */
1.255 brouard 10529: fprintf(ficrespijb,"# Cov Agex agex-h hbijx with i,j=");
1.217 brouard 10530: for(i=1; i<=nlstate;i++)
10531: for(j=1; j<=nlstate+ndeath;j++)
1.238 brouard 10532: fprintf(ficrespijb," %1d-%1d",i,j);
1.217 brouard 10533: fprintf(ficrespijb,"\n");
1.238 brouard 10534: for (h=0; h<=nhstepm; h++){
10535: /*agedebphstep = agedeb + h*hstepm/YEARM*stepm;*/
10536: fprintf(ficrespijb,"%d %3.f %3.f",k, agedeb, agedeb - h*hstepm/YEARM*stepm );
10537: /* fprintf(ficrespijb,"%d %3.f %3.f",k, agedeb, agedeb + h*hstepm/YEARM*stepm ); */
10538: for(i=1; i<=nlstate;i++)
10539: for(j=1; j<=nlstate+ndeath;j++)
10540: fprintf(ficrespijb," %.5f", p3mat[i][j][h]);
10541: fprintf(ficrespijb,"\n");
10542: }
10543: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
10544: fprintf(ficrespijb,"\n");
10545: } /* end age deb */
10546: } /* end combination */
10547: } /* end nres */
1.218 brouard 10548: return 0;
10549: } /* hBijx */
1.217 brouard 10550:
1.180 brouard 10551:
1.136 brouard 10552: /***********************************************/
10553: /**************** Main Program *****************/
10554: /***********************************************/
10555:
10556: int main(int argc, char *argv[])
10557: {
10558: #ifdef GSL
10559: const gsl_multimin_fminimizer_type *T;
10560: size_t iteri = 0, it;
10561: int rval = GSL_CONTINUE;
10562: int status = GSL_SUCCESS;
10563: double ssval;
10564: #endif
10565: int movingaverage(double ***probs, double bage,double fage, double ***mobaverage, int mobilav);
1.164 brouard 10566: int i,j, k, n=MAXN,iter=0,m,size=100, cptcod;
1.209 brouard 10567: int ncvyear=0; /* Number of years needed for the period prevalence to converge */
1.164 brouard 10568: int jj, ll, li, lj, lk;
1.136 brouard 10569: int numlinepar=0; /* Current linenumber of parameter file */
1.197 brouard 10570: int num_filled;
1.136 brouard 10571: int itimes;
10572: int NDIM=2;
10573: int vpopbased=0;
1.235 brouard 10574: int nres=0;
1.258 brouard 10575: int endishere=0;
1.136 brouard 10576:
1.164 brouard 10577: char ca[32], cb[32];
1.136 brouard 10578: /* FILE *fichtm; *//* Html File */
10579: /* FILE *ficgp;*/ /*Gnuplot File */
10580: struct stat info;
1.191 brouard 10581: double agedeb=0.;
1.194 brouard 10582:
10583: double ageminpar=AGEOVERFLOW,agemin=AGEOVERFLOW, agemaxpar=-AGEOVERFLOW, agemax=-AGEOVERFLOW;
1.219 brouard 10584: double ageminout=-AGEOVERFLOW,agemaxout=AGEOVERFLOW; /* Smaller Age range redefined after movingaverage */
1.136 brouard 10585:
1.165 brouard 10586: double fret;
1.191 brouard 10587: double dum=0.; /* Dummy variable */
1.136 brouard 10588: double ***p3mat;
1.218 brouard 10589: /* double ***mobaverage; */
1.164 brouard 10590:
10591: char line[MAXLINE];
1.197 brouard 10592: char path[MAXLINE],pathc[MAXLINE],pathcd[MAXLINE],pathtot[MAXLINE];
10593:
1.234 brouard 10594: char modeltemp[MAXLINE];
1.230 brouard 10595: char resultline[MAXLINE];
10596:
1.136 brouard 10597: char pathr[MAXLINE], pathimach[MAXLINE];
1.164 brouard 10598: char *tok, *val; /* pathtot */
1.136 brouard 10599: int firstobs=1, lastobs=10;
1.195 brouard 10600: int c, h , cpt, c2;
1.191 brouard 10601: int jl=0;
10602: int i1, j1, jk, stepsize=0;
1.194 brouard 10603: int count=0;
10604:
1.164 brouard 10605: int *tab;
1.136 brouard 10606: int mobilavproj=0 , prevfcast=0 ; /* moving average of prev, If prevfcast=1 prevalence projection */
1.217 brouard 10607: int backcast=0;
1.136 brouard 10608: int mobilav=0,popforecast=0;
1.191 brouard 10609: int hstepm=0, nhstepm=0;
1.136 brouard 10610: int agemortsup;
10611: float sumlpop=0.;
10612: double jprev1=1, mprev1=1,anprev1=2000,jprev2=1, mprev2=1,anprev2=2000;
10613: double jpyram=1, mpyram=1,anpyram=2000,jpyram1=1, mpyram1=1,anpyram1=2000;
10614:
1.191 brouard 10615: double bage=0, fage=110., age, agelim=0., agebase=0.;
1.136 brouard 10616: double ftolpl=FTOL;
10617: double **prlim;
1.217 brouard 10618: double **bprlim;
1.136 brouard 10619: double ***param; /* Matrix of parameters */
1.251 brouard 10620: double ***paramstart; /* Matrix of starting parameter values */
10621: double *p, *pstart; /* p=param[1][1] pstart is for starting values guessed by freqsummary */
1.136 brouard 10622: double **matcov; /* Matrix of covariance */
1.203 brouard 10623: double **hess; /* Hessian matrix */
1.136 brouard 10624: double ***delti3; /* Scale */
10625: double *delti; /* Scale */
10626: double ***eij, ***vareij;
10627: double **varpl; /* Variances of prevalence limits by age */
1.269 brouard 10628:
1.136 brouard 10629: double *epj, vepp;
1.164 brouard 10630:
1.136 brouard 10631: double dateprev1, dateprev2,jproj1=1,mproj1=1,anproj1=2000,jproj2=1,mproj2=1,anproj2=2000;
1.217 brouard 10632: double jback1=1,mback1=1,anback1=2000,jback2=1,mback2=1,anback2=2000;
10633:
1.136 brouard 10634: double **ximort;
1.145 brouard 10635: char *alph[]={"a","a","b","c","d","e"}, str[4]="1234";
1.136 brouard 10636: int *dcwave;
10637:
1.164 brouard 10638: char z[1]="c";
1.136 brouard 10639:
10640: /*char *strt;*/
10641: char strtend[80];
1.126 brouard 10642:
1.164 brouard 10643:
1.126 brouard 10644: /* setlocale (LC_ALL, ""); */
10645: /* bindtextdomain (PACKAGE, LOCALEDIR); */
10646: /* textdomain (PACKAGE); */
10647: /* setlocale (LC_CTYPE, ""); */
10648: /* setlocale (LC_MESSAGES, ""); */
10649:
10650: /* gettimeofday(&start_time, (struct timezone*)0); */ /* at first time */
1.157 brouard 10651: rstart_time = time(NULL);
10652: /* (void) gettimeofday(&start_time,&tzp);*/
10653: start_time = *localtime(&rstart_time);
1.126 brouard 10654: curr_time=start_time;
1.157 brouard 10655: /*tml = *localtime(&start_time.tm_sec);*/
10656: /* strcpy(strstart,asctime(&tml)); */
10657: strcpy(strstart,asctime(&start_time));
1.126 brouard 10658:
10659: /* printf("Localtime (at start)=%s",strstart); */
1.157 brouard 10660: /* tp.tm_sec = tp.tm_sec +86400; */
10661: /* tm = *localtime(&start_time.tm_sec); */
1.126 brouard 10662: /* tmg.tm_year=tmg.tm_year +dsign*dyear; */
10663: /* tmg.tm_mon=tmg.tm_mon +dsign*dmonth; */
10664: /* tmg.tm_hour=tmg.tm_hour + 1; */
1.157 brouard 10665: /* tp.tm_sec = mktime(&tmg); */
1.126 brouard 10666: /* strt=asctime(&tmg); */
10667: /* printf("Time(after) =%s",strstart); */
10668: /* (void) time (&time_value);
10669: * printf("time=%d,t-=%d\n",time_value,time_value-86400);
10670: * tm = *localtime(&time_value);
10671: * strstart=asctime(&tm);
10672: * printf("tim_value=%d,asctime=%s\n",time_value,strstart);
10673: */
10674:
10675: nberr=0; /* Number of errors and warnings */
10676: nbwarn=0;
1.184 brouard 10677: #ifdef WIN32
10678: _getcwd(pathcd, size);
10679: #else
1.126 brouard 10680: getcwd(pathcd, size);
1.184 brouard 10681: #endif
1.191 brouard 10682: syscompilerinfo(0);
1.196 brouard 10683: printf("\nIMaCh version %s, %s\n%s",version, copyright, fullversion);
1.126 brouard 10684: if(argc <=1){
10685: printf("\nEnter the parameter file name: ");
1.205 brouard 10686: if(!fgets(pathr,FILENAMELENGTH,stdin)){
10687: printf("ERROR Empty parameter file name\n");
10688: goto end;
10689: }
1.126 brouard 10690: i=strlen(pathr);
10691: if(pathr[i-1]=='\n')
10692: pathr[i-1]='\0';
1.156 brouard 10693: i=strlen(pathr);
1.205 brouard 10694: if(i >= 1 && pathr[i-1]==' ') {/* This may happen when dragging on oS/X! */
1.156 brouard 10695: pathr[i-1]='\0';
1.205 brouard 10696: }
10697: i=strlen(pathr);
10698: if( i==0 ){
10699: printf("ERROR Empty parameter file name\n");
10700: goto end;
10701: }
10702: for (tok = pathr; tok != NULL; ){
1.126 brouard 10703: printf("Pathr |%s|\n",pathr);
10704: while ((val = strsep(&tok, "\"" )) != NULL && *val == '\0');
10705: printf("val= |%s| pathr=%s\n",val,pathr);
10706: strcpy (pathtot, val);
10707: if(pathr[0] == '\0') break; /* Dirty */
10708: }
10709: }
10710: else{
10711: strcpy(pathtot,argv[1]);
10712: }
10713: /*if(getcwd(pathcd, MAXLINE)!= NULL)printf ("Error pathcd\n");*/
10714: /*cygwin_split_path(pathtot,path,optionfile);
10715: printf("pathtot=%s, path=%s, optionfile=%s\n",pathtot,path,optionfile);*/
10716: /* cutv(path,optionfile,pathtot,'\\');*/
10717:
10718: /* Split argv[0], imach program to get pathimach */
10719: printf("\nargv[0]=%s argv[1]=%s, \n",argv[0],argv[1]);
10720: split(argv[0],pathimach,optionfile,optionfilext,optionfilefiname);
10721: printf("\nargv[0]=%s pathimach=%s, \noptionfile=%s \noptionfilext=%s \noptionfilefiname=%s\n",argv[0],pathimach,optionfile,optionfilext,optionfilefiname);
10722: /* strcpy(pathimach,argv[0]); */
10723: /* Split argv[1]=pathtot, parameter file name to get path, optionfile, extension and name */
10724: split(pathtot,path,optionfile,optionfilext,optionfilefiname);
10725: printf("\npathtot=%s,\npath=%s,\noptionfile=%s \noptionfilext=%s \noptionfilefiname=%s\n",pathtot,path,optionfile,optionfilext,optionfilefiname);
1.184 brouard 10726: #ifdef WIN32
10727: _chdir(path); /* Can be a relative path */
10728: if(_getcwd(pathcd,MAXLINE) > 0) /* So pathcd is the full path */
10729: #else
1.126 brouard 10730: chdir(path); /* Can be a relative path */
1.184 brouard 10731: if (getcwd(pathcd, MAXLINE) > 0) /* So pathcd is the full path */
10732: #endif
10733: printf("Current directory %s!\n",pathcd);
1.126 brouard 10734: strcpy(command,"mkdir ");
10735: strcat(command,optionfilefiname);
10736: if((outcmd=system(command)) != 0){
1.169 brouard 10737: printf("Directory already exists (or can't create it) %s%s, err=%d\n",path,optionfilefiname,outcmd);
1.126 brouard 10738: /* fprintf(ficlog,"Problem creating directory %s%s\n",path,optionfilefiname); */
10739: /* fclose(ficlog); */
10740: /* exit(1); */
10741: }
10742: /* if((imk=mkdir(optionfilefiname))<0){ */
10743: /* perror("mkdir"); */
10744: /* } */
10745:
10746: /*-------- arguments in the command line --------*/
10747:
1.186 brouard 10748: /* Main Log file */
1.126 brouard 10749: strcat(filelog, optionfilefiname);
10750: strcat(filelog,".log"); /* */
10751: if((ficlog=fopen(filelog,"w"))==NULL) {
10752: printf("Problem with logfile %s\n",filelog);
10753: goto end;
10754: }
10755: fprintf(ficlog,"Log filename:%s\n",filelog);
1.197 brouard 10756: fprintf(ficlog,"Version %s %s",version,fullversion);
1.126 brouard 10757: fprintf(ficlog,"\nEnter the parameter file name: \n");
10758: fprintf(ficlog,"pathimach=%s\npathtot=%s\n\
10759: path=%s \n\
10760: optionfile=%s\n\
10761: optionfilext=%s\n\
1.156 brouard 10762: optionfilefiname='%s'\n",pathimach,pathtot,path,optionfile,optionfilext,optionfilefiname);
1.126 brouard 10763:
1.197 brouard 10764: syscompilerinfo(1);
1.167 brouard 10765:
1.126 brouard 10766: printf("Local time (at start):%s",strstart);
10767: fprintf(ficlog,"Local time (at start): %s",strstart);
10768: fflush(ficlog);
10769: /* (void) gettimeofday(&curr_time,&tzp); */
1.157 brouard 10770: /* printf("Elapsed time %d\n", asc_diff_time(curr_time.tm_sec-start_time.tm_sec,tmpout)); */
1.126 brouard 10771:
10772: /* */
10773: strcpy(fileres,"r");
10774: strcat(fileres, optionfilefiname);
1.201 brouard 10775: strcat(fileresu, optionfilefiname); /* Without r in front */
1.126 brouard 10776: strcat(fileres,".txt"); /* Other files have txt extension */
1.201 brouard 10777: strcat(fileresu,".txt"); /* Other files have txt extension */
1.126 brouard 10778:
1.186 brouard 10779: /* Main ---------arguments file --------*/
1.126 brouard 10780:
10781: if((ficpar=fopen(optionfile,"r"))==NULL) {
1.155 brouard 10782: printf("Problem with optionfile '%s' with errno='%s'\n",optionfile,strerror(errno));
10783: fprintf(ficlog,"Problem with optionfile '%s' with errno='%s'\n",optionfile,strerror(errno));
1.126 brouard 10784: fflush(ficlog);
1.149 brouard 10785: /* goto end; */
10786: exit(70);
1.126 brouard 10787: }
10788:
10789:
10790:
10791: strcpy(filereso,"o");
1.201 brouard 10792: strcat(filereso,fileresu);
1.126 brouard 10793: if((ficparo=fopen(filereso,"w"))==NULL) { /* opened on subdirectory */
10794: printf("Problem with Output resultfile: %s\n", filereso);
10795: fprintf(ficlog,"Problem with Output resultfile: %s\n", filereso);
10796: fflush(ficlog);
10797: goto end;
10798: }
10799:
10800: /* Reads comments: lines beginning with '#' */
10801: numlinepar=0;
1.197 brouard 10802:
10803: /* First parameter line */
10804: while(fgets(line, MAXLINE, ficpar)) {
10805: /* If line starts with a # it is a comment */
10806: if (line[0] == '#') {
10807: numlinepar++;
10808: fputs(line,stdout);
10809: fputs(line,ficparo);
10810: fputs(line,ficlog);
10811: continue;
10812: }else
10813: break;
10814: }
10815: if((num_filled=sscanf(line,"title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", \
10816: title, datafile, &lastobs, &firstpass,&lastpass)) !=EOF){
10817: if (num_filled != 5) {
10818: printf("Should be 5 parameters\n");
10819: }
1.126 brouard 10820: numlinepar++;
1.197 brouard 10821: printf("title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", title, datafile, lastobs, firstpass,lastpass);
10822: }
10823: /* Second parameter line */
10824: while(fgets(line, MAXLINE, ficpar)) {
10825: /* If line starts with a # it is a comment */
10826: if (line[0] == '#') {
10827: numlinepar++;
10828: fputs(line,stdout);
10829: fputs(line,ficparo);
10830: fputs(line,ficlog);
10831: continue;
10832: }else
10833: break;
10834: }
1.223 brouard 10835: 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", \
10836: &ftol, &stepm, &ncovcol, &nqv, &ntv, &nqtv, &nlstate, &ndeath, &maxwav, &mle, &weightopt)) !=EOF){
10837: if (num_filled != 11) {
10838: 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 10839: printf("but line=%s\n",line);
1.197 brouard 10840: }
1.223 brouard 10841: 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 10842: }
1.203 brouard 10843: /* ftolpl=6*ftol*1.e5; /\* 6.e-3 make convergences in less than 80 loops for the prevalence limit *\/ */
1.209 brouard 10844: /*ftolpl=6.e-4; *//* 6.e-3 make convergences in less than 80 loops for the prevalence limit */
1.197 brouard 10845: /* Third parameter line */
10846: while(fgets(line, MAXLINE, ficpar)) {
10847: /* If line starts with a # it is a comment */
10848: if (line[0] == '#') {
10849: numlinepar++;
10850: fputs(line,stdout);
10851: fputs(line,ficparo);
10852: fputs(line,ficlog);
10853: continue;
10854: }else
10855: break;
10856: }
1.201 brouard 10857: if((num_filled=sscanf(line,"model=1+age%[^.\n]", model)) !=EOF){
1.263 brouard 10858: if (num_filled == 0){
10859: printf("ERROR %d: Model should be at minimum 'model=1+age.' WITHOUT space:'%s'\n",num_filled, line);
10860: fprintf(ficlog,"ERROR %d: Model should be at minimum 'model=1+age.' WITHOUT space:'%s'\n",num_filled, line);
10861: model[0]='\0';
10862: goto end;
10863: } else if (num_filled != 1){
1.197 brouard 10864: printf("ERROR %d: Model should be at minimum 'model=1+age.' %s\n",num_filled, line);
10865: fprintf(ficlog,"ERROR %d: Model should be at minimum 'model=1+age.' %s\n",num_filled, line);
10866: model[0]='\0';
10867: goto end;
10868: }
10869: else{
10870: if (model[0]=='+'){
10871: for(i=1; i<=strlen(model);i++)
10872: modeltemp[i-1]=model[i];
1.201 brouard 10873: strcpy(model,modeltemp);
1.197 brouard 10874: }
10875: }
1.199 brouard 10876: /* printf(" model=1+age%s modeltemp= %s, model=%s\n",model, modeltemp, model);fflush(stdout); */
1.203 brouard 10877: printf("model=1+age+%s\n",model);fflush(stdout);
1.197 brouard 10878: }
10879: /* 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); */
10880: /* numlinepar=numlinepar+3; /\* In general *\/ */
10881: /* 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 10882: 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);
10883: 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 10884: fflush(ficlog);
1.190 brouard 10885: /* if(model[0]=='#'|| model[0]== '\0'){ */
10886: if(model[0]=='#'){
1.187 brouard 10887: printf("Error in 'model' line: model should start with 'model=1+age+' and end with '.' \n \
10888: 'model=1+age+.' or 'model=1+age+V1.' or 'model=1+age+age*age+V1+V1*age.' or \n \
10889: 'model=1+age+V1+V2.' or 'model=1+age+V1+V2+V1*V2.' etc. \n"); \
10890: if(mle != -1){
10891: printf("Fix the model line and run imach with mle=-1 to get a correct template of the parameter file.\n");
10892: exit(1);
10893: }
10894: }
1.126 brouard 10895: while((c=getc(ficpar))=='#' && c!= EOF){
10896: ungetc(c,ficpar);
10897: fgets(line, MAXLINE, ficpar);
10898: numlinepar++;
1.195 brouard 10899: if(line[1]=='q'){ /* This #q will quit imach (the answer is q) */
10900: z[0]=line[1];
10901: }
10902: /* printf("****line [1] = %c \n",line[1]); */
1.141 brouard 10903: fputs(line, stdout);
10904: //puts(line);
1.126 brouard 10905: fputs(line,ficparo);
10906: fputs(line,ficlog);
10907: }
10908: ungetc(c,ficpar);
10909:
10910:
1.145 brouard 10911: covar=matrix(0,NCOVMAX,1,n); /**< used in readdata */
1.268 brouard 10912: if(nqv>=1)coqvar=matrix(1,nqv,1,n); /**< Fixed quantitative covariate */
10913: if(nqtv>=1)cotqvar=ma3x(1,maxwav,1,nqtv,1,n); /**< Time varying quantitative covariate */
10914: if(ntv+nqtv>=1)cotvar=ma3x(1,maxwav,1,ntv+nqtv,1,n); /**< Time varying covariate (dummy and quantitative)*/
1.136 brouard 10915: cptcovn=0; /*Number of covariates, i.e. number of '+' in model statement plus one, indepently of n in Vn*/
10916: /* v1+v2+v3+v2*v4+v5*age makes cptcovn = 5
10917: v1+v2*age+v2*v3 makes cptcovn = 3
10918: */
10919: if (strlen(model)>1)
1.187 brouard 10920: 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 10921: else
1.187 brouard 10922: ncovmodel=2; /* Constant and age */
1.133 brouard 10923: nforce= (nlstate+ndeath-1)*nlstate; /* Number of forces ij from state i to j */
10924: npar= nforce*ncovmodel; /* Number of parameters like aij*/
1.131 brouard 10925: if(npar >MAXPARM || nlstate >NLSTATEMAX || ndeath >NDEATHMAX || ncovmodel>NCOVMAX){
10926: 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);
10927: 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);
10928: fflush(stdout);
10929: fclose (ficlog);
10930: goto end;
10931: }
1.126 brouard 10932: delti3= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
10933: delti=delti3[1][1];
10934: /*delti=vector(1,npar); *//* Scale of each paramater (output from hesscov)*/
10935: if(mle==-1){ /* Print a wizard for help writing covariance matrix */
1.247 brouard 10936: /* We could also provide initial parameters values giving by simple logistic regression
10937: * only one way, that is without matrix product. We will have nlstate maximizations */
10938: /* for(i=1;i<nlstate;i++){ */
10939: /* /\*reducing xi for 1 to npar to 1 to ncovmodel; *\/ */
10940: /* mlikeli(ficres,p, ncovmodel, ncovmodel, nlstate, ftol, funcnoprod); */
10941: /* } */
1.126 brouard 10942: prwizard(ncovmodel, nlstate, ndeath, model, ficparo);
1.191 brouard 10943: printf(" You chose mle=-1, look at file %s for a template of covariance matrix \n",filereso);
10944: fprintf(ficlog," You chose mle=-1, look at file %s for a template of covariance matrix \n",filereso);
1.126 brouard 10945: free_ma3x(delti3,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
10946: fclose (ficparo);
10947: fclose (ficlog);
10948: goto end;
10949: exit(0);
1.220 brouard 10950: } else if(mle==-5) { /* Main Wizard */
1.126 brouard 10951: prwizard(ncovmodel, nlstate, ndeath, model, ficparo);
1.192 brouard 10952: printf(" You chose mle=-3, look at file %s for a template of covariance matrix \n",filereso);
10953: fprintf(ficlog," You chose mle=-3, look at file %s for a template of covariance matrix \n",filereso);
1.126 brouard 10954: param= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
10955: matcov=matrix(1,npar,1,npar);
1.203 brouard 10956: hess=matrix(1,npar,1,npar);
1.220 brouard 10957: } else{ /* Begin of mle != -1 or -5 */
1.145 brouard 10958: /* Read guessed parameters */
1.126 brouard 10959: /* Reads comments: lines beginning with '#' */
10960: while((c=getc(ficpar))=='#' && c!= EOF){
10961: ungetc(c,ficpar);
10962: fgets(line, MAXLINE, ficpar);
10963: numlinepar++;
1.141 brouard 10964: fputs(line,stdout);
1.126 brouard 10965: fputs(line,ficparo);
10966: fputs(line,ficlog);
10967: }
10968: ungetc(c,ficpar);
10969:
10970: param= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
1.251 brouard 10971: paramstart= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
1.126 brouard 10972: for(i=1; i <=nlstate; i++){
1.234 brouard 10973: j=0;
1.126 brouard 10974: for(jj=1; jj <=nlstate+ndeath; jj++){
1.234 brouard 10975: if(jj==i) continue;
10976: j++;
10977: fscanf(ficpar,"%1d%1d",&i1,&j1);
10978: if ((i1 != i) || (j1 != jj)){
10979: printf("Error in line parameters number %d, %1d%1d instead of %1d%1d \n \
1.126 brouard 10980: It might be a problem of design; if ncovcol and the model are correct\n \
10981: run imach with mle=-1 to get a correct template of the parameter file.\n",numlinepar, i,j, i1, j1);
1.234 brouard 10982: exit(1);
10983: }
10984: fprintf(ficparo,"%1d%1d",i1,j1);
10985: if(mle==1)
10986: printf("%1d%1d",i,jj);
10987: fprintf(ficlog,"%1d%1d",i,jj);
10988: for(k=1; k<=ncovmodel;k++){
10989: fscanf(ficpar," %lf",¶m[i][j][k]);
10990: if(mle==1){
10991: printf(" %lf",param[i][j][k]);
10992: fprintf(ficlog," %lf",param[i][j][k]);
10993: }
10994: else
10995: fprintf(ficlog," %lf",param[i][j][k]);
10996: fprintf(ficparo," %lf",param[i][j][k]);
10997: }
10998: fscanf(ficpar,"\n");
10999: numlinepar++;
11000: if(mle==1)
11001: printf("\n");
11002: fprintf(ficlog,"\n");
11003: fprintf(ficparo,"\n");
1.126 brouard 11004: }
11005: }
11006: fflush(ficlog);
1.234 brouard 11007:
1.251 brouard 11008: /* Reads parameters values */
1.126 brouard 11009: p=param[1][1];
1.251 brouard 11010: pstart=paramstart[1][1];
1.126 brouard 11011:
11012: /* Reads comments: lines beginning with '#' */
11013: while((c=getc(ficpar))=='#' && c!= EOF){
11014: ungetc(c,ficpar);
11015: fgets(line, MAXLINE, ficpar);
11016: numlinepar++;
1.141 brouard 11017: fputs(line,stdout);
1.126 brouard 11018: fputs(line,ficparo);
11019: fputs(line,ficlog);
11020: }
11021: ungetc(c,ficpar);
11022:
11023: for(i=1; i <=nlstate; i++){
11024: for(j=1; j <=nlstate+ndeath-1; j++){
1.234 brouard 11025: fscanf(ficpar,"%1d%1d",&i1,&j1);
11026: if ( (i1-i) * (j1-j) != 0){
11027: printf("Error in line parameters number %d, %1d%1d instead of %1d%1d \n",numlinepar, i,j, i1, j1);
11028: exit(1);
11029: }
11030: printf("%1d%1d",i,j);
11031: fprintf(ficparo,"%1d%1d",i1,j1);
11032: fprintf(ficlog,"%1d%1d",i1,j1);
11033: for(k=1; k<=ncovmodel;k++){
11034: fscanf(ficpar,"%le",&delti3[i][j][k]);
11035: printf(" %le",delti3[i][j][k]);
11036: fprintf(ficparo," %le",delti3[i][j][k]);
11037: fprintf(ficlog," %le",delti3[i][j][k]);
11038: }
11039: fscanf(ficpar,"\n");
11040: numlinepar++;
11041: printf("\n");
11042: fprintf(ficparo,"\n");
11043: fprintf(ficlog,"\n");
1.126 brouard 11044: }
11045: }
11046: fflush(ficlog);
1.234 brouard 11047:
1.145 brouard 11048: /* Reads covariance matrix */
1.126 brouard 11049: delti=delti3[1][1];
1.220 brouard 11050:
11051:
1.126 brouard 11052: /* 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 11053:
1.126 brouard 11054: /* Reads comments: lines beginning with '#' */
11055: while((c=getc(ficpar))=='#' && c!= EOF){
11056: ungetc(c,ficpar);
11057: fgets(line, MAXLINE, ficpar);
11058: numlinepar++;
1.141 brouard 11059: fputs(line,stdout);
1.126 brouard 11060: fputs(line,ficparo);
11061: fputs(line,ficlog);
11062: }
11063: ungetc(c,ficpar);
1.220 brouard 11064:
1.126 brouard 11065: matcov=matrix(1,npar,1,npar);
1.203 brouard 11066: hess=matrix(1,npar,1,npar);
1.131 brouard 11067: for(i=1; i <=npar; i++)
11068: for(j=1; j <=npar; j++) matcov[i][j]=0.;
1.220 brouard 11069:
1.194 brouard 11070: /* Scans npar lines */
1.126 brouard 11071: for(i=1; i <=npar; i++){
1.226 brouard 11072: count=fscanf(ficpar,"%1d%1d%d",&i1,&j1,&jk);
1.194 brouard 11073: if(count != 3){
1.226 brouard 11074: printf("Error! Error in parameter file %s at line %d after line starting with %1d%1d%1d\n\
1.194 brouard 11075: This is probably because your covariance matrix doesn't \n contain exactly %d lines corresponding to your model line '1+age+%s'.\n\
11076: Please run with mle=-1 to get a correct covariance matrix.\n",optionfile,numlinepar, i1,j1,jk, npar, model);
1.226 brouard 11077: fprintf(ficlog,"Error! Error in parameter file %s at line %d after line starting with %1d%1d%1d\n\
1.194 brouard 11078: This is probably because your covariance matrix doesn't \n contain exactly %d lines corresponding to your model line '1+age+%s'.\n\
11079: Please run with mle=-1 to get a correct covariance matrix.\n",optionfile,numlinepar, i1,j1,jk, npar, model);
1.226 brouard 11080: exit(1);
1.220 brouard 11081: }else{
1.226 brouard 11082: if(mle==1)
11083: printf("%1d%1d%d",i1,j1,jk);
11084: }
11085: fprintf(ficlog,"%1d%1d%d",i1,j1,jk);
11086: fprintf(ficparo,"%1d%1d%d",i1,j1,jk);
1.126 brouard 11087: for(j=1; j <=i; j++){
1.226 brouard 11088: fscanf(ficpar," %le",&matcov[i][j]);
11089: if(mle==1){
11090: printf(" %.5le",matcov[i][j]);
11091: }
11092: fprintf(ficlog," %.5le",matcov[i][j]);
11093: fprintf(ficparo," %.5le",matcov[i][j]);
1.126 brouard 11094: }
11095: fscanf(ficpar,"\n");
11096: numlinepar++;
11097: if(mle==1)
1.220 brouard 11098: printf("\n");
1.126 brouard 11099: fprintf(ficlog,"\n");
11100: fprintf(ficparo,"\n");
11101: }
1.194 brouard 11102: /* End of read covariance matrix npar lines */
1.126 brouard 11103: for(i=1; i <=npar; i++)
11104: for(j=i+1;j<=npar;j++)
1.226 brouard 11105: matcov[i][j]=matcov[j][i];
1.126 brouard 11106:
11107: if(mle==1)
11108: printf("\n");
11109: fprintf(ficlog,"\n");
11110:
11111: fflush(ficlog);
11112:
11113: /*-------- Rewriting parameter file ----------*/
11114: strcpy(rfileres,"r"); /* "Rparameterfile */
11115: strcat(rfileres,optionfilefiname); /* Parameter file first name*/
11116: strcat(rfileres,"."); /* */
11117: strcat(rfileres,optionfilext); /* Other files have txt extension */
11118: if((ficres =fopen(rfileres,"w"))==NULL) {
1.201 brouard 11119: printf("Problem writing new parameter file: %s\n", rfileres);goto end;
11120: fprintf(ficlog,"Problem writing new parameter file: %s\n", rfileres);goto end;
1.126 brouard 11121: }
11122: fprintf(ficres,"#%s\n",version);
11123: } /* End of mle != -3 */
1.218 brouard 11124:
1.186 brouard 11125: /* Main data
11126: */
1.126 brouard 11127: n= lastobs;
11128: num=lvector(1,n);
11129: moisnais=vector(1,n);
11130: annais=vector(1,n);
11131: moisdc=vector(1,n);
11132: andc=vector(1,n);
1.220 brouard 11133: weight=vector(1,n);
1.126 brouard 11134: agedc=vector(1,n);
11135: cod=ivector(1,n);
1.220 brouard 11136: for(i=1;i<=n;i++){
1.234 brouard 11137: num[i]=0;
11138: moisnais[i]=0;
11139: annais[i]=0;
11140: moisdc[i]=0;
11141: andc[i]=0;
11142: agedc[i]=0;
11143: cod[i]=0;
11144: weight[i]=1.0; /* Equal weights, 1 by default */
11145: }
1.126 brouard 11146: mint=matrix(1,maxwav,1,n);
11147: anint=matrix(1,maxwav,1,n);
1.131 brouard 11148: s=imatrix(1,maxwav+1,1,n); /* s[i][j] health state for wave i and individual j */
1.126 brouard 11149: tab=ivector(1,NCOVMAX);
1.144 brouard 11150: ncodemax=ivector(1,NCOVMAX); /* Number of code per covariate; if O and 1 only, 2**ncov; V1+V2+V3+V4=>16 */
1.192 brouard 11151: 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 11152:
1.136 brouard 11153: /* Reads data from file datafile */
11154: if (readdata(datafile, firstobs, lastobs, &imx)==1)
11155: goto end;
11156:
11157: /* Calculation of the number of parameters from char model */
1.234 brouard 11158: /* modelsav=V2+V1+V4+age*V3 strb=age*V3 stra=V2+V1+V4
1.137 brouard 11159: k=4 (age*V3) Tvar[k=4]= 3 (from V3) Tag[cptcovage=1]=4
11160: k=3 V4 Tvar[k=3]= 4 (from V4)
11161: k=2 V1 Tvar[k=2]= 1 (from V1)
11162: k=1 Tvar[1]=2 (from V2)
1.234 brouard 11163: */
11164:
11165: Tvar=ivector(1,NCOVMAX); /* Was 15 changed to NCOVMAX. */
11166: TvarsDind=ivector(1,NCOVMAX); /* */
11167: TvarsD=ivector(1,NCOVMAX); /* */
11168: TvarsQind=ivector(1,NCOVMAX); /* */
11169: TvarsQ=ivector(1,NCOVMAX); /* */
1.232 brouard 11170: TvarF=ivector(1,NCOVMAX); /* */
11171: TvarFind=ivector(1,NCOVMAX); /* */
11172: TvarV=ivector(1,NCOVMAX); /* */
11173: TvarVind=ivector(1,NCOVMAX); /* */
11174: TvarA=ivector(1,NCOVMAX); /* */
11175: TvarAind=ivector(1,NCOVMAX); /* */
1.231 brouard 11176: TvarFD=ivector(1,NCOVMAX); /* */
11177: TvarFDind=ivector(1,NCOVMAX); /* */
11178: TvarFQ=ivector(1,NCOVMAX); /* */
11179: TvarFQind=ivector(1,NCOVMAX); /* */
11180: TvarVD=ivector(1,NCOVMAX); /* */
11181: TvarVDind=ivector(1,NCOVMAX); /* */
11182: TvarVQ=ivector(1,NCOVMAX); /* */
11183: TvarVQind=ivector(1,NCOVMAX); /* */
11184:
1.230 brouard 11185: Tvalsel=vector(1,NCOVMAX); /* */
1.233 brouard 11186: Tvarsel=ivector(1,NCOVMAX); /* */
1.226 brouard 11187: Typevar=ivector(-1,NCOVMAX); /* -1 to 2 */
11188: Fixed=ivector(-1,NCOVMAX); /* -1 to 3 */
11189: Dummy=ivector(-1,NCOVMAX); /* -1 to 3 */
1.137 brouard 11190: /* V2+V1+V4+age*V3 is a model with 4 covariates (3 plus signs).
11191: For each model-covariate stores the data-covariate id. Tvar[1]=2, Tvar[2]=1, Tvar[3]=4,
11192: Tvar[4=age*V3] is 3 and 'age' is recorded in Tage.
11193: */
11194: /* For model-covariate k tells which data-covariate to use but
11195: because this model-covariate is a construction we invent a new column
11196: ncovcol + k1
11197: If already ncovcol=4 and model=V2+V1+V1*V4+age*V3
11198: Tvar[3=V1*V4]=4+1 etc */
1.227 brouard 11199: Tprod=ivector(1,NCOVMAX); /* Gives the k position of the k1 product */
11200: Tposprod=ivector(1,NCOVMAX); /* Gives the k1 product from the k position */
1.137 brouard 11201: /* Tprod[k1=1]=3(=V1*V4) for V2+V1+V1*V4+age*V3
11202: if V2+V1+V1*V4+age*V3+V3*V2 TProd[k1=2]=5 (V3*V2)
1.227 brouard 11203: Tposprod[k]=k1 , Tposprod[3]=1, Tposprod[5]=2
1.137 brouard 11204: */
1.145 brouard 11205: Tvaraff=ivector(1,NCOVMAX); /* Unclear */
11206: 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 11207: * For V3*V2 (in V2+V1+V1*V4+age*V3+V3*V2), V3*V2 position is 2nd.
11208: * Tvard[k1=2][1]=3 (V3) Tvard[k1=2][2]=2(V2) */
1.145 brouard 11209: Tage=ivector(1,NCOVMAX); /* Gives the covariate id of covariates associated with age: V2 + V1 + age*V4 + V3*age
1.137 brouard 11210: 4 covariates (3 plus signs)
11211: Tage[1=V3*age]= 4; Tage[2=age*V4] = 3
11212: */
1.230 brouard 11213: Tmodelind=ivector(1,NCOVMAX);/** gives the k model position of an
1.227 brouard 11214: * individual dummy, fixed or varying:
11215: * Tmodelind[Tvaraff[3]]=9,Tvaraff[1]@9={4,
11216: * 3, 1, 0, 0, 0, 0, 0, 0},
1.230 brouard 11217: * model=V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 ,
11218: * V1 df, V2 qf, V3 & V4 dv, V5 qv
11219: * Tmodelind[1]@9={9,0,3,2,}*/
11220: TmodelInvind=ivector(1,NCOVMAX); /* TmodelInvind=Tvar[k]- ncovcol-nqv={5-2-1=2,*/
11221: TmodelInvQind=ivector(1,NCOVMAX);/** gives the k model position of an
1.228 brouard 11222: * individual quantitative, fixed or varying:
11223: * Tmodelqind[1]=1,Tvaraff[1]@9={4,
11224: * 3, 1, 0, 0, 0, 0, 0, 0},
11225: * model=V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1*/
1.186 brouard 11226: /* Main decodemodel */
11227:
1.187 brouard 11228:
1.223 brouard 11229: if(decodemodel(model, lastobs) == 1) /* In order to get Tvar[k] V4+V3+V5 p Tvar[1]@3 = {4, 3, 5}*/
1.136 brouard 11230: goto end;
11231:
1.137 brouard 11232: if((double)(lastobs-imx)/(double)imx > 1.10){
11233: nbwarn++;
11234: 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);
11235: 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);
11236: }
1.136 brouard 11237: /* if(mle==1){*/
1.137 brouard 11238: if (weightopt != 1) { /* Maximisation without weights. We can have weights different from 1 but want no weight*/
11239: for(i=1;i<=imx;i++) weight[i]=1.0; /* changed to imx */
1.136 brouard 11240: }
11241:
11242: /*-calculation of age at interview from date of interview and age at death -*/
11243: agev=matrix(1,maxwav,1,imx);
11244:
11245: if(calandcheckages(imx, maxwav, &agemin, &agemax, &nberr, &nbwarn) == 1)
11246: goto end;
11247:
1.126 brouard 11248:
1.136 brouard 11249: agegomp=(int)agemin;
11250: free_vector(moisnais,1,n);
11251: free_vector(annais,1,n);
1.126 brouard 11252: /* free_matrix(mint,1,maxwav,1,n);
11253: free_matrix(anint,1,maxwav,1,n);*/
1.215 brouard 11254: /* free_vector(moisdc,1,n); */
11255: /* free_vector(andc,1,n); */
1.145 brouard 11256: /* */
11257:
1.126 brouard 11258: wav=ivector(1,imx);
1.214 brouard 11259: /* dh=imatrix(1,lastpass-firstpass+1,1,imx); */
11260: /* bh=imatrix(1,lastpass-firstpass+1,1,imx); */
11261: /* mw=imatrix(1,lastpass-firstpass+1,1,imx); */
11262: 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.*/
11263: bh=imatrix(1,lastpass-firstpass+2,1,imx);
11264: mw=imatrix(1,lastpass-firstpass+2,1,imx);
1.126 brouard 11265:
11266: /* Concatenates waves */
1.214 brouard 11267: /* Concatenates waves: wav[i] is the number of effective (useful waves) of individual i.
11268: Death is a valid wave (if date is known).
11269: mw[mi][i] is the number of (mi=1 to wav[i]) effective wave out of mi of individual i
11270: dh[m][i] or dh[mw[mi][i]][i] is the delay between two effective waves m=mw[mi][i]
11271: and mw[mi+1][i]. dh depends on stepm.
11272: */
11273:
1.126 brouard 11274: concatwav(wav, dh, bh, mw, s, agedc, agev, firstpass, lastpass, imx, nlstate, stepm);
1.248 brouard 11275: /* Concatenates waves */
1.145 brouard 11276:
1.215 brouard 11277: free_vector(moisdc,1,n);
11278: free_vector(andc,1,n);
11279:
1.126 brouard 11280: /* Routine tricode is to calculate cptcoveff (real number of unique covariates) and to associate covariable number and modality */
11281: nbcode=imatrix(0,NCOVMAX,0,NCOVMAX);
11282: ncodemax[1]=1;
1.145 brouard 11283: Ndum =ivector(-1,NCOVMAX);
1.225 brouard 11284: cptcoveff=0;
1.220 brouard 11285: if (ncovmodel-nagesqr > 2 ){ /* That is if covariate other than cst, age and age*age */
11286: tricode(&cptcoveff,Tvar,nbcode,imx, Ndum); /**< Fills nbcode[Tvar[j]][l]; */
1.227 brouard 11287: }
11288:
11289: ncovcombmax=pow(2,cptcoveff);
11290: invalidvarcomb=ivector(1, ncovcombmax);
11291: for(i=1;i<ncovcombmax;i++)
11292: invalidvarcomb[i]=0;
11293:
1.211 brouard 11294: /* Nbcode gives the value of the lth modality (currently 1 to 2) of jth covariate, in
1.186 brouard 11295: V2+V1*age, there are 3 covariates Tvar[2]=1 (V1).*/
1.211 brouard 11296: /* 1 to ncodemax[j] which is the maximum value of this jth covariate */
1.227 brouard 11297:
1.200 brouard 11298: /* codtab=imatrix(1,100,1,10);*/ /* codtab[h,k]=( (h-1) - mod(k-1,2**(k-1) )/2**(k-1) */
1.198 brouard 11299: /*printf(" codtab[1,1],codtab[100,10]=%d,%d\n", codtab[1][1],codtabm(100,10));*/
1.186 brouard 11300: /* codtab gives the value 1 or 2 of the hth combination of k covariates (1 or 2).*/
1.211 brouard 11301: /* nbcode[Tvaraff[j]][codtabm(h,j)]) : if there are only 2 modalities for a covariate j,
11302: * codtabm(h,j) gives its value classified at position h and nbcode gives how it is coded
11303: * (currently 0 or 1) in the data.
11304: * In a loop on h=1 to 2**k, and a loop on j (=1 to k), we get the value of
11305: * corresponding modality (h,j).
11306: */
11307:
1.145 brouard 11308: h=0;
11309: /*if (cptcovn > 0) */
1.126 brouard 11310: m=pow(2,cptcoveff);
11311:
1.144 brouard 11312: /**< codtab(h,k) k = codtab[h,k]=( (h-1) - mod(k-1,2**(k-1) )/2**(k-1) + 1
1.211 brouard 11313: * For k=4 covariates, h goes from 1 to m=2**k
11314: * codtabm(h,k)= (1 & (h-1) >> (k-1)) + 1;
11315: * #define codtabm(h,k) (1 & (h-1) >> (k-1))+1
1.186 brouard 11316: * h\k 1 2 3 4
1.143 brouard 11317: *______________________________
11318: * 1 i=1 1 i=1 1 i=1 1 i=1 1
11319: * 2 2 1 1 1
11320: * 3 i=2 1 2 1 1
11321: * 4 2 2 1 1
11322: * 5 i=3 1 i=2 1 2 1
11323: * 6 2 1 2 1
11324: * 7 i=4 1 2 2 1
11325: * 8 2 2 2 1
1.197 brouard 11326: * 9 i=5 1 i=3 1 i=2 1 2
11327: * 10 2 1 1 2
11328: * 11 i=6 1 2 1 2
11329: * 12 2 2 1 2
11330: * 13 i=7 1 i=4 1 2 2
11331: * 14 2 1 2 2
11332: * 15 i=8 1 2 2 2
11333: * 16 2 2 2 2
1.143 brouard 11334: */
1.212 brouard 11335: /* How to do the opposite? From combination h (=1 to 2**k) how to get the value on the covariates? */
1.211 brouard 11336: /* from h=5 and m, we get then number of covariates k=log(m)/log(2)=4
11337: * and the value of each covariate?
11338: * V1=1, V2=1, V3=2, V4=1 ?
11339: * h-1=4 and 4 is 0100 or reverse 0010, and +1 is 1121 ok.
11340: * h=6, 6-1=5, 5 is 0101, 1010, 2121, V1=2nd, V2=1st, V3=2nd, V4=1st.
11341: * In order to get the real value in the data, we use nbcode
11342: * nbcode[Tvar[3][2nd]]=1 and nbcode[Tvar[4][1]]=0
11343: * We are keeping this crazy system in order to be able (in the future?)
11344: * to have more than 2 values (0 or 1) for a covariate.
11345: * #define codtabm(h,k) (1 & (h-1) >> (k-1))+1
11346: * h=6, k=2? h-1=5=0101, reverse 1010, +1=2121, k=2nd position: value is 1: codtabm(6,2)=1
11347: * bbbbbbbb
11348: * 76543210
11349: * h-1 00000101 (6-1=5)
1.219 brouard 11350: *(h-1)>>(k-1)= 00000010 >> (2-1) = 1 right shift
1.211 brouard 11351: * &
11352: * 1 00000001 (1)
1.219 brouard 11353: * 00000000 = 1 & ((h-1) >> (k-1))
11354: * +1= 00000001 =1
1.211 brouard 11355: *
11356: * h=14, k=3 => h'=h-1=13, k'=k-1=2
11357: * h' 1101 =2^3+2^2+0x2^1+2^0
11358: * >>k' 11
11359: * & 00000001
11360: * = 00000001
11361: * +1 = 00000010=2 = codtabm(14,3)
11362: * Reverse h=6 and m=16?
11363: * cptcoveff=log(16)/log(2)=4 covariate: 6-1=5=0101 reversed=1010 +1=2121 =>V1=2, V2=1, V3=2, V4=1.
11364: * for (j=1 to cptcoveff) Vj=decodtabm(j,h,cptcoveff)
11365: * decodtabm(h,j,cptcoveff)= (((h-1) >> (j-1)) & 1) +1
11366: * decodtabm(h,j,cptcoveff)= (h <= (1<<cptcoveff)?(((h-1) >> (j-1)) & 1) +1 : -1)
11367: * V3=decodtabm(14,3,2**4)=2
11368: * h'=13 1101 =2^3+2^2+0x2^1+2^0
11369: *(h-1) >> (j-1) 0011 =13 >> 2
11370: * &1 000000001
11371: * = 000000001
11372: * +1= 000000010 =2
11373: * 2211
11374: * V1=1+1, V2=0+1, V3=1+1, V4=1+1
11375: * V3=2
1.220 brouard 11376: * codtabm and decodtabm are identical
1.211 brouard 11377: */
11378:
1.145 brouard 11379:
11380: free_ivector(Ndum,-1,NCOVMAX);
11381:
11382:
1.126 brouard 11383:
1.186 brouard 11384: /* Initialisation of ----------- gnuplot -------------*/
1.126 brouard 11385: strcpy(optionfilegnuplot,optionfilefiname);
11386: if(mle==-3)
1.201 brouard 11387: strcat(optionfilegnuplot,"-MORT_");
1.126 brouard 11388: strcat(optionfilegnuplot,".gp");
11389:
11390: if((ficgp=fopen(optionfilegnuplot,"w"))==NULL) {
11391: printf("Problem with file %s",optionfilegnuplot);
11392: }
11393: else{
1.204 brouard 11394: fprintf(ficgp,"\n# IMaCh-%s\n", version);
1.126 brouard 11395: fprintf(ficgp,"# %s\n", optionfilegnuplot);
1.141 brouard 11396: //fprintf(ficgp,"set missing 'NaNq'\n");
11397: fprintf(ficgp,"set datafile missing 'NaNq'\n");
1.126 brouard 11398: }
11399: /* fclose(ficgp);*/
1.186 brouard 11400:
11401:
11402: /* Initialisation of --------- index.htm --------*/
1.126 brouard 11403:
11404: strcpy(optionfilehtm,optionfilefiname); /* Main html file */
11405: if(mle==-3)
1.201 brouard 11406: strcat(optionfilehtm,"-MORT_");
1.126 brouard 11407: strcat(optionfilehtm,".htm");
11408: if((fichtm=fopen(optionfilehtm,"w"))==NULL) {
1.131 brouard 11409: printf("Problem with %s \n",optionfilehtm);
11410: exit(0);
1.126 brouard 11411: }
11412:
11413: strcpy(optionfilehtmcov,optionfilefiname); /* Only for matrix of covariance */
11414: strcat(optionfilehtmcov,"-cov.htm");
11415: if((fichtmcov=fopen(optionfilehtmcov,"w"))==NULL) {
11416: printf("Problem with %s \n",optionfilehtmcov), exit(0);
11417: }
11418: else{
11419: fprintf(fichtmcov,"<html><head>\n<title>IMaCh Cov %s</title></head>\n <body><font size=\"2\">%s <br> %s</font> \
11420: <hr size=\"2\" color=\"#EC5E5E\"> \n\
1.204 brouard 11421: Title=%s <br>Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s<br>\n",\
1.126 brouard 11422: optionfilehtmcov,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model);
11423: }
11424:
1.213 brouard 11425: 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 11426: <hr size=\"2\" color=\"#EC5E5E\"> \n\
11427: <font size=\"2\">IMaCh-%s <br> %s</font> \
1.126 brouard 11428: <hr size=\"2\" color=\"#EC5E5E\"> \n\
1.204 brouard 11429: Title=%s <br>Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s<br>\n\
1.126 brouard 11430: \n\
11431: <hr size=\"2\" color=\"#EC5E5E\">\
11432: <ul><li><h4>Parameter files</h4>\n\
11433: - Parameter file: <a href=\"%s.%s\">%s.%s</a><br>\n\
11434: - Copy of the parameter file: <a href=\"o%s\">o%s</a><br>\n\
11435: - Log file of the run: <a href=\"%s\">%s</a><br>\n\
11436: - Gnuplot file name: <a href=\"%s\">%s</a><br>\n\
11437: - Date and time at start: %s</ul>\n",\
11438: optionfilehtm,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model,\
11439: optionfilefiname,optionfilext,optionfilefiname,optionfilext,\
11440: fileres,fileres,\
11441: filelog,filelog,optionfilegnuplot,optionfilegnuplot,strstart);
11442: fflush(fichtm);
11443:
11444: strcpy(pathr,path);
11445: strcat(pathr,optionfilefiname);
1.184 brouard 11446: #ifdef WIN32
11447: _chdir(optionfilefiname); /* Move to directory named optionfile */
11448: #else
1.126 brouard 11449: chdir(optionfilefiname); /* Move to directory named optionfile */
1.184 brouard 11450: #endif
11451:
1.126 brouard 11452:
1.220 brouard 11453: /* Calculates basic frequencies. Computes observed prevalence at single age
11454: and for any valid combination of covariates
1.126 brouard 11455: and prints on file fileres'p'. */
1.251 brouard 11456: freqsummary(fileres, p, pstart, agemin, agemax, s, agev, nlstate, imx, Tvaraff, invalidvarcomb, nbcode, ncodemax,mint,anint,strstart, \
1.227 brouard 11457: firstpass, lastpass, stepm, weightopt, model);
1.126 brouard 11458:
11459: fprintf(fichtm,"\n");
11460: fprintf(fichtm,"<br>Total number of observations=%d <br>\n\
11461: Youngest age at first (selected) pass %.2f, oldest age %.2f<br>\n\
11462: Interval (in months) between two waves: Min=%d Max=%d Mean=%.2lf<br>\n",\
11463: imx,agemin,agemax,jmin,jmax,jmean);
11464: pmmij= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
1.268 brouard 11465: oldms= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
11466: newms= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
11467: savms= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
11468: oldm=oldms; newm=newms; savm=savms; /* Keeps fixed addresses to free */
1.218 brouard 11469:
1.126 brouard 11470: /* For Powell, parameters are in a vector p[] starting at p[1]
11471: so we point p on param[1][1] so that p[1] maps on param[1][1][1] */
11472: p=param[1][1]; /* *(*(*(param +1)+1)+0) */
11473:
11474: globpr=0; /* To get the number ipmx of contributions and the sum of weights*/
1.186 brouard 11475: /* For mortality only */
1.126 brouard 11476: if (mle==-3){
1.136 brouard 11477: ximort=matrix(1,NDIM,1,NDIM);
1.248 brouard 11478: for(i=1;i<=NDIM;i++)
11479: for(j=1;j<=NDIM;j++)
11480: ximort[i][j]=0.;
1.186 brouard 11481: /* ximort=gsl_matrix_alloc(1,NDIM,1,NDIM); */
1.126 brouard 11482: cens=ivector(1,n);
11483: ageexmed=vector(1,n);
11484: agecens=vector(1,n);
11485: dcwave=ivector(1,n);
1.223 brouard 11486:
1.126 brouard 11487: for (i=1; i<=imx; i++){
11488: dcwave[i]=-1;
11489: for (m=firstpass; m<=lastpass; m++)
1.226 brouard 11490: if (s[m][i]>nlstate) {
11491: dcwave[i]=m;
11492: /* printf("i=%d j=%d s=%d dcwave=%d\n",i,j, s[j][i],dcwave[i]);*/
11493: break;
11494: }
1.126 brouard 11495: }
1.226 brouard 11496:
1.126 brouard 11497: for (i=1; i<=imx; i++) {
11498: if (wav[i]>0){
1.226 brouard 11499: ageexmed[i]=agev[mw[1][i]][i];
11500: j=wav[i];
11501: agecens[i]=1.;
11502:
11503: if (ageexmed[i]> 1 && wav[i] > 0){
11504: agecens[i]=agev[mw[j][i]][i];
11505: cens[i]= 1;
11506: }else if (ageexmed[i]< 1)
11507: cens[i]= -1;
11508: if (agedc[i]< AGESUP && agedc[i]>1 && dcwave[i]>firstpass && dcwave[i]<=lastpass)
11509: cens[i]=0 ;
1.126 brouard 11510: }
11511: else cens[i]=-1;
11512: }
11513:
11514: for (i=1;i<=NDIM;i++) {
11515: for (j=1;j<=NDIM;j++)
1.226 brouard 11516: ximort[i][j]=(i == j ? 1.0 : 0.0);
1.126 brouard 11517: }
11518:
1.145 brouard 11519: /*p[1]=0.0268; p[NDIM]=0.083;*/
1.126 brouard 11520: /*printf("%lf %lf", p[1], p[2]);*/
11521:
11522:
1.136 brouard 11523: #ifdef GSL
11524: printf("GSL optimization\n"); fprintf(ficlog,"Powell\n");
1.162 brouard 11525: #else
1.126 brouard 11526: printf("Powell\n"); fprintf(ficlog,"Powell\n");
1.136 brouard 11527: #endif
1.201 brouard 11528: strcpy(filerespow,"POW-MORT_");
11529: strcat(filerespow,fileresu);
1.126 brouard 11530: if((ficrespow=fopen(filerespow,"w"))==NULL) {
11531: printf("Problem with resultfile: %s\n", filerespow);
11532: fprintf(ficlog,"Problem with resultfile: %s\n", filerespow);
11533: }
1.136 brouard 11534: #ifdef GSL
11535: fprintf(ficrespow,"# GSL optimization\n# iter -2*LL");
1.162 brouard 11536: #else
1.126 brouard 11537: fprintf(ficrespow,"# Powell\n# iter -2*LL");
1.136 brouard 11538: #endif
1.126 brouard 11539: /* for (i=1;i<=nlstate;i++)
11540: for(j=1;j<=nlstate+ndeath;j++)
11541: if(j!=i)fprintf(ficrespow," p%1d%1d",i,j);
11542: */
11543: fprintf(ficrespow,"\n");
1.136 brouard 11544: #ifdef GSL
11545: /* gsl starts here */
11546: T = gsl_multimin_fminimizer_nmsimplex;
11547: gsl_multimin_fminimizer *sfm = NULL;
11548: gsl_vector *ss, *x;
11549: gsl_multimin_function minex_func;
11550:
11551: /* Initial vertex size vector */
11552: ss = gsl_vector_alloc (NDIM);
11553:
11554: if (ss == NULL){
11555: GSL_ERROR_VAL ("failed to allocate space for ss", GSL_ENOMEM, 0);
11556: }
11557: /* Set all step sizes to 1 */
11558: gsl_vector_set_all (ss, 0.001);
11559:
11560: /* Starting point */
1.126 brouard 11561:
1.136 brouard 11562: x = gsl_vector_alloc (NDIM);
11563:
11564: if (x == NULL){
11565: gsl_vector_free(ss);
11566: GSL_ERROR_VAL ("failed to allocate space for x", GSL_ENOMEM, 0);
11567: }
11568:
11569: /* Initialize method and iterate */
11570: /* p[1]=0.0268; p[NDIM]=0.083; */
1.186 brouard 11571: /* gsl_vector_set(x, 0, 0.0268); */
11572: /* gsl_vector_set(x, 1, 0.083); */
1.136 brouard 11573: gsl_vector_set(x, 0, p[1]);
11574: gsl_vector_set(x, 1, p[2]);
11575:
11576: minex_func.f = &gompertz_f;
11577: minex_func.n = NDIM;
11578: minex_func.params = (void *)&p; /* ??? */
11579:
11580: sfm = gsl_multimin_fminimizer_alloc (T, NDIM);
11581: gsl_multimin_fminimizer_set (sfm, &minex_func, x, ss);
11582:
11583: printf("Iterations beginning .....\n\n");
11584: printf("Iter. # Intercept Slope -Log Likelihood Simplex size\n");
11585:
11586: iteri=0;
11587: while (rval == GSL_CONTINUE){
11588: iteri++;
11589: status = gsl_multimin_fminimizer_iterate(sfm);
11590:
11591: if (status) printf("error: %s\n", gsl_strerror (status));
11592: fflush(0);
11593:
11594: if (status)
11595: break;
11596:
11597: rval = gsl_multimin_test_size (gsl_multimin_fminimizer_size (sfm), 1e-6);
11598: ssval = gsl_multimin_fminimizer_size (sfm);
11599:
11600: if (rval == GSL_SUCCESS)
11601: printf ("converged to a local maximum at\n");
11602:
11603: printf("%5d ", iteri);
11604: for (it = 0; it < NDIM; it++){
11605: printf ("%10.5f ", gsl_vector_get (sfm->x, it));
11606: }
11607: printf("f() = %-10.5f ssize = %.7f\n", sfm->fval, ssval);
11608: }
11609:
11610: printf("\n\n Please note: Program should be run many times with varying starting points to detemine global maximum\n\n");
11611:
11612: gsl_vector_free(x); /* initial values */
11613: gsl_vector_free(ss); /* inital step size */
11614: for (it=0; it<NDIM; it++){
11615: p[it+1]=gsl_vector_get(sfm->x,it);
11616: fprintf(ficrespow," %.12lf", p[it]);
11617: }
11618: gsl_multimin_fminimizer_free (sfm); /* p *(sfm.x.data) et p *(sfm.x.data+1) */
11619: #endif
11620: #ifdef POWELL
11621: powell(p,ximort,NDIM,ftol,&iter,&fret,gompertz);
11622: #endif
1.126 brouard 11623: fclose(ficrespow);
11624:
1.203 brouard 11625: hesscov(matcov, hess, p, NDIM, delti, 1e-4, gompertz);
1.126 brouard 11626:
11627: for(i=1; i <=NDIM; i++)
11628: for(j=i+1;j<=NDIM;j++)
1.220 brouard 11629: matcov[i][j]=matcov[j][i];
1.126 brouard 11630:
11631: printf("\nCovariance matrix\n ");
1.203 brouard 11632: fprintf(ficlog,"\nCovariance matrix\n ");
1.126 brouard 11633: for(i=1; i <=NDIM; i++) {
11634: for(j=1;j<=NDIM;j++){
1.220 brouard 11635: printf("%f ",matcov[i][j]);
11636: fprintf(ficlog,"%f ",matcov[i][j]);
1.126 brouard 11637: }
1.203 brouard 11638: printf("\n "); fprintf(ficlog,"\n ");
1.126 brouard 11639: }
11640:
11641: printf("iter=%d MLE=%f Eq=%lf*exp(%lf*(age-%d))\n",iter,-gompertz(p),p[1],p[2],agegomp);
1.193 brouard 11642: for (i=1;i<=NDIM;i++) {
1.126 brouard 11643: printf("%f [%f ; %f]\n",p[i],p[i]-2*sqrt(matcov[i][i]),p[i]+2*sqrt(matcov[i][i]));
1.193 brouard 11644: fprintf(ficlog,"%f [%f ; %f]\n",p[i],p[i]-2*sqrt(matcov[i][i]),p[i]+2*sqrt(matcov[i][i]));
11645: }
1.126 brouard 11646: lsurv=vector(1,AGESUP);
11647: lpop=vector(1,AGESUP);
11648: tpop=vector(1,AGESUP);
11649: lsurv[agegomp]=100000;
11650:
11651: for (k=agegomp;k<=AGESUP;k++) {
11652: agemortsup=k;
11653: if (p[1]*exp(p[2]*(k-agegomp))>1) break;
11654: }
11655:
11656: for (k=agegomp;k<agemortsup;k++)
11657: lsurv[k+1]=lsurv[k]-lsurv[k]*(p[1]*exp(p[2]*(k-agegomp)));
11658:
11659: for (k=agegomp;k<agemortsup;k++){
11660: lpop[k]=(lsurv[k]+lsurv[k+1])/2.;
11661: sumlpop=sumlpop+lpop[k];
11662: }
11663:
11664: tpop[agegomp]=sumlpop;
11665: for (k=agegomp;k<(agemortsup-3);k++){
11666: /* tpop[k+1]=2;*/
11667: tpop[k+1]=tpop[k]-lpop[k];
11668: }
11669:
11670:
11671: printf("\nAge lx qx dx Lx Tx e(x)\n");
11672: for (k=agegomp;k<(agemortsup-2);k++)
11673: 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]);
11674:
11675:
11676: replace_back_to_slash(pathc,pathcd); /* Even gnuplot wants a / */
1.220 brouard 11677: ageminpar=50;
11678: agemaxpar=100;
1.194 brouard 11679: if(ageminpar == AGEOVERFLOW ||agemaxpar == AGEOVERFLOW){
11680: printf("Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
11681: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
11682: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
11683: fprintf(ficlog,"Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
11684: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
11685: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
1.220 brouard 11686: }else{
11687: printf("Warning! ageminpar %f and agemaxpar %f have been fixed because for simplification until it is fixed...\n\n",ageminpar,agemaxpar);
11688: 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 11689: printinggnuplotmort(fileresu, optionfilefiname,ageminpar,agemaxpar,fage, pathc,p);
1.220 brouard 11690: }
1.201 brouard 11691: printinghtmlmort(fileresu,title,datafile, firstpass, lastpass, \
1.126 brouard 11692: stepm, weightopt,\
11693: model,imx,p,matcov,agemortsup);
11694:
11695: free_vector(lsurv,1,AGESUP);
11696: free_vector(lpop,1,AGESUP);
11697: free_vector(tpop,1,AGESUP);
1.220 brouard 11698: free_matrix(ximort,1,NDIM,1,NDIM);
1.136 brouard 11699: free_ivector(cens,1,n);
11700: free_vector(agecens,1,n);
11701: free_ivector(dcwave,1,n);
1.220 brouard 11702: #ifdef GSL
1.136 brouard 11703: #endif
1.186 brouard 11704: } /* Endof if mle==-3 mortality only */
1.205 brouard 11705: /* Standard */
11706: else{ /* For mle !=- 3, could be 0 or 1 or 4 etc. */
11707: globpr=0;/* Computes sum of likelihood for globpr=1 and funcone */
11708: /* Computes likelihood for initial parameters, uses funcone to compute gpimx and gsw */
1.132 brouard 11709: likelione(ficres, p, npar, nlstate, &globpr, &ipmx, &sw, &fretone, funcone); /* Prints the contributions to the likelihood */
1.126 brouard 11710: printf("First Likeli=%12.6f ipmx=%ld sw=%12.6f",fretone,ipmx,sw);
11711: for (k=1; k<=npar;k++)
11712: printf(" %d %8.5f",k,p[k]);
11713: printf("\n");
1.205 brouard 11714: if(mle>=1){ /* Could be 1 or 2, Real Maximization */
11715: /* mlikeli uses func not funcone */
1.247 brouard 11716: /* for(i=1;i<nlstate;i++){ */
11717: /* /\*reducing xi for 1 to npar to 1 to ncovmodel; *\/ */
11718: /* mlikeli(ficres,p, ncovmodel, ncovmodel, nlstate, ftol, funcnoprod); */
11719: /* } */
1.205 brouard 11720: mlikeli(ficres,p, npar, ncovmodel, nlstate, ftol, func);
11721: }
11722: if(mle==0) {/* No optimization, will print the likelihoods for the datafile */
11723: globpr=0;/* Computes sum of likelihood for globpr=1 and funcone */
11724: /* Computes likelihood for initial parameters, uses funcone to compute gpimx and gsw */
11725: likelione(ficres, p, npar, nlstate, &globpr, &ipmx, &sw, &fretone, funcone); /* Prints the contributions to the likelihood */
11726: }
11727: globpr=1; /* again, to print the individual contributions using computed gpimx and gsw */
1.126 brouard 11728: likelione(ficres, p, npar, nlstate, &globpr, &ipmx, &sw, &fretone, funcone); /* Prints the contributions to the likelihood */
11729: printf("Second Likeli=%12.6f ipmx=%ld sw=%12.6f",fretone,ipmx,sw);
11730: for (k=1; k<=npar;k++)
11731: printf(" %d %8.5f",k,p[k]);
11732: printf("\n");
11733:
11734: /*--------- results files --------------*/
1.224 brouard 11735: 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 11736:
11737:
11738: fprintf(ficres,"# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
11739: printf("# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
11740: fprintf(ficlog,"# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
11741: for(i=1,jk=1; i <=nlstate; i++){
11742: for(k=1; k <=(nlstate+ndeath); k++){
1.225 brouard 11743: if (k != i) {
11744: printf("%d%d ",i,k);
11745: fprintf(ficlog,"%d%d ",i,k);
11746: fprintf(ficres,"%1d%1d ",i,k);
11747: for(j=1; j <=ncovmodel; j++){
11748: printf("%12.7f ",p[jk]);
11749: fprintf(ficlog,"%12.7f ",p[jk]);
11750: fprintf(ficres,"%12.7f ",p[jk]);
11751: jk++;
11752: }
11753: printf("\n");
11754: fprintf(ficlog,"\n");
11755: fprintf(ficres,"\n");
11756: }
1.126 brouard 11757: }
11758: }
1.203 brouard 11759: if(mle != 0){
11760: /* Computing hessian and covariance matrix only at a peak of the Likelihood, that is after optimization */
1.126 brouard 11761: ftolhess=ftol; /* Usually correct */
1.203 brouard 11762: hesscov(matcov, hess, p, npar, delti, ftolhess, func);
11763: 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");
11764: 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");
11765: for(i=1,jk=1; i <=nlstate; i++){
1.225 brouard 11766: for(k=1; k <=(nlstate+ndeath); k++){
11767: if (k != i) {
11768: printf("%d%d ",i,k);
11769: fprintf(ficlog,"%d%d ",i,k);
11770: for(j=1; j <=ncovmodel; j++){
11771: 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]));
11772: 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]));
11773: jk++;
11774: }
11775: printf("\n");
11776: fprintf(ficlog,"\n");
11777: }
11778: }
1.193 brouard 11779: }
1.203 brouard 11780: } /* end of hesscov and Wald tests */
1.225 brouard 11781:
1.203 brouard 11782: /* */
1.126 brouard 11783: fprintf(ficres,"# Scales (for hessian or gradient estimation)\n");
11784: printf("# Scales (for hessian or gradient estimation)\n");
11785: fprintf(ficlog,"# Scales (for hessian or gradient estimation)\n");
11786: for(i=1,jk=1; i <=nlstate; i++){
11787: for(j=1; j <=nlstate+ndeath; j++){
1.225 brouard 11788: if (j!=i) {
11789: fprintf(ficres,"%1d%1d",i,j);
11790: printf("%1d%1d",i,j);
11791: fprintf(ficlog,"%1d%1d",i,j);
11792: for(k=1; k<=ncovmodel;k++){
11793: printf(" %.5e",delti[jk]);
11794: fprintf(ficlog," %.5e",delti[jk]);
11795: fprintf(ficres," %.5e",delti[jk]);
11796: jk++;
11797: }
11798: printf("\n");
11799: fprintf(ficlog,"\n");
11800: fprintf(ficres,"\n");
11801: }
1.126 brouard 11802: }
11803: }
11804:
11805: 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 11806: if(mle >= 1) /* To big for the screen */
1.126 brouard 11807: 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");
11808: 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");
11809: /* # 121 Var(a12)\n\ */
11810: /* # 122 Cov(b12,a12) Var(b12)\n\ */
11811: /* # 131 Cov(a13,a12) Cov(a13,b12, Var(a13)\n\ */
11812: /* # 132 Cov(b13,a12) Cov(b13,b12, Cov(b13,a13) Var(b13)\n\ */
11813: /* # 212 Cov(a21,a12) Cov(a21,b12, Cov(a21,a13) Cov(a21,b13) Var(a21)\n\ */
11814: /* # 212 Cov(b21,a12) Cov(b21,b12, Cov(b21,a13) Cov(b21,b13) Cov(b21,a21) Var(b21)\n\ */
11815: /* # 232 Cov(a23,a12) Cov(a23,b12, Cov(a23,a13) Cov(a23,b13) Cov(a23,a21) Cov(a23,b21) Var(a23)\n\ */
11816: /* # 232 Cov(b23,a12) Cov(b23,b12) ... Var (b23)\n" */
11817:
11818:
11819: /* Just to have a covariance matrix which will be more understandable
11820: even is we still don't want to manage dictionary of variables
11821: */
11822: for(itimes=1;itimes<=2;itimes++){
11823: jj=0;
11824: for(i=1; i <=nlstate; i++){
1.225 brouard 11825: for(j=1; j <=nlstate+ndeath; j++){
11826: if(j==i) continue;
11827: for(k=1; k<=ncovmodel;k++){
11828: jj++;
11829: ca[0]= k+'a'-1;ca[1]='\0';
11830: if(itimes==1){
11831: if(mle>=1)
11832: printf("#%1d%1d%d",i,j,k);
11833: fprintf(ficlog,"#%1d%1d%d",i,j,k);
11834: fprintf(ficres,"#%1d%1d%d",i,j,k);
11835: }else{
11836: if(mle>=1)
11837: printf("%1d%1d%d",i,j,k);
11838: fprintf(ficlog,"%1d%1d%d",i,j,k);
11839: fprintf(ficres,"%1d%1d%d",i,j,k);
11840: }
11841: ll=0;
11842: for(li=1;li <=nlstate; li++){
11843: for(lj=1;lj <=nlstate+ndeath; lj++){
11844: if(lj==li) continue;
11845: for(lk=1;lk<=ncovmodel;lk++){
11846: ll++;
11847: if(ll<=jj){
11848: cb[0]= lk +'a'-1;cb[1]='\0';
11849: if(ll<jj){
11850: if(itimes==1){
11851: if(mle>=1)
11852: printf(" Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
11853: fprintf(ficlog," Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
11854: fprintf(ficres," Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
11855: }else{
11856: if(mle>=1)
11857: printf(" %.5e",matcov[jj][ll]);
11858: fprintf(ficlog," %.5e",matcov[jj][ll]);
11859: fprintf(ficres," %.5e",matcov[jj][ll]);
11860: }
11861: }else{
11862: if(itimes==1){
11863: if(mle>=1)
11864: printf(" Var(%s%1d%1d)",ca,i,j);
11865: fprintf(ficlog," Var(%s%1d%1d)",ca,i,j);
11866: fprintf(ficres," Var(%s%1d%1d)",ca,i,j);
11867: }else{
11868: if(mle>=1)
11869: printf(" %.7e",matcov[jj][ll]);
11870: fprintf(ficlog," %.7e",matcov[jj][ll]);
11871: fprintf(ficres," %.7e",matcov[jj][ll]);
11872: }
11873: }
11874: }
11875: } /* end lk */
11876: } /* end lj */
11877: } /* end li */
11878: if(mle>=1)
11879: printf("\n");
11880: fprintf(ficlog,"\n");
11881: fprintf(ficres,"\n");
11882: numlinepar++;
11883: } /* end k*/
11884: } /*end j */
1.126 brouard 11885: } /* end i */
11886: } /* end itimes */
11887:
11888: fflush(ficlog);
11889: fflush(ficres);
1.225 brouard 11890: while(fgets(line, MAXLINE, ficpar)) {
11891: /* If line starts with a # it is a comment */
11892: if (line[0] == '#') {
11893: numlinepar++;
11894: fputs(line,stdout);
11895: fputs(line,ficparo);
11896: fputs(line,ficlog);
11897: continue;
11898: }else
11899: break;
11900: }
11901:
1.209 brouard 11902: /* while((c=getc(ficpar))=='#' && c!= EOF){ */
11903: /* ungetc(c,ficpar); */
11904: /* fgets(line, MAXLINE, ficpar); */
11905: /* fputs(line,stdout); */
11906: /* fputs(line,ficparo); */
11907: /* } */
11908: /* ungetc(c,ficpar); */
1.126 brouard 11909:
11910: estepm=0;
1.209 brouard 11911: 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 11912:
11913: if (num_filled != 6) {
11914: 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);
11915: 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);
11916: goto end;
11917: }
11918: printf("agemin=%lf agemax=%lf bage=%lf fage=%lf estepm=%d ftolpl=%lf\n",ageminpar,agemaxpar, bage, fage, estepm, ftolpl);
11919: }
11920: /* ftolpl=6*ftol*1.e5; /\* 6.e-3 make convergences in less than 80 loops for the prevalence limit *\/ */
11921: /*ftolpl=6.e-4;*/ /* 6.e-3 make convergences in less than 80 loops for the prevalence limit */
11922:
1.209 brouard 11923: /* fscanf(ficpar,"agemin=%lf agemax=%lf bage=%lf fage=%lf estepm=%d ftolpl=%\n",&ageminpar,&agemaxpar, &bage, &fage, &estepm); */
1.126 brouard 11924: if (estepm==0 || estepm < stepm) estepm=stepm;
11925: if (fage <= 2) {
11926: bage = ageminpar;
11927: fage = agemaxpar;
11928: }
11929:
11930: fprintf(ficres,"# agemin agemax for life expectancy, bage fage (if mle==0 ie no data nor Max likelihood).\n");
1.211 brouard 11931: fprintf(ficres,"agemin=%.0f agemax=%.0f bage=%.0f fage=%.0f estepm=%d ftolpl=%e\n",ageminpar,agemaxpar,bage,fage, estepm, ftolpl);
11932: fprintf(ficparo,"agemin=%.0f agemax=%.0f bage=%.0f fage=%.0f estepm=%d, ftolpl=%e\n",ageminpar,agemaxpar,bage,fage, estepm, ftolpl);
1.220 brouard 11933:
1.186 brouard 11934: /* Other stuffs, more or less useful */
1.254 brouard 11935: while(fgets(line, MAXLINE, ficpar)) {
11936: /* If line starts with a # it is a comment */
11937: if (line[0] == '#') {
11938: numlinepar++;
11939: fputs(line,stdout);
11940: fputs(line,ficparo);
11941: fputs(line,ficlog);
11942: continue;
11943: }else
11944: break;
11945: }
11946:
11947: 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){
11948:
11949: if (num_filled != 7) {
11950: 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);
11951: 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);
11952: goto end;
11953: }
11954: printf("begin-prev-date=%.lf/%.lf/%.lf end-prev-date=%.lf/%.lf/%.lf mov_average=%d\n",jprev1, mprev1,anprev1,jprev2, mprev2,anprev2,mobilav);
11955: 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);
11956: 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);
11957: 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 11958: }
1.254 brouard 11959:
11960: while(fgets(line, MAXLINE, ficpar)) {
11961: /* If line starts with a # it is a comment */
11962: if (line[0] == '#') {
11963: numlinepar++;
11964: fputs(line,stdout);
11965: fputs(line,ficparo);
11966: fputs(line,ficlog);
11967: continue;
11968: }else
11969: break;
1.126 brouard 11970: }
11971:
11972:
11973: dateprev1=anprev1+(mprev1-1)/12.+(jprev1-1)/365.;
11974: dateprev2=anprev2+(mprev2-1)/12.+(jprev2-1)/365.;
11975:
1.254 brouard 11976: if((num_filled=sscanf(line,"pop_based=%d\n",&popbased)) !=EOF){
11977: if (num_filled != 1) {
11978: 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);
11979: 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);
11980: goto end;
11981: }
11982: printf("pop_based=%d\n",popbased);
11983: fprintf(ficlog,"pop_based=%d\n",popbased);
11984: fprintf(ficparo,"pop_based=%d\n",popbased);
11985: fprintf(ficres,"pop_based=%d\n",popbased);
11986: }
11987:
1.258 brouard 11988: /* Results */
11989: nresult=0;
11990: do{
11991: if(!fgets(line, MAXLINE, ficpar)){
11992: endishere=1;
11993: parameterline=14;
11994: }else if (line[0] == '#') {
11995: /* If line starts with a # it is a comment */
1.254 brouard 11996: numlinepar++;
11997: fputs(line,stdout);
11998: fputs(line,ficparo);
11999: fputs(line,ficlog);
12000: continue;
1.258 brouard 12001: }else if(sscanf(line,"prevforecast=%[^\n]\n",modeltemp))
12002: parameterline=11;
12003: else if(sscanf(line,"backcast=%[^\n]\n",modeltemp))
12004: parameterline=12;
12005: else if(sscanf(line,"result:%[^\n]\n",modeltemp))
12006: parameterline=13;
12007: else{
12008: parameterline=14;
1.254 brouard 12009: }
1.258 brouard 12010: switch (parameterline){
12011: case 11:
12012: 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){
12013: if (num_filled != 8) {
12014: 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);
12015: 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);
12016: goto end;
12017: }
12018: 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);
12019: 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);
12020: 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);
12021: 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);
12022: /* day and month of proj2 are not used but only year anproj2.*/
12023: }
1.254 brouard 12024: break;
1.258 brouard 12025: case 12:
12026: /*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);*/
12027: 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){
12028: if (num_filled != 8) {
1.262 brouard 12029: 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);
12030: 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 12031: goto end;
12032: }
12033: 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);
12034: 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);
12035: 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);
12036: 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);
12037: /* day and month of proj2 are not used but only year anproj2.*/
12038: }
1.230 brouard 12039: break;
1.258 brouard 12040: case 13:
12041: if((num_filled=sscanf(line,"result:%[^\n]\n",resultline)) !=EOF){
12042: if (num_filled == 0){
12043: resultline[0]='\0';
12044: printf("Warning %d: no result line! It should be at minimum 'result: V2=0 V1=1 or result:.\n%s\n", num_filled, line);
12045: 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);
12046: break;
12047: } else if (num_filled != 1){
12048: printf("ERROR %d: result line! It should be at minimum 'result: V2=0 V1=1 or result:.' %s\n",num_filled, line);
12049: fprintf(ficlog,"ERROR %d: result line! It should be at minimum 'result: V2=0 V1=1 or result:.' %s\n",num_filled, line);
12050: }
12051: nresult++; /* Sum of resultlines */
12052: printf("Result %d: result=%s\n",nresult, resultline);
12053: if(nresult > MAXRESULTLINES){
12054: printf("ERROR: Current version of IMaCh limits the number of resultlines to %d, you used %d\n",MAXRESULTLINES,nresult);
12055: fprintf(ficlog,"ERROR: Current version of IMaCh limits the number of resultlines to %d, you used %d\n",MAXRESULTLINES,nresult);
12056: goto end;
12057: }
12058: decoderesult(resultline, nresult); /* Fills TKresult[nresult] combination and Tresult[nresult][k4+1] combination values */
12059: fprintf(ficparo,"result: %s\n",resultline);
12060: fprintf(ficres,"result: %s\n",resultline);
12061: fprintf(ficlog,"result: %s\n",resultline);
1.230 brouard 12062: break;
1.258 brouard 12063: case 14:
1.259 brouard 12064: if(ncovmodel >2 && nresult==0 ){
12065: printf("ERROR: no result lines! It should be at minimum 'result: V2=0 V1=1 or result:.' %s\n",line);
1.258 brouard 12066: goto end;
12067: }
1.259 brouard 12068: break;
1.258 brouard 12069: default:
12070: nresult=1;
12071: decoderesult(".",nresult ); /* No covariate */
12072: }
12073: } /* End switch parameterline */
12074: }while(endishere==0); /* End do */
1.126 brouard 12075:
1.230 brouard 12076: /* freqsummary(fileres, agemin, agemax, s, agev, nlstate, imx,Tvaraff,nbcode, ncodemax,mint,anint); */
1.145 brouard 12077: /* ,dateprev1,dateprev2,jprev1, mprev1,anprev1,jprev2, mprev2,anprev2); */
1.126 brouard 12078:
12079: replace_back_to_slash(pathc,pathcd); /* Even gnuplot wants a / */
1.194 brouard 12080: if(ageminpar == AGEOVERFLOW ||agemaxpar == -AGEOVERFLOW){
1.230 brouard 12081: printf("Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
1.194 brouard 12082: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
12083: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
1.230 brouard 12084: fprintf(ficlog,"Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
1.194 brouard 12085: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
12086: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
1.220 brouard 12087: }else{
1.270 brouard 12088: /* printinggnuplot(fileresu, optionfilefiname,ageminpar,agemaxpar,fage, prevfcast, backcast, pathc,p, (int)anproj1-(int)agemin, (int)anback1-(int)agemax+1); */
12089: printinggnuplot(fileresu, optionfilefiname,ageminpar,agemaxpar,bage, fage, prevfcast, backcast, pathc,p, (int)anproj1-bage, (int)anback1-fage);
1.220 brouard 12090: }
12091: printinghtml(fileresu,title,datafile, firstpass, lastpass, stepm, weightopt, \
1.258 brouard 12092: model,imx,jmin,jmax,jmean,rfileres,popforecast,mobilav,prevfcast,mobilavproj,backcast, estepm, \
1.225 brouard 12093: jprev1,mprev1,anprev1,dateprev1,jprev2,mprev2,anprev2,dateprev2);
1.220 brouard 12094:
1.225 brouard 12095: /*------------ free_vector -------------*/
12096: /* chdir(path); */
1.220 brouard 12097:
1.215 brouard 12098: /* free_ivector(wav,1,imx); */ /* Moved after last prevalence call */
12099: /* free_imatrix(dh,1,lastpass-firstpass+2,1,imx); */
12100: /* free_imatrix(bh,1,lastpass-firstpass+2,1,imx); */
12101: /* free_imatrix(mw,1,lastpass-firstpass+2,1,imx); */
1.126 brouard 12102: free_lvector(num,1,n);
12103: free_vector(agedc,1,n);
12104: /*free_matrix(covar,0,NCOVMAX,1,n);*/
12105: /*free_matrix(covar,1,NCOVMAX,1,n);*/
12106: fclose(ficparo);
12107: fclose(ficres);
1.220 brouard 12108:
12109:
1.186 brouard 12110: /* Other results (useful)*/
1.220 brouard 12111:
12112:
1.126 brouard 12113: /*--------------- Prevalence limit (period or stable prevalence) --------------*/
1.180 brouard 12114: /*#include "prevlim.h"*/ /* Use ficrespl, ficlog */
12115: prlim=matrix(1,nlstate,1,nlstate);
1.209 brouard 12116: prevalence_limit(p, prlim, ageminpar, agemaxpar, ftolpl, &ncvyear);
1.126 brouard 12117: fclose(ficrespl);
12118:
12119: /*------------- h Pij x at various ages ------------*/
1.180 brouard 12120: /*#include "hpijx.h"*/
12121: hPijx(p, bage, fage);
1.145 brouard 12122: fclose(ficrespij);
1.227 brouard 12123:
1.220 brouard 12124: /* ncovcombmax= pow(2,cptcoveff); */
1.219 brouard 12125: /*-------------- Variance of one-step probabilities---*/
1.145 brouard 12126: k=1;
1.126 brouard 12127: varprob(optionfilefiname, matcov, p, delti, nlstate, bage, fage,k,Tvar,nbcode, ncodemax,strstart);
1.227 brouard 12128:
1.269 brouard 12129: /* Prevalence for each covariate combination in probs[age][status][cov] */
12130: probs= ma3x(AGEINF,AGESUP,1,nlstate+ndeath, 1,ncovcombmax);
12131: for(i=AGEINF;i<=AGESUP;i++)
1.219 brouard 12132: for(j=1;j<=nlstate+ndeath;j++) /* ndeath is useless but a necessity to be compared with mobaverages */
1.225 brouard 12133: for(k=1;k<=ncovcombmax;k++)
12134: probs[i][j][k]=0.;
1.269 brouard 12135: prevalence(probs, ageminpar, agemaxpar, s, agev, nlstate, imx, Tvar, nbcode,
12136: ncodemax, mint, anint, dateprev1, dateprev2, firstpass, lastpass);
1.219 brouard 12137: if (mobilav!=0 ||mobilavproj !=0 ) {
1.269 brouard 12138: mobaverages= ma3x(AGEINF, AGESUP,1,nlstate+ndeath, 1,ncovcombmax);
12139: for(i=AGEINF;i<=AGESUP;i++)
1.268 brouard 12140: for(j=1;j<=nlstate+ndeath;j++)
1.227 brouard 12141: for(k=1;k<=ncovcombmax;k++)
12142: mobaverages[i][j][k]=0.;
1.219 brouard 12143: mobaverage=mobaverages;
12144: if (mobilav!=0) {
1.235 brouard 12145: printf("Movingaveraging observed prevalence\n");
1.258 brouard 12146: fprintf(ficlog,"Movingaveraging observed prevalence\n");
1.227 brouard 12147: if (movingaverage(probs, ageminpar, agemaxpar, mobaverage, mobilav)!=0){
12148: fprintf(ficlog," Error in movingaverage mobilav=%d\n",mobilav);
12149: printf(" Error in movingaverage mobilav=%d\n",mobilav);
12150: }
1.269 brouard 12151: } else if (mobilavproj !=0) {
1.235 brouard 12152: printf("Movingaveraging projected observed prevalence\n");
1.258 brouard 12153: fprintf(ficlog,"Movingaveraging projected observed prevalence\n");
1.227 brouard 12154: if (movingaverage(probs, ageminpar, agemaxpar, mobaverage, mobilavproj)!=0){
12155: fprintf(ficlog," Error in movingaverage mobilavproj=%d\n",mobilavproj);
12156: printf(" Error in movingaverage mobilavproj=%d\n",mobilavproj);
12157: }
1.269 brouard 12158: }else{
12159: printf("Internal error moving average\n");
12160: fflush(stdout);
12161: exit(1);
1.219 brouard 12162: }
12163: }/* end if moving average */
1.227 brouard 12164:
1.126 brouard 12165: /*---------- Forecasting ------------------*/
12166: if(prevfcast==1){
12167: /* if(stepm ==1){*/
1.269 brouard 12168: prevforecast(fileresu, anproj1, mproj1, jproj1, agemin, agemax, dateprev1, dateprev2, mobilavproj, mobaverage, bage, fage, firstpass, lastpass, anproj2, p, cptcoveff);
1.126 brouard 12169: }
1.269 brouard 12170:
12171: /* Backcasting */
1.217 brouard 12172: if(backcast==1){
1.219 brouard 12173: ddnewms=matrix(1,nlstate+ndeath,1,nlstate+ndeath);
12174: ddoldms=matrix(1,nlstate+ndeath,1,nlstate+ndeath);
12175: ddsavms=matrix(1,nlstate+ndeath,1,nlstate+ndeath);
12176:
12177: /*--------------- Back Prevalence limit (period or stable prevalence) --------------*/
12178:
12179: bprlim=matrix(1,nlstate,1,nlstate);
1.269 brouard 12180:
1.219 brouard 12181: back_prevalence_limit(p, bprlim, ageminpar, agemaxpar, ftolpl, &ncvyear, dateprev1, dateprev2, firstpass, lastpass, mobilavproj);
12182: fclose(ficresplb);
12183:
1.222 brouard 12184: hBijx(p, bage, fage, mobaverage);
12185: fclose(ficrespijb);
1.219 brouard 12186:
1.269 brouard 12187: prevbackforecast(fileresu, mobaverage, anback1, mback1, jback1, agemin, agemax, dateprev1, dateprev2,
12188: mobilavproj, bage, fage, firstpass, lastpass, anback2, p, cptcoveff);
12189: varbprlim(fileresu, nresult, mobaverage, mobilavproj, bage, fage, bprlim, &ncvyear, ftolpl, p, matcov, delti, stepm, cptcoveff);
1.268 brouard 12190:
12191:
1.269 brouard 12192: free_matrix(bprlim,1,nlstate,1,nlstate); /*here or after loop ? */
1.219 brouard 12193: free_matrix(ddnewms, 1, nlstate+ndeath, 1, nlstate+ndeath);
12194: free_matrix(ddsavms, 1, nlstate+ndeath, 1, nlstate+ndeath);
12195: free_matrix(ddoldms, 1, nlstate+ndeath, 1, nlstate+ndeath);
1.269 brouard 12196: } /* end Backcasting */
1.268 brouard 12197:
1.186 brouard 12198:
12199: /* ------ Other prevalence ratios------------ */
1.126 brouard 12200:
1.215 brouard 12201: free_ivector(wav,1,imx);
12202: free_imatrix(dh,1,lastpass-firstpass+2,1,imx);
12203: free_imatrix(bh,1,lastpass-firstpass+2,1,imx);
12204: free_imatrix(mw,1,lastpass-firstpass+2,1,imx);
1.218 brouard 12205:
12206:
1.127 brouard 12207: /*---------- Health expectancies, no variances ------------*/
1.218 brouard 12208:
1.201 brouard 12209: strcpy(filerese,"E_");
12210: strcat(filerese,fileresu);
1.126 brouard 12211: if((ficreseij=fopen(filerese,"w"))==NULL) {
12212: printf("Problem with Health Exp. resultfile: %s\n", filerese); exit(0);
12213: fprintf(ficlog,"Problem with Health Exp. resultfile: %s\n", filerese); exit(0);
12214: }
1.208 brouard 12215: printf("Computing Health Expectancies: result on file '%s' ...", filerese);fflush(stdout);
12216: fprintf(ficlog,"Computing Health Expectancies: result on file '%s' ...", filerese);fflush(ficlog);
1.238 brouard 12217:
12218: pstamp(ficreseij);
1.219 brouard 12219:
1.235 brouard 12220: i1=pow(2,cptcoveff); /* Number of combination of dummy covariates */
12221: if (cptcovn < 1){i1=1;}
12222:
12223: for(nres=1; nres <= nresult; nres++) /* For each resultline */
12224: for(k=1; k<=i1;k++){ /* For any combination of dummy covariates, fixed and varying */
1.253 brouard 12225: if(i1 != 1 && TKresult[nres]!= k)
1.235 brouard 12226: continue;
1.219 brouard 12227: fprintf(ficreseij,"\n#****** ");
1.235 brouard 12228: printf("\n#****** ");
1.225 brouard 12229: for(j=1;j<=cptcoveff;j++) {
1.227 brouard 12230: fprintf(ficreseij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
1.235 brouard 12231: printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
12232: }
12233: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
12234: printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
12235: fprintf(ficreseij," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
1.219 brouard 12236: }
12237: fprintf(ficreseij,"******\n");
1.235 brouard 12238: printf("******\n");
1.219 brouard 12239:
12240: eij=ma3x(1,nlstate,1,nlstate,(int) bage, (int) fage);
12241: oldm=oldms;savm=savms;
1.235 brouard 12242: evsij(eij, p, nlstate, stepm, (int) bage, (int)fage, oldm, savm, k, estepm, strstart, nres);
1.127 brouard 12243:
1.219 brouard 12244: free_ma3x(eij,1,nlstate,1,nlstate,(int) bage, (int)fage);
1.127 brouard 12245: }
12246: fclose(ficreseij);
1.208 brouard 12247: printf("done evsij\n");fflush(stdout);
12248: fprintf(ficlog,"done evsij\n");fflush(ficlog);
1.269 brouard 12249:
1.218 brouard 12250:
1.227 brouard 12251: /*---------- State-specific expectancies and variances ------------*/
1.218 brouard 12252:
1.201 brouard 12253: strcpy(filerest,"T_");
12254: strcat(filerest,fileresu);
1.127 brouard 12255: if((ficrest=fopen(filerest,"w"))==NULL) {
12256: printf("Problem with total LE resultfile: %s\n", filerest);goto end;
12257: fprintf(ficlog,"Problem with total LE resultfile: %s\n", filerest);goto end;
12258: }
1.208 brouard 12259: printf("Computing Total Life expectancies with their standard errors: file '%s' ...\n", filerest); fflush(stdout);
12260: fprintf(ficlog,"Computing Total Life expectancies with their standard errors: file '%s' ...\n", filerest); fflush(ficlog);
1.201 brouard 12261: strcpy(fileresstde,"STDE_");
12262: strcat(fileresstde,fileresu);
1.126 brouard 12263: if((ficresstdeij=fopen(fileresstde,"w"))==NULL) {
1.227 brouard 12264: printf("Problem with State specific Exp. and std errors resultfile: %s\n", fileresstde); exit(0);
12265: fprintf(ficlog,"Problem with State specific Exp. and std errors resultfile: %s\n", fileresstde); exit(0);
1.126 brouard 12266: }
1.227 brouard 12267: printf(" Computing State-specific Expectancies and standard errors: result on file '%s' \n", fileresstde);
12268: fprintf(ficlog," Computing State-specific Expectancies and standard errors: result on file '%s' \n", fileresstde);
1.126 brouard 12269:
1.201 brouard 12270: strcpy(filerescve,"CVE_");
12271: strcat(filerescve,fileresu);
1.126 brouard 12272: if((ficrescveij=fopen(filerescve,"w"))==NULL) {
1.227 brouard 12273: printf("Problem with Covar. State-specific Exp. resultfile: %s\n", filerescve); exit(0);
12274: fprintf(ficlog,"Problem with Covar. State-specific Exp. resultfile: %s\n", filerescve); exit(0);
1.126 brouard 12275: }
1.227 brouard 12276: printf(" Computing Covar. of State-specific Expectancies: result on file '%s' \n", filerescve);
12277: fprintf(ficlog," Computing Covar. of State-specific Expectancies: result on file '%s' \n", filerescve);
1.126 brouard 12278:
1.201 brouard 12279: strcpy(fileresv,"V_");
12280: strcat(fileresv,fileresu);
1.126 brouard 12281: if((ficresvij=fopen(fileresv,"w"))==NULL) {
12282: printf("Problem with variance resultfile: %s\n", fileresv);exit(0);
12283: fprintf(ficlog,"Problem with variance resultfile: %s\n", fileresv);exit(0);
12284: }
1.227 brouard 12285: printf(" Computing Variance-covariance of State-specific Expectancies: file '%s' ... ", fileresv);fflush(stdout);
12286: fprintf(ficlog," Computing Variance-covariance of State-specific Expectancies: file '%s' ... ", fileresv);fflush(ficlog);
1.126 brouard 12287:
1.235 brouard 12288: i1=pow(2,cptcoveff); /* Number of combination of dummy covariates */
12289: if (cptcovn < 1){i1=1;}
12290:
12291: for(nres=1; nres <= nresult; nres++) /* For each resultline */
12292: for(k=1; k<=i1;k++){ /* For any combination of dummy covariates, fixed and varying */
1.253 brouard 12293: if(i1 != 1 && TKresult[nres]!= k)
1.235 brouard 12294: continue;
1.242 brouard 12295: printf("\n#****** Result for:");
12296: fprintf(ficrest,"\n#****** Result for:");
12297: fprintf(ficlog,"\n#****** Result for:");
1.227 brouard 12298: for(j=1;j<=cptcoveff;j++){
12299: printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
12300: fprintf(ficrest,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
12301: fprintf(ficlog,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
12302: }
1.235 brouard 12303: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
12304: printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
12305: fprintf(ficrest," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
12306: fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
12307: }
1.208 brouard 12308: fprintf(ficrest,"******\n");
1.227 brouard 12309: fprintf(ficlog,"******\n");
12310: printf("******\n");
1.208 brouard 12311:
12312: fprintf(ficresstdeij,"\n#****** ");
12313: fprintf(ficrescveij,"\n#****** ");
1.225 brouard 12314: for(j=1;j<=cptcoveff;j++) {
1.227 brouard 12315: fprintf(ficresstdeij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
12316: fprintf(ficrescveij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
1.208 brouard 12317: }
1.235 brouard 12318: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
12319: fprintf(ficresstdeij," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
12320: fprintf(ficrescveij," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
12321: }
1.208 brouard 12322: fprintf(ficresstdeij,"******\n");
12323: fprintf(ficrescveij,"******\n");
12324:
12325: fprintf(ficresvij,"\n#****** ");
1.238 brouard 12326: /* pstamp(ficresvij); */
1.225 brouard 12327: for(j=1;j<=cptcoveff;j++)
1.227 brouard 12328: fprintf(ficresvij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
1.235 brouard 12329: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
12330: fprintf(ficresvij," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
12331: }
1.208 brouard 12332: fprintf(ficresvij,"******\n");
12333:
12334: eij=ma3x(1,nlstate,1,nlstate,(int) bage, (int) fage);
12335: oldm=oldms;savm=savms;
1.235 brouard 12336: printf(" cvevsij ");
12337: fprintf(ficlog, " cvevsij ");
12338: cvevsij(eij, p, nlstate, stepm, (int) bage, (int)fage, oldm, savm, k, estepm, delti, matcov, strstart, nres);
1.208 brouard 12339: printf(" end cvevsij \n ");
12340: fprintf(ficlog, " end cvevsij \n ");
12341:
12342: /*
12343: */
12344: /* goto endfree; */
12345:
12346: vareij=ma3x(1,nlstate,1,nlstate,(int) bage, (int) fage);
12347: pstamp(ficrest);
12348:
1.269 brouard 12349: epj=vector(1,nlstate+1);
1.208 brouard 12350: for(vpopbased=0; vpopbased <= popbased; vpopbased++){ /* Done for vpopbased=0 and vpopbased=1 if popbased==1*/
1.227 brouard 12351: oldm=oldms;savm=savms; /* ZZ Segmentation fault */
12352: cptcod= 0; /* To be deleted */
12353: printf("varevsij vpopbased=%d \n",vpopbased);
12354: fprintf(ficlog, "varevsij vpopbased=%d \n",vpopbased);
1.235 brouard 12355: 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 12356: 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 ");
12357: if(vpopbased==1)
12358: 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);
12359: else
12360: fprintf(ficrest,"the age specific period (stable) prevalences in each health state \n");
12361: fprintf(ficrest,"# Age popbased mobilav e.. (std) ");
12362: for (i=1;i<=nlstate;i++) fprintf(ficrest,"e.%d (std) ",i);
12363: fprintf(ficrest,"\n");
12364: /* printf("Which p?\n"); for(i=1;i<=npar;i++)printf("p[i=%d]=%lf,",i,p[i]);printf("\n"); */
12365: printf("Computing age specific period (stable) prevalences in each health state \n");
12366: fprintf(ficlog,"Computing age specific period (stable) prevalences in each health state \n");
12367: for(age=bage; age <=fage ;age++){
1.235 brouard 12368: prevalim(prlim, nlstate, p, age, oldm, savm, ftolpl, &ncvyear, k, nres); /*ZZ Is it the correct prevalim */
1.227 brouard 12369: if (vpopbased==1) {
12370: if(mobilav ==0){
12371: for(i=1; i<=nlstate;i++)
12372: prlim[i][i]=probs[(int)age][i][k];
12373: }else{ /* mobilav */
12374: for(i=1; i<=nlstate;i++)
12375: prlim[i][i]=mobaverage[(int)age][i][k];
12376: }
12377: }
1.219 brouard 12378:
1.227 brouard 12379: fprintf(ficrest," %4.0f %d %d",age, vpopbased, mobilav);
12380: /* fprintf(ficrest," %4.0f %d %d %d %d",age, vpopbased, mobilav,Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]); */ /* to be done */
12381: /* printf(" age %4.0f ",age); */
12382: for(j=1, epj[nlstate+1]=0.;j <=nlstate;j++){
12383: for(i=1, epj[j]=0.;i <=nlstate;i++) {
12384: epj[j] += prlim[i][i]*eij[i][j][(int)age];
12385: /*ZZZ printf("%lf %lf ", prlim[i][i] ,eij[i][j][(int)age]);*/
12386: /* printf("%lf %lf ", prlim[i][i] ,eij[i][j][(int)age]); */
12387: }
12388: epj[nlstate+1] +=epj[j];
12389: }
12390: /* printf(" age %4.0f \n",age); */
1.219 brouard 12391:
1.227 brouard 12392: for(i=1, vepp=0.;i <=nlstate;i++)
12393: for(j=1;j <=nlstate;j++)
12394: vepp += vareij[i][j][(int)age];
12395: fprintf(ficrest," %7.3f (%7.3f)", epj[nlstate+1],sqrt(vepp));
12396: for(j=1;j <=nlstate;j++){
12397: fprintf(ficrest," %7.3f (%7.3f)", epj[j],sqrt(vareij[j][j][(int)age]));
12398: }
12399: fprintf(ficrest,"\n");
12400: }
1.208 brouard 12401: } /* End vpopbased */
1.269 brouard 12402: free_vector(epj,1,nlstate+1);
1.208 brouard 12403: free_ma3x(eij,1,nlstate,1,nlstate,(int) bage, (int)fage);
12404: free_ma3x(vareij,1,nlstate,1,nlstate,(int) bage, (int)fage);
1.235 brouard 12405: printf("done selection\n");fflush(stdout);
12406: fprintf(ficlog,"done selection\n");fflush(ficlog);
1.208 brouard 12407:
1.235 brouard 12408: } /* End k selection */
1.227 brouard 12409:
12410: printf("done State-specific expectancies\n");fflush(stdout);
12411: fprintf(ficlog,"done State-specific expectancies\n");fflush(ficlog);
12412:
1.269 brouard 12413: /* variance-covariance of period prevalence*/
12414: varprlim(fileresu, nresult, mobaverage, mobilavproj, bage, fage, prlim, &ncvyear, ftolpl, p, matcov, delti, stepm, cptcoveff);
1.268 brouard 12415:
1.227 brouard 12416:
12417: free_vector(weight,1,n);
12418: free_imatrix(Tvard,1,NCOVMAX,1,2);
12419: free_imatrix(s,1,maxwav+1,1,n);
12420: free_matrix(anint,1,maxwav,1,n);
12421: free_matrix(mint,1,maxwav,1,n);
12422: free_ivector(cod,1,n);
12423: free_ivector(tab,1,NCOVMAX);
12424: fclose(ficresstdeij);
12425: fclose(ficrescveij);
12426: fclose(ficresvij);
12427: fclose(ficrest);
12428: fclose(ficpar);
12429:
12430:
1.126 brouard 12431: /*---------- End : free ----------------*/
1.219 brouard 12432: if (mobilav!=0 ||mobilavproj !=0)
1.269 brouard 12433: free_ma3x(mobaverages,AGEINF, AGESUP,1,nlstate+ndeath, 1,ncovcombmax); /* We need to have a squared matrix with prevalence of the dead! */
12434: free_ma3x(probs,AGEINF,AGESUP,1,nlstate+ndeath, 1,ncovcombmax);
1.220 brouard 12435: free_matrix(prlim,1,nlstate,1,nlstate); /*here or after loop ? */
12436: free_matrix(pmmij,1,nlstate+ndeath,1,nlstate+ndeath);
1.126 brouard 12437: } /* mle==-3 arrives here for freeing */
1.227 brouard 12438: /* endfree:*/
12439: free_matrix(oldms, 1,nlstate+ndeath,1,nlstate+ndeath);
12440: free_matrix(newms, 1,nlstate+ndeath,1,nlstate+ndeath);
12441: free_matrix(savms, 1,nlstate+ndeath,1,nlstate+ndeath);
1.268 brouard 12442: if(ntv+nqtv>=1)free_ma3x(cotvar,1,maxwav,1,ntv+nqtv,1,n);
12443: if(nqtv>=1)free_ma3x(cotqvar,1,maxwav,1,nqtv,1,n);
12444: if(nqv>=1)free_matrix(coqvar,1,nqv,1,n);
1.227 brouard 12445: free_matrix(covar,0,NCOVMAX,1,n);
12446: free_matrix(matcov,1,npar,1,npar);
12447: free_matrix(hess,1,npar,1,npar);
12448: /*free_vector(delti,1,npar);*/
12449: free_ma3x(delti3,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
12450: free_matrix(agev,1,maxwav,1,imx);
1.269 brouard 12451: free_ma3x(paramstart,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
1.227 brouard 12452: free_ma3x(param,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
12453:
12454: free_ivector(ncodemax,1,NCOVMAX);
12455: free_ivector(ncodemaxwundef,1,NCOVMAX);
12456: free_ivector(Dummy,-1,NCOVMAX);
12457: free_ivector(Fixed,-1,NCOVMAX);
1.238 brouard 12458: free_ivector(DummyV,1,NCOVMAX);
12459: free_ivector(FixedV,1,NCOVMAX);
1.227 brouard 12460: free_ivector(Typevar,-1,NCOVMAX);
12461: free_ivector(Tvar,1,NCOVMAX);
1.234 brouard 12462: free_ivector(TvarsQ,1,NCOVMAX);
12463: free_ivector(TvarsQind,1,NCOVMAX);
12464: free_ivector(TvarsD,1,NCOVMAX);
12465: free_ivector(TvarsDind,1,NCOVMAX);
1.231 brouard 12466: free_ivector(TvarFD,1,NCOVMAX);
12467: free_ivector(TvarFDind,1,NCOVMAX);
1.232 brouard 12468: free_ivector(TvarF,1,NCOVMAX);
12469: free_ivector(TvarFind,1,NCOVMAX);
12470: free_ivector(TvarV,1,NCOVMAX);
12471: free_ivector(TvarVind,1,NCOVMAX);
12472: free_ivector(TvarA,1,NCOVMAX);
12473: free_ivector(TvarAind,1,NCOVMAX);
1.231 brouard 12474: free_ivector(TvarFQ,1,NCOVMAX);
12475: free_ivector(TvarFQind,1,NCOVMAX);
12476: free_ivector(TvarVD,1,NCOVMAX);
12477: free_ivector(TvarVDind,1,NCOVMAX);
12478: free_ivector(TvarVQ,1,NCOVMAX);
12479: free_ivector(TvarVQind,1,NCOVMAX);
1.230 brouard 12480: free_ivector(Tvarsel,1,NCOVMAX);
12481: free_vector(Tvalsel,1,NCOVMAX);
1.227 brouard 12482: free_ivector(Tposprod,1,NCOVMAX);
12483: free_ivector(Tprod,1,NCOVMAX);
12484: free_ivector(Tvaraff,1,NCOVMAX);
12485: free_ivector(invalidvarcomb,1,ncovcombmax);
12486: free_ivector(Tage,1,NCOVMAX);
12487: free_ivector(Tmodelind,1,NCOVMAX);
1.228 brouard 12488: free_ivector(TmodelInvind,1,NCOVMAX);
12489: free_ivector(TmodelInvQind,1,NCOVMAX);
1.227 brouard 12490:
12491: free_imatrix(nbcode,0,NCOVMAX,0,NCOVMAX);
12492: /* free_imatrix(codtab,1,100,1,10); */
1.126 brouard 12493: fflush(fichtm);
12494: fflush(ficgp);
12495:
1.227 brouard 12496:
1.126 brouard 12497: if((nberr >0) || (nbwarn>0)){
1.216 brouard 12498: printf("End of Imach with %d errors and/or %d warnings. Please look at the log file for details.\n",nberr,nbwarn);
12499: 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 12500: }else{
12501: printf("End of Imach\n");
12502: fprintf(ficlog,"End of Imach\n");
12503: }
12504: printf("See log file on %s\n",filelog);
12505: /* gettimeofday(&end_time, (struct timezone*)0);*/ /* after time */
1.157 brouard 12506: /*(void) gettimeofday(&end_time,&tzp);*/
12507: rend_time = time(NULL);
12508: end_time = *localtime(&rend_time);
12509: /* tml = *localtime(&end_time.tm_sec); */
12510: strcpy(strtend,asctime(&end_time));
1.126 brouard 12511: printf("Local time at start %s\nLocal time at end %s",strstart, strtend);
12512: fprintf(ficlog,"Local time at start %s\nLocal time at end %s\n",strstart, strtend);
1.157 brouard 12513: printf("Total time used %s\n", asc_diff_time(rend_time -rstart_time,tmpout));
1.227 brouard 12514:
1.157 brouard 12515: printf("Total time was %.0lf Sec.\n", difftime(rend_time,rstart_time));
12516: fprintf(ficlog,"Total time used %s\n", asc_diff_time(rend_time -rstart_time,tmpout));
12517: fprintf(ficlog,"Total time was %.0lf Sec.\n", difftime(rend_time,rstart_time));
1.126 brouard 12518: /* printf("Total time was %d uSec.\n", total_usecs);*/
12519: /* if(fileappend(fichtm,optionfilehtm)){ */
12520: fprintf(fichtm,"<br>Local time at start %s<br>Local time at end %s<br>\n</body></html>",strstart, strtend);
12521: fclose(fichtm);
12522: fprintf(fichtmcov,"<br>Local time at start %s<br>Local time at end %s<br>\n</body></html>",strstart, strtend);
12523: fclose(fichtmcov);
12524: fclose(ficgp);
12525: fclose(ficlog);
12526: /*------ End -----------*/
1.227 brouard 12527:
12528:
12529: printf("Before Current directory %s!\n",pathcd);
1.184 brouard 12530: #ifdef WIN32
1.227 brouard 12531: if (_chdir(pathcd) != 0)
12532: printf("Can't move to directory %s!\n",path);
12533: if(_getcwd(pathcd,MAXLINE) > 0)
1.184 brouard 12534: #else
1.227 brouard 12535: if(chdir(pathcd) != 0)
12536: printf("Can't move to directory %s!\n", path);
12537: if (getcwd(pathcd, MAXLINE) > 0)
1.184 brouard 12538: #endif
1.126 brouard 12539: printf("Current directory %s!\n",pathcd);
12540: /*strcat(plotcmd,CHARSEPARATOR);*/
12541: sprintf(plotcmd,"gnuplot");
1.157 brouard 12542: #ifdef _WIN32
1.126 brouard 12543: sprintf(plotcmd,"\"%sgnuplot.exe\"",pathimach);
12544: #endif
12545: if(!stat(plotcmd,&info)){
1.158 brouard 12546: printf("Error or gnuplot program not found: '%s'\n",plotcmd);fflush(stdout);
1.126 brouard 12547: if(!stat(getenv("GNUPLOTBIN"),&info)){
1.158 brouard 12548: printf("Error or gnuplot program not found: '%s' Environment GNUPLOTBIN not set.\n",plotcmd);fflush(stdout);
1.126 brouard 12549: }else
12550: strcpy(pplotcmd,plotcmd);
1.157 brouard 12551: #ifdef __unix
1.126 brouard 12552: strcpy(plotcmd,GNUPLOTPROGRAM);
12553: if(!stat(plotcmd,&info)){
1.158 brouard 12554: printf("Error gnuplot program not found: '%s'\n",plotcmd);fflush(stdout);
1.126 brouard 12555: }else
12556: strcpy(pplotcmd,plotcmd);
12557: #endif
12558: }else
12559: strcpy(pplotcmd,plotcmd);
12560:
12561: sprintf(plotcmd,"%s %s",pplotcmd, optionfilegnuplot);
1.158 brouard 12562: printf("Starting graphs with: '%s'\n",plotcmd);fflush(stdout);
1.227 brouard 12563:
1.126 brouard 12564: if((outcmd=system(plotcmd)) != 0){
1.158 brouard 12565: printf("gnuplot command might not be in your path: '%s', err=%d\n", plotcmd, outcmd);
1.154 brouard 12566: printf("\n Trying if gnuplot resides on the same directory that IMaCh\n");
1.152 brouard 12567: sprintf(plotcmd,"%sgnuplot %s", pathimach, optionfilegnuplot);
1.150 brouard 12568: if((outcmd=system(plotcmd)) != 0)
1.153 brouard 12569: printf("\n Still a problem with gnuplot command %s, err=%d\n", plotcmd, outcmd);
1.126 brouard 12570: }
1.158 brouard 12571: printf(" Successful, please wait...");
1.126 brouard 12572: while (z[0] != 'q') {
12573: /* chdir(path); */
1.154 brouard 12574: printf("\nType e to edit results with your browser, g to graph again and q for exit: ");
1.126 brouard 12575: scanf("%s",z);
12576: /* if (z[0] == 'c') system("./imach"); */
12577: if (z[0] == 'e') {
1.158 brouard 12578: #ifdef __APPLE__
1.152 brouard 12579: sprintf(pplotcmd, "open %s", optionfilehtm);
1.157 brouard 12580: #elif __linux
12581: sprintf(pplotcmd, "xdg-open %s", optionfilehtm);
1.153 brouard 12582: #else
1.152 brouard 12583: sprintf(pplotcmd, "%s", optionfilehtm);
1.153 brouard 12584: #endif
12585: printf("Starting browser with: %s",pplotcmd);fflush(stdout);
12586: system(pplotcmd);
1.126 brouard 12587: }
12588: else if (z[0] == 'g') system(plotcmd);
12589: else if (z[0] == 'q') exit(0);
12590: }
1.227 brouard 12591: end:
1.126 brouard 12592: while (z[0] != 'q') {
1.195 brouard 12593: printf("\nType q for exiting: "); fflush(stdout);
1.126 brouard 12594: scanf("%s",z);
12595: }
12596: }
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