Annotation of imach/src/imach.c, revision 1.272
1.272 ! brouard 1: /* $Id: imach.c,v 1.271 2017/06/27 10:17:50 brouard Exp $
1.126 brouard 2: $State: Exp $
1.163 brouard 3: $Log: imach.c,v $
1.272 ! brouard 4: Revision 1.271 2017/06/27 10:17:50 brouard
! 5: Summary: Some bug with rint
! 6:
1.271 brouard 7: Revision 1.270 2017/05/24 05:45:29 brouard
8: *** empty log message ***
9:
1.270 brouard 10: Revision 1.269 2017/05/23 08:39:25 brouard
11: Summary: Code into subroutine, cleanings
12:
1.269 brouard 13: Revision 1.268 2017/05/18 20:09:32 brouard
14: Summary: backprojection and confidence intervals of backprevalence
15:
1.268 brouard 16: Revision 1.267 2017/05/13 10:25:05 brouard
17: Summary: temporary save for backprojection
18:
1.267 brouard 19: Revision 1.266 2017/05/13 07:26:12 brouard
20: Summary: Version 0.99r13 (improvements and bugs fixed)
21:
1.266 brouard 22: Revision 1.265 2017/04/26 16:22:11 brouard
23: Summary: imach 0.99r13 Some bugs fixed
24:
1.265 brouard 25: Revision 1.264 2017/04/26 06:01:29 brouard
26: Summary: Labels in graphs
27:
1.264 brouard 28: Revision 1.263 2017/04/24 15:23:15 brouard
29: Summary: to save
30:
1.263 brouard 31: Revision 1.262 2017/04/18 16:48:12 brouard
32: *** empty log message ***
33:
1.262 brouard 34: Revision 1.261 2017/04/05 10:14:09 brouard
35: Summary: Bug in E_ as well as in T_ fixed nres-1 vs k1-1
36:
1.261 brouard 37: Revision 1.260 2017/04/04 17:46:59 brouard
38: Summary: Gnuplot indexations fixed (humm)
39:
1.260 brouard 40: Revision 1.259 2017/04/04 13:01:16 brouard
41: Summary: Some errors to warnings only if date of death is unknown but status is death we could set to pi3
42:
1.259 brouard 43: Revision 1.258 2017/04/03 10:17:47 brouard
44: Summary: Version 0.99r12
45:
46: Some cleanings, conformed with updated documentation.
47:
1.258 brouard 48: Revision 1.257 2017/03/29 16:53:30 brouard
49: Summary: Temp
50:
1.257 brouard 51: Revision 1.256 2017/03/27 05:50:23 brouard
52: Summary: Temporary
53:
1.256 brouard 54: Revision 1.255 2017/03/08 16:02:28 brouard
55: Summary: IMaCh version 0.99r10 bugs in gnuplot fixed
56:
1.255 brouard 57: Revision 1.254 2017/03/08 07:13:00 brouard
58: Summary: Fixing data parameter line
59:
1.254 brouard 60: Revision 1.253 2016/12/15 11:59:41 brouard
61: Summary: 0.99 in progress
62:
1.253 brouard 63: Revision 1.252 2016/09/15 21:15:37 brouard
64: *** empty log message ***
65:
1.252 brouard 66: Revision 1.251 2016/09/15 15:01:13 brouard
67: Summary: not working
68:
1.251 brouard 69: Revision 1.250 2016/09/08 16:07:27 brouard
70: Summary: continue
71:
1.250 brouard 72: Revision 1.249 2016/09/07 17:14:18 brouard
73: Summary: Starting values from frequencies
74:
1.249 brouard 75: Revision 1.248 2016/09/07 14:10:18 brouard
76: *** empty log message ***
77:
1.248 brouard 78: Revision 1.247 2016/09/02 11:11:21 brouard
79: *** empty log message ***
80:
1.247 brouard 81: Revision 1.246 2016/09/02 08:49:22 brouard
82: *** empty log message ***
83:
1.246 brouard 84: Revision 1.245 2016/09/02 07:25:01 brouard
85: *** empty log message ***
86:
1.245 brouard 87: Revision 1.244 2016/09/02 07:17:34 brouard
88: *** empty log message ***
89:
1.244 brouard 90: Revision 1.243 2016/09/02 06:45:35 brouard
91: *** empty log message ***
92:
1.243 brouard 93: Revision 1.242 2016/08/30 15:01:20 brouard
94: Summary: Fixing a lots
95:
1.242 brouard 96: Revision 1.241 2016/08/29 17:17:25 brouard
97: Summary: gnuplot problem in Back projection to fix
98:
1.241 brouard 99: Revision 1.240 2016/08/29 07:53:18 brouard
100: Summary: Better
101:
1.240 brouard 102: Revision 1.239 2016/08/26 15:51:03 brouard
103: Summary: Improvement in Powell output in order to copy and paste
104:
105: Author:
106:
1.239 brouard 107: Revision 1.238 2016/08/26 14:23:35 brouard
108: Summary: Starting tests of 0.99
109:
1.238 brouard 110: Revision 1.237 2016/08/26 09:20:19 brouard
111: Summary: to valgrind
112:
1.237 brouard 113: Revision 1.236 2016/08/25 10:50:18 brouard
114: *** empty log message ***
115:
1.236 brouard 116: Revision 1.235 2016/08/25 06:59:23 brouard
117: *** empty log message ***
118:
1.235 brouard 119: Revision 1.234 2016/08/23 16:51:20 brouard
120: *** empty log message ***
121:
1.234 brouard 122: Revision 1.233 2016/08/23 07:40:50 brouard
123: Summary: not working
124:
1.233 brouard 125: Revision 1.232 2016/08/22 14:20:21 brouard
126: Summary: not working
127:
1.232 brouard 128: Revision 1.231 2016/08/22 07:17:15 brouard
129: Summary: not working
130:
1.231 brouard 131: Revision 1.230 2016/08/22 06:55:53 brouard
132: Summary: Not working
133:
1.230 brouard 134: Revision 1.229 2016/07/23 09:45:53 brouard
135: Summary: Completing for func too
136:
1.229 brouard 137: Revision 1.228 2016/07/22 17:45:30 brouard
138: Summary: Fixing some arrays, still debugging
139:
1.227 brouard 140: Revision 1.226 2016/07/12 18:42:34 brouard
141: Summary: temp
142:
1.226 brouard 143: Revision 1.225 2016/07/12 08:40:03 brouard
144: Summary: saving but not running
145:
1.225 brouard 146: Revision 1.224 2016/07/01 13:16:01 brouard
147: Summary: Fixes
148:
1.224 brouard 149: Revision 1.223 2016/02/19 09:23:35 brouard
150: Summary: temporary
151:
1.223 brouard 152: Revision 1.222 2016/02/17 08:14:50 brouard
153: Summary: Probably last 0.98 stable version 0.98r6
154:
1.222 brouard 155: Revision 1.221 2016/02/15 23:35:36 brouard
156: Summary: minor bug
157:
1.220 brouard 158: Revision 1.219 2016/02/15 00:48:12 brouard
159: *** empty log message ***
160:
1.219 brouard 161: Revision 1.218 2016/02/12 11:29:23 brouard
162: Summary: 0.99 Back projections
163:
1.218 brouard 164: Revision 1.217 2015/12/23 17:18:31 brouard
165: Summary: Experimental backcast
166:
1.217 brouard 167: Revision 1.216 2015/12/18 17:32:11 brouard
168: Summary: 0.98r4 Warning and status=-2
169:
170: Version 0.98r4 is now:
171: - displaying an error when status is -1, date of interview unknown and date of death known;
172: - permitting a status -2 when the vital status is unknown at a known date of right truncation.
173: Older changes concerning s=-2, dating from 2005 have been supersed.
174:
1.216 brouard 175: Revision 1.215 2015/12/16 08:52:24 brouard
176: Summary: 0.98r4 working
177:
1.215 brouard 178: Revision 1.214 2015/12/16 06:57:54 brouard
179: Summary: temporary not working
180:
1.214 brouard 181: Revision 1.213 2015/12/11 18:22:17 brouard
182: Summary: 0.98r4
183:
1.213 brouard 184: Revision 1.212 2015/11/21 12:47:24 brouard
185: Summary: minor typo
186:
1.212 brouard 187: Revision 1.211 2015/11/21 12:41:11 brouard
188: Summary: 0.98r3 with some graph of projected cross-sectional
189:
190: Author: Nicolas Brouard
191:
1.211 brouard 192: Revision 1.210 2015/11/18 17:41:20 brouard
1.252 brouard 193: Summary: Start working on projected prevalences Revision 1.209 2015/11/17 22:12:03 brouard
1.210 brouard 194: Summary: Adding ftolpl parameter
195: Author: N Brouard
196:
197: We had difficulties to get smoothed confidence intervals. It was due
198: to the period prevalence which wasn't computed accurately. The inner
199: parameter ftolpl is now an outer parameter of the .imach parameter
200: file after estepm. If ftolpl is small 1.e-4 and estepm too,
201: computation are long.
202:
1.209 brouard 203: Revision 1.208 2015/11/17 14:31:57 brouard
204: Summary: temporary
205:
1.208 brouard 206: Revision 1.207 2015/10/27 17:36:57 brouard
207: *** empty log message ***
208:
1.207 brouard 209: Revision 1.206 2015/10/24 07:14:11 brouard
210: *** empty log message ***
211:
1.206 brouard 212: Revision 1.205 2015/10/23 15:50:53 brouard
213: Summary: 0.98r3 some clarification for graphs on likelihood contributions
214:
1.205 brouard 215: Revision 1.204 2015/10/01 16:20:26 brouard
216: Summary: Some new graphs of contribution to likelihood
217:
1.204 brouard 218: Revision 1.203 2015/09/30 17:45:14 brouard
219: Summary: looking at better estimation of the hessian
220:
221: Also a better criteria for convergence to the period prevalence And
222: therefore adding the number of years needed to converge. (The
223: prevalence in any alive state shold sum to one
224:
1.203 brouard 225: Revision 1.202 2015/09/22 19:45:16 brouard
226: Summary: Adding some overall graph on contribution to likelihood. Might change
227:
1.202 brouard 228: Revision 1.201 2015/09/15 17:34:58 brouard
229: Summary: 0.98r0
230:
231: - Some new graphs like suvival functions
232: - Some bugs fixed like model=1+age+V2.
233:
1.201 brouard 234: Revision 1.200 2015/09/09 16:53:55 brouard
235: Summary: Big bug thanks to Flavia
236:
237: Even model=1+age+V2. did not work anymore
238:
1.200 brouard 239: Revision 1.199 2015/09/07 14:09:23 brouard
240: Summary: 0.98q6 changing default small png format for graph to vectorized svg.
241:
1.199 brouard 242: Revision 1.198 2015/09/03 07:14:39 brouard
243: Summary: 0.98q5 Flavia
244:
1.198 brouard 245: Revision 1.197 2015/09/01 18:24:39 brouard
246: *** empty log message ***
247:
1.197 brouard 248: Revision 1.196 2015/08/18 23:17:52 brouard
249: Summary: 0.98q5
250:
1.196 brouard 251: Revision 1.195 2015/08/18 16:28:39 brouard
252: Summary: Adding a hack for testing purpose
253:
254: After reading the title, ftol and model lines, if the comment line has
255: a q, starting with #q, the answer at the end of the run is quit. It
256: permits to run test files in batch with ctest. The former workaround was
257: $ echo q | imach foo.imach
258:
1.195 brouard 259: Revision 1.194 2015/08/18 13:32:00 brouard
260: Summary: Adding error when the covariance matrix doesn't contain the exact number of lines required by the model line.
261:
1.194 brouard 262: Revision 1.193 2015/08/04 07:17:42 brouard
263: Summary: 0.98q4
264:
1.193 brouard 265: Revision 1.192 2015/07/16 16:49:02 brouard
266: Summary: Fixing some outputs
267:
1.192 brouard 268: Revision 1.191 2015/07/14 10:00:33 brouard
269: Summary: Some fixes
270:
1.191 brouard 271: Revision 1.190 2015/05/05 08:51:13 brouard
272: Summary: Adding digits in output parameters (7 digits instead of 6)
273:
274: Fix 1+age+.
275:
1.190 brouard 276: Revision 1.189 2015/04/30 14:45:16 brouard
277: Summary: 0.98q2
278:
1.189 brouard 279: Revision 1.188 2015/04/30 08:27:53 brouard
280: *** empty log message ***
281:
1.188 brouard 282: Revision 1.187 2015/04/29 09:11:15 brouard
283: *** empty log message ***
284:
1.187 brouard 285: Revision 1.186 2015/04/23 12:01:52 brouard
286: Summary: V1*age is working now, version 0.98q1
287:
288: Some codes had been disabled in order to simplify and Vn*age was
289: working in the optimization phase, ie, giving correct MLE parameters,
290: but, as usual, outputs were not correct and program core dumped.
291:
1.186 brouard 292: Revision 1.185 2015/03/11 13:26:42 brouard
293: Summary: Inclusion of compile and links command line for Intel Compiler
294:
1.185 brouard 295: Revision 1.184 2015/03/11 11:52:39 brouard
296: Summary: Back from Windows 8. Intel Compiler
297:
1.184 brouard 298: Revision 1.183 2015/03/10 20:34:32 brouard
299: Summary: 0.98q0, trying with directest, mnbrak fixed
300:
301: We use directest instead of original Powell test; probably no
302: incidence on the results, but better justifications;
303: We fixed Numerical Recipes mnbrak routine which was wrong and gave
304: wrong results.
305:
1.183 brouard 306: Revision 1.182 2015/02/12 08:19:57 brouard
307: Summary: Trying to keep directest which seems simpler and more general
308: Author: Nicolas Brouard
309:
1.182 brouard 310: Revision 1.181 2015/02/11 23:22:24 brouard
311: Summary: Comments on Powell added
312:
313: Author:
314:
1.181 brouard 315: Revision 1.180 2015/02/11 17:33:45 brouard
316: Summary: Finishing move from main to function (hpijx and prevalence_limit)
317:
1.180 brouard 318: Revision 1.179 2015/01/04 09:57:06 brouard
319: Summary: back to OS/X
320:
1.179 brouard 321: Revision 1.178 2015/01/04 09:35:48 brouard
322: *** empty log message ***
323:
1.178 brouard 324: Revision 1.177 2015/01/03 18:40:56 brouard
325: Summary: Still testing ilc32 on OSX
326:
1.177 brouard 327: Revision 1.176 2015/01/03 16:45:04 brouard
328: *** empty log message ***
329:
1.176 brouard 330: Revision 1.175 2015/01/03 16:33:42 brouard
331: *** empty log message ***
332:
1.175 brouard 333: Revision 1.174 2015/01/03 16:15:49 brouard
334: Summary: Still in cross-compilation
335:
1.174 brouard 336: Revision 1.173 2015/01/03 12:06:26 brouard
337: Summary: trying to detect cross-compilation
338:
1.173 brouard 339: Revision 1.172 2014/12/27 12:07:47 brouard
340: Summary: Back from Visual Studio and Intel, options for compiling for Windows XP
341:
1.172 brouard 342: Revision 1.171 2014/12/23 13:26:59 brouard
343: Summary: Back from Visual C
344:
345: Still problem with utsname.h on Windows
346:
1.171 brouard 347: Revision 1.170 2014/12/23 11:17:12 brouard
348: Summary: Cleaning some \%% back to %%
349:
350: The escape was mandatory for a specific compiler (which one?), but too many warnings.
351:
1.170 brouard 352: Revision 1.169 2014/12/22 23:08:31 brouard
353: Summary: 0.98p
354:
355: Outputs some informations on compiler used, OS etc. Testing on different platforms.
356:
1.169 brouard 357: Revision 1.168 2014/12/22 15:17:42 brouard
1.170 brouard 358: Summary: update
1.169 brouard 359:
1.168 brouard 360: Revision 1.167 2014/12/22 13:50:56 brouard
361: Summary: Testing uname and compiler version and if compiled 32 or 64
362:
363: Testing on Linux 64
364:
1.167 brouard 365: Revision 1.166 2014/12/22 11:40:47 brouard
366: *** empty log message ***
367:
1.166 brouard 368: Revision 1.165 2014/12/16 11:20:36 brouard
369: Summary: After compiling on Visual C
370:
371: * imach.c (Module): Merging 1.61 to 1.162
372:
1.165 brouard 373: Revision 1.164 2014/12/16 10:52:11 brouard
374: Summary: Merging with Visual C after suppressing some warnings for unused variables. Also fixing Saito's bug 0.98Xn
375:
376: * imach.c (Module): Merging 1.61 to 1.162
377:
1.164 brouard 378: Revision 1.163 2014/12/16 10:30:11 brouard
379: * imach.c (Module): Merging 1.61 to 1.162
380:
1.163 brouard 381: Revision 1.162 2014/09/25 11:43:39 brouard
382: Summary: temporary backup 0.99!
383:
1.162 brouard 384: Revision 1.1 2014/09/16 11:06:58 brouard
385: Summary: With some code (wrong) for nlopt
386:
387: Author:
388:
389: Revision 1.161 2014/09/15 20:41:41 brouard
390: Summary: Problem with macro SQR on Intel compiler
391:
1.161 brouard 392: Revision 1.160 2014/09/02 09:24:05 brouard
393: *** empty log message ***
394:
1.160 brouard 395: Revision 1.159 2014/09/01 10:34:10 brouard
396: Summary: WIN32
397: Author: Brouard
398:
1.159 brouard 399: Revision 1.158 2014/08/27 17:11:51 brouard
400: *** empty log message ***
401:
1.158 brouard 402: Revision 1.157 2014/08/27 16:26:55 brouard
403: Summary: Preparing windows Visual studio version
404: Author: Brouard
405:
406: In order to compile on Visual studio, time.h is now correct and time_t
407: and tm struct should be used. difftime should be used but sometimes I
408: just make the differences in raw time format (time(&now).
409: Trying to suppress #ifdef LINUX
410: Add xdg-open for __linux in order to open default browser.
411:
1.157 brouard 412: Revision 1.156 2014/08/25 20:10:10 brouard
413: *** empty log message ***
414:
1.156 brouard 415: Revision 1.155 2014/08/25 18:32:34 brouard
416: Summary: New compile, minor changes
417: Author: Brouard
418:
1.155 brouard 419: Revision 1.154 2014/06/20 17:32:08 brouard
420: Summary: Outputs now all graphs of convergence to period prevalence
421:
1.154 brouard 422: Revision 1.153 2014/06/20 16:45:46 brouard
423: Summary: If 3 live state, convergence to period prevalence on same graph
424: Author: Brouard
425:
1.153 brouard 426: Revision 1.152 2014/06/18 17:54:09 brouard
427: Summary: open browser, use gnuplot on same dir than imach if not found in the path
428:
1.152 brouard 429: Revision 1.151 2014/06/18 16:43:30 brouard
430: *** empty log message ***
431:
1.151 brouard 432: Revision 1.150 2014/06/18 16:42:35 brouard
433: Summary: If gnuplot is not in the path try on same directory than imach binary (OSX)
434: Author: brouard
435:
1.150 brouard 436: Revision 1.149 2014/06/18 15:51:14 brouard
437: Summary: Some fixes in parameter files errors
438: Author: Nicolas Brouard
439:
1.149 brouard 440: Revision 1.148 2014/06/17 17:38:48 brouard
441: Summary: Nothing new
442: Author: Brouard
443:
444: Just a new packaging for OS/X version 0.98nS
445:
1.148 brouard 446: Revision 1.147 2014/06/16 10:33:11 brouard
447: *** empty log message ***
448:
1.147 brouard 449: Revision 1.146 2014/06/16 10:20:28 brouard
450: Summary: Merge
451: Author: Brouard
452:
453: Merge, before building revised version.
454:
1.146 brouard 455: Revision 1.145 2014/06/10 21:23:15 brouard
456: Summary: Debugging with valgrind
457: Author: Nicolas Brouard
458:
459: Lot of changes in order to output the results with some covariates
460: After the Edimburgh REVES conference 2014, it seems mandatory to
461: improve the code.
462: No more memory valgrind error but a lot has to be done in order to
463: continue the work of splitting the code into subroutines.
464: Also, decodemodel has been improved. Tricode is still not
465: optimal. nbcode should be improved. Documentation has been added in
466: the source code.
467:
1.144 brouard 468: Revision 1.143 2014/01/26 09:45:38 brouard
469: Summary: Version 0.98nR (to be improved, but gives same optimization results as 0.98k. Nice, promising
470:
471: * imach.c (Module): Trying to merge old staffs together while being at Tokyo. Not tested...
472: (Module): Version 0.98nR Running ok, but output format still only works for three covariates.
473:
1.143 brouard 474: Revision 1.142 2014/01/26 03:57:36 brouard
475: Summary: gnuplot changed plot w l 1 has to be changed to plot w l lt 2
476:
477: * imach.c (Module): Trying to merge old staffs together while being at Tokyo. Not tested...
478:
1.142 brouard 479: Revision 1.141 2014/01/26 02:42:01 brouard
480: * imach.c (Module): Trying to merge old staffs together while being at Tokyo. Not tested...
481:
1.141 brouard 482: Revision 1.140 2011/09/02 10:37:54 brouard
483: Summary: times.h is ok with mingw32 now.
484:
1.140 brouard 485: Revision 1.139 2010/06/14 07:50:17 brouard
486: After the theft of my laptop, I probably lost some lines of codes which were not uploaded to the CVS tree.
487: I remember having already fixed agemin agemax which are pointers now but not cvs saved.
488:
1.139 brouard 489: Revision 1.138 2010/04/30 18:19:40 brouard
490: *** empty log message ***
491:
1.138 brouard 492: Revision 1.137 2010/04/29 18:11:38 brouard
493: (Module): Checking covariates for more complex models
494: than V1+V2. A lot of change to be done. Unstable.
495:
1.137 brouard 496: Revision 1.136 2010/04/26 20:30:53 brouard
497: (Module): merging some libgsl code. Fixing computation
498: of likelione (using inter/intrapolation if mle = 0) in order to
499: get same likelihood as if mle=1.
500: Some cleaning of code and comments added.
501:
1.136 brouard 502: Revision 1.135 2009/10/29 15:33:14 brouard
503: (Module): Now imach stops if date of birth, at least year of birth, is not given. Some cleaning of the code.
504:
1.135 brouard 505: Revision 1.134 2009/10/29 13:18:53 brouard
506: (Module): Now imach stops if date of birth, at least year of birth, is not given. Some cleaning of the code.
507:
1.134 brouard 508: Revision 1.133 2009/07/06 10:21:25 brouard
509: just nforces
510:
1.133 brouard 511: Revision 1.132 2009/07/06 08:22:05 brouard
512: Many tings
513:
1.132 brouard 514: Revision 1.131 2009/06/20 16:22:47 brouard
515: Some dimensions resccaled
516:
1.131 brouard 517: Revision 1.130 2009/05/26 06:44:34 brouard
518: (Module): Max Covariate is now set to 20 instead of 8. A
519: lot of cleaning with variables initialized to 0. Trying to make
520: V2+V3*age+V1+V4 strb=V3*age+V1+V4 working better.
521:
1.130 brouard 522: Revision 1.129 2007/08/31 13:49:27 lievre
523: Modification of the way of exiting when the covariate is not binary in order to see on the window the error message before exiting
524:
1.129 lievre 525: Revision 1.128 2006/06/30 13:02:05 brouard
526: (Module): Clarifications on computing e.j
527:
1.128 brouard 528: Revision 1.127 2006/04/28 18:11:50 brouard
529: (Module): Yes the sum of survivors was wrong since
530: imach-114 because nhstepm was no more computed in the age
531: loop. Now we define nhstepma in the age loop.
532: (Module): In order to speed up (in case of numerous covariates) we
533: compute health expectancies (without variances) in a first step
534: and then all the health expectancies with variances or standard
535: deviation (needs data from the Hessian matrices) which slows the
536: computation.
537: In the future we should be able to stop the program is only health
538: expectancies and graph are needed without standard deviations.
539:
1.127 brouard 540: Revision 1.126 2006/04/28 17:23:28 brouard
541: (Module): Yes the sum of survivors was wrong since
542: imach-114 because nhstepm was no more computed in the age
543: loop. Now we define nhstepma in the age loop.
544: Version 0.98h
545:
1.126 brouard 546: Revision 1.125 2006/04/04 15:20:31 lievre
547: Errors in calculation of health expectancies. Age was not initialized.
548: Forecasting file added.
549:
550: Revision 1.124 2006/03/22 17:13:53 lievre
551: Parameters are printed with %lf instead of %f (more numbers after the comma).
552: The log-likelihood is printed in the log file
553:
554: Revision 1.123 2006/03/20 10:52:43 brouard
555: * imach.c (Module): <title> changed, corresponds to .htm file
556: name. <head> headers where missing.
557:
558: * imach.c (Module): Weights can have a decimal point as for
559: English (a comma might work with a correct LC_NUMERIC environment,
560: otherwise the weight is truncated).
561: Modification of warning when the covariates values are not 0 or
562: 1.
563: Version 0.98g
564:
565: Revision 1.122 2006/03/20 09:45:41 brouard
566: (Module): Weights can have a decimal point as for
567: English (a comma might work with a correct LC_NUMERIC environment,
568: otherwise the weight is truncated).
569: Modification of warning when the covariates values are not 0 or
570: 1.
571: Version 0.98g
572:
573: Revision 1.121 2006/03/16 17:45:01 lievre
574: * imach.c (Module): Comments concerning covariates added
575:
576: * imach.c (Module): refinements in the computation of lli if
577: status=-2 in order to have more reliable computation if stepm is
578: not 1 month. Version 0.98f
579:
580: Revision 1.120 2006/03/16 15:10:38 lievre
581: (Module): refinements in the computation of lli if
582: status=-2 in order to have more reliable computation if stepm is
583: not 1 month. Version 0.98f
584:
585: Revision 1.119 2006/03/15 17:42:26 brouard
586: (Module): Bug if status = -2, the loglikelihood was
587: computed as likelihood omitting the logarithm. Version O.98e
588:
589: Revision 1.118 2006/03/14 18:20:07 brouard
590: (Module): varevsij Comments added explaining the second
591: table of variances if popbased=1 .
592: (Module): Covariances of eij, ekl added, graphs fixed, new html link.
593: (Module): Function pstamp added
594: (Module): Version 0.98d
595:
596: Revision 1.117 2006/03/14 17:16:22 brouard
597: (Module): varevsij Comments added explaining the second
598: table of variances if popbased=1 .
599: (Module): Covariances of eij, ekl added, graphs fixed, new html link.
600: (Module): Function pstamp added
601: (Module): Version 0.98d
602:
603: Revision 1.116 2006/03/06 10:29:27 brouard
604: (Module): Variance-covariance wrong links and
605: varian-covariance of ej. is needed (Saito).
606:
607: Revision 1.115 2006/02/27 12:17:45 brouard
608: (Module): One freematrix added in mlikeli! 0.98c
609:
610: Revision 1.114 2006/02/26 12:57:58 brouard
611: (Module): Some improvements in processing parameter
612: filename with strsep.
613:
614: Revision 1.113 2006/02/24 14:20:24 brouard
615: (Module): Memory leaks checks with valgrind and:
616: datafile was not closed, some imatrix were not freed and on matrix
617: allocation too.
618:
619: Revision 1.112 2006/01/30 09:55:26 brouard
620: (Module): Back to gnuplot.exe instead of wgnuplot.exe
621:
622: Revision 1.111 2006/01/25 20:38:18 brouard
623: (Module): Lots of cleaning and bugs added (Gompertz)
624: (Module): Comments can be added in data file. Missing date values
625: can be a simple dot '.'.
626:
627: Revision 1.110 2006/01/25 00:51:50 brouard
628: (Module): Lots of cleaning and bugs added (Gompertz)
629:
630: Revision 1.109 2006/01/24 19:37:15 brouard
631: (Module): Comments (lines starting with a #) are allowed in data.
632:
633: Revision 1.108 2006/01/19 18:05:42 lievre
634: Gnuplot problem appeared...
635: To be fixed
636:
637: Revision 1.107 2006/01/19 16:20:37 brouard
638: Test existence of gnuplot in imach path
639:
640: Revision 1.106 2006/01/19 13:24:36 brouard
641: Some cleaning and links added in html output
642:
643: Revision 1.105 2006/01/05 20:23:19 lievre
644: *** empty log message ***
645:
646: Revision 1.104 2005/09/30 16:11:43 lievre
647: (Module): sump fixed, loop imx fixed, and simplifications.
648: (Module): If the status is missing at the last wave but we know
649: that the person is alive, then we can code his/her status as -2
650: (instead of missing=-1 in earlier versions) and his/her
651: contributions to the likelihood is 1 - Prob of dying from last
652: health status (= 1-p13= p11+p12 in the easiest case of somebody in
653: the healthy state at last known wave). Version is 0.98
654:
655: Revision 1.103 2005/09/30 15:54:49 lievre
656: (Module): sump fixed, loop imx fixed, and simplifications.
657:
658: Revision 1.102 2004/09/15 17:31:30 brouard
659: Add the possibility to read data file including tab characters.
660:
661: Revision 1.101 2004/09/15 10:38:38 brouard
662: Fix on curr_time
663:
664: Revision 1.100 2004/07/12 18:29:06 brouard
665: Add version for Mac OS X. Just define UNIX in Makefile
666:
667: Revision 1.99 2004/06/05 08:57:40 brouard
668: *** empty log message ***
669:
670: Revision 1.98 2004/05/16 15:05:56 brouard
671: New version 0.97 . First attempt to estimate force of mortality
672: directly from the data i.e. without the need of knowing the health
673: state at each age, but using a Gompertz model: log u =a + b*age .
674: This is the basic analysis of mortality and should be done before any
675: other analysis, in order to test if the mortality estimated from the
676: cross-longitudinal survey is different from the mortality estimated
677: from other sources like vital statistic data.
678:
679: The same imach parameter file can be used but the option for mle should be -3.
680:
1.133 brouard 681: Agnès, who wrote this part of the code, tried to keep most of the
1.126 brouard 682: former routines in order to include the new code within the former code.
683:
684: The output is very simple: only an estimate of the intercept and of
685: the slope with 95% confident intervals.
686:
687: Current limitations:
688: A) Even if you enter covariates, i.e. with the
689: model= V1+V2 equation for example, the programm does only estimate a unique global model without covariates.
690: B) There is no computation of Life Expectancy nor Life Table.
691:
692: Revision 1.97 2004/02/20 13:25:42 lievre
693: Version 0.96d. Population forecasting command line is (temporarily)
694: suppressed.
695:
696: Revision 1.96 2003/07/15 15:38:55 brouard
697: * imach.c (Repository): Errors in subdirf, 2, 3 while printing tmpout is
698: rewritten within the same printf. Workaround: many printfs.
699:
700: Revision 1.95 2003/07/08 07:54:34 brouard
701: * imach.c (Repository):
702: (Repository): Using imachwizard code to output a more meaningful covariance
703: matrix (cov(a12,c31) instead of numbers.
704:
705: Revision 1.94 2003/06/27 13:00:02 brouard
706: Just cleaning
707:
708: Revision 1.93 2003/06/25 16:33:55 brouard
709: (Module): On windows (cygwin) function asctime_r doesn't
710: exist so I changed back to asctime which exists.
711: (Module): Version 0.96b
712:
713: Revision 1.92 2003/06/25 16:30:45 brouard
714: (Module): On windows (cygwin) function asctime_r doesn't
715: exist so I changed back to asctime which exists.
716:
717: Revision 1.91 2003/06/25 15:30:29 brouard
718: * imach.c (Repository): Duplicated warning errors corrected.
719: (Repository): Elapsed time after each iteration is now output. It
720: helps to forecast when convergence will be reached. Elapsed time
721: is stamped in powell. We created a new html file for the graphs
722: concerning matrix of covariance. It has extension -cov.htm.
723:
724: Revision 1.90 2003/06/24 12:34:15 brouard
725: (Module): Some bugs corrected for windows. Also, when
726: mle=-1 a template is output in file "or"mypar.txt with the design
727: of the covariance matrix to be input.
728:
729: Revision 1.89 2003/06/24 12:30:52 brouard
730: (Module): Some bugs corrected for windows. Also, when
731: mle=-1 a template is output in file "or"mypar.txt with the design
732: of the covariance matrix to be input.
733:
734: Revision 1.88 2003/06/23 17:54:56 brouard
735: * 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.
736:
737: Revision 1.87 2003/06/18 12:26:01 brouard
738: Version 0.96
739:
740: Revision 1.86 2003/06/17 20:04:08 brouard
741: (Module): Change position of html and gnuplot routines and added
742: routine fileappend.
743:
744: Revision 1.85 2003/06/17 13:12:43 brouard
745: * imach.c (Repository): Check when date of death was earlier that
746: current date of interview. It may happen when the death was just
747: prior to the death. In this case, dh was negative and likelihood
748: was wrong (infinity). We still send an "Error" but patch by
749: assuming that the date of death was just one stepm after the
750: interview.
751: (Repository): Because some people have very long ID (first column)
752: we changed int to long in num[] and we added a new lvector for
753: memory allocation. But we also truncated to 8 characters (left
754: truncation)
755: (Repository): No more line truncation errors.
756:
757: Revision 1.84 2003/06/13 21:44:43 brouard
758: * imach.c (Repository): Replace "freqsummary" at a correct
759: place. It differs from routine "prevalence" which may be called
760: many times. Probs is memory consuming and must be used with
761: parcimony.
762: Version 0.95a3 (should output exactly the same maximization than 0.8a2)
763:
764: Revision 1.83 2003/06/10 13:39:11 lievre
765: *** empty log message ***
766:
767: Revision 1.82 2003/06/05 15:57:20 brouard
768: Add log in imach.c and fullversion number is now printed.
769:
770: */
771: /*
772: Interpolated Markov Chain
773:
774: Short summary of the programme:
775:
1.227 brouard 776: This program computes Healthy Life Expectancies or State-specific
777: (if states aren't health statuses) Expectancies from
778: cross-longitudinal data. Cross-longitudinal data consist in:
779:
780: -1- a first survey ("cross") where individuals from different ages
781: are interviewed on their health status or degree of disability (in
782: the case of a health survey which is our main interest)
783:
784: -2- at least a second wave of interviews ("longitudinal") which
785: measure each change (if any) in individual health status. Health
786: expectancies are computed from the time spent in each health state
787: according to a model. More health states you consider, more time is
788: necessary to reach the Maximum Likelihood of the parameters involved
789: in the model. The simplest model is the multinomial logistic model
790: where pij is the probability to be observed in state j at the second
791: wave conditional to be observed in state i at the first
792: wave. Therefore the model is: log(pij/pii)= aij + bij*age+ cij*sex +
793: etc , where 'age' is age and 'sex' is a covariate. If you want to
794: have a more complex model than "constant and age", you should modify
795: the program where the markup *Covariates have to be included here
796: again* invites you to do it. More covariates you add, slower the
1.126 brouard 797: convergence.
798:
799: The advantage of this computer programme, compared to a simple
800: multinomial logistic model, is clear when the delay between waves is not
801: identical for each individual. Also, if a individual missed an
802: intermediate interview, the information is lost, but taken into
803: account using an interpolation or extrapolation.
804:
805: hPijx is the probability to be observed in state i at age x+h
806: conditional to the observed state i at age x. The delay 'h' can be
807: split into an exact number (nh*stepm) of unobserved intermediate
808: states. This elementary transition (by month, quarter,
809: semester or year) is modelled as a multinomial logistic. The hPx
810: matrix is simply the matrix product of nh*stepm elementary matrices
811: and the contribution of each individual to the likelihood is simply
812: hPijx.
813:
814: Also this programme outputs the covariance matrix of the parameters but also
1.218 brouard 815: of the life expectancies. It also computes the period (stable) prevalence.
816:
817: Back prevalence and projections:
1.227 brouard 818:
819: - back_prevalence_limit(double *p, double **bprlim, double ageminpar,
820: double agemaxpar, double ftolpl, int *ncvyearp, double
821: dateprev1,double dateprev2, int firstpass, int lastpass, int
822: mobilavproj)
823:
824: Computes the back prevalence limit for any combination of
825: covariate values k at any age between ageminpar and agemaxpar and
826: returns it in **bprlim. In the loops,
827:
828: - **bprevalim(**bprlim, ***mobaverage, nlstate, *p, age, **oldm,
829: **savm, **dnewm, **doldm, **dsavm, ftolpl, ncvyearp, k);
830:
831: - hBijx Back Probability to be in state i at age x-h being in j at x
1.218 brouard 832: Computes for any combination of covariates k and any age between bage and fage
833: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
834: oldm=oldms;savm=savms;
1.227 brouard 835:
1.267 brouard 836: - hbxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k, nres);
1.218 brouard 837: Computes the transition matrix starting at age 'age' over
838: 'nhstepm*hstepm*stepm' months (i.e. until
839: age (in years) age+nhstepm*hstepm*stepm/12) by multiplying
1.227 brouard 840: nhstepm*hstepm matrices.
841:
842: Returns p3mat[i][j][h] after calling
843: p3mat[i][j][h]=matprod2(newm,
844: bmij(pmmij,cov,ncovmodel,x,nlstate,prevacurrent, dnewm, doldm,
845: dsavm,ij),\ 1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath,
846: oldm);
1.226 brouard 847:
848: Important routines
849:
850: - func (or funcone), computes logit (pij) distinguishing
851: o fixed variables (single or product dummies or quantitative);
852: o varying variables by:
853: (1) wave (single, product dummies, quantitative),
854: (2) by age (can be month) age (done), age*age (done), age*Vn where Vn can be:
855: % fixed dummy (treated) or quantitative (not done because time-consuming);
856: % varying dummy (not done) or quantitative (not done);
857: - Tricode which tests the modality of dummy variables (in order to warn with wrong or empty modalities)
858: and returns the number of efficient covariates cptcoveff and modalities nbcode[Tvar[k]][1]= 0 and nbcode[Tvar[k]][2]= 1 usually.
859: - printinghtml which outputs results like life expectancy in and from a state for a combination of modalities of dummy variables
860: o There are 2*cptcoveff combinations of (0,1) for cptcoveff variables. Outputting only combinations with people, éliminating 1 1 if
861: race White (0 0), Black vs White (1 0), Hispanic (0 1) and 1 1 being meaningless.
1.218 brouard 862:
1.226 brouard 863:
864:
1.133 brouard 865: Authors: Nicolas Brouard (brouard@ined.fr) and Agnès Lièvre (lievre@ined.fr).
866: Institut national d'études démographiques, Paris.
1.126 brouard 867: This software have been partly granted by Euro-REVES, a concerted action
868: from the European Union.
869: It is copyrighted identically to a GNU software product, ie programme and
870: software can be distributed freely for non commercial use. Latest version
871: can be accessed at http://euroreves.ined.fr/imach .
872:
873: Help to debug: LD_PRELOAD=/usr/local/lib/libnjamd.so ./imach foo.imach
874: or better on gdb : set env LD_PRELOAD=/usr/local/lib/libnjamd.so
875:
876: **********************************************************************/
877: /*
878: main
879: read parameterfile
880: read datafile
881: concatwav
882: freqsummary
883: if (mle >= 1)
884: mlikeli
885: print results files
886: if mle==1
887: computes hessian
888: read end of parameter file: agemin, agemax, bage, fage, estepm
889: begin-prev-date,...
890: open gnuplot file
891: open html file
1.145 brouard 892: period (stable) prevalence | pl_nom 1-1 2-2 etc by covariate
893: for age prevalim() | #****** V1=0 V2=1 V3=1 V4=0 ******
894: | 65 1 0 2 1 3 1 4 0 0.96326 0.03674
895: freexexit2 possible for memory heap.
896:
897: h Pij x | pij_nom ficrestpij
898: # Cov Agex agex+h hpijx with i,j= 1-1 1-2 1-3 2-1 2-2 2-3
899: 1 85 85 1.00000 0.00000 0.00000 0.00000 1.00000 0.00000
900: 1 85 86 0.68299 0.22291 0.09410 0.71093 0.00000 0.28907
901:
902: 1 65 99 0.00364 0.00322 0.99314 0.00350 0.00310 0.99340
903: 1 65 100 0.00214 0.00204 0.99581 0.00206 0.00196 0.99597
904: variance of p one-step probabilities varprob | prob_nom ficresprob #One-step probabilities and stand. devi in ()
905: Standard deviation of one-step probabilities | probcor_nom ficresprobcor #One-step probabilities and correlation matrix
906: Matrix of variance covariance of one-step probabilities | probcov_nom ficresprobcov #One-step probabilities and covariance matrix
907:
1.126 brouard 908: forecasting if prevfcast==1 prevforecast call prevalence()
909: health expectancies
910: Variance-covariance of DFLE
911: prevalence()
912: movingaverage()
913: varevsij()
914: if popbased==1 varevsij(,popbased)
915: total life expectancies
916: Variance of period (stable) prevalence
917: end
918: */
919:
1.187 brouard 920: /* #define DEBUG */
921: /* #define DEBUGBRENT */
1.203 brouard 922: /* #define DEBUGLINMIN */
923: /* #define DEBUGHESS */
924: #define DEBUGHESSIJ
1.224 brouard 925: /* #define LINMINORIGINAL /\* Don't use loop on scale in linmin (accepting nan) *\/ */
1.165 brouard 926: #define POWELL /* Instead of NLOPT */
1.224 brouard 927: #define POWELLNOF3INFF1TEST /* Skip test */
1.186 brouard 928: /* #define POWELLORIGINAL /\* Don't use Directest to decide new direction but original Powell test *\/ */
929: /* #define MNBRAKORIGINAL /\* Don't use mnbrak fix *\/ */
1.126 brouard 930:
931: #include <math.h>
932: #include <stdio.h>
933: #include <stdlib.h>
934: #include <string.h>
1.226 brouard 935: #include <ctype.h>
1.159 brouard 936:
937: #ifdef _WIN32
938: #include <io.h>
1.172 brouard 939: #include <windows.h>
940: #include <tchar.h>
1.159 brouard 941: #else
1.126 brouard 942: #include <unistd.h>
1.159 brouard 943: #endif
1.126 brouard 944:
945: #include <limits.h>
946: #include <sys/types.h>
1.171 brouard 947:
948: #if defined(__GNUC__)
949: #include <sys/utsname.h> /* Doesn't work on Windows */
950: #endif
951:
1.126 brouard 952: #include <sys/stat.h>
953: #include <errno.h>
1.159 brouard 954: /* extern int errno; */
1.126 brouard 955:
1.157 brouard 956: /* #ifdef LINUX */
957: /* #include <time.h> */
958: /* #include "timeval.h" */
959: /* #else */
960: /* #include <sys/time.h> */
961: /* #endif */
962:
1.126 brouard 963: #include <time.h>
964:
1.136 brouard 965: #ifdef GSL
966: #include <gsl/gsl_errno.h>
967: #include <gsl/gsl_multimin.h>
968: #endif
969:
1.167 brouard 970:
1.162 brouard 971: #ifdef NLOPT
972: #include <nlopt.h>
973: typedef struct {
974: double (* function)(double [] );
975: } myfunc_data ;
976: #endif
977:
1.126 brouard 978: /* #include <libintl.h> */
979: /* #define _(String) gettext (String) */
980:
1.251 brouard 981: #define MAXLINE 2048 /* Was 256 and 1024. Overflow with 312 with 2 states and 4 covariates. Should be ok */
1.126 brouard 982:
983: #define GNUPLOTPROGRAM "gnuplot"
984: /*#define GNUPLOTPROGRAM "..\\gp37mgw\\wgnuplot"*/
985: #define FILENAMELENGTH 132
986:
987: #define GLOCK_ERROR_NOPATH -1 /* empty path */
988: #define GLOCK_ERROR_GETCWD -2 /* cannot get cwd */
989:
1.144 brouard 990: #define MAXPARM 128 /**< Maximum number of parameters for the optimization */
991: #define NPARMAX 64 /**< (nlstate+ndeath-1)*nlstate*ncovmodel */
1.126 brouard 992:
993: #define NINTERVMAX 8
1.144 brouard 994: #define NLSTATEMAX 8 /**< Maximum number of live states (for func) */
995: #define NDEATHMAX 8 /**< Maximum number of dead states (for func) */
996: #define NCOVMAX 20 /**< Maximum number of covariates, including generated covariates V1*V2 */
1.197 brouard 997: #define codtabm(h,k) (1 & (h-1) >> (k-1))+1
1.211 brouard 998: /*#define decodtabm(h,k,cptcoveff)= (h <= (1<<cptcoveff)?(((h-1) >> (k-1)) & 1) +1 : -1)*/
999: #define decodtabm(h,k,cptcoveff) (((h-1) >> (k-1)) & 1) +1
1.126 brouard 1000: #define MAXN 20000
1.144 brouard 1001: #define YEARM 12. /**< Number of months per year */
1.218 brouard 1002: /* #define AGESUP 130 */
1003: #define AGESUP 150
1.268 brouard 1004: #define AGEINF 0
1.218 brouard 1005: #define AGEMARGE 25 /* Marge for agemin and agemax for(iage=agemin-AGEMARGE; iage <= agemax+3+AGEMARGE; iage++) */
1.126 brouard 1006: #define AGEBASE 40
1.194 brouard 1007: #define AGEOVERFLOW 1.e20
1.164 brouard 1008: #define AGEGOMP 10 /**< Minimal age for Gompertz adjustment */
1.157 brouard 1009: #ifdef _WIN32
1010: #define DIRSEPARATOR '\\'
1011: #define CHARSEPARATOR "\\"
1012: #define ODIRSEPARATOR '/'
1013: #else
1.126 brouard 1014: #define DIRSEPARATOR '/'
1015: #define CHARSEPARATOR "/"
1016: #define ODIRSEPARATOR '\\'
1017: #endif
1018:
1.272 ! brouard 1019: /* $Id: imach.c,v 1.271 2017/06/27 10:17:50 brouard Exp $ */
1.126 brouard 1020: /* $State: Exp $ */
1.196 brouard 1021: #include "version.h"
1022: char version[]=__IMACH_VERSION__;
1.224 brouard 1023: 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";
1.272 ! brouard 1024: char fullversion[]="$Revision: 1.271 $ $Date: 2017/06/27 10:17:50 $";
1.126 brouard 1025: char strstart[80];
1026: char optionfilext[10], optionfilefiname[FILENAMELENGTH];
1.130 brouard 1027: int erreur=0, nberr=0, nbwarn=0; /* Error number, number of errors number of warnings */
1.187 brouard 1028: int nagesqr=0, nforce=0; /* nagesqr=1 if model is including age*age, number of forces */
1.145 brouard 1029: /* Number of covariates model=V2+V1+ V3*age+V2*V4 */
1030: int cptcovn=0; /**< cptcovn number of covariates added in the model (excepting constant and age and age*product) */
1031: int cptcovt=0; /**< cptcovt number of covariates added in the model (excepting constant and age) */
1.225 brouard 1032: int cptcovs=0; /**< cptcovs number of simple covariates in the model V2+V1 =2 */
1033: int cptcovsnq=0; /**< cptcovsnq number of simple covariates in the model but non quantitative V2+V1 =2 */
1.145 brouard 1034: int cptcovage=0; /**< Number of covariates with age: V3*age only =1 */
1035: int cptcovprodnoage=0; /**< Number of covariate products without age */
1036: int cptcoveff=0; /* Total number of covariates to vary for printing results */
1.233 brouard 1037: int ncovf=0; /* Total number of effective fixed covariates (dummy or quantitative) in the model */
1038: int ncovv=0; /* Total number of effective (wave) varying covariates (dummy or quantitative) in the model */
1.232 brouard 1039: int ncova=0; /* Total number of effective (wave and stepm) varying with age covariates (dummy of quantitative) in the model */
1.234 brouard 1040: int nsd=0; /**< Total number of single dummy variables (output) */
1041: int nsq=0; /**< Total number of single quantitative variables (output) */
1.232 brouard 1042: int ncoveff=0; /* Total number of effective fixed dummy covariates in the model */
1.225 brouard 1043: int nqfveff=0; /**< nqfveff Number of Quantitative Fixed Variables Effective */
1.224 brouard 1044: int ntveff=0; /**< ntveff number of effective time varying variables */
1045: int nqtveff=0; /**< ntqveff number of effective time varying quantitative variables */
1.145 brouard 1046: int cptcov=0; /* Working variable */
1.218 brouard 1047: int ncovcombmax=NCOVMAX; /* Maximum calculated number of covariate combination = pow(2, cptcoveff) */
1.126 brouard 1048: int npar=NPARMAX;
1049: int nlstate=2; /* Number of live states */
1050: int ndeath=1; /* Number of dead states */
1.130 brouard 1051: int ncovmodel=0, ncovcol=0; /* Total number of covariables including constant a12*1 +b12*x ncovmodel=2 */
1.223 brouard 1052: int nqv=0, ntv=0, nqtv=0; /* Total number of quantitative variables, time variable (dummy), quantitative and time variable */
1.126 brouard 1053: int popbased=0;
1054:
1055: int *wav; /* Number of waves for this individuual 0 is possible */
1.130 brouard 1056: int maxwav=0; /* Maxim number of waves */
1057: int jmin=0, jmax=0; /* min, max spacing between 2 waves */
1058: int ijmin=0, ijmax=0; /* Individuals having jmin and jmax */
1059: int gipmx=0, gsw=0; /* Global variables on the number of contributions
1.126 brouard 1060: to the likelihood and the sum of weights (done by funcone)*/
1.130 brouard 1061: int mle=1, weightopt=0;
1.126 brouard 1062: int **mw; /* mw[mi][i] is number of the mi wave for this individual */
1063: int **dh; /* dh[mi][i] is number of steps between mi,mi+1 for this individual */
1064: int **bh; /* bh[mi][i] is the bias (+ or -) for this individual if the delay between
1065: * wave mi and wave mi+1 is not an exact multiple of stepm. */
1.162 brouard 1066: int countcallfunc=0; /* Count the number of calls to func */
1.230 brouard 1067: int selected(int kvar); /* Is covariate kvar selected for printing results */
1068:
1.130 brouard 1069: double jmean=1; /* Mean space between 2 waves */
1.145 brouard 1070: double **matprod2(); /* test */
1.126 brouard 1071: double **oldm, **newm, **savm; /* Working pointers to matrices */
1072: double **oldms, **newms, **savms; /* Fixed working pointers to matrices */
1.218 brouard 1073: double **ddnewms, **ddoldms, **ddsavms; /* for freeing later */
1074:
1.136 brouard 1075: /*FILE *fic ; */ /* Used in readdata only */
1.217 brouard 1076: FILE *ficpar, *ficparo,*ficres, *ficresp, *ficresphtm, *ficresphtmfr, *ficrespl, *ficresplb,*ficrespij, *ficrespijb, *ficrest,*ficresf, *ficresfb,*ficrespop;
1.126 brouard 1077: FILE *ficlog, *ficrespow;
1.130 brouard 1078: int globpr=0; /* Global variable for printing or not */
1.126 brouard 1079: double fretone; /* Only one call to likelihood */
1.130 brouard 1080: long ipmx=0; /* Number of contributions */
1.126 brouard 1081: double sw; /* Sum of weights */
1082: char filerespow[FILENAMELENGTH];
1083: char fileresilk[FILENAMELENGTH]; /* File of individual contributions to the likelihood */
1084: FILE *ficresilk;
1085: FILE *ficgp,*ficresprob,*ficpop, *ficresprobcov, *ficresprobcor;
1086: FILE *ficresprobmorprev;
1087: FILE *fichtm, *fichtmcov; /* Html File */
1088: FILE *ficreseij;
1089: char filerese[FILENAMELENGTH];
1090: FILE *ficresstdeij;
1091: char fileresstde[FILENAMELENGTH];
1092: FILE *ficrescveij;
1093: char filerescve[FILENAMELENGTH];
1094: FILE *ficresvij;
1095: char fileresv[FILENAMELENGTH];
1.269 brouard 1096:
1.126 brouard 1097: char title[MAXLINE];
1.234 brouard 1098: char model[MAXLINE]; /**< The model line */
1.217 brouard 1099: char optionfile[FILENAMELENGTH], datafile[FILENAMELENGTH], filerespl[FILENAMELENGTH], fileresplb[FILENAMELENGTH];
1.126 brouard 1100: char plotcmd[FILENAMELENGTH], pplotcmd[FILENAMELENGTH];
1101: char tmpout[FILENAMELENGTH], tmpout2[FILENAMELENGTH];
1102: char command[FILENAMELENGTH];
1103: int outcmd=0;
1104:
1.217 brouard 1105: char fileres[FILENAMELENGTH], filerespij[FILENAMELENGTH], filerespijb[FILENAMELENGTH], filereso[FILENAMELENGTH], rfileres[FILENAMELENGTH];
1.202 brouard 1106: char fileresu[FILENAMELENGTH]; /* fileres without r in front */
1.126 brouard 1107: char filelog[FILENAMELENGTH]; /* Log file */
1108: char filerest[FILENAMELENGTH];
1109: char fileregp[FILENAMELENGTH];
1110: char popfile[FILENAMELENGTH];
1111:
1112: char optionfilegnuplot[FILENAMELENGTH], optionfilehtm[FILENAMELENGTH], optionfilehtmcov[FILENAMELENGTH] ;
1113:
1.157 brouard 1114: /* struct timeval start_time, end_time, curr_time, last_time, forecast_time; */
1115: /* struct timezone tzp; */
1116: /* extern int gettimeofday(); */
1117: struct tm tml, *gmtime(), *localtime();
1118:
1119: extern time_t time();
1120:
1121: struct tm start_time, end_time, curr_time, last_time, forecast_time;
1122: time_t rstart_time, rend_time, rcurr_time, rlast_time, rforecast_time; /* raw time */
1123: struct tm tm;
1124:
1.126 brouard 1125: char strcurr[80], strfor[80];
1126:
1127: char *endptr;
1128: long lval;
1129: double dval;
1130:
1131: #define NR_END 1
1132: #define FREE_ARG char*
1133: #define FTOL 1.0e-10
1134:
1135: #define NRANSI
1.240 brouard 1136: #define ITMAX 200
1137: #define ITPOWMAX 20 /* This is now multiplied by the number of parameters */
1.126 brouard 1138:
1139: #define TOL 2.0e-4
1140:
1141: #define CGOLD 0.3819660
1142: #define ZEPS 1.0e-10
1143: #define SHFT(a,b,c,d) (a)=(b);(b)=(c);(c)=(d);
1144:
1145: #define GOLD 1.618034
1146: #define GLIMIT 100.0
1147: #define TINY 1.0e-20
1148:
1149: static double maxarg1,maxarg2;
1150: #define FMAX(a,b) (maxarg1=(a),maxarg2=(b),(maxarg1)>(maxarg2)? (maxarg1):(maxarg2))
1151: #define FMIN(a,b) (maxarg1=(a),maxarg2=(b),(maxarg1)<(maxarg2)? (maxarg1):(maxarg2))
1152:
1153: #define SIGN(a,b) ((b)>0.0 ? fabs(a) : -fabs(a))
1154: #define rint(a) floor(a+0.5)
1.166 brouard 1155: /* http://www.thphys.uni-heidelberg.de/~robbers/cmbeasy/doc/html/myutils_8h-source.html */
1.183 brouard 1156: #define mytinydouble 1.0e-16
1.166 brouard 1157: /* #define DEQUAL(a,b) (fabs((a)-(b))<mytinydouble) */
1158: /* http://www.thphys.uni-heidelberg.de/~robbers/cmbeasy/doc/html/mynrutils_8h-source.html */
1159: /* static double dsqrarg; */
1160: /* #define DSQR(a) (DEQUAL((dsqrarg=(a)),0.0) ? 0.0 : dsqrarg*dsqrarg) */
1.126 brouard 1161: static double sqrarg;
1162: #define SQR(a) ((sqrarg=(a)) == 0.0 ? 0.0 :sqrarg*sqrarg)
1163: #define SWAP(a,b) {temp=(a);(a)=(b);(b)=temp;}
1164: int agegomp= AGEGOMP;
1165:
1166: int imx;
1167: int stepm=1;
1168: /* Stepm, step in month: minimum step interpolation*/
1169:
1170: int estepm;
1171: /* Estepm, step in month to interpolate survival function in order to approximate Life Expectancy*/
1172:
1173: int m,nb;
1174: long *num;
1.197 brouard 1175: int firstpass=0, lastpass=4,*cod, *cens;
1.192 brouard 1176: int *ncodemax; /* ncodemax[j]= Number of modalities of the j th
1177: covariate for which somebody answered excluding
1178: undefined. Usually 2: 0 and 1. */
1179: int *ncodemaxwundef; /* ncodemax[j]= Number of modalities of the j th
1180: covariate for which somebody answered including
1181: undefined. Usually 3: -1, 0 and 1. */
1.126 brouard 1182: double **agev,*moisnais, *annais, *moisdc, *andc,**mint, **anint;
1.218 brouard 1183: double **pmmij, ***probs; /* Global pointer */
1.219 brouard 1184: double ***mobaverage, ***mobaverages; /* New global variable */
1.126 brouard 1185: double *ageexmed,*agecens;
1186: double dateintmean=0;
1187:
1188: double *weight;
1189: int **s; /* Status */
1.141 brouard 1190: double *agedc;
1.145 brouard 1191: double **covar; /**< covar[j,i], value of jth covariate for individual i,
1.141 brouard 1192: * covar=matrix(0,NCOVMAX,1,n);
1.187 brouard 1193: * cov[Tage[kk]+2]=covar[Tvar[Tage[kk]]][i]*age; */
1.268 brouard 1194: double **coqvar; /* Fixed quantitative covariate nqv */
1195: double ***cotvar; /* Time varying covariate ntv */
1.225 brouard 1196: double ***cotqvar; /* Time varying quantitative covariate itqv */
1.141 brouard 1197: double idx;
1198: int **nbcode, *Tvar; /**< model=V2 => Tvar[1]= 2 */
1.234 brouard 1199: /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1200: /*k 1 2 3 4 5 6 7 8 9 */
1201: /*Tvar[k]= 5 4 3 6 5 2 7 1 1 */
1202: /* Tndvar[k] 1 2 3 4 5 */
1203: /*TDvar 4 3 6 7 1 */ /* For outputs only; combination of dummies fixed or varying */
1204: /* Tns[k] 1 2 2 4 5 */ /* Number of single cova */
1205: /* TvarsD[k] 1 2 3 */ /* Number of single dummy cova */
1206: /* TvarsDind 2 3 9 */ /* position K of single dummy cova */
1207: /* TvarsQ[k] 1 2 */ /* Number of single quantitative cova */
1208: /* TvarsQind 1 6 */ /* position K of single quantitative cova */
1209: /* Tprod[i]=k 4 7 */
1210: /* Tage[i]=k 5 8 */
1211: /* */
1212: /* Type */
1213: /* V 1 2 3 4 5 */
1214: /* F F V V V */
1215: /* D Q D D Q */
1216: /* */
1217: int *TvarsD;
1218: int *TvarsDind;
1219: int *TvarsQ;
1220: int *TvarsQind;
1221:
1.235 brouard 1222: #define MAXRESULTLINES 10
1223: int nresult=0;
1.258 brouard 1224: int parameterline=0; /* # of the parameter (type) line */
1.235 brouard 1225: int TKresult[MAXRESULTLINES];
1.237 brouard 1226: int Tresult[MAXRESULTLINES][NCOVMAX];/* For dummy variable , value (output) */
1227: int Tinvresult[MAXRESULTLINES][NCOVMAX];/* For dummy variable , value (output) */
1.235 brouard 1228: int Tvresult[MAXRESULTLINES][NCOVMAX]; /* For dummy variable , variable # (output) */
1229: double Tqresult[MAXRESULTLINES][NCOVMAX]; /* For quantitative variable , value (output) */
1.237 brouard 1230: double Tqinvresult[MAXRESULTLINES][NCOVMAX]; /* For quantitative variable , value (output) */
1.235 brouard 1231: int Tvqresult[MAXRESULTLINES][NCOVMAX]; /* For quantitative variable , variable # (output) */
1232:
1.234 brouard 1233: /* 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 1234: 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 */
1235: 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 */
1236: 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 */
1237: int *TvarVind; /**< TvarVind[1]=1, TvarVind[2]=2 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1238: 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 */
1239: 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 1240: int *TvarFD; /**< TvarFD[1]=V1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1241: int *TvarFDind; /* TvarFDind[1]=9 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1242: int *TvarFQ; /* TvarFQ[1]=V2 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1243: int *TvarFQind; /* TvarFQind[1]=6 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1244: int *TvarVD; /* TvarVD[1]=V5 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1245: int *TvarVDind; /* TvarVDind[1]=1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1246: 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 */
1247: 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 */
1248:
1.230 brouard 1249: int *Tvarsel; /**< Selected covariates for output */
1250: double *Tvalsel; /**< Selected modality value of covariate for output */
1.226 brouard 1251: int *Typevar; /**< 0 for simple covariate (dummy, quantitative, fixed or varying), 1 for age product, 2 for product */
1.227 brouard 1252: int *Fixed; /** Fixed[k] 0=fixed, 1 varying, 2 fixed with age product, 3 varying with age product */
1253: 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 1254: int *DummyV; /** Dummy[v] 0=dummy (0 1), 1 quantitative */
1255: int *FixedV; /** FixedV[v] 0 fixed, 1 varying */
1.197 brouard 1256: int *Tage;
1.227 brouard 1257: int anyvaryingduminmodel=0; /**< Any varying dummy in Model=1 yes, 0 no, to avoid a loop on waves in freq */
1.228 brouard 1258: 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 1259: 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*/
1260: 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 1261: int *Ndum; /** Freq of modality (tricode */
1.200 brouard 1262: /* int **codtab;*/ /**< codtab=imatrix(1,100,1,10); */
1.227 brouard 1263: int **Tvard;
1264: int *Tprod;/**< Gives the k position of the k1 product */
1.238 brouard 1265: /* Tprod[k1=1]=3(=V1*V4) for V2+V1+V1*V4+age*V3 */
1.227 brouard 1266: int *Tposprod; /**< Gives the k1 product from the k position */
1.238 brouard 1267: /* if V2+V1+V1*V4+age*V3+V3*V2 TProd[k1=2]=5 (V3*V2) */
1268: /* Tposprod[k]=k1 , Tposprod[3]=1, Tposprod[5(V3*V2)]=2 (2nd product without age) */
1.227 brouard 1269: int cptcovprod, *Tvaraff, *invalidvarcomb;
1.126 brouard 1270: double *lsurv, *lpop, *tpop;
1271:
1.231 brouard 1272: #define FD 1; /* Fixed dummy covariate */
1273: #define FQ 2; /* Fixed quantitative covariate */
1274: #define FP 3; /* Fixed product covariate */
1275: #define FPDD 7; /* Fixed product dummy*dummy covariate */
1276: #define FPDQ 8; /* Fixed product dummy*quantitative covariate */
1277: #define FPQQ 9; /* Fixed product quantitative*quantitative covariate */
1278: #define VD 10; /* Varying dummy covariate */
1279: #define VQ 11; /* Varying quantitative covariate */
1280: #define VP 12; /* Varying product covariate */
1281: #define VPDD 13; /* Varying product dummy*dummy covariate */
1282: #define VPDQ 14; /* Varying product dummy*quantitative covariate */
1283: #define VPQQ 15; /* Varying product quantitative*quantitative covariate */
1284: #define APFD 16; /* Age product * fixed dummy covariate */
1285: #define APFQ 17; /* Age product * fixed quantitative covariate */
1286: #define APVD 18; /* Age product * varying dummy covariate */
1287: #define APVQ 19; /* Age product * varying quantitative covariate */
1288:
1289: #define FTYPE 1; /* Fixed covariate */
1290: #define VTYPE 2; /* Varying covariate (loop in wave) */
1291: #define ATYPE 2; /* Age product covariate (loop in dh within wave)*/
1292:
1293: struct kmodel{
1294: int maintype; /* main type */
1295: int subtype; /* subtype */
1296: };
1297: struct kmodel modell[NCOVMAX];
1298:
1.143 brouard 1299: double ftol=FTOL; /**< Tolerance for computing Max Likelihood */
1300: double ftolhess; /**< Tolerance for computing hessian */
1.126 brouard 1301:
1302: /**************** split *************************/
1303: static int split( char *path, char *dirc, char *name, char *ext, char *finame )
1304: {
1305: /* From a file name with (full) path (either Unix or Windows) we extract the directory (dirc)
1306: the name of the file (name), its extension only (ext) and its first part of the name (finame)
1307: */
1308: char *ss; /* pointer */
1.186 brouard 1309: int l1=0, l2=0; /* length counters */
1.126 brouard 1310:
1311: l1 = strlen(path ); /* length of path */
1312: if ( l1 == 0 ) return( GLOCK_ERROR_NOPATH );
1313: ss= strrchr( path, DIRSEPARATOR ); /* find last / */
1314: if ( ss == NULL ) { /* no directory, so determine current directory */
1315: strcpy( name, path ); /* we got the fullname name because no directory */
1316: /*if(strrchr(path, ODIRSEPARATOR )==NULL)
1317: printf("Warning you should use %s as a separator\n",DIRSEPARATOR);*/
1318: /* get current working directory */
1319: /* extern char* getcwd ( char *buf , int len);*/
1.184 brouard 1320: #ifdef WIN32
1321: if (_getcwd( dirc, FILENAME_MAX ) == NULL ) {
1322: #else
1323: if (getcwd(dirc, FILENAME_MAX) == NULL) {
1324: #endif
1.126 brouard 1325: return( GLOCK_ERROR_GETCWD );
1326: }
1327: /* got dirc from getcwd*/
1328: printf(" DIRC = %s \n",dirc);
1.205 brouard 1329: } else { /* strip directory from path */
1.126 brouard 1330: ss++; /* after this, the filename */
1331: l2 = strlen( ss ); /* length of filename */
1332: if ( l2 == 0 ) return( GLOCK_ERROR_NOPATH );
1333: strcpy( name, ss ); /* save file name */
1334: strncpy( dirc, path, l1 - l2 ); /* now the directory */
1.186 brouard 1335: dirc[l1-l2] = '\0'; /* add zero */
1.126 brouard 1336: printf(" DIRC2 = %s \n",dirc);
1337: }
1338: /* We add a separator at the end of dirc if not exists */
1339: l1 = strlen( dirc ); /* length of directory */
1340: if( dirc[l1-1] != DIRSEPARATOR ){
1341: dirc[l1] = DIRSEPARATOR;
1342: dirc[l1+1] = 0;
1343: printf(" DIRC3 = %s \n",dirc);
1344: }
1345: ss = strrchr( name, '.' ); /* find last / */
1346: if (ss >0){
1347: ss++;
1348: strcpy(ext,ss); /* save extension */
1349: l1= strlen( name);
1350: l2= strlen(ss)+1;
1351: strncpy( finame, name, l1-l2);
1352: finame[l1-l2]= 0;
1353: }
1354:
1355: return( 0 ); /* we're done */
1356: }
1357:
1358:
1359: /******************************************/
1360:
1361: void replace_back_to_slash(char *s, char*t)
1362: {
1363: int i;
1364: int lg=0;
1365: i=0;
1366: lg=strlen(t);
1367: for(i=0; i<= lg; i++) {
1368: (s[i] = t[i]);
1369: if (t[i]== '\\') s[i]='/';
1370: }
1371: }
1372:
1.132 brouard 1373: char *trimbb(char *out, char *in)
1.137 brouard 1374: { /* Trim multiple blanks in line but keeps first blanks if line starts with blanks */
1.132 brouard 1375: char *s;
1376: s=out;
1377: while (*in != '\0'){
1.137 brouard 1378: while( *in == ' ' && *(in+1) == ' '){ /* && *(in+1) != '\0'){*/
1.132 brouard 1379: in++;
1380: }
1381: *out++ = *in++;
1382: }
1383: *out='\0';
1384: return s;
1385: }
1386:
1.187 brouard 1387: /* char *substrchaine(char *out, char *in, char *chain) */
1388: /* { */
1389: /* /\* Substract chain 'chain' from 'in', return and output 'out' *\/ */
1390: /* char *s, *t; */
1391: /* t=in;s=out; */
1392: /* while ((*in != *chain) && (*in != '\0')){ */
1393: /* *out++ = *in++; */
1394: /* } */
1395:
1396: /* /\* *in matches *chain *\/ */
1397: /* while ((*in++ == *chain++) && (*in != '\0')){ */
1398: /* printf("*in = %c, *out= %c *chain= %c \n", *in, *out, *chain); */
1399: /* } */
1400: /* in--; chain--; */
1401: /* while ( (*in != '\0')){ */
1402: /* printf("Bef *in = %c, *out= %c *chain= %c \n", *in, *out, *chain); */
1403: /* *out++ = *in++; */
1404: /* printf("Aft *in = %c, *out= %c *chain= %c \n", *in, *out, *chain); */
1405: /* } */
1406: /* *out='\0'; */
1407: /* out=s; */
1408: /* return out; */
1409: /* } */
1410: char *substrchaine(char *out, char *in, char *chain)
1411: {
1412: /* Substract chain 'chain' from 'in', return and output 'out' */
1413: /* in="V1+V1*age+age*age+V2", chain="age*age" */
1414:
1415: char *strloc;
1416:
1417: strcpy (out, in);
1418: strloc = strstr(out, chain); /* strloc points to out at age*age+V2 */
1419: printf("Bef strloc=%s chain=%s out=%s \n", strloc, chain, out);
1420: if(strloc != NULL){
1421: /* will affect out */ /* strloc+strlenc(chain)=+V2 */ /* Will also work in Unicode */
1422: memmove(strloc,strloc+strlen(chain), strlen(strloc+strlen(chain))+1);
1423: /* strcpy (strloc, strloc +strlen(chain));*/
1424: }
1425: printf("Aft strloc=%s chain=%s in=%s out=%s \n", strloc, chain, in, out);
1426: return out;
1427: }
1428:
1429:
1.145 brouard 1430: char *cutl(char *blocc, char *alocc, char *in, char occ)
1431: {
1.187 brouard 1432: /* cuts string in into blocc and alocc where blocc ends before FIRST occurence of char 'occ'
1.145 brouard 1433: and alocc starts after first occurence of char 'occ' : ex cutv(blocc,alocc,"abcdef2ghi2j",'2')
1.187 brouard 1434: gives blocc="abcdef" and alocc="ghi2j".
1.145 brouard 1435: If occ is not found blocc is null and alocc is equal to in. Returns blocc
1436: */
1.160 brouard 1437: char *s, *t;
1.145 brouard 1438: t=in;s=in;
1439: while ((*in != occ) && (*in != '\0')){
1440: *alocc++ = *in++;
1441: }
1442: if( *in == occ){
1443: *(alocc)='\0';
1444: s=++in;
1445: }
1446:
1447: if (s == t) {/* occ not found */
1448: *(alocc-(in-s))='\0';
1449: in=s;
1450: }
1451: while ( *in != '\0'){
1452: *blocc++ = *in++;
1453: }
1454:
1455: *blocc='\0';
1456: return t;
1457: }
1.137 brouard 1458: char *cutv(char *blocc, char *alocc, char *in, char occ)
1459: {
1.187 brouard 1460: /* cuts string in into blocc and alocc where blocc ends before LAST occurence of char 'occ'
1.137 brouard 1461: and alocc starts after last occurence of char 'occ' : ex cutv(blocc,alocc,"abcdef2ghi2j",'2')
1462: gives blocc="abcdef2ghi" and alocc="j".
1463: If occ is not found blocc is null and alocc is equal to in. Returns alocc
1464: */
1465: char *s, *t;
1466: t=in;s=in;
1467: while (*in != '\0'){
1468: while( *in == occ){
1469: *blocc++ = *in++;
1470: s=in;
1471: }
1472: *blocc++ = *in++;
1473: }
1474: if (s == t) /* occ not found */
1475: *(blocc-(in-s))='\0';
1476: else
1477: *(blocc-(in-s)-1)='\0';
1478: in=s;
1479: while ( *in != '\0'){
1480: *alocc++ = *in++;
1481: }
1482:
1483: *alocc='\0';
1484: return s;
1485: }
1486:
1.126 brouard 1487: int nbocc(char *s, char occ)
1488: {
1489: int i,j=0;
1490: int lg=20;
1491: i=0;
1492: lg=strlen(s);
1493: for(i=0; i<= lg; i++) {
1.234 brouard 1494: if (s[i] == occ ) j++;
1.126 brouard 1495: }
1496: return j;
1497: }
1498:
1.137 brouard 1499: /* void cutv(char *u,char *v, char*t, char occ) */
1500: /* { */
1501: /* /\* cuts string t into u and v where u ends before last occurence of char 'occ' */
1502: /* and v starts after last occurence of char 'occ' : ex cutv(u,v,"abcdef2ghi2j",'2') */
1503: /* gives u="abcdef2ghi" and v="j" *\/ */
1504: /* int i,lg,j,p=0; */
1505: /* i=0; */
1506: /* lg=strlen(t); */
1507: /* for(j=0; j<=lg-1; j++) { */
1508: /* if((t[j]!= occ) && (t[j+1]== occ)) p=j+1; */
1509: /* } */
1.126 brouard 1510:
1.137 brouard 1511: /* for(j=0; j<p; j++) { */
1512: /* (u[j] = t[j]); */
1513: /* } */
1514: /* u[p]='\0'; */
1.126 brouard 1515:
1.137 brouard 1516: /* for(j=0; j<= lg; j++) { */
1517: /* if (j>=(p+1))(v[j-p-1] = t[j]); */
1518: /* } */
1519: /* } */
1.126 brouard 1520:
1.160 brouard 1521: #ifdef _WIN32
1522: char * strsep(char **pp, const char *delim)
1523: {
1524: char *p, *q;
1525:
1526: if ((p = *pp) == NULL)
1527: return 0;
1528: if ((q = strpbrk (p, delim)) != NULL)
1529: {
1530: *pp = q + 1;
1531: *q = '\0';
1532: }
1533: else
1534: *pp = 0;
1535: return p;
1536: }
1537: #endif
1538:
1.126 brouard 1539: /********************** nrerror ********************/
1540:
1541: void nrerror(char error_text[])
1542: {
1543: fprintf(stderr,"ERREUR ...\n");
1544: fprintf(stderr,"%s\n",error_text);
1545: exit(EXIT_FAILURE);
1546: }
1547: /*********************** vector *******************/
1548: double *vector(int nl, int nh)
1549: {
1550: double *v;
1551: v=(double *) malloc((size_t)((nh-nl+1+NR_END)*sizeof(double)));
1552: if (!v) nrerror("allocation failure in vector");
1553: return v-nl+NR_END;
1554: }
1555:
1556: /************************ free vector ******************/
1557: void free_vector(double*v, int nl, int nh)
1558: {
1559: free((FREE_ARG)(v+nl-NR_END));
1560: }
1561:
1562: /************************ivector *******************************/
1563: int *ivector(long nl,long nh)
1564: {
1565: int *v;
1566: v=(int *) malloc((size_t)((nh-nl+1+NR_END)*sizeof(int)));
1567: if (!v) nrerror("allocation failure in ivector");
1568: return v-nl+NR_END;
1569: }
1570:
1571: /******************free ivector **************************/
1572: void free_ivector(int *v, long nl, long nh)
1573: {
1574: free((FREE_ARG)(v+nl-NR_END));
1575: }
1576:
1577: /************************lvector *******************************/
1578: long *lvector(long nl,long nh)
1579: {
1580: long *v;
1581: v=(long *) malloc((size_t)((nh-nl+1+NR_END)*sizeof(long)));
1582: if (!v) nrerror("allocation failure in ivector");
1583: return v-nl+NR_END;
1584: }
1585:
1586: /******************free lvector **************************/
1587: void free_lvector(long *v, long nl, long nh)
1588: {
1589: free((FREE_ARG)(v+nl-NR_END));
1590: }
1591:
1592: /******************* imatrix *******************************/
1593: int **imatrix(long nrl, long nrh, long ncl, long nch)
1594: /* allocate a int matrix with subscript range m[nrl..nrh][ncl..nch] */
1595: {
1596: long i, nrow=nrh-nrl+1,ncol=nch-ncl+1;
1597: int **m;
1598:
1599: /* allocate pointers to rows */
1600: m=(int **) malloc((size_t)((nrow+NR_END)*sizeof(int*)));
1601: if (!m) nrerror("allocation failure 1 in matrix()");
1602: m += NR_END;
1603: m -= nrl;
1604:
1605:
1606: /* allocate rows and set pointers to them */
1607: m[nrl]=(int *) malloc((size_t)((nrow*ncol+NR_END)*sizeof(int)));
1608: if (!m[nrl]) nrerror("allocation failure 2 in matrix()");
1609: m[nrl] += NR_END;
1610: m[nrl] -= ncl;
1611:
1612: for(i=nrl+1;i<=nrh;i++) m[i]=m[i-1]+ncol;
1613:
1614: /* return pointer to array of pointers to rows */
1615: return m;
1616: }
1617:
1618: /****************** free_imatrix *************************/
1619: void free_imatrix(m,nrl,nrh,ncl,nch)
1620: int **m;
1621: long nch,ncl,nrh,nrl;
1622: /* free an int matrix allocated by imatrix() */
1623: {
1624: free((FREE_ARG) (m[nrl]+ncl-NR_END));
1625: free((FREE_ARG) (m+nrl-NR_END));
1626: }
1627:
1628: /******************* matrix *******************************/
1629: double **matrix(long nrl, long nrh, long ncl, long nch)
1630: {
1631: long i, nrow=nrh-nrl+1, ncol=nch-ncl+1;
1632: double **m;
1633:
1634: m=(double **) malloc((size_t)((nrow+NR_END)*sizeof(double*)));
1635: if (!m) nrerror("allocation failure 1 in matrix()");
1636: m += NR_END;
1637: m -= nrl;
1638:
1639: m[nrl]=(double *) malloc((size_t)((nrow*ncol+NR_END)*sizeof(double)));
1640: if (!m[nrl]) nrerror("allocation failure 2 in matrix()");
1641: m[nrl] += NR_END;
1642: m[nrl] -= ncl;
1643:
1644: for (i=nrl+1; i<=nrh; i++) m[i]=m[i-1]+ncol;
1645: return m;
1.145 brouard 1646: /* print *(*(m+1)+70) or print m[1][70]; print m+1 or print &(m[1]) or &(m[1][0])
1647: m[i] = address of ith row of the table. &(m[i]) is its value which is another adress
1648: that of m[i][0]. In order to get the value p m[i][0] but it is unitialized.
1.126 brouard 1649: */
1650: }
1651:
1652: /*************************free matrix ************************/
1653: void free_matrix(double **m, long nrl, long nrh, long ncl, long nch)
1654: {
1655: free((FREE_ARG)(m[nrl]+ncl-NR_END));
1656: free((FREE_ARG)(m+nrl-NR_END));
1657: }
1658:
1659: /******************* ma3x *******************************/
1660: double ***ma3x(long nrl, long nrh, long ncl, long nch, long nll, long nlh)
1661: {
1662: long i, j, nrow=nrh-nrl+1, ncol=nch-ncl+1, nlay=nlh-nll+1;
1663: double ***m;
1664:
1665: m=(double ***) malloc((size_t)((nrow+NR_END)*sizeof(double*)));
1666: if (!m) nrerror("allocation failure 1 in matrix()");
1667: m += NR_END;
1668: m -= nrl;
1669:
1670: m[nrl]=(double **) malloc((size_t)((nrow*ncol+NR_END)*sizeof(double)));
1671: if (!m[nrl]) nrerror("allocation failure 2 in matrix()");
1672: m[nrl] += NR_END;
1673: m[nrl] -= ncl;
1674:
1675: for (i=nrl+1; i<=nrh; i++) m[i]=m[i-1]+ncol;
1676:
1677: m[nrl][ncl]=(double *) malloc((size_t)((nrow*ncol*nlay+NR_END)*sizeof(double)));
1678: if (!m[nrl][ncl]) nrerror("allocation failure 3 in matrix()");
1679: m[nrl][ncl] += NR_END;
1680: m[nrl][ncl] -= nll;
1681: for (j=ncl+1; j<=nch; j++)
1682: m[nrl][j]=m[nrl][j-1]+nlay;
1683:
1684: for (i=nrl+1; i<=nrh; i++) {
1685: m[i][ncl]=m[i-1l][ncl]+ncol*nlay;
1686: for (j=ncl+1; j<=nch; j++)
1687: m[i][j]=m[i][j-1]+nlay;
1688: }
1689: return m;
1690: /* gdb: p *(m+1) <=> p m[1] and p (m+1) <=> p (m+1) <=> p &(m[1])
1691: &(m[i][j][k]) <=> *((*(m+i) + j)+k)
1692: */
1693: }
1694:
1695: /*************************free ma3x ************************/
1696: void free_ma3x(double ***m, long nrl, long nrh, long ncl, long nch,long nll, long nlh)
1697: {
1698: free((FREE_ARG)(m[nrl][ncl]+ nll-NR_END));
1699: free((FREE_ARG)(m[nrl]+ncl-NR_END));
1700: free((FREE_ARG)(m+nrl-NR_END));
1701: }
1702:
1703: /*************** function subdirf ***********/
1704: char *subdirf(char fileres[])
1705: {
1706: /* Caution optionfilefiname is hidden */
1707: strcpy(tmpout,optionfilefiname);
1708: strcat(tmpout,"/"); /* Add to the right */
1709: strcat(tmpout,fileres);
1710: return tmpout;
1711: }
1712:
1713: /*************** function subdirf2 ***********/
1714: char *subdirf2(char fileres[], char *preop)
1715: {
1716:
1717: /* Caution optionfilefiname is hidden */
1718: strcpy(tmpout,optionfilefiname);
1719: strcat(tmpout,"/");
1720: strcat(tmpout,preop);
1721: strcat(tmpout,fileres);
1722: return tmpout;
1723: }
1724:
1725: /*************** function subdirf3 ***********/
1726: char *subdirf3(char fileres[], char *preop, char *preop2)
1727: {
1728:
1729: /* Caution optionfilefiname is hidden */
1730: strcpy(tmpout,optionfilefiname);
1731: strcat(tmpout,"/");
1732: strcat(tmpout,preop);
1733: strcat(tmpout,preop2);
1734: strcat(tmpout,fileres);
1735: return tmpout;
1736: }
1.213 brouard 1737:
1738: /*************** function subdirfext ***********/
1739: char *subdirfext(char fileres[], char *preop, char *postop)
1740: {
1741:
1742: strcpy(tmpout,preop);
1743: strcat(tmpout,fileres);
1744: strcat(tmpout,postop);
1745: return tmpout;
1746: }
1.126 brouard 1747:
1.213 brouard 1748: /*************** function subdirfext3 ***********/
1749: char *subdirfext3(char fileres[], char *preop, char *postop)
1750: {
1751:
1752: /* Caution optionfilefiname is hidden */
1753: strcpy(tmpout,optionfilefiname);
1754: strcat(tmpout,"/");
1755: strcat(tmpout,preop);
1756: strcat(tmpout,fileres);
1757: strcat(tmpout,postop);
1758: return tmpout;
1759: }
1760:
1.162 brouard 1761: char *asc_diff_time(long time_sec, char ascdiff[])
1762: {
1763: long sec_left, days, hours, minutes;
1764: days = (time_sec) / (60*60*24);
1765: sec_left = (time_sec) % (60*60*24);
1766: hours = (sec_left) / (60*60) ;
1767: sec_left = (sec_left) %(60*60);
1768: minutes = (sec_left) /60;
1769: sec_left = (sec_left) % (60);
1770: sprintf(ascdiff,"%ld day(s) %ld hour(s) %ld minute(s) %ld second(s)",days, hours, minutes, sec_left);
1771: return ascdiff;
1772: }
1773:
1.126 brouard 1774: /***************** f1dim *************************/
1775: extern int ncom;
1776: extern double *pcom,*xicom;
1777: extern double (*nrfunc)(double []);
1778:
1779: double f1dim(double x)
1780: {
1781: int j;
1782: double f;
1783: double *xt;
1784:
1785: xt=vector(1,ncom);
1786: for (j=1;j<=ncom;j++) xt[j]=pcom[j]+x*xicom[j];
1787: f=(*nrfunc)(xt);
1788: free_vector(xt,1,ncom);
1789: return f;
1790: }
1791:
1792: /*****************brent *************************/
1793: double brent(double ax, double bx, double cx, double (*f)(double), double tol, double *xmin)
1.187 brouard 1794: {
1795: /* Given a function f, and given a bracketing triplet of abscissas ax, bx, cx (such that bx is
1796: * between ax and cx, and f(bx) is less than both f(ax) and f(cx) ), this routine isolates
1797: * the minimum to a fractional precision of about tol using Brent’s method. The abscissa of
1798: * the minimum is returned as xmin, and the minimum function value is returned as brent , the
1799: * returned function value.
1800: */
1.126 brouard 1801: int iter;
1802: double a,b,d,etemp;
1.159 brouard 1803: double fu=0,fv,fw,fx;
1.164 brouard 1804: double ftemp=0.;
1.126 brouard 1805: double p,q,r,tol1,tol2,u,v,w,x,xm;
1806: double e=0.0;
1807:
1808: a=(ax < cx ? ax : cx);
1809: b=(ax > cx ? ax : cx);
1810: x=w=v=bx;
1811: fw=fv=fx=(*f)(x);
1812: for (iter=1;iter<=ITMAX;iter++) {
1813: xm=0.5*(a+b);
1814: tol2=2.0*(tol1=tol*fabs(x)+ZEPS);
1815: /* if (2.0*fabs(fp-(*fret)) <= ftol*(fabs(fp)+fabs(*fret)))*/
1816: printf(".");fflush(stdout);
1817: fprintf(ficlog,".");fflush(ficlog);
1.162 brouard 1818: #ifdef DEBUGBRENT
1.126 brouard 1819: 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);
1820: 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);
1821: /* if ((fabs(x-xm) <= (tol2-0.5*(b-a)))||(2.0*fabs(fu-ftemp) <= ftol*1.e-2*(fabs(fu)+fabs(ftemp)))) { */
1822: #endif
1823: if (fabs(x-xm) <= (tol2-0.5*(b-a))){
1824: *xmin=x;
1825: return fx;
1826: }
1827: ftemp=fu;
1828: if (fabs(e) > tol1) {
1829: r=(x-w)*(fx-fv);
1830: q=(x-v)*(fx-fw);
1831: p=(x-v)*q-(x-w)*r;
1832: q=2.0*(q-r);
1833: if (q > 0.0) p = -p;
1834: q=fabs(q);
1835: etemp=e;
1836: e=d;
1837: if (fabs(p) >= fabs(0.5*q*etemp) || p <= q*(a-x) || p >= q*(b-x))
1.224 brouard 1838: d=CGOLD*(e=(x >= xm ? a-x : b-x));
1.126 brouard 1839: else {
1.224 brouard 1840: d=p/q;
1841: u=x+d;
1842: if (u-a < tol2 || b-u < tol2)
1843: d=SIGN(tol1,xm-x);
1.126 brouard 1844: }
1845: } else {
1846: d=CGOLD*(e=(x >= xm ? a-x : b-x));
1847: }
1848: u=(fabs(d) >= tol1 ? x+d : x+SIGN(tol1,d));
1849: fu=(*f)(u);
1850: if (fu <= fx) {
1851: if (u >= x) a=x; else b=x;
1852: SHFT(v,w,x,u)
1.183 brouard 1853: SHFT(fv,fw,fx,fu)
1854: } else {
1855: if (u < x) a=u; else b=u;
1856: if (fu <= fw || w == x) {
1.224 brouard 1857: v=w;
1858: w=u;
1859: fv=fw;
1860: fw=fu;
1.183 brouard 1861: } else if (fu <= fv || v == x || v == w) {
1.224 brouard 1862: v=u;
1863: fv=fu;
1.183 brouard 1864: }
1865: }
1.126 brouard 1866: }
1867: nrerror("Too many iterations in brent");
1868: *xmin=x;
1869: return fx;
1870: }
1871:
1872: /****************** mnbrak ***********************/
1873:
1874: void mnbrak(double *ax, double *bx, double *cx, double *fa, double *fb, double *fc,
1875: double (*func)(double))
1.183 brouard 1876: { /* Given a function func , and given distinct initial points ax and bx , this routine searches in
1877: the downhill direction (defined by the function as evaluated at the initial points) and returns
1878: new points ax , bx , cx that bracket a minimum of the function. Also returned are the function
1879: values at the three points, fa, fb , and fc such that fa > fb and fb < fc.
1880: */
1.126 brouard 1881: double ulim,u,r,q, dum;
1882: double fu;
1.187 brouard 1883:
1884: double scale=10.;
1885: int iterscale=0;
1886:
1887: *fa=(*func)(*ax); /* xta[j]=pcom[j]+(*ax)*xicom[j]; fa=f(xta[j])*/
1888: *fb=(*func)(*bx); /* xtb[j]=pcom[j]+(*bx)*xicom[j]; fb=f(xtb[j]) */
1889:
1890:
1891: /* while(*fb != *fb){ /\* *ax should be ok, reducing distance to *ax *\/ */
1892: /* printf("Warning mnbrak *fb = %lf, *bx=%lf *ax=%lf *fa==%lf iter=%d\n",*fb, *bx, *ax, *fa, iterscale++); */
1893: /* *bx = *ax - (*ax - *bx)/scale; */
1894: /* *fb=(*func)(*bx); /\* xtb[j]=pcom[j]+(*bx)*xicom[j]; fb=f(xtb[j]) *\/ */
1895: /* } */
1896:
1.126 brouard 1897: if (*fb > *fa) {
1898: SHFT(dum,*ax,*bx,dum)
1.183 brouard 1899: SHFT(dum,*fb,*fa,dum)
1900: }
1.126 brouard 1901: *cx=(*bx)+GOLD*(*bx-*ax);
1902: *fc=(*func)(*cx);
1.183 brouard 1903: #ifdef DEBUG
1.224 brouard 1904: printf("mnbrak0 a=%lf *fa=%lf, b=%lf *fb=%lf, c=%lf *fc=%lf\n",*ax,*fa,*bx,*fb,*cx, *fc);
1905: 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 1906: #endif
1.224 brouard 1907: 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 1908: r=(*bx-*ax)*(*fb-*fc);
1.224 brouard 1909: q=(*bx-*cx)*(*fb-*fa); /* What if fa=inf */
1.126 brouard 1910: u=(*bx)-((*bx-*cx)*q-(*bx-*ax)*r)/
1.183 brouard 1911: (2.0*SIGN(FMAX(fabs(q-r),TINY),q-r)); /* Minimum abscissa of a parabolic estimated from (a,fa), (b,fb) and (c,fc). */
1912: ulim=(*bx)+GLIMIT*(*cx-*bx); /* Maximum abscissa where function should be evaluated */
1913: if ((*bx-u)*(u-*cx) > 0.0) { /* if u_p is between b and c */
1.126 brouard 1914: fu=(*func)(u);
1.163 brouard 1915: #ifdef DEBUG
1916: /* f(x)=A(x-u)**2+f(u) */
1917: double A, fparabu;
1918: A= (*fb - *fa)/(*bx-*ax)/(*bx+*ax-2*u);
1919: fparabu= *fa - A*(*ax-u)*(*ax-u);
1.224 brouard 1920: 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);
1921: 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 1922: /* And thus,it can be that fu > *fc even if fparabu < *fc */
1923: /* mnbrak (*ax=7.666299858533, *fa=299039.693133272231), (*bx=8.595447774979, *fb=298976.598289369489),
1924: (*cx=10.098840694817, *fc=298946.631474258087), (*u=9.852501168332, fu=298948.773013752128, fparabu=298945.434711494134) */
1925: /* In that case, there is no bracket in the output! Routine is wrong with many consequences.*/
1.163 brouard 1926: #endif
1.184 brouard 1927: #ifdef MNBRAKORIGINAL
1.183 brouard 1928: #else
1.191 brouard 1929: /* if (fu > *fc) { */
1930: /* #ifdef DEBUG */
1931: /* printf("mnbrak4 fu > fc \n"); */
1932: /* fprintf(ficlog, "mnbrak4 fu > fc\n"); */
1933: /* #endif */
1934: /* /\* 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 *\\/ *\/ */
1935: /* /\* SHFT(*fa,*fc,fu,*fc) /\\* (b, u, c) is a bracket while test fb > fc will be fu > fc will exit *\\/ *\/ */
1936: /* dum=u; /\* Shifting c and u *\/ */
1937: /* u = *cx; */
1938: /* *cx = dum; */
1939: /* dum = fu; */
1940: /* fu = *fc; */
1941: /* *fc =dum; */
1942: /* } else { /\* end *\/ */
1943: /* #ifdef DEBUG */
1944: /* printf("mnbrak3 fu < fc \n"); */
1945: /* fprintf(ficlog, "mnbrak3 fu < fc\n"); */
1946: /* #endif */
1947: /* dum=u; /\* Shifting c and u *\/ */
1948: /* u = *cx; */
1949: /* *cx = dum; */
1950: /* dum = fu; */
1951: /* fu = *fc; */
1952: /* *fc =dum; */
1953: /* } */
1.224 brouard 1954: #ifdef DEBUGMNBRAK
1955: double A, fparabu;
1956: A= (*fb - *fa)/(*bx-*ax)/(*bx+*ax-2*u);
1957: fparabu= *fa - A*(*ax-u)*(*ax-u);
1958: 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);
1959: 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 1960: #endif
1.191 brouard 1961: dum=u; /* Shifting c and u */
1962: u = *cx;
1963: *cx = dum;
1964: dum = fu;
1965: fu = *fc;
1966: *fc =dum;
1.183 brouard 1967: #endif
1.162 brouard 1968: } else if ((*cx-u)*(u-ulim) > 0.0) { /* u is after c but before ulim */
1.183 brouard 1969: #ifdef DEBUG
1.224 brouard 1970: printf("\nmnbrak2 u=%lf after c=%lf but before ulim\n",u,*cx);
1971: fprintf(ficlog,"\nmnbrak2 u=%lf after c=%lf but before ulim\n",u,*cx);
1.183 brouard 1972: #endif
1.126 brouard 1973: fu=(*func)(u);
1974: if (fu < *fc) {
1.183 brouard 1975: #ifdef DEBUG
1.224 brouard 1976: printf("\nmnbrak2 u=%lf after c=%lf but before ulim=%lf AND fu=%lf < %lf=fc\n",u,*cx,ulim,fu, *fc);
1977: fprintf(ficlog,"\nmnbrak2 u=%lf after c=%lf but before ulim=%lf AND fu=%lf < %lf=fc\n",u,*cx,ulim,fu, *fc);
1978: #endif
1979: SHFT(*bx,*cx,u,*cx+GOLD*(*cx-*bx))
1980: SHFT(*fb,*fc,fu,(*func)(u))
1981: #ifdef DEBUG
1982: printf("\nmnbrak2 shift GOLD c=%lf",*cx+GOLD*(*cx-*bx));
1.183 brouard 1983: #endif
1984: }
1.162 brouard 1985: } else if ((u-ulim)*(ulim-*cx) >= 0.0) { /* u outside ulim (verifying that ulim is beyond c) */
1.183 brouard 1986: #ifdef DEBUG
1.224 brouard 1987: printf("\nmnbrak2 u=%lf outside ulim=%lf (verifying that ulim is beyond c=%lf)\n",u,ulim,*cx);
1988: fprintf(ficlog,"\nmnbrak2 u=%lf outside ulim=%lf (verifying that ulim is beyond c=%lf)\n",u,ulim,*cx);
1.183 brouard 1989: #endif
1.126 brouard 1990: u=ulim;
1991: fu=(*func)(u);
1.183 brouard 1992: } else { /* u could be left to b (if r > q parabola has a maximum) */
1993: #ifdef DEBUG
1.224 brouard 1994: printf("\nmnbrak2 u=%lf could be left to b=%lf (if r=%lf > q=%lf parabola has a maximum)\n",u,*bx,r,q);
1995: 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 1996: #endif
1.126 brouard 1997: u=(*cx)+GOLD*(*cx-*bx);
1998: fu=(*func)(u);
1.224 brouard 1999: #ifdef DEBUG
2000: printf("\nmnbrak2 new u=%lf fu=%lf shifted gold left from c=%lf and b=%lf \n",u,fu,*cx,*bx);
2001: fprintf(ficlog,"\nmnbrak2 new u=%lf fu=%lf shifted gold left from c=%lf and b=%lf \n",u,fu,*cx,*bx);
2002: #endif
1.183 brouard 2003: } /* end tests */
1.126 brouard 2004: SHFT(*ax,*bx,*cx,u)
1.183 brouard 2005: SHFT(*fa,*fb,*fc,fu)
2006: #ifdef DEBUG
1.224 brouard 2007: printf("\nmnbrak2 shift (*ax=%.12f, *fa=%.12lf), (*bx=%.12f, *fb=%.12lf), (*cx=%.12f, *fc=%.12lf)\n",*ax,*fa,*bx,*fb,*cx,*fc);
2008: 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 2009: #endif
2010: } /* 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 2011: }
2012:
2013: /*************** linmin ************************/
1.162 brouard 2014: /* Given an n -dimensional point p[1..n] and an n -dimensional direction xi[1..n] , moves and
2015: resets p to where the function func(p) takes on a minimum along the direction xi from p ,
2016: and replaces xi by the actual vector displacement that p was moved. Also returns as fret
2017: the value of func at the returned location p . This is actually all accomplished by calling the
2018: routines mnbrak and brent .*/
1.126 brouard 2019: int ncom;
2020: double *pcom,*xicom;
2021: double (*nrfunc)(double []);
2022:
1.224 brouard 2023: #ifdef LINMINORIGINAL
1.126 brouard 2024: void linmin(double p[], double xi[], int n, double *fret,double (*func)(double []))
1.224 brouard 2025: #else
2026: void linmin(double p[], double xi[], int n, double *fret,double (*func)(double []), int *flat)
2027: #endif
1.126 brouard 2028: {
2029: double brent(double ax, double bx, double cx,
2030: double (*f)(double), double tol, double *xmin);
2031: double f1dim(double x);
2032: void mnbrak(double *ax, double *bx, double *cx, double *fa, double *fb,
2033: double *fc, double (*func)(double));
2034: int j;
2035: double xx,xmin,bx,ax;
2036: double fx,fb,fa;
1.187 brouard 2037:
1.203 brouard 2038: #ifdef LINMINORIGINAL
2039: #else
2040: double scale=10., axs, xxs; /* Scale added for infinity */
2041: #endif
2042:
1.126 brouard 2043: ncom=n;
2044: pcom=vector(1,n);
2045: xicom=vector(1,n);
2046: nrfunc=func;
2047: for (j=1;j<=n;j++) {
2048: pcom[j]=p[j];
1.202 brouard 2049: xicom[j]=xi[j]; /* Former scale xi[j] of currrent direction i */
1.126 brouard 2050: }
1.187 brouard 2051:
1.203 brouard 2052: #ifdef LINMINORIGINAL
2053: xx=1.;
2054: #else
2055: axs=0.0;
2056: xxs=1.;
2057: do{
2058: xx= xxs;
2059: #endif
1.187 brouard 2060: ax=0.;
2061: mnbrak(&ax,&xx,&bx,&fa,&fx,&fb,f1dim); /* Outputs: xtx[j]=pcom[j]+(*xx)*xicom[j]; fx=f(xtx[j]) */
2062: /* brackets with inputs ax=0 and xx=1, but points, pcom=p, and directions values, xicom=xi, are sent via f1dim(x) */
2063: /* 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)) */
2064: /* Outputs: fa=f(p(j)) and fx=f(p(j) + xxs * xi(j) ) and f(bx)= f(p(j)+ bx* xi(j)) */
2065: /* Given input ax=axs and xx=xxs, xx might be too far from ax to get a finite f(xx) */
2066: /* Searches on line, outputs (ax, xx, bx) such that fx < min(fa and fb) */
2067: /* 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 2068: #ifdef LINMINORIGINAL
2069: #else
2070: if (fx != fx){
1.224 brouard 2071: xxs=xxs/scale; /* Trying a smaller xx, closer to initial ax=0 */
2072: printf("|");
2073: fprintf(ficlog,"|");
1.203 brouard 2074: #ifdef DEBUGLINMIN
1.224 brouard 2075: 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 2076: #endif
2077: }
1.224 brouard 2078: }while(fx != fx && xxs > 1.e-5);
1.203 brouard 2079: #endif
2080:
1.191 brouard 2081: #ifdef DEBUGLINMIN
2082: 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 2083: 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 2084: #endif
1.224 brouard 2085: #ifdef LINMINORIGINAL
2086: #else
2087: if(fb == fx){ /* Flat function in the direction */
2088: xmin=xx;
2089: *flat=1;
2090: }else{
2091: *flat=0;
2092: #endif
2093: /*Flat mnbrak2 shift (*ax=0.000000000000, *fa=51626.272983130431), (*bx=-1.618034000000, *fb=51590.149499362531), (*cx=-4.236068025156, *fc=51590.149499362531) */
1.187 brouard 2094: *fret=brent(ax,xx,bx,f1dim,TOL,&xmin); /* Giving a bracketting triplet (ax, xx, bx), find a minimum, xmin, according to f1dim, *fret(xmin),*/
2095: /* fa = f(p[j] + ax * xi[j]), fx = f(p[j] + xx * xi[j]), fb = f(p[j] + bx * xi[j]) */
2096: /* fmin = f(p[j] + xmin * xi[j]) */
2097: /* P+lambda n in that direction (lambdamin), with TOL between abscisses */
2098: /* f1dim(xmin): for (j=1;j<=ncom;j++) xt[j]=pcom[j]+xmin*xicom[j]; */
1.126 brouard 2099: #ifdef DEBUG
1.224 brouard 2100: 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);
2101: 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);
2102: #endif
2103: #ifdef LINMINORIGINAL
2104: #else
2105: }
1.126 brouard 2106: #endif
1.191 brouard 2107: #ifdef DEBUGLINMIN
2108: printf("linmin end ");
1.202 brouard 2109: fprintf(ficlog,"linmin end ");
1.191 brouard 2110: #endif
1.126 brouard 2111: for (j=1;j<=n;j++) {
1.203 brouard 2112: #ifdef LINMINORIGINAL
2113: xi[j] *= xmin;
2114: #else
2115: #ifdef DEBUGLINMIN
2116: if(xxs <1.0)
2117: printf(" before xi[%d]=%12.8f", j,xi[j]);
2118: #endif
2119: 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) */
2120: #ifdef DEBUGLINMIN
2121: if(xxs <1.0)
2122: 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 );
2123: #endif
2124: #endif
1.187 brouard 2125: p[j] += xi[j]; /* Parameters values are updated accordingly */
1.126 brouard 2126: }
1.191 brouard 2127: #ifdef DEBUGLINMIN
1.203 brouard 2128: printf("\n");
1.191 brouard 2129: printf("Comparing last *frec(xmin=%12.8f)=%12.8f from Brent and frec(0.)=%12.8f \n", xmin, *fret, (*func)(p));
1.202 brouard 2130: 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 2131: for (j=1;j<=n;j++) {
1.202 brouard 2132: printf(" xi[%d]= %14.10f p[%d]= %12.7f",j,xi[j],j,p[j]);
2133: fprintf(ficlog," xi[%d]= %14.10f p[%d]= %12.7f",j,xi[j],j,p[j]);
2134: if(j % ncovmodel == 0){
1.191 brouard 2135: printf("\n");
1.202 brouard 2136: fprintf(ficlog,"\n");
2137: }
1.191 brouard 2138: }
1.203 brouard 2139: #else
1.191 brouard 2140: #endif
1.126 brouard 2141: free_vector(xicom,1,n);
2142: free_vector(pcom,1,n);
2143: }
2144:
2145:
2146: /*************** powell ************************/
1.162 brouard 2147: /*
2148: Minimization of a function func of n variables. Input consists of an initial starting point
2149: p[1..n] ; an initial matrix xi[1..n][1..n] , whose columns contain the initial set of di-
2150: rections (usually the n unit vectors); and ftol , the fractional tolerance in the function value
2151: such that failure to decrease by more than this amount on one iteration signals doneness. On
2152: output, p is set to the best point found, xi is the then-current direction set, fret is the returned
2153: function value at p , and iter is the number of iterations taken. The routine linmin is used.
2154: */
1.224 brouard 2155: #ifdef LINMINORIGINAL
2156: #else
2157: int *flatdir; /* Function is vanishing in that direction */
1.225 brouard 2158: int flat=0, flatd=0; /* Function is vanishing in that direction */
1.224 brouard 2159: #endif
1.126 brouard 2160: void powell(double p[], double **xi, int n, double ftol, int *iter, double *fret,
2161: double (*func)(double []))
2162: {
1.224 brouard 2163: #ifdef LINMINORIGINAL
2164: void linmin(double p[], double xi[], int n, double *fret,
1.126 brouard 2165: double (*func)(double []));
1.224 brouard 2166: #else
1.241 brouard 2167: void linmin(double p[], double xi[], int n, double *fret,
2168: double (*func)(double []),int *flat);
1.224 brouard 2169: #endif
1.239 brouard 2170: int i,ibig,j,jk,k;
1.126 brouard 2171: double del,t,*pt,*ptt,*xit;
1.181 brouard 2172: double directest;
1.126 brouard 2173: double fp,fptt;
2174: double *xits;
2175: int niterf, itmp;
1.224 brouard 2176: #ifdef LINMINORIGINAL
2177: #else
2178:
2179: flatdir=ivector(1,n);
2180: for (j=1;j<=n;j++) flatdir[j]=0;
2181: #endif
1.126 brouard 2182:
2183: pt=vector(1,n);
2184: ptt=vector(1,n);
2185: xit=vector(1,n);
2186: xits=vector(1,n);
2187: *fret=(*func)(p);
2188: for (j=1;j<=n;j++) pt[j]=p[j];
1.202 brouard 2189: rcurr_time = time(NULL);
1.126 brouard 2190: for (*iter=1;;++(*iter)) {
1.187 brouard 2191: fp=(*fret); /* From former iteration or initial value */
1.126 brouard 2192: ibig=0;
2193: del=0.0;
1.157 brouard 2194: rlast_time=rcurr_time;
2195: /* (void) gettimeofday(&curr_time,&tzp); */
2196: rcurr_time = time(NULL);
2197: curr_time = *localtime(&rcurr_time);
2198: printf("\nPowell iter=%d -2*LL=%.12f %ld sec. %ld sec.",*iter,*fret, rcurr_time-rlast_time, rcurr_time-rstart_time);fflush(stdout);
2199: fprintf(ficlog,"\nPowell iter=%d -2*LL=%.12f %ld sec. %ld sec.",*iter,*fret,rcurr_time-rlast_time, rcurr_time-rstart_time); fflush(ficlog);
2200: /* fprintf(ficrespow,"%d %.12f %ld",*iter,*fret,curr_time.tm_sec-start_time.tm_sec); */
1.192 brouard 2201: for (i=1;i<=n;i++) {
1.126 brouard 2202: fprintf(ficrespow," %.12lf", p[i]);
2203: }
1.239 brouard 2204: fprintf(ficrespow,"\n");fflush(ficrespow);
2205: printf("\n#model= 1 + age ");
2206: fprintf(ficlog,"\n#model= 1 + age ");
2207: if(nagesqr==1){
1.241 brouard 2208: printf(" + age*age ");
2209: fprintf(ficlog," + age*age ");
1.239 brouard 2210: }
2211: for(j=1;j <=ncovmodel-2;j++){
2212: if(Typevar[j]==0) {
2213: printf(" + V%d ",Tvar[j]);
2214: fprintf(ficlog," + V%d ",Tvar[j]);
2215: }else if(Typevar[j]==1) {
2216: printf(" + V%d*age ",Tvar[j]);
2217: fprintf(ficlog," + V%d*age ",Tvar[j]);
2218: }else if(Typevar[j]==2) {
2219: printf(" + V%d*V%d ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
2220: fprintf(ficlog," + V%d*V%d ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
2221: }
2222: }
1.126 brouard 2223: printf("\n");
1.239 brouard 2224: /* printf("12 47.0114589 0.0154322 33.2424412 0.3279905 2.3731903 */
2225: /* 13 -21.5392400 0.1118147 1.2680506 1.2973408 -1.0663662 */
1.126 brouard 2226: fprintf(ficlog,"\n");
1.239 brouard 2227: for(i=1,jk=1; i <=nlstate; i++){
2228: for(k=1; k <=(nlstate+ndeath); k++){
2229: if (k != i) {
2230: printf("%d%d ",i,k);
2231: fprintf(ficlog,"%d%d ",i,k);
2232: for(j=1; j <=ncovmodel; j++){
2233: printf("%12.7f ",p[jk]);
2234: fprintf(ficlog,"%12.7f ",p[jk]);
2235: jk++;
2236: }
2237: printf("\n");
2238: fprintf(ficlog,"\n");
2239: }
2240: }
2241: }
1.241 brouard 2242: if(*iter <=3 && *iter >1){
1.157 brouard 2243: tml = *localtime(&rcurr_time);
2244: strcpy(strcurr,asctime(&tml));
2245: rforecast_time=rcurr_time;
1.126 brouard 2246: itmp = strlen(strcurr);
2247: if(strcurr[itmp-1]=='\n') /* Windows outputs with a new line */
1.241 brouard 2248: strcurr[itmp-1]='\0';
1.162 brouard 2249: printf("\nConsidering the time needed for the last iteration #%d: %ld seconds,\n",*iter,rcurr_time-rlast_time);
1.157 brouard 2250: fprintf(ficlog,"\nConsidering the time needed for this last iteration #%d: %ld seconds,\n",*iter,rcurr_time-rlast_time);
1.126 brouard 2251: for(niterf=10;niterf<=30;niterf+=10){
1.241 brouard 2252: rforecast_time=rcurr_time+(niterf-*iter)*(rcurr_time-rlast_time);
2253: forecast_time = *localtime(&rforecast_time);
2254: strcpy(strfor,asctime(&forecast_time));
2255: itmp = strlen(strfor);
2256: if(strfor[itmp-1]=='\n')
2257: strfor[itmp-1]='\0';
2258: 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);
2259: 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 2260: }
2261: }
1.187 brouard 2262: for (i=1;i<=n;i++) { /* For each direction i */
2263: for (j=1;j<=n;j++) xit[j]=xi[j][i]; /* Directions stored from previous iteration with previous scales */
1.126 brouard 2264: fptt=(*fret);
2265: #ifdef DEBUG
1.203 brouard 2266: printf("fret=%lf, %lf, %lf \n", *fret, *fret, *fret);
2267: fprintf(ficlog, "fret=%lf, %lf, %lf \n", *fret, *fret, *fret);
1.126 brouard 2268: #endif
1.203 brouard 2269: printf("%d",i);fflush(stdout); /* print direction (parameter) i */
1.126 brouard 2270: fprintf(ficlog,"%d",i);fflush(ficlog);
1.224 brouard 2271: #ifdef LINMINORIGINAL
1.188 brouard 2272: linmin(p,xit,n,fret,func); /* Point p[n]. xit[n] has been loaded for direction i as input.*/
1.224 brouard 2273: #else
2274: linmin(p,xit,n,fret,func,&flat); /* Point p[n]. xit[n] has been loaded for direction i as input.*/
2275: flatdir[i]=flat; /* Function is vanishing in that direction i */
2276: #endif
2277: /* Outputs are fret(new point p) p is updated and xit rescaled */
1.188 brouard 2278: if (fabs(fptt-(*fret)) > del) { /* We are keeping the max gain on each of the n directions */
1.224 brouard 2279: /* because that direction will be replaced unless the gain del is small */
2280: /* in comparison with the 'probable' gain, mu^2, with the last average direction. */
2281: /* Unless the n directions are conjugate some gain in the determinant may be obtained */
2282: /* with the new direction. */
2283: del=fabs(fptt-(*fret));
2284: ibig=i;
1.126 brouard 2285: }
2286: #ifdef DEBUG
2287: printf("%d %.12e",i,(*fret));
2288: fprintf(ficlog,"%d %.12e",i,(*fret));
2289: for (j=1;j<=n;j++) {
1.224 brouard 2290: xits[j]=FMAX(fabs(p[j]-pt[j]),1.e-5);
2291: printf(" x(%d)=%.12e",j,xit[j]);
2292: fprintf(ficlog," x(%d)=%.12e",j,xit[j]);
1.126 brouard 2293: }
2294: for(j=1;j<=n;j++) {
1.225 brouard 2295: printf(" p(%d)=%.12e",j,p[j]);
2296: fprintf(ficlog," p(%d)=%.12e",j,p[j]);
1.126 brouard 2297: }
2298: printf("\n");
2299: fprintf(ficlog,"\n");
2300: #endif
1.187 brouard 2301: } /* end loop on each direction i */
2302: /* Convergence test will use last linmin estimation (fret) and compare former iteration (fp) */
1.188 brouard 2303: /* But p and xit have been updated at the end of linmin, *fret corresponds to new p, xit */
1.187 brouard 2304: /* New value of last point Pn is not computed, P(n-1) */
1.224 brouard 2305: for(j=1;j<=n;j++) {
1.225 brouard 2306: if(flatdir[j] >0){
2307: printf(" p(%d)=%lf flat=%d ",j,p[j],flatdir[j]);
2308: fprintf(ficlog," p(%d)=%lf flat=%d ",j,p[j],flatdir[j]);
2309: }
2310: /* printf("\n"); */
2311: /* fprintf(ficlog,"\n"); */
2312: }
1.243 brouard 2313: /* if (2.0*fabs(fp-(*fret)) <= ftol*(fabs(fp)+fabs(*fret))) { /\* Did we reach enough precision? *\/ */
2314: if (2.0*fabs(fp-(*fret)) <= ftol) { /* Did we reach enough precision? */
1.188 brouard 2315: /* We could compare with a chi^2. chisquare(0.95,ddl=1)=3.84 */
2316: /* By adding age*age in a model, the new -2LL should be lower and the difference follows a */
2317: /* a chisquare statistics with 1 degree. To be significant at the 95% level, it should have */
2318: /* decreased of more than 3.84 */
2319: /* By adding age*age and V1*age the gain (-2LL) should be more than 5.99 (ddl=2) */
2320: /* By using V1+V2+V3, the gain should be 7.82, compared with basic 1+age. */
2321: /* By adding 10 parameters more the gain should be 18.31 */
1.224 brouard 2322:
1.188 brouard 2323: /* Starting the program with initial values given by a former maximization will simply change */
2324: /* the scales of the directions and the directions, because the are reset to canonical directions */
2325: /* Thus the first calls to linmin will give new points and better maximizations until fp-(*fret) is */
2326: /* under the tolerance value. If the tolerance is very small 1.e-9, it could last long. */
1.126 brouard 2327: #ifdef DEBUG
2328: int k[2],l;
2329: k[0]=1;
2330: k[1]=-1;
2331: printf("Max: %.12e",(*func)(p));
2332: fprintf(ficlog,"Max: %.12e",(*func)(p));
2333: for (j=1;j<=n;j++) {
2334: printf(" %.12e",p[j]);
2335: fprintf(ficlog," %.12e",p[j]);
2336: }
2337: printf("\n");
2338: fprintf(ficlog,"\n");
2339: for(l=0;l<=1;l++) {
2340: for (j=1;j<=n;j++) {
2341: ptt[j]=p[j]+(p[j]-pt[j])*k[l];
2342: printf("l=%d j=%d ptt=%.12e, xits=%.12e, p=%.12e, xit=%.12e", l,j,ptt[j],xits[j],p[j],xit[j]);
2343: fprintf(ficlog,"l=%d j=%d ptt=%.12e, xits=%.12e, p=%.12e, xit=%.12e", l,j,ptt[j],xits[j],p[j],xit[j]);
2344: }
2345: printf("func(ptt)=%.12e, deriv=%.12e\n",(*func)(ptt),(ptt[j]-p[j])/((*func)(ptt)-(*func)(p)));
2346: fprintf(ficlog,"func(ptt)=%.12e, deriv=%.12e\n",(*func)(ptt),(ptt[j]-p[j])/((*func)(ptt)-(*func)(p)));
2347: }
2348: #endif
2349:
1.224 brouard 2350: #ifdef LINMINORIGINAL
2351: #else
2352: free_ivector(flatdir,1,n);
2353: #endif
1.126 brouard 2354: free_vector(xit,1,n);
2355: free_vector(xits,1,n);
2356: free_vector(ptt,1,n);
2357: free_vector(pt,1,n);
2358: return;
1.192 brouard 2359: } /* enough precision */
1.240 brouard 2360: if (*iter == ITMAX*n) nrerror("powell exceeding maximum iterations.");
1.181 brouard 2361: for (j=1;j<=n;j++) { /* Computes the extrapolated point P_0 + 2 (P_n-P_0) */
1.126 brouard 2362: ptt[j]=2.0*p[j]-pt[j];
2363: xit[j]=p[j]-pt[j];
2364: pt[j]=p[j];
2365: }
1.181 brouard 2366: fptt=(*func)(ptt); /* f_3 */
1.224 brouard 2367: #ifdef NODIRECTIONCHANGEDUNTILNITER /* No change in drections until some iterations are done */
2368: if (*iter <=4) {
1.225 brouard 2369: #else
2370: #endif
1.224 brouard 2371: #ifdef POWELLNOF3INFF1TEST /* skips test F3 <F1 */
1.192 brouard 2372: #else
1.161 brouard 2373: if (fptt < fp) { /* If extrapolated point is better, decide if we keep that new direction or not */
1.192 brouard 2374: #endif
1.162 brouard 2375: /* (x1 f1=fp), (x2 f2=*fret), (x3 f3=fptt), (xm fm) */
1.161 brouard 2376: /* From x1 (P0) distance of x2 is at h and x3 is 2h */
1.162 brouard 2377: /* Let f"(x2) be the 2nd derivative equal everywhere. */
2378: /* Then the parabolic through (x1,f1), (x2,f2) and (x3,f3) */
2379: /* will reach at f3 = fm + h^2/2 f"m ; f" = (f1 -2f2 +f3 ) / h**2 */
1.224 brouard 2380: /* Conditional for using this new direction is that mu^2 = (f1-2f2+f3)^2 /2 < del or directest <0 */
2381: /* also lamda^2=(f1-f2)^2/mu² is a parasite solution of powell */
2382: /* For powell, inclusion of this average direction is only if t(del)<0 or del inbetween mu^2 and lambda^2 */
1.161 brouard 2383: /* t=2.0*(fp-2.0*(*fret)+fptt)*SQR(fp-(*fret)-del)-del*SQR(fp-fptt); */
1.224 brouard 2384: /* Even if f3 <f1, directest can be negative and t >0 */
2385: /* mu² and del² are equal when f3=f1 */
2386: /* f3 < f1 : mu² < del <= lambda^2 both test are equivalent */
2387: /* f3 < f1 : mu² < lambda^2 < del then directtest is negative and powell t is positive */
2388: /* f3 > f1 : lambda² < mu^2 < del then t is negative and directest >0 */
2389: /* f3 > f1 : lambda² < del < mu^2 then t is positive and directest >0 */
1.183 brouard 2390: #ifdef NRCORIGINAL
2391: t=2.0*(fp-2.0*(*fret)+fptt)*SQR(fp-(*fret)-del)- del*SQR(fp-fptt); /* Original Numerical Recipes in C*/
2392: #else
2393: 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 2394: t= t- del*SQR(fp-fptt);
1.183 brouard 2395: #endif
1.202 brouard 2396: directest = fp-2.0*(*fret)+fptt - 2.0 * del; /* If delta was big enough we change it for a new direction */
1.161 brouard 2397: #ifdef DEBUG
1.181 brouard 2398: 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);
2399: 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 2400: printf("t3= %.12lf, t4= %.12lf, t3*= %.12lf, t4*= %.12lf\n",SQR(fp-(*fret)-del),SQR(fp-fptt),
2401: (fp-(*fret)-del)*(fp-(*fret)-del),(fp-fptt)*(fp-fptt));
2402: fprintf(ficlog,"t3= %.12lf, t4= %.12lf, t3*= %.12lf, t4*= %.12lf\n",SQR(fp-(*fret)-del),SQR(fp-fptt),
2403: (fp-(*fret)-del)*(fp-(*fret)-del),(fp-fptt)*(fp-fptt));
2404: 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);
2405: 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);
2406: #endif
1.183 brouard 2407: #ifdef POWELLORIGINAL
2408: if (t < 0.0) { /* Then we use it for new direction */
2409: #else
1.182 brouard 2410: if (directest*t < 0.0) { /* Contradiction between both tests */
1.224 brouard 2411: 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 2412: 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 2413: 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 2414: fprintf(ficlog,"f1-2f2+f3= %.12lf, f1-f2-del= %.12lf, f1-f3= %.12lf\n",fp-2.0*(*fret)+fptt, fp -(*fret) -del, fp-fptt);
2415: }
1.181 brouard 2416: if (directest < 0.0) { /* Then we use it for new direction */
2417: #endif
1.191 brouard 2418: #ifdef DEBUGLINMIN
1.234 brouard 2419: printf("Before linmin in direction P%d-P0\n",n);
2420: for (j=1;j<=n;j++) {
2421: printf(" Before xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
2422: fprintf(ficlog," Before xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
2423: if(j % ncovmodel == 0){
2424: printf("\n");
2425: fprintf(ficlog,"\n");
2426: }
2427: }
1.224 brouard 2428: #endif
2429: #ifdef LINMINORIGINAL
1.234 brouard 2430: linmin(p,xit,n,fret,func); /* computes minimum on the extrapolated direction: changes p and rescales xit.*/
1.224 brouard 2431: #else
1.234 brouard 2432: linmin(p,xit,n,fret,func,&flat); /* computes minimum on the extrapolated direction: changes p and rescales xit.*/
2433: flatdir[i]=flat; /* Function is vanishing in that direction i */
1.191 brouard 2434: #endif
1.234 brouard 2435:
1.191 brouard 2436: #ifdef DEBUGLINMIN
1.234 brouard 2437: for (j=1;j<=n;j++) {
2438: printf("After xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
2439: fprintf(ficlog,"After xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
2440: if(j % ncovmodel == 0){
2441: printf("\n");
2442: fprintf(ficlog,"\n");
2443: }
2444: }
1.224 brouard 2445: #endif
1.234 brouard 2446: for (j=1;j<=n;j++) {
2447: xi[j][ibig]=xi[j][n]; /* Replace direction with biggest decrease by last direction n */
2448: xi[j][n]=xit[j]; /* and this nth direction by the by the average p_0 p_n */
2449: }
1.224 brouard 2450: #ifdef LINMINORIGINAL
2451: #else
1.234 brouard 2452: for (j=1, flatd=0;j<=n;j++) {
2453: if(flatdir[j]>0)
2454: flatd++;
2455: }
2456: if(flatd >0){
1.255 brouard 2457: printf("%d flat directions: ",flatd);
2458: fprintf(ficlog,"%d flat directions :",flatd);
1.234 brouard 2459: for (j=1;j<=n;j++) {
2460: if(flatdir[j]>0){
2461: printf("%d ",j);
2462: fprintf(ficlog,"%d ",j);
2463: }
2464: }
2465: printf("\n");
2466: fprintf(ficlog,"\n");
2467: }
1.191 brouard 2468: #endif
1.234 brouard 2469: printf("Gaining to use new average direction of P0 P%d instead of biggest increase direction %d :\n",n,ibig);
2470: fprintf(ficlog,"Gaining to use new average direction of P0 P%d instead of biggest increase direction %d :\n",n,ibig);
2471:
1.126 brouard 2472: #ifdef DEBUG
1.234 brouard 2473: printf("Direction changed last moved %d in place of ibig=%d, new last is the average:\n",n,ibig);
2474: fprintf(ficlog,"Direction changed last moved %d in place of ibig=%d, new last is the average:\n",n,ibig);
2475: for(j=1;j<=n;j++){
2476: printf(" %lf",xit[j]);
2477: fprintf(ficlog," %lf",xit[j]);
2478: }
2479: printf("\n");
2480: fprintf(ficlog,"\n");
1.126 brouard 2481: #endif
1.192 brouard 2482: } /* end of t or directest negative */
1.224 brouard 2483: #ifdef POWELLNOF3INFF1TEST
1.192 brouard 2484: #else
1.234 brouard 2485: } /* end if (fptt < fp) */
1.192 brouard 2486: #endif
1.225 brouard 2487: #ifdef NODIRECTIONCHANGEDUNTILNITER /* No change in drections until some iterations are done */
1.234 brouard 2488: } /*NODIRECTIONCHANGEDUNTILNITER No change in drections until some iterations are done */
1.225 brouard 2489: #else
1.224 brouard 2490: #endif
1.234 brouard 2491: } /* loop iteration */
1.126 brouard 2492: }
1.234 brouard 2493:
1.126 brouard 2494: /**** Prevalence limit (stable or period prevalence) ****************/
1.234 brouard 2495:
1.235 brouard 2496: 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 2497: {
1.235 brouard 2498: /* Computes the prevalence limit in each live state at age x and for covariate combination ij
2499: (and selected quantitative values in nres)
2500: by left multiplying the unit
1.234 brouard 2501: matrix by transitions matrix until convergence is reached with precision ftolpl */
1.206 brouard 2502: /* Wx= Wx-1 Px-1= Wx-2 Px-2 Px-1 = Wx-n Px-n ... Px-2 Px-1 I */
2503: /* Wx is row vector: population in state 1, population in state 2, population dead */
2504: /* or prevalence in state 1, prevalence in state 2, 0 */
2505: /* newm is the matrix after multiplications, its rows are identical at a factor */
2506: /* Initial matrix pimij */
2507: /* {0.85204250825084937, 0.13044499163996345, 0.017512500109187184, */
2508: /* 0.090851990222114765, 0.88271245433047185, 0.026435555447413338, */
2509: /* 0, 0 , 1} */
2510: /*
2511: * and after some iteration: */
2512: /* {0.45504275246439968, 0.42731458730878791, 0.11764266022681241, */
2513: /* 0.45201005341706885, 0.42865420071559901, 0.11933574586733192, */
2514: /* 0, 0 , 1} */
2515: /* And prevalence by suppressing the deaths are close to identical rows in prlim: */
2516: /* {0.51571254859325999, 0.4842874514067399, */
2517: /* 0.51326036147820708, 0.48673963852179264} */
2518: /* If we start from prlim again, prlim tends to a constant matrix */
1.234 brouard 2519:
1.126 brouard 2520: int i, ii,j,k;
1.209 brouard 2521: double *min, *max, *meandiff, maxmax,sumnew=0.;
1.145 brouard 2522: /* double **matprod2(); */ /* test */
1.218 brouard 2523: double **out, cov[NCOVMAX+1], **pmij(); /* **pmmij is a global variable feeded with oldms etc */
1.126 brouard 2524: double **newm;
1.209 brouard 2525: double agefin, delaymax=200. ; /* 100 Max number of years to converge */
1.203 brouard 2526: int ncvloop=0;
1.169 brouard 2527:
1.209 brouard 2528: min=vector(1,nlstate);
2529: max=vector(1,nlstate);
2530: meandiff=vector(1,nlstate);
2531:
1.218 brouard 2532: /* Starting with matrix unity */
1.126 brouard 2533: for (ii=1;ii<=nlstate+ndeath;ii++)
2534: for (j=1;j<=nlstate+ndeath;j++){
2535: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
2536: }
1.169 brouard 2537:
2538: cov[1]=1.;
2539:
2540: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
1.202 brouard 2541: /* Start at agefin= age, computes the matrix of passage and loops decreasing agefin until convergence is reached */
1.126 brouard 2542: for(agefin=age-stepm/YEARM; agefin>=age-delaymax; agefin=agefin-stepm/YEARM){
1.202 brouard 2543: ncvloop++;
1.126 brouard 2544: newm=savm;
2545: /* Covariates have to be included here again */
1.138 brouard 2546: cov[2]=agefin;
1.187 brouard 2547: if(nagesqr==1)
2548: cov[3]= agefin*agefin;;
1.234 brouard 2549: for (k=1; k<=nsd;k++) { /* For single dummy covariates only */
2550: /* Here comes the value of the covariate 'ij' after renumbering k with single dummy covariates */
2551: cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,k)];
1.235 brouard 2552: /* 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 2553: }
2554: for (k=1; k<=nsq;k++) { /* For single varying covariates only */
2555: /* Here comes the value of quantitative after renumbering k with single quantitative covariates */
1.235 brouard 2556: cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k];
2557: /* 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 2558: }
1.237 brouard 2559: for (k=1; k<=cptcovage;k++){ /* For product with age */
1.234 brouard 2560: if(Dummy[Tvar[Tage[k]]]){
2561: cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2];
2562: } else{
1.235 brouard 2563: cov[2+nagesqr+Tage[k]]=Tqresult[nres][k];
1.234 brouard 2564: }
1.235 brouard 2565: /* 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 2566: }
1.237 brouard 2567: for (k=1; k<=cptcovprod;k++){ /* For product without age */
1.235 brouard 2568: /* 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 2569: if(Dummy[Tvard[k][1]==0]){
2570: if(Dummy[Tvard[k][2]==0]){
2571: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)];
2572: }else{
2573: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * Tqresult[nres][k];
2574: }
2575: }else{
2576: if(Dummy[Tvard[k][2]==0]){
2577: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][2]][codtabm(ij,k)] * Tqinvresult[nres][Tvard[k][1]];
2578: }else{
2579: cov[2+nagesqr+Tprod[k]]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]];
2580: }
2581: }
1.234 brouard 2582: }
1.138 brouard 2583: /*printf("ij=%d cptcovprod=%d tvar=%d ", ij, cptcovprod, Tvar[1]);*/
2584: /*printf("ij=%d cov[3]=%lf cov[4]=%lf \n",ij, cov[3],cov[4]);*/
2585: /*printf("ij=%d cov[3]=%lf \n",ij, cov[3]);*/
1.145 brouard 2586: /* savm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
2587: /* out=matprod2(newm, pmij(pmmij,cov,ncovmodel,x,nlstate),1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); /\* Bug Valgrind *\/ */
1.218 brouard 2588: /* age and covariate values of ij are in 'cov' */
1.142 brouard 2589: out=matprod2(newm, pmij(pmmij,cov,ncovmodel,x,nlstate),1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); /* Bug Valgrind */
1.138 brouard 2590:
1.126 brouard 2591: savm=oldm;
2592: oldm=newm;
1.209 brouard 2593:
2594: for(j=1; j<=nlstate; j++){
2595: max[j]=0.;
2596: min[j]=1.;
2597: }
2598: for(i=1;i<=nlstate;i++){
2599: sumnew=0;
2600: for(k=1; k<=ndeath; k++) sumnew+=newm[i][nlstate+k];
2601: for(j=1; j<=nlstate; j++){
2602: prlim[i][j]= newm[i][j]/(1-sumnew);
2603: max[j]=FMAX(max[j],prlim[i][j]);
2604: min[j]=FMIN(min[j],prlim[i][j]);
2605: }
2606: }
2607:
1.126 brouard 2608: maxmax=0.;
1.209 brouard 2609: for(j=1; j<=nlstate; j++){
2610: meandiff[j]=(max[j]-min[j])/(max[j]+min[j])*2.; /* mean difference for each column */
2611: maxmax=FMAX(maxmax,meandiff[j]);
2612: /* 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 2613: } /* j loop */
1.203 brouard 2614: *ncvyear= (int)age- (int)agefin;
1.208 brouard 2615: /* 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 2616: if(maxmax < ftolpl){
1.209 brouard 2617: /* printf("maxmax=%lf ncvloop=%ld, age=%d, agefin=%d ncvyear=%d \n", maxmax, ncvloop, (int)age, (int)agefin, *ncvyear); */
2618: free_vector(min,1,nlstate);
2619: free_vector(max,1,nlstate);
2620: free_vector(meandiff,1,nlstate);
1.126 brouard 2621: return prlim;
2622: }
1.169 brouard 2623: } /* age loop */
1.208 brouard 2624: /* After some age loop it doesn't converge */
1.209 brouard 2625: 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 2626: 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 2627: /* 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); */
2628: free_vector(min,1,nlstate);
2629: free_vector(max,1,nlstate);
2630: free_vector(meandiff,1,nlstate);
1.208 brouard 2631:
1.169 brouard 2632: return prlim; /* should not reach here */
1.126 brouard 2633: }
2634:
1.217 brouard 2635:
2636: /**** Back Prevalence limit (stable or period prevalence) ****************/
2637:
1.218 brouard 2638: /* 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) */
2639: /* 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 2640: double **bprevalim(double **bprlim, double ***prevacurrent, int nlstate, double x[], double age, double ftolpl, int *ncvyear, int ij, int nres)
1.217 brouard 2641: {
1.264 brouard 2642: /* 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 2643: matrix by transitions matrix until convergence is reached with precision ftolpl */
2644: /* Wx= Wx-1 Px-1= Wx-2 Px-2 Px-1 = Wx-n Px-n ... Px-2 Px-1 I */
2645: /* Wx is row vector: population in state 1, population in state 2, population dead */
2646: /* or prevalence in state 1, prevalence in state 2, 0 */
2647: /* newm is the matrix after multiplications, its rows are identical at a factor */
2648: /* Initial matrix pimij */
2649: /* {0.85204250825084937, 0.13044499163996345, 0.017512500109187184, */
2650: /* 0.090851990222114765, 0.88271245433047185, 0.026435555447413338, */
2651: /* 0, 0 , 1} */
2652: /*
2653: * and after some iteration: */
2654: /* {0.45504275246439968, 0.42731458730878791, 0.11764266022681241, */
2655: /* 0.45201005341706885, 0.42865420071559901, 0.11933574586733192, */
2656: /* 0, 0 , 1} */
2657: /* And prevalence by suppressing the deaths are close to identical rows in prlim: */
2658: /* {0.51571254859325999, 0.4842874514067399, */
2659: /* 0.51326036147820708, 0.48673963852179264} */
2660: /* If we start from prlim again, prlim tends to a constant matrix */
2661:
2662: int i, ii,j,k;
1.247 brouard 2663: int first=0;
1.217 brouard 2664: double *min, *max, *meandiff, maxmax,sumnew=0.;
2665: /* double **matprod2(); */ /* test */
2666: double **out, cov[NCOVMAX+1], **bmij();
2667: double **newm;
1.218 brouard 2668: double **dnewm, **doldm, **dsavm; /* for use */
2669: double **oldm, **savm; /* for use */
2670:
1.217 brouard 2671: double agefin, delaymax=200. ; /* 100 Max number of years to converge */
2672: int ncvloop=0;
2673:
2674: min=vector(1,nlstate);
2675: max=vector(1,nlstate);
2676: meandiff=vector(1,nlstate);
2677:
1.266 brouard 2678: dnewm=ddnewms; doldm=ddoldms; dsavm=ddsavms;
2679: oldm=oldms; savm=savms;
2680:
2681: /* Starting with matrix unity */
2682: for (ii=1;ii<=nlstate+ndeath;ii++)
2683: for (j=1;j<=nlstate+ndeath;j++){
1.217 brouard 2684: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
2685: }
2686:
2687: cov[1]=1.;
2688:
2689: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
2690: /* Start at agefin= age, computes the matrix of passage and loops decreasing agefin until convergence is reached */
1.218 brouard 2691: /* for(agefin=age+stepm/YEARM; agefin<=age+delaymax; agefin=agefin+stepm/YEARM){ /\* A changer en age *\/ */
2692: for(agefin=age; agefin<AGESUP; agefin=agefin+stepm/YEARM){ /* A changer en age */
1.217 brouard 2693: ncvloop++;
1.218 brouard 2694: newm=savm; /* oldm should be kept from previous iteration or unity at start */
2695: /* newm points to the allocated table savm passed by the function it can be written, savm could be reallocated */
1.217 brouard 2696: /* Covariates have to be included here again */
2697: cov[2]=agefin;
2698: if(nagesqr==1)
2699: cov[3]= agefin*agefin;;
1.242 brouard 2700: for (k=1; k<=nsd;k++) { /* For single dummy covariates only */
2701: /* Here comes the value of the covariate 'ij' after renumbering k with single dummy covariates */
2702: cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,k)];
1.264 brouard 2703: /* 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 2704: }
2705: /* for (k=1; k<=cptcovn;k++) { */
2706: /* /\* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,Tvar[k])]; *\/ */
2707: /* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,k)]; */
2708: /* /\* 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])]); *\/ */
2709: /* } */
2710: for (k=1; k<=nsq;k++) { /* For single varying covariates only */
2711: /* Here comes the value of quantitative after renumbering k with single quantitative covariates */
2712: cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k];
2713: /* 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]); */
2714: }
2715: /* for (k=1; k<=cptcovage;k++) cov[2+nagesqr+Tage[k]]=nbcode[Tvar[k]][codtabm(ij,k)]*cov[2]; */
2716: /* for (k=1; k<=cptcovprod;k++) /\* Useless *\/ */
2717: /* /\* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])]; *\/ */
2718: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)]; */
2719: for (k=1; k<=cptcovage;k++){ /* For product with age */
2720: if(Dummy[Tvar[Tage[k]]]){
2721: cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2];
2722: } else{
2723: cov[2+nagesqr+Tage[k]]=Tqresult[nres][k];
2724: }
2725: /* 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]); */
2726: }
2727: for (k=1; k<=cptcovprod;k++){ /* For product without age */
2728: /* 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]); */
2729: if(Dummy[Tvard[k][1]==0]){
2730: if(Dummy[Tvard[k][2]==0]){
2731: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)];
2732: }else{
2733: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * Tqresult[nres][k];
2734: }
2735: }else{
2736: if(Dummy[Tvard[k][2]==0]){
2737: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][2]][codtabm(ij,k)] * Tqinvresult[nres][Tvard[k][1]];
2738: }else{
2739: cov[2+nagesqr+Tprod[k]]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]];
2740: }
2741: }
1.217 brouard 2742: }
2743:
2744: /*printf("ij=%d cptcovprod=%d tvar=%d ", ij, cptcovprod, Tvar[1]);*/
2745: /*printf("ij=%d cov[3]=%lf cov[4]=%lf \n",ij, cov[3],cov[4]);*/
2746: /*printf("ij=%d cov[3]=%lf \n",ij, cov[3]);*/
2747: /* savm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
2748: /* out=matprod2(newm, pmij(pmmij,cov,ncovmodel,x,nlstate),1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); /\* Bug Valgrind *\/ */
1.218 brouard 2749: /* ij should be linked to the correct index of cov */
2750: /* age and covariate values ij are in 'cov', but we need to pass
2751: * ij for the observed prevalence at age and status and covariate
2752: * number: prevacurrent[(int)agefin][ii][ij]
2753: */
2754: /* 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 *\/ */
2755: /* 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 *\/ */
2756: 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 2757: /* if((int)age == 86 || (int)age == 87){ */
1.266 brouard 2758: /* printf(" Backward prevalim age=%d agefin=%d \n", (int) age, (int) agefin); */
2759: /* for(i=1; i<=nlstate+ndeath; i++) { */
2760: /* printf("%d newm= ",i); */
2761: /* for(j=1;j<=nlstate+ndeath;j++) { */
2762: /* printf("%f ",newm[i][j]); */
2763: /* } */
2764: /* printf("oldm * "); */
2765: /* for(j=1;j<=nlstate+ndeath;j++) { */
2766: /* printf("%f ",oldm[i][j]); */
2767: /* } */
1.268 brouard 2768: /* printf(" bmmij "); */
1.266 brouard 2769: /* for(j=1;j<=nlstate+ndeath;j++) { */
2770: /* printf("%f ",pmmij[i][j]); */
2771: /* } */
2772: /* printf("\n"); */
2773: /* } */
2774: /* } */
1.217 brouard 2775: savm=oldm;
2776: oldm=newm;
1.266 brouard 2777:
1.217 brouard 2778: for(j=1; j<=nlstate; j++){
2779: max[j]=0.;
2780: min[j]=1.;
2781: }
2782: for(j=1; j<=nlstate; j++){
2783: for(i=1;i<=nlstate;i++){
1.234 brouard 2784: /* bprlim[i][j]= newm[i][j]/(1-sumnew); */
2785: bprlim[i][j]= newm[i][j];
2786: max[i]=FMAX(max[i],bprlim[i][j]); /* Max in line */
2787: min[i]=FMIN(min[i],bprlim[i][j]);
1.217 brouard 2788: }
2789: }
1.218 brouard 2790:
1.217 brouard 2791: maxmax=0.;
2792: for(i=1; i<=nlstate; i++){
2793: meandiff[i]=(max[i]-min[i])/(max[i]+min[i])*2.; /* mean difference for each column */
2794: maxmax=FMAX(maxmax,meandiff[i]);
2795: /* 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 2796: } /* i loop */
1.217 brouard 2797: *ncvyear= -( (int)age- (int)agefin);
1.268 brouard 2798: /* printf("Back maxmax=%lf ncvloop=%d, age=%d, agefin=%d ncvyear=%d \n", maxmax, ncvloop, (int)age, (int)agefin, *ncvyear); */
1.217 brouard 2799: if(maxmax < ftolpl){
1.220 brouard 2800: /* printf("OK Back maxmax=%lf ncvloop=%d, age=%d, agefin=%d ncvyear=%d \n", maxmax, ncvloop, (int)age, (int)agefin, *ncvyear); */
1.217 brouard 2801: free_vector(min,1,nlstate);
2802: free_vector(max,1,nlstate);
2803: free_vector(meandiff,1,nlstate);
2804: return bprlim;
2805: }
2806: } /* age loop */
2807: /* After some age loop it doesn't converge */
1.247 brouard 2808: if(first){
2809: first=1;
2810: 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\
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: }
2813: 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 2814: 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);
2815: /* 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); */
2816: free_vector(min,1,nlstate);
2817: free_vector(max,1,nlstate);
2818: free_vector(meandiff,1,nlstate);
2819:
2820: return bprlim; /* should not reach here */
2821: }
2822:
1.126 brouard 2823: /*************** transition probabilities ***************/
2824:
2825: double **pmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate )
2826: {
1.138 brouard 2827: /* According to parameters values stored in x and the covariate's values stored in cov,
1.266 brouard 2828: computes the probability to be observed in state j (after stepm years) being in state i by appying the
1.138 brouard 2829: model to the ncovmodel covariates (including constant and age).
2830: lnpijopii=ln(pij/pii)= aij+bij*age+cij*v1+dij*v2+... = sum_nc=1^ncovmodel xij(nc)*cov[nc]
2831: and, according on how parameters are entered, the position of the coefficient xij(nc) of the
2832: ncth covariate in the global vector x is given by the formula:
2833: j<i nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel
2834: j>=i nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel
2835: Computes ln(pij/pii) (lnpijopii), deduces pij/pii by exponentiation,
2836: sums on j different of i to get 1-pii/pii, deduces pii, and then all pij.
1.266 brouard 2837: Outputs ps[i][j] or probability to be observed in j being in i according to
1.138 brouard 2838: the values of the covariates cov[nc] and corresponding parameter values x[nc+shiftij]
1.266 brouard 2839: Sum on j ps[i][j] should equal to 1.
1.138 brouard 2840: */
2841: double s1, lnpijopii;
1.126 brouard 2842: /*double t34;*/
1.164 brouard 2843: int i,j, nc, ii, jj;
1.126 brouard 2844:
1.223 brouard 2845: for(i=1; i<= nlstate; i++){
2846: for(j=1; j<i;j++){
2847: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
2848: /*lnpijopii += param[i][j][nc]*cov[nc];*/
2849: lnpijopii += x[nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel]*cov[nc];
2850: /* printf("Int j<i s1=%.17e, lnpijopii=%.17e\n",s1,lnpijopii); */
2851: }
2852: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
2853: /* printf("s1=%.17e, lnpijopii=%.17e\n",s1,lnpijopii); */
2854: }
2855: for(j=i+1; j<=nlstate+ndeath;j++){
2856: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
2857: /*lnpijopii += x[(i-1)*nlstate*ncovmodel+(j-2)*ncovmodel+nc+(i-1)*(ndeath-1)*ncovmodel]*cov[nc];*/
2858: lnpijopii += x[nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel]*cov[nc];
2859: /* printf("Int j>i s1=%.17e, lnpijopii=%.17e %lx %lx\n",s1,lnpijopii,s1,lnpijopii); */
2860: }
2861: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
2862: }
2863: }
1.218 brouard 2864:
1.223 brouard 2865: for(i=1; i<= nlstate; i++){
2866: s1=0;
2867: for(j=1; j<i; j++){
2868: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
2869: /*printf("debug1 %d %d ps=%lf exp(ps)=%lf s1+=%lf\n",i,j,ps[i][j],exp(ps[i][j]),s1); */
2870: }
2871: for(j=i+1; j<=nlstate+ndeath; j++){
2872: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
2873: /*printf("debug2 %d %d ps=%lf exp(ps)=%lf s1+=%lf\n",i,j,ps[i][j],exp(ps[i][j]),s1); */
2874: }
2875: /* s1= sum_{j<>i} pij/pii=(1-pii)/pii and thus pii is known from s1 */
2876: ps[i][i]=1./(s1+1.);
2877: /* Computing other pijs */
2878: for(j=1; j<i; j++)
2879: ps[i][j]= exp(ps[i][j])*ps[i][i];
2880: for(j=i+1; j<=nlstate+ndeath; j++)
2881: ps[i][j]= exp(ps[i][j])*ps[i][i];
2882: /* ps[i][nlstate+1]=1.-s1- ps[i][i];*/ /* Sum should be 1 */
2883: } /* end i */
1.218 brouard 2884:
1.223 brouard 2885: for(ii=nlstate+1; ii<= nlstate+ndeath; ii++){
2886: for(jj=1; jj<= nlstate+ndeath; jj++){
2887: ps[ii][jj]=0;
2888: ps[ii][ii]=1;
2889: }
2890: }
1.218 brouard 2891:
2892:
1.223 brouard 2893: /* for(ii=1; ii<= nlstate+ndeath; ii++){ */
2894: /* for(jj=1; jj<= nlstate+ndeath; jj++){ */
2895: /* printf(" pmij ps[%d][%d]=%lf ",ii,jj,ps[ii][jj]); */
2896: /* } */
2897: /* printf("\n "); */
2898: /* } */
2899: /* printf("\n ");printf("%lf ",cov[2]);*/
2900: /*
2901: for(i=1; i<= npar; i++) printf("%f ",x[i]);
1.218 brouard 2902: goto end;*/
1.266 brouard 2903: return ps; /* Pointer is unchanged since its call */
1.126 brouard 2904: }
2905:
1.218 brouard 2906: /*************** backward transition probabilities ***************/
2907:
2908: /* 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 ) */
2909: /* double **bmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate, double ***prevacurrent, double ***dnewm, double **doldm, double **dsavm, int ij ) */
2910: double **bmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate, double ***prevacurrent, int ij )
2911: {
1.266 brouard 2912: /* Computes the backward probability at age agefin and covariate combination ij. In fact cov is already filled and x too.
2913: * 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 2914: */
1.218 brouard 2915: int i, ii, j,k;
1.222 brouard 2916:
2917: double **out, **pmij();
2918: double sumnew=0.;
1.218 brouard 2919: double agefin;
1.268 brouard 2920: 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 2921: double **dnewm, **dsavm, **doldm;
2922: double **bbmij;
2923:
1.218 brouard 2924: doldm=ddoldms; /* global pointers */
1.222 brouard 2925: dnewm=ddnewms;
2926: dsavm=ddsavms;
2927:
2928: agefin=cov[2];
1.268 brouard 2929: /* Bx = Diag(w_x) P_x Diag(Sum_i w^i_x p^ij_x */
1.222 brouard 2930: /* bmij *//* age is cov[2], ij is included in cov, but we need for
1.266 brouard 2931: the observed prevalence (with this covariate ij) at beginning of transition */
2932: /* dsavm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
1.268 brouard 2933:
2934: /* P_x */
1.266 brouard 2935: pmmij=pmij(pmmij,cov,ncovmodel,x,nlstate); /*This is forward probability from agefin to agefin + stepm */
1.268 brouard 2936: /* outputs pmmij which is a stochastic matrix in row */
2937:
2938: /* Diag(w_x) */
2939: /* Problem with prevacurrent which can be zero */
2940: sumnew=0.;
1.269 brouard 2941: /*for (ii=1;ii<=nlstate+ndeath;ii++){*/
1.268 brouard 2942: for (ii=1;ii<=nlstate;ii++){ /* Only on live states */
1.269 brouard 2943: /* printf(" agefin=%d, ii=%d, ij=%d, prev=%f\n",(int)agefin,ii, ij, prevacurrent[(int)agefin][ii][ij]); */
1.268 brouard 2944: sumnew+=prevacurrent[(int)agefin][ii][ij];
2945: }
2946: if(sumnew >0.01){ /* At least some value in the prevalence */
2947: for (ii=1;ii<=nlstate+ndeath;ii++){
2948: for (j=1;j<=nlstate+ndeath;j++)
1.269 brouard 2949: doldm[ii][j]=(ii==j ? prevacurrent[(int)agefin][ii][ij]/sumnew : 0.0);
1.268 brouard 2950: }
2951: }else{
2952: for (ii=1;ii<=nlstate+ndeath;ii++){
2953: for (j=1;j<=nlstate+ndeath;j++)
2954: doldm[ii][j]=(ii==j ? 1./nlstate : 0.0);
2955: }
2956: /* if(sumnew <0.9){ */
2957: /* printf("Problem internal bmij B: sum on i wi <0.9: j=%d, sum_i wi=%lf,agefin=%d\n",j,sumnew, (int)agefin); */
2958: /* } */
2959: }
2960: k3=0.0; /* We put the last diagonal to 0 */
2961: for (ii=nlstate+1;ii<=nlstate+ndeath;ii++){
2962: doldm[ii][ii]= k3;
2963: }
2964: /* End doldm, At the end doldm is diag[(w_i)] */
2965:
2966: /* left Product of this diag matrix by pmmij=Px (dnewm=dsavm*doldm) */
2967: bbmij=matprod2(dnewm, doldm,1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, pmmij); /* Bug Valgrind */
2968:
2969: /* Diag(Sum_i w^i_x p^ij_x */
2970: /* 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 2971: for (j=1;j<=nlstate+ndeath;j++){
1.268 brouard 2972: sumnew=0.;
1.222 brouard 2973: for (ii=1;ii<=nlstate;ii++){
1.266 brouard 2974: /* sumnew+=dsavm[ii][j]*prevacurrent[(int)agefin][ii][ij]; */
1.268 brouard 2975: sumnew+=pmmij[ii][j]*doldm[ii][ii]; /* Yes prevalence at beginning of transition */
1.222 brouard 2976: } /* sumnew is (N11+N21)/N..= N.1/N.. = sum on i of w_i pij */
1.268 brouard 2977: for (ii=1;ii<=nlstate+ndeath;ii++){
1.222 brouard 2978: /* if(agefin >= agemaxpar && agefin <= agemaxpar+stepm/YEARM){ */
1.268 brouard 2979: /* dsavm[ii][j]=(ii==j ? 1./sumnew : 0.0); */
1.222 brouard 2980: /* }else if(agefin >= agemaxpar+stepm/YEARM){ */
1.268 brouard 2981: /* dsavm[ii][j]=(ii==j ? 1./sumnew : 0.0); */
1.222 brouard 2982: /* }else */
1.268 brouard 2983: dsavm[ii][j]=(ii==j ? 1./sumnew : 0.0);
2984: } /*End ii */
2985: } /* 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 */
2986:
2987: ps=matprod2(ps, dnewm,1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, dsavm); /* Bug Valgrind */
2988: /* ps is now diag[w_i] * Px * diag [1/(w_1p1i+w_2 p2i)] */
1.222 brouard 2989: /* end bmij */
1.266 brouard 2990: return ps; /*pointer is unchanged */
1.218 brouard 2991: }
1.217 brouard 2992: /*************** transition probabilities ***************/
2993:
1.218 brouard 2994: double **bpmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate )
1.217 brouard 2995: {
2996: /* According to parameters values stored in x and the covariate's values stored in cov,
2997: computes the probability to be observed in state j being in state i by appying the
2998: model to the ncovmodel covariates (including constant and age).
2999: lnpijopii=ln(pij/pii)= aij+bij*age+cij*v1+dij*v2+... = sum_nc=1^ncovmodel xij(nc)*cov[nc]
3000: and, according on how parameters are entered, the position of the coefficient xij(nc) of the
3001: ncth covariate in the global vector x is given by the formula:
3002: j<i nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel
3003: j>=i nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel
3004: Computes ln(pij/pii) (lnpijopii), deduces pij/pii by exponentiation,
3005: sums on j different of i to get 1-pii/pii, deduces pii, and then all pij.
3006: Outputs ps[i][j] the probability to be observed in j being in j according to
3007: the values of the covariates cov[nc] and corresponding parameter values x[nc+shiftij]
3008: */
3009: double s1, lnpijopii;
3010: /*double t34;*/
3011: int i,j, nc, ii, jj;
3012:
1.234 brouard 3013: for(i=1; i<= nlstate; i++){
3014: for(j=1; j<i;j++){
3015: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
3016: /*lnpijopii += param[i][j][nc]*cov[nc];*/
3017: lnpijopii += x[nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel]*cov[nc];
3018: /* printf("Int j<i s1=%.17e, lnpijopii=%.17e\n",s1,lnpijopii); */
3019: }
3020: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
3021: /* printf("s1=%.17e, lnpijopii=%.17e\n",s1,lnpijopii); */
3022: }
3023: for(j=i+1; j<=nlstate+ndeath;j++){
3024: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
3025: /*lnpijopii += x[(i-1)*nlstate*ncovmodel+(j-2)*ncovmodel+nc+(i-1)*(ndeath-1)*ncovmodel]*cov[nc];*/
3026: lnpijopii += x[nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel]*cov[nc];
3027: /* printf("Int j>i s1=%.17e, lnpijopii=%.17e %lx %lx\n",s1,lnpijopii,s1,lnpijopii); */
3028: }
3029: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
3030: }
3031: }
3032:
3033: for(i=1; i<= nlstate; i++){
3034: s1=0;
3035: for(j=1; j<i; j++){
3036: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
3037: /*printf("debug1 %d %d ps=%lf exp(ps)=%lf s1+=%lf\n",i,j,ps[i][j],exp(ps[i][j]),s1); */
3038: }
3039: for(j=i+1; j<=nlstate+ndeath; j++){
3040: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
3041: /*printf("debug2 %d %d ps=%lf exp(ps)=%lf s1+=%lf\n",i,j,ps[i][j],exp(ps[i][j]),s1); */
3042: }
3043: /* s1= sum_{j<>i} pij/pii=(1-pii)/pii and thus pii is known from s1 */
3044: ps[i][i]=1./(s1+1.);
3045: /* Computing other pijs */
3046: for(j=1; j<i; j++)
3047: ps[i][j]= exp(ps[i][j])*ps[i][i];
3048: for(j=i+1; j<=nlstate+ndeath; j++)
3049: ps[i][j]= exp(ps[i][j])*ps[i][i];
3050: /* ps[i][nlstate+1]=1.-s1- ps[i][i];*/ /* Sum should be 1 */
3051: } /* end i */
3052:
3053: for(ii=nlstate+1; ii<= nlstate+ndeath; ii++){
3054: for(jj=1; jj<= nlstate+ndeath; jj++){
3055: ps[ii][jj]=0;
3056: ps[ii][ii]=1;
3057: }
3058: }
3059: /* Added for backcast */ /* Transposed matrix too */
3060: for(jj=1; jj<= nlstate+ndeath; jj++){
3061: s1=0.;
3062: for(ii=1; ii<= nlstate+ndeath; ii++){
3063: s1+=ps[ii][jj];
3064: }
3065: for(ii=1; ii<= nlstate; ii++){
3066: ps[ii][jj]=ps[ii][jj]/s1;
3067: }
3068: }
3069: /* Transposition */
3070: for(jj=1; jj<= nlstate+ndeath; jj++){
3071: for(ii=jj; ii<= nlstate+ndeath; ii++){
3072: s1=ps[ii][jj];
3073: ps[ii][jj]=ps[jj][ii];
3074: ps[jj][ii]=s1;
3075: }
3076: }
3077: /* for(ii=1; ii<= nlstate+ndeath; ii++){ */
3078: /* for(jj=1; jj<= nlstate+ndeath; jj++){ */
3079: /* printf(" pmij ps[%d][%d]=%lf ",ii,jj,ps[ii][jj]); */
3080: /* } */
3081: /* printf("\n "); */
3082: /* } */
3083: /* printf("\n ");printf("%lf ",cov[2]);*/
3084: /*
3085: for(i=1; i<= npar; i++) printf("%f ",x[i]);
3086: goto end;*/
3087: return ps;
1.217 brouard 3088: }
3089:
3090:
1.126 brouard 3091: /**************** Product of 2 matrices ******************/
3092:
1.145 brouard 3093: double **matprod2(double **out, double **in,int nrl, int nrh, int ncl, int nch, int ncolol, int ncoloh, double **b)
1.126 brouard 3094: {
3095: /* Computes the matrix product of in(1,nrh-nrl+1)(1,nch-ncl+1) times
3096: b(1,nch-ncl+1)(1,ncoloh-ncolol+1) into out(...) */
3097: /* in, b, out are matrice of pointers which should have been initialized
3098: before: only the contents of out is modified. The function returns
3099: a pointer to pointers identical to out */
1.145 brouard 3100: int i, j, k;
1.126 brouard 3101: for(i=nrl; i<= nrh; i++)
1.145 brouard 3102: for(k=ncolol; k<=ncoloh; k++){
3103: out[i][k]=0.;
3104: for(j=ncl; j<=nch; j++)
3105: out[i][k] +=in[i][j]*b[j][k];
3106: }
1.126 brouard 3107: return out;
3108: }
3109:
3110:
3111: /************* Higher Matrix Product ***************/
3112:
1.235 brouard 3113: 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 3114: {
1.218 brouard 3115: /* Computes the transition matrix starting at age 'age' and combination of covariate values corresponding to ij over
1.126 brouard 3116: 'nhstepm*hstepm*stepm' months (i.e. until
3117: age (in years) age+nhstepm*hstepm*stepm/12) by multiplying
3118: nhstepm*hstepm matrices.
3119: Output is stored in matrix po[i][j][h] for h every 'hstepm' step
3120: (typically every 2 years instead of every month which is too big
3121: for the memory).
3122: Model is determined by parameters x and covariates have to be
3123: included manually here.
3124:
3125: */
3126:
3127: int i, j, d, h, k;
1.131 brouard 3128: double **out, cov[NCOVMAX+1];
1.126 brouard 3129: double **newm;
1.187 brouard 3130: double agexact;
1.214 brouard 3131: double agebegin, ageend;
1.126 brouard 3132:
3133: /* Hstepm could be zero and should return the unit matrix */
3134: for (i=1;i<=nlstate+ndeath;i++)
3135: for (j=1;j<=nlstate+ndeath;j++){
3136: oldm[i][j]=(i==j ? 1.0 : 0.0);
3137: po[i][j][0]=(i==j ? 1.0 : 0.0);
3138: }
3139: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
3140: for(h=1; h <=nhstepm; h++){
3141: for(d=1; d <=hstepm; d++){
3142: newm=savm;
3143: /* Covariates have to be included here again */
3144: cov[1]=1.;
1.214 brouard 3145: agexact=age+((h-1)*hstepm + (d-1))*stepm/YEARM; /* age just before transition */
1.187 brouard 3146: cov[2]=agexact;
3147: if(nagesqr==1)
1.227 brouard 3148: cov[3]= agexact*agexact;
1.235 brouard 3149: for (k=1; k<=nsd;k++) { /* For single dummy covariates only */
3150: /* Here comes the value of the covariate 'ij' after renumbering k with single dummy covariates */
3151: cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,k)];
3152: /* 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)); */
3153: }
3154: for (k=1; k<=nsq;k++) { /* For single varying covariates only */
3155: /* Here comes the value of quantitative after renumbering k with single quantitative covariates */
3156: cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k];
3157: /* 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]); */
3158: }
3159: for (k=1; k<=cptcovage;k++){
3160: if(Dummy[Tvar[Tage[k]]]){
3161: cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2];
3162: } else{
3163: cov[2+nagesqr+Tage[k]]=Tqresult[nres][k];
3164: }
3165: /* 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]); */
3166: }
3167: for (k=1; k<=cptcovprod;k++){ /* */
3168: /* 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]); */
3169: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)];
3170: }
3171: /* for (k=1; k<=cptcovn;k++) */
3172: /* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,k)]; */
3173: /* for (k=1; k<=cptcovage;k++) /\* Should start at cptcovn+1 *\/ */
3174: /* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2]; */
3175: /* for (k=1; k<=cptcovprod;k++) /\* Useless because included in cptcovn *\/ */
3176: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)]*nbcode[Tvard[k][2]][codtabm(ij,k)]; */
1.227 brouard 3177:
3178:
1.126 brouard 3179: /*printf("hxi cptcov=%d cptcode=%d\n",cptcov,cptcode);*/
3180: /*printf("h=%d d=%d age=%f cov=%f\n",h,d,age,cov[2]);*/
1.218 brouard 3181: /* right multiplication of oldm by the current matrix */
1.126 brouard 3182: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath,
3183: pmij(pmmij,cov,ncovmodel,x,nlstate));
1.217 brouard 3184: /* if((int)age == 70){ */
3185: /* printf(" Forward hpxij age=%d agexact=%f d=%d nhstepm=%d hstepm=%d\n", (int) age, agexact, d, nhstepm, hstepm); */
3186: /* for(i=1; i<=nlstate+ndeath; i++) { */
3187: /* printf("%d pmmij ",i); */
3188: /* for(j=1;j<=nlstate+ndeath;j++) { */
3189: /* printf("%f ",pmmij[i][j]); */
3190: /* } */
3191: /* printf(" oldm "); */
3192: /* for(j=1;j<=nlstate+ndeath;j++) { */
3193: /* printf("%f ",oldm[i][j]); */
3194: /* } */
3195: /* printf("\n"); */
3196: /* } */
3197: /* } */
1.126 brouard 3198: savm=oldm;
3199: oldm=newm;
3200: }
3201: for(i=1; i<=nlstate+ndeath; i++)
3202: for(j=1;j<=nlstate+ndeath;j++) {
1.267 brouard 3203: po[i][j][h]=newm[i][j];
3204: /*if(h==nhstepm) printf("po[%d][%d][%d]=%f ",i,j,h,po[i][j][h]);*/
1.126 brouard 3205: }
1.128 brouard 3206: /*printf("h=%d ",h);*/
1.126 brouard 3207: } /* end h */
1.267 brouard 3208: /* printf("\n H=%d \n",h); */
1.126 brouard 3209: return po;
3210: }
3211:
1.217 brouard 3212: /************* Higher Back Matrix Product ***************/
1.218 brouard 3213: /* 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 3214: 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 3215: {
1.266 brouard 3216: /* For a combination of dummy covariate ij, computes the transition matrix starting at age 'age' over
1.217 brouard 3217: 'nhstepm*hstepm*stepm' months (i.e. until
1.218 brouard 3218: age (in years) age+nhstepm*hstepm*stepm/12) by multiplying
3219: nhstepm*hstepm matrices.
3220: Output is stored in matrix po[i][j][h] for h every 'hstepm' step
3221: (typically every 2 years instead of every month which is too big
1.217 brouard 3222: for the memory).
1.218 brouard 3223: Model is determined by parameters x and covariates have to be
1.266 brouard 3224: included manually here. Then we use a call to bmij(x and cov)
3225: The addresss of po (p3mat allocated to the dimension of nhstepm) should be stored for output
1.222 brouard 3226: */
1.217 brouard 3227:
3228: int i, j, d, h, k;
1.266 brouard 3229: double **out, cov[NCOVMAX+1], **bmij();
3230: double **newm, ***newmm;
1.217 brouard 3231: double agexact;
3232: double agebegin, ageend;
1.222 brouard 3233: double **oldm, **savm;
1.217 brouard 3234:
1.266 brouard 3235: newmm=po; /* To be saved */
3236: oldm=oldms;savm=savms; /* Global pointers */
1.217 brouard 3237: /* Hstepm could be zero and should return the unit matrix */
3238: for (i=1;i<=nlstate+ndeath;i++)
3239: for (j=1;j<=nlstate+ndeath;j++){
3240: oldm[i][j]=(i==j ? 1.0 : 0.0);
3241: po[i][j][0]=(i==j ? 1.0 : 0.0);
3242: }
3243: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
3244: for(h=1; h <=nhstepm; h++){
3245: for(d=1; d <=hstepm; d++){
3246: newm=savm;
3247: /* Covariates have to be included here again */
3248: cov[1]=1.;
1.271 brouard 3249: agexact=age-( (h-1)*hstepm + (d) )*stepm/YEARM; /* age just before transition, d or d-1? */
1.217 brouard 3250: /* agexact=age+((h-1)*hstepm + (d-1))*stepm/YEARM; /\* age just before transition *\/ */
3251: cov[2]=agexact;
3252: if(nagesqr==1)
1.222 brouard 3253: cov[3]= agexact*agexact;
1.266 brouard 3254: for (k=1; k<=cptcovn;k++){
3255: /* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,k)]; */
3256: /* /\* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,Tvar[k])]; *\/ */
3257: cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,k)];
3258: /* 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)); */
3259: }
1.267 brouard 3260: for (k=1; k<=nsq;k++) { /* For single varying covariates only */
3261: /* Here comes the value of quantitative after renumbering k with single quantitative covariates */
3262: cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k];
3263: /* 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]); */
3264: }
3265: for (k=1; k<=cptcovage;k++){ /* Should start at cptcovn+1 */
3266: if(Dummy[Tvar[Tage[k]]]){
3267: cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2];
3268: } else{
3269: cov[2+nagesqr+Tage[k]]=Tqresult[nres][k];
3270: }
3271: /* 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]); */
3272: }
3273: for (k=1; k<=cptcovprod;k++){ /* Useless because included in cptcovn */
1.222 brouard 3274: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)]*nbcode[Tvard[k][2]][codtabm(ij,k)];
1.267 brouard 3275: }
1.217 brouard 3276: /*printf("hxi cptcov=%d cptcode=%d\n",cptcov,cptcode);*/
3277: /*printf("h=%d d=%d age=%f cov=%f\n",h,d,age,cov[2]);*/
1.267 brouard 3278:
1.218 brouard 3279: /* Careful transposed matrix */
1.266 brouard 3280: /* age is in cov[2], prevacurrent at beginning of transition. */
1.218 brouard 3281: /* out=matprod2(newm, bmij(pmmij,cov,ncovmodel,x,nlstate,prevacurrent, dnewm, doldm, dsavm,ij),\ */
1.222 brouard 3282: /* 1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); */
1.218 brouard 3283: out=matprod2(newm, bmij(pmmij,cov,ncovmodel,x,nlstate,prevacurrent,ij),\
1.222 brouard 3284: 1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm);
1.217 brouard 3285: /* if((int)age == 70){ */
3286: /* printf(" Backward hbxij age=%d agexact=%f d=%d nhstepm=%d hstepm=%d\n", (int) age, agexact, d, nhstepm, hstepm); */
3287: /* for(i=1; i<=nlstate+ndeath; i++) { */
3288: /* printf("%d pmmij ",i); */
3289: /* for(j=1;j<=nlstate+ndeath;j++) { */
3290: /* printf("%f ",pmmij[i][j]); */
3291: /* } */
3292: /* printf(" oldm "); */
3293: /* for(j=1;j<=nlstate+ndeath;j++) { */
3294: /* printf("%f ",oldm[i][j]); */
3295: /* } */
3296: /* printf("\n"); */
3297: /* } */
3298: /* } */
3299: savm=oldm;
3300: oldm=newm;
3301: }
3302: for(i=1; i<=nlstate+ndeath; i++)
3303: for(j=1;j<=nlstate+ndeath;j++) {
1.222 brouard 3304: po[i][j][h]=newm[i][j];
1.268 brouard 3305: /* if(h==nhstepm) */
3306: /* printf("po[%d][%d][%d]=%f ",i,j,h,po[i][j][h]); */
1.217 brouard 3307: }
1.268 brouard 3308: /* printf("h=%d %.1f ",h, agexact); */
1.217 brouard 3309: } /* end h */
1.268 brouard 3310: /* printf("\n H=%d nhs=%d \n",h, nhstepm); */
1.217 brouard 3311: return po;
3312: }
3313:
3314:
1.162 brouard 3315: #ifdef NLOPT
3316: double myfunc(unsigned n, const double *p1, double *grad, void *pd){
3317: double fret;
3318: double *xt;
3319: int j;
3320: myfunc_data *d2 = (myfunc_data *) pd;
3321: /* xt = (p1-1); */
3322: xt=vector(1,n);
3323: for (j=1;j<=n;j++) xt[j]=p1[j-1]; /* xt[1]=p1[0] */
3324:
3325: fret=(d2->function)(xt); /* p xt[1]@8 is fine */
3326: /* fret=(*func)(xt); /\* p xt[1]@8 is fine *\/ */
3327: printf("Function = %.12lf ",fret);
3328: for (j=1;j<=n;j++) printf(" %d %.8lf", j, xt[j]);
3329: printf("\n");
3330: free_vector(xt,1,n);
3331: return fret;
3332: }
3333: #endif
1.126 brouard 3334:
3335: /*************** log-likelihood *************/
3336: double func( double *x)
3337: {
1.226 brouard 3338: int i, ii, j, k, mi, d, kk;
3339: int ioffset=0;
3340: double l, ll[NLSTATEMAX+1], cov[NCOVMAX+1];
3341: double **out;
3342: double lli; /* Individual log likelihood */
3343: int s1, s2;
1.228 brouard 3344: 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 3345: double bbh, survp;
3346: long ipmx;
3347: double agexact;
3348: /*extern weight */
3349: /* We are differentiating ll according to initial status */
3350: /* for (i=1;i<=npar;i++) printf("%f ", x[i]);*/
3351: /*for(i=1;i<imx;i++)
3352: printf(" %d\n",s[4][i]);
3353: */
1.162 brouard 3354:
1.226 brouard 3355: ++countcallfunc;
1.162 brouard 3356:
1.226 brouard 3357: cov[1]=1.;
1.126 brouard 3358:
1.226 brouard 3359: for(k=1; k<=nlstate; k++) ll[k]=0.;
1.224 brouard 3360: ioffset=0;
1.226 brouard 3361: if(mle==1){
3362: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
3363: /* Computes the values of the ncovmodel covariates of the model
3364: depending if the covariates are fixed or varying (age dependent) and stores them in cov[]
3365: Then computes with function pmij which return a matrix p[i][j] giving the elementary probability
3366: to be observed in j being in i according to the model.
3367: */
1.243 brouard 3368: ioffset=2+nagesqr ;
1.233 brouard 3369: /* Fixed */
1.234 brouard 3370: for (k=1; k<=ncovf;k++){ /* Simple and product fixed covariates without age* products */
3371: 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)*/
3372: }
1.226 brouard 3373: /* In model V2+V1*V4+age*V3+V3*V2 Tvar[1] is V2, Tvar[2=V1*V4]
3374: is 6, Tvar[3=age*V3] should not be computed because of age Tvar[4=V3*V2]
3375: has been calculated etc */
3376: /* For an individual i, wav[i] gives the number of effective waves */
3377: /* We compute the contribution to Likelihood of each effective transition
3378: mw[mi][i] is real wave of the mi th effectve wave */
3379: /* Then statuses are computed at each begin and end of an effective wave s1=s[ mw[mi][i] ][i];
3380: s2=s[mw[mi+1][i]][i];
3381: And the iv th varying covariate is the cotvar[mw[mi+1][i]][iv][i]
3382: But if the variable is not in the model TTvar[iv] is the real variable effective in the model:
3383: meaning that decodemodel should be used cotvar[mw[mi+1][i]][TTvar[iv]][i]
3384: */
3385: for(mi=1; mi<= wav[i]-1; mi++){
1.234 brouard 3386: for(k=1; k <= ncovv ; k++){ /* Varying covariates (single and product but no age )*/
1.242 brouard 3387: /* cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]][i]; */
3388: cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]-ncovcol-nqv][i];
1.234 brouard 3389: }
3390: for (ii=1;ii<=nlstate+ndeath;ii++)
3391: for (j=1;j<=nlstate+ndeath;j++){
3392: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
3393: savm[ii][j]=(ii==j ? 1.0 : 0.0);
3394: }
3395: for(d=0; d<dh[mi][i]; d++){
3396: newm=savm;
3397: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
3398: cov[2]=agexact;
3399: if(nagesqr==1)
3400: cov[3]= agexact*agexact; /* Should be changed here */
3401: for (kk=1; kk<=cptcovage;kk++) {
1.242 brouard 3402: if(!FixedV[Tvar[Tage[kk]]])
1.234 brouard 3403: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact; /* Tage[kk] gives the data-covariate associated with age */
1.242 brouard 3404: else
3405: cov[Tage[kk]+2+nagesqr]=cotvar[mw[mi][i]][Tvar[Tage[kk]]-ncovcol-nqv][i]*agexact;
1.234 brouard 3406: }
3407: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
3408: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
3409: savm=oldm;
3410: oldm=newm;
3411: } /* end mult */
3412:
3413: /*lli=log(out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]);*/ /* Original formula */
3414: /* But now since version 0.9 we anticipate for bias at large stepm.
3415: * If stepm is larger than one month (smallest stepm) and if the exact delay
3416: * (in months) between two waves is not a multiple of stepm, we rounded to
3417: * the nearest (and in case of equal distance, to the lowest) interval but now
3418: * we keep into memory the bias bh[mi][i] and also the previous matrix product
3419: * (i.e to dh[mi][i]-1) saved in 'savm'. Then we inter(extra)polate the
3420: * probability in order to take into account the bias as a fraction of the way
1.231 brouard 3421: * from savm to out if bh is negative or even beyond if bh is positive. bh varies
3422: * -stepm/2 to stepm/2 .
3423: * For stepm=1 the results are the same as for previous versions of Imach.
3424: * For stepm > 1 the results are less biased than in previous versions.
3425: */
1.234 brouard 3426: s1=s[mw[mi][i]][i];
3427: s2=s[mw[mi+1][i]][i];
3428: bbh=(double)bh[mi][i]/(double)stepm;
3429: /* bias bh is positive if real duration
3430: * is higher than the multiple of stepm and negative otherwise.
3431: */
3432: /* lli= (savm[s1][s2]>1.e-8 ?(1.+bbh)*log(out[s1][s2])- bbh*log(savm[s1][s2]):log((1.+bbh)*out[s1][s2]));*/
3433: if( s2 > nlstate){
3434: /* i.e. if s2 is a death state and if the date of death is known
3435: then the contribution to the likelihood is the probability to
3436: die between last step unit time and current step unit time,
3437: which is also equal to probability to die before dh
3438: minus probability to die before dh-stepm .
3439: In version up to 0.92 likelihood was computed
3440: as if date of death was unknown. Death was treated as any other
3441: health state: the date of the interview describes the actual state
3442: and not the date of a change in health state. The former idea was
3443: to consider that at each interview the state was recorded
3444: (healthy, disable or death) and IMaCh was corrected; but when we
3445: introduced the exact date of death then we should have modified
3446: the contribution of an exact death to the likelihood. This new
3447: contribution is smaller and very dependent of the step unit
3448: stepm. It is no more the probability to die between last interview
3449: and month of death but the probability to survive from last
3450: interview up to one month before death multiplied by the
3451: probability to die within a month. Thanks to Chris
3452: Jackson for correcting this bug. Former versions increased
3453: mortality artificially. The bad side is that we add another loop
3454: which slows down the processing. The difference can be up to 10%
3455: lower mortality.
3456: */
3457: /* If, at the beginning of the maximization mostly, the
3458: cumulative probability or probability to be dead is
3459: constant (ie = 1) over time d, the difference is equal to
3460: 0. out[s1][3] = savm[s1][3]: probability, being at state
3461: s1 at precedent wave, to be dead a month before current
3462: wave is equal to probability, being at state s1 at
3463: precedent wave, to be dead at mont of the current
3464: wave. Then the observed probability (that this person died)
3465: is null according to current estimated parameter. In fact,
3466: it should be very low but not zero otherwise the log go to
3467: infinity.
3468: */
1.183 brouard 3469: /* #ifdef INFINITYORIGINAL */
3470: /* lli=log(out[s1][s2] - savm[s1][s2]); */
3471: /* #else */
3472: /* if ((out[s1][s2] - savm[s1][s2]) < mytinydouble) */
3473: /* lli=log(mytinydouble); */
3474: /* else */
3475: /* lli=log(out[s1][s2] - savm[s1][s2]); */
3476: /* #endif */
1.226 brouard 3477: lli=log(out[s1][s2] - savm[s1][s2]);
1.216 brouard 3478:
1.226 brouard 3479: } else if ( s2==-1 ) { /* alive */
3480: for (j=1,survp=0. ; j<=nlstate; j++)
3481: survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j];
3482: /*survp += out[s1][j]; */
3483: lli= log(survp);
3484: }
3485: else if (s2==-4) {
3486: for (j=3,survp=0. ; j<=nlstate; j++)
3487: survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j];
3488: lli= log(survp);
3489: }
3490: else if (s2==-5) {
3491: for (j=1,survp=0. ; j<=2; j++)
3492: survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j];
3493: lli= log(survp);
3494: }
3495: else{
3496: lli= log((1.+bbh)*out[s1][s2]- bbh*savm[s1][s2]); /* linear interpolation */
3497: /* 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 */
3498: }
3499: /*lli=(1.+bbh)*log(out[s1][s2])- bbh*log(savm[s1][s2]);*/
3500: /*if(lli ==000.0)*/
3501: /*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); */
3502: ipmx +=1;
3503: sw += weight[i];
3504: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
3505: /* if (lli < log(mytinydouble)){ */
3506: /* 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); */
3507: /* 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]); */
3508: /* } */
3509: } /* end of wave */
3510: } /* end of individual */
3511: } else if(mle==2){
3512: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
3513: for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i];
3514: for(mi=1; mi<= wav[i]-1; mi++){
3515: for (ii=1;ii<=nlstate+ndeath;ii++)
3516: for (j=1;j<=nlstate+ndeath;j++){
3517: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
3518: savm[ii][j]=(ii==j ? 1.0 : 0.0);
3519: }
3520: for(d=0; d<=dh[mi][i]; d++){
3521: newm=savm;
3522: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
3523: cov[2]=agexact;
3524: if(nagesqr==1)
3525: cov[3]= agexact*agexact;
3526: for (kk=1; kk<=cptcovage;kk++) {
3527: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
3528: }
3529: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
3530: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
3531: savm=oldm;
3532: oldm=newm;
3533: } /* end mult */
3534:
3535: s1=s[mw[mi][i]][i];
3536: s2=s[mw[mi+1][i]][i];
3537: bbh=(double)bh[mi][i]/(double)stepm;
3538: lli= (savm[s1][s2]>(double)1.e-8 ?log((1.+bbh)*out[s1][s2]- bbh*(savm[s1][s2])):log((1.+bbh)*out[s1][s2])); /* linear interpolation */
3539: ipmx +=1;
3540: sw += weight[i];
3541: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
3542: } /* end of wave */
3543: } /* end of individual */
3544: } else if(mle==3){ /* exponential inter-extrapolation */
3545: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
3546: for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i];
3547: for(mi=1; mi<= wav[i]-1; mi++){
3548: for (ii=1;ii<=nlstate+ndeath;ii++)
3549: for (j=1;j<=nlstate+ndeath;j++){
3550: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
3551: savm[ii][j]=(ii==j ? 1.0 : 0.0);
3552: }
3553: for(d=0; d<dh[mi][i]; d++){
3554: newm=savm;
3555: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
3556: cov[2]=agexact;
3557: if(nagesqr==1)
3558: cov[3]= agexact*agexact;
3559: for (kk=1; kk<=cptcovage;kk++) {
3560: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
3561: }
3562: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
3563: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
3564: savm=oldm;
3565: oldm=newm;
3566: } /* end mult */
3567:
3568: s1=s[mw[mi][i]][i];
3569: s2=s[mw[mi+1][i]][i];
3570: bbh=(double)bh[mi][i]/(double)stepm;
3571: 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 */
3572: ipmx +=1;
3573: sw += weight[i];
3574: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
3575: } /* end of wave */
3576: } /* end of individual */
3577: }else if (mle==4){ /* ml=4 no inter-extrapolation */
3578: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
3579: for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i];
3580: for(mi=1; mi<= wav[i]-1; mi++){
3581: for (ii=1;ii<=nlstate+ndeath;ii++)
3582: for (j=1;j<=nlstate+ndeath;j++){
3583: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
3584: savm[ii][j]=(ii==j ? 1.0 : 0.0);
3585: }
3586: for(d=0; d<dh[mi][i]; d++){
3587: newm=savm;
3588: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
3589: cov[2]=agexact;
3590: if(nagesqr==1)
3591: cov[3]= agexact*agexact;
3592: for (kk=1; kk<=cptcovage;kk++) {
3593: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
3594: }
1.126 brouard 3595:
1.226 brouard 3596: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
3597: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
3598: savm=oldm;
3599: oldm=newm;
3600: } /* end mult */
3601:
3602: s1=s[mw[mi][i]][i];
3603: s2=s[mw[mi+1][i]][i];
3604: if( s2 > nlstate){
3605: lli=log(out[s1][s2] - savm[s1][s2]);
3606: } else if ( s2==-1 ) { /* alive */
3607: for (j=1,survp=0. ; j<=nlstate; j++)
3608: survp += out[s1][j];
3609: lli= log(survp);
3610: }else{
3611: lli=log(out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]); /* Original formula */
3612: }
3613: ipmx +=1;
3614: sw += weight[i];
3615: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
1.126 brouard 3616: /* 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 3617: } /* end of wave */
3618: } /* end of individual */
3619: }else{ /* ml=5 no inter-extrapolation no jackson =0.8a */
3620: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
3621: for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i];
3622: for(mi=1; mi<= wav[i]-1; mi++){
3623: for (ii=1;ii<=nlstate+ndeath;ii++)
3624: for (j=1;j<=nlstate+ndeath;j++){
3625: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
3626: savm[ii][j]=(ii==j ? 1.0 : 0.0);
3627: }
3628: for(d=0; d<dh[mi][i]; d++){
3629: newm=savm;
3630: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
3631: cov[2]=agexact;
3632: if(nagesqr==1)
3633: cov[3]= agexact*agexact;
3634: for (kk=1; kk<=cptcovage;kk++) {
3635: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
3636: }
1.126 brouard 3637:
1.226 brouard 3638: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
3639: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
3640: savm=oldm;
3641: oldm=newm;
3642: } /* end mult */
3643:
3644: s1=s[mw[mi][i]][i];
3645: s2=s[mw[mi+1][i]][i];
3646: lli=log(out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]); /* Original formula */
3647: ipmx +=1;
3648: sw += weight[i];
3649: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
3650: /*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]);*/
3651: } /* end of wave */
3652: } /* end of individual */
3653: } /* End of if */
3654: for(k=1,l=0.; k<=nlstate; k++) l += ll[k];
3655: /* printf("l1=%f l2=%f ",ll[1],ll[2]); */
3656: l= l*ipmx/sw; /* To get the same order of magnitude as if weight=1 for every body */
3657: return -l;
1.126 brouard 3658: }
3659:
3660: /*************** log-likelihood *************/
3661: double funcone( double *x)
3662: {
1.228 brouard 3663: /* Same as func but slower because of a lot of printf and if */
1.126 brouard 3664: int i, ii, j, k, mi, d, kk;
1.228 brouard 3665: int ioffset=0;
1.131 brouard 3666: double l, ll[NLSTATEMAX+1], cov[NCOVMAX+1];
1.126 brouard 3667: double **out;
3668: double lli; /* Individual log likelihood */
3669: double llt;
3670: int s1, s2;
1.228 brouard 3671: int iv=0, iqv=0, itv=0, iqtv=0 ; /* Index of varying covariate, fixed quantitative cov, time varying covariate, quantitative time varying covariate */
3672:
1.126 brouard 3673: double bbh, survp;
1.187 brouard 3674: double agexact;
1.214 brouard 3675: double agebegin, ageend;
1.126 brouard 3676: /*extern weight */
3677: /* We are differentiating ll according to initial status */
3678: /* for (i=1;i<=npar;i++) printf("%f ", x[i]);*/
3679: /*for(i=1;i<imx;i++)
3680: printf(" %d\n",s[4][i]);
3681: */
3682: cov[1]=1.;
3683:
3684: for(k=1; k<=nlstate; k++) ll[k]=0.;
1.224 brouard 3685: ioffset=0;
3686: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
1.243 brouard 3687: /* ioffset=2+nagesqr+cptcovage; */
3688: ioffset=2+nagesqr;
1.232 brouard 3689: /* Fixed */
1.224 brouard 3690: /* for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i]; */
1.232 brouard 3691: /* for (k=1; k<=ncoveff;k++){ /\* Simple and product fixed Dummy covariates without age* products *\/ */
3692: for (k=1; k<=ncovf;k++){ /* Simple and product fixed covariates without age* products */
3693: 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)*/
3694: /* cov[ioffset+TvarFind[1]]=covar[Tvar[TvarFind[1]]][i]; */
3695: /* cov[2+6]=covar[Tvar[6]][i]; */
3696: /* cov[2+6]=covar[2][i]; V2 */
3697: /* cov[TvarFind[2]]=covar[Tvar[TvarFind[2]]][i]; */
3698: /* cov[2+7]=covar[Tvar[7]][i]; */
3699: /* cov[2+7]=covar[7][i]; V7=V1*V2 */
3700: /* cov[TvarFind[3]]=covar[Tvar[TvarFind[3]]][i]; */
3701: /* cov[2+9]=covar[Tvar[9]][i]; */
3702: /* cov[2+9]=covar[1][i]; V1 */
1.225 brouard 3703: }
1.232 brouard 3704: /* for (k=1; k<=nqfveff;k++){ /\* Simple and product fixed Quantitative covariates without age* products *\/ */
3705: /* 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?)*\/ */
3706: /* } */
1.231 brouard 3707: /* for(iqv=1; iqv <= nqfveff; iqv++){ /\* Quantitative fixed covariates *\/ */
3708: /* cov[++ioffset]=coqvar[Tvar[iqv]][i]; /\* Only V2 k=6 and V1*V2 7 *\/ */
3709: /* } */
1.225 brouard 3710:
1.233 brouard 3711:
3712: for(mi=1; mi<= wav[i]-1; mi++){ /* Varying with waves */
1.232 brouard 3713: /* Wave varying (but not age varying) */
3714: for(k=1; k <= ncovv ; k++){ /* Varying covariates (single and product but no age )*/
1.242 brouard 3715: /* cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]][i]; */
3716: cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]-ncovcol-nqv][i];
3717: }
1.232 brouard 3718: /* for(itv=1; itv <= ntveff; itv++){ /\* Varying dummy covariates (single??)*\/ */
1.242 brouard 3719: /* iv= Tvar[Tmodelind[ioffset-2-nagesqr-cptcovage+itv]]-ncovcol-nqv; /\* Counting the # varying covariate from 1 to ntveff *\/ */
3720: /* cov[ioffset+iv]=cotvar[mw[mi][i]][iv][i]; */
3721: /* k=ioffset-2-nagesqr-cptcovage+itv; /\* position in simple model *\/ */
3722: /* cov[ioffset+itv]=cotvar[mw[mi][i]][TmodelInvind[itv]][i]; */
3723: /* 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 3724: /* for(iqtv=1; iqtv <= nqtveff; iqtv++){ /\* Varying quantitatives covariates *\/ */
1.242 brouard 3725: /* iv=TmodelInvQind[iqtv]; /\* Counting the # varying covariate from 1 to ntveff *\/ */
3726: /* /\* 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]); *\/ */
3727: /* cov[ioffset+ntveff+iqtv]=cotqvar[mw[mi][i]][TmodelInvQind[iqtv]][i]; */
1.232 brouard 3728: /* } */
1.126 brouard 3729: for (ii=1;ii<=nlstate+ndeath;ii++)
1.242 brouard 3730: for (j=1;j<=nlstate+ndeath;j++){
3731: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
3732: savm[ii][j]=(ii==j ? 1.0 : 0.0);
3733: }
1.214 brouard 3734:
3735: agebegin=agev[mw[mi][i]][i]; /* Age at beginning of effective wave */
3736: ageend=agev[mw[mi][i]][i] + (dh[mi][i])*stepm/YEARM; /* Age at end of effective wave and at the end of transition */
3737: for(d=0; d<dh[mi][i]; d++){ /* Delay between two effective waves */
1.247 brouard 3738: /* for(d=0; d<=0; d++){ /\* Delay between two effective waves Only one matrix to speed up*\/ */
1.242 brouard 3739: /*dh[m][i] or dh[mw[mi][i]][i] is the delay between two effective waves m=mw[mi][i]
3740: and mw[mi+1][i]. dh depends on stepm.*/
3741: newm=savm;
1.247 brouard 3742: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM; /* Here d is needed */
1.242 brouard 3743: cov[2]=agexact;
3744: if(nagesqr==1)
3745: cov[3]= agexact*agexact;
3746: for (kk=1; kk<=cptcovage;kk++) {
3747: if(!FixedV[Tvar[Tage[kk]]])
3748: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
3749: else
3750: cov[Tage[kk]+2+nagesqr]=cotvar[mw[mi][i]][Tvar[Tage[kk]]-ncovcol-nqv][i]*agexact;
3751: }
3752: /* printf("i=%d,mi=%d,d=%d,mw[mi][i]=%d\n",i, mi,d,mw[mi][i]); */
3753: /* savm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
3754: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
3755: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
3756: /* out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath, */
3757: /* 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate)); */
3758: savm=oldm;
3759: oldm=newm;
1.126 brouard 3760: } /* end mult */
3761:
3762: s1=s[mw[mi][i]][i];
3763: s2=s[mw[mi+1][i]][i];
1.217 brouard 3764: /* if(s2==-1){ */
1.268 brouard 3765: /* printf(" ERROR s1=%d, s2=%d i=%d \n", s1, s2, i); */
1.217 brouard 3766: /* /\* exit(1); *\/ */
3767: /* } */
1.126 brouard 3768: bbh=(double)bh[mi][i]/(double)stepm;
3769: /* bias is positive if real duration
3770: * is higher than the multiple of stepm and negative otherwise.
3771: */
3772: if( s2 > nlstate && (mle <5) ){ /* Jackson */
1.242 brouard 3773: lli=log(out[s1][s2] - savm[s1][s2]);
1.216 brouard 3774: } else if ( s2==-1 ) { /* alive */
1.242 brouard 3775: for (j=1,survp=0. ; j<=nlstate; j++)
3776: survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j];
3777: lli= log(survp);
1.126 brouard 3778: }else if (mle==1){
1.242 brouard 3779: lli= log((1.+bbh)*out[s1][s2]- bbh*savm[s1][s2]); /* linear interpolation */
1.126 brouard 3780: } else if(mle==2){
1.242 brouard 3781: 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 3782: } else if(mle==3){ /* exponential inter-extrapolation */
1.242 brouard 3783: 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 3784: } else if (mle==4){ /* mle=4 no inter-extrapolation */
1.242 brouard 3785: lli=log(out[s1][s2]); /* Original formula */
1.136 brouard 3786: } else{ /* mle=0 back to 1 */
1.242 brouard 3787: lli= log((1.+bbh)*out[s1][s2]- bbh*savm[s1][s2]); /* linear interpolation */
3788: /*lli=log(out[s1][s2]); */ /* Original formula */
1.126 brouard 3789: } /* End of if */
3790: ipmx +=1;
3791: sw += weight[i];
3792: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
1.132 brouard 3793: /*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 3794: if(globpr){
1.246 brouard 3795: fprintf(ficresilk,"%09ld %6.1f %6.1f %6d %2d %2d %2d %2d %3d %15.6f %8.4f %8.3f\
1.126 brouard 3796: %11.6f %11.6f %11.6f ", \
1.242 brouard 3797: 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 3798: 2*weight[i]*lli,(s2==-1? -1: out[s1][s2]),(s2==-1? -1: savm[s1][s2]));
1.242 brouard 3799: for(k=1,llt=0.,l=0.; k<=nlstate; k++){
3800: llt +=ll[k]*gipmx/gsw;
3801: fprintf(ficresilk," %10.6f",-ll[k]*gipmx/gsw);
3802: }
3803: fprintf(ficresilk," %10.6f\n", -llt);
1.126 brouard 3804: }
1.232 brouard 3805: } /* end of wave */
3806: } /* end of individual */
3807: for(k=1,l=0.; k<=nlstate; k++) l += ll[k];
3808: /* printf("l1=%f l2=%f ",ll[1],ll[2]); */
3809: l= l*ipmx/sw; /* To get the same order of magnitude as if weight=1 for every body */
3810: if(globpr==0){ /* First time we count the contributions and weights */
3811: gipmx=ipmx;
3812: gsw=sw;
3813: }
3814: return -l;
1.126 brouard 3815: }
3816:
3817:
3818: /*************** function likelione ***********/
3819: void likelione(FILE *ficres,double p[], int npar, int nlstate, int *globpri, long *ipmx, double *sw, double *fretone, double (*funcone)(double []))
3820: {
3821: /* This routine should help understanding what is done with
3822: the selection of individuals/waves and
3823: to check the exact contribution to the likelihood.
3824: Plotting could be done.
3825: */
3826: int k;
3827:
3828: if(*globpri !=0){ /* Just counts and sums, no printings */
1.201 brouard 3829: strcpy(fileresilk,"ILK_");
1.202 brouard 3830: strcat(fileresilk,fileresu);
1.126 brouard 3831: if((ficresilk=fopen(fileresilk,"w"))==NULL) {
3832: printf("Problem with resultfile: %s\n", fileresilk);
3833: fprintf(ficlog,"Problem with resultfile: %s\n", fileresilk);
3834: }
1.214 brouard 3835: 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");
3836: fprintf(ficresilk, "#num_i ageb agend i s1 s2 mi mw dh likeli weight %%weight 2wlli out sav ");
1.126 brouard 3837: /* i,s1,s2,mi,mw[mi][i],dh[mi][i],exp(lli),weight[i],2*weight[i]*lli,out[s1][s2],savm[s1][s2]); */
3838: for(k=1; k<=nlstate; k++)
3839: fprintf(ficresilk," -2*gipw/gsw*weight*ll[%d]++",k);
3840: fprintf(ficresilk," -2*gipw/gsw*weight*ll(total)\n");
3841: }
3842:
3843: *fretone=(*funcone)(p);
3844: if(*globpri !=0){
3845: fclose(ficresilk);
1.205 brouard 3846: if (mle ==0)
3847: fprintf(fichtm,"\n<br>File of contributions to the likelihood computed with initial parameters and mle = %d.",mle);
3848: else if(mle >=1)
3849: fprintf(fichtm,"\n<br>File of contributions to the likelihood computed with optimized parameters mle = %d.",mle);
3850: 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 3851:
1.208 brouard 3852:
3853: for (k=1; k<= nlstate ; k++) {
1.211 brouard 3854: 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 3855: <img src=\"%s-p%dj.png\">",k,k,subdirf2(optionfilefiname,"ILK_"),k,subdirf2(optionfilefiname,"ILK_"),k,subdirf2(optionfilefiname,"ILK_"),k);
3856: }
1.207 brouard 3857: 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 3858: <img src=\"%s-ori.png\">",subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"));
1.207 brouard 3859: fprintf(fichtm,"<br>- and by state of destination <a href=\"%s-dest.png\">%s-dest.png</a><br> \
1.204 brouard 3860: <img src=\"%s-dest.png\">",subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"));
1.207 brouard 3861: fflush(fichtm);
1.205 brouard 3862: }
1.126 brouard 3863: return;
3864: }
3865:
3866:
3867: /*********** Maximum Likelihood Estimation ***************/
3868:
3869: void mlikeli(FILE *ficres,double p[], int npar, int ncovmodel, int nlstate, double ftol, double (*func)(double []))
3870: {
1.165 brouard 3871: int i,j, iter=0;
1.126 brouard 3872: double **xi;
3873: double fret;
3874: double fretone; /* Only one call to likelihood */
3875: /* char filerespow[FILENAMELENGTH];*/
1.162 brouard 3876:
3877: #ifdef NLOPT
3878: int creturn;
3879: nlopt_opt opt;
3880: /* double lb[9] = { -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL }; /\* lower bounds *\/ */
3881: double *lb;
3882: double minf; /* the minimum objective value, upon return */
3883: double * p1; /* Shifted parameters from 0 instead of 1 */
3884: myfunc_data dinst, *d = &dinst;
3885: #endif
3886:
3887:
1.126 brouard 3888: xi=matrix(1,npar,1,npar);
3889: for (i=1;i<=npar;i++)
3890: for (j=1;j<=npar;j++)
3891: xi[i][j]=(i==j ? 1.0 : 0.0);
3892: printf("Powell\n"); fprintf(ficlog,"Powell\n");
1.201 brouard 3893: strcpy(filerespow,"POW_");
1.126 brouard 3894: strcat(filerespow,fileres);
3895: if((ficrespow=fopen(filerespow,"w"))==NULL) {
3896: printf("Problem with resultfile: %s\n", filerespow);
3897: fprintf(ficlog,"Problem with resultfile: %s\n", filerespow);
3898: }
3899: fprintf(ficrespow,"# Powell\n# iter -2*LL");
3900: for (i=1;i<=nlstate;i++)
3901: for(j=1;j<=nlstate+ndeath;j++)
3902: if(j!=i)fprintf(ficrespow," p%1d%1d",i,j);
3903: fprintf(ficrespow,"\n");
1.162 brouard 3904: #ifdef POWELL
1.126 brouard 3905: powell(p,xi,npar,ftol,&iter,&fret,func);
1.162 brouard 3906: #endif
1.126 brouard 3907:
1.162 brouard 3908: #ifdef NLOPT
3909: #ifdef NEWUOA
3910: opt = nlopt_create(NLOPT_LN_NEWUOA,npar);
3911: #else
3912: opt = nlopt_create(NLOPT_LN_BOBYQA,npar);
3913: #endif
3914: lb=vector(0,npar-1);
3915: for (i=0;i<npar;i++) lb[i]= -HUGE_VAL;
3916: nlopt_set_lower_bounds(opt, lb);
3917: nlopt_set_initial_step1(opt, 0.1);
3918:
3919: p1= (p+1); /* p *(p+1)@8 and p *(p1)@8 are equal p1[0]=p[1] */
3920: d->function = func;
3921: printf(" Func %.12lf \n",myfunc(npar,p1,NULL,d));
3922: nlopt_set_min_objective(opt, myfunc, d);
3923: nlopt_set_xtol_rel(opt, ftol);
3924: if ((creturn=nlopt_optimize(opt, p1, &minf)) < 0) {
3925: printf("nlopt failed! %d\n",creturn);
3926: }
3927: else {
3928: printf("found minimum after %d evaluations (NLOPT=%d)\n", countcallfunc ,NLOPT);
3929: printf("found minimum at f(%g,%g) = %0.10g\n", p[0], p[1], minf);
3930: iter=1; /* not equal */
3931: }
3932: nlopt_destroy(opt);
3933: #endif
1.126 brouard 3934: free_matrix(xi,1,npar,1,npar);
3935: fclose(ficrespow);
1.203 brouard 3936: printf("\n#Number of iterations & function calls = %d & %d, -2 Log likelihood = %.12f\n",iter, countcallfunc,func(p));
3937: fprintf(ficlog,"\n#Number of iterations & function calls = %d & %d, -2 Log likelihood = %.12f\n",iter, countcallfunc,func(p));
1.180 brouard 3938: fprintf(ficres,"#Number of iterations & function calls = %d & %d, -2 Log likelihood = %.12f\n",iter, countcallfunc,func(p));
1.126 brouard 3939:
3940: }
3941:
3942: /**** Computes Hessian and covariance matrix ***/
1.203 brouard 3943: void hesscov(double **matcov, double **hess, double p[], int npar, double delti[], double ftolhess, double (*func)(double []))
1.126 brouard 3944: {
3945: double **a,**y,*x,pd;
1.203 brouard 3946: /* double **hess; */
1.164 brouard 3947: int i, j;
1.126 brouard 3948: int *indx;
3949:
3950: double hessii(double p[], double delta, int theta, double delti[],double (*func)(double []),int npar);
1.203 brouard 3951: double hessij(double p[], double **hess, double delti[], int i, int j,double (*func)(double []),int npar);
1.126 brouard 3952: void lubksb(double **a, int npar, int *indx, double b[]) ;
3953: void ludcmp(double **a, int npar, int *indx, double *d) ;
3954: double gompertz(double p[]);
1.203 brouard 3955: /* hess=matrix(1,npar,1,npar); */
1.126 brouard 3956:
3957: printf("\nCalculation of the hessian matrix. Wait...\n");
3958: fprintf(ficlog,"\nCalculation of the hessian matrix. Wait...\n");
3959: for (i=1;i<=npar;i++){
1.203 brouard 3960: printf("%d-",i);fflush(stdout);
3961: fprintf(ficlog,"%d-",i);fflush(ficlog);
1.126 brouard 3962:
3963: hess[i][i]=hessii(p,ftolhess,i,delti,func,npar);
3964:
3965: /* printf(" %f ",p[i]);
3966: printf(" %lf %lf %lf",hess[i][i],ftolhess,delti[i]);*/
3967: }
3968:
3969: for (i=1;i<=npar;i++) {
3970: for (j=1;j<=npar;j++) {
3971: if (j>i) {
1.203 brouard 3972: printf(".%d-%d",i,j);fflush(stdout);
3973: fprintf(ficlog,".%d-%d",i,j);fflush(ficlog);
3974: hess[i][j]=hessij(p,hess, delti,i,j,func,npar);
1.126 brouard 3975:
3976: hess[j][i]=hess[i][j];
3977: /*printf(" %lf ",hess[i][j]);*/
3978: }
3979: }
3980: }
3981: printf("\n");
3982: fprintf(ficlog,"\n");
3983:
3984: printf("\nInverting the hessian to get the covariance matrix. Wait...\n");
3985: fprintf(ficlog,"\nInverting the hessian to get the covariance matrix. Wait...\n");
3986:
3987: a=matrix(1,npar,1,npar);
3988: y=matrix(1,npar,1,npar);
3989: x=vector(1,npar);
3990: indx=ivector(1,npar);
3991: for (i=1;i<=npar;i++)
3992: for (j=1;j<=npar;j++) a[i][j]=hess[i][j];
3993: ludcmp(a,npar,indx,&pd);
3994:
3995: for (j=1;j<=npar;j++) {
3996: for (i=1;i<=npar;i++) x[i]=0;
3997: x[j]=1;
3998: lubksb(a,npar,indx,x);
3999: for (i=1;i<=npar;i++){
4000: matcov[i][j]=x[i];
4001: }
4002: }
4003:
4004: printf("\n#Hessian matrix#\n");
4005: fprintf(ficlog,"\n#Hessian matrix#\n");
4006: for (i=1;i<=npar;i++) {
4007: for (j=1;j<=npar;j++) {
1.203 brouard 4008: printf("%.6e ",hess[i][j]);
4009: fprintf(ficlog,"%.6e ",hess[i][j]);
1.126 brouard 4010: }
4011: printf("\n");
4012: fprintf(ficlog,"\n");
4013: }
4014:
1.203 brouard 4015: /* printf("\n#Covariance matrix#\n"); */
4016: /* fprintf(ficlog,"\n#Covariance matrix#\n"); */
4017: /* for (i=1;i<=npar;i++) { */
4018: /* for (j=1;j<=npar;j++) { */
4019: /* printf("%.6e ",matcov[i][j]); */
4020: /* fprintf(ficlog,"%.6e ",matcov[i][j]); */
4021: /* } */
4022: /* printf("\n"); */
4023: /* fprintf(ficlog,"\n"); */
4024: /* } */
4025:
1.126 brouard 4026: /* Recompute Inverse */
1.203 brouard 4027: /* for (i=1;i<=npar;i++) */
4028: /* for (j=1;j<=npar;j++) a[i][j]=matcov[i][j]; */
4029: /* ludcmp(a,npar,indx,&pd); */
4030:
4031: /* printf("\n#Hessian matrix recomputed#\n"); */
4032:
4033: /* for (j=1;j<=npar;j++) { */
4034: /* for (i=1;i<=npar;i++) x[i]=0; */
4035: /* x[j]=1; */
4036: /* lubksb(a,npar,indx,x); */
4037: /* for (i=1;i<=npar;i++){ */
4038: /* y[i][j]=x[i]; */
4039: /* printf("%.3e ",y[i][j]); */
4040: /* fprintf(ficlog,"%.3e ",y[i][j]); */
4041: /* } */
4042: /* printf("\n"); */
4043: /* fprintf(ficlog,"\n"); */
4044: /* } */
4045:
4046: /* Verifying the inverse matrix */
4047: #ifdef DEBUGHESS
4048: y=matprod2(y,hess,1,npar,1,npar,1,npar,matcov);
1.126 brouard 4049:
1.203 brouard 4050: printf("\n#Verification: multiplying the matrix of covariance by the Hessian matrix, should be unity:#\n");
4051: fprintf(ficlog,"\n#Verification: multiplying the matrix of covariance by the Hessian matrix. Should be unity:#\n");
1.126 brouard 4052:
4053: for (j=1;j<=npar;j++) {
4054: for (i=1;i<=npar;i++){
1.203 brouard 4055: printf("%.2f ",y[i][j]);
4056: fprintf(ficlog,"%.2f ",y[i][j]);
1.126 brouard 4057: }
4058: printf("\n");
4059: fprintf(ficlog,"\n");
4060: }
1.203 brouard 4061: #endif
1.126 brouard 4062:
4063: free_matrix(a,1,npar,1,npar);
4064: free_matrix(y,1,npar,1,npar);
4065: free_vector(x,1,npar);
4066: free_ivector(indx,1,npar);
1.203 brouard 4067: /* free_matrix(hess,1,npar,1,npar); */
1.126 brouard 4068:
4069:
4070: }
4071:
4072: /*************** hessian matrix ****************/
4073: double hessii(double x[], double delta, int theta, double delti[], double (*func)(double []), int npar)
1.203 brouard 4074: { /* Around values of x, computes the function func and returns the scales delti and hessian */
1.126 brouard 4075: int i;
4076: int l=1, lmax=20;
1.203 brouard 4077: double k1,k2, res, fx;
1.132 brouard 4078: double p2[MAXPARM+1]; /* identical to x */
1.126 brouard 4079: double delt=0.0001, delts, nkhi=10.,nkhif=1., khi=1.e-4;
4080: int k=0,kmax=10;
4081: double l1;
4082:
4083: fx=func(x);
4084: for (i=1;i<=npar;i++) p2[i]=x[i];
1.145 brouard 4085: for(l=0 ; l <=lmax; l++){ /* Enlarging the zone around the Maximum */
1.126 brouard 4086: l1=pow(10,l);
4087: delts=delt;
4088: for(k=1 ; k <kmax; k=k+1){
4089: delt = delta*(l1*k);
4090: p2[theta]=x[theta] +delt;
1.145 brouard 4091: k1=func(p2)-fx; /* Might be negative if too close to the theoretical maximum */
1.126 brouard 4092: p2[theta]=x[theta]-delt;
4093: k2=func(p2)-fx;
4094: /*res= (k1-2.0*fx+k2)/delt/delt; */
1.203 brouard 4095: res= (k1+k2)/delt/delt/2.; /* Divided by 2 because L and not 2*L */
1.126 brouard 4096:
1.203 brouard 4097: #ifdef DEBUGHESSII
1.126 brouard 4098: 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);
4099: 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);
4100: #endif
4101: /*if(fabs(k1-2.0*fx+k2) <1.e-13){ */
4102: if((k1 <khi/nkhi/2.) || (k2 <khi/nkhi/2.)){
4103: k=kmax;
4104: }
4105: else if((k1 >khi/nkhif) || (k2 >khi/nkhif)){ /* Keeps lastvalue before 3.84/2 KHI2 5% 1d.f. */
1.164 brouard 4106: k=kmax; l=lmax*10;
1.126 brouard 4107: }
4108: else if((k1 >khi/nkhi) || (k2 >khi/nkhi)){
4109: delts=delt;
4110: }
1.203 brouard 4111: } /* End loop k */
1.126 brouard 4112: }
4113: delti[theta]=delts;
4114: return res;
4115:
4116: }
4117:
1.203 brouard 4118: double hessij( double x[], double **hess, double delti[], int thetai,int thetaj,double (*func)(double []),int npar)
1.126 brouard 4119: {
4120: int i;
1.164 brouard 4121: int l=1, lmax=20;
1.126 brouard 4122: double k1,k2,k3,k4,res,fx;
1.132 brouard 4123: double p2[MAXPARM+1];
1.203 brouard 4124: int k, kmax=1;
4125: double v1, v2, cv12, lc1, lc2;
1.208 brouard 4126:
4127: int firstime=0;
1.203 brouard 4128:
1.126 brouard 4129: fx=func(x);
1.203 brouard 4130: for (k=1; k<=kmax; k=k+10) {
1.126 brouard 4131: for (i=1;i<=npar;i++) p2[i]=x[i];
1.203 brouard 4132: p2[thetai]=x[thetai]+delti[thetai]*k;
4133: p2[thetaj]=x[thetaj]+delti[thetaj]*k;
1.126 brouard 4134: k1=func(p2)-fx;
4135:
1.203 brouard 4136: p2[thetai]=x[thetai]+delti[thetai]*k;
4137: p2[thetaj]=x[thetaj]-delti[thetaj]*k;
1.126 brouard 4138: k2=func(p2)-fx;
4139:
1.203 brouard 4140: p2[thetai]=x[thetai]-delti[thetai]*k;
4141: p2[thetaj]=x[thetaj]+delti[thetaj]*k;
1.126 brouard 4142: k3=func(p2)-fx;
4143:
1.203 brouard 4144: p2[thetai]=x[thetai]-delti[thetai]*k;
4145: p2[thetaj]=x[thetaj]-delti[thetaj]*k;
1.126 brouard 4146: k4=func(p2)-fx;
1.203 brouard 4147: res=(k1-k2-k3+k4)/4.0/delti[thetai]/k/delti[thetaj]/k/2.; /* Because of L not 2*L */
4148: if(k1*k2*k3*k4 <0.){
1.208 brouard 4149: firstime=1;
1.203 brouard 4150: kmax=kmax+10;
1.208 brouard 4151: }
4152: if(kmax >=10 || firstime ==1){
1.246 brouard 4153: 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);
4154: 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 4155: 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);
4156: 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);
4157: }
4158: #ifdef DEBUGHESSIJ
4159: v1=hess[thetai][thetai];
4160: v2=hess[thetaj][thetaj];
4161: cv12=res;
4162: /* Computing eigen value of Hessian matrix */
4163: lc1=((v1+v2)+sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
4164: lc2=((v1+v2)-sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
4165: if ((lc2 <0) || (lc1 <0) ){
4166: printf("Warning: sub Hessian matrix '%d%d' does not have positive eigen values \n",thetai,thetaj);
4167: fprintf(ficlog, "Warning: sub Hessian matrix '%d%d' does not have positive eigen values \n",thetai,thetaj);
4168: 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);
4169: 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);
4170: }
1.126 brouard 4171: #endif
4172: }
4173: return res;
4174: }
4175:
1.203 brouard 4176: /* Not done yet: Was supposed to fix if not exactly at the maximum */
4177: /* double hessij( double x[], double delti[], int thetai,int thetaj,double (*func)(double []),int npar) */
4178: /* { */
4179: /* int i; */
4180: /* int l=1, lmax=20; */
4181: /* double k1,k2,k3,k4,res,fx; */
4182: /* double p2[MAXPARM+1]; */
4183: /* double delt=0.0001, delts, nkhi=10.,nkhif=1., khi=1.e-4; */
4184: /* int k=0,kmax=10; */
4185: /* double l1; */
4186:
4187: /* fx=func(x); */
4188: /* for(l=0 ; l <=lmax; l++){ /\* Enlarging the zone around the Maximum *\/ */
4189: /* l1=pow(10,l); */
4190: /* delts=delt; */
4191: /* for(k=1 ; k <kmax; k=k+1){ */
4192: /* delt = delti*(l1*k); */
4193: /* for (i=1;i<=npar;i++) p2[i]=x[i]; */
4194: /* p2[thetai]=x[thetai]+delti[thetai]/k; */
4195: /* p2[thetaj]=x[thetaj]+delti[thetaj]/k; */
4196: /* k1=func(p2)-fx; */
4197:
4198: /* p2[thetai]=x[thetai]+delti[thetai]/k; */
4199: /* p2[thetaj]=x[thetaj]-delti[thetaj]/k; */
4200: /* k2=func(p2)-fx; */
4201:
4202: /* p2[thetai]=x[thetai]-delti[thetai]/k; */
4203: /* p2[thetaj]=x[thetaj]+delti[thetaj]/k; */
4204: /* k3=func(p2)-fx; */
4205:
4206: /* p2[thetai]=x[thetai]-delti[thetai]/k; */
4207: /* p2[thetaj]=x[thetaj]-delti[thetaj]/k; */
4208: /* k4=func(p2)-fx; */
4209: /* res=(k1-k2-k3+k4)/4.0/delti[thetai]*k/delti[thetaj]*k/2.; /\* Because of L not 2*L *\/ */
4210: /* #ifdef DEBUGHESSIJ */
4211: /* 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); */
4212: /* 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); */
4213: /* #endif */
4214: /* if((k1 <khi/nkhi/2.) || (k2 <khi/nkhi/2.)|| (k4 <khi/nkhi/2.)|| (k4 <khi/nkhi/2.)){ */
4215: /* k=kmax; */
4216: /* } */
4217: /* else if((k1 >khi/nkhif) || (k2 >khi/nkhif) || (k4 >khi/nkhif) || (k4 >khi/nkhif)){ /\* Keeps lastvalue before 3.84/2 KHI2 5% 1d.f. *\/ */
4218: /* k=kmax; l=lmax*10; */
4219: /* } */
4220: /* else if((k1 >khi/nkhi) || (k2 >khi/nkhi)){ */
4221: /* delts=delt; */
4222: /* } */
4223: /* } /\* End loop k *\/ */
4224: /* } */
4225: /* delti[theta]=delts; */
4226: /* return res; */
4227: /* } */
4228:
4229:
1.126 brouard 4230: /************** Inverse of matrix **************/
4231: void ludcmp(double **a, int n, int *indx, double *d)
4232: {
4233: int i,imax,j,k;
4234: double big,dum,sum,temp;
4235: double *vv;
4236:
4237: vv=vector(1,n);
4238: *d=1.0;
4239: for (i=1;i<=n;i++) {
4240: big=0.0;
4241: for (j=1;j<=n;j++)
4242: if ((temp=fabs(a[i][j])) > big) big=temp;
1.256 brouard 4243: if (big == 0.0){
4244: printf(" Singular Hessian matrix at row %d:\n",i);
4245: for (j=1;j<=n;j++) {
4246: printf(" a[%d][%d]=%f,",i,j,a[i][j]);
4247: fprintf(ficlog," a[%d][%d]=%f,",i,j,a[i][j]);
4248: }
4249: fflush(ficlog);
4250: fclose(ficlog);
4251: nrerror("Singular matrix in routine ludcmp");
4252: }
1.126 brouard 4253: vv[i]=1.0/big;
4254: }
4255: for (j=1;j<=n;j++) {
4256: for (i=1;i<j;i++) {
4257: sum=a[i][j];
4258: for (k=1;k<i;k++) sum -= a[i][k]*a[k][j];
4259: a[i][j]=sum;
4260: }
4261: big=0.0;
4262: for (i=j;i<=n;i++) {
4263: sum=a[i][j];
4264: for (k=1;k<j;k++)
4265: sum -= a[i][k]*a[k][j];
4266: a[i][j]=sum;
4267: if ( (dum=vv[i]*fabs(sum)) >= big) {
4268: big=dum;
4269: imax=i;
4270: }
4271: }
4272: if (j != imax) {
4273: for (k=1;k<=n;k++) {
4274: dum=a[imax][k];
4275: a[imax][k]=a[j][k];
4276: a[j][k]=dum;
4277: }
4278: *d = -(*d);
4279: vv[imax]=vv[j];
4280: }
4281: indx[j]=imax;
4282: if (a[j][j] == 0.0) a[j][j]=TINY;
4283: if (j != n) {
4284: dum=1.0/(a[j][j]);
4285: for (i=j+1;i<=n;i++) a[i][j] *= dum;
4286: }
4287: }
4288: free_vector(vv,1,n); /* Doesn't work */
4289: ;
4290: }
4291:
4292: void lubksb(double **a, int n, int *indx, double b[])
4293: {
4294: int i,ii=0,ip,j;
4295: double sum;
4296:
4297: for (i=1;i<=n;i++) {
4298: ip=indx[i];
4299: sum=b[ip];
4300: b[ip]=b[i];
4301: if (ii)
4302: for (j=ii;j<=i-1;j++) sum -= a[i][j]*b[j];
4303: else if (sum) ii=i;
4304: b[i]=sum;
4305: }
4306: for (i=n;i>=1;i--) {
4307: sum=b[i];
4308: for (j=i+1;j<=n;j++) sum -= a[i][j]*b[j];
4309: b[i]=sum/a[i][i];
4310: }
4311: }
4312:
4313: void pstamp(FILE *fichier)
4314: {
1.196 brouard 4315: fprintf(fichier,"# %s.%s\n#IMaCh version %s, %s\n#%s\n# %s", optionfilefiname,optionfilext,version,copyright, fullversion, strstart);
1.126 brouard 4316: }
4317:
1.253 brouard 4318:
4319:
1.126 brouard 4320: /************ Frequencies ********************/
1.251 brouard 4321: void freqsummary(char fileres[], double p[], double pstart[], int iagemin, int iagemax, int **s, double **agev, int nlstate, int imx, \
1.226 brouard 4322: int *Tvaraff, int *invalidvarcomb, int **nbcode, int *ncodemax,double **mint,double **anint, char strstart[], \
4323: int firstpass, int lastpass, int stepm, int weightopt, char model[])
1.250 brouard 4324: { /* Some frequencies as well as proposing some starting values */
1.226 brouard 4325:
1.265 brouard 4326: int i, m, jk, j1, bool, z1,j, nj, nl, k, iv, jj=0, s1=1, s2=1;
1.226 brouard 4327: int iind=0, iage=0;
4328: int mi; /* Effective wave */
4329: int first;
4330: double ***freq; /* Frequencies */
1.268 brouard 4331: 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 */
4332: 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 4333: double *meanq;
4334: double **meanqt;
4335: double *pp, **prop, *posprop, *pospropt;
4336: double pos=0., posproptt=0., pospropta=0., k2, dateintsum=0,k2cpt=0;
4337: char fileresp[FILENAMELENGTH], fileresphtm[FILENAMELENGTH], fileresphtmfr[FILENAMELENGTH];
4338: double agebegin, ageend;
4339:
4340: pp=vector(1,nlstate);
1.251 brouard 4341: prop=matrix(1,nlstate,iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.226 brouard 4342: posprop=vector(1,nlstate); /* Counting the number of transition starting from a live state per age */
4343: pospropt=vector(1,nlstate); /* Counting the number of transition starting from a live state */
4344: /* prop=matrix(1,nlstate,iagemin,iagemax+3); */
4345: meanq=vector(1,nqfveff); /* Number of Quantitative Fixed Variables Effective */
4346: meanqt=matrix(1,lastpass,1,nqtveff);
4347: strcpy(fileresp,"P_");
4348: strcat(fileresp,fileresu);
4349: /*strcat(fileresphtm,fileresu);*/
4350: if((ficresp=fopen(fileresp,"w"))==NULL) {
4351: printf("Problem with prevalence resultfile: %s\n", fileresp);
4352: fprintf(ficlog,"Problem with prevalence resultfile: %s\n", fileresp);
4353: exit(0);
4354: }
1.240 brouard 4355:
1.226 brouard 4356: strcpy(fileresphtm,subdirfext(optionfilefiname,"PHTM_",".htm"));
4357: if((ficresphtm=fopen(fileresphtm,"w"))==NULL) {
4358: printf("Problem with prevalence HTM resultfile '%s' with errno='%s'\n",fileresphtm,strerror(errno));
4359: fprintf(ficlog,"Problem with prevalence HTM resultfile '%s' with errno='%s'\n",fileresphtm,strerror(errno));
4360: fflush(ficlog);
4361: exit(70);
4362: }
4363: else{
4364: fprintf(ficresphtm,"<html><head>\n<title>IMaCh PHTM_ %s</title></head>\n <body><font size=\"2\">%s <br> %s</font> \
1.240 brouard 4365: <hr size=\"2\" color=\"#EC5E5E\"> \n \
1.214 brouard 4366: Title=%s <br>Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s<br>\n",\
1.226 brouard 4367: fileresphtm,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model);
4368: }
1.237 brouard 4369: 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 4370:
1.226 brouard 4371: strcpy(fileresphtmfr,subdirfext(optionfilefiname,"PHTMFR_",".htm"));
4372: if((ficresphtmfr=fopen(fileresphtmfr,"w"))==NULL) {
4373: printf("Problem with frequency table HTM resultfile '%s' with errno='%s'\n",fileresphtmfr,strerror(errno));
4374: fprintf(ficlog,"Problem with frequency table HTM resultfile '%s' with errno='%s'\n",fileresphtmfr,strerror(errno));
4375: fflush(ficlog);
4376: exit(70);
1.240 brouard 4377: } else{
1.226 brouard 4378: 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 4379: <hr size=\"2\" color=\"#EC5E5E\"> \n \
1.214 brouard 4380: Title=%s <br>Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s<br>\n",\
1.226 brouard 4381: fileresphtmfr,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model);
4382: }
1.240 brouard 4383: 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);
4384:
1.253 brouard 4385: y= vector(iagemin-AGEMARGE,iagemax+4+AGEMARGE);
4386: x= vector(iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.251 brouard 4387: freq= ma3x(-5,nlstate+ndeath,-5,nlstate+ndeath,iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.226 brouard 4388: j1=0;
1.126 brouard 4389:
1.227 brouard 4390: /* j=ncoveff; /\* Only fixed dummy covariates *\/ */
4391: j=cptcoveff; /* Only dummy covariates of the model */
1.226 brouard 4392: if (cptcovn<1) {j=1;ncodemax[1]=1;}
1.240 brouard 4393:
4394:
1.226 brouard 4395: /* Detects if a combination j1 is empty: for a multinomial variable like 3 education levels:
4396: reference=low_education V1=0,V2=0
4397: med_educ V1=1 V2=0,
4398: high_educ V1=0 V2=1
4399: Then V1=1 and V2=1 is a noisy combination that we want to exclude for the list 2**cptcoveff
4400: */
1.249 brouard 4401: dateintsum=0;
4402: k2cpt=0;
4403:
1.253 brouard 4404: if(cptcoveff == 0 )
1.265 brouard 4405: nl=1; /* Constant and age model only */
1.253 brouard 4406: else
4407: nl=2;
1.265 brouard 4408:
4409: /* if a constant only model, one pass to compute frequency tables and to write it on ficresp */
4410: /* Loop on nj=1 or 2 if dummy covariates j!=0
4411: * Loop on j1(1 to 2**cptcoveff) covariate combination
4412: * freq[s1][s2][iage] =0.
4413: * Loop on iind
4414: * ++freq[s1][s2][iage] weighted
4415: * end iind
4416: * if covariate and j!0
4417: * headers Variable on one line
4418: * endif cov j!=0
4419: * header of frequency table by age
4420: * Loop on age
4421: * pp[s1]+=freq[s1][s2][iage] weighted
4422: * pos+=freq[s1][s2][iage] weighted
4423: * Loop on s1 initial state
4424: * fprintf(ficresp
4425: * end s1
4426: * end age
4427: * if j!=0 computes starting values
4428: * end compute starting values
4429: * end j1
4430: * end nl
4431: */
1.253 brouard 4432: for (nj = 1; nj <= nl; nj++){ /* nj= 1 constant model, nl number of loops. */
4433: if(nj==1)
4434: j=0; /* First pass for the constant */
1.265 brouard 4435: else{
1.253 brouard 4436: j=cptcoveff; /* Other passes for the covariate values */
1.265 brouard 4437: }
1.251 brouard 4438: first=1;
1.265 brouard 4439: 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 4440: posproptt=0.;
4441: /*printf("cptcoveff=%d Tvaraff=%d", cptcoveff,Tvaraff[1]);
4442: scanf("%d", i);*/
4443: for (i=-5; i<=nlstate+ndeath; i++)
1.265 brouard 4444: for (s2=-5; s2<=nlstate+ndeath; s2++)
1.251 brouard 4445: for(m=iagemin; m <= iagemax+3; m++)
1.265 brouard 4446: freq[i][s2][m]=0;
1.251 brouard 4447:
4448: for (i=1; i<=nlstate; i++) {
1.240 brouard 4449: for(m=iagemin; m <= iagemax+3; m++)
1.251 brouard 4450: prop[i][m]=0;
4451: posprop[i]=0;
4452: pospropt[i]=0;
4453: }
4454: /* for (z1=1; z1<= nqfveff; z1++) { */
4455: /* meanq[z1]+=0.; */
4456: /* for(m=1;m<=lastpass;m++){ */
4457: /* meanqt[m][z1]=0.; */
4458: /* } */
4459: /* } */
4460:
4461: /* dateintsum=0; */
4462: /* k2cpt=0; */
4463:
1.265 brouard 4464: /* For that combination of covariates j1 (V4=1 V3=0 for example), we count and print the frequencies in one pass */
1.251 brouard 4465: for (iind=1; iind<=imx; iind++) { /* For each individual iind */
4466: bool=1;
4467: if(j !=0){
4468: if(anyvaryingduminmodel==0){ /* If All fixed covariates */
4469: if (cptcoveff >0) { /* Filter is here: Must be looked at for model=V1+V2+V3+V4 */
4470: /* for (z1=1; z1<= nqfveff; z1++) { */
4471: /* meanq[z1]+=coqvar[Tvar[z1]][iind]; /\* Computes mean of quantitative with selected filter *\/ */
4472: /* } */
4473: for (z1=1; z1<=cptcoveff; z1++) { /* loops on covariates in the model */
4474: /* if(Tvaraff[z1] ==-20){ */
4475: /* /\* sumnew+=cotvar[mw[mi][iind]][z1][iind]; *\/ */
4476: /* }else if(Tvaraff[z1] ==-10){ */
4477: /* /\* sumnew+=coqvar[z1][iind]; *\/ */
4478: /* }else */
4479: if (covar[Tvaraff[z1]][iind]!= nbcode[Tvaraff[z1]][codtabm(j1,z1)]){ /* for combination j1 of covariates */
1.265 brouard 4480: /* Tests if the value of the covariate z1 for this individual iind responded to combination j1 (V4=1 V3=0) */
1.251 brouard 4481: bool=0; /* bool should be equal to 1 to be selected, one covariate value failed */
4482: /* 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",
4483: bool,i,z1, z1, Tvaraff[z1],i,covar[Tvaraff[z1]][i],j1,z1,codtabm(j1,z1),
4484: j1,z1,nbcode[Tvaraff[z1]][codtabm(j1,z1)],j1);*/
4485: /* For j1=7 in V1+V2+V3+V4 = 0 1 1 0 and codtabm(7,3)=1 and nbcde[3][?]=1*/
4486: } /* Onlyf fixed */
4487: } /* end z1 */
4488: } /* cptcovn > 0 */
4489: } /* end any */
4490: }/* end j==0 */
1.265 brouard 4491: if (bool==1){ /* We selected an individual iind satisfying combination j1 (V4=1 V3=0) or all fixed covariates */
1.251 brouard 4492: /* for(m=firstpass; m<=lastpass; m++){ */
4493: for(mi=1; mi<wav[iind];mi++){ /* For that wave */
4494: m=mw[mi][iind];
4495: if(j!=0){
4496: if(anyvaryingduminmodel==1){ /* Some are varying covariates */
4497: for (z1=1; z1<=cptcoveff; z1++) {
4498: if( Fixed[Tmodelind[z1]]==1){
4499: iv= Tvar[Tmodelind[z1]]-ncovcol-nqv;
4500: if (cotvar[m][iv][iind]!= nbcode[Tvaraff[z1]][codtabm(j1,z1)]) /* iv=1 to ntv, right modality. If covariate's
4501: value is -1, we don't select. It differs from the
4502: constant and age model which counts them. */
4503: bool=0; /* not selected */
4504: }else if( Fixed[Tmodelind[z1]]== 0) { /* fixed */
4505: if (covar[Tvaraff[z1]][iind]!= nbcode[Tvaraff[z1]][codtabm(j1,z1)]) {
4506: bool=0;
4507: }
4508: }
4509: }
4510: }/* Some are varying covariates, we tried to speed up if all fixed covariates in the model, avoiding waves loop */
4511: } /* end j==0 */
4512: /* bool =0 we keep that guy which corresponds to the combination of dummy values */
4513: if(bool==1){
4514: /* dh[m][iind] or dh[mw[mi][iind]][iind] is the delay between two effective (mi) waves m=mw[mi][iind]
4515: and mw[mi+1][iind]. dh depends on stepm. */
4516: agebegin=agev[m][iind]; /* Age at beginning of wave before transition*/
4517: ageend=agev[m][iind]+(dh[m][iind])*stepm/YEARM; /* Age at end of wave and transition */
4518: if(m >=firstpass && m <=lastpass){
4519: k2=anint[m][iind]+(mint[m][iind]/12.);
4520: /*if ((k2>=dateprev1) && (k2<=dateprev2)) {*/
4521: if(agev[m][iind]==0) agev[m][iind]=iagemax+1; /* All ages equal to 0 are in iagemax+1 */
4522: if(agev[m][iind]==1) agev[m][iind]=iagemax+2; /* All ages equal to 1 are in iagemax+2 */
4523: if (s[m][iind]>0 && s[m][iind]<=nlstate) /* If status at wave m is known and a live state */
4524: prop[s[m][iind]][(int)agev[m][iind]] += weight[iind]; /* At age of beginning of transition, where status is known */
4525: if (m<lastpass) {
4526: /* if(s[m][iind]==4 && s[m+1][iind]==4) */
4527: /* 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]); */
4528: if(s[m][iind]==-1)
4529: 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.));
4530: freq[s[m][iind]][s[m+1][iind]][(int)agev[m][iind]] += weight[iind]; /* At age of beginning of transition, where status is known */
4531: /* if((int)agev[m][iind] == 55) */
4532: /* printf("j=%d, j1=%d Age %d, iind=%d, num=%09ld m=%d\n",j,j1,(int)agev[m][iind],iind, num[iind],m); */
4533: /* freq[s[m][iind]][s[m+1][iind]][(int)((agebegin+ageend)/2.)] += weight[iind]; */
4534: 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 4535: }
1.251 brouard 4536: } /* end if between passes */
4537: if ((agev[m][iind]>1) && (agev[m][iind]< (iagemax+3)) && (anint[m][iind]!=9999) && (mint[m][iind]!=99) && (j==0)) {
4538: dateintsum=dateintsum+k2; /* on all covariates ?*/
4539: k2cpt++;
4540: /* printf("iind=%ld dateintmean = %lf dateintsum=%lf k2cpt=%lf k2=%lf\n",iind, dateintsum/k2cpt, dateintsum,k2cpt, k2); */
1.234 brouard 4541: }
1.251 brouard 4542: }else{
4543: bool=1;
4544: }/* end bool 2 */
4545: } /* end m */
4546: } /* end bool */
4547: } /* end iind = 1 to imx */
4548: /* prop[s][age] is feeded for any initial and valid live state as well as
4549: freq[s1][s2][age] at single age of beginning the transition, for a combination j1 */
4550:
4551:
4552: /* fprintf(ficresp, "#Count between %.lf/%.lf/%.lf and %.lf/%.lf/%.lf\n",jprev1, mprev1,anprev1,jprev2, mprev2,anprev2);*/
1.265 brouard 4553: if(cptcoveff==0 && nj==1) /* no covariate and first pass */
4554: pstamp(ficresp);
1.251 brouard 4555: if (cptcoveff>0 && j!=0){
1.265 brouard 4556: pstamp(ficresp);
1.251 brouard 4557: printf( "\n#********** Variable ");
4558: fprintf(ficresp, "\n#********** Variable ");
4559: fprintf(ficresphtm, "\n<br/><br/><h3>********** Variable ");
4560: fprintf(ficresphtmfr, "\n<br/><br/><h3>********** Variable ");
4561: fprintf(ficlog, "\n#********** Variable ");
4562: for (z1=1; z1<=cptcoveff; z1++){
4563: if(!FixedV[Tvaraff[z1]]){
4564: printf( "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4565: fprintf(ficresp, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4566: fprintf(ficresphtm, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4567: fprintf(ficresphtmfr, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4568: fprintf(ficlog, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
1.250 brouard 4569: }else{
1.251 brouard 4570: printf( "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4571: fprintf(ficresp, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4572: fprintf(ficresphtm, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4573: fprintf(ficresphtmfr, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4574: fprintf(ficlog, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4575: }
4576: }
4577: printf( "**********\n#");
4578: fprintf(ficresp, "**********\n#");
4579: fprintf(ficresphtm, "**********</h3>\n");
4580: fprintf(ficresphtmfr, "**********</h3>\n");
4581: fprintf(ficlog, "**********\n");
4582: }
4583: fprintf(ficresphtm,"<table style=\"text-align:center; border: 1px solid\">");
1.265 brouard 4584: if((cptcoveff==0 && nj==1)|| nj==2 ) /* no covariate and first pass */
4585: fprintf(ficresp, " Age");
4586: 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 4587: for(i=1; i<=nlstate;i++) {
1.265 brouard 4588: if((cptcoveff==0 && nj==1)|| nj==2 ) fprintf(ficresp," Prev(%d) N(%d) N ",i,i);
1.251 brouard 4589: fprintf(ficresphtm, "<th>Age</th><th>Prev(%d)</th><th>N(%d)</th><th>N</th>",i,i);
4590: }
1.265 brouard 4591: if((cptcoveff==0 && nj==1)|| nj==2 ) fprintf(ficresp, "\n");
1.251 brouard 4592: fprintf(ficresphtm, "\n");
4593:
4594: /* Header of frequency table by age */
4595: fprintf(ficresphtmfr,"<table style=\"text-align:center; border: 1px solid\">");
4596: fprintf(ficresphtmfr,"<th>Age</th> ");
1.265 brouard 4597: for(s2=-1; s2 <=nlstate+ndeath; s2++){
1.251 brouard 4598: for(m=-1; m <=nlstate+ndeath; m++){
1.265 brouard 4599: if(s2!=0 && m!=0)
4600: fprintf(ficresphtmfr,"<th>%d%d</th> ",s2,m);
1.240 brouard 4601: }
1.226 brouard 4602: }
1.251 brouard 4603: fprintf(ficresphtmfr, "\n");
4604:
4605: /* For each age */
4606: for(iage=iagemin; iage <= iagemax+3; iage++){
4607: fprintf(ficresphtm,"<tr>");
4608: if(iage==iagemax+1){
4609: fprintf(ficlog,"1");
4610: fprintf(ficresphtmfr,"<tr><th>0</th> ");
4611: }else if(iage==iagemax+2){
4612: fprintf(ficlog,"0");
4613: fprintf(ficresphtmfr,"<tr><th>Unknown</th> ");
4614: }else if(iage==iagemax+3){
4615: fprintf(ficlog,"Total");
4616: fprintf(ficresphtmfr,"<tr><th>Total</th> ");
4617: }else{
1.240 brouard 4618: if(first==1){
1.251 brouard 4619: first=0;
4620: printf("See log file for details...\n");
4621: }
4622: fprintf(ficresphtmfr,"<tr><th>%d</th> ",iage);
4623: fprintf(ficlog,"Age %d", iage);
4624: }
1.265 brouard 4625: for(s1=1; s1 <=nlstate ; s1++){
4626: for(m=-1, pp[s1]=0; m <=nlstate+ndeath ; m++)
4627: pp[s1] += freq[s1][m][iage];
1.251 brouard 4628: }
1.265 brouard 4629: for(s1=1; s1 <=nlstate ; s1++){
1.251 brouard 4630: for(m=-1, pos=0; m <=0 ; m++)
1.265 brouard 4631: pos += freq[s1][m][iage];
4632: if(pp[s1]>=1.e-10){
1.251 brouard 4633: if(first==1){
1.265 brouard 4634: printf(" %d.=%.0f loss[%d]=%.1f%%",s1,pp[s1],s1,100*pos/pp[s1]);
1.251 brouard 4635: }
1.265 brouard 4636: fprintf(ficlog," %d.=%.0f loss[%d]=%.1f%%",s1,pp[s1],s1,100*pos/pp[s1]);
1.251 brouard 4637: }else{
4638: if(first==1)
1.265 brouard 4639: printf(" %d.=%.0f loss[%d]=NaNQ%%",s1,pp[s1],s1);
4640: fprintf(ficlog," %d.=%.0f loss[%d]=NaNQ%%",s1,pp[s1],s1);
1.240 brouard 4641: }
4642: }
4643:
1.265 brouard 4644: for(s1=1; s1 <=nlstate ; s1++){
4645: /* posprop[s1]=0; */
4646: for(m=0, pp[s1]=0; m <=nlstate+ndeath; m++)/* Summing on all ages */
4647: pp[s1] += freq[s1][m][iage];
4648: } /* pp[s1] is the total number of transitions starting from state s1 and any ending status until this age */
4649:
4650: for(s1=1,pos=0, pospropta=0.; s1 <=nlstate ; s1++){
4651: pos += pp[s1]; /* pos is the total number of transitions until this age */
4652: posprop[s1] += prop[s1][iage]; /* prop is the number of transitions from a live state
4653: from s1 at age iage prop[s[m][iind]][(int)agev[m][iind]] += weight[iind] */
4654: pospropta += prop[s1][iage]; /* prop is the number of transitions from a live state
4655: from s1 at age iage prop[s[m][iind]][(int)agev[m][iind]] += weight[iind] */
4656: }
4657:
4658: /* Writing ficresp */
4659: if(cptcoveff==0 && nj==1){ /* no covariate and first pass */
4660: if( iage <= iagemax){
4661: fprintf(ficresp," %d",iage);
4662: }
4663: }else if( nj==2){
4664: if( iage <= iagemax){
4665: fprintf(ficresp," %d",iage);
4666: for (z1=1; z1<=cptcoveff; z1++) fprintf(ficresp, " %d %d",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4667: }
1.240 brouard 4668: }
1.265 brouard 4669: for(s1=1; s1 <=nlstate ; s1++){
1.240 brouard 4670: if(pos>=1.e-5){
1.251 brouard 4671: if(first==1)
1.265 brouard 4672: printf(" %d.=%.0f prev[%d]=%.1f%%",s1,pp[s1],s1,100*pp[s1]/pos);
4673: fprintf(ficlog," %d.=%.0f prev[%d]=%.1f%%",s1,pp[s1],s1,100*pp[s1]/pos);
1.251 brouard 4674: }else{
4675: if(first==1)
1.265 brouard 4676: printf(" %d.=%.0f prev[%d]=NaNQ%%",s1,pp[s1],s1);
4677: fprintf(ficlog," %d.=%.0f prev[%d]=NaNQ%%",s1,pp[s1],s1);
1.251 brouard 4678: }
4679: if( iage <= iagemax){
4680: if(pos>=1.e-5){
1.265 brouard 4681: if(cptcoveff==0 && nj==1){ /* no covariate and first pass */
4682: fprintf(ficresp," %.5f %.0f %.0f",prop[s1][iage]/pospropta, prop[s1][iage],pospropta);
4683: }else if( nj==2){
4684: fprintf(ficresp," %.5f %.0f %.0f",prop[s1][iage]/pospropta, prop[s1][iage],pospropta);
4685: }
4686: fprintf(ficresphtm,"<th>%d</th><td>%.5f</td><td>%.0f</td><td>%.0f</td>",iage,prop[s1][iage]/pospropta, prop[s1][iage],pospropta);
4687: /*probs[iage][s1][j1]= pp[s1]/pos;*/
4688: /*printf("\niage=%d s1=%d j1=%d %.5f %.0f %.0f %f",iage,s1,j1,pp[s1]/pos, pp[s1],pos,probs[iage][s1][j1]);*/
4689: } else{
4690: if((cptcoveff==0 && nj==1)|| nj==2 ) fprintf(ficresp," NaNq %.0f %.0f",prop[s1][iage],pospropta);
4691: fprintf(ficresphtm,"<th>%d</th><td>NaNq</td><td>%.0f</td><td>%.0f</td>",iage, prop[s1][iage],pospropta);
1.251 brouard 4692: }
1.240 brouard 4693: }
1.265 brouard 4694: pospropt[s1] +=posprop[s1];
4695: } /* end loop s1 */
1.251 brouard 4696: /* pospropt=0.; */
1.265 brouard 4697: for(s1=-1; s1 <=nlstate+ndeath; s1++){
1.251 brouard 4698: for(m=-1; m <=nlstate+ndeath; m++){
1.265 brouard 4699: if(freq[s1][m][iage] !=0 ) { /* minimizing output */
1.251 brouard 4700: if(first==1){
1.265 brouard 4701: printf(" %d%d=%.0f",s1,m,freq[s1][m][iage]);
1.251 brouard 4702: }
1.265 brouard 4703: /* printf(" %d%d=%.0f",s1,m,freq[s1][m][iage]); */
4704: fprintf(ficlog," %d%d=%.0f",s1,m,freq[s1][m][iage]);
1.251 brouard 4705: }
1.265 brouard 4706: if(s1!=0 && m!=0)
4707: fprintf(ficresphtmfr,"<td>%.0f</td> ",freq[s1][m][iage]);
1.240 brouard 4708: }
1.265 brouard 4709: } /* end loop s1 */
1.251 brouard 4710: posproptt=0.;
1.265 brouard 4711: for(s1=1; s1 <=nlstate; s1++){
4712: posproptt += pospropt[s1];
1.251 brouard 4713: }
4714: fprintf(ficresphtmfr,"</tr>\n ");
1.265 brouard 4715: fprintf(ficresphtm,"</tr>\n");
4716: if((cptcoveff==0 && nj==1)|| nj==2 ) {
4717: if(iage <= iagemax)
4718: fprintf(ficresp,"\n");
1.240 brouard 4719: }
1.251 brouard 4720: if(first==1)
4721: printf("Others in log...\n");
4722: fprintf(ficlog,"\n");
4723: } /* end loop age iage */
1.265 brouard 4724:
1.251 brouard 4725: fprintf(ficresphtm,"<tr><th>Tot</th>");
1.265 brouard 4726: for(s1=1; s1 <=nlstate ; s1++){
1.251 brouard 4727: if(posproptt < 1.e-5){
1.265 brouard 4728: fprintf(ficresphtm,"<td>Nanq</td><td>%.0f</td><td>%.0f</td>",pospropt[s1],posproptt);
1.251 brouard 4729: }else{
1.265 brouard 4730: fprintf(ficresphtm,"<td>%.5f</td><td>%.0f</td><td>%.0f</td>",pospropt[s1]/posproptt,pospropt[s1],posproptt);
1.240 brouard 4731: }
1.226 brouard 4732: }
1.251 brouard 4733: fprintf(ficresphtm,"</tr>\n");
4734: fprintf(ficresphtm,"</table>\n");
4735: fprintf(ficresphtmfr,"</table>\n");
1.226 brouard 4736: if(posproptt < 1.e-5){
1.251 brouard 4737: fprintf(ficresphtm,"\n <p><b> This combination (%d) is not valid and no result will be produced</b></p>",j1);
4738: fprintf(ficresphtmfr,"\n <p><b> This combination (%d) is not valid and no result will be produced</b></p>",j1);
1.260 brouard 4739: fprintf(ficlog,"# This combination (%d) is not valid and no result will be produced\n",j1);
4740: printf("# This combination (%d) is not valid and no result will be produced\n",j1);
1.251 brouard 4741: invalidvarcomb[j1]=1;
1.226 brouard 4742: }else{
1.251 brouard 4743: fprintf(ficresphtm,"\n <p> This combination (%d) is valid and result will be produced.</p>",j1);
4744: invalidvarcomb[j1]=0;
1.226 brouard 4745: }
1.251 brouard 4746: fprintf(ficresphtmfr,"</table>\n");
4747: fprintf(ficlog,"\n");
4748: if(j!=0){
4749: printf("#Freqsummary: Starting values for combination j1=%d:\n", j1);
1.265 brouard 4750: for(i=1,s1=1; i <=nlstate; i++){
1.251 brouard 4751: for(k=1; k <=(nlstate+ndeath); k++){
4752: if (k != i) {
1.265 brouard 4753: for(jj=1; jj <=ncovmodel; jj++){ /* For counting s1 */
1.253 brouard 4754: if(jj==1){ /* Constant case (in fact cste + age) */
1.251 brouard 4755: if(j1==1){ /* All dummy covariates to zero */
4756: freq[i][k][iagemax+4]=freq[i][k][iagemax+3]; /* Stores case 0 0 0 */
4757: freq[i][i][iagemax+4]=freq[i][i][iagemax+3]; /* Stores case 0 0 0 */
1.252 brouard 4758: printf("%d%d ",i,k);
4759: fprintf(ficlog,"%d%d ",i,k);
1.265 brouard 4760: 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]));
4761: 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]));
4762: pstart[s1]= log(freq[i][k][iagemax+3]/freq[i][i][iagemax+3]);
1.251 brouard 4763: }
1.253 brouard 4764: }else if((j1==1) && (jj==2 || nagesqr==1)){ /* age or age*age parameter without covariate V4*age (to be done later) */
4765: for(iage=iagemin; iage <= iagemax+3; iage++){
4766: x[iage]= (double)iage;
4767: y[iage]= log(freq[i][k][iage]/freq[i][i][iage]);
1.265 brouard 4768: /* 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 4769: }
1.268 brouard 4770: /* Some are not finite, but linreg will ignore these ages */
4771: no=0;
1.253 brouard 4772: linreg(iagemin,iagemax,&no,x,y,&a,&b,&r, &sa, &sb ); /* y= a+b*x with standard errors */
1.265 brouard 4773: pstart[s1]=b;
4774: pstart[s1-1]=a;
1.252 brouard 4775: }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 */
4776: 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]);
4777: 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 4778: 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 4779: printf("%d%d ",i,k);
4780: fprintf(ficlog,"%d%d ",i,k);
1.265 brouard 4781: 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 4782: }else{ /* Other cases, like quantitative fixed or varying covariates */
4783: ;
4784: }
4785: /* printf("%12.7f )", param[i][jj][k]); */
4786: /* fprintf(ficlog,"%12.7f )", param[i][jj][k]); */
1.265 brouard 4787: s1++;
1.251 brouard 4788: } /* end jj */
4789: } /* end k!= i */
4790: } /* end k */
1.265 brouard 4791: } /* end i, s1 */
1.251 brouard 4792: } /* end j !=0 */
4793: } /* end selected combination of covariate j1 */
4794: if(j==0){ /* We can estimate starting values from the occurences in each case */
4795: printf("#Freqsummary: Starting values for the constants:\n");
4796: fprintf(ficlog,"\n");
1.265 brouard 4797: for(i=1,s1=1; i <=nlstate; i++){
1.251 brouard 4798: for(k=1; k <=(nlstate+ndeath); k++){
4799: if (k != i) {
4800: printf("%d%d ",i,k);
4801: fprintf(ficlog,"%d%d ",i,k);
4802: for(jj=1; jj <=ncovmodel; jj++){
1.265 brouard 4803: pstart[s1]=p[s1]; /* Setting pstart to p values by default */
1.253 brouard 4804: if(jj==1){ /* Age has to be done */
1.265 brouard 4805: pstart[s1]= log(freq[i][k][iagemax+3]/freq[i][i][iagemax+3]);
4806: 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]));
4807: 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 4808: }
4809: /* printf("%12.7f )", param[i][jj][k]); */
4810: /* fprintf(ficlog,"%12.7f )", param[i][jj][k]); */
1.265 brouard 4811: s1++;
1.250 brouard 4812: }
1.251 brouard 4813: printf("\n");
4814: fprintf(ficlog,"\n");
1.250 brouard 4815: }
4816: }
4817: }
1.251 brouard 4818: printf("#Freqsummary\n");
4819: fprintf(ficlog,"\n");
1.265 brouard 4820: for(s1=-1; s1 <=nlstate+ndeath; s1++){
4821: for(s2=-1; s2 <=nlstate+ndeath; s2++){
4822: /* param[i]|j][k]= freq[s1][s2][iagemax+3] */
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]);
4825: /* if(freq[s1][s2][iage] !=0 ) { /\* minimizing output *\/ */
4826: /* printf(" %d%d=%.0f",s1,s2,freq[s1][s2][iagemax+3]); */
4827: /* fprintf(ficlog," %d%d=%.0f",s1,s2,freq[s1][s2][iagemax+3]); */
1.251 brouard 4828: /* } */
4829: }
1.265 brouard 4830: } /* end loop s1 */
1.251 brouard 4831:
4832: printf("\n");
4833: fprintf(ficlog,"\n");
4834: } /* end j=0 */
1.249 brouard 4835: } /* end j */
1.252 brouard 4836:
1.253 brouard 4837: if(mle == -2){ /* We want to use these values as starting values */
1.252 brouard 4838: for(i=1, jk=1; i <=nlstate; i++){
4839: for(j=1; j <=nlstate+ndeath; j++){
4840: if(j!=i){
4841: /*ca[0]= k+'a'-1;ca[1]='\0';*/
4842: printf("%1d%1d",i,j);
4843: fprintf(ficparo,"%1d%1d",i,j);
4844: for(k=1; k<=ncovmodel;k++){
4845: /* printf(" %lf",param[i][j][k]); */
4846: /* fprintf(ficparo," %lf",param[i][j][k]); */
4847: p[jk]=pstart[jk];
4848: printf(" %f ",pstart[jk]);
4849: fprintf(ficparo," %f ",pstart[jk]);
4850: jk++;
4851: }
4852: printf("\n");
4853: fprintf(ficparo,"\n");
4854: }
4855: }
4856: }
4857: } /* end mle=-2 */
1.226 brouard 4858: dateintmean=dateintsum/k2cpt;
1.240 brouard 4859:
1.226 brouard 4860: fclose(ficresp);
4861: fclose(ficresphtm);
4862: fclose(ficresphtmfr);
4863: free_vector(meanq,1,nqfveff);
4864: free_matrix(meanqt,1,lastpass,1,nqtveff);
1.253 brouard 4865: free_vector(x, iagemin-AGEMARGE, iagemax+4+AGEMARGE);
4866: free_vector(y, iagemin-AGEMARGE, iagemax+4+AGEMARGE);
1.251 brouard 4867: free_ma3x(freq,-5,nlstate+ndeath,-5,nlstate+ndeath, iagemin-AGEMARGE, iagemax+4+AGEMARGE);
1.226 brouard 4868: free_vector(pospropt,1,nlstate);
4869: free_vector(posprop,1,nlstate);
1.251 brouard 4870: free_matrix(prop,1,nlstate,iagemin-AGEMARGE, iagemax+4+AGEMARGE);
1.226 brouard 4871: free_vector(pp,1,nlstate);
4872: /* End of freqsummary */
4873: }
1.126 brouard 4874:
1.268 brouard 4875: /* Simple linear regression */
4876: int linreg(int ifi, int ila, int *no, const double x[], const double y[], double* a, double* b, double* r, double* sa, double * sb) {
4877:
4878: /* y=a+bx regression */
4879: double sumx = 0.0; /* sum of x */
4880: double sumx2 = 0.0; /* sum of x**2 */
4881: double sumxy = 0.0; /* sum of x * y */
4882: double sumy = 0.0; /* sum of y */
4883: double sumy2 = 0.0; /* sum of y**2 */
4884: double sume2 = 0.0; /* sum of square or residuals */
4885: double yhat;
4886:
4887: double denom=0;
4888: int i;
4889: int ne=*no;
4890:
4891: for ( i=ifi, ne=0;i<=ila;i++) {
4892: if(!isfinite(x[i]) || !isfinite(y[i])){
4893: /* printf(" x[%d]=%f, y[%d]=%f\n",i,x[i],i,y[i]); */
4894: continue;
4895: }
4896: ne=ne+1;
4897: sumx += x[i];
4898: sumx2 += x[i]*x[i];
4899: sumxy += x[i] * y[i];
4900: sumy += y[i];
4901: sumy2 += y[i]*y[i];
4902: denom = (ne * sumx2 - sumx*sumx);
4903: /* 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); */
4904: }
4905:
4906: denom = (ne * sumx2 - sumx*sumx);
4907: if (denom == 0) {
4908: // vertical, slope m is infinity
4909: *b = INFINITY;
4910: *a = 0;
4911: if (r) *r = 0;
4912: return 1;
4913: }
4914:
4915: *b = (ne * sumxy - sumx * sumy) / denom;
4916: *a = (sumy * sumx2 - sumx * sumxy) / denom;
4917: if (r!=NULL) {
4918: *r = (sumxy - sumx * sumy / ne) / /* compute correlation coeff */
4919: sqrt((sumx2 - sumx*sumx/ne) *
4920: (sumy2 - sumy*sumy/ne));
4921: }
4922: *no=ne;
4923: for ( i=ifi, ne=0;i<=ila;i++) {
4924: if(!isfinite(x[i]) || !isfinite(y[i])){
4925: /* printf(" x[%d]=%f, y[%d]=%f\n",i,x[i],i,y[i]); */
4926: continue;
4927: }
4928: ne=ne+1;
4929: yhat = y[i] - *a -*b* x[i];
4930: sume2 += yhat * yhat ;
4931:
4932: denom = (ne * sumx2 - sumx*sumx);
4933: /* 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); */
4934: }
4935: *sb = sqrt(sume2/(double)(ne-2)/(sumx2 - sumx * sumx /(double)ne));
4936: *sa= *sb * sqrt(sumx2/ne);
4937:
4938: return 0;
4939: }
4940:
1.126 brouard 4941: /************ Prevalence ********************/
1.227 brouard 4942: 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)
4943: {
4944: /* Compute observed prevalence between dateprev1 and dateprev2 by counting the number of people
4945: in each health status at the date of interview (if between dateprev1 and dateprev2).
4946: We still use firstpass and lastpass as another selection.
4947: */
1.126 brouard 4948:
1.227 brouard 4949: int i, m, jk, j1, bool, z1,j, iv;
4950: int mi; /* Effective wave */
4951: int iage;
4952: double agebegin, ageend;
4953:
4954: double **prop;
4955: double posprop;
4956: double y2; /* in fractional years */
4957: int iagemin, iagemax;
4958: int first; /** to stop verbosity which is redirected to log file */
4959:
4960: iagemin= (int) agemin;
4961: iagemax= (int) agemax;
4962: /*pp=vector(1,nlstate);*/
1.251 brouard 4963: prop=matrix(1,nlstate,iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.227 brouard 4964: /* freq=ma3x(-1,nlstate+ndeath,-1,nlstate+ndeath,iagemin,iagemax+3);*/
4965: j1=0;
1.222 brouard 4966:
1.227 brouard 4967: /*j=cptcoveff;*/
4968: if (cptcovn<1) {j=1;ncodemax[1]=1;}
1.222 brouard 4969:
1.227 brouard 4970: first=1;
4971: for(j1=1; j1<= (int) pow(2,cptcoveff);j1++){ /* For each combination of covariate */
4972: for (i=1; i<=nlstate; i++)
1.251 brouard 4973: for(iage=iagemin-AGEMARGE; iage <= iagemax+4+AGEMARGE; iage++)
1.227 brouard 4974: prop[i][iage]=0.0;
4975: printf("Prevalence combination of varying and fixed dummies %d\n",j1);
4976: /* fprintf(ficlog," V%d=%d ",Tvaraff[j1],nbcode[Tvaraff[j1]][codtabm(k,j1)]); */
4977: fprintf(ficlog,"Prevalence combination of varying and fixed dummies %d\n",j1);
4978:
4979: for (i=1; i<=imx; i++) { /* Each individual */
4980: bool=1;
4981: /* for(m=firstpass; m<=lastpass; m++){/\* Other selection (we can limit to certain interviews*\/ */
4982: for(mi=1; mi<wav[i];mi++){ /* For this wave too look where individual can be counted V4=0 V3=0 */
4983: m=mw[mi][i];
4984: /* Tmodelind[z1]=k is the position of the varying covariate in the model, but which # within 1 to ntv? */
4985: /* Tvar[Tmodelind[z1]] is the n of Vn; n-ncovcol-nqv is the first time varying covariate or iv */
4986: for (z1=1; z1<=cptcoveff; z1++){
4987: if( Fixed[Tmodelind[z1]]==1){
4988: iv= Tvar[Tmodelind[z1]]-ncovcol-nqv;
4989: if (cotvar[m][iv][i]!= nbcode[Tvaraff[z1]][codtabm(j1,z1)]) /* iv=1 to ntv, right modality */
4990: bool=0;
4991: }else if( Fixed[Tmodelind[z1]]== 0) /* fixed */
4992: if (covar[Tvaraff[z1]][i]!= nbcode[Tvaraff[z1]][codtabm(j1,z1)]) {
4993: bool=0;
4994: }
4995: }
4996: if(bool==1){ /* Otherwise we skip that wave/person */
4997: agebegin=agev[m][i]; /* Age at beginning of wave before transition*/
4998: /* ageend=agev[m][i]+(dh[m][i])*stepm/YEARM; /\* Age at end of wave and transition *\/ */
4999: if(m >=firstpass && m <=lastpass){
5000: y2=anint[m][i]+(mint[m][i]/12.); /* Fractional date in year */
5001: if ((y2>=dateprev1) && (y2<=dateprev2)) { /* Here is the main selection (fractional years) */
5002: if(agev[m][i]==0) agev[m][i]=iagemax+1;
5003: if(agev[m][i]==1) agev[m][i]=iagemax+2;
1.251 brouard 5004: if((int)agev[m][i] <iagemin-AGEMARGE || (int)agev[m][i] >iagemax+4+AGEMARGE){
1.227 brouard 5005: 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);
5006: exit(1);
5007: }
5008: if (s[m][i]>0 && s[m][i]<=nlstate) {
5009: /*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]]);*/
5010: prop[s[m][i]][(int)agev[m][i]] += weight[i];/* At age of beginning of transition, where status is known */
5011: prop[s[m][i]][iagemax+3] += weight[i];
5012: } /* end valid statuses */
5013: } /* end selection of dates */
5014: } /* end selection of waves */
5015: } /* end bool */
5016: } /* end wave */
5017: } /* end individual */
5018: for(i=iagemin; i <= iagemax+3; i++){
5019: for(jk=1,posprop=0; jk <=nlstate ; jk++) {
5020: posprop += prop[jk][i];
5021: }
5022:
5023: for(jk=1; jk <=nlstate ; jk++){
5024: if( i <= iagemax){
5025: if(posprop>=1.e-5){
5026: probs[i][jk][j1]= prop[jk][i]/posprop;
5027: } else{
5028: if(first==1){
5029: first=0;
1.266 brouard 5030: 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]);
5031: 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]);
5032: }else{
5033: 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 5034: }
5035: }
5036: }
5037: }/* end jk */
5038: }/* end i */
1.222 brouard 5039: /*} *//* end i1 */
1.227 brouard 5040: } /* end j1 */
1.222 brouard 5041:
1.227 brouard 5042: /* free_ma3x(freq,-1,nlstate+ndeath,-1,nlstate+ndeath, iagemin, iagemax+3);*/
5043: /*free_vector(pp,1,nlstate);*/
1.251 brouard 5044: free_matrix(prop,1,nlstate, iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.227 brouard 5045: } /* End of prevalence */
1.126 brouard 5046:
5047: /************* Waves Concatenation ***************/
5048:
5049: 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)
5050: {
5051: /* Concatenates waves: wav[i] is the number of effective (useful waves) of individual i.
5052: Death is a valid wave (if date is known).
5053: mw[mi][i] is the mi (mi=1 to wav[i]) effective wave of individual i
5054: dh[m][i] or dh[mw[mi][i]][i] is the delay between two effective waves m=mw[mi][i]
5055: and mw[mi+1][i]. dh depends on stepm.
1.227 brouard 5056: */
1.126 brouard 5057:
1.224 brouard 5058: int i=0, mi=0, m=0, mli=0;
1.126 brouard 5059: /* int j, k=0,jk, ju, jl,jmin=1e+5, jmax=-1;
5060: double sum=0., jmean=0.;*/
1.224 brouard 5061: int first=0, firstwo=0, firsthree=0, firstfour=0, firstfiv=0;
1.126 brouard 5062: int j, k=0,jk, ju, jl;
5063: double sum=0.;
5064: first=0;
1.214 brouard 5065: firstwo=0;
1.217 brouard 5066: firsthree=0;
1.218 brouard 5067: firstfour=0;
1.164 brouard 5068: jmin=100000;
1.126 brouard 5069: jmax=-1;
5070: jmean=0.;
1.224 brouard 5071:
5072: /* Treating live states */
1.214 brouard 5073: for(i=1; i<=imx; i++){ /* For simple cases and if state is death */
1.224 brouard 5074: mi=0; /* First valid wave */
1.227 brouard 5075: mli=0; /* Last valid wave */
1.126 brouard 5076: m=firstpass;
1.214 brouard 5077: while(s[m][i] <= nlstate){ /* a live state */
1.227 brouard 5078: 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 */
5079: mli=m-1;/* mw[++mi][i]=m-1; */
5080: }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 */
5081: mw[++mi][i]=m;
5082: mli=m;
1.224 brouard 5083: } /* else might be a useless wave -1 and mi is not incremented and mw[mi] not updated */
5084: if(m < lastpass){ /* m < lastpass, standard case */
1.227 brouard 5085: m++; /* mi gives the "effective" current wave, m the current wave, go to next wave by incrementing m */
1.216 brouard 5086: }
1.227 brouard 5087: else{ /* m >= lastpass, eventual special issue with warning */
1.224 brouard 5088: #ifdef UNKNOWNSTATUSNOTCONTRIBUTING
1.227 brouard 5089: break;
1.224 brouard 5090: #else
1.227 brouard 5091: if(s[m][i]==-1 && (int) andc[i] == 9999 && (int)anint[m][i] != 9999){
5092: if(firsthree == 0){
1.262 brouard 5093: 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 5094: firsthree=1;
5095: }
1.262 brouard 5096: 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 5097: mw[++mi][i]=m;
5098: mli=m;
5099: }
5100: if(s[m][i]==-2){ /* Vital status is really unknown */
5101: nbwarn++;
5102: if((int)anint[m][i] == 9999){ /* Has the vital status really been verified? */
5103: 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);
5104: 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);
5105: }
5106: break;
5107: }
5108: break;
1.224 brouard 5109: #endif
1.227 brouard 5110: }/* End m >= lastpass */
1.126 brouard 5111: }/* end while */
1.224 brouard 5112:
1.227 brouard 5113: /* 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 5114: /* After last pass */
1.224 brouard 5115: /* Treating death states */
1.214 brouard 5116: if (s[m][i] > nlstate){ /* In a death state */
1.227 brouard 5117: /* if( mint[m][i]==mdc[m][i] && anint[m][i]==andc[m][i]){ /\* same date of death and date of interview *\/ */
5118: /* } */
1.126 brouard 5119: mi++; /* Death is another wave */
5120: /* if(mi==0) never been interviewed correctly before death */
1.227 brouard 5121: /* Only death is a correct wave */
1.126 brouard 5122: mw[mi][i]=m;
1.257 brouard 5123: } /* else not in a death state */
1.224 brouard 5124: #ifndef DISPATCHINGKNOWNDEATHAFTERLASTWAVE
1.257 brouard 5125: else if ((int) andc[i] != 9999) { /* Date of death is known */
1.218 brouard 5126: if ((int)anint[m][i]!= 9999) { /* date of last interview is known */
1.227 brouard 5127: 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 */
5128: nbwarn++;
5129: if(firstfiv==0){
5130: 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 );
5131: firstfiv=1;
5132: }else{
5133: 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 );
5134: }
5135: }else{ /* Death occured afer last wave potential bias */
5136: nberr++;
5137: if(firstwo==0){
1.257 brouard 5138: 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 5139: firstwo=1;
5140: }
1.257 brouard 5141: 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 5142: }
1.257 brouard 5143: }else{ /* if date of interview is unknown */
1.227 brouard 5144: /* death is known but not confirmed by death status at any wave */
5145: if(firstfour==0){
5146: 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 );
5147: firstfour=1;
5148: }
5149: 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 5150: }
1.224 brouard 5151: } /* end if date of death is known */
5152: #endif
5153: wav[i]=mi; /* mi should be the last effective wave (or mli) */
5154: /* wav[i]=mw[mi][i]; */
1.126 brouard 5155: if(mi==0){
5156: nbwarn++;
5157: if(first==0){
1.227 brouard 5158: printf("Warning! No valid information for individual %ld line=%d (skipped) and may be others, see log file\n",num[i],i);
5159: first=1;
1.126 brouard 5160: }
5161: if(first==1){
1.227 brouard 5162: fprintf(ficlog,"Warning! No valid information for individual %ld line=%d (skipped)\n",num[i],i);
1.126 brouard 5163: }
5164: } /* end mi==0 */
5165: } /* End individuals */
1.214 brouard 5166: /* wav and mw are no more changed */
1.223 brouard 5167:
1.214 brouard 5168:
1.126 brouard 5169: for(i=1; i<=imx; i++){
5170: for(mi=1; mi<wav[i];mi++){
5171: if (stepm <=0)
1.227 brouard 5172: dh[mi][i]=1;
1.126 brouard 5173: else{
1.260 brouard 5174: if (s[mw[mi+1][i]][i] > nlstate) { /* A death, but what if date is unknown? */
1.227 brouard 5175: if (agedc[i] < 2*AGESUP) {
5176: j= rint(agedc[i]*12-agev[mw[mi][i]][i]*12);
5177: if(j==0) j=1; /* Survives at least one month after exam */
5178: else if(j<0){
5179: nberr++;
5180: 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]);
5181: j=1; /* Temporary Dangerous patch */
5182: 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);
5183: 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]);
5184: 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);
5185: }
5186: k=k+1;
5187: if (j >= jmax){
5188: jmax=j;
5189: ijmax=i;
5190: }
5191: if (j <= jmin){
5192: jmin=j;
5193: ijmin=i;
5194: }
5195: sum=sum+j;
5196: /*if (j<0) printf("j=%d num=%d \n",j,i);*/
5197: /* printf("%d %d %d %d\n", s[mw[mi][i]][i] ,s[mw[mi+1][i]][i],j,i);*/
5198: }
5199: }
5200: else{
5201: j= rint( (agev[mw[mi+1][i]][i]*12 - agev[mw[mi][i]][i]*12));
1.126 brouard 5202: /* 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 5203:
1.227 brouard 5204: k=k+1;
5205: if (j >= jmax) {
5206: jmax=j;
5207: ijmax=i;
5208: }
5209: else if (j <= jmin){
5210: jmin=j;
5211: ijmin=i;
5212: }
5213: /* if (j<10) printf("j=%d jmin=%d num=%d ",j,jmin,i); */
5214: /*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]);*/
5215: if(j<0){
5216: nberr++;
5217: 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]);
5218: 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]);
5219: }
5220: sum=sum+j;
5221: }
5222: jk= j/stepm;
5223: jl= j -jk*stepm;
5224: ju= j -(jk+1)*stepm;
5225: if(mle <=1){ /* only if we use a the linear-interpoloation pseudo-likelihood */
5226: if(jl==0){
5227: dh[mi][i]=jk;
5228: bh[mi][i]=0;
5229: }else{ /* We want a negative bias in order to only have interpolation ie
5230: * to avoid the price of an extra matrix product in likelihood */
5231: dh[mi][i]=jk+1;
5232: bh[mi][i]=ju;
5233: }
5234: }else{
5235: if(jl <= -ju){
5236: dh[mi][i]=jk;
5237: bh[mi][i]=jl; /* bias is positive if real duration
5238: * is higher than the multiple of stepm and negative otherwise.
5239: */
5240: }
5241: else{
5242: dh[mi][i]=jk+1;
5243: bh[mi][i]=ju;
5244: }
5245: if(dh[mi][i]==0){
5246: dh[mi][i]=1; /* At least one step */
5247: bh[mi][i]=ju; /* At least one step */
5248: /* 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);*/
5249: }
5250: } /* end if mle */
1.126 brouard 5251: }
5252: } /* end wave */
5253: }
5254: jmean=sum/k;
5255: 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 5256: 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 5257: }
1.126 brouard 5258:
5259: /*********** Tricode ****************************/
1.220 brouard 5260: void tricode(int *cptcov, int *Tvar, int **nbcode, int imx, int *Ndum)
1.242 brouard 5261: {
5262: /**< Uses cptcovn+2*cptcovprod as the number of covariates */
5263: /* Tvar[i]=atoi(stre); find 'n' in Vn and stores in Tvar. If model=V2+V1 Tvar[1]=2 and Tvar[2]=1
5264: * Boring subroutine which should only output nbcode[Tvar[j]][k]
5265: * Tvar[5] in V2+V1+V3*age+V2*V4 is 4 (V4) even it is a time varying or quantitative variable
5266: * nbcode[Tvar[5]][1]= nbcode[4][1]=0, nbcode[4][2]=1 (usually);
5267: */
1.130 brouard 5268:
1.242 brouard 5269: int ij=1, k=0, j=0, i=0, maxncov=NCOVMAX;
5270: int modmaxcovj=0; /* Modality max of covariates j */
5271: int cptcode=0; /* Modality max of covariates j */
5272: int modmincovj=0; /* Modality min of covariates j */
1.145 brouard 5273:
5274:
1.242 brouard 5275: /* cptcoveff=0; */
5276: /* *cptcov=0; */
1.126 brouard 5277:
1.242 brouard 5278: for (k=1; k <= maxncov; k++) ncodemax[k]=0; /* Horrible constant again replaced by NCOVMAX */
1.126 brouard 5279:
1.242 brouard 5280: /* Loop on covariates without age and products and no quantitative variable */
5281: /* for (j=1; j<=(cptcovs); j++) { /\* From model V1 + V2*age+ V3 + V3*V4 keeps V1 + V3 = 2 only *\/ */
5282: for (k=1; k<=cptcovt; k++) { /* From model V1 + V2*age + V3 + V3*V4 keeps V1 + V3 = 2 only */
5283: for (j=-1; (j < maxncov); j++) Ndum[j]=0;
5284: if(Dummy[k]==0 && Typevar[k] !=1){ /* Dummy covariate and not age product */
5285: switch(Fixed[k]) {
5286: case 0: /* Testing on fixed dummy covariate, simple or product of fixed */
5287: 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*/
5288: ij=(int)(covar[Tvar[k]][i]);
5289: /* ij=0 or 1 or -1. Value of the covariate Tvar[j] for individual i
5290: * If product of Vn*Vm, still boolean *:
5291: * If it was coded 1, 2, 3, 4 should be splitted into 3 boolean variables
5292: * 1 => 0 0 0, 2 => 0 0 1, 3 => 0 1 1, 4=1 0 0 */
5293: /* Finds for covariate j, n=Tvar[j] of Vn . ij is the
5294: modality of the nth covariate of individual i. */
5295: if (ij > modmaxcovj)
5296: modmaxcovj=ij;
5297: else if (ij < modmincovj)
5298: modmincovj=ij;
5299: if ((ij < -1) && (ij > NCOVMAX)){
5300: printf( "Error: minimal is less than -1 or maximal is bigger than %d. Exiting. \n", NCOVMAX );
5301: exit(1);
5302: }else
5303: Ndum[ij]++; /*counts and stores the occurence of this modality 0, 1, -1*/
5304: /* If coded 1, 2, 3 , counts the number of 1 Ndum[1], number of 2, Ndum[2], etc */
5305: /*printf("i=%d ij=%d Ndum[ij]=%d imx=%d",i,ij,Ndum[ij],imx);*/
5306: /* getting the maximum value of the modality of the covariate
5307: (should be 0 or 1 now) Tvar[j]. If V=sex and male is coded 0 and
5308: female ies 1, then modmaxcovj=1.
5309: */
5310: } /* end for loop on individuals i */
5311: printf(" Minimal and maximal values of %d th (fixed) covariate V%d: min=%d max=%d \n", k, Tvar[k], modmincovj, modmaxcovj);
5312: fprintf(ficlog," Minimal and maximal values of %d th (fixed) covariate V%d: min=%d max=%d \n", k, Tvar[k], modmincovj, modmaxcovj);
5313: cptcode=modmaxcovj;
5314: /* Ndum[0] = frequency of 0 for model-covariate j, Ndum[1] frequency of 1 etc. */
5315: /*for (i=0; i<=cptcode; i++) {*/
5316: for (j=modmincovj; j<=modmaxcovj; j++) { /* j=-1 ? 0 and 1*//* For each value j of the modality of model-cov k */
5317: printf("Frequencies of (fixed) covariate %d ie V%d with value %d: %d\n", k, Tvar[k], j, Ndum[j]);
5318: fprintf(ficlog, "Frequencies of (fixed) covariate %d ie V%d with value %d: %d\n", k, Tvar[k], j, Ndum[j]);
5319: if( Ndum[j] != 0 ){ /* Counts if nobody answered modality j ie empty modality, we skip it and reorder */
5320: if( j != -1){
5321: ncodemax[k]++; /* ncodemax[k]= Number of modalities of the k th
5322: covariate for which somebody answered excluding
5323: undefined. Usually 2: 0 and 1. */
5324: }
5325: ncodemaxwundef[k]++; /* ncodemax[j]= Number of modalities of the k th
5326: covariate for which somebody answered including
5327: undefined. Usually 3: -1, 0 and 1. */
5328: } /* In fact ncodemax[k]=2 (dichotom. variables only) but it could be more for
5329: * historical reasons: 3 if coded 1, 2, 3 and 4 and Ndum[2]=0 */
5330: } /* Ndum[-1] number of undefined modalities */
1.231 brouard 5331:
1.242 brouard 5332: /* j is a covariate, n=Tvar[j] of Vn; Fills nbcode */
5333: /* For covariate j, modalities could be 1, 2, 3, 4, 5, 6, 7. */
5334: /* If Ndum[1]=0, Ndum[2]=0, Ndum[3]= 635, Ndum[4]=0, Ndum[5]=0, Ndum[6]=27, Ndum[7]=125; */
5335: /* modmincovj=3; modmaxcovj = 7; */
5336: /* There are only 3 modalities non empty 3, 6, 7 (or 2 if 27 is too few) : ncodemax[j]=3; */
5337: /* which will be coded 0, 1, 2 which in binary on 2=3-1 digits are 0=00 1=01, 2=10; */
5338: /* defining two dummy variables: variables V1_1 and V1_2.*/
5339: /* nbcode[Tvar[j]][ij]=k; */
5340: /* nbcode[Tvar[j]][1]=0; */
5341: /* nbcode[Tvar[j]][2]=1; */
5342: /* nbcode[Tvar[j]][3]=2; */
5343: /* To be continued (not working yet). */
5344: ij=0; /* ij is similar to i but can jump over null modalities */
5345: 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*/
5346: if (Ndum[i] == 0) { /* If nobody responded to this modality k */
5347: break;
5348: }
5349: ij++;
5350: 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*/
5351: cptcode = ij; /* New max modality for covar j */
5352: } /* end of loop on modality i=-1 to 1 or more */
5353: break;
5354: case 1: /* Testing on varying covariate, could be simple and
5355: * should look at waves or product of fixed *
5356: * varying. No time to test -1, assuming 0 and 1 only */
5357: ij=0;
5358: for(i=0; i<=1;i++){
5359: nbcode[Tvar[k]][++ij]=i;
5360: }
5361: break;
5362: default:
5363: break;
5364: } /* end switch */
5365: } /* end dummy test */
5366:
5367: /* for (k=0; k<= cptcode; k++) { /\* k=-1 ? k=0 to 1 *\//\* Could be 1 to 4 *\//\* cptcode=modmaxcovj *\/ */
5368: /* /\*recode from 0 *\/ */
5369: /* k is a modality. If we have model=V1+V1*sex */
5370: /* then: nbcode[1][1]=0 ; nbcode[1][2]=1; nbcode[2][1]=0 ; nbcode[2][2]=1; */
5371: /* But if some modality were not used, it is recoded from 0 to a newer modmaxcovj=cptcode *\/ */
5372: /* } */
5373: /* /\* cptcode = ij; *\/ /\* New max modality for covar j *\/ */
5374: /* if (ij > ncodemax[j]) { */
5375: /* printf( " Error ij=%d > ncodemax[%d]=%d\n", ij, j, ncodemax[j]); */
5376: /* fprintf(ficlog, " Error ij=%d > ncodemax[%d]=%d\n", ij, j, ncodemax[j]); */
5377: /* break; */
5378: /* } */
5379: /* } /\* end of loop on modality k *\/ */
5380: } /* end of loop on model-covariate j. nbcode[Tvarj][1]=0 and nbcode[Tvarj][2]=1 sets the value of covariate j*/
5381:
5382: for (k=-1; k< maxncov; k++) Ndum[k]=0;
5383: /* Look at fixed dummy (single or product) covariates to check empty modalities */
5384: for (i=1; i<=ncovmodel-2-nagesqr; i++) { /* -2, cste and age and eventually age*age */
5385: /* Listing of all covariables in statement model to see if some covariates appear twice. For example, V1 appears twice in V1+V1*V2.*/
5386: 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 */
5387: 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 */
5388: /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, {2, 1, 1, 1, 2, 1, 1, 0, 0} */
5389: } /* V4+V3+V5, Ndum[1]@5={0, 0, 1, 1, 1} */
5390:
5391: ij=0;
5392: /* for (i=0; i<= maxncov-1; i++) { /\* modmaxcovj is unknown here. Only Ndum[2(V2),3(age*V3), 5(V3*V2) 6(V1*V4) *\/ */
5393: for (k=1; k<= cptcovt; k++) { /* modmaxcovj is unknown here. Only Ndum[2(V2),3(age*V3), 5(V3*V2) 6(V1*V4) */
5394: /*printf("Ndum[%d]=%d\n",i, Ndum[i]);*/
5395: /* if((Ndum[i]!=0) && (i<=ncovcol)){ /\* Tvar[i] <= ncovmodel ? *\/ */
5396: if(Ndum[Tvar[k]]!=0 && Dummy[k] == 0 && Typevar[k]==0){ /* Only Dummy and non empty in the model */
5397: /* If product not in single variable we don't print results */
5398: /*printf("diff Ndum[%d]=%d\n",i, Ndum[i]);*/
5399: ++ij;/* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, */
5400: 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*/
5401: Tmodelind[ij]=k; /* Tmodelind: index in model of dummies Tmodelind[1]=2 V4: pos=2; V3: pos=3, V1=9 {2, 3, 9, ?, ?,} */
5402: 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 */
5403: if(Fixed[k]!=0)
5404: anyvaryingduminmodel=1;
5405: /* }else if((Ndum[i]!=0) && (i<=ncovcol+nqv)){ */
5406: /* Tvaraff[++ij]=-10; /\* Dont'n know how to treat quantitative variables yet *\/ */
5407: /* }else if((Ndum[i]!=0) && (i<=ncovcol+nqv+ntv)){ */
5408: /* Tvaraff[++ij]=i; /\*For printing (unclear) *\/ */
5409: /* }else if((Ndum[i]!=0) && (i<=ncovcol+nqv+ntv+nqtv)){ */
5410: /* Tvaraff[++ij]=-20; /\* Dont'n know how to treat quantitative variables yet *\/ */
5411: }
5412: } /* Tvaraff[1]@5 {3, 4, -20, 0, 0} Very strange */
5413: /* ij--; */
5414: /* cptcoveff=ij; /\*Number of total covariates*\/ */
5415: *cptcov=ij; /*Number of total real effective covariates: effective
5416: * because they can be excluded from the model and real
5417: * if in the model but excluded because missing values, but how to get k from ij?*/
5418: for(j=ij+1; j<= cptcovt; j++){
5419: Tvaraff[j]=0;
5420: Tmodelind[j]=0;
5421: }
5422: for(j=ntveff+1; j<= cptcovt; j++){
5423: TmodelInvind[j]=0;
5424: }
5425: /* To be sorted */
5426: ;
5427: }
1.126 brouard 5428:
1.145 brouard 5429:
1.126 brouard 5430: /*********** Health Expectancies ****************/
5431:
1.235 brouard 5432: 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 5433:
5434: {
5435: /* Health expectancies, no variances */
1.164 brouard 5436: int i, j, nhstepm, hstepm, h, nstepm;
1.126 brouard 5437: int nhstepma, nstepma; /* Decreasing with age */
5438: double age, agelim, hf;
5439: double ***p3mat;
5440: double eip;
5441:
1.238 brouard 5442: /* pstamp(ficreseij); */
1.126 brouard 5443: fprintf(ficreseij,"# (a) Life expectancies by health status at initial age and (b) health expectancies by health status at initial age\n");
5444: fprintf(ficreseij,"# Age");
5445: for(i=1; i<=nlstate;i++){
5446: for(j=1; j<=nlstate;j++){
5447: fprintf(ficreseij," e%1d%1d ",i,j);
5448: }
5449: fprintf(ficreseij," e%1d. ",i);
5450: }
5451: fprintf(ficreseij,"\n");
5452:
5453:
5454: if(estepm < stepm){
5455: printf ("Problem %d lower than %d\n",estepm, stepm);
5456: }
5457: else hstepm=estepm;
5458: /* We compute the life expectancy from trapezoids spaced every estepm months
5459: * This is mainly to measure the difference between two models: for example
5460: * if stepm=24 months pijx are given only every 2 years and by summing them
5461: * we are calculating an estimate of the Life Expectancy assuming a linear
5462: * progression in between and thus overestimating or underestimating according
5463: * to the curvature of the survival function. If, for the same date, we
5464: * estimate the model with stepm=1 month, we can keep estepm to 24 months
5465: * to compare the new estimate of Life expectancy with the same linear
5466: * hypothesis. A more precise result, taking into account a more precise
5467: * curvature will be obtained if estepm is as small as stepm. */
5468:
5469: /* For example we decided to compute the life expectancy with the smallest unit */
5470: /* hstepm beeing the number of stepms, if hstepm=1 the length of hstepm is stepm.
5471: nhstepm is the number of hstepm from age to agelim
5472: nstepm is the number of stepm from age to agelin.
1.270 brouard 5473: Look at hpijx to understand the reason which relies in memory size consideration
1.126 brouard 5474: and note for a fixed period like estepm months */
5475: /* We decided (b) to get a life expectancy respecting the most precise curvature of the
5476: survival function given by stepm (the optimization length). Unfortunately it
5477: means that if the survival funtion is printed only each two years of age and if
5478: you sum them up and add 1 year (area under the trapezoids) you won't get the same
5479: results. So we changed our mind and took the option of the best precision.
5480: */
5481: hstepm=hstepm/stepm; /* Typically in stepm units, if stepm=6 & estepm=24 , = 24/6 months = 4 */
5482:
5483: agelim=AGESUP;
5484: /* If stepm=6 months */
5485: /* Computed by stepm unit matrices, product of hstepm matrices, stored
5486: in an array of nhstepm length: nhstepm=10, hstepm=4, stepm=6 months */
5487:
5488: /* nhstepm age range expressed in number of stepm */
5489: nstepm=(int) rint((agelim-bage)*YEARM/stepm); /* Biggest nstepm */
5490: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
5491: /* if (stepm >= YEARM) hstepm=1;*/
5492: nhstepm = nstepm/hstepm;/* Expressed in hstepm, typically nhstepm=40/4=10 */
5493: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
5494:
5495: for (age=bage; age<=fage; age ++){
5496: nstepma=(int) rint((agelim-bage)*YEARM/stepm); /* Biggest nstepm */
5497: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
5498: /* if (stepm >= YEARM) hstepm=1;*/
5499: nhstepma = nstepma/hstepm;/* Expressed in hstepm, typically nhstepma=40/4=10 */
5500:
5501: /* If stepm=6 months */
5502: /* Computed by stepm unit matrices, product of hstepma matrices, stored
5503: in an array of nhstepma length: nhstepma=10, hstepm=4, stepm=6 months */
5504:
1.235 brouard 5505: hpxij(p3mat,nhstepma,age,hstepm,x,nlstate,stepm,oldm, savm, cij, nres);
1.126 brouard 5506:
5507: hf=hstepm*stepm/YEARM; /* Duration of hstepm expressed in year unit. */
5508:
5509: printf("%d|",(int)age);fflush(stdout);
5510: fprintf(ficlog,"%d|",(int)age);fflush(ficlog);
5511:
5512: /* Computing expectancies */
5513: for(i=1; i<=nlstate;i++)
5514: for(j=1; j<=nlstate;j++)
5515: for (h=0, eij[i][j][(int)age]=0; h<=nhstepm-1; h++){
5516: eij[i][j][(int)age] += (p3mat[i][j][h]+p3mat[i][j][h+1])/2.0*hf;
5517:
5518: /* 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]);*/
5519:
5520: }
5521:
5522: fprintf(ficreseij,"%3.0f",age );
5523: for(i=1; i<=nlstate;i++){
5524: eip=0;
5525: for(j=1; j<=nlstate;j++){
5526: eip +=eij[i][j][(int)age];
5527: fprintf(ficreseij,"%9.4f", eij[i][j][(int)age] );
5528: }
5529: fprintf(ficreseij,"%9.4f", eip );
5530: }
5531: fprintf(ficreseij,"\n");
5532:
5533: }
5534: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
5535: printf("\n");
5536: fprintf(ficlog,"\n");
5537:
5538: }
5539:
1.235 brouard 5540: 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 5541:
5542: {
5543: /* Covariances of health expectancies eij and of total life expectancies according
1.222 brouard 5544: to initial status i, ei. .
1.126 brouard 5545: */
5546: int i, j, nhstepm, hstepm, h, nstepm, k, cptj, cptj2, i2, j2, ij, ji;
5547: int nhstepma, nstepma; /* Decreasing with age */
5548: double age, agelim, hf;
5549: double ***p3matp, ***p3matm, ***varhe;
5550: double **dnewm,**doldm;
5551: double *xp, *xm;
5552: double **gp, **gm;
5553: double ***gradg, ***trgradg;
5554: int theta;
5555:
5556: double eip, vip;
5557:
5558: varhe=ma3x(1,nlstate*nlstate,1,nlstate*nlstate,(int) bage, (int) fage);
5559: xp=vector(1,npar);
5560: xm=vector(1,npar);
5561: dnewm=matrix(1,nlstate*nlstate,1,npar);
5562: doldm=matrix(1,nlstate*nlstate,1,nlstate*nlstate);
5563:
5564: pstamp(ficresstdeij);
5565: fprintf(ficresstdeij,"# Health expectancies with standard errors\n");
5566: fprintf(ficresstdeij,"# Age");
5567: for(i=1; i<=nlstate;i++){
5568: for(j=1; j<=nlstate;j++)
5569: fprintf(ficresstdeij," e%1d%1d (SE)",i,j);
5570: fprintf(ficresstdeij," e%1d. ",i);
5571: }
5572: fprintf(ficresstdeij,"\n");
5573:
5574: pstamp(ficrescveij);
5575: fprintf(ficrescveij,"# Subdiagonal matrix of covariances of health expectancies by age: cov(eij,ekl)\n");
5576: fprintf(ficrescveij,"# Age");
5577: for(i=1; i<=nlstate;i++)
5578: for(j=1; j<=nlstate;j++){
5579: cptj= (j-1)*nlstate+i;
5580: for(i2=1; i2<=nlstate;i2++)
5581: for(j2=1; j2<=nlstate;j2++){
5582: cptj2= (j2-1)*nlstate+i2;
5583: if(cptj2 <= cptj)
5584: fprintf(ficrescveij," %1d%1d,%1d%1d",i,j,i2,j2);
5585: }
5586: }
5587: fprintf(ficrescveij,"\n");
5588:
5589: if(estepm < stepm){
5590: printf ("Problem %d lower than %d\n",estepm, stepm);
5591: }
5592: else hstepm=estepm;
5593: /* We compute the life expectancy from trapezoids spaced every estepm months
5594: * This is mainly to measure the difference between two models: for example
5595: * if stepm=24 months pijx are given only every 2 years and by summing them
5596: * we are calculating an estimate of the Life Expectancy assuming a linear
5597: * progression in between and thus overestimating or underestimating according
5598: * to the curvature of the survival function. If, for the same date, we
5599: * estimate the model with stepm=1 month, we can keep estepm to 24 months
5600: * to compare the new estimate of Life expectancy with the same linear
5601: * hypothesis. A more precise result, taking into account a more precise
5602: * curvature will be obtained if estepm is as small as stepm. */
5603:
5604: /* For example we decided to compute the life expectancy with the smallest unit */
5605: /* hstepm beeing the number of stepms, if hstepm=1 the length of hstepm is stepm.
5606: nhstepm is the number of hstepm from age to agelim
5607: nstepm is the number of stepm from age to agelin.
5608: Look at hpijx to understand the reason of that which relies in memory size
5609: and note for a fixed period like estepm months */
5610: /* We decided (b) to get a life expectancy respecting the most precise curvature of the
5611: survival function given by stepm (the optimization length). Unfortunately it
5612: means that if the survival funtion is printed only each two years of age and if
5613: you sum them up and add 1 year (area under the trapezoids) you won't get the same
5614: results. So we changed our mind and took the option of the best precision.
5615: */
5616: hstepm=hstepm/stepm; /* Typically in stepm units, if stepm=6 & estepm=24 , = 24/6 months = 4 */
5617:
5618: /* If stepm=6 months */
5619: /* nhstepm age range expressed in number of stepm */
5620: agelim=AGESUP;
5621: nstepm=(int) rint((agelim-bage)*YEARM/stepm);
5622: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
5623: /* if (stepm >= YEARM) hstepm=1;*/
5624: nhstepm = nstepm/hstepm;/* Expressed in hstepm, typically nhstepm=40/4=10 */
5625:
5626: p3matp=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
5627: p3matm=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
5628: gradg=ma3x(0,nhstepm,1,npar,1,nlstate*nlstate);
5629: trgradg =ma3x(0,nhstepm,1,nlstate*nlstate,1,npar);
5630: gp=matrix(0,nhstepm,1,nlstate*nlstate);
5631: gm=matrix(0,nhstepm,1,nlstate*nlstate);
5632:
5633: for (age=bage; age<=fage; age ++){
5634: nstepma=(int) rint((agelim-bage)*YEARM/stepm); /* Biggest nstepm */
5635: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
5636: /* if (stepm >= YEARM) hstepm=1;*/
5637: nhstepma = nstepma/hstepm;/* Expressed in hstepm, typically nhstepma=40/4=10 */
1.218 brouard 5638:
1.126 brouard 5639: /* If stepm=6 months */
5640: /* Computed by stepm unit matrices, product of hstepma matrices, stored
5641: in an array of nhstepma length: nhstepma=10, hstepm=4, stepm=6 months */
5642:
5643: hf=hstepm*stepm/YEARM; /* Duration of hstepm expressed in year unit. */
1.218 brouard 5644:
1.126 brouard 5645: /* Computing Variances of health expectancies */
5646: /* Gradient is computed with plus gp and minus gm. Code is duplicated in order to
5647: decrease memory allocation */
5648: for(theta=1; theta <=npar; theta++){
5649: for(i=1; i<=npar; i++){
1.222 brouard 5650: xp[i] = x[i] + (i==theta ?delti[theta]:0);
5651: xm[i] = x[i] - (i==theta ?delti[theta]:0);
1.126 brouard 5652: }
1.235 brouard 5653: hpxij(p3matp,nhstepm,age,hstepm,xp,nlstate,stepm,oldm,savm, cij, nres);
5654: hpxij(p3matm,nhstepm,age,hstepm,xm,nlstate,stepm,oldm,savm, cij, nres);
1.218 brouard 5655:
1.126 brouard 5656: for(j=1; j<= nlstate; j++){
1.222 brouard 5657: for(i=1; i<=nlstate; i++){
5658: for(h=0; h<=nhstepm-1; h++){
5659: gp[h][(j-1)*nlstate + i] = (p3matp[i][j][h]+p3matp[i][j][h+1])/2.;
5660: gm[h][(j-1)*nlstate + i] = (p3matm[i][j][h]+p3matm[i][j][h+1])/2.;
5661: }
5662: }
1.126 brouard 5663: }
1.218 brouard 5664:
1.126 brouard 5665: for(ij=1; ij<= nlstate*nlstate; ij++)
1.222 brouard 5666: for(h=0; h<=nhstepm-1; h++){
5667: gradg[h][theta][ij]= (gp[h][ij]-gm[h][ij])/2./delti[theta];
5668: }
1.126 brouard 5669: }/* End theta */
5670:
5671:
5672: for(h=0; h<=nhstepm-1; h++)
5673: for(j=1; j<=nlstate*nlstate;j++)
1.222 brouard 5674: for(theta=1; theta <=npar; theta++)
5675: trgradg[h][j][theta]=gradg[h][theta][j];
1.126 brouard 5676:
1.218 brouard 5677:
1.222 brouard 5678: for(ij=1;ij<=nlstate*nlstate;ij++)
1.126 brouard 5679: for(ji=1;ji<=nlstate*nlstate;ji++)
1.222 brouard 5680: varhe[ij][ji][(int)age] =0.;
1.218 brouard 5681:
1.222 brouard 5682: printf("%d|",(int)age);fflush(stdout);
5683: fprintf(ficlog,"%d|",(int)age);fflush(ficlog);
5684: for(h=0;h<=nhstepm-1;h++){
1.126 brouard 5685: for(k=0;k<=nhstepm-1;k++){
1.222 brouard 5686: matprod2(dnewm,trgradg[h],1,nlstate*nlstate,1,npar,1,npar,matcov);
5687: matprod2(doldm,dnewm,1,nlstate*nlstate,1,npar,1,nlstate*nlstate,gradg[k]);
5688: for(ij=1;ij<=nlstate*nlstate;ij++)
5689: for(ji=1;ji<=nlstate*nlstate;ji++)
5690: varhe[ij][ji][(int)age] += doldm[ij][ji]*hf*hf;
1.126 brouard 5691: }
5692: }
1.218 brouard 5693:
1.126 brouard 5694: /* Computing expectancies */
1.235 brouard 5695: hpxij(p3matm,nhstepm,age,hstepm,x,nlstate,stepm,oldm, savm, cij,nres);
1.126 brouard 5696: for(i=1; i<=nlstate;i++)
5697: for(j=1; j<=nlstate;j++)
1.222 brouard 5698: for (h=0, eij[i][j][(int)age]=0; h<=nhstepm-1; h++){
5699: eij[i][j][(int)age] += (p3matm[i][j][h]+p3matm[i][j][h+1])/2.0*hf;
1.218 brouard 5700:
1.222 brouard 5701: /* 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 5702:
1.222 brouard 5703: }
1.269 brouard 5704:
5705: /* Standard deviation of expectancies ij */
1.126 brouard 5706: fprintf(ficresstdeij,"%3.0f",age );
5707: for(i=1; i<=nlstate;i++){
5708: eip=0.;
5709: vip=0.;
5710: for(j=1; j<=nlstate;j++){
1.222 brouard 5711: eip += eij[i][j][(int)age];
5712: for(k=1; k<=nlstate;k++) /* Sum on j and k of cov(eij,eik) */
5713: vip += varhe[(j-1)*nlstate+i][(k-1)*nlstate+i][(int)age];
5714: 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 5715: }
5716: fprintf(ficresstdeij," %9.4f (%.4f)", eip, sqrt(vip));
5717: }
5718: fprintf(ficresstdeij,"\n");
1.218 brouard 5719:
1.269 brouard 5720: /* Variance of expectancies ij */
1.126 brouard 5721: fprintf(ficrescveij,"%3.0f",age );
5722: for(i=1; i<=nlstate;i++)
5723: for(j=1; j<=nlstate;j++){
1.222 brouard 5724: cptj= (j-1)*nlstate+i;
5725: for(i2=1; i2<=nlstate;i2++)
5726: for(j2=1; j2<=nlstate;j2++){
5727: cptj2= (j2-1)*nlstate+i2;
5728: if(cptj2 <= cptj)
5729: fprintf(ficrescveij," %.4f", varhe[cptj][cptj2][(int)age]);
5730: }
1.126 brouard 5731: }
5732: fprintf(ficrescveij,"\n");
1.218 brouard 5733:
1.126 brouard 5734: }
5735: free_matrix(gm,0,nhstepm,1,nlstate*nlstate);
5736: free_matrix(gp,0,nhstepm,1,nlstate*nlstate);
5737: free_ma3x(gradg,0,nhstepm,1,npar,1,nlstate*nlstate);
5738: free_ma3x(trgradg,0,nhstepm,1,nlstate*nlstate,1,npar);
5739: free_ma3x(p3matm,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
5740: free_ma3x(p3matp,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
5741: printf("\n");
5742: fprintf(ficlog,"\n");
1.218 brouard 5743:
1.126 brouard 5744: free_vector(xm,1,npar);
5745: free_vector(xp,1,npar);
5746: free_matrix(dnewm,1,nlstate*nlstate,1,npar);
5747: free_matrix(doldm,1,nlstate*nlstate,1,nlstate*nlstate);
5748: free_ma3x(varhe,1,nlstate*nlstate,1,nlstate*nlstate,(int) bage, (int)fage);
5749: }
1.218 brouard 5750:
1.126 brouard 5751: /************ Variance ******************/
1.235 brouard 5752: 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 5753: {
5754: /* Variance of health expectancies */
5755: /* double **prevalim(double **prlim, int nlstate, double *xp, double age, double **oldm, double ** savm,double ftolpl);*/
5756: /* double **newm;*/
5757: /* int movingaverage(double ***probs, double bage,double fage, double ***mobaverage, int mobilav)*/
5758:
5759: /* int movingaverage(); */
5760: double **dnewm,**doldm;
5761: double **dnewmp,**doldmp;
5762: int i, j, nhstepm, hstepm, h, nstepm ;
5763: int k;
5764: double *xp;
5765: double **gp, **gm; /* for var eij */
5766: double ***gradg, ***trgradg; /*for var eij */
5767: double **gradgp, **trgradgp; /* for var p point j */
5768: double *gpp, *gmp; /* for var p point j */
5769: double **varppt; /* for var p point j nlstate to nlstate+ndeath */
5770: double ***p3mat;
5771: double age,agelim, hf;
5772: /* double ***mobaverage; */
5773: int theta;
5774: char digit[4];
5775: char digitp[25];
5776:
5777: char fileresprobmorprev[FILENAMELENGTH];
5778:
5779: if(popbased==1){
5780: if(mobilav!=0)
5781: strcpy(digitp,"-POPULBASED-MOBILAV_");
5782: else strcpy(digitp,"-POPULBASED-NOMOBIL_");
5783: }
5784: else
5785: strcpy(digitp,"-STABLBASED_");
1.126 brouard 5786:
1.218 brouard 5787: /* if (mobilav!=0) { */
5788: /* mobaverage= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
5789: /* if (movingaverage(probs, bage, fage, mobaverage,mobilav)!=0){ */
5790: /* fprintf(ficlog," Error in movingaverage mobilav=%d\n",mobilav); */
5791: /* printf(" Error in movingaverage mobilav=%d\n",mobilav); */
5792: /* } */
5793: /* } */
5794:
5795: strcpy(fileresprobmorprev,"PRMORPREV-");
5796: sprintf(digit,"%-d",ij);
5797: /*printf("DIGIT=%s, ij=%d ijr=%-d|\n",digit, ij,ij);*/
5798: strcat(fileresprobmorprev,digit); /* Tvar to be done */
5799: strcat(fileresprobmorprev,digitp); /* Popbased or not, mobilav or not */
5800: strcat(fileresprobmorprev,fileresu);
5801: if((ficresprobmorprev=fopen(fileresprobmorprev,"w"))==NULL) {
5802: printf("Problem with resultfile: %s\n", fileresprobmorprev);
5803: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprobmorprev);
5804: }
5805: printf("Computing total mortality p.j=w1*p1j+w2*p2j+..: result on file '%s' \n",fileresprobmorprev);
5806: fprintf(ficlog,"Computing total mortality p.j=w1*p1j+w2*p2j+..: result on file '%s' \n",fileresprobmorprev);
5807: pstamp(ficresprobmorprev);
5808: 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 5809: fprintf(ficresprobmorprev,"# Selected quantitative variables and dummies");
5810: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
5811: fprintf(ficresprobmorprev," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
5812: }
5813: for(j=1;j<=cptcoveff;j++)
5814: fprintf(ficresprobmorprev,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(ij,j)]);
5815: fprintf(ficresprobmorprev,"\n");
5816:
1.218 brouard 5817: fprintf(ficresprobmorprev,"# Age cov=%-d",ij);
5818: for(j=nlstate+1; j<=(nlstate+ndeath);j++){
5819: fprintf(ficresprobmorprev," p.%-d SE",j);
5820: for(i=1; i<=nlstate;i++)
5821: fprintf(ficresprobmorprev," w%1d p%-d%-d",i,i,j);
5822: }
5823: fprintf(ficresprobmorprev,"\n");
5824:
5825: fprintf(ficgp,"\n# Routine varevsij");
5826: fprintf(ficgp,"\nunset title \n");
5827: /* fprintf(fichtm, "#Local time at start: %s", strstart);*/
5828: 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");
5829: fprintf(fichtm,"\n<br>%s <br>\n",digitp);
5830: /* } */
5831: varppt = matrix(nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
5832: pstamp(ficresvij);
5833: fprintf(ficresvij,"# Variance and covariance of health expectancies e.j \n# (weighted average of eij where weights are ");
5834: if(popbased==1)
5835: 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);
5836: else
5837: fprintf(ficresvij,"the age specific period (stable) prevalences in each health state \n");
5838: fprintf(ficresvij,"# Age");
5839: for(i=1; i<=nlstate;i++)
5840: for(j=1; j<=nlstate;j++)
5841: fprintf(ficresvij," Cov(e.%1d, e.%1d)",i,j);
5842: fprintf(ficresvij,"\n");
5843:
5844: xp=vector(1,npar);
5845: dnewm=matrix(1,nlstate,1,npar);
5846: doldm=matrix(1,nlstate,1,nlstate);
5847: dnewmp= matrix(nlstate+1,nlstate+ndeath,1,npar);
5848: doldmp= matrix(nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
5849:
5850: gradgp=matrix(1,npar,nlstate+1,nlstate+ndeath);
5851: gpp=vector(nlstate+1,nlstate+ndeath);
5852: gmp=vector(nlstate+1,nlstate+ndeath);
5853: trgradgp =matrix(nlstate+1,nlstate+ndeath,1,npar); /* mu or p point j*/
1.126 brouard 5854:
1.218 brouard 5855: if(estepm < stepm){
5856: printf ("Problem %d lower than %d\n",estepm, stepm);
5857: }
5858: else hstepm=estepm;
5859: /* For example we decided to compute the life expectancy with the smallest unit */
5860: /* hstepm beeing the number of stepms, if hstepm=1 the length of hstepm is stepm.
5861: nhstepm is the number of hstepm from age to agelim
5862: nstepm is the number of stepm from age to agelim.
5863: Look at function hpijx to understand why because of memory size limitations,
5864: we decided (b) to get a life expectancy respecting the most precise curvature of the
5865: survival function given by stepm (the optimization length). Unfortunately it
5866: means that if the survival funtion is printed every two years of age and if
5867: you sum them up and add 1 year (area under the trapezoids) you won't get the same
5868: results. So we changed our mind and took the option of the best precision.
5869: */
5870: hstepm=hstepm/stepm; /* Typically in stepm units, if stepm=6 & estepm=24 , = 24/6 months = 4 */
5871: agelim = AGESUP;
5872: for (age=bage; age<=fage; age ++){ /* If stepm=6 months */
5873: nstepm=(int) rint((agelim-age)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
5874: nhstepm = nstepm/hstepm;/* Expressed in hstepm, typically nhstepm=40/4=10 */
5875: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
5876: gradg=ma3x(0,nhstepm,1,npar,1,nlstate);
5877: gp=matrix(0,nhstepm,1,nlstate);
5878: gm=matrix(0,nhstepm,1,nlstate);
5879:
5880:
5881: for(theta=1; theta <=npar; theta++){
5882: for(i=1; i<=npar; i++){ /* Computes gradient x + delta*/
5883: xp[i] = x[i] + (i==theta ?delti[theta]:0);
5884: }
5885:
1.242 brouard 5886: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij, nres);
1.218 brouard 5887:
5888: if (popbased==1) {
5889: if(mobilav ==0){
5890: for(i=1; i<=nlstate;i++)
5891: prlim[i][i]=probs[(int)age][i][ij];
5892: }else{ /* mobilav */
5893: for(i=1; i<=nlstate;i++)
5894: prlim[i][i]=mobaverage[(int)age][i][ij];
5895: }
5896: }
5897:
1.235 brouard 5898: 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 5899: for(j=1; j<= nlstate; j++){
5900: for(h=0; h<=nhstepm; h++){
5901: for(i=1, gp[h][j]=0.;i<=nlstate;i++)
5902: gp[h][j] += prlim[i][i]*p3mat[i][j][h];
5903: }
5904: }
5905: /* Next for computing probability of death (h=1 means
5906: computed over hstepm matrices product = hstepm*stepm months)
5907: as a weighted average of prlim.
5908: */
5909: for(j=nlstate+1;j<=nlstate+ndeath;j++){
5910: for(i=1,gpp[j]=0.; i<= nlstate; i++)
5911: gpp[j] += prlim[i][i]*p3mat[i][j][1];
5912: }
5913: /* end probability of death */
5914:
5915: for(i=1; i<=npar; i++) /* Computes gradient x - delta */
5916: xp[i] = x[i] - (i==theta ?delti[theta]:0);
5917:
1.242 brouard 5918: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp, ij, nres);
1.218 brouard 5919:
5920: if (popbased==1) {
5921: if(mobilav ==0){
5922: for(i=1; i<=nlstate;i++)
5923: prlim[i][i]=probs[(int)age][i][ij];
5924: }else{ /* mobilav */
5925: for(i=1; i<=nlstate;i++)
5926: prlim[i][i]=mobaverage[(int)age][i][ij];
5927: }
5928: }
5929:
1.235 brouard 5930: hpxij(p3mat,nhstepm,age,hstepm,xp,nlstate,stepm,oldm,savm, ij,nres);
1.218 brouard 5931:
5932: for(j=1; j<= nlstate; j++){ /* Sum of wi * eij = e.j */
5933: for(h=0; h<=nhstepm; h++){
5934: for(i=1, gm[h][j]=0.;i<=nlstate;i++)
5935: gm[h][j] += prlim[i][i]*p3mat[i][j][h];
5936: }
5937: }
5938: /* This for computing probability of death (h=1 means
5939: computed over hstepm matrices product = hstepm*stepm months)
5940: as a weighted average of prlim.
5941: */
5942: for(j=nlstate+1;j<=nlstate+ndeath;j++){
5943: for(i=1,gmp[j]=0.; i<= nlstate; i++)
5944: gmp[j] += prlim[i][i]*p3mat[i][j][1];
5945: }
5946: /* end probability of death */
5947:
5948: for(j=1; j<= nlstate; j++) /* vareij */
5949: for(h=0; h<=nhstepm; h++){
5950: gradg[h][theta][j]= (gp[h][j]-gm[h][j])/2./delti[theta];
5951: }
5952:
5953: for(j=nlstate+1; j<= nlstate+ndeath; j++){ /* var mu */
5954: gradgp[theta][j]= (gpp[j]-gmp[j])/2./delti[theta];
5955: }
5956:
5957: } /* End theta */
5958:
5959: trgradg =ma3x(0,nhstepm,1,nlstate,1,npar); /* veij */
5960:
5961: for(h=0; h<=nhstepm; h++) /* veij */
5962: for(j=1; j<=nlstate;j++)
5963: for(theta=1; theta <=npar; theta++)
5964: trgradg[h][j][theta]=gradg[h][theta][j];
5965:
5966: for(j=nlstate+1; j<=nlstate+ndeath;j++) /* mu */
5967: for(theta=1; theta <=npar; theta++)
5968: trgradgp[j][theta]=gradgp[theta][j];
5969:
5970:
5971: hf=hstepm*stepm/YEARM; /* Duration of hstepm expressed in year unit. */
5972: for(i=1;i<=nlstate;i++)
5973: for(j=1;j<=nlstate;j++)
5974: vareij[i][j][(int)age] =0.;
5975:
5976: for(h=0;h<=nhstepm;h++){
5977: for(k=0;k<=nhstepm;k++){
5978: matprod2(dnewm,trgradg[h],1,nlstate,1,npar,1,npar,matcov);
5979: matprod2(doldm,dnewm,1,nlstate,1,npar,1,nlstate,gradg[k]);
5980: for(i=1;i<=nlstate;i++)
5981: for(j=1;j<=nlstate;j++)
5982: vareij[i][j][(int)age] += doldm[i][j]*hf*hf;
5983: }
5984: }
5985:
5986: /* pptj */
5987: matprod2(dnewmp,trgradgp,nlstate+1,nlstate+ndeath,1,npar,1,npar,matcov);
5988: matprod2(doldmp,dnewmp,nlstate+1,nlstate+ndeath,1,npar,nlstate+1,nlstate+ndeath,gradgp);
5989: for(j=nlstate+1;j<=nlstate+ndeath;j++)
5990: for(i=nlstate+1;i<=nlstate+ndeath;i++)
5991: varppt[j][i]=doldmp[j][i];
5992: /* end ppptj */
5993: /* x centered again */
5994:
1.242 brouard 5995: prevalim(prlim,nlstate,x,age,oldm,savm,ftolpl,ncvyearp,ij, nres);
1.218 brouard 5996:
5997: if (popbased==1) {
5998: if(mobilav ==0){
5999: for(i=1; i<=nlstate;i++)
6000: prlim[i][i]=probs[(int)age][i][ij];
6001: }else{ /* mobilav */
6002: for(i=1; i<=nlstate;i++)
6003: prlim[i][i]=mobaverage[(int)age][i][ij];
6004: }
6005: }
6006:
6007: /* This for computing probability of death (h=1 means
6008: computed over hstepm (estepm) matrices product = hstepm*stepm months)
6009: as a weighted average of prlim.
6010: */
1.235 brouard 6011: hpxij(p3mat,nhstepm,age,hstepm,x,nlstate,stepm,oldm,savm, ij, nres);
1.218 brouard 6012: for(j=nlstate+1;j<=nlstate+ndeath;j++){
6013: for(i=1,gmp[j]=0.;i<= nlstate; i++)
6014: gmp[j] += prlim[i][i]*p3mat[i][j][1];
6015: }
6016: /* end probability of death */
6017:
6018: fprintf(ficresprobmorprev,"%3d %d ",(int) age, ij);
6019: for(j=nlstate+1; j<=(nlstate+ndeath);j++){
6020: fprintf(ficresprobmorprev," %11.3e %11.3e",gmp[j], sqrt(varppt[j][j]));
6021: for(i=1; i<=nlstate;i++){
6022: fprintf(ficresprobmorprev," %11.3e %11.3e ",prlim[i][i],p3mat[i][j][1]);
6023: }
6024: }
6025: fprintf(ficresprobmorprev,"\n");
6026:
6027: fprintf(ficresvij,"%.0f ",age );
6028: for(i=1; i<=nlstate;i++)
6029: for(j=1; j<=nlstate;j++){
6030: fprintf(ficresvij," %.4f", vareij[i][j][(int)age]);
6031: }
6032: fprintf(ficresvij,"\n");
6033: free_matrix(gp,0,nhstepm,1,nlstate);
6034: free_matrix(gm,0,nhstepm,1,nlstate);
6035: free_ma3x(gradg,0,nhstepm,1,npar,1,nlstate);
6036: free_ma3x(trgradg,0,nhstepm,1,nlstate,1,npar);
6037: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
6038: } /* End age */
6039: free_vector(gpp,nlstate+1,nlstate+ndeath);
6040: free_vector(gmp,nlstate+1,nlstate+ndeath);
6041: free_matrix(gradgp,1,npar,nlstate+1,nlstate+ndeath);
6042: free_matrix(trgradgp,nlstate+1,nlstate+ndeath,1,npar); /* mu or p point j*/
6043: /* fprintf(ficgp,"\nunset parametric;unset label; set ter png small size 320, 240"); */
6044: fprintf(ficgp,"\nunset parametric;unset label; set ter svg size 640, 480");
6045: /* for(j=nlstate+1; j<= nlstate+ndeath; j++){ *//* Only the first actually */
6046: fprintf(ficgp,"\n set log y; unset log x;set xlabel \"Age\"; set ylabel \"Force of mortality (year-1)\";");
6047: fprintf(ficgp,"\nset out \"%s%s.svg\";",subdirf3(optionfilefiname,"VARMUPTJGR-",digitp),digit);
6048: /* fprintf(ficgp,"\n plot \"%s\" u 1:($3*%6.3f) not w l 1 ",fileresprobmorprev,YEARM/estepm); */
6049: /* fprintf(ficgp,"\n replot \"%s\" u 1:(($3+1.96*$4)*%6.3f) t \"95\%% interval\" w l 2 ",fileresprobmorprev,YEARM/estepm); */
6050: /* fprintf(ficgp,"\n replot \"%s\" u 1:(($3-1.96*$4)*%6.3f) not w l 2 ",fileresprobmorprev,YEARM/estepm); */
6051: fprintf(ficgp,"\n plot \"%s\" u 1:($3) not w l lt 1 ",subdirf(fileresprobmorprev));
6052: fprintf(ficgp,"\n replot \"%s\" u 1:(($3+1.96*$4)) t \"95%% interval\" w l lt 2 ",subdirf(fileresprobmorprev));
6053: fprintf(ficgp,"\n replot \"%s\" u 1:(($3-1.96*$4)) not w l lt 2 ",subdirf(fileresprobmorprev));
6054: fprintf(fichtm,"\n<br> File (multiple files are possible if covariates are present): <A href=\"%s\">%s</a>\n",subdirf(fileresprobmorprev),subdirf(fileresprobmorprev));
6055: 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);
6056: /* 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 6057: */
1.218 brouard 6058: /* fprintf(ficgp,"\nset out \"varmuptjgr%s%s%s.svg\";replot;",digitp,optionfilefiname,digit); */
6059: fprintf(ficgp,"\nset out;\nset out \"%s%s.svg\";replot;set out;\n",subdirf3(optionfilefiname,"VARMUPTJGR-",digitp),digit);
1.126 brouard 6060:
1.218 brouard 6061: free_vector(xp,1,npar);
6062: free_matrix(doldm,1,nlstate,1,nlstate);
6063: free_matrix(dnewm,1,nlstate,1,npar);
6064: free_matrix(doldmp,nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
6065: free_matrix(dnewmp,nlstate+1,nlstate+ndeath,1,npar);
6066: free_matrix(varppt,nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
6067: /* if (mobilav!=0) free_ma3x(mobaverage,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
6068: fclose(ficresprobmorprev);
6069: fflush(ficgp);
6070: fflush(fichtm);
6071: } /* end varevsij */
1.126 brouard 6072:
6073: /************ Variance of prevlim ******************/
1.269 brouard 6074: 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 6075: {
1.205 brouard 6076: /* Variance of prevalence limit for each state ij using current parameters x[] and estimates of neighbourhood give by delti*/
1.126 brouard 6077: /* double **prevalim(double **prlim, int nlstate, double *xp, double age, double **oldm, double **savm,double ftolpl);*/
1.164 brouard 6078:
1.268 brouard 6079: double **dnewmpar,**doldm;
1.126 brouard 6080: int i, j, nhstepm, hstepm;
6081: double *xp;
6082: double *gp, *gm;
6083: double **gradg, **trgradg;
1.208 brouard 6084: double **mgm, **mgp;
1.126 brouard 6085: double age,agelim;
6086: int theta;
6087:
6088: pstamp(ficresvpl);
6089: fprintf(ficresvpl,"# Standard deviation of period (stable) prevalences \n");
1.241 brouard 6090: fprintf(ficresvpl,"# Age ");
6091: if(nresult >=1)
6092: fprintf(ficresvpl," Result# ");
1.126 brouard 6093: for(i=1; i<=nlstate;i++)
6094: fprintf(ficresvpl," %1d-%1d",i,i);
6095: fprintf(ficresvpl,"\n");
6096:
6097: xp=vector(1,npar);
1.268 brouard 6098: dnewmpar=matrix(1,nlstate,1,npar);
1.126 brouard 6099: doldm=matrix(1,nlstate,1,nlstate);
6100:
6101: hstepm=1*YEARM; /* Every year of age */
6102: hstepm=hstepm/stepm; /* Typically in stepm units, if j= 2 years, = 2/6 months = 4 */
6103: agelim = AGESUP;
6104: for (age=bage; age<=fage; age ++){ /* If stepm=6 months */
6105: nhstepm=(int) rint((agelim-age)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
6106: if (stepm >= YEARM) hstepm=1;
6107: nhstepm = nhstepm/hstepm; /* Typically 40/4=10 */
6108: gradg=matrix(1,npar,1,nlstate);
1.208 brouard 6109: mgp=matrix(1,npar,1,nlstate);
6110: mgm=matrix(1,npar,1,nlstate);
1.126 brouard 6111: gp=vector(1,nlstate);
6112: gm=vector(1,nlstate);
6113:
6114: for(theta=1; theta <=npar; theta++){
6115: for(i=1; i<=npar; i++){ /* Computes gradient */
6116: xp[i] = x[i] + (i==theta ?delti[theta]:0);
6117: }
1.209 brouard 6118: if((int)age==79 ||(int)age== 80 ||(int)age== 81 )
1.235 brouard 6119: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres);
1.209 brouard 6120: else
1.235 brouard 6121: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres);
1.208 brouard 6122: for(i=1;i<=nlstate;i++){
1.126 brouard 6123: gp[i] = prlim[i][i];
1.208 brouard 6124: mgp[theta][i] = prlim[i][i];
6125: }
1.126 brouard 6126: for(i=1; i<=npar; i++) /* Computes gradient */
6127: xp[i] = x[i] - (i==theta ?delti[theta]:0);
1.209 brouard 6128: if((int)age==79 ||(int)age== 80 ||(int)age== 81 )
1.235 brouard 6129: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres);
1.209 brouard 6130: else
1.235 brouard 6131: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres);
1.208 brouard 6132: for(i=1;i<=nlstate;i++){
1.126 brouard 6133: gm[i] = prlim[i][i];
1.208 brouard 6134: mgm[theta][i] = prlim[i][i];
6135: }
1.126 brouard 6136: for(i=1;i<=nlstate;i++)
6137: gradg[theta][i]= (gp[i]-gm[i])/2./delti[theta];
1.209 brouard 6138: /* gradg[theta][2]= -gradg[theta][1]; */ /* For testing if nlstate=2 */
1.126 brouard 6139: } /* End theta */
6140:
6141: trgradg =matrix(1,nlstate,1,npar);
6142:
6143: for(j=1; j<=nlstate;j++)
6144: for(theta=1; theta <=npar; theta++)
6145: trgradg[j][theta]=gradg[theta][j];
1.209 brouard 6146: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
6147: /* printf("\nmgm mgp %d ",(int)age); */
6148: /* for(j=1; j<=nlstate;j++){ */
6149: /* printf(" %d ",j); */
6150: /* for(theta=1; theta <=npar; theta++) */
6151: /* printf(" %d %lf %lf",theta,mgm[theta][j],mgp[theta][j]); */
6152: /* printf("\n "); */
6153: /* } */
6154: /* } */
6155: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
6156: /* printf("\n gradg %d ",(int)age); */
6157: /* for(j=1; j<=nlstate;j++){ */
6158: /* printf("%d ",j); */
6159: /* for(theta=1; theta <=npar; theta++) */
6160: /* printf("%d %lf ",theta,gradg[theta][j]); */
6161: /* printf("\n "); */
6162: /* } */
6163: /* } */
1.126 brouard 6164:
6165: for(i=1;i<=nlstate;i++)
6166: varpl[i][(int)age] =0.;
1.209 brouard 6167: if((int)age==79 ||(int)age== 80 ||(int)age== 81){
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: }else{
1.268 brouard 6171: matprod2(dnewmpar,trgradg,1,nlstate,1,npar,1,npar,matcov);
6172: matprod2(doldm,dnewmpar,1,nlstate,1,npar,1,nlstate,gradg);
1.205 brouard 6173: }
1.126 brouard 6174: for(i=1;i<=nlstate;i++)
6175: varpl[i][(int)age] = doldm[i][i]; /* Covariances are useless */
6176:
6177: fprintf(ficresvpl,"%.0f ",age );
1.241 brouard 6178: if(nresult >=1)
6179: fprintf(ficresvpl,"%d ",nres );
1.126 brouard 6180: for(i=1; i<=nlstate;i++)
6181: fprintf(ficresvpl," %.5f (%.5f)",prlim[i][i],sqrt(varpl[i][(int)age]));
6182: fprintf(ficresvpl,"\n");
6183: free_vector(gp,1,nlstate);
6184: free_vector(gm,1,nlstate);
1.208 brouard 6185: free_matrix(mgm,1,npar,1,nlstate);
6186: free_matrix(mgp,1,npar,1,nlstate);
1.126 brouard 6187: free_matrix(gradg,1,npar,1,nlstate);
6188: free_matrix(trgradg,1,nlstate,1,npar);
6189: } /* End age */
6190:
6191: free_vector(xp,1,npar);
6192: free_matrix(doldm,1,nlstate,1,npar);
1.268 brouard 6193: free_matrix(dnewmpar,1,nlstate,1,nlstate);
6194:
6195: }
6196:
6197:
6198: /************ Variance of backprevalence limit ******************/
1.269 brouard 6199: 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 6200: {
6201: /* Variance of backward prevalence limit for each state ij using current parameters x[] and estimates of neighbourhood give by delti*/
6202: /* double **prevalim(double **prlim, int nlstate, double *xp, double age, double **oldm, double **savm,double ftolpl);*/
6203:
6204: double **dnewmpar,**doldm;
6205: int i, j, nhstepm, hstepm;
6206: double *xp;
6207: double *gp, *gm;
6208: double **gradg, **trgradg;
6209: double **mgm, **mgp;
6210: double age,agelim;
6211: int theta;
6212:
6213: pstamp(ficresvbl);
6214: fprintf(ficresvbl,"# Standard deviation of back (stable) prevalences \n");
6215: fprintf(ficresvbl,"# Age ");
6216: if(nresult >=1)
6217: fprintf(ficresvbl," Result# ");
6218: for(i=1; i<=nlstate;i++)
6219: fprintf(ficresvbl," %1d-%1d",i,i);
6220: fprintf(ficresvbl,"\n");
6221:
6222: xp=vector(1,npar);
6223: dnewmpar=matrix(1,nlstate,1,npar);
6224: doldm=matrix(1,nlstate,1,nlstate);
6225:
6226: hstepm=1*YEARM; /* Every year of age */
6227: hstepm=hstepm/stepm; /* Typically in stepm units, if j= 2 years, = 2/6 months = 4 */
6228: agelim = AGEINF;
6229: for (age=fage; age>=bage; age --){ /* If stepm=6 months */
6230: nhstepm=(int) rint((age-agelim)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
6231: if (stepm >= YEARM) hstepm=1;
6232: nhstepm = nhstepm/hstepm; /* Typically 40/4=10 */
6233: gradg=matrix(1,npar,1,nlstate);
6234: mgp=matrix(1,npar,1,nlstate);
6235: mgm=matrix(1,npar,1,nlstate);
6236: gp=vector(1,nlstate);
6237: gm=vector(1,nlstate);
6238:
6239: for(theta=1; theta <=npar; theta++){
6240: for(i=1; i<=npar; i++){ /* Computes gradient */
6241: xp[i] = x[i] + (i==theta ?delti[theta]:0);
6242: }
6243: if(mobilavproj > 0 )
6244: bprevalim(bprlim, mobaverage,nlstate,xp,age,ftolpl,ncvyearp,ij,nres);
6245: else
6246: bprevalim(bprlim, mobaverage,nlstate,xp,age,ftolpl,ncvyearp,ij,nres);
6247: for(i=1;i<=nlstate;i++){
6248: gp[i] = bprlim[i][i];
6249: mgp[theta][i] = bprlim[i][i];
6250: }
6251: for(i=1; i<=npar; i++) /* Computes gradient */
6252: xp[i] = x[i] - (i==theta ?delti[theta]:0);
6253: if(mobilavproj > 0 )
6254: bprevalim(bprlim, mobaverage,nlstate,xp,age,ftolpl,ncvyearp,ij,nres);
6255: else
6256: bprevalim(bprlim, mobaverage,nlstate,xp,age,ftolpl,ncvyearp,ij,nres);
6257: for(i=1;i<=nlstate;i++){
6258: gm[i] = bprlim[i][i];
6259: mgm[theta][i] = bprlim[i][i];
6260: }
6261: for(i=1;i<=nlstate;i++)
6262: gradg[theta][i]= (gp[i]-gm[i])/2./delti[theta];
6263: /* gradg[theta][2]= -gradg[theta][1]; */ /* For testing if nlstate=2 */
6264: } /* End theta */
6265:
6266: trgradg =matrix(1,nlstate,1,npar);
6267:
6268: for(j=1; j<=nlstate;j++)
6269: for(theta=1; theta <=npar; theta++)
6270: trgradg[j][theta]=gradg[theta][j];
6271: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
6272: /* printf("\nmgm mgp %d ",(int)age); */
6273: /* for(j=1; j<=nlstate;j++){ */
6274: /* printf(" %d ",j); */
6275: /* for(theta=1; theta <=npar; theta++) */
6276: /* printf(" %d %lf %lf",theta,mgm[theta][j],mgp[theta][j]); */
6277: /* printf("\n "); */
6278: /* } */
6279: /* } */
6280: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
6281: /* printf("\n gradg %d ",(int)age); */
6282: /* for(j=1; j<=nlstate;j++){ */
6283: /* printf("%d ",j); */
6284: /* for(theta=1; theta <=npar; theta++) */
6285: /* printf("%d %lf ",theta,gradg[theta][j]); */
6286: /* printf("\n "); */
6287: /* } */
6288: /* } */
6289:
6290: for(i=1;i<=nlstate;i++)
6291: varbpl[i][(int)age] =0.;
6292: if((int)age==79 ||(int)age== 80 ||(int)age== 81){
6293: matprod2(dnewmpar,trgradg,1,nlstate,1,npar,1,npar,matcov);
6294: matprod2(doldm,dnewmpar,1,nlstate,1,npar,1,nlstate,gradg);
6295: }else{
6296: matprod2(dnewmpar,trgradg,1,nlstate,1,npar,1,npar,matcov);
6297: matprod2(doldm,dnewmpar,1,nlstate,1,npar,1,nlstate,gradg);
6298: }
6299: for(i=1;i<=nlstate;i++)
6300: varbpl[i][(int)age] = doldm[i][i]; /* Covariances are useless */
6301:
6302: fprintf(ficresvbl,"%.0f ",age );
6303: if(nresult >=1)
6304: fprintf(ficresvbl,"%d ",nres );
6305: for(i=1; i<=nlstate;i++)
6306: fprintf(ficresvbl," %.5f (%.5f)",bprlim[i][i],sqrt(varbpl[i][(int)age]));
6307: fprintf(ficresvbl,"\n");
6308: free_vector(gp,1,nlstate);
6309: free_vector(gm,1,nlstate);
6310: free_matrix(mgm,1,npar,1,nlstate);
6311: free_matrix(mgp,1,npar,1,nlstate);
6312: free_matrix(gradg,1,npar,1,nlstate);
6313: free_matrix(trgradg,1,nlstate,1,npar);
6314: } /* End age */
6315:
6316: free_vector(xp,1,npar);
6317: free_matrix(doldm,1,nlstate,1,npar);
6318: free_matrix(dnewmpar,1,nlstate,1,nlstate);
1.126 brouard 6319:
6320: }
6321:
6322: /************ Variance of one-step probabilities ******************/
6323: 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 6324: {
6325: int i, j=0, k1, l1, tj;
6326: int k2, l2, j1, z1;
6327: int k=0, l;
6328: int first=1, first1, first2;
6329: double cv12, mu1, mu2, lc1, lc2, v12, v21, v11, v22,v1,v2, c12, tnalp;
6330: double **dnewm,**doldm;
6331: double *xp;
6332: double *gp, *gm;
6333: double **gradg, **trgradg;
6334: double **mu;
6335: double age, cov[NCOVMAX+1];
6336: double std=2.0; /* Number of standard deviation wide of confidence ellipsoids */
6337: int theta;
6338: char fileresprob[FILENAMELENGTH];
6339: char fileresprobcov[FILENAMELENGTH];
6340: char fileresprobcor[FILENAMELENGTH];
6341: double ***varpij;
6342:
6343: strcpy(fileresprob,"PROB_");
6344: strcat(fileresprob,fileres);
6345: if((ficresprob=fopen(fileresprob,"w"))==NULL) {
6346: printf("Problem with resultfile: %s\n", fileresprob);
6347: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprob);
6348: }
6349: strcpy(fileresprobcov,"PROBCOV_");
6350: strcat(fileresprobcov,fileresu);
6351: if((ficresprobcov=fopen(fileresprobcov,"w"))==NULL) {
6352: printf("Problem with resultfile: %s\n", fileresprobcov);
6353: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprobcov);
6354: }
6355: strcpy(fileresprobcor,"PROBCOR_");
6356: strcat(fileresprobcor,fileresu);
6357: if((ficresprobcor=fopen(fileresprobcor,"w"))==NULL) {
6358: printf("Problem with resultfile: %s\n", fileresprobcor);
6359: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprobcor);
6360: }
6361: printf("Computing standard deviation of one-step probabilities: result on file '%s' \n",fileresprob);
6362: fprintf(ficlog,"Computing standard deviation of one-step probabilities: result on file '%s' \n",fileresprob);
6363: printf("Computing matrix of variance covariance of one-step probabilities: result on file '%s' \n",fileresprobcov);
6364: fprintf(ficlog,"Computing matrix of variance covariance of one-step probabilities: result on file '%s' \n",fileresprobcov);
6365: printf("and correlation matrix of one-step probabilities: result on file '%s' \n",fileresprobcor);
6366: fprintf(ficlog,"and correlation matrix of one-step probabilities: result on file '%s' \n",fileresprobcor);
6367: pstamp(ficresprob);
6368: fprintf(ficresprob,"#One-step probabilities and stand. devi in ()\n");
6369: fprintf(ficresprob,"# Age");
6370: pstamp(ficresprobcov);
6371: fprintf(ficresprobcov,"#One-step probabilities and covariance matrix\n");
6372: fprintf(ficresprobcov,"# Age");
6373: pstamp(ficresprobcor);
6374: fprintf(ficresprobcor,"#One-step probabilities and correlation matrix\n");
6375: fprintf(ficresprobcor,"# Age");
1.126 brouard 6376:
6377:
1.222 brouard 6378: for(i=1; i<=nlstate;i++)
6379: for(j=1; j<=(nlstate+ndeath);j++){
6380: fprintf(ficresprob," p%1d-%1d (SE)",i,j);
6381: fprintf(ficresprobcov," p%1d-%1d ",i,j);
6382: fprintf(ficresprobcor," p%1d-%1d ",i,j);
6383: }
6384: /* fprintf(ficresprob,"\n");
6385: fprintf(ficresprobcov,"\n");
6386: fprintf(ficresprobcor,"\n");
6387: */
6388: xp=vector(1,npar);
6389: dnewm=matrix(1,(nlstate)*(nlstate+ndeath),1,npar);
6390: doldm=matrix(1,(nlstate)*(nlstate+ndeath),1,(nlstate)*(nlstate+ndeath));
6391: mu=matrix(1,(nlstate)*(nlstate+ndeath), (int) bage, (int)fage);
6392: varpij=ma3x(1,nlstate*(nlstate+ndeath),1,nlstate*(nlstate+ndeath),(int) bage, (int) fage);
6393: first=1;
6394: fprintf(ficgp,"\n# Routine varprob");
6395: fprintf(fichtm,"\n<li><h4> Computing and drawing one step probabilities with their confidence intervals</h4></li>\n");
6396: fprintf(fichtm,"\n");
6397:
1.266 brouard 6398: 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 6399: 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);
6400: fprintf(fichtmcov,"\nEllipsoids of confidence centered on point (p<inf>ij</inf>, p<inf>kl</inf>) are estimated \
1.126 brouard 6401: and drawn. It helps understanding how is the covariance between two incidences.\
6402: They are expressed in year<sup>-1</sup> in order to be less dependent of stepm.<br>\n");
1.222 brouard 6403: 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 6404: It can be understood this way: if pij and pkl where uncorrelated the (2x2) matrix of covariance \
6405: would have been (1/(var pij), 0 , 0, 1/(var pkl)), and the confidence interval would be 2 \
6406: standard deviations wide on each axis. <br>\
6407: Now, if both incidences are correlated (usual case) we diagonalised the inverse of the covariance matrix\
6408: and made the appropriate rotation to look at the uncorrelated principal directions.<br>\
6409: To be simple, these graphs help to understand the significativity of each parameter in relation to a second other one.<br> \n");
6410:
1.222 brouard 6411: cov[1]=1;
6412: /* tj=cptcoveff; */
1.225 brouard 6413: tj = (int) pow(2,cptcoveff);
1.222 brouard 6414: if (cptcovn<1) {tj=1;ncodemax[1]=1;}
6415: j1=0;
1.224 brouard 6416: for(j1=1; j1<=tj;j1++){ /* For each valid combination of covariates or only once*/
1.222 brouard 6417: if (cptcovn>0) {
6418: fprintf(ficresprob, "\n#********** Variable ");
1.225 brouard 6419: for (z1=1; z1<=cptcoveff; z1++) fprintf(ficresprob, "V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
1.222 brouard 6420: fprintf(ficresprob, "**********\n#\n");
6421: fprintf(ficresprobcov, "\n#********** Variable ");
1.225 brouard 6422: for (z1=1; z1<=cptcoveff; z1++) fprintf(ficresprobcov, "V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
1.222 brouard 6423: fprintf(ficresprobcov, "**********\n#\n");
1.220 brouard 6424:
1.222 brouard 6425: fprintf(ficgp, "\n#********** Variable ");
1.225 brouard 6426: for (z1=1; z1<=cptcoveff; z1++) fprintf(ficgp, " V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
1.222 brouard 6427: fprintf(ficgp, "**********\n#\n");
1.220 brouard 6428:
6429:
1.222 brouard 6430: fprintf(fichtmcov, "\n<hr size=\"2\" color=\"#EC5E5E\">********** Variable ");
1.225 brouard 6431: for (z1=1; z1<=cptcoveff; z1++) fprintf(fichtm, "V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
1.222 brouard 6432: fprintf(fichtmcov, "**********\n<hr size=\"2\" color=\"#EC5E5E\">");
1.220 brouard 6433:
1.222 brouard 6434: fprintf(ficresprobcor, "\n#********** Variable ");
1.225 brouard 6435: for (z1=1; z1<=cptcoveff; z1++) fprintf(ficresprobcor, "V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
1.222 brouard 6436: fprintf(ficresprobcor, "**********\n#");
6437: if(invalidvarcomb[j1]){
6438: fprintf(ficgp,"\n#Combination (%d) ignored because no cases \n",j1);
6439: fprintf(fichtmcov,"\n<h3>Combination (%d) ignored because no cases </h3>\n",j1);
6440: continue;
6441: }
6442: }
6443: gradg=matrix(1,npar,1,(nlstate)*(nlstate+ndeath));
6444: trgradg=matrix(1,(nlstate)*(nlstate+ndeath),1,npar);
6445: gp=vector(1,(nlstate)*(nlstate+ndeath));
6446: gm=vector(1,(nlstate)*(nlstate+ndeath));
6447: for (age=bage; age<=fage; age ++){
6448: cov[2]=age;
6449: if(nagesqr==1)
6450: cov[3]= age*age;
6451: for (k=1; k<=cptcovn;k++) {
6452: cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(j1,k)];
6453: /*cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(j1,Tvar[k])];*//* j1 1 2 3 4
6454: * 1 1 1 1 1
6455: * 2 2 1 1 1
6456: * 3 1 2 1 1
6457: */
6458: /* nbcode[1][1]=0 nbcode[1][2]=1;*/
6459: }
6460: /* for (k=1; k<=cptcovage;k++) cov[2+Tage[k]]=cov[2+Tage[k]]*cov[2]; */
6461: for (k=1; k<=cptcovage;k++) cov[2+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2];
6462: for (k=1; k<=cptcovprod;k++)
6463: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)]*nbcode[Tvard[k][2]][codtabm(ij,k)];
1.220 brouard 6464:
6465:
1.222 brouard 6466: for(theta=1; theta <=npar; theta++){
6467: for(i=1; i<=npar; i++)
6468: xp[i] = x[i] + (i==theta ?delti[theta]:(double)0);
1.220 brouard 6469:
1.222 brouard 6470: pmij(pmmij,cov,ncovmodel,xp,nlstate);
1.220 brouard 6471:
1.222 brouard 6472: k=0;
6473: for(i=1; i<= (nlstate); i++){
6474: for(j=1; j<=(nlstate+ndeath);j++){
6475: k=k+1;
6476: gp[k]=pmmij[i][j];
6477: }
6478: }
1.220 brouard 6479:
1.222 brouard 6480: for(i=1; i<=npar; i++)
6481: xp[i] = x[i] - (i==theta ?delti[theta]:(double)0);
1.220 brouard 6482:
1.222 brouard 6483: pmij(pmmij,cov,ncovmodel,xp,nlstate);
6484: k=0;
6485: for(i=1; i<=(nlstate); i++){
6486: for(j=1; j<=(nlstate+ndeath);j++){
6487: k=k+1;
6488: gm[k]=pmmij[i][j];
6489: }
6490: }
1.220 brouard 6491:
1.222 brouard 6492: for(i=1; i<= (nlstate)*(nlstate+ndeath); i++)
6493: gradg[theta][i]=(gp[i]-gm[i])/(double)2./delti[theta];
6494: }
1.126 brouard 6495:
1.222 brouard 6496: for(j=1; j<=(nlstate)*(nlstate+ndeath);j++)
6497: for(theta=1; theta <=npar; theta++)
6498: trgradg[j][theta]=gradg[theta][j];
1.220 brouard 6499:
1.222 brouard 6500: matprod2(dnewm,trgradg,1,(nlstate)*(nlstate+ndeath),1,npar,1,npar,matcov);
6501: matprod2(doldm,dnewm,1,(nlstate)*(nlstate+ndeath),1,npar,1,(nlstate)*(nlstate+ndeath),gradg);
1.220 brouard 6502:
1.222 brouard 6503: pmij(pmmij,cov,ncovmodel,x,nlstate);
1.220 brouard 6504:
1.222 brouard 6505: k=0;
6506: for(i=1; i<=(nlstate); i++){
6507: for(j=1; j<=(nlstate+ndeath);j++){
6508: k=k+1;
6509: mu[k][(int) age]=pmmij[i][j];
6510: }
6511: }
6512: for(i=1;i<=(nlstate)*(nlstate+ndeath);i++)
6513: for(j=1;j<=(nlstate)*(nlstate+ndeath);j++)
6514: varpij[i][j][(int)age] = doldm[i][j];
1.220 brouard 6515:
1.222 brouard 6516: /*printf("\n%d ",(int)age);
6517: for (i=1; i<=(nlstate)*(nlstate+ndeath);i++){
6518: printf("%e [%e ;%e] ",gm[i],gm[i]-2*sqrt(doldm[i][i]),gm[i]+2*sqrt(doldm[i][i]));
6519: fprintf(ficlog,"%e [%e ;%e] ",gm[i],gm[i]-2*sqrt(doldm[i][i]),gm[i]+2*sqrt(doldm[i][i]));
6520: }*/
1.220 brouard 6521:
1.222 brouard 6522: fprintf(ficresprob,"\n%d ",(int)age);
6523: fprintf(ficresprobcov,"\n%d ",(int)age);
6524: fprintf(ficresprobcor,"\n%d ",(int)age);
1.220 brouard 6525:
1.222 brouard 6526: for (i=1; i<=(nlstate)*(nlstate+ndeath);i++)
6527: fprintf(ficresprob,"%11.3e (%11.3e) ",mu[i][(int) age],sqrt(varpij[i][i][(int)age]));
6528: for (i=1; i<=(nlstate)*(nlstate+ndeath);i++){
6529: fprintf(ficresprobcov,"%11.3e ",mu[i][(int) age]);
6530: fprintf(ficresprobcor,"%11.3e ",mu[i][(int) age]);
6531: }
6532: i=0;
6533: for (k=1; k<=(nlstate);k++){
6534: for (l=1; l<=(nlstate+ndeath);l++){
6535: i++;
6536: fprintf(ficresprobcov,"\n%d %d-%d",(int)age,k,l);
6537: fprintf(ficresprobcor,"\n%d %d-%d",(int)age,k,l);
6538: for (j=1; j<=i;j++){
6539: /* printf(" k=%d l=%d i=%d j=%d\n",k,l,i,j);fflush(stdout); */
6540: fprintf(ficresprobcov," %11.3e",varpij[i][j][(int)age]);
6541: fprintf(ficresprobcor," %11.3e",varpij[i][j][(int) age]/sqrt(varpij[i][i][(int) age])/sqrt(varpij[j][j][(int)age]));
6542: }
6543: }
6544: }/* end of loop for state */
6545: } /* end of loop for age */
6546: free_vector(gp,1,(nlstate+ndeath)*(nlstate+ndeath));
6547: free_vector(gm,1,(nlstate+ndeath)*(nlstate+ndeath));
6548: free_matrix(trgradg,1,(nlstate+ndeath)*(nlstate+ndeath),1,npar);
6549: free_matrix(gradg,1,(nlstate+ndeath)*(nlstate+ndeath),1,npar);
6550:
6551: /* Confidence intervalle of pij */
6552: /*
6553: fprintf(ficgp,"\nunset parametric;unset label");
6554: fprintf(ficgp,"\nset log y;unset log x; set xlabel \"Age\";set ylabel \"probability (year-1)\"");
6555: fprintf(ficgp,"\nset ter png small\nset size 0.65,0.65");
6556: 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);
6557: fprintf(fichtm,"\n<br><img src=\"pijgr%s.png\"> ",optionfilefiname);
6558: fprintf(ficgp,"\nset out \"pijgr%s.png\"",optionfilefiname);
6559: fprintf(ficgp,"\nplot \"%s\" every :::%d::%d u 1:2 \"\%%lf",k1,k2,xfilevarprob);
6560: */
6561:
6562: /* Drawing ellipsoids of confidence of two variables p(k1-l1,k2-l2)*/
6563: first1=1;first2=2;
6564: for (k2=1; k2<=(nlstate);k2++){
6565: for (l2=1; l2<=(nlstate+ndeath);l2++){
6566: if(l2==k2) continue;
6567: j=(k2-1)*(nlstate+ndeath)+l2;
6568: for (k1=1; k1<=(nlstate);k1++){
6569: for (l1=1; l1<=(nlstate+ndeath);l1++){
6570: if(l1==k1) continue;
6571: i=(k1-1)*(nlstate+ndeath)+l1;
6572: if(i<=j) continue;
6573: for (age=bage; age<=fage; age ++){
6574: if ((int)age %5==0){
6575: v1=varpij[i][i][(int)age]/stepm*YEARM/stepm*YEARM;
6576: v2=varpij[j][j][(int)age]/stepm*YEARM/stepm*YEARM;
6577: cv12=varpij[i][j][(int)age]/stepm*YEARM/stepm*YEARM;
6578: mu1=mu[i][(int) age]/stepm*YEARM ;
6579: mu2=mu[j][(int) age]/stepm*YEARM;
6580: c12=cv12/sqrt(v1*v2);
6581: /* Computing eigen value of matrix of covariance */
6582: lc1=((v1+v2)+sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
6583: lc2=((v1+v2)-sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
6584: if ((lc2 <0) || (lc1 <0) ){
6585: if(first2==1){
6586: first1=0;
6587: 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);
6588: }
6589: 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);
6590: /* lc1=fabs(lc1); */ /* If we want to have them positive */
6591: /* lc2=fabs(lc2); */
6592: }
1.220 brouard 6593:
1.222 brouard 6594: /* Eigen vectors */
6595: v11=(1./sqrt(1+(v1-lc1)*(v1-lc1)/cv12/cv12));
6596: /*v21=sqrt(1.-v11*v11); *//* error */
6597: v21=(lc1-v1)/cv12*v11;
6598: v12=-v21;
6599: v22=v11;
6600: tnalp=v21/v11;
6601: if(first1==1){
6602: first1=0;
6603: 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);
6604: }
6605: 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);
6606: /*printf(fignu*/
6607: /* mu1+ v11*lc1*cost + v12*lc2*sin(t) */
6608: /* mu2+ v21*lc1*cost + v22*lc2*sin(t) */
6609: if(first==1){
6610: first=0;
6611: fprintf(ficgp,"\n# Ellipsoids of confidence\n#\n");
6612: fprintf(ficgp,"\nset parametric;unset label");
6613: 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);
6614: fprintf(ficgp,"\nset ter svg size 640, 480");
1.266 brouard 6615: fprintf(fichtmcov,"\n<p><br>Ellipsoids of confidence cov(p%1d%1d,p%1d%1d) expressed in year<sup>-1</sup>\
1.220 brouard 6616: :<a href=\"%s_%d%1d%1d-%1d%1d.svg\"> \
1.201 brouard 6617: %s_%d%1d%1d-%1d%1d.svg</A>, ",k1,l1,k2,l2,\
1.222 brouard 6618: subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2, \
6619: subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
6620: fprintf(fichtmcov,"\n<br><img src=\"%s_%d%1d%1d-%1d%1d.svg\"> ",subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
6621: fprintf(fichtmcov,"\n<br> Correlation at age %d (%.3f),",(int) age, c12);
6622: fprintf(ficgp,"\nset out \"%s_%d%1d%1d-%1d%1d.svg\"",subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
6623: fprintf(ficgp,"\nset label \"%d\" at %11.3e,%11.3e center",(int) age, mu1,mu2);
6624: fprintf(ficgp,"\n# Age %d, p%1d%1d - p%1d%1d",(int) age, k1,l1,k2,l2);
6625: 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 6626: mu1,std,v11,sqrt(lc1),v12,sqrt(fabs(lc2)), \
6627: mu2,std,v21,sqrt(lc1),v22,sqrt(fabs(lc2))); /* For gnuplot only */
1.222 brouard 6628: }else{
6629: first=0;
6630: fprintf(fichtmcov," %d (%.3f),",(int) age, c12);
6631: fprintf(ficgp,"\n# Age %d, p%1d%1d - p%1d%1d",(int) age, k1,l1,k2,l2);
6632: fprintf(ficgp,"\nset label \"%d\" at %11.3e,%11.3e center",(int) age, mu1,mu2);
6633: 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 6634: mu1,std,v11,sqrt(lc1),v12,sqrt(fabs(lc2)), \
6635: mu2,std,v21,sqrt(lc1),v22,sqrt(fabs(lc2)));
1.222 brouard 6636: }/* if first */
6637: } /* age mod 5 */
6638: } /* end loop age */
6639: fprintf(ficgp,"\nset out;\nset out \"%s_%d%1d%1d-%1d%1d.svg\";replot;set out;",subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
6640: first=1;
6641: } /*l12 */
6642: } /* k12 */
6643: } /*l1 */
6644: }/* k1 */
6645: } /* loop on combination of covariates j1 */
6646: free_ma3x(varpij,1,nlstate,1,nlstate+ndeath,(int) bage, (int)fage);
6647: free_matrix(mu,1,(nlstate+ndeath)*(nlstate+ndeath),(int) bage, (int)fage);
6648: free_matrix(doldm,1,(nlstate)*(nlstate+ndeath),1,(nlstate)*(nlstate+ndeath));
6649: free_matrix(dnewm,1,(nlstate)*(nlstate+ndeath),1,npar);
6650: free_vector(xp,1,npar);
6651: fclose(ficresprob);
6652: fclose(ficresprobcov);
6653: fclose(ficresprobcor);
6654: fflush(ficgp);
6655: fflush(fichtmcov);
6656: }
1.126 brouard 6657:
6658:
6659: /******************* Printing html file ***********/
1.201 brouard 6660: void printinghtml(char fileresu[], char title[], char datafile[], int firstpass, \
1.126 brouard 6661: int lastpass, int stepm, int weightopt, char model[],\
6662: int imx,int jmin, int jmax, double jmeanint,char rfileres[],\
1.258 brouard 6663: int popforecast, int mobilav, int prevfcast, int mobilavproj, int backcast, int estepm , \
1.213 brouard 6664: double jprev1, double mprev1,double anprev1, double dateprev1, \
6665: double jprev2, double mprev2,double anprev2, double dateprev2){
1.237 brouard 6666: int jj1, k1, i1, cpt, k4, nres;
1.126 brouard 6667:
6668: fprintf(fichtm,"<ul><li><a href='#firstorder'>Result files (first order: no variance)</a>\n \
6669: <li><a href='#secondorder'>Result files (second order (variance)</a>\n \
6670: </ul>");
1.237 brouard 6671: fprintf(fichtm,"<ul><li> model=1+age+%s\n \
6672: </ul>", model);
1.214 brouard 6673: fprintf(fichtm,"<ul><li><h4><a name='firstorder'>Result files (first order: no variance)</a></h4>\n");
6674: 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",
6675: jprev1, mprev1,anprev1,jprev2, mprev2,anprev2,subdirfext3(optionfilefiname,"PHTMFR_",".htm"),subdirfext3(optionfilefiname,"PHTMFR_",".htm"));
6676: 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 6677: jprev1, mprev1,anprev1,jprev2, mprev2,anprev2,subdirfext3(optionfilefiname,"PHTM_",".htm"),subdirfext3(optionfilefiname,"PHTM_",".htm"));
6678: fprintf(fichtm,", <a href=\"%s\">%s</a> (text file) <br>\n",subdirf2(fileresu,"P_"),subdirf2(fileresu,"P_"));
1.126 brouard 6679: fprintf(fichtm,"\
6680: - Estimated transition probabilities over %d (stepm) months: <a href=\"%s\">%s</a><br>\n ",
1.201 brouard 6681: stepm,subdirf2(fileresu,"PIJ_"),subdirf2(fileresu,"PIJ_"));
1.126 brouard 6682: fprintf(fichtm,"\
1.217 brouard 6683: - Estimated back transition probabilities over %d (stepm) months: <a href=\"%s\">%s</a><br>\n ",
6684: stepm,subdirf2(fileresu,"PIJB_"),subdirf2(fileresu,"PIJB_"));
6685: fprintf(fichtm,"\
1.126 brouard 6686: - Period (stable) prevalence in each health state: <a href=\"%s\">%s</a> <br>\n",
1.201 brouard 6687: subdirf2(fileresu,"PL_"),subdirf2(fileresu,"PL_"));
1.126 brouard 6688: fprintf(fichtm,"\
1.217 brouard 6689: - Period (stable) back prevalence in each health state: <a href=\"%s\">%s</a> <br>\n",
6690: subdirf2(fileresu,"PLB_"),subdirf2(fileresu,"PLB_"));
6691: fprintf(fichtm,"\
1.211 brouard 6692: - (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 6693: <a href=\"%s\">%s</a> <br>\n",
1.201 brouard 6694: estepm,subdirf2(fileresu,"E_"),subdirf2(fileresu,"E_"));
1.211 brouard 6695: if(prevfcast==1){
6696: fprintf(fichtm,"\
6697: - Prevalence projections by age and states: \
1.201 brouard 6698: <a href=\"%s\">%s</a> <br>\n</li>", subdirf2(fileresu,"F_"),subdirf2(fileresu,"F_"));
1.211 brouard 6699: }
1.126 brouard 6700:
6701:
1.225 brouard 6702: m=pow(2,cptcoveff);
1.222 brouard 6703: if (cptcovn < 1) {m=1;ncodemax[1]=1;}
1.126 brouard 6704:
1.264 brouard 6705: fprintf(fichtm," \n<ul><li><b>Graphs</b></li><p>");
6706:
6707: jj1=0;
6708:
6709: fprintf(fichtm," \n<ul>");
6710: for(nres=1; nres <= nresult; nres++) /* For each resultline */
6711: for(k1=1; k1<=m;k1++){ /* For each combination of covariate */
6712: if(m != 1 && TKresult[nres]!= k1)
6713: continue;
6714: jj1++;
6715: if (cptcovn > 0) {
6716: fprintf(fichtm,"\n<li><a size=\"1\" color=\"#EC5E5E\" href=\"#rescov");
6717: for (cpt=1; cpt<=cptcoveff;cpt++){
6718: fprintf(fichtm,"_V%d=%d_",Tvresult[nres][cpt],(int)Tresult[nres][cpt]);
6719: }
6720: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
6721: fprintf(fichtm,"_V%d=%f_",Tvqresult[nres][k4],Tqresult[nres][k4]);
6722: }
6723: fprintf(fichtm,"\">");
6724:
6725: /* if(nqfveff+nqtveff 0) */ /* Test to be done */
6726: fprintf(fichtm,"************ Results for covariates");
6727: for (cpt=1; cpt<=cptcoveff;cpt++){
6728: fprintf(fichtm," V%d=%d ",Tvresult[nres][cpt],(int)Tresult[nres][cpt]);
6729: }
6730: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
6731: fprintf(fichtm," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
6732: }
6733: if(invalidvarcomb[k1]){
6734: fprintf(fichtm," Warning Combination (%d) ignored because no cases ",k1);
6735: continue;
6736: }
6737: fprintf(fichtm,"</a></li>");
6738: } /* cptcovn >0 */
6739: }
6740: fprintf(fichtm," \n</ul>");
6741:
1.222 brouard 6742: jj1=0;
1.237 brouard 6743:
6744: for(nres=1; nres <= nresult; nres++) /* For each resultline */
1.241 brouard 6745: for(k1=1; k1<=m;k1++){ /* For each combination of covariate */
1.253 brouard 6746: if(m != 1 && TKresult[nres]!= k1)
1.237 brouard 6747: continue;
1.220 brouard 6748:
1.222 brouard 6749: /* for(i1=1; i1<=ncodemax[k1];i1++){ */
6750: jj1++;
6751: if (cptcovn > 0) {
1.264 brouard 6752: fprintf(fichtm,"\n<p><a name=\"rescov");
6753: for (cpt=1; cpt<=cptcoveff;cpt++){
6754: fprintf(fichtm,"_V%d=%d_",Tvresult[nres][cpt],(int)Tresult[nres][cpt]);
6755: }
6756: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
6757: fprintf(fichtm,"_V%d=%f_",Tvqresult[nres][k4],Tqresult[nres][k4]);
6758: }
6759: fprintf(fichtm,"\"</a>");
6760:
1.222 brouard 6761: fprintf(fichtm,"<hr size=\"2\" color=\"#EC5E5E\">************ Results for covariates");
1.225 brouard 6762: for (cpt=1; cpt<=cptcoveff;cpt++){
1.237 brouard 6763: fprintf(fichtm," V%d=%d ",Tvresult[nres][cpt],(int)Tresult[nres][cpt]);
6764: printf(" V%d=%d ",Tvresult[nres][cpt],Tresult[nres][cpt]);fflush(stdout);
6765: /* fprintf(fichtm," V%d=%d ",Tvaraff[cpt],nbcode[Tvaraff[cpt]][codtabm(jj1,cpt)]); */
6766: /* printf(" V%d=%d ",Tvaraff[cpt],nbcode[Tvaraff[cpt]][codtabm(jj1,cpt)]);fflush(stdout); */
1.222 brouard 6767: }
1.237 brouard 6768: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
6769: fprintf(fichtm," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
6770: printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);fflush(stdout);
6771: }
6772:
1.230 brouard 6773: /* if(nqfveff+nqtveff 0) */ /* Test to be done */
1.222 brouard 6774: fprintf(fichtm," ************\n<hr size=\"2\" color=\"#EC5E5E\">");
6775: if(invalidvarcomb[k1]){
6776: fprintf(fichtm,"\n<h3>Combination (%d) ignored because no cases </h3>\n",k1);
6777: printf("\nCombination (%d) ignored because no cases \n",k1);
6778: continue;
6779: }
6780: }
6781: /* aij, bij */
1.259 brouard 6782: 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 6783: <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 6784: /* Pij */
1.241 brouard 6785: 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> \
6786: <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 6787: /* Quasi-incidences */
6788: 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 6789: before but expressed in per year i.e. quasi incidences if stepm is small and probabilities too, \
1.211 brouard 6790: 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 6791: 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> \
6792: <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 6793: /* Survival functions (period) in state j */
6794: for(cpt=1; cpt<=nlstate;cpt++){
1.241 brouard 6795: 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> \
6796: <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 6797: }
6798: /* State specific survival functions (period) */
6799: for(cpt=1; cpt<=nlstate;cpt++){
6800: fprintf(fichtm,"<br>\n- Survival functions from state %d in each live state and total.\
1.220 brouard 6801: Or probability to survive in various states (1 to %d) being in state %d at different ages. \
1.241 brouard 6802: <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 6803: }
6804: /* Period (stable) prevalence in each health state */
6805: for(cpt=1; cpt<=nlstate;cpt++){
1.264 brouard 6806: 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> \
6807: <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 6808: }
6809: if(backcast==1){
6810: /* Period (stable) back prevalence in each health state */
6811: for(cpt=1; cpt<=nlstate;cpt++){
1.264 brouard 6812: 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 6813: <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 6814: }
1.217 brouard 6815: }
1.222 brouard 6816: if(prevfcast==1){
6817: /* Projection of prevalence up to period (stable) prevalence in each health state */
6818: for(cpt=1; cpt<=nlstate;cpt++){
1.268 brouard 6819: 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 6820: <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 6821: }
6822: }
1.268 brouard 6823: if(backcast==1){
6824: /* Back projection of prevalence up to stable (mixed) back-prevalence in each health state */
6825: for(cpt=1; cpt<=nlstate;cpt++){
6826: 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> \
6827: <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);
6828: }
6829: }
1.220 brouard 6830:
1.222 brouard 6831: for(cpt=1; cpt<=nlstate;cpt++) {
1.241 brouard 6832: 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> \
6833: <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 6834: }
6835: /* } /\* end i1 *\/ */
6836: }/* End k1 */
6837: fprintf(fichtm,"</ul>");
1.126 brouard 6838:
1.222 brouard 6839: fprintf(fichtm,"\
1.126 brouard 6840: \n<br><li><h4> <a name='secondorder'>Result files (second order: variances)</a></h4>\n\
1.193 brouard 6841: - Parameter file with estimated parameters and covariance matrix: <a href=\"%s\">%s</a> <br> \
1.203 brouard 6842: - 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 6843: But because parameters are usually highly correlated (a higher incidence of disability \
6844: and a higher incidence of recovery can give very close observed transition) it might \
6845: be very useful to look not only at linear confidence intervals estimated from the \
6846: variances but at the covariance matrix. And instead of looking at the estimated coefficients \
6847: (parameters) of the logistic regression, it might be more meaningful to visualize the \
6848: covariance matrix of the one-step probabilities. \
6849: See page 'Matrix of variance-covariance of one-step probabilities' below. \n", rfileres,rfileres);
1.126 brouard 6850:
1.222 brouard 6851: fprintf(fichtm," - Standard deviation of one-step probabilities: <a href=\"%s\">%s</a> <br>\n",
6852: subdirf2(fileresu,"PROB_"),subdirf2(fileresu,"PROB_"));
6853: fprintf(fichtm,"\
1.126 brouard 6854: - Variance-covariance of one-step probabilities: <a href=\"%s\">%s</a> <br>\n",
1.222 brouard 6855: subdirf2(fileresu,"PROBCOV_"),subdirf2(fileresu,"PROBCOV_"));
1.126 brouard 6856:
1.222 brouard 6857: fprintf(fichtm,"\
1.126 brouard 6858: - Correlation matrix of one-step probabilities: <a href=\"%s\">%s</a> <br>\n",
1.222 brouard 6859: subdirf2(fileresu,"PROBCOR_"),subdirf2(fileresu,"PROBCOR_"));
6860: fprintf(fichtm,"\
1.126 brouard 6861: - 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): \
6862: <a href=\"%s\">%s</a> <br>\n</li>",
1.201 brouard 6863: estepm,subdirf2(fileresu,"CVE_"),subdirf2(fileresu,"CVE_"));
1.222 brouard 6864: fprintf(fichtm,"\
1.126 brouard 6865: - (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): \
6866: <a href=\"%s\">%s</a> <br>\n</li>",
1.201 brouard 6867: estepm,subdirf2(fileresu,"STDE_"),subdirf2(fileresu,"STDE_"));
1.222 brouard 6868: fprintf(fichtm,"\
1.128 brouard 6869: - 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 6870: estepm, subdirf2(fileresu,"V_"),subdirf2(fileresu,"V_"));
6871: fprintf(fichtm,"\
1.128 brouard 6872: - 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 6873: estepm, subdirf2(fileresu,"T_"),subdirf2(fileresu,"T_"));
6874: fprintf(fichtm,"\
1.126 brouard 6875: - Standard deviation of period (stable) prevalences: <a href=\"%s\">%s</a> <br>\n",\
1.222 brouard 6876: subdirf2(fileresu,"VPL_"),subdirf2(fileresu,"VPL_"));
1.126 brouard 6877:
6878: /* if(popforecast==1) fprintf(fichtm,"\n */
6879: /* - Prevalences forecasting: <a href=\"f%s\">f%s</a> <br>\n */
6880: /* - Population forecasting (if popforecast=1): <a href=\"pop%s\">pop%s</a> <br>\n */
6881: /* <br>",fileres,fileres,fileres,fileres); */
6882: /* else */
6883: /* 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 6884: fflush(fichtm);
6885: fprintf(fichtm," <ul><li><b>Graphs</b></li><p>");
1.126 brouard 6886:
1.225 brouard 6887: m=pow(2,cptcoveff);
1.222 brouard 6888: if (cptcovn < 1) {m=1;ncodemax[1]=1;}
1.126 brouard 6889:
1.222 brouard 6890: jj1=0;
1.237 brouard 6891:
1.241 brouard 6892: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.222 brouard 6893: for(k1=1; k1<=m;k1++){
1.253 brouard 6894: if(m != 1 && TKresult[nres]!= k1)
1.237 brouard 6895: continue;
1.222 brouard 6896: /* for(i1=1; i1<=ncodemax[k1];i1++){ */
6897: jj1++;
1.126 brouard 6898: if (cptcovn > 0) {
6899: fprintf(fichtm,"<hr size=\"2\" color=\"#EC5E5E\">************ Results for covariates");
1.225 brouard 6900: for (cpt=1; cpt<=cptcoveff;cpt++) /**< cptcoveff number of variables */
1.237 brouard 6901: fprintf(fichtm," V%d=%d ",Tvresult[nres][cpt],Tresult[nres][cpt]);
6902: /* fprintf(fichtm," V%d=%d ",Tvaraff[cpt],nbcode[Tvaraff[cpt]][codtabm(jj1,cpt)]); */
6903: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
6904: fprintf(fichtm," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
6905: }
6906:
1.126 brouard 6907: fprintf(fichtm," ************\n<hr size=\"2\" color=\"#EC5E5E\">");
1.220 brouard 6908:
1.222 brouard 6909: if(invalidvarcomb[k1]){
6910: fprintf(fichtm,"\n<h4>Combination (%d) ignored because no cases </h4>\n",k1);
6911: continue;
6912: }
1.126 brouard 6913: }
6914: for(cpt=1; cpt<=nlstate;cpt++) {
1.258 brouard 6915: fprintf(fichtm,"\n<br>- Observed (cross-sectional with mov_average=%d) and period (incidence based) \
1.241 brouard 6916: 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 6917: <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 6918: }
6919: fprintf(fichtm,"\n<br>- Total life expectancy by age and \
1.128 brouard 6920: health expectancies in states (1) and (2). If popbased=1 the smooth (due to the model) \
6921: true period expectancies (those weighted with period prevalences are also\
6922: drawn in addition to the population based expectancies computed using\
1.241 brouard 6923: observed and cahotic prevalences: <a href=\"%s_%d-%d.svg\">%s_%d-%d.svg</a>\n<br>\
6924: <img src=\"%s_%d-%d.svg\">",subdirf2(optionfilefiname,"E_"),k1,nres,subdirf2(optionfilefiname,"E_"),k1,nres,subdirf2(optionfilefiname,"E_"),k1,nres);
1.222 brouard 6925: /* } /\* end i1 *\/ */
6926: }/* End k1 */
1.241 brouard 6927: }/* End nres */
1.222 brouard 6928: fprintf(fichtm,"</ul>");
6929: fflush(fichtm);
1.126 brouard 6930: }
6931:
6932: /******************* Gnuplot file **************/
1.270 brouard 6933: 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 6934:
6935: char dirfileres[132],optfileres[132];
1.264 brouard 6936: char gplotcondition[132], gplotlabel[132];
1.237 brouard 6937: 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 6938: int lv=0, vlv=0, kl=0;
1.130 brouard 6939: int ng=0;
1.201 brouard 6940: int vpopbased;
1.223 brouard 6941: int ioffset; /* variable offset for columns */
1.270 brouard 6942: int iyearc=1; /* variable column for year of projection */
6943: int iagec=1; /* variable column for age of projection */
1.235 brouard 6944: int nres=0; /* Index of resultline */
1.266 brouard 6945: int istart=1; /* For starting graphs in projections */
1.219 brouard 6946:
1.126 brouard 6947: /* if((ficgp=fopen(optionfilegnuplot,"a"))==NULL) { */
6948: /* printf("Problem with file %s",optionfilegnuplot); */
6949: /* fprintf(ficlog,"Problem with file %s",optionfilegnuplot); */
6950: /* } */
6951:
6952: /*#ifdef windows */
6953: fprintf(ficgp,"cd \"%s\" \n",pathc);
1.223 brouard 6954: /*#endif */
1.225 brouard 6955: m=pow(2,cptcoveff);
1.126 brouard 6956:
1.202 brouard 6957: /* Contribution to likelihood */
6958: /* Plot the probability implied in the likelihood */
1.223 brouard 6959: fprintf(ficgp,"\n# Contributions to the Likelihood, mle >=1. For mle=4 no interpolation, pure matrix products.\n#\n");
6960: fprintf(ficgp,"\n set log y; unset log x;set xlabel \"Age\"; set ylabel \"Likelihood (-2Log(L))\";");
6961: /* fprintf(ficgp,"\nset ter svg size 640, 480"); */ /* Too big for svg */
6962: fprintf(ficgp,"\nset ter pngcairo size 640, 480");
1.204 brouard 6963: /* nice for mle=4 plot by number of matrix products.
1.202 brouard 6964: replot "rrtest1/toto.txt" u 2:($4 == 1 && $5==2 ? $9 : 1/0):5 t "p12" with point lc 1 */
6965: /* replot exp(p1+p2*x)/(1+exp(p1+p2*x)+exp(p3+p4*x)+exp(p5+p6*x)) t "p12(x)" */
1.223 brouard 6966: /* fprintf(ficgp,"\nset out \"%s.svg\";",subdirf2(optionfilefiname,"ILK_")); */
6967: fprintf(ficgp,"\nset out \"%s-dest.png\";",subdirf2(optionfilefiname,"ILK_"));
6968: 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));
6969: fprintf(ficgp,"\nset out \"%s-ori.png\";",subdirf2(optionfilefiname,"ILK_"));
6970: 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));
6971: for (i=1; i<= nlstate ; i ++) {
6972: fprintf(ficgp,"\nset out \"%s-p%dj.png\";set ylabel \"Probability for each individual/wave\";",subdirf2(optionfilefiname,"ILK_"),i);
6973: fprintf(ficgp,"unset log;\n# plot weighted, mean weight should have point size of 0.5\n plot \"%s\"",subdirf(fileresilk));
6974: 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);
6975: for (j=2; j<= nlstate+ndeath ; j ++) {
6976: 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);
6977: }
6978: fprintf(ficgp,";\nset out; unset ylabel;\n");
6979: }
6980: /* 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 */
6981: /* fprintf(ficgp,"\nset log y;plot \"%s\" u 2:(-$11):3 t \"All sample, all transitions\" with dots lc variable",subdirf(fileresilk)); */
6982: /* fprintf(ficgp,"\nreplot \"%s\" u 2:($3 <= 3 ? -$11 : 1/0):3 t \"First 3 individuals\" with line lc variable", subdirf(fileresilk)); */
6983: fprintf(ficgp,"\nset out;unset log\n");
6984: /* fprintf(ficgp,"\nset out \"%s.svg\"; replot; set out; # bug gnuplot",subdirf2(optionfilefiname,"ILK_")); */
1.202 brouard 6985:
1.126 brouard 6986: strcpy(dirfileres,optionfilefiname);
6987: strcpy(optfileres,"vpl");
1.223 brouard 6988: /* 1eme*/
1.238 brouard 6989: for (cpt=1; cpt<= nlstate ; cpt ++){ /* For each live state */
6990: for (k1=1; k1<= m ; k1 ++){ /* For each valid combination of covariate */
1.236 brouard 6991: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.238 brouard 6992: /* plot [100000000000000000000:-100000000000000000000] "mysbiaspar/vplrmysbiaspar.txt to check */
1.253 brouard 6993: if(m != 1 && TKresult[nres]!= k1)
1.238 brouard 6994: continue;
6995: /* We are interested in selected combination by the resultline */
1.246 brouard 6996: /* printf("\n# 1st: Period (stable) prevalence with CI: 'VPL_' files and live state =%d ", cpt); */
1.238 brouard 6997: fprintf(ficgp,"\n# 1st: Period (stable) prevalence with CI: 'VPL_' files and live state =%d ", cpt);
1.264 brouard 6998: strcpy(gplotlabel,"(");
1.238 brouard 6999: for (k=1; k<=cptcoveff; k++){ /* For each covariate k get corresponding value lv for combination k1 */
7000: lv= decodtabm(k1,k,cptcoveff); /* Should be the value of the covariate corresponding to k1 combination */
7001: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7002: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7003: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7004: vlv= nbcode[Tvaraff[k]][lv]; /* vlv is the value of the covariate lv, 0 or 1 */
7005: /* For each combination of covariate k1 (V1=1, V3=0), we printed the current covariate k and its value vlv */
1.246 brouard 7006: /* printf(" V%d=%d ",Tvaraff[k],vlv); */
1.238 brouard 7007: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 7008: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.238 brouard 7009: }
7010: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
1.246 brouard 7011: /* printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
1.238 brouard 7012: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7013: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
7014: }
7015: strcpy(gplotlabel+strlen(gplotlabel),")");
1.246 brouard 7016: /* printf("\n#\n"); */
1.238 brouard 7017: fprintf(ficgp,"\n#\n");
7018: if(invalidvarcomb[k1]){
1.260 brouard 7019: /*k1=k1-1;*/ /* To be checked */
1.238 brouard 7020: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7021: continue;
7022: }
1.235 brouard 7023:
1.241 brouard 7024: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"V_"),cpt,k1,nres);
7025: fprintf(ficgp,"\n#set out \"V_%s_%d-%d-%d.svg\" \n",optionfilefiname,cpt,k1,nres);
1.264 brouard 7026: 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 7027: 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);
7028: /* 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); */
7029: /* k1-1 error should be nres-1*/
1.238 brouard 7030: for (i=1; i<= nlstate ; i ++) {
7031: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
7032: else fprintf(ficgp," %%*lf (%%*lf)");
7033: }
1.260 brouard 7034: 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 7035: for (i=1; i<= nlstate ; i ++) {
7036: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
7037: else fprintf(ficgp," %%*lf (%%*lf)");
7038: }
1.260 brouard 7039: fprintf(ficgp,"\" t\"95%% CI\" w l lt 1,\"%s\" every :::%d::%d u 1:($2==%d ? $3-1.96*$4 : 1/0) \"%%lf %%lf",subdirf2(fileresu,"VPL_"),nres-1,nres-1,nres);
1.238 brouard 7040: for (i=1; i<= nlstate ; i ++) {
7041: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
7042: else fprintf(ficgp," %%*lf (%%*lf)");
7043: }
1.265 brouard 7044: /* fprintf(ficgp,"\" t\"\" w l lt 1,\"%s\" every :::%d::%d u 1:($%d) t\"Observed prevalence\" w l lt 2",subdirf2(fileresu,"P_"),k1-1,k1-1,2+4*(cpt-1)); */
7045:
7046: fprintf(ficgp,"\" t\"\" w l lt 1,\"%s\" u 1:((",subdirf2(fileresu,"P_"));
7047: if(cptcoveff ==0){
1.271 brouard 7048: fprintf(ficgp,"$%d)) t 'Observed prevalence in state %d' with line lt 3", 2+3*(cpt-1), cpt );
1.265 brouard 7049: }else{
7050: kl=0;
7051: for (k=1; k<=cptcoveff; k++){ /* For each combination of covariate */
7052: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate value corresponding to k1 combination and kth covariate */
7053: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7054: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7055: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7056: vlv= nbcode[Tvaraff[k]][lv];
7057: kl++;
7058: /* 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 *\/ */
7059: /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */
7060: /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */
7061: /* '' u 6:(($1==1 && $2==0 && $3==2 && $4==0)? $9/(1.-$15) : 1/0):($5==2000? 3:2) t 'p.1' with line lc variable*/
7062: if(k==cptcoveff){
7063: fprintf(ficgp,"$%d==%d && $%d==%d)? $%d : 1/0) t 'Observed prevalence in state %d' w l lt 2",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][lv], \
7064: 2+cptcoveff*2+3*(cpt-1), cpt ); /* 4 or 6 ?*/
7065: }else{
7066: fprintf(ficgp,"$%d==%d && $%d==%d && ",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][lv]);
7067: kl++;
7068: }
7069: } /* end covariate */
7070: } /* end if no covariate */
7071:
1.238 brouard 7072: if(backcast==1){ /* We need to get the corresponding values of the covariates involved in this combination k1 */
7073: /* fprintf(ficgp,",\"%s\" every :::%d::%d u 1:($%d) t\"Backward stable prevalence\" w l lt 3",subdirf2(fileresu,"PLB_"),k1-1,k1-1,1+cpt); */
1.242 brouard 7074: fprintf(ficgp,",\"%s\" u 1:((",subdirf2(fileresu,"PLB_")); /* Age is in 1, nres in 2 to be fixed */
1.238 brouard 7075: if(cptcoveff ==0){
1.245 brouard 7076: fprintf(ficgp,"$%d)) t 'Backward prevalence in state %d' with line lt 3", 2+(cpt-1), cpt );
1.238 brouard 7077: }else{
7078: kl=0;
7079: for (k=1; k<=cptcoveff; k++){ /* For each combination of covariate */
7080: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate value corresponding to k1 combination and kth covariate */
7081: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7082: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7083: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7084: vlv= nbcode[Tvaraff[k]][lv];
1.223 brouard 7085: kl++;
1.238 brouard 7086: /* 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 *\/ */
7087: /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */
7088: /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */
7089: /* '' u 6:(($1==1 && $2==0 && $3==2 && $4==0)? $9/(1.-$15) : 1/0):($5==2000? 3:2) t 'p.1' with line lc variable*/
7090: if(k==cptcoveff){
1.245 brouard 7091: fprintf(ficgp,"$%d==%d && $%d==%d)? $%d : 1/0) t 'Backward prevalence in state %d' w l lt 3",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][lv], \
1.242 brouard 7092: 2+cptcoveff*2+(cpt-1), cpt ); /* 4 or 6 ?*/
1.238 brouard 7093: }else{
7094: fprintf(ficgp,"$%d==%d && $%d==%d && ",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][lv]);
7095: kl++;
7096: }
7097: } /* end covariate */
7098: } /* end if no covariate */
1.268 brouard 7099: if(backcast == 1){
7100: fprintf(ficgp,", \"%s\" every :::%d::%d u 1:($2==%d ? $3:1/0) \"%%lf %%lf",subdirf2(fileresu,"VBL_"),nres-1,nres-1,nres);
7101: /* k1-1 error should be nres-1*/
7102: for (i=1; i<= nlstate ; i ++) {
7103: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
7104: else fprintf(ficgp," %%*lf (%%*lf)");
7105: }
1.271 brouard 7106: 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 7107: for (i=1; i<= nlstate ; i ++) {
7108: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
7109: else fprintf(ficgp," %%*lf (%%*lf)");
7110: }
1.272 ! brouard 7111: fprintf(ficgp,"\" t\"95%% CI\" w l lt 5,\"%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 7112: for (i=1; i<= nlstate ; i ++) {
7113: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
7114: else fprintf(ficgp," %%*lf (%%*lf)");
7115: }
1.272 ! brouard 7116: fprintf(ficgp,"\" t\"\" w l lt 5");
1.268 brouard 7117: } /* end if backprojcast */
1.238 brouard 7118: } /* end if backcast */
1.264 brouard 7119: fprintf(ficgp,"\nset out ;unset label;\n");
1.238 brouard 7120: } /* nres */
1.201 brouard 7121: } /* k1 */
7122: } /* cpt */
1.235 brouard 7123:
7124:
1.126 brouard 7125: /*2 eme*/
1.238 brouard 7126: for (k1=1; k1<= m ; k1 ++){
7127: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 7128: if(m != 1 && TKresult[nres]!= k1)
1.238 brouard 7129: continue;
7130: fprintf(ficgp,"\n# 2nd: Total life expectancy with CI: 't' files ");
1.264 brouard 7131: strcpy(gplotlabel,"(");
1.238 brouard 7132: for (k=1; k<=cptcoveff; k++){ /* For each covariate and each value */
1.225 brouard 7133: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate number corresponding to k1 combination */
1.223 brouard 7134: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7135: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7136: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7137: vlv= nbcode[Tvaraff[k]][lv];
7138: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 7139: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.211 brouard 7140: }
1.237 brouard 7141: /* for(k=1; k <= ncovds; k++){ */
1.236 brouard 7142: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
1.238 brouard 7143: printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.236 brouard 7144: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7145: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.238 brouard 7146: }
1.264 brouard 7147: strcpy(gplotlabel+strlen(gplotlabel),")");
1.211 brouard 7148: fprintf(ficgp,"\n#\n");
1.223 brouard 7149: if(invalidvarcomb[k1]){
7150: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7151: continue;
7152: }
1.219 brouard 7153:
1.241 brouard 7154: fprintf(ficgp,"\nset out \"%s_%d-%d.svg\" \n",subdirf2(optionfilefiname,"E_"),k1,nres);
1.238 brouard 7155: for(vpopbased=0; vpopbased <= popbased; vpopbased++){ /* Done for vpopbased=0 and vpopbased=1 if popbased==1*/
1.264 brouard 7156: fprintf(ficgp,"\nset label \"popbased %d %s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",vpopbased,gplotlabel);
7157: if(vpopbased==0){
1.238 brouard 7158: fprintf(ficgp,"set ylabel \"Years\" \nset ter svg size 640, 480\nplot [%.f:%.f] ",ageminpar,fage);
1.264 brouard 7159: }else
1.238 brouard 7160: fprintf(ficgp,"\nreplot ");
7161: for (i=1; i<= nlstate+1 ; i ++) {
7162: k=2*i;
1.261 brouard 7163: 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 7164: for (j=1; j<= nlstate+1 ; j ++) {
7165: if (j==i) fprintf(ficgp," %%lf (%%lf)");
7166: else fprintf(ficgp," %%*lf (%%*lf)");
7167: }
7168: if (i== 1) fprintf(ficgp,"\" t\"TLE\" w l lt %d, \\\n",i);
7169: else fprintf(ficgp,"\" t\"LE in state (%d)\" w l lt %d, \\\n",i-1,i+1);
1.261 brouard 7170: 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 7171: for (j=1; j<= nlstate+1 ; j ++) {
7172: if (j==i) fprintf(ficgp," %%lf (%%lf)");
7173: else fprintf(ficgp," %%*lf (%%*lf)");
7174: }
7175: fprintf(ficgp,"\" t\"\" w l lt 0,");
1.261 brouard 7176: 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 7177: for (j=1; j<= nlstate+1 ; j ++) {
7178: if (j==i) fprintf(ficgp," %%lf (%%lf)");
7179: else fprintf(ficgp," %%*lf (%%*lf)");
7180: }
7181: if (i== (nlstate+1)) fprintf(ficgp,"\" t\"\" w l lt 0");
7182: else fprintf(ficgp,"\" t\"\" w l lt 0,\\\n");
7183: } /* state */
7184: } /* vpopbased */
1.264 brouard 7185: 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 7186: } /* end nres */
7187: } /* k1 end 2 eme*/
7188:
7189:
7190: /*3eme*/
7191: for (k1=1; k1<= m ; k1 ++){
7192: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 7193: if(m != 1 && TKresult[nres]!= k1)
1.238 brouard 7194: continue;
7195:
7196: for (cpt=1; cpt<= nlstate ; cpt ++) {
1.261 brouard 7197: fprintf(ficgp,"\n\n# 3d: Life expectancy with EXP_ files: combination=%d state=%d",k1, cpt);
1.264 brouard 7198: strcpy(gplotlabel,"(");
1.238 brouard 7199: for (k=1; k<=cptcoveff; k++){ /* For each covariate and each value */
7200: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate number corresponding to k1 combination */
7201: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7202: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7203: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7204: vlv= nbcode[Tvaraff[k]][lv];
7205: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 7206: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.238 brouard 7207: }
7208: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7209: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7210: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.238 brouard 7211: }
1.264 brouard 7212: strcpy(gplotlabel+strlen(gplotlabel),")");
1.238 brouard 7213: fprintf(ficgp,"\n#\n");
7214: if(invalidvarcomb[k1]){
7215: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7216: continue;
7217: }
7218:
7219: /* k=2+nlstate*(2*cpt-2); */
7220: k=2+(nlstate+1)*(cpt-1);
1.241 brouard 7221: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"EXP_"),cpt,k1,nres);
1.264 brouard 7222: fprintf(ficgp,"set label \"%s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",gplotlabel);
1.238 brouard 7223: fprintf(ficgp,"set ter svg size 640, 480\n\
1.261 brouard 7224: 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 7225: /*fprintf(ficgp,",\"e%s\" every :::%d::%d u 1:($%d-2*$%d) \"\%%lf ",fileres,k1-1,k1-1,k,k+1);
7226: for (i=1; i<= nlstate*2 ; i ++) fprintf(ficgp,"\%%lf (\%%lf) ");
7227: fprintf(ficgp,"\" t \"e%d1\" w l",cpt);
7228: fprintf(ficgp,",\"e%s\" every :::%d::%d u 1:($%d+2*$%d) \"\%%lf ",fileres,k1-1,k1-1,k,k+1);
7229: for (i=1; i<= nlstate*2 ; i ++) fprintf(ficgp,"\%%lf (\%%lf) ");
7230: fprintf(ficgp,"\" t \"e%d1\" w l",cpt);
1.219 brouard 7231:
1.238 brouard 7232: */
7233: for (i=1; i< nlstate ; i ++) {
1.261 brouard 7234: 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 7235: /* 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 7236:
1.238 brouard 7237: }
1.261 brouard 7238: 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 7239: }
1.264 brouard 7240: fprintf(ficgp,"\nunset label;\n");
1.238 brouard 7241: } /* end nres */
7242: } /* end kl 3eme */
1.126 brouard 7243:
1.223 brouard 7244: /* 4eme */
1.201 brouard 7245: /* Survival functions (period) from state i in state j by initial state i */
1.238 brouard 7246: for (k1=1; k1<=m; k1++){ /* For each covariate and each value */
7247: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 7248: if(m != 1 && TKresult[nres]!= k1)
1.223 brouard 7249: continue;
1.238 brouard 7250: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state cpt*/
1.264 brouard 7251: strcpy(gplotlabel,"(");
1.238 brouard 7252: fprintf(ficgp,"\n#\n#\n# Survival functions in state j : 'LIJ_' files, cov=%d state=%d",k1, cpt);
7253: for (k=1; k<=cptcoveff; k++){ /* For each covariate and each value */
7254: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate number corresponding to k1 combination */
7255: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7256: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7257: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7258: vlv= nbcode[Tvaraff[k]][lv];
7259: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 7260: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.238 brouard 7261: }
7262: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7263: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7264: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.238 brouard 7265: }
1.264 brouard 7266: strcpy(gplotlabel+strlen(gplotlabel),")");
1.238 brouard 7267: fprintf(ficgp,"\n#\n");
7268: if(invalidvarcomb[k1]){
7269: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7270: continue;
1.223 brouard 7271: }
1.238 brouard 7272:
1.241 brouard 7273: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"LIJ_"),cpt,k1,nres);
1.264 brouard 7274: 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 7275: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability to be alive\" \n\
7276: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
7277: k=3;
7278: for (i=1; i<= nlstate ; i ++){
7279: if(i==1){
7280: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJ_"));
7281: }else{
7282: fprintf(ficgp,", '' ");
7283: }
7284: l=(nlstate+ndeath)*(i-1)+1;
7285: fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d/($%d",k1,k+l+(cpt-1),k+l);
7286: for (j=2; j<= nlstate+ndeath ; j ++)
7287: fprintf(ficgp,"+$%d",k+l+j-1);
7288: fprintf(ficgp,")) t \"l(%d,%d)\" w l",i,cpt);
7289: } /* nlstate */
1.264 brouard 7290: fprintf(ficgp,"\nset out; unset label;\n");
1.238 brouard 7291: } /* end cpt state*/
7292: } /* end nres */
7293: } /* end covariate k1 */
7294:
1.220 brouard 7295: /* 5eme */
1.201 brouard 7296: /* Survival functions (period) from state i in state j by final state j */
1.238 brouard 7297: for (k1=1; k1<= m ; k1++){ /* For each covariate combination if any */
7298: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 7299: if(m != 1 && TKresult[nres]!= k1)
1.227 brouard 7300: continue;
1.238 brouard 7301: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each inital state */
1.264 brouard 7302: strcpy(gplotlabel,"(");
1.238 brouard 7303: 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);
7304: for (k=1; k<=cptcoveff; k++){ /* For each covariate and each value */
7305: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate number corresponding to k1 combination */
7306: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7307: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7308: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7309: vlv= nbcode[Tvaraff[k]][lv];
7310: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 7311: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.238 brouard 7312: }
7313: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7314: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7315: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.238 brouard 7316: }
1.264 brouard 7317: strcpy(gplotlabel+strlen(gplotlabel),")");
1.238 brouard 7318: fprintf(ficgp,"\n#\n");
7319: if(invalidvarcomb[k1]){
7320: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7321: continue;
7322: }
1.227 brouard 7323:
1.241 brouard 7324: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"LIJT_"),cpt,k1,nres);
1.264 brouard 7325: 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 7326: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability to be alive\" \n\
7327: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
7328: k=3;
7329: for (j=1; j<= nlstate ; j ++){ /* Lived in state j */
7330: if(j==1)
7331: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJ_"));
7332: else
7333: fprintf(ficgp,", '' ");
7334: l=(nlstate+ndeath)*(cpt-1) +j;
7335: fprintf(ficgp," u (($1==%d && (floor($2)%%5 == 0)) ? ($3):1/0):($%d",k1,k+l);
7336: /* for (i=2; i<= nlstate+ndeath ; i ++) */
7337: /* fprintf(ficgp,"+$%d",k+l+i-1); */
7338: fprintf(ficgp,") t \"l(%d,%d)\" w l",cpt,j);
7339: } /* nlstate */
7340: fprintf(ficgp,", '' ");
7341: fprintf(ficgp," u (($1==%d && (floor($2)%%5 == 0)) ? ($3):1/0):(",k1);
7342: for (j=1; j<= nlstate ; j ++){ /* Lived in state j */
7343: l=(nlstate+ndeath)*(cpt-1) +j;
7344: if(j < nlstate)
7345: fprintf(ficgp,"$%d +",k+l);
7346: else
7347: fprintf(ficgp,"$%d) t\"l(%d,.)\" w l",k+l,cpt);
7348: }
1.264 brouard 7349: fprintf(ficgp,"\nset out; unset label;\n");
1.238 brouard 7350: } /* end cpt state*/
7351: } /* end covariate */
7352: } /* end nres */
1.227 brouard 7353:
1.220 brouard 7354: /* 6eme */
1.202 brouard 7355: /* CV preval stable (period) for each covariate */
1.237 brouard 7356: for (k1=1; k1<= m ; k1 ++) /* For each covariate combination if any */
7357: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 7358: if(m != 1 && TKresult[nres]!= k1)
1.237 brouard 7359: continue;
1.255 brouard 7360: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state of arrival */
1.264 brouard 7361: strcpy(gplotlabel,"(");
1.211 brouard 7362: fprintf(ficgp,"\n#\n#\n#CV preval stable (period): 'pij' files, covariatecombination#=%d state=%d",k1, cpt);
1.225 brouard 7363: for (k=1; k<=cptcoveff; k++){ /* For each covariate and each value */
1.227 brouard 7364: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate number corresponding to k1 combination */
7365: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7366: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7367: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7368: vlv= nbcode[Tvaraff[k]][lv];
7369: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 7370: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.211 brouard 7371: }
1.237 brouard 7372: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7373: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7374: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.237 brouard 7375: }
1.264 brouard 7376: strcpy(gplotlabel+strlen(gplotlabel),")");
1.211 brouard 7377: fprintf(ficgp,"\n#\n");
1.223 brouard 7378: if(invalidvarcomb[k1]){
1.227 brouard 7379: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7380: continue;
1.223 brouard 7381: }
1.227 brouard 7382:
1.241 brouard 7383: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"P_"),cpt,k1,nres);
1.264 brouard 7384: 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 7385: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability\" \n\
1.238 brouard 7386: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
1.211 brouard 7387: k=3; /* Offset */
1.255 brouard 7388: for (i=1; i<= nlstate ; i ++){ /* State of origin */
1.227 brouard 7389: if(i==1)
7390: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJ_"));
7391: else
7392: fprintf(ficgp,", '' ");
1.255 brouard 7393: l=(nlstate+ndeath)*(i-1)+1; /* 1, 1+ nlstate+ndeath, 1+2*(nlstate+ndeath) */
1.227 brouard 7394: fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d/($%d",k1,k+l+(cpt-1),k+l);
7395: for (j=2; j<= nlstate ; j ++)
7396: fprintf(ficgp,"+$%d",k+l+j-1);
7397: fprintf(ficgp,")) t \"prev(%d,%d)\" w l",i,cpt);
1.153 brouard 7398: } /* nlstate */
1.264 brouard 7399: fprintf(ficgp,"\nset out; unset label;\n");
1.153 brouard 7400: } /* end cpt state*/
7401: } /* end covariate */
1.227 brouard 7402:
7403:
1.220 brouard 7404: /* 7eme */
1.218 brouard 7405: if(backcast == 1){
1.217 brouard 7406: /* CV back preval stable (period) for each covariate */
1.237 brouard 7407: for (k1=1; k1<= m ; k1 ++) /* For each covariate combination if any */
7408: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 7409: if(m != 1 && TKresult[nres]!= k1)
1.237 brouard 7410: continue;
1.268 brouard 7411: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life origin state */
1.264 brouard 7412: strcpy(gplotlabel,"(");
7413: fprintf(ficgp,"\n#\n#\n#CV Back preval stable (period): 'pijb' files, covariatecombination#=%d state=%d",k1, cpt);
1.227 brouard 7414: for (k=1; k<=cptcoveff; k++){ /* For each covariate and each value */
7415: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate number corresponding to k1 combination */
7416: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7417: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
1.223 brouard 7418: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
1.227 brouard 7419: vlv= nbcode[Tvaraff[k]][lv];
7420: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 7421: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.227 brouard 7422: }
1.237 brouard 7423: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7424: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7425: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.237 brouard 7426: }
1.264 brouard 7427: strcpy(gplotlabel+strlen(gplotlabel),")");
1.227 brouard 7428: fprintf(ficgp,"\n#\n");
7429: if(invalidvarcomb[k1]){
7430: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7431: continue;
7432: }
7433:
1.241 brouard 7434: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"PB_"),cpt,k1,nres);
1.268 brouard 7435: 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 7436: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability\" \n\
1.238 brouard 7437: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
1.227 brouard 7438: k=3; /* Offset */
1.268 brouard 7439: for (i=1; i<= nlstate ; i ++){ /* State of arrival */
1.227 brouard 7440: if(i==1)
7441: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJB_"));
7442: else
7443: fprintf(ficgp,", '' ");
7444: /* l=(nlstate+ndeath)*(i-1)+1; */
1.255 brouard 7445: l=(nlstate+ndeath)*(cpt-1)+1; /* fixed for i; cpt=1 1, cpt=2 1+ nlstate+ndeath, 1+2*(nlstate+ndeath) */
1.227 brouard 7446: /* fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d/($%d",k1,k+l+(cpt-1),k+l); /\* a vérifier *\/ */
7447: /* 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 7448: fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d",k1,k+l+i-1); /* To be verified */
1.227 brouard 7449: /* for (j=2; j<= nlstate ; j ++) */
7450: /* fprintf(ficgp,"+$%d",k+l+j-1); */
7451: /* /\* fprintf(ficgp,"+$%d",k+l+j-1); *\/ */
1.268 brouard 7452: fprintf(ficgp,") t \"bprev(%d,%d)\" w l",cpt,i);
1.227 brouard 7453: } /* nlstate */
1.264 brouard 7454: fprintf(ficgp,"\nset out; unset label;\n");
1.218 brouard 7455: } /* end cpt state*/
7456: } /* end covariate */
7457: } /* End if backcast */
7458:
1.223 brouard 7459: /* 8eme */
1.218 brouard 7460: if(prevfcast==1){
7461: /* Projection from cross-sectional to stable (period) for each covariate */
7462:
1.237 brouard 7463: for (k1=1; k1<= m ; k1 ++) /* For each covariate combination if any */
7464: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 7465: if(m != 1 && TKresult[nres]!= k1)
1.237 brouard 7466: continue;
1.211 brouard 7467: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state */
1.264 brouard 7468: strcpy(gplotlabel,"(");
1.227 brouard 7469: fprintf(ficgp,"\n#\n#\n#Projection of prevalence to stable (period): 'PROJ_' files, covariatecombination#=%d state=%d",k1, cpt);
7470: for (k=1; k<=cptcoveff; k++){ /* For each correspondig covariate value */
7471: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate value corresponding to k1 combination and kth covariate */
7472: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7473: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7474: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7475: vlv= nbcode[Tvaraff[k]][lv];
7476: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 7477: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.227 brouard 7478: }
1.237 brouard 7479: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7480: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7481: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.237 brouard 7482: }
1.264 brouard 7483: strcpy(gplotlabel+strlen(gplotlabel),")");
1.227 brouard 7484: fprintf(ficgp,"\n#\n");
7485: if(invalidvarcomb[k1]){
7486: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7487: continue;
7488: }
7489:
7490: fprintf(ficgp,"# hpijx=probability over h years, hp.jx is weighted by observed prev\n ");
1.241 brouard 7491: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"PROJ_"),cpt,k1,nres);
1.264 brouard 7492: 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 7493: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Prevalence\" \n\
1.238 brouard 7494: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
1.266 brouard 7495:
7496: /* for (i=1; i<= nlstate+1 ; i ++){ /\* nlstate +1 p11 p21 p.1 *\/ */
7497: istart=nlstate+1; /* Could be one if by state, but nlstate+1 is w.i projection only */
7498: /*istart=1;*/ /* Could be one if by state, but nlstate+1 is w.i projection only */
7499: for (i=istart; i<= nlstate+1 ; i ++){ /* nlstate +1 p11 p21 p.1 */
1.227 brouard 7500: /*# V1 = 1 V2 = 0 yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
7501: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
7502: /*# yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
7503: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
1.266 brouard 7504: if(i==istart){
1.227 brouard 7505: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"F_"));
7506: }else{
7507: fprintf(ficgp,",\\\n '' ");
7508: }
7509: if(cptcoveff ==0){ /* No covariate */
7510: ioffset=2; /* Age is in 2 */
7511: /*# yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/
7512: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */
7513: /*# V1 = 1 yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/
7514: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */
7515: fprintf(ficgp," u %d:(", ioffset);
1.266 brouard 7516: if(i==nlstate+1){
1.270 brouard 7517: fprintf(ficgp," $%d/(1.-$%d)):1 t 'pw.%d' with line lc variable ", \
1.266 brouard 7518: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,cpt );
7519: fprintf(ficgp,",\\\n '' ");
7520: fprintf(ficgp," u %d:(",ioffset);
1.270 brouard 7521: fprintf(ficgp," (($1-$2) == %d ) ? $%d/(1.-$%d) : 1/0):1 with labels center not ", \
1.266 brouard 7522: offyear, \
1.268 brouard 7523: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate );
1.266 brouard 7524: }else
1.227 brouard 7525: fprintf(ficgp," $%d/(1.-$%d)) t 'p%d%d' with line ", \
7526: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,i,cpt );
7527: }else{ /* more than 2 covariates */
1.270 brouard 7528: ioffset=2*cptcoveff+2; /* Age is in 4 or 6 or etc.*/
7529: /*# V1 = 1 V2 = 0 yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
7530: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
7531: iyearc=ioffset-1;
7532: iagec=ioffset;
1.227 brouard 7533: fprintf(ficgp," u %d:(",ioffset);
7534: kl=0;
7535: strcpy(gplotcondition,"(");
7536: for (k=1; k<=cptcoveff; k++){ /* For each covariate writing the chain of conditions */
7537: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate value corresponding to combination k1 and covariate k */
7538: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7539: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7540: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7541: vlv= nbcode[Tvaraff[k]][lv]; /* Value of the modality of Tvaraff[k] */
7542: kl++;
7543: sprintf(gplotcondition+strlen(gplotcondition),"$%d==%d && $%d==%d " ,kl,Tvaraff[k], kl+1, nbcode[Tvaraff[k]][lv]);
7544: kl++;
7545: if(k <cptcoveff && cptcoveff>1)
7546: sprintf(gplotcondition+strlen(gplotcondition)," && ");
7547: }
7548: strcpy(gplotcondition+strlen(gplotcondition),")");
7549: /* 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 *\/ */
7550: /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */
7551: /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */
7552: /* '' 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*/
7553: if(i==nlstate+1){
1.270 brouard 7554: fprintf(ficgp,"%s ? $%d/(1.-$%d) : 1/0):%d t 'p.%d' with line lc variable", gplotcondition, \
7555: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,iyearc, cpt );
1.266 brouard 7556: fprintf(ficgp,",\\\n '' ");
1.270 brouard 7557: fprintf(ficgp," u %d:(",iagec);
7558: fprintf(ficgp,"%s && (($%d-$%d) == %d ) ? $%d/(1.-$%d) : 1/0):%d with labels center not ", gplotcondition, \
7559: iyearc, iagec, offyear, \
7560: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate, iyearc );
1.266 brouard 7561: /* '' 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 7562: }else{
7563: fprintf(ficgp,"%s ? $%d/(1.-$%d) : 1/0) t 'p%d%d' with line ", gplotcondition, \
7564: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset +1+(i-1)+(nlstate+1)*nlstate,i,cpt );
7565: }
7566: } /* end if covariate */
7567: } /* nlstate */
1.264 brouard 7568: fprintf(ficgp,"\nset out; unset label;\n");
1.223 brouard 7569: } /* end cpt state*/
7570: } /* end covariate */
7571: } /* End if prevfcast */
1.227 brouard 7572:
1.268 brouard 7573: if(backcast==1){
7574: /* Back projection from cross-sectional to stable (mixed) for each covariate */
7575:
7576: for (k1=1; k1<= m ; k1 ++) /* For each covariate combination if any */
7577: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
7578: if(m != 1 && TKresult[nres]!= k1)
7579: continue;
7580: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state */
7581: strcpy(gplotlabel,"(");
7582: fprintf(ficgp,"\n#\n#\n#Back projection of prevalence to stable (mixed) back prevalence: 'BPROJ_' files, covariatecombination#=%d originstate=%d",k1, cpt);
7583: for (k=1; k<=cptcoveff; k++){ /* For each correspondig covariate value */
7584: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate value corresponding to k1 combination and kth covariate */
7585: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7586: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7587: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7588: vlv= nbcode[Tvaraff[k]][lv];
7589: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
7590: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
7591: }
7592: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7593: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
7594: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
7595: }
7596: strcpy(gplotlabel+strlen(gplotlabel),")");
7597: fprintf(ficgp,"\n#\n");
7598: if(invalidvarcomb[k1]){
7599: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7600: continue;
7601: }
7602:
7603: fprintf(ficgp,"# hbijx=backprobability over h years, hb.jx is weighted by observed prev at destination state\n ");
7604: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"PROJB_"),cpt,k1,nres);
7605: fprintf(ficgp,"set label \"Origin alive state %d %s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",cpt,gplotlabel);
7606: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Prevalence\" \n\
7607: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
7608:
7609: /* for (i=1; i<= nlstate+1 ; i ++){ /\* nlstate +1 p11 p21 p.1 *\/ */
7610: istart=nlstate+1; /* Could be one if by state, but nlstate+1 is w.i projection only */
7611: /*istart=1;*/ /* Could be one if by state, but nlstate+1 is w.i projection only */
7612: for (i=istart; i<= nlstate+1 ; i ++){ /* nlstate +1 p11 p21 p.1 */
7613: /*# V1 = 1 V2 = 0 yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
7614: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
7615: /*# yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
7616: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
7617: if(i==istart){
7618: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"FB_"));
7619: }else{
7620: fprintf(ficgp,",\\\n '' ");
7621: }
7622: if(cptcoveff ==0){ /* No covariate */
7623: ioffset=2; /* Age is in 2 */
7624: /*# yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/
7625: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */
7626: /*# V1 = 1 yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/
7627: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */
7628: fprintf(ficgp," u %d:(", ioffset);
7629: if(i==nlstate+1){
1.270 brouard 7630: fprintf(ficgp," $%d/(1.-$%d)):1 t 'bw%d' with line lc variable ", \
1.268 brouard 7631: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,cpt );
7632: fprintf(ficgp,",\\\n '' ");
7633: fprintf(ficgp," u %d:(",ioffset);
1.270 brouard 7634: fprintf(ficgp," (($1-$2) == %d ) ? $%d : 1/0):1 with labels center not ", \
1.268 brouard 7635: offbyear, \
7636: ioffset+(cpt-1)*(nlstate+1)+1+(i-1) );
7637: }else
7638: fprintf(ficgp," $%d/(1.-$%d)) t 'b%d%d' with line ", \
7639: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,cpt,i );
7640: }else{ /* more than 2 covariates */
1.270 brouard 7641: ioffset=2*cptcoveff+2; /* Age is in 4 or 6 or etc.*/
7642: /*# V1 = 1 V2 = 0 yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
7643: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
7644: iyearc=ioffset-1;
7645: iagec=ioffset;
1.268 brouard 7646: fprintf(ficgp," u %d:(",ioffset);
7647: kl=0;
7648: strcpy(gplotcondition,"(");
7649: for (k=1; k<=cptcoveff; k++){ /* For each covariate writing the chain of conditions */
7650: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate value corresponding to combination k1 and covariate k */
7651: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7652: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7653: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7654: vlv= nbcode[Tvaraff[k]][lv]; /* Value of the modality of Tvaraff[k] */
7655: kl++;
7656: sprintf(gplotcondition+strlen(gplotcondition),"$%d==%d && $%d==%d " ,kl,Tvaraff[k], kl+1, nbcode[Tvaraff[k]][lv]);
7657: kl++;
7658: if(k <cptcoveff && cptcoveff>1)
7659: sprintf(gplotcondition+strlen(gplotcondition)," && ");
7660: }
7661: strcpy(gplotcondition+strlen(gplotcondition),")");
7662: /* 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 *\/ */
7663: /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */
7664: /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */
7665: /* '' 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*/
7666: if(i==nlstate+1){
1.270 brouard 7667: fprintf(ficgp,"%s ? $%d : 1/0):%d t 'bw%d' with line lc variable", gplotcondition, \
7668: ioffset+(cpt-1)*(nlstate+1)+1+(i-1),iyearc,cpt );
1.268 brouard 7669: fprintf(ficgp,",\\\n '' ");
1.270 brouard 7670: fprintf(ficgp," u %d:(",iagec);
1.268 brouard 7671: /* fprintf(ficgp,"%s && (($5-$6) == %d ) ? $%d/(1.-$%d) : 1/0):5 with labels center not ", gplotcondition, \ */
1.270 brouard 7672: fprintf(ficgp,"%s && (($%d-$%d) == %d ) ? $%d : 1/0):%d with labels center not ", gplotcondition, \
7673: iyearc,iagec,offbyear, \
7674: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), iyearc );
1.268 brouard 7675: /* '' u 6:(($1==1 && $2==0 && $3==2 && $4==0) && (($5-$6) == 1947) ? $10/(1.-$22) : 1/0):5 with labels center boxed not*/
7676: }else{
7677: /* fprintf(ficgp,"%s ? $%d/(1.-$%d) : 1/0) t 'p%d%d' with line ", gplotcondition, \ */
7678: fprintf(ficgp,"%s ? $%d : 1/0) t 'b%d%d' with line ", gplotcondition, \
7679: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), cpt,i );
7680: }
7681: } /* end if covariate */
7682: } /* nlstate */
7683: fprintf(ficgp,"\nset out; unset label;\n");
7684: } /* end cpt state*/
7685: } /* end covariate */
7686: } /* End if backcast */
7687:
1.227 brouard 7688:
1.238 brouard 7689: /* 9eme writing MLE parameters */
7690: fprintf(ficgp,"\n##############\n#9eme MLE estimated parameters\n#############\n");
1.126 brouard 7691: for(i=1,jk=1; i <=nlstate; i++){
1.187 brouard 7692: fprintf(ficgp,"# initial state %d\n",i);
1.126 brouard 7693: for(k=1; k <=(nlstate+ndeath); k++){
7694: if (k != i) {
1.227 brouard 7695: fprintf(ficgp,"# current state %d\n",k);
7696: for(j=1; j <=ncovmodel; j++){
7697: fprintf(ficgp,"p%d=%f; ",jk,p[jk]);
7698: jk++;
7699: }
7700: fprintf(ficgp,"\n");
1.126 brouard 7701: }
7702: }
1.223 brouard 7703: }
1.187 brouard 7704: fprintf(ficgp,"##############\n#\n");
1.227 brouard 7705:
1.145 brouard 7706: /*goto avoid;*/
1.238 brouard 7707: /* 10eme Graphics of probabilities or incidences using written MLE parameters */
7708: fprintf(ficgp,"\n##############\n#10eme Graphics of probabilities or incidences\n#############\n");
1.187 brouard 7709: fprintf(ficgp,"# logi(p12/p11)=a12+b12*age+c12age*age+d12*V1+e12*V1*age\n");
7710: fprintf(ficgp,"# logi(p12/p11)=p1 +p2*age +p3*age*age+ p4*V1+ p5*V1*age\n");
7711: fprintf(ficgp,"# logi(p13/p11)=a13+b13*age+c13age*age+d13*V1+e13*V1*age\n");
7712: fprintf(ficgp,"# logi(p13/p11)=p6 +p7*age +p8*age*age+ p9*V1+ p10*V1*age\n");
7713: fprintf(ficgp,"# p12+p13+p14+p11=1=p11(1+exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)\n");
7714: fprintf(ficgp,"# +exp(a13+b13*age+c13age*age+d13*V1+e13*V1*age)+...)\n");
7715: fprintf(ficgp,"# p11=1/(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,"# p12=exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)/\n");
7718: fprintf(ficgp,"# (1+exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)\n");
7719: fprintf(ficgp,"# +exp(a13+b13*age+c13age*age+d13*V1+e13*V1*age))\n");
7720: fprintf(ficgp,"# +exp(a14+b14*age+c14age*age+d14*V1+e14*V1*age)+...)\n");
7721: fprintf(ficgp,"#\n");
1.223 brouard 7722: for(ng=1; ng<=3;ng++){ /* Number of graphics: first is logit, 2nd is probabilities, third is incidences per year*/
1.238 brouard 7723: fprintf(ficgp,"#Number of graphics: first is logit, 2nd is probabilities, third is incidences per year\n");
1.237 brouard 7724: fprintf(ficgp,"#model=%s \n",model);
1.238 brouard 7725: fprintf(ficgp,"# Type of graphic ng=%d\n",ng);
1.264 brouard 7726: fprintf(ficgp,"# k1=1 to 2^%d=%d\n",cptcoveff,m);/* to be checked */
7727: for(k1=1; k1 <=m; k1++) /* For each combination of covariate */
1.237 brouard 7728: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.264 brouard 7729: if(m != 1 && TKresult[nres]!= k1)
1.237 brouard 7730: continue;
1.264 brouard 7731: fprintf(ficgp,"\n\n# Combination of dummy k1=%d which is ",k1);
7732: strcpy(gplotlabel,"(");
7733: sprintf(gplotlabel+strlen(gplotlabel)," Dummy combination %d ",k1);
7734: for (k=1; k<=cptcoveff; k++){ /* For each correspondig covariate value */
7735: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate value corresponding to k1 combination and kth covariate */
7736: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7737: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7738: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7739: vlv= nbcode[Tvaraff[k]][lv];
7740: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
7741: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
7742: }
1.237 brouard 7743: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7744: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7745: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.237 brouard 7746: }
1.264 brouard 7747: strcpy(gplotlabel+strlen(gplotlabel),")");
1.237 brouard 7748: fprintf(ficgp,"\n#\n");
1.264 brouard 7749: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" ",subdirf2(optionfilefiname,"PE_"),k1,ng,nres);
7750: fprintf(ficgp,"\nset label \"%s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",gplotlabel);
1.223 brouard 7751: fprintf(ficgp,"\nset ter svg size 640, 480 ");
7752: if (ng==1){
7753: fprintf(ficgp,"\nset ylabel \"Value of the logit of the model\"\n"); /* exp(a12+b12*x) could be nice */
7754: fprintf(ficgp,"\nunset log y");
7755: }else if (ng==2){
7756: fprintf(ficgp,"\nset ylabel \"Probability\"\n");
7757: fprintf(ficgp,"\nset log y");
7758: }else if (ng==3){
7759: fprintf(ficgp,"\nset ylabel \"Quasi-incidence per year\"\n");
7760: fprintf(ficgp,"\nset log y");
7761: }else
7762: fprintf(ficgp,"\nunset title ");
7763: fprintf(ficgp,"\nplot [%.f:%.f] ",ageminpar,agemaxpar);
7764: i=1;
7765: for(k2=1; k2<=nlstate; k2++) {
7766: k3=i;
7767: for(k=1; k<=(nlstate+ndeath); k++) {
7768: if (k != k2){
7769: switch( ng) {
7770: case 1:
7771: if(nagesqr==0)
7772: fprintf(ficgp," p%d+p%d*x",i,i+1);
7773: else /* nagesqr =1 */
7774: fprintf(ficgp," p%d+p%d*x+p%d*x*x",i,i+1,i+1+nagesqr);
7775: break;
7776: case 2: /* ng=2 */
7777: if(nagesqr==0)
7778: fprintf(ficgp," exp(p%d+p%d*x",i,i+1);
7779: else /* nagesqr =1 */
7780: fprintf(ficgp," exp(p%d+p%d*x+p%d*x*x",i,i+1,i+1+nagesqr);
7781: break;
7782: case 3:
7783: if(nagesqr==0)
7784: fprintf(ficgp," %f*exp(p%d+p%d*x",YEARM/stepm,i,i+1);
7785: else /* nagesqr =1 */
7786: fprintf(ficgp," %f*exp(p%d+p%d*x+p%d*x*x",YEARM/stepm,i,i+1,i+1+nagesqr);
7787: break;
7788: }
7789: ij=1;/* To be checked else nbcode[0][0] wrong */
1.237 brouard 7790: ijp=1; /* product no age */
7791: /* for(j=3; j <=ncovmodel-nagesqr; j++) { */
7792: for(j=1; j <=cptcovt; j++) { /* For each covariate of the simplified model */
1.223 brouard 7793: /* printf("Tage[%d]=%d, j=%d\n", ij, Tage[ij], j); */
1.268 brouard 7794: if(cptcovage >0){ /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, 2 V5 and V1 */
7795: if(j==Tage[ij]) { /* Product by age To be looked at!!*/
7796: if(ij <=cptcovage) { /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, 2 V5 and V1 */
7797: if(DummyV[j]==0){
7798: fprintf(ficgp,"+p%d*%d*x",i+j+2+nagesqr-1,Tinvresult[nres][Tvar[j]]);;
7799: }else{ /* quantitative */
7800: fprintf(ficgp,"+p%d*%f*x",i+j+2+nagesqr-1,Tqinvresult[nres][Tvar[j]]); /* Tqinvresult in decoderesult */
7801: /* fprintf(ficgp,"+p%d*%d*x",i+j+nagesqr-1,nbcode[Tvar[j-2]][codtabm(k1,Tvar[j-2])]); */
7802: }
7803: ij++;
1.237 brouard 7804: }
1.268 brouard 7805: }
7806: }else if(cptcovprod >0){
7807: if(j==Tprod[ijp]) { /* */
7808: /* printf("Tprod[%d]=%d, j=%d\n", ij, Tprod[ijp], j); */
7809: if(ijp <=cptcovprod) { /* Product */
7810: if(DummyV[Tvard[ijp][1]]==0){/* Vn is dummy */
7811: if(DummyV[Tvard[ijp][2]]==0){/* Vn and Vm are dummy */
7812: /* 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)]); */
7813: fprintf(ficgp,"+p%d*%d*%d",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tinvresult[nres][Tvard[ijp][2]]);
7814: }else{ /* Vn is dummy and Vm is quanti */
7815: /* fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,nbcode[Tvard[ijp][1]][codtabm(k1,j)],Tqinvresult[nres][Tvard[ijp][2]]); */
7816: fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]);
7817: }
7818: }else{ /* Vn*Vm Vn is quanti */
7819: if(DummyV[Tvard[ijp][2]]==0){
7820: fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][2]],Tqinvresult[nres][Tvard[ijp][1]]);
7821: }else{ /* Both quanti */
7822: fprintf(ficgp,"+p%d*%f*%f",i+j+2+nagesqr-1,Tqinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]);
7823: }
1.237 brouard 7824: }
1.268 brouard 7825: ijp++;
1.237 brouard 7826: }
1.268 brouard 7827: } /* end Tprod */
1.237 brouard 7828: } else{ /* simple covariate */
1.264 brouard 7829: /* fprintf(ficgp,"+p%d*%d",i+j+2+nagesqr-1,nbcode[Tvar[j]][codtabm(k1,j)]); /\* Valgrind bug nbcode *\/ */
1.237 brouard 7830: if(Dummy[j]==0){
7831: fprintf(ficgp,"+p%d*%d",i+j+2+nagesqr-1,Tinvresult[nres][Tvar[j]]); /* */
7832: }else{ /* quantitative */
7833: fprintf(ficgp,"+p%d*%f",i+j+2+nagesqr-1,Tqinvresult[nres][Tvar[j]]); /* */
1.264 brouard 7834: /* fprintf(ficgp,"+p%d*%d*x",i+j+nagesqr-1,nbcode[Tvar[j-2]][codtabm(k1,Tvar[j-2])]); */
1.223 brouard 7835: }
1.237 brouard 7836: } /* end simple */
7837: } /* end j */
1.223 brouard 7838: }else{
7839: i=i-ncovmodel;
7840: if(ng !=1 ) /* For logit formula of log p11 is more difficult to get */
7841: fprintf(ficgp," (1.");
7842: }
1.227 brouard 7843:
1.223 brouard 7844: if(ng != 1){
7845: fprintf(ficgp,")/(1");
1.227 brouard 7846:
1.264 brouard 7847: for(cpt=1; cpt <=nlstate; cpt++){
1.223 brouard 7848: if(nagesqr==0)
1.264 brouard 7849: fprintf(ficgp,"+exp(p%d+p%d*x",k3+(cpt-1)*ncovmodel,k3+(cpt-1)*ncovmodel+1);
1.223 brouard 7850: else /* nagesqr =1 */
1.264 brouard 7851: 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 7852:
1.223 brouard 7853: ij=1;
7854: for(j=3; j <=ncovmodel-nagesqr; j++){
1.268 brouard 7855: if(cptcovage >0){
7856: if((j-2)==Tage[ij]) { /* Bug valgrind */
7857: if(ij <=cptcovage) { /* Bug valgrind */
7858: fprintf(ficgp,"+p%d*%d*x",k3+(cpt-1)*ncovmodel+1+j-2+nagesqr,nbcode[Tvar[j-2]][codtabm(k1,j-2)]);
7859: /* fprintf(ficgp,"+p%d*%d*x",k3+(cpt-1)*ncovmodel+1+j-2+nagesqr,nbcode[Tvar[j-2]][codtabm(k1,Tvar[j-2])]); */
7860: ij++;
7861: }
7862: }
7863: }else
7864: 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 7865: }
7866: fprintf(ficgp,")");
7867: }
7868: fprintf(ficgp,")");
7869: if(ng ==2)
7870: fprintf(ficgp," t \"p%d%d\" ", k2,k);
7871: else /* ng= 3 */
7872: fprintf(ficgp," t \"i%d%d\" ", k2,k);
7873: }else{ /* end ng <> 1 */
7874: if( k !=k2) /* logit p11 is hard to draw */
7875: fprintf(ficgp," t \"logit(p%d%d)\" ", k2,k);
7876: }
7877: if ((k+k2)!= (nlstate*2+ndeath) && ng != 1)
7878: fprintf(ficgp,",");
7879: if (ng == 1 && k!=k2 && (k+k2)!= (nlstate*2+ndeath))
7880: fprintf(ficgp,",");
7881: i=i+ncovmodel;
7882: } /* end k */
7883: } /* end k2 */
1.264 brouard 7884: fprintf(ficgp,"\n set out; unset label;\n");
7885: } /* end k1 */
1.223 brouard 7886: } /* end ng */
7887: /* avoid: */
7888: fflush(ficgp);
1.126 brouard 7889: } /* end gnuplot */
7890:
7891:
7892: /*************** Moving average **************/
1.219 brouard 7893: /* int movingaverage(double ***probs, double bage, double fage, double ***mobaverage, int mobilav, double bageout, double fageout){ */
1.222 brouard 7894: int movingaverage(double ***probs, double bage, double fage, double ***mobaverage, int mobilav){
1.218 brouard 7895:
1.222 brouard 7896: int i, cpt, cptcod;
7897: int modcovmax =1;
7898: int mobilavrange, mob;
7899: int iage=0;
7900:
1.266 brouard 7901: double sum=0., sumr=0.;
1.222 brouard 7902: double age;
1.266 brouard 7903: double *sumnewp, *sumnewm, *sumnewmr;
7904: double *agemingood, *agemaxgood;
7905: double *agemingoodr, *agemaxgoodr;
1.222 brouard 7906:
7907:
1.225 brouard 7908: /* modcovmax=2*cptcoveff;/\* Max number of modalities. We suppose */
1.222 brouard 7909: /* a covariate has 2 modalities, should be equal to ncovcombmax *\/ */
7910:
7911: sumnewp = vector(1,ncovcombmax);
7912: sumnewm = vector(1,ncovcombmax);
1.266 brouard 7913: sumnewmr = vector(1,ncovcombmax);
1.222 brouard 7914: agemingood = vector(1,ncovcombmax);
1.266 brouard 7915: agemingoodr = vector(1,ncovcombmax);
1.222 brouard 7916: agemaxgood = vector(1,ncovcombmax);
1.266 brouard 7917: agemaxgoodr = vector(1,ncovcombmax);
1.222 brouard 7918:
7919: for (cptcod=1;cptcod<=ncovcombmax;cptcod++){
1.266 brouard 7920: sumnewm[cptcod]=0.; sumnewmr[cptcod]=0.;
1.222 brouard 7921: sumnewp[cptcod]=0.;
1.266 brouard 7922: agemingood[cptcod]=0, agemingoodr[cptcod]=0;
7923: agemaxgood[cptcod]=0, agemaxgoodr[cptcod]=0;
1.222 brouard 7924: }
7925: if (cptcovn<1) ncovcombmax=1; /* At least 1 pass */
7926:
1.266 brouard 7927: if(mobilav==-1 || mobilav==1||mobilav ==3 ||mobilav==5 ||mobilav== 7){
7928: if(mobilav==1 || mobilav==-1) mobilavrange=5; /* default */
1.222 brouard 7929: else mobilavrange=mobilav;
7930: for (age=bage; age<=fage; age++)
7931: for (i=1; i<=nlstate;i++)
7932: for (cptcod=1;cptcod<=ncovcombmax;cptcod++)
7933: mobaverage[(int)age][i][cptcod]=probs[(int)age][i][cptcod];
7934: /* We keep the original values on the extreme ages bage, fage and for
7935: fage+1 and bage-1 we use a 3 terms moving average; for fage+2 bage+2
7936: we use a 5 terms etc. until the borders are no more concerned.
7937: */
7938: for (mob=3;mob <=mobilavrange;mob=mob+2){
7939: for (age=bage+(mob-1)/2; age<=fage-(mob-1)/2; age++){
1.266 brouard 7940: for (cptcod=1;cptcod<=ncovcombmax;cptcod++){
7941: sumnewm[cptcod]=0.;
7942: for (i=1; i<=nlstate;i++){
1.222 brouard 7943: mobaverage[(int)age][i][cptcod] =probs[(int)age][i][cptcod];
7944: for (cpt=1;cpt<=(mob-1)/2;cpt++){
7945: mobaverage[(int)age][i][cptcod] +=probs[(int)age-cpt][i][cptcod];
7946: mobaverage[(int)age][i][cptcod] +=probs[(int)age+cpt][i][cptcod];
7947: }
7948: mobaverage[(int)age][i][cptcod]=mobaverage[(int)age][i][cptcod]/mob;
1.266 brouard 7949: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
7950: } /* end i */
7951: if(sumnewm[cptcod] >1.e-3) mobaverage[(int)age][i][cptcod]=mobaverage[(int)age][i][cptcod]/sumnewm[cptcod]; /* Rescaling to sum one */
7952: } /* end cptcod */
1.222 brouard 7953: }/* end age */
7954: }/* end mob */
1.266 brouard 7955: }else{
7956: printf("Error internal in movingaverage, mobilav=%d.\n",mobilav);
1.222 brouard 7957: return -1;
1.266 brouard 7958: }
7959:
7960: for (cptcod=1;cptcod<=ncovcombmax;cptcod++){ /* for each combination */
1.222 brouard 7961: /* for (age=bage+(mob-1)/2; age<=fage-(mob-1)/2; age++){ */
7962: if(invalidvarcomb[cptcod]){
7963: printf("\nCombination (%d) ignored because no cases \n",cptcod);
7964: continue;
7965: }
1.219 brouard 7966:
1.266 brouard 7967: for (age=fage-(mob-1)/2; age>=bage+(mob-1)/2; age--){ /*looking for the youngest and oldest good age */
7968: sumnewm[cptcod]=0.;
7969: sumnewmr[cptcod]=0.;
7970: for (i=1; i<=nlstate;i++){
7971: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
7972: sumnewmr[cptcod]+=probs[(int)age][i][cptcod];
7973: }
7974: if(fabs(sumnewmr[cptcod] - 1.) <= 1.e-3) { /* good without smoothing */
7975: agemingoodr[cptcod]=age;
7976: }
7977: if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
7978: agemingood[cptcod]=age;
7979: }
7980: } /* age */
7981: for (age=bage+(mob-1)/2; age<=fage-(mob-1)/2; age++){ /*looking for the youngest and oldest good age */
1.222 brouard 7982: sumnewm[cptcod]=0.;
1.266 brouard 7983: sumnewmr[cptcod]=0.;
1.222 brouard 7984: for (i=1; i<=nlstate;i++){
7985: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
1.266 brouard 7986: sumnewmr[cptcod]+=probs[(int)age][i][cptcod];
7987: }
7988: if(fabs(sumnewmr[cptcod] - 1.) <= 1.e-3) { /* good without smoothing */
7989: agemaxgoodr[cptcod]=age;
1.222 brouard 7990: }
7991: if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
1.266 brouard 7992: agemaxgood[cptcod]=age;
7993: }
7994: } /* age */
7995: /* Thus we have agemingood and agemaxgood as well as goodr for raw (preobs) */
7996: /* but they will change */
7997: for (age=fage-(mob-1)/2; age>=bage; age--){/* From oldest to youngest, filling up to the youngest */
7998: sumnewm[cptcod]=0.;
7999: sumnewmr[cptcod]=0.;
8000: for (i=1; i<=nlstate;i++){
8001: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
8002: sumnewmr[cptcod]+=probs[(int)age][i][cptcod];
8003: }
8004: if(mobilav==-1){ /* Forcing raw ages if good else agemingood */
8005: if(fabs(sumnewmr[cptcod] - 1.) <= 1.e-3) { /* good without smoothing */
8006: agemaxgoodr[cptcod]=age; /* age min */
8007: for (i=1; i<=nlstate;i++)
8008: mobaverage[(int)age][i][cptcod]=probs[(int)age][i][cptcod];
8009: }else{ /* bad we change the value with the values of good ages */
8010: for (i=1; i<=nlstate;i++){
8011: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemaxgoodr[cptcod]][i][cptcod];
8012: } /* i */
8013: } /* end bad */
8014: }else{
8015: if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
8016: agemaxgood[cptcod]=age;
8017: }else{ /* bad we change the value with the values of good ages */
8018: for (i=1; i<=nlstate;i++){
8019: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemaxgood[cptcod]][i][cptcod];
8020: } /* i */
8021: } /* end bad */
8022: }/* end else */
8023: sum=0.;sumr=0.;
8024: for (i=1; i<=nlstate;i++){
8025: sum+=mobaverage[(int)age][i][cptcod];
8026: sumr+=probs[(int)age][i][cptcod];
8027: }
8028: if(fabs(sum - 1.) > 1.e-3) { /* bad */
1.268 brouard 8029: 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 8030: } /* end bad */
8031: /* else{ /\* We found some ages summing to one, we will smooth the oldest *\/ */
8032: if(fabs(sumr - 1.) > 1.e-3) { /* bad */
1.268 brouard 8033: 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 8034: } /* end bad */
8035: }/* age */
1.266 brouard 8036:
8037: for (age=bage+(mob-1)/2; age<=fage; age++){/* From youngest, finding the oldest wrong */
1.222 brouard 8038: sumnewm[cptcod]=0.;
1.266 brouard 8039: sumnewmr[cptcod]=0.;
1.222 brouard 8040: for (i=1; i<=nlstate;i++){
8041: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
1.266 brouard 8042: sumnewmr[cptcod]+=probs[(int)age][i][cptcod];
8043: }
8044: if(mobilav==-1){ /* Forcing raw ages if good else agemingood */
8045: if(fabs(sumnewmr[cptcod] - 1.) <= 1.e-3) { /* good */
8046: agemingoodr[cptcod]=age;
8047: for (i=1; i<=nlstate;i++)
8048: mobaverage[(int)age][i][cptcod]=probs[(int)age][i][cptcod];
8049: }else{ /* bad we change the value with the values of good ages */
8050: for (i=1; i<=nlstate;i++){
8051: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemingoodr[cptcod]][i][cptcod];
8052: } /* i */
8053: } /* end bad */
8054: }else{
8055: if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
8056: agemingood[cptcod]=age;
8057: }else{ /* bad */
8058: for (i=1; i<=nlstate;i++){
8059: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemingood[cptcod]][i][cptcod];
8060: } /* i */
8061: } /* end bad */
8062: }/* end else */
8063: sum=0.;sumr=0.;
8064: for (i=1; i<=nlstate;i++){
8065: sum+=mobaverage[(int)age][i][cptcod];
8066: sumr+=mobaverage[(int)age][i][cptcod];
1.222 brouard 8067: }
1.266 brouard 8068: if(fabs(sum - 1.) > 1.e-3) { /* bad */
1.268 brouard 8069: 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 8070: } /* end bad */
8071: /* else{ /\* We found some ages summing to one, we will smooth the oldest *\/ */
8072: if(fabs(sumr - 1.) > 1.e-3) { /* bad */
1.268 brouard 8073: 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 8074: } /* end bad */
8075: }/* age */
1.266 brouard 8076:
1.222 brouard 8077:
8078: for (age=bage; age<=fage; age++){
1.235 brouard 8079: /* printf("%d %d ", cptcod, (int)age); */
1.222 brouard 8080: sumnewp[cptcod]=0.;
8081: sumnewm[cptcod]=0.;
8082: for (i=1; i<=nlstate;i++){
8083: sumnewp[cptcod]+=probs[(int)age][i][cptcod];
8084: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
8085: /* printf("%.4f %.4f ",probs[(int)age][i][cptcod], mobaverage[(int)age][i][cptcod]); */
8086: }
8087: /* printf("%.4f %.4f \n",sumnewp[cptcod], sumnewm[cptcod]); */
8088: }
8089: /* printf("\n"); */
8090: /* } */
1.266 brouard 8091:
1.222 brouard 8092: /* brutal averaging */
1.266 brouard 8093: /* for (i=1; i<=nlstate;i++){ */
8094: /* for (age=1; age<=bage; age++){ */
8095: /* mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemingood[cptcod]][i][cptcod]; */
8096: /* /\* printf("age=%d i=%d cptcod=%d mobaverage=%.4f \n",(int)age,i, cptcod, mobaverage[(int)age][i][cptcod]); *\/ */
8097: /* } */
8098: /* for (age=fage; age<=AGESUP; age++){ */
8099: /* mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemaxgood[cptcod]][i][cptcod]; */
8100: /* /\* printf("age=%d i=%d cptcod=%d mobaverage=%.4f \n",(int)age,i, cptcod, mobaverage[(int)age][i][cptcod]); *\/ */
8101: /* } */
8102: /* } /\* end i status *\/ */
8103: /* for (i=nlstate+1; i<=nlstate+ndeath;i++){ */
8104: /* for (age=1; age<=AGESUP; age++){ */
8105: /* /\*printf("i=%d, age=%d, cptcod=%d\n",i, (int)age, cptcod);*\/ */
8106: /* mobaverage[(int)age][i][cptcod]=0.; */
8107: /* } */
8108: /* } */
1.222 brouard 8109: }/* end cptcod */
1.266 brouard 8110: free_vector(agemaxgoodr,1, ncovcombmax);
8111: free_vector(agemaxgood,1, ncovcombmax);
8112: free_vector(agemingood,1, ncovcombmax);
8113: free_vector(agemingoodr,1, ncovcombmax);
8114: free_vector(sumnewmr,1, ncovcombmax);
1.222 brouard 8115: free_vector(sumnewm,1, ncovcombmax);
8116: free_vector(sumnewp,1, ncovcombmax);
8117: return 0;
8118: }/* End movingaverage */
1.218 brouard 8119:
1.126 brouard 8120:
8121: /************** Forecasting ******************/
1.269 brouard 8122: 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 8123: /* proj1, year, month, day of starting projection
8124: agemin, agemax range of age
8125: dateprev1 dateprev2 range of dates during which prevalence is computed
8126: anproj2 year of en of projection (same day and month as proj1).
8127: */
1.267 brouard 8128: int yearp, stepsize, hstepm, nhstepm, j, k, cptcod, i, h, i1, k4, nres=0;
1.126 brouard 8129: double agec; /* generic age */
8130: double agelim, ppij, yp,yp1,yp2,jprojmean,mprojmean,anprojmean;
8131: double *popeffectif,*popcount;
8132: double ***p3mat;
1.218 brouard 8133: /* double ***mobaverage; */
1.126 brouard 8134: char fileresf[FILENAMELENGTH];
8135:
8136: agelim=AGESUP;
1.211 brouard 8137: /* Compute observed prevalence between dateprev1 and dateprev2 by counting the number of people
8138: in each health status at the date of interview (if between dateprev1 and dateprev2).
8139: We still use firstpass and lastpass as another selection.
8140: */
1.214 brouard 8141: /* freqsummary(fileres, agemin, agemax, s, agev, nlstate, imx,Tvaraff,nbcode, ncodemax,mint,anint,strstart,\ */
8142: /* firstpass, lastpass, stepm, weightopt, model); */
1.126 brouard 8143:
1.201 brouard 8144: strcpy(fileresf,"F_");
8145: strcat(fileresf,fileresu);
1.126 brouard 8146: if((ficresf=fopen(fileresf,"w"))==NULL) {
8147: printf("Problem with forecast resultfile: %s\n", fileresf);
8148: fprintf(ficlog,"Problem with forecast resultfile: %s\n", fileresf);
8149: }
1.235 brouard 8150: printf("\nComputing forecasting: result on file '%s', please wait... \n", fileresf);
8151: fprintf(ficlog,"\nComputing forecasting: result on file '%s', please wait... \n", fileresf);
1.126 brouard 8152:
1.225 brouard 8153: if (cptcoveff==0) ncodemax[cptcoveff]=1;
1.126 brouard 8154:
8155:
8156: stepsize=(int) (stepm+YEARM-1)/YEARM;
8157: if (stepm<=12) stepsize=1;
8158: if(estepm < stepm){
8159: printf ("Problem %d lower than %d\n",estepm, stepm);
8160: }
1.270 brouard 8161: else{
8162: hstepm=estepm;
8163: }
8164: if(estepm > stepm){ /* Yes every two year */
8165: stepsize=2;
8166: }
1.126 brouard 8167:
8168: hstepm=hstepm/stepm;
8169: yp1=modf(dateintmean,&yp);/* extracts integral of datemean in yp and
8170: fractional in yp1 */
8171: anprojmean=yp;
8172: yp2=modf((yp1*12),&yp);
8173: mprojmean=yp;
8174: yp1=modf((yp2*30.5),&yp);
8175: jprojmean=yp;
8176: if(jprojmean==0) jprojmean=1;
8177: if(mprojmean==0) jprojmean=1;
8178:
1.227 brouard 8179: i1=pow(2,cptcoveff);
1.126 brouard 8180: if (cptcovn < 1){i1=1;}
8181:
8182: fprintf(ficresf,"# Mean day of interviews %.lf/%.lf/%.lf (%.2f) between %.2f and %.2f \n",jprojmean,mprojmean,anprojmean,dateintmean,dateprev1,dateprev2);
8183:
8184: fprintf(ficresf,"#****** Routine prevforecast **\n");
1.227 brouard 8185:
1.126 brouard 8186: /* if (h==(int)(YEARM*yearp)){ */
1.235 brouard 8187: for(nres=1; nres <= nresult; nres++) /* For each resultline */
8188: for(k=1; k<=i1;k++){
1.253 brouard 8189: if(i1 != 1 && TKresult[nres]!= k)
1.235 brouard 8190: continue;
1.227 brouard 8191: if(invalidvarcomb[k]){
8192: printf("\nCombination (%d) projection ignored because no cases \n",k);
8193: continue;
8194: }
8195: fprintf(ficresf,"\n#****** hpijx=probability over h years, hp.jx is weighted by observed prev \n#");
8196: for(j=1;j<=cptcoveff;j++) {
8197: fprintf(ficresf," V%d (=) %d",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
8198: }
1.235 brouard 8199: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
1.238 brouard 8200: fprintf(ficresf," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.235 brouard 8201: }
1.227 brouard 8202: fprintf(ficresf," yearproj age");
8203: for(j=1; j<=nlstate+ndeath;j++){
8204: for(i=1; i<=nlstate;i++)
8205: fprintf(ficresf," p%d%d",i,j);
8206: fprintf(ficresf," wp.%d",j);
8207: }
8208: for (yearp=0; yearp<=(anproj2-anproj1);yearp +=stepsize) {
8209: fprintf(ficresf,"\n");
8210: fprintf(ficresf,"\n# Forecasting at date %.lf/%.lf/%.lf ",jproj1,mproj1,anproj1+yearp);
1.270 brouard 8211: /* for (agec=fage; agec>=(ageminpar-1); agec--){ */
8212: for (agec=fage; agec>=(bage); agec--){
1.227 brouard 8213: nhstepm=(int) rint((agelim-agec)*YEARM/stepm);
8214: nhstepm = nhstepm/hstepm;
8215: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
8216: oldm=oldms;savm=savms;
1.268 brouard 8217: /* We compute pii at age agec over nhstepm);*/
1.235 brouard 8218: hpxij(p3mat,nhstepm,agec,hstepm,p,nlstate,stepm,oldm,savm, k,nres);
1.268 brouard 8219: /* Then we print p3mat for h corresponding to the right agec+h*stepms=yearp */
1.227 brouard 8220: for (h=0; h<=nhstepm; h++){
8221: if (h*hstepm/YEARM*stepm ==yearp) {
1.268 brouard 8222: break;
8223: }
8224: }
8225: fprintf(ficresf,"\n");
8226: for(j=1;j<=cptcoveff;j++)
8227: fprintf(ficresf,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
8228: fprintf(ficresf,"%.f %.f ",anproj1+yearp,agec+h*hstepm/YEARM*stepm);
8229:
8230: for(j=1; j<=nlstate+ndeath;j++) {
8231: ppij=0.;
8232: for(i=1; i<=nlstate;i++) {
8233: /* if (mobilav>=1) */
1.269 brouard 8234: ppij=ppij+p3mat[i][j][h]*prev[(int)agec][i][k];
1.268 brouard 8235: /* else { */ /* even if mobilav==-1 we use mobaverage */
8236: /* ppij=ppij+p3mat[i][j][h]*probs[(int)(agec)][i][k]; */
8237: /* } */
8238: fprintf(ficresf," %.3f", p3mat[i][j][h]);
8239: } /* end i */
8240: fprintf(ficresf," %.3f", ppij);
8241: }/* end j */
1.227 brouard 8242: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
8243: } /* end agec */
1.266 brouard 8244: /* diffyear=(int) anproj1+yearp-ageminpar-1; */
8245: /*printf("Prevforecast %d+%d-%d=diffyear=%d\n",(int) anproj1, (int)yearp,(int)ageminpar,(int) anproj1-(int)ageminpar);*/
1.227 brouard 8246: } /* end yearp */
8247: } /* end k */
1.219 brouard 8248:
1.126 brouard 8249: fclose(ficresf);
1.215 brouard 8250: printf("End of Computing forecasting \n");
8251: fprintf(ficlog,"End of Computing forecasting\n");
8252:
1.126 brouard 8253: }
8254:
1.269 brouard 8255: /************** Back Forecasting ******************/
8256: 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 8257: /* back1, year, month, day of starting backection
8258: agemin, agemax range of age
8259: dateprev1 dateprev2 range of dates during which prevalence is computed
1.269 brouard 8260: anback2 year of end of backprojection (same day and month as back1).
8261: prevacurrent and prev are prevalences.
1.267 brouard 8262: */
8263: int yearp, stepsize, hstepm, nhstepm, j, k, cptcod, i, h, i1, k4, nres=0;
8264: double agec; /* generic age */
1.268 brouard 8265: double agelim, ppij, ppi, yp,yp1,yp2,jprojmean,mprojmean,anprojmean;
1.267 brouard 8266: double *popeffectif,*popcount;
8267: double ***p3mat;
8268: /* double ***mobaverage; */
8269: char fileresfb[FILENAMELENGTH];
8270:
1.268 brouard 8271: agelim=AGEINF;
1.267 brouard 8272: /* Compute observed prevalence between dateprev1 and dateprev2 by counting the number of people
8273: in each health status at the date of interview (if between dateprev1 and dateprev2).
8274: We still use firstpass and lastpass as another selection.
8275: */
8276: /* freqsummary(fileres, agemin, agemax, s, agev, nlstate, imx,Tvaraff,nbcode, ncodemax,mint,anint,strstart,\ */
8277: /* firstpass, lastpass, stepm, weightopt, model); */
8278:
8279: /*Do we need to compute prevalence again?*/
8280:
8281: /* prevalence(probs, ageminpar, agemax, s, agev, nlstate, imx, Tvar, nbcode, ncodemax, mint, anint, dateprev1, dateprev2, firstpass, lastpass); */
8282:
8283: strcpy(fileresfb,"FB_");
8284: strcat(fileresfb,fileresu);
8285: if((ficresfb=fopen(fileresfb,"w"))==NULL) {
8286: printf("Problem with back forecast resultfile: %s\n", fileresfb);
8287: fprintf(ficlog,"Problem with back forecast resultfile: %s\n", fileresfb);
8288: }
8289: printf("\nComputing back forecasting: result on file '%s', please wait... \n", fileresfb);
8290: fprintf(ficlog,"\nComputing back forecasting: result on file '%s', please wait... \n", fileresfb);
8291:
8292: if (cptcoveff==0) ncodemax[cptcoveff]=1;
8293:
8294:
8295: stepsize=(int) (stepm+YEARM-1)/YEARM;
8296: if (stepm<=12) stepsize=1;
8297: if(estepm < stepm){
8298: printf ("Problem %d lower than %d\n",estepm, stepm);
8299: }
1.270 brouard 8300: else{
8301: hstepm=estepm;
8302: }
8303: if(estepm >= stepm){ /* Yes every two year */
8304: stepsize=2;
8305: }
1.267 brouard 8306:
8307: hstepm=hstepm/stepm;
8308: yp1=modf(dateintmean,&yp);/* extracts integral of datemean in yp and
8309: fractional in yp1 */
8310: anprojmean=yp;
8311: yp2=modf((yp1*12),&yp);
8312: mprojmean=yp;
8313: yp1=modf((yp2*30.5),&yp);
8314: jprojmean=yp;
8315: if(jprojmean==0) jprojmean=1;
8316: if(mprojmean==0) jprojmean=1;
8317:
8318: i1=pow(2,cptcoveff);
8319: if (cptcovn < 1){i1=1;}
8320:
8321: fprintf(ficresfb,"# Mean day of interviews %.lf/%.lf/%.lf (%.2f) between %.2f and %.2f \n",jprojmean,mprojmean,anprojmean,dateintmean,dateprev1,dateprev2);
1.268 brouard 8322: printf("# Mean day of interviews %.lf/%.lf/%.lf (%.2f) between %.2f and %.2f \n",jprojmean,mprojmean,anprojmean,dateintmean,dateprev1,dateprev2);
1.267 brouard 8323:
8324: fprintf(ficresfb,"#****** Routine prevbackforecast **\n");
8325:
8326: for(nres=1; nres <= nresult; nres++) /* For each resultline */
8327: for(k=1; k<=i1;k++){
8328: if(i1 != 1 && TKresult[nres]!= k)
8329: continue;
8330: if(invalidvarcomb[k]){
8331: printf("\nCombination (%d) projection ignored because no cases \n",k);
8332: continue;
8333: }
1.268 brouard 8334: fprintf(ficresfb,"\n#****** hbijx=probability over h years, hb.jx is weighted by observed prev \n#");
1.267 brouard 8335: for(j=1;j<=cptcoveff;j++) {
8336: fprintf(ficresfb," V%d (=) %d",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
8337: }
8338: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
8339: fprintf(ficresf," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
8340: }
8341: fprintf(ficresfb," yearbproj age");
8342: for(j=1; j<=nlstate+ndeath;j++){
8343: for(i=1; i<=nlstate;i++)
1.268 brouard 8344: fprintf(ficresfb," b%d%d",i,j);
8345: fprintf(ficresfb," b.%d",j);
1.267 brouard 8346: }
8347: for (yearp=0; yearp>=(anback2-anback1);yearp -=stepsize) {
8348: /* for (yearp=0; yearp<=(anproj2-anproj1);yearp +=stepsize) { */
8349: fprintf(ficresfb,"\n");
8350: fprintf(ficresfb,"\n# Back Forecasting at date %.lf/%.lf/%.lf ",jback1,mback1,anback1+yearp);
1.271 brouard 8351: printf("\n# Back Forecasting at date %.lf/%.lf/%.lf ",jback1,mback1,anback1+yearp);
1.270 brouard 8352: /* for (agec=bage; agec<=agemax-1; agec++){ /\* testing *\/ */
8353: for (agec=bage; agec<=fage; agec++){ /* testing */
1.268 brouard 8354: /* We compute bij at age agec over nhstepm, nhstepm decreases when agec increases because of agemax;*/
1.271 brouard 8355: nhstepm=(int) (agec-agelim) *YEARM/stepm;/* nhstepm=(int) rint((agec-agelim)*YEARM/stepm);*/
1.267 brouard 8356: nhstepm = nhstepm/hstepm;
8357: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
8358: oldm=oldms;savm=savms;
1.268 brouard 8359: /* computes hbxij at age agec over 1 to nhstepm */
1.271 brouard 8360: /* printf("####prevbackforecast debug agec=%.2f nhstepm=%d\n",agec, nhstepm);fflush(stdout); */
1.267 brouard 8361: hbxij(p3mat,nhstepm,agec,hstepm,p,prevacurrent,nlstate,stepm, k, nres);
1.268 brouard 8362: /* hpxij(p3mat,nhstepm,agec,hstepm,p, nlstate,stepm,oldm,savm, k,nres); */
8363: /* Then we print p3mat for h corresponding to the right agec+h*stepms=yearp */
8364: /* printf(" agec=%.2f\n",agec);fflush(stdout); */
1.267 brouard 8365: for (h=0; h<=nhstepm; h++){
1.268 brouard 8366: if (h*hstepm/YEARM*stepm ==-yearp) {
8367: break;
8368: }
8369: }
8370: fprintf(ficresfb,"\n");
8371: for(j=1;j<=cptcoveff;j++)
8372: fprintf(ficresfb,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
8373: fprintf(ficresfb,"%.f %.f ",anback1+yearp,agec-h*hstepm/YEARM*stepm);
8374: for(i=1; i<=nlstate+ndeath;i++) {
8375: ppij=0.;ppi=0.;
8376: for(j=1; j<=nlstate;j++) {
8377: /* if (mobilav==1) */
1.269 brouard 8378: ppij=ppij+p3mat[i][j][h]*prevacurrent[(int)agec][j][k];
8379: ppi=ppi+prevacurrent[(int)agec][j][k];
8380: /* ppij=ppij+p3mat[i][j][h]*mobaverage[(int)agec][j][k]; */
8381: /* ppi=ppi+mobaverage[(int)agec][j][k]; */
1.267 brouard 8382: /* else { */
8383: /* ppij=ppij+p3mat[i][j][h]*probs[(int)(agec)][i][k]; */
8384: /* } */
1.268 brouard 8385: fprintf(ficresfb," %.3f", p3mat[i][j][h]);
8386: } /* end j */
8387: if(ppi <0.99){
8388: printf("Error in prevbackforecast, prevalence doesn't sum to 1 for state %d: %3f\n",i, ppi);
8389: fprintf(ficlog,"Error in prevbackforecast, prevalence doesn't sum to 1 for state %d: %3f\n",i, ppi);
8390: }
8391: fprintf(ficresfb," %.3f", ppij);
8392: }/* end j */
1.267 brouard 8393: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
8394: } /* end agec */
8395: } /* end yearp */
8396: } /* end k */
1.217 brouard 8397:
1.267 brouard 8398: /* if (mobilav!=0) free_ma3x(mobaverage,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
1.217 brouard 8399:
1.267 brouard 8400: fclose(ficresfb);
8401: printf("End of Computing Back forecasting \n");
8402: fprintf(ficlog,"End of Computing Back forecasting\n");
1.218 brouard 8403:
1.267 brouard 8404: }
1.217 brouard 8405:
1.269 brouard 8406: /* Variance of prevalence limit: varprlim */
8407: 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){
8408: /*------- Variance of period (stable) prevalence------*/
8409:
8410: char fileresvpl[FILENAMELENGTH];
8411: FILE *ficresvpl;
8412: double **oldm, **savm;
8413: double **varpl; /* Variances of prevalence limits by age */
8414: int i1, k, nres, j ;
8415:
8416: strcpy(fileresvpl,"VPL_");
8417: strcat(fileresvpl,fileresu);
8418: if((ficresvpl=fopen(fileresvpl,"w"))==NULL) {
8419: printf("Problem with variance of period (stable) prevalence resultfile: %s\n", fileresvpl);
8420: exit(0);
8421: }
8422: printf("Computing Variance-covariance of period (stable) prevalence: file '%s' ...", fileresvpl);fflush(stdout);
8423: fprintf(ficlog, "Computing Variance-covariance of period (stable) prevalence: file '%s' ...", fileresvpl);fflush(ficlog);
8424:
8425: /*for(cptcov=1,k=0;cptcov<=i1;cptcov++){
8426: for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){*/
8427:
8428: i1=pow(2,cptcoveff);
8429: if (cptcovn < 1){i1=1;}
8430:
8431: for(nres=1; nres <= nresult; nres++) /* For each resultline */
8432: for(k=1; k<=i1;k++){
8433: if(i1 != 1 && TKresult[nres]!= k)
8434: continue;
8435: fprintf(ficresvpl,"\n#****** ");
8436: printf("\n#****** ");
8437: fprintf(ficlog,"\n#****** ");
8438: for(j=1;j<=cptcoveff;j++) {
8439: fprintf(ficresvpl,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
8440: fprintf(ficlog,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
8441: printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
8442: }
8443: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
8444: printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
8445: fprintf(ficresvpl," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
8446: fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
8447: }
8448: fprintf(ficresvpl,"******\n");
8449: printf("******\n");
8450: fprintf(ficlog,"******\n");
8451:
8452: varpl=matrix(1,nlstate,(int) bage, (int) fage);
8453: oldm=oldms;savm=savms;
8454: varprevlim(fileresvpl, ficresvpl, varpl, matcov, p, delti, nlstate, stepm, (int) bage, (int) fage, oldm, savm, prlim, ftolpl, ncvyearp, k, strstart, nres);
8455: free_matrix(varpl,1,nlstate,(int) bage, (int)fage);
8456: /*}*/
8457: }
8458:
8459: fclose(ficresvpl);
8460: printf("done variance-covariance of period prevalence\n");fflush(stdout);
8461: fprintf(ficlog,"done variance-covariance of period prevalence\n");fflush(ficlog);
8462:
8463: }
8464: /* Variance of back prevalence: varbprlim */
8465: 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){
8466: /*------- Variance of back (stable) prevalence------*/
8467:
8468: char fileresvbl[FILENAMELENGTH];
8469: FILE *ficresvbl;
8470:
8471: double **oldm, **savm;
8472: double **varbpl; /* Variances of back prevalence limits by age */
8473: int i1, k, nres, j ;
8474:
8475: strcpy(fileresvbl,"VBL_");
8476: strcat(fileresvbl,fileresu);
8477: if((ficresvbl=fopen(fileresvbl,"w"))==NULL) {
8478: printf("Problem with variance of back (stable) prevalence resultfile: %s\n", fileresvbl);
8479: exit(0);
8480: }
8481: printf("Computing Variance-covariance of back (stable) prevalence: file '%s' ...", fileresvbl);fflush(stdout);
8482: fprintf(ficlog, "Computing Variance-covariance of back (stable) prevalence: file '%s' ...", fileresvbl);fflush(ficlog);
8483:
8484:
8485: i1=pow(2,cptcoveff);
8486: if (cptcovn < 1){i1=1;}
8487:
8488: for(nres=1; nres <= nresult; nres++) /* For each resultline */
8489: for(k=1; k<=i1;k++){
8490: if(i1 != 1 && TKresult[nres]!= k)
8491: continue;
8492: fprintf(ficresvbl,"\n#****** ");
8493: printf("\n#****** ");
8494: fprintf(ficlog,"\n#****** ");
8495: for(j=1;j<=cptcoveff;j++) {
8496: fprintf(ficresvbl,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
8497: fprintf(ficlog,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
8498: printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
8499: }
8500: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
8501: printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
8502: fprintf(ficresvbl," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
8503: fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
8504: }
8505: fprintf(ficresvbl,"******\n");
8506: printf("******\n");
8507: fprintf(ficlog,"******\n");
8508:
8509: varbpl=matrix(1,nlstate,(int) bage, (int) fage);
8510: oldm=oldms;savm=savms;
8511:
8512: varbrevlim(fileresvbl, ficresvbl, varbpl, matcov, p, delti, nlstate, stepm, (int) bage, (int) fage, oldm, savm, bprlim, ftolpl, mobilavproj, ncvyearp, k, strstart, nres);
8513: free_matrix(varbpl,1,nlstate,(int) bage, (int)fage);
8514: /*}*/
8515: }
8516:
8517: fclose(ficresvbl);
8518: printf("done variance-covariance of back prevalence\n");fflush(stdout);
8519: fprintf(ficlog,"done variance-covariance of back prevalence\n");fflush(ficlog);
8520:
8521: } /* End of varbprlim */
8522:
1.126 brouard 8523: /************** Forecasting *****not tested NB*************/
1.227 brouard 8524: /* 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 8525:
1.227 brouard 8526: /* int cpt, stepsize, hstepm, nhstepm, j,k,c, cptcod, i,h; */
8527: /* int *popage; */
8528: /* double calagedatem, agelim, kk1, kk2; */
8529: /* double *popeffectif,*popcount; */
8530: /* double ***p3mat,***tabpop,***tabpopprev; */
8531: /* /\* double ***mobaverage; *\/ */
8532: /* char filerespop[FILENAMELENGTH]; */
1.126 brouard 8533:
1.227 brouard 8534: /* tabpop= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
8535: /* tabpopprev= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
8536: /* agelim=AGESUP; */
8537: /* calagedatem=(anpyram+mpyram/12.+jpyram/365.-dateintmean)*YEARM; */
1.126 brouard 8538:
1.227 brouard 8539: /* prevalence(probs, ageminpar, agemax, s, agev, nlstate, imx, Tvar, nbcode, ncodemax, mint, anint, dateprev1, dateprev2, firstpass, lastpass); */
1.126 brouard 8540:
8541:
1.227 brouard 8542: /* strcpy(filerespop,"POP_"); */
8543: /* strcat(filerespop,fileresu); */
8544: /* if((ficrespop=fopen(filerespop,"w"))==NULL) { */
8545: /* printf("Problem with forecast resultfile: %s\n", filerespop); */
8546: /* fprintf(ficlog,"Problem with forecast resultfile: %s\n", filerespop); */
8547: /* } */
8548: /* printf("Computing forecasting: result on file '%s' \n", filerespop); */
8549: /* fprintf(ficlog,"Computing forecasting: result on file '%s' \n", filerespop); */
1.126 brouard 8550:
1.227 brouard 8551: /* if (cptcoveff==0) ncodemax[cptcoveff]=1; */
1.126 brouard 8552:
1.227 brouard 8553: /* /\* if (mobilav!=0) { *\/ */
8554: /* /\* mobaverage= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); *\/ */
8555: /* /\* if (movingaverage(probs, ageminpar, fage, mobaverage,mobilav)!=0){ *\/ */
8556: /* /\* fprintf(ficlog," Error in movingaverage mobilav=%d\n",mobilav); *\/ */
8557: /* /\* printf(" Error in movingaverage mobilav=%d\n",mobilav); *\/ */
8558: /* /\* } *\/ */
8559: /* /\* } *\/ */
1.126 brouard 8560:
1.227 brouard 8561: /* stepsize=(int) (stepm+YEARM-1)/YEARM; */
8562: /* if (stepm<=12) stepsize=1; */
1.126 brouard 8563:
1.227 brouard 8564: /* agelim=AGESUP; */
1.126 brouard 8565:
1.227 brouard 8566: /* hstepm=1; */
8567: /* hstepm=hstepm/stepm; */
1.218 brouard 8568:
1.227 brouard 8569: /* if (popforecast==1) { */
8570: /* if((ficpop=fopen(popfile,"r"))==NULL) { */
8571: /* printf("Problem with population file : %s\n",popfile);exit(0); */
8572: /* fprintf(ficlog,"Problem with population file : %s\n",popfile);exit(0); */
8573: /* } */
8574: /* popage=ivector(0,AGESUP); */
8575: /* popeffectif=vector(0,AGESUP); */
8576: /* popcount=vector(0,AGESUP); */
1.126 brouard 8577:
1.227 brouard 8578: /* i=1; */
8579: /* while ((c=fscanf(ficpop,"%d %lf\n",&popage[i],&popcount[i])) != EOF) i=i+1; */
1.218 brouard 8580:
1.227 brouard 8581: /* imx=i; */
8582: /* for (i=1; i<imx;i++) popeffectif[popage[i]]=popcount[i]; */
8583: /* } */
1.218 brouard 8584:
1.227 brouard 8585: /* for(cptcov=1,k=0;cptcov<=i2;cptcov++){ */
8586: /* for(cptcod=1;cptcod<=ncodemax[cptcoveff];cptcod++){ */
8587: /* k=k+1; */
8588: /* fprintf(ficrespop,"\n#******"); */
8589: /* for(j=1;j<=cptcoveff;j++) { */
8590: /* fprintf(ficrespop," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]); */
8591: /* } */
8592: /* fprintf(ficrespop,"******\n"); */
8593: /* fprintf(ficrespop,"# Age"); */
8594: /* for(j=1; j<=nlstate+ndeath;j++) fprintf(ficrespop," P.%d",j); */
8595: /* if (popforecast==1) fprintf(ficrespop," [Population]"); */
1.126 brouard 8596:
1.227 brouard 8597: /* for (cpt=0; cpt<=0;cpt++) { */
8598: /* fprintf(ficrespop,"\n\n# Forecasting at date %.lf/%.lf/%.lf ",jpyram,mpyram,anpyram+cpt); */
1.126 brouard 8599:
1.227 brouard 8600: /* for (agedeb=(fage-((int)calagedatem %12/12.)); agedeb>=(ageminpar-((int)calagedatem %12)/12.); agedeb--){ */
8601: /* nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); */
8602: /* nhstepm = nhstepm/hstepm; */
1.126 brouard 8603:
1.227 brouard 8604: /* p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
8605: /* oldm=oldms;savm=savms; */
8606: /* hpxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k); */
1.218 brouard 8607:
1.227 brouard 8608: /* for (h=0; h<=nhstepm; h++){ */
8609: /* if (h==(int) (calagedatem+YEARM*cpt)) { */
8610: /* fprintf(ficrespop,"\n %3.f ",agedeb+h*hstepm/YEARM*stepm); */
8611: /* } */
8612: /* for(j=1; j<=nlstate+ndeath;j++) { */
8613: /* kk1=0.;kk2=0; */
8614: /* for(i=1; i<=nlstate;i++) { */
8615: /* if (mobilav==1) */
8616: /* kk1=kk1+p3mat[i][j][h]*mobaverage[(int)agedeb+1][i][cptcod]; */
8617: /* else { */
8618: /* kk1=kk1+p3mat[i][j][h]*probs[(int)(agedeb+1)][i][cptcod]; */
8619: /* } */
8620: /* } */
8621: /* if (h==(int)(calagedatem+12*cpt)){ */
8622: /* tabpop[(int)(agedeb)][j][cptcod]=kk1; */
8623: /* /\*fprintf(ficrespop," %.3f", kk1); */
8624: /* if (popforecast==1) fprintf(ficrespop," [%.f]", kk1*popeffectif[(int)agedeb+1]);*\/ */
8625: /* } */
8626: /* } */
8627: /* for(i=1; i<=nlstate;i++){ */
8628: /* kk1=0.; */
8629: /* for(j=1; j<=nlstate;j++){ */
8630: /* kk1= kk1+tabpop[(int)(agedeb)][j][cptcod]; */
8631: /* } */
8632: /* tabpopprev[(int)(agedeb)][i][cptcod]=tabpop[(int)(agedeb)][i][cptcod]/kk1*popeffectif[(int)(agedeb+(calagedatem+12*cpt)*hstepm/YEARM*stepm-1)]; */
8633: /* } */
1.218 brouard 8634:
1.227 brouard 8635: /* if (h==(int)(calagedatem+12*cpt)) */
8636: /* for(j=1; j<=nlstate;j++) */
8637: /* fprintf(ficrespop," %15.2f",tabpopprev[(int)(agedeb+1)][j][cptcod]); */
8638: /* } */
8639: /* free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
8640: /* } */
8641: /* } */
1.218 brouard 8642:
1.227 brouard 8643: /* /\******\/ */
1.218 brouard 8644:
1.227 brouard 8645: /* for (cpt=1; cpt<=(anpyram1-anpyram);cpt++) { */
8646: /* fprintf(ficrespop,"\n\n# Forecasting at date %.lf/%.lf/%.lf ",jpyram,mpyram,anpyram+cpt); */
8647: /* for (agedeb=(fage-((int)calagedatem %12/12.)); agedeb>=(ageminpar-((int)calagedatem %12)/12.); agedeb--){ */
8648: /* nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); */
8649: /* nhstepm = nhstepm/hstepm; */
1.126 brouard 8650:
1.227 brouard 8651: /* p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
8652: /* oldm=oldms;savm=savms; */
8653: /* hpxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k); */
8654: /* for (h=0; h<=nhstepm; h++){ */
8655: /* if (h==(int) (calagedatem+YEARM*cpt)) { */
8656: /* fprintf(ficresf,"\n %3.f ",agedeb+h*hstepm/YEARM*stepm); */
8657: /* } */
8658: /* for(j=1; j<=nlstate+ndeath;j++) { */
8659: /* kk1=0.;kk2=0; */
8660: /* for(i=1; i<=nlstate;i++) { */
8661: /* kk1=kk1+p3mat[i][j][h]*tabpopprev[(int)agedeb+1][i][cptcod]; */
8662: /* } */
8663: /* if (h==(int)(calagedatem+12*cpt)) fprintf(ficresf," %15.2f", kk1); */
8664: /* } */
8665: /* } */
8666: /* free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
8667: /* } */
8668: /* } */
8669: /* } */
8670: /* } */
1.218 brouard 8671:
1.227 brouard 8672: /* /\* if (mobilav!=0) free_ma3x(mobaverage,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); *\/ */
1.218 brouard 8673:
1.227 brouard 8674: /* if (popforecast==1) { */
8675: /* free_ivector(popage,0,AGESUP); */
8676: /* free_vector(popeffectif,0,AGESUP); */
8677: /* free_vector(popcount,0,AGESUP); */
8678: /* } */
8679: /* free_ma3x(tabpop,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
8680: /* free_ma3x(tabpopprev,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
8681: /* fclose(ficrespop); */
8682: /* } /\* End of popforecast *\/ */
1.218 brouard 8683:
1.126 brouard 8684: int fileappend(FILE *fichier, char *optionfich)
8685: {
8686: if((fichier=fopen(optionfich,"a"))==NULL) {
8687: printf("Problem with file: %s\n", optionfich);
8688: fprintf(ficlog,"Problem with file: %s\n", optionfich);
8689: return (0);
8690: }
8691: fflush(fichier);
8692: return (1);
8693: }
8694:
8695:
8696: /**************** function prwizard **********************/
8697: void prwizard(int ncovmodel, int nlstate, int ndeath, char model[], FILE *ficparo)
8698: {
8699:
8700: /* Wizard to print covariance matrix template */
8701:
1.164 brouard 8702: char ca[32], cb[32];
8703: int i,j, k, li, lj, lk, ll, jj, npar, itimes;
1.126 brouard 8704: int numlinepar;
8705:
8706: printf("# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
8707: fprintf(ficparo,"# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
8708: for(i=1; i <=nlstate; i++){
8709: jj=0;
8710: for(j=1; j <=nlstate+ndeath; j++){
8711: if(j==i) continue;
8712: jj++;
8713: /*ca[0]= k+'a'-1;ca[1]='\0';*/
8714: printf("%1d%1d",i,j);
8715: fprintf(ficparo,"%1d%1d",i,j);
8716: for(k=1; k<=ncovmodel;k++){
8717: /* printf(" %lf",param[i][j][k]); */
8718: /* fprintf(ficparo," %lf",param[i][j][k]); */
8719: printf(" 0.");
8720: fprintf(ficparo," 0.");
8721: }
8722: printf("\n");
8723: fprintf(ficparo,"\n");
8724: }
8725: }
8726: printf("# Scales (for hessian or gradient estimation)\n");
8727: fprintf(ficparo,"# Scales (for hessian or gradient estimation)\n");
8728: npar= (nlstate+ndeath-1)*nlstate*ncovmodel; /* Number of parameters*/
8729: for(i=1; i <=nlstate; i++){
8730: jj=0;
8731: for(j=1; j <=nlstate+ndeath; j++){
8732: if(j==i) continue;
8733: jj++;
8734: fprintf(ficparo,"%1d%1d",i,j);
8735: printf("%1d%1d",i,j);
8736: fflush(stdout);
8737: for(k=1; k<=ncovmodel;k++){
8738: /* printf(" %le",delti3[i][j][k]); */
8739: /* fprintf(ficparo," %le",delti3[i][j][k]); */
8740: printf(" 0.");
8741: fprintf(ficparo," 0.");
8742: }
8743: numlinepar++;
8744: printf("\n");
8745: fprintf(ficparo,"\n");
8746: }
8747: }
8748: printf("# Covariance matrix\n");
8749: /* # 121 Var(a12)\n\ */
8750: /* # 122 Cov(b12,a12) Var(b12)\n\ */
8751: /* # 131 Cov(a13,a12) Cov(a13,b12, Var(a13)\n\ */
8752: /* # 132 Cov(b13,a12) Cov(b13,b12, Cov(b13,a13) Var(b13)\n\ */
8753: /* # 212 Cov(a21,a12) Cov(a21,b12, Cov(a21,a13) Cov(a21,b13) Var(a21)\n\ */
8754: /* # 212 Cov(b21,a12) Cov(b21,b12, Cov(b21,a13) Cov(b21,b13) Cov(b21,a21) Var(b21)\n\ */
8755: /* # 232 Cov(a23,a12) Cov(a23,b12, Cov(a23,a13) Cov(a23,b13) Cov(a23,a21) Cov(a23,b21) Var(a23)\n\ */
8756: /* # 232 Cov(b23,a12) Cov(b23,b12) ... Var (b23)\n" */
8757: fflush(stdout);
8758: fprintf(ficparo,"# Covariance matrix\n");
8759: /* # 121 Var(a12)\n\ */
8760: /* # 122 Cov(b12,a12) Var(b12)\n\ */
8761: /* # ...\n\ */
8762: /* # 232 Cov(b23,a12) Cov(b23,b12) ... Var (b23)\n" */
8763:
8764: for(itimes=1;itimes<=2;itimes++){
8765: jj=0;
8766: for(i=1; i <=nlstate; i++){
8767: for(j=1; j <=nlstate+ndeath; j++){
8768: if(j==i) continue;
8769: for(k=1; k<=ncovmodel;k++){
8770: jj++;
8771: ca[0]= k+'a'-1;ca[1]='\0';
8772: if(itimes==1){
8773: printf("#%1d%1d%d",i,j,k);
8774: fprintf(ficparo,"#%1d%1d%d",i,j,k);
8775: }else{
8776: printf("%1d%1d%d",i,j,k);
8777: fprintf(ficparo,"%1d%1d%d",i,j,k);
8778: /* printf(" %.5le",matcov[i][j]); */
8779: }
8780: ll=0;
8781: for(li=1;li <=nlstate; li++){
8782: for(lj=1;lj <=nlstate+ndeath; lj++){
8783: if(lj==li) continue;
8784: for(lk=1;lk<=ncovmodel;lk++){
8785: ll++;
8786: if(ll<=jj){
8787: cb[0]= lk +'a'-1;cb[1]='\0';
8788: if(ll<jj){
8789: if(itimes==1){
8790: printf(" Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
8791: fprintf(ficparo," Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
8792: }else{
8793: printf(" 0.");
8794: fprintf(ficparo," 0.");
8795: }
8796: }else{
8797: if(itimes==1){
8798: printf(" Var(%s%1d%1d)",ca,i,j);
8799: fprintf(ficparo," Var(%s%1d%1d)",ca,i,j);
8800: }else{
8801: printf(" 0.");
8802: fprintf(ficparo," 0.");
8803: }
8804: }
8805: }
8806: } /* end lk */
8807: } /* end lj */
8808: } /* end li */
8809: printf("\n");
8810: fprintf(ficparo,"\n");
8811: numlinepar++;
8812: } /* end k*/
8813: } /*end j */
8814: } /* end i */
8815: } /* end itimes */
8816:
8817: } /* end of prwizard */
8818: /******************* Gompertz Likelihood ******************************/
8819: double gompertz(double x[])
8820: {
8821: double A,B,L=0.0,sump=0.,num=0.;
8822: int i,n=0; /* n is the size of the sample */
8823:
1.220 brouard 8824: for (i=1;i<=imx ; i++) {
1.126 brouard 8825: sump=sump+weight[i];
8826: /* sump=sump+1;*/
8827: num=num+1;
8828: }
8829:
8830:
8831: /* for (i=0; i<=imx; i++)
8832: 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]);*/
8833:
8834: for (i=1;i<=imx ; i++)
8835: {
8836: if (cens[i] == 1 && wav[i]>1)
8837: A=-x[1]/(x[2])*(exp(x[2]*(agecens[i]-agegomp))-exp(x[2]*(ageexmed[i]-agegomp)));
8838:
8839: if (cens[i] == 0 && wav[i]>1)
8840: A=-x[1]/(x[2])*(exp(x[2]*(agedc[i]-agegomp))-exp(x[2]*(ageexmed[i]-agegomp)))
8841: +log(x[1]/YEARM)+x[2]*(agedc[i]-agegomp)+log(YEARM);
8842:
8843: /*if (wav[i] > 1 && agecens[i] > 15) {*/ /* ??? */
8844: if (wav[i] > 1 ) { /* ??? */
8845: L=L+A*weight[i];
8846: /* 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]);*/
8847: }
8848: }
8849:
8850: /*printf("x1=%2.9f x2=%2.9f x3=%2.9f L=%f\n",x[1],x[2],x[3],L);*/
8851:
8852: return -2*L*num/sump;
8853: }
8854:
1.136 brouard 8855: #ifdef GSL
8856: /******************* Gompertz_f Likelihood ******************************/
8857: double gompertz_f(const gsl_vector *v, void *params)
8858: {
8859: double A,B,LL=0.0,sump=0.,num=0.;
8860: double *x= (double *) v->data;
8861: int i,n=0; /* n is the size of the sample */
8862:
8863: for (i=0;i<=imx-1 ; i++) {
8864: sump=sump+weight[i];
8865: /* sump=sump+1;*/
8866: num=num+1;
8867: }
8868:
8869:
8870: /* for (i=0; i<=imx; i++)
8871: 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]);*/
8872: printf("x[0]=%lf x[1]=%lf\n",x[0],x[1]);
8873: for (i=1;i<=imx ; i++)
8874: {
8875: if (cens[i] == 1 && wav[i]>1)
8876: A=-x[0]/(x[1])*(exp(x[1]*(agecens[i]-agegomp))-exp(x[1]*(ageexmed[i]-agegomp)));
8877:
8878: if (cens[i] == 0 && wav[i]>1)
8879: A=-x[0]/(x[1])*(exp(x[1]*(agedc[i]-agegomp))-exp(x[1]*(ageexmed[i]-agegomp)))
8880: +log(x[0]/YEARM)+x[1]*(agedc[i]-agegomp)+log(YEARM);
8881:
8882: /*if (wav[i] > 1 && agecens[i] > 15) {*/ /* ??? */
8883: if (wav[i] > 1 ) { /* ??? */
8884: LL=LL+A*weight[i];
8885: /* 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]);*/
8886: }
8887: }
8888:
8889: /*printf("x1=%2.9f x2=%2.9f x3=%2.9f L=%f\n",x[1],x[2],x[3],L);*/
8890: printf("x[0]=%lf x[1]=%lf -2*LL*num/sump=%lf\n",x[0],x[1],-2*LL*num/sump);
8891:
8892: return -2*LL*num/sump;
8893: }
8894: #endif
8895:
1.126 brouard 8896: /******************* Printing html file ***********/
1.201 brouard 8897: void printinghtmlmort(char fileresu[], char title[], char datafile[], int firstpass, \
1.126 brouard 8898: int lastpass, int stepm, int weightopt, char model[],\
8899: int imx, double p[],double **matcov,double agemortsup){
8900: int i,k;
8901:
8902: fprintf(fichtm,"<ul><li><h4>Result files </h4>\n Force of mortality. Parameters of the Gompertz fit (with confidence interval in brackets):<br>");
8903: fprintf(fichtm," mu(age) =%lf*exp(%lf*(age-%d)) per year<br><br>",p[1],p[2],agegomp);
8904: for (i=1;i<=2;i++)
8905: 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 8906: fprintf(fichtm,"<br><br><img src=\"graphmort.svg\">");
1.126 brouard 8907: fprintf(fichtm,"</ul>");
8908:
8909: fprintf(fichtm,"<ul><li><h4>Life table</h4>\n <br>");
8910:
8911: 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>");
8912:
8913: for (k=agegomp;k<(agemortsup-2);k++)
8914: 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]);
8915:
8916:
8917: fflush(fichtm);
8918: }
8919:
8920: /******************* Gnuplot file **************/
1.201 brouard 8921: void printinggnuplotmort(char fileresu[], char optionfilefiname[], double ageminpar, double agemaxpar, double fage , char pathc[], double p[]){
1.126 brouard 8922:
8923: char dirfileres[132],optfileres[132];
1.164 brouard 8924:
1.126 brouard 8925: int ng;
8926:
8927:
8928: /*#ifdef windows */
8929: fprintf(ficgp,"cd \"%s\" \n",pathc);
8930: /*#endif */
8931:
8932:
8933: strcpy(dirfileres,optionfilefiname);
8934: strcpy(optfileres,"vpl");
1.199 brouard 8935: fprintf(ficgp,"set out \"graphmort.svg\"\n ");
1.126 brouard 8936: fprintf(ficgp,"set xlabel \"Age\"\n set ylabel \"Force of mortality (per year)\" \n ");
1.199 brouard 8937: fprintf(ficgp, "set ter svg size 640, 480\n set log y\n");
1.145 brouard 8938: /* fprintf(ficgp, "set size 0.65,0.65\n"); */
1.126 brouard 8939: fprintf(ficgp,"plot [%d:100] %lf*exp(%lf*(x-%d))",agegomp,p[1],p[2],agegomp);
8940:
8941: }
8942:
1.136 brouard 8943: int readdata(char datafile[], int firstobs, int lastobs, int *imax)
8944: {
1.126 brouard 8945:
1.136 brouard 8946: /*-------- data file ----------*/
8947: FILE *fic;
8948: char dummy[]=" ";
1.240 brouard 8949: int i=0, j=0, n=0, iv=0, v;
1.223 brouard 8950: int lstra;
1.136 brouard 8951: int linei, month, year,iout;
8952: char line[MAXLINE], linetmp[MAXLINE];
1.164 brouard 8953: char stra[MAXLINE], strb[MAXLINE];
1.136 brouard 8954: char *stratrunc;
1.223 brouard 8955:
1.240 brouard 8956: DummyV=ivector(1,NCOVMAX); /* 1 to 3 */
8957: FixedV=ivector(1,NCOVMAX); /* 1 to 3 */
1.126 brouard 8958:
1.240 brouard 8959: for(v=1; v <=ncovcol;v++){
8960: DummyV[v]=0;
8961: FixedV[v]=0;
8962: }
8963: for(v=ncovcol+1; v <=ncovcol+nqv;v++){
8964: DummyV[v]=1;
8965: FixedV[v]=0;
8966: }
8967: for(v=ncovcol+nqv+1; v <=ncovcol+nqv+ntv;v++){
8968: DummyV[v]=0;
8969: FixedV[v]=1;
8970: }
8971: for(v=ncovcol+nqv+ntv+1; v <=ncovcol+nqv+ntv+nqtv;v++){
8972: DummyV[v]=1;
8973: FixedV[v]=1;
8974: }
8975: for(v=1; v <=ncovcol+nqv+ntv+nqtv;v++){
8976: printf("Covariate type in the data: V%d, DummyV(V%d)=%d, FixedV(V%d)=%d\n",v,v,DummyV[v],v,FixedV[v]);
8977: 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]);
8978: }
1.126 brouard 8979:
1.136 brouard 8980: if((fic=fopen(datafile,"r"))==NULL) {
1.218 brouard 8981: printf("Problem while opening datafile: %s with errno='%s'\n", datafile,strerror(errno));fflush(stdout);
8982: fprintf(ficlog,"Problem while opening datafile: %s with errno='%s'\n", datafile,strerror(errno));fflush(ficlog);return 1;
1.136 brouard 8983: }
1.126 brouard 8984:
1.136 brouard 8985: i=1;
8986: linei=0;
8987: while ((fgets(line, MAXLINE, fic) != NULL) &&((i >= firstobs) && (i <=lastobs))) {
8988: linei=linei+1;
8989: for(j=strlen(line); j>=0;j--){ /* Untabifies line */
8990: if(line[j] == '\t')
8991: line[j] = ' ';
8992: }
8993: for(j=strlen(line)-1; (line[j]==' ')||(line[j]==10)||(line[j]==13);j--){
8994: ;
8995: };
8996: line[j+1]=0; /* Trims blanks at end of line */
8997: if(line[0]=='#'){
8998: fprintf(ficlog,"Comment line\n%s\n",line);
8999: printf("Comment line\n%s\n",line);
9000: continue;
9001: }
9002: trimbb(linetmp,line); /* Trims multiple blanks in line */
1.164 brouard 9003: strcpy(line, linetmp);
1.223 brouard 9004:
9005: /* Loops on waves */
9006: for (j=maxwav;j>=1;j--){
9007: for (iv=nqtv;iv>=1;iv--){ /* Loop on time varying quantitative variables */
1.238 brouard 9008: cutv(stra, strb, line, ' ');
9009: if(strb[0]=='.') { /* Missing value */
9010: lval=-1;
9011: cotqvar[j][iv][i]=-1; /* 0.0/0.0 */
9012: cotvar[j][ntv+iv][i]=-1; /* For performance reasons */
9013: if(isalpha(strb[1])) { /* .m or .d Really Missing value */
9014: 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);
9015: 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);
9016: return 1;
9017: }
9018: }else{
9019: errno=0;
9020: /* what_kind_of_number(strb); */
9021: dval=strtod(strb,&endptr);
9022: /* if( strb[0]=='\0' || (*endptr != '\0')){ */
9023: /* if(strb != endptr && *endptr == '\0') */
9024: /* dval=dlval; */
9025: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN)) */
9026: if( strb[0]=='\0' || (*endptr != '\0')){
9027: 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);
9028: 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);
9029: return 1;
9030: }
9031: cotqvar[j][iv][i]=dval;
9032: cotvar[j][ntv+iv][i]=dval;
9033: }
9034: strcpy(line,stra);
1.223 brouard 9035: }/* end loop ntqv */
1.225 brouard 9036:
1.223 brouard 9037: for (iv=ntv;iv>=1;iv--){ /* Loop on time varying dummies */
1.238 brouard 9038: cutv(stra, strb, line, ' ');
9039: if(strb[0]=='.') { /* Missing value */
9040: lval=-1;
9041: }else{
9042: errno=0;
9043: lval=strtol(strb,&endptr,10);
9044: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN))*/
9045: if( strb[0]=='\0' || (*endptr != '\0')){
9046: 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);
9047: 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);
9048: return 1;
9049: }
9050: }
9051: if(lval <-1 || lval >1){
9052: printf("Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.223 brouard 9053: Should be a value of %d(nth) covariate (0 should be the value for the reference and 1\n \
9054: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.238 brouard 9055: For example, for multinomial values like 1, 2 and 3,\n \
9056: build V1=0 V2=0 for the reference value (1),\n \
9057: V1=1 V2=0 for (2) \n \
1.223 brouard 9058: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.238 brouard 9059: output of IMaCh is often meaningless.\n \
1.223 brouard 9060: Exiting.\n",lval,linei, i,line,j);
1.238 brouard 9061: fprintf(ficlog,"Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.223 brouard 9062: Should be a value of %d(nth) covariate (0 should be the value for the reference and 1\n \
9063: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.238 brouard 9064: For example, for multinomial values like 1, 2 and 3,\n \
9065: build V1=0 V2=0 for the reference value (1),\n \
9066: V1=1 V2=0 for (2) \n \
1.223 brouard 9067: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.238 brouard 9068: output of IMaCh is often meaningless.\n \
1.223 brouard 9069: Exiting.\n",lval,linei, i,line,j);fflush(ficlog);
1.238 brouard 9070: return 1;
9071: }
9072: cotvar[j][iv][i]=(double)(lval);
9073: strcpy(line,stra);
1.223 brouard 9074: }/* end loop ntv */
1.225 brouard 9075:
1.223 brouard 9076: /* Statuses at wave */
1.137 brouard 9077: cutv(stra, strb, line, ' ');
1.223 brouard 9078: if(strb[0]=='.') { /* Missing value */
1.238 brouard 9079: lval=-1;
1.136 brouard 9080: }else{
1.238 brouard 9081: errno=0;
9082: lval=strtol(strb,&endptr,10);
9083: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN))*/
9084: if( strb[0]=='\0' || (*endptr != '\0')){
9085: 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);
9086: 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);
9087: return 1;
9088: }
1.136 brouard 9089: }
1.225 brouard 9090:
1.136 brouard 9091: s[j][i]=lval;
1.225 brouard 9092:
1.223 brouard 9093: /* Date of Interview */
1.136 brouard 9094: strcpy(line,stra);
9095: cutv(stra, strb,line,' ');
1.169 brouard 9096: if( (iout=sscanf(strb,"%d/%d",&month, &year)) != 0){
1.136 brouard 9097: }
1.169 brouard 9098: else if( (iout=sscanf(strb,"%s.",dummy)) != 0){
1.225 brouard 9099: month=99;
9100: year=9999;
1.136 brouard 9101: }else{
1.225 brouard 9102: 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);
9103: 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);
9104: return 1;
1.136 brouard 9105: }
9106: anint[j][i]= (double) year;
9107: mint[j][i]= (double)month;
9108: strcpy(line,stra);
1.223 brouard 9109: } /* End loop on waves */
1.225 brouard 9110:
1.223 brouard 9111: /* Date of death */
1.136 brouard 9112: cutv(stra, strb,line,' ');
1.169 brouard 9113: if( (iout=sscanf(strb,"%d/%d",&month, &year)) != 0){
1.136 brouard 9114: }
1.169 brouard 9115: else if( (iout=sscanf(strb,"%s.",dummy)) != 0){
1.136 brouard 9116: month=99;
9117: year=9999;
9118: }else{
1.141 brouard 9119: 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 9120: 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);
9121: return 1;
1.136 brouard 9122: }
9123: andc[i]=(double) year;
9124: moisdc[i]=(double) month;
9125: strcpy(line,stra);
9126:
1.223 brouard 9127: /* Date of birth */
1.136 brouard 9128: cutv(stra, strb,line,' ');
1.169 brouard 9129: if( (iout=sscanf(strb,"%d/%d",&month, &year)) != 0){
1.136 brouard 9130: }
1.169 brouard 9131: else if( (iout=sscanf(strb,"%s.", dummy)) != 0){
1.136 brouard 9132: month=99;
9133: year=9999;
9134: }else{
1.141 brouard 9135: 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);
9136: 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 9137: return 1;
1.136 brouard 9138: }
9139: if (year==9999) {
1.141 brouard 9140: 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);
9141: 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 9142: return 1;
9143:
1.136 brouard 9144: }
9145: annais[i]=(double)(year);
9146: moisnais[i]=(double)(month);
9147: strcpy(line,stra);
1.225 brouard 9148:
1.223 brouard 9149: /* Sample weight */
1.136 brouard 9150: cutv(stra, strb,line,' ');
9151: errno=0;
9152: dval=strtod(strb,&endptr);
9153: if( strb[0]=='\0' || (*endptr != '\0')){
1.141 brouard 9154: printf("Error reading data around '%f' at line number %d, \"%s\" for individual %d\nShould be a weight. Exiting.\n",dval, i,line,linei);
9155: 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 9156: fflush(ficlog);
9157: return 1;
9158: }
9159: weight[i]=dval;
9160: strcpy(line,stra);
1.225 brouard 9161:
1.223 brouard 9162: for (iv=nqv;iv>=1;iv--){ /* Loop on fixed quantitative variables */
9163: cutv(stra, strb, line, ' ');
9164: if(strb[0]=='.') { /* Missing value */
1.225 brouard 9165: lval=-1;
1.223 brouard 9166: }else{
1.225 brouard 9167: errno=0;
9168: /* what_kind_of_number(strb); */
9169: dval=strtod(strb,&endptr);
9170: /* if(strb != endptr && *endptr == '\0') */
9171: /* dval=dlval; */
9172: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN)) */
9173: if( strb[0]=='\0' || (*endptr != '\0')){
9174: 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);
9175: 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);
9176: return 1;
9177: }
9178: coqvar[iv][i]=dval;
1.226 brouard 9179: covar[ncovcol+iv][i]=dval; /* including qvar in standard covar for performance reasons */
1.223 brouard 9180: }
9181: strcpy(line,stra);
9182: }/* end loop nqv */
1.136 brouard 9183:
1.223 brouard 9184: /* Covariate values */
1.136 brouard 9185: for (j=ncovcol;j>=1;j--){
9186: cutv(stra, strb,line,' ');
1.223 brouard 9187: if(strb[0]=='.') { /* Missing covariate value */
1.225 brouard 9188: lval=-1;
1.136 brouard 9189: }else{
1.225 brouard 9190: errno=0;
9191: lval=strtol(strb,&endptr,10);
9192: if( strb[0]=='\0' || (*endptr != '\0')){
9193: 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);
9194: 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);
9195: return 1;
9196: }
1.136 brouard 9197: }
9198: if(lval <-1 || lval >1){
1.225 brouard 9199: printf("Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.136 brouard 9200: Should be a value of %d(nth) covariate (0 should be the value for the reference and 1\n \
9201: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.225 brouard 9202: For example, for multinomial values like 1, 2 and 3,\n \
9203: build V1=0 V2=0 for the reference value (1),\n \
9204: V1=1 V2=0 for (2) \n \
1.136 brouard 9205: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.225 brouard 9206: output of IMaCh is often meaningless.\n \
1.136 brouard 9207: Exiting.\n",lval,linei, i,line,j);
1.225 brouard 9208: fprintf(ficlog,"Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.136 brouard 9209: Should be a value of %d(nth) covariate (0 should be the value for the reference and 1\n \
9210: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.225 brouard 9211: For example, for multinomial values like 1, 2 and 3,\n \
9212: build V1=0 V2=0 for the reference value (1),\n \
9213: V1=1 V2=0 for (2) \n \
1.136 brouard 9214: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.225 brouard 9215: output of IMaCh is often meaningless.\n \
1.136 brouard 9216: Exiting.\n",lval,linei, i,line,j);fflush(ficlog);
1.225 brouard 9217: return 1;
1.136 brouard 9218: }
9219: covar[j][i]=(double)(lval);
9220: strcpy(line,stra);
9221: }
9222: lstra=strlen(stra);
1.225 brouard 9223:
1.136 brouard 9224: if(lstra > 9){ /* More than 2**32 or max of what printf can write with %ld */
9225: stratrunc = &(stra[lstra-9]);
9226: num[i]=atol(stratrunc);
9227: }
9228: else
9229: num[i]=atol(stra);
9230: /*if((s[2][i]==2) && (s[3][i]==-1)&&(s[4][i]==9)){
9231: 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;}*/
9232:
9233: i=i+1;
9234: } /* End loop reading data */
1.225 brouard 9235:
1.136 brouard 9236: *imax=i-1; /* Number of individuals */
9237: fclose(fic);
1.225 brouard 9238:
1.136 brouard 9239: return (0);
1.164 brouard 9240: /* endread: */
1.225 brouard 9241: printf("Exiting readdata: ");
9242: fclose(fic);
9243: return (1);
1.223 brouard 9244: }
1.126 brouard 9245:
1.234 brouard 9246: void removefirstspace(char **stri){/*, char stro[]) {*/
1.230 brouard 9247: char *p1 = *stri, *p2 = *stri;
1.235 brouard 9248: while (*p2 == ' ')
1.234 brouard 9249: p2++;
9250: /* while ((*p1++ = *p2++) !=0) */
9251: /* ; */
9252: /* do */
9253: /* while (*p2 == ' ') */
9254: /* p2++; */
9255: /* while (*p1++ == *p2++); */
9256: *stri=p2;
1.145 brouard 9257: }
9258:
1.235 brouard 9259: int decoderesult ( char resultline[], int nres)
1.230 brouard 9260: /**< This routine decode one result line and returns the combination # of dummy covariates only **/
9261: {
1.235 brouard 9262: int j=0, k=0, k1=0, k2=0, k3=0, k4=0, match=0, k2q=0, k3q=0, k4q=0;
1.230 brouard 9263: char resultsav[MAXLINE];
1.234 brouard 9264: int resultmodel[MAXLINE];
9265: int modelresult[MAXLINE];
1.230 brouard 9266: char stra[80], strb[80], strc[80], strd[80],stre[80];
9267:
1.234 brouard 9268: removefirstspace(&resultline);
1.233 brouard 9269: printf("decoderesult:%s\n",resultline);
1.230 brouard 9270:
9271: if (strstr(resultline,"v") !=0){
9272: printf("Error. 'v' must be in upper case 'V' result: %s ",resultline);
9273: fprintf(ficlog,"Error. 'v' must be in upper case result: %s ",resultline);fflush(ficlog);
9274: return 1;
9275: }
9276: trimbb(resultsav, resultline);
9277: if (strlen(resultsav) >1){
9278: j=nbocc(resultsav,'='); /**< j=Number of covariate values'=' */
9279: }
1.253 brouard 9280: if(j == 0){ /* Resultline but no = */
9281: TKresult[nres]=0; /* Combination for the nresult and the model */
9282: return (0);
9283: }
9284:
1.234 brouard 9285: if( j != cptcovs ){ /* Be careful if a variable is in a product but not single */
9286: 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);
9287: 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);
9288: }
9289: for(k=1; k<=j;k++){ /* Loop on any covariate of the result line */
9290: if(nbocc(resultsav,'=') >1){
9291: cutl(stra,strb,resultsav,' '); /* keeps in strb after the first ' '
9292: resultsav= V4=1 V5=25.1 V3=0 strb=V3=0 stra= V4=1 V5=25.1 */
9293: cutl(strc,strd,strb,'='); /* strb:V4=1 strc=1 strd=V4 */
9294: }else
9295: cutl(strc,strd,resultsav,'=');
1.230 brouard 9296: Tvalsel[k]=atof(strc); /* 1 */
1.234 brouard 9297:
1.230 brouard 9298: cutl(strc,stre,strd,'V'); /* strd='V4' strc=4 stre='V' */;
9299: Tvarsel[k]=atoi(strc);
9300: /* Typevarsel[k]=1; /\* 1 for age product *\/ */
9301: /* cptcovsel++; */
9302: if (nbocc(stra,'=') >0)
9303: strcpy(resultsav,stra); /* and analyzes it */
9304: }
1.235 brouard 9305: /* Checking for missing or useless values in comparison of current model needs */
1.236 brouard 9306: for(k1=1; k1<= cptcovt ;k1++){ /* model line V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
9307: if(Typevar[k1]==0){ /* Single covariate in model */
1.234 brouard 9308: match=0;
1.236 brouard 9309: for(k2=1; k2 <=j;k2++){/* result line V4=1 V5=24.1 V3=1 V2=8 V1=0 */
1.237 brouard 9310: if(Tvar[k1]==Tvarsel[k2]) {/* Tvar[1]=5 == Tvarsel[2]=5 */
1.236 brouard 9311: modelresult[k2]=k1;/* modelresult[2]=1 modelresult[1]=2 modelresult[3]=3 modelresult[6]=4 modelresult[9]=5 */
1.234 brouard 9312: match=1;
9313: break;
9314: }
9315: }
9316: if(match == 0){
9317: printf("Error in result line: %d value missing; result: %s, model=%s\n",k1, resultline, model);
9318: }
9319: }
9320: }
1.235 brouard 9321: /* Checking for missing or useless values in comparison of current model needs */
9322: for(k2=1; k2 <=j;k2++){ /* result line V4=1 V5=24.1 V3=1 V2=8 V1=0 */
1.234 brouard 9323: match=0;
1.235 brouard 9324: for(k1=1; k1<= cptcovt ;k1++){ /* model line V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
9325: if(Typevar[k1]==0){ /* Single */
1.237 brouard 9326: if(Tvar[k1]==Tvarsel[k2]) { /* Tvar[2]=4 == Tvarsel[1]=4 */
1.235 brouard 9327: resultmodel[k1]=k2; /* resultmodel[2]=1 resultmodel[1]=2 resultmodel[3]=3 resultmodel[6]=4 resultmodel[9]=5 */
1.234 brouard 9328: ++match;
9329: }
9330: }
9331: }
9332: if(match == 0){
9333: printf("Error in result line: %d value missing; result: %s, model=%s\n",k1, resultline, model);
9334: }else if(match > 1){
9335: printf("Error in result line: %d doubled; result: %s, model=%s\n",k2, resultline, model);
9336: }
9337: }
1.235 brouard 9338:
1.234 brouard 9339: /* We need to deduce which combination number is chosen and save quantitative values */
1.235 brouard 9340: /* model line V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
9341: /* result line V4=1 V5=25.1 V3=0 V2=8 V1=1 */
9342: /* should give a combination of dummy V4=1, V3=0, V1=1 => V4*2**(0) + V3*2**(1) + V1*2**(2) = 5 + (1offset) = 6*/
9343: /* result line V4=1 V5=24.1 V3=1 V2=8 V1=0 */
9344: /* should give a combination of dummy V4=1, V3=1, V1=0 => V4*2**(0) + V3*2**(1) + V1*2**(2) = 3 + (1offset) = 4*/
9345: /* 1 0 0 0 */
9346: /* 2 1 0 0 */
9347: /* 3 0 1 0 */
9348: /* 4 1 1 0 */ /* V4=1, V3=1, V1=0 */
9349: /* 5 0 0 1 */
9350: /* 6 1 0 1 */ /* V4=1, V3=0, V1=1 */
9351: /* 7 0 1 1 */
9352: /* 8 1 1 1 */
1.237 brouard 9353: /* V(Tvresult)=Tresult V4=1 V3=0 V1=1 Tresult[nres=1][2]=0 */
9354: /* V(Tvqresult)=Tqresult V5=25.1 V2=8 Tqresult[nres=1][1]=25.1 */
9355: /* V5*age V5 known which value for nres? */
9356: /* Tqinvresult[2]=8 Tqinvresult[1]=25.1 */
1.235 brouard 9357: for(k1=1, k=0, k4=0, k4q=0; k1 <=cptcovt;k1++){ /* model line */
9358: if( Dummy[k1]==0 && Typevar[k1]==0 ){ /* Single dummy */
1.237 brouard 9359: k3= resultmodel[k1]; /* resultmodel[2(V4)] = 1=k3 */
1.235 brouard 9360: k2=(int)Tvarsel[k3]; /* Tvarsel[resultmodel[2]]= Tvarsel[1] = 4=k2 */
9361: k+=Tvalsel[k3]*pow(2,k4); /* Tvalsel[1]=1 */
1.237 brouard 9362: Tresult[nres][k4+1]=Tvalsel[k3];/* Tresult[nres][1]=1(V4=1) Tresult[nres][2]=0(V3=0) */
9363: Tvresult[nres][k4+1]=(int)Tvarsel[k3];/* Tvresult[nres][1]=4 Tvresult[nres][3]=1 */
9364: Tinvresult[nres][(int)Tvarsel[k3]]=Tvalsel[k3]; /* Tinvresult[nres][4]=1 */
1.235 brouard 9365: printf("Decoderesult Dummy k=%d, V(k2=V%d)= Tvalsel[%d]=%d, 2**(%d)\n",k, k2, k3, (int)Tvalsel[k3], k4);
9366: k4++;;
9367: } else if( Dummy[k1]==1 && Typevar[k1]==0 ){ /* Single quantitative */
9368: k3q= resultmodel[k1]; /* resultmodel[2] = 1=k3 */
9369: k2q=(int)Tvarsel[k3q]; /* Tvarsel[resultmodel[2]]= Tvarsel[1] = 4=k2 */
1.237 brouard 9370: Tqresult[nres][k4q+1]=Tvalsel[k3q]; /* Tqresult[nres][1]=25.1 */
9371: Tvqresult[nres][k4q+1]=(int)Tvarsel[k3q]; /* Tvqresult[nres][1]=5 */
9372: Tqinvresult[nres][(int)Tvarsel[k3q]]=Tvalsel[k3q]; /* Tqinvresult[nres][5]=25.1 */
1.235 brouard 9373: printf("Decoderesult Quantitative nres=%d, V(k2q=V%d)= Tvalsel[%d]=%d, Tvarsel[%d]=%f\n",nres, k2q, k3q, Tvarsel[k3q], k3q, Tvalsel[k3q]);
9374: k4q++;;
9375: }
9376: }
1.234 brouard 9377:
1.235 brouard 9378: TKresult[nres]=++k; /* Combination for the nresult and the model */
1.230 brouard 9379: return (0);
9380: }
1.235 brouard 9381:
1.230 brouard 9382: int decodemodel( char model[], int lastobs)
9383: /**< This routine decodes the model and returns:
1.224 brouard 9384: * Model V1+V2+V3+V8+V7*V8+V5*V6+V8*age+V3*age+age*age
9385: * - nagesqr = 1 if age*age in the model, otherwise 0.
9386: * - cptcovt total number of covariates of the model nbocc(+)+1 = 8 excepting constant and age and age*age
9387: * - cptcovn or number of covariates k of the models excluding age*products =6 and age*age
9388: * - cptcovage number of covariates with age*products =2
9389: * - cptcovs number of simple covariates
9390: * - 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
9391: * which is a new column after the 9 (ncovcol) variables.
9392: * - if k is a product Vn*Vm covar[k][i] is filled with correct values for each individual
9393: * - Tprod[l] gives the kth covariates of the product Vn*Vm l=1 to cptcovprod-cptcovage
9394: * Tprod[1]@2 {5, 6}: position of first product V7*V8 is 5, and second V5*V6 is 6.
9395: * - Tvard[k] p Tvard[1][1]@4 {7, 8, 5, 6} for V7*V8 and V5*V6 .
9396: */
1.136 brouard 9397: {
1.238 brouard 9398: int i, j, k, ks, v;
1.227 brouard 9399: int j1, k1, k2, k3, k4;
1.136 brouard 9400: char modelsav[80];
1.145 brouard 9401: char stra[80], strb[80], strc[80], strd[80],stre[80];
1.187 brouard 9402: char *strpt;
1.136 brouard 9403:
1.145 brouard 9404: /*removespace(model);*/
1.136 brouard 9405: if (strlen(model) >1){ /* If there is at least 1 covariate */
1.145 brouard 9406: j=0, j1=0, k1=0, k2=-1, ks=0, cptcovn=0;
1.137 brouard 9407: if (strstr(model,"AGE") !=0){
1.192 brouard 9408: printf("Error. AGE must be in lower case 'age' model=1+age+%s. ",model);
9409: fprintf(ficlog,"Error. AGE must be in lower case model=1+age+%s. ",model);fflush(ficlog);
1.136 brouard 9410: return 1;
9411: }
1.141 brouard 9412: if (strstr(model,"v") !=0){
9413: printf("Error. 'v' must be in upper case 'V' model=%s ",model);
9414: fprintf(ficlog,"Error. 'v' must be in upper case model=%s ",model);fflush(ficlog);
9415: return 1;
9416: }
1.187 brouard 9417: strcpy(modelsav,model);
9418: if ((strpt=strstr(model,"age*age")) !=0){
9419: printf(" strpt=%s, model=%s\n",strpt, model);
9420: if(strpt != model){
1.234 brouard 9421: printf("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);
1.234 brouard 9424: fprintf(ficlog,"Error in model: 'model=%s'; 'age*age' should in first place before other covariates\n \
1.192 brouard 9425: 'model=1+age+age*age+V1.' or 'model=1+age+age*age+V1+V1*age.', please swap as well as \n \
1.187 brouard 9426: corresponding column of parameters.\n",model); fflush(ficlog);
1.234 brouard 9427: return 1;
1.225 brouard 9428: }
1.187 brouard 9429: nagesqr=1;
9430: if (strstr(model,"+age*age") !=0)
1.234 brouard 9431: substrchaine(modelsav, model, "+age*age");
1.187 brouard 9432: else if (strstr(model,"age*age+") !=0)
1.234 brouard 9433: substrchaine(modelsav, model, "age*age+");
1.187 brouard 9434: else
1.234 brouard 9435: substrchaine(modelsav, model, "age*age");
1.187 brouard 9436: }else
9437: nagesqr=0;
9438: if (strlen(modelsav) >1){
9439: j=nbocc(modelsav,'+'); /**< j=Number of '+' */
9440: j1=nbocc(modelsav,'*'); /**< j1=Number of '*' */
1.224 brouard 9441: cptcovs=j+1-j1; /**< Number of simple covariates V1+V1*age+V3 +V3*V4+age*age=> V1 + V3 =5-3=2 */
1.187 brouard 9442: cptcovt= j+1; /* Number of total covariates in the model, not including
1.225 brouard 9443: * cst, age and age*age
9444: * V1+V1*age+ V3 + V3*V4+age*age=> 3+1=4*/
9445: /* including age products which are counted in cptcovage.
9446: * but the covariates which are products must be treated
9447: * separately: ncovn=4- 2=2 (V1+V3). */
1.187 brouard 9448: cptcovprod=j1; /**< Number of products V1*V2 +v3*age = 2 */
9449: cptcovprodnoage=0; /**< Number of covariate products without age: V3*V4 =1 */
1.225 brouard 9450:
9451:
1.187 brouard 9452: /* Design
9453: * V1 V2 V3 V4 V5 V6 V7 V8 V9 Weight
9454: * < ncovcol=8 >
9455: * Model V2 + V1 + V3*age + V3 + V5*V6 + V7*V8 + V8*age + V8
9456: * k= 1 2 3 4 5 6 7 8
9457: * cptcovn number of covariates (not including constant and age ) = # of + plus 1 = 7+1=8
9458: * covar[k,i], value of kth covariate if not including age for individual i:
1.224 brouard 9459: * covar[1][i]= (V1), covar[4][i]=(V4), covar[8][i]=(V8)
9460: * Tvar[k] # of the kth covariate: Tvar[1]=2 Tvar[2]=1 Tvar[4]=3 Tvar[8]=8
1.187 brouard 9461: * if multiplied by age: V3*age Tvar[3=V3*age]=3 (V3) Tvar[7]=8 and
9462: * Tage[++cptcovage]=k
9463: * if products, new covar are created after ncovcol with k1
9464: * Tvar[k]=ncovcol+k1; # of the kth covariate product: Tvar[5]=ncovcol+1=10 Tvar[6]=ncovcol+1=11
9465: * Tprod[k1]=k; Tprod[1]=5 Tprod[2]= 6; gives the position of the k1th product
9466: * 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
9467: * Tvar[cptcovn+k2]=Tvard[k1][1];Tvar[cptcovn+k2+1]=Tvard[k1][2];
9468: * Tvar[8+1]=5;Tvar[8+2]=6;Tvar[8+3]=7;Tvar[8+4]=8 inverted
9469: * V1 V2 V3 V4 V5 V6 V7 V8 V9 V10 V11
9470: * < ncovcol=8 >
9471: * Model V2 + V1 + V3*age + V3 + V5*V6 + V7*V8 + V8*age + V8 d1 d1 d2 d2
9472: * k= 1 2 3 4 5 6 7 8 9 10 11 12
9473: * Tvar[k]= 2 1 3 3 10 11 8 8 5 6 7 8
9474: * p Tvar[1]@12={2, 1, 3, 3, 11, 10, 8, 8, 7, 8, 5, 6}
9475: * p Tprod[1]@2={ 6, 5}
9476: *p Tvard[1][1]@4= {7, 8, 5, 6}
9477: * covar[k][i]= V2 V1 ? V3 V5*V6? V7*V8? ? V8
9478: * cov[Tage[kk]+2]=covar[Tvar[Tage[kk]]][i]*cov[2];
9479: *How to reorganize?
9480: * Model V1 + V2 + V3 + V8 + V5*V6 + V7*V8 + V3*age + V8*age
9481: * Tvars {2, 1, 3, 3, 11, 10, 8, 8, 7, 8, 5, 6}
9482: * {2, 1, 4, 8, 5, 6, 3, 7}
9483: * Struct []
9484: */
1.225 brouard 9485:
1.187 brouard 9486: /* This loop fills the array Tvar from the string 'model'.*/
9487: /* j is the number of + signs in the model V1+V2+V3 j=2 i=3 to 1 */
9488: /* modelsav=V2+V1+V4+age*V3 strb=age*V3 stra=V2+V1+V4 */
9489: /* k=4 (age*V3) Tvar[k=4]= 3 (from V3) Tage[cptcovage=1]=4 */
9490: /* k=3 V4 Tvar[k=3]= 4 (from V4) */
9491: /* k=2 V1 Tvar[k=2]= 1 (from V1) */
9492: /* k=1 Tvar[1]=2 (from V2) */
9493: /* k=5 Tvar[5] */
9494: /* for (k=1; k<=cptcovn;k++) { */
1.198 brouard 9495: /* cov[2+k]=nbcode[Tvar[k]][codtabm(ij,Tvar[k])]; */
1.187 brouard 9496: /* } */
1.198 brouard 9497: /* for (k=1; k<=cptcovage;k++) cov[2+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,Tvar[Tage[k])]]*cov[2]; */
1.187 brouard 9498: /*
9499: * Treating invertedly V2+V1+V3*age+V2*V4 is as if written V2*V4 +V3*age + V1 + V2 */
1.227 brouard 9500: for(k=cptcovt; k>=1;k--){ /**< Number of covariates not including constant and age, neither age*age*/
9501: Tvar[k]=0; Tprod[k]=0; Tposprod[k]=0;
9502: }
1.187 brouard 9503: cptcovage=0;
9504: for(k=1; k<=cptcovt;k++){ /* Loop on total covariates of the model */
1.234 brouard 9505: cutl(stra,strb,modelsav,'+'); /* keeps in strb after the first '+'
1.225 brouard 9506: modelsav==V2+V1+V4+V3*age strb=V3*age stra=V2+V1+V4 */
1.234 brouard 9507: if (nbocc(modelsav,'+')==0) strcpy(strb,modelsav); /* and analyzes it */
9508: /* printf("i=%d a=%s b=%s sav=%s\n",i, stra,strb,modelsav);*/
9509: /*scanf("%d",i);*/
9510: if (strchr(strb,'*')) { /**< Model includes a product V2+V1+V4+V3*age strb=V3*age */
9511: cutl(strc,strd,strb,'*'); /**< strd*strc Vm*Vn: strb=V3*age(input) strc=age strd=V3 ; V3*V2 strc=V2, strd=V3 */
9512: if (strcmp(strc,"age")==0) { /**< Model includes age: Vn*age */
9513: /* covar is not filled and then is empty */
9514: cptcovprod--;
9515: cutl(stre,strb,strd,'V'); /* strd=V3(input): stre="3" */
9516: Tvar[k]=atoi(stre); /* V2+V1+V4+V3*age Tvar[4]=3 ; V1+V2*age Tvar[2]=2; V1+V1*age Tvar[2]=1 */
9517: Typevar[k]=1; /* 1 for age product */
9518: cptcovage++; /* Sums the number of covariates which include age as a product */
9519: Tage[cptcovage]=k; /* Tvar[4]=3, Tage[1] = 4 or V1+V1*age Tvar[2]=1, Tage[1]=2 */
9520: /*printf("stre=%s ", stre);*/
9521: } else if (strcmp(strd,"age")==0) { /* or age*Vn */
9522: cptcovprod--;
9523: cutl(stre,strb,strc,'V');
9524: Tvar[k]=atoi(stre);
9525: Typevar[k]=1; /* 1 for age product */
9526: cptcovage++;
9527: Tage[cptcovage]=k;
9528: } else { /* Age is not in the model product V2+V1+V1*V4+V3*age+V3*V2 strb=V3*V2*/
9529: /* loops on k1=1 (V3*V2) and k1=2 V4*V3 */
9530: cptcovn++;
9531: cptcovprodnoage++;k1++;
9532: cutl(stre,strb,strc,'V'); /* strc= Vn, stre is n; strb=V3*V2 stre=3 strc=*/
9533: Tvar[k]=ncovcol+nqv+ntv+nqtv+k1; /* For model-covariate k tells which data-covariate to use but
9534: because this model-covariate is a construction we invent a new column
9535: which is after existing variables ncovcol+nqv+ntv+nqtv + k1
9536: If already ncovcol=4 and model=V2+V1+V1*V4+age*V3+V3*V2
9537: Tvar[3=V1*V4]=4+1 Tvar[5=V3*V2]=4 + 2= 6, etc */
9538: Typevar[k]=2; /* 2 for double fixed dummy covariates */
9539: cutl(strc,strb,strd,'V'); /* strd was Vm, strc is m */
9540: Tprod[k1]=k; /* Tprod[1]=3(=V1*V4) for V2+V1+V1*V4+age*V3+V3*V2 */
9541: Tposprod[k]=k1; /* Tpsprod[3]=1, Tposprod[2]=5 */
9542: Tvard[k1][1] =atoi(strc); /* m 1 for V1*/
9543: Tvard[k1][2] =atoi(stre); /* n 4 for V4*/
9544: k2=k2+2; /* k2 is initialize to -1, We want to store the n and m in Vn*Vm at the end of Tvar */
9545: /* Tvar[cptcovt+k2]=Tvard[k1][1]; /\* Tvar[(cptcovt=4+k2=1)=5]= 1 (V1) *\/ */
9546: /* Tvar[cptcovt+k2+1]=Tvard[k1][2]; /\* Tvar[(cptcovt=4+(k2=1)+1)=6]= 4 (V4) *\/ */
1.225 brouard 9547: /*ncovcol=4 and model=V2+V1+V1*V4+age*V3+V3*V2, Tvar[3]=5, Tvar[4]=6, cptcovt=5 */
1.234 brouard 9548: /* 1 2 3 4 5 | Tvar[5+1)=1, Tvar[7]=2 */
9549: for (i=1; i<=lastobs;i++){
9550: /* Computes the new covariate which is a product of
9551: covar[n][i]* covar[m][i] and stores it at ncovol+k1 May not be defined */
9552: covar[ncovcol+k1][i]=covar[atoi(stre)][i]*covar[atoi(strc)][i];
9553: }
9554: } /* End age is not in the model */
9555: } /* End if model includes a product */
9556: else { /* no more sum */
9557: /*printf("d=%s c=%s b=%s\n", strd,strc,strb);*/
9558: /* scanf("%d",i);*/
9559: cutl(strd,strc,strb,'V');
9560: ks++; /**< Number of simple covariates dummy or quantitative, fixe or varying */
9561: cptcovn++; /** V4+V3+V5: V4 and V3 timevarying dummy covariates, V5 timevarying quantitative */
9562: Tvar[k]=atoi(strd);
9563: Typevar[k]=0; /* 0 for simple covariates */
9564: }
9565: strcpy(modelsav,stra); /* modelsav=V2+V1+V4 stra=V2+V1+V4 */
1.223 brouard 9566: /*printf("a=%s b=%s sav=%s\n", stra,strb,modelsav);
1.225 brouard 9567: scanf("%d",i);*/
1.187 brouard 9568: } /* end of loop + on total covariates */
9569: } /* end if strlen(modelsave == 0) age*age might exist */
9570: } /* end if strlen(model == 0) */
1.136 brouard 9571:
9572: /*The number n of Vn is stored in Tvar. cptcovage =number of age covariate. Tage gives the position of age. cptcovprod= number of products.
9573: If model=V1+V1*age then Tvar[1]=1 Tvar[2]=1 cptcovage=1 Tage[1]=2 cptcovprod=0*/
1.225 brouard 9574:
1.136 brouard 9575: /* printf("tvar1=%d tvar2=%d tvar3=%d cptcovage=%d Tage=%d",Tvar[1],Tvar[2],Tvar[3],cptcovage,Tage[1]);
1.225 brouard 9576: printf("cptcovprod=%d ", cptcovprod);
9577: fprintf(ficlog,"cptcovprod=%d ", cptcovprod);
9578: scanf("%d ",i);*/
9579:
9580:
1.230 brouard 9581: /* Until here, decodemodel knows only the grammar (simple, product, age*) of the model but not what kind
9582: of variable (dummy vs quantitative, fixed vs time varying) is behind. But we know the # of each. */
1.226 brouard 9583: /* ncovcol= 1, nqv=1 | ntv=2, nqtv= 1 = 5 possible variables data: 2 fixed 3, varying
9584: model= V5 + V4 +V3 + V4*V3 + V5*age + V2 + V1*V2 + V1*age + V5*age, V1 is not used saving its place
9585: k = 1 2 3 4 5 6 7 8 9
9586: Tvar[k]= 5 4 3 1+1+2+1+1=6 5 2 7 1 5
9587: Typevar[k]= 0 0 0 2 1 0 2 1 1
1.227 brouard 9588: Fixed[k] 1 1 1 1 3 0 0 or 2 2 3
9589: Dummy[k] 1 0 0 0 3 1 1 2 3
9590: Tmodelind[combination of covar]=k;
1.225 brouard 9591: */
9592: /* Dispatching between quantitative and time varying covariates */
1.226 brouard 9593: /* If Tvar[k] >ncovcol it is a product */
1.225 brouard 9594: /* 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 9595: /* Computing effective variables, ie used by the model, that is from the cptcovt variables */
1.227 brouard 9596: printf("Model=%s\n\
9597: Typevar: 0 for simple covariate (dummy, quantitative, fixed or varying), 1 for age product, 2 for product \n\
9598: Fixed[k] 0=fixed (product or simple), 1 varying, 2 fixed with age product, 3 varying with age product \n\
9599: 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);
9600: fprintf(ficlog,"Model=%s\n\
9601: Typevar: 0 for simple covariate (dummy, quantitative, fixed or varying), 1 for age product, 2 for product \n\
9602: Fixed[k] 0=fixed (product or simple), 1 varying, 2 fixed with age product, 3 varying with age product \n\
9603: 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 9604: for(k=1;k<=cptcovt; k++){ Fixed[k]=0; Dummy[k]=0;}
1.234 brouard 9605: 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 */
9606: if (Tvar[k] <=ncovcol && Typevar[k]==0 ){ /* Simple fixed dummy (<=ncovcol) covariates */
1.227 brouard 9607: Fixed[k]= 0;
9608: Dummy[k]= 0;
1.225 brouard 9609: ncoveff++;
1.232 brouard 9610: ncovf++;
1.234 brouard 9611: nsd++;
9612: modell[k].maintype= FTYPE;
9613: TvarsD[nsd]=Tvar[k];
9614: TvarsDind[nsd]=k;
9615: TvarF[ncovf]=Tvar[k];
9616: TvarFind[ncovf]=k;
9617: TvarFD[ncoveff]=Tvar[k]; /* TvarFD[1]=V1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
9618: TvarFDind[ncoveff]=k; /* TvarFDind[1]=9 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
9619: }else if( Tvar[k] <=ncovcol && Typevar[k]==2){ /* Product of fixed dummy (<=ncovcol) covariates */
9620: Fixed[k]= 0;
9621: Dummy[k]= 0;
9622: ncoveff++;
9623: ncovf++;
9624: modell[k].maintype= FTYPE;
9625: TvarF[ncovf]=Tvar[k];
9626: TvarFind[ncovf]=k;
1.230 brouard 9627: TvarFD[ncoveff]=Tvar[k]; /* TvarFD[1]=V1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1.231 brouard 9628: TvarFDind[ncoveff]=k; /* TvarFDind[1]=9 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1.240 brouard 9629: }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 9630: Fixed[k]= 0;
9631: Dummy[k]= 1;
1.230 brouard 9632: nqfveff++;
1.234 brouard 9633: modell[k].maintype= FTYPE;
9634: modell[k].subtype= FQ;
9635: nsq++;
9636: TvarsQ[nsq]=Tvar[k];
9637: TvarsQind[nsq]=k;
1.232 brouard 9638: ncovf++;
1.234 brouard 9639: TvarF[ncovf]=Tvar[k];
9640: TvarFind[ncovf]=k;
1.231 brouard 9641: 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 9642: 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 9643: }else if( Tvar[k] <=ncovcol+nqv+ntv && Typevar[k]==0){/* Only simple time varying dummy variables */
1.227 brouard 9644: Fixed[k]= 1;
9645: Dummy[k]= 0;
1.225 brouard 9646: ntveff++; /* Only simple time varying dummy variable */
1.234 brouard 9647: modell[k].maintype= VTYPE;
9648: modell[k].subtype= VD;
9649: nsd++;
9650: TvarsD[nsd]=Tvar[k];
9651: TvarsDind[nsd]=k;
9652: ncovv++; /* Only simple time varying variables */
9653: TvarV[ncovv]=Tvar[k];
1.242 brouard 9654: 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 9655: 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 */
9656: 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 9657: 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);
9658: printf("Quasi TmodelInvind[%d]=%d\n",k,Tvar[k]- ncovcol-nqv);
1.231 brouard 9659: }else if( Tvar[k] <=ncovcol+nqv+ntv+nqtv && Typevar[k]==0){ /* Only simple time varying quantitative variable V5*/
1.234 brouard 9660: Fixed[k]= 1;
9661: Dummy[k]= 1;
9662: nqtveff++;
9663: modell[k].maintype= VTYPE;
9664: modell[k].subtype= VQ;
9665: ncovv++; /* Only simple time varying variables */
9666: nsq++;
9667: TvarsQ[nsq]=Tvar[k];
9668: TvarsQind[nsq]=k;
9669: TvarV[ncovv]=Tvar[k];
1.242 brouard 9670: 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 9671: 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 */
9672: 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 9673: TmodelInvQind[nqtveff]=Tvar[k]- ncovcol-nqv-ntv;/* Only simple time varying quantitative variable */
9674: /* Tmodeliqind[k]=nqtveff;/\* Only simple time varying quantitative variable *\/ */
9675: 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 9676: printf("Quasi TmodelInvQind[%d]=%d\n",k,Tvar[k]- ncovcol-nqv-ntv);
1.227 brouard 9677: }else if (Typevar[k] == 1) { /* product with age */
1.234 brouard 9678: ncova++;
9679: TvarA[ncova]=Tvar[k];
9680: TvarAind[ncova]=k;
1.231 brouard 9681: if (Tvar[k] <=ncovcol ){ /* Product age with fixed dummy covariatee */
1.240 brouard 9682: Fixed[k]= 2;
9683: Dummy[k]= 2;
9684: modell[k].maintype= ATYPE;
9685: modell[k].subtype= APFD;
9686: /* ncoveff++; */
1.227 brouard 9687: }else if( Tvar[k] <=ncovcol+nqv) { /* Remind that product Vn*Vm are added in k*/
1.240 brouard 9688: Fixed[k]= 2;
9689: Dummy[k]= 3;
9690: modell[k].maintype= ATYPE;
9691: modell[k].subtype= APFQ; /* Product age * fixed quantitative */
9692: /* nqfveff++; /\* Only simple fixed quantitative variable *\/ */
1.227 brouard 9693: }else if( Tvar[k] <=ncovcol+nqv+ntv ){
1.240 brouard 9694: Fixed[k]= 3;
9695: Dummy[k]= 2;
9696: modell[k].maintype= ATYPE;
9697: modell[k].subtype= APVD; /* Product age * varying dummy */
9698: /* ntveff++; /\* Only simple time varying dummy variable *\/ */
1.227 brouard 9699: }else if( Tvar[k] <=ncovcol+nqv+ntv+nqtv){
1.240 brouard 9700: Fixed[k]= 3;
9701: Dummy[k]= 3;
9702: modell[k].maintype= ATYPE;
9703: modell[k].subtype= APVQ; /* Product age * varying quantitative */
9704: /* nqtveff++;/\* Only simple time varying quantitative variable *\/ */
1.227 brouard 9705: }
9706: }else if (Typevar[k] == 2) { /* product without age */
9707: k1=Tposprod[k];
9708: if(Tvard[k1][1] <=ncovcol){
1.240 brouard 9709: if(Tvard[k1][2] <=ncovcol){
9710: Fixed[k]= 1;
9711: Dummy[k]= 0;
9712: modell[k].maintype= FTYPE;
9713: modell[k].subtype= FPDD; /* Product fixed dummy * fixed dummy */
9714: ncovf++; /* Fixed variables without age */
9715: TvarF[ncovf]=Tvar[k];
9716: TvarFind[ncovf]=k;
9717: }else if(Tvard[k1][2] <=ncovcol+nqv){
9718: Fixed[k]= 0; /* or 2 ?*/
9719: Dummy[k]= 1;
9720: modell[k].maintype= FTYPE;
9721: modell[k].subtype= FPDQ; /* Product fixed dummy * fixed quantitative */
9722: ncovf++; /* Varying variables without age */
9723: TvarF[ncovf]=Tvar[k];
9724: TvarFind[ncovf]=k;
9725: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){
9726: Fixed[k]= 1;
9727: Dummy[k]= 0;
9728: modell[k].maintype= VTYPE;
9729: modell[k].subtype= VPDD; /* Product fixed dummy * varying dummy */
9730: ncovv++; /* Varying variables without age */
9731: TvarV[ncovv]=Tvar[k];
9732: TvarVind[ncovv]=k;
9733: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){
9734: Fixed[k]= 1;
9735: Dummy[k]= 1;
9736: modell[k].maintype= VTYPE;
9737: modell[k].subtype= VPDQ; /* Product fixed dummy * varying quantitative */
9738: ncovv++; /* Varying variables without age */
9739: TvarV[ncovv]=Tvar[k];
9740: TvarVind[ncovv]=k;
9741: }
1.227 brouard 9742: }else if(Tvard[k1][1] <=ncovcol+nqv){
1.240 brouard 9743: if(Tvard[k1][2] <=ncovcol){
9744: Fixed[k]= 0; /* or 2 ?*/
9745: Dummy[k]= 1;
9746: modell[k].maintype= FTYPE;
9747: modell[k].subtype= FPDQ; /* Product fixed quantitative * fixed dummy */
9748: ncovf++; /* Fixed variables without age */
9749: TvarF[ncovf]=Tvar[k];
9750: TvarFind[ncovf]=k;
9751: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){
9752: Fixed[k]= 1;
9753: Dummy[k]= 1;
9754: modell[k].maintype= VTYPE;
9755: modell[k].subtype= VPDQ; /* Product fixed quantitative * varying dummy */
9756: ncovv++; /* Varying variables without age */
9757: TvarV[ncovv]=Tvar[k];
9758: TvarVind[ncovv]=k;
9759: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){
9760: Fixed[k]= 1;
9761: Dummy[k]= 1;
9762: modell[k].maintype= VTYPE;
9763: modell[k].subtype= VPQQ; /* Product fixed quantitative * varying quantitative */
9764: ncovv++; /* Varying variables without age */
9765: TvarV[ncovv]=Tvar[k];
9766: TvarVind[ncovv]=k;
9767: ncovv++; /* Varying variables without age */
9768: TvarV[ncovv]=Tvar[k];
9769: TvarVind[ncovv]=k;
9770: }
1.227 brouard 9771: }else if(Tvard[k1][1] <=ncovcol+nqv+ntv){
1.240 brouard 9772: if(Tvard[k1][2] <=ncovcol){
9773: Fixed[k]= 1;
9774: Dummy[k]= 1;
9775: modell[k].maintype= VTYPE;
9776: modell[k].subtype= VPDD; /* Product time varying dummy * fixed dummy */
9777: ncovv++; /* Varying variables without age */
9778: TvarV[ncovv]=Tvar[k];
9779: TvarVind[ncovv]=k;
9780: }else if(Tvard[k1][2] <=ncovcol+nqv){
9781: Fixed[k]= 1;
9782: Dummy[k]= 1;
9783: modell[k].maintype= VTYPE;
9784: modell[k].subtype= VPDQ; /* Product time varying dummy * fixed quantitative */
9785: ncovv++; /* Varying variables without age */
9786: TvarV[ncovv]=Tvar[k];
9787: TvarVind[ncovv]=k;
9788: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){
9789: Fixed[k]= 1;
9790: Dummy[k]= 0;
9791: modell[k].maintype= VTYPE;
9792: modell[k].subtype= VPDD; /* Product time varying dummy * time varying dummy */
9793: ncovv++; /* Varying variables without age */
9794: TvarV[ncovv]=Tvar[k];
9795: TvarVind[ncovv]=k;
9796: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){
9797: Fixed[k]= 1;
9798: Dummy[k]= 1;
9799: modell[k].maintype= VTYPE;
9800: modell[k].subtype= VPDQ; /* Product time varying dummy * time varying quantitative */
9801: ncovv++; /* Varying variables without age */
9802: TvarV[ncovv]=Tvar[k];
9803: TvarVind[ncovv]=k;
9804: }
1.227 brouard 9805: }else if(Tvard[k1][1] <=ncovcol+nqv+ntv+nqtv){
1.240 brouard 9806: if(Tvard[k1][2] <=ncovcol){
9807: Fixed[k]= 1;
9808: Dummy[k]= 1;
9809: modell[k].maintype= VTYPE;
9810: modell[k].subtype= VPDQ; /* Product time varying quantitative * fixed dummy */
9811: ncovv++; /* Varying variables without age */
9812: TvarV[ncovv]=Tvar[k];
9813: TvarVind[ncovv]=k;
9814: }else if(Tvard[k1][2] <=ncovcol+nqv){
9815: Fixed[k]= 1;
9816: Dummy[k]= 1;
9817: modell[k].maintype= VTYPE;
9818: modell[k].subtype= VPQQ; /* Product time varying quantitative * fixed quantitative */
9819: ncovv++; /* Varying variables without age */
9820: TvarV[ncovv]=Tvar[k];
9821: TvarVind[ncovv]=k;
9822: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){
9823: Fixed[k]= 1;
9824: Dummy[k]= 1;
9825: modell[k].maintype= VTYPE;
9826: modell[k].subtype= VPDQ; /* Product time varying quantitative * time varying dummy */
9827: ncovv++; /* Varying variables without age */
9828: TvarV[ncovv]=Tvar[k];
9829: TvarVind[ncovv]=k;
9830: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){
9831: Fixed[k]= 1;
9832: Dummy[k]= 1;
9833: modell[k].maintype= VTYPE;
9834: modell[k].subtype= VPQQ; /* Product time varying quantitative * time varying quantitative */
9835: ncovv++; /* Varying variables without age */
9836: TvarV[ncovv]=Tvar[k];
9837: TvarVind[ncovv]=k;
9838: }
1.227 brouard 9839: }else{
1.240 brouard 9840: printf("Error unknown type of covariate: Tvard[%d][1]=%d,Tvard[%d][2]=%d\n",k1,Tvard[k1][1],k1,Tvard[k1][2]);
9841: fprintf(ficlog,"Error unknown type of covariate: Tvard[%d][1]=%d,Tvard[%d][2]=%d\n",k1,Tvard[k1][1],k1,Tvard[k1][2]);
9842: } /*end k1*/
1.225 brouard 9843: }else{
1.226 brouard 9844: printf("Error, current version can't treat for performance reasons, Tvar[%d]=%d, Typevar[%d]=%d\n", k, Tvar[k], k, Typevar[k]);
9845: 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 9846: }
1.227 brouard 9847: 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 9848: printf(" modell[%d].maintype=%d, modell[%d].subtype=%d\n",k,modell[k].maintype,k,modell[k].subtype);
1.227 brouard 9849: 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]);
9850: }
9851: /* Searching for doublons in the model */
9852: for(k1=1; k1<= cptcovt;k1++){
9853: for(k2=1; k2 <k1;k2++){
9854: if((Typevar[k1]==Typevar[k2]) && (Fixed[Tvar[k1]]==Fixed[Tvar[k2]]) && (Dummy[Tvar[k1]]==Dummy[Tvar[k2]] )){
1.234 brouard 9855: if((Typevar[k1] == 0 || Typevar[k1] == 1)){ /* Simple or age product */
9856: if(Tvar[k1]==Tvar[k2]){
9857: 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]]);
9858: 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);
9859: return(1);
9860: }
9861: }else if (Typevar[k1] ==2){
9862: k3=Tposprod[k1];
9863: k4=Tposprod[k2];
9864: 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])) ){
9865: 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]]);
9866: 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);
9867: return(1);
9868: }
9869: }
1.227 brouard 9870: }
9871: }
1.225 brouard 9872: }
9873: printf("ncoveff=%d, nqfveff=%d, ntveff=%d, nqtveff=%d, cptcovn=%d\n",ncoveff,nqfveff,ntveff,nqtveff,cptcovn);
9874: fprintf(ficlog,"ncoveff=%d, nqfveff=%d, ntveff=%d, nqtveff=%d, cptcovn=%d\n",ncoveff,nqfveff,ntveff,nqtveff,cptcovn);
1.234 brouard 9875: printf("ncovf=%d, ncovv=%d, ncova=%d, nsd=%d, nsq=%d\n",ncovf,ncovv,ncova,nsd,nsq);
9876: fprintf(ficlog,"ncovf=%d, ncovv=%d, ncova=%d, nsd=%d, nsq=%d\n",ncovf,ncovv,ncova,nsd, nsq);
1.137 brouard 9877: return (0); /* with covar[new additional covariate if product] and Tage if age */
1.164 brouard 9878: /*endread:*/
1.225 brouard 9879: printf("Exiting decodemodel: ");
9880: return (1);
1.136 brouard 9881: }
9882:
1.169 brouard 9883: int calandcheckages(int imx, int maxwav, double *agemin, double *agemax, int *nberr, int *nbwarn )
1.248 brouard 9884: {/* Check ages at death */
1.136 brouard 9885: int i, m;
1.218 brouard 9886: int firstone=0;
9887:
1.136 brouard 9888: for (i=1; i<=imx; i++) {
9889: for(m=2; (m<= maxwav); m++) {
9890: if (((int)mint[m][i]== 99) && (s[m][i] <= nlstate)){
9891: anint[m][i]=9999;
1.216 brouard 9892: if (s[m][i] != -2) /* Keeping initial status of unknown vital status */
9893: s[m][i]=-1;
1.136 brouard 9894: }
9895: if((int)moisdc[i]==99 && (int)andc[i]==9999 && s[m][i]>nlstate){
1.260 brouard 9896: *nberr = *nberr + 1;
1.218 brouard 9897: if(firstone == 0){
9898: firstone=1;
1.260 brouard 9899: 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 9900: }
1.262 brouard 9901: 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 9902: s[m][i]=-1; /* Droping the death status */
1.136 brouard 9903: }
9904: if((int)moisdc[i]==99 && (int)andc[i]!=9999 && s[m][i]>nlstate){
1.169 brouard 9905: (*nberr)++;
1.259 brouard 9906: 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 9907: 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 9908: s[m][i]=-2; /* We prefer to skip it (and to skip it in version 0.8a1 too */
1.136 brouard 9909: }
9910: }
9911: }
9912:
9913: for (i=1; i<=imx; i++) {
9914: agedc[i]=(moisdc[i]/12.+andc[i])-(moisnais[i]/12.+annais[i]);
9915: for(m=firstpass; (m<= lastpass); m++){
1.214 brouard 9916: 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 9917: if (s[m][i] >= nlstate+1) {
1.169 brouard 9918: if(agedc[i]>0){
9919: if((int)moisdc[i]!=99 && (int)andc[i]!=9999){
1.136 brouard 9920: agev[m][i]=agedc[i];
1.214 brouard 9921: /*if(moisdc[i]==99 && andc[i]==9999) s[m][i]=-1;*/
1.169 brouard 9922: }else {
1.136 brouard 9923: if ((int)andc[i]!=9999){
9924: nbwarn++;
9925: printf("Warning negative age at death: %ld line:%d\n",num[i],i);
9926: fprintf(ficlog,"Warning negative age at death: %ld line:%d\n",num[i],i);
9927: agev[m][i]=-1;
9928: }
9929: }
1.169 brouard 9930: } /* agedc > 0 */
1.214 brouard 9931: } /* end if */
1.136 brouard 9932: else if(s[m][i] !=9){ /* Standard case, age in fractional
9933: years but with the precision of a month */
9934: agev[m][i]=(mint[m][i]/12.+1./24.+anint[m][i])-(moisnais[i]/12.+1./24.+annais[i]);
9935: if((int)mint[m][i]==99 || (int)anint[m][i]==9999)
9936: agev[m][i]=1;
9937: else if(agev[m][i] < *agemin){
9938: *agemin=agev[m][i];
9939: printf(" Min anint[%d][%d]=%.2f annais[%d]=%.2f, agemin=%.2f\n",m,i,anint[m][i], i,annais[i], *agemin);
9940: }
9941: else if(agev[m][i] >*agemax){
9942: *agemax=agev[m][i];
1.156 brouard 9943: /* printf(" Max anint[%d][%d]=%.0f annais[%d]=%.0f, agemax=%.2f\n",m,i,anint[m][i], i,annais[i], *agemax);*/
1.136 brouard 9944: }
9945: /*agev[m][i]=anint[m][i]-annais[i];*/
9946: /* agev[m][i] = age[i]+2*m;*/
1.214 brouard 9947: } /* en if 9*/
1.136 brouard 9948: else { /* =9 */
1.214 brouard 9949: /* printf("Debug num[%d]=%ld s[%d][%d]=%d\n",i,num[i], m,i, s[m][i]); */
1.136 brouard 9950: agev[m][i]=1;
9951: s[m][i]=-1;
9952: }
9953: }
1.214 brouard 9954: else if(s[m][i]==0) /*= 0 Unknown */
1.136 brouard 9955: agev[m][i]=1;
1.214 brouard 9956: else{
9957: printf("Warning, num[%d]=%ld, s[%d][%d]=%d\n", i, num[i], m, i,s[m][i]);
9958: fprintf(ficlog, "Warning, num[%d]=%ld, s[%d][%d]=%d\n", i, num[i], m, i,s[m][i]);
9959: agev[m][i]=0;
9960: }
9961: } /* End for lastpass */
9962: }
1.136 brouard 9963:
9964: for (i=1; i<=imx; i++) {
9965: for(m=firstpass; (m<=lastpass); m++){
9966: if (s[m][i] > (nlstate+ndeath)) {
1.169 brouard 9967: (*nberr)++;
1.136 brouard 9968: 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);
9969: 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);
9970: return 1;
9971: }
9972: }
9973: }
9974:
9975: /*for (i=1; i<=imx; i++){
9976: for (m=firstpass; (m<lastpass); m++){
9977: printf("%ld %d %.lf %d %d\n", num[i],(covar[1][i]),agev[m][i],s[m][i],s[m+1][i]);
9978: }
9979:
9980: }*/
9981:
9982:
1.139 brouard 9983: printf("Total number of individuals= %d, Agemin = %.2f, Agemax= %.2f\n\n", imx, *agemin, *agemax);
9984: fprintf(ficlog,"Total number of individuals= %d, Agemin = %.2f, Agemax= %.2f\n\n", imx, *agemin, *agemax);
1.136 brouard 9985:
9986: return (0);
1.164 brouard 9987: /* endread:*/
1.136 brouard 9988: printf("Exiting calandcheckages: ");
9989: return (1);
9990: }
9991:
1.172 brouard 9992: #if defined(_MSC_VER)
9993: /*printf("Visual C++ compiler: %s \n;", _MSC_FULL_VER);*/
9994: /*fprintf(ficlog, "Visual C++ compiler: %s \n;", _MSC_FULL_VER);*/
9995: //#include "stdafx.h"
9996: //#include <stdio.h>
9997: //#include <tchar.h>
9998: //#include <windows.h>
9999: //#include <iostream>
10000: typedef BOOL(WINAPI *LPFN_ISWOW64PROCESS) (HANDLE, PBOOL);
10001:
10002: LPFN_ISWOW64PROCESS fnIsWow64Process;
10003:
10004: BOOL IsWow64()
10005: {
10006: BOOL bIsWow64 = FALSE;
10007:
10008: //typedef BOOL (APIENTRY *LPFN_ISWOW64PROCESS)
10009: // (HANDLE, PBOOL);
10010:
10011: //LPFN_ISWOW64PROCESS fnIsWow64Process;
10012:
10013: HMODULE module = GetModuleHandle(_T("kernel32"));
10014: const char funcName[] = "IsWow64Process";
10015: fnIsWow64Process = (LPFN_ISWOW64PROCESS)
10016: GetProcAddress(module, funcName);
10017:
10018: if (NULL != fnIsWow64Process)
10019: {
10020: if (!fnIsWow64Process(GetCurrentProcess(),
10021: &bIsWow64))
10022: //throw std::exception("Unknown error");
10023: printf("Unknown error\n");
10024: }
10025: return bIsWow64 != FALSE;
10026: }
10027: #endif
1.177 brouard 10028:
1.191 brouard 10029: void syscompilerinfo(int logged)
1.167 brouard 10030: {
10031: /* #include "syscompilerinfo.h"*/
1.185 brouard 10032: /* command line Intel compiler 32bit windows, XP compatible:*/
10033: /* /GS /W3 /Gy
10034: /Zc:wchar_t /Zi /O2 /Fd"Release\vc120.pdb" /D "WIN32" /D "NDEBUG" /D
10035: "_CONSOLE" /D "_LIB" /D "_USING_V110_SDK71_" /D "_UNICODE" /D
10036: "UNICODE" /Qipo /Zc:forScope /Gd /Oi /MT /Fa"Release\" /EHsc /nologo
1.186 brouard 10037: /Fo"Release\" /Qprof-dir "Release\" /Fp"Release\IMaCh.pch"
10038: */
10039: /* 64 bits */
1.185 brouard 10040: /*
10041: /GS /W3 /Gy
10042: /Zc:wchar_t /Zi /O2 /Fd"x64\Release\vc120.pdb" /D "WIN32" /D "NDEBUG"
10043: /D "_CONSOLE" /D "_LIB" /D "_UNICODE" /D "UNICODE" /Qipo /Zc:forScope
10044: /Oi /MD /Fa"x64\Release\" /EHsc /nologo /Fo"x64\Release\" /Qprof-dir
10045: "x64\Release\" /Fp"x64\Release\IMaCh.pch" */
10046: /* Optimization are useless and O3 is slower than O2 */
10047: /*
10048: /GS /W3 /Gy /Zc:wchar_t /Zi /O3 /Fd"x64\Release\vc120.pdb" /D "WIN32"
10049: /D "NDEBUG" /D "_CONSOLE" /D "_LIB" /D "_UNICODE" /D "UNICODE" /Qipo
10050: /Zc:forScope /Oi /MD /Fa"x64\Release\" /EHsc /nologo /Qparallel
10051: /Fo"x64\Release\" /Qprof-dir "x64\Release\" /Fp"x64\Release\IMaCh.pch"
10052: */
1.186 brouard 10053: /* Link is */ /* /OUT:"visual studio
1.185 brouard 10054: 2013\Projects\IMaCh\Release\IMaCh.exe" /MANIFEST /NXCOMPAT
10055: /PDB:"visual studio
10056: 2013\Projects\IMaCh\Release\IMaCh.pdb" /DYNAMICBASE
10057: "kernel32.lib" "user32.lib" "gdi32.lib" "winspool.lib"
10058: "comdlg32.lib" "advapi32.lib" "shell32.lib" "ole32.lib"
10059: "oleaut32.lib" "uuid.lib" "odbc32.lib" "odbccp32.lib"
10060: /MACHINE:X86 /OPT:REF /SAFESEH /INCREMENTAL:NO
10061: /SUBSYSTEM:CONSOLE",5.01" /MANIFESTUAC:"level='asInvoker'
10062: uiAccess='false'"
10063: /ManifestFile:"Release\IMaCh.exe.intermediate.manifest" /OPT:ICF
10064: /NOLOGO /TLBID:1
10065: */
1.177 brouard 10066: #if defined __INTEL_COMPILER
1.178 brouard 10067: #if defined(__GNUC__)
10068: struct utsname sysInfo; /* For Intel on Linux and OS/X */
10069: #endif
1.177 brouard 10070: #elif defined(__GNUC__)
1.179 brouard 10071: #ifndef __APPLE__
1.174 brouard 10072: #include <gnu/libc-version.h> /* Only on gnu */
1.179 brouard 10073: #endif
1.177 brouard 10074: struct utsname sysInfo;
1.178 brouard 10075: int cross = CROSS;
10076: if (cross){
10077: printf("Cross-");
1.191 brouard 10078: if(logged) fprintf(ficlog, "Cross-");
1.178 brouard 10079: }
1.174 brouard 10080: #endif
10081:
1.171 brouard 10082: #include <stdint.h>
1.178 brouard 10083:
1.191 brouard 10084: printf("Compiled with:");if(logged)fprintf(ficlog,"Compiled with:");
1.169 brouard 10085: #if defined(__clang__)
1.191 brouard 10086: printf(" Clang/LLVM");if(logged)fprintf(ficlog," Clang/LLVM"); /* Clang/LLVM. ---------------------------------------------- */
1.169 brouard 10087: #endif
10088: #if defined(__ICC) || defined(__INTEL_COMPILER)
1.191 brouard 10089: printf(" Intel ICC/ICPC");if(logged)fprintf(ficlog," Intel ICC/ICPC");/* Intel ICC/ICPC. ------------------------------------------ */
1.169 brouard 10090: #endif
10091: #if defined(__GNUC__) || defined(__GNUG__)
1.191 brouard 10092: printf(" GNU GCC/G++");if(logged)fprintf(ficlog," GNU GCC/G++");/* GNU GCC/G++. --------------------------------------------- */
1.169 brouard 10093: #endif
10094: #if defined(__HP_cc) || defined(__HP_aCC)
1.191 brouard 10095: printf(" Hewlett-Packard C/aC++");if(logged)fprintf(fcilog," Hewlett-Packard C/aC++"); /* Hewlett-Packard C/aC++. ---------------------------------- */
1.169 brouard 10096: #endif
10097: #if defined(__IBMC__) || defined(__IBMCPP__)
1.191 brouard 10098: printf(" IBM XL C/C++"); if(logged) fprintf(ficlog," IBM XL C/C++");/* IBM XL C/C++. -------------------------------------------- */
1.169 brouard 10099: #endif
10100: #if defined(_MSC_VER)
1.191 brouard 10101: printf(" Microsoft Visual Studio");if(logged)fprintf(ficlog," Microsoft Visual Studio");/* Microsoft Visual Studio. --------------------------------- */
1.169 brouard 10102: #endif
10103: #if defined(__PGI)
1.191 brouard 10104: printf(" Portland Group PGCC/PGCPP");if(logged) fprintf(ficlog," Portland Group PGCC/PGCPP");/* Portland Group PGCC/PGCPP. ------------------------------- */
1.169 brouard 10105: #endif
10106: #if defined(__SUNPRO_C) || defined(__SUNPRO_CC)
1.191 brouard 10107: printf(" Oracle Solaris Studio");if(logged)fprintf(ficlog," Oracle Solaris Studio\n");/* Oracle Solaris Studio. ----------------------------------- */
1.167 brouard 10108: #endif
1.191 brouard 10109: printf(" for "); if (logged) fprintf(ficlog, " for ");
1.169 brouard 10110:
1.167 brouard 10111: // http://stackoverflow.com/questions/4605842/how-to-identify-platform-compiler-from-preprocessor-macros
10112: #ifdef _WIN32 // note the underscore: without it, it's not msdn official!
10113: // Windows (x64 and x86)
1.191 brouard 10114: printf("Windows (x64 and x86) ");if(logged) fprintf(ficlog,"Windows (x64 and x86) ");
1.167 brouard 10115: #elif __unix__ // all unices, not all compilers
10116: // Unix
1.191 brouard 10117: printf("Unix ");if(logged) fprintf(ficlog,"Unix ");
1.167 brouard 10118: #elif __linux__
10119: // linux
1.191 brouard 10120: printf("linux ");if(logged) fprintf(ficlog,"linux ");
1.167 brouard 10121: #elif __APPLE__
1.174 brouard 10122: // Mac OS, not sure if this is covered by __posix__ and/or __unix__ though..
1.191 brouard 10123: printf("Mac OS ");if(logged) fprintf(ficlog,"Mac OS ");
1.167 brouard 10124: #endif
10125:
10126: /* __MINGW32__ */
10127: /* __CYGWIN__ */
10128: /* __MINGW64__ */
10129: // http://msdn.microsoft.com/en-us/library/b0084kay.aspx
10130: /* _MSC_VER //the Visual C++ compiler is 17.00.51106.1, the _MSC_VER macro evaluates to 1700. Type cl /? */
10131: /* _MSC_FULL_VER //the Visual C++ compiler is 15.00.20706.01, the _MSC_FULL_VER macro evaluates to 150020706 */
10132: /* _WIN64 // Defined for applications for Win64. */
10133: /* _M_X64 // Defined for compilations that target x64 processors. */
10134: /* _DEBUG // Defined when you compile with /LDd, /MDd, and /MTd. */
1.171 brouard 10135:
1.167 brouard 10136: #if UINTPTR_MAX == 0xffffffff
1.191 brouard 10137: printf(" 32-bit"); if(logged) fprintf(ficlog," 32-bit");/* 32-bit */
1.167 brouard 10138: #elif UINTPTR_MAX == 0xffffffffffffffff
1.191 brouard 10139: printf(" 64-bit"); if(logged) fprintf(ficlog," 64-bit");/* 64-bit */
1.167 brouard 10140: #else
1.191 brouard 10141: printf(" wtf-bit"); if(logged) fprintf(ficlog," wtf-bit");/* wtf */
1.167 brouard 10142: #endif
10143:
1.169 brouard 10144: #if defined(__GNUC__)
10145: # if defined(__GNUC_PATCHLEVEL__)
10146: # define __GNUC_VERSION__ (__GNUC__ * 10000 \
10147: + __GNUC_MINOR__ * 100 \
10148: + __GNUC_PATCHLEVEL__)
10149: # else
10150: # define __GNUC_VERSION__ (__GNUC__ * 10000 \
10151: + __GNUC_MINOR__ * 100)
10152: # endif
1.174 brouard 10153: printf(" using GNU C version %d.\n", __GNUC_VERSION__);
1.191 brouard 10154: if(logged) fprintf(ficlog, " using GNU C version %d.\n", __GNUC_VERSION__);
1.176 brouard 10155:
10156: if (uname(&sysInfo) != -1) {
10157: printf("Running on: %s %s %s %s %s\n",sysInfo.sysname, sysInfo.nodename, sysInfo.release, sysInfo.version, sysInfo.machine);
1.191 brouard 10158: 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 10159: }
10160: else
10161: perror("uname() error");
1.179 brouard 10162: //#ifndef __INTEL_COMPILER
10163: #if !defined (__INTEL_COMPILER) && !defined(__APPLE__)
1.174 brouard 10164: printf("GNU libc version: %s\n", gnu_get_libc_version());
1.191 brouard 10165: if(logged) fprintf(ficlog,"GNU libc version: %s\n", gnu_get_libc_version());
1.177 brouard 10166: #endif
1.169 brouard 10167: #endif
1.172 brouard 10168:
10169: // void main()
10170: // {
1.169 brouard 10171: #if defined(_MSC_VER)
1.174 brouard 10172: if (IsWow64()){
1.191 brouard 10173: printf("\nThe program (probably compiled for 32bit) is running under WOW64 (64bit) emulation.\n");
10174: if (logged) fprintf(ficlog, "\nThe program (probably compiled for 32bit) is running under WOW64 (64bit) emulation.\n");
1.174 brouard 10175: }
10176: else{
1.191 brouard 10177: printf("\nThe program is not running under WOW64 (i.e probably on a 64bit Windows).\n");
10178: if (logged) fprintf(ficlog, "\nThe programm is not running under WOW64 (i.e probably on a 64bit Windows).\n");
1.174 brouard 10179: }
1.172 brouard 10180: // printf("\nPress Enter to continue...");
10181: // getchar();
10182: // }
10183:
1.169 brouard 10184: #endif
10185:
1.167 brouard 10186:
1.219 brouard 10187: }
1.136 brouard 10188:
1.219 brouard 10189: int prevalence_limit(double *p, double **prlim, double ageminpar, double agemaxpar, double ftolpl, int *ncvyearp){
1.180 brouard 10190: /*--------------- Prevalence limit (period or stable prevalence) --------------*/
1.235 brouard 10191: int i, j, k, i1, k4=0, nres=0 ;
1.202 brouard 10192: /* double ftolpl = 1.e-10; */
1.180 brouard 10193: double age, agebase, agelim;
1.203 brouard 10194: double tot;
1.180 brouard 10195:
1.202 brouard 10196: strcpy(filerespl,"PL_");
10197: strcat(filerespl,fileresu);
10198: if((ficrespl=fopen(filerespl,"w"))==NULL) {
10199: printf("Problem with period (stable) prevalence resultfile: %s\n", filerespl);return 1;
10200: fprintf(ficlog,"Problem with period (stable) prevalence resultfile: %s\n", filerespl);return 1;
10201: }
1.227 brouard 10202: printf("\nComputing period (stable) prevalence: result on file '%s' \n", filerespl);
10203: fprintf(ficlog,"\nComputing period (stable) prevalence: result on file '%s' \n", filerespl);
1.202 brouard 10204: pstamp(ficrespl);
1.203 brouard 10205: fprintf(ficrespl,"# Period (stable) prevalence. Precision given by ftolpl=%g \n", ftolpl);
1.202 brouard 10206: fprintf(ficrespl,"#Age ");
10207: for(i=1; i<=nlstate;i++) fprintf(ficrespl,"%d-%d ",i,i);
10208: fprintf(ficrespl,"\n");
1.180 brouard 10209:
1.219 brouard 10210: /* prlim=matrix(1,nlstate,1,nlstate);*/ /* back in main */
1.180 brouard 10211:
1.219 brouard 10212: agebase=ageminpar;
10213: agelim=agemaxpar;
1.180 brouard 10214:
1.227 brouard 10215: /* i1=pow(2,ncoveff); */
1.234 brouard 10216: i1=pow(2,cptcoveff); /* Number of combination of dummy covariates */
1.219 brouard 10217: if (cptcovn < 1){i1=1;}
1.180 brouard 10218:
1.238 brouard 10219: for(k=1; k<=i1;k++){ /* For each combination k of dummy covariates in the model */
10220: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 10221: if(i1 != 1 && TKresult[nres]!= k)
1.238 brouard 10222: continue;
1.235 brouard 10223:
1.238 brouard 10224: /* for(cptcov=1,k=0;cptcov<=i1;cptcov++){ */
10225: /* for(cptcov=1,k=0;cptcov<=1;cptcov++){ */
10226: //for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){
10227: /* k=k+1; */
10228: /* to clean */
10229: //printf("cptcov=%d cptcod=%d codtab=%d\n",cptcov, cptcod,codtabm(cptcod,cptcov));
10230: fprintf(ficrespl,"#******");
10231: printf("#******");
10232: fprintf(ficlog,"#******");
10233: for(j=1;j<=cptcoveff ;j++) {/* all covariates */
10234: fprintf(ficrespl," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]); /* Here problem for varying dummy*/
10235: printf(" V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10236: fprintf(ficlog," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10237: }
10238: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
10239: printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
10240: fprintf(ficrespl," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
10241: fprintf(ficlog," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
10242: }
10243: fprintf(ficrespl,"******\n");
10244: printf("******\n");
10245: fprintf(ficlog,"******\n");
10246: if(invalidvarcomb[k]){
10247: printf("\nCombination (%d) ignored because no case \n",k);
10248: fprintf(ficrespl,"#Combination (%d) ignored because no case \n",k);
10249: fprintf(ficlog,"\nCombination (%d) ignored because no case \n",k);
10250: continue;
10251: }
1.219 brouard 10252:
1.238 brouard 10253: fprintf(ficrespl,"#Age ");
10254: for(j=1;j<=cptcoveff;j++) {
10255: fprintf(ficrespl,"V%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10256: }
10257: for(i=1; i<=nlstate;i++) fprintf(ficrespl," %d-%d ",i,i);
10258: fprintf(ficrespl,"Total Years_to_converge\n");
1.227 brouard 10259:
1.238 brouard 10260: for (age=agebase; age<=agelim; age++){
10261: /* for (age=agebase; age<=agebase; age++){ */
10262: prevalim(prlim, nlstate, p, age, oldm, savm, ftolpl, ncvyearp, k, nres);
10263: fprintf(ficrespl,"%.0f ",age );
10264: for(j=1;j<=cptcoveff;j++)
10265: fprintf(ficrespl,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10266: tot=0.;
10267: for(i=1; i<=nlstate;i++){
10268: tot += prlim[i][i];
10269: fprintf(ficrespl," %.5f", prlim[i][i]);
10270: }
10271: fprintf(ficrespl," %.3f %d\n", tot, *ncvyearp);
10272: } /* Age */
10273: /* was end of cptcod */
10274: } /* cptcov */
10275: } /* nres */
1.219 brouard 10276: return 0;
1.180 brouard 10277: }
10278:
1.218 brouard 10279: 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){
10280: /*--------------- Back Prevalence limit (period or stable prevalence) --------------*/
10281:
10282: /* Computes the back prevalence limit for any combination of covariate values
10283: * at any age between ageminpar and agemaxpar
10284: */
1.235 brouard 10285: int i, j, k, i1, nres=0 ;
1.217 brouard 10286: /* double ftolpl = 1.e-10; */
10287: double age, agebase, agelim;
10288: double tot;
1.218 brouard 10289: /* double ***mobaverage; */
10290: /* double **dnewm, **doldm, **dsavm; /\* for use *\/ */
1.217 brouard 10291:
10292: strcpy(fileresplb,"PLB_");
10293: strcat(fileresplb,fileresu);
10294: if((ficresplb=fopen(fileresplb,"w"))==NULL) {
10295: printf("Problem with period (stable) back prevalence resultfile: %s\n", fileresplb);return 1;
10296: fprintf(ficlog,"Problem with period (stable) back prevalence resultfile: %s\n", fileresplb);return 1;
10297: }
10298: printf("Computing period (stable) back prevalence: result on file '%s' \n", fileresplb);
10299: fprintf(ficlog,"Computing period (stable) back prevalence: result on file '%s' \n", fileresplb);
10300: pstamp(ficresplb);
10301: fprintf(ficresplb,"# Period (stable) back prevalence. Precision given by ftolpl=%g \n", ftolpl);
10302: fprintf(ficresplb,"#Age ");
10303: for(i=1; i<=nlstate;i++) fprintf(ficresplb,"%d-%d ",i,i);
10304: fprintf(ficresplb,"\n");
10305:
1.218 brouard 10306:
10307: /* prlim=matrix(1,nlstate,1,nlstate);*/ /* back in main */
10308:
10309: agebase=ageminpar;
10310: agelim=agemaxpar;
10311:
10312:
1.227 brouard 10313: i1=pow(2,cptcoveff);
1.218 brouard 10314: if (cptcovn < 1){i1=1;}
1.227 brouard 10315:
1.238 brouard 10316: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
10317: for(k=1; k<=i1;k++){ /* For any combination of dummy covariates, fixed and varying */
1.253 brouard 10318: if(i1 != 1 && TKresult[nres]!= k)
1.238 brouard 10319: continue;
10320: //printf("cptcov=%d cptcod=%d codtab=%d\n",cptcov, cptcod,codtabm(cptcod,cptcov));
10321: fprintf(ficresplb,"#******");
10322: printf("#******");
10323: fprintf(ficlog,"#******");
10324: for(j=1;j<=cptcoveff ;j++) {/* all covariates */
10325: fprintf(ficresplb," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10326: printf(" V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10327: fprintf(ficlog," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10328: }
10329: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
10330: printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
10331: fprintf(ficresplb," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
10332: fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
10333: }
10334: fprintf(ficresplb,"******\n");
10335: printf("******\n");
10336: fprintf(ficlog,"******\n");
10337: if(invalidvarcomb[k]){
10338: printf("\nCombination (%d) ignored because no cases \n",k);
10339: fprintf(ficresplb,"#Combination (%d) ignored because no cases \n",k);
10340: fprintf(ficlog,"\nCombination (%d) ignored because no cases \n",k);
10341: continue;
10342: }
1.218 brouard 10343:
1.238 brouard 10344: fprintf(ficresplb,"#Age ");
10345: for(j=1;j<=cptcoveff;j++) {
10346: fprintf(ficresplb,"V%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10347: }
10348: for(i=1; i<=nlstate;i++) fprintf(ficresplb," %d-%d ",i,i);
10349: fprintf(ficresplb,"Total Years_to_converge\n");
1.218 brouard 10350:
10351:
1.238 brouard 10352: for (age=agebase; age<=agelim; age++){
10353: /* for (age=agebase; age<=agebase; age++){ */
10354: if(mobilavproj > 0){
10355: /* bprevalim(bprlim, mobaverage, nlstate, p, age, ageminpar, agemaxpar, oldm, savm, doldm, dsavm, ftolpl, ncvyearp, k); */
10356: /* bprevalim(bprlim, mobaverage, nlstate, p, age, oldm, savm, dnewm, doldm, dsavm, ftolpl, ncvyearp, k); */
1.242 brouard 10357: bprevalim(bprlim, mobaverage, nlstate, p, age, ftolpl, ncvyearp, k, nres);
1.238 brouard 10358: }else if (mobilavproj == 0){
10359: 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);
10360: 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);
10361: exit(1);
10362: }else{
10363: /* bprevalim(bprlim, probs, nlstate, p, age, oldm, savm, dnewm, doldm, dsavm, ftolpl, ncvyearp, k); */
1.242 brouard 10364: bprevalim(bprlim, probs, nlstate, p, age, ftolpl, ncvyearp, k,nres);
1.266 brouard 10365: /* printf("TOTOT\n"); */
10366: /* exit(1); */
1.238 brouard 10367: }
10368: fprintf(ficresplb,"%.0f ",age );
10369: for(j=1;j<=cptcoveff;j++)
10370: fprintf(ficresplb,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10371: tot=0.;
10372: for(i=1; i<=nlstate;i++){
10373: tot += bprlim[i][i];
10374: fprintf(ficresplb," %.5f", bprlim[i][i]);
10375: }
10376: fprintf(ficresplb," %.3f %d\n", tot, *ncvyearp);
10377: } /* Age */
10378: /* was end of cptcod */
1.255 brouard 10379: /*fprintf(ficresplb,"\n");*/ /* Seems to be necessary for gnuplot only if two result lines and no covariate. */
1.238 brouard 10380: } /* end of any combination */
10381: } /* end of nres */
1.218 brouard 10382: /* hBijx(p, bage, fage); */
10383: /* fclose(ficrespijb); */
10384:
10385: return 0;
1.217 brouard 10386: }
1.218 brouard 10387:
1.180 brouard 10388: int hPijx(double *p, int bage, int fage){
10389: /*------------- h Pij x at various ages ------------*/
10390:
10391: int stepsize;
10392: int agelim;
10393: int hstepm;
10394: int nhstepm;
1.235 brouard 10395: int h, i, i1, j, k, k4, nres=0;
1.180 brouard 10396:
10397: double agedeb;
10398: double ***p3mat;
10399:
1.201 brouard 10400: strcpy(filerespij,"PIJ_"); strcat(filerespij,fileresu);
1.180 brouard 10401: if((ficrespij=fopen(filerespij,"w"))==NULL) {
10402: printf("Problem with Pij resultfile: %s\n", filerespij); return 1;
10403: fprintf(ficlog,"Problem with Pij resultfile: %s\n", filerespij); return 1;
10404: }
10405: printf("Computing pij: result on file '%s' \n", filerespij);
10406: fprintf(ficlog,"Computing pij: result on file '%s' \n", filerespij);
10407:
10408: stepsize=(int) (stepm+YEARM-1)/YEARM;
10409: /*if (stepm<=24) stepsize=2;*/
10410:
10411: agelim=AGESUP;
10412: hstepm=stepsize*YEARM; /* Every year of age */
10413: hstepm=hstepm/stepm; /* Typically 2 years, = 2/6 months = 4 */
1.218 brouard 10414:
1.180 brouard 10415: /* hstepm=1; aff par mois*/
10416: pstamp(ficrespij);
10417: fprintf(ficrespij,"#****** h Pij x Probability to be in state j at age x+h being in i at x ");
1.227 brouard 10418: i1= pow(2,cptcoveff);
1.218 brouard 10419: /* for(cptcov=1,k=0;cptcov<=i1;cptcov++){ */
10420: /* /\*for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){*\/ */
10421: /* k=k+1; */
1.235 brouard 10422: for(nres=1; nres <= nresult; nres++) /* For each resultline */
10423: for(k=1; k<=i1;k++){
1.253 brouard 10424: if(i1 != 1 && TKresult[nres]!= k)
1.235 brouard 10425: continue;
1.183 brouard 10426: fprintf(ficrespij,"\n#****** ");
1.227 brouard 10427: for(j=1;j<=cptcoveff;j++)
1.198 brouard 10428: fprintf(ficrespij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
1.235 brouard 10429: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
10430: printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
10431: fprintf(ficrespij," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
10432: }
1.183 brouard 10433: fprintf(ficrespij,"******\n");
10434:
10435: for (agedeb=fage; agedeb>=bage; agedeb--){ /* If stepm=6 months */
10436: nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
10437: nhstepm = nhstepm/hstepm; /* Typically 40/4=10 */
10438:
10439: /* nhstepm=nhstepm*YEARM; aff par mois*/
1.180 brouard 10440:
1.183 brouard 10441: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
10442: oldm=oldms;savm=savms;
1.235 brouard 10443: hpxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k, nres);
1.183 brouard 10444: fprintf(ficrespij,"# Cov Agex agex+h hpijx with i,j=");
10445: for(i=1; i<=nlstate;i++)
10446: for(j=1; j<=nlstate+ndeath;j++)
10447: fprintf(ficrespij," %1d-%1d",i,j);
10448: fprintf(ficrespij,"\n");
10449: for (h=0; h<=nhstepm; h++){
10450: /*agedebphstep = agedeb + h*hstepm/YEARM*stepm;*/
10451: fprintf(ficrespij,"%d %3.f %3.f",k, agedeb, agedeb + h*hstepm/YEARM*stepm );
1.180 brouard 10452: for(i=1; i<=nlstate;i++)
10453: for(j=1; j<=nlstate+ndeath;j++)
1.183 brouard 10454: fprintf(ficrespij," %.5f", p3mat[i][j][h]);
1.180 brouard 10455: fprintf(ficrespij,"\n");
10456: }
1.183 brouard 10457: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
10458: fprintf(ficrespij,"\n");
10459: }
1.180 brouard 10460: /*}*/
10461: }
1.218 brouard 10462: return 0;
1.180 brouard 10463: }
1.218 brouard 10464:
10465: int hBijx(double *p, int bage, int fage, double ***prevacurrent){
1.217 brouard 10466: /*------------- h Bij x at various ages ------------*/
10467:
10468: int stepsize;
1.218 brouard 10469: /* int agelim; */
10470: int ageminl;
1.217 brouard 10471: int hstepm;
10472: int nhstepm;
1.238 brouard 10473: int h, i, i1, j, k, nres;
1.218 brouard 10474:
1.217 brouard 10475: double agedeb;
10476: double ***p3mat;
1.218 brouard 10477:
10478: strcpy(filerespijb,"PIJB_"); strcat(filerespijb,fileresu);
10479: if((ficrespijb=fopen(filerespijb,"w"))==NULL) {
10480: printf("Problem with Pij back resultfile: %s\n", filerespijb); return 1;
10481: fprintf(ficlog,"Problem with Pij back resultfile: %s\n", filerespijb); return 1;
10482: }
10483: printf("Computing pij back: result on file '%s' \n", filerespijb);
10484: fprintf(ficlog,"Computing pij back: result on file '%s' \n", filerespijb);
10485:
10486: stepsize=(int) (stepm+YEARM-1)/YEARM;
10487: /*if (stepm<=24) stepsize=2;*/
1.217 brouard 10488:
1.218 brouard 10489: /* agelim=AGESUP; */
10490: ageminl=30;
10491: hstepm=stepsize*YEARM; /* Every year of age */
10492: hstepm=hstepm/stepm; /* Typically 2 years, = 2/6 months = 4 */
10493:
10494: /* hstepm=1; aff par mois*/
10495: pstamp(ficrespijb);
1.255 brouard 10496: 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 10497: i1= pow(2,cptcoveff);
1.218 brouard 10498: /* for(cptcov=1,k=0;cptcov<=i1;cptcov++){ */
10499: /* /\*for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){*\/ */
10500: /* k=k+1; */
1.238 brouard 10501: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
10502: for(k=1; k<=i1;k++){ /* For any combination of dummy covariates, fixed and varying */
1.253 brouard 10503: if(i1 != 1 && TKresult[nres]!= k)
1.238 brouard 10504: continue;
10505: fprintf(ficrespijb,"\n#****** ");
10506: for(j=1;j<=cptcoveff;j++)
10507: fprintf(ficrespijb,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10508: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
10509: fprintf(ficrespijb," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
10510: }
10511: fprintf(ficrespijb,"******\n");
1.264 brouard 10512: if(invalidvarcomb[k]){ /* Is it necessary here? */
1.238 brouard 10513: fprintf(ficrespijb,"\n#Combination (%d) ignored because no cases \n",k);
10514: continue;
10515: }
10516:
10517: /* for (agedeb=fage; agedeb>=bage; agedeb--){ /\* If stepm=6 months *\/ */
10518: for (agedeb=bage; agedeb<=fage; agedeb++){ /* If stepm=6 months and estepm=24 (2 years) */
10519: /* nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); /\* Typically 20 years = 20*12/6=40 *\/ */
10520: nhstepm=(int) rint((agedeb-ageminl)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
10521: nhstepm = nhstepm/hstepm; /* Typically 40/4=10, because estepm=24 stepm=6 => hstepm=24/6=4 */
10522:
10523: /* nhstepm=nhstepm*YEARM; aff par mois*/
10524:
1.266 brouard 10525: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); /* We can't have it at an upper level because of nhstepm */
10526: /* and memory limitations if stepm is small */
10527:
1.238 brouard 10528: /* oldm=oldms;savm=savms; */
10529: /* hbxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k); */
1.267 brouard 10530: hbxij(p3mat,nhstepm,agedeb,hstepm,p,prevacurrent,nlstate,stepm, k, nres);
1.238 brouard 10531: /* hbxij(p3mat,nhstepm,agedeb,hstepm,p,prevacurrent,nlstate,stepm,oldm,savm, dnewm, doldm, dsavm, k); */
1.255 brouard 10532: fprintf(ficrespijb,"# Cov Agex agex-h hbijx with i,j=");
1.217 brouard 10533: for(i=1; i<=nlstate;i++)
10534: for(j=1; j<=nlstate+ndeath;j++)
1.238 brouard 10535: fprintf(ficrespijb," %1d-%1d",i,j);
1.217 brouard 10536: fprintf(ficrespijb,"\n");
1.238 brouard 10537: for (h=0; h<=nhstepm; h++){
10538: /*agedebphstep = agedeb + h*hstepm/YEARM*stepm;*/
10539: fprintf(ficrespijb,"%d %3.f %3.f",k, agedeb, agedeb - h*hstepm/YEARM*stepm );
10540: /* fprintf(ficrespijb,"%d %3.f %3.f",k, agedeb, agedeb + h*hstepm/YEARM*stepm ); */
10541: for(i=1; i<=nlstate;i++)
10542: for(j=1; j<=nlstate+ndeath;j++)
10543: fprintf(ficrespijb," %.5f", p3mat[i][j][h]);
10544: fprintf(ficrespijb,"\n");
10545: }
10546: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
10547: fprintf(ficrespijb,"\n");
10548: } /* end age deb */
10549: } /* end combination */
10550: } /* end nres */
1.218 brouard 10551: return 0;
10552: } /* hBijx */
1.217 brouard 10553:
1.180 brouard 10554:
1.136 brouard 10555: /***********************************************/
10556: /**************** Main Program *****************/
10557: /***********************************************/
10558:
10559: int main(int argc, char *argv[])
10560: {
10561: #ifdef GSL
10562: const gsl_multimin_fminimizer_type *T;
10563: size_t iteri = 0, it;
10564: int rval = GSL_CONTINUE;
10565: int status = GSL_SUCCESS;
10566: double ssval;
10567: #endif
10568: int movingaverage(double ***probs, double bage,double fage, double ***mobaverage, int mobilav);
1.164 brouard 10569: int i,j, k, n=MAXN,iter=0,m,size=100, cptcod;
1.209 brouard 10570: int ncvyear=0; /* Number of years needed for the period prevalence to converge */
1.164 brouard 10571: int jj, ll, li, lj, lk;
1.136 brouard 10572: int numlinepar=0; /* Current linenumber of parameter file */
1.197 brouard 10573: int num_filled;
1.136 brouard 10574: int itimes;
10575: int NDIM=2;
10576: int vpopbased=0;
1.235 brouard 10577: int nres=0;
1.258 brouard 10578: int endishere=0;
1.136 brouard 10579:
1.164 brouard 10580: char ca[32], cb[32];
1.136 brouard 10581: /* FILE *fichtm; *//* Html File */
10582: /* FILE *ficgp;*/ /*Gnuplot File */
10583: struct stat info;
1.191 brouard 10584: double agedeb=0.;
1.194 brouard 10585:
10586: double ageminpar=AGEOVERFLOW,agemin=AGEOVERFLOW, agemaxpar=-AGEOVERFLOW, agemax=-AGEOVERFLOW;
1.219 brouard 10587: double ageminout=-AGEOVERFLOW,agemaxout=AGEOVERFLOW; /* Smaller Age range redefined after movingaverage */
1.136 brouard 10588:
1.165 brouard 10589: double fret;
1.191 brouard 10590: double dum=0.; /* Dummy variable */
1.136 brouard 10591: double ***p3mat;
1.218 brouard 10592: /* double ***mobaverage; */
1.164 brouard 10593:
10594: char line[MAXLINE];
1.197 brouard 10595: char path[MAXLINE],pathc[MAXLINE],pathcd[MAXLINE],pathtot[MAXLINE];
10596:
1.234 brouard 10597: char modeltemp[MAXLINE];
1.230 brouard 10598: char resultline[MAXLINE];
10599:
1.136 brouard 10600: char pathr[MAXLINE], pathimach[MAXLINE];
1.164 brouard 10601: char *tok, *val; /* pathtot */
1.136 brouard 10602: int firstobs=1, lastobs=10;
1.195 brouard 10603: int c, h , cpt, c2;
1.191 brouard 10604: int jl=0;
10605: int i1, j1, jk, stepsize=0;
1.194 brouard 10606: int count=0;
10607:
1.164 brouard 10608: int *tab;
1.136 brouard 10609: int mobilavproj=0 , prevfcast=0 ; /* moving average of prev, If prevfcast=1 prevalence projection */
1.217 brouard 10610: int backcast=0;
1.136 brouard 10611: int mobilav=0,popforecast=0;
1.191 brouard 10612: int hstepm=0, nhstepm=0;
1.136 brouard 10613: int agemortsup;
10614: float sumlpop=0.;
10615: double jprev1=1, mprev1=1,anprev1=2000,jprev2=1, mprev2=1,anprev2=2000;
10616: double jpyram=1, mpyram=1,anpyram=2000,jpyram1=1, mpyram1=1,anpyram1=2000;
10617:
1.191 brouard 10618: double bage=0, fage=110., age, agelim=0., agebase=0.;
1.136 brouard 10619: double ftolpl=FTOL;
10620: double **prlim;
1.217 brouard 10621: double **bprlim;
1.136 brouard 10622: double ***param; /* Matrix of parameters */
1.251 brouard 10623: double ***paramstart; /* Matrix of starting parameter values */
10624: double *p, *pstart; /* p=param[1][1] pstart is for starting values guessed by freqsummary */
1.136 brouard 10625: double **matcov; /* Matrix of covariance */
1.203 brouard 10626: double **hess; /* Hessian matrix */
1.136 brouard 10627: double ***delti3; /* Scale */
10628: double *delti; /* Scale */
10629: double ***eij, ***vareij;
10630: double **varpl; /* Variances of prevalence limits by age */
1.269 brouard 10631:
1.136 brouard 10632: double *epj, vepp;
1.164 brouard 10633:
1.136 brouard 10634: double dateprev1, dateprev2,jproj1=1,mproj1=1,anproj1=2000,jproj2=1,mproj2=1,anproj2=2000;
1.217 brouard 10635: double jback1=1,mback1=1,anback1=2000,jback2=1,mback2=1,anback2=2000;
10636:
1.136 brouard 10637: double **ximort;
1.145 brouard 10638: char *alph[]={"a","a","b","c","d","e"}, str[4]="1234";
1.136 brouard 10639: int *dcwave;
10640:
1.164 brouard 10641: char z[1]="c";
1.136 brouard 10642:
10643: /*char *strt;*/
10644: char strtend[80];
1.126 brouard 10645:
1.164 brouard 10646:
1.126 brouard 10647: /* setlocale (LC_ALL, ""); */
10648: /* bindtextdomain (PACKAGE, LOCALEDIR); */
10649: /* textdomain (PACKAGE); */
10650: /* setlocale (LC_CTYPE, ""); */
10651: /* setlocale (LC_MESSAGES, ""); */
10652:
10653: /* gettimeofday(&start_time, (struct timezone*)0); */ /* at first time */
1.157 brouard 10654: rstart_time = time(NULL);
10655: /* (void) gettimeofday(&start_time,&tzp);*/
10656: start_time = *localtime(&rstart_time);
1.126 brouard 10657: curr_time=start_time;
1.157 brouard 10658: /*tml = *localtime(&start_time.tm_sec);*/
10659: /* strcpy(strstart,asctime(&tml)); */
10660: strcpy(strstart,asctime(&start_time));
1.126 brouard 10661:
10662: /* printf("Localtime (at start)=%s",strstart); */
1.157 brouard 10663: /* tp.tm_sec = tp.tm_sec +86400; */
10664: /* tm = *localtime(&start_time.tm_sec); */
1.126 brouard 10665: /* tmg.tm_year=tmg.tm_year +dsign*dyear; */
10666: /* tmg.tm_mon=tmg.tm_mon +dsign*dmonth; */
10667: /* tmg.tm_hour=tmg.tm_hour + 1; */
1.157 brouard 10668: /* tp.tm_sec = mktime(&tmg); */
1.126 brouard 10669: /* strt=asctime(&tmg); */
10670: /* printf("Time(after) =%s",strstart); */
10671: /* (void) time (&time_value);
10672: * printf("time=%d,t-=%d\n",time_value,time_value-86400);
10673: * tm = *localtime(&time_value);
10674: * strstart=asctime(&tm);
10675: * printf("tim_value=%d,asctime=%s\n",time_value,strstart);
10676: */
10677:
10678: nberr=0; /* Number of errors and warnings */
10679: nbwarn=0;
1.184 brouard 10680: #ifdef WIN32
10681: _getcwd(pathcd, size);
10682: #else
1.126 brouard 10683: getcwd(pathcd, size);
1.184 brouard 10684: #endif
1.191 brouard 10685: syscompilerinfo(0);
1.196 brouard 10686: printf("\nIMaCh version %s, %s\n%s",version, copyright, fullversion);
1.126 brouard 10687: if(argc <=1){
10688: printf("\nEnter the parameter file name: ");
1.205 brouard 10689: if(!fgets(pathr,FILENAMELENGTH,stdin)){
10690: printf("ERROR Empty parameter file name\n");
10691: goto end;
10692: }
1.126 brouard 10693: i=strlen(pathr);
10694: if(pathr[i-1]=='\n')
10695: pathr[i-1]='\0';
1.156 brouard 10696: i=strlen(pathr);
1.205 brouard 10697: if(i >= 1 && pathr[i-1]==' ') {/* This may happen when dragging on oS/X! */
1.156 brouard 10698: pathr[i-1]='\0';
1.205 brouard 10699: }
10700: i=strlen(pathr);
10701: if( i==0 ){
10702: printf("ERROR Empty parameter file name\n");
10703: goto end;
10704: }
10705: for (tok = pathr; tok != NULL; ){
1.126 brouard 10706: printf("Pathr |%s|\n",pathr);
10707: while ((val = strsep(&tok, "\"" )) != NULL && *val == '\0');
10708: printf("val= |%s| pathr=%s\n",val,pathr);
10709: strcpy (pathtot, val);
10710: if(pathr[0] == '\0') break; /* Dirty */
10711: }
10712: }
10713: else{
10714: strcpy(pathtot,argv[1]);
10715: }
10716: /*if(getcwd(pathcd, MAXLINE)!= NULL)printf ("Error pathcd\n");*/
10717: /*cygwin_split_path(pathtot,path,optionfile);
10718: printf("pathtot=%s, path=%s, optionfile=%s\n",pathtot,path,optionfile);*/
10719: /* cutv(path,optionfile,pathtot,'\\');*/
10720:
10721: /* Split argv[0], imach program to get pathimach */
10722: printf("\nargv[0]=%s argv[1]=%s, \n",argv[0],argv[1]);
10723: split(argv[0],pathimach,optionfile,optionfilext,optionfilefiname);
10724: printf("\nargv[0]=%s pathimach=%s, \noptionfile=%s \noptionfilext=%s \noptionfilefiname=%s\n",argv[0],pathimach,optionfile,optionfilext,optionfilefiname);
10725: /* strcpy(pathimach,argv[0]); */
10726: /* Split argv[1]=pathtot, parameter file name to get path, optionfile, extension and name */
10727: split(pathtot,path,optionfile,optionfilext,optionfilefiname);
10728: printf("\npathtot=%s,\npath=%s,\noptionfile=%s \noptionfilext=%s \noptionfilefiname=%s\n",pathtot,path,optionfile,optionfilext,optionfilefiname);
1.184 brouard 10729: #ifdef WIN32
10730: _chdir(path); /* Can be a relative path */
10731: if(_getcwd(pathcd,MAXLINE) > 0) /* So pathcd is the full path */
10732: #else
1.126 brouard 10733: chdir(path); /* Can be a relative path */
1.184 brouard 10734: if (getcwd(pathcd, MAXLINE) > 0) /* So pathcd is the full path */
10735: #endif
10736: printf("Current directory %s!\n",pathcd);
1.126 brouard 10737: strcpy(command,"mkdir ");
10738: strcat(command,optionfilefiname);
10739: if((outcmd=system(command)) != 0){
1.169 brouard 10740: printf("Directory already exists (or can't create it) %s%s, err=%d\n",path,optionfilefiname,outcmd);
1.126 brouard 10741: /* fprintf(ficlog,"Problem creating directory %s%s\n",path,optionfilefiname); */
10742: /* fclose(ficlog); */
10743: /* exit(1); */
10744: }
10745: /* if((imk=mkdir(optionfilefiname))<0){ */
10746: /* perror("mkdir"); */
10747: /* } */
10748:
10749: /*-------- arguments in the command line --------*/
10750:
1.186 brouard 10751: /* Main Log file */
1.126 brouard 10752: strcat(filelog, optionfilefiname);
10753: strcat(filelog,".log"); /* */
10754: if((ficlog=fopen(filelog,"w"))==NULL) {
10755: printf("Problem with logfile %s\n",filelog);
10756: goto end;
10757: }
10758: fprintf(ficlog,"Log filename:%s\n",filelog);
1.197 brouard 10759: fprintf(ficlog,"Version %s %s",version,fullversion);
1.126 brouard 10760: fprintf(ficlog,"\nEnter the parameter file name: \n");
10761: fprintf(ficlog,"pathimach=%s\npathtot=%s\n\
10762: path=%s \n\
10763: optionfile=%s\n\
10764: optionfilext=%s\n\
1.156 brouard 10765: optionfilefiname='%s'\n",pathimach,pathtot,path,optionfile,optionfilext,optionfilefiname);
1.126 brouard 10766:
1.197 brouard 10767: syscompilerinfo(1);
1.167 brouard 10768:
1.126 brouard 10769: printf("Local time (at start):%s",strstart);
10770: fprintf(ficlog,"Local time (at start): %s",strstart);
10771: fflush(ficlog);
10772: /* (void) gettimeofday(&curr_time,&tzp); */
1.157 brouard 10773: /* printf("Elapsed time %d\n", asc_diff_time(curr_time.tm_sec-start_time.tm_sec,tmpout)); */
1.126 brouard 10774:
10775: /* */
10776: strcpy(fileres,"r");
10777: strcat(fileres, optionfilefiname);
1.201 brouard 10778: strcat(fileresu, optionfilefiname); /* Without r in front */
1.126 brouard 10779: strcat(fileres,".txt"); /* Other files have txt extension */
1.201 brouard 10780: strcat(fileresu,".txt"); /* Other files have txt extension */
1.126 brouard 10781:
1.186 brouard 10782: /* Main ---------arguments file --------*/
1.126 brouard 10783:
10784: if((ficpar=fopen(optionfile,"r"))==NULL) {
1.155 brouard 10785: printf("Problem with optionfile '%s' with errno='%s'\n",optionfile,strerror(errno));
10786: fprintf(ficlog,"Problem with optionfile '%s' with errno='%s'\n",optionfile,strerror(errno));
1.126 brouard 10787: fflush(ficlog);
1.149 brouard 10788: /* goto end; */
10789: exit(70);
1.126 brouard 10790: }
10791:
10792:
10793:
10794: strcpy(filereso,"o");
1.201 brouard 10795: strcat(filereso,fileresu);
1.126 brouard 10796: if((ficparo=fopen(filereso,"w"))==NULL) { /* opened on subdirectory */
10797: printf("Problem with Output resultfile: %s\n", filereso);
10798: fprintf(ficlog,"Problem with Output resultfile: %s\n", filereso);
10799: fflush(ficlog);
10800: goto end;
10801: }
10802:
10803: /* Reads comments: lines beginning with '#' */
10804: numlinepar=0;
1.197 brouard 10805:
10806: /* First parameter line */
10807: while(fgets(line, MAXLINE, ficpar)) {
10808: /* If line starts with a # it is a comment */
10809: if (line[0] == '#') {
10810: numlinepar++;
10811: fputs(line,stdout);
10812: fputs(line,ficparo);
10813: fputs(line,ficlog);
10814: continue;
10815: }else
10816: break;
10817: }
10818: if((num_filled=sscanf(line,"title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", \
10819: title, datafile, &lastobs, &firstpass,&lastpass)) !=EOF){
10820: if (num_filled != 5) {
10821: printf("Should be 5 parameters\n");
10822: }
1.126 brouard 10823: numlinepar++;
1.197 brouard 10824: printf("title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", title, datafile, lastobs, firstpass,lastpass);
10825: }
10826: /* Second parameter line */
10827: while(fgets(line, MAXLINE, ficpar)) {
10828: /* If line starts with a # it is a comment */
10829: if (line[0] == '#') {
10830: numlinepar++;
10831: fputs(line,stdout);
10832: fputs(line,ficparo);
10833: fputs(line,ficlog);
10834: continue;
10835: }else
10836: break;
10837: }
1.223 brouard 10838: 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", \
10839: &ftol, &stepm, &ncovcol, &nqv, &ntv, &nqtv, &nlstate, &ndeath, &maxwav, &mle, &weightopt)) !=EOF){
10840: if (num_filled != 11) {
10841: 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 10842: printf("but line=%s\n",line);
1.197 brouard 10843: }
1.223 brouard 10844: 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 10845: }
1.203 brouard 10846: /* ftolpl=6*ftol*1.e5; /\* 6.e-3 make convergences in less than 80 loops for the prevalence limit *\/ */
1.209 brouard 10847: /*ftolpl=6.e-4; *//* 6.e-3 make convergences in less than 80 loops for the prevalence limit */
1.197 brouard 10848: /* Third parameter line */
10849: while(fgets(line, MAXLINE, ficpar)) {
10850: /* If line starts with a # it is a comment */
10851: if (line[0] == '#') {
10852: numlinepar++;
10853: fputs(line,stdout);
10854: fputs(line,ficparo);
10855: fputs(line,ficlog);
10856: continue;
10857: }else
10858: break;
10859: }
1.201 brouard 10860: if((num_filled=sscanf(line,"model=1+age%[^.\n]", model)) !=EOF){
1.263 brouard 10861: if (num_filled == 0){
10862: printf("ERROR %d: Model should be at minimum 'model=1+age.' WITHOUT space:'%s'\n",num_filled, line);
10863: fprintf(ficlog,"ERROR %d: Model should be at minimum 'model=1+age.' WITHOUT space:'%s'\n",num_filled, line);
10864: model[0]='\0';
10865: goto end;
10866: } else if (num_filled != 1){
1.197 brouard 10867: printf("ERROR %d: Model should be at minimum 'model=1+age.' %s\n",num_filled, line);
10868: fprintf(ficlog,"ERROR %d: Model should be at minimum 'model=1+age.' %s\n",num_filled, line);
10869: model[0]='\0';
10870: goto end;
10871: }
10872: else{
10873: if (model[0]=='+'){
10874: for(i=1; i<=strlen(model);i++)
10875: modeltemp[i-1]=model[i];
1.201 brouard 10876: strcpy(model,modeltemp);
1.197 brouard 10877: }
10878: }
1.199 brouard 10879: /* printf(" model=1+age%s modeltemp= %s, model=%s\n",model, modeltemp, model);fflush(stdout); */
1.203 brouard 10880: printf("model=1+age+%s\n",model);fflush(stdout);
1.197 brouard 10881: }
10882: /* 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); */
10883: /* numlinepar=numlinepar+3; /\* In general *\/ */
10884: /* 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 10885: 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);
10886: 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 10887: fflush(ficlog);
1.190 brouard 10888: /* if(model[0]=='#'|| model[0]== '\0'){ */
10889: if(model[0]=='#'){
1.187 brouard 10890: printf("Error in 'model' line: model should start with 'model=1+age+' and end with '.' \n \
10891: 'model=1+age+.' or 'model=1+age+V1.' or 'model=1+age+age*age+V1+V1*age.' or \n \
10892: 'model=1+age+V1+V2.' or 'model=1+age+V1+V2+V1*V2.' etc. \n"); \
10893: if(mle != -1){
10894: printf("Fix the model line and run imach with mle=-1 to get a correct template of the parameter file.\n");
10895: exit(1);
10896: }
10897: }
1.126 brouard 10898: while((c=getc(ficpar))=='#' && c!= EOF){
10899: ungetc(c,ficpar);
10900: fgets(line, MAXLINE, ficpar);
10901: numlinepar++;
1.195 brouard 10902: if(line[1]=='q'){ /* This #q will quit imach (the answer is q) */
10903: z[0]=line[1];
10904: }
10905: /* printf("****line [1] = %c \n",line[1]); */
1.141 brouard 10906: fputs(line, stdout);
10907: //puts(line);
1.126 brouard 10908: fputs(line,ficparo);
10909: fputs(line,ficlog);
10910: }
10911: ungetc(c,ficpar);
10912:
10913:
1.145 brouard 10914: covar=matrix(0,NCOVMAX,1,n); /**< used in readdata */
1.268 brouard 10915: if(nqv>=1)coqvar=matrix(1,nqv,1,n); /**< Fixed quantitative covariate */
10916: if(nqtv>=1)cotqvar=ma3x(1,maxwav,1,nqtv,1,n); /**< Time varying quantitative covariate */
10917: if(ntv+nqtv>=1)cotvar=ma3x(1,maxwav,1,ntv+nqtv,1,n); /**< Time varying covariate (dummy and quantitative)*/
1.136 brouard 10918: cptcovn=0; /*Number of covariates, i.e. number of '+' in model statement plus one, indepently of n in Vn*/
10919: /* v1+v2+v3+v2*v4+v5*age makes cptcovn = 5
10920: v1+v2*age+v2*v3 makes cptcovn = 3
10921: */
10922: if (strlen(model)>1)
1.187 brouard 10923: 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 10924: else
1.187 brouard 10925: ncovmodel=2; /* Constant and age */
1.133 brouard 10926: nforce= (nlstate+ndeath-1)*nlstate; /* Number of forces ij from state i to j */
10927: npar= nforce*ncovmodel; /* Number of parameters like aij*/
1.131 brouard 10928: if(npar >MAXPARM || nlstate >NLSTATEMAX || ndeath >NDEATHMAX || ncovmodel>NCOVMAX){
10929: 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);
10930: 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);
10931: fflush(stdout);
10932: fclose (ficlog);
10933: goto end;
10934: }
1.126 brouard 10935: delti3= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
10936: delti=delti3[1][1];
10937: /*delti=vector(1,npar); *//* Scale of each paramater (output from hesscov)*/
10938: if(mle==-1){ /* Print a wizard for help writing covariance matrix */
1.247 brouard 10939: /* We could also provide initial parameters values giving by simple logistic regression
10940: * only one way, that is without matrix product. We will have nlstate maximizations */
10941: /* for(i=1;i<nlstate;i++){ */
10942: /* /\*reducing xi for 1 to npar to 1 to ncovmodel; *\/ */
10943: /* mlikeli(ficres,p, ncovmodel, ncovmodel, nlstate, ftol, funcnoprod); */
10944: /* } */
1.126 brouard 10945: prwizard(ncovmodel, nlstate, ndeath, model, ficparo);
1.191 brouard 10946: printf(" You chose mle=-1, look at file %s for a template of covariance matrix \n",filereso);
10947: fprintf(ficlog," You chose mle=-1, look at file %s for a template of covariance matrix \n",filereso);
1.126 brouard 10948: free_ma3x(delti3,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
10949: fclose (ficparo);
10950: fclose (ficlog);
10951: goto end;
10952: exit(0);
1.220 brouard 10953: } else if(mle==-5) { /* Main Wizard */
1.126 brouard 10954: prwizard(ncovmodel, nlstate, ndeath, model, ficparo);
1.192 brouard 10955: printf(" You chose mle=-3, look at file %s for a template of covariance matrix \n",filereso);
10956: fprintf(ficlog," You chose mle=-3, look at file %s for a template of covariance matrix \n",filereso);
1.126 brouard 10957: param= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
10958: matcov=matrix(1,npar,1,npar);
1.203 brouard 10959: hess=matrix(1,npar,1,npar);
1.220 brouard 10960: } else{ /* Begin of mle != -1 or -5 */
1.145 brouard 10961: /* Read guessed parameters */
1.126 brouard 10962: /* Reads comments: lines beginning with '#' */
10963: while((c=getc(ficpar))=='#' && c!= EOF){
10964: ungetc(c,ficpar);
10965: fgets(line, MAXLINE, ficpar);
10966: numlinepar++;
1.141 brouard 10967: fputs(line,stdout);
1.126 brouard 10968: fputs(line,ficparo);
10969: fputs(line,ficlog);
10970: }
10971: ungetc(c,ficpar);
10972:
10973: param= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
1.251 brouard 10974: paramstart= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
1.126 brouard 10975: for(i=1; i <=nlstate; i++){
1.234 brouard 10976: j=0;
1.126 brouard 10977: for(jj=1; jj <=nlstate+ndeath; jj++){
1.234 brouard 10978: if(jj==i) continue;
10979: j++;
10980: fscanf(ficpar,"%1d%1d",&i1,&j1);
10981: if ((i1 != i) || (j1 != jj)){
10982: printf("Error in line parameters number %d, %1d%1d instead of %1d%1d \n \
1.126 brouard 10983: It might be a problem of design; if ncovcol and the model are correct\n \
10984: run imach with mle=-1 to get a correct template of the parameter file.\n",numlinepar, i,j, i1, j1);
1.234 brouard 10985: exit(1);
10986: }
10987: fprintf(ficparo,"%1d%1d",i1,j1);
10988: if(mle==1)
10989: printf("%1d%1d",i,jj);
10990: fprintf(ficlog,"%1d%1d",i,jj);
10991: for(k=1; k<=ncovmodel;k++){
10992: fscanf(ficpar," %lf",¶m[i][j][k]);
10993: if(mle==1){
10994: printf(" %lf",param[i][j][k]);
10995: fprintf(ficlog," %lf",param[i][j][k]);
10996: }
10997: else
10998: fprintf(ficlog," %lf",param[i][j][k]);
10999: fprintf(ficparo," %lf",param[i][j][k]);
11000: }
11001: fscanf(ficpar,"\n");
11002: numlinepar++;
11003: if(mle==1)
11004: printf("\n");
11005: fprintf(ficlog,"\n");
11006: fprintf(ficparo,"\n");
1.126 brouard 11007: }
11008: }
11009: fflush(ficlog);
1.234 brouard 11010:
1.251 brouard 11011: /* Reads parameters values */
1.126 brouard 11012: p=param[1][1];
1.251 brouard 11013: pstart=paramstart[1][1];
1.126 brouard 11014:
11015: /* Reads comments: lines beginning with '#' */
11016: while((c=getc(ficpar))=='#' && c!= EOF){
11017: ungetc(c,ficpar);
11018: fgets(line, MAXLINE, ficpar);
11019: numlinepar++;
1.141 brouard 11020: fputs(line,stdout);
1.126 brouard 11021: fputs(line,ficparo);
11022: fputs(line,ficlog);
11023: }
11024: ungetc(c,ficpar);
11025:
11026: for(i=1; i <=nlstate; i++){
11027: for(j=1; j <=nlstate+ndeath-1; j++){
1.234 brouard 11028: fscanf(ficpar,"%1d%1d",&i1,&j1);
11029: if ( (i1-i) * (j1-j) != 0){
11030: printf("Error in line parameters number %d, %1d%1d instead of %1d%1d \n",numlinepar, i,j, i1, j1);
11031: exit(1);
11032: }
11033: printf("%1d%1d",i,j);
11034: fprintf(ficparo,"%1d%1d",i1,j1);
11035: fprintf(ficlog,"%1d%1d",i1,j1);
11036: for(k=1; k<=ncovmodel;k++){
11037: fscanf(ficpar,"%le",&delti3[i][j][k]);
11038: printf(" %le",delti3[i][j][k]);
11039: fprintf(ficparo," %le",delti3[i][j][k]);
11040: fprintf(ficlog," %le",delti3[i][j][k]);
11041: }
11042: fscanf(ficpar,"\n");
11043: numlinepar++;
11044: printf("\n");
11045: fprintf(ficparo,"\n");
11046: fprintf(ficlog,"\n");
1.126 brouard 11047: }
11048: }
11049: fflush(ficlog);
1.234 brouard 11050:
1.145 brouard 11051: /* Reads covariance matrix */
1.126 brouard 11052: delti=delti3[1][1];
1.220 brouard 11053:
11054:
1.126 brouard 11055: /* 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 11056:
1.126 brouard 11057: /* Reads comments: lines beginning with '#' */
11058: while((c=getc(ficpar))=='#' && c!= EOF){
11059: ungetc(c,ficpar);
11060: fgets(line, MAXLINE, ficpar);
11061: numlinepar++;
1.141 brouard 11062: fputs(line,stdout);
1.126 brouard 11063: fputs(line,ficparo);
11064: fputs(line,ficlog);
11065: }
11066: ungetc(c,ficpar);
1.220 brouard 11067:
1.126 brouard 11068: matcov=matrix(1,npar,1,npar);
1.203 brouard 11069: hess=matrix(1,npar,1,npar);
1.131 brouard 11070: for(i=1; i <=npar; i++)
11071: for(j=1; j <=npar; j++) matcov[i][j]=0.;
1.220 brouard 11072:
1.194 brouard 11073: /* Scans npar lines */
1.126 brouard 11074: for(i=1; i <=npar; i++){
1.226 brouard 11075: count=fscanf(ficpar,"%1d%1d%d",&i1,&j1,&jk);
1.194 brouard 11076: if(count != 3){
1.226 brouard 11077: printf("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: fprintf(ficlog,"Error! Error in parameter file %s at line %d after line starting with %1d%1d%1d\n\
1.194 brouard 11081: This is probably because your covariance matrix doesn't \n contain exactly %d lines corresponding to your model line '1+age+%s'.\n\
11082: Please run with mle=-1 to get a correct covariance matrix.\n",optionfile,numlinepar, i1,j1,jk, npar, model);
1.226 brouard 11083: exit(1);
1.220 brouard 11084: }else{
1.226 brouard 11085: if(mle==1)
11086: printf("%1d%1d%d",i1,j1,jk);
11087: }
11088: fprintf(ficlog,"%1d%1d%d",i1,j1,jk);
11089: fprintf(ficparo,"%1d%1d%d",i1,j1,jk);
1.126 brouard 11090: for(j=1; j <=i; j++){
1.226 brouard 11091: fscanf(ficpar," %le",&matcov[i][j]);
11092: if(mle==1){
11093: printf(" %.5le",matcov[i][j]);
11094: }
11095: fprintf(ficlog," %.5le",matcov[i][j]);
11096: fprintf(ficparo," %.5le",matcov[i][j]);
1.126 brouard 11097: }
11098: fscanf(ficpar,"\n");
11099: numlinepar++;
11100: if(mle==1)
1.220 brouard 11101: printf("\n");
1.126 brouard 11102: fprintf(ficlog,"\n");
11103: fprintf(ficparo,"\n");
11104: }
1.194 brouard 11105: /* End of read covariance matrix npar lines */
1.126 brouard 11106: for(i=1; i <=npar; i++)
11107: for(j=i+1;j<=npar;j++)
1.226 brouard 11108: matcov[i][j]=matcov[j][i];
1.126 brouard 11109:
11110: if(mle==1)
11111: printf("\n");
11112: fprintf(ficlog,"\n");
11113:
11114: fflush(ficlog);
11115:
11116: /*-------- Rewriting parameter file ----------*/
11117: strcpy(rfileres,"r"); /* "Rparameterfile */
11118: strcat(rfileres,optionfilefiname); /* Parameter file first name*/
11119: strcat(rfileres,"."); /* */
11120: strcat(rfileres,optionfilext); /* Other files have txt extension */
11121: if((ficres =fopen(rfileres,"w"))==NULL) {
1.201 brouard 11122: printf("Problem writing new parameter file: %s\n", rfileres);goto end;
11123: fprintf(ficlog,"Problem writing new parameter file: %s\n", rfileres);goto end;
1.126 brouard 11124: }
11125: fprintf(ficres,"#%s\n",version);
11126: } /* End of mle != -3 */
1.218 brouard 11127:
1.186 brouard 11128: /* Main data
11129: */
1.126 brouard 11130: n= lastobs;
11131: num=lvector(1,n);
11132: moisnais=vector(1,n);
11133: annais=vector(1,n);
11134: moisdc=vector(1,n);
11135: andc=vector(1,n);
1.220 brouard 11136: weight=vector(1,n);
1.126 brouard 11137: agedc=vector(1,n);
11138: cod=ivector(1,n);
1.220 brouard 11139: for(i=1;i<=n;i++){
1.234 brouard 11140: num[i]=0;
11141: moisnais[i]=0;
11142: annais[i]=0;
11143: moisdc[i]=0;
11144: andc[i]=0;
11145: agedc[i]=0;
11146: cod[i]=0;
11147: weight[i]=1.0; /* Equal weights, 1 by default */
11148: }
1.126 brouard 11149: mint=matrix(1,maxwav,1,n);
11150: anint=matrix(1,maxwav,1,n);
1.131 brouard 11151: s=imatrix(1,maxwav+1,1,n); /* s[i][j] health state for wave i and individual j */
1.126 brouard 11152: tab=ivector(1,NCOVMAX);
1.144 brouard 11153: ncodemax=ivector(1,NCOVMAX); /* Number of code per covariate; if O and 1 only, 2**ncov; V1+V2+V3+V4=>16 */
1.192 brouard 11154: 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 11155:
1.136 brouard 11156: /* Reads data from file datafile */
11157: if (readdata(datafile, firstobs, lastobs, &imx)==1)
11158: goto end;
11159:
11160: /* Calculation of the number of parameters from char model */
1.234 brouard 11161: /* modelsav=V2+V1+V4+age*V3 strb=age*V3 stra=V2+V1+V4
1.137 brouard 11162: k=4 (age*V3) Tvar[k=4]= 3 (from V3) Tag[cptcovage=1]=4
11163: k=3 V4 Tvar[k=3]= 4 (from V4)
11164: k=2 V1 Tvar[k=2]= 1 (from V1)
11165: k=1 Tvar[1]=2 (from V2)
1.234 brouard 11166: */
11167:
11168: Tvar=ivector(1,NCOVMAX); /* Was 15 changed to NCOVMAX. */
11169: TvarsDind=ivector(1,NCOVMAX); /* */
11170: TvarsD=ivector(1,NCOVMAX); /* */
11171: TvarsQind=ivector(1,NCOVMAX); /* */
11172: TvarsQ=ivector(1,NCOVMAX); /* */
1.232 brouard 11173: TvarF=ivector(1,NCOVMAX); /* */
11174: TvarFind=ivector(1,NCOVMAX); /* */
11175: TvarV=ivector(1,NCOVMAX); /* */
11176: TvarVind=ivector(1,NCOVMAX); /* */
11177: TvarA=ivector(1,NCOVMAX); /* */
11178: TvarAind=ivector(1,NCOVMAX); /* */
1.231 brouard 11179: TvarFD=ivector(1,NCOVMAX); /* */
11180: TvarFDind=ivector(1,NCOVMAX); /* */
11181: TvarFQ=ivector(1,NCOVMAX); /* */
11182: TvarFQind=ivector(1,NCOVMAX); /* */
11183: TvarVD=ivector(1,NCOVMAX); /* */
11184: TvarVDind=ivector(1,NCOVMAX); /* */
11185: TvarVQ=ivector(1,NCOVMAX); /* */
11186: TvarVQind=ivector(1,NCOVMAX); /* */
11187:
1.230 brouard 11188: Tvalsel=vector(1,NCOVMAX); /* */
1.233 brouard 11189: Tvarsel=ivector(1,NCOVMAX); /* */
1.226 brouard 11190: Typevar=ivector(-1,NCOVMAX); /* -1 to 2 */
11191: Fixed=ivector(-1,NCOVMAX); /* -1 to 3 */
11192: Dummy=ivector(-1,NCOVMAX); /* -1 to 3 */
1.137 brouard 11193: /* V2+V1+V4+age*V3 is a model with 4 covariates (3 plus signs).
11194: For each model-covariate stores the data-covariate id. Tvar[1]=2, Tvar[2]=1, Tvar[3]=4,
11195: Tvar[4=age*V3] is 3 and 'age' is recorded in Tage.
11196: */
11197: /* For model-covariate k tells which data-covariate to use but
11198: because this model-covariate is a construction we invent a new column
11199: ncovcol + k1
11200: If already ncovcol=4 and model=V2+V1+V1*V4+age*V3
11201: Tvar[3=V1*V4]=4+1 etc */
1.227 brouard 11202: Tprod=ivector(1,NCOVMAX); /* Gives the k position of the k1 product */
11203: Tposprod=ivector(1,NCOVMAX); /* Gives the k1 product from the k position */
1.137 brouard 11204: /* Tprod[k1=1]=3(=V1*V4) for V2+V1+V1*V4+age*V3
11205: if V2+V1+V1*V4+age*V3+V3*V2 TProd[k1=2]=5 (V3*V2)
1.227 brouard 11206: Tposprod[k]=k1 , Tposprod[3]=1, Tposprod[5]=2
1.137 brouard 11207: */
1.145 brouard 11208: Tvaraff=ivector(1,NCOVMAX); /* Unclear */
11209: 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 11210: * For V3*V2 (in V2+V1+V1*V4+age*V3+V3*V2), V3*V2 position is 2nd.
11211: * Tvard[k1=2][1]=3 (V3) Tvard[k1=2][2]=2(V2) */
1.145 brouard 11212: Tage=ivector(1,NCOVMAX); /* Gives the covariate id of covariates associated with age: V2 + V1 + age*V4 + V3*age
1.137 brouard 11213: 4 covariates (3 plus signs)
11214: Tage[1=V3*age]= 4; Tage[2=age*V4] = 3
11215: */
1.230 brouard 11216: Tmodelind=ivector(1,NCOVMAX);/** gives the k model position of an
1.227 brouard 11217: * individual dummy, fixed or varying:
11218: * Tmodelind[Tvaraff[3]]=9,Tvaraff[1]@9={4,
11219: * 3, 1, 0, 0, 0, 0, 0, 0},
1.230 brouard 11220: * model=V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 ,
11221: * V1 df, V2 qf, V3 & V4 dv, V5 qv
11222: * Tmodelind[1]@9={9,0,3,2,}*/
11223: TmodelInvind=ivector(1,NCOVMAX); /* TmodelInvind=Tvar[k]- ncovcol-nqv={5-2-1=2,*/
11224: TmodelInvQind=ivector(1,NCOVMAX);/** gives the k model position of an
1.228 brouard 11225: * individual quantitative, fixed or varying:
11226: * Tmodelqind[1]=1,Tvaraff[1]@9={4,
11227: * 3, 1, 0, 0, 0, 0, 0, 0},
11228: * model=V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1*/
1.186 brouard 11229: /* Main decodemodel */
11230:
1.187 brouard 11231:
1.223 brouard 11232: if(decodemodel(model, lastobs) == 1) /* In order to get Tvar[k] V4+V3+V5 p Tvar[1]@3 = {4, 3, 5}*/
1.136 brouard 11233: goto end;
11234:
1.137 brouard 11235: if((double)(lastobs-imx)/(double)imx > 1.10){
11236: nbwarn++;
11237: 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);
11238: 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);
11239: }
1.136 brouard 11240: /* if(mle==1){*/
1.137 brouard 11241: if (weightopt != 1) { /* Maximisation without weights. We can have weights different from 1 but want no weight*/
11242: for(i=1;i<=imx;i++) weight[i]=1.0; /* changed to imx */
1.136 brouard 11243: }
11244:
11245: /*-calculation of age at interview from date of interview and age at death -*/
11246: agev=matrix(1,maxwav,1,imx);
11247:
11248: if(calandcheckages(imx, maxwav, &agemin, &agemax, &nberr, &nbwarn) == 1)
11249: goto end;
11250:
1.126 brouard 11251:
1.136 brouard 11252: agegomp=(int)agemin;
11253: free_vector(moisnais,1,n);
11254: free_vector(annais,1,n);
1.126 brouard 11255: /* free_matrix(mint,1,maxwav,1,n);
11256: free_matrix(anint,1,maxwav,1,n);*/
1.215 brouard 11257: /* free_vector(moisdc,1,n); */
11258: /* free_vector(andc,1,n); */
1.145 brouard 11259: /* */
11260:
1.126 brouard 11261: wav=ivector(1,imx);
1.214 brouard 11262: /* dh=imatrix(1,lastpass-firstpass+1,1,imx); */
11263: /* bh=imatrix(1,lastpass-firstpass+1,1,imx); */
11264: /* mw=imatrix(1,lastpass-firstpass+1,1,imx); */
11265: 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.*/
11266: bh=imatrix(1,lastpass-firstpass+2,1,imx);
11267: mw=imatrix(1,lastpass-firstpass+2,1,imx);
1.126 brouard 11268:
11269: /* Concatenates waves */
1.214 brouard 11270: /* Concatenates waves: wav[i] is the number of effective (useful waves) of individual i.
11271: Death is a valid wave (if date is known).
11272: mw[mi][i] is the number of (mi=1 to wav[i]) effective wave out of mi of individual i
11273: dh[m][i] or dh[mw[mi][i]][i] is the delay between two effective waves m=mw[mi][i]
11274: and mw[mi+1][i]. dh depends on stepm.
11275: */
11276:
1.126 brouard 11277: concatwav(wav, dh, bh, mw, s, agedc, agev, firstpass, lastpass, imx, nlstate, stepm);
1.248 brouard 11278: /* Concatenates waves */
1.145 brouard 11279:
1.215 brouard 11280: free_vector(moisdc,1,n);
11281: free_vector(andc,1,n);
11282:
1.126 brouard 11283: /* Routine tricode is to calculate cptcoveff (real number of unique covariates) and to associate covariable number and modality */
11284: nbcode=imatrix(0,NCOVMAX,0,NCOVMAX);
11285: ncodemax[1]=1;
1.145 brouard 11286: Ndum =ivector(-1,NCOVMAX);
1.225 brouard 11287: cptcoveff=0;
1.220 brouard 11288: if (ncovmodel-nagesqr > 2 ){ /* That is if covariate other than cst, age and age*age */
11289: tricode(&cptcoveff,Tvar,nbcode,imx, Ndum); /**< Fills nbcode[Tvar[j]][l]; */
1.227 brouard 11290: }
11291:
11292: ncovcombmax=pow(2,cptcoveff);
11293: invalidvarcomb=ivector(1, ncovcombmax);
11294: for(i=1;i<ncovcombmax;i++)
11295: invalidvarcomb[i]=0;
11296:
1.211 brouard 11297: /* Nbcode gives the value of the lth modality (currently 1 to 2) of jth covariate, in
1.186 brouard 11298: V2+V1*age, there are 3 covariates Tvar[2]=1 (V1).*/
1.211 brouard 11299: /* 1 to ncodemax[j] which is the maximum value of this jth covariate */
1.227 brouard 11300:
1.200 brouard 11301: /* codtab=imatrix(1,100,1,10);*/ /* codtab[h,k]=( (h-1) - mod(k-1,2**(k-1) )/2**(k-1) */
1.198 brouard 11302: /*printf(" codtab[1,1],codtab[100,10]=%d,%d\n", codtab[1][1],codtabm(100,10));*/
1.186 brouard 11303: /* codtab gives the value 1 or 2 of the hth combination of k covariates (1 or 2).*/
1.211 brouard 11304: /* nbcode[Tvaraff[j]][codtabm(h,j)]) : if there are only 2 modalities for a covariate j,
11305: * codtabm(h,j) gives its value classified at position h and nbcode gives how it is coded
11306: * (currently 0 or 1) in the data.
11307: * In a loop on h=1 to 2**k, and a loop on j (=1 to k), we get the value of
11308: * corresponding modality (h,j).
11309: */
11310:
1.145 brouard 11311: h=0;
11312: /*if (cptcovn > 0) */
1.126 brouard 11313: m=pow(2,cptcoveff);
11314:
1.144 brouard 11315: /**< codtab(h,k) k = codtab[h,k]=( (h-1) - mod(k-1,2**(k-1) )/2**(k-1) + 1
1.211 brouard 11316: * For k=4 covariates, h goes from 1 to m=2**k
11317: * codtabm(h,k)= (1 & (h-1) >> (k-1)) + 1;
11318: * #define codtabm(h,k) (1 & (h-1) >> (k-1))+1
1.186 brouard 11319: * h\k 1 2 3 4
1.143 brouard 11320: *______________________________
11321: * 1 i=1 1 i=1 1 i=1 1 i=1 1
11322: * 2 2 1 1 1
11323: * 3 i=2 1 2 1 1
11324: * 4 2 2 1 1
11325: * 5 i=3 1 i=2 1 2 1
11326: * 6 2 1 2 1
11327: * 7 i=4 1 2 2 1
11328: * 8 2 2 2 1
1.197 brouard 11329: * 9 i=5 1 i=3 1 i=2 1 2
11330: * 10 2 1 1 2
11331: * 11 i=6 1 2 1 2
11332: * 12 2 2 1 2
11333: * 13 i=7 1 i=4 1 2 2
11334: * 14 2 1 2 2
11335: * 15 i=8 1 2 2 2
11336: * 16 2 2 2 2
1.143 brouard 11337: */
1.212 brouard 11338: /* How to do the opposite? From combination h (=1 to 2**k) how to get the value on the covariates? */
1.211 brouard 11339: /* from h=5 and m, we get then number of covariates k=log(m)/log(2)=4
11340: * and the value of each covariate?
11341: * V1=1, V2=1, V3=2, V4=1 ?
11342: * h-1=4 and 4 is 0100 or reverse 0010, and +1 is 1121 ok.
11343: * h=6, 6-1=5, 5 is 0101, 1010, 2121, V1=2nd, V2=1st, V3=2nd, V4=1st.
11344: * In order to get the real value in the data, we use nbcode
11345: * nbcode[Tvar[3][2nd]]=1 and nbcode[Tvar[4][1]]=0
11346: * We are keeping this crazy system in order to be able (in the future?)
11347: * to have more than 2 values (0 or 1) for a covariate.
11348: * #define codtabm(h,k) (1 & (h-1) >> (k-1))+1
11349: * h=6, k=2? h-1=5=0101, reverse 1010, +1=2121, k=2nd position: value is 1: codtabm(6,2)=1
11350: * bbbbbbbb
11351: * 76543210
11352: * h-1 00000101 (6-1=5)
1.219 brouard 11353: *(h-1)>>(k-1)= 00000010 >> (2-1) = 1 right shift
1.211 brouard 11354: * &
11355: * 1 00000001 (1)
1.219 brouard 11356: * 00000000 = 1 & ((h-1) >> (k-1))
11357: * +1= 00000001 =1
1.211 brouard 11358: *
11359: * h=14, k=3 => h'=h-1=13, k'=k-1=2
11360: * h' 1101 =2^3+2^2+0x2^1+2^0
11361: * >>k' 11
11362: * & 00000001
11363: * = 00000001
11364: * +1 = 00000010=2 = codtabm(14,3)
11365: * Reverse h=6 and m=16?
11366: * cptcoveff=log(16)/log(2)=4 covariate: 6-1=5=0101 reversed=1010 +1=2121 =>V1=2, V2=1, V3=2, V4=1.
11367: * for (j=1 to cptcoveff) Vj=decodtabm(j,h,cptcoveff)
11368: * decodtabm(h,j,cptcoveff)= (((h-1) >> (j-1)) & 1) +1
11369: * decodtabm(h,j,cptcoveff)= (h <= (1<<cptcoveff)?(((h-1) >> (j-1)) & 1) +1 : -1)
11370: * V3=decodtabm(14,3,2**4)=2
11371: * h'=13 1101 =2^3+2^2+0x2^1+2^0
11372: *(h-1) >> (j-1) 0011 =13 >> 2
11373: * &1 000000001
11374: * = 000000001
11375: * +1= 000000010 =2
11376: * 2211
11377: * V1=1+1, V2=0+1, V3=1+1, V4=1+1
11378: * V3=2
1.220 brouard 11379: * codtabm and decodtabm are identical
1.211 brouard 11380: */
11381:
1.145 brouard 11382:
11383: free_ivector(Ndum,-1,NCOVMAX);
11384:
11385:
1.126 brouard 11386:
1.186 brouard 11387: /* Initialisation of ----------- gnuplot -------------*/
1.126 brouard 11388: strcpy(optionfilegnuplot,optionfilefiname);
11389: if(mle==-3)
1.201 brouard 11390: strcat(optionfilegnuplot,"-MORT_");
1.126 brouard 11391: strcat(optionfilegnuplot,".gp");
11392:
11393: if((ficgp=fopen(optionfilegnuplot,"w"))==NULL) {
11394: printf("Problem with file %s",optionfilegnuplot);
11395: }
11396: else{
1.204 brouard 11397: fprintf(ficgp,"\n# IMaCh-%s\n", version);
1.126 brouard 11398: fprintf(ficgp,"# %s\n", optionfilegnuplot);
1.141 brouard 11399: //fprintf(ficgp,"set missing 'NaNq'\n");
11400: fprintf(ficgp,"set datafile missing 'NaNq'\n");
1.126 brouard 11401: }
11402: /* fclose(ficgp);*/
1.186 brouard 11403:
11404:
11405: /* Initialisation of --------- index.htm --------*/
1.126 brouard 11406:
11407: strcpy(optionfilehtm,optionfilefiname); /* Main html file */
11408: if(mle==-3)
1.201 brouard 11409: strcat(optionfilehtm,"-MORT_");
1.126 brouard 11410: strcat(optionfilehtm,".htm");
11411: if((fichtm=fopen(optionfilehtm,"w"))==NULL) {
1.131 brouard 11412: printf("Problem with %s \n",optionfilehtm);
11413: exit(0);
1.126 brouard 11414: }
11415:
11416: strcpy(optionfilehtmcov,optionfilefiname); /* Only for matrix of covariance */
11417: strcat(optionfilehtmcov,"-cov.htm");
11418: if((fichtmcov=fopen(optionfilehtmcov,"w"))==NULL) {
11419: printf("Problem with %s \n",optionfilehtmcov), exit(0);
11420: }
11421: else{
11422: fprintf(fichtmcov,"<html><head>\n<title>IMaCh Cov %s</title></head>\n <body><font size=\"2\">%s <br> %s</font> \
11423: <hr size=\"2\" color=\"#EC5E5E\"> \n\
1.204 brouard 11424: Title=%s <br>Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s<br>\n",\
1.126 brouard 11425: optionfilehtmcov,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model);
11426: }
11427:
1.213 brouard 11428: 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 11429: <hr size=\"2\" color=\"#EC5E5E\"> \n\
11430: <font size=\"2\">IMaCh-%s <br> %s</font> \
1.126 brouard 11431: <hr size=\"2\" color=\"#EC5E5E\"> \n\
1.204 brouard 11432: Title=%s <br>Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s<br>\n\
1.126 brouard 11433: \n\
11434: <hr size=\"2\" color=\"#EC5E5E\">\
11435: <ul><li><h4>Parameter files</h4>\n\
11436: - Parameter file: <a href=\"%s.%s\">%s.%s</a><br>\n\
11437: - Copy of the parameter file: <a href=\"o%s\">o%s</a><br>\n\
11438: - Log file of the run: <a href=\"%s\">%s</a><br>\n\
11439: - Gnuplot file name: <a href=\"%s\">%s</a><br>\n\
11440: - Date and time at start: %s</ul>\n",\
11441: optionfilehtm,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model,\
11442: optionfilefiname,optionfilext,optionfilefiname,optionfilext,\
11443: fileres,fileres,\
11444: filelog,filelog,optionfilegnuplot,optionfilegnuplot,strstart);
11445: fflush(fichtm);
11446:
11447: strcpy(pathr,path);
11448: strcat(pathr,optionfilefiname);
1.184 brouard 11449: #ifdef WIN32
11450: _chdir(optionfilefiname); /* Move to directory named optionfile */
11451: #else
1.126 brouard 11452: chdir(optionfilefiname); /* Move to directory named optionfile */
1.184 brouard 11453: #endif
11454:
1.126 brouard 11455:
1.220 brouard 11456: /* Calculates basic frequencies. Computes observed prevalence at single age
11457: and for any valid combination of covariates
1.126 brouard 11458: and prints on file fileres'p'. */
1.251 brouard 11459: freqsummary(fileres, p, pstart, agemin, agemax, s, agev, nlstate, imx, Tvaraff, invalidvarcomb, nbcode, ncodemax,mint,anint,strstart, \
1.227 brouard 11460: firstpass, lastpass, stepm, weightopt, model);
1.126 brouard 11461:
11462: fprintf(fichtm,"\n");
11463: fprintf(fichtm,"<br>Total number of observations=%d <br>\n\
11464: Youngest age at first (selected) pass %.2f, oldest age %.2f<br>\n\
11465: Interval (in months) between two waves: Min=%d Max=%d Mean=%.2lf<br>\n",\
11466: imx,agemin,agemax,jmin,jmax,jmean);
11467: pmmij= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
1.268 brouard 11468: oldms= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
11469: newms= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
11470: savms= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
11471: oldm=oldms; newm=newms; savm=savms; /* Keeps fixed addresses to free */
1.218 brouard 11472:
1.126 brouard 11473: /* For Powell, parameters are in a vector p[] starting at p[1]
11474: so we point p on param[1][1] so that p[1] maps on param[1][1][1] */
11475: p=param[1][1]; /* *(*(*(param +1)+1)+0) */
11476:
11477: globpr=0; /* To get the number ipmx of contributions and the sum of weights*/
1.186 brouard 11478: /* For mortality only */
1.126 brouard 11479: if (mle==-3){
1.136 brouard 11480: ximort=matrix(1,NDIM,1,NDIM);
1.248 brouard 11481: for(i=1;i<=NDIM;i++)
11482: for(j=1;j<=NDIM;j++)
11483: ximort[i][j]=0.;
1.186 brouard 11484: /* ximort=gsl_matrix_alloc(1,NDIM,1,NDIM); */
1.126 brouard 11485: cens=ivector(1,n);
11486: ageexmed=vector(1,n);
11487: agecens=vector(1,n);
11488: dcwave=ivector(1,n);
1.223 brouard 11489:
1.126 brouard 11490: for (i=1; i<=imx; i++){
11491: dcwave[i]=-1;
11492: for (m=firstpass; m<=lastpass; m++)
1.226 brouard 11493: if (s[m][i]>nlstate) {
11494: dcwave[i]=m;
11495: /* printf("i=%d j=%d s=%d dcwave=%d\n",i,j, s[j][i],dcwave[i]);*/
11496: break;
11497: }
1.126 brouard 11498: }
1.226 brouard 11499:
1.126 brouard 11500: for (i=1; i<=imx; i++) {
11501: if (wav[i]>0){
1.226 brouard 11502: ageexmed[i]=agev[mw[1][i]][i];
11503: j=wav[i];
11504: agecens[i]=1.;
11505:
11506: if (ageexmed[i]> 1 && wav[i] > 0){
11507: agecens[i]=agev[mw[j][i]][i];
11508: cens[i]= 1;
11509: }else if (ageexmed[i]< 1)
11510: cens[i]= -1;
11511: if (agedc[i]< AGESUP && agedc[i]>1 && dcwave[i]>firstpass && dcwave[i]<=lastpass)
11512: cens[i]=0 ;
1.126 brouard 11513: }
11514: else cens[i]=-1;
11515: }
11516:
11517: for (i=1;i<=NDIM;i++) {
11518: for (j=1;j<=NDIM;j++)
1.226 brouard 11519: ximort[i][j]=(i == j ? 1.0 : 0.0);
1.126 brouard 11520: }
11521:
1.145 brouard 11522: /*p[1]=0.0268; p[NDIM]=0.083;*/
1.126 brouard 11523: /*printf("%lf %lf", p[1], p[2]);*/
11524:
11525:
1.136 brouard 11526: #ifdef GSL
11527: printf("GSL optimization\n"); fprintf(ficlog,"Powell\n");
1.162 brouard 11528: #else
1.126 brouard 11529: printf("Powell\n"); fprintf(ficlog,"Powell\n");
1.136 brouard 11530: #endif
1.201 brouard 11531: strcpy(filerespow,"POW-MORT_");
11532: strcat(filerespow,fileresu);
1.126 brouard 11533: if((ficrespow=fopen(filerespow,"w"))==NULL) {
11534: printf("Problem with resultfile: %s\n", filerespow);
11535: fprintf(ficlog,"Problem with resultfile: %s\n", filerespow);
11536: }
1.136 brouard 11537: #ifdef GSL
11538: fprintf(ficrespow,"# GSL optimization\n# iter -2*LL");
1.162 brouard 11539: #else
1.126 brouard 11540: fprintf(ficrespow,"# Powell\n# iter -2*LL");
1.136 brouard 11541: #endif
1.126 brouard 11542: /* for (i=1;i<=nlstate;i++)
11543: for(j=1;j<=nlstate+ndeath;j++)
11544: if(j!=i)fprintf(ficrespow," p%1d%1d",i,j);
11545: */
11546: fprintf(ficrespow,"\n");
1.136 brouard 11547: #ifdef GSL
11548: /* gsl starts here */
11549: T = gsl_multimin_fminimizer_nmsimplex;
11550: gsl_multimin_fminimizer *sfm = NULL;
11551: gsl_vector *ss, *x;
11552: gsl_multimin_function minex_func;
11553:
11554: /* Initial vertex size vector */
11555: ss = gsl_vector_alloc (NDIM);
11556:
11557: if (ss == NULL){
11558: GSL_ERROR_VAL ("failed to allocate space for ss", GSL_ENOMEM, 0);
11559: }
11560: /* Set all step sizes to 1 */
11561: gsl_vector_set_all (ss, 0.001);
11562:
11563: /* Starting point */
1.126 brouard 11564:
1.136 brouard 11565: x = gsl_vector_alloc (NDIM);
11566:
11567: if (x == NULL){
11568: gsl_vector_free(ss);
11569: GSL_ERROR_VAL ("failed to allocate space for x", GSL_ENOMEM, 0);
11570: }
11571:
11572: /* Initialize method and iterate */
11573: /* p[1]=0.0268; p[NDIM]=0.083; */
1.186 brouard 11574: /* gsl_vector_set(x, 0, 0.0268); */
11575: /* gsl_vector_set(x, 1, 0.083); */
1.136 brouard 11576: gsl_vector_set(x, 0, p[1]);
11577: gsl_vector_set(x, 1, p[2]);
11578:
11579: minex_func.f = &gompertz_f;
11580: minex_func.n = NDIM;
11581: minex_func.params = (void *)&p; /* ??? */
11582:
11583: sfm = gsl_multimin_fminimizer_alloc (T, NDIM);
11584: gsl_multimin_fminimizer_set (sfm, &minex_func, x, ss);
11585:
11586: printf("Iterations beginning .....\n\n");
11587: printf("Iter. # Intercept Slope -Log Likelihood Simplex size\n");
11588:
11589: iteri=0;
11590: while (rval == GSL_CONTINUE){
11591: iteri++;
11592: status = gsl_multimin_fminimizer_iterate(sfm);
11593:
11594: if (status) printf("error: %s\n", gsl_strerror (status));
11595: fflush(0);
11596:
11597: if (status)
11598: break;
11599:
11600: rval = gsl_multimin_test_size (gsl_multimin_fminimizer_size (sfm), 1e-6);
11601: ssval = gsl_multimin_fminimizer_size (sfm);
11602:
11603: if (rval == GSL_SUCCESS)
11604: printf ("converged to a local maximum at\n");
11605:
11606: printf("%5d ", iteri);
11607: for (it = 0; it < NDIM; it++){
11608: printf ("%10.5f ", gsl_vector_get (sfm->x, it));
11609: }
11610: printf("f() = %-10.5f ssize = %.7f\n", sfm->fval, ssval);
11611: }
11612:
11613: printf("\n\n Please note: Program should be run many times with varying starting points to detemine global maximum\n\n");
11614:
11615: gsl_vector_free(x); /* initial values */
11616: gsl_vector_free(ss); /* inital step size */
11617: for (it=0; it<NDIM; it++){
11618: p[it+1]=gsl_vector_get(sfm->x,it);
11619: fprintf(ficrespow," %.12lf", p[it]);
11620: }
11621: gsl_multimin_fminimizer_free (sfm); /* p *(sfm.x.data) et p *(sfm.x.data+1) */
11622: #endif
11623: #ifdef POWELL
11624: powell(p,ximort,NDIM,ftol,&iter,&fret,gompertz);
11625: #endif
1.126 brouard 11626: fclose(ficrespow);
11627:
1.203 brouard 11628: hesscov(matcov, hess, p, NDIM, delti, 1e-4, gompertz);
1.126 brouard 11629:
11630: for(i=1; i <=NDIM; i++)
11631: for(j=i+1;j<=NDIM;j++)
1.220 brouard 11632: matcov[i][j]=matcov[j][i];
1.126 brouard 11633:
11634: printf("\nCovariance matrix\n ");
1.203 brouard 11635: fprintf(ficlog,"\nCovariance matrix\n ");
1.126 brouard 11636: for(i=1; i <=NDIM; i++) {
11637: for(j=1;j<=NDIM;j++){
1.220 brouard 11638: printf("%f ",matcov[i][j]);
11639: fprintf(ficlog,"%f ",matcov[i][j]);
1.126 brouard 11640: }
1.203 brouard 11641: printf("\n "); fprintf(ficlog,"\n ");
1.126 brouard 11642: }
11643:
11644: printf("iter=%d MLE=%f Eq=%lf*exp(%lf*(age-%d))\n",iter,-gompertz(p),p[1],p[2],agegomp);
1.193 brouard 11645: for (i=1;i<=NDIM;i++) {
1.126 brouard 11646: printf("%f [%f ; %f]\n",p[i],p[i]-2*sqrt(matcov[i][i]),p[i]+2*sqrt(matcov[i][i]));
1.193 brouard 11647: fprintf(ficlog,"%f [%f ; %f]\n",p[i],p[i]-2*sqrt(matcov[i][i]),p[i]+2*sqrt(matcov[i][i]));
11648: }
1.126 brouard 11649: lsurv=vector(1,AGESUP);
11650: lpop=vector(1,AGESUP);
11651: tpop=vector(1,AGESUP);
11652: lsurv[agegomp]=100000;
11653:
11654: for (k=agegomp;k<=AGESUP;k++) {
11655: agemortsup=k;
11656: if (p[1]*exp(p[2]*(k-agegomp))>1) break;
11657: }
11658:
11659: for (k=agegomp;k<agemortsup;k++)
11660: lsurv[k+1]=lsurv[k]-lsurv[k]*(p[1]*exp(p[2]*(k-agegomp)));
11661:
11662: for (k=agegomp;k<agemortsup;k++){
11663: lpop[k]=(lsurv[k]+lsurv[k+1])/2.;
11664: sumlpop=sumlpop+lpop[k];
11665: }
11666:
11667: tpop[agegomp]=sumlpop;
11668: for (k=agegomp;k<(agemortsup-3);k++){
11669: /* tpop[k+1]=2;*/
11670: tpop[k+1]=tpop[k]-lpop[k];
11671: }
11672:
11673:
11674: printf("\nAge lx qx dx Lx Tx e(x)\n");
11675: for (k=agegomp;k<(agemortsup-2);k++)
11676: 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]);
11677:
11678:
11679: replace_back_to_slash(pathc,pathcd); /* Even gnuplot wants a / */
1.220 brouard 11680: ageminpar=50;
11681: agemaxpar=100;
1.194 brouard 11682: if(ageminpar == AGEOVERFLOW ||agemaxpar == AGEOVERFLOW){
11683: printf("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);
11686: fprintf(ficlog,"Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
11687: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
11688: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
1.220 brouard 11689: }else{
11690: printf("Warning! ageminpar %f and agemaxpar %f have been fixed because for simplification until it is fixed...\n\n",ageminpar,agemaxpar);
11691: 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 11692: printinggnuplotmort(fileresu, optionfilefiname,ageminpar,agemaxpar,fage, pathc,p);
1.220 brouard 11693: }
1.201 brouard 11694: printinghtmlmort(fileresu,title,datafile, firstpass, lastpass, \
1.126 brouard 11695: stepm, weightopt,\
11696: model,imx,p,matcov,agemortsup);
11697:
11698: free_vector(lsurv,1,AGESUP);
11699: free_vector(lpop,1,AGESUP);
11700: free_vector(tpop,1,AGESUP);
1.220 brouard 11701: free_matrix(ximort,1,NDIM,1,NDIM);
1.136 brouard 11702: free_ivector(cens,1,n);
11703: free_vector(agecens,1,n);
11704: free_ivector(dcwave,1,n);
1.220 brouard 11705: #ifdef GSL
1.136 brouard 11706: #endif
1.186 brouard 11707: } /* Endof if mle==-3 mortality only */
1.205 brouard 11708: /* Standard */
11709: else{ /* For mle !=- 3, could be 0 or 1 or 4 etc. */
11710: globpr=0;/* Computes sum of likelihood for globpr=1 and funcone */
11711: /* Computes likelihood for initial parameters, uses funcone to compute gpimx and gsw */
1.132 brouard 11712: likelione(ficres, p, npar, nlstate, &globpr, &ipmx, &sw, &fretone, funcone); /* Prints the contributions to the likelihood */
1.126 brouard 11713: printf("First Likeli=%12.6f ipmx=%ld sw=%12.6f",fretone,ipmx,sw);
11714: for (k=1; k<=npar;k++)
11715: printf(" %d %8.5f",k,p[k]);
11716: printf("\n");
1.205 brouard 11717: if(mle>=1){ /* Could be 1 or 2, Real Maximization */
11718: /* mlikeli uses func not funcone */
1.247 brouard 11719: /* for(i=1;i<nlstate;i++){ */
11720: /* /\*reducing xi for 1 to npar to 1 to ncovmodel; *\/ */
11721: /* mlikeli(ficres,p, ncovmodel, ncovmodel, nlstate, ftol, funcnoprod); */
11722: /* } */
1.205 brouard 11723: mlikeli(ficres,p, npar, ncovmodel, nlstate, ftol, func);
11724: }
11725: if(mle==0) {/* No optimization, will print the likelihoods for the datafile */
11726: globpr=0;/* Computes sum of likelihood for globpr=1 and funcone */
11727: /* Computes likelihood for initial parameters, uses funcone to compute gpimx and gsw */
11728: likelione(ficres, p, npar, nlstate, &globpr, &ipmx, &sw, &fretone, funcone); /* Prints the contributions to the likelihood */
11729: }
11730: globpr=1; /* again, to print the individual contributions using computed gpimx and gsw */
1.126 brouard 11731: likelione(ficres, p, npar, nlstate, &globpr, &ipmx, &sw, &fretone, funcone); /* Prints the contributions to the likelihood */
11732: printf("Second Likeli=%12.6f ipmx=%ld sw=%12.6f",fretone,ipmx,sw);
11733: for (k=1; k<=npar;k++)
11734: printf(" %d %8.5f",k,p[k]);
11735: printf("\n");
11736:
11737: /*--------- results files --------------*/
1.224 brouard 11738: 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 11739:
11740:
11741: fprintf(ficres,"# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
11742: printf("# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
11743: fprintf(ficlog,"# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
11744: for(i=1,jk=1; i <=nlstate; i++){
11745: for(k=1; k <=(nlstate+ndeath); k++){
1.225 brouard 11746: if (k != i) {
11747: printf("%d%d ",i,k);
11748: fprintf(ficlog,"%d%d ",i,k);
11749: fprintf(ficres,"%1d%1d ",i,k);
11750: for(j=1; j <=ncovmodel; j++){
11751: printf("%12.7f ",p[jk]);
11752: fprintf(ficlog,"%12.7f ",p[jk]);
11753: fprintf(ficres,"%12.7f ",p[jk]);
11754: jk++;
11755: }
11756: printf("\n");
11757: fprintf(ficlog,"\n");
11758: fprintf(ficres,"\n");
11759: }
1.126 brouard 11760: }
11761: }
1.203 brouard 11762: if(mle != 0){
11763: /* Computing hessian and covariance matrix only at a peak of the Likelihood, that is after optimization */
1.126 brouard 11764: ftolhess=ftol; /* Usually correct */
1.203 brouard 11765: hesscov(matcov, hess, p, npar, delti, ftolhess, func);
11766: 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");
11767: 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");
11768: for(i=1,jk=1; i <=nlstate; i++){
1.225 brouard 11769: for(k=1; k <=(nlstate+ndeath); k++){
11770: if (k != i) {
11771: printf("%d%d ",i,k);
11772: fprintf(ficlog,"%d%d ",i,k);
11773: for(j=1; j <=ncovmodel; j++){
11774: 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]));
11775: 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]));
11776: jk++;
11777: }
11778: printf("\n");
11779: fprintf(ficlog,"\n");
11780: }
11781: }
1.193 brouard 11782: }
1.203 brouard 11783: } /* end of hesscov and Wald tests */
1.225 brouard 11784:
1.203 brouard 11785: /* */
1.126 brouard 11786: fprintf(ficres,"# Scales (for hessian or gradient estimation)\n");
11787: printf("# Scales (for hessian or gradient estimation)\n");
11788: fprintf(ficlog,"# Scales (for hessian or gradient estimation)\n");
11789: for(i=1,jk=1; i <=nlstate; i++){
11790: for(j=1; j <=nlstate+ndeath; j++){
1.225 brouard 11791: if (j!=i) {
11792: fprintf(ficres,"%1d%1d",i,j);
11793: printf("%1d%1d",i,j);
11794: fprintf(ficlog,"%1d%1d",i,j);
11795: for(k=1; k<=ncovmodel;k++){
11796: printf(" %.5e",delti[jk]);
11797: fprintf(ficlog," %.5e",delti[jk]);
11798: fprintf(ficres," %.5e",delti[jk]);
11799: jk++;
11800: }
11801: printf("\n");
11802: fprintf(ficlog,"\n");
11803: fprintf(ficres,"\n");
11804: }
1.126 brouard 11805: }
11806: }
11807:
11808: 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 11809: if(mle >= 1) /* To big for the screen */
1.126 brouard 11810: 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");
11811: 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");
11812: /* # 121 Var(a12)\n\ */
11813: /* # 122 Cov(b12,a12) Var(b12)\n\ */
11814: /* # 131 Cov(a13,a12) Cov(a13,b12, Var(a13)\n\ */
11815: /* # 132 Cov(b13,a12) Cov(b13,b12, Cov(b13,a13) Var(b13)\n\ */
11816: /* # 212 Cov(a21,a12) Cov(a21,b12, Cov(a21,a13) Cov(a21,b13) Var(a21)\n\ */
11817: /* # 212 Cov(b21,a12) Cov(b21,b12, Cov(b21,a13) Cov(b21,b13) Cov(b21,a21) Var(b21)\n\ */
11818: /* # 232 Cov(a23,a12) Cov(a23,b12, Cov(a23,a13) Cov(a23,b13) Cov(a23,a21) Cov(a23,b21) Var(a23)\n\ */
11819: /* # 232 Cov(b23,a12) Cov(b23,b12) ... Var (b23)\n" */
11820:
11821:
11822: /* Just to have a covariance matrix which will be more understandable
11823: even is we still don't want to manage dictionary of variables
11824: */
11825: for(itimes=1;itimes<=2;itimes++){
11826: jj=0;
11827: for(i=1; i <=nlstate; i++){
1.225 brouard 11828: for(j=1; j <=nlstate+ndeath; j++){
11829: if(j==i) continue;
11830: for(k=1; k<=ncovmodel;k++){
11831: jj++;
11832: ca[0]= k+'a'-1;ca[1]='\0';
11833: if(itimes==1){
11834: if(mle>=1)
11835: printf("#%1d%1d%d",i,j,k);
11836: fprintf(ficlog,"#%1d%1d%d",i,j,k);
11837: fprintf(ficres,"#%1d%1d%d",i,j,k);
11838: }else{
11839: if(mle>=1)
11840: printf("%1d%1d%d",i,j,k);
11841: fprintf(ficlog,"%1d%1d%d",i,j,k);
11842: fprintf(ficres,"%1d%1d%d",i,j,k);
11843: }
11844: ll=0;
11845: for(li=1;li <=nlstate; li++){
11846: for(lj=1;lj <=nlstate+ndeath; lj++){
11847: if(lj==li) continue;
11848: for(lk=1;lk<=ncovmodel;lk++){
11849: ll++;
11850: if(ll<=jj){
11851: cb[0]= lk +'a'-1;cb[1]='\0';
11852: if(ll<jj){
11853: if(itimes==1){
11854: if(mle>=1)
11855: printf(" Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
11856: fprintf(ficlog," Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
11857: fprintf(ficres," Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
11858: }else{
11859: if(mle>=1)
11860: printf(" %.5e",matcov[jj][ll]);
11861: fprintf(ficlog," %.5e",matcov[jj][ll]);
11862: fprintf(ficres," %.5e",matcov[jj][ll]);
11863: }
11864: }else{
11865: if(itimes==1){
11866: if(mle>=1)
11867: printf(" Var(%s%1d%1d)",ca,i,j);
11868: fprintf(ficlog," Var(%s%1d%1d)",ca,i,j);
11869: fprintf(ficres," Var(%s%1d%1d)",ca,i,j);
11870: }else{
11871: if(mle>=1)
11872: printf(" %.7e",matcov[jj][ll]);
11873: fprintf(ficlog," %.7e",matcov[jj][ll]);
11874: fprintf(ficres," %.7e",matcov[jj][ll]);
11875: }
11876: }
11877: }
11878: } /* end lk */
11879: } /* end lj */
11880: } /* end li */
11881: if(mle>=1)
11882: printf("\n");
11883: fprintf(ficlog,"\n");
11884: fprintf(ficres,"\n");
11885: numlinepar++;
11886: } /* end k*/
11887: } /*end j */
1.126 brouard 11888: } /* end i */
11889: } /* end itimes */
11890:
11891: fflush(ficlog);
11892: fflush(ficres);
1.225 brouard 11893: while(fgets(line, MAXLINE, ficpar)) {
11894: /* If line starts with a # it is a comment */
11895: if (line[0] == '#') {
11896: numlinepar++;
11897: fputs(line,stdout);
11898: fputs(line,ficparo);
11899: fputs(line,ficlog);
11900: continue;
11901: }else
11902: break;
11903: }
11904:
1.209 brouard 11905: /* while((c=getc(ficpar))=='#' && c!= EOF){ */
11906: /* ungetc(c,ficpar); */
11907: /* fgets(line, MAXLINE, ficpar); */
11908: /* fputs(line,stdout); */
11909: /* fputs(line,ficparo); */
11910: /* } */
11911: /* ungetc(c,ficpar); */
1.126 brouard 11912:
11913: estepm=0;
1.209 brouard 11914: 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 11915:
11916: if (num_filled != 6) {
11917: 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);
11918: 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);
11919: goto end;
11920: }
11921: printf("agemin=%lf agemax=%lf bage=%lf fage=%lf estepm=%d ftolpl=%lf\n",ageminpar,agemaxpar, bage, fage, estepm, ftolpl);
11922: }
11923: /* ftolpl=6*ftol*1.e5; /\* 6.e-3 make convergences in less than 80 loops for the prevalence limit *\/ */
11924: /*ftolpl=6.e-4;*/ /* 6.e-3 make convergences in less than 80 loops for the prevalence limit */
11925:
1.209 brouard 11926: /* fscanf(ficpar,"agemin=%lf agemax=%lf bage=%lf fage=%lf estepm=%d ftolpl=%\n",&ageminpar,&agemaxpar, &bage, &fage, &estepm); */
1.126 brouard 11927: if (estepm==0 || estepm < stepm) estepm=stepm;
11928: if (fage <= 2) {
11929: bage = ageminpar;
11930: fage = agemaxpar;
11931: }
11932:
11933: fprintf(ficres,"# agemin agemax for life expectancy, bage fage (if mle==0 ie no data nor Max likelihood).\n");
1.211 brouard 11934: fprintf(ficres,"agemin=%.0f agemax=%.0f bage=%.0f fage=%.0f estepm=%d ftolpl=%e\n",ageminpar,agemaxpar,bage,fage, estepm, ftolpl);
11935: fprintf(ficparo,"agemin=%.0f agemax=%.0f bage=%.0f fage=%.0f estepm=%d, ftolpl=%e\n",ageminpar,agemaxpar,bage,fage, estepm, ftolpl);
1.220 brouard 11936:
1.186 brouard 11937: /* Other stuffs, more or less useful */
1.254 brouard 11938: while(fgets(line, MAXLINE, ficpar)) {
11939: /* If line starts with a # it is a comment */
11940: if (line[0] == '#') {
11941: numlinepar++;
11942: fputs(line,stdout);
11943: fputs(line,ficparo);
11944: fputs(line,ficlog);
11945: continue;
11946: }else
11947: break;
11948: }
11949:
11950: 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){
11951:
11952: if (num_filled != 7) {
11953: 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);
11954: 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);
11955: goto end;
11956: }
11957: printf("begin-prev-date=%.lf/%.lf/%.lf end-prev-date=%.lf/%.lf/%.lf mov_average=%d\n",jprev1, mprev1,anprev1,jprev2, mprev2,anprev2,mobilav);
11958: 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);
11959: 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);
11960: 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 11961: }
1.254 brouard 11962:
11963: while(fgets(line, MAXLINE, ficpar)) {
11964: /* If line starts with a # it is a comment */
11965: if (line[0] == '#') {
11966: numlinepar++;
11967: fputs(line,stdout);
11968: fputs(line,ficparo);
11969: fputs(line,ficlog);
11970: continue;
11971: }else
11972: break;
1.126 brouard 11973: }
11974:
11975:
11976: dateprev1=anprev1+(mprev1-1)/12.+(jprev1-1)/365.;
11977: dateprev2=anprev2+(mprev2-1)/12.+(jprev2-1)/365.;
11978:
1.254 brouard 11979: if((num_filled=sscanf(line,"pop_based=%d\n",&popbased)) !=EOF){
11980: if (num_filled != 1) {
11981: 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);
11982: 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);
11983: goto end;
11984: }
11985: printf("pop_based=%d\n",popbased);
11986: fprintf(ficlog,"pop_based=%d\n",popbased);
11987: fprintf(ficparo,"pop_based=%d\n",popbased);
11988: fprintf(ficres,"pop_based=%d\n",popbased);
11989: }
11990:
1.258 brouard 11991: /* Results */
11992: nresult=0;
11993: do{
11994: if(!fgets(line, MAXLINE, ficpar)){
11995: endishere=1;
11996: parameterline=14;
11997: }else if (line[0] == '#') {
11998: /* If line starts with a # it is a comment */
1.254 brouard 11999: numlinepar++;
12000: fputs(line,stdout);
12001: fputs(line,ficparo);
12002: fputs(line,ficlog);
12003: continue;
1.258 brouard 12004: }else if(sscanf(line,"prevforecast=%[^\n]\n",modeltemp))
12005: parameterline=11;
12006: else if(sscanf(line,"backcast=%[^\n]\n",modeltemp))
12007: parameterline=12;
12008: else if(sscanf(line,"result:%[^\n]\n",modeltemp))
12009: parameterline=13;
12010: else{
12011: parameterline=14;
1.254 brouard 12012: }
1.258 brouard 12013: switch (parameterline){
12014: case 11:
12015: 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){
12016: if (num_filled != 8) {
12017: 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);
12018: 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);
12019: goto end;
12020: }
12021: 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);
12022: 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);
12023: 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);
12024: 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);
12025: /* day and month of proj2 are not used but only year anproj2.*/
12026: }
1.254 brouard 12027: break;
1.258 brouard 12028: case 12:
12029: /*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);*/
12030: 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){
12031: if (num_filled != 8) {
1.262 brouard 12032: 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);
12033: 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 12034: goto end;
12035: }
12036: 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);
12037: 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);
12038: 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);
12039: 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);
12040: /* day and month of proj2 are not used but only year anproj2.*/
12041: }
1.230 brouard 12042: break;
1.258 brouard 12043: case 13:
12044: if((num_filled=sscanf(line,"result:%[^\n]\n",resultline)) !=EOF){
12045: if (num_filled == 0){
12046: resultline[0]='\0';
12047: printf("Warning %d: no result line! It should be at minimum 'result: V2=0 V1=1 or result:.\n%s\n", num_filled, line);
12048: 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);
12049: break;
12050: } else if (num_filled != 1){
12051: printf("ERROR %d: result line! It should be at minimum 'result: V2=0 V1=1 or result:.' %s\n",num_filled, line);
12052: fprintf(ficlog,"ERROR %d: result line! It should be at minimum 'result: V2=0 V1=1 or result:.' %s\n",num_filled, line);
12053: }
12054: nresult++; /* Sum of resultlines */
12055: printf("Result %d: result=%s\n",nresult, resultline);
12056: if(nresult > MAXRESULTLINES){
12057: printf("ERROR: Current version of IMaCh limits the number of resultlines to %d, you used %d\n",MAXRESULTLINES,nresult);
12058: fprintf(ficlog,"ERROR: Current version of IMaCh limits the number of resultlines to %d, you used %d\n",MAXRESULTLINES,nresult);
12059: goto end;
12060: }
12061: decoderesult(resultline, nresult); /* Fills TKresult[nresult] combination and Tresult[nresult][k4+1] combination values */
12062: fprintf(ficparo,"result: %s\n",resultline);
12063: fprintf(ficres,"result: %s\n",resultline);
12064: fprintf(ficlog,"result: %s\n",resultline);
1.230 brouard 12065: break;
1.258 brouard 12066: case 14:
1.259 brouard 12067: if(ncovmodel >2 && nresult==0 ){
12068: printf("ERROR: no result lines! It should be at minimum 'result: V2=0 V1=1 or result:.' %s\n",line);
1.258 brouard 12069: goto end;
12070: }
1.259 brouard 12071: break;
1.258 brouard 12072: default:
12073: nresult=1;
12074: decoderesult(".",nresult ); /* No covariate */
12075: }
12076: } /* End switch parameterline */
12077: }while(endishere==0); /* End do */
1.126 brouard 12078:
1.230 brouard 12079: /* freqsummary(fileres, agemin, agemax, s, agev, nlstate, imx,Tvaraff,nbcode, ncodemax,mint,anint); */
1.145 brouard 12080: /* ,dateprev1,dateprev2,jprev1, mprev1,anprev1,jprev2, mprev2,anprev2); */
1.126 brouard 12081:
12082: replace_back_to_slash(pathc,pathcd); /* Even gnuplot wants a / */
1.194 brouard 12083: if(ageminpar == AGEOVERFLOW ||agemaxpar == -AGEOVERFLOW){
1.230 brouard 12084: printf("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);
1.230 brouard 12087: fprintf(ficlog,"Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
1.194 brouard 12088: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
12089: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
1.220 brouard 12090: }else{
1.270 brouard 12091: /* printinggnuplot(fileresu, optionfilefiname,ageminpar,agemaxpar,fage, prevfcast, backcast, pathc,p, (int)anproj1-(int)agemin, (int)anback1-(int)agemax+1); */
12092: printinggnuplot(fileresu, optionfilefiname,ageminpar,agemaxpar,bage, fage, prevfcast, backcast, pathc,p, (int)anproj1-bage, (int)anback1-fage);
1.220 brouard 12093: }
12094: printinghtml(fileresu,title,datafile, firstpass, lastpass, stepm, weightopt, \
1.258 brouard 12095: model,imx,jmin,jmax,jmean,rfileres,popforecast,mobilav,prevfcast,mobilavproj,backcast, estepm, \
1.225 brouard 12096: jprev1,mprev1,anprev1,dateprev1,jprev2,mprev2,anprev2,dateprev2);
1.220 brouard 12097:
1.225 brouard 12098: /*------------ free_vector -------------*/
12099: /* chdir(path); */
1.220 brouard 12100:
1.215 brouard 12101: /* free_ivector(wav,1,imx); */ /* Moved after last prevalence call */
12102: /* free_imatrix(dh,1,lastpass-firstpass+2,1,imx); */
12103: /* free_imatrix(bh,1,lastpass-firstpass+2,1,imx); */
12104: /* free_imatrix(mw,1,lastpass-firstpass+2,1,imx); */
1.126 brouard 12105: free_lvector(num,1,n);
12106: free_vector(agedc,1,n);
12107: /*free_matrix(covar,0,NCOVMAX,1,n);*/
12108: /*free_matrix(covar,1,NCOVMAX,1,n);*/
12109: fclose(ficparo);
12110: fclose(ficres);
1.220 brouard 12111:
12112:
1.186 brouard 12113: /* Other results (useful)*/
1.220 brouard 12114:
12115:
1.126 brouard 12116: /*--------------- Prevalence limit (period or stable prevalence) --------------*/
1.180 brouard 12117: /*#include "prevlim.h"*/ /* Use ficrespl, ficlog */
12118: prlim=matrix(1,nlstate,1,nlstate);
1.209 brouard 12119: prevalence_limit(p, prlim, ageminpar, agemaxpar, ftolpl, &ncvyear);
1.126 brouard 12120: fclose(ficrespl);
12121:
12122: /*------------- h Pij x at various ages ------------*/
1.180 brouard 12123: /*#include "hpijx.h"*/
12124: hPijx(p, bage, fage);
1.145 brouard 12125: fclose(ficrespij);
1.227 brouard 12126:
1.220 brouard 12127: /* ncovcombmax= pow(2,cptcoveff); */
1.219 brouard 12128: /*-------------- Variance of one-step probabilities---*/
1.145 brouard 12129: k=1;
1.126 brouard 12130: varprob(optionfilefiname, matcov, p, delti, nlstate, bage, fage,k,Tvar,nbcode, ncodemax,strstart);
1.227 brouard 12131:
1.269 brouard 12132: /* Prevalence for each covariate combination in probs[age][status][cov] */
12133: probs= ma3x(AGEINF,AGESUP,1,nlstate+ndeath, 1,ncovcombmax);
12134: for(i=AGEINF;i<=AGESUP;i++)
1.219 brouard 12135: for(j=1;j<=nlstate+ndeath;j++) /* ndeath is useless but a necessity to be compared with mobaverages */
1.225 brouard 12136: for(k=1;k<=ncovcombmax;k++)
12137: probs[i][j][k]=0.;
1.269 brouard 12138: prevalence(probs, ageminpar, agemaxpar, s, agev, nlstate, imx, Tvar, nbcode,
12139: ncodemax, mint, anint, dateprev1, dateprev2, firstpass, lastpass);
1.219 brouard 12140: if (mobilav!=0 ||mobilavproj !=0 ) {
1.269 brouard 12141: mobaverages= ma3x(AGEINF, AGESUP,1,nlstate+ndeath, 1,ncovcombmax);
12142: for(i=AGEINF;i<=AGESUP;i++)
1.268 brouard 12143: for(j=1;j<=nlstate+ndeath;j++)
1.227 brouard 12144: for(k=1;k<=ncovcombmax;k++)
12145: mobaverages[i][j][k]=0.;
1.219 brouard 12146: mobaverage=mobaverages;
12147: if (mobilav!=0) {
1.235 brouard 12148: printf("Movingaveraging observed prevalence\n");
1.258 brouard 12149: fprintf(ficlog,"Movingaveraging observed prevalence\n");
1.227 brouard 12150: if (movingaverage(probs, ageminpar, agemaxpar, mobaverage, mobilav)!=0){
12151: fprintf(ficlog," Error in movingaverage mobilav=%d\n",mobilav);
12152: printf(" Error in movingaverage mobilav=%d\n",mobilav);
12153: }
1.269 brouard 12154: } else if (mobilavproj !=0) {
1.235 brouard 12155: printf("Movingaveraging projected observed prevalence\n");
1.258 brouard 12156: fprintf(ficlog,"Movingaveraging projected observed prevalence\n");
1.227 brouard 12157: if (movingaverage(probs, ageminpar, agemaxpar, mobaverage, mobilavproj)!=0){
12158: fprintf(ficlog," Error in movingaverage mobilavproj=%d\n",mobilavproj);
12159: printf(" Error in movingaverage mobilavproj=%d\n",mobilavproj);
12160: }
1.269 brouard 12161: }else{
12162: printf("Internal error moving average\n");
12163: fflush(stdout);
12164: exit(1);
1.219 brouard 12165: }
12166: }/* end if moving average */
1.227 brouard 12167:
1.126 brouard 12168: /*---------- Forecasting ------------------*/
12169: if(prevfcast==1){
12170: /* if(stepm ==1){*/
1.269 brouard 12171: prevforecast(fileresu, anproj1, mproj1, jproj1, agemin, agemax, dateprev1, dateprev2, mobilavproj, mobaverage, bage, fage, firstpass, lastpass, anproj2, p, cptcoveff);
1.126 brouard 12172: }
1.269 brouard 12173:
12174: /* Backcasting */
1.217 brouard 12175: if(backcast==1){
1.219 brouard 12176: ddnewms=matrix(1,nlstate+ndeath,1,nlstate+ndeath);
12177: ddoldms=matrix(1,nlstate+ndeath,1,nlstate+ndeath);
12178: ddsavms=matrix(1,nlstate+ndeath,1,nlstate+ndeath);
12179:
12180: /*--------------- Back Prevalence limit (period or stable prevalence) --------------*/
12181:
12182: bprlim=matrix(1,nlstate,1,nlstate);
1.269 brouard 12183:
1.219 brouard 12184: back_prevalence_limit(p, bprlim, ageminpar, agemaxpar, ftolpl, &ncvyear, dateprev1, dateprev2, firstpass, lastpass, mobilavproj);
12185: fclose(ficresplb);
12186:
1.222 brouard 12187: hBijx(p, bage, fage, mobaverage);
12188: fclose(ficrespijb);
1.219 brouard 12189:
1.269 brouard 12190: prevbackforecast(fileresu, mobaverage, anback1, mback1, jback1, agemin, agemax, dateprev1, dateprev2,
12191: mobilavproj, bage, fage, firstpass, lastpass, anback2, p, cptcoveff);
12192: varbprlim(fileresu, nresult, mobaverage, mobilavproj, bage, fage, bprlim, &ncvyear, ftolpl, p, matcov, delti, stepm, cptcoveff);
1.268 brouard 12193:
12194:
1.269 brouard 12195: free_matrix(bprlim,1,nlstate,1,nlstate); /*here or after loop ? */
1.219 brouard 12196: free_matrix(ddnewms, 1, nlstate+ndeath, 1, nlstate+ndeath);
12197: free_matrix(ddsavms, 1, nlstate+ndeath, 1, nlstate+ndeath);
12198: free_matrix(ddoldms, 1, nlstate+ndeath, 1, nlstate+ndeath);
1.269 brouard 12199: } /* end Backcasting */
1.268 brouard 12200:
1.186 brouard 12201:
12202: /* ------ Other prevalence ratios------------ */
1.126 brouard 12203:
1.215 brouard 12204: free_ivector(wav,1,imx);
12205: free_imatrix(dh,1,lastpass-firstpass+2,1,imx);
12206: free_imatrix(bh,1,lastpass-firstpass+2,1,imx);
12207: free_imatrix(mw,1,lastpass-firstpass+2,1,imx);
1.218 brouard 12208:
12209:
1.127 brouard 12210: /*---------- Health expectancies, no variances ------------*/
1.218 brouard 12211:
1.201 brouard 12212: strcpy(filerese,"E_");
12213: strcat(filerese,fileresu);
1.126 brouard 12214: if((ficreseij=fopen(filerese,"w"))==NULL) {
12215: printf("Problem with Health Exp. resultfile: %s\n", filerese); exit(0);
12216: fprintf(ficlog,"Problem with Health Exp. resultfile: %s\n", filerese); exit(0);
12217: }
1.208 brouard 12218: printf("Computing Health Expectancies: result on file '%s' ...", filerese);fflush(stdout);
12219: fprintf(ficlog,"Computing Health Expectancies: result on file '%s' ...", filerese);fflush(ficlog);
1.238 brouard 12220:
12221: pstamp(ficreseij);
1.219 brouard 12222:
1.235 brouard 12223: i1=pow(2,cptcoveff); /* Number of combination of dummy covariates */
12224: if (cptcovn < 1){i1=1;}
12225:
12226: for(nres=1; nres <= nresult; nres++) /* For each resultline */
12227: for(k=1; k<=i1;k++){ /* For any combination of dummy covariates, fixed and varying */
1.253 brouard 12228: if(i1 != 1 && TKresult[nres]!= k)
1.235 brouard 12229: continue;
1.219 brouard 12230: fprintf(ficreseij,"\n#****** ");
1.235 brouard 12231: printf("\n#****** ");
1.225 brouard 12232: for(j=1;j<=cptcoveff;j++) {
1.227 brouard 12233: fprintf(ficreseij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
1.235 brouard 12234: printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
12235: }
12236: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
12237: printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
12238: fprintf(ficreseij," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
1.219 brouard 12239: }
12240: fprintf(ficreseij,"******\n");
1.235 brouard 12241: printf("******\n");
1.219 brouard 12242:
12243: eij=ma3x(1,nlstate,1,nlstate,(int) bage, (int) fage);
12244: oldm=oldms;savm=savms;
1.235 brouard 12245: evsij(eij, p, nlstate, stepm, (int) bage, (int)fage, oldm, savm, k, estepm, strstart, nres);
1.127 brouard 12246:
1.219 brouard 12247: free_ma3x(eij,1,nlstate,1,nlstate,(int) bage, (int)fage);
1.127 brouard 12248: }
12249: fclose(ficreseij);
1.208 brouard 12250: printf("done evsij\n");fflush(stdout);
12251: fprintf(ficlog,"done evsij\n");fflush(ficlog);
1.269 brouard 12252:
1.218 brouard 12253:
1.227 brouard 12254: /*---------- State-specific expectancies and variances ------------*/
1.218 brouard 12255:
1.201 brouard 12256: strcpy(filerest,"T_");
12257: strcat(filerest,fileresu);
1.127 brouard 12258: if((ficrest=fopen(filerest,"w"))==NULL) {
12259: printf("Problem with total LE resultfile: %s\n", filerest);goto end;
12260: fprintf(ficlog,"Problem with total LE resultfile: %s\n", filerest);goto end;
12261: }
1.208 brouard 12262: printf("Computing Total Life expectancies with their standard errors: file '%s' ...\n", filerest); fflush(stdout);
12263: fprintf(ficlog,"Computing Total Life expectancies with their standard errors: file '%s' ...\n", filerest); fflush(ficlog);
1.201 brouard 12264: strcpy(fileresstde,"STDE_");
12265: strcat(fileresstde,fileresu);
1.126 brouard 12266: if((ficresstdeij=fopen(fileresstde,"w"))==NULL) {
1.227 brouard 12267: printf("Problem with State specific Exp. and std errors resultfile: %s\n", fileresstde); exit(0);
12268: fprintf(ficlog,"Problem with State specific Exp. and std errors resultfile: %s\n", fileresstde); exit(0);
1.126 brouard 12269: }
1.227 brouard 12270: printf(" Computing State-specific Expectancies and standard errors: result on file '%s' \n", fileresstde);
12271: fprintf(ficlog," Computing State-specific Expectancies and standard errors: result on file '%s' \n", fileresstde);
1.126 brouard 12272:
1.201 brouard 12273: strcpy(filerescve,"CVE_");
12274: strcat(filerescve,fileresu);
1.126 brouard 12275: if((ficrescveij=fopen(filerescve,"w"))==NULL) {
1.227 brouard 12276: printf("Problem with Covar. State-specific Exp. resultfile: %s\n", filerescve); exit(0);
12277: fprintf(ficlog,"Problem with Covar. State-specific Exp. resultfile: %s\n", filerescve); exit(0);
1.126 brouard 12278: }
1.227 brouard 12279: printf(" Computing Covar. of State-specific Expectancies: result on file '%s' \n", filerescve);
12280: fprintf(ficlog," Computing Covar. of State-specific Expectancies: result on file '%s' \n", filerescve);
1.126 brouard 12281:
1.201 brouard 12282: strcpy(fileresv,"V_");
12283: strcat(fileresv,fileresu);
1.126 brouard 12284: if((ficresvij=fopen(fileresv,"w"))==NULL) {
12285: printf("Problem with variance resultfile: %s\n", fileresv);exit(0);
12286: fprintf(ficlog,"Problem with variance resultfile: %s\n", fileresv);exit(0);
12287: }
1.227 brouard 12288: printf(" Computing Variance-covariance of State-specific Expectancies: file '%s' ... ", fileresv);fflush(stdout);
12289: fprintf(ficlog," Computing Variance-covariance of State-specific Expectancies: file '%s' ... ", fileresv);fflush(ficlog);
1.126 brouard 12290:
1.235 brouard 12291: i1=pow(2,cptcoveff); /* Number of combination of dummy covariates */
12292: if (cptcovn < 1){i1=1;}
12293:
12294: for(nres=1; nres <= nresult; nres++) /* For each resultline */
12295: for(k=1; k<=i1;k++){ /* For any combination of dummy covariates, fixed and varying */
1.253 brouard 12296: if(i1 != 1 && TKresult[nres]!= k)
1.235 brouard 12297: continue;
1.242 brouard 12298: printf("\n#****** Result for:");
12299: fprintf(ficrest,"\n#****** Result for:");
12300: fprintf(ficlog,"\n#****** Result for:");
1.227 brouard 12301: for(j=1;j<=cptcoveff;j++){
12302: printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
12303: fprintf(ficrest,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
12304: fprintf(ficlog,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
12305: }
1.235 brouard 12306: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
12307: printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
12308: fprintf(ficrest," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
12309: fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
12310: }
1.208 brouard 12311: fprintf(ficrest,"******\n");
1.227 brouard 12312: fprintf(ficlog,"******\n");
12313: printf("******\n");
1.208 brouard 12314:
12315: fprintf(ficresstdeij,"\n#****** ");
12316: fprintf(ficrescveij,"\n#****** ");
1.225 brouard 12317: for(j=1;j<=cptcoveff;j++) {
1.227 brouard 12318: fprintf(ficresstdeij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
12319: fprintf(ficrescveij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
1.208 brouard 12320: }
1.235 brouard 12321: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
12322: fprintf(ficresstdeij," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
12323: fprintf(ficrescveij," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
12324: }
1.208 brouard 12325: fprintf(ficresstdeij,"******\n");
12326: fprintf(ficrescveij,"******\n");
12327:
12328: fprintf(ficresvij,"\n#****** ");
1.238 brouard 12329: /* pstamp(ficresvij); */
1.225 brouard 12330: for(j=1;j<=cptcoveff;j++)
1.227 brouard 12331: fprintf(ficresvij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
1.235 brouard 12332: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
12333: fprintf(ficresvij," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
12334: }
1.208 brouard 12335: fprintf(ficresvij,"******\n");
12336:
12337: eij=ma3x(1,nlstate,1,nlstate,(int) bage, (int) fage);
12338: oldm=oldms;savm=savms;
1.235 brouard 12339: printf(" cvevsij ");
12340: fprintf(ficlog, " cvevsij ");
12341: cvevsij(eij, p, nlstate, stepm, (int) bage, (int)fage, oldm, savm, k, estepm, delti, matcov, strstart, nres);
1.208 brouard 12342: printf(" end cvevsij \n ");
12343: fprintf(ficlog, " end cvevsij \n ");
12344:
12345: /*
12346: */
12347: /* goto endfree; */
12348:
12349: vareij=ma3x(1,nlstate,1,nlstate,(int) bage, (int) fage);
12350: pstamp(ficrest);
12351:
1.269 brouard 12352: epj=vector(1,nlstate+1);
1.208 brouard 12353: for(vpopbased=0; vpopbased <= popbased; vpopbased++){ /* Done for vpopbased=0 and vpopbased=1 if popbased==1*/
1.227 brouard 12354: oldm=oldms;savm=savms; /* ZZ Segmentation fault */
12355: cptcod= 0; /* To be deleted */
12356: printf("varevsij vpopbased=%d \n",vpopbased);
12357: fprintf(ficlog, "varevsij vpopbased=%d \n",vpopbased);
1.235 brouard 12358: 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 12359: 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 ");
12360: if(vpopbased==1)
12361: 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);
12362: else
12363: fprintf(ficrest,"the age specific period (stable) prevalences in each health state \n");
12364: fprintf(ficrest,"# Age popbased mobilav e.. (std) ");
12365: for (i=1;i<=nlstate;i++) fprintf(ficrest,"e.%d (std) ",i);
12366: fprintf(ficrest,"\n");
12367: /* printf("Which p?\n"); for(i=1;i<=npar;i++)printf("p[i=%d]=%lf,",i,p[i]);printf("\n"); */
12368: printf("Computing age specific period (stable) prevalences in each health state \n");
12369: fprintf(ficlog,"Computing age specific period (stable) prevalences in each health state \n");
12370: for(age=bage; age <=fage ;age++){
1.235 brouard 12371: prevalim(prlim, nlstate, p, age, oldm, savm, ftolpl, &ncvyear, k, nres); /*ZZ Is it the correct prevalim */
1.227 brouard 12372: if (vpopbased==1) {
12373: if(mobilav ==0){
12374: for(i=1; i<=nlstate;i++)
12375: prlim[i][i]=probs[(int)age][i][k];
12376: }else{ /* mobilav */
12377: for(i=1; i<=nlstate;i++)
12378: prlim[i][i]=mobaverage[(int)age][i][k];
12379: }
12380: }
1.219 brouard 12381:
1.227 brouard 12382: fprintf(ficrest," %4.0f %d %d",age, vpopbased, mobilav);
12383: /* fprintf(ficrest," %4.0f %d %d %d %d",age, vpopbased, mobilav,Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]); */ /* to be done */
12384: /* printf(" age %4.0f ",age); */
12385: for(j=1, epj[nlstate+1]=0.;j <=nlstate;j++){
12386: for(i=1, epj[j]=0.;i <=nlstate;i++) {
12387: epj[j] += prlim[i][i]*eij[i][j][(int)age];
12388: /*ZZZ printf("%lf %lf ", prlim[i][i] ,eij[i][j][(int)age]);*/
12389: /* printf("%lf %lf ", prlim[i][i] ,eij[i][j][(int)age]); */
12390: }
12391: epj[nlstate+1] +=epj[j];
12392: }
12393: /* printf(" age %4.0f \n",age); */
1.219 brouard 12394:
1.227 brouard 12395: for(i=1, vepp=0.;i <=nlstate;i++)
12396: for(j=1;j <=nlstate;j++)
12397: vepp += vareij[i][j][(int)age];
12398: fprintf(ficrest," %7.3f (%7.3f)", epj[nlstate+1],sqrt(vepp));
12399: for(j=1;j <=nlstate;j++){
12400: fprintf(ficrest," %7.3f (%7.3f)", epj[j],sqrt(vareij[j][j][(int)age]));
12401: }
12402: fprintf(ficrest,"\n");
12403: }
1.208 brouard 12404: } /* End vpopbased */
1.269 brouard 12405: free_vector(epj,1,nlstate+1);
1.208 brouard 12406: free_ma3x(eij,1,nlstate,1,nlstate,(int) bage, (int)fage);
12407: free_ma3x(vareij,1,nlstate,1,nlstate,(int) bage, (int)fage);
1.235 brouard 12408: printf("done selection\n");fflush(stdout);
12409: fprintf(ficlog,"done selection\n");fflush(ficlog);
1.208 brouard 12410:
1.235 brouard 12411: } /* End k selection */
1.227 brouard 12412:
12413: printf("done State-specific expectancies\n");fflush(stdout);
12414: fprintf(ficlog,"done State-specific expectancies\n");fflush(ficlog);
12415:
1.269 brouard 12416: /* variance-covariance of period prevalence*/
12417: varprlim(fileresu, nresult, mobaverage, mobilavproj, bage, fage, prlim, &ncvyear, ftolpl, p, matcov, delti, stepm, cptcoveff);
1.268 brouard 12418:
1.227 brouard 12419:
12420: free_vector(weight,1,n);
12421: free_imatrix(Tvard,1,NCOVMAX,1,2);
12422: free_imatrix(s,1,maxwav+1,1,n);
12423: free_matrix(anint,1,maxwav,1,n);
12424: free_matrix(mint,1,maxwav,1,n);
12425: free_ivector(cod,1,n);
12426: free_ivector(tab,1,NCOVMAX);
12427: fclose(ficresstdeij);
12428: fclose(ficrescveij);
12429: fclose(ficresvij);
12430: fclose(ficrest);
12431: fclose(ficpar);
12432:
12433:
1.126 brouard 12434: /*---------- End : free ----------------*/
1.219 brouard 12435: if (mobilav!=0 ||mobilavproj !=0)
1.269 brouard 12436: free_ma3x(mobaverages,AGEINF, AGESUP,1,nlstate+ndeath, 1,ncovcombmax); /* We need to have a squared matrix with prevalence of the dead! */
12437: free_ma3x(probs,AGEINF,AGESUP,1,nlstate+ndeath, 1,ncovcombmax);
1.220 brouard 12438: free_matrix(prlim,1,nlstate,1,nlstate); /*here or after loop ? */
12439: free_matrix(pmmij,1,nlstate+ndeath,1,nlstate+ndeath);
1.126 brouard 12440: } /* mle==-3 arrives here for freeing */
1.227 brouard 12441: /* endfree:*/
12442: free_matrix(oldms, 1,nlstate+ndeath,1,nlstate+ndeath);
12443: free_matrix(newms, 1,nlstate+ndeath,1,nlstate+ndeath);
12444: free_matrix(savms, 1,nlstate+ndeath,1,nlstate+ndeath);
1.268 brouard 12445: if(ntv+nqtv>=1)free_ma3x(cotvar,1,maxwav,1,ntv+nqtv,1,n);
12446: if(nqtv>=1)free_ma3x(cotqvar,1,maxwav,1,nqtv,1,n);
12447: if(nqv>=1)free_matrix(coqvar,1,nqv,1,n);
1.227 brouard 12448: free_matrix(covar,0,NCOVMAX,1,n);
12449: free_matrix(matcov,1,npar,1,npar);
12450: free_matrix(hess,1,npar,1,npar);
12451: /*free_vector(delti,1,npar);*/
12452: free_ma3x(delti3,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
12453: free_matrix(agev,1,maxwav,1,imx);
1.269 brouard 12454: free_ma3x(paramstart,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
1.227 brouard 12455: free_ma3x(param,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
12456:
12457: free_ivector(ncodemax,1,NCOVMAX);
12458: free_ivector(ncodemaxwundef,1,NCOVMAX);
12459: free_ivector(Dummy,-1,NCOVMAX);
12460: free_ivector(Fixed,-1,NCOVMAX);
1.238 brouard 12461: free_ivector(DummyV,1,NCOVMAX);
12462: free_ivector(FixedV,1,NCOVMAX);
1.227 brouard 12463: free_ivector(Typevar,-1,NCOVMAX);
12464: free_ivector(Tvar,1,NCOVMAX);
1.234 brouard 12465: free_ivector(TvarsQ,1,NCOVMAX);
12466: free_ivector(TvarsQind,1,NCOVMAX);
12467: free_ivector(TvarsD,1,NCOVMAX);
12468: free_ivector(TvarsDind,1,NCOVMAX);
1.231 brouard 12469: free_ivector(TvarFD,1,NCOVMAX);
12470: free_ivector(TvarFDind,1,NCOVMAX);
1.232 brouard 12471: free_ivector(TvarF,1,NCOVMAX);
12472: free_ivector(TvarFind,1,NCOVMAX);
12473: free_ivector(TvarV,1,NCOVMAX);
12474: free_ivector(TvarVind,1,NCOVMAX);
12475: free_ivector(TvarA,1,NCOVMAX);
12476: free_ivector(TvarAind,1,NCOVMAX);
1.231 brouard 12477: free_ivector(TvarFQ,1,NCOVMAX);
12478: free_ivector(TvarFQind,1,NCOVMAX);
12479: free_ivector(TvarVD,1,NCOVMAX);
12480: free_ivector(TvarVDind,1,NCOVMAX);
12481: free_ivector(TvarVQ,1,NCOVMAX);
12482: free_ivector(TvarVQind,1,NCOVMAX);
1.230 brouard 12483: free_ivector(Tvarsel,1,NCOVMAX);
12484: free_vector(Tvalsel,1,NCOVMAX);
1.227 brouard 12485: free_ivector(Tposprod,1,NCOVMAX);
12486: free_ivector(Tprod,1,NCOVMAX);
12487: free_ivector(Tvaraff,1,NCOVMAX);
12488: free_ivector(invalidvarcomb,1,ncovcombmax);
12489: free_ivector(Tage,1,NCOVMAX);
12490: free_ivector(Tmodelind,1,NCOVMAX);
1.228 brouard 12491: free_ivector(TmodelInvind,1,NCOVMAX);
12492: free_ivector(TmodelInvQind,1,NCOVMAX);
1.227 brouard 12493:
12494: free_imatrix(nbcode,0,NCOVMAX,0,NCOVMAX);
12495: /* free_imatrix(codtab,1,100,1,10); */
1.126 brouard 12496: fflush(fichtm);
12497: fflush(ficgp);
12498:
1.227 brouard 12499:
1.126 brouard 12500: if((nberr >0) || (nbwarn>0)){
1.216 brouard 12501: printf("End of Imach with %d errors and/or %d warnings. Please look at the log file for details.\n",nberr,nbwarn);
12502: 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 12503: }else{
12504: printf("End of Imach\n");
12505: fprintf(ficlog,"End of Imach\n");
12506: }
12507: printf("See log file on %s\n",filelog);
12508: /* gettimeofday(&end_time, (struct timezone*)0);*/ /* after time */
1.157 brouard 12509: /*(void) gettimeofday(&end_time,&tzp);*/
12510: rend_time = time(NULL);
12511: end_time = *localtime(&rend_time);
12512: /* tml = *localtime(&end_time.tm_sec); */
12513: strcpy(strtend,asctime(&end_time));
1.126 brouard 12514: printf("Local time at start %s\nLocal time at end %s",strstart, strtend);
12515: fprintf(ficlog,"Local time at start %s\nLocal time at end %s\n",strstart, strtend);
1.157 brouard 12516: printf("Total time used %s\n", asc_diff_time(rend_time -rstart_time,tmpout));
1.227 brouard 12517:
1.157 brouard 12518: printf("Total time was %.0lf Sec.\n", difftime(rend_time,rstart_time));
12519: fprintf(ficlog,"Total time used %s\n", asc_diff_time(rend_time -rstart_time,tmpout));
12520: fprintf(ficlog,"Total time was %.0lf Sec.\n", difftime(rend_time,rstart_time));
1.126 brouard 12521: /* printf("Total time was %d uSec.\n", total_usecs);*/
12522: /* if(fileappend(fichtm,optionfilehtm)){ */
12523: fprintf(fichtm,"<br>Local time at start %s<br>Local time at end %s<br>\n</body></html>",strstart, strtend);
12524: fclose(fichtm);
12525: fprintf(fichtmcov,"<br>Local time at start %s<br>Local time at end %s<br>\n</body></html>",strstart, strtend);
12526: fclose(fichtmcov);
12527: fclose(ficgp);
12528: fclose(ficlog);
12529: /*------ End -----------*/
1.227 brouard 12530:
12531:
12532: printf("Before Current directory %s!\n",pathcd);
1.184 brouard 12533: #ifdef WIN32
1.227 brouard 12534: if (_chdir(pathcd) != 0)
12535: printf("Can't move to directory %s!\n",path);
12536: if(_getcwd(pathcd,MAXLINE) > 0)
1.184 brouard 12537: #else
1.227 brouard 12538: if(chdir(pathcd) != 0)
12539: printf("Can't move to directory %s!\n", path);
12540: if (getcwd(pathcd, MAXLINE) > 0)
1.184 brouard 12541: #endif
1.126 brouard 12542: printf("Current directory %s!\n",pathcd);
12543: /*strcat(plotcmd,CHARSEPARATOR);*/
12544: sprintf(plotcmd,"gnuplot");
1.157 brouard 12545: #ifdef _WIN32
1.126 brouard 12546: sprintf(plotcmd,"\"%sgnuplot.exe\"",pathimach);
12547: #endif
12548: if(!stat(plotcmd,&info)){
1.158 brouard 12549: printf("Error or gnuplot program not found: '%s'\n",plotcmd);fflush(stdout);
1.126 brouard 12550: if(!stat(getenv("GNUPLOTBIN"),&info)){
1.158 brouard 12551: printf("Error or gnuplot program not found: '%s' Environment GNUPLOTBIN not set.\n",plotcmd);fflush(stdout);
1.126 brouard 12552: }else
12553: strcpy(pplotcmd,plotcmd);
1.157 brouard 12554: #ifdef __unix
1.126 brouard 12555: strcpy(plotcmd,GNUPLOTPROGRAM);
12556: if(!stat(plotcmd,&info)){
1.158 brouard 12557: printf("Error gnuplot program not found: '%s'\n",plotcmd);fflush(stdout);
1.126 brouard 12558: }else
12559: strcpy(pplotcmd,plotcmd);
12560: #endif
12561: }else
12562: strcpy(pplotcmd,plotcmd);
12563:
12564: sprintf(plotcmd,"%s %s",pplotcmd, optionfilegnuplot);
1.158 brouard 12565: printf("Starting graphs with: '%s'\n",plotcmd);fflush(stdout);
1.227 brouard 12566:
1.126 brouard 12567: if((outcmd=system(plotcmd)) != 0){
1.158 brouard 12568: printf("gnuplot command might not be in your path: '%s', err=%d\n", plotcmd, outcmd);
1.154 brouard 12569: printf("\n Trying if gnuplot resides on the same directory that IMaCh\n");
1.152 brouard 12570: sprintf(plotcmd,"%sgnuplot %s", pathimach, optionfilegnuplot);
1.150 brouard 12571: if((outcmd=system(plotcmd)) != 0)
1.153 brouard 12572: printf("\n Still a problem with gnuplot command %s, err=%d\n", plotcmd, outcmd);
1.126 brouard 12573: }
1.158 brouard 12574: printf(" Successful, please wait...");
1.126 brouard 12575: while (z[0] != 'q') {
12576: /* chdir(path); */
1.154 brouard 12577: printf("\nType e to edit results with your browser, g to graph again and q for exit: ");
1.126 brouard 12578: scanf("%s",z);
12579: /* if (z[0] == 'c') system("./imach"); */
12580: if (z[0] == 'e') {
1.158 brouard 12581: #ifdef __APPLE__
1.152 brouard 12582: sprintf(pplotcmd, "open %s", optionfilehtm);
1.157 brouard 12583: #elif __linux
12584: sprintf(pplotcmd, "xdg-open %s", optionfilehtm);
1.153 brouard 12585: #else
1.152 brouard 12586: sprintf(pplotcmd, "%s", optionfilehtm);
1.153 brouard 12587: #endif
12588: printf("Starting browser with: %s",pplotcmd);fflush(stdout);
12589: system(pplotcmd);
1.126 brouard 12590: }
12591: else if (z[0] == 'g') system(plotcmd);
12592: else if (z[0] == 'q') exit(0);
12593: }
1.227 brouard 12594: end:
1.126 brouard 12595: while (z[0] != 'q') {
1.195 brouard 12596: printf("\nType q for exiting: "); fflush(stdout);
1.126 brouard 12597: scanf("%s",z);
12598: }
12599: }
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