Annotation of imach/src/imach.c, revision 1.270
1.270 ! brouard 1: /* $Id: imach.c,v 1.269 2017/05/23 08:39:25 brouard Exp $
1.126 brouard 2: $State: Exp $
1.163 brouard 3: $Log: imach.c,v $
1.270 ! brouard 4: Revision 1.269 2017/05/23 08:39:25 brouard
! 5: Summary: Code into subroutine, cleanings
! 6:
1.269 brouard 7: Revision 1.268 2017/05/18 20:09:32 brouard
8: Summary: backprojection and confidence intervals of backprevalence
9:
1.268 brouard 10: Revision 1.267 2017/05/13 10:25:05 brouard
11: Summary: temporary save for backprojection
12:
1.267 brouard 13: Revision 1.266 2017/05/13 07:26:12 brouard
14: Summary: Version 0.99r13 (improvements and bugs fixed)
15:
1.266 brouard 16: Revision 1.265 2017/04/26 16:22:11 brouard
17: Summary: imach 0.99r13 Some bugs fixed
18:
1.265 brouard 19: Revision 1.264 2017/04/26 06:01:29 brouard
20: Summary: Labels in graphs
21:
1.264 brouard 22: Revision 1.263 2017/04/24 15:23:15 brouard
23: Summary: to save
24:
1.263 brouard 25: Revision 1.262 2017/04/18 16:48:12 brouard
26: *** empty log message ***
27:
1.262 brouard 28: Revision 1.261 2017/04/05 10:14:09 brouard
29: Summary: Bug in E_ as well as in T_ fixed nres-1 vs k1-1
30:
1.261 brouard 31: Revision 1.260 2017/04/04 17:46:59 brouard
32: Summary: Gnuplot indexations fixed (humm)
33:
1.260 brouard 34: Revision 1.259 2017/04/04 13:01:16 brouard
35: Summary: Some errors to warnings only if date of death is unknown but status is death we could set to pi3
36:
1.259 brouard 37: Revision 1.258 2017/04/03 10:17:47 brouard
38: Summary: Version 0.99r12
39:
40: Some cleanings, conformed with updated documentation.
41:
1.258 brouard 42: Revision 1.257 2017/03/29 16:53:30 brouard
43: Summary: Temp
44:
1.257 brouard 45: Revision 1.256 2017/03/27 05:50:23 brouard
46: Summary: Temporary
47:
1.256 brouard 48: Revision 1.255 2017/03/08 16:02:28 brouard
49: Summary: IMaCh version 0.99r10 bugs in gnuplot fixed
50:
1.255 brouard 51: Revision 1.254 2017/03/08 07:13:00 brouard
52: Summary: Fixing data parameter line
53:
1.254 brouard 54: Revision 1.253 2016/12/15 11:59:41 brouard
55: Summary: 0.99 in progress
56:
1.253 brouard 57: Revision 1.252 2016/09/15 21:15:37 brouard
58: *** empty log message ***
59:
1.252 brouard 60: Revision 1.251 2016/09/15 15:01:13 brouard
61: Summary: not working
62:
1.251 brouard 63: Revision 1.250 2016/09/08 16:07:27 brouard
64: Summary: continue
65:
1.250 brouard 66: Revision 1.249 2016/09/07 17:14:18 brouard
67: Summary: Starting values from frequencies
68:
1.249 brouard 69: Revision 1.248 2016/09/07 14:10:18 brouard
70: *** empty log message ***
71:
1.248 brouard 72: Revision 1.247 2016/09/02 11:11:21 brouard
73: *** empty log message ***
74:
1.247 brouard 75: Revision 1.246 2016/09/02 08:49:22 brouard
76: *** empty log message ***
77:
1.246 brouard 78: Revision 1.245 2016/09/02 07:25:01 brouard
79: *** empty log message ***
80:
1.245 brouard 81: Revision 1.244 2016/09/02 07:17:34 brouard
82: *** empty log message ***
83:
1.244 brouard 84: Revision 1.243 2016/09/02 06:45:35 brouard
85: *** empty log message ***
86:
1.243 brouard 87: Revision 1.242 2016/08/30 15:01:20 brouard
88: Summary: Fixing a lots
89:
1.242 brouard 90: Revision 1.241 2016/08/29 17:17:25 brouard
91: Summary: gnuplot problem in Back projection to fix
92:
1.241 brouard 93: Revision 1.240 2016/08/29 07:53:18 brouard
94: Summary: Better
95:
1.240 brouard 96: Revision 1.239 2016/08/26 15:51:03 brouard
97: Summary: Improvement in Powell output in order to copy and paste
98:
99: Author:
100:
1.239 brouard 101: Revision 1.238 2016/08/26 14:23:35 brouard
102: Summary: Starting tests of 0.99
103:
1.238 brouard 104: Revision 1.237 2016/08/26 09:20:19 brouard
105: Summary: to valgrind
106:
1.237 brouard 107: Revision 1.236 2016/08/25 10:50:18 brouard
108: *** empty log message ***
109:
1.236 brouard 110: Revision 1.235 2016/08/25 06:59:23 brouard
111: *** empty log message ***
112:
1.235 brouard 113: Revision 1.234 2016/08/23 16:51:20 brouard
114: *** empty log message ***
115:
1.234 brouard 116: Revision 1.233 2016/08/23 07:40:50 brouard
117: Summary: not working
118:
1.233 brouard 119: Revision 1.232 2016/08/22 14:20:21 brouard
120: Summary: not working
121:
1.232 brouard 122: Revision 1.231 2016/08/22 07:17:15 brouard
123: Summary: not working
124:
1.231 brouard 125: Revision 1.230 2016/08/22 06:55:53 brouard
126: Summary: Not working
127:
1.230 brouard 128: Revision 1.229 2016/07/23 09:45:53 brouard
129: Summary: Completing for func too
130:
1.229 brouard 131: Revision 1.228 2016/07/22 17:45:30 brouard
132: Summary: Fixing some arrays, still debugging
133:
1.227 brouard 134: Revision 1.226 2016/07/12 18:42:34 brouard
135: Summary: temp
136:
1.226 brouard 137: Revision 1.225 2016/07/12 08:40:03 brouard
138: Summary: saving but not running
139:
1.225 brouard 140: Revision 1.224 2016/07/01 13:16:01 brouard
141: Summary: Fixes
142:
1.224 brouard 143: Revision 1.223 2016/02/19 09:23:35 brouard
144: Summary: temporary
145:
1.223 brouard 146: Revision 1.222 2016/02/17 08:14:50 brouard
147: Summary: Probably last 0.98 stable version 0.98r6
148:
1.222 brouard 149: Revision 1.221 2016/02/15 23:35:36 brouard
150: Summary: minor bug
151:
1.220 brouard 152: Revision 1.219 2016/02/15 00:48:12 brouard
153: *** empty log message ***
154:
1.219 brouard 155: Revision 1.218 2016/02/12 11:29:23 brouard
156: Summary: 0.99 Back projections
157:
1.218 brouard 158: Revision 1.217 2015/12/23 17:18:31 brouard
159: Summary: Experimental backcast
160:
1.217 brouard 161: Revision 1.216 2015/12/18 17:32:11 brouard
162: Summary: 0.98r4 Warning and status=-2
163:
164: Version 0.98r4 is now:
165: - displaying an error when status is -1, date of interview unknown and date of death known;
166: - permitting a status -2 when the vital status is unknown at a known date of right truncation.
167: Older changes concerning s=-2, dating from 2005 have been supersed.
168:
1.216 brouard 169: Revision 1.215 2015/12/16 08:52:24 brouard
170: Summary: 0.98r4 working
171:
1.215 brouard 172: Revision 1.214 2015/12/16 06:57:54 brouard
173: Summary: temporary not working
174:
1.214 brouard 175: Revision 1.213 2015/12/11 18:22:17 brouard
176: Summary: 0.98r4
177:
1.213 brouard 178: Revision 1.212 2015/11/21 12:47:24 brouard
179: Summary: minor typo
180:
1.212 brouard 181: Revision 1.211 2015/11/21 12:41:11 brouard
182: Summary: 0.98r3 with some graph of projected cross-sectional
183:
184: Author: Nicolas Brouard
185:
1.211 brouard 186: Revision 1.210 2015/11/18 17:41:20 brouard
1.252 brouard 187: Summary: Start working on projected prevalences Revision 1.209 2015/11/17 22:12:03 brouard
1.210 brouard 188: Summary: Adding ftolpl parameter
189: Author: N Brouard
190:
191: We had difficulties to get smoothed confidence intervals. It was due
192: to the period prevalence which wasn't computed accurately. The inner
193: parameter ftolpl is now an outer parameter of the .imach parameter
194: file after estepm. If ftolpl is small 1.e-4 and estepm too,
195: computation are long.
196:
1.209 brouard 197: Revision 1.208 2015/11/17 14:31:57 brouard
198: Summary: temporary
199:
1.208 brouard 200: Revision 1.207 2015/10/27 17:36:57 brouard
201: *** empty log message ***
202:
1.207 brouard 203: Revision 1.206 2015/10/24 07:14:11 brouard
204: *** empty log message ***
205:
1.206 brouard 206: Revision 1.205 2015/10/23 15:50:53 brouard
207: Summary: 0.98r3 some clarification for graphs on likelihood contributions
208:
1.205 brouard 209: Revision 1.204 2015/10/01 16:20:26 brouard
210: Summary: Some new graphs of contribution to likelihood
211:
1.204 brouard 212: Revision 1.203 2015/09/30 17:45:14 brouard
213: Summary: looking at better estimation of the hessian
214:
215: Also a better criteria for convergence to the period prevalence And
216: therefore adding the number of years needed to converge. (The
217: prevalence in any alive state shold sum to one
218:
1.203 brouard 219: Revision 1.202 2015/09/22 19:45:16 brouard
220: Summary: Adding some overall graph on contribution to likelihood. Might change
221:
1.202 brouard 222: Revision 1.201 2015/09/15 17:34:58 brouard
223: Summary: 0.98r0
224:
225: - Some new graphs like suvival functions
226: - Some bugs fixed like model=1+age+V2.
227:
1.201 brouard 228: Revision 1.200 2015/09/09 16:53:55 brouard
229: Summary: Big bug thanks to Flavia
230:
231: Even model=1+age+V2. did not work anymore
232:
1.200 brouard 233: Revision 1.199 2015/09/07 14:09:23 brouard
234: Summary: 0.98q6 changing default small png format for graph to vectorized svg.
235:
1.199 brouard 236: Revision 1.198 2015/09/03 07:14:39 brouard
237: Summary: 0.98q5 Flavia
238:
1.198 brouard 239: Revision 1.197 2015/09/01 18:24:39 brouard
240: *** empty log message ***
241:
1.197 brouard 242: Revision 1.196 2015/08/18 23:17:52 brouard
243: Summary: 0.98q5
244:
1.196 brouard 245: Revision 1.195 2015/08/18 16:28:39 brouard
246: Summary: Adding a hack for testing purpose
247:
248: After reading the title, ftol and model lines, if the comment line has
249: a q, starting with #q, the answer at the end of the run is quit. It
250: permits to run test files in batch with ctest. The former workaround was
251: $ echo q | imach foo.imach
252:
1.195 brouard 253: Revision 1.194 2015/08/18 13:32:00 brouard
254: Summary: Adding error when the covariance matrix doesn't contain the exact number of lines required by the model line.
255:
1.194 brouard 256: Revision 1.193 2015/08/04 07:17:42 brouard
257: Summary: 0.98q4
258:
1.193 brouard 259: Revision 1.192 2015/07/16 16:49:02 brouard
260: Summary: Fixing some outputs
261:
1.192 brouard 262: Revision 1.191 2015/07/14 10:00:33 brouard
263: Summary: Some fixes
264:
1.191 brouard 265: Revision 1.190 2015/05/05 08:51:13 brouard
266: Summary: Adding digits in output parameters (7 digits instead of 6)
267:
268: Fix 1+age+.
269:
1.190 brouard 270: Revision 1.189 2015/04/30 14:45:16 brouard
271: Summary: 0.98q2
272:
1.189 brouard 273: Revision 1.188 2015/04/30 08:27:53 brouard
274: *** empty log message ***
275:
1.188 brouard 276: Revision 1.187 2015/04/29 09:11:15 brouard
277: *** empty log message ***
278:
1.187 brouard 279: Revision 1.186 2015/04/23 12:01:52 brouard
280: Summary: V1*age is working now, version 0.98q1
281:
282: Some codes had been disabled in order to simplify and Vn*age was
283: working in the optimization phase, ie, giving correct MLE parameters,
284: but, as usual, outputs were not correct and program core dumped.
285:
1.186 brouard 286: Revision 1.185 2015/03/11 13:26:42 brouard
287: Summary: Inclusion of compile and links command line for Intel Compiler
288:
1.185 brouard 289: Revision 1.184 2015/03/11 11:52:39 brouard
290: Summary: Back from Windows 8. Intel Compiler
291:
1.184 brouard 292: Revision 1.183 2015/03/10 20:34:32 brouard
293: Summary: 0.98q0, trying with directest, mnbrak fixed
294:
295: We use directest instead of original Powell test; probably no
296: incidence on the results, but better justifications;
297: We fixed Numerical Recipes mnbrak routine which was wrong and gave
298: wrong results.
299:
1.183 brouard 300: Revision 1.182 2015/02/12 08:19:57 brouard
301: Summary: Trying to keep directest which seems simpler and more general
302: Author: Nicolas Brouard
303:
1.182 brouard 304: Revision 1.181 2015/02/11 23:22:24 brouard
305: Summary: Comments on Powell added
306:
307: Author:
308:
1.181 brouard 309: Revision 1.180 2015/02/11 17:33:45 brouard
310: Summary: Finishing move from main to function (hpijx and prevalence_limit)
311:
1.180 brouard 312: Revision 1.179 2015/01/04 09:57:06 brouard
313: Summary: back to OS/X
314:
1.179 brouard 315: Revision 1.178 2015/01/04 09:35:48 brouard
316: *** empty log message ***
317:
1.178 brouard 318: Revision 1.177 2015/01/03 18:40:56 brouard
319: Summary: Still testing ilc32 on OSX
320:
1.177 brouard 321: Revision 1.176 2015/01/03 16:45:04 brouard
322: *** empty log message ***
323:
1.176 brouard 324: Revision 1.175 2015/01/03 16:33:42 brouard
325: *** empty log message ***
326:
1.175 brouard 327: Revision 1.174 2015/01/03 16:15:49 brouard
328: Summary: Still in cross-compilation
329:
1.174 brouard 330: Revision 1.173 2015/01/03 12:06:26 brouard
331: Summary: trying to detect cross-compilation
332:
1.173 brouard 333: Revision 1.172 2014/12/27 12:07:47 brouard
334: Summary: Back from Visual Studio and Intel, options for compiling for Windows XP
335:
1.172 brouard 336: Revision 1.171 2014/12/23 13:26:59 brouard
337: Summary: Back from Visual C
338:
339: Still problem with utsname.h on Windows
340:
1.171 brouard 341: Revision 1.170 2014/12/23 11:17:12 brouard
342: Summary: Cleaning some \%% back to %%
343:
344: The escape was mandatory for a specific compiler (which one?), but too many warnings.
345:
1.170 brouard 346: Revision 1.169 2014/12/22 23:08:31 brouard
347: Summary: 0.98p
348:
349: Outputs some informations on compiler used, OS etc. Testing on different platforms.
350:
1.169 brouard 351: Revision 1.168 2014/12/22 15:17:42 brouard
1.170 brouard 352: Summary: update
1.169 brouard 353:
1.168 brouard 354: Revision 1.167 2014/12/22 13:50:56 brouard
355: Summary: Testing uname and compiler version and if compiled 32 or 64
356:
357: Testing on Linux 64
358:
1.167 brouard 359: Revision 1.166 2014/12/22 11:40:47 brouard
360: *** empty log message ***
361:
1.166 brouard 362: Revision 1.165 2014/12/16 11:20:36 brouard
363: Summary: After compiling on Visual C
364:
365: * imach.c (Module): Merging 1.61 to 1.162
366:
1.165 brouard 367: Revision 1.164 2014/12/16 10:52:11 brouard
368: Summary: Merging with Visual C after suppressing some warnings for unused variables. Also fixing Saito's bug 0.98Xn
369:
370: * imach.c (Module): Merging 1.61 to 1.162
371:
1.164 brouard 372: Revision 1.163 2014/12/16 10:30:11 brouard
373: * imach.c (Module): Merging 1.61 to 1.162
374:
1.163 brouard 375: Revision 1.162 2014/09/25 11:43:39 brouard
376: Summary: temporary backup 0.99!
377:
1.162 brouard 378: Revision 1.1 2014/09/16 11:06:58 brouard
379: Summary: With some code (wrong) for nlopt
380:
381: Author:
382:
383: Revision 1.161 2014/09/15 20:41:41 brouard
384: Summary: Problem with macro SQR on Intel compiler
385:
1.161 brouard 386: Revision 1.160 2014/09/02 09:24:05 brouard
387: *** empty log message ***
388:
1.160 brouard 389: Revision 1.159 2014/09/01 10:34:10 brouard
390: Summary: WIN32
391: Author: Brouard
392:
1.159 brouard 393: Revision 1.158 2014/08/27 17:11:51 brouard
394: *** empty log message ***
395:
1.158 brouard 396: Revision 1.157 2014/08/27 16:26:55 brouard
397: Summary: Preparing windows Visual studio version
398: Author: Brouard
399:
400: In order to compile on Visual studio, time.h is now correct and time_t
401: and tm struct should be used. difftime should be used but sometimes I
402: just make the differences in raw time format (time(&now).
403: Trying to suppress #ifdef LINUX
404: Add xdg-open for __linux in order to open default browser.
405:
1.157 brouard 406: Revision 1.156 2014/08/25 20:10:10 brouard
407: *** empty log message ***
408:
1.156 brouard 409: Revision 1.155 2014/08/25 18:32:34 brouard
410: Summary: New compile, minor changes
411: Author: Brouard
412:
1.155 brouard 413: Revision 1.154 2014/06/20 17:32:08 brouard
414: Summary: Outputs now all graphs of convergence to period prevalence
415:
1.154 brouard 416: Revision 1.153 2014/06/20 16:45:46 brouard
417: Summary: If 3 live state, convergence to period prevalence on same graph
418: Author: Brouard
419:
1.153 brouard 420: Revision 1.152 2014/06/18 17:54:09 brouard
421: Summary: open browser, use gnuplot on same dir than imach if not found in the path
422:
1.152 brouard 423: Revision 1.151 2014/06/18 16:43:30 brouard
424: *** empty log message ***
425:
1.151 brouard 426: Revision 1.150 2014/06/18 16:42:35 brouard
427: Summary: If gnuplot is not in the path try on same directory than imach binary (OSX)
428: Author: brouard
429:
1.150 brouard 430: Revision 1.149 2014/06/18 15:51:14 brouard
431: Summary: Some fixes in parameter files errors
432: Author: Nicolas Brouard
433:
1.149 brouard 434: Revision 1.148 2014/06/17 17:38:48 brouard
435: Summary: Nothing new
436: Author: Brouard
437:
438: Just a new packaging for OS/X version 0.98nS
439:
1.148 brouard 440: Revision 1.147 2014/06/16 10:33:11 brouard
441: *** empty log message ***
442:
1.147 brouard 443: Revision 1.146 2014/06/16 10:20:28 brouard
444: Summary: Merge
445: Author: Brouard
446:
447: Merge, before building revised version.
448:
1.146 brouard 449: Revision 1.145 2014/06/10 21:23:15 brouard
450: Summary: Debugging with valgrind
451: Author: Nicolas Brouard
452:
453: Lot of changes in order to output the results with some covariates
454: After the Edimburgh REVES conference 2014, it seems mandatory to
455: improve the code.
456: No more memory valgrind error but a lot has to be done in order to
457: continue the work of splitting the code into subroutines.
458: Also, decodemodel has been improved. Tricode is still not
459: optimal. nbcode should be improved. Documentation has been added in
460: the source code.
461:
1.144 brouard 462: Revision 1.143 2014/01/26 09:45:38 brouard
463: Summary: Version 0.98nR (to be improved, but gives same optimization results as 0.98k. Nice, promising
464:
465: * imach.c (Module): Trying to merge old staffs together while being at Tokyo. Not tested...
466: (Module): Version 0.98nR Running ok, but output format still only works for three covariates.
467:
1.143 brouard 468: Revision 1.142 2014/01/26 03:57:36 brouard
469: Summary: gnuplot changed plot w l 1 has to be changed to plot w l lt 2
470:
471: * imach.c (Module): Trying to merge old staffs together while being at Tokyo. Not tested...
472:
1.142 brouard 473: Revision 1.141 2014/01/26 02:42:01 brouard
474: * imach.c (Module): Trying to merge old staffs together while being at Tokyo. Not tested...
475:
1.141 brouard 476: Revision 1.140 2011/09/02 10:37:54 brouard
477: Summary: times.h is ok with mingw32 now.
478:
1.140 brouard 479: Revision 1.139 2010/06/14 07:50:17 brouard
480: After the theft of my laptop, I probably lost some lines of codes which were not uploaded to the CVS tree.
481: I remember having already fixed agemin agemax which are pointers now but not cvs saved.
482:
1.139 brouard 483: Revision 1.138 2010/04/30 18:19:40 brouard
484: *** empty log message ***
485:
1.138 brouard 486: Revision 1.137 2010/04/29 18:11:38 brouard
487: (Module): Checking covariates for more complex models
488: than V1+V2. A lot of change to be done. Unstable.
489:
1.137 brouard 490: Revision 1.136 2010/04/26 20:30:53 brouard
491: (Module): merging some libgsl code. Fixing computation
492: of likelione (using inter/intrapolation if mle = 0) in order to
493: get same likelihood as if mle=1.
494: Some cleaning of code and comments added.
495:
1.136 brouard 496: Revision 1.135 2009/10/29 15:33:14 brouard
497: (Module): Now imach stops if date of birth, at least year of birth, is not given. Some cleaning of the code.
498:
1.135 brouard 499: Revision 1.134 2009/10/29 13:18:53 brouard
500: (Module): Now imach stops if date of birth, at least year of birth, is not given. Some cleaning of the code.
501:
1.134 brouard 502: Revision 1.133 2009/07/06 10:21:25 brouard
503: just nforces
504:
1.133 brouard 505: Revision 1.132 2009/07/06 08:22:05 brouard
506: Many tings
507:
1.132 brouard 508: Revision 1.131 2009/06/20 16:22:47 brouard
509: Some dimensions resccaled
510:
1.131 brouard 511: Revision 1.130 2009/05/26 06:44:34 brouard
512: (Module): Max Covariate is now set to 20 instead of 8. A
513: lot of cleaning with variables initialized to 0. Trying to make
514: V2+V3*age+V1+V4 strb=V3*age+V1+V4 working better.
515:
1.130 brouard 516: Revision 1.129 2007/08/31 13:49:27 lievre
517: Modification of the way of exiting when the covariate is not binary in order to see on the window the error message before exiting
518:
1.129 lievre 519: Revision 1.128 2006/06/30 13:02:05 brouard
520: (Module): Clarifications on computing e.j
521:
1.128 brouard 522: Revision 1.127 2006/04/28 18:11:50 brouard
523: (Module): Yes the sum of survivors was wrong since
524: imach-114 because nhstepm was no more computed in the age
525: loop. Now we define nhstepma in the age loop.
526: (Module): In order to speed up (in case of numerous covariates) we
527: compute health expectancies (without variances) in a first step
528: and then all the health expectancies with variances or standard
529: deviation (needs data from the Hessian matrices) which slows the
530: computation.
531: In the future we should be able to stop the program is only health
532: expectancies and graph are needed without standard deviations.
533:
1.127 brouard 534: Revision 1.126 2006/04/28 17:23:28 brouard
535: (Module): Yes the sum of survivors was wrong since
536: imach-114 because nhstepm was no more computed in the age
537: loop. Now we define nhstepma in the age loop.
538: Version 0.98h
539:
1.126 brouard 540: Revision 1.125 2006/04/04 15:20:31 lievre
541: Errors in calculation of health expectancies. Age was not initialized.
542: Forecasting file added.
543:
544: Revision 1.124 2006/03/22 17:13:53 lievre
545: Parameters are printed with %lf instead of %f (more numbers after the comma).
546: The log-likelihood is printed in the log file
547:
548: Revision 1.123 2006/03/20 10:52:43 brouard
549: * imach.c (Module): <title> changed, corresponds to .htm file
550: name. <head> headers where missing.
551:
552: * imach.c (Module): Weights can have a decimal point as for
553: English (a comma might work with a correct LC_NUMERIC environment,
554: otherwise the weight is truncated).
555: Modification of warning when the covariates values are not 0 or
556: 1.
557: Version 0.98g
558:
559: Revision 1.122 2006/03/20 09:45:41 brouard
560: (Module): Weights can have a decimal point as for
561: English (a comma might work with a correct LC_NUMERIC environment,
562: otherwise the weight is truncated).
563: Modification of warning when the covariates values are not 0 or
564: 1.
565: Version 0.98g
566:
567: Revision 1.121 2006/03/16 17:45:01 lievre
568: * imach.c (Module): Comments concerning covariates added
569:
570: * imach.c (Module): refinements in the computation of lli if
571: status=-2 in order to have more reliable computation if stepm is
572: not 1 month. Version 0.98f
573:
574: Revision 1.120 2006/03/16 15:10:38 lievre
575: (Module): refinements in the computation of lli if
576: status=-2 in order to have more reliable computation if stepm is
577: not 1 month. Version 0.98f
578:
579: Revision 1.119 2006/03/15 17:42:26 brouard
580: (Module): Bug if status = -2, the loglikelihood was
581: computed as likelihood omitting the logarithm. Version O.98e
582:
583: Revision 1.118 2006/03/14 18:20:07 brouard
584: (Module): varevsij Comments added explaining the second
585: table of variances if popbased=1 .
586: (Module): Covariances of eij, ekl added, graphs fixed, new html link.
587: (Module): Function pstamp added
588: (Module): Version 0.98d
589:
590: Revision 1.117 2006/03/14 17:16:22 brouard
591: (Module): varevsij Comments added explaining the second
592: table of variances if popbased=1 .
593: (Module): Covariances of eij, ekl added, graphs fixed, new html link.
594: (Module): Function pstamp added
595: (Module): Version 0.98d
596:
597: Revision 1.116 2006/03/06 10:29:27 brouard
598: (Module): Variance-covariance wrong links and
599: varian-covariance of ej. is needed (Saito).
600:
601: Revision 1.115 2006/02/27 12:17:45 brouard
602: (Module): One freematrix added in mlikeli! 0.98c
603:
604: Revision 1.114 2006/02/26 12:57:58 brouard
605: (Module): Some improvements in processing parameter
606: filename with strsep.
607:
608: Revision 1.113 2006/02/24 14:20:24 brouard
609: (Module): Memory leaks checks with valgrind and:
610: datafile was not closed, some imatrix were not freed and on matrix
611: allocation too.
612:
613: Revision 1.112 2006/01/30 09:55:26 brouard
614: (Module): Back to gnuplot.exe instead of wgnuplot.exe
615:
616: Revision 1.111 2006/01/25 20:38:18 brouard
617: (Module): Lots of cleaning and bugs added (Gompertz)
618: (Module): Comments can be added in data file. Missing date values
619: can be a simple dot '.'.
620:
621: Revision 1.110 2006/01/25 00:51:50 brouard
622: (Module): Lots of cleaning and bugs added (Gompertz)
623:
624: Revision 1.109 2006/01/24 19:37:15 brouard
625: (Module): Comments (lines starting with a #) are allowed in data.
626:
627: Revision 1.108 2006/01/19 18:05:42 lievre
628: Gnuplot problem appeared...
629: To be fixed
630:
631: Revision 1.107 2006/01/19 16:20:37 brouard
632: Test existence of gnuplot in imach path
633:
634: Revision 1.106 2006/01/19 13:24:36 brouard
635: Some cleaning and links added in html output
636:
637: Revision 1.105 2006/01/05 20:23:19 lievre
638: *** empty log message ***
639:
640: Revision 1.104 2005/09/30 16:11:43 lievre
641: (Module): sump fixed, loop imx fixed, and simplifications.
642: (Module): If the status is missing at the last wave but we know
643: that the person is alive, then we can code his/her status as -2
644: (instead of missing=-1 in earlier versions) and his/her
645: contributions to the likelihood is 1 - Prob of dying from last
646: health status (= 1-p13= p11+p12 in the easiest case of somebody in
647: the healthy state at last known wave). Version is 0.98
648:
649: Revision 1.103 2005/09/30 15:54:49 lievre
650: (Module): sump fixed, loop imx fixed, and simplifications.
651:
652: Revision 1.102 2004/09/15 17:31:30 brouard
653: Add the possibility to read data file including tab characters.
654:
655: Revision 1.101 2004/09/15 10:38:38 brouard
656: Fix on curr_time
657:
658: Revision 1.100 2004/07/12 18:29:06 brouard
659: Add version for Mac OS X. Just define UNIX in Makefile
660:
661: Revision 1.99 2004/06/05 08:57:40 brouard
662: *** empty log message ***
663:
664: Revision 1.98 2004/05/16 15:05:56 brouard
665: New version 0.97 . First attempt to estimate force of mortality
666: directly from the data i.e. without the need of knowing the health
667: state at each age, but using a Gompertz model: log u =a + b*age .
668: This is the basic analysis of mortality and should be done before any
669: other analysis, in order to test if the mortality estimated from the
670: cross-longitudinal survey is different from the mortality estimated
671: from other sources like vital statistic data.
672:
673: The same imach parameter file can be used but the option for mle should be -3.
674:
1.133 brouard 675: Agnès, who wrote this part of the code, tried to keep most of the
1.126 brouard 676: former routines in order to include the new code within the former code.
677:
678: The output is very simple: only an estimate of the intercept and of
679: the slope with 95% confident intervals.
680:
681: Current limitations:
682: A) Even if you enter covariates, i.e. with the
683: model= V1+V2 equation for example, the programm does only estimate a unique global model without covariates.
684: B) There is no computation of Life Expectancy nor Life Table.
685:
686: Revision 1.97 2004/02/20 13:25:42 lievre
687: Version 0.96d. Population forecasting command line is (temporarily)
688: suppressed.
689:
690: Revision 1.96 2003/07/15 15:38:55 brouard
691: * imach.c (Repository): Errors in subdirf, 2, 3 while printing tmpout is
692: rewritten within the same printf. Workaround: many printfs.
693:
694: Revision 1.95 2003/07/08 07:54:34 brouard
695: * imach.c (Repository):
696: (Repository): Using imachwizard code to output a more meaningful covariance
697: matrix (cov(a12,c31) instead of numbers.
698:
699: Revision 1.94 2003/06/27 13:00:02 brouard
700: Just cleaning
701:
702: Revision 1.93 2003/06/25 16:33:55 brouard
703: (Module): On windows (cygwin) function asctime_r doesn't
704: exist so I changed back to asctime which exists.
705: (Module): Version 0.96b
706:
707: Revision 1.92 2003/06/25 16:30:45 brouard
708: (Module): On windows (cygwin) function asctime_r doesn't
709: exist so I changed back to asctime which exists.
710:
711: Revision 1.91 2003/06/25 15:30:29 brouard
712: * imach.c (Repository): Duplicated warning errors corrected.
713: (Repository): Elapsed time after each iteration is now output. It
714: helps to forecast when convergence will be reached. Elapsed time
715: is stamped in powell. We created a new html file for the graphs
716: concerning matrix of covariance. It has extension -cov.htm.
717:
718: Revision 1.90 2003/06/24 12:34:15 brouard
719: (Module): Some bugs corrected for windows. Also, when
720: mle=-1 a template is output in file "or"mypar.txt with the design
721: of the covariance matrix to be input.
722:
723: Revision 1.89 2003/06/24 12:30:52 brouard
724: (Module): Some bugs corrected for windows. Also, when
725: mle=-1 a template is output in file "or"mypar.txt with the design
726: of the covariance matrix to be input.
727:
728: Revision 1.88 2003/06/23 17:54:56 brouard
729: * 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.
730:
731: Revision 1.87 2003/06/18 12:26:01 brouard
732: Version 0.96
733:
734: Revision 1.86 2003/06/17 20:04:08 brouard
735: (Module): Change position of html and gnuplot routines and added
736: routine fileappend.
737:
738: Revision 1.85 2003/06/17 13:12:43 brouard
739: * imach.c (Repository): Check when date of death was earlier that
740: current date of interview. It may happen when the death was just
741: prior to the death. In this case, dh was negative and likelihood
742: was wrong (infinity). We still send an "Error" but patch by
743: assuming that the date of death was just one stepm after the
744: interview.
745: (Repository): Because some people have very long ID (first column)
746: we changed int to long in num[] and we added a new lvector for
747: memory allocation. But we also truncated to 8 characters (left
748: truncation)
749: (Repository): No more line truncation errors.
750:
751: Revision 1.84 2003/06/13 21:44:43 brouard
752: * imach.c (Repository): Replace "freqsummary" at a correct
753: place. It differs from routine "prevalence" which may be called
754: many times. Probs is memory consuming and must be used with
755: parcimony.
756: Version 0.95a3 (should output exactly the same maximization than 0.8a2)
757:
758: Revision 1.83 2003/06/10 13:39:11 lievre
759: *** empty log message ***
760:
761: Revision 1.82 2003/06/05 15:57:20 brouard
762: Add log in imach.c and fullversion number is now printed.
763:
764: */
765: /*
766: Interpolated Markov Chain
767:
768: Short summary of the programme:
769:
1.227 brouard 770: This program computes Healthy Life Expectancies or State-specific
771: (if states aren't health statuses) Expectancies from
772: cross-longitudinal data. Cross-longitudinal data consist in:
773:
774: -1- a first survey ("cross") where individuals from different ages
775: are interviewed on their health status or degree of disability (in
776: the case of a health survey which is our main interest)
777:
778: -2- at least a second wave of interviews ("longitudinal") which
779: measure each change (if any) in individual health status. Health
780: expectancies are computed from the time spent in each health state
781: according to a model. More health states you consider, more time is
782: necessary to reach the Maximum Likelihood of the parameters involved
783: in the model. The simplest model is the multinomial logistic model
784: where pij is the probability to be observed in state j at the second
785: wave conditional to be observed in state i at the first
786: wave. Therefore the model is: log(pij/pii)= aij + bij*age+ cij*sex +
787: etc , where 'age' is age and 'sex' is a covariate. If you want to
788: have a more complex model than "constant and age", you should modify
789: the program where the markup *Covariates have to be included here
790: again* invites you to do it. More covariates you add, slower the
1.126 brouard 791: convergence.
792:
793: The advantage of this computer programme, compared to a simple
794: multinomial logistic model, is clear when the delay between waves is not
795: identical for each individual. Also, if a individual missed an
796: intermediate interview, the information is lost, but taken into
797: account using an interpolation or extrapolation.
798:
799: hPijx is the probability to be observed in state i at age x+h
800: conditional to the observed state i at age x. The delay 'h' can be
801: split into an exact number (nh*stepm) of unobserved intermediate
802: states. This elementary transition (by month, quarter,
803: semester or year) is modelled as a multinomial logistic. The hPx
804: matrix is simply the matrix product of nh*stepm elementary matrices
805: and the contribution of each individual to the likelihood is simply
806: hPijx.
807:
808: Also this programme outputs the covariance matrix of the parameters but also
1.218 brouard 809: of the life expectancies. It also computes the period (stable) prevalence.
810:
811: Back prevalence and projections:
1.227 brouard 812:
813: - back_prevalence_limit(double *p, double **bprlim, double ageminpar,
814: double agemaxpar, double ftolpl, int *ncvyearp, double
815: dateprev1,double dateprev2, int firstpass, int lastpass, int
816: mobilavproj)
817:
818: Computes the back prevalence limit for any combination of
819: covariate values k at any age between ageminpar and agemaxpar and
820: returns it in **bprlim. In the loops,
821:
822: - **bprevalim(**bprlim, ***mobaverage, nlstate, *p, age, **oldm,
823: **savm, **dnewm, **doldm, **dsavm, ftolpl, ncvyearp, k);
824:
825: - hBijx Back Probability to be in state i at age x-h being in j at x
1.218 brouard 826: Computes for any combination of covariates k and any age between bage and fage
827: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
828: oldm=oldms;savm=savms;
1.227 brouard 829:
1.267 brouard 830: - hbxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k, nres);
1.218 brouard 831: Computes the transition matrix starting at age 'age' over
832: 'nhstepm*hstepm*stepm' months (i.e. until
833: age (in years) age+nhstepm*hstepm*stepm/12) by multiplying
1.227 brouard 834: nhstepm*hstepm matrices.
835:
836: Returns p3mat[i][j][h] after calling
837: p3mat[i][j][h]=matprod2(newm,
838: bmij(pmmij,cov,ncovmodel,x,nlstate,prevacurrent, dnewm, doldm,
839: dsavm,ij),\ 1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath,
840: oldm);
1.226 brouard 841:
842: Important routines
843:
844: - func (or funcone), computes logit (pij) distinguishing
845: o fixed variables (single or product dummies or quantitative);
846: o varying variables by:
847: (1) wave (single, product dummies, quantitative),
848: (2) by age (can be month) age (done), age*age (done), age*Vn where Vn can be:
849: % fixed dummy (treated) or quantitative (not done because time-consuming);
850: % varying dummy (not done) or quantitative (not done);
851: - Tricode which tests the modality of dummy variables (in order to warn with wrong or empty modalities)
852: and returns the number of efficient covariates cptcoveff and modalities nbcode[Tvar[k]][1]= 0 and nbcode[Tvar[k]][2]= 1 usually.
853: - printinghtml which outputs results like life expectancy in and from a state for a combination of modalities of dummy variables
854: o There are 2*cptcoveff combinations of (0,1) for cptcoveff variables. Outputting only combinations with people, éliminating 1 1 if
855: race White (0 0), Black vs White (1 0), Hispanic (0 1) and 1 1 being meaningless.
1.218 brouard 856:
1.226 brouard 857:
858:
1.133 brouard 859: Authors: Nicolas Brouard (brouard@ined.fr) and Agnès Lièvre (lievre@ined.fr).
860: Institut national d'études démographiques, Paris.
1.126 brouard 861: This software have been partly granted by Euro-REVES, a concerted action
862: from the European Union.
863: It is copyrighted identically to a GNU software product, ie programme and
864: software can be distributed freely for non commercial use. Latest version
865: can be accessed at http://euroreves.ined.fr/imach .
866:
867: Help to debug: LD_PRELOAD=/usr/local/lib/libnjamd.so ./imach foo.imach
868: or better on gdb : set env LD_PRELOAD=/usr/local/lib/libnjamd.so
869:
870: **********************************************************************/
871: /*
872: main
873: read parameterfile
874: read datafile
875: concatwav
876: freqsummary
877: if (mle >= 1)
878: mlikeli
879: print results files
880: if mle==1
881: computes hessian
882: read end of parameter file: agemin, agemax, bage, fage, estepm
883: begin-prev-date,...
884: open gnuplot file
885: open html file
1.145 brouard 886: period (stable) prevalence | pl_nom 1-1 2-2 etc by covariate
887: for age prevalim() | #****** V1=0 V2=1 V3=1 V4=0 ******
888: | 65 1 0 2 1 3 1 4 0 0.96326 0.03674
889: freexexit2 possible for memory heap.
890:
891: h Pij x | pij_nom ficrestpij
892: # Cov Agex agex+h hpijx with i,j= 1-1 1-2 1-3 2-1 2-2 2-3
893: 1 85 85 1.00000 0.00000 0.00000 0.00000 1.00000 0.00000
894: 1 85 86 0.68299 0.22291 0.09410 0.71093 0.00000 0.28907
895:
896: 1 65 99 0.00364 0.00322 0.99314 0.00350 0.00310 0.99340
897: 1 65 100 0.00214 0.00204 0.99581 0.00206 0.00196 0.99597
898: variance of p one-step probabilities varprob | prob_nom ficresprob #One-step probabilities and stand. devi in ()
899: Standard deviation of one-step probabilities | probcor_nom ficresprobcor #One-step probabilities and correlation matrix
900: Matrix of variance covariance of one-step probabilities | probcov_nom ficresprobcov #One-step probabilities and covariance matrix
901:
1.126 brouard 902: forecasting if prevfcast==1 prevforecast call prevalence()
903: health expectancies
904: Variance-covariance of DFLE
905: prevalence()
906: movingaverage()
907: varevsij()
908: if popbased==1 varevsij(,popbased)
909: total life expectancies
910: Variance of period (stable) prevalence
911: end
912: */
913:
1.187 brouard 914: /* #define DEBUG */
915: /* #define DEBUGBRENT */
1.203 brouard 916: /* #define DEBUGLINMIN */
917: /* #define DEBUGHESS */
918: #define DEBUGHESSIJ
1.224 brouard 919: /* #define LINMINORIGINAL /\* Don't use loop on scale in linmin (accepting nan) *\/ */
1.165 brouard 920: #define POWELL /* Instead of NLOPT */
1.224 brouard 921: #define POWELLNOF3INFF1TEST /* Skip test */
1.186 brouard 922: /* #define POWELLORIGINAL /\* Don't use Directest to decide new direction but original Powell test *\/ */
923: /* #define MNBRAKORIGINAL /\* Don't use mnbrak fix *\/ */
1.126 brouard 924:
925: #include <math.h>
926: #include <stdio.h>
927: #include <stdlib.h>
928: #include <string.h>
1.226 brouard 929: #include <ctype.h>
1.159 brouard 930:
931: #ifdef _WIN32
932: #include <io.h>
1.172 brouard 933: #include <windows.h>
934: #include <tchar.h>
1.159 brouard 935: #else
1.126 brouard 936: #include <unistd.h>
1.159 brouard 937: #endif
1.126 brouard 938:
939: #include <limits.h>
940: #include <sys/types.h>
1.171 brouard 941:
942: #if defined(__GNUC__)
943: #include <sys/utsname.h> /* Doesn't work on Windows */
944: #endif
945:
1.126 brouard 946: #include <sys/stat.h>
947: #include <errno.h>
1.159 brouard 948: /* extern int errno; */
1.126 brouard 949:
1.157 brouard 950: /* #ifdef LINUX */
951: /* #include <time.h> */
952: /* #include "timeval.h" */
953: /* #else */
954: /* #include <sys/time.h> */
955: /* #endif */
956:
1.126 brouard 957: #include <time.h>
958:
1.136 brouard 959: #ifdef GSL
960: #include <gsl/gsl_errno.h>
961: #include <gsl/gsl_multimin.h>
962: #endif
963:
1.167 brouard 964:
1.162 brouard 965: #ifdef NLOPT
966: #include <nlopt.h>
967: typedef struct {
968: double (* function)(double [] );
969: } myfunc_data ;
970: #endif
971:
1.126 brouard 972: /* #include <libintl.h> */
973: /* #define _(String) gettext (String) */
974:
1.251 brouard 975: #define MAXLINE 2048 /* Was 256 and 1024. Overflow with 312 with 2 states and 4 covariates. Should be ok */
1.126 brouard 976:
977: #define GNUPLOTPROGRAM "gnuplot"
978: /*#define GNUPLOTPROGRAM "..\\gp37mgw\\wgnuplot"*/
979: #define FILENAMELENGTH 132
980:
981: #define GLOCK_ERROR_NOPATH -1 /* empty path */
982: #define GLOCK_ERROR_GETCWD -2 /* cannot get cwd */
983:
1.144 brouard 984: #define MAXPARM 128 /**< Maximum number of parameters for the optimization */
985: #define NPARMAX 64 /**< (nlstate+ndeath-1)*nlstate*ncovmodel */
1.126 brouard 986:
987: #define NINTERVMAX 8
1.144 brouard 988: #define NLSTATEMAX 8 /**< Maximum number of live states (for func) */
989: #define NDEATHMAX 8 /**< Maximum number of dead states (for func) */
990: #define NCOVMAX 20 /**< Maximum number of covariates, including generated covariates V1*V2 */
1.197 brouard 991: #define codtabm(h,k) (1 & (h-1) >> (k-1))+1
1.211 brouard 992: /*#define decodtabm(h,k,cptcoveff)= (h <= (1<<cptcoveff)?(((h-1) >> (k-1)) & 1) +1 : -1)*/
993: #define decodtabm(h,k,cptcoveff) (((h-1) >> (k-1)) & 1) +1
1.126 brouard 994: #define MAXN 20000
1.144 brouard 995: #define YEARM 12. /**< Number of months per year */
1.218 brouard 996: /* #define AGESUP 130 */
997: #define AGESUP 150
1.268 brouard 998: #define AGEINF 0
1.218 brouard 999: #define AGEMARGE 25 /* Marge for agemin and agemax for(iage=agemin-AGEMARGE; iage <= agemax+3+AGEMARGE; iage++) */
1.126 brouard 1000: #define AGEBASE 40
1.194 brouard 1001: #define AGEOVERFLOW 1.e20
1.164 brouard 1002: #define AGEGOMP 10 /**< Minimal age for Gompertz adjustment */
1.157 brouard 1003: #ifdef _WIN32
1004: #define DIRSEPARATOR '\\'
1005: #define CHARSEPARATOR "\\"
1006: #define ODIRSEPARATOR '/'
1007: #else
1.126 brouard 1008: #define DIRSEPARATOR '/'
1009: #define CHARSEPARATOR "/"
1010: #define ODIRSEPARATOR '\\'
1011: #endif
1012:
1.270 ! brouard 1013: /* $Id: imach.c,v 1.269 2017/05/23 08:39:25 brouard Exp $ */
1.126 brouard 1014: /* $State: Exp $ */
1.196 brouard 1015: #include "version.h"
1016: char version[]=__IMACH_VERSION__;
1.224 brouard 1017: 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";
1.270 ! brouard 1018: char fullversion[]="$Revision: 1.269 $ $Date: 2017/05/23 08:39:25 $";
1.126 brouard 1019: char strstart[80];
1020: char optionfilext[10], optionfilefiname[FILENAMELENGTH];
1.130 brouard 1021: int erreur=0, nberr=0, nbwarn=0; /* Error number, number of errors number of warnings */
1.187 brouard 1022: int nagesqr=0, nforce=0; /* nagesqr=1 if model is including age*age, number of forces */
1.145 brouard 1023: /* Number of covariates model=V2+V1+ V3*age+V2*V4 */
1024: int cptcovn=0; /**< cptcovn number of covariates added in the model (excepting constant and age and age*product) */
1025: int cptcovt=0; /**< cptcovt number of covariates added in the model (excepting constant and age) */
1.225 brouard 1026: int cptcovs=0; /**< cptcovs number of simple covariates in the model V2+V1 =2 */
1027: int cptcovsnq=0; /**< cptcovsnq number of simple covariates in the model but non quantitative V2+V1 =2 */
1.145 brouard 1028: int cptcovage=0; /**< Number of covariates with age: V3*age only =1 */
1029: int cptcovprodnoage=0; /**< Number of covariate products without age */
1030: int cptcoveff=0; /* Total number of covariates to vary for printing results */
1.233 brouard 1031: int ncovf=0; /* Total number of effective fixed covariates (dummy or quantitative) in the model */
1032: int ncovv=0; /* Total number of effective (wave) varying covariates (dummy or quantitative) in the model */
1.232 brouard 1033: int ncova=0; /* Total number of effective (wave and stepm) varying with age covariates (dummy of quantitative) in the model */
1.234 brouard 1034: int nsd=0; /**< Total number of single dummy variables (output) */
1035: int nsq=0; /**< Total number of single quantitative variables (output) */
1.232 brouard 1036: int ncoveff=0; /* Total number of effective fixed dummy covariates in the model */
1.225 brouard 1037: int nqfveff=0; /**< nqfveff Number of Quantitative Fixed Variables Effective */
1.224 brouard 1038: int ntveff=0; /**< ntveff number of effective time varying variables */
1039: int nqtveff=0; /**< ntqveff number of effective time varying quantitative variables */
1.145 brouard 1040: int cptcov=0; /* Working variable */
1.218 brouard 1041: int ncovcombmax=NCOVMAX; /* Maximum calculated number of covariate combination = pow(2, cptcoveff) */
1.126 brouard 1042: int npar=NPARMAX;
1043: int nlstate=2; /* Number of live states */
1044: int ndeath=1; /* Number of dead states */
1.130 brouard 1045: int ncovmodel=0, ncovcol=0; /* Total number of covariables including constant a12*1 +b12*x ncovmodel=2 */
1.223 brouard 1046: int nqv=0, ntv=0, nqtv=0; /* Total number of quantitative variables, time variable (dummy), quantitative and time variable */
1.126 brouard 1047: int popbased=0;
1048:
1049: int *wav; /* Number of waves for this individuual 0 is possible */
1.130 brouard 1050: int maxwav=0; /* Maxim number of waves */
1051: int jmin=0, jmax=0; /* min, max spacing between 2 waves */
1052: int ijmin=0, ijmax=0; /* Individuals having jmin and jmax */
1053: int gipmx=0, gsw=0; /* Global variables on the number of contributions
1.126 brouard 1054: to the likelihood and the sum of weights (done by funcone)*/
1.130 brouard 1055: int mle=1, weightopt=0;
1.126 brouard 1056: int **mw; /* mw[mi][i] is number of the mi wave for this individual */
1057: int **dh; /* dh[mi][i] is number of steps between mi,mi+1 for this individual */
1058: int **bh; /* bh[mi][i] is the bias (+ or -) for this individual if the delay between
1059: * wave mi and wave mi+1 is not an exact multiple of stepm. */
1.162 brouard 1060: int countcallfunc=0; /* Count the number of calls to func */
1.230 brouard 1061: int selected(int kvar); /* Is covariate kvar selected for printing results */
1062:
1.130 brouard 1063: double jmean=1; /* Mean space between 2 waves */
1.145 brouard 1064: double **matprod2(); /* test */
1.126 brouard 1065: double **oldm, **newm, **savm; /* Working pointers to matrices */
1066: double **oldms, **newms, **savms; /* Fixed working pointers to matrices */
1.218 brouard 1067: double **ddnewms, **ddoldms, **ddsavms; /* for freeing later */
1068:
1.136 brouard 1069: /*FILE *fic ; */ /* Used in readdata only */
1.217 brouard 1070: FILE *ficpar, *ficparo,*ficres, *ficresp, *ficresphtm, *ficresphtmfr, *ficrespl, *ficresplb,*ficrespij, *ficrespijb, *ficrest,*ficresf, *ficresfb,*ficrespop;
1.126 brouard 1071: FILE *ficlog, *ficrespow;
1.130 brouard 1072: int globpr=0; /* Global variable for printing or not */
1.126 brouard 1073: double fretone; /* Only one call to likelihood */
1.130 brouard 1074: long ipmx=0; /* Number of contributions */
1.126 brouard 1075: double sw; /* Sum of weights */
1076: char filerespow[FILENAMELENGTH];
1077: char fileresilk[FILENAMELENGTH]; /* File of individual contributions to the likelihood */
1078: FILE *ficresilk;
1079: FILE *ficgp,*ficresprob,*ficpop, *ficresprobcov, *ficresprobcor;
1080: FILE *ficresprobmorprev;
1081: FILE *fichtm, *fichtmcov; /* Html File */
1082: FILE *ficreseij;
1083: char filerese[FILENAMELENGTH];
1084: FILE *ficresstdeij;
1085: char fileresstde[FILENAMELENGTH];
1086: FILE *ficrescveij;
1087: char filerescve[FILENAMELENGTH];
1088: FILE *ficresvij;
1089: char fileresv[FILENAMELENGTH];
1.269 brouard 1090:
1.126 brouard 1091: char title[MAXLINE];
1.234 brouard 1092: char model[MAXLINE]; /**< The model line */
1.217 brouard 1093: char optionfile[FILENAMELENGTH], datafile[FILENAMELENGTH], filerespl[FILENAMELENGTH], fileresplb[FILENAMELENGTH];
1.126 brouard 1094: char plotcmd[FILENAMELENGTH], pplotcmd[FILENAMELENGTH];
1095: char tmpout[FILENAMELENGTH], tmpout2[FILENAMELENGTH];
1096: char command[FILENAMELENGTH];
1097: int outcmd=0;
1098:
1.217 brouard 1099: char fileres[FILENAMELENGTH], filerespij[FILENAMELENGTH], filerespijb[FILENAMELENGTH], filereso[FILENAMELENGTH], rfileres[FILENAMELENGTH];
1.202 brouard 1100: char fileresu[FILENAMELENGTH]; /* fileres without r in front */
1.126 brouard 1101: char filelog[FILENAMELENGTH]; /* Log file */
1102: char filerest[FILENAMELENGTH];
1103: char fileregp[FILENAMELENGTH];
1104: char popfile[FILENAMELENGTH];
1105:
1106: char optionfilegnuplot[FILENAMELENGTH], optionfilehtm[FILENAMELENGTH], optionfilehtmcov[FILENAMELENGTH] ;
1107:
1.157 brouard 1108: /* struct timeval start_time, end_time, curr_time, last_time, forecast_time; */
1109: /* struct timezone tzp; */
1110: /* extern int gettimeofday(); */
1111: struct tm tml, *gmtime(), *localtime();
1112:
1113: extern time_t time();
1114:
1115: struct tm start_time, end_time, curr_time, last_time, forecast_time;
1116: time_t rstart_time, rend_time, rcurr_time, rlast_time, rforecast_time; /* raw time */
1117: struct tm tm;
1118:
1.126 brouard 1119: char strcurr[80], strfor[80];
1120:
1121: char *endptr;
1122: long lval;
1123: double dval;
1124:
1125: #define NR_END 1
1126: #define FREE_ARG char*
1127: #define FTOL 1.0e-10
1128:
1129: #define NRANSI
1.240 brouard 1130: #define ITMAX 200
1131: #define ITPOWMAX 20 /* This is now multiplied by the number of parameters */
1.126 brouard 1132:
1133: #define TOL 2.0e-4
1134:
1135: #define CGOLD 0.3819660
1136: #define ZEPS 1.0e-10
1137: #define SHFT(a,b,c,d) (a)=(b);(b)=(c);(c)=(d);
1138:
1139: #define GOLD 1.618034
1140: #define GLIMIT 100.0
1141: #define TINY 1.0e-20
1142:
1143: static double maxarg1,maxarg2;
1144: #define FMAX(a,b) (maxarg1=(a),maxarg2=(b),(maxarg1)>(maxarg2)? (maxarg1):(maxarg2))
1145: #define FMIN(a,b) (maxarg1=(a),maxarg2=(b),(maxarg1)<(maxarg2)? (maxarg1):(maxarg2))
1146:
1147: #define SIGN(a,b) ((b)>0.0 ? fabs(a) : -fabs(a))
1148: #define rint(a) floor(a+0.5)
1.166 brouard 1149: /* http://www.thphys.uni-heidelberg.de/~robbers/cmbeasy/doc/html/myutils_8h-source.html */
1.183 brouard 1150: #define mytinydouble 1.0e-16
1.166 brouard 1151: /* #define DEQUAL(a,b) (fabs((a)-(b))<mytinydouble) */
1152: /* http://www.thphys.uni-heidelberg.de/~robbers/cmbeasy/doc/html/mynrutils_8h-source.html */
1153: /* static double dsqrarg; */
1154: /* #define DSQR(a) (DEQUAL((dsqrarg=(a)),0.0) ? 0.0 : dsqrarg*dsqrarg) */
1.126 brouard 1155: static double sqrarg;
1156: #define SQR(a) ((sqrarg=(a)) == 0.0 ? 0.0 :sqrarg*sqrarg)
1157: #define SWAP(a,b) {temp=(a);(a)=(b);(b)=temp;}
1158: int agegomp= AGEGOMP;
1159:
1160: int imx;
1161: int stepm=1;
1162: /* Stepm, step in month: minimum step interpolation*/
1163:
1164: int estepm;
1165: /* Estepm, step in month to interpolate survival function in order to approximate Life Expectancy*/
1166:
1167: int m,nb;
1168: long *num;
1.197 brouard 1169: int firstpass=0, lastpass=4,*cod, *cens;
1.192 brouard 1170: int *ncodemax; /* ncodemax[j]= Number of modalities of the j th
1171: covariate for which somebody answered excluding
1172: undefined. Usually 2: 0 and 1. */
1173: int *ncodemaxwundef; /* ncodemax[j]= Number of modalities of the j th
1174: covariate for which somebody answered including
1175: undefined. Usually 3: -1, 0 and 1. */
1.126 brouard 1176: double **agev,*moisnais, *annais, *moisdc, *andc,**mint, **anint;
1.218 brouard 1177: double **pmmij, ***probs; /* Global pointer */
1.219 brouard 1178: double ***mobaverage, ***mobaverages; /* New global variable */
1.126 brouard 1179: double *ageexmed,*agecens;
1180: double dateintmean=0;
1181:
1182: double *weight;
1183: int **s; /* Status */
1.141 brouard 1184: double *agedc;
1.145 brouard 1185: double **covar; /**< covar[j,i], value of jth covariate for individual i,
1.141 brouard 1186: * covar=matrix(0,NCOVMAX,1,n);
1.187 brouard 1187: * cov[Tage[kk]+2]=covar[Tvar[Tage[kk]]][i]*age; */
1.268 brouard 1188: double **coqvar; /* Fixed quantitative covariate nqv */
1189: double ***cotvar; /* Time varying covariate ntv */
1.225 brouard 1190: double ***cotqvar; /* Time varying quantitative covariate itqv */
1.141 brouard 1191: double idx;
1192: int **nbcode, *Tvar; /**< model=V2 => Tvar[1]= 2 */
1.234 brouard 1193: /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1194: /*k 1 2 3 4 5 6 7 8 9 */
1195: /*Tvar[k]= 5 4 3 6 5 2 7 1 1 */
1196: /* Tndvar[k] 1 2 3 4 5 */
1197: /*TDvar 4 3 6 7 1 */ /* For outputs only; combination of dummies fixed or varying */
1198: /* Tns[k] 1 2 2 4 5 */ /* Number of single cova */
1199: /* TvarsD[k] 1 2 3 */ /* Number of single dummy cova */
1200: /* TvarsDind 2 3 9 */ /* position K of single dummy cova */
1201: /* TvarsQ[k] 1 2 */ /* Number of single quantitative cova */
1202: /* TvarsQind 1 6 */ /* position K of single quantitative cova */
1203: /* Tprod[i]=k 4 7 */
1204: /* Tage[i]=k 5 8 */
1205: /* */
1206: /* Type */
1207: /* V 1 2 3 4 5 */
1208: /* F F V V V */
1209: /* D Q D D Q */
1210: /* */
1211: int *TvarsD;
1212: int *TvarsDind;
1213: int *TvarsQ;
1214: int *TvarsQind;
1215:
1.235 brouard 1216: #define MAXRESULTLINES 10
1217: int nresult=0;
1.258 brouard 1218: int parameterline=0; /* # of the parameter (type) line */
1.235 brouard 1219: int TKresult[MAXRESULTLINES];
1.237 brouard 1220: int Tresult[MAXRESULTLINES][NCOVMAX];/* For dummy variable , value (output) */
1221: int Tinvresult[MAXRESULTLINES][NCOVMAX];/* For dummy variable , value (output) */
1.235 brouard 1222: int Tvresult[MAXRESULTLINES][NCOVMAX]; /* For dummy variable , variable # (output) */
1223: double Tqresult[MAXRESULTLINES][NCOVMAX]; /* For quantitative variable , value (output) */
1.237 brouard 1224: double Tqinvresult[MAXRESULTLINES][NCOVMAX]; /* For quantitative variable , value (output) */
1.235 brouard 1225: int Tvqresult[MAXRESULTLINES][NCOVMAX]; /* For quantitative variable , variable # (output) */
1226:
1.234 brouard 1227: /* 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 1228: 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 */
1229: 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 */
1230: 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 */
1231: int *TvarVind; /**< TvarVind[1]=1, TvarVind[2]=2 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1232: 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 */
1233: 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 1234: int *TvarFD; /**< TvarFD[1]=V1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1235: int *TvarFDind; /* TvarFDind[1]=9 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1236: int *TvarFQ; /* TvarFQ[1]=V2 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1237: int *TvarFQind; /* TvarFQind[1]=6 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1238: int *TvarVD; /* TvarVD[1]=V5 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1239: int *TvarVDind; /* TvarVDind[1]=1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1240: 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 */
1241: 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 */
1242:
1.230 brouard 1243: int *Tvarsel; /**< Selected covariates for output */
1244: double *Tvalsel; /**< Selected modality value of covariate for output */
1.226 brouard 1245: int *Typevar; /**< 0 for simple covariate (dummy, quantitative, fixed or varying), 1 for age product, 2 for product */
1.227 brouard 1246: int *Fixed; /** Fixed[k] 0=fixed, 1 varying, 2 fixed with age product, 3 varying with age product */
1247: 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 1248: int *DummyV; /** Dummy[v] 0=dummy (0 1), 1 quantitative */
1249: int *FixedV; /** FixedV[v] 0 fixed, 1 varying */
1.197 brouard 1250: int *Tage;
1.227 brouard 1251: int anyvaryingduminmodel=0; /**< Any varying dummy in Model=1 yes, 0 no, to avoid a loop on waves in freq */
1.228 brouard 1252: 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 1253: 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*/
1254: 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 1255: int *Ndum; /** Freq of modality (tricode */
1.200 brouard 1256: /* int **codtab;*/ /**< codtab=imatrix(1,100,1,10); */
1.227 brouard 1257: int **Tvard;
1258: int *Tprod;/**< Gives the k position of the k1 product */
1.238 brouard 1259: /* Tprod[k1=1]=3(=V1*V4) for V2+V1+V1*V4+age*V3 */
1.227 brouard 1260: int *Tposprod; /**< Gives the k1 product from the k position */
1.238 brouard 1261: /* if V2+V1+V1*V4+age*V3+V3*V2 TProd[k1=2]=5 (V3*V2) */
1262: /* Tposprod[k]=k1 , Tposprod[3]=1, Tposprod[5(V3*V2)]=2 (2nd product without age) */
1.227 brouard 1263: int cptcovprod, *Tvaraff, *invalidvarcomb;
1.126 brouard 1264: double *lsurv, *lpop, *tpop;
1265:
1.231 brouard 1266: #define FD 1; /* Fixed dummy covariate */
1267: #define FQ 2; /* Fixed quantitative covariate */
1268: #define FP 3; /* Fixed product covariate */
1269: #define FPDD 7; /* Fixed product dummy*dummy covariate */
1270: #define FPDQ 8; /* Fixed product dummy*quantitative covariate */
1271: #define FPQQ 9; /* Fixed product quantitative*quantitative covariate */
1272: #define VD 10; /* Varying dummy covariate */
1273: #define VQ 11; /* Varying quantitative covariate */
1274: #define VP 12; /* Varying product covariate */
1275: #define VPDD 13; /* Varying product dummy*dummy covariate */
1276: #define VPDQ 14; /* Varying product dummy*quantitative covariate */
1277: #define VPQQ 15; /* Varying product quantitative*quantitative covariate */
1278: #define APFD 16; /* Age product * fixed dummy covariate */
1279: #define APFQ 17; /* Age product * fixed quantitative covariate */
1280: #define APVD 18; /* Age product * varying dummy covariate */
1281: #define APVQ 19; /* Age product * varying quantitative covariate */
1282:
1283: #define FTYPE 1; /* Fixed covariate */
1284: #define VTYPE 2; /* Varying covariate (loop in wave) */
1285: #define ATYPE 2; /* Age product covariate (loop in dh within wave)*/
1286:
1287: struct kmodel{
1288: int maintype; /* main type */
1289: int subtype; /* subtype */
1290: };
1291: struct kmodel modell[NCOVMAX];
1292:
1.143 brouard 1293: double ftol=FTOL; /**< Tolerance for computing Max Likelihood */
1294: double ftolhess; /**< Tolerance for computing hessian */
1.126 brouard 1295:
1296: /**************** split *************************/
1297: static int split( char *path, char *dirc, char *name, char *ext, char *finame )
1298: {
1299: /* From a file name with (full) path (either Unix or Windows) we extract the directory (dirc)
1300: the name of the file (name), its extension only (ext) and its first part of the name (finame)
1301: */
1302: char *ss; /* pointer */
1.186 brouard 1303: int l1=0, l2=0; /* length counters */
1.126 brouard 1304:
1305: l1 = strlen(path ); /* length of path */
1306: if ( l1 == 0 ) return( GLOCK_ERROR_NOPATH );
1307: ss= strrchr( path, DIRSEPARATOR ); /* find last / */
1308: if ( ss == NULL ) { /* no directory, so determine current directory */
1309: strcpy( name, path ); /* we got the fullname name because no directory */
1310: /*if(strrchr(path, ODIRSEPARATOR )==NULL)
1311: printf("Warning you should use %s as a separator\n",DIRSEPARATOR);*/
1312: /* get current working directory */
1313: /* extern char* getcwd ( char *buf , int len);*/
1.184 brouard 1314: #ifdef WIN32
1315: if (_getcwd( dirc, FILENAME_MAX ) == NULL ) {
1316: #else
1317: if (getcwd(dirc, FILENAME_MAX) == NULL) {
1318: #endif
1.126 brouard 1319: return( GLOCK_ERROR_GETCWD );
1320: }
1321: /* got dirc from getcwd*/
1322: printf(" DIRC = %s \n",dirc);
1.205 brouard 1323: } else { /* strip directory from path */
1.126 brouard 1324: ss++; /* after this, the filename */
1325: l2 = strlen( ss ); /* length of filename */
1326: if ( l2 == 0 ) return( GLOCK_ERROR_NOPATH );
1327: strcpy( name, ss ); /* save file name */
1328: strncpy( dirc, path, l1 - l2 ); /* now the directory */
1.186 brouard 1329: dirc[l1-l2] = '\0'; /* add zero */
1.126 brouard 1330: printf(" DIRC2 = %s \n",dirc);
1331: }
1332: /* We add a separator at the end of dirc if not exists */
1333: l1 = strlen( dirc ); /* length of directory */
1334: if( dirc[l1-1] != DIRSEPARATOR ){
1335: dirc[l1] = DIRSEPARATOR;
1336: dirc[l1+1] = 0;
1337: printf(" DIRC3 = %s \n",dirc);
1338: }
1339: ss = strrchr( name, '.' ); /* find last / */
1340: if (ss >0){
1341: ss++;
1342: strcpy(ext,ss); /* save extension */
1343: l1= strlen( name);
1344: l2= strlen(ss)+1;
1345: strncpy( finame, name, l1-l2);
1346: finame[l1-l2]= 0;
1347: }
1348:
1349: return( 0 ); /* we're done */
1350: }
1351:
1352:
1353: /******************************************/
1354:
1355: void replace_back_to_slash(char *s, char*t)
1356: {
1357: int i;
1358: int lg=0;
1359: i=0;
1360: lg=strlen(t);
1361: for(i=0; i<= lg; i++) {
1362: (s[i] = t[i]);
1363: if (t[i]== '\\') s[i]='/';
1364: }
1365: }
1366:
1.132 brouard 1367: char *trimbb(char *out, char *in)
1.137 brouard 1368: { /* Trim multiple blanks in line but keeps first blanks if line starts with blanks */
1.132 brouard 1369: char *s;
1370: s=out;
1371: while (*in != '\0'){
1.137 brouard 1372: while( *in == ' ' && *(in+1) == ' '){ /* && *(in+1) != '\0'){*/
1.132 brouard 1373: in++;
1374: }
1375: *out++ = *in++;
1376: }
1377: *out='\0';
1378: return s;
1379: }
1380:
1.187 brouard 1381: /* char *substrchaine(char *out, char *in, char *chain) */
1382: /* { */
1383: /* /\* Substract chain 'chain' from 'in', return and output 'out' *\/ */
1384: /* char *s, *t; */
1385: /* t=in;s=out; */
1386: /* while ((*in != *chain) && (*in != '\0')){ */
1387: /* *out++ = *in++; */
1388: /* } */
1389:
1390: /* /\* *in matches *chain *\/ */
1391: /* while ((*in++ == *chain++) && (*in != '\0')){ */
1392: /* printf("*in = %c, *out= %c *chain= %c \n", *in, *out, *chain); */
1393: /* } */
1394: /* in--; chain--; */
1395: /* while ( (*in != '\0')){ */
1396: /* printf("Bef *in = %c, *out= %c *chain= %c \n", *in, *out, *chain); */
1397: /* *out++ = *in++; */
1398: /* printf("Aft *in = %c, *out= %c *chain= %c \n", *in, *out, *chain); */
1399: /* } */
1400: /* *out='\0'; */
1401: /* out=s; */
1402: /* return out; */
1403: /* } */
1404: char *substrchaine(char *out, char *in, char *chain)
1405: {
1406: /* Substract chain 'chain' from 'in', return and output 'out' */
1407: /* in="V1+V1*age+age*age+V2", chain="age*age" */
1408:
1409: char *strloc;
1410:
1411: strcpy (out, in);
1412: strloc = strstr(out, chain); /* strloc points to out at age*age+V2 */
1413: printf("Bef strloc=%s chain=%s out=%s \n", strloc, chain, out);
1414: if(strloc != NULL){
1415: /* will affect out */ /* strloc+strlenc(chain)=+V2 */ /* Will also work in Unicode */
1416: memmove(strloc,strloc+strlen(chain), strlen(strloc+strlen(chain))+1);
1417: /* strcpy (strloc, strloc +strlen(chain));*/
1418: }
1419: printf("Aft strloc=%s chain=%s in=%s out=%s \n", strloc, chain, in, out);
1420: return out;
1421: }
1422:
1423:
1.145 brouard 1424: char *cutl(char *blocc, char *alocc, char *in, char occ)
1425: {
1.187 brouard 1426: /* cuts string in into blocc and alocc where blocc ends before FIRST occurence of char 'occ'
1.145 brouard 1427: and alocc starts after first occurence of char 'occ' : ex cutv(blocc,alocc,"abcdef2ghi2j",'2')
1.187 brouard 1428: gives blocc="abcdef" and alocc="ghi2j".
1.145 brouard 1429: If occ is not found blocc is null and alocc is equal to in. Returns blocc
1430: */
1.160 brouard 1431: char *s, *t;
1.145 brouard 1432: t=in;s=in;
1433: while ((*in != occ) && (*in != '\0')){
1434: *alocc++ = *in++;
1435: }
1436: if( *in == occ){
1437: *(alocc)='\0';
1438: s=++in;
1439: }
1440:
1441: if (s == t) {/* occ not found */
1442: *(alocc-(in-s))='\0';
1443: in=s;
1444: }
1445: while ( *in != '\0'){
1446: *blocc++ = *in++;
1447: }
1448:
1449: *blocc='\0';
1450: return t;
1451: }
1.137 brouard 1452: char *cutv(char *blocc, char *alocc, char *in, char occ)
1453: {
1.187 brouard 1454: /* cuts string in into blocc and alocc where blocc ends before LAST occurence of char 'occ'
1.137 brouard 1455: and alocc starts after last occurence of char 'occ' : ex cutv(blocc,alocc,"abcdef2ghi2j",'2')
1456: gives blocc="abcdef2ghi" and alocc="j".
1457: If occ is not found blocc is null and alocc is equal to in. Returns alocc
1458: */
1459: char *s, *t;
1460: t=in;s=in;
1461: while (*in != '\0'){
1462: while( *in == occ){
1463: *blocc++ = *in++;
1464: s=in;
1465: }
1466: *blocc++ = *in++;
1467: }
1468: if (s == t) /* occ not found */
1469: *(blocc-(in-s))='\0';
1470: else
1471: *(blocc-(in-s)-1)='\0';
1472: in=s;
1473: while ( *in != '\0'){
1474: *alocc++ = *in++;
1475: }
1476:
1477: *alocc='\0';
1478: return s;
1479: }
1480:
1.126 brouard 1481: int nbocc(char *s, char occ)
1482: {
1483: int i,j=0;
1484: int lg=20;
1485: i=0;
1486: lg=strlen(s);
1487: for(i=0; i<= lg; i++) {
1.234 brouard 1488: if (s[i] == occ ) j++;
1.126 brouard 1489: }
1490: return j;
1491: }
1492:
1.137 brouard 1493: /* void cutv(char *u,char *v, char*t, char occ) */
1494: /* { */
1495: /* /\* cuts string t into u and v where u ends before last occurence of char 'occ' */
1496: /* and v starts after last occurence of char 'occ' : ex cutv(u,v,"abcdef2ghi2j",'2') */
1497: /* gives u="abcdef2ghi" and v="j" *\/ */
1498: /* int i,lg,j,p=0; */
1499: /* i=0; */
1500: /* lg=strlen(t); */
1501: /* for(j=0; j<=lg-1; j++) { */
1502: /* if((t[j]!= occ) && (t[j+1]== occ)) p=j+1; */
1503: /* } */
1.126 brouard 1504:
1.137 brouard 1505: /* for(j=0; j<p; j++) { */
1506: /* (u[j] = t[j]); */
1507: /* } */
1508: /* u[p]='\0'; */
1.126 brouard 1509:
1.137 brouard 1510: /* for(j=0; j<= lg; j++) { */
1511: /* if (j>=(p+1))(v[j-p-1] = t[j]); */
1512: /* } */
1513: /* } */
1.126 brouard 1514:
1.160 brouard 1515: #ifdef _WIN32
1516: char * strsep(char **pp, const char *delim)
1517: {
1518: char *p, *q;
1519:
1520: if ((p = *pp) == NULL)
1521: return 0;
1522: if ((q = strpbrk (p, delim)) != NULL)
1523: {
1524: *pp = q + 1;
1525: *q = '\0';
1526: }
1527: else
1528: *pp = 0;
1529: return p;
1530: }
1531: #endif
1532:
1.126 brouard 1533: /********************** nrerror ********************/
1534:
1535: void nrerror(char error_text[])
1536: {
1537: fprintf(stderr,"ERREUR ...\n");
1538: fprintf(stderr,"%s\n",error_text);
1539: exit(EXIT_FAILURE);
1540: }
1541: /*********************** vector *******************/
1542: double *vector(int nl, int nh)
1543: {
1544: double *v;
1545: v=(double *) malloc((size_t)((nh-nl+1+NR_END)*sizeof(double)));
1546: if (!v) nrerror("allocation failure in vector");
1547: return v-nl+NR_END;
1548: }
1549:
1550: /************************ free vector ******************/
1551: void free_vector(double*v, int nl, int nh)
1552: {
1553: free((FREE_ARG)(v+nl-NR_END));
1554: }
1555:
1556: /************************ivector *******************************/
1557: int *ivector(long nl,long nh)
1558: {
1559: int *v;
1560: v=(int *) malloc((size_t)((nh-nl+1+NR_END)*sizeof(int)));
1561: if (!v) nrerror("allocation failure in ivector");
1562: return v-nl+NR_END;
1563: }
1564:
1565: /******************free ivector **************************/
1566: void free_ivector(int *v, long nl, long nh)
1567: {
1568: free((FREE_ARG)(v+nl-NR_END));
1569: }
1570:
1571: /************************lvector *******************************/
1572: long *lvector(long nl,long nh)
1573: {
1574: long *v;
1575: v=(long *) malloc((size_t)((nh-nl+1+NR_END)*sizeof(long)));
1576: if (!v) nrerror("allocation failure in ivector");
1577: return v-nl+NR_END;
1578: }
1579:
1580: /******************free lvector **************************/
1581: void free_lvector(long *v, long nl, long nh)
1582: {
1583: free((FREE_ARG)(v+nl-NR_END));
1584: }
1585:
1586: /******************* imatrix *******************************/
1587: int **imatrix(long nrl, long nrh, long ncl, long nch)
1588: /* allocate a int matrix with subscript range m[nrl..nrh][ncl..nch] */
1589: {
1590: long i, nrow=nrh-nrl+1,ncol=nch-ncl+1;
1591: int **m;
1592:
1593: /* allocate pointers to rows */
1594: m=(int **) malloc((size_t)((nrow+NR_END)*sizeof(int*)));
1595: if (!m) nrerror("allocation failure 1 in matrix()");
1596: m += NR_END;
1597: m -= nrl;
1598:
1599:
1600: /* allocate rows and set pointers to them */
1601: m[nrl]=(int *) malloc((size_t)((nrow*ncol+NR_END)*sizeof(int)));
1602: if (!m[nrl]) nrerror("allocation failure 2 in matrix()");
1603: m[nrl] += NR_END;
1604: m[nrl] -= ncl;
1605:
1606: for(i=nrl+1;i<=nrh;i++) m[i]=m[i-1]+ncol;
1607:
1608: /* return pointer to array of pointers to rows */
1609: return m;
1610: }
1611:
1612: /****************** free_imatrix *************************/
1613: void free_imatrix(m,nrl,nrh,ncl,nch)
1614: int **m;
1615: long nch,ncl,nrh,nrl;
1616: /* free an int matrix allocated by imatrix() */
1617: {
1618: free((FREE_ARG) (m[nrl]+ncl-NR_END));
1619: free((FREE_ARG) (m+nrl-NR_END));
1620: }
1621:
1622: /******************* matrix *******************************/
1623: double **matrix(long nrl, long nrh, long ncl, long nch)
1624: {
1625: long i, nrow=nrh-nrl+1, ncol=nch-ncl+1;
1626: double **m;
1627:
1628: m=(double **) malloc((size_t)((nrow+NR_END)*sizeof(double*)));
1629: if (!m) nrerror("allocation failure 1 in matrix()");
1630: m += NR_END;
1631: m -= nrl;
1632:
1633: m[nrl]=(double *) malloc((size_t)((nrow*ncol+NR_END)*sizeof(double)));
1634: if (!m[nrl]) nrerror("allocation failure 2 in matrix()");
1635: m[nrl] += NR_END;
1636: m[nrl] -= ncl;
1637:
1638: for (i=nrl+1; i<=nrh; i++) m[i]=m[i-1]+ncol;
1639: return m;
1.145 brouard 1640: /* print *(*(m+1)+70) or print m[1][70]; print m+1 or print &(m[1]) or &(m[1][0])
1641: m[i] = address of ith row of the table. &(m[i]) is its value which is another adress
1642: that of m[i][0]. In order to get the value p m[i][0] but it is unitialized.
1.126 brouard 1643: */
1644: }
1645:
1646: /*************************free matrix ************************/
1647: void free_matrix(double **m, long nrl, long nrh, long ncl, long nch)
1648: {
1649: free((FREE_ARG)(m[nrl]+ncl-NR_END));
1650: free((FREE_ARG)(m+nrl-NR_END));
1651: }
1652:
1653: /******************* ma3x *******************************/
1654: double ***ma3x(long nrl, long nrh, long ncl, long nch, long nll, long nlh)
1655: {
1656: long i, j, nrow=nrh-nrl+1, ncol=nch-ncl+1, nlay=nlh-nll+1;
1657: double ***m;
1658:
1659: m=(double ***) malloc((size_t)((nrow+NR_END)*sizeof(double*)));
1660: if (!m) nrerror("allocation failure 1 in matrix()");
1661: m += NR_END;
1662: m -= nrl;
1663:
1664: m[nrl]=(double **) malloc((size_t)((nrow*ncol+NR_END)*sizeof(double)));
1665: if (!m[nrl]) nrerror("allocation failure 2 in matrix()");
1666: m[nrl] += NR_END;
1667: m[nrl] -= ncl;
1668:
1669: for (i=nrl+1; i<=nrh; i++) m[i]=m[i-1]+ncol;
1670:
1671: m[nrl][ncl]=(double *) malloc((size_t)((nrow*ncol*nlay+NR_END)*sizeof(double)));
1672: if (!m[nrl][ncl]) nrerror("allocation failure 3 in matrix()");
1673: m[nrl][ncl] += NR_END;
1674: m[nrl][ncl] -= nll;
1675: for (j=ncl+1; j<=nch; j++)
1676: m[nrl][j]=m[nrl][j-1]+nlay;
1677:
1678: for (i=nrl+1; i<=nrh; i++) {
1679: m[i][ncl]=m[i-1l][ncl]+ncol*nlay;
1680: for (j=ncl+1; j<=nch; j++)
1681: m[i][j]=m[i][j-1]+nlay;
1682: }
1683: return m;
1684: /* gdb: p *(m+1) <=> p m[1] and p (m+1) <=> p (m+1) <=> p &(m[1])
1685: &(m[i][j][k]) <=> *((*(m+i) + j)+k)
1686: */
1687: }
1688:
1689: /*************************free ma3x ************************/
1690: void free_ma3x(double ***m, long nrl, long nrh, long ncl, long nch,long nll, long nlh)
1691: {
1692: free((FREE_ARG)(m[nrl][ncl]+ nll-NR_END));
1693: free((FREE_ARG)(m[nrl]+ncl-NR_END));
1694: free((FREE_ARG)(m+nrl-NR_END));
1695: }
1696:
1697: /*************** function subdirf ***********/
1698: char *subdirf(char fileres[])
1699: {
1700: /* Caution optionfilefiname is hidden */
1701: strcpy(tmpout,optionfilefiname);
1702: strcat(tmpout,"/"); /* Add to the right */
1703: strcat(tmpout,fileres);
1704: return tmpout;
1705: }
1706:
1707: /*************** function subdirf2 ***********/
1708: char *subdirf2(char fileres[], char *preop)
1709: {
1710:
1711: /* Caution optionfilefiname is hidden */
1712: strcpy(tmpout,optionfilefiname);
1713: strcat(tmpout,"/");
1714: strcat(tmpout,preop);
1715: strcat(tmpout,fileres);
1716: return tmpout;
1717: }
1718:
1719: /*************** function subdirf3 ***********/
1720: char *subdirf3(char fileres[], char *preop, char *preop2)
1721: {
1722:
1723: /* Caution optionfilefiname is hidden */
1724: strcpy(tmpout,optionfilefiname);
1725: strcat(tmpout,"/");
1726: strcat(tmpout,preop);
1727: strcat(tmpout,preop2);
1728: strcat(tmpout,fileres);
1729: return tmpout;
1730: }
1.213 brouard 1731:
1732: /*************** function subdirfext ***********/
1733: char *subdirfext(char fileres[], char *preop, char *postop)
1734: {
1735:
1736: strcpy(tmpout,preop);
1737: strcat(tmpout,fileres);
1738: strcat(tmpout,postop);
1739: return tmpout;
1740: }
1.126 brouard 1741:
1.213 brouard 1742: /*************** function subdirfext3 ***********/
1743: char *subdirfext3(char fileres[], char *preop, char *postop)
1744: {
1745:
1746: /* Caution optionfilefiname is hidden */
1747: strcpy(tmpout,optionfilefiname);
1748: strcat(tmpout,"/");
1749: strcat(tmpout,preop);
1750: strcat(tmpout,fileres);
1751: strcat(tmpout,postop);
1752: return tmpout;
1753: }
1754:
1.162 brouard 1755: char *asc_diff_time(long time_sec, char ascdiff[])
1756: {
1757: long sec_left, days, hours, minutes;
1758: days = (time_sec) / (60*60*24);
1759: sec_left = (time_sec) % (60*60*24);
1760: hours = (sec_left) / (60*60) ;
1761: sec_left = (sec_left) %(60*60);
1762: minutes = (sec_left) /60;
1763: sec_left = (sec_left) % (60);
1764: sprintf(ascdiff,"%ld day(s) %ld hour(s) %ld minute(s) %ld second(s)",days, hours, minutes, sec_left);
1765: return ascdiff;
1766: }
1767:
1.126 brouard 1768: /***************** f1dim *************************/
1769: extern int ncom;
1770: extern double *pcom,*xicom;
1771: extern double (*nrfunc)(double []);
1772:
1773: double f1dim(double x)
1774: {
1775: int j;
1776: double f;
1777: double *xt;
1778:
1779: xt=vector(1,ncom);
1780: for (j=1;j<=ncom;j++) xt[j]=pcom[j]+x*xicom[j];
1781: f=(*nrfunc)(xt);
1782: free_vector(xt,1,ncom);
1783: return f;
1784: }
1785:
1786: /*****************brent *************************/
1787: double brent(double ax, double bx, double cx, double (*f)(double), double tol, double *xmin)
1.187 brouard 1788: {
1789: /* Given a function f, and given a bracketing triplet of abscissas ax, bx, cx (such that bx is
1790: * between ax and cx, and f(bx) is less than both f(ax) and f(cx) ), this routine isolates
1791: * the minimum to a fractional precision of about tol using Brent’s method. The abscissa of
1792: * the minimum is returned as xmin, and the minimum function value is returned as brent , the
1793: * returned function value.
1794: */
1.126 brouard 1795: int iter;
1796: double a,b,d,etemp;
1.159 brouard 1797: double fu=0,fv,fw,fx;
1.164 brouard 1798: double ftemp=0.;
1.126 brouard 1799: double p,q,r,tol1,tol2,u,v,w,x,xm;
1800: double e=0.0;
1801:
1802: a=(ax < cx ? ax : cx);
1803: b=(ax > cx ? ax : cx);
1804: x=w=v=bx;
1805: fw=fv=fx=(*f)(x);
1806: for (iter=1;iter<=ITMAX;iter++) {
1807: xm=0.5*(a+b);
1808: tol2=2.0*(tol1=tol*fabs(x)+ZEPS);
1809: /* if (2.0*fabs(fp-(*fret)) <= ftol*(fabs(fp)+fabs(*fret)))*/
1810: printf(".");fflush(stdout);
1811: fprintf(ficlog,".");fflush(ficlog);
1.162 brouard 1812: #ifdef DEBUGBRENT
1.126 brouard 1813: 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);
1814: 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);
1815: /* if ((fabs(x-xm) <= (tol2-0.5*(b-a)))||(2.0*fabs(fu-ftemp) <= ftol*1.e-2*(fabs(fu)+fabs(ftemp)))) { */
1816: #endif
1817: if (fabs(x-xm) <= (tol2-0.5*(b-a))){
1818: *xmin=x;
1819: return fx;
1820: }
1821: ftemp=fu;
1822: if (fabs(e) > tol1) {
1823: r=(x-w)*(fx-fv);
1824: q=(x-v)*(fx-fw);
1825: p=(x-v)*q-(x-w)*r;
1826: q=2.0*(q-r);
1827: if (q > 0.0) p = -p;
1828: q=fabs(q);
1829: etemp=e;
1830: e=d;
1831: if (fabs(p) >= fabs(0.5*q*etemp) || p <= q*(a-x) || p >= q*(b-x))
1.224 brouard 1832: d=CGOLD*(e=(x >= xm ? a-x : b-x));
1.126 brouard 1833: else {
1.224 brouard 1834: d=p/q;
1835: u=x+d;
1836: if (u-a < tol2 || b-u < tol2)
1837: d=SIGN(tol1,xm-x);
1.126 brouard 1838: }
1839: } else {
1840: d=CGOLD*(e=(x >= xm ? a-x : b-x));
1841: }
1842: u=(fabs(d) >= tol1 ? x+d : x+SIGN(tol1,d));
1843: fu=(*f)(u);
1844: if (fu <= fx) {
1845: if (u >= x) a=x; else b=x;
1846: SHFT(v,w,x,u)
1.183 brouard 1847: SHFT(fv,fw,fx,fu)
1848: } else {
1849: if (u < x) a=u; else b=u;
1850: if (fu <= fw || w == x) {
1.224 brouard 1851: v=w;
1852: w=u;
1853: fv=fw;
1854: fw=fu;
1.183 brouard 1855: } else if (fu <= fv || v == x || v == w) {
1.224 brouard 1856: v=u;
1857: fv=fu;
1.183 brouard 1858: }
1859: }
1.126 brouard 1860: }
1861: nrerror("Too many iterations in brent");
1862: *xmin=x;
1863: return fx;
1864: }
1865:
1866: /****************** mnbrak ***********************/
1867:
1868: void mnbrak(double *ax, double *bx, double *cx, double *fa, double *fb, double *fc,
1869: double (*func)(double))
1.183 brouard 1870: { /* Given a function func , and given distinct initial points ax and bx , this routine searches in
1871: the downhill direction (defined by the function as evaluated at the initial points) and returns
1872: new points ax , bx , cx that bracket a minimum of the function. Also returned are the function
1873: values at the three points, fa, fb , and fc such that fa > fb and fb < fc.
1874: */
1.126 brouard 1875: double ulim,u,r,q, dum;
1876: double fu;
1.187 brouard 1877:
1878: double scale=10.;
1879: int iterscale=0;
1880:
1881: *fa=(*func)(*ax); /* xta[j]=pcom[j]+(*ax)*xicom[j]; fa=f(xta[j])*/
1882: *fb=(*func)(*bx); /* xtb[j]=pcom[j]+(*bx)*xicom[j]; fb=f(xtb[j]) */
1883:
1884:
1885: /* while(*fb != *fb){ /\* *ax should be ok, reducing distance to *ax *\/ */
1886: /* printf("Warning mnbrak *fb = %lf, *bx=%lf *ax=%lf *fa==%lf iter=%d\n",*fb, *bx, *ax, *fa, iterscale++); */
1887: /* *bx = *ax - (*ax - *bx)/scale; */
1888: /* *fb=(*func)(*bx); /\* xtb[j]=pcom[j]+(*bx)*xicom[j]; fb=f(xtb[j]) *\/ */
1889: /* } */
1890:
1.126 brouard 1891: if (*fb > *fa) {
1892: SHFT(dum,*ax,*bx,dum)
1.183 brouard 1893: SHFT(dum,*fb,*fa,dum)
1894: }
1.126 brouard 1895: *cx=(*bx)+GOLD*(*bx-*ax);
1896: *fc=(*func)(*cx);
1.183 brouard 1897: #ifdef DEBUG
1.224 brouard 1898: printf("mnbrak0 a=%lf *fa=%lf, b=%lf *fb=%lf, c=%lf *fc=%lf\n",*ax,*fa,*bx,*fb,*cx, *fc);
1899: 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 1900: #endif
1.224 brouard 1901: 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 1902: r=(*bx-*ax)*(*fb-*fc);
1.224 brouard 1903: q=(*bx-*cx)*(*fb-*fa); /* What if fa=inf */
1.126 brouard 1904: u=(*bx)-((*bx-*cx)*q-(*bx-*ax)*r)/
1.183 brouard 1905: (2.0*SIGN(FMAX(fabs(q-r),TINY),q-r)); /* Minimum abscissa of a parabolic estimated from (a,fa), (b,fb) and (c,fc). */
1906: ulim=(*bx)+GLIMIT*(*cx-*bx); /* Maximum abscissa where function should be evaluated */
1907: if ((*bx-u)*(u-*cx) > 0.0) { /* if u_p is between b and c */
1.126 brouard 1908: fu=(*func)(u);
1.163 brouard 1909: #ifdef DEBUG
1910: /* f(x)=A(x-u)**2+f(u) */
1911: double A, fparabu;
1912: A= (*fb - *fa)/(*bx-*ax)/(*bx+*ax-2*u);
1913: fparabu= *fa - A*(*ax-u)*(*ax-u);
1.224 brouard 1914: 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);
1915: 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 1916: /* And thus,it can be that fu > *fc even if fparabu < *fc */
1917: /* mnbrak (*ax=7.666299858533, *fa=299039.693133272231), (*bx=8.595447774979, *fb=298976.598289369489),
1918: (*cx=10.098840694817, *fc=298946.631474258087), (*u=9.852501168332, fu=298948.773013752128, fparabu=298945.434711494134) */
1919: /* In that case, there is no bracket in the output! Routine is wrong with many consequences.*/
1.163 brouard 1920: #endif
1.184 brouard 1921: #ifdef MNBRAKORIGINAL
1.183 brouard 1922: #else
1.191 brouard 1923: /* if (fu > *fc) { */
1924: /* #ifdef DEBUG */
1925: /* printf("mnbrak4 fu > fc \n"); */
1926: /* fprintf(ficlog, "mnbrak4 fu > fc\n"); */
1927: /* #endif */
1928: /* /\* 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 *\\/ *\/ */
1929: /* /\* SHFT(*fa,*fc,fu,*fc) /\\* (b, u, c) is a bracket while test fb > fc will be fu > fc will exit *\\/ *\/ */
1930: /* dum=u; /\* Shifting c and u *\/ */
1931: /* u = *cx; */
1932: /* *cx = dum; */
1933: /* dum = fu; */
1934: /* fu = *fc; */
1935: /* *fc =dum; */
1936: /* } else { /\* end *\/ */
1937: /* #ifdef DEBUG */
1938: /* printf("mnbrak3 fu < fc \n"); */
1939: /* fprintf(ficlog, "mnbrak3 fu < fc\n"); */
1940: /* #endif */
1941: /* dum=u; /\* Shifting c and u *\/ */
1942: /* u = *cx; */
1943: /* *cx = dum; */
1944: /* dum = fu; */
1945: /* fu = *fc; */
1946: /* *fc =dum; */
1947: /* } */
1.224 brouard 1948: #ifdef DEBUGMNBRAK
1949: double A, fparabu;
1950: A= (*fb - *fa)/(*bx-*ax)/(*bx+*ax-2*u);
1951: fparabu= *fa - A*(*ax-u)*(*ax-u);
1952: 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);
1953: 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 1954: #endif
1.191 brouard 1955: dum=u; /* Shifting c and u */
1956: u = *cx;
1957: *cx = dum;
1958: dum = fu;
1959: fu = *fc;
1960: *fc =dum;
1.183 brouard 1961: #endif
1.162 brouard 1962: } else if ((*cx-u)*(u-ulim) > 0.0) { /* u is after c but before ulim */
1.183 brouard 1963: #ifdef DEBUG
1.224 brouard 1964: printf("\nmnbrak2 u=%lf after c=%lf but before ulim\n",u,*cx);
1965: fprintf(ficlog,"\nmnbrak2 u=%lf after c=%lf but before ulim\n",u,*cx);
1.183 brouard 1966: #endif
1.126 brouard 1967: fu=(*func)(u);
1968: if (fu < *fc) {
1.183 brouard 1969: #ifdef DEBUG
1.224 brouard 1970: printf("\nmnbrak2 u=%lf after c=%lf but before ulim=%lf AND fu=%lf < %lf=fc\n",u,*cx,ulim,fu, *fc);
1971: fprintf(ficlog,"\nmnbrak2 u=%lf after c=%lf but before ulim=%lf AND fu=%lf < %lf=fc\n",u,*cx,ulim,fu, *fc);
1972: #endif
1973: SHFT(*bx,*cx,u,*cx+GOLD*(*cx-*bx))
1974: SHFT(*fb,*fc,fu,(*func)(u))
1975: #ifdef DEBUG
1976: printf("\nmnbrak2 shift GOLD c=%lf",*cx+GOLD*(*cx-*bx));
1.183 brouard 1977: #endif
1978: }
1.162 brouard 1979: } else if ((u-ulim)*(ulim-*cx) >= 0.0) { /* u outside ulim (verifying that ulim is beyond c) */
1.183 brouard 1980: #ifdef DEBUG
1.224 brouard 1981: printf("\nmnbrak2 u=%lf outside ulim=%lf (verifying that ulim is beyond c=%lf)\n",u,ulim,*cx);
1982: fprintf(ficlog,"\nmnbrak2 u=%lf outside ulim=%lf (verifying that ulim is beyond c=%lf)\n",u,ulim,*cx);
1.183 brouard 1983: #endif
1.126 brouard 1984: u=ulim;
1985: fu=(*func)(u);
1.183 brouard 1986: } else { /* u could be left to b (if r > q parabola has a maximum) */
1987: #ifdef DEBUG
1.224 brouard 1988: printf("\nmnbrak2 u=%lf could be left to b=%lf (if r=%lf > q=%lf parabola has a maximum)\n",u,*bx,r,q);
1989: 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 1990: #endif
1.126 brouard 1991: u=(*cx)+GOLD*(*cx-*bx);
1992: fu=(*func)(u);
1.224 brouard 1993: #ifdef DEBUG
1994: printf("\nmnbrak2 new u=%lf fu=%lf shifted gold left from c=%lf and b=%lf \n",u,fu,*cx,*bx);
1995: fprintf(ficlog,"\nmnbrak2 new u=%lf fu=%lf shifted gold left from c=%lf and b=%lf \n",u,fu,*cx,*bx);
1996: #endif
1.183 brouard 1997: } /* end tests */
1.126 brouard 1998: SHFT(*ax,*bx,*cx,u)
1.183 brouard 1999: SHFT(*fa,*fb,*fc,fu)
2000: #ifdef DEBUG
1.224 brouard 2001: printf("\nmnbrak2 shift (*ax=%.12f, *fa=%.12lf), (*bx=%.12f, *fb=%.12lf), (*cx=%.12f, *fc=%.12lf)\n",*ax,*fa,*bx,*fb,*cx,*fc);
2002: 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 2003: #endif
2004: } /* 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 2005: }
2006:
2007: /*************** linmin ************************/
1.162 brouard 2008: /* Given an n -dimensional point p[1..n] and an n -dimensional direction xi[1..n] , moves and
2009: resets p to where the function func(p) takes on a minimum along the direction xi from p ,
2010: and replaces xi by the actual vector displacement that p was moved. Also returns as fret
2011: the value of func at the returned location p . This is actually all accomplished by calling the
2012: routines mnbrak and brent .*/
1.126 brouard 2013: int ncom;
2014: double *pcom,*xicom;
2015: double (*nrfunc)(double []);
2016:
1.224 brouard 2017: #ifdef LINMINORIGINAL
1.126 brouard 2018: void linmin(double p[], double xi[], int n, double *fret,double (*func)(double []))
1.224 brouard 2019: #else
2020: void linmin(double p[], double xi[], int n, double *fret,double (*func)(double []), int *flat)
2021: #endif
1.126 brouard 2022: {
2023: double brent(double ax, double bx, double cx,
2024: double (*f)(double), double tol, double *xmin);
2025: double f1dim(double x);
2026: void mnbrak(double *ax, double *bx, double *cx, double *fa, double *fb,
2027: double *fc, double (*func)(double));
2028: int j;
2029: double xx,xmin,bx,ax;
2030: double fx,fb,fa;
1.187 brouard 2031:
1.203 brouard 2032: #ifdef LINMINORIGINAL
2033: #else
2034: double scale=10., axs, xxs; /* Scale added for infinity */
2035: #endif
2036:
1.126 brouard 2037: ncom=n;
2038: pcom=vector(1,n);
2039: xicom=vector(1,n);
2040: nrfunc=func;
2041: for (j=1;j<=n;j++) {
2042: pcom[j]=p[j];
1.202 brouard 2043: xicom[j]=xi[j]; /* Former scale xi[j] of currrent direction i */
1.126 brouard 2044: }
1.187 brouard 2045:
1.203 brouard 2046: #ifdef LINMINORIGINAL
2047: xx=1.;
2048: #else
2049: axs=0.0;
2050: xxs=1.;
2051: do{
2052: xx= xxs;
2053: #endif
1.187 brouard 2054: ax=0.;
2055: mnbrak(&ax,&xx,&bx,&fa,&fx,&fb,f1dim); /* Outputs: xtx[j]=pcom[j]+(*xx)*xicom[j]; fx=f(xtx[j]) */
2056: /* brackets with inputs ax=0 and xx=1, but points, pcom=p, and directions values, xicom=xi, are sent via f1dim(x) */
2057: /* 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)) */
2058: /* Outputs: fa=f(p(j)) and fx=f(p(j) + xxs * xi(j) ) and f(bx)= f(p(j)+ bx* xi(j)) */
2059: /* Given input ax=axs and xx=xxs, xx might be too far from ax to get a finite f(xx) */
2060: /* Searches on line, outputs (ax, xx, bx) such that fx < min(fa and fb) */
2061: /* 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 2062: #ifdef LINMINORIGINAL
2063: #else
2064: if (fx != fx){
1.224 brouard 2065: xxs=xxs/scale; /* Trying a smaller xx, closer to initial ax=0 */
2066: printf("|");
2067: fprintf(ficlog,"|");
1.203 brouard 2068: #ifdef DEBUGLINMIN
1.224 brouard 2069: 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 2070: #endif
2071: }
1.224 brouard 2072: }while(fx != fx && xxs > 1.e-5);
1.203 brouard 2073: #endif
2074:
1.191 brouard 2075: #ifdef DEBUGLINMIN
2076: 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 2077: 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 2078: #endif
1.224 brouard 2079: #ifdef LINMINORIGINAL
2080: #else
2081: if(fb == fx){ /* Flat function in the direction */
2082: xmin=xx;
2083: *flat=1;
2084: }else{
2085: *flat=0;
2086: #endif
2087: /*Flat mnbrak2 shift (*ax=0.000000000000, *fa=51626.272983130431), (*bx=-1.618034000000, *fb=51590.149499362531), (*cx=-4.236068025156, *fc=51590.149499362531) */
1.187 brouard 2088: *fret=brent(ax,xx,bx,f1dim,TOL,&xmin); /* Giving a bracketting triplet (ax, xx, bx), find a minimum, xmin, according to f1dim, *fret(xmin),*/
2089: /* fa = f(p[j] + ax * xi[j]), fx = f(p[j] + xx * xi[j]), fb = f(p[j] + bx * xi[j]) */
2090: /* fmin = f(p[j] + xmin * xi[j]) */
2091: /* P+lambda n in that direction (lambdamin), with TOL between abscisses */
2092: /* f1dim(xmin): for (j=1;j<=ncom;j++) xt[j]=pcom[j]+xmin*xicom[j]; */
1.126 brouard 2093: #ifdef DEBUG
1.224 brouard 2094: 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);
2095: 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);
2096: #endif
2097: #ifdef LINMINORIGINAL
2098: #else
2099: }
1.126 brouard 2100: #endif
1.191 brouard 2101: #ifdef DEBUGLINMIN
2102: printf("linmin end ");
1.202 brouard 2103: fprintf(ficlog,"linmin end ");
1.191 brouard 2104: #endif
1.126 brouard 2105: for (j=1;j<=n;j++) {
1.203 brouard 2106: #ifdef LINMINORIGINAL
2107: xi[j] *= xmin;
2108: #else
2109: #ifdef DEBUGLINMIN
2110: if(xxs <1.0)
2111: printf(" before xi[%d]=%12.8f", j,xi[j]);
2112: #endif
2113: 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) */
2114: #ifdef DEBUGLINMIN
2115: if(xxs <1.0)
2116: 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 );
2117: #endif
2118: #endif
1.187 brouard 2119: p[j] += xi[j]; /* Parameters values are updated accordingly */
1.126 brouard 2120: }
1.191 brouard 2121: #ifdef DEBUGLINMIN
1.203 brouard 2122: printf("\n");
1.191 brouard 2123: printf("Comparing last *frec(xmin=%12.8f)=%12.8f from Brent and frec(0.)=%12.8f \n", xmin, *fret, (*func)(p));
1.202 brouard 2124: 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 2125: for (j=1;j<=n;j++) {
1.202 brouard 2126: printf(" xi[%d]= %14.10f p[%d]= %12.7f",j,xi[j],j,p[j]);
2127: fprintf(ficlog," xi[%d]= %14.10f p[%d]= %12.7f",j,xi[j],j,p[j]);
2128: if(j % ncovmodel == 0){
1.191 brouard 2129: printf("\n");
1.202 brouard 2130: fprintf(ficlog,"\n");
2131: }
1.191 brouard 2132: }
1.203 brouard 2133: #else
1.191 brouard 2134: #endif
1.126 brouard 2135: free_vector(xicom,1,n);
2136: free_vector(pcom,1,n);
2137: }
2138:
2139:
2140: /*************** powell ************************/
1.162 brouard 2141: /*
2142: Minimization of a function func of n variables. Input consists of an initial starting point
2143: p[1..n] ; an initial matrix xi[1..n][1..n] , whose columns contain the initial set of di-
2144: rections (usually the n unit vectors); and ftol , the fractional tolerance in the function value
2145: such that failure to decrease by more than this amount on one iteration signals doneness. On
2146: output, p is set to the best point found, xi is the then-current direction set, fret is the returned
2147: function value at p , and iter is the number of iterations taken. The routine linmin is used.
2148: */
1.224 brouard 2149: #ifdef LINMINORIGINAL
2150: #else
2151: int *flatdir; /* Function is vanishing in that direction */
1.225 brouard 2152: int flat=0, flatd=0; /* Function is vanishing in that direction */
1.224 brouard 2153: #endif
1.126 brouard 2154: void powell(double p[], double **xi, int n, double ftol, int *iter, double *fret,
2155: double (*func)(double []))
2156: {
1.224 brouard 2157: #ifdef LINMINORIGINAL
2158: void linmin(double p[], double xi[], int n, double *fret,
1.126 brouard 2159: double (*func)(double []));
1.224 brouard 2160: #else
1.241 brouard 2161: void linmin(double p[], double xi[], int n, double *fret,
2162: double (*func)(double []),int *flat);
1.224 brouard 2163: #endif
1.239 brouard 2164: int i,ibig,j,jk,k;
1.126 brouard 2165: double del,t,*pt,*ptt,*xit;
1.181 brouard 2166: double directest;
1.126 brouard 2167: double fp,fptt;
2168: double *xits;
2169: int niterf, itmp;
1.224 brouard 2170: #ifdef LINMINORIGINAL
2171: #else
2172:
2173: flatdir=ivector(1,n);
2174: for (j=1;j<=n;j++) flatdir[j]=0;
2175: #endif
1.126 brouard 2176:
2177: pt=vector(1,n);
2178: ptt=vector(1,n);
2179: xit=vector(1,n);
2180: xits=vector(1,n);
2181: *fret=(*func)(p);
2182: for (j=1;j<=n;j++) pt[j]=p[j];
1.202 brouard 2183: rcurr_time = time(NULL);
1.126 brouard 2184: for (*iter=1;;++(*iter)) {
1.187 brouard 2185: fp=(*fret); /* From former iteration or initial value */
1.126 brouard 2186: ibig=0;
2187: del=0.0;
1.157 brouard 2188: rlast_time=rcurr_time;
2189: /* (void) gettimeofday(&curr_time,&tzp); */
2190: rcurr_time = time(NULL);
2191: curr_time = *localtime(&rcurr_time);
2192: printf("\nPowell iter=%d -2*LL=%.12f %ld sec. %ld sec.",*iter,*fret, rcurr_time-rlast_time, rcurr_time-rstart_time);fflush(stdout);
2193: fprintf(ficlog,"\nPowell iter=%d -2*LL=%.12f %ld sec. %ld sec.",*iter,*fret,rcurr_time-rlast_time, rcurr_time-rstart_time); fflush(ficlog);
2194: /* fprintf(ficrespow,"%d %.12f %ld",*iter,*fret,curr_time.tm_sec-start_time.tm_sec); */
1.192 brouard 2195: for (i=1;i<=n;i++) {
1.126 brouard 2196: fprintf(ficrespow," %.12lf", p[i]);
2197: }
1.239 brouard 2198: fprintf(ficrespow,"\n");fflush(ficrespow);
2199: printf("\n#model= 1 + age ");
2200: fprintf(ficlog,"\n#model= 1 + age ");
2201: if(nagesqr==1){
1.241 brouard 2202: printf(" + age*age ");
2203: fprintf(ficlog," + age*age ");
1.239 brouard 2204: }
2205: for(j=1;j <=ncovmodel-2;j++){
2206: if(Typevar[j]==0) {
2207: printf(" + V%d ",Tvar[j]);
2208: fprintf(ficlog," + V%d ",Tvar[j]);
2209: }else if(Typevar[j]==1) {
2210: printf(" + V%d*age ",Tvar[j]);
2211: fprintf(ficlog," + V%d*age ",Tvar[j]);
2212: }else if(Typevar[j]==2) {
2213: printf(" + V%d*V%d ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
2214: fprintf(ficlog," + V%d*V%d ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
2215: }
2216: }
1.126 brouard 2217: printf("\n");
1.239 brouard 2218: /* printf("12 47.0114589 0.0154322 33.2424412 0.3279905 2.3731903 */
2219: /* 13 -21.5392400 0.1118147 1.2680506 1.2973408 -1.0663662 */
1.126 brouard 2220: fprintf(ficlog,"\n");
1.239 brouard 2221: for(i=1,jk=1; i <=nlstate; i++){
2222: for(k=1; k <=(nlstate+ndeath); k++){
2223: if (k != i) {
2224: printf("%d%d ",i,k);
2225: fprintf(ficlog,"%d%d ",i,k);
2226: for(j=1; j <=ncovmodel; j++){
2227: printf("%12.7f ",p[jk]);
2228: fprintf(ficlog,"%12.7f ",p[jk]);
2229: jk++;
2230: }
2231: printf("\n");
2232: fprintf(ficlog,"\n");
2233: }
2234: }
2235: }
1.241 brouard 2236: if(*iter <=3 && *iter >1){
1.157 brouard 2237: tml = *localtime(&rcurr_time);
2238: strcpy(strcurr,asctime(&tml));
2239: rforecast_time=rcurr_time;
1.126 brouard 2240: itmp = strlen(strcurr);
2241: if(strcurr[itmp-1]=='\n') /* Windows outputs with a new line */
1.241 brouard 2242: strcurr[itmp-1]='\0';
1.162 brouard 2243: printf("\nConsidering the time needed for the last iteration #%d: %ld seconds,\n",*iter,rcurr_time-rlast_time);
1.157 brouard 2244: fprintf(ficlog,"\nConsidering the time needed for this last iteration #%d: %ld seconds,\n",*iter,rcurr_time-rlast_time);
1.126 brouard 2245: for(niterf=10;niterf<=30;niterf+=10){
1.241 brouard 2246: rforecast_time=rcurr_time+(niterf-*iter)*(rcurr_time-rlast_time);
2247: forecast_time = *localtime(&rforecast_time);
2248: strcpy(strfor,asctime(&forecast_time));
2249: itmp = strlen(strfor);
2250: if(strfor[itmp-1]=='\n')
2251: strfor[itmp-1]='\0';
2252: 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);
2253: 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 2254: }
2255: }
1.187 brouard 2256: for (i=1;i<=n;i++) { /* For each direction i */
2257: for (j=1;j<=n;j++) xit[j]=xi[j][i]; /* Directions stored from previous iteration with previous scales */
1.126 brouard 2258: fptt=(*fret);
2259: #ifdef DEBUG
1.203 brouard 2260: printf("fret=%lf, %lf, %lf \n", *fret, *fret, *fret);
2261: fprintf(ficlog, "fret=%lf, %lf, %lf \n", *fret, *fret, *fret);
1.126 brouard 2262: #endif
1.203 brouard 2263: printf("%d",i);fflush(stdout); /* print direction (parameter) i */
1.126 brouard 2264: fprintf(ficlog,"%d",i);fflush(ficlog);
1.224 brouard 2265: #ifdef LINMINORIGINAL
1.188 brouard 2266: linmin(p,xit,n,fret,func); /* Point p[n]. xit[n] has been loaded for direction i as input.*/
1.224 brouard 2267: #else
2268: linmin(p,xit,n,fret,func,&flat); /* Point p[n]. xit[n] has been loaded for direction i as input.*/
2269: flatdir[i]=flat; /* Function is vanishing in that direction i */
2270: #endif
2271: /* Outputs are fret(new point p) p is updated and xit rescaled */
1.188 brouard 2272: if (fabs(fptt-(*fret)) > del) { /* We are keeping the max gain on each of the n directions */
1.224 brouard 2273: /* because that direction will be replaced unless the gain del is small */
2274: /* in comparison with the 'probable' gain, mu^2, with the last average direction. */
2275: /* Unless the n directions are conjugate some gain in the determinant may be obtained */
2276: /* with the new direction. */
2277: del=fabs(fptt-(*fret));
2278: ibig=i;
1.126 brouard 2279: }
2280: #ifdef DEBUG
2281: printf("%d %.12e",i,(*fret));
2282: fprintf(ficlog,"%d %.12e",i,(*fret));
2283: for (j=1;j<=n;j++) {
1.224 brouard 2284: xits[j]=FMAX(fabs(p[j]-pt[j]),1.e-5);
2285: printf(" x(%d)=%.12e",j,xit[j]);
2286: fprintf(ficlog," x(%d)=%.12e",j,xit[j]);
1.126 brouard 2287: }
2288: for(j=1;j<=n;j++) {
1.225 brouard 2289: printf(" p(%d)=%.12e",j,p[j]);
2290: fprintf(ficlog," p(%d)=%.12e",j,p[j]);
1.126 brouard 2291: }
2292: printf("\n");
2293: fprintf(ficlog,"\n");
2294: #endif
1.187 brouard 2295: } /* end loop on each direction i */
2296: /* Convergence test will use last linmin estimation (fret) and compare former iteration (fp) */
1.188 brouard 2297: /* But p and xit have been updated at the end of linmin, *fret corresponds to new p, xit */
1.187 brouard 2298: /* New value of last point Pn is not computed, P(n-1) */
1.224 brouard 2299: for(j=1;j<=n;j++) {
1.225 brouard 2300: if(flatdir[j] >0){
2301: printf(" p(%d)=%lf flat=%d ",j,p[j],flatdir[j]);
2302: fprintf(ficlog," p(%d)=%lf flat=%d ",j,p[j],flatdir[j]);
2303: }
2304: /* printf("\n"); */
2305: /* fprintf(ficlog,"\n"); */
2306: }
1.243 brouard 2307: /* if (2.0*fabs(fp-(*fret)) <= ftol*(fabs(fp)+fabs(*fret))) { /\* Did we reach enough precision? *\/ */
2308: if (2.0*fabs(fp-(*fret)) <= ftol) { /* Did we reach enough precision? */
1.188 brouard 2309: /* We could compare with a chi^2. chisquare(0.95,ddl=1)=3.84 */
2310: /* By adding age*age in a model, the new -2LL should be lower and the difference follows a */
2311: /* a chisquare statistics with 1 degree. To be significant at the 95% level, it should have */
2312: /* decreased of more than 3.84 */
2313: /* By adding age*age and V1*age the gain (-2LL) should be more than 5.99 (ddl=2) */
2314: /* By using V1+V2+V3, the gain should be 7.82, compared with basic 1+age. */
2315: /* By adding 10 parameters more the gain should be 18.31 */
1.224 brouard 2316:
1.188 brouard 2317: /* Starting the program with initial values given by a former maximization will simply change */
2318: /* the scales of the directions and the directions, because the are reset to canonical directions */
2319: /* Thus the first calls to linmin will give new points and better maximizations until fp-(*fret) is */
2320: /* under the tolerance value. If the tolerance is very small 1.e-9, it could last long. */
1.126 brouard 2321: #ifdef DEBUG
2322: int k[2],l;
2323: k[0]=1;
2324: k[1]=-1;
2325: printf("Max: %.12e",(*func)(p));
2326: fprintf(ficlog,"Max: %.12e",(*func)(p));
2327: for (j=1;j<=n;j++) {
2328: printf(" %.12e",p[j]);
2329: fprintf(ficlog," %.12e",p[j]);
2330: }
2331: printf("\n");
2332: fprintf(ficlog,"\n");
2333: for(l=0;l<=1;l++) {
2334: for (j=1;j<=n;j++) {
2335: ptt[j]=p[j]+(p[j]-pt[j])*k[l];
2336: printf("l=%d j=%d ptt=%.12e, xits=%.12e, p=%.12e, xit=%.12e", l,j,ptt[j],xits[j],p[j],xit[j]);
2337: fprintf(ficlog,"l=%d j=%d ptt=%.12e, xits=%.12e, p=%.12e, xit=%.12e", l,j,ptt[j],xits[j],p[j],xit[j]);
2338: }
2339: printf("func(ptt)=%.12e, deriv=%.12e\n",(*func)(ptt),(ptt[j]-p[j])/((*func)(ptt)-(*func)(p)));
2340: fprintf(ficlog,"func(ptt)=%.12e, deriv=%.12e\n",(*func)(ptt),(ptt[j]-p[j])/((*func)(ptt)-(*func)(p)));
2341: }
2342: #endif
2343:
1.224 brouard 2344: #ifdef LINMINORIGINAL
2345: #else
2346: free_ivector(flatdir,1,n);
2347: #endif
1.126 brouard 2348: free_vector(xit,1,n);
2349: free_vector(xits,1,n);
2350: free_vector(ptt,1,n);
2351: free_vector(pt,1,n);
2352: return;
1.192 brouard 2353: } /* enough precision */
1.240 brouard 2354: if (*iter == ITMAX*n) nrerror("powell exceeding maximum iterations.");
1.181 brouard 2355: for (j=1;j<=n;j++) { /* Computes the extrapolated point P_0 + 2 (P_n-P_0) */
1.126 brouard 2356: ptt[j]=2.0*p[j]-pt[j];
2357: xit[j]=p[j]-pt[j];
2358: pt[j]=p[j];
2359: }
1.181 brouard 2360: fptt=(*func)(ptt); /* f_3 */
1.224 brouard 2361: #ifdef NODIRECTIONCHANGEDUNTILNITER /* No change in drections until some iterations are done */
2362: if (*iter <=4) {
1.225 brouard 2363: #else
2364: #endif
1.224 brouard 2365: #ifdef POWELLNOF3INFF1TEST /* skips test F3 <F1 */
1.192 brouard 2366: #else
1.161 brouard 2367: if (fptt < fp) { /* If extrapolated point is better, decide if we keep that new direction or not */
1.192 brouard 2368: #endif
1.162 brouard 2369: /* (x1 f1=fp), (x2 f2=*fret), (x3 f3=fptt), (xm fm) */
1.161 brouard 2370: /* From x1 (P0) distance of x2 is at h and x3 is 2h */
1.162 brouard 2371: /* Let f"(x2) be the 2nd derivative equal everywhere. */
2372: /* Then the parabolic through (x1,f1), (x2,f2) and (x3,f3) */
2373: /* will reach at f3 = fm + h^2/2 f"m ; f" = (f1 -2f2 +f3 ) / h**2 */
1.224 brouard 2374: /* Conditional for using this new direction is that mu^2 = (f1-2f2+f3)^2 /2 < del or directest <0 */
2375: /* also lamda^2=(f1-f2)^2/mu² is a parasite solution of powell */
2376: /* For powell, inclusion of this average direction is only if t(del)<0 or del inbetween mu^2 and lambda^2 */
1.161 brouard 2377: /* t=2.0*(fp-2.0*(*fret)+fptt)*SQR(fp-(*fret)-del)-del*SQR(fp-fptt); */
1.224 brouard 2378: /* Even if f3 <f1, directest can be negative and t >0 */
2379: /* mu² and del² are equal when f3=f1 */
2380: /* f3 < f1 : mu² < del <= lambda^2 both test are equivalent */
2381: /* f3 < f1 : mu² < lambda^2 < del then directtest is negative and powell t is positive */
2382: /* f3 > f1 : lambda² < mu^2 < del then t is negative and directest >0 */
2383: /* f3 > f1 : lambda² < del < mu^2 then t is positive and directest >0 */
1.183 brouard 2384: #ifdef NRCORIGINAL
2385: t=2.0*(fp-2.0*(*fret)+fptt)*SQR(fp-(*fret)-del)- del*SQR(fp-fptt); /* Original Numerical Recipes in C*/
2386: #else
2387: 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 2388: t= t- del*SQR(fp-fptt);
1.183 brouard 2389: #endif
1.202 brouard 2390: directest = fp-2.0*(*fret)+fptt - 2.0 * del; /* If delta was big enough we change it for a new direction */
1.161 brouard 2391: #ifdef DEBUG
1.181 brouard 2392: 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);
2393: 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 2394: printf("t3= %.12lf, t4= %.12lf, t3*= %.12lf, t4*= %.12lf\n",SQR(fp-(*fret)-del),SQR(fp-fptt),
2395: (fp-(*fret)-del)*(fp-(*fret)-del),(fp-fptt)*(fp-fptt));
2396: fprintf(ficlog,"t3= %.12lf, t4= %.12lf, t3*= %.12lf, t4*= %.12lf\n",SQR(fp-(*fret)-del),SQR(fp-fptt),
2397: (fp-(*fret)-del)*(fp-(*fret)-del),(fp-fptt)*(fp-fptt));
2398: 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);
2399: 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);
2400: #endif
1.183 brouard 2401: #ifdef POWELLORIGINAL
2402: if (t < 0.0) { /* Then we use it for new direction */
2403: #else
1.182 brouard 2404: if (directest*t < 0.0) { /* Contradiction between both tests */
1.224 brouard 2405: 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 2406: 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 2407: 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 2408: fprintf(ficlog,"f1-2f2+f3= %.12lf, f1-f2-del= %.12lf, f1-f3= %.12lf\n",fp-2.0*(*fret)+fptt, fp -(*fret) -del, fp-fptt);
2409: }
1.181 brouard 2410: if (directest < 0.0) { /* Then we use it for new direction */
2411: #endif
1.191 brouard 2412: #ifdef DEBUGLINMIN
1.234 brouard 2413: printf("Before linmin in direction P%d-P0\n",n);
2414: for (j=1;j<=n;j++) {
2415: printf(" Before xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
2416: fprintf(ficlog," Before xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
2417: if(j % ncovmodel == 0){
2418: printf("\n");
2419: fprintf(ficlog,"\n");
2420: }
2421: }
1.224 brouard 2422: #endif
2423: #ifdef LINMINORIGINAL
1.234 brouard 2424: linmin(p,xit,n,fret,func); /* computes minimum on the extrapolated direction: changes p and rescales xit.*/
1.224 brouard 2425: #else
1.234 brouard 2426: linmin(p,xit,n,fret,func,&flat); /* computes minimum on the extrapolated direction: changes p and rescales xit.*/
2427: flatdir[i]=flat; /* Function is vanishing in that direction i */
1.191 brouard 2428: #endif
1.234 brouard 2429:
1.191 brouard 2430: #ifdef DEBUGLINMIN
1.234 brouard 2431: for (j=1;j<=n;j++) {
2432: printf("After xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
2433: fprintf(ficlog,"After xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
2434: if(j % ncovmodel == 0){
2435: printf("\n");
2436: fprintf(ficlog,"\n");
2437: }
2438: }
1.224 brouard 2439: #endif
1.234 brouard 2440: for (j=1;j<=n;j++) {
2441: xi[j][ibig]=xi[j][n]; /* Replace direction with biggest decrease by last direction n */
2442: xi[j][n]=xit[j]; /* and this nth direction by the by the average p_0 p_n */
2443: }
1.224 brouard 2444: #ifdef LINMINORIGINAL
2445: #else
1.234 brouard 2446: for (j=1, flatd=0;j<=n;j++) {
2447: if(flatdir[j]>0)
2448: flatd++;
2449: }
2450: if(flatd >0){
1.255 brouard 2451: printf("%d flat directions: ",flatd);
2452: fprintf(ficlog,"%d flat directions :",flatd);
1.234 brouard 2453: for (j=1;j<=n;j++) {
2454: if(flatdir[j]>0){
2455: printf("%d ",j);
2456: fprintf(ficlog,"%d ",j);
2457: }
2458: }
2459: printf("\n");
2460: fprintf(ficlog,"\n");
2461: }
1.191 brouard 2462: #endif
1.234 brouard 2463: printf("Gaining to use new average direction of P0 P%d instead of biggest increase direction %d :\n",n,ibig);
2464: fprintf(ficlog,"Gaining to use new average direction of P0 P%d instead of biggest increase direction %d :\n",n,ibig);
2465:
1.126 brouard 2466: #ifdef DEBUG
1.234 brouard 2467: printf("Direction changed last moved %d in place of ibig=%d, new last is the average:\n",n,ibig);
2468: fprintf(ficlog,"Direction changed last moved %d in place of ibig=%d, new last is the average:\n",n,ibig);
2469: for(j=1;j<=n;j++){
2470: printf(" %lf",xit[j]);
2471: fprintf(ficlog," %lf",xit[j]);
2472: }
2473: printf("\n");
2474: fprintf(ficlog,"\n");
1.126 brouard 2475: #endif
1.192 brouard 2476: } /* end of t or directest negative */
1.224 brouard 2477: #ifdef POWELLNOF3INFF1TEST
1.192 brouard 2478: #else
1.234 brouard 2479: } /* end if (fptt < fp) */
1.192 brouard 2480: #endif
1.225 brouard 2481: #ifdef NODIRECTIONCHANGEDUNTILNITER /* No change in drections until some iterations are done */
1.234 brouard 2482: } /*NODIRECTIONCHANGEDUNTILNITER No change in drections until some iterations are done */
1.225 brouard 2483: #else
1.224 brouard 2484: #endif
1.234 brouard 2485: } /* loop iteration */
1.126 brouard 2486: }
1.234 brouard 2487:
1.126 brouard 2488: /**** Prevalence limit (stable or period prevalence) ****************/
1.234 brouard 2489:
1.235 brouard 2490: 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 2491: {
1.235 brouard 2492: /* Computes the prevalence limit in each live state at age x and for covariate combination ij
2493: (and selected quantitative values in nres)
2494: by left multiplying the unit
1.234 brouard 2495: matrix by transitions matrix until convergence is reached with precision ftolpl */
1.206 brouard 2496: /* Wx= Wx-1 Px-1= Wx-2 Px-2 Px-1 = Wx-n Px-n ... Px-2 Px-1 I */
2497: /* Wx is row vector: population in state 1, population in state 2, population dead */
2498: /* or prevalence in state 1, prevalence in state 2, 0 */
2499: /* newm is the matrix after multiplications, its rows are identical at a factor */
2500: /* Initial matrix pimij */
2501: /* {0.85204250825084937, 0.13044499163996345, 0.017512500109187184, */
2502: /* 0.090851990222114765, 0.88271245433047185, 0.026435555447413338, */
2503: /* 0, 0 , 1} */
2504: /*
2505: * and after some iteration: */
2506: /* {0.45504275246439968, 0.42731458730878791, 0.11764266022681241, */
2507: /* 0.45201005341706885, 0.42865420071559901, 0.11933574586733192, */
2508: /* 0, 0 , 1} */
2509: /* And prevalence by suppressing the deaths are close to identical rows in prlim: */
2510: /* {0.51571254859325999, 0.4842874514067399, */
2511: /* 0.51326036147820708, 0.48673963852179264} */
2512: /* If we start from prlim again, prlim tends to a constant matrix */
1.234 brouard 2513:
1.126 brouard 2514: int i, ii,j,k;
1.209 brouard 2515: double *min, *max, *meandiff, maxmax,sumnew=0.;
1.145 brouard 2516: /* double **matprod2(); */ /* test */
1.218 brouard 2517: double **out, cov[NCOVMAX+1], **pmij(); /* **pmmij is a global variable feeded with oldms etc */
1.126 brouard 2518: double **newm;
1.209 brouard 2519: double agefin, delaymax=200. ; /* 100 Max number of years to converge */
1.203 brouard 2520: int ncvloop=0;
1.169 brouard 2521:
1.209 brouard 2522: min=vector(1,nlstate);
2523: max=vector(1,nlstate);
2524: meandiff=vector(1,nlstate);
2525:
1.218 brouard 2526: /* Starting with matrix unity */
1.126 brouard 2527: for (ii=1;ii<=nlstate+ndeath;ii++)
2528: for (j=1;j<=nlstate+ndeath;j++){
2529: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
2530: }
1.169 brouard 2531:
2532: cov[1]=1.;
2533:
2534: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
1.202 brouard 2535: /* Start at agefin= age, computes the matrix of passage and loops decreasing agefin until convergence is reached */
1.126 brouard 2536: for(agefin=age-stepm/YEARM; agefin>=age-delaymax; agefin=agefin-stepm/YEARM){
1.202 brouard 2537: ncvloop++;
1.126 brouard 2538: newm=savm;
2539: /* Covariates have to be included here again */
1.138 brouard 2540: cov[2]=agefin;
1.187 brouard 2541: if(nagesqr==1)
2542: cov[3]= agefin*agefin;;
1.234 brouard 2543: for (k=1; k<=nsd;k++) { /* For single dummy covariates only */
2544: /* Here comes the value of the covariate 'ij' after renumbering k with single dummy covariates */
2545: cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,k)];
1.235 brouard 2546: /* 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 2547: }
2548: for (k=1; k<=nsq;k++) { /* For single varying covariates only */
2549: /* Here comes the value of quantitative after renumbering k with single quantitative covariates */
1.235 brouard 2550: cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k];
2551: /* 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 2552: }
1.237 brouard 2553: for (k=1; k<=cptcovage;k++){ /* For product with age */
1.234 brouard 2554: if(Dummy[Tvar[Tage[k]]]){
2555: cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2];
2556: } else{
1.235 brouard 2557: cov[2+nagesqr+Tage[k]]=Tqresult[nres][k];
1.234 brouard 2558: }
1.235 brouard 2559: /* 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 2560: }
1.237 brouard 2561: for (k=1; k<=cptcovprod;k++){ /* For product without age */
1.235 brouard 2562: /* 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 2563: if(Dummy[Tvard[k][1]==0]){
2564: if(Dummy[Tvard[k][2]==0]){
2565: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)];
2566: }else{
2567: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * Tqresult[nres][k];
2568: }
2569: }else{
2570: if(Dummy[Tvard[k][2]==0]){
2571: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][2]][codtabm(ij,k)] * Tqinvresult[nres][Tvard[k][1]];
2572: }else{
2573: cov[2+nagesqr+Tprod[k]]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]];
2574: }
2575: }
1.234 brouard 2576: }
1.138 brouard 2577: /*printf("ij=%d cptcovprod=%d tvar=%d ", ij, cptcovprod, Tvar[1]);*/
2578: /*printf("ij=%d cov[3]=%lf cov[4]=%lf \n",ij, cov[3],cov[4]);*/
2579: /*printf("ij=%d cov[3]=%lf \n",ij, cov[3]);*/
1.145 brouard 2580: /* savm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
2581: /* out=matprod2(newm, pmij(pmmij,cov,ncovmodel,x,nlstate),1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); /\* Bug Valgrind *\/ */
1.218 brouard 2582: /* age and covariate values of ij are in 'cov' */
1.142 brouard 2583: out=matprod2(newm, pmij(pmmij,cov,ncovmodel,x,nlstate),1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); /* Bug Valgrind */
1.138 brouard 2584:
1.126 brouard 2585: savm=oldm;
2586: oldm=newm;
1.209 brouard 2587:
2588: for(j=1; j<=nlstate; j++){
2589: max[j]=0.;
2590: min[j]=1.;
2591: }
2592: for(i=1;i<=nlstate;i++){
2593: sumnew=0;
2594: for(k=1; k<=ndeath; k++) sumnew+=newm[i][nlstate+k];
2595: for(j=1; j<=nlstate; j++){
2596: prlim[i][j]= newm[i][j]/(1-sumnew);
2597: max[j]=FMAX(max[j],prlim[i][j]);
2598: min[j]=FMIN(min[j],prlim[i][j]);
2599: }
2600: }
2601:
1.126 brouard 2602: maxmax=0.;
1.209 brouard 2603: for(j=1; j<=nlstate; j++){
2604: meandiff[j]=(max[j]-min[j])/(max[j]+min[j])*2.; /* mean difference for each column */
2605: maxmax=FMAX(maxmax,meandiff[j]);
2606: /* 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 2607: } /* j loop */
1.203 brouard 2608: *ncvyear= (int)age- (int)agefin;
1.208 brouard 2609: /* 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 2610: if(maxmax < ftolpl){
1.209 brouard 2611: /* printf("maxmax=%lf ncvloop=%ld, age=%d, agefin=%d ncvyear=%d \n", maxmax, ncvloop, (int)age, (int)agefin, *ncvyear); */
2612: free_vector(min,1,nlstate);
2613: free_vector(max,1,nlstate);
2614: free_vector(meandiff,1,nlstate);
1.126 brouard 2615: return prlim;
2616: }
1.169 brouard 2617: } /* age loop */
1.208 brouard 2618: /* After some age loop it doesn't converge */
1.209 brouard 2619: 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 2620: 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 2621: /* 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); */
2622: free_vector(min,1,nlstate);
2623: free_vector(max,1,nlstate);
2624: free_vector(meandiff,1,nlstate);
1.208 brouard 2625:
1.169 brouard 2626: return prlim; /* should not reach here */
1.126 brouard 2627: }
2628:
1.217 brouard 2629:
2630: /**** Back Prevalence limit (stable or period prevalence) ****************/
2631:
1.218 brouard 2632: /* 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) */
2633: /* 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 2634: double **bprevalim(double **bprlim, double ***prevacurrent, int nlstate, double x[], double age, double ftolpl, int *ncvyear, int ij, int nres)
1.217 brouard 2635: {
1.264 brouard 2636: /* 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 2637: matrix by transitions matrix until convergence is reached with precision ftolpl */
2638: /* Wx= Wx-1 Px-1= Wx-2 Px-2 Px-1 = Wx-n Px-n ... Px-2 Px-1 I */
2639: /* Wx is row vector: population in state 1, population in state 2, population dead */
2640: /* or prevalence in state 1, prevalence in state 2, 0 */
2641: /* newm is the matrix after multiplications, its rows are identical at a factor */
2642: /* Initial matrix pimij */
2643: /* {0.85204250825084937, 0.13044499163996345, 0.017512500109187184, */
2644: /* 0.090851990222114765, 0.88271245433047185, 0.026435555447413338, */
2645: /* 0, 0 , 1} */
2646: /*
2647: * and after some iteration: */
2648: /* {0.45504275246439968, 0.42731458730878791, 0.11764266022681241, */
2649: /* 0.45201005341706885, 0.42865420071559901, 0.11933574586733192, */
2650: /* 0, 0 , 1} */
2651: /* And prevalence by suppressing the deaths are close to identical rows in prlim: */
2652: /* {0.51571254859325999, 0.4842874514067399, */
2653: /* 0.51326036147820708, 0.48673963852179264} */
2654: /* If we start from prlim again, prlim tends to a constant matrix */
2655:
2656: int i, ii,j,k;
1.247 brouard 2657: int first=0;
1.217 brouard 2658: double *min, *max, *meandiff, maxmax,sumnew=0.;
2659: /* double **matprod2(); */ /* test */
2660: double **out, cov[NCOVMAX+1], **bmij();
2661: double **newm;
1.218 brouard 2662: double **dnewm, **doldm, **dsavm; /* for use */
2663: double **oldm, **savm; /* for use */
2664:
1.217 brouard 2665: double agefin, delaymax=200. ; /* 100 Max number of years to converge */
2666: int ncvloop=0;
2667:
2668: min=vector(1,nlstate);
2669: max=vector(1,nlstate);
2670: meandiff=vector(1,nlstate);
2671:
1.266 brouard 2672: dnewm=ddnewms; doldm=ddoldms; dsavm=ddsavms;
2673: oldm=oldms; savm=savms;
2674:
2675: /* Starting with matrix unity */
2676: for (ii=1;ii<=nlstate+ndeath;ii++)
2677: for (j=1;j<=nlstate+ndeath;j++){
1.217 brouard 2678: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
2679: }
2680:
2681: cov[1]=1.;
2682:
2683: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
2684: /* Start at agefin= age, computes the matrix of passage and loops decreasing agefin until convergence is reached */
1.218 brouard 2685: /* for(agefin=age+stepm/YEARM; agefin<=age+delaymax; agefin=agefin+stepm/YEARM){ /\* A changer en age *\/ */
2686: for(agefin=age; agefin<AGESUP; agefin=agefin+stepm/YEARM){ /* A changer en age */
1.217 brouard 2687: ncvloop++;
1.218 brouard 2688: newm=savm; /* oldm should be kept from previous iteration or unity at start */
2689: /* newm points to the allocated table savm passed by the function it can be written, savm could be reallocated */
1.217 brouard 2690: /* Covariates have to be included here again */
2691: cov[2]=agefin;
2692: if(nagesqr==1)
2693: cov[3]= agefin*agefin;;
1.242 brouard 2694: for (k=1; k<=nsd;k++) { /* For single dummy covariates only */
2695: /* Here comes the value of the covariate 'ij' after renumbering k with single dummy covariates */
2696: cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,k)];
1.264 brouard 2697: /* 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 2698: }
2699: /* for (k=1; k<=cptcovn;k++) { */
2700: /* /\* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,Tvar[k])]; *\/ */
2701: /* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,k)]; */
2702: /* /\* 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])]); *\/ */
2703: /* } */
2704: for (k=1; k<=nsq;k++) { /* For single varying covariates only */
2705: /* Here comes the value of quantitative after renumbering k with single quantitative covariates */
2706: cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k];
2707: /* 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]); */
2708: }
2709: /* for (k=1; k<=cptcovage;k++) cov[2+nagesqr+Tage[k]]=nbcode[Tvar[k]][codtabm(ij,k)]*cov[2]; */
2710: /* for (k=1; k<=cptcovprod;k++) /\* Useless *\/ */
2711: /* /\* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])]; *\/ */
2712: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)]; */
2713: for (k=1; k<=cptcovage;k++){ /* For product with age */
2714: if(Dummy[Tvar[Tage[k]]]){
2715: cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2];
2716: } else{
2717: cov[2+nagesqr+Tage[k]]=Tqresult[nres][k];
2718: }
2719: /* 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]); */
2720: }
2721: for (k=1; k<=cptcovprod;k++){ /* For product without age */
2722: /* 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]); */
2723: if(Dummy[Tvard[k][1]==0]){
2724: if(Dummy[Tvard[k][2]==0]){
2725: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)];
2726: }else{
2727: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * Tqresult[nres][k];
2728: }
2729: }else{
2730: if(Dummy[Tvard[k][2]==0]){
2731: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][2]][codtabm(ij,k)] * Tqinvresult[nres][Tvard[k][1]];
2732: }else{
2733: cov[2+nagesqr+Tprod[k]]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]];
2734: }
2735: }
1.217 brouard 2736: }
2737:
2738: /*printf("ij=%d cptcovprod=%d tvar=%d ", ij, cptcovprod, Tvar[1]);*/
2739: /*printf("ij=%d cov[3]=%lf cov[4]=%lf \n",ij, cov[3],cov[4]);*/
2740: /*printf("ij=%d cov[3]=%lf \n",ij, cov[3]);*/
2741: /* savm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
2742: /* out=matprod2(newm, pmij(pmmij,cov,ncovmodel,x,nlstate),1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); /\* Bug Valgrind *\/ */
1.218 brouard 2743: /* ij should be linked to the correct index of cov */
2744: /* age and covariate values ij are in 'cov', but we need to pass
2745: * ij for the observed prevalence at age and status and covariate
2746: * number: prevacurrent[(int)agefin][ii][ij]
2747: */
2748: /* 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 *\/ */
2749: /* 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 *\/ */
2750: 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 2751: /* if((int)age == 86 || (int)age == 87){ */
1.266 brouard 2752: /* printf(" Backward prevalim age=%d agefin=%d \n", (int) age, (int) agefin); */
2753: /* for(i=1; i<=nlstate+ndeath; i++) { */
2754: /* printf("%d newm= ",i); */
2755: /* for(j=1;j<=nlstate+ndeath;j++) { */
2756: /* printf("%f ",newm[i][j]); */
2757: /* } */
2758: /* printf("oldm * "); */
2759: /* for(j=1;j<=nlstate+ndeath;j++) { */
2760: /* printf("%f ",oldm[i][j]); */
2761: /* } */
1.268 brouard 2762: /* printf(" bmmij "); */
1.266 brouard 2763: /* for(j=1;j<=nlstate+ndeath;j++) { */
2764: /* printf("%f ",pmmij[i][j]); */
2765: /* } */
2766: /* printf("\n"); */
2767: /* } */
2768: /* } */
1.217 brouard 2769: savm=oldm;
2770: oldm=newm;
1.266 brouard 2771:
1.217 brouard 2772: for(j=1; j<=nlstate; j++){
2773: max[j]=0.;
2774: min[j]=1.;
2775: }
2776: for(j=1; j<=nlstate; j++){
2777: for(i=1;i<=nlstate;i++){
1.234 brouard 2778: /* bprlim[i][j]= newm[i][j]/(1-sumnew); */
2779: bprlim[i][j]= newm[i][j];
2780: max[i]=FMAX(max[i],bprlim[i][j]); /* Max in line */
2781: min[i]=FMIN(min[i],bprlim[i][j]);
1.217 brouard 2782: }
2783: }
1.218 brouard 2784:
1.217 brouard 2785: maxmax=0.;
2786: for(i=1; i<=nlstate; i++){
2787: meandiff[i]=(max[i]-min[i])/(max[i]+min[i])*2.; /* mean difference for each column */
2788: maxmax=FMAX(maxmax,meandiff[i]);
2789: /* 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 2790: } /* i loop */
1.217 brouard 2791: *ncvyear= -( (int)age- (int)agefin);
1.268 brouard 2792: /* printf("Back maxmax=%lf ncvloop=%d, age=%d, agefin=%d ncvyear=%d \n", maxmax, ncvloop, (int)age, (int)agefin, *ncvyear); */
1.217 brouard 2793: if(maxmax < ftolpl){
1.220 brouard 2794: /* printf("OK Back maxmax=%lf ncvloop=%d, age=%d, agefin=%d ncvyear=%d \n", maxmax, ncvloop, (int)age, (int)agefin, *ncvyear); */
1.217 brouard 2795: free_vector(min,1,nlstate);
2796: free_vector(max,1,nlstate);
2797: free_vector(meandiff,1,nlstate);
2798: return bprlim;
2799: }
2800: } /* age loop */
2801: /* After some age loop it doesn't converge */
1.247 brouard 2802: if(first){
2803: first=1;
2804: 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\
2805: 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);
2806: }
2807: 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 2808: Oldest age to start was %d-%d=%d, ncvloop=%d, ncvyear=%d\n", (int)age, maxmax, ftolpl, delaymax, (int)age, (int)delaymax, (int)agefin, ncvloop, *ncvyear);
2809: /* 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); */
2810: free_vector(min,1,nlstate);
2811: free_vector(max,1,nlstate);
2812: free_vector(meandiff,1,nlstate);
2813:
2814: return bprlim; /* should not reach here */
2815: }
2816:
1.126 brouard 2817: /*************** transition probabilities ***************/
2818:
2819: double **pmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate )
2820: {
1.138 brouard 2821: /* According to parameters values stored in x and the covariate's values stored in cov,
1.266 brouard 2822: computes the probability to be observed in state j (after stepm years) being in state i by appying the
1.138 brouard 2823: model to the ncovmodel covariates (including constant and age).
2824: lnpijopii=ln(pij/pii)= aij+bij*age+cij*v1+dij*v2+... = sum_nc=1^ncovmodel xij(nc)*cov[nc]
2825: and, according on how parameters are entered, the position of the coefficient xij(nc) of the
2826: ncth covariate in the global vector x is given by the formula:
2827: j<i nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel
2828: j>=i nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel
2829: Computes ln(pij/pii) (lnpijopii), deduces pij/pii by exponentiation,
2830: sums on j different of i to get 1-pii/pii, deduces pii, and then all pij.
1.266 brouard 2831: Outputs ps[i][j] or probability to be observed in j being in i according to
1.138 brouard 2832: the values of the covariates cov[nc] and corresponding parameter values x[nc+shiftij]
1.266 brouard 2833: Sum on j ps[i][j] should equal to 1.
1.138 brouard 2834: */
2835: double s1, lnpijopii;
1.126 brouard 2836: /*double t34;*/
1.164 brouard 2837: int i,j, nc, ii, jj;
1.126 brouard 2838:
1.223 brouard 2839: for(i=1; i<= nlstate; i++){
2840: for(j=1; j<i;j++){
2841: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
2842: /*lnpijopii += param[i][j][nc]*cov[nc];*/
2843: lnpijopii += x[nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel]*cov[nc];
2844: /* printf("Int j<i s1=%.17e, lnpijopii=%.17e\n",s1,lnpijopii); */
2845: }
2846: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
2847: /* printf("s1=%.17e, lnpijopii=%.17e\n",s1,lnpijopii); */
2848: }
2849: for(j=i+1; j<=nlstate+ndeath;j++){
2850: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
2851: /*lnpijopii += x[(i-1)*nlstate*ncovmodel+(j-2)*ncovmodel+nc+(i-1)*(ndeath-1)*ncovmodel]*cov[nc];*/
2852: lnpijopii += x[nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel]*cov[nc];
2853: /* printf("Int j>i s1=%.17e, lnpijopii=%.17e %lx %lx\n",s1,lnpijopii,s1,lnpijopii); */
2854: }
2855: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
2856: }
2857: }
1.218 brouard 2858:
1.223 brouard 2859: for(i=1; i<= nlstate; i++){
2860: s1=0;
2861: for(j=1; j<i; j++){
2862: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
2863: /*printf("debug1 %d %d ps=%lf exp(ps)=%lf s1+=%lf\n",i,j,ps[i][j],exp(ps[i][j]),s1); */
2864: }
2865: for(j=i+1; j<=nlstate+ndeath; j++){
2866: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
2867: /*printf("debug2 %d %d ps=%lf exp(ps)=%lf s1+=%lf\n",i,j,ps[i][j],exp(ps[i][j]),s1); */
2868: }
2869: /* s1= sum_{j<>i} pij/pii=(1-pii)/pii and thus pii is known from s1 */
2870: ps[i][i]=1./(s1+1.);
2871: /* Computing other pijs */
2872: for(j=1; j<i; j++)
2873: ps[i][j]= exp(ps[i][j])*ps[i][i];
2874: for(j=i+1; j<=nlstate+ndeath; j++)
2875: ps[i][j]= exp(ps[i][j])*ps[i][i];
2876: /* ps[i][nlstate+1]=1.-s1- ps[i][i];*/ /* Sum should be 1 */
2877: } /* end i */
1.218 brouard 2878:
1.223 brouard 2879: for(ii=nlstate+1; ii<= nlstate+ndeath; ii++){
2880: for(jj=1; jj<= nlstate+ndeath; jj++){
2881: ps[ii][jj]=0;
2882: ps[ii][ii]=1;
2883: }
2884: }
1.218 brouard 2885:
2886:
1.223 brouard 2887: /* for(ii=1; ii<= nlstate+ndeath; ii++){ */
2888: /* for(jj=1; jj<= nlstate+ndeath; jj++){ */
2889: /* printf(" pmij ps[%d][%d]=%lf ",ii,jj,ps[ii][jj]); */
2890: /* } */
2891: /* printf("\n "); */
2892: /* } */
2893: /* printf("\n ");printf("%lf ",cov[2]);*/
2894: /*
2895: for(i=1; i<= npar; i++) printf("%f ",x[i]);
1.218 brouard 2896: goto end;*/
1.266 brouard 2897: return ps; /* Pointer is unchanged since its call */
1.126 brouard 2898: }
2899:
1.218 brouard 2900: /*************** backward transition probabilities ***************/
2901:
2902: /* 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 ) */
2903: /* double **bmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate, double ***prevacurrent, double ***dnewm, double **doldm, double **dsavm, int ij ) */
2904: double **bmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate, double ***prevacurrent, int ij )
2905: {
1.266 brouard 2906: /* Computes the backward probability at age agefin and covariate combination ij. In fact cov is already filled and x too.
2907: * 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 2908: */
1.218 brouard 2909: int i, ii, j,k;
1.222 brouard 2910:
2911: double **out, **pmij();
2912: double sumnew=0.;
1.218 brouard 2913: double agefin;
1.268 brouard 2914: 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 2915: double **dnewm, **dsavm, **doldm;
2916: double **bbmij;
2917:
1.218 brouard 2918: doldm=ddoldms; /* global pointers */
1.222 brouard 2919: dnewm=ddnewms;
2920: dsavm=ddsavms;
2921:
2922: agefin=cov[2];
1.268 brouard 2923: /* Bx = Diag(w_x) P_x Diag(Sum_i w^i_x p^ij_x */
1.222 brouard 2924: /* bmij *//* age is cov[2], ij is included in cov, but we need for
1.266 brouard 2925: the observed prevalence (with this covariate ij) at beginning of transition */
2926: /* dsavm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
1.268 brouard 2927:
2928: /* P_x */
1.266 brouard 2929: pmmij=pmij(pmmij,cov,ncovmodel,x,nlstate); /*This is forward probability from agefin to agefin + stepm */
1.268 brouard 2930: /* outputs pmmij which is a stochastic matrix in row */
2931:
2932: /* Diag(w_x) */
2933: /* Problem with prevacurrent which can be zero */
2934: sumnew=0.;
1.269 brouard 2935: /*for (ii=1;ii<=nlstate+ndeath;ii++){*/
1.268 brouard 2936: for (ii=1;ii<=nlstate;ii++){ /* Only on live states */
1.269 brouard 2937: /* printf(" agefin=%d, ii=%d, ij=%d, prev=%f\n",(int)agefin,ii, ij, prevacurrent[(int)agefin][ii][ij]); */
1.268 brouard 2938: sumnew+=prevacurrent[(int)agefin][ii][ij];
2939: }
2940: if(sumnew >0.01){ /* At least some value in the prevalence */
2941: for (ii=1;ii<=nlstate+ndeath;ii++){
2942: for (j=1;j<=nlstate+ndeath;j++)
1.269 brouard 2943: doldm[ii][j]=(ii==j ? prevacurrent[(int)agefin][ii][ij]/sumnew : 0.0);
1.268 brouard 2944: }
2945: }else{
2946: for (ii=1;ii<=nlstate+ndeath;ii++){
2947: for (j=1;j<=nlstate+ndeath;j++)
2948: doldm[ii][j]=(ii==j ? 1./nlstate : 0.0);
2949: }
2950: /* if(sumnew <0.9){ */
2951: /* printf("Problem internal bmij B: sum on i wi <0.9: j=%d, sum_i wi=%lf,agefin=%d\n",j,sumnew, (int)agefin); */
2952: /* } */
2953: }
2954: k3=0.0; /* We put the last diagonal to 0 */
2955: for (ii=nlstate+1;ii<=nlstate+ndeath;ii++){
2956: doldm[ii][ii]= k3;
2957: }
2958: /* End doldm, At the end doldm is diag[(w_i)] */
2959:
2960: /* left Product of this diag matrix by pmmij=Px (dnewm=dsavm*doldm) */
2961: bbmij=matprod2(dnewm, doldm,1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, pmmij); /* Bug Valgrind */
2962:
2963: /* Diag(Sum_i w^i_x p^ij_x */
2964: /* 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 2965: for (j=1;j<=nlstate+ndeath;j++){
1.268 brouard 2966: sumnew=0.;
1.222 brouard 2967: for (ii=1;ii<=nlstate;ii++){
1.266 brouard 2968: /* sumnew+=dsavm[ii][j]*prevacurrent[(int)agefin][ii][ij]; */
1.268 brouard 2969: sumnew+=pmmij[ii][j]*doldm[ii][ii]; /* Yes prevalence at beginning of transition */
1.222 brouard 2970: } /* sumnew is (N11+N21)/N..= N.1/N.. = sum on i of w_i pij */
1.268 brouard 2971: for (ii=1;ii<=nlstate+ndeath;ii++){
1.222 brouard 2972: /* if(agefin >= agemaxpar && agefin <= agemaxpar+stepm/YEARM){ */
1.268 brouard 2973: /* dsavm[ii][j]=(ii==j ? 1./sumnew : 0.0); */
1.222 brouard 2974: /* }else if(agefin >= agemaxpar+stepm/YEARM){ */
1.268 brouard 2975: /* dsavm[ii][j]=(ii==j ? 1./sumnew : 0.0); */
1.222 brouard 2976: /* }else */
1.268 brouard 2977: dsavm[ii][j]=(ii==j ? 1./sumnew : 0.0);
2978: } /*End ii */
2979: } /* 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 */
2980:
2981: ps=matprod2(ps, dnewm,1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, dsavm); /* Bug Valgrind */
2982: /* ps is now diag[w_i] * Px * diag [1/(w_1p1i+w_2 p2i)] */
1.222 brouard 2983: /* end bmij */
1.266 brouard 2984: return ps; /*pointer is unchanged */
1.218 brouard 2985: }
1.217 brouard 2986: /*************** transition probabilities ***************/
2987:
1.218 brouard 2988: double **bpmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate )
1.217 brouard 2989: {
2990: /* According to parameters values stored in x and the covariate's values stored in cov,
2991: computes the probability to be observed in state j being in state i by appying the
2992: model to the ncovmodel covariates (including constant and age).
2993: lnpijopii=ln(pij/pii)= aij+bij*age+cij*v1+dij*v2+... = sum_nc=1^ncovmodel xij(nc)*cov[nc]
2994: and, according on how parameters are entered, the position of the coefficient xij(nc) of the
2995: ncth covariate in the global vector x is given by the formula:
2996: j<i nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel
2997: j>=i nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel
2998: Computes ln(pij/pii) (lnpijopii), deduces pij/pii by exponentiation,
2999: sums on j different of i to get 1-pii/pii, deduces pii, and then all pij.
3000: Outputs ps[i][j] the probability to be observed in j being in j according to
3001: the values of the covariates cov[nc] and corresponding parameter values x[nc+shiftij]
3002: */
3003: double s1, lnpijopii;
3004: /*double t34;*/
3005: int i,j, nc, ii, jj;
3006:
1.234 brouard 3007: for(i=1; i<= nlstate; i++){
3008: for(j=1; j<i;j++){
3009: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
3010: /*lnpijopii += param[i][j][nc]*cov[nc];*/
3011: lnpijopii += x[nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel]*cov[nc];
3012: /* printf("Int j<i s1=%.17e, lnpijopii=%.17e\n",s1,lnpijopii); */
3013: }
3014: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
3015: /* printf("s1=%.17e, lnpijopii=%.17e\n",s1,lnpijopii); */
3016: }
3017: for(j=i+1; j<=nlstate+ndeath;j++){
3018: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
3019: /*lnpijopii += x[(i-1)*nlstate*ncovmodel+(j-2)*ncovmodel+nc+(i-1)*(ndeath-1)*ncovmodel]*cov[nc];*/
3020: lnpijopii += x[nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel]*cov[nc];
3021: /* printf("Int j>i s1=%.17e, lnpijopii=%.17e %lx %lx\n",s1,lnpijopii,s1,lnpijopii); */
3022: }
3023: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
3024: }
3025: }
3026:
3027: for(i=1; i<= nlstate; i++){
3028: s1=0;
3029: for(j=1; j<i; j++){
3030: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
3031: /*printf("debug1 %d %d ps=%lf exp(ps)=%lf s1+=%lf\n",i,j,ps[i][j],exp(ps[i][j]),s1); */
3032: }
3033: for(j=i+1; j<=nlstate+ndeath; j++){
3034: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
3035: /*printf("debug2 %d %d ps=%lf exp(ps)=%lf s1+=%lf\n",i,j,ps[i][j],exp(ps[i][j]),s1); */
3036: }
3037: /* s1= sum_{j<>i} pij/pii=(1-pii)/pii and thus pii is known from s1 */
3038: ps[i][i]=1./(s1+1.);
3039: /* Computing other pijs */
3040: for(j=1; j<i; j++)
3041: ps[i][j]= exp(ps[i][j])*ps[i][i];
3042: for(j=i+1; j<=nlstate+ndeath; j++)
3043: ps[i][j]= exp(ps[i][j])*ps[i][i];
3044: /* ps[i][nlstate+1]=1.-s1- ps[i][i];*/ /* Sum should be 1 */
3045: } /* end i */
3046:
3047: for(ii=nlstate+1; ii<= nlstate+ndeath; ii++){
3048: for(jj=1; jj<= nlstate+ndeath; jj++){
3049: ps[ii][jj]=0;
3050: ps[ii][ii]=1;
3051: }
3052: }
3053: /* Added for backcast */ /* Transposed matrix too */
3054: for(jj=1; jj<= nlstate+ndeath; jj++){
3055: s1=0.;
3056: for(ii=1; ii<= nlstate+ndeath; ii++){
3057: s1+=ps[ii][jj];
3058: }
3059: for(ii=1; ii<= nlstate; ii++){
3060: ps[ii][jj]=ps[ii][jj]/s1;
3061: }
3062: }
3063: /* Transposition */
3064: for(jj=1; jj<= nlstate+ndeath; jj++){
3065: for(ii=jj; ii<= nlstate+ndeath; ii++){
3066: s1=ps[ii][jj];
3067: ps[ii][jj]=ps[jj][ii];
3068: ps[jj][ii]=s1;
3069: }
3070: }
3071: /* for(ii=1; ii<= nlstate+ndeath; ii++){ */
3072: /* for(jj=1; jj<= nlstate+ndeath; jj++){ */
3073: /* printf(" pmij ps[%d][%d]=%lf ",ii,jj,ps[ii][jj]); */
3074: /* } */
3075: /* printf("\n "); */
3076: /* } */
3077: /* printf("\n ");printf("%lf ",cov[2]);*/
3078: /*
3079: for(i=1; i<= npar; i++) printf("%f ",x[i]);
3080: goto end;*/
3081: return ps;
1.217 brouard 3082: }
3083:
3084:
1.126 brouard 3085: /**************** Product of 2 matrices ******************/
3086:
1.145 brouard 3087: double **matprod2(double **out, double **in,int nrl, int nrh, int ncl, int nch, int ncolol, int ncoloh, double **b)
1.126 brouard 3088: {
3089: /* Computes the matrix product of in(1,nrh-nrl+1)(1,nch-ncl+1) times
3090: b(1,nch-ncl+1)(1,ncoloh-ncolol+1) into out(...) */
3091: /* in, b, out are matrice of pointers which should have been initialized
3092: before: only the contents of out is modified. The function returns
3093: a pointer to pointers identical to out */
1.145 brouard 3094: int i, j, k;
1.126 brouard 3095: for(i=nrl; i<= nrh; i++)
1.145 brouard 3096: for(k=ncolol; k<=ncoloh; k++){
3097: out[i][k]=0.;
3098: for(j=ncl; j<=nch; j++)
3099: out[i][k] +=in[i][j]*b[j][k];
3100: }
1.126 brouard 3101: return out;
3102: }
3103:
3104:
3105: /************* Higher Matrix Product ***************/
3106:
1.235 brouard 3107: 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 3108: {
1.218 brouard 3109: /* Computes the transition matrix starting at age 'age' and combination of covariate values corresponding to ij over
1.126 brouard 3110: 'nhstepm*hstepm*stepm' months (i.e. until
3111: age (in years) age+nhstepm*hstepm*stepm/12) by multiplying
3112: nhstepm*hstepm matrices.
3113: Output is stored in matrix po[i][j][h] for h every 'hstepm' step
3114: (typically every 2 years instead of every month which is too big
3115: for the memory).
3116: Model is determined by parameters x and covariates have to be
3117: included manually here.
3118:
3119: */
3120:
3121: int i, j, d, h, k;
1.131 brouard 3122: double **out, cov[NCOVMAX+1];
1.126 brouard 3123: double **newm;
1.187 brouard 3124: double agexact;
1.214 brouard 3125: double agebegin, ageend;
1.126 brouard 3126:
3127: /* Hstepm could be zero and should return the unit matrix */
3128: for (i=1;i<=nlstate+ndeath;i++)
3129: for (j=1;j<=nlstate+ndeath;j++){
3130: oldm[i][j]=(i==j ? 1.0 : 0.0);
3131: po[i][j][0]=(i==j ? 1.0 : 0.0);
3132: }
3133: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
3134: for(h=1; h <=nhstepm; h++){
3135: for(d=1; d <=hstepm; d++){
3136: newm=savm;
3137: /* Covariates have to be included here again */
3138: cov[1]=1.;
1.214 brouard 3139: agexact=age+((h-1)*hstepm + (d-1))*stepm/YEARM; /* age just before transition */
1.187 brouard 3140: cov[2]=agexact;
3141: if(nagesqr==1)
1.227 brouard 3142: cov[3]= agexact*agexact;
1.235 brouard 3143: for (k=1; k<=nsd;k++) { /* For single dummy covariates only */
3144: /* Here comes the value of the covariate 'ij' after renumbering k with single dummy covariates */
3145: cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,k)];
3146: /* 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)); */
3147: }
3148: for (k=1; k<=nsq;k++) { /* For single varying covariates only */
3149: /* Here comes the value of quantitative after renumbering k with single quantitative covariates */
3150: cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k];
3151: /* 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]); */
3152: }
3153: for (k=1; k<=cptcovage;k++){
3154: if(Dummy[Tvar[Tage[k]]]){
3155: cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2];
3156: } else{
3157: cov[2+nagesqr+Tage[k]]=Tqresult[nres][k];
3158: }
3159: /* 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]); */
3160: }
3161: for (k=1; k<=cptcovprod;k++){ /* */
3162: /* 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]); */
3163: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)];
3164: }
3165: /* for (k=1; k<=cptcovn;k++) */
3166: /* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,k)]; */
3167: /* for (k=1; k<=cptcovage;k++) /\* Should start at cptcovn+1 *\/ */
3168: /* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2]; */
3169: /* for (k=1; k<=cptcovprod;k++) /\* Useless because included in cptcovn *\/ */
3170: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)]*nbcode[Tvard[k][2]][codtabm(ij,k)]; */
1.227 brouard 3171:
3172:
1.126 brouard 3173: /*printf("hxi cptcov=%d cptcode=%d\n",cptcov,cptcode);*/
3174: /*printf("h=%d d=%d age=%f cov=%f\n",h,d,age,cov[2]);*/
1.218 brouard 3175: /* right multiplication of oldm by the current matrix */
1.126 brouard 3176: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath,
3177: pmij(pmmij,cov,ncovmodel,x,nlstate));
1.217 brouard 3178: /* if((int)age == 70){ */
3179: /* printf(" Forward hpxij age=%d agexact=%f d=%d nhstepm=%d hstepm=%d\n", (int) age, agexact, d, nhstepm, hstepm); */
3180: /* for(i=1; i<=nlstate+ndeath; i++) { */
3181: /* printf("%d pmmij ",i); */
3182: /* for(j=1;j<=nlstate+ndeath;j++) { */
3183: /* printf("%f ",pmmij[i][j]); */
3184: /* } */
3185: /* printf(" oldm "); */
3186: /* for(j=1;j<=nlstate+ndeath;j++) { */
3187: /* printf("%f ",oldm[i][j]); */
3188: /* } */
3189: /* printf("\n"); */
3190: /* } */
3191: /* } */
1.126 brouard 3192: savm=oldm;
3193: oldm=newm;
3194: }
3195: for(i=1; i<=nlstate+ndeath; i++)
3196: for(j=1;j<=nlstate+ndeath;j++) {
1.267 brouard 3197: po[i][j][h]=newm[i][j];
3198: /*if(h==nhstepm) printf("po[%d][%d][%d]=%f ",i,j,h,po[i][j][h]);*/
1.126 brouard 3199: }
1.128 brouard 3200: /*printf("h=%d ",h);*/
1.126 brouard 3201: } /* end h */
1.267 brouard 3202: /* printf("\n H=%d \n",h); */
1.126 brouard 3203: return po;
3204: }
3205:
1.217 brouard 3206: /************* Higher Back Matrix Product ***************/
1.218 brouard 3207: /* 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 3208: 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 3209: {
1.266 brouard 3210: /* For a combination of dummy covariate ij, computes the transition matrix starting at age 'age' over
1.217 brouard 3211: 'nhstepm*hstepm*stepm' months (i.e. until
1.218 brouard 3212: age (in years) age+nhstepm*hstepm*stepm/12) by multiplying
3213: nhstepm*hstepm matrices.
3214: Output is stored in matrix po[i][j][h] for h every 'hstepm' step
3215: (typically every 2 years instead of every month which is too big
1.217 brouard 3216: for the memory).
1.218 brouard 3217: Model is determined by parameters x and covariates have to be
1.266 brouard 3218: included manually here. Then we use a call to bmij(x and cov)
3219: The addresss of po (p3mat allocated to the dimension of nhstepm) should be stored for output
1.222 brouard 3220: */
1.217 brouard 3221:
3222: int i, j, d, h, k;
1.266 brouard 3223: double **out, cov[NCOVMAX+1], **bmij();
3224: double **newm, ***newmm;
1.217 brouard 3225: double agexact;
3226: double agebegin, ageend;
1.222 brouard 3227: double **oldm, **savm;
1.217 brouard 3228:
1.266 brouard 3229: newmm=po; /* To be saved */
3230: oldm=oldms;savm=savms; /* Global pointers */
1.217 brouard 3231: /* Hstepm could be zero and should return the unit matrix */
3232: for (i=1;i<=nlstate+ndeath;i++)
3233: for (j=1;j<=nlstate+ndeath;j++){
3234: oldm[i][j]=(i==j ? 1.0 : 0.0);
3235: po[i][j][0]=(i==j ? 1.0 : 0.0);
3236: }
3237: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
3238: for(h=1; h <=nhstepm; h++){
3239: for(d=1; d <=hstepm; d++){
3240: newm=savm;
3241: /* Covariates have to be included here again */
3242: cov[1]=1.;
1.266 brouard 3243: agexact=age-((h-1)*hstepm + (d))*stepm/YEARM; /* age just before transition, d or d-1? */
1.217 brouard 3244: /* agexact=age+((h-1)*hstepm + (d-1))*stepm/YEARM; /\* age just before transition *\/ */
3245: cov[2]=agexact;
3246: if(nagesqr==1)
1.222 brouard 3247: cov[3]= agexact*agexact;
1.266 brouard 3248: for (k=1; k<=cptcovn;k++){
3249: /* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,k)]; */
3250: /* /\* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,Tvar[k])]; *\/ */
3251: cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,k)];
3252: /* 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)); */
3253: }
1.267 brouard 3254: for (k=1; k<=nsq;k++) { /* For single varying covariates only */
3255: /* Here comes the value of quantitative after renumbering k with single quantitative covariates */
3256: cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k];
3257: /* 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]); */
3258: }
3259: for (k=1; k<=cptcovage;k++){ /* Should start at cptcovn+1 */
3260: if(Dummy[Tvar[Tage[k]]]){
3261: cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2];
3262: } else{
3263: cov[2+nagesqr+Tage[k]]=Tqresult[nres][k];
3264: }
3265: /* 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]); */
3266: }
3267: for (k=1; k<=cptcovprod;k++){ /* Useless because included in cptcovn */
1.222 brouard 3268: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)]*nbcode[Tvard[k][2]][codtabm(ij,k)];
1.267 brouard 3269: }
1.217 brouard 3270: /*printf("hxi cptcov=%d cptcode=%d\n",cptcov,cptcode);*/
3271: /*printf("h=%d d=%d age=%f cov=%f\n",h,d,age,cov[2]);*/
1.267 brouard 3272:
1.218 brouard 3273: /* Careful transposed matrix */
1.266 brouard 3274: /* age is in cov[2], prevacurrent at beginning of transition. */
1.218 brouard 3275: /* out=matprod2(newm, bmij(pmmij,cov,ncovmodel,x,nlstate,prevacurrent, dnewm, doldm, dsavm,ij),\ */
1.222 brouard 3276: /* 1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); */
1.218 brouard 3277: out=matprod2(newm, bmij(pmmij,cov,ncovmodel,x,nlstate,prevacurrent,ij),\
1.222 brouard 3278: 1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm);
1.217 brouard 3279: /* if((int)age == 70){ */
3280: /* printf(" Backward hbxij age=%d agexact=%f d=%d nhstepm=%d hstepm=%d\n", (int) age, agexact, d, nhstepm, hstepm); */
3281: /* for(i=1; i<=nlstate+ndeath; i++) { */
3282: /* printf("%d pmmij ",i); */
3283: /* for(j=1;j<=nlstate+ndeath;j++) { */
3284: /* printf("%f ",pmmij[i][j]); */
3285: /* } */
3286: /* printf(" oldm "); */
3287: /* for(j=1;j<=nlstate+ndeath;j++) { */
3288: /* printf("%f ",oldm[i][j]); */
3289: /* } */
3290: /* printf("\n"); */
3291: /* } */
3292: /* } */
3293: savm=oldm;
3294: oldm=newm;
3295: }
3296: for(i=1; i<=nlstate+ndeath; i++)
3297: for(j=1;j<=nlstate+ndeath;j++) {
1.222 brouard 3298: po[i][j][h]=newm[i][j];
1.268 brouard 3299: /* if(h==nhstepm) */
3300: /* printf("po[%d][%d][%d]=%f ",i,j,h,po[i][j][h]); */
1.217 brouard 3301: }
1.268 brouard 3302: /* printf("h=%d %.1f ",h, agexact); */
1.217 brouard 3303: } /* end h */
1.268 brouard 3304: /* printf("\n H=%d nhs=%d \n",h, nhstepm); */
1.217 brouard 3305: return po;
3306: }
3307:
3308:
1.162 brouard 3309: #ifdef NLOPT
3310: double myfunc(unsigned n, const double *p1, double *grad, void *pd){
3311: double fret;
3312: double *xt;
3313: int j;
3314: myfunc_data *d2 = (myfunc_data *) pd;
3315: /* xt = (p1-1); */
3316: xt=vector(1,n);
3317: for (j=1;j<=n;j++) xt[j]=p1[j-1]; /* xt[1]=p1[0] */
3318:
3319: fret=(d2->function)(xt); /* p xt[1]@8 is fine */
3320: /* fret=(*func)(xt); /\* p xt[1]@8 is fine *\/ */
3321: printf("Function = %.12lf ",fret);
3322: for (j=1;j<=n;j++) printf(" %d %.8lf", j, xt[j]);
3323: printf("\n");
3324: free_vector(xt,1,n);
3325: return fret;
3326: }
3327: #endif
1.126 brouard 3328:
3329: /*************** log-likelihood *************/
3330: double func( double *x)
3331: {
1.226 brouard 3332: int i, ii, j, k, mi, d, kk;
3333: int ioffset=0;
3334: double l, ll[NLSTATEMAX+1], cov[NCOVMAX+1];
3335: double **out;
3336: double lli; /* Individual log likelihood */
3337: int s1, s2;
1.228 brouard 3338: 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 3339: double bbh, survp;
3340: long ipmx;
3341: double agexact;
3342: /*extern weight */
3343: /* We are differentiating ll according to initial status */
3344: /* for (i=1;i<=npar;i++) printf("%f ", x[i]);*/
3345: /*for(i=1;i<imx;i++)
3346: printf(" %d\n",s[4][i]);
3347: */
1.162 brouard 3348:
1.226 brouard 3349: ++countcallfunc;
1.162 brouard 3350:
1.226 brouard 3351: cov[1]=1.;
1.126 brouard 3352:
1.226 brouard 3353: for(k=1; k<=nlstate; k++) ll[k]=0.;
1.224 brouard 3354: ioffset=0;
1.226 brouard 3355: if(mle==1){
3356: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
3357: /* Computes the values of the ncovmodel covariates of the model
3358: depending if the covariates are fixed or varying (age dependent) and stores them in cov[]
3359: Then computes with function pmij which return a matrix p[i][j] giving the elementary probability
3360: to be observed in j being in i according to the model.
3361: */
1.243 brouard 3362: ioffset=2+nagesqr ;
1.233 brouard 3363: /* Fixed */
1.234 brouard 3364: for (k=1; k<=ncovf;k++){ /* Simple and product fixed covariates without age* products */
3365: 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)*/
3366: }
1.226 brouard 3367: /* In model V2+V1*V4+age*V3+V3*V2 Tvar[1] is V2, Tvar[2=V1*V4]
3368: is 6, Tvar[3=age*V3] should not be computed because of age Tvar[4=V3*V2]
3369: has been calculated etc */
3370: /* For an individual i, wav[i] gives the number of effective waves */
3371: /* We compute the contribution to Likelihood of each effective transition
3372: mw[mi][i] is real wave of the mi th effectve wave */
3373: /* Then statuses are computed at each begin and end of an effective wave s1=s[ mw[mi][i] ][i];
3374: s2=s[mw[mi+1][i]][i];
3375: And the iv th varying covariate is the cotvar[mw[mi+1][i]][iv][i]
3376: But if the variable is not in the model TTvar[iv] is the real variable effective in the model:
3377: meaning that decodemodel should be used cotvar[mw[mi+1][i]][TTvar[iv]][i]
3378: */
3379: for(mi=1; mi<= wav[i]-1; mi++){
1.234 brouard 3380: for(k=1; k <= ncovv ; k++){ /* Varying covariates (single and product but no age )*/
1.242 brouard 3381: /* cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]][i]; */
3382: cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]-ncovcol-nqv][i];
1.234 brouard 3383: }
3384: for (ii=1;ii<=nlstate+ndeath;ii++)
3385: for (j=1;j<=nlstate+ndeath;j++){
3386: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
3387: savm[ii][j]=(ii==j ? 1.0 : 0.0);
3388: }
3389: for(d=0; d<dh[mi][i]; d++){
3390: newm=savm;
3391: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
3392: cov[2]=agexact;
3393: if(nagesqr==1)
3394: cov[3]= agexact*agexact; /* Should be changed here */
3395: for (kk=1; kk<=cptcovage;kk++) {
1.242 brouard 3396: if(!FixedV[Tvar[Tage[kk]]])
1.234 brouard 3397: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact; /* Tage[kk] gives the data-covariate associated with age */
1.242 brouard 3398: else
3399: cov[Tage[kk]+2+nagesqr]=cotvar[mw[mi][i]][Tvar[Tage[kk]]-ncovcol-nqv][i]*agexact;
1.234 brouard 3400: }
3401: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
3402: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
3403: savm=oldm;
3404: oldm=newm;
3405: } /* end mult */
3406:
3407: /*lli=log(out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]);*/ /* Original formula */
3408: /* But now since version 0.9 we anticipate for bias at large stepm.
3409: * If stepm is larger than one month (smallest stepm) and if the exact delay
3410: * (in months) between two waves is not a multiple of stepm, we rounded to
3411: * the nearest (and in case of equal distance, to the lowest) interval but now
3412: * we keep into memory the bias bh[mi][i] and also the previous matrix product
3413: * (i.e to dh[mi][i]-1) saved in 'savm'. Then we inter(extra)polate the
3414: * probability in order to take into account the bias as a fraction of the way
1.231 brouard 3415: * from savm to out if bh is negative or even beyond if bh is positive. bh varies
3416: * -stepm/2 to stepm/2 .
3417: * For stepm=1 the results are the same as for previous versions of Imach.
3418: * For stepm > 1 the results are less biased than in previous versions.
3419: */
1.234 brouard 3420: s1=s[mw[mi][i]][i];
3421: s2=s[mw[mi+1][i]][i];
3422: bbh=(double)bh[mi][i]/(double)stepm;
3423: /* bias bh is positive if real duration
3424: * is higher than the multiple of stepm and negative otherwise.
3425: */
3426: /* lli= (savm[s1][s2]>1.e-8 ?(1.+bbh)*log(out[s1][s2])- bbh*log(savm[s1][s2]):log((1.+bbh)*out[s1][s2]));*/
3427: if( s2 > nlstate){
3428: /* i.e. if s2 is a death state and if the date of death is known
3429: then the contribution to the likelihood is the probability to
3430: die between last step unit time and current step unit time,
3431: which is also equal to probability to die before dh
3432: minus probability to die before dh-stepm .
3433: In version up to 0.92 likelihood was computed
3434: as if date of death was unknown. Death was treated as any other
3435: health state: the date of the interview describes the actual state
3436: and not the date of a change in health state. The former idea was
3437: to consider that at each interview the state was recorded
3438: (healthy, disable or death) and IMaCh was corrected; but when we
3439: introduced the exact date of death then we should have modified
3440: the contribution of an exact death to the likelihood. This new
3441: contribution is smaller and very dependent of the step unit
3442: stepm. It is no more the probability to die between last interview
3443: and month of death but the probability to survive from last
3444: interview up to one month before death multiplied by the
3445: probability to die within a month. Thanks to Chris
3446: Jackson for correcting this bug. Former versions increased
3447: mortality artificially. The bad side is that we add another loop
3448: which slows down the processing. The difference can be up to 10%
3449: lower mortality.
3450: */
3451: /* If, at the beginning of the maximization mostly, the
3452: cumulative probability or probability to be dead is
3453: constant (ie = 1) over time d, the difference is equal to
3454: 0. out[s1][3] = savm[s1][3]: probability, being at state
3455: s1 at precedent wave, to be dead a month before current
3456: wave is equal to probability, being at state s1 at
3457: precedent wave, to be dead at mont of the current
3458: wave. Then the observed probability (that this person died)
3459: is null according to current estimated parameter. In fact,
3460: it should be very low but not zero otherwise the log go to
3461: infinity.
3462: */
1.183 brouard 3463: /* #ifdef INFINITYORIGINAL */
3464: /* lli=log(out[s1][s2] - savm[s1][s2]); */
3465: /* #else */
3466: /* if ((out[s1][s2] - savm[s1][s2]) < mytinydouble) */
3467: /* lli=log(mytinydouble); */
3468: /* else */
3469: /* lli=log(out[s1][s2] - savm[s1][s2]); */
3470: /* #endif */
1.226 brouard 3471: lli=log(out[s1][s2] - savm[s1][s2]);
1.216 brouard 3472:
1.226 brouard 3473: } else if ( s2==-1 ) { /* alive */
3474: for (j=1,survp=0. ; j<=nlstate; j++)
3475: survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j];
3476: /*survp += out[s1][j]; */
3477: lli= log(survp);
3478: }
3479: else if (s2==-4) {
3480: for (j=3,survp=0. ; j<=nlstate; j++)
3481: survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j];
3482: lli= log(survp);
3483: }
3484: else if (s2==-5) {
3485: for (j=1,survp=0. ; j<=2; j++)
3486: survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j];
3487: lli= log(survp);
3488: }
3489: else{
3490: lli= log((1.+bbh)*out[s1][s2]- bbh*savm[s1][s2]); /* linear interpolation */
3491: /* 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 */
3492: }
3493: /*lli=(1.+bbh)*log(out[s1][s2])- bbh*log(savm[s1][s2]);*/
3494: /*if(lli ==000.0)*/
3495: /*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); */
3496: ipmx +=1;
3497: sw += weight[i];
3498: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
3499: /* if (lli < log(mytinydouble)){ */
3500: /* 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); */
3501: /* 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]); */
3502: /* } */
3503: } /* end of wave */
3504: } /* end of individual */
3505: } else if(mle==2){
3506: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
3507: for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i];
3508: for(mi=1; mi<= wav[i]-1; mi++){
3509: for (ii=1;ii<=nlstate+ndeath;ii++)
3510: for (j=1;j<=nlstate+ndeath;j++){
3511: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
3512: savm[ii][j]=(ii==j ? 1.0 : 0.0);
3513: }
3514: for(d=0; d<=dh[mi][i]; d++){
3515: newm=savm;
3516: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
3517: cov[2]=agexact;
3518: if(nagesqr==1)
3519: cov[3]= agexact*agexact;
3520: for (kk=1; kk<=cptcovage;kk++) {
3521: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
3522: }
3523: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
3524: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
3525: savm=oldm;
3526: oldm=newm;
3527: } /* end mult */
3528:
3529: s1=s[mw[mi][i]][i];
3530: s2=s[mw[mi+1][i]][i];
3531: bbh=(double)bh[mi][i]/(double)stepm;
3532: 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 */
3533: ipmx +=1;
3534: sw += weight[i];
3535: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
3536: } /* end of wave */
3537: } /* end of individual */
3538: } else if(mle==3){ /* exponential inter-extrapolation */
3539: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
3540: for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i];
3541: for(mi=1; mi<= wav[i]-1; mi++){
3542: for (ii=1;ii<=nlstate+ndeath;ii++)
3543: for (j=1;j<=nlstate+ndeath;j++){
3544: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
3545: savm[ii][j]=(ii==j ? 1.0 : 0.0);
3546: }
3547: for(d=0; d<dh[mi][i]; d++){
3548: newm=savm;
3549: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
3550: cov[2]=agexact;
3551: if(nagesqr==1)
3552: cov[3]= agexact*agexact;
3553: for (kk=1; kk<=cptcovage;kk++) {
3554: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
3555: }
3556: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
3557: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
3558: savm=oldm;
3559: oldm=newm;
3560: } /* end mult */
3561:
3562: s1=s[mw[mi][i]][i];
3563: s2=s[mw[mi+1][i]][i];
3564: bbh=(double)bh[mi][i]/(double)stepm;
3565: 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 */
3566: ipmx +=1;
3567: sw += weight[i];
3568: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
3569: } /* end of wave */
3570: } /* end of individual */
3571: }else if (mle==4){ /* ml=4 no inter-extrapolation */
3572: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
3573: for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i];
3574: for(mi=1; mi<= wav[i]-1; mi++){
3575: for (ii=1;ii<=nlstate+ndeath;ii++)
3576: for (j=1;j<=nlstate+ndeath;j++){
3577: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
3578: savm[ii][j]=(ii==j ? 1.0 : 0.0);
3579: }
3580: for(d=0; d<dh[mi][i]; d++){
3581: newm=savm;
3582: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
3583: cov[2]=agexact;
3584: if(nagesqr==1)
3585: cov[3]= agexact*agexact;
3586: for (kk=1; kk<=cptcovage;kk++) {
3587: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
3588: }
1.126 brouard 3589:
1.226 brouard 3590: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
3591: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
3592: savm=oldm;
3593: oldm=newm;
3594: } /* end mult */
3595:
3596: s1=s[mw[mi][i]][i];
3597: s2=s[mw[mi+1][i]][i];
3598: if( s2 > nlstate){
3599: lli=log(out[s1][s2] - savm[s1][s2]);
3600: } else if ( s2==-1 ) { /* alive */
3601: for (j=1,survp=0. ; j<=nlstate; j++)
3602: survp += out[s1][j];
3603: lli= log(survp);
3604: }else{
3605: lli=log(out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]); /* Original formula */
3606: }
3607: ipmx +=1;
3608: sw += weight[i];
3609: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
1.126 brouard 3610: /* 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 3611: } /* end of wave */
3612: } /* end of individual */
3613: }else{ /* ml=5 no inter-extrapolation no jackson =0.8a */
3614: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
3615: for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i];
3616: for(mi=1; mi<= wav[i]-1; mi++){
3617: for (ii=1;ii<=nlstate+ndeath;ii++)
3618: for (j=1;j<=nlstate+ndeath;j++){
3619: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
3620: savm[ii][j]=(ii==j ? 1.0 : 0.0);
3621: }
3622: for(d=0; d<dh[mi][i]; d++){
3623: newm=savm;
3624: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
3625: cov[2]=agexact;
3626: if(nagesqr==1)
3627: cov[3]= agexact*agexact;
3628: for (kk=1; kk<=cptcovage;kk++) {
3629: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
3630: }
1.126 brouard 3631:
1.226 brouard 3632: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
3633: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
3634: savm=oldm;
3635: oldm=newm;
3636: } /* end mult */
3637:
3638: s1=s[mw[mi][i]][i];
3639: s2=s[mw[mi+1][i]][i];
3640: lli=log(out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]); /* Original formula */
3641: ipmx +=1;
3642: sw += weight[i];
3643: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
3644: /*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]);*/
3645: } /* end of wave */
3646: } /* end of individual */
3647: } /* End of if */
3648: for(k=1,l=0.; k<=nlstate; k++) l += ll[k];
3649: /* printf("l1=%f l2=%f ",ll[1],ll[2]); */
3650: l= l*ipmx/sw; /* To get the same order of magnitude as if weight=1 for every body */
3651: return -l;
1.126 brouard 3652: }
3653:
3654: /*************** log-likelihood *************/
3655: double funcone( double *x)
3656: {
1.228 brouard 3657: /* Same as func but slower because of a lot of printf and if */
1.126 brouard 3658: int i, ii, j, k, mi, d, kk;
1.228 brouard 3659: int ioffset=0;
1.131 brouard 3660: double l, ll[NLSTATEMAX+1], cov[NCOVMAX+1];
1.126 brouard 3661: double **out;
3662: double lli; /* Individual log likelihood */
3663: double llt;
3664: int s1, s2;
1.228 brouard 3665: int iv=0, iqv=0, itv=0, iqtv=0 ; /* Index of varying covariate, fixed quantitative cov, time varying covariate, quantitative time varying covariate */
3666:
1.126 brouard 3667: double bbh, survp;
1.187 brouard 3668: double agexact;
1.214 brouard 3669: double agebegin, ageend;
1.126 brouard 3670: /*extern weight */
3671: /* We are differentiating ll according to initial status */
3672: /* for (i=1;i<=npar;i++) printf("%f ", x[i]);*/
3673: /*for(i=1;i<imx;i++)
3674: printf(" %d\n",s[4][i]);
3675: */
3676: cov[1]=1.;
3677:
3678: for(k=1; k<=nlstate; k++) ll[k]=0.;
1.224 brouard 3679: ioffset=0;
3680: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
1.243 brouard 3681: /* ioffset=2+nagesqr+cptcovage; */
3682: ioffset=2+nagesqr;
1.232 brouard 3683: /* Fixed */
1.224 brouard 3684: /* for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i]; */
1.232 brouard 3685: /* for (k=1; k<=ncoveff;k++){ /\* Simple and product fixed Dummy covariates without age* products *\/ */
3686: for (k=1; k<=ncovf;k++){ /* Simple and product fixed covariates without age* products */
3687: 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)*/
3688: /* cov[ioffset+TvarFind[1]]=covar[Tvar[TvarFind[1]]][i]; */
3689: /* cov[2+6]=covar[Tvar[6]][i]; */
3690: /* cov[2+6]=covar[2][i]; V2 */
3691: /* cov[TvarFind[2]]=covar[Tvar[TvarFind[2]]][i]; */
3692: /* cov[2+7]=covar[Tvar[7]][i]; */
3693: /* cov[2+7]=covar[7][i]; V7=V1*V2 */
3694: /* cov[TvarFind[3]]=covar[Tvar[TvarFind[3]]][i]; */
3695: /* cov[2+9]=covar[Tvar[9]][i]; */
3696: /* cov[2+9]=covar[1][i]; V1 */
1.225 brouard 3697: }
1.232 brouard 3698: /* for (k=1; k<=nqfveff;k++){ /\* Simple and product fixed Quantitative covariates without age* products *\/ */
3699: /* 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?)*\/ */
3700: /* } */
1.231 brouard 3701: /* for(iqv=1; iqv <= nqfveff; iqv++){ /\* Quantitative fixed covariates *\/ */
3702: /* cov[++ioffset]=coqvar[Tvar[iqv]][i]; /\* Only V2 k=6 and V1*V2 7 *\/ */
3703: /* } */
1.225 brouard 3704:
1.233 brouard 3705:
3706: for(mi=1; mi<= wav[i]-1; mi++){ /* Varying with waves */
1.232 brouard 3707: /* Wave varying (but not age varying) */
3708: for(k=1; k <= ncovv ; k++){ /* Varying covariates (single and product but no age )*/
1.242 brouard 3709: /* cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]][i]; */
3710: cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]-ncovcol-nqv][i];
3711: }
1.232 brouard 3712: /* for(itv=1; itv <= ntveff; itv++){ /\* Varying dummy covariates (single??)*\/ */
1.242 brouard 3713: /* iv= Tvar[Tmodelind[ioffset-2-nagesqr-cptcovage+itv]]-ncovcol-nqv; /\* Counting the # varying covariate from 1 to ntveff *\/ */
3714: /* cov[ioffset+iv]=cotvar[mw[mi][i]][iv][i]; */
3715: /* k=ioffset-2-nagesqr-cptcovage+itv; /\* position in simple model *\/ */
3716: /* cov[ioffset+itv]=cotvar[mw[mi][i]][TmodelInvind[itv]][i]; */
3717: /* 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 3718: /* for(iqtv=1; iqtv <= nqtveff; iqtv++){ /\* Varying quantitatives covariates *\/ */
1.242 brouard 3719: /* iv=TmodelInvQind[iqtv]; /\* Counting the # varying covariate from 1 to ntveff *\/ */
3720: /* /\* 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]); *\/ */
3721: /* cov[ioffset+ntveff+iqtv]=cotqvar[mw[mi][i]][TmodelInvQind[iqtv]][i]; */
1.232 brouard 3722: /* } */
1.126 brouard 3723: for (ii=1;ii<=nlstate+ndeath;ii++)
1.242 brouard 3724: for (j=1;j<=nlstate+ndeath;j++){
3725: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
3726: savm[ii][j]=(ii==j ? 1.0 : 0.0);
3727: }
1.214 brouard 3728:
3729: agebegin=agev[mw[mi][i]][i]; /* Age at beginning of effective wave */
3730: ageend=agev[mw[mi][i]][i] + (dh[mi][i])*stepm/YEARM; /* Age at end of effective wave and at the end of transition */
3731: for(d=0; d<dh[mi][i]; d++){ /* Delay between two effective waves */
1.247 brouard 3732: /* for(d=0; d<=0; d++){ /\* Delay between two effective waves Only one matrix to speed up*\/ */
1.242 brouard 3733: /*dh[m][i] or dh[mw[mi][i]][i] is the delay between two effective waves m=mw[mi][i]
3734: and mw[mi+1][i]. dh depends on stepm.*/
3735: newm=savm;
1.247 brouard 3736: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM; /* Here d is needed */
1.242 brouard 3737: cov[2]=agexact;
3738: if(nagesqr==1)
3739: cov[3]= agexact*agexact;
3740: for (kk=1; kk<=cptcovage;kk++) {
3741: if(!FixedV[Tvar[Tage[kk]]])
3742: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
3743: else
3744: cov[Tage[kk]+2+nagesqr]=cotvar[mw[mi][i]][Tvar[Tage[kk]]-ncovcol-nqv][i]*agexact;
3745: }
3746: /* printf("i=%d,mi=%d,d=%d,mw[mi][i]=%d\n",i, mi,d,mw[mi][i]); */
3747: /* savm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
3748: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
3749: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
3750: /* out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath, */
3751: /* 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate)); */
3752: savm=oldm;
3753: oldm=newm;
1.126 brouard 3754: } /* end mult */
3755:
3756: s1=s[mw[mi][i]][i];
3757: s2=s[mw[mi+1][i]][i];
1.217 brouard 3758: /* if(s2==-1){ */
1.268 brouard 3759: /* printf(" ERROR s1=%d, s2=%d i=%d \n", s1, s2, i); */
1.217 brouard 3760: /* /\* exit(1); *\/ */
3761: /* } */
1.126 brouard 3762: bbh=(double)bh[mi][i]/(double)stepm;
3763: /* bias is positive if real duration
3764: * is higher than the multiple of stepm and negative otherwise.
3765: */
3766: if( s2 > nlstate && (mle <5) ){ /* Jackson */
1.242 brouard 3767: lli=log(out[s1][s2] - savm[s1][s2]);
1.216 brouard 3768: } else if ( s2==-1 ) { /* alive */
1.242 brouard 3769: for (j=1,survp=0. ; j<=nlstate; j++)
3770: survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j];
3771: lli= log(survp);
1.126 brouard 3772: }else if (mle==1){
1.242 brouard 3773: lli= log((1.+bbh)*out[s1][s2]- bbh*savm[s1][s2]); /* linear interpolation */
1.126 brouard 3774: } else if(mle==2){
1.242 brouard 3775: 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 3776: } else if(mle==3){ /* exponential inter-extrapolation */
1.242 brouard 3777: 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 3778: } else if (mle==4){ /* mle=4 no inter-extrapolation */
1.242 brouard 3779: lli=log(out[s1][s2]); /* Original formula */
1.136 brouard 3780: } else{ /* mle=0 back to 1 */
1.242 brouard 3781: lli= log((1.+bbh)*out[s1][s2]- bbh*savm[s1][s2]); /* linear interpolation */
3782: /*lli=log(out[s1][s2]); */ /* Original formula */
1.126 brouard 3783: } /* End of if */
3784: ipmx +=1;
3785: sw += weight[i];
3786: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
1.132 brouard 3787: /*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 3788: if(globpr){
1.246 brouard 3789: fprintf(ficresilk,"%09ld %6.1f %6.1f %6d %2d %2d %2d %2d %3d %15.6f %8.4f %8.3f\
1.126 brouard 3790: %11.6f %11.6f %11.6f ", \
1.242 brouard 3791: 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 3792: 2*weight[i]*lli,(s2==-1? -1: out[s1][s2]),(s2==-1? -1: savm[s1][s2]));
1.242 brouard 3793: for(k=1,llt=0.,l=0.; k<=nlstate; k++){
3794: llt +=ll[k]*gipmx/gsw;
3795: fprintf(ficresilk," %10.6f",-ll[k]*gipmx/gsw);
3796: }
3797: fprintf(ficresilk," %10.6f\n", -llt);
1.126 brouard 3798: }
1.232 brouard 3799: } /* end of wave */
3800: } /* end of individual */
3801: for(k=1,l=0.; k<=nlstate; k++) l += ll[k];
3802: /* printf("l1=%f l2=%f ",ll[1],ll[2]); */
3803: l= l*ipmx/sw; /* To get the same order of magnitude as if weight=1 for every body */
3804: if(globpr==0){ /* First time we count the contributions and weights */
3805: gipmx=ipmx;
3806: gsw=sw;
3807: }
3808: return -l;
1.126 brouard 3809: }
3810:
3811:
3812: /*************** function likelione ***********/
3813: void likelione(FILE *ficres,double p[], int npar, int nlstate, int *globpri, long *ipmx, double *sw, double *fretone, double (*funcone)(double []))
3814: {
3815: /* This routine should help understanding what is done with
3816: the selection of individuals/waves and
3817: to check the exact contribution to the likelihood.
3818: Plotting could be done.
3819: */
3820: int k;
3821:
3822: if(*globpri !=0){ /* Just counts and sums, no printings */
1.201 brouard 3823: strcpy(fileresilk,"ILK_");
1.202 brouard 3824: strcat(fileresilk,fileresu);
1.126 brouard 3825: if((ficresilk=fopen(fileresilk,"w"))==NULL) {
3826: printf("Problem with resultfile: %s\n", fileresilk);
3827: fprintf(ficlog,"Problem with resultfile: %s\n", fileresilk);
3828: }
1.214 brouard 3829: 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");
3830: fprintf(ficresilk, "#num_i ageb agend i s1 s2 mi mw dh likeli weight %%weight 2wlli out sav ");
1.126 brouard 3831: /* i,s1,s2,mi,mw[mi][i],dh[mi][i],exp(lli),weight[i],2*weight[i]*lli,out[s1][s2],savm[s1][s2]); */
3832: for(k=1; k<=nlstate; k++)
3833: fprintf(ficresilk," -2*gipw/gsw*weight*ll[%d]++",k);
3834: fprintf(ficresilk," -2*gipw/gsw*weight*ll(total)\n");
3835: }
3836:
3837: *fretone=(*funcone)(p);
3838: if(*globpri !=0){
3839: fclose(ficresilk);
1.205 brouard 3840: if (mle ==0)
3841: fprintf(fichtm,"\n<br>File of contributions to the likelihood computed with initial parameters and mle = %d.",mle);
3842: else if(mle >=1)
3843: fprintf(fichtm,"\n<br>File of contributions to the likelihood computed with optimized parameters mle = %d.",mle);
3844: 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 3845:
1.208 brouard 3846:
3847: for (k=1; k<= nlstate ; k++) {
1.211 brouard 3848: 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 3849: <img src=\"%s-p%dj.png\">",k,k,subdirf2(optionfilefiname,"ILK_"),k,subdirf2(optionfilefiname,"ILK_"),k,subdirf2(optionfilefiname,"ILK_"),k);
3850: }
1.207 brouard 3851: 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 3852: <img src=\"%s-ori.png\">",subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"));
1.207 brouard 3853: fprintf(fichtm,"<br>- and by state of destination <a href=\"%s-dest.png\">%s-dest.png</a><br> \
1.204 brouard 3854: <img src=\"%s-dest.png\">",subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"));
1.207 brouard 3855: fflush(fichtm);
1.205 brouard 3856: }
1.126 brouard 3857: return;
3858: }
3859:
3860:
3861: /*********** Maximum Likelihood Estimation ***************/
3862:
3863: void mlikeli(FILE *ficres,double p[], int npar, int ncovmodel, int nlstate, double ftol, double (*func)(double []))
3864: {
1.165 brouard 3865: int i,j, iter=0;
1.126 brouard 3866: double **xi;
3867: double fret;
3868: double fretone; /* Only one call to likelihood */
3869: /* char filerespow[FILENAMELENGTH];*/
1.162 brouard 3870:
3871: #ifdef NLOPT
3872: int creturn;
3873: nlopt_opt opt;
3874: /* double lb[9] = { -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL }; /\* lower bounds *\/ */
3875: double *lb;
3876: double minf; /* the minimum objective value, upon return */
3877: double * p1; /* Shifted parameters from 0 instead of 1 */
3878: myfunc_data dinst, *d = &dinst;
3879: #endif
3880:
3881:
1.126 brouard 3882: xi=matrix(1,npar,1,npar);
3883: for (i=1;i<=npar;i++)
3884: for (j=1;j<=npar;j++)
3885: xi[i][j]=(i==j ? 1.0 : 0.0);
3886: printf("Powell\n"); fprintf(ficlog,"Powell\n");
1.201 brouard 3887: strcpy(filerespow,"POW_");
1.126 brouard 3888: strcat(filerespow,fileres);
3889: if((ficrespow=fopen(filerespow,"w"))==NULL) {
3890: printf("Problem with resultfile: %s\n", filerespow);
3891: fprintf(ficlog,"Problem with resultfile: %s\n", filerespow);
3892: }
3893: fprintf(ficrespow,"# Powell\n# iter -2*LL");
3894: for (i=1;i<=nlstate;i++)
3895: for(j=1;j<=nlstate+ndeath;j++)
3896: if(j!=i)fprintf(ficrespow," p%1d%1d",i,j);
3897: fprintf(ficrespow,"\n");
1.162 brouard 3898: #ifdef POWELL
1.126 brouard 3899: powell(p,xi,npar,ftol,&iter,&fret,func);
1.162 brouard 3900: #endif
1.126 brouard 3901:
1.162 brouard 3902: #ifdef NLOPT
3903: #ifdef NEWUOA
3904: opt = nlopt_create(NLOPT_LN_NEWUOA,npar);
3905: #else
3906: opt = nlopt_create(NLOPT_LN_BOBYQA,npar);
3907: #endif
3908: lb=vector(0,npar-1);
3909: for (i=0;i<npar;i++) lb[i]= -HUGE_VAL;
3910: nlopt_set_lower_bounds(opt, lb);
3911: nlopt_set_initial_step1(opt, 0.1);
3912:
3913: p1= (p+1); /* p *(p+1)@8 and p *(p1)@8 are equal p1[0]=p[1] */
3914: d->function = func;
3915: printf(" Func %.12lf \n",myfunc(npar,p1,NULL,d));
3916: nlopt_set_min_objective(opt, myfunc, d);
3917: nlopt_set_xtol_rel(opt, ftol);
3918: if ((creturn=nlopt_optimize(opt, p1, &minf)) < 0) {
3919: printf("nlopt failed! %d\n",creturn);
3920: }
3921: else {
3922: printf("found minimum after %d evaluations (NLOPT=%d)\n", countcallfunc ,NLOPT);
3923: printf("found minimum at f(%g,%g) = %0.10g\n", p[0], p[1], minf);
3924: iter=1; /* not equal */
3925: }
3926: nlopt_destroy(opt);
3927: #endif
1.126 brouard 3928: free_matrix(xi,1,npar,1,npar);
3929: fclose(ficrespow);
1.203 brouard 3930: printf("\n#Number of iterations & function calls = %d & %d, -2 Log likelihood = %.12f\n",iter, countcallfunc,func(p));
3931: fprintf(ficlog,"\n#Number of iterations & function calls = %d & %d, -2 Log likelihood = %.12f\n",iter, countcallfunc,func(p));
1.180 brouard 3932: fprintf(ficres,"#Number of iterations & function calls = %d & %d, -2 Log likelihood = %.12f\n",iter, countcallfunc,func(p));
1.126 brouard 3933:
3934: }
3935:
3936: /**** Computes Hessian and covariance matrix ***/
1.203 brouard 3937: void hesscov(double **matcov, double **hess, double p[], int npar, double delti[], double ftolhess, double (*func)(double []))
1.126 brouard 3938: {
3939: double **a,**y,*x,pd;
1.203 brouard 3940: /* double **hess; */
1.164 brouard 3941: int i, j;
1.126 brouard 3942: int *indx;
3943:
3944: double hessii(double p[], double delta, int theta, double delti[],double (*func)(double []),int npar);
1.203 brouard 3945: double hessij(double p[], double **hess, double delti[], int i, int j,double (*func)(double []),int npar);
1.126 brouard 3946: void lubksb(double **a, int npar, int *indx, double b[]) ;
3947: void ludcmp(double **a, int npar, int *indx, double *d) ;
3948: double gompertz(double p[]);
1.203 brouard 3949: /* hess=matrix(1,npar,1,npar); */
1.126 brouard 3950:
3951: printf("\nCalculation of the hessian matrix. Wait...\n");
3952: fprintf(ficlog,"\nCalculation of the hessian matrix. Wait...\n");
3953: for (i=1;i<=npar;i++){
1.203 brouard 3954: printf("%d-",i);fflush(stdout);
3955: fprintf(ficlog,"%d-",i);fflush(ficlog);
1.126 brouard 3956:
3957: hess[i][i]=hessii(p,ftolhess,i,delti,func,npar);
3958:
3959: /* printf(" %f ",p[i]);
3960: printf(" %lf %lf %lf",hess[i][i],ftolhess,delti[i]);*/
3961: }
3962:
3963: for (i=1;i<=npar;i++) {
3964: for (j=1;j<=npar;j++) {
3965: if (j>i) {
1.203 brouard 3966: printf(".%d-%d",i,j);fflush(stdout);
3967: fprintf(ficlog,".%d-%d",i,j);fflush(ficlog);
3968: hess[i][j]=hessij(p,hess, delti,i,j,func,npar);
1.126 brouard 3969:
3970: hess[j][i]=hess[i][j];
3971: /*printf(" %lf ",hess[i][j]);*/
3972: }
3973: }
3974: }
3975: printf("\n");
3976: fprintf(ficlog,"\n");
3977:
3978: printf("\nInverting the hessian to get the covariance matrix. Wait...\n");
3979: fprintf(ficlog,"\nInverting the hessian to get the covariance matrix. Wait...\n");
3980:
3981: a=matrix(1,npar,1,npar);
3982: y=matrix(1,npar,1,npar);
3983: x=vector(1,npar);
3984: indx=ivector(1,npar);
3985: for (i=1;i<=npar;i++)
3986: for (j=1;j<=npar;j++) a[i][j]=hess[i][j];
3987: ludcmp(a,npar,indx,&pd);
3988:
3989: for (j=1;j<=npar;j++) {
3990: for (i=1;i<=npar;i++) x[i]=0;
3991: x[j]=1;
3992: lubksb(a,npar,indx,x);
3993: for (i=1;i<=npar;i++){
3994: matcov[i][j]=x[i];
3995: }
3996: }
3997:
3998: printf("\n#Hessian matrix#\n");
3999: fprintf(ficlog,"\n#Hessian matrix#\n");
4000: for (i=1;i<=npar;i++) {
4001: for (j=1;j<=npar;j++) {
1.203 brouard 4002: printf("%.6e ",hess[i][j]);
4003: fprintf(ficlog,"%.6e ",hess[i][j]);
1.126 brouard 4004: }
4005: printf("\n");
4006: fprintf(ficlog,"\n");
4007: }
4008:
1.203 brouard 4009: /* printf("\n#Covariance matrix#\n"); */
4010: /* fprintf(ficlog,"\n#Covariance matrix#\n"); */
4011: /* for (i=1;i<=npar;i++) { */
4012: /* for (j=1;j<=npar;j++) { */
4013: /* printf("%.6e ",matcov[i][j]); */
4014: /* fprintf(ficlog,"%.6e ",matcov[i][j]); */
4015: /* } */
4016: /* printf("\n"); */
4017: /* fprintf(ficlog,"\n"); */
4018: /* } */
4019:
1.126 brouard 4020: /* Recompute Inverse */
1.203 brouard 4021: /* for (i=1;i<=npar;i++) */
4022: /* for (j=1;j<=npar;j++) a[i][j]=matcov[i][j]; */
4023: /* ludcmp(a,npar,indx,&pd); */
4024:
4025: /* printf("\n#Hessian matrix recomputed#\n"); */
4026:
4027: /* for (j=1;j<=npar;j++) { */
4028: /* for (i=1;i<=npar;i++) x[i]=0; */
4029: /* x[j]=1; */
4030: /* lubksb(a,npar,indx,x); */
4031: /* for (i=1;i<=npar;i++){ */
4032: /* y[i][j]=x[i]; */
4033: /* printf("%.3e ",y[i][j]); */
4034: /* fprintf(ficlog,"%.3e ",y[i][j]); */
4035: /* } */
4036: /* printf("\n"); */
4037: /* fprintf(ficlog,"\n"); */
4038: /* } */
4039:
4040: /* Verifying the inverse matrix */
4041: #ifdef DEBUGHESS
4042: y=matprod2(y,hess,1,npar,1,npar,1,npar,matcov);
1.126 brouard 4043:
1.203 brouard 4044: printf("\n#Verification: multiplying the matrix of covariance by the Hessian matrix, should be unity:#\n");
4045: fprintf(ficlog,"\n#Verification: multiplying the matrix of covariance by the Hessian matrix. Should be unity:#\n");
1.126 brouard 4046:
4047: for (j=1;j<=npar;j++) {
4048: for (i=1;i<=npar;i++){
1.203 brouard 4049: printf("%.2f ",y[i][j]);
4050: fprintf(ficlog,"%.2f ",y[i][j]);
1.126 brouard 4051: }
4052: printf("\n");
4053: fprintf(ficlog,"\n");
4054: }
1.203 brouard 4055: #endif
1.126 brouard 4056:
4057: free_matrix(a,1,npar,1,npar);
4058: free_matrix(y,1,npar,1,npar);
4059: free_vector(x,1,npar);
4060: free_ivector(indx,1,npar);
1.203 brouard 4061: /* free_matrix(hess,1,npar,1,npar); */
1.126 brouard 4062:
4063:
4064: }
4065:
4066: /*************** hessian matrix ****************/
4067: double hessii(double x[], double delta, int theta, double delti[], double (*func)(double []), int npar)
1.203 brouard 4068: { /* Around values of x, computes the function func and returns the scales delti and hessian */
1.126 brouard 4069: int i;
4070: int l=1, lmax=20;
1.203 brouard 4071: double k1,k2, res, fx;
1.132 brouard 4072: double p2[MAXPARM+1]; /* identical to x */
1.126 brouard 4073: double delt=0.0001, delts, nkhi=10.,nkhif=1., khi=1.e-4;
4074: int k=0,kmax=10;
4075: double l1;
4076:
4077: fx=func(x);
4078: for (i=1;i<=npar;i++) p2[i]=x[i];
1.145 brouard 4079: for(l=0 ; l <=lmax; l++){ /* Enlarging the zone around the Maximum */
1.126 brouard 4080: l1=pow(10,l);
4081: delts=delt;
4082: for(k=1 ; k <kmax; k=k+1){
4083: delt = delta*(l1*k);
4084: p2[theta]=x[theta] +delt;
1.145 brouard 4085: k1=func(p2)-fx; /* Might be negative if too close to the theoretical maximum */
1.126 brouard 4086: p2[theta]=x[theta]-delt;
4087: k2=func(p2)-fx;
4088: /*res= (k1-2.0*fx+k2)/delt/delt; */
1.203 brouard 4089: res= (k1+k2)/delt/delt/2.; /* Divided by 2 because L and not 2*L */
1.126 brouard 4090:
1.203 brouard 4091: #ifdef DEBUGHESSII
1.126 brouard 4092: 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);
4093: 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);
4094: #endif
4095: /*if(fabs(k1-2.0*fx+k2) <1.e-13){ */
4096: if((k1 <khi/nkhi/2.) || (k2 <khi/nkhi/2.)){
4097: k=kmax;
4098: }
4099: else if((k1 >khi/nkhif) || (k2 >khi/nkhif)){ /* Keeps lastvalue before 3.84/2 KHI2 5% 1d.f. */
1.164 brouard 4100: k=kmax; l=lmax*10;
1.126 brouard 4101: }
4102: else if((k1 >khi/nkhi) || (k2 >khi/nkhi)){
4103: delts=delt;
4104: }
1.203 brouard 4105: } /* End loop k */
1.126 brouard 4106: }
4107: delti[theta]=delts;
4108: return res;
4109:
4110: }
4111:
1.203 brouard 4112: double hessij( double x[], double **hess, double delti[], int thetai,int thetaj,double (*func)(double []),int npar)
1.126 brouard 4113: {
4114: int i;
1.164 brouard 4115: int l=1, lmax=20;
1.126 brouard 4116: double k1,k2,k3,k4,res,fx;
1.132 brouard 4117: double p2[MAXPARM+1];
1.203 brouard 4118: int k, kmax=1;
4119: double v1, v2, cv12, lc1, lc2;
1.208 brouard 4120:
4121: int firstime=0;
1.203 brouard 4122:
1.126 brouard 4123: fx=func(x);
1.203 brouard 4124: for (k=1; k<=kmax; k=k+10) {
1.126 brouard 4125: for (i=1;i<=npar;i++) p2[i]=x[i];
1.203 brouard 4126: p2[thetai]=x[thetai]+delti[thetai]*k;
4127: p2[thetaj]=x[thetaj]+delti[thetaj]*k;
1.126 brouard 4128: k1=func(p2)-fx;
4129:
1.203 brouard 4130: p2[thetai]=x[thetai]+delti[thetai]*k;
4131: p2[thetaj]=x[thetaj]-delti[thetaj]*k;
1.126 brouard 4132: k2=func(p2)-fx;
4133:
1.203 brouard 4134: p2[thetai]=x[thetai]-delti[thetai]*k;
4135: p2[thetaj]=x[thetaj]+delti[thetaj]*k;
1.126 brouard 4136: k3=func(p2)-fx;
4137:
1.203 brouard 4138: p2[thetai]=x[thetai]-delti[thetai]*k;
4139: p2[thetaj]=x[thetaj]-delti[thetaj]*k;
1.126 brouard 4140: k4=func(p2)-fx;
1.203 brouard 4141: res=(k1-k2-k3+k4)/4.0/delti[thetai]/k/delti[thetaj]/k/2.; /* Because of L not 2*L */
4142: if(k1*k2*k3*k4 <0.){
1.208 brouard 4143: firstime=1;
1.203 brouard 4144: kmax=kmax+10;
1.208 brouard 4145: }
4146: if(kmax >=10 || firstime ==1){
1.246 brouard 4147: 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);
4148: 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 4149: 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);
4150: 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);
4151: }
4152: #ifdef DEBUGHESSIJ
4153: v1=hess[thetai][thetai];
4154: v2=hess[thetaj][thetaj];
4155: cv12=res;
4156: /* Computing eigen value of Hessian matrix */
4157: lc1=((v1+v2)+sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
4158: lc2=((v1+v2)-sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
4159: if ((lc2 <0) || (lc1 <0) ){
4160: printf("Warning: sub Hessian matrix '%d%d' does not have positive eigen values \n",thetai,thetaj);
4161: fprintf(ficlog, "Warning: sub Hessian matrix '%d%d' does not have positive eigen values \n",thetai,thetaj);
4162: 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);
4163: 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);
4164: }
1.126 brouard 4165: #endif
4166: }
4167: return res;
4168: }
4169:
1.203 brouard 4170: /* Not done yet: Was supposed to fix if not exactly at the maximum */
4171: /* double hessij( double x[], double delti[], int thetai,int thetaj,double (*func)(double []),int npar) */
4172: /* { */
4173: /* int i; */
4174: /* int l=1, lmax=20; */
4175: /* double k1,k2,k3,k4,res,fx; */
4176: /* double p2[MAXPARM+1]; */
4177: /* double delt=0.0001, delts, nkhi=10.,nkhif=1., khi=1.e-4; */
4178: /* int k=0,kmax=10; */
4179: /* double l1; */
4180:
4181: /* fx=func(x); */
4182: /* for(l=0 ; l <=lmax; l++){ /\* Enlarging the zone around the Maximum *\/ */
4183: /* l1=pow(10,l); */
4184: /* delts=delt; */
4185: /* for(k=1 ; k <kmax; k=k+1){ */
4186: /* delt = delti*(l1*k); */
4187: /* for (i=1;i<=npar;i++) p2[i]=x[i]; */
4188: /* p2[thetai]=x[thetai]+delti[thetai]/k; */
4189: /* p2[thetaj]=x[thetaj]+delti[thetaj]/k; */
4190: /* k1=func(p2)-fx; */
4191:
4192: /* p2[thetai]=x[thetai]+delti[thetai]/k; */
4193: /* p2[thetaj]=x[thetaj]-delti[thetaj]/k; */
4194: /* k2=func(p2)-fx; */
4195:
4196: /* p2[thetai]=x[thetai]-delti[thetai]/k; */
4197: /* p2[thetaj]=x[thetaj]+delti[thetaj]/k; */
4198: /* k3=func(p2)-fx; */
4199:
4200: /* p2[thetai]=x[thetai]-delti[thetai]/k; */
4201: /* p2[thetaj]=x[thetaj]-delti[thetaj]/k; */
4202: /* k4=func(p2)-fx; */
4203: /* res=(k1-k2-k3+k4)/4.0/delti[thetai]*k/delti[thetaj]*k/2.; /\* Because of L not 2*L *\/ */
4204: /* #ifdef DEBUGHESSIJ */
4205: /* 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); */
4206: /* 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); */
4207: /* #endif */
4208: /* if((k1 <khi/nkhi/2.) || (k2 <khi/nkhi/2.)|| (k4 <khi/nkhi/2.)|| (k4 <khi/nkhi/2.)){ */
4209: /* k=kmax; */
4210: /* } */
4211: /* else if((k1 >khi/nkhif) || (k2 >khi/nkhif) || (k4 >khi/nkhif) || (k4 >khi/nkhif)){ /\* Keeps lastvalue before 3.84/2 KHI2 5% 1d.f. *\/ */
4212: /* k=kmax; l=lmax*10; */
4213: /* } */
4214: /* else if((k1 >khi/nkhi) || (k2 >khi/nkhi)){ */
4215: /* delts=delt; */
4216: /* } */
4217: /* } /\* End loop k *\/ */
4218: /* } */
4219: /* delti[theta]=delts; */
4220: /* return res; */
4221: /* } */
4222:
4223:
1.126 brouard 4224: /************** Inverse of matrix **************/
4225: void ludcmp(double **a, int n, int *indx, double *d)
4226: {
4227: int i,imax,j,k;
4228: double big,dum,sum,temp;
4229: double *vv;
4230:
4231: vv=vector(1,n);
4232: *d=1.0;
4233: for (i=1;i<=n;i++) {
4234: big=0.0;
4235: for (j=1;j<=n;j++)
4236: if ((temp=fabs(a[i][j])) > big) big=temp;
1.256 brouard 4237: if (big == 0.0){
4238: printf(" Singular Hessian matrix at row %d:\n",i);
4239: for (j=1;j<=n;j++) {
4240: printf(" a[%d][%d]=%f,",i,j,a[i][j]);
4241: fprintf(ficlog," a[%d][%d]=%f,",i,j,a[i][j]);
4242: }
4243: fflush(ficlog);
4244: fclose(ficlog);
4245: nrerror("Singular matrix in routine ludcmp");
4246: }
1.126 brouard 4247: vv[i]=1.0/big;
4248: }
4249: for (j=1;j<=n;j++) {
4250: for (i=1;i<j;i++) {
4251: sum=a[i][j];
4252: for (k=1;k<i;k++) sum -= a[i][k]*a[k][j];
4253: a[i][j]=sum;
4254: }
4255: big=0.0;
4256: for (i=j;i<=n;i++) {
4257: sum=a[i][j];
4258: for (k=1;k<j;k++)
4259: sum -= a[i][k]*a[k][j];
4260: a[i][j]=sum;
4261: if ( (dum=vv[i]*fabs(sum)) >= big) {
4262: big=dum;
4263: imax=i;
4264: }
4265: }
4266: if (j != imax) {
4267: for (k=1;k<=n;k++) {
4268: dum=a[imax][k];
4269: a[imax][k]=a[j][k];
4270: a[j][k]=dum;
4271: }
4272: *d = -(*d);
4273: vv[imax]=vv[j];
4274: }
4275: indx[j]=imax;
4276: if (a[j][j] == 0.0) a[j][j]=TINY;
4277: if (j != n) {
4278: dum=1.0/(a[j][j]);
4279: for (i=j+1;i<=n;i++) a[i][j] *= dum;
4280: }
4281: }
4282: free_vector(vv,1,n); /* Doesn't work */
4283: ;
4284: }
4285:
4286: void lubksb(double **a, int n, int *indx, double b[])
4287: {
4288: int i,ii=0,ip,j;
4289: double sum;
4290:
4291: for (i=1;i<=n;i++) {
4292: ip=indx[i];
4293: sum=b[ip];
4294: b[ip]=b[i];
4295: if (ii)
4296: for (j=ii;j<=i-1;j++) sum -= a[i][j]*b[j];
4297: else if (sum) ii=i;
4298: b[i]=sum;
4299: }
4300: for (i=n;i>=1;i--) {
4301: sum=b[i];
4302: for (j=i+1;j<=n;j++) sum -= a[i][j]*b[j];
4303: b[i]=sum/a[i][i];
4304: }
4305: }
4306:
4307: void pstamp(FILE *fichier)
4308: {
1.196 brouard 4309: fprintf(fichier,"# %s.%s\n#IMaCh version %s, %s\n#%s\n# %s", optionfilefiname,optionfilext,version,copyright, fullversion, strstart);
1.126 brouard 4310: }
4311:
1.253 brouard 4312:
4313:
1.126 brouard 4314: /************ Frequencies ********************/
1.251 brouard 4315: void freqsummary(char fileres[], double p[], double pstart[], int iagemin, int iagemax, int **s, double **agev, int nlstate, int imx, \
1.226 brouard 4316: int *Tvaraff, int *invalidvarcomb, int **nbcode, int *ncodemax,double **mint,double **anint, char strstart[], \
4317: int firstpass, int lastpass, int stepm, int weightopt, char model[])
1.250 brouard 4318: { /* Some frequencies as well as proposing some starting values */
1.226 brouard 4319:
1.265 brouard 4320: int i, m, jk, j1, bool, z1,j, nj, nl, k, iv, jj=0, s1=1, s2=1;
1.226 brouard 4321: int iind=0, iage=0;
4322: int mi; /* Effective wave */
4323: int first;
4324: double ***freq; /* Frequencies */
1.268 brouard 4325: 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 */
4326: 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 4327: double *meanq;
4328: double **meanqt;
4329: double *pp, **prop, *posprop, *pospropt;
4330: double pos=0., posproptt=0., pospropta=0., k2, dateintsum=0,k2cpt=0;
4331: char fileresp[FILENAMELENGTH], fileresphtm[FILENAMELENGTH], fileresphtmfr[FILENAMELENGTH];
4332: double agebegin, ageend;
4333:
4334: pp=vector(1,nlstate);
1.251 brouard 4335: prop=matrix(1,nlstate,iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.226 brouard 4336: posprop=vector(1,nlstate); /* Counting the number of transition starting from a live state per age */
4337: pospropt=vector(1,nlstate); /* Counting the number of transition starting from a live state */
4338: /* prop=matrix(1,nlstate,iagemin,iagemax+3); */
4339: meanq=vector(1,nqfveff); /* Number of Quantitative Fixed Variables Effective */
4340: meanqt=matrix(1,lastpass,1,nqtveff);
4341: strcpy(fileresp,"P_");
4342: strcat(fileresp,fileresu);
4343: /*strcat(fileresphtm,fileresu);*/
4344: if((ficresp=fopen(fileresp,"w"))==NULL) {
4345: printf("Problem with prevalence resultfile: %s\n", fileresp);
4346: fprintf(ficlog,"Problem with prevalence resultfile: %s\n", fileresp);
4347: exit(0);
4348: }
1.240 brouard 4349:
1.226 brouard 4350: strcpy(fileresphtm,subdirfext(optionfilefiname,"PHTM_",".htm"));
4351: if((ficresphtm=fopen(fileresphtm,"w"))==NULL) {
4352: printf("Problem with prevalence HTM resultfile '%s' with errno='%s'\n",fileresphtm,strerror(errno));
4353: fprintf(ficlog,"Problem with prevalence HTM resultfile '%s' with errno='%s'\n",fileresphtm,strerror(errno));
4354: fflush(ficlog);
4355: exit(70);
4356: }
4357: else{
4358: fprintf(ficresphtm,"<html><head>\n<title>IMaCh PHTM_ %s</title></head>\n <body><font size=\"2\">%s <br> %s</font> \
1.240 brouard 4359: <hr size=\"2\" color=\"#EC5E5E\"> \n \
1.214 brouard 4360: Title=%s <br>Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s<br>\n",\
1.226 brouard 4361: fileresphtm,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model);
4362: }
1.237 brouard 4363: 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 4364:
1.226 brouard 4365: strcpy(fileresphtmfr,subdirfext(optionfilefiname,"PHTMFR_",".htm"));
4366: if((ficresphtmfr=fopen(fileresphtmfr,"w"))==NULL) {
4367: printf("Problem with frequency table HTM resultfile '%s' with errno='%s'\n",fileresphtmfr,strerror(errno));
4368: fprintf(ficlog,"Problem with frequency table HTM resultfile '%s' with errno='%s'\n",fileresphtmfr,strerror(errno));
4369: fflush(ficlog);
4370: exit(70);
1.240 brouard 4371: } else{
1.226 brouard 4372: 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 4373: <hr size=\"2\" color=\"#EC5E5E\"> \n \
1.214 brouard 4374: Title=%s <br>Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s<br>\n",\
1.226 brouard 4375: fileresphtmfr,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model);
4376: }
1.240 brouard 4377: 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);
4378:
1.253 brouard 4379: y= vector(iagemin-AGEMARGE,iagemax+4+AGEMARGE);
4380: x= vector(iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.251 brouard 4381: freq= ma3x(-5,nlstate+ndeath,-5,nlstate+ndeath,iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.226 brouard 4382: j1=0;
1.126 brouard 4383:
1.227 brouard 4384: /* j=ncoveff; /\* Only fixed dummy covariates *\/ */
4385: j=cptcoveff; /* Only dummy covariates of the model */
1.226 brouard 4386: if (cptcovn<1) {j=1;ncodemax[1]=1;}
1.240 brouard 4387:
4388:
1.226 brouard 4389: /* Detects if a combination j1 is empty: for a multinomial variable like 3 education levels:
4390: reference=low_education V1=0,V2=0
4391: med_educ V1=1 V2=0,
4392: high_educ V1=0 V2=1
4393: Then V1=1 and V2=1 is a noisy combination that we want to exclude for the list 2**cptcoveff
4394: */
1.249 brouard 4395: dateintsum=0;
4396: k2cpt=0;
4397:
1.253 brouard 4398: if(cptcoveff == 0 )
1.265 brouard 4399: nl=1; /* Constant and age model only */
1.253 brouard 4400: else
4401: nl=2;
1.265 brouard 4402:
4403: /* if a constant only model, one pass to compute frequency tables and to write it on ficresp */
4404: /* Loop on nj=1 or 2 if dummy covariates j!=0
4405: * Loop on j1(1 to 2**cptcoveff) covariate combination
4406: * freq[s1][s2][iage] =0.
4407: * Loop on iind
4408: * ++freq[s1][s2][iage] weighted
4409: * end iind
4410: * if covariate and j!0
4411: * headers Variable on one line
4412: * endif cov j!=0
4413: * header of frequency table by age
4414: * Loop on age
4415: * pp[s1]+=freq[s1][s2][iage] weighted
4416: * pos+=freq[s1][s2][iage] weighted
4417: * Loop on s1 initial state
4418: * fprintf(ficresp
4419: * end s1
4420: * end age
4421: * if j!=0 computes starting values
4422: * end compute starting values
4423: * end j1
4424: * end nl
4425: */
1.253 brouard 4426: for (nj = 1; nj <= nl; nj++){ /* nj= 1 constant model, nl number of loops. */
4427: if(nj==1)
4428: j=0; /* First pass for the constant */
1.265 brouard 4429: else{
1.253 brouard 4430: j=cptcoveff; /* Other passes for the covariate values */
1.265 brouard 4431: }
1.251 brouard 4432: first=1;
1.265 brouard 4433: 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 4434: posproptt=0.;
4435: /*printf("cptcoveff=%d Tvaraff=%d", cptcoveff,Tvaraff[1]);
4436: scanf("%d", i);*/
4437: for (i=-5; i<=nlstate+ndeath; i++)
1.265 brouard 4438: for (s2=-5; s2<=nlstate+ndeath; s2++)
1.251 brouard 4439: for(m=iagemin; m <= iagemax+3; m++)
1.265 brouard 4440: freq[i][s2][m]=0;
1.251 brouard 4441:
4442: for (i=1; i<=nlstate; i++) {
1.240 brouard 4443: for(m=iagemin; m <= iagemax+3; m++)
1.251 brouard 4444: prop[i][m]=0;
4445: posprop[i]=0;
4446: pospropt[i]=0;
4447: }
4448: /* for (z1=1; z1<= nqfveff; z1++) { */
4449: /* meanq[z1]+=0.; */
4450: /* for(m=1;m<=lastpass;m++){ */
4451: /* meanqt[m][z1]=0.; */
4452: /* } */
4453: /* } */
4454:
4455: /* dateintsum=0; */
4456: /* k2cpt=0; */
4457:
1.265 brouard 4458: /* For that combination of covariates j1 (V4=1 V3=0 for example), we count and print the frequencies in one pass */
1.251 brouard 4459: for (iind=1; iind<=imx; iind++) { /* For each individual iind */
4460: bool=1;
4461: if(j !=0){
4462: if(anyvaryingduminmodel==0){ /* If All fixed covariates */
4463: if (cptcoveff >0) { /* Filter is here: Must be looked at for model=V1+V2+V3+V4 */
4464: /* for (z1=1; z1<= nqfveff; z1++) { */
4465: /* meanq[z1]+=coqvar[Tvar[z1]][iind]; /\* Computes mean of quantitative with selected filter *\/ */
4466: /* } */
4467: for (z1=1; z1<=cptcoveff; z1++) { /* loops on covariates in the model */
4468: /* if(Tvaraff[z1] ==-20){ */
4469: /* /\* sumnew+=cotvar[mw[mi][iind]][z1][iind]; *\/ */
4470: /* }else if(Tvaraff[z1] ==-10){ */
4471: /* /\* sumnew+=coqvar[z1][iind]; *\/ */
4472: /* }else */
4473: if (covar[Tvaraff[z1]][iind]!= nbcode[Tvaraff[z1]][codtabm(j1,z1)]){ /* for combination j1 of covariates */
1.265 brouard 4474: /* Tests if the value of the covariate z1 for this individual iind responded to combination j1 (V4=1 V3=0) */
1.251 brouard 4475: bool=0; /* bool should be equal to 1 to be selected, one covariate value failed */
4476: /* 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",
4477: bool,i,z1, z1, Tvaraff[z1],i,covar[Tvaraff[z1]][i],j1,z1,codtabm(j1,z1),
4478: j1,z1,nbcode[Tvaraff[z1]][codtabm(j1,z1)],j1);*/
4479: /* For j1=7 in V1+V2+V3+V4 = 0 1 1 0 and codtabm(7,3)=1 and nbcde[3][?]=1*/
4480: } /* Onlyf fixed */
4481: } /* end z1 */
4482: } /* cptcovn > 0 */
4483: } /* end any */
4484: }/* end j==0 */
1.265 brouard 4485: if (bool==1){ /* We selected an individual iind satisfying combination j1 (V4=1 V3=0) or all fixed covariates */
1.251 brouard 4486: /* for(m=firstpass; m<=lastpass; m++){ */
4487: for(mi=1; mi<wav[iind];mi++){ /* For that wave */
4488: m=mw[mi][iind];
4489: if(j!=0){
4490: if(anyvaryingduminmodel==1){ /* Some are varying covariates */
4491: for (z1=1; z1<=cptcoveff; z1++) {
4492: if( Fixed[Tmodelind[z1]]==1){
4493: iv= Tvar[Tmodelind[z1]]-ncovcol-nqv;
4494: if (cotvar[m][iv][iind]!= nbcode[Tvaraff[z1]][codtabm(j1,z1)]) /* iv=1 to ntv, right modality. If covariate's
4495: value is -1, we don't select. It differs from the
4496: constant and age model which counts them. */
4497: bool=0; /* not selected */
4498: }else if( Fixed[Tmodelind[z1]]== 0) { /* fixed */
4499: if (covar[Tvaraff[z1]][iind]!= nbcode[Tvaraff[z1]][codtabm(j1,z1)]) {
4500: bool=0;
4501: }
4502: }
4503: }
4504: }/* Some are varying covariates, we tried to speed up if all fixed covariates in the model, avoiding waves loop */
4505: } /* end j==0 */
4506: /* bool =0 we keep that guy which corresponds to the combination of dummy values */
4507: if(bool==1){
4508: /* dh[m][iind] or dh[mw[mi][iind]][iind] is the delay between two effective (mi) waves m=mw[mi][iind]
4509: and mw[mi+1][iind]. dh depends on stepm. */
4510: agebegin=agev[m][iind]; /* Age at beginning of wave before transition*/
4511: ageend=agev[m][iind]+(dh[m][iind])*stepm/YEARM; /* Age at end of wave and transition */
4512: if(m >=firstpass && m <=lastpass){
4513: k2=anint[m][iind]+(mint[m][iind]/12.);
4514: /*if ((k2>=dateprev1) && (k2<=dateprev2)) {*/
4515: if(agev[m][iind]==0) agev[m][iind]=iagemax+1; /* All ages equal to 0 are in iagemax+1 */
4516: if(agev[m][iind]==1) agev[m][iind]=iagemax+2; /* All ages equal to 1 are in iagemax+2 */
4517: if (s[m][iind]>0 && s[m][iind]<=nlstate) /* If status at wave m is known and a live state */
4518: prop[s[m][iind]][(int)agev[m][iind]] += weight[iind]; /* At age of beginning of transition, where status is known */
4519: if (m<lastpass) {
4520: /* if(s[m][iind]==4 && s[m+1][iind]==4) */
4521: /* 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]); */
4522: if(s[m][iind]==-1)
4523: 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.));
4524: freq[s[m][iind]][s[m+1][iind]][(int)agev[m][iind]] += weight[iind]; /* At age of beginning of transition, where status is known */
4525: /* if((int)agev[m][iind] == 55) */
4526: /* printf("j=%d, j1=%d Age %d, iind=%d, num=%09ld m=%d\n",j,j1,(int)agev[m][iind],iind, num[iind],m); */
4527: /* freq[s[m][iind]][s[m+1][iind]][(int)((agebegin+ageend)/2.)] += weight[iind]; */
4528: 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 4529: }
1.251 brouard 4530: } /* end if between passes */
4531: if ((agev[m][iind]>1) && (agev[m][iind]< (iagemax+3)) && (anint[m][iind]!=9999) && (mint[m][iind]!=99) && (j==0)) {
4532: dateintsum=dateintsum+k2; /* on all covariates ?*/
4533: k2cpt++;
4534: /* printf("iind=%ld dateintmean = %lf dateintsum=%lf k2cpt=%lf k2=%lf\n",iind, dateintsum/k2cpt, dateintsum,k2cpt, k2); */
1.234 brouard 4535: }
1.251 brouard 4536: }else{
4537: bool=1;
4538: }/* end bool 2 */
4539: } /* end m */
4540: } /* end bool */
4541: } /* end iind = 1 to imx */
4542: /* prop[s][age] is feeded for any initial and valid live state as well as
4543: freq[s1][s2][age] at single age of beginning the transition, for a combination j1 */
4544:
4545:
4546: /* fprintf(ficresp, "#Count between %.lf/%.lf/%.lf and %.lf/%.lf/%.lf\n",jprev1, mprev1,anprev1,jprev2, mprev2,anprev2);*/
1.265 brouard 4547: if(cptcoveff==0 && nj==1) /* no covariate and first pass */
4548: pstamp(ficresp);
1.251 brouard 4549: if (cptcoveff>0 && j!=0){
1.265 brouard 4550: pstamp(ficresp);
1.251 brouard 4551: printf( "\n#********** Variable ");
4552: fprintf(ficresp, "\n#********** Variable ");
4553: fprintf(ficresphtm, "\n<br/><br/><h3>********** Variable ");
4554: fprintf(ficresphtmfr, "\n<br/><br/><h3>********** Variable ");
4555: fprintf(ficlog, "\n#********** Variable ");
4556: for (z1=1; z1<=cptcoveff; z1++){
4557: if(!FixedV[Tvaraff[z1]]){
4558: printf( "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4559: fprintf(ficresp, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4560: fprintf(ficresphtm, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4561: fprintf(ficresphtmfr, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4562: fprintf(ficlog, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
1.250 brouard 4563: }else{
1.251 brouard 4564: printf( "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4565: fprintf(ficresp, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4566: fprintf(ficresphtm, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4567: fprintf(ficresphtmfr, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4568: fprintf(ficlog, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4569: }
4570: }
4571: printf( "**********\n#");
4572: fprintf(ficresp, "**********\n#");
4573: fprintf(ficresphtm, "**********</h3>\n");
4574: fprintf(ficresphtmfr, "**********</h3>\n");
4575: fprintf(ficlog, "**********\n");
4576: }
4577: fprintf(ficresphtm,"<table style=\"text-align:center; border: 1px solid\">");
1.265 brouard 4578: if((cptcoveff==0 && nj==1)|| nj==2 ) /* no covariate and first pass */
4579: fprintf(ficresp, " Age");
4580: 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 4581: for(i=1; i<=nlstate;i++) {
1.265 brouard 4582: if((cptcoveff==0 && nj==1)|| nj==2 ) fprintf(ficresp," Prev(%d) N(%d) N ",i,i);
1.251 brouard 4583: fprintf(ficresphtm, "<th>Age</th><th>Prev(%d)</th><th>N(%d)</th><th>N</th>",i,i);
4584: }
1.265 brouard 4585: if((cptcoveff==0 && nj==1)|| nj==2 ) fprintf(ficresp, "\n");
1.251 brouard 4586: fprintf(ficresphtm, "\n");
4587:
4588: /* Header of frequency table by age */
4589: fprintf(ficresphtmfr,"<table style=\"text-align:center; border: 1px solid\">");
4590: fprintf(ficresphtmfr,"<th>Age</th> ");
1.265 brouard 4591: for(s2=-1; s2 <=nlstate+ndeath; s2++){
1.251 brouard 4592: for(m=-1; m <=nlstate+ndeath; m++){
1.265 brouard 4593: if(s2!=0 && m!=0)
4594: fprintf(ficresphtmfr,"<th>%d%d</th> ",s2,m);
1.240 brouard 4595: }
1.226 brouard 4596: }
1.251 brouard 4597: fprintf(ficresphtmfr, "\n");
4598:
4599: /* For each age */
4600: for(iage=iagemin; iage <= iagemax+3; iage++){
4601: fprintf(ficresphtm,"<tr>");
4602: if(iage==iagemax+1){
4603: fprintf(ficlog,"1");
4604: fprintf(ficresphtmfr,"<tr><th>0</th> ");
4605: }else if(iage==iagemax+2){
4606: fprintf(ficlog,"0");
4607: fprintf(ficresphtmfr,"<tr><th>Unknown</th> ");
4608: }else if(iage==iagemax+3){
4609: fprintf(ficlog,"Total");
4610: fprintf(ficresphtmfr,"<tr><th>Total</th> ");
4611: }else{
1.240 brouard 4612: if(first==1){
1.251 brouard 4613: first=0;
4614: printf("See log file for details...\n");
4615: }
4616: fprintf(ficresphtmfr,"<tr><th>%d</th> ",iage);
4617: fprintf(ficlog,"Age %d", iage);
4618: }
1.265 brouard 4619: for(s1=1; s1 <=nlstate ; s1++){
4620: for(m=-1, pp[s1]=0; m <=nlstate+ndeath ; m++)
4621: pp[s1] += freq[s1][m][iage];
1.251 brouard 4622: }
1.265 brouard 4623: for(s1=1; s1 <=nlstate ; s1++){
1.251 brouard 4624: for(m=-1, pos=0; m <=0 ; m++)
1.265 brouard 4625: pos += freq[s1][m][iage];
4626: if(pp[s1]>=1.e-10){
1.251 brouard 4627: if(first==1){
1.265 brouard 4628: printf(" %d.=%.0f loss[%d]=%.1f%%",s1,pp[s1],s1,100*pos/pp[s1]);
1.251 brouard 4629: }
1.265 brouard 4630: fprintf(ficlog," %d.=%.0f loss[%d]=%.1f%%",s1,pp[s1],s1,100*pos/pp[s1]);
1.251 brouard 4631: }else{
4632: if(first==1)
1.265 brouard 4633: printf(" %d.=%.0f loss[%d]=NaNQ%%",s1,pp[s1],s1);
4634: fprintf(ficlog," %d.=%.0f loss[%d]=NaNQ%%",s1,pp[s1],s1);
1.240 brouard 4635: }
4636: }
4637:
1.265 brouard 4638: for(s1=1; s1 <=nlstate ; s1++){
4639: /* posprop[s1]=0; */
4640: for(m=0, pp[s1]=0; m <=nlstate+ndeath; m++)/* Summing on all ages */
4641: pp[s1] += freq[s1][m][iage];
4642: } /* pp[s1] is the total number of transitions starting from state s1 and any ending status until this age */
4643:
4644: for(s1=1,pos=0, pospropta=0.; s1 <=nlstate ; s1++){
4645: pos += pp[s1]; /* pos is the total number of transitions until this age */
4646: posprop[s1] += prop[s1][iage]; /* prop is the number of transitions from a live state
4647: from s1 at age iage prop[s[m][iind]][(int)agev[m][iind]] += weight[iind] */
4648: pospropta += prop[s1][iage]; /* prop is the number of transitions from a live state
4649: from s1 at age iage prop[s[m][iind]][(int)agev[m][iind]] += weight[iind] */
4650: }
4651:
4652: /* Writing ficresp */
4653: if(cptcoveff==0 && nj==1){ /* no covariate and first pass */
4654: if( iage <= iagemax){
4655: fprintf(ficresp," %d",iage);
4656: }
4657: }else if( nj==2){
4658: if( iage <= iagemax){
4659: fprintf(ficresp," %d",iage);
4660: for (z1=1; z1<=cptcoveff; z1++) fprintf(ficresp, " %d %d",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4661: }
1.240 brouard 4662: }
1.265 brouard 4663: for(s1=1; s1 <=nlstate ; s1++){
1.240 brouard 4664: if(pos>=1.e-5){
1.251 brouard 4665: if(first==1)
1.265 brouard 4666: printf(" %d.=%.0f prev[%d]=%.1f%%",s1,pp[s1],s1,100*pp[s1]/pos);
4667: fprintf(ficlog," %d.=%.0f prev[%d]=%.1f%%",s1,pp[s1],s1,100*pp[s1]/pos);
1.251 brouard 4668: }else{
4669: if(first==1)
1.265 brouard 4670: printf(" %d.=%.0f prev[%d]=NaNQ%%",s1,pp[s1],s1);
4671: fprintf(ficlog," %d.=%.0f prev[%d]=NaNQ%%",s1,pp[s1],s1);
1.251 brouard 4672: }
4673: if( iage <= iagemax){
4674: if(pos>=1.e-5){
1.265 brouard 4675: if(cptcoveff==0 && nj==1){ /* no covariate and first pass */
4676: fprintf(ficresp," %.5f %.0f %.0f",prop[s1][iage]/pospropta, prop[s1][iage],pospropta);
4677: }else if( nj==2){
4678: fprintf(ficresp," %.5f %.0f %.0f",prop[s1][iage]/pospropta, prop[s1][iage],pospropta);
4679: }
4680: fprintf(ficresphtm,"<th>%d</th><td>%.5f</td><td>%.0f</td><td>%.0f</td>",iage,prop[s1][iage]/pospropta, prop[s1][iage],pospropta);
4681: /*probs[iage][s1][j1]= pp[s1]/pos;*/
4682: /*printf("\niage=%d s1=%d j1=%d %.5f %.0f %.0f %f",iage,s1,j1,pp[s1]/pos, pp[s1],pos,probs[iage][s1][j1]);*/
4683: } else{
4684: if((cptcoveff==0 && nj==1)|| nj==2 ) fprintf(ficresp," NaNq %.0f %.0f",prop[s1][iage],pospropta);
4685: fprintf(ficresphtm,"<th>%d</th><td>NaNq</td><td>%.0f</td><td>%.0f</td>",iage, prop[s1][iage],pospropta);
1.251 brouard 4686: }
1.240 brouard 4687: }
1.265 brouard 4688: pospropt[s1] +=posprop[s1];
4689: } /* end loop s1 */
1.251 brouard 4690: /* pospropt=0.; */
1.265 brouard 4691: for(s1=-1; s1 <=nlstate+ndeath; s1++){
1.251 brouard 4692: for(m=-1; m <=nlstate+ndeath; m++){
1.265 brouard 4693: if(freq[s1][m][iage] !=0 ) { /* minimizing output */
1.251 brouard 4694: if(first==1){
1.265 brouard 4695: printf(" %d%d=%.0f",s1,m,freq[s1][m][iage]);
1.251 brouard 4696: }
1.265 brouard 4697: /* printf(" %d%d=%.0f",s1,m,freq[s1][m][iage]); */
4698: fprintf(ficlog," %d%d=%.0f",s1,m,freq[s1][m][iage]);
1.251 brouard 4699: }
1.265 brouard 4700: if(s1!=0 && m!=0)
4701: fprintf(ficresphtmfr,"<td>%.0f</td> ",freq[s1][m][iage]);
1.240 brouard 4702: }
1.265 brouard 4703: } /* end loop s1 */
1.251 brouard 4704: posproptt=0.;
1.265 brouard 4705: for(s1=1; s1 <=nlstate; s1++){
4706: posproptt += pospropt[s1];
1.251 brouard 4707: }
4708: fprintf(ficresphtmfr,"</tr>\n ");
1.265 brouard 4709: fprintf(ficresphtm,"</tr>\n");
4710: if((cptcoveff==0 && nj==1)|| nj==2 ) {
4711: if(iage <= iagemax)
4712: fprintf(ficresp,"\n");
1.240 brouard 4713: }
1.251 brouard 4714: if(first==1)
4715: printf("Others in log...\n");
4716: fprintf(ficlog,"\n");
4717: } /* end loop age iage */
1.265 brouard 4718:
1.251 brouard 4719: fprintf(ficresphtm,"<tr><th>Tot</th>");
1.265 brouard 4720: for(s1=1; s1 <=nlstate ; s1++){
1.251 brouard 4721: if(posproptt < 1.e-5){
1.265 brouard 4722: fprintf(ficresphtm,"<td>Nanq</td><td>%.0f</td><td>%.0f</td>",pospropt[s1],posproptt);
1.251 brouard 4723: }else{
1.265 brouard 4724: fprintf(ficresphtm,"<td>%.5f</td><td>%.0f</td><td>%.0f</td>",pospropt[s1]/posproptt,pospropt[s1],posproptt);
1.240 brouard 4725: }
1.226 brouard 4726: }
1.251 brouard 4727: fprintf(ficresphtm,"</tr>\n");
4728: fprintf(ficresphtm,"</table>\n");
4729: fprintf(ficresphtmfr,"</table>\n");
1.226 brouard 4730: if(posproptt < 1.e-5){
1.251 brouard 4731: fprintf(ficresphtm,"\n <p><b> This combination (%d) is not valid and no result will be produced</b></p>",j1);
4732: fprintf(ficresphtmfr,"\n <p><b> This combination (%d) is not valid and no result will be produced</b></p>",j1);
1.260 brouard 4733: fprintf(ficlog,"# This combination (%d) is not valid and no result will be produced\n",j1);
4734: printf("# This combination (%d) is not valid and no result will be produced\n",j1);
1.251 brouard 4735: invalidvarcomb[j1]=1;
1.226 brouard 4736: }else{
1.251 brouard 4737: fprintf(ficresphtm,"\n <p> This combination (%d) is valid and result will be produced.</p>",j1);
4738: invalidvarcomb[j1]=0;
1.226 brouard 4739: }
1.251 brouard 4740: fprintf(ficresphtmfr,"</table>\n");
4741: fprintf(ficlog,"\n");
4742: if(j!=0){
4743: printf("#Freqsummary: Starting values for combination j1=%d:\n", j1);
1.265 brouard 4744: for(i=1,s1=1; i <=nlstate; i++){
1.251 brouard 4745: for(k=1; k <=(nlstate+ndeath); k++){
4746: if (k != i) {
1.265 brouard 4747: for(jj=1; jj <=ncovmodel; jj++){ /* For counting s1 */
1.253 brouard 4748: if(jj==1){ /* Constant case (in fact cste + age) */
1.251 brouard 4749: if(j1==1){ /* All dummy covariates to zero */
4750: freq[i][k][iagemax+4]=freq[i][k][iagemax+3]; /* Stores case 0 0 0 */
4751: freq[i][i][iagemax+4]=freq[i][i][iagemax+3]; /* Stores case 0 0 0 */
1.252 brouard 4752: printf("%d%d ",i,k);
4753: fprintf(ficlog,"%d%d ",i,k);
1.265 brouard 4754: 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]));
4755: 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]));
4756: pstart[s1]= log(freq[i][k][iagemax+3]/freq[i][i][iagemax+3]);
1.251 brouard 4757: }
1.253 brouard 4758: }else if((j1==1) && (jj==2 || nagesqr==1)){ /* age or age*age parameter without covariate V4*age (to be done later) */
4759: for(iage=iagemin; iage <= iagemax+3; iage++){
4760: x[iage]= (double)iage;
4761: y[iage]= log(freq[i][k][iage]/freq[i][i][iage]);
1.265 brouard 4762: /* 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 4763: }
1.268 brouard 4764: /* Some are not finite, but linreg will ignore these ages */
4765: no=0;
1.253 brouard 4766: linreg(iagemin,iagemax,&no,x,y,&a,&b,&r, &sa, &sb ); /* y= a+b*x with standard errors */
1.265 brouard 4767: pstart[s1]=b;
4768: pstart[s1-1]=a;
1.252 brouard 4769: }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 */
4770: 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]);
4771: 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 4772: 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 4773: printf("%d%d ",i,k);
4774: fprintf(ficlog,"%d%d ",i,k);
1.265 brouard 4775: 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 4776: }else{ /* Other cases, like quantitative fixed or varying covariates */
4777: ;
4778: }
4779: /* printf("%12.7f )", param[i][jj][k]); */
4780: /* fprintf(ficlog,"%12.7f )", param[i][jj][k]); */
1.265 brouard 4781: s1++;
1.251 brouard 4782: } /* end jj */
4783: } /* end k!= i */
4784: } /* end k */
1.265 brouard 4785: } /* end i, s1 */
1.251 brouard 4786: } /* end j !=0 */
4787: } /* end selected combination of covariate j1 */
4788: if(j==0){ /* We can estimate starting values from the occurences in each case */
4789: printf("#Freqsummary: Starting values for the constants:\n");
4790: fprintf(ficlog,"\n");
1.265 brouard 4791: for(i=1,s1=1; i <=nlstate; i++){
1.251 brouard 4792: for(k=1; k <=(nlstate+ndeath); k++){
4793: if (k != i) {
4794: printf("%d%d ",i,k);
4795: fprintf(ficlog,"%d%d ",i,k);
4796: for(jj=1; jj <=ncovmodel; jj++){
1.265 brouard 4797: pstart[s1]=p[s1]; /* Setting pstart to p values by default */
1.253 brouard 4798: if(jj==1){ /* Age has to be done */
1.265 brouard 4799: pstart[s1]= log(freq[i][k][iagemax+3]/freq[i][i][iagemax+3]);
4800: 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]));
4801: 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 4802: }
4803: /* printf("%12.7f )", param[i][jj][k]); */
4804: /* fprintf(ficlog,"%12.7f )", param[i][jj][k]); */
1.265 brouard 4805: s1++;
1.250 brouard 4806: }
1.251 brouard 4807: printf("\n");
4808: fprintf(ficlog,"\n");
1.250 brouard 4809: }
4810: }
4811: }
1.251 brouard 4812: printf("#Freqsummary\n");
4813: fprintf(ficlog,"\n");
1.265 brouard 4814: for(s1=-1; s1 <=nlstate+ndeath; s1++){
4815: for(s2=-1; s2 <=nlstate+ndeath; s2++){
4816: /* param[i]|j][k]= freq[s1][s2][iagemax+3] */
4817: printf(" %d%d=%.0f",s1,s2,freq[s1][s2][iagemax+3]);
4818: fprintf(ficlog," %d%d=%.0f",s1,s2,freq[s1][s2][iagemax+3]);
4819: /* if(freq[s1][s2][iage] !=0 ) { /\* minimizing output *\/ */
4820: /* printf(" %d%d=%.0f",s1,s2,freq[s1][s2][iagemax+3]); */
4821: /* fprintf(ficlog," %d%d=%.0f",s1,s2,freq[s1][s2][iagemax+3]); */
1.251 brouard 4822: /* } */
4823: }
1.265 brouard 4824: } /* end loop s1 */
1.251 brouard 4825:
4826: printf("\n");
4827: fprintf(ficlog,"\n");
4828: } /* end j=0 */
1.249 brouard 4829: } /* end j */
1.252 brouard 4830:
1.253 brouard 4831: if(mle == -2){ /* We want to use these values as starting values */
1.252 brouard 4832: for(i=1, jk=1; i <=nlstate; i++){
4833: for(j=1; j <=nlstate+ndeath; j++){
4834: if(j!=i){
4835: /*ca[0]= k+'a'-1;ca[1]='\0';*/
4836: printf("%1d%1d",i,j);
4837: fprintf(ficparo,"%1d%1d",i,j);
4838: for(k=1; k<=ncovmodel;k++){
4839: /* printf(" %lf",param[i][j][k]); */
4840: /* fprintf(ficparo," %lf",param[i][j][k]); */
4841: p[jk]=pstart[jk];
4842: printf(" %f ",pstart[jk]);
4843: fprintf(ficparo," %f ",pstart[jk]);
4844: jk++;
4845: }
4846: printf("\n");
4847: fprintf(ficparo,"\n");
4848: }
4849: }
4850: }
4851: } /* end mle=-2 */
1.226 brouard 4852: dateintmean=dateintsum/k2cpt;
1.240 brouard 4853:
1.226 brouard 4854: fclose(ficresp);
4855: fclose(ficresphtm);
4856: fclose(ficresphtmfr);
4857: free_vector(meanq,1,nqfveff);
4858: free_matrix(meanqt,1,lastpass,1,nqtveff);
1.253 brouard 4859: free_vector(x, iagemin-AGEMARGE, iagemax+4+AGEMARGE);
4860: free_vector(y, iagemin-AGEMARGE, iagemax+4+AGEMARGE);
1.251 brouard 4861: free_ma3x(freq,-5,nlstate+ndeath,-5,nlstate+ndeath, iagemin-AGEMARGE, iagemax+4+AGEMARGE);
1.226 brouard 4862: free_vector(pospropt,1,nlstate);
4863: free_vector(posprop,1,nlstate);
1.251 brouard 4864: free_matrix(prop,1,nlstate,iagemin-AGEMARGE, iagemax+4+AGEMARGE);
1.226 brouard 4865: free_vector(pp,1,nlstate);
4866: /* End of freqsummary */
4867: }
1.126 brouard 4868:
1.268 brouard 4869: /* Simple linear regression */
4870: int linreg(int ifi, int ila, int *no, const double x[], const double y[], double* a, double* b, double* r, double* sa, double * sb) {
4871:
4872: /* y=a+bx regression */
4873: double sumx = 0.0; /* sum of x */
4874: double sumx2 = 0.0; /* sum of x**2 */
4875: double sumxy = 0.0; /* sum of x * y */
4876: double sumy = 0.0; /* sum of y */
4877: double sumy2 = 0.0; /* sum of y**2 */
4878: double sume2 = 0.0; /* sum of square or residuals */
4879: double yhat;
4880:
4881: double denom=0;
4882: int i;
4883: int ne=*no;
4884:
4885: for ( i=ifi, ne=0;i<=ila;i++) {
4886: if(!isfinite(x[i]) || !isfinite(y[i])){
4887: /* printf(" x[%d]=%f, y[%d]=%f\n",i,x[i],i,y[i]); */
4888: continue;
4889: }
4890: ne=ne+1;
4891: sumx += x[i];
4892: sumx2 += x[i]*x[i];
4893: sumxy += x[i] * y[i];
4894: sumy += y[i];
4895: sumy2 += y[i]*y[i];
4896: denom = (ne * sumx2 - sumx*sumx);
4897: /* 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); */
4898: }
4899:
4900: denom = (ne * sumx2 - sumx*sumx);
4901: if (denom == 0) {
4902: // vertical, slope m is infinity
4903: *b = INFINITY;
4904: *a = 0;
4905: if (r) *r = 0;
4906: return 1;
4907: }
4908:
4909: *b = (ne * sumxy - sumx * sumy) / denom;
4910: *a = (sumy * sumx2 - sumx * sumxy) / denom;
4911: if (r!=NULL) {
4912: *r = (sumxy - sumx * sumy / ne) / /* compute correlation coeff */
4913: sqrt((sumx2 - sumx*sumx/ne) *
4914: (sumy2 - sumy*sumy/ne));
4915: }
4916: *no=ne;
4917: for ( i=ifi, ne=0;i<=ila;i++) {
4918: if(!isfinite(x[i]) || !isfinite(y[i])){
4919: /* printf(" x[%d]=%f, y[%d]=%f\n",i,x[i],i,y[i]); */
4920: continue;
4921: }
4922: ne=ne+1;
4923: yhat = y[i] - *a -*b* x[i];
4924: sume2 += yhat * yhat ;
4925:
4926: denom = (ne * sumx2 - sumx*sumx);
4927: /* 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); */
4928: }
4929: *sb = sqrt(sume2/(double)(ne-2)/(sumx2 - sumx * sumx /(double)ne));
4930: *sa= *sb * sqrt(sumx2/ne);
4931:
4932: return 0;
4933: }
4934:
1.126 brouard 4935: /************ Prevalence ********************/
1.227 brouard 4936: 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)
4937: {
4938: /* Compute observed prevalence between dateprev1 and dateprev2 by counting the number of people
4939: in each health status at the date of interview (if between dateprev1 and dateprev2).
4940: We still use firstpass and lastpass as another selection.
4941: */
1.126 brouard 4942:
1.227 brouard 4943: int i, m, jk, j1, bool, z1,j, iv;
4944: int mi; /* Effective wave */
4945: int iage;
4946: double agebegin, ageend;
4947:
4948: double **prop;
4949: double posprop;
4950: double y2; /* in fractional years */
4951: int iagemin, iagemax;
4952: int first; /** to stop verbosity which is redirected to log file */
4953:
4954: iagemin= (int) agemin;
4955: iagemax= (int) agemax;
4956: /*pp=vector(1,nlstate);*/
1.251 brouard 4957: prop=matrix(1,nlstate,iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.227 brouard 4958: /* freq=ma3x(-1,nlstate+ndeath,-1,nlstate+ndeath,iagemin,iagemax+3);*/
4959: j1=0;
1.222 brouard 4960:
1.227 brouard 4961: /*j=cptcoveff;*/
4962: if (cptcovn<1) {j=1;ncodemax[1]=1;}
1.222 brouard 4963:
1.227 brouard 4964: first=1;
4965: for(j1=1; j1<= (int) pow(2,cptcoveff);j1++){ /* For each combination of covariate */
4966: for (i=1; i<=nlstate; i++)
1.251 brouard 4967: for(iage=iagemin-AGEMARGE; iage <= iagemax+4+AGEMARGE; iage++)
1.227 brouard 4968: prop[i][iage]=0.0;
4969: printf("Prevalence combination of varying and fixed dummies %d\n",j1);
4970: /* fprintf(ficlog," V%d=%d ",Tvaraff[j1],nbcode[Tvaraff[j1]][codtabm(k,j1)]); */
4971: fprintf(ficlog,"Prevalence combination of varying and fixed dummies %d\n",j1);
4972:
4973: for (i=1; i<=imx; i++) { /* Each individual */
4974: bool=1;
4975: /* for(m=firstpass; m<=lastpass; m++){/\* Other selection (we can limit to certain interviews*\/ */
4976: for(mi=1; mi<wav[i];mi++){ /* For this wave too look where individual can be counted V4=0 V3=0 */
4977: m=mw[mi][i];
4978: /* Tmodelind[z1]=k is the position of the varying covariate in the model, but which # within 1 to ntv? */
4979: /* Tvar[Tmodelind[z1]] is the n of Vn; n-ncovcol-nqv is the first time varying covariate or iv */
4980: for (z1=1; z1<=cptcoveff; z1++){
4981: if( Fixed[Tmodelind[z1]]==1){
4982: iv= Tvar[Tmodelind[z1]]-ncovcol-nqv;
4983: if (cotvar[m][iv][i]!= nbcode[Tvaraff[z1]][codtabm(j1,z1)]) /* iv=1 to ntv, right modality */
4984: bool=0;
4985: }else if( Fixed[Tmodelind[z1]]== 0) /* fixed */
4986: if (covar[Tvaraff[z1]][i]!= nbcode[Tvaraff[z1]][codtabm(j1,z1)]) {
4987: bool=0;
4988: }
4989: }
4990: if(bool==1){ /* Otherwise we skip that wave/person */
4991: agebegin=agev[m][i]; /* Age at beginning of wave before transition*/
4992: /* ageend=agev[m][i]+(dh[m][i])*stepm/YEARM; /\* Age at end of wave and transition *\/ */
4993: if(m >=firstpass && m <=lastpass){
4994: y2=anint[m][i]+(mint[m][i]/12.); /* Fractional date in year */
4995: if ((y2>=dateprev1) && (y2<=dateprev2)) { /* Here is the main selection (fractional years) */
4996: if(agev[m][i]==0) agev[m][i]=iagemax+1;
4997: if(agev[m][i]==1) agev[m][i]=iagemax+2;
1.251 brouard 4998: if((int)agev[m][i] <iagemin-AGEMARGE || (int)agev[m][i] >iagemax+4+AGEMARGE){
1.227 brouard 4999: 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);
5000: exit(1);
5001: }
5002: if (s[m][i]>0 && s[m][i]<=nlstate) {
5003: /*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]]);*/
5004: prop[s[m][i]][(int)agev[m][i]] += weight[i];/* At age of beginning of transition, where status is known */
5005: prop[s[m][i]][iagemax+3] += weight[i];
5006: } /* end valid statuses */
5007: } /* end selection of dates */
5008: } /* end selection of waves */
5009: } /* end bool */
5010: } /* end wave */
5011: } /* end individual */
5012: for(i=iagemin; i <= iagemax+3; i++){
5013: for(jk=1,posprop=0; jk <=nlstate ; jk++) {
5014: posprop += prop[jk][i];
5015: }
5016:
5017: for(jk=1; jk <=nlstate ; jk++){
5018: if( i <= iagemax){
5019: if(posprop>=1.e-5){
5020: probs[i][jk][j1]= prop[jk][i]/posprop;
5021: } else{
5022: if(first==1){
5023: first=0;
1.266 brouard 5024: 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]);
5025: 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]);
5026: }else{
5027: 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 5028: }
5029: }
5030: }
5031: }/* end jk */
5032: }/* end i */
1.222 brouard 5033: /*} *//* end i1 */
1.227 brouard 5034: } /* end j1 */
1.222 brouard 5035:
1.227 brouard 5036: /* free_ma3x(freq,-1,nlstate+ndeath,-1,nlstate+ndeath, iagemin, iagemax+3);*/
5037: /*free_vector(pp,1,nlstate);*/
1.251 brouard 5038: free_matrix(prop,1,nlstate, iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.227 brouard 5039: } /* End of prevalence */
1.126 brouard 5040:
5041: /************* Waves Concatenation ***************/
5042:
5043: 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)
5044: {
5045: /* Concatenates waves: wav[i] is the number of effective (useful waves) of individual i.
5046: Death is a valid wave (if date is known).
5047: mw[mi][i] is the mi (mi=1 to wav[i]) effective wave of individual i
5048: dh[m][i] or dh[mw[mi][i]][i] is the delay between two effective waves m=mw[mi][i]
5049: and mw[mi+1][i]. dh depends on stepm.
1.227 brouard 5050: */
1.126 brouard 5051:
1.224 brouard 5052: int i=0, mi=0, m=0, mli=0;
1.126 brouard 5053: /* int j, k=0,jk, ju, jl,jmin=1e+5, jmax=-1;
5054: double sum=0., jmean=0.;*/
1.224 brouard 5055: int first=0, firstwo=0, firsthree=0, firstfour=0, firstfiv=0;
1.126 brouard 5056: int j, k=0,jk, ju, jl;
5057: double sum=0.;
5058: first=0;
1.214 brouard 5059: firstwo=0;
1.217 brouard 5060: firsthree=0;
1.218 brouard 5061: firstfour=0;
1.164 brouard 5062: jmin=100000;
1.126 brouard 5063: jmax=-1;
5064: jmean=0.;
1.224 brouard 5065:
5066: /* Treating live states */
1.214 brouard 5067: for(i=1; i<=imx; i++){ /* For simple cases and if state is death */
1.224 brouard 5068: mi=0; /* First valid wave */
1.227 brouard 5069: mli=0; /* Last valid wave */
1.126 brouard 5070: m=firstpass;
1.214 brouard 5071: while(s[m][i] <= nlstate){ /* a live state */
1.227 brouard 5072: 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 */
5073: mli=m-1;/* mw[++mi][i]=m-1; */
5074: }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 */
5075: mw[++mi][i]=m;
5076: mli=m;
1.224 brouard 5077: } /* else might be a useless wave -1 and mi is not incremented and mw[mi] not updated */
5078: if(m < lastpass){ /* m < lastpass, standard case */
1.227 brouard 5079: m++; /* mi gives the "effective" current wave, m the current wave, go to next wave by incrementing m */
1.216 brouard 5080: }
1.227 brouard 5081: else{ /* m >= lastpass, eventual special issue with warning */
1.224 brouard 5082: #ifdef UNKNOWNSTATUSNOTCONTRIBUTING
1.227 brouard 5083: break;
1.224 brouard 5084: #else
1.227 brouard 5085: if(s[m][i]==-1 && (int) andc[i] == 9999 && (int)anint[m][i] != 9999){
5086: if(firsthree == 0){
1.262 brouard 5087: 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 5088: firsthree=1;
5089: }
1.262 brouard 5090: 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 5091: mw[++mi][i]=m;
5092: mli=m;
5093: }
5094: if(s[m][i]==-2){ /* Vital status is really unknown */
5095: nbwarn++;
5096: if((int)anint[m][i] == 9999){ /* Has the vital status really been verified? */
5097: 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);
5098: 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);
5099: }
5100: break;
5101: }
5102: break;
1.224 brouard 5103: #endif
1.227 brouard 5104: }/* End m >= lastpass */
1.126 brouard 5105: }/* end while */
1.224 brouard 5106:
1.227 brouard 5107: /* 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 5108: /* After last pass */
1.224 brouard 5109: /* Treating death states */
1.214 brouard 5110: if (s[m][i] > nlstate){ /* In a death state */
1.227 brouard 5111: /* if( mint[m][i]==mdc[m][i] && anint[m][i]==andc[m][i]){ /\* same date of death and date of interview *\/ */
5112: /* } */
1.126 brouard 5113: mi++; /* Death is another wave */
5114: /* if(mi==0) never been interviewed correctly before death */
1.227 brouard 5115: /* Only death is a correct wave */
1.126 brouard 5116: mw[mi][i]=m;
1.257 brouard 5117: } /* else not in a death state */
1.224 brouard 5118: #ifndef DISPATCHINGKNOWNDEATHAFTERLASTWAVE
1.257 brouard 5119: else if ((int) andc[i] != 9999) { /* Date of death is known */
1.218 brouard 5120: if ((int)anint[m][i]!= 9999) { /* date of last interview is known */
1.227 brouard 5121: 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 */
5122: nbwarn++;
5123: if(firstfiv==0){
5124: 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 );
5125: firstfiv=1;
5126: }else{
5127: 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 );
5128: }
5129: }else{ /* Death occured afer last wave potential bias */
5130: nberr++;
5131: if(firstwo==0){
1.257 brouard 5132: 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 5133: firstwo=1;
5134: }
1.257 brouard 5135: 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 5136: }
1.257 brouard 5137: }else{ /* if date of interview is unknown */
1.227 brouard 5138: /* death is known but not confirmed by death status at any wave */
5139: if(firstfour==0){
5140: 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 );
5141: firstfour=1;
5142: }
5143: 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 5144: }
1.224 brouard 5145: } /* end if date of death is known */
5146: #endif
5147: wav[i]=mi; /* mi should be the last effective wave (or mli) */
5148: /* wav[i]=mw[mi][i]; */
1.126 brouard 5149: if(mi==0){
5150: nbwarn++;
5151: if(first==0){
1.227 brouard 5152: printf("Warning! No valid information for individual %ld line=%d (skipped) and may be others, see log file\n",num[i],i);
5153: first=1;
1.126 brouard 5154: }
5155: if(first==1){
1.227 brouard 5156: fprintf(ficlog,"Warning! No valid information for individual %ld line=%d (skipped)\n",num[i],i);
1.126 brouard 5157: }
5158: } /* end mi==0 */
5159: } /* End individuals */
1.214 brouard 5160: /* wav and mw are no more changed */
1.223 brouard 5161:
1.214 brouard 5162:
1.126 brouard 5163: for(i=1; i<=imx; i++){
5164: for(mi=1; mi<wav[i];mi++){
5165: if (stepm <=0)
1.227 brouard 5166: dh[mi][i]=1;
1.126 brouard 5167: else{
1.260 brouard 5168: if (s[mw[mi+1][i]][i] > nlstate) { /* A death, but what if date is unknown? */
1.227 brouard 5169: if (agedc[i] < 2*AGESUP) {
5170: j= rint(agedc[i]*12-agev[mw[mi][i]][i]*12);
5171: if(j==0) j=1; /* Survives at least one month after exam */
5172: else if(j<0){
5173: nberr++;
5174: 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]);
5175: j=1; /* Temporary Dangerous patch */
5176: 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);
5177: 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]);
5178: 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);
5179: }
5180: k=k+1;
5181: if (j >= jmax){
5182: jmax=j;
5183: ijmax=i;
5184: }
5185: if (j <= jmin){
5186: jmin=j;
5187: ijmin=i;
5188: }
5189: sum=sum+j;
5190: /*if (j<0) printf("j=%d num=%d \n",j,i);*/
5191: /* printf("%d %d %d %d\n", s[mw[mi][i]][i] ,s[mw[mi+1][i]][i],j,i);*/
5192: }
5193: }
5194: else{
5195: j= rint( (agev[mw[mi+1][i]][i]*12 - agev[mw[mi][i]][i]*12));
1.126 brouard 5196: /* 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 5197:
1.227 brouard 5198: k=k+1;
5199: if (j >= jmax) {
5200: jmax=j;
5201: ijmax=i;
5202: }
5203: else if (j <= jmin){
5204: jmin=j;
5205: ijmin=i;
5206: }
5207: /* if (j<10) printf("j=%d jmin=%d num=%d ",j,jmin,i); */
5208: /*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]);*/
5209: if(j<0){
5210: nberr++;
5211: 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]);
5212: 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]);
5213: }
5214: sum=sum+j;
5215: }
5216: jk= j/stepm;
5217: jl= j -jk*stepm;
5218: ju= j -(jk+1)*stepm;
5219: if(mle <=1){ /* only if we use a the linear-interpoloation pseudo-likelihood */
5220: if(jl==0){
5221: dh[mi][i]=jk;
5222: bh[mi][i]=0;
5223: }else{ /* We want a negative bias in order to only have interpolation ie
5224: * to avoid the price of an extra matrix product in likelihood */
5225: dh[mi][i]=jk+1;
5226: bh[mi][i]=ju;
5227: }
5228: }else{
5229: if(jl <= -ju){
5230: dh[mi][i]=jk;
5231: bh[mi][i]=jl; /* bias is positive if real duration
5232: * is higher than the multiple of stepm and negative otherwise.
5233: */
5234: }
5235: else{
5236: dh[mi][i]=jk+1;
5237: bh[mi][i]=ju;
5238: }
5239: if(dh[mi][i]==0){
5240: dh[mi][i]=1; /* At least one step */
5241: bh[mi][i]=ju; /* At least one step */
5242: /* 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);*/
5243: }
5244: } /* end if mle */
1.126 brouard 5245: }
5246: } /* end wave */
5247: }
5248: jmean=sum/k;
5249: 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 5250: 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 5251: }
1.126 brouard 5252:
5253: /*********** Tricode ****************************/
1.220 brouard 5254: void tricode(int *cptcov, int *Tvar, int **nbcode, int imx, int *Ndum)
1.242 brouard 5255: {
5256: /**< Uses cptcovn+2*cptcovprod as the number of covariates */
5257: /* Tvar[i]=atoi(stre); find 'n' in Vn and stores in Tvar. If model=V2+V1 Tvar[1]=2 and Tvar[2]=1
5258: * Boring subroutine which should only output nbcode[Tvar[j]][k]
5259: * Tvar[5] in V2+V1+V3*age+V2*V4 is 4 (V4) even it is a time varying or quantitative variable
5260: * nbcode[Tvar[5]][1]= nbcode[4][1]=0, nbcode[4][2]=1 (usually);
5261: */
1.130 brouard 5262:
1.242 brouard 5263: int ij=1, k=0, j=0, i=0, maxncov=NCOVMAX;
5264: int modmaxcovj=0; /* Modality max of covariates j */
5265: int cptcode=0; /* Modality max of covariates j */
5266: int modmincovj=0; /* Modality min of covariates j */
1.145 brouard 5267:
5268:
1.242 brouard 5269: /* cptcoveff=0; */
5270: /* *cptcov=0; */
1.126 brouard 5271:
1.242 brouard 5272: for (k=1; k <= maxncov; k++) ncodemax[k]=0; /* Horrible constant again replaced by NCOVMAX */
1.126 brouard 5273:
1.242 brouard 5274: /* Loop on covariates without age and products and no quantitative variable */
5275: /* for (j=1; j<=(cptcovs); j++) { /\* From model V1 + V2*age+ V3 + V3*V4 keeps V1 + V3 = 2 only *\/ */
5276: for (k=1; k<=cptcovt; k++) { /* From model V1 + V2*age + V3 + V3*V4 keeps V1 + V3 = 2 only */
5277: for (j=-1; (j < maxncov); j++) Ndum[j]=0;
5278: if(Dummy[k]==0 && Typevar[k] !=1){ /* Dummy covariate and not age product */
5279: switch(Fixed[k]) {
5280: case 0: /* Testing on fixed dummy covariate, simple or product of fixed */
5281: 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*/
5282: ij=(int)(covar[Tvar[k]][i]);
5283: /* ij=0 or 1 or -1. Value of the covariate Tvar[j] for individual i
5284: * If product of Vn*Vm, still boolean *:
5285: * If it was coded 1, 2, 3, 4 should be splitted into 3 boolean variables
5286: * 1 => 0 0 0, 2 => 0 0 1, 3 => 0 1 1, 4=1 0 0 */
5287: /* Finds for covariate j, n=Tvar[j] of Vn . ij is the
5288: modality of the nth covariate of individual i. */
5289: if (ij > modmaxcovj)
5290: modmaxcovj=ij;
5291: else if (ij < modmincovj)
5292: modmincovj=ij;
5293: if ((ij < -1) && (ij > NCOVMAX)){
5294: printf( "Error: minimal is less than -1 or maximal is bigger than %d. Exiting. \n", NCOVMAX );
5295: exit(1);
5296: }else
5297: Ndum[ij]++; /*counts and stores the occurence of this modality 0, 1, -1*/
5298: /* If coded 1, 2, 3 , counts the number of 1 Ndum[1], number of 2, Ndum[2], etc */
5299: /*printf("i=%d ij=%d Ndum[ij]=%d imx=%d",i,ij,Ndum[ij],imx);*/
5300: /* getting the maximum value of the modality of the covariate
5301: (should be 0 or 1 now) Tvar[j]. If V=sex and male is coded 0 and
5302: female ies 1, then modmaxcovj=1.
5303: */
5304: } /* end for loop on individuals i */
5305: printf(" Minimal and maximal values of %d th (fixed) covariate V%d: min=%d max=%d \n", k, Tvar[k], modmincovj, modmaxcovj);
5306: fprintf(ficlog," Minimal and maximal values of %d th (fixed) covariate V%d: min=%d max=%d \n", k, Tvar[k], modmincovj, modmaxcovj);
5307: cptcode=modmaxcovj;
5308: /* Ndum[0] = frequency of 0 for model-covariate j, Ndum[1] frequency of 1 etc. */
5309: /*for (i=0; i<=cptcode; i++) {*/
5310: for (j=modmincovj; j<=modmaxcovj; j++) { /* j=-1 ? 0 and 1*//* For each value j of the modality of model-cov k */
5311: printf("Frequencies of (fixed) covariate %d ie V%d with value %d: %d\n", k, Tvar[k], j, Ndum[j]);
5312: fprintf(ficlog, "Frequencies of (fixed) covariate %d ie V%d with value %d: %d\n", k, Tvar[k], j, Ndum[j]);
5313: if( Ndum[j] != 0 ){ /* Counts if nobody answered modality j ie empty modality, we skip it and reorder */
5314: if( j != -1){
5315: ncodemax[k]++; /* ncodemax[k]= Number of modalities of the k th
5316: covariate for which somebody answered excluding
5317: undefined. Usually 2: 0 and 1. */
5318: }
5319: ncodemaxwundef[k]++; /* ncodemax[j]= Number of modalities of the k th
5320: covariate for which somebody answered including
5321: undefined. Usually 3: -1, 0 and 1. */
5322: } /* In fact ncodemax[k]=2 (dichotom. variables only) but it could be more for
5323: * historical reasons: 3 if coded 1, 2, 3 and 4 and Ndum[2]=0 */
5324: } /* Ndum[-1] number of undefined modalities */
1.231 brouard 5325:
1.242 brouard 5326: /* j is a covariate, n=Tvar[j] of Vn; Fills nbcode */
5327: /* For covariate j, modalities could be 1, 2, 3, 4, 5, 6, 7. */
5328: /* If Ndum[1]=0, Ndum[2]=0, Ndum[3]= 635, Ndum[4]=0, Ndum[5]=0, Ndum[6]=27, Ndum[7]=125; */
5329: /* modmincovj=3; modmaxcovj = 7; */
5330: /* There are only 3 modalities non empty 3, 6, 7 (or 2 if 27 is too few) : ncodemax[j]=3; */
5331: /* which will be coded 0, 1, 2 which in binary on 2=3-1 digits are 0=00 1=01, 2=10; */
5332: /* defining two dummy variables: variables V1_1 and V1_2.*/
5333: /* nbcode[Tvar[j]][ij]=k; */
5334: /* nbcode[Tvar[j]][1]=0; */
5335: /* nbcode[Tvar[j]][2]=1; */
5336: /* nbcode[Tvar[j]][3]=2; */
5337: /* To be continued (not working yet). */
5338: ij=0; /* ij is similar to i but can jump over null modalities */
5339: 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*/
5340: if (Ndum[i] == 0) { /* If nobody responded to this modality k */
5341: break;
5342: }
5343: ij++;
5344: 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*/
5345: cptcode = ij; /* New max modality for covar j */
5346: } /* end of loop on modality i=-1 to 1 or more */
5347: break;
5348: case 1: /* Testing on varying covariate, could be simple and
5349: * should look at waves or product of fixed *
5350: * varying. No time to test -1, assuming 0 and 1 only */
5351: ij=0;
5352: for(i=0; i<=1;i++){
5353: nbcode[Tvar[k]][++ij]=i;
5354: }
5355: break;
5356: default:
5357: break;
5358: } /* end switch */
5359: } /* end dummy test */
5360:
5361: /* for (k=0; k<= cptcode; k++) { /\* k=-1 ? k=0 to 1 *\//\* Could be 1 to 4 *\//\* cptcode=modmaxcovj *\/ */
5362: /* /\*recode from 0 *\/ */
5363: /* k is a modality. If we have model=V1+V1*sex */
5364: /* then: nbcode[1][1]=0 ; nbcode[1][2]=1; nbcode[2][1]=0 ; nbcode[2][2]=1; */
5365: /* But if some modality were not used, it is recoded from 0 to a newer modmaxcovj=cptcode *\/ */
5366: /* } */
5367: /* /\* cptcode = ij; *\/ /\* New max modality for covar j *\/ */
5368: /* if (ij > ncodemax[j]) { */
5369: /* printf( " Error ij=%d > ncodemax[%d]=%d\n", ij, j, ncodemax[j]); */
5370: /* fprintf(ficlog, " Error ij=%d > ncodemax[%d]=%d\n", ij, j, ncodemax[j]); */
5371: /* break; */
5372: /* } */
5373: /* } /\* end of loop on modality k *\/ */
5374: } /* end of loop on model-covariate j. nbcode[Tvarj][1]=0 and nbcode[Tvarj][2]=1 sets the value of covariate j*/
5375:
5376: for (k=-1; k< maxncov; k++) Ndum[k]=0;
5377: /* Look at fixed dummy (single or product) covariates to check empty modalities */
5378: for (i=1; i<=ncovmodel-2-nagesqr; i++) { /* -2, cste and age and eventually age*age */
5379: /* Listing of all covariables in statement model to see if some covariates appear twice. For example, V1 appears twice in V1+V1*V2.*/
5380: 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 */
5381: 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 */
5382: /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, {2, 1, 1, 1, 2, 1, 1, 0, 0} */
5383: } /* V4+V3+V5, Ndum[1]@5={0, 0, 1, 1, 1} */
5384:
5385: ij=0;
5386: /* for (i=0; i<= maxncov-1; i++) { /\* modmaxcovj is unknown here. Only Ndum[2(V2),3(age*V3), 5(V3*V2) 6(V1*V4) *\/ */
5387: for (k=1; k<= cptcovt; k++) { /* modmaxcovj is unknown here. Only Ndum[2(V2),3(age*V3), 5(V3*V2) 6(V1*V4) */
5388: /*printf("Ndum[%d]=%d\n",i, Ndum[i]);*/
5389: /* if((Ndum[i]!=0) && (i<=ncovcol)){ /\* Tvar[i] <= ncovmodel ? *\/ */
5390: if(Ndum[Tvar[k]]!=0 && Dummy[k] == 0 && Typevar[k]==0){ /* Only Dummy and non empty in the model */
5391: /* If product not in single variable we don't print results */
5392: /*printf("diff Ndum[%d]=%d\n",i, Ndum[i]);*/
5393: ++ij;/* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, */
5394: 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*/
5395: Tmodelind[ij]=k; /* Tmodelind: index in model of dummies Tmodelind[1]=2 V4: pos=2; V3: pos=3, V1=9 {2, 3, 9, ?, ?,} */
5396: 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 */
5397: if(Fixed[k]!=0)
5398: anyvaryingduminmodel=1;
5399: /* }else if((Ndum[i]!=0) && (i<=ncovcol+nqv)){ */
5400: /* Tvaraff[++ij]=-10; /\* Dont'n know how to treat quantitative variables yet *\/ */
5401: /* }else if((Ndum[i]!=0) && (i<=ncovcol+nqv+ntv)){ */
5402: /* Tvaraff[++ij]=i; /\*For printing (unclear) *\/ */
5403: /* }else if((Ndum[i]!=0) && (i<=ncovcol+nqv+ntv+nqtv)){ */
5404: /* Tvaraff[++ij]=-20; /\* Dont'n know how to treat quantitative variables yet *\/ */
5405: }
5406: } /* Tvaraff[1]@5 {3, 4, -20, 0, 0} Very strange */
5407: /* ij--; */
5408: /* cptcoveff=ij; /\*Number of total covariates*\/ */
5409: *cptcov=ij; /*Number of total real effective covariates: effective
5410: * because they can be excluded from the model and real
5411: * if in the model but excluded because missing values, but how to get k from ij?*/
5412: for(j=ij+1; j<= cptcovt; j++){
5413: Tvaraff[j]=0;
5414: Tmodelind[j]=0;
5415: }
5416: for(j=ntveff+1; j<= cptcovt; j++){
5417: TmodelInvind[j]=0;
5418: }
5419: /* To be sorted */
5420: ;
5421: }
1.126 brouard 5422:
1.145 brouard 5423:
1.126 brouard 5424: /*********** Health Expectancies ****************/
5425:
1.235 brouard 5426: 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 5427:
5428: {
5429: /* Health expectancies, no variances */
1.164 brouard 5430: int i, j, nhstepm, hstepm, h, nstepm;
1.126 brouard 5431: int nhstepma, nstepma; /* Decreasing with age */
5432: double age, agelim, hf;
5433: double ***p3mat;
5434: double eip;
5435:
1.238 brouard 5436: /* pstamp(ficreseij); */
1.126 brouard 5437: fprintf(ficreseij,"# (a) Life expectancies by health status at initial age and (b) health expectancies by health status at initial age\n");
5438: fprintf(ficreseij,"# Age");
5439: for(i=1; i<=nlstate;i++){
5440: for(j=1; j<=nlstate;j++){
5441: fprintf(ficreseij," e%1d%1d ",i,j);
5442: }
5443: fprintf(ficreseij," e%1d. ",i);
5444: }
5445: fprintf(ficreseij,"\n");
5446:
5447:
5448: if(estepm < stepm){
5449: printf ("Problem %d lower than %d\n",estepm, stepm);
5450: }
5451: else hstepm=estepm;
5452: /* We compute the life expectancy from trapezoids spaced every estepm months
5453: * This is mainly to measure the difference between two models: for example
5454: * if stepm=24 months pijx are given only every 2 years and by summing them
5455: * we are calculating an estimate of the Life Expectancy assuming a linear
5456: * progression in between and thus overestimating or underestimating according
5457: * to the curvature of the survival function. If, for the same date, we
5458: * estimate the model with stepm=1 month, we can keep estepm to 24 months
5459: * to compare the new estimate of Life expectancy with the same linear
5460: * hypothesis. A more precise result, taking into account a more precise
5461: * curvature will be obtained if estepm is as small as stepm. */
5462:
5463: /* For example we decided to compute the life expectancy with the smallest unit */
5464: /* hstepm beeing the number of stepms, if hstepm=1 the length of hstepm is stepm.
5465: nhstepm is the number of hstepm from age to agelim
5466: nstepm is the number of stepm from age to agelin.
1.270 ! brouard 5467: Look at hpijx to understand the reason which relies in memory size consideration
1.126 brouard 5468: and note for a fixed period like estepm months */
5469: /* We decided (b) to get a life expectancy respecting the most precise curvature of the
5470: survival function given by stepm (the optimization length). Unfortunately it
5471: means that if the survival funtion is printed only each two years of age and if
5472: you sum them up and add 1 year (area under the trapezoids) you won't get the same
5473: results. So we changed our mind and took the option of the best precision.
5474: */
5475: hstepm=hstepm/stepm; /* Typically in stepm units, if stepm=6 & estepm=24 , = 24/6 months = 4 */
5476:
5477: agelim=AGESUP;
5478: /* If stepm=6 months */
5479: /* Computed by stepm unit matrices, product of hstepm matrices, stored
5480: in an array of nhstepm length: nhstepm=10, hstepm=4, stepm=6 months */
5481:
5482: /* nhstepm age range expressed in number of stepm */
5483: nstepm=(int) rint((agelim-bage)*YEARM/stepm); /* Biggest nstepm */
5484: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
5485: /* if (stepm >= YEARM) hstepm=1;*/
5486: nhstepm = nstepm/hstepm;/* Expressed in hstepm, typically nhstepm=40/4=10 */
5487: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
5488:
5489: for (age=bage; age<=fage; age ++){
5490: nstepma=(int) rint((agelim-bage)*YEARM/stepm); /* Biggest nstepm */
5491: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
5492: /* if (stepm >= YEARM) hstepm=1;*/
5493: nhstepma = nstepma/hstepm;/* Expressed in hstepm, typically nhstepma=40/4=10 */
5494:
5495: /* If stepm=6 months */
5496: /* Computed by stepm unit matrices, product of hstepma matrices, stored
5497: in an array of nhstepma length: nhstepma=10, hstepm=4, stepm=6 months */
5498:
1.235 brouard 5499: hpxij(p3mat,nhstepma,age,hstepm,x,nlstate,stepm,oldm, savm, cij, nres);
1.126 brouard 5500:
5501: hf=hstepm*stepm/YEARM; /* Duration of hstepm expressed in year unit. */
5502:
5503: printf("%d|",(int)age);fflush(stdout);
5504: fprintf(ficlog,"%d|",(int)age);fflush(ficlog);
5505:
5506: /* Computing expectancies */
5507: for(i=1; i<=nlstate;i++)
5508: for(j=1; j<=nlstate;j++)
5509: for (h=0, eij[i][j][(int)age]=0; h<=nhstepm-1; h++){
5510: eij[i][j][(int)age] += (p3mat[i][j][h]+p3mat[i][j][h+1])/2.0*hf;
5511:
5512: /* 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]);*/
5513:
5514: }
5515:
5516: fprintf(ficreseij,"%3.0f",age );
5517: for(i=1; i<=nlstate;i++){
5518: eip=0;
5519: for(j=1; j<=nlstate;j++){
5520: eip +=eij[i][j][(int)age];
5521: fprintf(ficreseij,"%9.4f", eij[i][j][(int)age] );
5522: }
5523: fprintf(ficreseij,"%9.4f", eip );
5524: }
5525: fprintf(ficreseij,"\n");
5526:
5527: }
5528: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
5529: printf("\n");
5530: fprintf(ficlog,"\n");
5531:
5532: }
5533:
1.235 brouard 5534: 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 5535:
5536: {
5537: /* Covariances of health expectancies eij and of total life expectancies according
1.222 brouard 5538: to initial status i, ei. .
1.126 brouard 5539: */
5540: int i, j, nhstepm, hstepm, h, nstepm, k, cptj, cptj2, i2, j2, ij, ji;
5541: int nhstepma, nstepma; /* Decreasing with age */
5542: double age, agelim, hf;
5543: double ***p3matp, ***p3matm, ***varhe;
5544: double **dnewm,**doldm;
5545: double *xp, *xm;
5546: double **gp, **gm;
5547: double ***gradg, ***trgradg;
5548: int theta;
5549:
5550: double eip, vip;
5551:
5552: varhe=ma3x(1,nlstate*nlstate,1,nlstate*nlstate,(int) bage, (int) fage);
5553: xp=vector(1,npar);
5554: xm=vector(1,npar);
5555: dnewm=matrix(1,nlstate*nlstate,1,npar);
5556: doldm=matrix(1,nlstate*nlstate,1,nlstate*nlstate);
5557:
5558: pstamp(ficresstdeij);
5559: fprintf(ficresstdeij,"# Health expectancies with standard errors\n");
5560: fprintf(ficresstdeij,"# Age");
5561: for(i=1; i<=nlstate;i++){
5562: for(j=1; j<=nlstate;j++)
5563: fprintf(ficresstdeij," e%1d%1d (SE)",i,j);
5564: fprintf(ficresstdeij," e%1d. ",i);
5565: }
5566: fprintf(ficresstdeij,"\n");
5567:
5568: pstamp(ficrescveij);
5569: fprintf(ficrescveij,"# Subdiagonal matrix of covariances of health expectancies by age: cov(eij,ekl)\n");
5570: fprintf(ficrescveij,"# Age");
5571: for(i=1; i<=nlstate;i++)
5572: for(j=1; j<=nlstate;j++){
5573: cptj= (j-1)*nlstate+i;
5574: for(i2=1; i2<=nlstate;i2++)
5575: for(j2=1; j2<=nlstate;j2++){
5576: cptj2= (j2-1)*nlstate+i2;
5577: if(cptj2 <= cptj)
5578: fprintf(ficrescveij," %1d%1d,%1d%1d",i,j,i2,j2);
5579: }
5580: }
5581: fprintf(ficrescveij,"\n");
5582:
5583: if(estepm < stepm){
5584: printf ("Problem %d lower than %d\n",estepm, stepm);
5585: }
5586: else hstepm=estepm;
5587: /* We compute the life expectancy from trapezoids spaced every estepm months
5588: * This is mainly to measure the difference between two models: for example
5589: * if stepm=24 months pijx are given only every 2 years and by summing them
5590: * we are calculating an estimate of the Life Expectancy assuming a linear
5591: * progression in between and thus overestimating or underestimating according
5592: * to the curvature of the survival function. If, for the same date, we
5593: * estimate the model with stepm=1 month, we can keep estepm to 24 months
5594: * to compare the new estimate of Life expectancy with the same linear
5595: * hypothesis. A more precise result, taking into account a more precise
5596: * curvature will be obtained if estepm is as small as stepm. */
5597:
5598: /* For example we decided to compute the life expectancy with the smallest unit */
5599: /* hstepm beeing the number of stepms, if hstepm=1 the length of hstepm is stepm.
5600: nhstepm is the number of hstepm from age to agelim
5601: nstepm is the number of stepm from age to agelin.
5602: Look at hpijx to understand the reason of that which relies in memory size
5603: and note for a fixed period like estepm months */
5604: /* We decided (b) to get a life expectancy respecting the most precise curvature of the
5605: survival function given by stepm (the optimization length). Unfortunately it
5606: means that if the survival funtion is printed only each two years of age and if
5607: you sum them up and add 1 year (area under the trapezoids) you won't get the same
5608: results. So we changed our mind and took the option of the best precision.
5609: */
5610: hstepm=hstepm/stepm; /* Typically in stepm units, if stepm=6 & estepm=24 , = 24/6 months = 4 */
5611:
5612: /* If stepm=6 months */
5613: /* nhstepm age range expressed in number of stepm */
5614: agelim=AGESUP;
5615: nstepm=(int) rint((agelim-bage)*YEARM/stepm);
5616: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
5617: /* if (stepm >= YEARM) hstepm=1;*/
5618: nhstepm = nstepm/hstepm;/* Expressed in hstepm, typically nhstepm=40/4=10 */
5619:
5620: p3matp=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
5621: p3matm=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
5622: gradg=ma3x(0,nhstepm,1,npar,1,nlstate*nlstate);
5623: trgradg =ma3x(0,nhstepm,1,nlstate*nlstate,1,npar);
5624: gp=matrix(0,nhstepm,1,nlstate*nlstate);
5625: gm=matrix(0,nhstepm,1,nlstate*nlstate);
5626:
5627: for (age=bage; age<=fage; age ++){
5628: nstepma=(int) rint((agelim-bage)*YEARM/stepm); /* Biggest nstepm */
5629: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
5630: /* if (stepm >= YEARM) hstepm=1;*/
5631: nhstepma = nstepma/hstepm;/* Expressed in hstepm, typically nhstepma=40/4=10 */
1.218 brouard 5632:
1.126 brouard 5633: /* If stepm=6 months */
5634: /* Computed by stepm unit matrices, product of hstepma matrices, stored
5635: in an array of nhstepma length: nhstepma=10, hstepm=4, stepm=6 months */
5636:
5637: hf=hstepm*stepm/YEARM; /* Duration of hstepm expressed in year unit. */
1.218 brouard 5638:
1.126 brouard 5639: /* Computing Variances of health expectancies */
5640: /* Gradient is computed with plus gp and minus gm. Code is duplicated in order to
5641: decrease memory allocation */
5642: for(theta=1; theta <=npar; theta++){
5643: for(i=1; i<=npar; i++){
1.222 brouard 5644: xp[i] = x[i] + (i==theta ?delti[theta]:0);
5645: xm[i] = x[i] - (i==theta ?delti[theta]:0);
1.126 brouard 5646: }
1.235 brouard 5647: hpxij(p3matp,nhstepm,age,hstepm,xp,nlstate,stepm,oldm,savm, cij, nres);
5648: hpxij(p3matm,nhstepm,age,hstepm,xm,nlstate,stepm,oldm,savm, cij, nres);
1.218 brouard 5649:
1.126 brouard 5650: for(j=1; j<= nlstate; j++){
1.222 brouard 5651: for(i=1; i<=nlstate; i++){
5652: for(h=0; h<=nhstepm-1; h++){
5653: gp[h][(j-1)*nlstate + i] = (p3matp[i][j][h]+p3matp[i][j][h+1])/2.;
5654: gm[h][(j-1)*nlstate + i] = (p3matm[i][j][h]+p3matm[i][j][h+1])/2.;
5655: }
5656: }
1.126 brouard 5657: }
1.218 brouard 5658:
1.126 brouard 5659: for(ij=1; ij<= nlstate*nlstate; ij++)
1.222 brouard 5660: for(h=0; h<=nhstepm-1; h++){
5661: gradg[h][theta][ij]= (gp[h][ij]-gm[h][ij])/2./delti[theta];
5662: }
1.126 brouard 5663: }/* End theta */
5664:
5665:
5666: for(h=0; h<=nhstepm-1; h++)
5667: for(j=1; j<=nlstate*nlstate;j++)
1.222 brouard 5668: for(theta=1; theta <=npar; theta++)
5669: trgradg[h][j][theta]=gradg[h][theta][j];
1.126 brouard 5670:
1.218 brouard 5671:
1.222 brouard 5672: for(ij=1;ij<=nlstate*nlstate;ij++)
1.126 brouard 5673: for(ji=1;ji<=nlstate*nlstate;ji++)
1.222 brouard 5674: varhe[ij][ji][(int)age] =0.;
1.218 brouard 5675:
1.222 brouard 5676: printf("%d|",(int)age);fflush(stdout);
5677: fprintf(ficlog,"%d|",(int)age);fflush(ficlog);
5678: for(h=0;h<=nhstepm-1;h++){
1.126 brouard 5679: for(k=0;k<=nhstepm-1;k++){
1.222 brouard 5680: matprod2(dnewm,trgradg[h],1,nlstate*nlstate,1,npar,1,npar,matcov);
5681: matprod2(doldm,dnewm,1,nlstate*nlstate,1,npar,1,nlstate*nlstate,gradg[k]);
5682: for(ij=1;ij<=nlstate*nlstate;ij++)
5683: for(ji=1;ji<=nlstate*nlstate;ji++)
5684: varhe[ij][ji][(int)age] += doldm[ij][ji]*hf*hf;
1.126 brouard 5685: }
5686: }
1.218 brouard 5687:
1.126 brouard 5688: /* Computing expectancies */
1.235 brouard 5689: hpxij(p3matm,nhstepm,age,hstepm,x,nlstate,stepm,oldm, savm, cij,nres);
1.126 brouard 5690: for(i=1; i<=nlstate;i++)
5691: for(j=1; j<=nlstate;j++)
1.222 brouard 5692: for (h=0, eij[i][j][(int)age]=0; h<=nhstepm-1; h++){
5693: eij[i][j][(int)age] += (p3matm[i][j][h]+p3matm[i][j][h+1])/2.0*hf;
1.218 brouard 5694:
1.222 brouard 5695: /* 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 5696:
1.222 brouard 5697: }
1.269 brouard 5698:
5699: /* Standard deviation of expectancies ij */
1.126 brouard 5700: fprintf(ficresstdeij,"%3.0f",age );
5701: for(i=1; i<=nlstate;i++){
5702: eip=0.;
5703: vip=0.;
5704: for(j=1; j<=nlstate;j++){
1.222 brouard 5705: eip += eij[i][j][(int)age];
5706: for(k=1; k<=nlstate;k++) /* Sum on j and k of cov(eij,eik) */
5707: vip += varhe[(j-1)*nlstate+i][(k-1)*nlstate+i][(int)age];
5708: 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 5709: }
5710: fprintf(ficresstdeij," %9.4f (%.4f)", eip, sqrt(vip));
5711: }
5712: fprintf(ficresstdeij,"\n");
1.218 brouard 5713:
1.269 brouard 5714: /* Variance of expectancies ij */
1.126 brouard 5715: fprintf(ficrescveij,"%3.0f",age );
5716: for(i=1; i<=nlstate;i++)
5717: for(j=1; j<=nlstate;j++){
1.222 brouard 5718: cptj= (j-1)*nlstate+i;
5719: for(i2=1; i2<=nlstate;i2++)
5720: for(j2=1; j2<=nlstate;j2++){
5721: cptj2= (j2-1)*nlstate+i2;
5722: if(cptj2 <= cptj)
5723: fprintf(ficrescveij," %.4f", varhe[cptj][cptj2][(int)age]);
5724: }
1.126 brouard 5725: }
5726: fprintf(ficrescveij,"\n");
1.218 brouard 5727:
1.126 brouard 5728: }
5729: free_matrix(gm,0,nhstepm,1,nlstate*nlstate);
5730: free_matrix(gp,0,nhstepm,1,nlstate*nlstate);
5731: free_ma3x(gradg,0,nhstepm,1,npar,1,nlstate*nlstate);
5732: free_ma3x(trgradg,0,nhstepm,1,nlstate*nlstate,1,npar);
5733: free_ma3x(p3matm,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
5734: free_ma3x(p3matp,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
5735: printf("\n");
5736: fprintf(ficlog,"\n");
1.218 brouard 5737:
1.126 brouard 5738: free_vector(xm,1,npar);
5739: free_vector(xp,1,npar);
5740: free_matrix(dnewm,1,nlstate*nlstate,1,npar);
5741: free_matrix(doldm,1,nlstate*nlstate,1,nlstate*nlstate);
5742: free_ma3x(varhe,1,nlstate*nlstate,1,nlstate*nlstate,(int) bage, (int)fage);
5743: }
1.218 brouard 5744:
1.126 brouard 5745: /************ Variance ******************/
1.235 brouard 5746: 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 5747: {
5748: /* Variance of health expectancies */
5749: /* double **prevalim(double **prlim, int nlstate, double *xp, double age, double **oldm, double ** savm,double ftolpl);*/
5750: /* double **newm;*/
5751: /* int movingaverage(double ***probs, double bage,double fage, double ***mobaverage, int mobilav)*/
5752:
5753: /* int movingaverage(); */
5754: double **dnewm,**doldm;
5755: double **dnewmp,**doldmp;
5756: int i, j, nhstepm, hstepm, h, nstepm ;
5757: int k;
5758: double *xp;
5759: double **gp, **gm; /* for var eij */
5760: double ***gradg, ***trgradg; /*for var eij */
5761: double **gradgp, **trgradgp; /* for var p point j */
5762: double *gpp, *gmp; /* for var p point j */
5763: double **varppt; /* for var p point j nlstate to nlstate+ndeath */
5764: double ***p3mat;
5765: double age,agelim, hf;
5766: /* double ***mobaverage; */
5767: int theta;
5768: char digit[4];
5769: char digitp[25];
5770:
5771: char fileresprobmorprev[FILENAMELENGTH];
5772:
5773: if(popbased==1){
5774: if(mobilav!=0)
5775: strcpy(digitp,"-POPULBASED-MOBILAV_");
5776: else strcpy(digitp,"-POPULBASED-NOMOBIL_");
5777: }
5778: else
5779: strcpy(digitp,"-STABLBASED_");
1.126 brouard 5780:
1.218 brouard 5781: /* if (mobilav!=0) { */
5782: /* mobaverage= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
5783: /* if (movingaverage(probs, bage, fage, mobaverage,mobilav)!=0){ */
5784: /* fprintf(ficlog," Error in movingaverage mobilav=%d\n",mobilav); */
5785: /* printf(" Error in movingaverage mobilav=%d\n",mobilav); */
5786: /* } */
5787: /* } */
5788:
5789: strcpy(fileresprobmorprev,"PRMORPREV-");
5790: sprintf(digit,"%-d",ij);
5791: /*printf("DIGIT=%s, ij=%d ijr=%-d|\n",digit, ij,ij);*/
5792: strcat(fileresprobmorprev,digit); /* Tvar to be done */
5793: strcat(fileresprobmorprev,digitp); /* Popbased or not, mobilav or not */
5794: strcat(fileresprobmorprev,fileresu);
5795: if((ficresprobmorprev=fopen(fileresprobmorprev,"w"))==NULL) {
5796: printf("Problem with resultfile: %s\n", fileresprobmorprev);
5797: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprobmorprev);
5798: }
5799: printf("Computing total mortality p.j=w1*p1j+w2*p2j+..: result on file '%s' \n",fileresprobmorprev);
5800: fprintf(ficlog,"Computing total mortality p.j=w1*p1j+w2*p2j+..: result on file '%s' \n",fileresprobmorprev);
5801: pstamp(ficresprobmorprev);
5802: 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 5803: fprintf(ficresprobmorprev,"# Selected quantitative variables and dummies");
5804: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
5805: fprintf(ficresprobmorprev," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
5806: }
5807: for(j=1;j<=cptcoveff;j++)
5808: fprintf(ficresprobmorprev,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(ij,j)]);
5809: fprintf(ficresprobmorprev,"\n");
5810:
1.218 brouard 5811: fprintf(ficresprobmorprev,"# Age cov=%-d",ij);
5812: for(j=nlstate+1; j<=(nlstate+ndeath);j++){
5813: fprintf(ficresprobmorprev," p.%-d SE",j);
5814: for(i=1; i<=nlstate;i++)
5815: fprintf(ficresprobmorprev," w%1d p%-d%-d",i,i,j);
5816: }
5817: fprintf(ficresprobmorprev,"\n");
5818:
5819: fprintf(ficgp,"\n# Routine varevsij");
5820: fprintf(ficgp,"\nunset title \n");
5821: /* fprintf(fichtm, "#Local time at start: %s", strstart);*/
5822: 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");
5823: fprintf(fichtm,"\n<br>%s <br>\n",digitp);
5824: /* } */
5825: varppt = matrix(nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
5826: pstamp(ficresvij);
5827: fprintf(ficresvij,"# Variance and covariance of health expectancies e.j \n# (weighted average of eij where weights are ");
5828: if(popbased==1)
5829: 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);
5830: else
5831: fprintf(ficresvij,"the age specific period (stable) prevalences in each health state \n");
5832: fprintf(ficresvij,"# Age");
5833: for(i=1; i<=nlstate;i++)
5834: for(j=1; j<=nlstate;j++)
5835: fprintf(ficresvij," Cov(e.%1d, e.%1d)",i,j);
5836: fprintf(ficresvij,"\n");
5837:
5838: xp=vector(1,npar);
5839: dnewm=matrix(1,nlstate,1,npar);
5840: doldm=matrix(1,nlstate,1,nlstate);
5841: dnewmp= matrix(nlstate+1,nlstate+ndeath,1,npar);
5842: doldmp= matrix(nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
5843:
5844: gradgp=matrix(1,npar,nlstate+1,nlstate+ndeath);
5845: gpp=vector(nlstate+1,nlstate+ndeath);
5846: gmp=vector(nlstate+1,nlstate+ndeath);
5847: trgradgp =matrix(nlstate+1,nlstate+ndeath,1,npar); /* mu or p point j*/
1.126 brouard 5848:
1.218 brouard 5849: if(estepm < stepm){
5850: printf ("Problem %d lower than %d\n",estepm, stepm);
5851: }
5852: else hstepm=estepm;
5853: /* For example we decided to compute the life expectancy with the smallest unit */
5854: /* hstepm beeing the number of stepms, if hstepm=1 the length of hstepm is stepm.
5855: nhstepm is the number of hstepm from age to agelim
5856: nstepm is the number of stepm from age to agelim.
5857: Look at function hpijx to understand why because of memory size limitations,
5858: we decided (b) to get a life expectancy respecting the most precise curvature of the
5859: survival function given by stepm (the optimization length). Unfortunately it
5860: means that if the survival funtion is printed every two years of age and if
5861: you sum them up and add 1 year (area under the trapezoids) you won't get the same
5862: results. So we changed our mind and took the option of the best precision.
5863: */
5864: hstepm=hstepm/stepm; /* Typically in stepm units, if stepm=6 & estepm=24 , = 24/6 months = 4 */
5865: agelim = AGESUP;
5866: for (age=bage; age<=fage; age ++){ /* If stepm=6 months */
5867: nstepm=(int) rint((agelim-age)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
5868: nhstepm = nstepm/hstepm;/* Expressed in hstepm, typically nhstepm=40/4=10 */
5869: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
5870: gradg=ma3x(0,nhstepm,1,npar,1,nlstate);
5871: gp=matrix(0,nhstepm,1,nlstate);
5872: gm=matrix(0,nhstepm,1,nlstate);
5873:
5874:
5875: for(theta=1; theta <=npar; theta++){
5876: for(i=1; i<=npar; i++){ /* Computes gradient x + delta*/
5877: xp[i] = x[i] + (i==theta ?delti[theta]:0);
5878: }
5879:
1.242 brouard 5880: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij, nres);
1.218 brouard 5881:
5882: if (popbased==1) {
5883: if(mobilav ==0){
5884: for(i=1; i<=nlstate;i++)
5885: prlim[i][i]=probs[(int)age][i][ij];
5886: }else{ /* mobilav */
5887: for(i=1; i<=nlstate;i++)
5888: prlim[i][i]=mobaverage[(int)age][i][ij];
5889: }
5890: }
5891:
1.235 brouard 5892: 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 5893: for(j=1; j<= nlstate; j++){
5894: for(h=0; h<=nhstepm; h++){
5895: for(i=1, gp[h][j]=0.;i<=nlstate;i++)
5896: gp[h][j] += prlim[i][i]*p3mat[i][j][h];
5897: }
5898: }
5899: /* Next for computing probability of death (h=1 means
5900: computed over hstepm matrices product = hstepm*stepm months)
5901: as a weighted average of prlim.
5902: */
5903: for(j=nlstate+1;j<=nlstate+ndeath;j++){
5904: for(i=1,gpp[j]=0.; i<= nlstate; i++)
5905: gpp[j] += prlim[i][i]*p3mat[i][j][1];
5906: }
5907: /* end probability of death */
5908:
5909: for(i=1; i<=npar; i++) /* Computes gradient x - delta */
5910: xp[i] = x[i] - (i==theta ?delti[theta]:0);
5911:
1.242 brouard 5912: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp, ij, nres);
1.218 brouard 5913:
5914: if (popbased==1) {
5915: if(mobilav ==0){
5916: for(i=1; i<=nlstate;i++)
5917: prlim[i][i]=probs[(int)age][i][ij];
5918: }else{ /* mobilav */
5919: for(i=1; i<=nlstate;i++)
5920: prlim[i][i]=mobaverage[(int)age][i][ij];
5921: }
5922: }
5923:
1.235 brouard 5924: hpxij(p3mat,nhstepm,age,hstepm,xp,nlstate,stepm,oldm,savm, ij,nres);
1.218 brouard 5925:
5926: for(j=1; j<= nlstate; j++){ /* Sum of wi * eij = e.j */
5927: for(h=0; h<=nhstepm; h++){
5928: for(i=1, gm[h][j]=0.;i<=nlstate;i++)
5929: gm[h][j] += prlim[i][i]*p3mat[i][j][h];
5930: }
5931: }
5932: /* This for computing probability of death (h=1 means
5933: computed over hstepm matrices product = hstepm*stepm months)
5934: as a weighted average of prlim.
5935: */
5936: for(j=nlstate+1;j<=nlstate+ndeath;j++){
5937: for(i=1,gmp[j]=0.; i<= nlstate; i++)
5938: gmp[j] += prlim[i][i]*p3mat[i][j][1];
5939: }
5940: /* end probability of death */
5941:
5942: for(j=1; j<= nlstate; j++) /* vareij */
5943: for(h=0; h<=nhstepm; h++){
5944: gradg[h][theta][j]= (gp[h][j]-gm[h][j])/2./delti[theta];
5945: }
5946:
5947: for(j=nlstate+1; j<= nlstate+ndeath; j++){ /* var mu */
5948: gradgp[theta][j]= (gpp[j]-gmp[j])/2./delti[theta];
5949: }
5950:
5951: } /* End theta */
5952:
5953: trgradg =ma3x(0,nhstepm,1,nlstate,1,npar); /* veij */
5954:
5955: for(h=0; h<=nhstepm; h++) /* veij */
5956: for(j=1; j<=nlstate;j++)
5957: for(theta=1; theta <=npar; theta++)
5958: trgradg[h][j][theta]=gradg[h][theta][j];
5959:
5960: for(j=nlstate+1; j<=nlstate+ndeath;j++) /* mu */
5961: for(theta=1; theta <=npar; theta++)
5962: trgradgp[j][theta]=gradgp[theta][j];
5963:
5964:
5965: hf=hstepm*stepm/YEARM; /* Duration of hstepm expressed in year unit. */
5966: for(i=1;i<=nlstate;i++)
5967: for(j=1;j<=nlstate;j++)
5968: vareij[i][j][(int)age] =0.;
5969:
5970: for(h=0;h<=nhstepm;h++){
5971: for(k=0;k<=nhstepm;k++){
5972: matprod2(dnewm,trgradg[h],1,nlstate,1,npar,1,npar,matcov);
5973: matprod2(doldm,dnewm,1,nlstate,1,npar,1,nlstate,gradg[k]);
5974: for(i=1;i<=nlstate;i++)
5975: for(j=1;j<=nlstate;j++)
5976: vareij[i][j][(int)age] += doldm[i][j]*hf*hf;
5977: }
5978: }
5979:
5980: /* pptj */
5981: matprod2(dnewmp,trgradgp,nlstate+1,nlstate+ndeath,1,npar,1,npar,matcov);
5982: matprod2(doldmp,dnewmp,nlstate+1,nlstate+ndeath,1,npar,nlstate+1,nlstate+ndeath,gradgp);
5983: for(j=nlstate+1;j<=nlstate+ndeath;j++)
5984: for(i=nlstate+1;i<=nlstate+ndeath;i++)
5985: varppt[j][i]=doldmp[j][i];
5986: /* end ppptj */
5987: /* x centered again */
5988:
1.242 brouard 5989: prevalim(prlim,nlstate,x,age,oldm,savm,ftolpl,ncvyearp,ij, nres);
1.218 brouard 5990:
5991: if (popbased==1) {
5992: if(mobilav ==0){
5993: for(i=1; i<=nlstate;i++)
5994: prlim[i][i]=probs[(int)age][i][ij];
5995: }else{ /* mobilav */
5996: for(i=1; i<=nlstate;i++)
5997: prlim[i][i]=mobaverage[(int)age][i][ij];
5998: }
5999: }
6000:
6001: /* This for computing probability of death (h=1 means
6002: computed over hstepm (estepm) matrices product = hstepm*stepm months)
6003: as a weighted average of prlim.
6004: */
1.235 brouard 6005: hpxij(p3mat,nhstepm,age,hstepm,x,nlstate,stepm,oldm,savm, ij, nres);
1.218 brouard 6006: for(j=nlstate+1;j<=nlstate+ndeath;j++){
6007: for(i=1,gmp[j]=0.;i<= nlstate; i++)
6008: gmp[j] += prlim[i][i]*p3mat[i][j][1];
6009: }
6010: /* end probability of death */
6011:
6012: fprintf(ficresprobmorprev,"%3d %d ",(int) age, ij);
6013: for(j=nlstate+1; j<=(nlstate+ndeath);j++){
6014: fprintf(ficresprobmorprev," %11.3e %11.3e",gmp[j], sqrt(varppt[j][j]));
6015: for(i=1; i<=nlstate;i++){
6016: fprintf(ficresprobmorprev," %11.3e %11.3e ",prlim[i][i],p3mat[i][j][1]);
6017: }
6018: }
6019: fprintf(ficresprobmorprev,"\n");
6020:
6021: fprintf(ficresvij,"%.0f ",age );
6022: for(i=1; i<=nlstate;i++)
6023: for(j=1; j<=nlstate;j++){
6024: fprintf(ficresvij," %.4f", vareij[i][j][(int)age]);
6025: }
6026: fprintf(ficresvij,"\n");
6027: free_matrix(gp,0,nhstepm,1,nlstate);
6028: free_matrix(gm,0,nhstepm,1,nlstate);
6029: free_ma3x(gradg,0,nhstepm,1,npar,1,nlstate);
6030: free_ma3x(trgradg,0,nhstepm,1,nlstate,1,npar);
6031: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
6032: } /* End age */
6033: free_vector(gpp,nlstate+1,nlstate+ndeath);
6034: free_vector(gmp,nlstate+1,nlstate+ndeath);
6035: free_matrix(gradgp,1,npar,nlstate+1,nlstate+ndeath);
6036: free_matrix(trgradgp,nlstate+1,nlstate+ndeath,1,npar); /* mu or p point j*/
6037: /* fprintf(ficgp,"\nunset parametric;unset label; set ter png small size 320, 240"); */
6038: fprintf(ficgp,"\nunset parametric;unset label; set ter svg size 640, 480");
6039: /* for(j=nlstate+1; j<= nlstate+ndeath; j++){ *//* Only the first actually */
6040: fprintf(ficgp,"\n set log y; unset log x;set xlabel \"Age\"; set ylabel \"Force of mortality (year-1)\";");
6041: fprintf(ficgp,"\nset out \"%s%s.svg\";",subdirf3(optionfilefiname,"VARMUPTJGR-",digitp),digit);
6042: /* fprintf(ficgp,"\n plot \"%s\" u 1:($3*%6.3f) not w l 1 ",fileresprobmorprev,YEARM/estepm); */
6043: /* fprintf(ficgp,"\n replot \"%s\" u 1:(($3+1.96*$4)*%6.3f) t \"95\%% interval\" w l 2 ",fileresprobmorprev,YEARM/estepm); */
6044: /* fprintf(ficgp,"\n replot \"%s\" u 1:(($3-1.96*$4)*%6.3f) not w l 2 ",fileresprobmorprev,YEARM/estepm); */
6045: fprintf(ficgp,"\n plot \"%s\" u 1:($3) not w l lt 1 ",subdirf(fileresprobmorprev));
6046: fprintf(ficgp,"\n replot \"%s\" u 1:(($3+1.96*$4)) t \"95%% interval\" w l lt 2 ",subdirf(fileresprobmorprev));
6047: fprintf(ficgp,"\n replot \"%s\" u 1:(($3-1.96*$4)) not w l lt 2 ",subdirf(fileresprobmorprev));
6048: fprintf(fichtm,"\n<br> File (multiple files are possible if covariates are present): <A href=\"%s\">%s</a>\n",subdirf(fileresprobmorprev),subdirf(fileresprobmorprev));
6049: 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);
6050: /* 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 6051: */
1.218 brouard 6052: /* fprintf(ficgp,"\nset out \"varmuptjgr%s%s%s.svg\";replot;",digitp,optionfilefiname,digit); */
6053: fprintf(ficgp,"\nset out;\nset out \"%s%s.svg\";replot;set out;\n",subdirf3(optionfilefiname,"VARMUPTJGR-",digitp),digit);
1.126 brouard 6054:
1.218 brouard 6055: free_vector(xp,1,npar);
6056: free_matrix(doldm,1,nlstate,1,nlstate);
6057: free_matrix(dnewm,1,nlstate,1,npar);
6058: free_matrix(doldmp,nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
6059: free_matrix(dnewmp,nlstate+1,nlstate+ndeath,1,npar);
6060: free_matrix(varppt,nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
6061: /* if (mobilav!=0) free_ma3x(mobaverage,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
6062: fclose(ficresprobmorprev);
6063: fflush(ficgp);
6064: fflush(fichtm);
6065: } /* end varevsij */
1.126 brouard 6066:
6067: /************ Variance of prevlim ******************/
1.269 brouard 6068: 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 6069: {
1.205 brouard 6070: /* Variance of prevalence limit for each state ij using current parameters x[] and estimates of neighbourhood give by delti*/
1.126 brouard 6071: /* double **prevalim(double **prlim, int nlstate, double *xp, double age, double **oldm, double **savm,double ftolpl);*/
1.164 brouard 6072:
1.268 brouard 6073: double **dnewmpar,**doldm;
1.126 brouard 6074: int i, j, nhstepm, hstepm;
6075: double *xp;
6076: double *gp, *gm;
6077: double **gradg, **trgradg;
1.208 brouard 6078: double **mgm, **mgp;
1.126 brouard 6079: double age,agelim;
6080: int theta;
6081:
6082: pstamp(ficresvpl);
6083: fprintf(ficresvpl,"# Standard deviation of period (stable) prevalences \n");
1.241 brouard 6084: fprintf(ficresvpl,"# Age ");
6085: if(nresult >=1)
6086: fprintf(ficresvpl," Result# ");
1.126 brouard 6087: for(i=1; i<=nlstate;i++)
6088: fprintf(ficresvpl," %1d-%1d",i,i);
6089: fprintf(ficresvpl,"\n");
6090:
6091: xp=vector(1,npar);
1.268 brouard 6092: dnewmpar=matrix(1,nlstate,1,npar);
1.126 brouard 6093: doldm=matrix(1,nlstate,1,nlstate);
6094:
6095: hstepm=1*YEARM; /* Every year of age */
6096: hstepm=hstepm/stepm; /* Typically in stepm units, if j= 2 years, = 2/6 months = 4 */
6097: agelim = AGESUP;
6098: for (age=bage; age<=fage; age ++){ /* If stepm=6 months */
6099: nhstepm=(int) rint((agelim-age)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
6100: if (stepm >= YEARM) hstepm=1;
6101: nhstepm = nhstepm/hstepm; /* Typically 40/4=10 */
6102: gradg=matrix(1,npar,1,nlstate);
1.208 brouard 6103: mgp=matrix(1,npar,1,nlstate);
6104: mgm=matrix(1,npar,1,nlstate);
1.126 brouard 6105: gp=vector(1,nlstate);
6106: gm=vector(1,nlstate);
6107:
6108: for(theta=1; theta <=npar; theta++){
6109: for(i=1; i<=npar; i++){ /* Computes gradient */
6110: xp[i] = x[i] + (i==theta ?delti[theta]:0);
6111: }
1.209 brouard 6112: if((int)age==79 ||(int)age== 80 ||(int)age== 81 )
1.235 brouard 6113: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres);
1.209 brouard 6114: else
1.235 brouard 6115: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres);
1.208 brouard 6116: for(i=1;i<=nlstate;i++){
1.126 brouard 6117: gp[i] = prlim[i][i];
1.208 brouard 6118: mgp[theta][i] = prlim[i][i];
6119: }
1.126 brouard 6120: for(i=1; i<=npar; i++) /* Computes gradient */
6121: xp[i] = x[i] - (i==theta ?delti[theta]:0);
1.209 brouard 6122: if((int)age==79 ||(int)age== 80 ||(int)age== 81 )
1.235 brouard 6123: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres);
1.209 brouard 6124: else
1.235 brouard 6125: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres);
1.208 brouard 6126: for(i=1;i<=nlstate;i++){
1.126 brouard 6127: gm[i] = prlim[i][i];
1.208 brouard 6128: mgm[theta][i] = prlim[i][i];
6129: }
1.126 brouard 6130: for(i=1;i<=nlstate;i++)
6131: gradg[theta][i]= (gp[i]-gm[i])/2./delti[theta];
1.209 brouard 6132: /* gradg[theta][2]= -gradg[theta][1]; */ /* For testing if nlstate=2 */
1.126 brouard 6133: } /* End theta */
6134:
6135: trgradg =matrix(1,nlstate,1,npar);
6136:
6137: for(j=1; j<=nlstate;j++)
6138: for(theta=1; theta <=npar; theta++)
6139: trgradg[j][theta]=gradg[theta][j];
1.209 brouard 6140: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
6141: /* printf("\nmgm mgp %d ",(int)age); */
6142: /* for(j=1; j<=nlstate;j++){ */
6143: /* printf(" %d ",j); */
6144: /* for(theta=1; theta <=npar; theta++) */
6145: /* printf(" %d %lf %lf",theta,mgm[theta][j],mgp[theta][j]); */
6146: /* printf("\n "); */
6147: /* } */
6148: /* } */
6149: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
6150: /* printf("\n gradg %d ",(int)age); */
6151: /* for(j=1; j<=nlstate;j++){ */
6152: /* printf("%d ",j); */
6153: /* for(theta=1; theta <=npar; theta++) */
6154: /* printf("%d %lf ",theta,gradg[theta][j]); */
6155: /* printf("\n "); */
6156: /* } */
6157: /* } */
1.126 brouard 6158:
6159: for(i=1;i<=nlstate;i++)
6160: varpl[i][(int)age] =0.;
1.209 brouard 6161: if((int)age==79 ||(int)age== 80 ||(int)age== 81){
1.268 brouard 6162: matprod2(dnewmpar,trgradg,1,nlstate,1,npar,1,npar,matcov);
6163: matprod2(doldm,dnewmpar,1,nlstate,1,npar,1,nlstate,gradg);
1.205 brouard 6164: }else{
1.268 brouard 6165: matprod2(dnewmpar,trgradg,1,nlstate,1,npar,1,npar,matcov);
6166: matprod2(doldm,dnewmpar,1,nlstate,1,npar,1,nlstate,gradg);
1.205 brouard 6167: }
1.126 brouard 6168: for(i=1;i<=nlstate;i++)
6169: varpl[i][(int)age] = doldm[i][i]; /* Covariances are useless */
6170:
6171: fprintf(ficresvpl,"%.0f ",age );
1.241 brouard 6172: if(nresult >=1)
6173: fprintf(ficresvpl,"%d ",nres );
1.126 brouard 6174: for(i=1; i<=nlstate;i++)
6175: fprintf(ficresvpl," %.5f (%.5f)",prlim[i][i],sqrt(varpl[i][(int)age]));
6176: fprintf(ficresvpl,"\n");
6177: free_vector(gp,1,nlstate);
6178: free_vector(gm,1,nlstate);
1.208 brouard 6179: free_matrix(mgm,1,npar,1,nlstate);
6180: free_matrix(mgp,1,npar,1,nlstate);
1.126 brouard 6181: free_matrix(gradg,1,npar,1,nlstate);
6182: free_matrix(trgradg,1,nlstate,1,npar);
6183: } /* End age */
6184:
6185: free_vector(xp,1,npar);
6186: free_matrix(doldm,1,nlstate,1,npar);
1.268 brouard 6187: free_matrix(dnewmpar,1,nlstate,1,nlstate);
6188:
6189: }
6190:
6191:
6192: /************ Variance of backprevalence limit ******************/
1.269 brouard 6193: 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 6194: {
6195: /* Variance of backward prevalence limit for each state ij using current parameters x[] and estimates of neighbourhood give by delti*/
6196: /* double **prevalim(double **prlim, int nlstate, double *xp, double age, double **oldm, double **savm,double ftolpl);*/
6197:
6198: double **dnewmpar,**doldm;
6199: int i, j, nhstepm, hstepm;
6200: double *xp;
6201: double *gp, *gm;
6202: double **gradg, **trgradg;
6203: double **mgm, **mgp;
6204: double age,agelim;
6205: int theta;
6206:
6207: pstamp(ficresvbl);
6208: fprintf(ficresvbl,"# Standard deviation of back (stable) prevalences \n");
6209: fprintf(ficresvbl,"# Age ");
6210: if(nresult >=1)
6211: fprintf(ficresvbl," Result# ");
6212: for(i=1; i<=nlstate;i++)
6213: fprintf(ficresvbl," %1d-%1d",i,i);
6214: fprintf(ficresvbl,"\n");
6215:
6216: xp=vector(1,npar);
6217: dnewmpar=matrix(1,nlstate,1,npar);
6218: doldm=matrix(1,nlstate,1,nlstate);
6219:
6220: hstepm=1*YEARM; /* Every year of age */
6221: hstepm=hstepm/stepm; /* Typically in stepm units, if j= 2 years, = 2/6 months = 4 */
6222: agelim = AGEINF;
6223: for (age=fage; age>=bage; age --){ /* If stepm=6 months */
6224: nhstepm=(int) rint((age-agelim)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
6225: if (stepm >= YEARM) hstepm=1;
6226: nhstepm = nhstepm/hstepm; /* Typically 40/4=10 */
6227: gradg=matrix(1,npar,1,nlstate);
6228: mgp=matrix(1,npar,1,nlstate);
6229: mgm=matrix(1,npar,1,nlstate);
6230: gp=vector(1,nlstate);
6231: gm=vector(1,nlstate);
6232:
6233: for(theta=1; theta <=npar; theta++){
6234: for(i=1; i<=npar; i++){ /* Computes gradient */
6235: xp[i] = x[i] + (i==theta ?delti[theta]:0);
6236: }
6237: if(mobilavproj > 0 )
6238: bprevalim(bprlim, mobaverage,nlstate,xp,age,ftolpl,ncvyearp,ij,nres);
6239: else
6240: bprevalim(bprlim, mobaverage,nlstate,xp,age,ftolpl,ncvyearp,ij,nres);
6241: for(i=1;i<=nlstate;i++){
6242: gp[i] = bprlim[i][i];
6243: mgp[theta][i] = bprlim[i][i];
6244: }
6245: for(i=1; i<=npar; i++) /* Computes gradient */
6246: xp[i] = x[i] - (i==theta ?delti[theta]:0);
6247: if(mobilavproj > 0 )
6248: bprevalim(bprlim, mobaverage,nlstate,xp,age,ftolpl,ncvyearp,ij,nres);
6249: else
6250: bprevalim(bprlim, mobaverage,nlstate,xp,age,ftolpl,ncvyearp,ij,nres);
6251: for(i=1;i<=nlstate;i++){
6252: gm[i] = bprlim[i][i];
6253: mgm[theta][i] = bprlim[i][i];
6254: }
6255: for(i=1;i<=nlstate;i++)
6256: gradg[theta][i]= (gp[i]-gm[i])/2./delti[theta];
6257: /* gradg[theta][2]= -gradg[theta][1]; */ /* For testing if nlstate=2 */
6258: } /* End theta */
6259:
6260: trgradg =matrix(1,nlstate,1,npar);
6261:
6262: for(j=1; j<=nlstate;j++)
6263: for(theta=1; theta <=npar; theta++)
6264: trgradg[j][theta]=gradg[theta][j];
6265: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
6266: /* printf("\nmgm mgp %d ",(int)age); */
6267: /* for(j=1; j<=nlstate;j++){ */
6268: /* printf(" %d ",j); */
6269: /* for(theta=1; theta <=npar; theta++) */
6270: /* printf(" %d %lf %lf",theta,mgm[theta][j],mgp[theta][j]); */
6271: /* printf("\n "); */
6272: /* } */
6273: /* } */
6274: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
6275: /* printf("\n gradg %d ",(int)age); */
6276: /* for(j=1; j<=nlstate;j++){ */
6277: /* printf("%d ",j); */
6278: /* for(theta=1; theta <=npar; theta++) */
6279: /* printf("%d %lf ",theta,gradg[theta][j]); */
6280: /* printf("\n "); */
6281: /* } */
6282: /* } */
6283:
6284: for(i=1;i<=nlstate;i++)
6285: varbpl[i][(int)age] =0.;
6286: if((int)age==79 ||(int)age== 80 ||(int)age== 81){
6287: matprod2(dnewmpar,trgradg,1,nlstate,1,npar,1,npar,matcov);
6288: matprod2(doldm,dnewmpar,1,nlstate,1,npar,1,nlstate,gradg);
6289: }else{
6290: matprod2(dnewmpar,trgradg,1,nlstate,1,npar,1,npar,matcov);
6291: matprod2(doldm,dnewmpar,1,nlstate,1,npar,1,nlstate,gradg);
6292: }
6293: for(i=1;i<=nlstate;i++)
6294: varbpl[i][(int)age] = doldm[i][i]; /* Covariances are useless */
6295:
6296: fprintf(ficresvbl,"%.0f ",age );
6297: if(nresult >=1)
6298: fprintf(ficresvbl,"%d ",nres );
6299: for(i=1; i<=nlstate;i++)
6300: fprintf(ficresvbl," %.5f (%.5f)",bprlim[i][i],sqrt(varbpl[i][(int)age]));
6301: fprintf(ficresvbl,"\n");
6302: free_vector(gp,1,nlstate);
6303: free_vector(gm,1,nlstate);
6304: free_matrix(mgm,1,npar,1,nlstate);
6305: free_matrix(mgp,1,npar,1,nlstate);
6306: free_matrix(gradg,1,npar,1,nlstate);
6307: free_matrix(trgradg,1,nlstate,1,npar);
6308: } /* End age */
6309:
6310: free_vector(xp,1,npar);
6311: free_matrix(doldm,1,nlstate,1,npar);
6312: free_matrix(dnewmpar,1,nlstate,1,nlstate);
1.126 brouard 6313:
6314: }
6315:
6316: /************ Variance of one-step probabilities ******************/
6317: 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 6318: {
6319: int i, j=0, k1, l1, tj;
6320: int k2, l2, j1, z1;
6321: int k=0, l;
6322: int first=1, first1, first2;
6323: double cv12, mu1, mu2, lc1, lc2, v12, v21, v11, v22,v1,v2, c12, tnalp;
6324: double **dnewm,**doldm;
6325: double *xp;
6326: double *gp, *gm;
6327: double **gradg, **trgradg;
6328: double **mu;
6329: double age, cov[NCOVMAX+1];
6330: double std=2.0; /* Number of standard deviation wide of confidence ellipsoids */
6331: int theta;
6332: char fileresprob[FILENAMELENGTH];
6333: char fileresprobcov[FILENAMELENGTH];
6334: char fileresprobcor[FILENAMELENGTH];
6335: double ***varpij;
6336:
6337: strcpy(fileresprob,"PROB_");
6338: strcat(fileresprob,fileres);
6339: if((ficresprob=fopen(fileresprob,"w"))==NULL) {
6340: printf("Problem with resultfile: %s\n", fileresprob);
6341: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprob);
6342: }
6343: strcpy(fileresprobcov,"PROBCOV_");
6344: strcat(fileresprobcov,fileresu);
6345: if((ficresprobcov=fopen(fileresprobcov,"w"))==NULL) {
6346: printf("Problem with resultfile: %s\n", fileresprobcov);
6347: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprobcov);
6348: }
6349: strcpy(fileresprobcor,"PROBCOR_");
6350: strcat(fileresprobcor,fileresu);
6351: if((ficresprobcor=fopen(fileresprobcor,"w"))==NULL) {
6352: printf("Problem with resultfile: %s\n", fileresprobcor);
6353: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprobcor);
6354: }
6355: printf("Computing standard deviation of one-step probabilities: result on file '%s' \n",fileresprob);
6356: fprintf(ficlog,"Computing standard deviation of one-step probabilities: result on file '%s' \n",fileresprob);
6357: printf("Computing matrix of variance covariance of one-step probabilities: result on file '%s' \n",fileresprobcov);
6358: fprintf(ficlog,"Computing matrix of variance covariance of one-step probabilities: result on file '%s' \n",fileresprobcov);
6359: printf("and correlation matrix of one-step probabilities: result on file '%s' \n",fileresprobcor);
6360: fprintf(ficlog,"and correlation matrix of one-step probabilities: result on file '%s' \n",fileresprobcor);
6361: pstamp(ficresprob);
6362: fprintf(ficresprob,"#One-step probabilities and stand. devi in ()\n");
6363: fprintf(ficresprob,"# Age");
6364: pstamp(ficresprobcov);
6365: fprintf(ficresprobcov,"#One-step probabilities and covariance matrix\n");
6366: fprintf(ficresprobcov,"# Age");
6367: pstamp(ficresprobcor);
6368: fprintf(ficresprobcor,"#One-step probabilities and correlation matrix\n");
6369: fprintf(ficresprobcor,"# Age");
1.126 brouard 6370:
6371:
1.222 brouard 6372: for(i=1; i<=nlstate;i++)
6373: for(j=1; j<=(nlstate+ndeath);j++){
6374: fprintf(ficresprob," p%1d-%1d (SE)",i,j);
6375: fprintf(ficresprobcov," p%1d-%1d ",i,j);
6376: fprintf(ficresprobcor," p%1d-%1d ",i,j);
6377: }
6378: /* fprintf(ficresprob,"\n");
6379: fprintf(ficresprobcov,"\n");
6380: fprintf(ficresprobcor,"\n");
6381: */
6382: xp=vector(1,npar);
6383: dnewm=matrix(1,(nlstate)*(nlstate+ndeath),1,npar);
6384: doldm=matrix(1,(nlstate)*(nlstate+ndeath),1,(nlstate)*(nlstate+ndeath));
6385: mu=matrix(1,(nlstate)*(nlstate+ndeath), (int) bage, (int)fage);
6386: varpij=ma3x(1,nlstate*(nlstate+ndeath),1,nlstate*(nlstate+ndeath),(int) bage, (int) fage);
6387: first=1;
6388: fprintf(ficgp,"\n# Routine varprob");
6389: fprintf(fichtm,"\n<li><h4> Computing and drawing one step probabilities with their confidence intervals</h4></li>\n");
6390: fprintf(fichtm,"\n");
6391:
1.266 brouard 6392: 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 6393: 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);
6394: fprintf(fichtmcov,"\nEllipsoids of confidence centered on point (p<inf>ij</inf>, p<inf>kl</inf>) are estimated \
1.126 brouard 6395: and drawn. It helps understanding how is the covariance between two incidences.\
6396: They are expressed in year<sup>-1</sup> in order to be less dependent of stepm.<br>\n");
1.222 brouard 6397: 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 6398: It can be understood this way: if pij and pkl where uncorrelated the (2x2) matrix of covariance \
6399: would have been (1/(var pij), 0 , 0, 1/(var pkl)), and the confidence interval would be 2 \
6400: standard deviations wide on each axis. <br>\
6401: Now, if both incidences are correlated (usual case) we diagonalised the inverse of the covariance matrix\
6402: and made the appropriate rotation to look at the uncorrelated principal directions.<br>\
6403: To be simple, these graphs help to understand the significativity of each parameter in relation to a second other one.<br> \n");
6404:
1.222 brouard 6405: cov[1]=1;
6406: /* tj=cptcoveff; */
1.225 brouard 6407: tj = (int) pow(2,cptcoveff);
1.222 brouard 6408: if (cptcovn<1) {tj=1;ncodemax[1]=1;}
6409: j1=0;
1.224 brouard 6410: for(j1=1; j1<=tj;j1++){ /* For each valid combination of covariates or only once*/
1.222 brouard 6411: if (cptcovn>0) {
6412: fprintf(ficresprob, "\n#********** Variable ");
1.225 brouard 6413: for (z1=1; z1<=cptcoveff; z1++) fprintf(ficresprob, "V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
1.222 brouard 6414: fprintf(ficresprob, "**********\n#\n");
6415: fprintf(ficresprobcov, "\n#********** Variable ");
1.225 brouard 6416: for (z1=1; z1<=cptcoveff; z1++) fprintf(ficresprobcov, "V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
1.222 brouard 6417: fprintf(ficresprobcov, "**********\n#\n");
1.220 brouard 6418:
1.222 brouard 6419: fprintf(ficgp, "\n#********** Variable ");
1.225 brouard 6420: for (z1=1; z1<=cptcoveff; z1++) fprintf(ficgp, " V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
1.222 brouard 6421: fprintf(ficgp, "**********\n#\n");
1.220 brouard 6422:
6423:
1.222 brouard 6424: fprintf(fichtmcov, "\n<hr size=\"2\" color=\"#EC5E5E\">********** Variable ");
1.225 brouard 6425: for (z1=1; z1<=cptcoveff; z1++) fprintf(fichtm, "V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
1.222 brouard 6426: fprintf(fichtmcov, "**********\n<hr size=\"2\" color=\"#EC5E5E\">");
1.220 brouard 6427:
1.222 brouard 6428: fprintf(ficresprobcor, "\n#********** Variable ");
1.225 brouard 6429: for (z1=1; z1<=cptcoveff; z1++) fprintf(ficresprobcor, "V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
1.222 brouard 6430: fprintf(ficresprobcor, "**********\n#");
6431: if(invalidvarcomb[j1]){
6432: fprintf(ficgp,"\n#Combination (%d) ignored because no cases \n",j1);
6433: fprintf(fichtmcov,"\n<h3>Combination (%d) ignored because no cases </h3>\n",j1);
6434: continue;
6435: }
6436: }
6437: gradg=matrix(1,npar,1,(nlstate)*(nlstate+ndeath));
6438: trgradg=matrix(1,(nlstate)*(nlstate+ndeath),1,npar);
6439: gp=vector(1,(nlstate)*(nlstate+ndeath));
6440: gm=vector(1,(nlstate)*(nlstate+ndeath));
6441: for (age=bage; age<=fage; age ++){
6442: cov[2]=age;
6443: if(nagesqr==1)
6444: cov[3]= age*age;
6445: for (k=1; k<=cptcovn;k++) {
6446: cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(j1,k)];
6447: /*cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(j1,Tvar[k])];*//* j1 1 2 3 4
6448: * 1 1 1 1 1
6449: * 2 2 1 1 1
6450: * 3 1 2 1 1
6451: */
6452: /* nbcode[1][1]=0 nbcode[1][2]=1;*/
6453: }
6454: /* for (k=1; k<=cptcovage;k++) cov[2+Tage[k]]=cov[2+Tage[k]]*cov[2]; */
6455: for (k=1; k<=cptcovage;k++) cov[2+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2];
6456: for (k=1; k<=cptcovprod;k++)
6457: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)]*nbcode[Tvard[k][2]][codtabm(ij,k)];
1.220 brouard 6458:
6459:
1.222 brouard 6460: for(theta=1; theta <=npar; theta++){
6461: for(i=1; i<=npar; i++)
6462: xp[i] = x[i] + (i==theta ?delti[theta]:(double)0);
1.220 brouard 6463:
1.222 brouard 6464: pmij(pmmij,cov,ncovmodel,xp,nlstate);
1.220 brouard 6465:
1.222 brouard 6466: k=0;
6467: for(i=1; i<= (nlstate); i++){
6468: for(j=1; j<=(nlstate+ndeath);j++){
6469: k=k+1;
6470: gp[k]=pmmij[i][j];
6471: }
6472: }
1.220 brouard 6473:
1.222 brouard 6474: for(i=1; i<=npar; i++)
6475: xp[i] = x[i] - (i==theta ?delti[theta]:(double)0);
1.220 brouard 6476:
1.222 brouard 6477: pmij(pmmij,cov,ncovmodel,xp,nlstate);
6478: k=0;
6479: for(i=1; i<=(nlstate); i++){
6480: for(j=1; j<=(nlstate+ndeath);j++){
6481: k=k+1;
6482: gm[k]=pmmij[i][j];
6483: }
6484: }
1.220 brouard 6485:
1.222 brouard 6486: for(i=1; i<= (nlstate)*(nlstate+ndeath); i++)
6487: gradg[theta][i]=(gp[i]-gm[i])/(double)2./delti[theta];
6488: }
1.126 brouard 6489:
1.222 brouard 6490: for(j=1; j<=(nlstate)*(nlstate+ndeath);j++)
6491: for(theta=1; theta <=npar; theta++)
6492: trgradg[j][theta]=gradg[theta][j];
1.220 brouard 6493:
1.222 brouard 6494: matprod2(dnewm,trgradg,1,(nlstate)*(nlstate+ndeath),1,npar,1,npar,matcov);
6495: matprod2(doldm,dnewm,1,(nlstate)*(nlstate+ndeath),1,npar,1,(nlstate)*(nlstate+ndeath),gradg);
1.220 brouard 6496:
1.222 brouard 6497: pmij(pmmij,cov,ncovmodel,x,nlstate);
1.220 brouard 6498:
1.222 brouard 6499: k=0;
6500: for(i=1; i<=(nlstate); i++){
6501: for(j=1; j<=(nlstate+ndeath);j++){
6502: k=k+1;
6503: mu[k][(int) age]=pmmij[i][j];
6504: }
6505: }
6506: for(i=1;i<=(nlstate)*(nlstate+ndeath);i++)
6507: for(j=1;j<=(nlstate)*(nlstate+ndeath);j++)
6508: varpij[i][j][(int)age] = doldm[i][j];
1.220 brouard 6509:
1.222 brouard 6510: /*printf("\n%d ",(int)age);
6511: for (i=1; i<=(nlstate)*(nlstate+ndeath);i++){
6512: printf("%e [%e ;%e] ",gm[i],gm[i]-2*sqrt(doldm[i][i]),gm[i]+2*sqrt(doldm[i][i]));
6513: fprintf(ficlog,"%e [%e ;%e] ",gm[i],gm[i]-2*sqrt(doldm[i][i]),gm[i]+2*sqrt(doldm[i][i]));
6514: }*/
1.220 brouard 6515:
1.222 brouard 6516: fprintf(ficresprob,"\n%d ",(int)age);
6517: fprintf(ficresprobcov,"\n%d ",(int)age);
6518: fprintf(ficresprobcor,"\n%d ",(int)age);
1.220 brouard 6519:
1.222 brouard 6520: for (i=1; i<=(nlstate)*(nlstate+ndeath);i++)
6521: fprintf(ficresprob,"%11.3e (%11.3e) ",mu[i][(int) age],sqrt(varpij[i][i][(int)age]));
6522: for (i=1; i<=(nlstate)*(nlstate+ndeath);i++){
6523: fprintf(ficresprobcov,"%11.3e ",mu[i][(int) age]);
6524: fprintf(ficresprobcor,"%11.3e ",mu[i][(int) age]);
6525: }
6526: i=0;
6527: for (k=1; k<=(nlstate);k++){
6528: for (l=1; l<=(nlstate+ndeath);l++){
6529: i++;
6530: fprintf(ficresprobcov,"\n%d %d-%d",(int)age,k,l);
6531: fprintf(ficresprobcor,"\n%d %d-%d",(int)age,k,l);
6532: for (j=1; j<=i;j++){
6533: /* printf(" k=%d l=%d i=%d j=%d\n",k,l,i,j);fflush(stdout); */
6534: fprintf(ficresprobcov," %11.3e",varpij[i][j][(int)age]);
6535: fprintf(ficresprobcor," %11.3e",varpij[i][j][(int) age]/sqrt(varpij[i][i][(int) age])/sqrt(varpij[j][j][(int)age]));
6536: }
6537: }
6538: }/* end of loop for state */
6539: } /* end of loop for age */
6540: free_vector(gp,1,(nlstate+ndeath)*(nlstate+ndeath));
6541: free_vector(gm,1,(nlstate+ndeath)*(nlstate+ndeath));
6542: free_matrix(trgradg,1,(nlstate+ndeath)*(nlstate+ndeath),1,npar);
6543: free_matrix(gradg,1,(nlstate+ndeath)*(nlstate+ndeath),1,npar);
6544:
6545: /* Confidence intervalle of pij */
6546: /*
6547: fprintf(ficgp,"\nunset parametric;unset label");
6548: fprintf(ficgp,"\nset log y;unset log x; set xlabel \"Age\";set ylabel \"probability (year-1)\"");
6549: fprintf(ficgp,"\nset ter png small\nset size 0.65,0.65");
6550: 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);
6551: fprintf(fichtm,"\n<br><img src=\"pijgr%s.png\"> ",optionfilefiname);
6552: fprintf(ficgp,"\nset out \"pijgr%s.png\"",optionfilefiname);
6553: fprintf(ficgp,"\nplot \"%s\" every :::%d::%d u 1:2 \"\%%lf",k1,k2,xfilevarprob);
6554: */
6555:
6556: /* Drawing ellipsoids of confidence of two variables p(k1-l1,k2-l2)*/
6557: first1=1;first2=2;
6558: for (k2=1; k2<=(nlstate);k2++){
6559: for (l2=1; l2<=(nlstate+ndeath);l2++){
6560: if(l2==k2) continue;
6561: j=(k2-1)*(nlstate+ndeath)+l2;
6562: for (k1=1; k1<=(nlstate);k1++){
6563: for (l1=1; l1<=(nlstate+ndeath);l1++){
6564: if(l1==k1) continue;
6565: i=(k1-1)*(nlstate+ndeath)+l1;
6566: if(i<=j) continue;
6567: for (age=bage; age<=fage; age ++){
6568: if ((int)age %5==0){
6569: v1=varpij[i][i][(int)age]/stepm*YEARM/stepm*YEARM;
6570: v2=varpij[j][j][(int)age]/stepm*YEARM/stepm*YEARM;
6571: cv12=varpij[i][j][(int)age]/stepm*YEARM/stepm*YEARM;
6572: mu1=mu[i][(int) age]/stepm*YEARM ;
6573: mu2=mu[j][(int) age]/stepm*YEARM;
6574: c12=cv12/sqrt(v1*v2);
6575: /* Computing eigen value of matrix of covariance */
6576: lc1=((v1+v2)+sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
6577: lc2=((v1+v2)-sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
6578: if ((lc2 <0) || (lc1 <0) ){
6579: if(first2==1){
6580: first1=0;
6581: 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);
6582: }
6583: 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);
6584: /* lc1=fabs(lc1); */ /* If we want to have them positive */
6585: /* lc2=fabs(lc2); */
6586: }
1.220 brouard 6587:
1.222 brouard 6588: /* Eigen vectors */
6589: v11=(1./sqrt(1+(v1-lc1)*(v1-lc1)/cv12/cv12));
6590: /*v21=sqrt(1.-v11*v11); *//* error */
6591: v21=(lc1-v1)/cv12*v11;
6592: v12=-v21;
6593: v22=v11;
6594: tnalp=v21/v11;
6595: if(first1==1){
6596: first1=0;
6597: 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);
6598: }
6599: 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);
6600: /*printf(fignu*/
6601: /* mu1+ v11*lc1*cost + v12*lc2*sin(t) */
6602: /* mu2+ v21*lc1*cost + v22*lc2*sin(t) */
6603: if(first==1){
6604: first=0;
6605: fprintf(ficgp,"\n# Ellipsoids of confidence\n#\n");
6606: fprintf(ficgp,"\nset parametric;unset label");
6607: 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);
6608: fprintf(ficgp,"\nset ter svg size 640, 480");
1.266 brouard 6609: fprintf(fichtmcov,"\n<p><br>Ellipsoids of confidence cov(p%1d%1d,p%1d%1d) expressed in year<sup>-1</sup>\
1.220 brouard 6610: :<a href=\"%s_%d%1d%1d-%1d%1d.svg\"> \
1.201 brouard 6611: %s_%d%1d%1d-%1d%1d.svg</A>, ",k1,l1,k2,l2,\
1.222 brouard 6612: subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2, \
6613: subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
6614: fprintf(fichtmcov,"\n<br><img src=\"%s_%d%1d%1d-%1d%1d.svg\"> ",subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
6615: fprintf(fichtmcov,"\n<br> Correlation at age %d (%.3f),",(int) age, c12);
6616: fprintf(ficgp,"\nset out \"%s_%d%1d%1d-%1d%1d.svg\"",subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
6617: fprintf(ficgp,"\nset label \"%d\" at %11.3e,%11.3e center",(int) age, mu1,mu2);
6618: fprintf(ficgp,"\n# Age %d, p%1d%1d - p%1d%1d",(int) age, k1,l1,k2,l2);
6619: 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 6620: mu1,std,v11,sqrt(lc1),v12,sqrt(fabs(lc2)), \
6621: mu2,std,v21,sqrt(lc1),v22,sqrt(fabs(lc2))); /* For gnuplot only */
1.222 brouard 6622: }else{
6623: first=0;
6624: fprintf(fichtmcov," %d (%.3f),",(int) age, c12);
6625: fprintf(ficgp,"\n# Age %d, p%1d%1d - p%1d%1d",(int) age, k1,l1,k2,l2);
6626: fprintf(ficgp,"\nset label \"%d\" at %11.3e,%11.3e center",(int) age, mu1,mu2);
6627: 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 6628: mu1,std,v11,sqrt(lc1),v12,sqrt(fabs(lc2)), \
6629: mu2,std,v21,sqrt(lc1),v22,sqrt(fabs(lc2)));
1.222 brouard 6630: }/* if first */
6631: } /* age mod 5 */
6632: } /* end loop age */
6633: fprintf(ficgp,"\nset out;\nset out \"%s_%d%1d%1d-%1d%1d.svg\";replot;set out;",subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
6634: first=1;
6635: } /*l12 */
6636: } /* k12 */
6637: } /*l1 */
6638: }/* k1 */
6639: } /* loop on combination of covariates j1 */
6640: free_ma3x(varpij,1,nlstate,1,nlstate+ndeath,(int) bage, (int)fage);
6641: free_matrix(mu,1,(nlstate+ndeath)*(nlstate+ndeath),(int) bage, (int)fage);
6642: free_matrix(doldm,1,(nlstate)*(nlstate+ndeath),1,(nlstate)*(nlstate+ndeath));
6643: free_matrix(dnewm,1,(nlstate)*(nlstate+ndeath),1,npar);
6644: free_vector(xp,1,npar);
6645: fclose(ficresprob);
6646: fclose(ficresprobcov);
6647: fclose(ficresprobcor);
6648: fflush(ficgp);
6649: fflush(fichtmcov);
6650: }
1.126 brouard 6651:
6652:
6653: /******************* Printing html file ***********/
1.201 brouard 6654: void printinghtml(char fileresu[], char title[], char datafile[], int firstpass, \
1.126 brouard 6655: int lastpass, int stepm, int weightopt, char model[],\
6656: int imx,int jmin, int jmax, double jmeanint,char rfileres[],\
1.258 brouard 6657: int popforecast, int mobilav, int prevfcast, int mobilavproj, int backcast, int estepm , \
1.213 brouard 6658: double jprev1, double mprev1,double anprev1, double dateprev1, \
6659: double jprev2, double mprev2,double anprev2, double dateprev2){
1.237 brouard 6660: int jj1, k1, i1, cpt, k4, nres;
1.126 brouard 6661:
6662: fprintf(fichtm,"<ul><li><a href='#firstorder'>Result files (first order: no variance)</a>\n \
6663: <li><a href='#secondorder'>Result files (second order (variance)</a>\n \
6664: </ul>");
1.237 brouard 6665: fprintf(fichtm,"<ul><li> model=1+age+%s\n \
6666: </ul>", model);
1.214 brouard 6667: fprintf(fichtm,"<ul><li><h4><a name='firstorder'>Result files (first order: no variance)</a></h4>\n");
6668: 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",
6669: jprev1, mprev1,anprev1,jprev2, mprev2,anprev2,subdirfext3(optionfilefiname,"PHTMFR_",".htm"),subdirfext3(optionfilefiname,"PHTMFR_",".htm"));
6670: 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 6671: jprev1, mprev1,anprev1,jprev2, mprev2,anprev2,subdirfext3(optionfilefiname,"PHTM_",".htm"),subdirfext3(optionfilefiname,"PHTM_",".htm"));
6672: fprintf(fichtm,", <a href=\"%s\">%s</a> (text file) <br>\n",subdirf2(fileresu,"P_"),subdirf2(fileresu,"P_"));
1.126 brouard 6673: fprintf(fichtm,"\
6674: - Estimated transition probabilities over %d (stepm) months: <a href=\"%s\">%s</a><br>\n ",
1.201 brouard 6675: stepm,subdirf2(fileresu,"PIJ_"),subdirf2(fileresu,"PIJ_"));
1.126 brouard 6676: fprintf(fichtm,"\
1.217 brouard 6677: - Estimated back transition probabilities over %d (stepm) months: <a href=\"%s\">%s</a><br>\n ",
6678: stepm,subdirf2(fileresu,"PIJB_"),subdirf2(fileresu,"PIJB_"));
6679: fprintf(fichtm,"\
1.126 brouard 6680: - Period (stable) prevalence in each health state: <a href=\"%s\">%s</a> <br>\n",
1.201 brouard 6681: subdirf2(fileresu,"PL_"),subdirf2(fileresu,"PL_"));
1.126 brouard 6682: fprintf(fichtm,"\
1.217 brouard 6683: - Period (stable) back prevalence in each health state: <a href=\"%s\">%s</a> <br>\n",
6684: subdirf2(fileresu,"PLB_"),subdirf2(fileresu,"PLB_"));
6685: fprintf(fichtm,"\
1.211 brouard 6686: - (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 6687: <a href=\"%s\">%s</a> <br>\n",
1.201 brouard 6688: estepm,subdirf2(fileresu,"E_"),subdirf2(fileresu,"E_"));
1.211 brouard 6689: if(prevfcast==1){
6690: fprintf(fichtm,"\
6691: - Prevalence projections by age and states: \
1.201 brouard 6692: <a href=\"%s\">%s</a> <br>\n</li>", subdirf2(fileresu,"F_"),subdirf2(fileresu,"F_"));
1.211 brouard 6693: }
1.126 brouard 6694:
6695:
1.225 brouard 6696: m=pow(2,cptcoveff);
1.222 brouard 6697: if (cptcovn < 1) {m=1;ncodemax[1]=1;}
1.126 brouard 6698:
1.264 brouard 6699: fprintf(fichtm," \n<ul><li><b>Graphs</b></li><p>");
6700:
6701: jj1=0;
6702:
6703: fprintf(fichtm," \n<ul>");
6704: for(nres=1; nres <= nresult; nres++) /* For each resultline */
6705: for(k1=1; k1<=m;k1++){ /* For each combination of covariate */
6706: if(m != 1 && TKresult[nres]!= k1)
6707: continue;
6708: jj1++;
6709: if (cptcovn > 0) {
6710: fprintf(fichtm,"\n<li><a size=\"1\" color=\"#EC5E5E\" href=\"#rescov");
6711: for (cpt=1; cpt<=cptcoveff;cpt++){
6712: fprintf(fichtm,"_V%d=%d_",Tvresult[nres][cpt],(int)Tresult[nres][cpt]);
6713: }
6714: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
6715: fprintf(fichtm,"_V%d=%f_",Tvqresult[nres][k4],Tqresult[nres][k4]);
6716: }
6717: fprintf(fichtm,"\">");
6718:
6719: /* if(nqfveff+nqtveff 0) */ /* Test to be done */
6720: fprintf(fichtm,"************ Results for covariates");
6721: for (cpt=1; cpt<=cptcoveff;cpt++){
6722: fprintf(fichtm," V%d=%d ",Tvresult[nres][cpt],(int)Tresult[nres][cpt]);
6723: }
6724: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
6725: fprintf(fichtm," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
6726: }
6727: if(invalidvarcomb[k1]){
6728: fprintf(fichtm," Warning Combination (%d) ignored because no cases ",k1);
6729: continue;
6730: }
6731: fprintf(fichtm,"</a></li>");
6732: } /* cptcovn >0 */
6733: }
6734: fprintf(fichtm," \n</ul>");
6735:
1.222 brouard 6736: jj1=0;
1.237 brouard 6737:
6738: for(nres=1; nres <= nresult; nres++) /* For each resultline */
1.241 brouard 6739: for(k1=1; k1<=m;k1++){ /* For each combination of covariate */
1.253 brouard 6740: if(m != 1 && TKresult[nres]!= k1)
1.237 brouard 6741: continue;
1.220 brouard 6742:
1.222 brouard 6743: /* for(i1=1; i1<=ncodemax[k1];i1++){ */
6744: jj1++;
6745: if (cptcovn > 0) {
1.264 brouard 6746: fprintf(fichtm,"\n<p><a name=\"rescov");
6747: for (cpt=1; cpt<=cptcoveff;cpt++){
6748: fprintf(fichtm,"_V%d=%d_",Tvresult[nres][cpt],(int)Tresult[nres][cpt]);
6749: }
6750: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
6751: fprintf(fichtm,"_V%d=%f_",Tvqresult[nres][k4],Tqresult[nres][k4]);
6752: }
6753: fprintf(fichtm,"\"</a>");
6754:
1.222 brouard 6755: fprintf(fichtm,"<hr size=\"2\" color=\"#EC5E5E\">************ Results for covariates");
1.225 brouard 6756: for (cpt=1; cpt<=cptcoveff;cpt++){
1.237 brouard 6757: fprintf(fichtm," V%d=%d ",Tvresult[nres][cpt],(int)Tresult[nres][cpt]);
6758: printf(" V%d=%d ",Tvresult[nres][cpt],Tresult[nres][cpt]);fflush(stdout);
6759: /* fprintf(fichtm," V%d=%d ",Tvaraff[cpt],nbcode[Tvaraff[cpt]][codtabm(jj1,cpt)]); */
6760: /* printf(" V%d=%d ",Tvaraff[cpt],nbcode[Tvaraff[cpt]][codtabm(jj1,cpt)]);fflush(stdout); */
1.222 brouard 6761: }
1.237 brouard 6762: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
6763: fprintf(fichtm," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
6764: printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);fflush(stdout);
6765: }
6766:
1.230 brouard 6767: /* if(nqfveff+nqtveff 0) */ /* Test to be done */
1.222 brouard 6768: fprintf(fichtm," ************\n<hr size=\"2\" color=\"#EC5E5E\">");
6769: if(invalidvarcomb[k1]){
6770: fprintf(fichtm,"\n<h3>Combination (%d) ignored because no cases </h3>\n",k1);
6771: printf("\nCombination (%d) ignored because no cases \n",k1);
6772: continue;
6773: }
6774: }
6775: /* aij, bij */
1.259 brouard 6776: 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 6777: <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 6778: /* Pij */
1.241 brouard 6779: 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> \
6780: <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 6781: /* Quasi-incidences */
6782: 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 6783: before but expressed in per year i.e. quasi incidences if stepm is small and probabilities too, \
1.211 brouard 6784: 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 6785: 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> \
6786: <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 6787: /* Survival functions (period) in state j */
6788: for(cpt=1; cpt<=nlstate;cpt++){
1.241 brouard 6789: 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> \
6790: <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 6791: }
6792: /* State specific survival functions (period) */
6793: for(cpt=1; cpt<=nlstate;cpt++){
6794: fprintf(fichtm,"<br>\n- Survival functions from state %d in each live state and total.\
1.220 brouard 6795: Or probability to survive in various states (1 to %d) being in state %d at different ages. \
1.241 brouard 6796: <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 6797: }
6798: /* Period (stable) prevalence in each health state */
6799: for(cpt=1; cpt<=nlstate;cpt++){
1.264 brouard 6800: 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> \
6801: <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 6802: }
6803: if(backcast==1){
6804: /* Period (stable) back prevalence in each health state */
6805: for(cpt=1; cpt<=nlstate;cpt++){
1.264 brouard 6806: 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 6807: <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 6808: }
1.217 brouard 6809: }
1.222 brouard 6810: if(prevfcast==1){
6811: /* Projection of prevalence up to period (stable) prevalence in each health state */
6812: for(cpt=1; cpt<=nlstate;cpt++){
1.268 brouard 6813: 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 6814: <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 6815: }
6816: }
1.268 brouard 6817: if(backcast==1){
6818: /* Back projection of prevalence up to stable (mixed) back-prevalence in each health state */
6819: for(cpt=1; cpt<=nlstate;cpt++){
6820: 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> \
6821: <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);
6822: }
6823: }
1.220 brouard 6824:
1.222 brouard 6825: for(cpt=1; cpt<=nlstate;cpt++) {
1.241 brouard 6826: 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> \
6827: <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 6828: }
6829: /* } /\* end i1 *\/ */
6830: }/* End k1 */
6831: fprintf(fichtm,"</ul>");
1.126 brouard 6832:
1.222 brouard 6833: fprintf(fichtm,"\
1.126 brouard 6834: \n<br><li><h4> <a name='secondorder'>Result files (second order: variances)</a></h4>\n\
1.193 brouard 6835: - Parameter file with estimated parameters and covariance matrix: <a href=\"%s\">%s</a> <br> \
1.203 brouard 6836: - 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 6837: But because parameters are usually highly correlated (a higher incidence of disability \
6838: and a higher incidence of recovery can give very close observed transition) it might \
6839: be very useful to look not only at linear confidence intervals estimated from the \
6840: variances but at the covariance matrix. And instead of looking at the estimated coefficients \
6841: (parameters) of the logistic regression, it might be more meaningful to visualize the \
6842: covariance matrix of the one-step probabilities. \
6843: See page 'Matrix of variance-covariance of one-step probabilities' below. \n", rfileres,rfileres);
1.126 brouard 6844:
1.222 brouard 6845: fprintf(fichtm," - Standard deviation of one-step probabilities: <a href=\"%s\">%s</a> <br>\n",
6846: subdirf2(fileresu,"PROB_"),subdirf2(fileresu,"PROB_"));
6847: fprintf(fichtm,"\
1.126 brouard 6848: - Variance-covariance of one-step probabilities: <a href=\"%s\">%s</a> <br>\n",
1.222 brouard 6849: subdirf2(fileresu,"PROBCOV_"),subdirf2(fileresu,"PROBCOV_"));
1.126 brouard 6850:
1.222 brouard 6851: fprintf(fichtm,"\
1.126 brouard 6852: - Correlation matrix of one-step probabilities: <a href=\"%s\">%s</a> <br>\n",
1.222 brouard 6853: subdirf2(fileresu,"PROBCOR_"),subdirf2(fileresu,"PROBCOR_"));
6854: fprintf(fichtm,"\
1.126 brouard 6855: - 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): \
6856: <a href=\"%s\">%s</a> <br>\n</li>",
1.201 brouard 6857: estepm,subdirf2(fileresu,"CVE_"),subdirf2(fileresu,"CVE_"));
1.222 brouard 6858: fprintf(fichtm,"\
1.126 brouard 6859: - (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): \
6860: <a href=\"%s\">%s</a> <br>\n</li>",
1.201 brouard 6861: estepm,subdirf2(fileresu,"STDE_"),subdirf2(fileresu,"STDE_"));
1.222 brouard 6862: fprintf(fichtm,"\
1.128 brouard 6863: - 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 6864: estepm, subdirf2(fileresu,"V_"),subdirf2(fileresu,"V_"));
6865: fprintf(fichtm,"\
1.128 brouard 6866: - 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 6867: estepm, subdirf2(fileresu,"T_"),subdirf2(fileresu,"T_"));
6868: fprintf(fichtm,"\
1.126 brouard 6869: - Standard deviation of period (stable) prevalences: <a href=\"%s\">%s</a> <br>\n",\
1.222 brouard 6870: subdirf2(fileresu,"VPL_"),subdirf2(fileresu,"VPL_"));
1.126 brouard 6871:
6872: /* if(popforecast==1) fprintf(fichtm,"\n */
6873: /* - Prevalences forecasting: <a href=\"f%s\">f%s</a> <br>\n */
6874: /* - Population forecasting (if popforecast=1): <a href=\"pop%s\">pop%s</a> <br>\n */
6875: /* <br>",fileres,fileres,fileres,fileres); */
6876: /* else */
6877: /* 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 6878: fflush(fichtm);
6879: fprintf(fichtm," <ul><li><b>Graphs</b></li><p>");
1.126 brouard 6880:
1.225 brouard 6881: m=pow(2,cptcoveff);
1.222 brouard 6882: if (cptcovn < 1) {m=1;ncodemax[1]=1;}
1.126 brouard 6883:
1.222 brouard 6884: jj1=0;
1.237 brouard 6885:
1.241 brouard 6886: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.222 brouard 6887: for(k1=1; k1<=m;k1++){
1.253 brouard 6888: if(m != 1 && TKresult[nres]!= k1)
1.237 brouard 6889: continue;
1.222 brouard 6890: /* for(i1=1; i1<=ncodemax[k1];i1++){ */
6891: jj1++;
1.126 brouard 6892: if (cptcovn > 0) {
6893: fprintf(fichtm,"<hr size=\"2\" color=\"#EC5E5E\">************ Results for covariates");
1.225 brouard 6894: for (cpt=1; cpt<=cptcoveff;cpt++) /**< cptcoveff number of variables */
1.237 brouard 6895: fprintf(fichtm," V%d=%d ",Tvresult[nres][cpt],Tresult[nres][cpt]);
6896: /* fprintf(fichtm," V%d=%d ",Tvaraff[cpt],nbcode[Tvaraff[cpt]][codtabm(jj1,cpt)]); */
6897: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
6898: fprintf(fichtm," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
6899: }
6900:
1.126 brouard 6901: fprintf(fichtm," ************\n<hr size=\"2\" color=\"#EC5E5E\">");
1.220 brouard 6902:
1.222 brouard 6903: if(invalidvarcomb[k1]){
6904: fprintf(fichtm,"\n<h4>Combination (%d) ignored because no cases </h4>\n",k1);
6905: continue;
6906: }
1.126 brouard 6907: }
6908: for(cpt=1; cpt<=nlstate;cpt++) {
1.258 brouard 6909: fprintf(fichtm,"\n<br>- Observed (cross-sectional with mov_average=%d) and period (incidence based) \
1.241 brouard 6910: 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 6911: <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 6912: }
6913: fprintf(fichtm,"\n<br>- Total life expectancy by age and \
1.128 brouard 6914: health expectancies in states (1) and (2). If popbased=1 the smooth (due to the model) \
6915: true period expectancies (those weighted with period prevalences are also\
6916: drawn in addition to the population based expectancies computed using\
1.241 brouard 6917: observed and cahotic prevalences: <a href=\"%s_%d-%d.svg\">%s_%d-%d.svg</a>\n<br>\
6918: <img src=\"%s_%d-%d.svg\">",subdirf2(optionfilefiname,"E_"),k1,nres,subdirf2(optionfilefiname,"E_"),k1,nres,subdirf2(optionfilefiname,"E_"),k1,nres);
1.222 brouard 6919: /* } /\* end i1 *\/ */
6920: }/* End k1 */
1.241 brouard 6921: }/* End nres */
1.222 brouard 6922: fprintf(fichtm,"</ul>");
6923: fflush(fichtm);
1.126 brouard 6924: }
6925:
6926: /******************* Gnuplot file **************/
1.270 ! brouard 6927: 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 6928:
6929: char dirfileres[132],optfileres[132];
1.264 brouard 6930: char gplotcondition[132], gplotlabel[132];
1.237 brouard 6931: 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 6932: int lv=0, vlv=0, kl=0;
1.130 brouard 6933: int ng=0;
1.201 brouard 6934: int vpopbased;
1.223 brouard 6935: int ioffset; /* variable offset for columns */
1.270 ! brouard 6936: int iyearc=1; /* variable column for year of projection */
! 6937: int iagec=1; /* variable column for age of projection */
1.235 brouard 6938: int nres=0; /* Index of resultline */
1.266 brouard 6939: int istart=1; /* For starting graphs in projections */
1.219 brouard 6940:
1.126 brouard 6941: /* if((ficgp=fopen(optionfilegnuplot,"a"))==NULL) { */
6942: /* printf("Problem with file %s",optionfilegnuplot); */
6943: /* fprintf(ficlog,"Problem with file %s",optionfilegnuplot); */
6944: /* } */
6945:
6946: /*#ifdef windows */
6947: fprintf(ficgp,"cd \"%s\" \n",pathc);
1.223 brouard 6948: /*#endif */
1.225 brouard 6949: m=pow(2,cptcoveff);
1.126 brouard 6950:
1.202 brouard 6951: /* Contribution to likelihood */
6952: /* Plot the probability implied in the likelihood */
1.223 brouard 6953: fprintf(ficgp,"\n# Contributions to the Likelihood, mle >=1. For mle=4 no interpolation, pure matrix products.\n#\n");
6954: fprintf(ficgp,"\n set log y; unset log x;set xlabel \"Age\"; set ylabel \"Likelihood (-2Log(L))\";");
6955: /* fprintf(ficgp,"\nset ter svg size 640, 480"); */ /* Too big for svg */
6956: fprintf(ficgp,"\nset ter pngcairo size 640, 480");
1.204 brouard 6957: /* nice for mle=4 plot by number of matrix products.
1.202 brouard 6958: replot "rrtest1/toto.txt" u 2:($4 == 1 && $5==2 ? $9 : 1/0):5 t "p12" with point lc 1 */
6959: /* replot exp(p1+p2*x)/(1+exp(p1+p2*x)+exp(p3+p4*x)+exp(p5+p6*x)) t "p12(x)" */
1.223 brouard 6960: /* fprintf(ficgp,"\nset out \"%s.svg\";",subdirf2(optionfilefiname,"ILK_")); */
6961: fprintf(ficgp,"\nset out \"%s-dest.png\";",subdirf2(optionfilefiname,"ILK_"));
6962: 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));
6963: fprintf(ficgp,"\nset out \"%s-ori.png\";",subdirf2(optionfilefiname,"ILK_"));
6964: 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));
6965: for (i=1; i<= nlstate ; i ++) {
6966: fprintf(ficgp,"\nset out \"%s-p%dj.png\";set ylabel \"Probability for each individual/wave\";",subdirf2(optionfilefiname,"ILK_"),i);
6967: fprintf(ficgp,"unset log;\n# plot weighted, mean weight should have point size of 0.5\n plot \"%s\"",subdirf(fileresilk));
6968: 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);
6969: for (j=2; j<= nlstate+ndeath ; j ++) {
6970: 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);
6971: }
6972: fprintf(ficgp,";\nset out; unset ylabel;\n");
6973: }
6974: /* 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 */
6975: /* fprintf(ficgp,"\nset log y;plot \"%s\" u 2:(-$11):3 t \"All sample, all transitions\" with dots lc variable",subdirf(fileresilk)); */
6976: /* fprintf(ficgp,"\nreplot \"%s\" u 2:($3 <= 3 ? -$11 : 1/0):3 t \"First 3 individuals\" with line lc variable", subdirf(fileresilk)); */
6977: fprintf(ficgp,"\nset out;unset log\n");
6978: /* fprintf(ficgp,"\nset out \"%s.svg\"; replot; set out; # bug gnuplot",subdirf2(optionfilefiname,"ILK_")); */
1.202 brouard 6979:
1.126 brouard 6980: strcpy(dirfileres,optionfilefiname);
6981: strcpy(optfileres,"vpl");
1.223 brouard 6982: /* 1eme*/
1.238 brouard 6983: for (cpt=1; cpt<= nlstate ; cpt ++){ /* For each live state */
6984: for (k1=1; k1<= m ; k1 ++){ /* For each valid combination of covariate */
1.236 brouard 6985: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.238 brouard 6986: /* plot [100000000000000000000:-100000000000000000000] "mysbiaspar/vplrmysbiaspar.txt to check */
1.253 brouard 6987: if(m != 1 && TKresult[nres]!= k1)
1.238 brouard 6988: continue;
6989: /* We are interested in selected combination by the resultline */
1.246 brouard 6990: /* printf("\n# 1st: Period (stable) prevalence with CI: 'VPL_' files and live state =%d ", cpt); */
1.238 brouard 6991: fprintf(ficgp,"\n# 1st: Period (stable) prevalence with CI: 'VPL_' files and live state =%d ", cpt);
1.264 brouard 6992: strcpy(gplotlabel,"(");
1.238 brouard 6993: for (k=1; k<=cptcoveff; k++){ /* For each covariate k get corresponding value lv for combination k1 */
6994: lv= decodtabm(k1,k,cptcoveff); /* Should be the value of the covariate corresponding to k1 combination */
6995: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
6996: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
6997: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
6998: vlv= nbcode[Tvaraff[k]][lv]; /* vlv is the value of the covariate lv, 0 or 1 */
6999: /* For each combination of covariate k1 (V1=1, V3=0), we printed the current covariate k and its value vlv */
1.246 brouard 7000: /* printf(" V%d=%d ",Tvaraff[k],vlv); */
1.238 brouard 7001: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 7002: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.238 brouard 7003: }
7004: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
1.246 brouard 7005: /* printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
1.238 brouard 7006: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7007: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
7008: }
7009: strcpy(gplotlabel+strlen(gplotlabel),")");
1.246 brouard 7010: /* printf("\n#\n"); */
1.238 brouard 7011: fprintf(ficgp,"\n#\n");
7012: if(invalidvarcomb[k1]){
1.260 brouard 7013: /*k1=k1-1;*/ /* To be checked */
1.238 brouard 7014: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7015: continue;
7016: }
1.235 brouard 7017:
1.241 brouard 7018: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"V_"),cpt,k1,nres);
7019: fprintf(ficgp,"\n#set out \"V_%s_%d-%d-%d.svg\" \n",optionfilefiname,cpt,k1,nres);
1.264 brouard 7020: 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 7021: 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);
7022: /* 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); */
7023: /* k1-1 error should be nres-1*/
1.238 brouard 7024: for (i=1; i<= nlstate ; i ++) {
7025: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
7026: else fprintf(ficgp," %%*lf (%%*lf)");
7027: }
1.260 brouard 7028: 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 7029: for (i=1; i<= nlstate ; i ++) {
7030: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
7031: else fprintf(ficgp," %%*lf (%%*lf)");
7032: }
1.260 brouard 7033: fprintf(ficgp,"\" t\"95%% CI\" w l lt 1,\"%s\" every :::%d::%d u 1:($2==%d ? $3-1.96*$4 : 1/0) \"%%lf %%lf",subdirf2(fileresu,"VPL_"),nres-1,nres-1,nres);
1.238 brouard 7034: for (i=1; i<= nlstate ; i ++) {
7035: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
7036: else fprintf(ficgp," %%*lf (%%*lf)");
7037: }
1.265 brouard 7038: /* fprintf(ficgp,"\" t\"\" w l lt 1,\"%s\" every :::%d::%d u 1:($%d) t\"Observed prevalence\" w l lt 2",subdirf2(fileresu,"P_"),k1-1,k1-1,2+4*(cpt-1)); */
7039:
7040: fprintf(ficgp,"\" t\"\" w l lt 1,\"%s\" u 1:((",subdirf2(fileresu,"P_"));
7041: if(cptcoveff ==0){
7042: fprintf(ficgp,"$%d)) t 'Observed prevalence in state %d' with line lt 3", 2+(cpt-1), cpt );
7043: }else{
7044: kl=0;
7045: for (k=1; k<=cptcoveff; k++){ /* For each combination of covariate */
7046: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate value corresponding to k1 combination and kth covariate */
7047: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7048: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7049: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7050: vlv= nbcode[Tvaraff[k]][lv];
7051: kl++;
7052: /* 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 *\/ */
7053: /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */
7054: /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */
7055: /* '' u 6:(($1==1 && $2==0 && $3==2 && $4==0)? $9/(1.-$15) : 1/0):($5==2000? 3:2) t 'p.1' with line lc variable*/
7056: if(k==cptcoveff){
7057: fprintf(ficgp,"$%d==%d && $%d==%d)? $%d : 1/0) t 'Observed prevalence in state %d' w l lt 2",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][lv], \
7058: 2+cptcoveff*2+3*(cpt-1), cpt ); /* 4 or 6 ?*/
7059: }else{
7060: fprintf(ficgp,"$%d==%d && $%d==%d && ",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][lv]);
7061: kl++;
7062: }
7063: } /* end covariate */
7064: } /* end if no covariate */
7065:
1.238 brouard 7066: if(backcast==1){ /* We need to get the corresponding values of the covariates involved in this combination k1 */
7067: /* fprintf(ficgp,",\"%s\" every :::%d::%d u 1:($%d) t\"Backward stable prevalence\" w l lt 3",subdirf2(fileresu,"PLB_"),k1-1,k1-1,1+cpt); */
1.242 brouard 7068: fprintf(ficgp,",\"%s\" u 1:((",subdirf2(fileresu,"PLB_")); /* Age is in 1, nres in 2 to be fixed */
1.238 brouard 7069: if(cptcoveff ==0){
1.245 brouard 7070: fprintf(ficgp,"$%d)) t 'Backward prevalence in state %d' with line lt 3", 2+(cpt-1), cpt );
1.238 brouard 7071: }else{
7072: kl=0;
7073: for (k=1; k<=cptcoveff; k++){ /* For each combination of covariate */
7074: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate value corresponding to k1 combination and kth covariate */
7075: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7076: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7077: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7078: vlv= nbcode[Tvaraff[k]][lv];
1.223 brouard 7079: kl++;
1.238 brouard 7080: /* 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 *\/ */
7081: /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */
7082: /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */
7083: /* '' u 6:(($1==1 && $2==0 && $3==2 && $4==0)? $9/(1.-$15) : 1/0):($5==2000? 3:2) t 'p.1' with line lc variable*/
7084: if(k==cptcoveff){
1.245 brouard 7085: fprintf(ficgp,"$%d==%d && $%d==%d)? $%d : 1/0) t 'Backward prevalence in state %d' w l lt 3",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][lv], \
1.242 brouard 7086: 2+cptcoveff*2+(cpt-1), cpt ); /* 4 or 6 ?*/
1.238 brouard 7087: }else{
7088: fprintf(ficgp,"$%d==%d && $%d==%d && ",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][lv]);
7089: kl++;
7090: }
7091: } /* end covariate */
7092: } /* end if no covariate */
1.268 brouard 7093: if(backcast == 1){
7094: fprintf(ficgp,", \"%s\" every :::%d::%d u 1:($2==%d ? $3:1/0) \"%%lf %%lf",subdirf2(fileresu,"VBL_"),nres-1,nres-1,nres);
7095: /* k1-1 error should be nres-1*/
7096: for (i=1; i<= nlstate ; i ++) {
7097: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
7098: else fprintf(ficgp," %%*lf (%%*lf)");
7099: }
7100: fprintf(ficgp,"\" t\"Backward (stable) prevalence\" w l lt 0,\"%s\" every :::%d::%d u 1:($2==%d ? $3+1.96*$4 : 1/0) \"%%lf %%lf",subdirf2(fileresu,"VBL_"),nres-1,nres-1,nres);
7101: for (i=1; i<= nlstate ; i ++) {
7102: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
7103: else fprintf(ficgp," %%*lf (%%*lf)");
7104: }
7105: 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,"VBL_"),nres-1,nres-1,nres);
7106: for (i=1; i<= nlstate ; i ++) {
7107: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
7108: else fprintf(ficgp," %%*lf (%%*lf)");
7109: }
7110: fprintf(ficgp,"\" t\"\" w l lt 1");
7111: } /* end if backprojcast */
1.238 brouard 7112: } /* end if backcast */
1.264 brouard 7113: fprintf(ficgp,"\nset out ;unset label;\n");
1.238 brouard 7114: } /* nres */
1.201 brouard 7115: } /* k1 */
7116: } /* cpt */
1.235 brouard 7117:
7118:
1.126 brouard 7119: /*2 eme*/
1.238 brouard 7120: for (k1=1; k1<= m ; k1 ++){
7121: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 7122: if(m != 1 && TKresult[nres]!= k1)
1.238 brouard 7123: continue;
7124: fprintf(ficgp,"\n# 2nd: Total life expectancy with CI: 't' files ");
1.264 brouard 7125: strcpy(gplotlabel,"(");
1.238 brouard 7126: for (k=1; k<=cptcoveff; k++){ /* For each covariate and each value */
1.225 brouard 7127: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate number corresponding to k1 combination */
1.223 brouard 7128: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7129: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7130: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7131: vlv= nbcode[Tvaraff[k]][lv];
7132: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 7133: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.211 brouard 7134: }
1.237 brouard 7135: /* for(k=1; k <= ncovds; k++){ */
1.236 brouard 7136: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
1.238 brouard 7137: printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.236 brouard 7138: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7139: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.238 brouard 7140: }
1.264 brouard 7141: strcpy(gplotlabel+strlen(gplotlabel),")");
1.211 brouard 7142: fprintf(ficgp,"\n#\n");
1.223 brouard 7143: if(invalidvarcomb[k1]){
7144: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7145: continue;
7146: }
1.219 brouard 7147:
1.241 brouard 7148: fprintf(ficgp,"\nset out \"%s_%d-%d.svg\" \n",subdirf2(optionfilefiname,"E_"),k1,nres);
1.238 brouard 7149: for(vpopbased=0; vpopbased <= popbased; vpopbased++){ /* Done for vpopbased=0 and vpopbased=1 if popbased==1*/
1.264 brouard 7150: fprintf(ficgp,"\nset label \"popbased %d %s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",vpopbased,gplotlabel);
7151: if(vpopbased==0){
1.238 brouard 7152: fprintf(ficgp,"set ylabel \"Years\" \nset ter svg size 640, 480\nplot [%.f:%.f] ",ageminpar,fage);
1.264 brouard 7153: }else
1.238 brouard 7154: fprintf(ficgp,"\nreplot ");
7155: for (i=1; i<= nlstate+1 ; i ++) {
7156: k=2*i;
1.261 brouard 7157: 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 7158: for (j=1; j<= nlstate+1 ; j ++) {
7159: if (j==i) fprintf(ficgp," %%lf (%%lf)");
7160: else fprintf(ficgp," %%*lf (%%*lf)");
7161: }
7162: if (i== 1) fprintf(ficgp,"\" t\"TLE\" w l lt %d, \\\n",i);
7163: else fprintf(ficgp,"\" t\"LE in state (%d)\" w l lt %d, \\\n",i-1,i+1);
1.261 brouard 7164: 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 7165: for (j=1; j<= nlstate+1 ; j ++) {
7166: if (j==i) fprintf(ficgp," %%lf (%%lf)");
7167: else fprintf(ficgp," %%*lf (%%*lf)");
7168: }
7169: fprintf(ficgp,"\" t\"\" w l lt 0,");
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: if (i== (nlstate+1)) fprintf(ficgp,"\" t\"\" w l lt 0");
7176: else fprintf(ficgp,"\" t\"\" w l lt 0,\\\n");
7177: } /* state */
7178: } /* vpopbased */
1.264 brouard 7179: 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 7180: } /* end nres */
7181: } /* k1 end 2 eme*/
7182:
7183:
7184: /*3eme*/
7185: for (k1=1; k1<= m ; k1 ++){
7186: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 7187: if(m != 1 && TKresult[nres]!= k1)
1.238 brouard 7188: continue;
7189:
7190: for (cpt=1; cpt<= nlstate ; cpt ++) {
1.261 brouard 7191: fprintf(ficgp,"\n\n# 3d: Life expectancy with EXP_ files: combination=%d state=%d",k1, cpt);
1.264 brouard 7192: strcpy(gplotlabel,"(");
1.238 brouard 7193: for (k=1; k<=cptcoveff; k++){ /* For each covariate and each value */
7194: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate number corresponding to k1 combination */
7195: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7196: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7197: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7198: vlv= nbcode[Tvaraff[k]][lv];
7199: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 7200: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.238 brouard 7201: }
7202: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7203: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7204: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.238 brouard 7205: }
1.264 brouard 7206: strcpy(gplotlabel+strlen(gplotlabel),")");
1.238 brouard 7207: fprintf(ficgp,"\n#\n");
7208: if(invalidvarcomb[k1]){
7209: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7210: continue;
7211: }
7212:
7213: /* k=2+nlstate*(2*cpt-2); */
7214: k=2+(nlstate+1)*(cpt-1);
1.241 brouard 7215: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"EXP_"),cpt,k1,nres);
1.264 brouard 7216: fprintf(ficgp,"set label \"%s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",gplotlabel);
1.238 brouard 7217: fprintf(ficgp,"set ter svg size 640, 480\n\
1.261 brouard 7218: 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 7219: /*fprintf(ficgp,",\"e%s\" every :::%d::%d u 1:($%d-2*$%d) \"\%%lf ",fileres,k1-1,k1-1,k,k+1);
7220: for (i=1; i<= nlstate*2 ; i ++) fprintf(ficgp,"\%%lf (\%%lf) ");
7221: fprintf(ficgp,"\" t \"e%d1\" w l",cpt);
7222: fprintf(ficgp,",\"e%s\" every :::%d::%d u 1:($%d+2*$%d) \"\%%lf ",fileres,k1-1,k1-1,k,k+1);
7223: for (i=1; i<= nlstate*2 ; i ++) fprintf(ficgp,"\%%lf (\%%lf) ");
7224: fprintf(ficgp,"\" t \"e%d1\" w l",cpt);
1.219 brouard 7225:
1.238 brouard 7226: */
7227: for (i=1; i< nlstate ; i ++) {
1.261 brouard 7228: 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 7229: /* 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 7230:
1.238 brouard 7231: }
1.261 brouard 7232: 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 7233: }
1.264 brouard 7234: fprintf(ficgp,"\nunset label;\n");
1.238 brouard 7235: } /* end nres */
7236: } /* end kl 3eme */
1.126 brouard 7237:
1.223 brouard 7238: /* 4eme */
1.201 brouard 7239: /* Survival functions (period) from state i in state j by initial state i */
1.238 brouard 7240: for (k1=1; k1<=m; k1++){ /* For each covariate and each value */
7241: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 7242: if(m != 1 && TKresult[nres]!= k1)
1.223 brouard 7243: continue;
1.238 brouard 7244: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state cpt*/
1.264 brouard 7245: strcpy(gplotlabel,"(");
1.238 brouard 7246: fprintf(ficgp,"\n#\n#\n# Survival functions in state j : 'LIJ_' files, cov=%d state=%d",k1, cpt);
7247: for (k=1; k<=cptcoveff; k++){ /* For each covariate and each value */
7248: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate number corresponding to k1 combination */
7249: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7250: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7251: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7252: vlv= nbcode[Tvaraff[k]][lv];
7253: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 7254: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.238 brouard 7255: }
7256: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7257: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7258: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.238 brouard 7259: }
1.264 brouard 7260: strcpy(gplotlabel+strlen(gplotlabel),")");
1.238 brouard 7261: fprintf(ficgp,"\n#\n");
7262: if(invalidvarcomb[k1]){
7263: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7264: continue;
1.223 brouard 7265: }
1.238 brouard 7266:
1.241 brouard 7267: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"LIJ_"),cpt,k1,nres);
1.264 brouard 7268: 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 7269: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability to be alive\" \n\
7270: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
7271: k=3;
7272: for (i=1; i<= nlstate ; i ++){
7273: if(i==1){
7274: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJ_"));
7275: }else{
7276: fprintf(ficgp,", '' ");
7277: }
7278: l=(nlstate+ndeath)*(i-1)+1;
7279: fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d/($%d",k1,k+l+(cpt-1),k+l);
7280: for (j=2; j<= nlstate+ndeath ; j ++)
7281: fprintf(ficgp,"+$%d",k+l+j-1);
7282: fprintf(ficgp,")) t \"l(%d,%d)\" w l",i,cpt);
7283: } /* nlstate */
1.264 brouard 7284: fprintf(ficgp,"\nset out; unset label;\n");
1.238 brouard 7285: } /* end cpt state*/
7286: } /* end nres */
7287: } /* end covariate k1 */
7288:
1.220 brouard 7289: /* 5eme */
1.201 brouard 7290: /* Survival functions (period) from state i in state j by final state j */
1.238 brouard 7291: for (k1=1; k1<= m ; k1++){ /* For each covariate combination if any */
7292: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 7293: if(m != 1 && TKresult[nres]!= k1)
1.227 brouard 7294: continue;
1.238 brouard 7295: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each inital state */
1.264 brouard 7296: strcpy(gplotlabel,"(");
1.238 brouard 7297: 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);
7298: for (k=1; k<=cptcoveff; k++){ /* For each covariate and each value */
7299: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate number corresponding to k1 combination */
7300: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7301: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7302: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7303: vlv= nbcode[Tvaraff[k]][lv];
7304: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 7305: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.238 brouard 7306: }
7307: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7308: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7309: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.238 brouard 7310: }
1.264 brouard 7311: strcpy(gplotlabel+strlen(gplotlabel),")");
1.238 brouard 7312: fprintf(ficgp,"\n#\n");
7313: if(invalidvarcomb[k1]){
7314: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7315: continue;
7316: }
1.227 brouard 7317:
1.241 brouard 7318: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"LIJT_"),cpt,k1,nres);
1.264 brouard 7319: 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 7320: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability to be alive\" \n\
7321: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
7322: k=3;
7323: for (j=1; j<= nlstate ; j ++){ /* Lived in state j */
7324: if(j==1)
7325: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJ_"));
7326: else
7327: fprintf(ficgp,", '' ");
7328: l=(nlstate+ndeath)*(cpt-1) +j;
7329: fprintf(ficgp," u (($1==%d && (floor($2)%%5 == 0)) ? ($3):1/0):($%d",k1,k+l);
7330: /* for (i=2; i<= nlstate+ndeath ; i ++) */
7331: /* fprintf(ficgp,"+$%d",k+l+i-1); */
7332: fprintf(ficgp,") t \"l(%d,%d)\" w l",cpt,j);
7333: } /* nlstate */
7334: fprintf(ficgp,", '' ");
7335: fprintf(ficgp," u (($1==%d && (floor($2)%%5 == 0)) ? ($3):1/0):(",k1);
7336: for (j=1; j<= nlstate ; j ++){ /* Lived in state j */
7337: l=(nlstate+ndeath)*(cpt-1) +j;
7338: if(j < nlstate)
7339: fprintf(ficgp,"$%d +",k+l);
7340: else
7341: fprintf(ficgp,"$%d) t\"l(%d,.)\" w l",k+l,cpt);
7342: }
1.264 brouard 7343: fprintf(ficgp,"\nset out; unset label;\n");
1.238 brouard 7344: } /* end cpt state*/
7345: } /* end covariate */
7346: } /* end nres */
1.227 brouard 7347:
1.220 brouard 7348: /* 6eme */
1.202 brouard 7349: /* CV preval stable (period) for each covariate */
1.237 brouard 7350: for (k1=1; k1<= m ; k1 ++) /* For each covariate combination if any */
7351: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 7352: if(m != 1 && TKresult[nres]!= k1)
1.237 brouard 7353: continue;
1.255 brouard 7354: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state of arrival */
1.264 brouard 7355: strcpy(gplotlabel,"(");
1.211 brouard 7356: fprintf(ficgp,"\n#\n#\n#CV preval stable (period): 'pij' files, covariatecombination#=%d state=%d",k1, cpt);
1.225 brouard 7357: for (k=1; k<=cptcoveff; k++){ /* For each covariate and each value */
1.227 brouard 7358: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate number corresponding to k1 combination */
7359: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7360: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7361: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7362: vlv= nbcode[Tvaraff[k]][lv];
7363: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 7364: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.211 brouard 7365: }
1.237 brouard 7366: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7367: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7368: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.237 brouard 7369: }
1.264 brouard 7370: strcpy(gplotlabel+strlen(gplotlabel),")");
1.211 brouard 7371: fprintf(ficgp,"\n#\n");
1.223 brouard 7372: if(invalidvarcomb[k1]){
1.227 brouard 7373: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7374: continue;
1.223 brouard 7375: }
1.227 brouard 7376:
1.241 brouard 7377: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"P_"),cpt,k1,nres);
1.264 brouard 7378: 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 7379: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability\" \n\
1.238 brouard 7380: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
1.211 brouard 7381: k=3; /* Offset */
1.255 brouard 7382: for (i=1; i<= nlstate ; i ++){ /* State of origin */
1.227 brouard 7383: if(i==1)
7384: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJ_"));
7385: else
7386: fprintf(ficgp,", '' ");
1.255 brouard 7387: l=(nlstate+ndeath)*(i-1)+1; /* 1, 1+ nlstate+ndeath, 1+2*(nlstate+ndeath) */
1.227 brouard 7388: fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d/($%d",k1,k+l+(cpt-1),k+l);
7389: for (j=2; j<= nlstate ; j ++)
7390: fprintf(ficgp,"+$%d",k+l+j-1);
7391: fprintf(ficgp,")) t \"prev(%d,%d)\" w l",i,cpt);
1.153 brouard 7392: } /* nlstate */
1.264 brouard 7393: fprintf(ficgp,"\nset out; unset label;\n");
1.153 brouard 7394: } /* end cpt state*/
7395: } /* end covariate */
1.227 brouard 7396:
7397:
1.220 brouard 7398: /* 7eme */
1.218 brouard 7399: if(backcast == 1){
1.217 brouard 7400: /* CV back preval stable (period) for each covariate */
1.237 brouard 7401: for (k1=1; k1<= m ; k1 ++) /* For each covariate combination if any */
7402: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 7403: if(m != 1 && TKresult[nres]!= k1)
1.237 brouard 7404: continue;
1.268 brouard 7405: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life origin state */
1.264 brouard 7406: strcpy(gplotlabel,"(");
7407: fprintf(ficgp,"\n#\n#\n#CV Back preval stable (period): 'pijb' files, covariatecombination#=%d state=%d",k1, cpt);
1.227 brouard 7408: for (k=1; k<=cptcoveff; k++){ /* For each covariate and each value */
7409: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate number corresponding to k1 combination */
7410: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7411: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
1.223 brouard 7412: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
1.227 brouard 7413: vlv= nbcode[Tvaraff[k]][lv];
7414: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 7415: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.227 brouard 7416: }
1.237 brouard 7417: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7418: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7419: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.237 brouard 7420: }
1.264 brouard 7421: strcpy(gplotlabel+strlen(gplotlabel),")");
1.227 brouard 7422: fprintf(ficgp,"\n#\n");
7423: if(invalidvarcomb[k1]){
7424: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7425: continue;
7426: }
7427:
1.241 brouard 7428: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"PB_"),cpt,k1,nres);
1.268 brouard 7429: 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 7430: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability\" \n\
1.238 brouard 7431: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
1.227 brouard 7432: k=3; /* Offset */
1.268 brouard 7433: for (i=1; i<= nlstate ; i ++){ /* State of arrival */
1.227 brouard 7434: if(i==1)
7435: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJB_"));
7436: else
7437: fprintf(ficgp,", '' ");
7438: /* l=(nlstate+ndeath)*(i-1)+1; */
1.255 brouard 7439: l=(nlstate+ndeath)*(cpt-1)+1; /* fixed for i; cpt=1 1, cpt=2 1+ nlstate+ndeath, 1+2*(nlstate+ndeath) */
1.227 brouard 7440: /* fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d/($%d",k1,k+l+(cpt-1),k+l); /\* a vérifier *\/ */
7441: /* 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 7442: fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d",k1,k+l+i-1); /* To be verified */
1.227 brouard 7443: /* for (j=2; j<= nlstate ; j ++) */
7444: /* fprintf(ficgp,"+$%d",k+l+j-1); */
7445: /* /\* fprintf(ficgp,"+$%d",k+l+j-1); *\/ */
1.268 brouard 7446: fprintf(ficgp,") t \"bprev(%d,%d)\" w l",cpt,i);
1.227 brouard 7447: } /* nlstate */
1.264 brouard 7448: fprintf(ficgp,"\nset out; unset label;\n");
1.218 brouard 7449: } /* end cpt state*/
7450: } /* end covariate */
7451: } /* End if backcast */
7452:
1.223 brouard 7453: /* 8eme */
1.218 brouard 7454: if(prevfcast==1){
7455: /* Projection from cross-sectional to stable (period) for each covariate */
7456:
1.237 brouard 7457: for (k1=1; k1<= m ; k1 ++) /* For each covariate combination if any */
7458: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 7459: if(m != 1 && TKresult[nres]!= k1)
1.237 brouard 7460: continue;
1.211 brouard 7461: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state */
1.264 brouard 7462: strcpy(gplotlabel,"(");
1.227 brouard 7463: fprintf(ficgp,"\n#\n#\n#Projection of prevalence to stable (period): 'PROJ_' files, covariatecombination#=%d state=%d",k1, cpt);
7464: for (k=1; k<=cptcoveff; k++){ /* For each correspondig covariate value */
7465: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate value corresponding to k1 combination and kth covariate */
7466: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7467: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7468: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7469: vlv= nbcode[Tvaraff[k]][lv];
7470: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 7471: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.227 brouard 7472: }
1.237 brouard 7473: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7474: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7475: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.237 brouard 7476: }
1.264 brouard 7477: strcpy(gplotlabel+strlen(gplotlabel),")");
1.227 brouard 7478: fprintf(ficgp,"\n#\n");
7479: if(invalidvarcomb[k1]){
7480: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7481: continue;
7482: }
7483:
7484: fprintf(ficgp,"# hpijx=probability over h years, hp.jx is weighted by observed prev\n ");
1.241 brouard 7485: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"PROJ_"),cpt,k1,nres);
1.264 brouard 7486: 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 7487: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Prevalence\" \n\
1.238 brouard 7488: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
1.266 brouard 7489:
7490: /* for (i=1; i<= nlstate+1 ; i ++){ /\* nlstate +1 p11 p21 p.1 *\/ */
7491: istart=nlstate+1; /* Could be one if by state, but nlstate+1 is w.i projection only */
7492: /*istart=1;*/ /* Could be one if by state, but nlstate+1 is w.i projection only */
7493: for (i=istart; i<= nlstate+1 ; i ++){ /* nlstate +1 p11 p21 p.1 */
1.227 brouard 7494: /*# V1 = 1 V2 = 0 yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
7495: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
7496: /*# yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
7497: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
1.266 brouard 7498: if(i==istart){
1.227 brouard 7499: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"F_"));
7500: }else{
7501: fprintf(ficgp,",\\\n '' ");
7502: }
7503: if(cptcoveff ==0){ /* No covariate */
7504: ioffset=2; /* Age is in 2 */
7505: /*# yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/
7506: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */
7507: /*# V1 = 1 yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/
7508: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */
7509: fprintf(ficgp," u %d:(", ioffset);
1.266 brouard 7510: if(i==nlstate+1){
1.270 ! brouard 7511: fprintf(ficgp," $%d/(1.-$%d)):1 t 'pw.%d' with line lc variable ", \
1.266 brouard 7512: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,cpt );
7513: fprintf(ficgp,",\\\n '' ");
7514: fprintf(ficgp," u %d:(",ioffset);
1.270 ! brouard 7515: fprintf(ficgp," (($1-$2) == %d ) ? $%d/(1.-$%d) : 1/0):1 with labels center not ", \
1.266 brouard 7516: offyear, \
1.268 brouard 7517: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate );
1.266 brouard 7518: }else
1.227 brouard 7519: fprintf(ficgp," $%d/(1.-$%d)) t 'p%d%d' with line ", \
7520: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,i,cpt );
7521: }else{ /* more than 2 covariates */
1.270 ! brouard 7522: ioffset=2*cptcoveff+2; /* Age is in 4 or 6 or etc.*/
! 7523: /*# V1 = 1 V2 = 0 yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
! 7524: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
! 7525: iyearc=ioffset-1;
! 7526: iagec=ioffset;
1.227 brouard 7527: fprintf(ficgp," u %d:(",ioffset);
7528: kl=0;
7529: strcpy(gplotcondition,"(");
7530: for (k=1; k<=cptcoveff; k++){ /* For each covariate writing the chain of conditions */
7531: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate value corresponding to combination k1 and covariate k */
7532: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7533: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7534: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7535: vlv= nbcode[Tvaraff[k]][lv]; /* Value of the modality of Tvaraff[k] */
7536: kl++;
7537: sprintf(gplotcondition+strlen(gplotcondition),"$%d==%d && $%d==%d " ,kl,Tvaraff[k], kl+1, nbcode[Tvaraff[k]][lv]);
7538: kl++;
7539: if(k <cptcoveff && cptcoveff>1)
7540: sprintf(gplotcondition+strlen(gplotcondition)," && ");
7541: }
7542: strcpy(gplotcondition+strlen(gplotcondition),")");
7543: /* 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 *\/ */
7544: /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */
7545: /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */
7546: /* '' 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*/
7547: if(i==nlstate+1){
1.270 ! brouard 7548: fprintf(ficgp,"%s ? $%d/(1.-$%d) : 1/0):%d t 'p.%d' with line lc variable", gplotcondition, \
! 7549: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,iyearc, cpt );
1.266 brouard 7550: fprintf(ficgp,",\\\n '' ");
1.270 ! brouard 7551: fprintf(ficgp," u %d:(",iagec);
! 7552: fprintf(ficgp,"%s && (($%d-$%d) == %d ) ? $%d/(1.-$%d) : 1/0):%d with labels center not ", gplotcondition, \
! 7553: iyearc, iagec, offyear, \
! 7554: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate, iyearc );
1.266 brouard 7555: /* '' 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 7556: }else{
7557: fprintf(ficgp,"%s ? $%d/(1.-$%d) : 1/0) t 'p%d%d' with line ", gplotcondition, \
7558: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset +1+(i-1)+(nlstate+1)*nlstate,i,cpt );
7559: }
7560: } /* end if covariate */
7561: } /* nlstate */
1.264 brouard 7562: fprintf(ficgp,"\nset out; unset label;\n");
1.223 brouard 7563: } /* end cpt state*/
7564: } /* end covariate */
7565: } /* End if prevfcast */
1.227 brouard 7566:
1.268 brouard 7567: if(backcast==1){
7568: /* Back projection from cross-sectional to stable (mixed) for each covariate */
7569:
7570: for (k1=1; k1<= m ; k1 ++) /* For each covariate combination if any */
7571: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
7572: if(m != 1 && TKresult[nres]!= k1)
7573: continue;
7574: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state */
7575: strcpy(gplotlabel,"(");
7576: fprintf(ficgp,"\n#\n#\n#Back projection of prevalence to stable (mixed) back prevalence: 'BPROJ_' files, covariatecombination#=%d originstate=%d",k1, cpt);
7577: for (k=1; k<=cptcoveff; k++){ /* For each correspondig covariate value */
7578: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate value corresponding to k1 combination and kth covariate */
7579: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7580: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7581: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7582: vlv= nbcode[Tvaraff[k]][lv];
7583: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
7584: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
7585: }
7586: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7587: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
7588: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
7589: }
7590: strcpy(gplotlabel+strlen(gplotlabel),")");
7591: fprintf(ficgp,"\n#\n");
7592: if(invalidvarcomb[k1]){
7593: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7594: continue;
7595: }
7596:
7597: fprintf(ficgp,"# hbijx=backprobability over h years, hb.jx is weighted by observed prev at destination state\n ");
7598: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"PROJB_"),cpt,k1,nres);
7599: fprintf(ficgp,"set label \"Origin alive state %d %s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",cpt,gplotlabel);
7600: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Prevalence\" \n\
7601: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
7602:
7603: /* for (i=1; i<= nlstate+1 ; i ++){ /\* nlstate +1 p11 p21 p.1 *\/ */
7604: istart=nlstate+1; /* Could be one if by state, but nlstate+1 is w.i projection only */
7605: /*istart=1;*/ /* Could be one if by state, but nlstate+1 is w.i projection only */
7606: for (i=istart; i<= nlstate+1 ; i ++){ /* nlstate +1 p11 p21 p.1 */
7607: /*# V1 = 1 V2 = 0 yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
7608: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
7609: /*# yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
7610: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
7611: if(i==istart){
7612: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"FB_"));
7613: }else{
7614: fprintf(ficgp,",\\\n '' ");
7615: }
7616: if(cptcoveff ==0){ /* No covariate */
7617: ioffset=2; /* Age is in 2 */
7618: /*# yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/
7619: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */
7620: /*# V1 = 1 yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/
7621: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */
7622: fprintf(ficgp," u %d:(", ioffset);
7623: if(i==nlstate+1){
1.270 ! brouard 7624: fprintf(ficgp," $%d/(1.-$%d)):1 t 'bw%d' with line lc variable ", \
1.268 brouard 7625: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,cpt );
7626: fprintf(ficgp,",\\\n '' ");
7627: fprintf(ficgp," u %d:(",ioffset);
1.270 ! brouard 7628: fprintf(ficgp," (($1-$2) == %d ) ? $%d : 1/0):1 with labels center not ", \
1.268 brouard 7629: offbyear, \
7630: ioffset+(cpt-1)*(nlstate+1)+1+(i-1) );
7631: }else
7632: fprintf(ficgp," $%d/(1.-$%d)) t 'b%d%d' with line ", \
7633: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,cpt,i );
7634: }else{ /* more than 2 covariates */
1.270 ! brouard 7635: ioffset=2*cptcoveff+2; /* Age is in 4 or 6 or etc.*/
! 7636: /*# V1 = 1 V2 = 0 yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
! 7637: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
! 7638: iyearc=ioffset-1;
! 7639: iagec=ioffset;
1.268 brouard 7640: fprintf(ficgp," u %d:(",ioffset);
7641: kl=0;
7642: strcpy(gplotcondition,"(");
7643: for (k=1; k<=cptcoveff; k++){ /* For each covariate writing the chain of conditions */
7644: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate value corresponding to combination k1 and covariate k */
7645: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7646: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7647: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7648: vlv= nbcode[Tvaraff[k]][lv]; /* Value of the modality of Tvaraff[k] */
7649: kl++;
7650: sprintf(gplotcondition+strlen(gplotcondition),"$%d==%d && $%d==%d " ,kl,Tvaraff[k], kl+1, nbcode[Tvaraff[k]][lv]);
7651: kl++;
7652: if(k <cptcoveff && cptcoveff>1)
7653: sprintf(gplotcondition+strlen(gplotcondition)," && ");
7654: }
7655: strcpy(gplotcondition+strlen(gplotcondition),")");
7656: /* 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 *\/ */
7657: /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */
7658: /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */
7659: /* '' 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*/
7660: if(i==nlstate+1){
1.270 ! brouard 7661: fprintf(ficgp,"%s ? $%d : 1/0):%d t 'bw%d' with line lc variable", gplotcondition, \
! 7662: ioffset+(cpt-1)*(nlstate+1)+1+(i-1),iyearc,cpt );
1.268 brouard 7663: fprintf(ficgp,",\\\n '' ");
1.270 ! brouard 7664: fprintf(ficgp," u %d:(",iagec);
1.268 brouard 7665: /* fprintf(ficgp,"%s && (($5-$6) == %d ) ? $%d/(1.-$%d) : 1/0):5 with labels center not ", gplotcondition, \ */
1.270 ! brouard 7666: fprintf(ficgp,"%s && (($%d-$%d) == %d ) ? $%d : 1/0):%d with labels center not ", gplotcondition, \
! 7667: iyearc,iagec,offbyear, \
! 7668: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), iyearc );
1.268 brouard 7669: /* '' u 6:(($1==1 && $2==0 && $3==2 && $4==0) && (($5-$6) == 1947) ? $10/(1.-$22) : 1/0):5 with labels center boxed not*/
7670: }else{
7671: /* fprintf(ficgp,"%s ? $%d/(1.-$%d) : 1/0) t 'p%d%d' with line ", gplotcondition, \ */
7672: fprintf(ficgp,"%s ? $%d : 1/0) t 'b%d%d' with line ", gplotcondition, \
7673: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), cpt,i );
7674: }
7675: } /* end if covariate */
7676: } /* nlstate */
7677: fprintf(ficgp,"\nset out; unset label;\n");
7678: } /* end cpt state*/
7679: } /* end covariate */
7680: } /* End if backcast */
7681:
1.227 brouard 7682:
1.238 brouard 7683: /* 9eme writing MLE parameters */
7684: fprintf(ficgp,"\n##############\n#9eme MLE estimated parameters\n#############\n");
1.126 brouard 7685: for(i=1,jk=1; i <=nlstate; i++){
1.187 brouard 7686: fprintf(ficgp,"# initial state %d\n",i);
1.126 brouard 7687: for(k=1; k <=(nlstate+ndeath); k++){
7688: if (k != i) {
1.227 brouard 7689: fprintf(ficgp,"# current state %d\n",k);
7690: for(j=1; j <=ncovmodel; j++){
7691: fprintf(ficgp,"p%d=%f; ",jk,p[jk]);
7692: jk++;
7693: }
7694: fprintf(ficgp,"\n");
1.126 brouard 7695: }
7696: }
1.223 brouard 7697: }
1.187 brouard 7698: fprintf(ficgp,"##############\n#\n");
1.227 brouard 7699:
1.145 brouard 7700: /*goto avoid;*/
1.238 brouard 7701: /* 10eme Graphics of probabilities or incidences using written MLE parameters */
7702: fprintf(ficgp,"\n##############\n#10eme Graphics of probabilities or incidences\n#############\n");
1.187 brouard 7703: fprintf(ficgp,"# logi(p12/p11)=a12+b12*age+c12age*age+d12*V1+e12*V1*age\n");
7704: fprintf(ficgp,"# logi(p12/p11)=p1 +p2*age +p3*age*age+ p4*V1+ p5*V1*age\n");
7705: fprintf(ficgp,"# logi(p13/p11)=a13+b13*age+c13age*age+d13*V1+e13*V1*age\n");
7706: fprintf(ficgp,"# logi(p13/p11)=p6 +p7*age +p8*age*age+ p9*V1+ p10*V1*age\n");
7707: fprintf(ficgp,"# p12+p13+p14+p11=1=p11(1+exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)\n");
7708: fprintf(ficgp,"# +exp(a13+b13*age+c13age*age+d13*V1+e13*V1*age)+...)\n");
7709: fprintf(ficgp,"# p11=1/(1+exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)\n");
7710: fprintf(ficgp,"# +exp(a13+b13*age+c13age*age+d13*V1+e13*V1*age)+...)\n");
7711: fprintf(ficgp,"# p12=exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)/\n");
7712: fprintf(ficgp,"# (1+exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)\n");
7713: fprintf(ficgp,"# +exp(a13+b13*age+c13age*age+d13*V1+e13*V1*age))\n");
7714: fprintf(ficgp,"# +exp(a14+b14*age+c14age*age+d14*V1+e14*V1*age)+...)\n");
7715: fprintf(ficgp,"#\n");
1.223 brouard 7716: for(ng=1; ng<=3;ng++){ /* Number of graphics: first is logit, 2nd is probabilities, third is incidences per year*/
1.238 brouard 7717: fprintf(ficgp,"#Number of graphics: first is logit, 2nd is probabilities, third is incidences per year\n");
1.237 brouard 7718: fprintf(ficgp,"#model=%s \n",model);
1.238 brouard 7719: fprintf(ficgp,"# Type of graphic ng=%d\n",ng);
1.264 brouard 7720: fprintf(ficgp,"# k1=1 to 2^%d=%d\n",cptcoveff,m);/* to be checked */
7721: for(k1=1; k1 <=m; k1++) /* For each combination of covariate */
1.237 brouard 7722: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.264 brouard 7723: if(m != 1 && TKresult[nres]!= k1)
1.237 brouard 7724: continue;
1.264 brouard 7725: fprintf(ficgp,"\n\n# Combination of dummy k1=%d which is ",k1);
7726: strcpy(gplotlabel,"(");
7727: sprintf(gplotlabel+strlen(gplotlabel)," Dummy combination %d ",k1);
7728: for (k=1; k<=cptcoveff; k++){ /* For each correspondig covariate value */
7729: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate value corresponding to k1 combination and kth covariate */
7730: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7731: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7732: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7733: vlv= nbcode[Tvaraff[k]][lv];
7734: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
7735: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
7736: }
1.237 brouard 7737: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7738: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7739: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.237 brouard 7740: }
1.264 brouard 7741: strcpy(gplotlabel+strlen(gplotlabel),")");
1.237 brouard 7742: fprintf(ficgp,"\n#\n");
1.264 brouard 7743: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" ",subdirf2(optionfilefiname,"PE_"),k1,ng,nres);
7744: fprintf(ficgp,"\nset label \"%s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",gplotlabel);
1.223 brouard 7745: fprintf(ficgp,"\nset ter svg size 640, 480 ");
7746: if (ng==1){
7747: fprintf(ficgp,"\nset ylabel \"Value of the logit of the model\"\n"); /* exp(a12+b12*x) could be nice */
7748: fprintf(ficgp,"\nunset log y");
7749: }else if (ng==2){
7750: fprintf(ficgp,"\nset ylabel \"Probability\"\n");
7751: fprintf(ficgp,"\nset log y");
7752: }else if (ng==3){
7753: fprintf(ficgp,"\nset ylabel \"Quasi-incidence per year\"\n");
7754: fprintf(ficgp,"\nset log y");
7755: }else
7756: fprintf(ficgp,"\nunset title ");
7757: fprintf(ficgp,"\nplot [%.f:%.f] ",ageminpar,agemaxpar);
7758: i=1;
7759: for(k2=1; k2<=nlstate; k2++) {
7760: k3=i;
7761: for(k=1; k<=(nlstate+ndeath); k++) {
7762: if (k != k2){
7763: switch( ng) {
7764: case 1:
7765: if(nagesqr==0)
7766: fprintf(ficgp," p%d+p%d*x",i,i+1);
7767: else /* nagesqr =1 */
7768: fprintf(ficgp," p%d+p%d*x+p%d*x*x",i,i+1,i+1+nagesqr);
7769: break;
7770: case 2: /* ng=2 */
7771: if(nagesqr==0)
7772: fprintf(ficgp," exp(p%d+p%d*x",i,i+1);
7773: else /* nagesqr =1 */
7774: fprintf(ficgp," exp(p%d+p%d*x+p%d*x*x",i,i+1,i+1+nagesqr);
7775: break;
7776: case 3:
7777: if(nagesqr==0)
7778: fprintf(ficgp," %f*exp(p%d+p%d*x",YEARM/stepm,i,i+1);
7779: else /* nagesqr =1 */
7780: fprintf(ficgp," %f*exp(p%d+p%d*x+p%d*x*x",YEARM/stepm,i,i+1,i+1+nagesqr);
7781: break;
7782: }
7783: ij=1;/* To be checked else nbcode[0][0] wrong */
1.237 brouard 7784: ijp=1; /* product no age */
7785: /* for(j=3; j <=ncovmodel-nagesqr; j++) { */
7786: for(j=1; j <=cptcovt; j++) { /* For each covariate of the simplified model */
1.223 brouard 7787: /* printf("Tage[%d]=%d, j=%d\n", ij, Tage[ij], j); */
1.268 brouard 7788: if(cptcovage >0){ /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, 2 V5 and V1 */
7789: if(j==Tage[ij]) { /* Product by age To be looked at!!*/
7790: if(ij <=cptcovage) { /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, 2 V5 and V1 */
7791: if(DummyV[j]==0){
7792: fprintf(ficgp,"+p%d*%d*x",i+j+2+nagesqr-1,Tinvresult[nres][Tvar[j]]);;
7793: }else{ /* quantitative */
7794: fprintf(ficgp,"+p%d*%f*x",i+j+2+nagesqr-1,Tqinvresult[nres][Tvar[j]]); /* Tqinvresult in decoderesult */
7795: /* fprintf(ficgp,"+p%d*%d*x",i+j+nagesqr-1,nbcode[Tvar[j-2]][codtabm(k1,Tvar[j-2])]); */
7796: }
7797: ij++;
1.237 brouard 7798: }
1.268 brouard 7799: }
7800: }else if(cptcovprod >0){
7801: if(j==Tprod[ijp]) { /* */
7802: /* printf("Tprod[%d]=%d, j=%d\n", ij, Tprod[ijp], j); */
7803: if(ijp <=cptcovprod) { /* Product */
7804: if(DummyV[Tvard[ijp][1]]==0){/* Vn is dummy */
7805: if(DummyV[Tvard[ijp][2]]==0){/* Vn and Vm are dummy */
7806: /* 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)]); */
7807: fprintf(ficgp,"+p%d*%d*%d",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tinvresult[nres][Tvard[ijp][2]]);
7808: }else{ /* Vn is dummy and Vm is quanti */
7809: /* fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,nbcode[Tvard[ijp][1]][codtabm(k1,j)],Tqinvresult[nres][Tvard[ijp][2]]); */
7810: fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]);
7811: }
7812: }else{ /* Vn*Vm Vn is quanti */
7813: if(DummyV[Tvard[ijp][2]]==0){
7814: fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][2]],Tqinvresult[nres][Tvard[ijp][1]]);
7815: }else{ /* Both quanti */
7816: fprintf(ficgp,"+p%d*%f*%f",i+j+2+nagesqr-1,Tqinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]);
7817: }
1.237 brouard 7818: }
1.268 brouard 7819: ijp++;
1.237 brouard 7820: }
1.268 brouard 7821: } /* end Tprod */
1.237 brouard 7822: } else{ /* simple covariate */
1.264 brouard 7823: /* fprintf(ficgp,"+p%d*%d",i+j+2+nagesqr-1,nbcode[Tvar[j]][codtabm(k1,j)]); /\* Valgrind bug nbcode *\/ */
1.237 brouard 7824: if(Dummy[j]==0){
7825: fprintf(ficgp,"+p%d*%d",i+j+2+nagesqr-1,Tinvresult[nres][Tvar[j]]); /* */
7826: }else{ /* quantitative */
7827: fprintf(ficgp,"+p%d*%f",i+j+2+nagesqr-1,Tqinvresult[nres][Tvar[j]]); /* */
1.264 brouard 7828: /* fprintf(ficgp,"+p%d*%d*x",i+j+nagesqr-1,nbcode[Tvar[j-2]][codtabm(k1,Tvar[j-2])]); */
1.223 brouard 7829: }
1.237 brouard 7830: } /* end simple */
7831: } /* end j */
1.223 brouard 7832: }else{
7833: i=i-ncovmodel;
7834: if(ng !=1 ) /* For logit formula of log p11 is more difficult to get */
7835: fprintf(ficgp," (1.");
7836: }
1.227 brouard 7837:
1.223 brouard 7838: if(ng != 1){
7839: fprintf(ficgp,")/(1");
1.227 brouard 7840:
1.264 brouard 7841: for(cpt=1; cpt <=nlstate; cpt++){
1.223 brouard 7842: if(nagesqr==0)
1.264 brouard 7843: fprintf(ficgp,"+exp(p%d+p%d*x",k3+(cpt-1)*ncovmodel,k3+(cpt-1)*ncovmodel+1);
1.223 brouard 7844: else /* nagesqr =1 */
1.264 brouard 7845: 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 7846:
1.223 brouard 7847: ij=1;
7848: for(j=3; j <=ncovmodel-nagesqr; j++){
1.268 brouard 7849: if(cptcovage >0){
7850: if((j-2)==Tage[ij]) { /* Bug valgrind */
7851: if(ij <=cptcovage) { /* Bug valgrind */
7852: fprintf(ficgp,"+p%d*%d*x",k3+(cpt-1)*ncovmodel+1+j-2+nagesqr,nbcode[Tvar[j-2]][codtabm(k1,j-2)]);
7853: /* fprintf(ficgp,"+p%d*%d*x",k3+(cpt-1)*ncovmodel+1+j-2+nagesqr,nbcode[Tvar[j-2]][codtabm(k1,Tvar[j-2])]); */
7854: ij++;
7855: }
7856: }
7857: }else
7858: 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 7859: }
7860: fprintf(ficgp,")");
7861: }
7862: fprintf(ficgp,")");
7863: if(ng ==2)
7864: fprintf(ficgp," t \"p%d%d\" ", k2,k);
7865: else /* ng= 3 */
7866: fprintf(ficgp," t \"i%d%d\" ", k2,k);
7867: }else{ /* end ng <> 1 */
7868: if( k !=k2) /* logit p11 is hard to draw */
7869: fprintf(ficgp," t \"logit(p%d%d)\" ", k2,k);
7870: }
7871: if ((k+k2)!= (nlstate*2+ndeath) && ng != 1)
7872: fprintf(ficgp,",");
7873: if (ng == 1 && k!=k2 && (k+k2)!= (nlstate*2+ndeath))
7874: fprintf(ficgp,",");
7875: i=i+ncovmodel;
7876: } /* end k */
7877: } /* end k2 */
1.264 brouard 7878: fprintf(ficgp,"\n set out; unset label;\n");
7879: } /* end k1 */
1.223 brouard 7880: } /* end ng */
7881: /* avoid: */
7882: fflush(ficgp);
1.126 brouard 7883: } /* end gnuplot */
7884:
7885:
7886: /*************** Moving average **************/
1.219 brouard 7887: /* int movingaverage(double ***probs, double bage, double fage, double ***mobaverage, int mobilav, double bageout, double fageout){ */
1.222 brouard 7888: int movingaverage(double ***probs, double bage, double fage, double ***mobaverage, int mobilav){
1.218 brouard 7889:
1.222 brouard 7890: int i, cpt, cptcod;
7891: int modcovmax =1;
7892: int mobilavrange, mob;
7893: int iage=0;
7894:
1.266 brouard 7895: double sum=0., sumr=0.;
1.222 brouard 7896: double age;
1.266 brouard 7897: double *sumnewp, *sumnewm, *sumnewmr;
7898: double *agemingood, *agemaxgood;
7899: double *agemingoodr, *agemaxgoodr;
1.222 brouard 7900:
7901:
1.225 brouard 7902: /* modcovmax=2*cptcoveff;/\* Max number of modalities. We suppose */
1.222 brouard 7903: /* a covariate has 2 modalities, should be equal to ncovcombmax *\/ */
7904:
7905: sumnewp = vector(1,ncovcombmax);
7906: sumnewm = vector(1,ncovcombmax);
1.266 brouard 7907: sumnewmr = vector(1,ncovcombmax);
1.222 brouard 7908: agemingood = vector(1,ncovcombmax);
1.266 brouard 7909: agemingoodr = vector(1,ncovcombmax);
1.222 brouard 7910: agemaxgood = vector(1,ncovcombmax);
1.266 brouard 7911: agemaxgoodr = vector(1,ncovcombmax);
1.222 brouard 7912:
7913: for (cptcod=1;cptcod<=ncovcombmax;cptcod++){
1.266 brouard 7914: sumnewm[cptcod]=0.; sumnewmr[cptcod]=0.;
1.222 brouard 7915: sumnewp[cptcod]=0.;
1.266 brouard 7916: agemingood[cptcod]=0, agemingoodr[cptcod]=0;
7917: agemaxgood[cptcod]=0, agemaxgoodr[cptcod]=0;
1.222 brouard 7918: }
7919: if (cptcovn<1) ncovcombmax=1; /* At least 1 pass */
7920:
1.266 brouard 7921: if(mobilav==-1 || mobilav==1||mobilav ==3 ||mobilav==5 ||mobilav== 7){
7922: if(mobilav==1 || mobilav==-1) mobilavrange=5; /* default */
1.222 brouard 7923: else mobilavrange=mobilav;
7924: for (age=bage; age<=fage; age++)
7925: for (i=1; i<=nlstate;i++)
7926: for (cptcod=1;cptcod<=ncovcombmax;cptcod++)
7927: mobaverage[(int)age][i][cptcod]=probs[(int)age][i][cptcod];
7928: /* We keep the original values on the extreme ages bage, fage and for
7929: fage+1 and bage-1 we use a 3 terms moving average; for fage+2 bage+2
7930: we use a 5 terms etc. until the borders are no more concerned.
7931: */
7932: for (mob=3;mob <=mobilavrange;mob=mob+2){
7933: for (age=bage+(mob-1)/2; age<=fage-(mob-1)/2; age++){
1.266 brouard 7934: for (cptcod=1;cptcod<=ncovcombmax;cptcod++){
7935: sumnewm[cptcod]=0.;
7936: for (i=1; i<=nlstate;i++){
1.222 brouard 7937: mobaverage[(int)age][i][cptcod] =probs[(int)age][i][cptcod];
7938: for (cpt=1;cpt<=(mob-1)/2;cpt++){
7939: mobaverage[(int)age][i][cptcod] +=probs[(int)age-cpt][i][cptcod];
7940: mobaverage[(int)age][i][cptcod] +=probs[(int)age+cpt][i][cptcod];
7941: }
7942: mobaverage[(int)age][i][cptcod]=mobaverage[(int)age][i][cptcod]/mob;
1.266 brouard 7943: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
7944: } /* end i */
7945: if(sumnewm[cptcod] >1.e-3) mobaverage[(int)age][i][cptcod]=mobaverage[(int)age][i][cptcod]/sumnewm[cptcod]; /* Rescaling to sum one */
7946: } /* end cptcod */
1.222 brouard 7947: }/* end age */
7948: }/* end mob */
1.266 brouard 7949: }else{
7950: printf("Error internal in movingaverage, mobilav=%d.\n",mobilav);
1.222 brouard 7951: return -1;
1.266 brouard 7952: }
7953:
7954: for (cptcod=1;cptcod<=ncovcombmax;cptcod++){ /* for each combination */
1.222 brouard 7955: /* for (age=bage+(mob-1)/2; age<=fage-(mob-1)/2; age++){ */
7956: if(invalidvarcomb[cptcod]){
7957: printf("\nCombination (%d) ignored because no cases \n",cptcod);
7958: continue;
7959: }
1.219 brouard 7960:
1.266 brouard 7961: for (age=fage-(mob-1)/2; age>=bage+(mob-1)/2; age--){ /*looking for the youngest and oldest good age */
7962: sumnewm[cptcod]=0.;
7963: sumnewmr[cptcod]=0.;
7964: for (i=1; i<=nlstate;i++){
7965: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
7966: sumnewmr[cptcod]+=probs[(int)age][i][cptcod];
7967: }
7968: if(fabs(sumnewmr[cptcod] - 1.) <= 1.e-3) { /* good without smoothing */
7969: agemingoodr[cptcod]=age;
7970: }
7971: if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
7972: agemingood[cptcod]=age;
7973: }
7974: } /* age */
7975: for (age=bage+(mob-1)/2; age<=fage-(mob-1)/2; age++){ /*looking for the youngest and oldest good age */
1.222 brouard 7976: sumnewm[cptcod]=0.;
1.266 brouard 7977: sumnewmr[cptcod]=0.;
1.222 brouard 7978: for (i=1; i<=nlstate;i++){
7979: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
1.266 brouard 7980: sumnewmr[cptcod]+=probs[(int)age][i][cptcod];
7981: }
7982: if(fabs(sumnewmr[cptcod] - 1.) <= 1.e-3) { /* good without smoothing */
7983: agemaxgoodr[cptcod]=age;
1.222 brouard 7984: }
7985: if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
1.266 brouard 7986: agemaxgood[cptcod]=age;
7987: }
7988: } /* age */
7989: /* Thus we have agemingood and agemaxgood as well as goodr for raw (preobs) */
7990: /* but they will change */
7991: for (age=fage-(mob-1)/2; age>=bage; age--){/* From oldest to youngest, filling up to the youngest */
7992: sumnewm[cptcod]=0.;
7993: sumnewmr[cptcod]=0.;
7994: for (i=1; i<=nlstate;i++){
7995: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
7996: sumnewmr[cptcod]+=probs[(int)age][i][cptcod];
7997: }
7998: if(mobilav==-1){ /* Forcing raw ages if good else agemingood */
7999: if(fabs(sumnewmr[cptcod] - 1.) <= 1.e-3) { /* good without smoothing */
8000: agemaxgoodr[cptcod]=age; /* age min */
8001: for (i=1; i<=nlstate;i++)
8002: mobaverage[(int)age][i][cptcod]=probs[(int)age][i][cptcod];
8003: }else{ /* bad we change the value with the values of good ages */
8004: for (i=1; i<=nlstate;i++){
8005: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemaxgoodr[cptcod]][i][cptcod];
8006: } /* i */
8007: } /* end bad */
8008: }else{
8009: if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
8010: agemaxgood[cptcod]=age;
8011: }else{ /* bad we change the value with the values of good ages */
8012: for (i=1; i<=nlstate;i++){
8013: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemaxgood[cptcod]][i][cptcod];
8014: } /* i */
8015: } /* end bad */
8016: }/* end else */
8017: sum=0.;sumr=0.;
8018: for (i=1; i<=nlstate;i++){
8019: sum+=mobaverage[(int)age][i][cptcod];
8020: sumr+=probs[(int)age][i][cptcod];
8021: }
8022: if(fabs(sum - 1.) > 1.e-3) { /* bad */
1.268 brouard 8023: 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 8024: } /* end bad */
8025: /* else{ /\* We found some ages summing to one, we will smooth the oldest *\/ */
8026: if(fabs(sumr - 1.) > 1.e-3) { /* bad */
1.268 brouard 8027: 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 8028: } /* end bad */
8029: }/* age */
1.266 brouard 8030:
8031: for (age=bage+(mob-1)/2; age<=fage; age++){/* From youngest, finding the oldest wrong */
1.222 brouard 8032: sumnewm[cptcod]=0.;
1.266 brouard 8033: sumnewmr[cptcod]=0.;
1.222 brouard 8034: for (i=1; i<=nlstate;i++){
8035: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
1.266 brouard 8036: sumnewmr[cptcod]+=probs[(int)age][i][cptcod];
8037: }
8038: if(mobilav==-1){ /* Forcing raw ages if good else agemingood */
8039: if(fabs(sumnewmr[cptcod] - 1.) <= 1.e-3) { /* good */
8040: agemingoodr[cptcod]=age;
8041: for (i=1; i<=nlstate;i++)
8042: mobaverage[(int)age][i][cptcod]=probs[(int)age][i][cptcod];
8043: }else{ /* bad we change the value with the values of good ages */
8044: for (i=1; i<=nlstate;i++){
8045: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemingoodr[cptcod]][i][cptcod];
8046: } /* i */
8047: } /* end bad */
8048: }else{
8049: if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
8050: agemingood[cptcod]=age;
8051: }else{ /* bad */
8052: for (i=1; i<=nlstate;i++){
8053: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemingood[cptcod]][i][cptcod];
8054: } /* i */
8055: } /* end bad */
8056: }/* end else */
8057: sum=0.;sumr=0.;
8058: for (i=1; i<=nlstate;i++){
8059: sum+=mobaverage[(int)age][i][cptcod];
8060: sumr+=mobaverage[(int)age][i][cptcod];
1.222 brouard 8061: }
1.266 brouard 8062: if(fabs(sum - 1.) > 1.e-3) { /* bad */
1.268 brouard 8063: 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 8064: } /* end bad */
8065: /* else{ /\* We found some ages summing to one, we will smooth the oldest *\/ */
8066: if(fabs(sumr - 1.) > 1.e-3) { /* bad */
1.268 brouard 8067: 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 8068: } /* end bad */
8069: }/* age */
1.266 brouard 8070:
1.222 brouard 8071:
8072: for (age=bage; age<=fage; age++){
1.235 brouard 8073: /* printf("%d %d ", cptcod, (int)age); */
1.222 brouard 8074: sumnewp[cptcod]=0.;
8075: sumnewm[cptcod]=0.;
8076: for (i=1; i<=nlstate;i++){
8077: sumnewp[cptcod]+=probs[(int)age][i][cptcod];
8078: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
8079: /* printf("%.4f %.4f ",probs[(int)age][i][cptcod], mobaverage[(int)age][i][cptcod]); */
8080: }
8081: /* printf("%.4f %.4f \n",sumnewp[cptcod], sumnewm[cptcod]); */
8082: }
8083: /* printf("\n"); */
8084: /* } */
1.266 brouard 8085:
1.222 brouard 8086: /* brutal averaging */
1.266 brouard 8087: /* for (i=1; i<=nlstate;i++){ */
8088: /* for (age=1; age<=bage; age++){ */
8089: /* mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemingood[cptcod]][i][cptcod]; */
8090: /* /\* printf("age=%d i=%d cptcod=%d mobaverage=%.4f \n",(int)age,i, cptcod, mobaverage[(int)age][i][cptcod]); *\/ */
8091: /* } */
8092: /* for (age=fage; age<=AGESUP; age++){ */
8093: /* mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemaxgood[cptcod]][i][cptcod]; */
8094: /* /\* printf("age=%d i=%d cptcod=%d mobaverage=%.4f \n",(int)age,i, cptcod, mobaverage[(int)age][i][cptcod]); *\/ */
8095: /* } */
8096: /* } /\* end i status *\/ */
8097: /* for (i=nlstate+1; i<=nlstate+ndeath;i++){ */
8098: /* for (age=1; age<=AGESUP; age++){ */
8099: /* /\*printf("i=%d, age=%d, cptcod=%d\n",i, (int)age, cptcod);*\/ */
8100: /* mobaverage[(int)age][i][cptcod]=0.; */
8101: /* } */
8102: /* } */
1.222 brouard 8103: }/* end cptcod */
1.266 brouard 8104: free_vector(agemaxgoodr,1, ncovcombmax);
8105: free_vector(agemaxgood,1, ncovcombmax);
8106: free_vector(agemingood,1, ncovcombmax);
8107: free_vector(agemingoodr,1, ncovcombmax);
8108: free_vector(sumnewmr,1, ncovcombmax);
1.222 brouard 8109: free_vector(sumnewm,1, ncovcombmax);
8110: free_vector(sumnewp,1, ncovcombmax);
8111: return 0;
8112: }/* End movingaverage */
1.218 brouard 8113:
1.126 brouard 8114:
8115: /************** Forecasting ******************/
1.269 brouard 8116: 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 8117: /* proj1, year, month, day of starting projection
8118: agemin, agemax range of age
8119: dateprev1 dateprev2 range of dates during which prevalence is computed
8120: anproj2 year of en of projection (same day and month as proj1).
8121: */
1.267 brouard 8122: int yearp, stepsize, hstepm, nhstepm, j, k, cptcod, i, h, i1, k4, nres=0;
1.126 brouard 8123: double agec; /* generic age */
8124: double agelim, ppij, yp,yp1,yp2,jprojmean,mprojmean,anprojmean;
8125: double *popeffectif,*popcount;
8126: double ***p3mat;
1.218 brouard 8127: /* double ***mobaverage; */
1.126 brouard 8128: char fileresf[FILENAMELENGTH];
8129:
8130: agelim=AGESUP;
1.211 brouard 8131: /* Compute observed prevalence between dateprev1 and dateprev2 by counting the number of people
8132: in each health status at the date of interview (if between dateprev1 and dateprev2).
8133: We still use firstpass and lastpass as another selection.
8134: */
1.214 brouard 8135: /* freqsummary(fileres, agemin, agemax, s, agev, nlstate, imx,Tvaraff,nbcode, ncodemax,mint,anint,strstart,\ */
8136: /* firstpass, lastpass, stepm, weightopt, model); */
1.126 brouard 8137:
1.201 brouard 8138: strcpy(fileresf,"F_");
8139: strcat(fileresf,fileresu);
1.126 brouard 8140: if((ficresf=fopen(fileresf,"w"))==NULL) {
8141: printf("Problem with forecast resultfile: %s\n", fileresf);
8142: fprintf(ficlog,"Problem with forecast resultfile: %s\n", fileresf);
8143: }
1.235 brouard 8144: printf("\nComputing forecasting: result on file '%s', please wait... \n", fileresf);
8145: fprintf(ficlog,"\nComputing forecasting: result on file '%s', please wait... \n", fileresf);
1.126 brouard 8146:
1.225 brouard 8147: if (cptcoveff==0) ncodemax[cptcoveff]=1;
1.126 brouard 8148:
8149:
8150: stepsize=(int) (stepm+YEARM-1)/YEARM;
8151: if (stepm<=12) stepsize=1;
8152: if(estepm < stepm){
8153: printf ("Problem %d lower than %d\n",estepm, stepm);
8154: }
1.270 ! brouard 8155: else{
! 8156: hstepm=estepm;
! 8157: }
! 8158: if(estepm > stepm){ /* Yes every two year */
! 8159: stepsize=2;
! 8160: }
1.126 brouard 8161:
8162: hstepm=hstepm/stepm;
8163: yp1=modf(dateintmean,&yp);/* extracts integral of datemean in yp and
8164: fractional in yp1 */
8165: anprojmean=yp;
8166: yp2=modf((yp1*12),&yp);
8167: mprojmean=yp;
8168: yp1=modf((yp2*30.5),&yp);
8169: jprojmean=yp;
8170: if(jprojmean==0) jprojmean=1;
8171: if(mprojmean==0) jprojmean=1;
8172:
1.227 brouard 8173: i1=pow(2,cptcoveff);
1.126 brouard 8174: if (cptcovn < 1){i1=1;}
8175:
8176: fprintf(ficresf,"# Mean day of interviews %.lf/%.lf/%.lf (%.2f) between %.2f and %.2f \n",jprojmean,mprojmean,anprojmean,dateintmean,dateprev1,dateprev2);
8177:
8178: fprintf(ficresf,"#****** Routine prevforecast **\n");
1.227 brouard 8179:
1.126 brouard 8180: /* if (h==(int)(YEARM*yearp)){ */
1.235 brouard 8181: for(nres=1; nres <= nresult; nres++) /* For each resultline */
8182: for(k=1; k<=i1;k++){
1.253 brouard 8183: if(i1 != 1 && TKresult[nres]!= k)
1.235 brouard 8184: continue;
1.227 brouard 8185: if(invalidvarcomb[k]){
8186: printf("\nCombination (%d) projection ignored because no cases \n",k);
8187: continue;
8188: }
8189: fprintf(ficresf,"\n#****** hpijx=probability over h years, hp.jx is weighted by observed prev \n#");
8190: for(j=1;j<=cptcoveff;j++) {
8191: fprintf(ficresf," V%d (=) %d",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
8192: }
1.235 brouard 8193: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
1.238 brouard 8194: fprintf(ficresf," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.235 brouard 8195: }
1.227 brouard 8196: fprintf(ficresf," yearproj age");
8197: for(j=1; j<=nlstate+ndeath;j++){
8198: for(i=1; i<=nlstate;i++)
8199: fprintf(ficresf," p%d%d",i,j);
8200: fprintf(ficresf," wp.%d",j);
8201: }
8202: for (yearp=0; yearp<=(anproj2-anproj1);yearp +=stepsize) {
8203: fprintf(ficresf,"\n");
8204: fprintf(ficresf,"\n# Forecasting at date %.lf/%.lf/%.lf ",jproj1,mproj1,anproj1+yearp);
1.270 ! brouard 8205: /* for (agec=fage; agec>=(ageminpar-1); agec--){ */
! 8206: for (agec=fage; agec>=(bage); agec--){
1.227 brouard 8207: nhstepm=(int) rint((agelim-agec)*YEARM/stepm);
8208: nhstepm = nhstepm/hstepm;
8209: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
8210: oldm=oldms;savm=savms;
1.268 brouard 8211: /* We compute pii at age agec over nhstepm);*/
1.235 brouard 8212: hpxij(p3mat,nhstepm,agec,hstepm,p,nlstate,stepm,oldm,savm, k,nres);
1.268 brouard 8213: /* Then we print p3mat for h corresponding to the right agec+h*stepms=yearp */
1.227 brouard 8214: for (h=0; h<=nhstepm; h++){
8215: if (h*hstepm/YEARM*stepm ==yearp) {
1.268 brouard 8216: break;
8217: }
8218: }
8219: fprintf(ficresf,"\n");
8220: for(j=1;j<=cptcoveff;j++)
8221: fprintf(ficresf,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
8222: fprintf(ficresf,"%.f %.f ",anproj1+yearp,agec+h*hstepm/YEARM*stepm);
8223:
8224: for(j=1; j<=nlstate+ndeath;j++) {
8225: ppij=0.;
8226: for(i=1; i<=nlstate;i++) {
8227: /* if (mobilav>=1) */
1.269 brouard 8228: ppij=ppij+p3mat[i][j][h]*prev[(int)agec][i][k];
1.268 brouard 8229: /* else { */ /* even if mobilav==-1 we use mobaverage */
8230: /* ppij=ppij+p3mat[i][j][h]*probs[(int)(agec)][i][k]; */
8231: /* } */
8232: fprintf(ficresf," %.3f", p3mat[i][j][h]);
8233: } /* end i */
8234: fprintf(ficresf," %.3f", ppij);
8235: }/* end j */
1.227 brouard 8236: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
8237: } /* end agec */
1.266 brouard 8238: /* diffyear=(int) anproj1+yearp-ageminpar-1; */
8239: /*printf("Prevforecast %d+%d-%d=diffyear=%d\n",(int) anproj1, (int)yearp,(int)ageminpar,(int) anproj1-(int)ageminpar);*/
1.227 brouard 8240: } /* end yearp */
8241: } /* end k */
1.219 brouard 8242:
1.126 brouard 8243: fclose(ficresf);
1.215 brouard 8244: printf("End of Computing forecasting \n");
8245: fprintf(ficlog,"End of Computing forecasting\n");
8246:
1.126 brouard 8247: }
8248:
1.269 brouard 8249: /************** Back Forecasting ******************/
8250: 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 8251: /* back1, year, month, day of starting backection
8252: agemin, agemax range of age
8253: dateprev1 dateprev2 range of dates during which prevalence is computed
1.269 brouard 8254: anback2 year of end of backprojection (same day and month as back1).
8255: prevacurrent and prev are prevalences.
1.267 brouard 8256: */
8257: int yearp, stepsize, hstepm, nhstepm, j, k, cptcod, i, h, i1, k4, nres=0;
8258: double agec; /* generic age */
1.268 brouard 8259: double agelim, ppij, ppi, yp,yp1,yp2,jprojmean,mprojmean,anprojmean;
1.267 brouard 8260: double *popeffectif,*popcount;
8261: double ***p3mat;
8262: /* double ***mobaverage; */
8263: char fileresfb[FILENAMELENGTH];
8264:
1.268 brouard 8265: agelim=AGEINF;
1.267 brouard 8266: /* Compute observed prevalence between dateprev1 and dateprev2 by counting the number of people
8267: in each health status at the date of interview (if between dateprev1 and dateprev2).
8268: We still use firstpass and lastpass as another selection.
8269: */
8270: /* freqsummary(fileres, agemin, agemax, s, agev, nlstate, imx,Tvaraff,nbcode, ncodemax,mint,anint,strstart,\ */
8271: /* firstpass, lastpass, stepm, weightopt, model); */
8272:
8273: /*Do we need to compute prevalence again?*/
8274:
8275: /* prevalence(probs, ageminpar, agemax, s, agev, nlstate, imx, Tvar, nbcode, ncodemax, mint, anint, dateprev1, dateprev2, firstpass, lastpass); */
8276:
8277: strcpy(fileresfb,"FB_");
8278: strcat(fileresfb,fileresu);
8279: if((ficresfb=fopen(fileresfb,"w"))==NULL) {
8280: printf("Problem with back forecast resultfile: %s\n", fileresfb);
8281: fprintf(ficlog,"Problem with back forecast resultfile: %s\n", fileresfb);
8282: }
8283: printf("\nComputing back forecasting: result on file '%s', please wait... \n", fileresfb);
8284: fprintf(ficlog,"\nComputing back forecasting: result on file '%s', please wait... \n", fileresfb);
8285:
8286: if (cptcoveff==0) ncodemax[cptcoveff]=1;
8287:
8288:
8289: stepsize=(int) (stepm+YEARM-1)/YEARM;
8290: if (stepm<=12) stepsize=1;
8291: if(estepm < stepm){
8292: printf ("Problem %d lower than %d\n",estepm, stepm);
8293: }
1.270 ! brouard 8294: else{
! 8295: hstepm=estepm;
! 8296: }
! 8297: if(estepm >= stepm){ /* Yes every two year */
! 8298: stepsize=2;
! 8299: }
1.267 brouard 8300:
8301: hstepm=hstepm/stepm;
8302: yp1=modf(dateintmean,&yp);/* extracts integral of datemean in yp and
8303: fractional in yp1 */
8304: anprojmean=yp;
8305: yp2=modf((yp1*12),&yp);
8306: mprojmean=yp;
8307: yp1=modf((yp2*30.5),&yp);
8308: jprojmean=yp;
8309: if(jprojmean==0) jprojmean=1;
8310: if(mprojmean==0) jprojmean=1;
8311:
8312: i1=pow(2,cptcoveff);
8313: if (cptcovn < 1){i1=1;}
8314:
8315: fprintf(ficresfb,"# Mean day of interviews %.lf/%.lf/%.lf (%.2f) between %.2f and %.2f \n",jprojmean,mprojmean,anprojmean,dateintmean,dateprev1,dateprev2);
1.268 brouard 8316: printf("# Mean day of interviews %.lf/%.lf/%.lf (%.2f) between %.2f and %.2f \n",jprojmean,mprojmean,anprojmean,dateintmean,dateprev1,dateprev2);
1.267 brouard 8317:
8318: fprintf(ficresfb,"#****** Routine prevbackforecast **\n");
8319:
8320: for(nres=1; nres <= nresult; nres++) /* For each resultline */
8321: for(k=1; k<=i1;k++){
8322: if(i1 != 1 && TKresult[nres]!= k)
8323: continue;
8324: if(invalidvarcomb[k]){
8325: printf("\nCombination (%d) projection ignored because no cases \n",k);
8326: continue;
8327: }
1.268 brouard 8328: fprintf(ficresfb,"\n#****** hbijx=probability over h years, hb.jx is weighted by observed prev \n#");
1.267 brouard 8329: for(j=1;j<=cptcoveff;j++) {
8330: fprintf(ficresfb," V%d (=) %d",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
8331: }
8332: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
8333: fprintf(ficresf," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
8334: }
8335: fprintf(ficresfb," yearbproj age");
8336: for(j=1; j<=nlstate+ndeath;j++){
8337: for(i=1; i<=nlstate;i++)
1.268 brouard 8338: fprintf(ficresfb," b%d%d",i,j);
8339: fprintf(ficresfb," b.%d",j);
1.267 brouard 8340: }
8341: for (yearp=0; yearp>=(anback2-anback1);yearp -=stepsize) {
8342: /* for (yearp=0; yearp<=(anproj2-anproj1);yearp +=stepsize) { */
8343: fprintf(ficresfb,"\n");
8344: fprintf(ficresfb,"\n# Back Forecasting at date %.lf/%.lf/%.lf ",jback1,mback1,anback1+yearp);
1.269 brouard 8345: /* printf("\n# Back Forecasting at date %.lf/%.lf/%.lf ",jback1,mback1,anback1+yearp); */
1.270 ! brouard 8346: /* for (agec=bage; agec<=agemax-1; agec++){ /\* testing *\/ */
! 8347: for (agec=bage; agec<=fage; agec++){ /* testing */
1.268 brouard 8348: /* We compute bij at age agec over nhstepm, nhstepm decreases when agec increases because of agemax;*/
8349: nhstepm=(int) rint((agec-agelim)*YEARM/stepm);
1.267 brouard 8350: nhstepm = nhstepm/hstepm;
8351: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
8352: oldm=oldms;savm=savms;
1.268 brouard 8353: /* computes hbxij at age agec over 1 to nhstepm */
1.267 brouard 8354: hbxij(p3mat,nhstepm,agec,hstepm,p,prevacurrent,nlstate,stepm, k, nres);
1.268 brouard 8355: /* hpxij(p3mat,nhstepm,agec,hstepm,p, nlstate,stepm,oldm,savm, k,nres); */
8356: /* Then we print p3mat for h corresponding to the right agec+h*stepms=yearp */
8357: /* printf(" agec=%.2f\n",agec);fflush(stdout); */
1.267 brouard 8358: for (h=0; h<=nhstepm; h++){
1.268 brouard 8359: if (h*hstepm/YEARM*stepm ==-yearp) {
8360: break;
8361: }
8362: }
8363: fprintf(ficresfb,"\n");
8364: for(j=1;j<=cptcoveff;j++)
8365: fprintf(ficresfb,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
8366: fprintf(ficresfb,"%.f %.f ",anback1+yearp,agec-h*hstepm/YEARM*stepm);
8367: for(i=1; i<=nlstate+ndeath;i++) {
8368: ppij=0.;ppi=0.;
8369: for(j=1; j<=nlstate;j++) {
8370: /* if (mobilav==1) */
1.269 brouard 8371: ppij=ppij+p3mat[i][j][h]*prevacurrent[(int)agec][j][k];
8372: ppi=ppi+prevacurrent[(int)agec][j][k];
8373: /* ppij=ppij+p3mat[i][j][h]*mobaverage[(int)agec][j][k]; */
8374: /* ppi=ppi+mobaverage[(int)agec][j][k]; */
1.267 brouard 8375: /* else { */
8376: /* ppij=ppij+p3mat[i][j][h]*probs[(int)(agec)][i][k]; */
8377: /* } */
1.268 brouard 8378: fprintf(ficresfb," %.3f", p3mat[i][j][h]);
8379: } /* end j */
8380: if(ppi <0.99){
8381: printf("Error in prevbackforecast, prevalence doesn't sum to 1 for state %d: %3f\n",i, ppi);
8382: fprintf(ficlog,"Error in prevbackforecast, prevalence doesn't sum to 1 for state %d: %3f\n",i, ppi);
8383: }
8384: fprintf(ficresfb," %.3f", ppij);
8385: }/* end j */
1.267 brouard 8386: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
8387: } /* end agec */
8388: } /* end yearp */
8389: } /* end k */
1.217 brouard 8390:
1.267 brouard 8391: /* if (mobilav!=0) free_ma3x(mobaverage,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
1.217 brouard 8392:
1.267 brouard 8393: fclose(ficresfb);
8394: printf("End of Computing Back forecasting \n");
8395: fprintf(ficlog,"End of Computing Back forecasting\n");
1.218 brouard 8396:
1.267 brouard 8397: }
1.217 brouard 8398:
1.269 brouard 8399: /* Variance of prevalence limit: varprlim */
8400: 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){
8401: /*------- Variance of period (stable) prevalence------*/
8402:
8403: char fileresvpl[FILENAMELENGTH];
8404: FILE *ficresvpl;
8405: double **oldm, **savm;
8406: double **varpl; /* Variances of prevalence limits by age */
8407: int i1, k, nres, j ;
8408:
8409: strcpy(fileresvpl,"VPL_");
8410: strcat(fileresvpl,fileresu);
8411: if((ficresvpl=fopen(fileresvpl,"w"))==NULL) {
8412: printf("Problem with variance of period (stable) prevalence resultfile: %s\n", fileresvpl);
8413: exit(0);
8414: }
8415: printf("Computing Variance-covariance of period (stable) prevalence: file '%s' ...", fileresvpl);fflush(stdout);
8416: fprintf(ficlog, "Computing Variance-covariance of period (stable) prevalence: file '%s' ...", fileresvpl);fflush(ficlog);
8417:
8418: /*for(cptcov=1,k=0;cptcov<=i1;cptcov++){
8419: for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){*/
8420:
8421: i1=pow(2,cptcoveff);
8422: if (cptcovn < 1){i1=1;}
8423:
8424: for(nres=1; nres <= nresult; nres++) /* For each resultline */
8425: for(k=1; k<=i1;k++){
8426: if(i1 != 1 && TKresult[nres]!= k)
8427: continue;
8428: fprintf(ficresvpl,"\n#****** ");
8429: printf("\n#****** ");
8430: fprintf(ficlog,"\n#****** ");
8431: for(j=1;j<=cptcoveff;j++) {
8432: fprintf(ficresvpl,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
8433: fprintf(ficlog,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
8434: printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
8435: }
8436: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
8437: printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
8438: fprintf(ficresvpl," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
8439: fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
8440: }
8441: fprintf(ficresvpl,"******\n");
8442: printf("******\n");
8443: fprintf(ficlog,"******\n");
8444:
8445: varpl=matrix(1,nlstate,(int) bage, (int) fage);
8446: oldm=oldms;savm=savms;
8447: varprevlim(fileresvpl, ficresvpl, varpl, matcov, p, delti, nlstate, stepm, (int) bage, (int) fage, oldm, savm, prlim, ftolpl, ncvyearp, k, strstart, nres);
8448: free_matrix(varpl,1,nlstate,(int) bage, (int)fage);
8449: /*}*/
8450: }
8451:
8452: fclose(ficresvpl);
8453: printf("done variance-covariance of period prevalence\n");fflush(stdout);
8454: fprintf(ficlog,"done variance-covariance of period prevalence\n");fflush(ficlog);
8455:
8456: }
8457: /* Variance of back prevalence: varbprlim */
8458: 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){
8459: /*------- Variance of back (stable) prevalence------*/
8460:
8461: char fileresvbl[FILENAMELENGTH];
8462: FILE *ficresvbl;
8463:
8464: double **oldm, **savm;
8465: double **varbpl; /* Variances of back prevalence limits by age */
8466: int i1, k, nres, j ;
8467:
8468: strcpy(fileresvbl,"VBL_");
8469: strcat(fileresvbl,fileresu);
8470: if((ficresvbl=fopen(fileresvbl,"w"))==NULL) {
8471: printf("Problem with variance of back (stable) prevalence resultfile: %s\n", fileresvbl);
8472: exit(0);
8473: }
8474: printf("Computing Variance-covariance of back (stable) prevalence: file '%s' ...", fileresvbl);fflush(stdout);
8475: fprintf(ficlog, "Computing Variance-covariance of back (stable) prevalence: file '%s' ...", fileresvbl);fflush(ficlog);
8476:
8477:
8478: i1=pow(2,cptcoveff);
8479: if (cptcovn < 1){i1=1;}
8480:
8481: for(nres=1; nres <= nresult; nres++) /* For each resultline */
8482: for(k=1; k<=i1;k++){
8483: if(i1 != 1 && TKresult[nres]!= k)
8484: continue;
8485: fprintf(ficresvbl,"\n#****** ");
8486: printf("\n#****** ");
8487: fprintf(ficlog,"\n#****** ");
8488: for(j=1;j<=cptcoveff;j++) {
8489: fprintf(ficresvbl,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
8490: fprintf(ficlog,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
8491: printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
8492: }
8493: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
8494: printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
8495: fprintf(ficresvbl," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
8496: fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
8497: }
8498: fprintf(ficresvbl,"******\n");
8499: printf("******\n");
8500: fprintf(ficlog,"******\n");
8501:
8502: varbpl=matrix(1,nlstate,(int) bage, (int) fage);
8503: oldm=oldms;savm=savms;
8504:
8505: varbrevlim(fileresvbl, ficresvbl, varbpl, matcov, p, delti, nlstate, stepm, (int) bage, (int) fage, oldm, savm, bprlim, ftolpl, mobilavproj, ncvyearp, k, strstart, nres);
8506: free_matrix(varbpl,1,nlstate,(int) bage, (int)fage);
8507: /*}*/
8508: }
8509:
8510: fclose(ficresvbl);
8511: printf("done variance-covariance of back prevalence\n");fflush(stdout);
8512: fprintf(ficlog,"done variance-covariance of back prevalence\n");fflush(ficlog);
8513:
8514: } /* End of varbprlim */
8515:
1.126 brouard 8516: /************** Forecasting *****not tested NB*************/
1.227 brouard 8517: /* 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 8518:
1.227 brouard 8519: /* int cpt, stepsize, hstepm, nhstepm, j,k,c, cptcod, i,h; */
8520: /* int *popage; */
8521: /* double calagedatem, agelim, kk1, kk2; */
8522: /* double *popeffectif,*popcount; */
8523: /* double ***p3mat,***tabpop,***tabpopprev; */
8524: /* /\* double ***mobaverage; *\/ */
8525: /* char filerespop[FILENAMELENGTH]; */
1.126 brouard 8526:
1.227 brouard 8527: /* tabpop= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
8528: /* tabpopprev= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
8529: /* agelim=AGESUP; */
8530: /* calagedatem=(anpyram+mpyram/12.+jpyram/365.-dateintmean)*YEARM; */
1.126 brouard 8531:
1.227 brouard 8532: /* prevalence(probs, ageminpar, agemax, s, agev, nlstate, imx, Tvar, nbcode, ncodemax, mint, anint, dateprev1, dateprev2, firstpass, lastpass); */
1.126 brouard 8533:
8534:
1.227 brouard 8535: /* strcpy(filerespop,"POP_"); */
8536: /* strcat(filerespop,fileresu); */
8537: /* if((ficrespop=fopen(filerespop,"w"))==NULL) { */
8538: /* printf("Problem with forecast resultfile: %s\n", filerespop); */
8539: /* fprintf(ficlog,"Problem with forecast resultfile: %s\n", filerespop); */
8540: /* } */
8541: /* printf("Computing forecasting: result on file '%s' \n", filerespop); */
8542: /* fprintf(ficlog,"Computing forecasting: result on file '%s' \n", filerespop); */
1.126 brouard 8543:
1.227 brouard 8544: /* if (cptcoveff==0) ncodemax[cptcoveff]=1; */
1.126 brouard 8545:
1.227 brouard 8546: /* /\* if (mobilav!=0) { *\/ */
8547: /* /\* mobaverage= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); *\/ */
8548: /* /\* if (movingaverage(probs, ageminpar, fage, mobaverage,mobilav)!=0){ *\/ */
8549: /* /\* fprintf(ficlog," Error in movingaverage mobilav=%d\n",mobilav); *\/ */
8550: /* /\* printf(" Error in movingaverage mobilav=%d\n",mobilav); *\/ */
8551: /* /\* } *\/ */
8552: /* /\* } *\/ */
1.126 brouard 8553:
1.227 brouard 8554: /* stepsize=(int) (stepm+YEARM-1)/YEARM; */
8555: /* if (stepm<=12) stepsize=1; */
1.126 brouard 8556:
1.227 brouard 8557: /* agelim=AGESUP; */
1.126 brouard 8558:
1.227 brouard 8559: /* hstepm=1; */
8560: /* hstepm=hstepm/stepm; */
1.218 brouard 8561:
1.227 brouard 8562: /* if (popforecast==1) { */
8563: /* if((ficpop=fopen(popfile,"r"))==NULL) { */
8564: /* printf("Problem with population file : %s\n",popfile);exit(0); */
8565: /* fprintf(ficlog,"Problem with population file : %s\n",popfile);exit(0); */
8566: /* } */
8567: /* popage=ivector(0,AGESUP); */
8568: /* popeffectif=vector(0,AGESUP); */
8569: /* popcount=vector(0,AGESUP); */
1.126 brouard 8570:
1.227 brouard 8571: /* i=1; */
8572: /* while ((c=fscanf(ficpop,"%d %lf\n",&popage[i],&popcount[i])) != EOF) i=i+1; */
1.218 brouard 8573:
1.227 brouard 8574: /* imx=i; */
8575: /* for (i=1; i<imx;i++) popeffectif[popage[i]]=popcount[i]; */
8576: /* } */
1.218 brouard 8577:
1.227 brouard 8578: /* for(cptcov=1,k=0;cptcov<=i2;cptcov++){ */
8579: /* for(cptcod=1;cptcod<=ncodemax[cptcoveff];cptcod++){ */
8580: /* k=k+1; */
8581: /* fprintf(ficrespop,"\n#******"); */
8582: /* for(j=1;j<=cptcoveff;j++) { */
8583: /* fprintf(ficrespop," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]); */
8584: /* } */
8585: /* fprintf(ficrespop,"******\n"); */
8586: /* fprintf(ficrespop,"# Age"); */
8587: /* for(j=1; j<=nlstate+ndeath;j++) fprintf(ficrespop," P.%d",j); */
8588: /* if (popforecast==1) fprintf(ficrespop," [Population]"); */
1.126 brouard 8589:
1.227 brouard 8590: /* for (cpt=0; cpt<=0;cpt++) { */
8591: /* fprintf(ficrespop,"\n\n# Forecasting at date %.lf/%.lf/%.lf ",jpyram,mpyram,anpyram+cpt); */
1.126 brouard 8592:
1.227 brouard 8593: /* for (agedeb=(fage-((int)calagedatem %12/12.)); agedeb>=(ageminpar-((int)calagedatem %12)/12.); agedeb--){ */
8594: /* nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); */
8595: /* nhstepm = nhstepm/hstepm; */
1.126 brouard 8596:
1.227 brouard 8597: /* p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
8598: /* oldm=oldms;savm=savms; */
8599: /* hpxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k); */
1.218 brouard 8600:
1.227 brouard 8601: /* for (h=0; h<=nhstepm; h++){ */
8602: /* if (h==(int) (calagedatem+YEARM*cpt)) { */
8603: /* fprintf(ficrespop,"\n %3.f ",agedeb+h*hstepm/YEARM*stepm); */
8604: /* } */
8605: /* for(j=1; j<=nlstate+ndeath;j++) { */
8606: /* kk1=0.;kk2=0; */
8607: /* for(i=1; i<=nlstate;i++) { */
8608: /* if (mobilav==1) */
8609: /* kk1=kk1+p3mat[i][j][h]*mobaverage[(int)agedeb+1][i][cptcod]; */
8610: /* else { */
8611: /* kk1=kk1+p3mat[i][j][h]*probs[(int)(agedeb+1)][i][cptcod]; */
8612: /* } */
8613: /* } */
8614: /* if (h==(int)(calagedatem+12*cpt)){ */
8615: /* tabpop[(int)(agedeb)][j][cptcod]=kk1; */
8616: /* /\*fprintf(ficrespop," %.3f", kk1); */
8617: /* if (popforecast==1) fprintf(ficrespop," [%.f]", kk1*popeffectif[(int)agedeb+1]);*\/ */
8618: /* } */
8619: /* } */
8620: /* for(i=1; i<=nlstate;i++){ */
8621: /* kk1=0.; */
8622: /* for(j=1; j<=nlstate;j++){ */
8623: /* kk1= kk1+tabpop[(int)(agedeb)][j][cptcod]; */
8624: /* } */
8625: /* tabpopprev[(int)(agedeb)][i][cptcod]=tabpop[(int)(agedeb)][i][cptcod]/kk1*popeffectif[(int)(agedeb+(calagedatem+12*cpt)*hstepm/YEARM*stepm-1)]; */
8626: /* } */
1.218 brouard 8627:
1.227 brouard 8628: /* if (h==(int)(calagedatem+12*cpt)) */
8629: /* for(j=1; j<=nlstate;j++) */
8630: /* fprintf(ficrespop," %15.2f",tabpopprev[(int)(agedeb+1)][j][cptcod]); */
8631: /* } */
8632: /* free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
8633: /* } */
8634: /* } */
1.218 brouard 8635:
1.227 brouard 8636: /* /\******\/ */
1.218 brouard 8637:
1.227 brouard 8638: /* for (cpt=1; cpt<=(anpyram1-anpyram);cpt++) { */
8639: /* fprintf(ficrespop,"\n\n# Forecasting at date %.lf/%.lf/%.lf ",jpyram,mpyram,anpyram+cpt); */
8640: /* for (agedeb=(fage-((int)calagedatem %12/12.)); agedeb>=(ageminpar-((int)calagedatem %12)/12.); agedeb--){ */
8641: /* nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); */
8642: /* nhstepm = nhstepm/hstepm; */
1.126 brouard 8643:
1.227 brouard 8644: /* p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
8645: /* oldm=oldms;savm=savms; */
8646: /* hpxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k); */
8647: /* for (h=0; h<=nhstepm; h++){ */
8648: /* if (h==(int) (calagedatem+YEARM*cpt)) { */
8649: /* fprintf(ficresf,"\n %3.f ",agedeb+h*hstepm/YEARM*stepm); */
8650: /* } */
8651: /* for(j=1; j<=nlstate+ndeath;j++) { */
8652: /* kk1=0.;kk2=0; */
8653: /* for(i=1; i<=nlstate;i++) { */
8654: /* kk1=kk1+p3mat[i][j][h]*tabpopprev[(int)agedeb+1][i][cptcod]; */
8655: /* } */
8656: /* if (h==(int)(calagedatem+12*cpt)) fprintf(ficresf," %15.2f", kk1); */
8657: /* } */
8658: /* } */
8659: /* free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
8660: /* } */
8661: /* } */
8662: /* } */
8663: /* } */
1.218 brouard 8664:
1.227 brouard 8665: /* /\* if (mobilav!=0) free_ma3x(mobaverage,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); *\/ */
1.218 brouard 8666:
1.227 brouard 8667: /* if (popforecast==1) { */
8668: /* free_ivector(popage,0,AGESUP); */
8669: /* free_vector(popeffectif,0,AGESUP); */
8670: /* free_vector(popcount,0,AGESUP); */
8671: /* } */
8672: /* free_ma3x(tabpop,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
8673: /* free_ma3x(tabpopprev,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
8674: /* fclose(ficrespop); */
8675: /* } /\* End of popforecast *\/ */
1.218 brouard 8676:
1.126 brouard 8677: int fileappend(FILE *fichier, char *optionfich)
8678: {
8679: if((fichier=fopen(optionfich,"a"))==NULL) {
8680: printf("Problem with file: %s\n", optionfich);
8681: fprintf(ficlog,"Problem with file: %s\n", optionfich);
8682: return (0);
8683: }
8684: fflush(fichier);
8685: return (1);
8686: }
8687:
8688:
8689: /**************** function prwizard **********************/
8690: void prwizard(int ncovmodel, int nlstate, int ndeath, char model[], FILE *ficparo)
8691: {
8692:
8693: /* Wizard to print covariance matrix template */
8694:
1.164 brouard 8695: char ca[32], cb[32];
8696: int i,j, k, li, lj, lk, ll, jj, npar, itimes;
1.126 brouard 8697: int numlinepar;
8698:
8699: printf("# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
8700: fprintf(ficparo,"# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
8701: for(i=1; i <=nlstate; i++){
8702: jj=0;
8703: for(j=1; j <=nlstate+ndeath; j++){
8704: if(j==i) continue;
8705: jj++;
8706: /*ca[0]= k+'a'-1;ca[1]='\0';*/
8707: printf("%1d%1d",i,j);
8708: fprintf(ficparo,"%1d%1d",i,j);
8709: for(k=1; k<=ncovmodel;k++){
8710: /* printf(" %lf",param[i][j][k]); */
8711: /* fprintf(ficparo," %lf",param[i][j][k]); */
8712: printf(" 0.");
8713: fprintf(ficparo," 0.");
8714: }
8715: printf("\n");
8716: fprintf(ficparo,"\n");
8717: }
8718: }
8719: printf("# Scales (for hessian or gradient estimation)\n");
8720: fprintf(ficparo,"# Scales (for hessian or gradient estimation)\n");
8721: npar= (nlstate+ndeath-1)*nlstate*ncovmodel; /* Number of parameters*/
8722: for(i=1; i <=nlstate; i++){
8723: jj=0;
8724: for(j=1; j <=nlstate+ndeath; j++){
8725: if(j==i) continue;
8726: jj++;
8727: fprintf(ficparo,"%1d%1d",i,j);
8728: printf("%1d%1d",i,j);
8729: fflush(stdout);
8730: for(k=1; k<=ncovmodel;k++){
8731: /* printf(" %le",delti3[i][j][k]); */
8732: /* fprintf(ficparo," %le",delti3[i][j][k]); */
8733: printf(" 0.");
8734: fprintf(ficparo," 0.");
8735: }
8736: numlinepar++;
8737: printf("\n");
8738: fprintf(ficparo,"\n");
8739: }
8740: }
8741: printf("# Covariance matrix\n");
8742: /* # 121 Var(a12)\n\ */
8743: /* # 122 Cov(b12,a12) Var(b12)\n\ */
8744: /* # 131 Cov(a13,a12) Cov(a13,b12, Var(a13)\n\ */
8745: /* # 132 Cov(b13,a12) Cov(b13,b12, Cov(b13,a13) Var(b13)\n\ */
8746: /* # 212 Cov(a21,a12) Cov(a21,b12, Cov(a21,a13) Cov(a21,b13) Var(a21)\n\ */
8747: /* # 212 Cov(b21,a12) Cov(b21,b12, Cov(b21,a13) Cov(b21,b13) Cov(b21,a21) Var(b21)\n\ */
8748: /* # 232 Cov(a23,a12) Cov(a23,b12, Cov(a23,a13) Cov(a23,b13) Cov(a23,a21) Cov(a23,b21) Var(a23)\n\ */
8749: /* # 232 Cov(b23,a12) Cov(b23,b12) ... Var (b23)\n" */
8750: fflush(stdout);
8751: fprintf(ficparo,"# Covariance matrix\n");
8752: /* # 121 Var(a12)\n\ */
8753: /* # 122 Cov(b12,a12) Var(b12)\n\ */
8754: /* # ...\n\ */
8755: /* # 232 Cov(b23,a12) Cov(b23,b12) ... Var (b23)\n" */
8756:
8757: for(itimes=1;itimes<=2;itimes++){
8758: jj=0;
8759: for(i=1; i <=nlstate; i++){
8760: for(j=1; j <=nlstate+ndeath; j++){
8761: if(j==i) continue;
8762: for(k=1; k<=ncovmodel;k++){
8763: jj++;
8764: ca[0]= k+'a'-1;ca[1]='\0';
8765: if(itimes==1){
8766: printf("#%1d%1d%d",i,j,k);
8767: fprintf(ficparo,"#%1d%1d%d",i,j,k);
8768: }else{
8769: printf("%1d%1d%d",i,j,k);
8770: fprintf(ficparo,"%1d%1d%d",i,j,k);
8771: /* printf(" %.5le",matcov[i][j]); */
8772: }
8773: ll=0;
8774: for(li=1;li <=nlstate; li++){
8775: for(lj=1;lj <=nlstate+ndeath; lj++){
8776: if(lj==li) continue;
8777: for(lk=1;lk<=ncovmodel;lk++){
8778: ll++;
8779: if(ll<=jj){
8780: cb[0]= lk +'a'-1;cb[1]='\0';
8781: if(ll<jj){
8782: if(itimes==1){
8783: printf(" Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
8784: fprintf(ficparo," Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
8785: }else{
8786: printf(" 0.");
8787: fprintf(ficparo," 0.");
8788: }
8789: }else{
8790: if(itimes==1){
8791: printf(" Var(%s%1d%1d)",ca,i,j);
8792: fprintf(ficparo," Var(%s%1d%1d)",ca,i,j);
8793: }else{
8794: printf(" 0.");
8795: fprintf(ficparo," 0.");
8796: }
8797: }
8798: }
8799: } /* end lk */
8800: } /* end lj */
8801: } /* end li */
8802: printf("\n");
8803: fprintf(ficparo,"\n");
8804: numlinepar++;
8805: } /* end k*/
8806: } /*end j */
8807: } /* end i */
8808: } /* end itimes */
8809:
8810: } /* end of prwizard */
8811: /******************* Gompertz Likelihood ******************************/
8812: double gompertz(double x[])
8813: {
8814: double A,B,L=0.0,sump=0.,num=0.;
8815: int i,n=0; /* n is the size of the sample */
8816:
1.220 brouard 8817: for (i=1;i<=imx ; i++) {
1.126 brouard 8818: sump=sump+weight[i];
8819: /* sump=sump+1;*/
8820: num=num+1;
8821: }
8822:
8823:
8824: /* for (i=0; i<=imx; i++)
8825: 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]);*/
8826:
8827: for (i=1;i<=imx ; i++)
8828: {
8829: if (cens[i] == 1 && wav[i]>1)
8830: A=-x[1]/(x[2])*(exp(x[2]*(agecens[i]-agegomp))-exp(x[2]*(ageexmed[i]-agegomp)));
8831:
8832: if (cens[i] == 0 && wav[i]>1)
8833: A=-x[1]/(x[2])*(exp(x[2]*(agedc[i]-agegomp))-exp(x[2]*(ageexmed[i]-agegomp)))
8834: +log(x[1]/YEARM)+x[2]*(agedc[i]-agegomp)+log(YEARM);
8835:
8836: /*if (wav[i] > 1 && agecens[i] > 15) {*/ /* ??? */
8837: if (wav[i] > 1 ) { /* ??? */
8838: L=L+A*weight[i];
8839: /* 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]);*/
8840: }
8841: }
8842:
8843: /*printf("x1=%2.9f x2=%2.9f x3=%2.9f L=%f\n",x[1],x[2],x[3],L);*/
8844:
8845: return -2*L*num/sump;
8846: }
8847:
1.136 brouard 8848: #ifdef GSL
8849: /******************* Gompertz_f Likelihood ******************************/
8850: double gompertz_f(const gsl_vector *v, void *params)
8851: {
8852: double A,B,LL=0.0,sump=0.,num=0.;
8853: double *x= (double *) v->data;
8854: int i,n=0; /* n is the size of the sample */
8855:
8856: for (i=0;i<=imx-1 ; i++) {
8857: sump=sump+weight[i];
8858: /* sump=sump+1;*/
8859: num=num+1;
8860: }
8861:
8862:
8863: /* for (i=0; i<=imx; i++)
8864: 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]);*/
8865: printf("x[0]=%lf x[1]=%lf\n",x[0],x[1]);
8866: for (i=1;i<=imx ; i++)
8867: {
8868: if (cens[i] == 1 && wav[i]>1)
8869: A=-x[0]/(x[1])*(exp(x[1]*(agecens[i]-agegomp))-exp(x[1]*(ageexmed[i]-agegomp)));
8870:
8871: if (cens[i] == 0 && wav[i]>1)
8872: A=-x[0]/(x[1])*(exp(x[1]*(agedc[i]-agegomp))-exp(x[1]*(ageexmed[i]-agegomp)))
8873: +log(x[0]/YEARM)+x[1]*(agedc[i]-agegomp)+log(YEARM);
8874:
8875: /*if (wav[i] > 1 && agecens[i] > 15) {*/ /* ??? */
8876: if (wav[i] > 1 ) { /* ??? */
8877: LL=LL+A*weight[i];
8878: /* 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]);*/
8879: }
8880: }
8881:
8882: /*printf("x1=%2.9f x2=%2.9f x3=%2.9f L=%f\n",x[1],x[2],x[3],L);*/
8883: printf("x[0]=%lf x[1]=%lf -2*LL*num/sump=%lf\n",x[0],x[1],-2*LL*num/sump);
8884:
8885: return -2*LL*num/sump;
8886: }
8887: #endif
8888:
1.126 brouard 8889: /******************* Printing html file ***********/
1.201 brouard 8890: void printinghtmlmort(char fileresu[], char title[], char datafile[], int firstpass, \
1.126 brouard 8891: int lastpass, int stepm, int weightopt, char model[],\
8892: int imx, double p[],double **matcov,double agemortsup){
8893: int i,k;
8894:
8895: fprintf(fichtm,"<ul><li><h4>Result files </h4>\n Force of mortality. Parameters of the Gompertz fit (with confidence interval in brackets):<br>");
8896: fprintf(fichtm," mu(age) =%lf*exp(%lf*(age-%d)) per year<br><br>",p[1],p[2],agegomp);
8897: for (i=1;i<=2;i++)
8898: 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 8899: fprintf(fichtm,"<br><br><img src=\"graphmort.svg\">");
1.126 brouard 8900: fprintf(fichtm,"</ul>");
8901:
8902: fprintf(fichtm,"<ul><li><h4>Life table</h4>\n <br>");
8903:
8904: 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>");
8905:
8906: for (k=agegomp;k<(agemortsup-2);k++)
8907: 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]);
8908:
8909:
8910: fflush(fichtm);
8911: }
8912:
8913: /******************* Gnuplot file **************/
1.201 brouard 8914: void printinggnuplotmort(char fileresu[], char optionfilefiname[], double ageminpar, double agemaxpar, double fage , char pathc[], double p[]){
1.126 brouard 8915:
8916: char dirfileres[132],optfileres[132];
1.164 brouard 8917:
1.126 brouard 8918: int ng;
8919:
8920:
8921: /*#ifdef windows */
8922: fprintf(ficgp,"cd \"%s\" \n",pathc);
8923: /*#endif */
8924:
8925:
8926: strcpy(dirfileres,optionfilefiname);
8927: strcpy(optfileres,"vpl");
1.199 brouard 8928: fprintf(ficgp,"set out \"graphmort.svg\"\n ");
1.126 brouard 8929: fprintf(ficgp,"set xlabel \"Age\"\n set ylabel \"Force of mortality (per year)\" \n ");
1.199 brouard 8930: fprintf(ficgp, "set ter svg size 640, 480\n set log y\n");
1.145 brouard 8931: /* fprintf(ficgp, "set size 0.65,0.65\n"); */
1.126 brouard 8932: fprintf(ficgp,"plot [%d:100] %lf*exp(%lf*(x-%d))",agegomp,p[1],p[2],agegomp);
8933:
8934: }
8935:
1.136 brouard 8936: int readdata(char datafile[], int firstobs, int lastobs, int *imax)
8937: {
1.126 brouard 8938:
1.136 brouard 8939: /*-------- data file ----------*/
8940: FILE *fic;
8941: char dummy[]=" ";
1.240 brouard 8942: int i=0, j=0, n=0, iv=0, v;
1.223 brouard 8943: int lstra;
1.136 brouard 8944: int linei, month, year,iout;
8945: char line[MAXLINE], linetmp[MAXLINE];
1.164 brouard 8946: char stra[MAXLINE], strb[MAXLINE];
1.136 brouard 8947: char *stratrunc;
1.223 brouard 8948:
1.240 brouard 8949: DummyV=ivector(1,NCOVMAX); /* 1 to 3 */
8950: FixedV=ivector(1,NCOVMAX); /* 1 to 3 */
1.126 brouard 8951:
1.240 brouard 8952: for(v=1; v <=ncovcol;v++){
8953: DummyV[v]=0;
8954: FixedV[v]=0;
8955: }
8956: for(v=ncovcol+1; v <=ncovcol+nqv;v++){
8957: DummyV[v]=1;
8958: FixedV[v]=0;
8959: }
8960: for(v=ncovcol+nqv+1; v <=ncovcol+nqv+ntv;v++){
8961: DummyV[v]=0;
8962: FixedV[v]=1;
8963: }
8964: for(v=ncovcol+nqv+ntv+1; v <=ncovcol+nqv+ntv+nqtv;v++){
8965: DummyV[v]=1;
8966: FixedV[v]=1;
8967: }
8968: for(v=1; v <=ncovcol+nqv+ntv+nqtv;v++){
8969: printf("Covariate type in the data: V%d, DummyV(V%d)=%d, FixedV(V%d)=%d\n",v,v,DummyV[v],v,FixedV[v]);
8970: 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]);
8971: }
1.126 brouard 8972:
1.136 brouard 8973: if((fic=fopen(datafile,"r"))==NULL) {
1.218 brouard 8974: printf("Problem while opening datafile: %s with errno='%s'\n", datafile,strerror(errno));fflush(stdout);
8975: fprintf(ficlog,"Problem while opening datafile: %s with errno='%s'\n", datafile,strerror(errno));fflush(ficlog);return 1;
1.136 brouard 8976: }
1.126 brouard 8977:
1.136 brouard 8978: i=1;
8979: linei=0;
8980: while ((fgets(line, MAXLINE, fic) != NULL) &&((i >= firstobs) && (i <=lastobs))) {
8981: linei=linei+1;
8982: for(j=strlen(line); j>=0;j--){ /* Untabifies line */
8983: if(line[j] == '\t')
8984: line[j] = ' ';
8985: }
8986: for(j=strlen(line)-1; (line[j]==' ')||(line[j]==10)||(line[j]==13);j--){
8987: ;
8988: };
8989: line[j+1]=0; /* Trims blanks at end of line */
8990: if(line[0]=='#'){
8991: fprintf(ficlog,"Comment line\n%s\n",line);
8992: printf("Comment line\n%s\n",line);
8993: continue;
8994: }
8995: trimbb(linetmp,line); /* Trims multiple blanks in line */
1.164 brouard 8996: strcpy(line, linetmp);
1.223 brouard 8997:
8998: /* Loops on waves */
8999: for (j=maxwav;j>=1;j--){
9000: for (iv=nqtv;iv>=1;iv--){ /* Loop on time varying quantitative variables */
1.238 brouard 9001: cutv(stra, strb, line, ' ');
9002: if(strb[0]=='.') { /* Missing value */
9003: lval=-1;
9004: cotqvar[j][iv][i]=-1; /* 0.0/0.0 */
9005: cotvar[j][ntv+iv][i]=-1; /* For performance reasons */
9006: if(isalpha(strb[1])) { /* .m or .d Really Missing value */
9007: 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);
9008: 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);
9009: return 1;
9010: }
9011: }else{
9012: errno=0;
9013: /* what_kind_of_number(strb); */
9014: dval=strtod(strb,&endptr);
9015: /* if( strb[0]=='\0' || (*endptr != '\0')){ */
9016: /* if(strb != endptr && *endptr == '\0') */
9017: /* dval=dlval; */
9018: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN)) */
9019: if( strb[0]=='\0' || (*endptr != '\0')){
9020: 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);
9021: 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);
9022: return 1;
9023: }
9024: cotqvar[j][iv][i]=dval;
9025: cotvar[j][ntv+iv][i]=dval;
9026: }
9027: strcpy(line,stra);
1.223 brouard 9028: }/* end loop ntqv */
1.225 brouard 9029:
1.223 brouard 9030: for (iv=ntv;iv>=1;iv--){ /* Loop on time varying dummies */
1.238 brouard 9031: cutv(stra, strb, line, ' ');
9032: if(strb[0]=='.') { /* Missing value */
9033: lval=-1;
9034: }else{
9035: errno=0;
9036: lval=strtol(strb,&endptr,10);
9037: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN))*/
9038: if( strb[0]=='\0' || (*endptr != '\0')){
9039: 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);
9040: 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);
9041: return 1;
9042: }
9043: }
9044: if(lval <-1 || lval >1){
9045: printf("Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.223 brouard 9046: Should be a value of %d(nth) covariate (0 should be the value for the reference and 1\n \
9047: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.238 brouard 9048: For example, for multinomial values like 1, 2 and 3,\n \
9049: build V1=0 V2=0 for the reference value (1),\n \
9050: V1=1 V2=0 for (2) \n \
1.223 brouard 9051: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.238 brouard 9052: output of IMaCh is often meaningless.\n \
1.223 brouard 9053: Exiting.\n",lval,linei, i,line,j);
1.238 brouard 9054: fprintf(ficlog,"Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.223 brouard 9055: Should be a value of %d(nth) covariate (0 should be the value for the reference and 1\n \
9056: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.238 brouard 9057: For example, for multinomial values like 1, 2 and 3,\n \
9058: build V1=0 V2=0 for the reference value (1),\n \
9059: V1=1 V2=0 for (2) \n \
1.223 brouard 9060: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.238 brouard 9061: output of IMaCh is often meaningless.\n \
1.223 brouard 9062: Exiting.\n",lval,linei, i,line,j);fflush(ficlog);
1.238 brouard 9063: return 1;
9064: }
9065: cotvar[j][iv][i]=(double)(lval);
9066: strcpy(line,stra);
1.223 brouard 9067: }/* end loop ntv */
1.225 brouard 9068:
1.223 brouard 9069: /* Statuses at wave */
1.137 brouard 9070: cutv(stra, strb, line, ' ');
1.223 brouard 9071: if(strb[0]=='.') { /* Missing value */
1.238 brouard 9072: lval=-1;
1.136 brouard 9073: }else{
1.238 brouard 9074: errno=0;
9075: lval=strtol(strb,&endptr,10);
9076: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN))*/
9077: if( strb[0]=='\0' || (*endptr != '\0')){
9078: 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);
9079: 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);
9080: return 1;
9081: }
1.136 brouard 9082: }
1.225 brouard 9083:
1.136 brouard 9084: s[j][i]=lval;
1.225 brouard 9085:
1.223 brouard 9086: /* Date of Interview */
1.136 brouard 9087: strcpy(line,stra);
9088: cutv(stra, strb,line,' ');
1.169 brouard 9089: if( (iout=sscanf(strb,"%d/%d",&month, &year)) != 0){
1.136 brouard 9090: }
1.169 brouard 9091: else if( (iout=sscanf(strb,"%s.",dummy)) != 0){
1.225 brouard 9092: month=99;
9093: year=9999;
1.136 brouard 9094: }else{
1.225 brouard 9095: 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);
9096: 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);
9097: return 1;
1.136 brouard 9098: }
9099: anint[j][i]= (double) year;
9100: mint[j][i]= (double)month;
9101: strcpy(line,stra);
1.223 brouard 9102: } /* End loop on waves */
1.225 brouard 9103:
1.223 brouard 9104: /* Date of death */
1.136 brouard 9105: cutv(stra, strb,line,' ');
1.169 brouard 9106: if( (iout=sscanf(strb,"%d/%d",&month, &year)) != 0){
1.136 brouard 9107: }
1.169 brouard 9108: else if( (iout=sscanf(strb,"%s.",dummy)) != 0){
1.136 brouard 9109: month=99;
9110: year=9999;
9111: }else{
1.141 brouard 9112: 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 9113: 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);
9114: return 1;
1.136 brouard 9115: }
9116: andc[i]=(double) year;
9117: moisdc[i]=(double) month;
9118: strcpy(line,stra);
9119:
1.223 brouard 9120: /* Date of birth */
1.136 brouard 9121: cutv(stra, strb,line,' ');
1.169 brouard 9122: if( (iout=sscanf(strb,"%d/%d",&month, &year)) != 0){
1.136 brouard 9123: }
1.169 brouard 9124: else if( (iout=sscanf(strb,"%s.", dummy)) != 0){
1.136 brouard 9125: month=99;
9126: year=9999;
9127: }else{
1.141 brouard 9128: 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);
9129: 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 9130: return 1;
1.136 brouard 9131: }
9132: if (year==9999) {
1.141 brouard 9133: 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);
9134: 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 9135: return 1;
9136:
1.136 brouard 9137: }
9138: annais[i]=(double)(year);
9139: moisnais[i]=(double)(month);
9140: strcpy(line,stra);
1.225 brouard 9141:
1.223 brouard 9142: /* Sample weight */
1.136 brouard 9143: cutv(stra, strb,line,' ');
9144: errno=0;
9145: dval=strtod(strb,&endptr);
9146: if( strb[0]=='\0' || (*endptr != '\0')){
1.141 brouard 9147: printf("Error reading data around '%f' at line number %d, \"%s\" for individual %d\nShould be a weight. Exiting.\n",dval, i,line,linei);
9148: 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 9149: fflush(ficlog);
9150: return 1;
9151: }
9152: weight[i]=dval;
9153: strcpy(line,stra);
1.225 brouard 9154:
1.223 brouard 9155: for (iv=nqv;iv>=1;iv--){ /* Loop on fixed quantitative variables */
9156: cutv(stra, strb, line, ' ');
9157: if(strb[0]=='.') { /* Missing value */
1.225 brouard 9158: lval=-1;
1.223 brouard 9159: }else{
1.225 brouard 9160: errno=0;
9161: /* what_kind_of_number(strb); */
9162: dval=strtod(strb,&endptr);
9163: /* if(strb != endptr && *endptr == '\0') */
9164: /* dval=dlval; */
9165: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN)) */
9166: if( strb[0]=='\0' || (*endptr != '\0')){
9167: 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);
9168: 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);
9169: return 1;
9170: }
9171: coqvar[iv][i]=dval;
1.226 brouard 9172: covar[ncovcol+iv][i]=dval; /* including qvar in standard covar for performance reasons */
1.223 brouard 9173: }
9174: strcpy(line,stra);
9175: }/* end loop nqv */
1.136 brouard 9176:
1.223 brouard 9177: /* Covariate values */
1.136 brouard 9178: for (j=ncovcol;j>=1;j--){
9179: cutv(stra, strb,line,' ');
1.223 brouard 9180: if(strb[0]=='.') { /* Missing covariate value */
1.225 brouard 9181: lval=-1;
1.136 brouard 9182: }else{
1.225 brouard 9183: errno=0;
9184: lval=strtol(strb,&endptr,10);
9185: if( strb[0]=='\0' || (*endptr != '\0')){
9186: 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);
9187: 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);
9188: return 1;
9189: }
1.136 brouard 9190: }
9191: if(lval <-1 || lval >1){
1.225 brouard 9192: printf("Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.136 brouard 9193: Should be a value of %d(nth) covariate (0 should be the value for the reference and 1\n \
9194: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.225 brouard 9195: For example, for multinomial values like 1, 2 and 3,\n \
9196: build V1=0 V2=0 for the reference value (1),\n \
9197: V1=1 V2=0 for (2) \n \
1.136 brouard 9198: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.225 brouard 9199: output of IMaCh is often meaningless.\n \
1.136 brouard 9200: Exiting.\n",lval,linei, i,line,j);
1.225 brouard 9201: fprintf(ficlog,"Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.136 brouard 9202: Should be a value of %d(nth) covariate (0 should be the value for the reference and 1\n \
9203: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.225 brouard 9204: For example, for multinomial values like 1, 2 and 3,\n \
9205: build V1=0 V2=0 for the reference value (1),\n \
9206: V1=1 V2=0 for (2) \n \
1.136 brouard 9207: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.225 brouard 9208: output of IMaCh is often meaningless.\n \
1.136 brouard 9209: Exiting.\n",lval,linei, i,line,j);fflush(ficlog);
1.225 brouard 9210: return 1;
1.136 brouard 9211: }
9212: covar[j][i]=(double)(lval);
9213: strcpy(line,stra);
9214: }
9215: lstra=strlen(stra);
1.225 brouard 9216:
1.136 brouard 9217: if(lstra > 9){ /* More than 2**32 or max of what printf can write with %ld */
9218: stratrunc = &(stra[lstra-9]);
9219: num[i]=atol(stratrunc);
9220: }
9221: else
9222: num[i]=atol(stra);
9223: /*if((s[2][i]==2) && (s[3][i]==-1)&&(s[4][i]==9)){
9224: 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;}*/
9225:
9226: i=i+1;
9227: } /* End loop reading data */
1.225 brouard 9228:
1.136 brouard 9229: *imax=i-1; /* Number of individuals */
9230: fclose(fic);
1.225 brouard 9231:
1.136 brouard 9232: return (0);
1.164 brouard 9233: /* endread: */
1.225 brouard 9234: printf("Exiting readdata: ");
9235: fclose(fic);
9236: return (1);
1.223 brouard 9237: }
1.126 brouard 9238:
1.234 brouard 9239: void removefirstspace(char **stri){/*, char stro[]) {*/
1.230 brouard 9240: char *p1 = *stri, *p2 = *stri;
1.235 brouard 9241: while (*p2 == ' ')
1.234 brouard 9242: p2++;
9243: /* while ((*p1++ = *p2++) !=0) */
9244: /* ; */
9245: /* do */
9246: /* while (*p2 == ' ') */
9247: /* p2++; */
9248: /* while (*p1++ == *p2++); */
9249: *stri=p2;
1.145 brouard 9250: }
9251:
1.235 brouard 9252: int decoderesult ( char resultline[], int nres)
1.230 brouard 9253: /**< This routine decode one result line and returns the combination # of dummy covariates only **/
9254: {
1.235 brouard 9255: int j=0, k=0, k1=0, k2=0, k3=0, k4=0, match=0, k2q=0, k3q=0, k4q=0;
1.230 brouard 9256: char resultsav[MAXLINE];
1.234 brouard 9257: int resultmodel[MAXLINE];
9258: int modelresult[MAXLINE];
1.230 brouard 9259: char stra[80], strb[80], strc[80], strd[80],stre[80];
9260:
1.234 brouard 9261: removefirstspace(&resultline);
1.233 brouard 9262: printf("decoderesult:%s\n",resultline);
1.230 brouard 9263:
9264: if (strstr(resultline,"v") !=0){
9265: printf("Error. 'v' must be in upper case 'V' result: %s ",resultline);
9266: fprintf(ficlog,"Error. 'v' must be in upper case result: %s ",resultline);fflush(ficlog);
9267: return 1;
9268: }
9269: trimbb(resultsav, resultline);
9270: if (strlen(resultsav) >1){
9271: j=nbocc(resultsav,'='); /**< j=Number of covariate values'=' */
9272: }
1.253 brouard 9273: if(j == 0){ /* Resultline but no = */
9274: TKresult[nres]=0; /* Combination for the nresult and the model */
9275: return (0);
9276: }
9277:
1.234 brouard 9278: if( j != cptcovs ){ /* Be careful if a variable is in a product but not single */
9279: 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);
9280: 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);
9281: }
9282: for(k=1; k<=j;k++){ /* Loop on any covariate of the result line */
9283: if(nbocc(resultsav,'=') >1){
9284: cutl(stra,strb,resultsav,' '); /* keeps in strb after the first ' '
9285: resultsav= V4=1 V5=25.1 V3=0 strb=V3=0 stra= V4=1 V5=25.1 */
9286: cutl(strc,strd,strb,'='); /* strb:V4=1 strc=1 strd=V4 */
9287: }else
9288: cutl(strc,strd,resultsav,'=');
1.230 brouard 9289: Tvalsel[k]=atof(strc); /* 1 */
1.234 brouard 9290:
1.230 brouard 9291: cutl(strc,stre,strd,'V'); /* strd='V4' strc=4 stre='V' */;
9292: Tvarsel[k]=atoi(strc);
9293: /* Typevarsel[k]=1; /\* 1 for age product *\/ */
9294: /* cptcovsel++; */
9295: if (nbocc(stra,'=') >0)
9296: strcpy(resultsav,stra); /* and analyzes it */
9297: }
1.235 brouard 9298: /* Checking for missing or useless values in comparison of current model needs */
1.236 brouard 9299: for(k1=1; k1<= cptcovt ;k1++){ /* model line V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
9300: if(Typevar[k1]==0){ /* Single covariate in model */
1.234 brouard 9301: match=0;
1.236 brouard 9302: for(k2=1; k2 <=j;k2++){/* result line V4=1 V5=24.1 V3=1 V2=8 V1=0 */
1.237 brouard 9303: if(Tvar[k1]==Tvarsel[k2]) {/* Tvar[1]=5 == Tvarsel[2]=5 */
1.236 brouard 9304: modelresult[k2]=k1;/* modelresult[2]=1 modelresult[1]=2 modelresult[3]=3 modelresult[6]=4 modelresult[9]=5 */
1.234 brouard 9305: match=1;
9306: break;
9307: }
9308: }
9309: if(match == 0){
9310: printf("Error in result line: %d value missing; result: %s, model=%s\n",k1, resultline, model);
9311: }
9312: }
9313: }
1.235 brouard 9314: /* Checking for missing or useless values in comparison of current model needs */
9315: for(k2=1; k2 <=j;k2++){ /* result line V4=1 V5=24.1 V3=1 V2=8 V1=0 */
1.234 brouard 9316: match=0;
1.235 brouard 9317: for(k1=1; k1<= cptcovt ;k1++){ /* model line V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
9318: if(Typevar[k1]==0){ /* Single */
1.237 brouard 9319: if(Tvar[k1]==Tvarsel[k2]) { /* Tvar[2]=4 == Tvarsel[1]=4 */
1.235 brouard 9320: resultmodel[k1]=k2; /* resultmodel[2]=1 resultmodel[1]=2 resultmodel[3]=3 resultmodel[6]=4 resultmodel[9]=5 */
1.234 brouard 9321: ++match;
9322: }
9323: }
9324: }
9325: if(match == 0){
9326: printf("Error in result line: %d value missing; result: %s, model=%s\n",k1, resultline, model);
9327: }else if(match > 1){
9328: printf("Error in result line: %d doubled; result: %s, model=%s\n",k2, resultline, model);
9329: }
9330: }
1.235 brouard 9331:
1.234 brouard 9332: /* We need to deduce which combination number is chosen and save quantitative values */
1.235 brouard 9333: /* model line V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
9334: /* result line V4=1 V5=25.1 V3=0 V2=8 V1=1 */
9335: /* should give a combination of dummy V4=1, V3=0, V1=1 => V4*2**(0) + V3*2**(1) + V1*2**(2) = 5 + (1offset) = 6*/
9336: /* result line V4=1 V5=24.1 V3=1 V2=8 V1=0 */
9337: /* should give a combination of dummy V4=1, V3=1, V1=0 => V4*2**(0) + V3*2**(1) + V1*2**(2) = 3 + (1offset) = 4*/
9338: /* 1 0 0 0 */
9339: /* 2 1 0 0 */
9340: /* 3 0 1 0 */
9341: /* 4 1 1 0 */ /* V4=1, V3=1, V1=0 */
9342: /* 5 0 0 1 */
9343: /* 6 1 0 1 */ /* V4=1, V3=0, V1=1 */
9344: /* 7 0 1 1 */
9345: /* 8 1 1 1 */
1.237 brouard 9346: /* V(Tvresult)=Tresult V4=1 V3=0 V1=1 Tresult[nres=1][2]=0 */
9347: /* V(Tvqresult)=Tqresult V5=25.1 V2=8 Tqresult[nres=1][1]=25.1 */
9348: /* V5*age V5 known which value for nres? */
9349: /* Tqinvresult[2]=8 Tqinvresult[1]=25.1 */
1.235 brouard 9350: for(k1=1, k=0, k4=0, k4q=0; k1 <=cptcovt;k1++){ /* model line */
9351: if( Dummy[k1]==0 && Typevar[k1]==0 ){ /* Single dummy */
1.237 brouard 9352: k3= resultmodel[k1]; /* resultmodel[2(V4)] = 1=k3 */
1.235 brouard 9353: k2=(int)Tvarsel[k3]; /* Tvarsel[resultmodel[2]]= Tvarsel[1] = 4=k2 */
9354: k+=Tvalsel[k3]*pow(2,k4); /* Tvalsel[1]=1 */
1.237 brouard 9355: Tresult[nres][k4+1]=Tvalsel[k3];/* Tresult[nres][1]=1(V4=1) Tresult[nres][2]=0(V3=0) */
9356: Tvresult[nres][k4+1]=(int)Tvarsel[k3];/* Tvresult[nres][1]=4 Tvresult[nres][3]=1 */
9357: Tinvresult[nres][(int)Tvarsel[k3]]=Tvalsel[k3]; /* Tinvresult[nres][4]=1 */
1.235 brouard 9358: printf("Decoderesult Dummy k=%d, V(k2=V%d)= Tvalsel[%d]=%d, 2**(%d)\n",k, k2, k3, (int)Tvalsel[k3], k4);
9359: k4++;;
9360: } else if( Dummy[k1]==1 && Typevar[k1]==0 ){ /* Single quantitative */
9361: k3q= resultmodel[k1]; /* resultmodel[2] = 1=k3 */
9362: k2q=(int)Tvarsel[k3q]; /* Tvarsel[resultmodel[2]]= Tvarsel[1] = 4=k2 */
1.237 brouard 9363: Tqresult[nres][k4q+1]=Tvalsel[k3q]; /* Tqresult[nres][1]=25.1 */
9364: Tvqresult[nres][k4q+1]=(int)Tvarsel[k3q]; /* Tvqresult[nres][1]=5 */
9365: Tqinvresult[nres][(int)Tvarsel[k3q]]=Tvalsel[k3q]; /* Tqinvresult[nres][5]=25.1 */
1.235 brouard 9366: printf("Decoderesult Quantitative nres=%d, V(k2q=V%d)= Tvalsel[%d]=%d, Tvarsel[%d]=%f\n",nres, k2q, k3q, Tvarsel[k3q], k3q, Tvalsel[k3q]);
9367: k4q++;;
9368: }
9369: }
1.234 brouard 9370:
1.235 brouard 9371: TKresult[nres]=++k; /* Combination for the nresult and the model */
1.230 brouard 9372: return (0);
9373: }
1.235 brouard 9374:
1.230 brouard 9375: int decodemodel( char model[], int lastobs)
9376: /**< This routine decodes the model and returns:
1.224 brouard 9377: * Model V1+V2+V3+V8+V7*V8+V5*V6+V8*age+V3*age+age*age
9378: * - nagesqr = 1 if age*age in the model, otherwise 0.
9379: * - cptcovt total number of covariates of the model nbocc(+)+1 = 8 excepting constant and age and age*age
9380: * - cptcovn or number of covariates k of the models excluding age*products =6 and age*age
9381: * - cptcovage number of covariates with age*products =2
9382: * - cptcovs number of simple covariates
9383: * - 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
9384: * which is a new column after the 9 (ncovcol) variables.
9385: * - if k is a product Vn*Vm covar[k][i] is filled with correct values for each individual
9386: * - Tprod[l] gives the kth covariates of the product Vn*Vm l=1 to cptcovprod-cptcovage
9387: * Tprod[1]@2 {5, 6}: position of first product V7*V8 is 5, and second V5*V6 is 6.
9388: * - Tvard[k] p Tvard[1][1]@4 {7, 8, 5, 6} for V7*V8 and V5*V6 .
9389: */
1.136 brouard 9390: {
1.238 brouard 9391: int i, j, k, ks, v;
1.227 brouard 9392: int j1, k1, k2, k3, k4;
1.136 brouard 9393: char modelsav[80];
1.145 brouard 9394: char stra[80], strb[80], strc[80], strd[80],stre[80];
1.187 brouard 9395: char *strpt;
1.136 brouard 9396:
1.145 brouard 9397: /*removespace(model);*/
1.136 brouard 9398: if (strlen(model) >1){ /* If there is at least 1 covariate */
1.145 brouard 9399: j=0, j1=0, k1=0, k2=-1, ks=0, cptcovn=0;
1.137 brouard 9400: if (strstr(model,"AGE") !=0){
1.192 brouard 9401: printf("Error. AGE must be in lower case 'age' model=1+age+%s. ",model);
9402: fprintf(ficlog,"Error. AGE must be in lower case model=1+age+%s. ",model);fflush(ficlog);
1.136 brouard 9403: return 1;
9404: }
1.141 brouard 9405: if (strstr(model,"v") !=0){
9406: printf("Error. 'v' must be in upper case 'V' model=%s ",model);
9407: fprintf(ficlog,"Error. 'v' must be in upper case model=%s ",model);fflush(ficlog);
9408: return 1;
9409: }
1.187 brouard 9410: strcpy(modelsav,model);
9411: if ((strpt=strstr(model,"age*age")) !=0){
9412: printf(" strpt=%s, model=%s\n",strpt, model);
9413: if(strpt != model){
1.234 brouard 9414: printf("Error in model: 'model=%s'; 'age*age' should in first place before other covariates\n \
1.192 brouard 9415: 'model=1+age+age*age+V1.' or 'model=1+age+age*age+V1+V1*age.', please swap as well as \n \
1.187 brouard 9416: corresponding column of parameters.\n",model);
1.234 brouard 9417: fprintf(ficlog,"Error in model: 'model=%s'; 'age*age' should in first place before other covariates\n \
1.192 brouard 9418: 'model=1+age+age*age+V1.' or 'model=1+age+age*age+V1+V1*age.', please swap as well as \n \
1.187 brouard 9419: corresponding column of parameters.\n",model); fflush(ficlog);
1.234 brouard 9420: return 1;
1.225 brouard 9421: }
1.187 brouard 9422: nagesqr=1;
9423: if (strstr(model,"+age*age") !=0)
1.234 brouard 9424: substrchaine(modelsav, model, "+age*age");
1.187 brouard 9425: else if (strstr(model,"age*age+") !=0)
1.234 brouard 9426: substrchaine(modelsav, model, "age*age+");
1.187 brouard 9427: else
1.234 brouard 9428: substrchaine(modelsav, model, "age*age");
1.187 brouard 9429: }else
9430: nagesqr=0;
9431: if (strlen(modelsav) >1){
9432: j=nbocc(modelsav,'+'); /**< j=Number of '+' */
9433: j1=nbocc(modelsav,'*'); /**< j1=Number of '*' */
1.224 brouard 9434: cptcovs=j+1-j1; /**< Number of simple covariates V1+V1*age+V3 +V3*V4+age*age=> V1 + V3 =5-3=2 */
1.187 brouard 9435: cptcovt= j+1; /* Number of total covariates in the model, not including
1.225 brouard 9436: * cst, age and age*age
9437: * V1+V1*age+ V3 + V3*V4+age*age=> 3+1=4*/
9438: /* including age products which are counted in cptcovage.
9439: * but the covariates which are products must be treated
9440: * separately: ncovn=4- 2=2 (V1+V3). */
1.187 brouard 9441: cptcovprod=j1; /**< Number of products V1*V2 +v3*age = 2 */
9442: cptcovprodnoage=0; /**< Number of covariate products without age: V3*V4 =1 */
1.225 brouard 9443:
9444:
1.187 brouard 9445: /* Design
9446: * V1 V2 V3 V4 V5 V6 V7 V8 V9 Weight
9447: * < ncovcol=8 >
9448: * Model V2 + V1 + V3*age + V3 + V5*V6 + V7*V8 + V8*age + V8
9449: * k= 1 2 3 4 5 6 7 8
9450: * cptcovn number of covariates (not including constant and age ) = # of + plus 1 = 7+1=8
9451: * covar[k,i], value of kth covariate if not including age for individual i:
1.224 brouard 9452: * covar[1][i]= (V1), covar[4][i]=(V4), covar[8][i]=(V8)
9453: * Tvar[k] # of the kth covariate: Tvar[1]=2 Tvar[2]=1 Tvar[4]=3 Tvar[8]=8
1.187 brouard 9454: * if multiplied by age: V3*age Tvar[3=V3*age]=3 (V3) Tvar[7]=8 and
9455: * Tage[++cptcovage]=k
9456: * if products, new covar are created after ncovcol with k1
9457: * Tvar[k]=ncovcol+k1; # of the kth covariate product: Tvar[5]=ncovcol+1=10 Tvar[6]=ncovcol+1=11
9458: * Tprod[k1]=k; Tprod[1]=5 Tprod[2]= 6; gives the position of the k1th product
9459: * 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
9460: * Tvar[cptcovn+k2]=Tvard[k1][1];Tvar[cptcovn+k2+1]=Tvard[k1][2];
9461: * Tvar[8+1]=5;Tvar[8+2]=6;Tvar[8+3]=7;Tvar[8+4]=8 inverted
9462: * V1 V2 V3 V4 V5 V6 V7 V8 V9 V10 V11
9463: * < ncovcol=8 >
9464: * Model V2 + V1 + V3*age + V3 + V5*V6 + V7*V8 + V8*age + V8 d1 d1 d2 d2
9465: * k= 1 2 3 4 5 6 7 8 9 10 11 12
9466: * Tvar[k]= 2 1 3 3 10 11 8 8 5 6 7 8
9467: * p Tvar[1]@12={2, 1, 3, 3, 11, 10, 8, 8, 7, 8, 5, 6}
9468: * p Tprod[1]@2={ 6, 5}
9469: *p Tvard[1][1]@4= {7, 8, 5, 6}
9470: * covar[k][i]= V2 V1 ? V3 V5*V6? V7*V8? ? V8
9471: * cov[Tage[kk]+2]=covar[Tvar[Tage[kk]]][i]*cov[2];
9472: *How to reorganize?
9473: * Model V1 + V2 + V3 + V8 + V5*V6 + V7*V8 + V3*age + V8*age
9474: * Tvars {2, 1, 3, 3, 11, 10, 8, 8, 7, 8, 5, 6}
9475: * {2, 1, 4, 8, 5, 6, 3, 7}
9476: * Struct []
9477: */
1.225 brouard 9478:
1.187 brouard 9479: /* This loop fills the array Tvar from the string 'model'.*/
9480: /* j is the number of + signs in the model V1+V2+V3 j=2 i=3 to 1 */
9481: /* modelsav=V2+V1+V4+age*V3 strb=age*V3 stra=V2+V1+V4 */
9482: /* k=4 (age*V3) Tvar[k=4]= 3 (from V3) Tage[cptcovage=1]=4 */
9483: /* k=3 V4 Tvar[k=3]= 4 (from V4) */
9484: /* k=2 V1 Tvar[k=2]= 1 (from V1) */
9485: /* k=1 Tvar[1]=2 (from V2) */
9486: /* k=5 Tvar[5] */
9487: /* for (k=1; k<=cptcovn;k++) { */
1.198 brouard 9488: /* cov[2+k]=nbcode[Tvar[k]][codtabm(ij,Tvar[k])]; */
1.187 brouard 9489: /* } */
1.198 brouard 9490: /* for (k=1; k<=cptcovage;k++) cov[2+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,Tvar[Tage[k])]]*cov[2]; */
1.187 brouard 9491: /*
9492: * Treating invertedly V2+V1+V3*age+V2*V4 is as if written V2*V4 +V3*age + V1 + V2 */
1.227 brouard 9493: for(k=cptcovt; k>=1;k--){ /**< Number of covariates not including constant and age, neither age*age*/
9494: Tvar[k]=0; Tprod[k]=0; Tposprod[k]=0;
9495: }
1.187 brouard 9496: cptcovage=0;
9497: for(k=1; k<=cptcovt;k++){ /* Loop on total covariates of the model */
1.234 brouard 9498: cutl(stra,strb,modelsav,'+'); /* keeps in strb after the first '+'
1.225 brouard 9499: modelsav==V2+V1+V4+V3*age strb=V3*age stra=V2+V1+V4 */
1.234 brouard 9500: if (nbocc(modelsav,'+')==0) strcpy(strb,modelsav); /* and analyzes it */
9501: /* printf("i=%d a=%s b=%s sav=%s\n",i, stra,strb,modelsav);*/
9502: /*scanf("%d",i);*/
9503: if (strchr(strb,'*')) { /**< Model includes a product V2+V1+V4+V3*age strb=V3*age */
9504: cutl(strc,strd,strb,'*'); /**< strd*strc Vm*Vn: strb=V3*age(input) strc=age strd=V3 ; V3*V2 strc=V2, strd=V3 */
9505: if (strcmp(strc,"age")==0) { /**< Model includes age: Vn*age */
9506: /* covar is not filled and then is empty */
9507: cptcovprod--;
9508: cutl(stre,strb,strd,'V'); /* strd=V3(input): stre="3" */
9509: Tvar[k]=atoi(stre); /* V2+V1+V4+V3*age Tvar[4]=3 ; V1+V2*age Tvar[2]=2; V1+V1*age Tvar[2]=1 */
9510: Typevar[k]=1; /* 1 for age product */
9511: cptcovage++; /* Sums the number of covariates which include age as a product */
9512: Tage[cptcovage]=k; /* Tvar[4]=3, Tage[1] = 4 or V1+V1*age Tvar[2]=1, Tage[1]=2 */
9513: /*printf("stre=%s ", stre);*/
9514: } else if (strcmp(strd,"age")==0) { /* or age*Vn */
9515: cptcovprod--;
9516: cutl(stre,strb,strc,'V');
9517: Tvar[k]=atoi(stre);
9518: Typevar[k]=1; /* 1 for age product */
9519: cptcovage++;
9520: Tage[cptcovage]=k;
9521: } else { /* Age is not in the model product V2+V1+V1*V4+V3*age+V3*V2 strb=V3*V2*/
9522: /* loops on k1=1 (V3*V2) and k1=2 V4*V3 */
9523: cptcovn++;
9524: cptcovprodnoage++;k1++;
9525: cutl(stre,strb,strc,'V'); /* strc= Vn, stre is n; strb=V3*V2 stre=3 strc=*/
9526: Tvar[k]=ncovcol+nqv+ntv+nqtv+k1; /* For model-covariate k tells which data-covariate to use but
9527: because this model-covariate is a construction we invent a new column
9528: which is after existing variables ncovcol+nqv+ntv+nqtv + k1
9529: If already ncovcol=4 and model=V2+V1+V1*V4+age*V3+V3*V2
9530: Tvar[3=V1*V4]=4+1 Tvar[5=V3*V2]=4 + 2= 6, etc */
9531: Typevar[k]=2; /* 2 for double fixed dummy covariates */
9532: cutl(strc,strb,strd,'V'); /* strd was Vm, strc is m */
9533: Tprod[k1]=k; /* Tprod[1]=3(=V1*V4) for V2+V1+V1*V4+age*V3+V3*V2 */
9534: Tposprod[k]=k1; /* Tpsprod[3]=1, Tposprod[2]=5 */
9535: Tvard[k1][1] =atoi(strc); /* m 1 for V1*/
9536: Tvard[k1][2] =atoi(stre); /* n 4 for V4*/
9537: k2=k2+2; /* k2 is initialize to -1, We want to store the n and m in Vn*Vm at the end of Tvar */
9538: /* Tvar[cptcovt+k2]=Tvard[k1][1]; /\* Tvar[(cptcovt=4+k2=1)=5]= 1 (V1) *\/ */
9539: /* Tvar[cptcovt+k2+1]=Tvard[k1][2]; /\* Tvar[(cptcovt=4+(k2=1)+1)=6]= 4 (V4) *\/ */
1.225 brouard 9540: /*ncovcol=4 and model=V2+V1+V1*V4+age*V3+V3*V2, Tvar[3]=5, Tvar[4]=6, cptcovt=5 */
1.234 brouard 9541: /* 1 2 3 4 5 | Tvar[5+1)=1, Tvar[7]=2 */
9542: for (i=1; i<=lastobs;i++){
9543: /* Computes the new covariate which is a product of
9544: covar[n][i]* covar[m][i] and stores it at ncovol+k1 May not be defined */
9545: covar[ncovcol+k1][i]=covar[atoi(stre)][i]*covar[atoi(strc)][i];
9546: }
9547: } /* End age is not in the model */
9548: } /* End if model includes a product */
9549: else { /* no more sum */
9550: /*printf("d=%s c=%s b=%s\n", strd,strc,strb);*/
9551: /* scanf("%d",i);*/
9552: cutl(strd,strc,strb,'V');
9553: ks++; /**< Number of simple covariates dummy or quantitative, fixe or varying */
9554: cptcovn++; /** V4+V3+V5: V4 and V3 timevarying dummy covariates, V5 timevarying quantitative */
9555: Tvar[k]=atoi(strd);
9556: Typevar[k]=0; /* 0 for simple covariates */
9557: }
9558: strcpy(modelsav,stra); /* modelsav=V2+V1+V4 stra=V2+V1+V4 */
1.223 brouard 9559: /*printf("a=%s b=%s sav=%s\n", stra,strb,modelsav);
1.225 brouard 9560: scanf("%d",i);*/
1.187 brouard 9561: } /* end of loop + on total covariates */
9562: } /* end if strlen(modelsave == 0) age*age might exist */
9563: } /* end if strlen(model == 0) */
1.136 brouard 9564:
9565: /*The number n of Vn is stored in Tvar. cptcovage =number of age covariate. Tage gives the position of age. cptcovprod= number of products.
9566: If model=V1+V1*age then Tvar[1]=1 Tvar[2]=1 cptcovage=1 Tage[1]=2 cptcovprod=0*/
1.225 brouard 9567:
1.136 brouard 9568: /* printf("tvar1=%d tvar2=%d tvar3=%d cptcovage=%d Tage=%d",Tvar[1],Tvar[2],Tvar[3],cptcovage,Tage[1]);
1.225 brouard 9569: printf("cptcovprod=%d ", cptcovprod);
9570: fprintf(ficlog,"cptcovprod=%d ", cptcovprod);
9571: scanf("%d ",i);*/
9572:
9573:
1.230 brouard 9574: /* Until here, decodemodel knows only the grammar (simple, product, age*) of the model but not what kind
9575: of variable (dummy vs quantitative, fixed vs time varying) is behind. But we know the # of each. */
1.226 brouard 9576: /* ncovcol= 1, nqv=1 | ntv=2, nqtv= 1 = 5 possible variables data: 2 fixed 3, varying
9577: model= V5 + V4 +V3 + V4*V3 + V5*age + V2 + V1*V2 + V1*age + V5*age, V1 is not used saving its place
9578: k = 1 2 3 4 5 6 7 8 9
9579: Tvar[k]= 5 4 3 1+1+2+1+1=6 5 2 7 1 5
9580: Typevar[k]= 0 0 0 2 1 0 2 1 1
1.227 brouard 9581: Fixed[k] 1 1 1 1 3 0 0 or 2 2 3
9582: Dummy[k] 1 0 0 0 3 1 1 2 3
9583: Tmodelind[combination of covar]=k;
1.225 brouard 9584: */
9585: /* Dispatching between quantitative and time varying covariates */
1.226 brouard 9586: /* If Tvar[k] >ncovcol it is a product */
1.225 brouard 9587: /* 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 9588: /* Computing effective variables, ie used by the model, that is from the cptcovt variables */
1.227 brouard 9589: printf("Model=%s\n\
9590: Typevar: 0 for simple covariate (dummy, quantitative, fixed or varying), 1 for age product, 2 for product \n\
9591: Fixed[k] 0=fixed (product or simple), 1 varying, 2 fixed with age product, 3 varying with age product \n\
9592: 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);
9593: fprintf(ficlog,"Model=%s\n\
9594: Typevar: 0 for simple covariate (dummy, quantitative, fixed or varying), 1 for age product, 2 for product \n\
9595: Fixed[k] 0=fixed (product or simple), 1 varying, 2 fixed with age product, 3 varying with age product \n\
9596: Dummy[k] 0=dummy (0 1), 1 quantitative (single or product without age), 2 dummy with age product, 3 quant with age product\n",model);
1.240 brouard 9597: for(k=1;k<=cptcovt; k++){ Fixed[k]=0; Dummy[k]=0;}
1.234 brouard 9598: 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 */
9599: if (Tvar[k] <=ncovcol && Typevar[k]==0 ){ /* Simple fixed dummy (<=ncovcol) covariates */
1.227 brouard 9600: Fixed[k]= 0;
9601: Dummy[k]= 0;
1.225 brouard 9602: ncoveff++;
1.232 brouard 9603: ncovf++;
1.234 brouard 9604: nsd++;
9605: modell[k].maintype= FTYPE;
9606: TvarsD[nsd]=Tvar[k];
9607: TvarsDind[nsd]=k;
9608: TvarF[ncovf]=Tvar[k];
9609: TvarFind[ncovf]=k;
9610: TvarFD[ncoveff]=Tvar[k]; /* TvarFD[1]=V1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
9611: TvarFDind[ncoveff]=k; /* TvarFDind[1]=9 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
9612: }else if( Tvar[k] <=ncovcol && Typevar[k]==2){ /* Product of fixed dummy (<=ncovcol) covariates */
9613: Fixed[k]= 0;
9614: Dummy[k]= 0;
9615: ncoveff++;
9616: ncovf++;
9617: modell[k].maintype= FTYPE;
9618: TvarF[ncovf]=Tvar[k];
9619: TvarFind[ncovf]=k;
1.230 brouard 9620: TvarFD[ncoveff]=Tvar[k]; /* TvarFD[1]=V1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1.231 brouard 9621: TvarFDind[ncoveff]=k; /* TvarFDind[1]=9 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1.240 brouard 9622: }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 9623: Fixed[k]= 0;
9624: Dummy[k]= 1;
1.230 brouard 9625: nqfveff++;
1.234 brouard 9626: modell[k].maintype= FTYPE;
9627: modell[k].subtype= FQ;
9628: nsq++;
9629: TvarsQ[nsq]=Tvar[k];
9630: TvarsQind[nsq]=k;
1.232 brouard 9631: ncovf++;
1.234 brouard 9632: TvarF[ncovf]=Tvar[k];
9633: TvarFind[ncovf]=k;
1.231 brouard 9634: 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 9635: 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 9636: }else if( Tvar[k] <=ncovcol+nqv+ntv && Typevar[k]==0){/* Only simple time varying dummy variables */
1.227 brouard 9637: Fixed[k]= 1;
9638: Dummy[k]= 0;
1.225 brouard 9639: ntveff++; /* Only simple time varying dummy variable */
1.234 brouard 9640: modell[k].maintype= VTYPE;
9641: modell[k].subtype= VD;
9642: nsd++;
9643: TvarsD[nsd]=Tvar[k];
9644: TvarsDind[nsd]=k;
9645: ncovv++; /* Only simple time varying variables */
9646: TvarV[ncovv]=Tvar[k];
1.242 brouard 9647: 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 9648: 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 */
9649: 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 9650: 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);
9651: printf("Quasi TmodelInvind[%d]=%d\n",k,Tvar[k]- ncovcol-nqv);
1.231 brouard 9652: }else if( Tvar[k] <=ncovcol+nqv+ntv+nqtv && Typevar[k]==0){ /* Only simple time varying quantitative variable V5*/
1.234 brouard 9653: Fixed[k]= 1;
9654: Dummy[k]= 1;
9655: nqtveff++;
9656: modell[k].maintype= VTYPE;
9657: modell[k].subtype= VQ;
9658: ncovv++; /* Only simple time varying variables */
9659: nsq++;
9660: TvarsQ[nsq]=Tvar[k];
9661: TvarsQind[nsq]=k;
9662: TvarV[ncovv]=Tvar[k];
1.242 brouard 9663: 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 9664: 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 */
9665: 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 9666: TmodelInvQind[nqtveff]=Tvar[k]- ncovcol-nqv-ntv;/* Only simple time varying quantitative variable */
9667: /* Tmodeliqind[k]=nqtveff;/\* Only simple time varying quantitative variable *\/ */
9668: 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 9669: printf("Quasi TmodelInvQind[%d]=%d\n",k,Tvar[k]- ncovcol-nqv-ntv);
1.227 brouard 9670: }else if (Typevar[k] == 1) { /* product with age */
1.234 brouard 9671: ncova++;
9672: TvarA[ncova]=Tvar[k];
9673: TvarAind[ncova]=k;
1.231 brouard 9674: if (Tvar[k] <=ncovcol ){ /* Product age with fixed dummy covariatee */
1.240 brouard 9675: Fixed[k]= 2;
9676: Dummy[k]= 2;
9677: modell[k].maintype= ATYPE;
9678: modell[k].subtype= APFD;
9679: /* ncoveff++; */
1.227 brouard 9680: }else if( Tvar[k] <=ncovcol+nqv) { /* Remind that product Vn*Vm are added in k*/
1.240 brouard 9681: Fixed[k]= 2;
9682: Dummy[k]= 3;
9683: modell[k].maintype= ATYPE;
9684: modell[k].subtype= APFQ; /* Product age * fixed quantitative */
9685: /* nqfveff++; /\* Only simple fixed quantitative variable *\/ */
1.227 brouard 9686: }else if( Tvar[k] <=ncovcol+nqv+ntv ){
1.240 brouard 9687: Fixed[k]= 3;
9688: Dummy[k]= 2;
9689: modell[k].maintype= ATYPE;
9690: modell[k].subtype= APVD; /* Product age * varying dummy */
9691: /* ntveff++; /\* Only simple time varying dummy variable *\/ */
1.227 brouard 9692: }else if( Tvar[k] <=ncovcol+nqv+ntv+nqtv){
1.240 brouard 9693: Fixed[k]= 3;
9694: Dummy[k]= 3;
9695: modell[k].maintype= ATYPE;
9696: modell[k].subtype= APVQ; /* Product age * varying quantitative */
9697: /* nqtveff++;/\* Only simple time varying quantitative variable *\/ */
1.227 brouard 9698: }
9699: }else if (Typevar[k] == 2) { /* product without age */
9700: k1=Tposprod[k];
9701: if(Tvard[k1][1] <=ncovcol){
1.240 brouard 9702: if(Tvard[k1][2] <=ncovcol){
9703: Fixed[k]= 1;
9704: Dummy[k]= 0;
9705: modell[k].maintype= FTYPE;
9706: modell[k].subtype= FPDD; /* Product fixed dummy * fixed dummy */
9707: ncovf++; /* Fixed variables without age */
9708: TvarF[ncovf]=Tvar[k];
9709: TvarFind[ncovf]=k;
9710: }else if(Tvard[k1][2] <=ncovcol+nqv){
9711: Fixed[k]= 0; /* or 2 ?*/
9712: Dummy[k]= 1;
9713: modell[k].maintype= FTYPE;
9714: modell[k].subtype= FPDQ; /* Product fixed dummy * fixed quantitative */
9715: ncovf++; /* Varying variables without age */
9716: TvarF[ncovf]=Tvar[k];
9717: TvarFind[ncovf]=k;
9718: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){
9719: Fixed[k]= 1;
9720: Dummy[k]= 0;
9721: modell[k].maintype= VTYPE;
9722: modell[k].subtype= VPDD; /* Product fixed dummy * varying dummy */
9723: ncovv++; /* Varying variables without age */
9724: TvarV[ncovv]=Tvar[k];
9725: TvarVind[ncovv]=k;
9726: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){
9727: Fixed[k]= 1;
9728: Dummy[k]= 1;
9729: modell[k].maintype= VTYPE;
9730: modell[k].subtype= VPDQ; /* Product fixed dummy * varying quantitative */
9731: ncovv++; /* Varying variables without age */
9732: TvarV[ncovv]=Tvar[k];
9733: TvarVind[ncovv]=k;
9734: }
1.227 brouard 9735: }else if(Tvard[k1][1] <=ncovcol+nqv){
1.240 brouard 9736: if(Tvard[k1][2] <=ncovcol){
9737: Fixed[k]= 0; /* or 2 ?*/
9738: Dummy[k]= 1;
9739: modell[k].maintype= FTYPE;
9740: modell[k].subtype= FPDQ; /* Product fixed quantitative * fixed dummy */
9741: ncovf++; /* Fixed variables without age */
9742: TvarF[ncovf]=Tvar[k];
9743: TvarFind[ncovf]=k;
9744: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){
9745: Fixed[k]= 1;
9746: Dummy[k]= 1;
9747: modell[k].maintype= VTYPE;
9748: modell[k].subtype= VPDQ; /* Product fixed quantitative * varying dummy */
9749: ncovv++; /* Varying variables without age */
9750: TvarV[ncovv]=Tvar[k];
9751: TvarVind[ncovv]=k;
9752: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){
9753: Fixed[k]= 1;
9754: Dummy[k]= 1;
9755: modell[k].maintype= VTYPE;
9756: modell[k].subtype= VPQQ; /* Product fixed quantitative * varying quantitative */
9757: ncovv++; /* Varying variables without age */
9758: TvarV[ncovv]=Tvar[k];
9759: TvarVind[ncovv]=k;
9760: ncovv++; /* Varying variables without age */
9761: TvarV[ncovv]=Tvar[k];
9762: TvarVind[ncovv]=k;
9763: }
1.227 brouard 9764: }else if(Tvard[k1][1] <=ncovcol+nqv+ntv){
1.240 brouard 9765: if(Tvard[k1][2] <=ncovcol){
9766: Fixed[k]= 1;
9767: Dummy[k]= 1;
9768: modell[k].maintype= VTYPE;
9769: modell[k].subtype= VPDD; /* Product time varying dummy * fixed dummy */
9770: ncovv++; /* Varying variables without age */
9771: TvarV[ncovv]=Tvar[k];
9772: TvarVind[ncovv]=k;
9773: }else if(Tvard[k1][2] <=ncovcol+nqv){
9774: Fixed[k]= 1;
9775: Dummy[k]= 1;
9776: modell[k].maintype= VTYPE;
9777: modell[k].subtype= VPDQ; /* Product time varying dummy * fixed quantitative */
9778: ncovv++; /* Varying variables without age */
9779: TvarV[ncovv]=Tvar[k];
9780: TvarVind[ncovv]=k;
9781: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){
9782: Fixed[k]= 1;
9783: Dummy[k]= 0;
9784: modell[k].maintype= VTYPE;
9785: modell[k].subtype= VPDD; /* Product time varying dummy * time varying dummy */
9786: ncovv++; /* Varying variables without age */
9787: TvarV[ncovv]=Tvar[k];
9788: TvarVind[ncovv]=k;
9789: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){
9790: Fixed[k]= 1;
9791: Dummy[k]= 1;
9792: modell[k].maintype= VTYPE;
9793: modell[k].subtype= VPDQ; /* Product time varying dummy * time varying quantitative */
9794: ncovv++; /* Varying variables without age */
9795: TvarV[ncovv]=Tvar[k];
9796: TvarVind[ncovv]=k;
9797: }
1.227 brouard 9798: }else if(Tvard[k1][1] <=ncovcol+nqv+ntv+nqtv){
1.240 brouard 9799: if(Tvard[k1][2] <=ncovcol){
9800: Fixed[k]= 1;
9801: Dummy[k]= 1;
9802: modell[k].maintype= VTYPE;
9803: modell[k].subtype= VPDQ; /* Product time varying quantitative * fixed dummy */
9804: ncovv++; /* Varying variables without age */
9805: TvarV[ncovv]=Tvar[k];
9806: TvarVind[ncovv]=k;
9807: }else if(Tvard[k1][2] <=ncovcol+nqv){
9808: Fixed[k]= 1;
9809: Dummy[k]= 1;
9810: modell[k].maintype= VTYPE;
9811: modell[k].subtype= VPQQ; /* Product time varying quantitative * fixed quantitative */
9812: ncovv++; /* Varying variables without age */
9813: TvarV[ncovv]=Tvar[k];
9814: TvarVind[ncovv]=k;
9815: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){
9816: Fixed[k]= 1;
9817: Dummy[k]= 1;
9818: modell[k].maintype= VTYPE;
9819: modell[k].subtype= VPDQ; /* Product time varying quantitative * time varying dummy */
9820: ncovv++; /* Varying variables without age */
9821: TvarV[ncovv]=Tvar[k];
9822: TvarVind[ncovv]=k;
9823: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){
9824: Fixed[k]= 1;
9825: Dummy[k]= 1;
9826: modell[k].maintype= VTYPE;
9827: modell[k].subtype= VPQQ; /* Product time varying quantitative * time varying quantitative */
9828: ncovv++; /* Varying variables without age */
9829: TvarV[ncovv]=Tvar[k];
9830: TvarVind[ncovv]=k;
9831: }
1.227 brouard 9832: }else{
1.240 brouard 9833: printf("Error unknown type of covariate: Tvard[%d][1]=%d,Tvard[%d][2]=%d\n",k1,Tvard[k1][1],k1,Tvard[k1][2]);
9834: fprintf(ficlog,"Error unknown type of covariate: Tvard[%d][1]=%d,Tvard[%d][2]=%d\n",k1,Tvard[k1][1],k1,Tvard[k1][2]);
9835: } /*end k1*/
1.225 brouard 9836: }else{
1.226 brouard 9837: printf("Error, current version can't treat for performance reasons, Tvar[%d]=%d, Typevar[%d]=%d\n", k, Tvar[k], k, Typevar[k]);
9838: 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 9839: }
1.227 brouard 9840: 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 9841: printf(" modell[%d].maintype=%d, modell[%d].subtype=%d\n",k,modell[k].maintype,k,modell[k].subtype);
1.227 brouard 9842: 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]);
9843: }
9844: /* Searching for doublons in the model */
9845: for(k1=1; k1<= cptcovt;k1++){
9846: for(k2=1; k2 <k1;k2++){
9847: if((Typevar[k1]==Typevar[k2]) && (Fixed[Tvar[k1]]==Fixed[Tvar[k2]]) && (Dummy[Tvar[k1]]==Dummy[Tvar[k2]] )){
1.234 brouard 9848: if((Typevar[k1] == 0 || Typevar[k1] == 1)){ /* Simple or age product */
9849: if(Tvar[k1]==Tvar[k2]){
9850: 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]]);
9851: 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);
9852: return(1);
9853: }
9854: }else if (Typevar[k1] ==2){
9855: k3=Tposprod[k1];
9856: k4=Tposprod[k2];
9857: 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])) ){
9858: 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]]);
9859: 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);
9860: return(1);
9861: }
9862: }
1.227 brouard 9863: }
9864: }
1.225 brouard 9865: }
9866: printf("ncoveff=%d, nqfveff=%d, ntveff=%d, nqtveff=%d, cptcovn=%d\n",ncoveff,nqfveff,ntveff,nqtveff,cptcovn);
9867: fprintf(ficlog,"ncoveff=%d, nqfveff=%d, ntveff=%d, nqtveff=%d, cptcovn=%d\n",ncoveff,nqfveff,ntveff,nqtveff,cptcovn);
1.234 brouard 9868: printf("ncovf=%d, ncovv=%d, ncova=%d, nsd=%d, nsq=%d\n",ncovf,ncovv,ncova,nsd,nsq);
9869: fprintf(ficlog,"ncovf=%d, ncovv=%d, ncova=%d, nsd=%d, nsq=%d\n",ncovf,ncovv,ncova,nsd, nsq);
1.137 brouard 9870: return (0); /* with covar[new additional covariate if product] and Tage if age */
1.164 brouard 9871: /*endread:*/
1.225 brouard 9872: printf("Exiting decodemodel: ");
9873: return (1);
1.136 brouard 9874: }
9875:
1.169 brouard 9876: int calandcheckages(int imx, int maxwav, double *agemin, double *agemax, int *nberr, int *nbwarn )
1.248 brouard 9877: {/* Check ages at death */
1.136 brouard 9878: int i, m;
1.218 brouard 9879: int firstone=0;
9880:
1.136 brouard 9881: for (i=1; i<=imx; i++) {
9882: for(m=2; (m<= maxwav); m++) {
9883: if (((int)mint[m][i]== 99) && (s[m][i] <= nlstate)){
9884: anint[m][i]=9999;
1.216 brouard 9885: if (s[m][i] != -2) /* Keeping initial status of unknown vital status */
9886: s[m][i]=-1;
1.136 brouard 9887: }
9888: if((int)moisdc[i]==99 && (int)andc[i]==9999 && s[m][i]>nlstate){
1.260 brouard 9889: *nberr = *nberr + 1;
1.218 brouard 9890: if(firstone == 0){
9891: firstone=1;
1.260 brouard 9892: 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 9893: }
1.262 brouard 9894: 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 9895: s[m][i]=-1; /* Droping the death status */
1.136 brouard 9896: }
9897: if((int)moisdc[i]==99 && (int)andc[i]!=9999 && s[m][i]>nlstate){
1.169 brouard 9898: (*nberr)++;
1.259 brouard 9899: 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 9900: 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 9901: s[m][i]=-2; /* We prefer to skip it (and to skip it in version 0.8a1 too */
1.136 brouard 9902: }
9903: }
9904: }
9905:
9906: for (i=1; i<=imx; i++) {
9907: agedc[i]=(moisdc[i]/12.+andc[i])-(moisnais[i]/12.+annais[i]);
9908: for(m=firstpass; (m<= lastpass); m++){
1.214 brouard 9909: 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 9910: if (s[m][i] >= nlstate+1) {
1.169 brouard 9911: if(agedc[i]>0){
9912: if((int)moisdc[i]!=99 && (int)andc[i]!=9999){
1.136 brouard 9913: agev[m][i]=agedc[i];
1.214 brouard 9914: /*if(moisdc[i]==99 && andc[i]==9999) s[m][i]=-1;*/
1.169 brouard 9915: }else {
1.136 brouard 9916: if ((int)andc[i]!=9999){
9917: nbwarn++;
9918: printf("Warning negative age at death: %ld line:%d\n",num[i],i);
9919: fprintf(ficlog,"Warning negative age at death: %ld line:%d\n",num[i],i);
9920: agev[m][i]=-1;
9921: }
9922: }
1.169 brouard 9923: } /* agedc > 0 */
1.214 brouard 9924: } /* end if */
1.136 brouard 9925: else if(s[m][i] !=9){ /* Standard case, age in fractional
9926: years but with the precision of a month */
9927: agev[m][i]=(mint[m][i]/12.+1./24.+anint[m][i])-(moisnais[i]/12.+1./24.+annais[i]);
9928: if((int)mint[m][i]==99 || (int)anint[m][i]==9999)
9929: agev[m][i]=1;
9930: else if(agev[m][i] < *agemin){
9931: *agemin=agev[m][i];
9932: printf(" Min anint[%d][%d]=%.2f annais[%d]=%.2f, agemin=%.2f\n",m,i,anint[m][i], i,annais[i], *agemin);
9933: }
9934: else if(agev[m][i] >*agemax){
9935: *agemax=agev[m][i];
1.156 brouard 9936: /* printf(" Max anint[%d][%d]=%.0f annais[%d]=%.0f, agemax=%.2f\n",m,i,anint[m][i], i,annais[i], *agemax);*/
1.136 brouard 9937: }
9938: /*agev[m][i]=anint[m][i]-annais[i];*/
9939: /* agev[m][i] = age[i]+2*m;*/
1.214 brouard 9940: } /* en if 9*/
1.136 brouard 9941: else { /* =9 */
1.214 brouard 9942: /* printf("Debug num[%d]=%ld s[%d][%d]=%d\n",i,num[i], m,i, s[m][i]); */
1.136 brouard 9943: agev[m][i]=1;
9944: s[m][i]=-1;
9945: }
9946: }
1.214 brouard 9947: else if(s[m][i]==0) /*= 0 Unknown */
1.136 brouard 9948: agev[m][i]=1;
1.214 brouard 9949: else{
9950: printf("Warning, num[%d]=%ld, s[%d][%d]=%d\n", i, num[i], m, i,s[m][i]);
9951: fprintf(ficlog, "Warning, num[%d]=%ld, s[%d][%d]=%d\n", i, num[i], m, i,s[m][i]);
9952: agev[m][i]=0;
9953: }
9954: } /* End for lastpass */
9955: }
1.136 brouard 9956:
9957: for (i=1; i<=imx; i++) {
9958: for(m=firstpass; (m<=lastpass); m++){
9959: if (s[m][i] > (nlstate+ndeath)) {
1.169 brouard 9960: (*nberr)++;
1.136 brouard 9961: 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);
9962: 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);
9963: return 1;
9964: }
9965: }
9966: }
9967:
9968: /*for (i=1; i<=imx; i++){
9969: for (m=firstpass; (m<lastpass); m++){
9970: printf("%ld %d %.lf %d %d\n", num[i],(covar[1][i]),agev[m][i],s[m][i],s[m+1][i]);
9971: }
9972:
9973: }*/
9974:
9975:
1.139 brouard 9976: printf("Total number of individuals= %d, Agemin = %.2f, Agemax= %.2f\n\n", imx, *agemin, *agemax);
9977: fprintf(ficlog,"Total number of individuals= %d, Agemin = %.2f, Agemax= %.2f\n\n", imx, *agemin, *agemax);
1.136 brouard 9978:
9979: return (0);
1.164 brouard 9980: /* endread:*/
1.136 brouard 9981: printf("Exiting calandcheckages: ");
9982: return (1);
9983: }
9984:
1.172 brouard 9985: #if defined(_MSC_VER)
9986: /*printf("Visual C++ compiler: %s \n;", _MSC_FULL_VER);*/
9987: /*fprintf(ficlog, "Visual C++ compiler: %s \n;", _MSC_FULL_VER);*/
9988: //#include "stdafx.h"
9989: //#include <stdio.h>
9990: //#include <tchar.h>
9991: //#include <windows.h>
9992: //#include <iostream>
9993: typedef BOOL(WINAPI *LPFN_ISWOW64PROCESS) (HANDLE, PBOOL);
9994:
9995: LPFN_ISWOW64PROCESS fnIsWow64Process;
9996:
9997: BOOL IsWow64()
9998: {
9999: BOOL bIsWow64 = FALSE;
10000:
10001: //typedef BOOL (APIENTRY *LPFN_ISWOW64PROCESS)
10002: // (HANDLE, PBOOL);
10003:
10004: //LPFN_ISWOW64PROCESS fnIsWow64Process;
10005:
10006: HMODULE module = GetModuleHandle(_T("kernel32"));
10007: const char funcName[] = "IsWow64Process";
10008: fnIsWow64Process = (LPFN_ISWOW64PROCESS)
10009: GetProcAddress(module, funcName);
10010:
10011: if (NULL != fnIsWow64Process)
10012: {
10013: if (!fnIsWow64Process(GetCurrentProcess(),
10014: &bIsWow64))
10015: //throw std::exception("Unknown error");
10016: printf("Unknown error\n");
10017: }
10018: return bIsWow64 != FALSE;
10019: }
10020: #endif
1.177 brouard 10021:
1.191 brouard 10022: void syscompilerinfo(int logged)
1.167 brouard 10023: {
10024: /* #include "syscompilerinfo.h"*/
1.185 brouard 10025: /* command line Intel compiler 32bit windows, XP compatible:*/
10026: /* /GS /W3 /Gy
10027: /Zc:wchar_t /Zi /O2 /Fd"Release\vc120.pdb" /D "WIN32" /D "NDEBUG" /D
10028: "_CONSOLE" /D "_LIB" /D "_USING_V110_SDK71_" /D "_UNICODE" /D
10029: "UNICODE" /Qipo /Zc:forScope /Gd /Oi /MT /Fa"Release\" /EHsc /nologo
1.186 brouard 10030: /Fo"Release\" /Qprof-dir "Release\" /Fp"Release\IMaCh.pch"
10031: */
10032: /* 64 bits */
1.185 brouard 10033: /*
10034: /GS /W3 /Gy
10035: /Zc:wchar_t /Zi /O2 /Fd"x64\Release\vc120.pdb" /D "WIN32" /D "NDEBUG"
10036: /D "_CONSOLE" /D "_LIB" /D "_UNICODE" /D "UNICODE" /Qipo /Zc:forScope
10037: /Oi /MD /Fa"x64\Release\" /EHsc /nologo /Fo"x64\Release\" /Qprof-dir
10038: "x64\Release\" /Fp"x64\Release\IMaCh.pch" */
10039: /* Optimization are useless and O3 is slower than O2 */
10040: /*
10041: /GS /W3 /Gy /Zc:wchar_t /Zi /O3 /Fd"x64\Release\vc120.pdb" /D "WIN32"
10042: /D "NDEBUG" /D "_CONSOLE" /D "_LIB" /D "_UNICODE" /D "UNICODE" /Qipo
10043: /Zc:forScope /Oi /MD /Fa"x64\Release\" /EHsc /nologo /Qparallel
10044: /Fo"x64\Release\" /Qprof-dir "x64\Release\" /Fp"x64\Release\IMaCh.pch"
10045: */
1.186 brouard 10046: /* Link is */ /* /OUT:"visual studio
1.185 brouard 10047: 2013\Projects\IMaCh\Release\IMaCh.exe" /MANIFEST /NXCOMPAT
10048: /PDB:"visual studio
10049: 2013\Projects\IMaCh\Release\IMaCh.pdb" /DYNAMICBASE
10050: "kernel32.lib" "user32.lib" "gdi32.lib" "winspool.lib"
10051: "comdlg32.lib" "advapi32.lib" "shell32.lib" "ole32.lib"
10052: "oleaut32.lib" "uuid.lib" "odbc32.lib" "odbccp32.lib"
10053: /MACHINE:X86 /OPT:REF /SAFESEH /INCREMENTAL:NO
10054: /SUBSYSTEM:CONSOLE",5.01" /MANIFESTUAC:"level='asInvoker'
10055: uiAccess='false'"
10056: /ManifestFile:"Release\IMaCh.exe.intermediate.manifest" /OPT:ICF
10057: /NOLOGO /TLBID:1
10058: */
1.177 brouard 10059: #if defined __INTEL_COMPILER
1.178 brouard 10060: #if defined(__GNUC__)
10061: struct utsname sysInfo; /* For Intel on Linux and OS/X */
10062: #endif
1.177 brouard 10063: #elif defined(__GNUC__)
1.179 brouard 10064: #ifndef __APPLE__
1.174 brouard 10065: #include <gnu/libc-version.h> /* Only on gnu */
1.179 brouard 10066: #endif
1.177 brouard 10067: struct utsname sysInfo;
1.178 brouard 10068: int cross = CROSS;
10069: if (cross){
10070: printf("Cross-");
1.191 brouard 10071: if(logged) fprintf(ficlog, "Cross-");
1.178 brouard 10072: }
1.174 brouard 10073: #endif
10074:
1.171 brouard 10075: #include <stdint.h>
1.178 brouard 10076:
1.191 brouard 10077: printf("Compiled with:");if(logged)fprintf(ficlog,"Compiled with:");
1.169 brouard 10078: #if defined(__clang__)
1.191 brouard 10079: printf(" Clang/LLVM");if(logged)fprintf(ficlog," Clang/LLVM"); /* Clang/LLVM. ---------------------------------------------- */
1.169 brouard 10080: #endif
10081: #if defined(__ICC) || defined(__INTEL_COMPILER)
1.191 brouard 10082: printf(" Intel ICC/ICPC");if(logged)fprintf(ficlog," Intel ICC/ICPC");/* Intel ICC/ICPC. ------------------------------------------ */
1.169 brouard 10083: #endif
10084: #if defined(__GNUC__) || defined(__GNUG__)
1.191 brouard 10085: printf(" GNU GCC/G++");if(logged)fprintf(ficlog," GNU GCC/G++");/* GNU GCC/G++. --------------------------------------------- */
1.169 brouard 10086: #endif
10087: #if defined(__HP_cc) || defined(__HP_aCC)
1.191 brouard 10088: printf(" Hewlett-Packard C/aC++");if(logged)fprintf(fcilog," Hewlett-Packard C/aC++"); /* Hewlett-Packard C/aC++. ---------------------------------- */
1.169 brouard 10089: #endif
10090: #if defined(__IBMC__) || defined(__IBMCPP__)
1.191 brouard 10091: printf(" IBM XL C/C++"); if(logged) fprintf(ficlog," IBM XL C/C++");/* IBM XL C/C++. -------------------------------------------- */
1.169 brouard 10092: #endif
10093: #if defined(_MSC_VER)
1.191 brouard 10094: printf(" Microsoft Visual Studio");if(logged)fprintf(ficlog," Microsoft Visual Studio");/* Microsoft Visual Studio. --------------------------------- */
1.169 brouard 10095: #endif
10096: #if defined(__PGI)
1.191 brouard 10097: printf(" Portland Group PGCC/PGCPP");if(logged) fprintf(ficlog," Portland Group PGCC/PGCPP");/* Portland Group PGCC/PGCPP. ------------------------------- */
1.169 brouard 10098: #endif
10099: #if defined(__SUNPRO_C) || defined(__SUNPRO_CC)
1.191 brouard 10100: printf(" Oracle Solaris Studio");if(logged)fprintf(ficlog," Oracle Solaris Studio\n");/* Oracle Solaris Studio. ----------------------------------- */
1.167 brouard 10101: #endif
1.191 brouard 10102: printf(" for "); if (logged) fprintf(ficlog, " for ");
1.169 brouard 10103:
1.167 brouard 10104: // http://stackoverflow.com/questions/4605842/how-to-identify-platform-compiler-from-preprocessor-macros
10105: #ifdef _WIN32 // note the underscore: without it, it's not msdn official!
10106: // Windows (x64 and x86)
1.191 brouard 10107: printf("Windows (x64 and x86) ");if(logged) fprintf(ficlog,"Windows (x64 and x86) ");
1.167 brouard 10108: #elif __unix__ // all unices, not all compilers
10109: // Unix
1.191 brouard 10110: printf("Unix ");if(logged) fprintf(ficlog,"Unix ");
1.167 brouard 10111: #elif __linux__
10112: // linux
1.191 brouard 10113: printf("linux ");if(logged) fprintf(ficlog,"linux ");
1.167 brouard 10114: #elif __APPLE__
1.174 brouard 10115: // Mac OS, not sure if this is covered by __posix__ and/or __unix__ though..
1.191 brouard 10116: printf("Mac OS ");if(logged) fprintf(ficlog,"Mac OS ");
1.167 brouard 10117: #endif
10118:
10119: /* __MINGW32__ */
10120: /* __CYGWIN__ */
10121: /* __MINGW64__ */
10122: // http://msdn.microsoft.com/en-us/library/b0084kay.aspx
10123: /* _MSC_VER //the Visual C++ compiler is 17.00.51106.1, the _MSC_VER macro evaluates to 1700. Type cl /? */
10124: /* _MSC_FULL_VER //the Visual C++ compiler is 15.00.20706.01, the _MSC_FULL_VER macro evaluates to 150020706 */
10125: /* _WIN64 // Defined for applications for Win64. */
10126: /* _M_X64 // Defined for compilations that target x64 processors. */
10127: /* _DEBUG // Defined when you compile with /LDd, /MDd, and /MTd. */
1.171 brouard 10128:
1.167 brouard 10129: #if UINTPTR_MAX == 0xffffffff
1.191 brouard 10130: printf(" 32-bit"); if(logged) fprintf(ficlog," 32-bit");/* 32-bit */
1.167 brouard 10131: #elif UINTPTR_MAX == 0xffffffffffffffff
1.191 brouard 10132: printf(" 64-bit"); if(logged) fprintf(ficlog," 64-bit");/* 64-bit */
1.167 brouard 10133: #else
1.191 brouard 10134: printf(" wtf-bit"); if(logged) fprintf(ficlog," wtf-bit");/* wtf */
1.167 brouard 10135: #endif
10136:
1.169 brouard 10137: #if defined(__GNUC__)
10138: # if defined(__GNUC_PATCHLEVEL__)
10139: # define __GNUC_VERSION__ (__GNUC__ * 10000 \
10140: + __GNUC_MINOR__ * 100 \
10141: + __GNUC_PATCHLEVEL__)
10142: # else
10143: # define __GNUC_VERSION__ (__GNUC__ * 10000 \
10144: + __GNUC_MINOR__ * 100)
10145: # endif
1.174 brouard 10146: printf(" using GNU C version %d.\n", __GNUC_VERSION__);
1.191 brouard 10147: if(logged) fprintf(ficlog, " using GNU C version %d.\n", __GNUC_VERSION__);
1.176 brouard 10148:
10149: if (uname(&sysInfo) != -1) {
10150: printf("Running on: %s %s %s %s %s\n",sysInfo.sysname, sysInfo.nodename, sysInfo.release, sysInfo.version, sysInfo.machine);
1.191 brouard 10151: 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 10152: }
10153: else
10154: perror("uname() error");
1.179 brouard 10155: //#ifndef __INTEL_COMPILER
10156: #if !defined (__INTEL_COMPILER) && !defined(__APPLE__)
1.174 brouard 10157: printf("GNU libc version: %s\n", gnu_get_libc_version());
1.191 brouard 10158: if(logged) fprintf(ficlog,"GNU libc version: %s\n", gnu_get_libc_version());
1.177 brouard 10159: #endif
1.169 brouard 10160: #endif
1.172 brouard 10161:
10162: // void main()
10163: // {
1.169 brouard 10164: #if defined(_MSC_VER)
1.174 brouard 10165: if (IsWow64()){
1.191 brouard 10166: printf("\nThe program (probably compiled for 32bit) is running under WOW64 (64bit) emulation.\n");
10167: if (logged) fprintf(ficlog, "\nThe program (probably compiled for 32bit) is running under WOW64 (64bit) emulation.\n");
1.174 brouard 10168: }
10169: else{
1.191 brouard 10170: printf("\nThe program is not running under WOW64 (i.e probably on a 64bit Windows).\n");
10171: if (logged) fprintf(ficlog, "\nThe programm is not running under WOW64 (i.e probably on a 64bit Windows).\n");
1.174 brouard 10172: }
1.172 brouard 10173: // printf("\nPress Enter to continue...");
10174: // getchar();
10175: // }
10176:
1.169 brouard 10177: #endif
10178:
1.167 brouard 10179:
1.219 brouard 10180: }
1.136 brouard 10181:
1.219 brouard 10182: int prevalence_limit(double *p, double **prlim, double ageminpar, double agemaxpar, double ftolpl, int *ncvyearp){
1.180 brouard 10183: /*--------------- Prevalence limit (period or stable prevalence) --------------*/
1.235 brouard 10184: int i, j, k, i1, k4=0, nres=0 ;
1.202 brouard 10185: /* double ftolpl = 1.e-10; */
1.180 brouard 10186: double age, agebase, agelim;
1.203 brouard 10187: double tot;
1.180 brouard 10188:
1.202 brouard 10189: strcpy(filerespl,"PL_");
10190: strcat(filerespl,fileresu);
10191: if((ficrespl=fopen(filerespl,"w"))==NULL) {
10192: printf("Problem with period (stable) prevalence resultfile: %s\n", filerespl);return 1;
10193: fprintf(ficlog,"Problem with period (stable) prevalence resultfile: %s\n", filerespl);return 1;
10194: }
1.227 brouard 10195: printf("\nComputing period (stable) prevalence: result on file '%s' \n", filerespl);
10196: fprintf(ficlog,"\nComputing period (stable) prevalence: result on file '%s' \n", filerespl);
1.202 brouard 10197: pstamp(ficrespl);
1.203 brouard 10198: fprintf(ficrespl,"# Period (stable) prevalence. Precision given by ftolpl=%g \n", ftolpl);
1.202 brouard 10199: fprintf(ficrespl,"#Age ");
10200: for(i=1; i<=nlstate;i++) fprintf(ficrespl,"%d-%d ",i,i);
10201: fprintf(ficrespl,"\n");
1.180 brouard 10202:
1.219 brouard 10203: /* prlim=matrix(1,nlstate,1,nlstate);*/ /* back in main */
1.180 brouard 10204:
1.219 brouard 10205: agebase=ageminpar;
10206: agelim=agemaxpar;
1.180 brouard 10207:
1.227 brouard 10208: /* i1=pow(2,ncoveff); */
1.234 brouard 10209: i1=pow(2,cptcoveff); /* Number of combination of dummy covariates */
1.219 brouard 10210: if (cptcovn < 1){i1=1;}
1.180 brouard 10211:
1.238 brouard 10212: for(k=1; k<=i1;k++){ /* For each combination k of dummy covariates in the model */
10213: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 10214: if(i1 != 1 && TKresult[nres]!= k)
1.238 brouard 10215: continue;
1.235 brouard 10216:
1.238 brouard 10217: /* for(cptcov=1,k=0;cptcov<=i1;cptcov++){ */
10218: /* for(cptcov=1,k=0;cptcov<=1;cptcov++){ */
10219: //for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){
10220: /* k=k+1; */
10221: /* to clean */
10222: //printf("cptcov=%d cptcod=%d codtab=%d\n",cptcov, cptcod,codtabm(cptcod,cptcov));
10223: fprintf(ficrespl,"#******");
10224: printf("#******");
10225: fprintf(ficlog,"#******");
10226: for(j=1;j<=cptcoveff ;j++) {/* all covariates */
10227: fprintf(ficrespl," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]); /* Here problem for varying dummy*/
10228: printf(" V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10229: fprintf(ficlog," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10230: }
10231: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
10232: printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
10233: fprintf(ficrespl," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
10234: fprintf(ficlog," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
10235: }
10236: fprintf(ficrespl,"******\n");
10237: printf("******\n");
10238: fprintf(ficlog,"******\n");
10239: if(invalidvarcomb[k]){
10240: printf("\nCombination (%d) ignored because no case \n",k);
10241: fprintf(ficrespl,"#Combination (%d) ignored because no case \n",k);
10242: fprintf(ficlog,"\nCombination (%d) ignored because no case \n",k);
10243: continue;
10244: }
1.219 brouard 10245:
1.238 brouard 10246: fprintf(ficrespl,"#Age ");
10247: for(j=1;j<=cptcoveff;j++) {
10248: fprintf(ficrespl,"V%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10249: }
10250: for(i=1; i<=nlstate;i++) fprintf(ficrespl," %d-%d ",i,i);
10251: fprintf(ficrespl,"Total Years_to_converge\n");
1.227 brouard 10252:
1.238 brouard 10253: for (age=agebase; age<=agelim; age++){
10254: /* for (age=agebase; age<=agebase; age++){ */
10255: prevalim(prlim, nlstate, p, age, oldm, savm, ftolpl, ncvyearp, k, nres);
10256: fprintf(ficrespl,"%.0f ",age );
10257: for(j=1;j<=cptcoveff;j++)
10258: fprintf(ficrespl,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10259: tot=0.;
10260: for(i=1; i<=nlstate;i++){
10261: tot += prlim[i][i];
10262: fprintf(ficrespl," %.5f", prlim[i][i]);
10263: }
10264: fprintf(ficrespl," %.3f %d\n", tot, *ncvyearp);
10265: } /* Age */
10266: /* was end of cptcod */
10267: } /* cptcov */
10268: } /* nres */
1.219 brouard 10269: return 0;
1.180 brouard 10270: }
10271:
1.218 brouard 10272: 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){
10273: /*--------------- Back Prevalence limit (period or stable prevalence) --------------*/
10274:
10275: /* Computes the back prevalence limit for any combination of covariate values
10276: * at any age between ageminpar and agemaxpar
10277: */
1.235 brouard 10278: int i, j, k, i1, nres=0 ;
1.217 brouard 10279: /* double ftolpl = 1.e-10; */
10280: double age, agebase, agelim;
10281: double tot;
1.218 brouard 10282: /* double ***mobaverage; */
10283: /* double **dnewm, **doldm, **dsavm; /\* for use *\/ */
1.217 brouard 10284:
10285: strcpy(fileresplb,"PLB_");
10286: strcat(fileresplb,fileresu);
10287: if((ficresplb=fopen(fileresplb,"w"))==NULL) {
10288: printf("Problem with period (stable) back prevalence resultfile: %s\n", fileresplb);return 1;
10289: fprintf(ficlog,"Problem with period (stable) back prevalence resultfile: %s\n", fileresplb);return 1;
10290: }
10291: printf("Computing period (stable) back prevalence: result on file '%s' \n", fileresplb);
10292: fprintf(ficlog,"Computing period (stable) back prevalence: result on file '%s' \n", fileresplb);
10293: pstamp(ficresplb);
10294: fprintf(ficresplb,"# Period (stable) back prevalence. Precision given by ftolpl=%g \n", ftolpl);
10295: fprintf(ficresplb,"#Age ");
10296: for(i=1; i<=nlstate;i++) fprintf(ficresplb,"%d-%d ",i,i);
10297: fprintf(ficresplb,"\n");
10298:
1.218 brouard 10299:
10300: /* prlim=matrix(1,nlstate,1,nlstate);*/ /* back in main */
10301:
10302: agebase=ageminpar;
10303: agelim=agemaxpar;
10304:
10305:
1.227 brouard 10306: i1=pow(2,cptcoveff);
1.218 brouard 10307: if (cptcovn < 1){i1=1;}
1.227 brouard 10308:
1.238 brouard 10309: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
10310: for(k=1; k<=i1;k++){ /* For any combination of dummy covariates, fixed and varying */
1.253 brouard 10311: if(i1 != 1 && TKresult[nres]!= k)
1.238 brouard 10312: continue;
10313: //printf("cptcov=%d cptcod=%d codtab=%d\n",cptcov, cptcod,codtabm(cptcod,cptcov));
10314: fprintf(ficresplb,"#******");
10315: printf("#******");
10316: fprintf(ficlog,"#******");
10317: for(j=1;j<=cptcoveff ;j++) {/* all covariates */
10318: fprintf(ficresplb," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10319: printf(" V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10320: fprintf(ficlog," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10321: }
10322: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
10323: printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
10324: fprintf(ficresplb," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
10325: fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
10326: }
10327: fprintf(ficresplb,"******\n");
10328: printf("******\n");
10329: fprintf(ficlog,"******\n");
10330: if(invalidvarcomb[k]){
10331: printf("\nCombination (%d) ignored because no cases \n",k);
10332: fprintf(ficresplb,"#Combination (%d) ignored because no cases \n",k);
10333: fprintf(ficlog,"\nCombination (%d) ignored because no cases \n",k);
10334: continue;
10335: }
1.218 brouard 10336:
1.238 brouard 10337: fprintf(ficresplb,"#Age ");
10338: for(j=1;j<=cptcoveff;j++) {
10339: fprintf(ficresplb,"V%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10340: }
10341: for(i=1; i<=nlstate;i++) fprintf(ficresplb," %d-%d ",i,i);
10342: fprintf(ficresplb,"Total Years_to_converge\n");
1.218 brouard 10343:
10344:
1.238 brouard 10345: for (age=agebase; age<=agelim; age++){
10346: /* for (age=agebase; age<=agebase; age++){ */
10347: if(mobilavproj > 0){
10348: /* bprevalim(bprlim, mobaverage, nlstate, p, age, ageminpar, agemaxpar, oldm, savm, doldm, dsavm, ftolpl, ncvyearp, k); */
10349: /* bprevalim(bprlim, mobaverage, nlstate, p, age, oldm, savm, dnewm, doldm, dsavm, ftolpl, ncvyearp, k); */
1.242 brouard 10350: bprevalim(bprlim, mobaverage, nlstate, p, age, ftolpl, ncvyearp, k, nres);
1.238 brouard 10351: }else if (mobilavproj == 0){
10352: 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);
10353: 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);
10354: exit(1);
10355: }else{
10356: /* bprevalim(bprlim, probs, nlstate, p, age, oldm, savm, dnewm, doldm, dsavm, ftolpl, ncvyearp, k); */
1.242 brouard 10357: bprevalim(bprlim, probs, nlstate, p, age, ftolpl, ncvyearp, k,nres);
1.266 brouard 10358: /* printf("TOTOT\n"); */
10359: /* exit(1); */
1.238 brouard 10360: }
10361: fprintf(ficresplb,"%.0f ",age );
10362: for(j=1;j<=cptcoveff;j++)
10363: fprintf(ficresplb,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10364: tot=0.;
10365: for(i=1; i<=nlstate;i++){
10366: tot += bprlim[i][i];
10367: fprintf(ficresplb," %.5f", bprlim[i][i]);
10368: }
10369: fprintf(ficresplb," %.3f %d\n", tot, *ncvyearp);
10370: } /* Age */
10371: /* was end of cptcod */
1.255 brouard 10372: /*fprintf(ficresplb,"\n");*/ /* Seems to be necessary for gnuplot only if two result lines and no covariate. */
1.238 brouard 10373: } /* end of any combination */
10374: } /* end of nres */
1.218 brouard 10375: /* hBijx(p, bage, fage); */
10376: /* fclose(ficrespijb); */
10377:
10378: return 0;
1.217 brouard 10379: }
1.218 brouard 10380:
1.180 brouard 10381: int hPijx(double *p, int bage, int fage){
10382: /*------------- h Pij x at various ages ------------*/
10383:
10384: int stepsize;
10385: int agelim;
10386: int hstepm;
10387: int nhstepm;
1.235 brouard 10388: int h, i, i1, j, k, k4, nres=0;
1.180 brouard 10389:
10390: double agedeb;
10391: double ***p3mat;
10392:
1.201 brouard 10393: strcpy(filerespij,"PIJ_"); strcat(filerespij,fileresu);
1.180 brouard 10394: if((ficrespij=fopen(filerespij,"w"))==NULL) {
10395: printf("Problem with Pij resultfile: %s\n", filerespij); return 1;
10396: fprintf(ficlog,"Problem with Pij resultfile: %s\n", filerespij); return 1;
10397: }
10398: printf("Computing pij: result on file '%s' \n", filerespij);
10399: fprintf(ficlog,"Computing pij: result on file '%s' \n", filerespij);
10400:
10401: stepsize=(int) (stepm+YEARM-1)/YEARM;
10402: /*if (stepm<=24) stepsize=2;*/
10403:
10404: agelim=AGESUP;
10405: hstepm=stepsize*YEARM; /* Every year of age */
10406: hstepm=hstepm/stepm; /* Typically 2 years, = 2/6 months = 4 */
1.218 brouard 10407:
1.180 brouard 10408: /* hstepm=1; aff par mois*/
10409: pstamp(ficrespij);
10410: fprintf(ficrespij,"#****** h Pij x Probability to be in state j at age x+h being in i at x ");
1.227 brouard 10411: i1= pow(2,cptcoveff);
1.218 brouard 10412: /* for(cptcov=1,k=0;cptcov<=i1;cptcov++){ */
10413: /* /\*for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){*\/ */
10414: /* k=k+1; */
1.235 brouard 10415: for(nres=1; nres <= nresult; nres++) /* For each resultline */
10416: for(k=1; k<=i1;k++){
1.253 brouard 10417: if(i1 != 1 && TKresult[nres]!= k)
1.235 brouard 10418: continue;
1.183 brouard 10419: fprintf(ficrespij,"\n#****** ");
1.227 brouard 10420: for(j=1;j<=cptcoveff;j++)
1.198 brouard 10421: fprintf(ficrespij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
1.235 brouard 10422: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
10423: printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
10424: fprintf(ficrespij," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
10425: }
1.183 brouard 10426: fprintf(ficrespij,"******\n");
10427:
10428: for (agedeb=fage; agedeb>=bage; agedeb--){ /* If stepm=6 months */
10429: nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
10430: nhstepm = nhstepm/hstepm; /* Typically 40/4=10 */
10431:
10432: /* nhstepm=nhstepm*YEARM; aff par mois*/
1.180 brouard 10433:
1.183 brouard 10434: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
10435: oldm=oldms;savm=savms;
1.235 brouard 10436: hpxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k, nres);
1.183 brouard 10437: fprintf(ficrespij,"# Cov Agex agex+h hpijx with i,j=");
10438: for(i=1; i<=nlstate;i++)
10439: for(j=1; j<=nlstate+ndeath;j++)
10440: fprintf(ficrespij," %1d-%1d",i,j);
10441: fprintf(ficrespij,"\n");
10442: for (h=0; h<=nhstepm; h++){
10443: /*agedebphstep = agedeb + h*hstepm/YEARM*stepm;*/
10444: fprintf(ficrespij,"%d %3.f %3.f",k, agedeb, agedeb + h*hstepm/YEARM*stepm );
1.180 brouard 10445: for(i=1; i<=nlstate;i++)
10446: for(j=1; j<=nlstate+ndeath;j++)
1.183 brouard 10447: fprintf(ficrespij," %.5f", p3mat[i][j][h]);
1.180 brouard 10448: fprintf(ficrespij,"\n");
10449: }
1.183 brouard 10450: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
10451: fprintf(ficrespij,"\n");
10452: }
1.180 brouard 10453: /*}*/
10454: }
1.218 brouard 10455: return 0;
1.180 brouard 10456: }
1.218 brouard 10457:
10458: int hBijx(double *p, int bage, int fage, double ***prevacurrent){
1.217 brouard 10459: /*------------- h Bij x at various ages ------------*/
10460:
10461: int stepsize;
1.218 brouard 10462: /* int agelim; */
10463: int ageminl;
1.217 brouard 10464: int hstepm;
10465: int nhstepm;
1.238 brouard 10466: int h, i, i1, j, k, nres;
1.218 brouard 10467:
1.217 brouard 10468: double agedeb;
10469: double ***p3mat;
1.218 brouard 10470:
10471: strcpy(filerespijb,"PIJB_"); strcat(filerespijb,fileresu);
10472: if((ficrespijb=fopen(filerespijb,"w"))==NULL) {
10473: printf("Problem with Pij back resultfile: %s\n", filerespijb); return 1;
10474: fprintf(ficlog,"Problem with Pij back resultfile: %s\n", filerespijb); return 1;
10475: }
10476: printf("Computing pij back: result on file '%s' \n", filerespijb);
10477: fprintf(ficlog,"Computing pij back: result on file '%s' \n", filerespijb);
10478:
10479: stepsize=(int) (stepm+YEARM-1)/YEARM;
10480: /*if (stepm<=24) stepsize=2;*/
1.217 brouard 10481:
1.218 brouard 10482: /* agelim=AGESUP; */
10483: ageminl=30;
10484: hstepm=stepsize*YEARM; /* Every year of age */
10485: hstepm=hstepm/stepm; /* Typically 2 years, = 2/6 months = 4 */
10486:
10487: /* hstepm=1; aff par mois*/
10488: pstamp(ficrespijb);
1.255 brouard 10489: 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 10490: i1= pow(2,cptcoveff);
1.218 brouard 10491: /* for(cptcov=1,k=0;cptcov<=i1;cptcov++){ */
10492: /* /\*for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){*\/ */
10493: /* k=k+1; */
1.238 brouard 10494: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
10495: for(k=1; k<=i1;k++){ /* For any combination of dummy covariates, fixed and varying */
1.253 brouard 10496: if(i1 != 1 && TKresult[nres]!= k)
1.238 brouard 10497: continue;
10498: fprintf(ficrespijb,"\n#****** ");
10499: for(j=1;j<=cptcoveff;j++)
10500: fprintf(ficrespijb,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10501: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
10502: fprintf(ficrespijb," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
10503: }
10504: fprintf(ficrespijb,"******\n");
1.264 brouard 10505: if(invalidvarcomb[k]){ /* Is it necessary here? */
1.238 brouard 10506: fprintf(ficrespijb,"\n#Combination (%d) ignored because no cases \n",k);
10507: continue;
10508: }
10509:
10510: /* for (agedeb=fage; agedeb>=bage; agedeb--){ /\* If stepm=6 months *\/ */
10511: for (agedeb=bage; agedeb<=fage; agedeb++){ /* If stepm=6 months and estepm=24 (2 years) */
10512: /* nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); /\* Typically 20 years = 20*12/6=40 *\/ */
10513: nhstepm=(int) rint((agedeb-ageminl)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
10514: nhstepm = nhstepm/hstepm; /* Typically 40/4=10, because estepm=24 stepm=6 => hstepm=24/6=4 */
10515:
10516: /* nhstepm=nhstepm*YEARM; aff par mois*/
10517:
1.266 brouard 10518: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); /* We can't have it at an upper level because of nhstepm */
10519: /* and memory limitations if stepm is small */
10520:
1.238 brouard 10521: /* oldm=oldms;savm=savms; */
10522: /* hbxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k); */
1.267 brouard 10523: hbxij(p3mat,nhstepm,agedeb,hstepm,p,prevacurrent,nlstate,stepm, k, nres);
1.238 brouard 10524: /* hbxij(p3mat,nhstepm,agedeb,hstepm,p,prevacurrent,nlstate,stepm,oldm,savm, dnewm, doldm, dsavm, k); */
1.255 brouard 10525: fprintf(ficrespijb,"# Cov Agex agex-h hbijx with i,j=");
1.217 brouard 10526: for(i=1; i<=nlstate;i++)
10527: for(j=1; j<=nlstate+ndeath;j++)
1.238 brouard 10528: fprintf(ficrespijb," %1d-%1d",i,j);
1.217 brouard 10529: fprintf(ficrespijb,"\n");
1.238 brouard 10530: for (h=0; h<=nhstepm; h++){
10531: /*agedebphstep = agedeb + h*hstepm/YEARM*stepm;*/
10532: fprintf(ficrespijb,"%d %3.f %3.f",k, agedeb, agedeb - h*hstepm/YEARM*stepm );
10533: /* fprintf(ficrespijb,"%d %3.f %3.f",k, agedeb, agedeb + h*hstepm/YEARM*stepm ); */
10534: for(i=1; i<=nlstate;i++)
10535: for(j=1; j<=nlstate+ndeath;j++)
10536: fprintf(ficrespijb," %.5f", p3mat[i][j][h]);
10537: fprintf(ficrespijb,"\n");
10538: }
10539: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
10540: fprintf(ficrespijb,"\n");
10541: } /* end age deb */
10542: } /* end combination */
10543: } /* end nres */
1.218 brouard 10544: return 0;
10545: } /* hBijx */
1.217 brouard 10546:
1.180 brouard 10547:
1.136 brouard 10548: /***********************************************/
10549: /**************** Main Program *****************/
10550: /***********************************************/
10551:
10552: int main(int argc, char *argv[])
10553: {
10554: #ifdef GSL
10555: const gsl_multimin_fminimizer_type *T;
10556: size_t iteri = 0, it;
10557: int rval = GSL_CONTINUE;
10558: int status = GSL_SUCCESS;
10559: double ssval;
10560: #endif
10561: int movingaverage(double ***probs, double bage,double fage, double ***mobaverage, int mobilav);
1.164 brouard 10562: int i,j, k, n=MAXN,iter=0,m,size=100, cptcod;
1.209 brouard 10563: int ncvyear=0; /* Number of years needed for the period prevalence to converge */
1.164 brouard 10564: int jj, ll, li, lj, lk;
1.136 brouard 10565: int numlinepar=0; /* Current linenumber of parameter file */
1.197 brouard 10566: int num_filled;
1.136 brouard 10567: int itimes;
10568: int NDIM=2;
10569: int vpopbased=0;
1.235 brouard 10570: int nres=0;
1.258 brouard 10571: int endishere=0;
1.136 brouard 10572:
1.164 brouard 10573: char ca[32], cb[32];
1.136 brouard 10574: /* FILE *fichtm; *//* Html File */
10575: /* FILE *ficgp;*/ /*Gnuplot File */
10576: struct stat info;
1.191 brouard 10577: double agedeb=0.;
1.194 brouard 10578:
10579: double ageminpar=AGEOVERFLOW,agemin=AGEOVERFLOW, agemaxpar=-AGEOVERFLOW, agemax=-AGEOVERFLOW;
1.219 brouard 10580: double ageminout=-AGEOVERFLOW,agemaxout=AGEOVERFLOW; /* Smaller Age range redefined after movingaverage */
1.136 brouard 10581:
1.165 brouard 10582: double fret;
1.191 brouard 10583: double dum=0.; /* Dummy variable */
1.136 brouard 10584: double ***p3mat;
1.218 brouard 10585: /* double ***mobaverage; */
1.164 brouard 10586:
10587: char line[MAXLINE];
1.197 brouard 10588: char path[MAXLINE],pathc[MAXLINE],pathcd[MAXLINE],pathtot[MAXLINE];
10589:
1.234 brouard 10590: char modeltemp[MAXLINE];
1.230 brouard 10591: char resultline[MAXLINE];
10592:
1.136 brouard 10593: char pathr[MAXLINE], pathimach[MAXLINE];
1.164 brouard 10594: char *tok, *val; /* pathtot */
1.136 brouard 10595: int firstobs=1, lastobs=10;
1.195 brouard 10596: int c, h , cpt, c2;
1.191 brouard 10597: int jl=0;
10598: int i1, j1, jk, stepsize=0;
1.194 brouard 10599: int count=0;
10600:
1.164 brouard 10601: int *tab;
1.136 brouard 10602: int mobilavproj=0 , prevfcast=0 ; /* moving average of prev, If prevfcast=1 prevalence projection */
1.217 brouard 10603: int backcast=0;
1.136 brouard 10604: int mobilav=0,popforecast=0;
1.191 brouard 10605: int hstepm=0, nhstepm=0;
1.136 brouard 10606: int agemortsup;
10607: float sumlpop=0.;
10608: double jprev1=1, mprev1=1,anprev1=2000,jprev2=1, mprev2=1,anprev2=2000;
10609: double jpyram=1, mpyram=1,anpyram=2000,jpyram1=1, mpyram1=1,anpyram1=2000;
10610:
1.191 brouard 10611: double bage=0, fage=110., age, agelim=0., agebase=0.;
1.136 brouard 10612: double ftolpl=FTOL;
10613: double **prlim;
1.217 brouard 10614: double **bprlim;
1.136 brouard 10615: double ***param; /* Matrix of parameters */
1.251 brouard 10616: double ***paramstart; /* Matrix of starting parameter values */
10617: double *p, *pstart; /* p=param[1][1] pstart is for starting values guessed by freqsummary */
1.136 brouard 10618: double **matcov; /* Matrix of covariance */
1.203 brouard 10619: double **hess; /* Hessian matrix */
1.136 brouard 10620: double ***delti3; /* Scale */
10621: double *delti; /* Scale */
10622: double ***eij, ***vareij;
10623: double **varpl; /* Variances of prevalence limits by age */
1.269 brouard 10624:
1.136 brouard 10625: double *epj, vepp;
1.164 brouard 10626:
1.136 brouard 10627: double dateprev1, dateprev2,jproj1=1,mproj1=1,anproj1=2000,jproj2=1,mproj2=1,anproj2=2000;
1.217 brouard 10628: double jback1=1,mback1=1,anback1=2000,jback2=1,mback2=1,anback2=2000;
10629:
1.136 brouard 10630: double **ximort;
1.145 brouard 10631: char *alph[]={"a","a","b","c","d","e"}, str[4]="1234";
1.136 brouard 10632: int *dcwave;
10633:
1.164 brouard 10634: char z[1]="c";
1.136 brouard 10635:
10636: /*char *strt;*/
10637: char strtend[80];
1.126 brouard 10638:
1.164 brouard 10639:
1.126 brouard 10640: /* setlocale (LC_ALL, ""); */
10641: /* bindtextdomain (PACKAGE, LOCALEDIR); */
10642: /* textdomain (PACKAGE); */
10643: /* setlocale (LC_CTYPE, ""); */
10644: /* setlocale (LC_MESSAGES, ""); */
10645:
10646: /* gettimeofday(&start_time, (struct timezone*)0); */ /* at first time */
1.157 brouard 10647: rstart_time = time(NULL);
10648: /* (void) gettimeofday(&start_time,&tzp);*/
10649: start_time = *localtime(&rstart_time);
1.126 brouard 10650: curr_time=start_time;
1.157 brouard 10651: /*tml = *localtime(&start_time.tm_sec);*/
10652: /* strcpy(strstart,asctime(&tml)); */
10653: strcpy(strstart,asctime(&start_time));
1.126 brouard 10654:
10655: /* printf("Localtime (at start)=%s",strstart); */
1.157 brouard 10656: /* tp.tm_sec = tp.tm_sec +86400; */
10657: /* tm = *localtime(&start_time.tm_sec); */
1.126 brouard 10658: /* tmg.tm_year=tmg.tm_year +dsign*dyear; */
10659: /* tmg.tm_mon=tmg.tm_mon +dsign*dmonth; */
10660: /* tmg.tm_hour=tmg.tm_hour + 1; */
1.157 brouard 10661: /* tp.tm_sec = mktime(&tmg); */
1.126 brouard 10662: /* strt=asctime(&tmg); */
10663: /* printf("Time(after) =%s",strstart); */
10664: /* (void) time (&time_value);
10665: * printf("time=%d,t-=%d\n",time_value,time_value-86400);
10666: * tm = *localtime(&time_value);
10667: * strstart=asctime(&tm);
10668: * printf("tim_value=%d,asctime=%s\n",time_value,strstart);
10669: */
10670:
10671: nberr=0; /* Number of errors and warnings */
10672: nbwarn=0;
1.184 brouard 10673: #ifdef WIN32
10674: _getcwd(pathcd, size);
10675: #else
1.126 brouard 10676: getcwd(pathcd, size);
1.184 brouard 10677: #endif
1.191 brouard 10678: syscompilerinfo(0);
1.196 brouard 10679: printf("\nIMaCh version %s, %s\n%s",version, copyright, fullversion);
1.126 brouard 10680: if(argc <=1){
10681: printf("\nEnter the parameter file name: ");
1.205 brouard 10682: if(!fgets(pathr,FILENAMELENGTH,stdin)){
10683: printf("ERROR Empty parameter file name\n");
10684: goto end;
10685: }
1.126 brouard 10686: i=strlen(pathr);
10687: if(pathr[i-1]=='\n')
10688: pathr[i-1]='\0';
1.156 brouard 10689: i=strlen(pathr);
1.205 brouard 10690: if(i >= 1 && pathr[i-1]==' ') {/* This may happen when dragging on oS/X! */
1.156 brouard 10691: pathr[i-1]='\0';
1.205 brouard 10692: }
10693: i=strlen(pathr);
10694: if( i==0 ){
10695: printf("ERROR Empty parameter file name\n");
10696: goto end;
10697: }
10698: for (tok = pathr; tok != NULL; ){
1.126 brouard 10699: printf("Pathr |%s|\n",pathr);
10700: while ((val = strsep(&tok, "\"" )) != NULL && *val == '\0');
10701: printf("val= |%s| pathr=%s\n",val,pathr);
10702: strcpy (pathtot, val);
10703: if(pathr[0] == '\0') break; /* Dirty */
10704: }
10705: }
10706: else{
10707: strcpy(pathtot,argv[1]);
10708: }
10709: /*if(getcwd(pathcd, MAXLINE)!= NULL)printf ("Error pathcd\n");*/
10710: /*cygwin_split_path(pathtot,path,optionfile);
10711: printf("pathtot=%s, path=%s, optionfile=%s\n",pathtot,path,optionfile);*/
10712: /* cutv(path,optionfile,pathtot,'\\');*/
10713:
10714: /* Split argv[0], imach program to get pathimach */
10715: printf("\nargv[0]=%s argv[1]=%s, \n",argv[0],argv[1]);
10716: split(argv[0],pathimach,optionfile,optionfilext,optionfilefiname);
10717: printf("\nargv[0]=%s pathimach=%s, \noptionfile=%s \noptionfilext=%s \noptionfilefiname=%s\n",argv[0],pathimach,optionfile,optionfilext,optionfilefiname);
10718: /* strcpy(pathimach,argv[0]); */
10719: /* Split argv[1]=pathtot, parameter file name to get path, optionfile, extension and name */
10720: split(pathtot,path,optionfile,optionfilext,optionfilefiname);
10721: printf("\npathtot=%s,\npath=%s,\noptionfile=%s \noptionfilext=%s \noptionfilefiname=%s\n",pathtot,path,optionfile,optionfilext,optionfilefiname);
1.184 brouard 10722: #ifdef WIN32
10723: _chdir(path); /* Can be a relative path */
10724: if(_getcwd(pathcd,MAXLINE) > 0) /* So pathcd is the full path */
10725: #else
1.126 brouard 10726: chdir(path); /* Can be a relative path */
1.184 brouard 10727: if (getcwd(pathcd, MAXLINE) > 0) /* So pathcd is the full path */
10728: #endif
10729: printf("Current directory %s!\n",pathcd);
1.126 brouard 10730: strcpy(command,"mkdir ");
10731: strcat(command,optionfilefiname);
10732: if((outcmd=system(command)) != 0){
1.169 brouard 10733: printf("Directory already exists (or can't create it) %s%s, err=%d\n",path,optionfilefiname,outcmd);
1.126 brouard 10734: /* fprintf(ficlog,"Problem creating directory %s%s\n",path,optionfilefiname); */
10735: /* fclose(ficlog); */
10736: /* exit(1); */
10737: }
10738: /* if((imk=mkdir(optionfilefiname))<0){ */
10739: /* perror("mkdir"); */
10740: /* } */
10741:
10742: /*-------- arguments in the command line --------*/
10743:
1.186 brouard 10744: /* Main Log file */
1.126 brouard 10745: strcat(filelog, optionfilefiname);
10746: strcat(filelog,".log"); /* */
10747: if((ficlog=fopen(filelog,"w"))==NULL) {
10748: printf("Problem with logfile %s\n",filelog);
10749: goto end;
10750: }
10751: fprintf(ficlog,"Log filename:%s\n",filelog);
1.197 brouard 10752: fprintf(ficlog,"Version %s %s",version,fullversion);
1.126 brouard 10753: fprintf(ficlog,"\nEnter the parameter file name: \n");
10754: fprintf(ficlog,"pathimach=%s\npathtot=%s\n\
10755: path=%s \n\
10756: optionfile=%s\n\
10757: optionfilext=%s\n\
1.156 brouard 10758: optionfilefiname='%s'\n",pathimach,pathtot,path,optionfile,optionfilext,optionfilefiname);
1.126 brouard 10759:
1.197 brouard 10760: syscompilerinfo(1);
1.167 brouard 10761:
1.126 brouard 10762: printf("Local time (at start):%s",strstart);
10763: fprintf(ficlog,"Local time (at start): %s",strstart);
10764: fflush(ficlog);
10765: /* (void) gettimeofday(&curr_time,&tzp); */
1.157 brouard 10766: /* printf("Elapsed time %d\n", asc_diff_time(curr_time.tm_sec-start_time.tm_sec,tmpout)); */
1.126 brouard 10767:
10768: /* */
10769: strcpy(fileres,"r");
10770: strcat(fileres, optionfilefiname);
1.201 brouard 10771: strcat(fileresu, optionfilefiname); /* Without r in front */
1.126 brouard 10772: strcat(fileres,".txt"); /* Other files have txt extension */
1.201 brouard 10773: strcat(fileresu,".txt"); /* Other files have txt extension */
1.126 brouard 10774:
1.186 brouard 10775: /* Main ---------arguments file --------*/
1.126 brouard 10776:
10777: if((ficpar=fopen(optionfile,"r"))==NULL) {
1.155 brouard 10778: printf("Problem with optionfile '%s' with errno='%s'\n",optionfile,strerror(errno));
10779: fprintf(ficlog,"Problem with optionfile '%s' with errno='%s'\n",optionfile,strerror(errno));
1.126 brouard 10780: fflush(ficlog);
1.149 brouard 10781: /* goto end; */
10782: exit(70);
1.126 brouard 10783: }
10784:
10785:
10786:
10787: strcpy(filereso,"o");
1.201 brouard 10788: strcat(filereso,fileresu);
1.126 brouard 10789: if((ficparo=fopen(filereso,"w"))==NULL) { /* opened on subdirectory */
10790: printf("Problem with Output resultfile: %s\n", filereso);
10791: fprintf(ficlog,"Problem with Output resultfile: %s\n", filereso);
10792: fflush(ficlog);
10793: goto end;
10794: }
10795:
10796: /* Reads comments: lines beginning with '#' */
10797: numlinepar=0;
1.197 brouard 10798:
10799: /* First parameter line */
10800: while(fgets(line, MAXLINE, ficpar)) {
10801: /* If line starts with a # it is a comment */
10802: if (line[0] == '#') {
10803: numlinepar++;
10804: fputs(line,stdout);
10805: fputs(line,ficparo);
10806: fputs(line,ficlog);
10807: continue;
10808: }else
10809: break;
10810: }
10811: if((num_filled=sscanf(line,"title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", \
10812: title, datafile, &lastobs, &firstpass,&lastpass)) !=EOF){
10813: if (num_filled != 5) {
10814: printf("Should be 5 parameters\n");
10815: }
1.126 brouard 10816: numlinepar++;
1.197 brouard 10817: printf("title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", title, datafile, lastobs, firstpass,lastpass);
10818: }
10819: /* Second parameter line */
10820: while(fgets(line, MAXLINE, ficpar)) {
10821: /* If line starts with a # it is a comment */
10822: if (line[0] == '#') {
10823: numlinepar++;
10824: fputs(line,stdout);
10825: fputs(line,ficparo);
10826: fputs(line,ficlog);
10827: continue;
10828: }else
10829: break;
10830: }
1.223 brouard 10831: 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", \
10832: &ftol, &stepm, &ncovcol, &nqv, &ntv, &nqtv, &nlstate, &ndeath, &maxwav, &mle, &weightopt)) !=EOF){
10833: if (num_filled != 11) {
10834: 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 10835: printf("but line=%s\n",line);
1.197 brouard 10836: }
1.223 brouard 10837: 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 10838: }
1.203 brouard 10839: /* ftolpl=6*ftol*1.e5; /\* 6.e-3 make convergences in less than 80 loops for the prevalence limit *\/ */
1.209 brouard 10840: /*ftolpl=6.e-4; *//* 6.e-3 make convergences in less than 80 loops for the prevalence limit */
1.197 brouard 10841: /* Third parameter line */
10842: while(fgets(line, MAXLINE, ficpar)) {
10843: /* If line starts with a # it is a comment */
10844: if (line[0] == '#') {
10845: numlinepar++;
10846: fputs(line,stdout);
10847: fputs(line,ficparo);
10848: fputs(line,ficlog);
10849: continue;
10850: }else
10851: break;
10852: }
1.201 brouard 10853: if((num_filled=sscanf(line,"model=1+age%[^.\n]", model)) !=EOF){
1.263 brouard 10854: if (num_filled == 0){
10855: printf("ERROR %d: Model should be at minimum 'model=1+age.' WITHOUT space:'%s'\n",num_filled, line);
10856: fprintf(ficlog,"ERROR %d: Model should be at minimum 'model=1+age.' WITHOUT space:'%s'\n",num_filled, line);
10857: model[0]='\0';
10858: goto end;
10859: } else if (num_filled != 1){
1.197 brouard 10860: printf("ERROR %d: Model should be at minimum 'model=1+age.' %s\n",num_filled, line);
10861: fprintf(ficlog,"ERROR %d: Model should be at minimum 'model=1+age.' %s\n",num_filled, line);
10862: model[0]='\0';
10863: goto end;
10864: }
10865: else{
10866: if (model[0]=='+'){
10867: for(i=1; i<=strlen(model);i++)
10868: modeltemp[i-1]=model[i];
1.201 brouard 10869: strcpy(model,modeltemp);
1.197 brouard 10870: }
10871: }
1.199 brouard 10872: /* printf(" model=1+age%s modeltemp= %s, model=%s\n",model, modeltemp, model);fflush(stdout); */
1.203 brouard 10873: printf("model=1+age+%s\n",model);fflush(stdout);
1.197 brouard 10874: }
10875: /* 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); */
10876: /* numlinepar=numlinepar+3; /\* In general *\/ */
10877: /* 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 10878: 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);
10879: 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 10880: fflush(ficlog);
1.190 brouard 10881: /* if(model[0]=='#'|| model[0]== '\0'){ */
10882: if(model[0]=='#'){
1.187 brouard 10883: printf("Error in 'model' line: model should start with 'model=1+age+' and end with '.' \n \
10884: 'model=1+age+.' or 'model=1+age+V1.' or 'model=1+age+age*age+V1+V1*age.' or \n \
10885: 'model=1+age+V1+V2.' or 'model=1+age+V1+V2+V1*V2.' etc. \n"); \
10886: if(mle != -1){
10887: printf("Fix the model line and run imach with mle=-1 to get a correct template of the parameter file.\n");
10888: exit(1);
10889: }
10890: }
1.126 brouard 10891: while((c=getc(ficpar))=='#' && c!= EOF){
10892: ungetc(c,ficpar);
10893: fgets(line, MAXLINE, ficpar);
10894: numlinepar++;
1.195 brouard 10895: if(line[1]=='q'){ /* This #q will quit imach (the answer is q) */
10896: z[0]=line[1];
10897: }
10898: /* printf("****line [1] = %c \n",line[1]); */
1.141 brouard 10899: fputs(line, stdout);
10900: //puts(line);
1.126 brouard 10901: fputs(line,ficparo);
10902: fputs(line,ficlog);
10903: }
10904: ungetc(c,ficpar);
10905:
10906:
1.145 brouard 10907: covar=matrix(0,NCOVMAX,1,n); /**< used in readdata */
1.268 brouard 10908: if(nqv>=1)coqvar=matrix(1,nqv,1,n); /**< Fixed quantitative covariate */
10909: if(nqtv>=1)cotqvar=ma3x(1,maxwav,1,nqtv,1,n); /**< Time varying quantitative covariate */
10910: if(ntv+nqtv>=1)cotvar=ma3x(1,maxwav,1,ntv+nqtv,1,n); /**< Time varying covariate (dummy and quantitative)*/
1.136 brouard 10911: cptcovn=0; /*Number of covariates, i.e. number of '+' in model statement plus one, indepently of n in Vn*/
10912: /* v1+v2+v3+v2*v4+v5*age makes cptcovn = 5
10913: v1+v2*age+v2*v3 makes cptcovn = 3
10914: */
10915: if (strlen(model)>1)
1.187 brouard 10916: 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 10917: else
1.187 brouard 10918: ncovmodel=2; /* Constant and age */
1.133 brouard 10919: nforce= (nlstate+ndeath-1)*nlstate; /* Number of forces ij from state i to j */
10920: npar= nforce*ncovmodel; /* Number of parameters like aij*/
1.131 brouard 10921: if(npar >MAXPARM || nlstate >NLSTATEMAX || ndeath >NDEATHMAX || ncovmodel>NCOVMAX){
10922: 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);
10923: 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);
10924: fflush(stdout);
10925: fclose (ficlog);
10926: goto end;
10927: }
1.126 brouard 10928: delti3= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
10929: delti=delti3[1][1];
10930: /*delti=vector(1,npar); *//* Scale of each paramater (output from hesscov)*/
10931: if(mle==-1){ /* Print a wizard for help writing covariance matrix */
1.247 brouard 10932: /* We could also provide initial parameters values giving by simple logistic regression
10933: * only one way, that is without matrix product. We will have nlstate maximizations */
10934: /* for(i=1;i<nlstate;i++){ */
10935: /* /\*reducing xi for 1 to npar to 1 to ncovmodel; *\/ */
10936: /* mlikeli(ficres,p, ncovmodel, ncovmodel, nlstate, ftol, funcnoprod); */
10937: /* } */
1.126 brouard 10938: prwizard(ncovmodel, nlstate, ndeath, model, ficparo);
1.191 brouard 10939: printf(" You chose mle=-1, look at file %s for a template of covariance matrix \n",filereso);
10940: fprintf(ficlog," You chose mle=-1, look at file %s for a template of covariance matrix \n",filereso);
1.126 brouard 10941: free_ma3x(delti3,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
10942: fclose (ficparo);
10943: fclose (ficlog);
10944: goto end;
10945: exit(0);
1.220 brouard 10946: } else if(mle==-5) { /* Main Wizard */
1.126 brouard 10947: prwizard(ncovmodel, nlstate, ndeath, model, ficparo);
1.192 brouard 10948: printf(" You chose mle=-3, look at file %s for a template of covariance matrix \n",filereso);
10949: fprintf(ficlog," You chose mle=-3, look at file %s for a template of covariance matrix \n",filereso);
1.126 brouard 10950: param= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
10951: matcov=matrix(1,npar,1,npar);
1.203 brouard 10952: hess=matrix(1,npar,1,npar);
1.220 brouard 10953: } else{ /* Begin of mle != -1 or -5 */
1.145 brouard 10954: /* Read guessed parameters */
1.126 brouard 10955: /* Reads comments: lines beginning with '#' */
10956: while((c=getc(ficpar))=='#' && c!= EOF){
10957: ungetc(c,ficpar);
10958: fgets(line, MAXLINE, ficpar);
10959: numlinepar++;
1.141 brouard 10960: fputs(line,stdout);
1.126 brouard 10961: fputs(line,ficparo);
10962: fputs(line,ficlog);
10963: }
10964: ungetc(c,ficpar);
10965:
10966: param= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
1.251 brouard 10967: paramstart= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
1.126 brouard 10968: for(i=1; i <=nlstate; i++){
1.234 brouard 10969: j=0;
1.126 brouard 10970: for(jj=1; jj <=nlstate+ndeath; jj++){
1.234 brouard 10971: if(jj==i) continue;
10972: j++;
10973: fscanf(ficpar,"%1d%1d",&i1,&j1);
10974: if ((i1 != i) || (j1 != jj)){
10975: printf("Error in line parameters number %d, %1d%1d instead of %1d%1d \n \
1.126 brouard 10976: It might be a problem of design; if ncovcol and the model are correct\n \
10977: run imach with mle=-1 to get a correct template of the parameter file.\n",numlinepar, i,j, i1, j1);
1.234 brouard 10978: exit(1);
10979: }
10980: fprintf(ficparo,"%1d%1d",i1,j1);
10981: if(mle==1)
10982: printf("%1d%1d",i,jj);
10983: fprintf(ficlog,"%1d%1d",i,jj);
10984: for(k=1; k<=ncovmodel;k++){
10985: fscanf(ficpar," %lf",¶m[i][j][k]);
10986: if(mle==1){
10987: printf(" %lf",param[i][j][k]);
10988: fprintf(ficlog," %lf",param[i][j][k]);
10989: }
10990: else
10991: fprintf(ficlog," %lf",param[i][j][k]);
10992: fprintf(ficparo," %lf",param[i][j][k]);
10993: }
10994: fscanf(ficpar,"\n");
10995: numlinepar++;
10996: if(mle==1)
10997: printf("\n");
10998: fprintf(ficlog,"\n");
10999: fprintf(ficparo,"\n");
1.126 brouard 11000: }
11001: }
11002: fflush(ficlog);
1.234 brouard 11003:
1.251 brouard 11004: /* Reads parameters values */
1.126 brouard 11005: p=param[1][1];
1.251 brouard 11006: pstart=paramstart[1][1];
1.126 brouard 11007:
11008: /* Reads comments: lines beginning with '#' */
11009: while((c=getc(ficpar))=='#' && c!= EOF){
11010: ungetc(c,ficpar);
11011: fgets(line, MAXLINE, ficpar);
11012: numlinepar++;
1.141 brouard 11013: fputs(line,stdout);
1.126 brouard 11014: fputs(line,ficparo);
11015: fputs(line,ficlog);
11016: }
11017: ungetc(c,ficpar);
11018:
11019: for(i=1; i <=nlstate; i++){
11020: for(j=1; j <=nlstate+ndeath-1; j++){
1.234 brouard 11021: fscanf(ficpar,"%1d%1d",&i1,&j1);
11022: if ( (i1-i) * (j1-j) != 0){
11023: printf("Error in line parameters number %d, %1d%1d instead of %1d%1d \n",numlinepar, i,j, i1, j1);
11024: exit(1);
11025: }
11026: printf("%1d%1d",i,j);
11027: fprintf(ficparo,"%1d%1d",i1,j1);
11028: fprintf(ficlog,"%1d%1d",i1,j1);
11029: for(k=1; k<=ncovmodel;k++){
11030: fscanf(ficpar,"%le",&delti3[i][j][k]);
11031: printf(" %le",delti3[i][j][k]);
11032: fprintf(ficparo," %le",delti3[i][j][k]);
11033: fprintf(ficlog," %le",delti3[i][j][k]);
11034: }
11035: fscanf(ficpar,"\n");
11036: numlinepar++;
11037: printf("\n");
11038: fprintf(ficparo,"\n");
11039: fprintf(ficlog,"\n");
1.126 brouard 11040: }
11041: }
11042: fflush(ficlog);
1.234 brouard 11043:
1.145 brouard 11044: /* Reads covariance matrix */
1.126 brouard 11045: delti=delti3[1][1];
1.220 brouard 11046:
11047:
1.126 brouard 11048: /* 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 11049:
1.126 brouard 11050: /* Reads comments: lines beginning with '#' */
11051: while((c=getc(ficpar))=='#' && c!= EOF){
11052: ungetc(c,ficpar);
11053: fgets(line, MAXLINE, ficpar);
11054: numlinepar++;
1.141 brouard 11055: fputs(line,stdout);
1.126 brouard 11056: fputs(line,ficparo);
11057: fputs(line,ficlog);
11058: }
11059: ungetc(c,ficpar);
1.220 brouard 11060:
1.126 brouard 11061: matcov=matrix(1,npar,1,npar);
1.203 brouard 11062: hess=matrix(1,npar,1,npar);
1.131 brouard 11063: for(i=1; i <=npar; i++)
11064: for(j=1; j <=npar; j++) matcov[i][j]=0.;
1.220 brouard 11065:
1.194 brouard 11066: /* Scans npar lines */
1.126 brouard 11067: for(i=1; i <=npar; i++){
1.226 brouard 11068: count=fscanf(ficpar,"%1d%1d%d",&i1,&j1,&jk);
1.194 brouard 11069: if(count != 3){
1.226 brouard 11070: printf("Error! Error in parameter file %s at line %d after line starting with %1d%1d%1d\n\
1.194 brouard 11071: This is probably because your covariance matrix doesn't \n contain exactly %d lines corresponding to your model line '1+age+%s'.\n\
11072: Please run with mle=-1 to get a correct covariance matrix.\n",optionfile,numlinepar, i1,j1,jk, npar, model);
1.226 brouard 11073: fprintf(ficlog,"Error! Error in parameter file %s at line %d after line starting with %1d%1d%1d\n\
1.194 brouard 11074: This is probably because your covariance matrix doesn't \n contain exactly %d lines corresponding to your model line '1+age+%s'.\n\
11075: Please run with mle=-1 to get a correct covariance matrix.\n",optionfile,numlinepar, i1,j1,jk, npar, model);
1.226 brouard 11076: exit(1);
1.220 brouard 11077: }else{
1.226 brouard 11078: if(mle==1)
11079: printf("%1d%1d%d",i1,j1,jk);
11080: }
11081: fprintf(ficlog,"%1d%1d%d",i1,j1,jk);
11082: fprintf(ficparo,"%1d%1d%d",i1,j1,jk);
1.126 brouard 11083: for(j=1; j <=i; j++){
1.226 brouard 11084: fscanf(ficpar," %le",&matcov[i][j]);
11085: if(mle==1){
11086: printf(" %.5le",matcov[i][j]);
11087: }
11088: fprintf(ficlog," %.5le",matcov[i][j]);
11089: fprintf(ficparo," %.5le",matcov[i][j]);
1.126 brouard 11090: }
11091: fscanf(ficpar,"\n");
11092: numlinepar++;
11093: if(mle==1)
1.220 brouard 11094: printf("\n");
1.126 brouard 11095: fprintf(ficlog,"\n");
11096: fprintf(ficparo,"\n");
11097: }
1.194 brouard 11098: /* End of read covariance matrix npar lines */
1.126 brouard 11099: for(i=1; i <=npar; i++)
11100: for(j=i+1;j<=npar;j++)
1.226 brouard 11101: matcov[i][j]=matcov[j][i];
1.126 brouard 11102:
11103: if(mle==1)
11104: printf("\n");
11105: fprintf(ficlog,"\n");
11106:
11107: fflush(ficlog);
11108:
11109: /*-------- Rewriting parameter file ----------*/
11110: strcpy(rfileres,"r"); /* "Rparameterfile */
11111: strcat(rfileres,optionfilefiname); /* Parameter file first name*/
11112: strcat(rfileres,"."); /* */
11113: strcat(rfileres,optionfilext); /* Other files have txt extension */
11114: if((ficres =fopen(rfileres,"w"))==NULL) {
1.201 brouard 11115: printf("Problem writing new parameter file: %s\n", rfileres);goto end;
11116: fprintf(ficlog,"Problem writing new parameter file: %s\n", rfileres);goto end;
1.126 brouard 11117: }
11118: fprintf(ficres,"#%s\n",version);
11119: } /* End of mle != -3 */
1.218 brouard 11120:
1.186 brouard 11121: /* Main data
11122: */
1.126 brouard 11123: n= lastobs;
11124: num=lvector(1,n);
11125: moisnais=vector(1,n);
11126: annais=vector(1,n);
11127: moisdc=vector(1,n);
11128: andc=vector(1,n);
1.220 brouard 11129: weight=vector(1,n);
1.126 brouard 11130: agedc=vector(1,n);
11131: cod=ivector(1,n);
1.220 brouard 11132: for(i=1;i<=n;i++){
1.234 brouard 11133: num[i]=0;
11134: moisnais[i]=0;
11135: annais[i]=0;
11136: moisdc[i]=0;
11137: andc[i]=0;
11138: agedc[i]=0;
11139: cod[i]=0;
11140: weight[i]=1.0; /* Equal weights, 1 by default */
11141: }
1.126 brouard 11142: mint=matrix(1,maxwav,1,n);
11143: anint=matrix(1,maxwav,1,n);
1.131 brouard 11144: s=imatrix(1,maxwav+1,1,n); /* s[i][j] health state for wave i and individual j */
1.126 brouard 11145: tab=ivector(1,NCOVMAX);
1.144 brouard 11146: ncodemax=ivector(1,NCOVMAX); /* Number of code per covariate; if O and 1 only, 2**ncov; V1+V2+V3+V4=>16 */
1.192 brouard 11147: 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 11148:
1.136 brouard 11149: /* Reads data from file datafile */
11150: if (readdata(datafile, firstobs, lastobs, &imx)==1)
11151: goto end;
11152:
11153: /* Calculation of the number of parameters from char model */
1.234 brouard 11154: /* modelsav=V2+V1+V4+age*V3 strb=age*V3 stra=V2+V1+V4
1.137 brouard 11155: k=4 (age*V3) Tvar[k=4]= 3 (from V3) Tag[cptcovage=1]=4
11156: k=3 V4 Tvar[k=3]= 4 (from V4)
11157: k=2 V1 Tvar[k=2]= 1 (from V1)
11158: k=1 Tvar[1]=2 (from V2)
1.234 brouard 11159: */
11160:
11161: Tvar=ivector(1,NCOVMAX); /* Was 15 changed to NCOVMAX. */
11162: TvarsDind=ivector(1,NCOVMAX); /* */
11163: TvarsD=ivector(1,NCOVMAX); /* */
11164: TvarsQind=ivector(1,NCOVMAX); /* */
11165: TvarsQ=ivector(1,NCOVMAX); /* */
1.232 brouard 11166: TvarF=ivector(1,NCOVMAX); /* */
11167: TvarFind=ivector(1,NCOVMAX); /* */
11168: TvarV=ivector(1,NCOVMAX); /* */
11169: TvarVind=ivector(1,NCOVMAX); /* */
11170: TvarA=ivector(1,NCOVMAX); /* */
11171: TvarAind=ivector(1,NCOVMAX); /* */
1.231 brouard 11172: TvarFD=ivector(1,NCOVMAX); /* */
11173: TvarFDind=ivector(1,NCOVMAX); /* */
11174: TvarFQ=ivector(1,NCOVMAX); /* */
11175: TvarFQind=ivector(1,NCOVMAX); /* */
11176: TvarVD=ivector(1,NCOVMAX); /* */
11177: TvarVDind=ivector(1,NCOVMAX); /* */
11178: TvarVQ=ivector(1,NCOVMAX); /* */
11179: TvarVQind=ivector(1,NCOVMAX); /* */
11180:
1.230 brouard 11181: Tvalsel=vector(1,NCOVMAX); /* */
1.233 brouard 11182: Tvarsel=ivector(1,NCOVMAX); /* */
1.226 brouard 11183: Typevar=ivector(-1,NCOVMAX); /* -1 to 2 */
11184: Fixed=ivector(-1,NCOVMAX); /* -1 to 3 */
11185: Dummy=ivector(-1,NCOVMAX); /* -1 to 3 */
1.137 brouard 11186: /* V2+V1+V4+age*V3 is a model with 4 covariates (3 plus signs).
11187: For each model-covariate stores the data-covariate id. Tvar[1]=2, Tvar[2]=1, Tvar[3]=4,
11188: Tvar[4=age*V3] is 3 and 'age' is recorded in Tage.
11189: */
11190: /* For model-covariate k tells which data-covariate to use but
11191: because this model-covariate is a construction we invent a new column
11192: ncovcol + k1
11193: If already ncovcol=4 and model=V2+V1+V1*V4+age*V3
11194: Tvar[3=V1*V4]=4+1 etc */
1.227 brouard 11195: Tprod=ivector(1,NCOVMAX); /* Gives the k position of the k1 product */
11196: Tposprod=ivector(1,NCOVMAX); /* Gives the k1 product from the k position */
1.137 brouard 11197: /* Tprod[k1=1]=3(=V1*V4) for V2+V1+V1*V4+age*V3
11198: if V2+V1+V1*V4+age*V3+V3*V2 TProd[k1=2]=5 (V3*V2)
1.227 brouard 11199: Tposprod[k]=k1 , Tposprod[3]=1, Tposprod[5]=2
1.137 brouard 11200: */
1.145 brouard 11201: Tvaraff=ivector(1,NCOVMAX); /* Unclear */
11202: 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 11203: * For V3*V2 (in V2+V1+V1*V4+age*V3+V3*V2), V3*V2 position is 2nd.
11204: * Tvard[k1=2][1]=3 (V3) Tvard[k1=2][2]=2(V2) */
1.145 brouard 11205: Tage=ivector(1,NCOVMAX); /* Gives the covariate id of covariates associated with age: V2 + V1 + age*V4 + V3*age
1.137 brouard 11206: 4 covariates (3 plus signs)
11207: Tage[1=V3*age]= 4; Tage[2=age*V4] = 3
11208: */
1.230 brouard 11209: Tmodelind=ivector(1,NCOVMAX);/** gives the k model position of an
1.227 brouard 11210: * individual dummy, fixed or varying:
11211: * Tmodelind[Tvaraff[3]]=9,Tvaraff[1]@9={4,
11212: * 3, 1, 0, 0, 0, 0, 0, 0},
1.230 brouard 11213: * model=V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 ,
11214: * V1 df, V2 qf, V3 & V4 dv, V5 qv
11215: * Tmodelind[1]@9={9,0,3,2,}*/
11216: TmodelInvind=ivector(1,NCOVMAX); /* TmodelInvind=Tvar[k]- ncovcol-nqv={5-2-1=2,*/
11217: TmodelInvQind=ivector(1,NCOVMAX);/** gives the k model position of an
1.228 brouard 11218: * individual quantitative, fixed or varying:
11219: * Tmodelqind[1]=1,Tvaraff[1]@9={4,
11220: * 3, 1, 0, 0, 0, 0, 0, 0},
11221: * model=V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1*/
1.186 brouard 11222: /* Main decodemodel */
11223:
1.187 brouard 11224:
1.223 brouard 11225: if(decodemodel(model, lastobs) == 1) /* In order to get Tvar[k] V4+V3+V5 p Tvar[1]@3 = {4, 3, 5}*/
1.136 brouard 11226: goto end;
11227:
1.137 brouard 11228: if((double)(lastobs-imx)/(double)imx > 1.10){
11229: nbwarn++;
11230: 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);
11231: 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);
11232: }
1.136 brouard 11233: /* if(mle==1){*/
1.137 brouard 11234: if (weightopt != 1) { /* Maximisation without weights. We can have weights different from 1 but want no weight*/
11235: for(i=1;i<=imx;i++) weight[i]=1.0; /* changed to imx */
1.136 brouard 11236: }
11237:
11238: /*-calculation of age at interview from date of interview and age at death -*/
11239: agev=matrix(1,maxwav,1,imx);
11240:
11241: if(calandcheckages(imx, maxwav, &agemin, &agemax, &nberr, &nbwarn) == 1)
11242: goto end;
11243:
1.126 brouard 11244:
1.136 brouard 11245: agegomp=(int)agemin;
11246: free_vector(moisnais,1,n);
11247: free_vector(annais,1,n);
1.126 brouard 11248: /* free_matrix(mint,1,maxwav,1,n);
11249: free_matrix(anint,1,maxwav,1,n);*/
1.215 brouard 11250: /* free_vector(moisdc,1,n); */
11251: /* free_vector(andc,1,n); */
1.145 brouard 11252: /* */
11253:
1.126 brouard 11254: wav=ivector(1,imx);
1.214 brouard 11255: /* dh=imatrix(1,lastpass-firstpass+1,1,imx); */
11256: /* bh=imatrix(1,lastpass-firstpass+1,1,imx); */
11257: /* mw=imatrix(1,lastpass-firstpass+1,1,imx); */
11258: 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.*/
11259: bh=imatrix(1,lastpass-firstpass+2,1,imx);
11260: mw=imatrix(1,lastpass-firstpass+2,1,imx);
1.126 brouard 11261:
11262: /* Concatenates waves */
1.214 brouard 11263: /* Concatenates waves: wav[i] is the number of effective (useful waves) of individual i.
11264: Death is a valid wave (if date is known).
11265: mw[mi][i] is the number of (mi=1 to wav[i]) effective wave out of mi of individual i
11266: dh[m][i] or dh[mw[mi][i]][i] is the delay between two effective waves m=mw[mi][i]
11267: and mw[mi+1][i]. dh depends on stepm.
11268: */
11269:
1.126 brouard 11270: concatwav(wav, dh, bh, mw, s, agedc, agev, firstpass, lastpass, imx, nlstate, stepm);
1.248 brouard 11271: /* Concatenates waves */
1.145 brouard 11272:
1.215 brouard 11273: free_vector(moisdc,1,n);
11274: free_vector(andc,1,n);
11275:
1.126 brouard 11276: /* Routine tricode is to calculate cptcoveff (real number of unique covariates) and to associate covariable number and modality */
11277: nbcode=imatrix(0,NCOVMAX,0,NCOVMAX);
11278: ncodemax[1]=1;
1.145 brouard 11279: Ndum =ivector(-1,NCOVMAX);
1.225 brouard 11280: cptcoveff=0;
1.220 brouard 11281: if (ncovmodel-nagesqr > 2 ){ /* That is if covariate other than cst, age and age*age */
11282: tricode(&cptcoveff,Tvar,nbcode,imx, Ndum); /**< Fills nbcode[Tvar[j]][l]; */
1.227 brouard 11283: }
11284:
11285: ncovcombmax=pow(2,cptcoveff);
11286: invalidvarcomb=ivector(1, ncovcombmax);
11287: for(i=1;i<ncovcombmax;i++)
11288: invalidvarcomb[i]=0;
11289:
1.211 brouard 11290: /* Nbcode gives the value of the lth modality (currently 1 to 2) of jth covariate, in
1.186 brouard 11291: V2+V1*age, there are 3 covariates Tvar[2]=1 (V1).*/
1.211 brouard 11292: /* 1 to ncodemax[j] which is the maximum value of this jth covariate */
1.227 brouard 11293:
1.200 brouard 11294: /* codtab=imatrix(1,100,1,10);*/ /* codtab[h,k]=( (h-1) - mod(k-1,2**(k-1) )/2**(k-1) */
1.198 brouard 11295: /*printf(" codtab[1,1],codtab[100,10]=%d,%d\n", codtab[1][1],codtabm(100,10));*/
1.186 brouard 11296: /* codtab gives the value 1 or 2 of the hth combination of k covariates (1 or 2).*/
1.211 brouard 11297: /* nbcode[Tvaraff[j]][codtabm(h,j)]) : if there are only 2 modalities for a covariate j,
11298: * codtabm(h,j) gives its value classified at position h and nbcode gives how it is coded
11299: * (currently 0 or 1) in the data.
11300: * In a loop on h=1 to 2**k, and a loop on j (=1 to k), we get the value of
11301: * corresponding modality (h,j).
11302: */
11303:
1.145 brouard 11304: h=0;
11305: /*if (cptcovn > 0) */
1.126 brouard 11306: m=pow(2,cptcoveff);
11307:
1.144 brouard 11308: /**< codtab(h,k) k = codtab[h,k]=( (h-1) - mod(k-1,2**(k-1) )/2**(k-1) + 1
1.211 brouard 11309: * For k=4 covariates, h goes from 1 to m=2**k
11310: * codtabm(h,k)= (1 & (h-1) >> (k-1)) + 1;
11311: * #define codtabm(h,k) (1 & (h-1) >> (k-1))+1
1.186 brouard 11312: * h\k 1 2 3 4
1.143 brouard 11313: *______________________________
11314: * 1 i=1 1 i=1 1 i=1 1 i=1 1
11315: * 2 2 1 1 1
11316: * 3 i=2 1 2 1 1
11317: * 4 2 2 1 1
11318: * 5 i=3 1 i=2 1 2 1
11319: * 6 2 1 2 1
11320: * 7 i=4 1 2 2 1
11321: * 8 2 2 2 1
1.197 brouard 11322: * 9 i=5 1 i=3 1 i=2 1 2
11323: * 10 2 1 1 2
11324: * 11 i=6 1 2 1 2
11325: * 12 2 2 1 2
11326: * 13 i=7 1 i=4 1 2 2
11327: * 14 2 1 2 2
11328: * 15 i=8 1 2 2 2
11329: * 16 2 2 2 2
1.143 brouard 11330: */
1.212 brouard 11331: /* How to do the opposite? From combination h (=1 to 2**k) how to get the value on the covariates? */
1.211 brouard 11332: /* from h=5 and m, we get then number of covariates k=log(m)/log(2)=4
11333: * and the value of each covariate?
11334: * V1=1, V2=1, V3=2, V4=1 ?
11335: * h-1=4 and 4 is 0100 or reverse 0010, and +1 is 1121 ok.
11336: * h=6, 6-1=5, 5 is 0101, 1010, 2121, V1=2nd, V2=1st, V3=2nd, V4=1st.
11337: * In order to get the real value in the data, we use nbcode
11338: * nbcode[Tvar[3][2nd]]=1 and nbcode[Tvar[4][1]]=0
11339: * We are keeping this crazy system in order to be able (in the future?)
11340: * to have more than 2 values (0 or 1) for a covariate.
11341: * #define codtabm(h,k) (1 & (h-1) >> (k-1))+1
11342: * h=6, k=2? h-1=5=0101, reverse 1010, +1=2121, k=2nd position: value is 1: codtabm(6,2)=1
11343: * bbbbbbbb
11344: * 76543210
11345: * h-1 00000101 (6-1=5)
1.219 brouard 11346: *(h-1)>>(k-1)= 00000010 >> (2-1) = 1 right shift
1.211 brouard 11347: * &
11348: * 1 00000001 (1)
1.219 brouard 11349: * 00000000 = 1 & ((h-1) >> (k-1))
11350: * +1= 00000001 =1
1.211 brouard 11351: *
11352: * h=14, k=3 => h'=h-1=13, k'=k-1=2
11353: * h' 1101 =2^3+2^2+0x2^1+2^0
11354: * >>k' 11
11355: * & 00000001
11356: * = 00000001
11357: * +1 = 00000010=2 = codtabm(14,3)
11358: * Reverse h=6 and m=16?
11359: * cptcoveff=log(16)/log(2)=4 covariate: 6-1=5=0101 reversed=1010 +1=2121 =>V1=2, V2=1, V3=2, V4=1.
11360: * for (j=1 to cptcoveff) Vj=decodtabm(j,h,cptcoveff)
11361: * decodtabm(h,j,cptcoveff)= (((h-1) >> (j-1)) & 1) +1
11362: * decodtabm(h,j,cptcoveff)= (h <= (1<<cptcoveff)?(((h-1) >> (j-1)) & 1) +1 : -1)
11363: * V3=decodtabm(14,3,2**4)=2
11364: * h'=13 1101 =2^3+2^2+0x2^1+2^0
11365: *(h-1) >> (j-1) 0011 =13 >> 2
11366: * &1 000000001
11367: * = 000000001
11368: * +1= 000000010 =2
11369: * 2211
11370: * V1=1+1, V2=0+1, V3=1+1, V4=1+1
11371: * V3=2
1.220 brouard 11372: * codtabm and decodtabm are identical
1.211 brouard 11373: */
11374:
1.145 brouard 11375:
11376: free_ivector(Ndum,-1,NCOVMAX);
11377:
11378:
1.126 brouard 11379:
1.186 brouard 11380: /* Initialisation of ----------- gnuplot -------------*/
1.126 brouard 11381: strcpy(optionfilegnuplot,optionfilefiname);
11382: if(mle==-3)
1.201 brouard 11383: strcat(optionfilegnuplot,"-MORT_");
1.126 brouard 11384: strcat(optionfilegnuplot,".gp");
11385:
11386: if((ficgp=fopen(optionfilegnuplot,"w"))==NULL) {
11387: printf("Problem with file %s",optionfilegnuplot);
11388: }
11389: else{
1.204 brouard 11390: fprintf(ficgp,"\n# IMaCh-%s\n", version);
1.126 brouard 11391: fprintf(ficgp,"# %s\n", optionfilegnuplot);
1.141 brouard 11392: //fprintf(ficgp,"set missing 'NaNq'\n");
11393: fprintf(ficgp,"set datafile missing 'NaNq'\n");
1.126 brouard 11394: }
11395: /* fclose(ficgp);*/
1.186 brouard 11396:
11397:
11398: /* Initialisation of --------- index.htm --------*/
1.126 brouard 11399:
11400: strcpy(optionfilehtm,optionfilefiname); /* Main html file */
11401: if(mle==-3)
1.201 brouard 11402: strcat(optionfilehtm,"-MORT_");
1.126 brouard 11403: strcat(optionfilehtm,".htm");
11404: if((fichtm=fopen(optionfilehtm,"w"))==NULL) {
1.131 brouard 11405: printf("Problem with %s \n",optionfilehtm);
11406: exit(0);
1.126 brouard 11407: }
11408:
11409: strcpy(optionfilehtmcov,optionfilefiname); /* Only for matrix of covariance */
11410: strcat(optionfilehtmcov,"-cov.htm");
11411: if((fichtmcov=fopen(optionfilehtmcov,"w"))==NULL) {
11412: printf("Problem with %s \n",optionfilehtmcov), exit(0);
11413: }
11414: else{
11415: fprintf(fichtmcov,"<html><head>\n<title>IMaCh Cov %s</title></head>\n <body><font size=\"2\">%s <br> %s</font> \
11416: <hr size=\"2\" color=\"#EC5E5E\"> \n\
1.204 brouard 11417: Title=%s <br>Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s<br>\n",\
1.126 brouard 11418: optionfilehtmcov,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model);
11419: }
11420:
1.213 brouard 11421: 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 11422: <hr size=\"2\" color=\"#EC5E5E\"> \n\
11423: <font size=\"2\">IMaCh-%s <br> %s</font> \
1.126 brouard 11424: <hr size=\"2\" color=\"#EC5E5E\"> \n\
1.204 brouard 11425: Title=%s <br>Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s<br>\n\
1.126 brouard 11426: \n\
11427: <hr size=\"2\" color=\"#EC5E5E\">\
11428: <ul><li><h4>Parameter files</h4>\n\
11429: - Parameter file: <a href=\"%s.%s\">%s.%s</a><br>\n\
11430: - Copy of the parameter file: <a href=\"o%s\">o%s</a><br>\n\
11431: - Log file of the run: <a href=\"%s\">%s</a><br>\n\
11432: - Gnuplot file name: <a href=\"%s\">%s</a><br>\n\
11433: - Date and time at start: %s</ul>\n",\
11434: optionfilehtm,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model,\
11435: optionfilefiname,optionfilext,optionfilefiname,optionfilext,\
11436: fileres,fileres,\
11437: filelog,filelog,optionfilegnuplot,optionfilegnuplot,strstart);
11438: fflush(fichtm);
11439:
11440: strcpy(pathr,path);
11441: strcat(pathr,optionfilefiname);
1.184 brouard 11442: #ifdef WIN32
11443: _chdir(optionfilefiname); /* Move to directory named optionfile */
11444: #else
1.126 brouard 11445: chdir(optionfilefiname); /* Move to directory named optionfile */
1.184 brouard 11446: #endif
11447:
1.126 brouard 11448:
1.220 brouard 11449: /* Calculates basic frequencies. Computes observed prevalence at single age
11450: and for any valid combination of covariates
1.126 brouard 11451: and prints on file fileres'p'. */
1.251 brouard 11452: freqsummary(fileres, p, pstart, agemin, agemax, s, agev, nlstate, imx, Tvaraff, invalidvarcomb, nbcode, ncodemax,mint,anint,strstart, \
1.227 brouard 11453: firstpass, lastpass, stepm, weightopt, model);
1.126 brouard 11454:
11455: fprintf(fichtm,"\n");
11456: fprintf(fichtm,"<br>Total number of observations=%d <br>\n\
11457: Youngest age at first (selected) pass %.2f, oldest age %.2f<br>\n\
11458: Interval (in months) between two waves: Min=%d Max=%d Mean=%.2lf<br>\n",\
11459: imx,agemin,agemax,jmin,jmax,jmean);
11460: pmmij= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
1.268 brouard 11461: oldms= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
11462: newms= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
11463: savms= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
11464: oldm=oldms; newm=newms; savm=savms; /* Keeps fixed addresses to free */
1.218 brouard 11465:
1.126 brouard 11466: /* For Powell, parameters are in a vector p[] starting at p[1]
11467: so we point p on param[1][1] so that p[1] maps on param[1][1][1] */
11468: p=param[1][1]; /* *(*(*(param +1)+1)+0) */
11469:
11470: globpr=0; /* To get the number ipmx of contributions and the sum of weights*/
1.186 brouard 11471: /* For mortality only */
1.126 brouard 11472: if (mle==-3){
1.136 brouard 11473: ximort=matrix(1,NDIM,1,NDIM);
1.248 brouard 11474: for(i=1;i<=NDIM;i++)
11475: for(j=1;j<=NDIM;j++)
11476: ximort[i][j]=0.;
1.186 brouard 11477: /* ximort=gsl_matrix_alloc(1,NDIM,1,NDIM); */
1.126 brouard 11478: cens=ivector(1,n);
11479: ageexmed=vector(1,n);
11480: agecens=vector(1,n);
11481: dcwave=ivector(1,n);
1.223 brouard 11482:
1.126 brouard 11483: for (i=1; i<=imx; i++){
11484: dcwave[i]=-1;
11485: for (m=firstpass; m<=lastpass; m++)
1.226 brouard 11486: if (s[m][i]>nlstate) {
11487: dcwave[i]=m;
11488: /* printf("i=%d j=%d s=%d dcwave=%d\n",i,j, s[j][i],dcwave[i]);*/
11489: break;
11490: }
1.126 brouard 11491: }
1.226 brouard 11492:
1.126 brouard 11493: for (i=1; i<=imx; i++) {
11494: if (wav[i]>0){
1.226 brouard 11495: ageexmed[i]=agev[mw[1][i]][i];
11496: j=wav[i];
11497: agecens[i]=1.;
11498:
11499: if (ageexmed[i]> 1 && wav[i] > 0){
11500: agecens[i]=agev[mw[j][i]][i];
11501: cens[i]= 1;
11502: }else if (ageexmed[i]< 1)
11503: cens[i]= -1;
11504: if (agedc[i]< AGESUP && agedc[i]>1 && dcwave[i]>firstpass && dcwave[i]<=lastpass)
11505: cens[i]=0 ;
1.126 brouard 11506: }
11507: else cens[i]=-1;
11508: }
11509:
11510: for (i=1;i<=NDIM;i++) {
11511: for (j=1;j<=NDIM;j++)
1.226 brouard 11512: ximort[i][j]=(i == j ? 1.0 : 0.0);
1.126 brouard 11513: }
11514:
1.145 brouard 11515: /*p[1]=0.0268; p[NDIM]=0.083;*/
1.126 brouard 11516: /*printf("%lf %lf", p[1], p[2]);*/
11517:
11518:
1.136 brouard 11519: #ifdef GSL
11520: printf("GSL optimization\n"); fprintf(ficlog,"Powell\n");
1.162 brouard 11521: #else
1.126 brouard 11522: printf("Powell\n"); fprintf(ficlog,"Powell\n");
1.136 brouard 11523: #endif
1.201 brouard 11524: strcpy(filerespow,"POW-MORT_");
11525: strcat(filerespow,fileresu);
1.126 brouard 11526: if((ficrespow=fopen(filerespow,"w"))==NULL) {
11527: printf("Problem with resultfile: %s\n", filerespow);
11528: fprintf(ficlog,"Problem with resultfile: %s\n", filerespow);
11529: }
1.136 brouard 11530: #ifdef GSL
11531: fprintf(ficrespow,"# GSL optimization\n# iter -2*LL");
1.162 brouard 11532: #else
1.126 brouard 11533: fprintf(ficrespow,"# Powell\n# iter -2*LL");
1.136 brouard 11534: #endif
1.126 brouard 11535: /* for (i=1;i<=nlstate;i++)
11536: for(j=1;j<=nlstate+ndeath;j++)
11537: if(j!=i)fprintf(ficrespow," p%1d%1d",i,j);
11538: */
11539: fprintf(ficrespow,"\n");
1.136 brouard 11540: #ifdef GSL
11541: /* gsl starts here */
11542: T = gsl_multimin_fminimizer_nmsimplex;
11543: gsl_multimin_fminimizer *sfm = NULL;
11544: gsl_vector *ss, *x;
11545: gsl_multimin_function minex_func;
11546:
11547: /* Initial vertex size vector */
11548: ss = gsl_vector_alloc (NDIM);
11549:
11550: if (ss == NULL){
11551: GSL_ERROR_VAL ("failed to allocate space for ss", GSL_ENOMEM, 0);
11552: }
11553: /* Set all step sizes to 1 */
11554: gsl_vector_set_all (ss, 0.001);
11555:
11556: /* Starting point */
1.126 brouard 11557:
1.136 brouard 11558: x = gsl_vector_alloc (NDIM);
11559:
11560: if (x == NULL){
11561: gsl_vector_free(ss);
11562: GSL_ERROR_VAL ("failed to allocate space for x", GSL_ENOMEM, 0);
11563: }
11564:
11565: /* Initialize method and iterate */
11566: /* p[1]=0.0268; p[NDIM]=0.083; */
1.186 brouard 11567: /* gsl_vector_set(x, 0, 0.0268); */
11568: /* gsl_vector_set(x, 1, 0.083); */
1.136 brouard 11569: gsl_vector_set(x, 0, p[1]);
11570: gsl_vector_set(x, 1, p[2]);
11571:
11572: minex_func.f = &gompertz_f;
11573: minex_func.n = NDIM;
11574: minex_func.params = (void *)&p; /* ??? */
11575:
11576: sfm = gsl_multimin_fminimizer_alloc (T, NDIM);
11577: gsl_multimin_fminimizer_set (sfm, &minex_func, x, ss);
11578:
11579: printf("Iterations beginning .....\n\n");
11580: printf("Iter. # Intercept Slope -Log Likelihood Simplex size\n");
11581:
11582: iteri=0;
11583: while (rval == GSL_CONTINUE){
11584: iteri++;
11585: status = gsl_multimin_fminimizer_iterate(sfm);
11586:
11587: if (status) printf("error: %s\n", gsl_strerror (status));
11588: fflush(0);
11589:
11590: if (status)
11591: break;
11592:
11593: rval = gsl_multimin_test_size (gsl_multimin_fminimizer_size (sfm), 1e-6);
11594: ssval = gsl_multimin_fminimizer_size (sfm);
11595:
11596: if (rval == GSL_SUCCESS)
11597: printf ("converged to a local maximum at\n");
11598:
11599: printf("%5d ", iteri);
11600: for (it = 0; it < NDIM; it++){
11601: printf ("%10.5f ", gsl_vector_get (sfm->x, it));
11602: }
11603: printf("f() = %-10.5f ssize = %.7f\n", sfm->fval, ssval);
11604: }
11605:
11606: printf("\n\n Please note: Program should be run many times with varying starting points to detemine global maximum\n\n");
11607:
11608: gsl_vector_free(x); /* initial values */
11609: gsl_vector_free(ss); /* inital step size */
11610: for (it=0; it<NDIM; it++){
11611: p[it+1]=gsl_vector_get(sfm->x,it);
11612: fprintf(ficrespow," %.12lf", p[it]);
11613: }
11614: gsl_multimin_fminimizer_free (sfm); /* p *(sfm.x.data) et p *(sfm.x.data+1) */
11615: #endif
11616: #ifdef POWELL
11617: powell(p,ximort,NDIM,ftol,&iter,&fret,gompertz);
11618: #endif
1.126 brouard 11619: fclose(ficrespow);
11620:
1.203 brouard 11621: hesscov(matcov, hess, p, NDIM, delti, 1e-4, gompertz);
1.126 brouard 11622:
11623: for(i=1; i <=NDIM; i++)
11624: for(j=i+1;j<=NDIM;j++)
1.220 brouard 11625: matcov[i][j]=matcov[j][i];
1.126 brouard 11626:
11627: printf("\nCovariance matrix\n ");
1.203 brouard 11628: fprintf(ficlog,"\nCovariance matrix\n ");
1.126 brouard 11629: for(i=1; i <=NDIM; i++) {
11630: for(j=1;j<=NDIM;j++){
1.220 brouard 11631: printf("%f ",matcov[i][j]);
11632: fprintf(ficlog,"%f ",matcov[i][j]);
1.126 brouard 11633: }
1.203 brouard 11634: printf("\n "); fprintf(ficlog,"\n ");
1.126 brouard 11635: }
11636:
11637: printf("iter=%d MLE=%f Eq=%lf*exp(%lf*(age-%d))\n",iter,-gompertz(p),p[1],p[2],agegomp);
1.193 brouard 11638: for (i=1;i<=NDIM;i++) {
1.126 brouard 11639: printf("%f [%f ; %f]\n",p[i],p[i]-2*sqrt(matcov[i][i]),p[i]+2*sqrt(matcov[i][i]));
1.193 brouard 11640: fprintf(ficlog,"%f [%f ; %f]\n",p[i],p[i]-2*sqrt(matcov[i][i]),p[i]+2*sqrt(matcov[i][i]));
11641: }
1.126 brouard 11642: lsurv=vector(1,AGESUP);
11643: lpop=vector(1,AGESUP);
11644: tpop=vector(1,AGESUP);
11645: lsurv[agegomp]=100000;
11646:
11647: for (k=agegomp;k<=AGESUP;k++) {
11648: agemortsup=k;
11649: if (p[1]*exp(p[2]*(k-agegomp))>1) break;
11650: }
11651:
11652: for (k=agegomp;k<agemortsup;k++)
11653: lsurv[k+1]=lsurv[k]-lsurv[k]*(p[1]*exp(p[2]*(k-agegomp)));
11654:
11655: for (k=agegomp;k<agemortsup;k++){
11656: lpop[k]=(lsurv[k]+lsurv[k+1])/2.;
11657: sumlpop=sumlpop+lpop[k];
11658: }
11659:
11660: tpop[agegomp]=sumlpop;
11661: for (k=agegomp;k<(agemortsup-3);k++){
11662: /* tpop[k+1]=2;*/
11663: tpop[k+1]=tpop[k]-lpop[k];
11664: }
11665:
11666:
11667: printf("\nAge lx qx dx Lx Tx e(x)\n");
11668: for (k=agegomp;k<(agemortsup-2);k++)
11669: 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]);
11670:
11671:
11672: replace_back_to_slash(pathc,pathcd); /* Even gnuplot wants a / */
1.220 brouard 11673: ageminpar=50;
11674: agemaxpar=100;
1.194 brouard 11675: if(ageminpar == AGEOVERFLOW ||agemaxpar == AGEOVERFLOW){
11676: printf("Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
11677: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
11678: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
11679: fprintf(ficlog,"Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
11680: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
11681: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
1.220 brouard 11682: }else{
11683: printf("Warning! ageminpar %f and agemaxpar %f have been fixed because for simplification until it is fixed...\n\n",ageminpar,agemaxpar);
11684: 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 11685: printinggnuplotmort(fileresu, optionfilefiname,ageminpar,agemaxpar,fage, pathc,p);
1.220 brouard 11686: }
1.201 brouard 11687: printinghtmlmort(fileresu,title,datafile, firstpass, lastpass, \
1.126 brouard 11688: stepm, weightopt,\
11689: model,imx,p,matcov,agemortsup);
11690:
11691: free_vector(lsurv,1,AGESUP);
11692: free_vector(lpop,1,AGESUP);
11693: free_vector(tpop,1,AGESUP);
1.220 brouard 11694: free_matrix(ximort,1,NDIM,1,NDIM);
1.136 brouard 11695: free_ivector(cens,1,n);
11696: free_vector(agecens,1,n);
11697: free_ivector(dcwave,1,n);
1.220 brouard 11698: #ifdef GSL
1.136 brouard 11699: #endif
1.186 brouard 11700: } /* Endof if mle==-3 mortality only */
1.205 brouard 11701: /* Standard */
11702: else{ /* For mle !=- 3, could be 0 or 1 or 4 etc. */
11703: globpr=0;/* Computes sum of likelihood for globpr=1 and funcone */
11704: /* Computes likelihood for initial parameters, uses funcone to compute gpimx and gsw */
1.132 brouard 11705: likelione(ficres, p, npar, nlstate, &globpr, &ipmx, &sw, &fretone, funcone); /* Prints the contributions to the likelihood */
1.126 brouard 11706: printf("First Likeli=%12.6f ipmx=%ld sw=%12.6f",fretone,ipmx,sw);
11707: for (k=1; k<=npar;k++)
11708: printf(" %d %8.5f",k,p[k]);
11709: printf("\n");
1.205 brouard 11710: if(mle>=1){ /* Could be 1 or 2, Real Maximization */
11711: /* mlikeli uses func not funcone */
1.247 brouard 11712: /* for(i=1;i<nlstate;i++){ */
11713: /* /\*reducing xi for 1 to npar to 1 to ncovmodel; *\/ */
11714: /* mlikeli(ficres,p, ncovmodel, ncovmodel, nlstate, ftol, funcnoprod); */
11715: /* } */
1.205 brouard 11716: mlikeli(ficres,p, npar, ncovmodel, nlstate, ftol, func);
11717: }
11718: if(mle==0) {/* No optimization, will print the likelihoods for the datafile */
11719: globpr=0;/* Computes sum of likelihood for globpr=1 and funcone */
11720: /* Computes likelihood for initial parameters, uses funcone to compute gpimx and gsw */
11721: likelione(ficres, p, npar, nlstate, &globpr, &ipmx, &sw, &fretone, funcone); /* Prints the contributions to the likelihood */
11722: }
11723: globpr=1; /* again, to print the individual contributions using computed gpimx and gsw */
1.126 brouard 11724: likelione(ficres, p, npar, nlstate, &globpr, &ipmx, &sw, &fretone, funcone); /* Prints the contributions to the likelihood */
11725: printf("Second Likeli=%12.6f ipmx=%ld sw=%12.6f",fretone,ipmx,sw);
11726: for (k=1; k<=npar;k++)
11727: printf(" %d %8.5f",k,p[k]);
11728: printf("\n");
11729:
11730: /*--------- results files --------------*/
1.224 brouard 11731: 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 11732:
11733:
11734: fprintf(ficres,"# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
11735: printf("# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
11736: fprintf(ficlog,"# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
11737: for(i=1,jk=1; i <=nlstate; i++){
11738: for(k=1; k <=(nlstate+ndeath); k++){
1.225 brouard 11739: if (k != i) {
11740: printf("%d%d ",i,k);
11741: fprintf(ficlog,"%d%d ",i,k);
11742: fprintf(ficres,"%1d%1d ",i,k);
11743: for(j=1; j <=ncovmodel; j++){
11744: printf("%12.7f ",p[jk]);
11745: fprintf(ficlog,"%12.7f ",p[jk]);
11746: fprintf(ficres,"%12.7f ",p[jk]);
11747: jk++;
11748: }
11749: printf("\n");
11750: fprintf(ficlog,"\n");
11751: fprintf(ficres,"\n");
11752: }
1.126 brouard 11753: }
11754: }
1.203 brouard 11755: if(mle != 0){
11756: /* Computing hessian and covariance matrix only at a peak of the Likelihood, that is after optimization */
1.126 brouard 11757: ftolhess=ftol; /* Usually correct */
1.203 brouard 11758: hesscov(matcov, hess, p, npar, delti, ftolhess, func);
11759: 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");
11760: 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");
11761: for(i=1,jk=1; i <=nlstate; i++){
1.225 brouard 11762: for(k=1; k <=(nlstate+ndeath); k++){
11763: if (k != i) {
11764: printf("%d%d ",i,k);
11765: fprintf(ficlog,"%d%d ",i,k);
11766: for(j=1; j <=ncovmodel; j++){
11767: 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]));
11768: 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]));
11769: jk++;
11770: }
11771: printf("\n");
11772: fprintf(ficlog,"\n");
11773: }
11774: }
1.193 brouard 11775: }
1.203 brouard 11776: } /* end of hesscov and Wald tests */
1.225 brouard 11777:
1.203 brouard 11778: /* */
1.126 brouard 11779: fprintf(ficres,"# Scales (for hessian or gradient estimation)\n");
11780: printf("# Scales (for hessian or gradient estimation)\n");
11781: fprintf(ficlog,"# Scales (for hessian or gradient estimation)\n");
11782: for(i=1,jk=1; i <=nlstate; i++){
11783: for(j=1; j <=nlstate+ndeath; j++){
1.225 brouard 11784: if (j!=i) {
11785: fprintf(ficres,"%1d%1d",i,j);
11786: printf("%1d%1d",i,j);
11787: fprintf(ficlog,"%1d%1d",i,j);
11788: for(k=1; k<=ncovmodel;k++){
11789: printf(" %.5e",delti[jk]);
11790: fprintf(ficlog," %.5e",delti[jk]);
11791: fprintf(ficres," %.5e",delti[jk]);
11792: jk++;
11793: }
11794: printf("\n");
11795: fprintf(ficlog,"\n");
11796: fprintf(ficres,"\n");
11797: }
1.126 brouard 11798: }
11799: }
11800:
11801: 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 11802: if(mle >= 1) /* To big for the screen */
1.126 brouard 11803: 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");
11804: 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");
11805: /* # 121 Var(a12)\n\ */
11806: /* # 122 Cov(b12,a12) Var(b12)\n\ */
11807: /* # 131 Cov(a13,a12) Cov(a13,b12, Var(a13)\n\ */
11808: /* # 132 Cov(b13,a12) Cov(b13,b12, Cov(b13,a13) Var(b13)\n\ */
11809: /* # 212 Cov(a21,a12) Cov(a21,b12, Cov(a21,a13) Cov(a21,b13) Var(a21)\n\ */
11810: /* # 212 Cov(b21,a12) Cov(b21,b12, Cov(b21,a13) Cov(b21,b13) Cov(b21,a21) Var(b21)\n\ */
11811: /* # 232 Cov(a23,a12) Cov(a23,b12, Cov(a23,a13) Cov(a23,b13) Cov(a23,a21) Cov(a23,b21) Var(a23)\n\ */
11812: /* # 232 Cov(b23,a12) Cov(b23,b12) ... Var (b23)\n" */
11813:
11814:
11815: /* Just to have a covariance matrix which will be more understandable
11816: even is we still don't want to manage dictionary of variables
11817: */
11818: for(itimes=1;itimes<=2;itimes++){
11819: jj=0;
11820: for(i=1; i <=nlstate; i++){
1.225 brouard 11821: for(j=1; j <=nlstate+ndeath; j++){
11822: if(j==i) continue;
11823: for(k=1; k<=ncovmodel;k++){
11824: jj++;
11825: ca[0]= k+'a'-1;ca[1]='\0';
11826: if(itimes==1){
11827: if(mle>=1)
11828: printf("#%1d%1d%d",i,j,k);
11829: fprintf(ficlog,"#%1d%1d%d",i,j,k);
11830: fprintf(ficres,"#%1d%1d%d",i,j,k);
11831: }else{
11832: if(mle>=1)
11833: printf("%1d%1d%d",i,j,k);
11834: fprintf(ficlog,"%1d%1d%d",i,j,k);
11835: fprintf(ficres,"%1d%1d%d",i,j,k);
11836: }
11837: ll=0;
11838: for(li=1;li <=nlstate; li++){
11839: for(lj=1;lj <=nlstate+ndeath; lj++){
11840: if(lj==li) continue;
11841: for(lk=1;lk<=ncovmodel;lk++){
11842: ll++;
11843: if(ll<=jj){
11844: cb[0]= lk +'a'-1;cb[1]='\0';
11845: if(ll<jj){
11846: if(itimes==1){
11847: if(mle>=1)
11848: printf(" Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
11849: fprintf(ficlog," Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
11850: fprintf(ficres," Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
11851: }else{
11852: if(mle>=1)
11853: printf(" %.5e",matcov[jj][ll]);
11854: fprintf(ficlog," %.5e",matcov[jj][ll]);
11855: fprintf(ficres," %.5e",matcov[jj][ll]);
11856: }
11857: }else{
11858: if(itimes==1){
11859: if(mle>=1)
11860: printf(" Var(%s%1d%1d)",ca,i,j);
11861: fprintf(ficlog," Var(%s%1d%1d)",ca,i,j);
11862: fprintf(ficres," Var(%s%1d%1d)",ca,i,j);
11863: }else{
11864: if(mle>=1)
11865: printf(" %.7e",matcov[jj][ll]);
11866: fprintf(ficlog," %.7e",matcov[jj][ll]);
11867: fprintf(ficres," %.7e",matcov[jj][ll]);
11868: }
11869: }
11870: }
11871: } /* end lk */
11872: } /* end lj */
11873: } /* end li */
11874: if(mle>=1)
11875: printf("\n");
11876: fprintf(ficlog,"\n");
11877: fprintf(ficres,"\n");
11878: numlinepar++;
11879: } /* end k*/
11880: } /*end j */
1.126 brouard 11881: } /* end i */
11882: } /* end itimes */
11883:
11884: fflush(ficlog);
11885: fflush(ficres);
1.225 brouard 11886: while(fgets(line, MAXLINE, ficpar)) {
11887: /* If line starts with a # it is a comment */
11888: if (line[0] == '#') {
11889: numlinepar++;
11890: fputs(line,stdout);
11891: fputs(line,ficparo);
11892: fputs(line,ficlog);
11893: continue;
11894: }else
11895: break;
11896: }
11897:
1.209 brouard 11898: /* while((c=getc(ficpar))=='#' && c!= EOF){ */
11899: /* ungetc(c,ficpar); */
11900: /* fgets(line, MAXLINE, ficpar); */
11901: /* fputs(line,stdout); */
11902: /* fputs(line,ficparo); */
11903: /* } */
11904: /* ungetc(c,ficpar); */
1.126 brouard 11905:
11906: estepm=0;
1.209 brouard 11907: 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 11908:
11909: if (num_filled != 6) {
11910: 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);
11911: 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);
11912: goto end;
11913: }
11914: printf("agemin=%lf agemax=%lf bage=%lf fage=%lf estepm=%d ftolpl=%lf\n",ageminpar,agemaxpar, bage, fage, estepm, ftolpl);
11915: }
11916: /* ftolpl=6*ftol*1.e5; /\* 6.e-3 make convergences in less than 80 loops for the prevalence limit *\/ */
11917: /*ftolpl=6.e-4;*/ /* 6.e-3 make convergences in less than 80 loops for the prevalence limit */
11918:
1.209 brouard 11919: /* fscanf(ficpar,"agemin=%lf agemax=%lf bage=%lf fage=%lf estepm=%d ftolpl=%\n",&ageminpar,&agemaxpar, &bage, &fage, &estepm); */
1.126 brouard 11920: if (estepm==0 || estepm < stepm) estepm=stepm;
11921: if (fage <= 2) {
11922: bage = ageminpar;
11923: fage = agemaxpar;
11924: }
11925:
11926: fprintf(ficres,"# agemin agemax for life expectancy, bage fage (if mle==0 ie no data nor Max likelihood).\n");
1.211 brouard 11927: fprintf(ficres,"agemin=%.0f agemax=%.0f bage=%.0f fage=%.0f estepm=%d ftolpl=%e\n",ageminpar,agemaxpar,bage,fage, estepm, ftolpl);
11928: fprintf(ficparo,"agemin=%.0f agemax=%.0f bage=%.0f fage=%.0f estepm=%d, ftolpl=%e\n",ageminpar,agemaxpar,bage,fage, estepm, ftolpl);
1.220 brouard 11929:
1.186 brouard 11930: /* Other stuffs, more or less useful */
1.254 brouard 11931: while(fgets(line, MAXLINE, ficpar)) {
11932: /* If line starts with a # it is a comment */
11933: if (line[0] == '#') {
11934: numlinepar++;
11935: fputs(line,stdout);
11936: fputs(line,ficparo);
11937: fputs(line,ficlog);
11938: continue;
11939: }else
11940: break;
11941: }
11942:
11943: 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){
11944:
11945: if (num_filled != 7) {
11946: 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);
11947: 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);
11948: goto end;
11949: }
11950: printf("begin-prev-date=%.lf/%.lf/%.lf end-prev-date=%.lf/%.lf/%.lf mov_average=%d\n",jprev1, mprev1,anprev1,jprev2, mprev2,anprev2,mobilav);
11951: 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);
11952: 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);
11953: 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 11954: }
1.254 brouard 11955:
11956: while(fgets(line, MAXLINE, ficpar)) {
11957: /* If line starts with a # it is a comment */
11958: if (line[0] == '#') {
11959: numlinepar++;
11960: fputs(line,stdout);
11961: fputs(line,ficparo);
11962: fputs(line,ficlog);
11963: continue;
11964: }else
11965: break;
1.126 brouard 11966: }
11967:
11968:
11969: dateprev1=anprev1+(mprev1-1)/12.+(jprev1-1)/365.;
11970: dateprev2=anprev2+(mprev2-1)/12.+(jprev2-1)/365.;
11971:
1.254 brouard 11972: if((num_filled=sscanf(line,"pop_based=%d\n",&popbased)) !=EOF){
11973: if (num_filled != 1) {
11974: 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);
11975: 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);
11976: goto end;
11977: }
11978: printf("pop_based=%d\n",popbased);
11979: fprintf(ficlog,"pop_based=%d\n",popbased);
11980: fprintf(ficparo,"pop_based=%d\n",popbased);
11981: fprintf(ficres,"pop_based=%d\n",popbased);
11982: }
11983:
1.258 brouard 11984: /* Results */
11985: nresult=0;
11986: do{
11987: if(!fgets(line, MAXLINE, ficpar)){
11988: endishere=1;
11989: parameterline=14;
11990: }else if (line[0] == '#') {
11991: /* If line starts with a # it is a comment */
1.254 brouard 11992: numlinepar++;
11993: fputs(line,stdout);
11994: fputs(line,ficparo);
11995: fputs(line,ficlog);
11996: continue;
1.258 brouard 11997: }else if(sscanf(line,"prevforecast=%[^\n]\n",modeltemp))
11998: parameterline=11;
11999: else if(sscanf(line,"backcast=%[^\n]\n",modeltemp))
12000: parameterline=12;
12001: else if(sscanf(line,"result:%[^\n]\n",modeltemp))
12002: parameterline=13;
12003: else{
12004: parameterline=14;
1.254 brouard 12005: }
1.258 brouard 12006: switch (parameterline){
12007: case 11:
12008: 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){
12009: if (num_filled != 8) {
12010: 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);
12011: 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);
12012: goto end;
12013: }
12014: 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);
12015: 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);
12016: 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);
12017: 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);
12018: /* day and month of proj2 are not used but only year anproj2.*/
12019: }
1.254 brouard 12020: break;
1.258 brouard 12021: case 12:
12022: /*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);*/
12023: 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){
12024: if (num_filled != 8) {
1.262 brouard 12025: 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);
12026: 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 12027: goto end;
12028: }
12029: 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);
12030: 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);
12031: 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);
12032: 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);
12033: /* day and month of proj2 are not used but only year anproj2.*/
12034: }
1.230 brouard 12035: break;
1.258 brouard 12036: case 13:
12037: if((num_filled=sscanf(line,"result:%[^\n]\n",resultline)) !=EOF){
12038: if (num_filled == 0){
12039: resultline[0]='\0';
12040: printf("Warning %d: no result line! It should be at minimum 'result: V2=0 V1=1 or result:.\n%s\n", num_filled, line);
12041: 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);
12042: break;
12043: } else if (num_filled != 1){
12044: printf("ERROR %d: result line! It should be at minimum 'result: V2=0 V1=1 or result:.' %s\n",num_filled, line);
12045: fprintf(ficlog,"ERROR %d: result line! It should be at minimum 'result: V2=0 V1=1 or result:.' %s\n",num_filled, line);
12046: }
12047: nresult++; /* Sum of resultlines */
12048: printf("Result %d: result=%s\n",nresult, resultline);
12049: if(nresult > MAXRESULTLINES){
12050: printf("ERROR: Current version of IMaCh limits the number of resultlines to %d, you used %d\n",MAXRESULTLINES,nresult);
12051: fprintf(ficlog,"ERROR: Current version of IMaCh limits the number of resultlines to %d, you used %d\n",MAXRESULTLINES,nresult);
12052: goto end;
12053: }
12054: decoderesult(resultline, nresult); /* Fills TKresult[nresult] combination and Tresult[nresult][k4+1] combination values */
12055: fprintf(ficparo,"result: %s\n",resultline);
12056: fprintf(ficres,"result: %s\n",resultline);
12057: fprintf(ficlog,"result: %s\n",resultline);
1.230 brouard 12058: break;
1.258 brouard 12059: case 14:
1.259 brouard 12060: if(ncovmodel >2 && nresult==0 ){
12061: printf("ERROR: no result lines! It should be at minimum 'result: V2=0 V1=1 or result:.' %s\n",line);
1.258 brouard 12062: goto end;
12063: }
1.259 brouard 12064: break;
1.258 brouard 12065: default:
12066: nresult=1;
12067: decoderesult(".",nresult ); /* No covariate */
12068: }
12069: } /* End switch parameterline */
12070: }while(endishere==0); /* End do */
1.126 brouard 12071:
1.230 brouard 12072: /* freqsummary(fileres, agemin, agemax, s, agev, nlstate, imx,Tvaraff,nbcode, ncodemax,mint,anint); */
1.145 brouard 12073: /* ,dateprev1,dateprev2,jprev1, mprev1,anprev1,jprev2, mprev2,anprev2); */
1.126 brouard 12074:
12075: replace_back_to_slash(pathc,pathcd); /* Even gnuplot wants a / */
1.194 brouard 12076: if(ageminpar == AGEOVERFLOW ||agemaxpar == -AGEOVERFLOW){
1.230 brouard 12077: printf("Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
1.194 brouard 12078: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
12079: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
1.230 brouard 12080: fprintf(ficlog,"Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
1.194 brouard 12081: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
12082: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
1.220 brouard 12083: }else{
1.270 ! brouard 12084: /* printinggnuplot(fileresu, optionfilefiname,ageminpar,agemaxpar,fage, prevfcast, backcast, pathc,p, (int)anproj1-(int)agemin, (int)anback1-(int)agemax+1); */
! 12085: printinggnuplot(fileresu, optionfilefiname,ageminpar,agemaxpar,bage, fage, prevfcast, backcast, pathc,p, (int)anproj1-bage, (int)anback1-fage);
1.220 brouard 12086: }
12087: printinghtml(fileresu,title,datafile, firstpass, lastpass, stepm, weightopt, \
1.258 brouard 12088: model,imx,jmin,jmax,jmean,rfileres,popforecast,mobilav,prevfcast,mobilavproj,backcast, estepm, \
1.225 brouard 12089: jprev1,mprev1,anprev1,dateprev1,jprev2,mprev2,anprev2,dateprev2);
1.220 brouard 12090:
1.225 brouard 12091: /*------------ free_vector -------------*/
12092: /* chdir(path); */
1.220 brouard 12093:
1.215 brouard 12094: /* free_ivector(wav,1,imx); */ /* Moved after last prevalence call */
12095: /* free_imatrix(dh,1,lastpass-firstpass+2,1,imx); */
12096: /* free_imatrix(bh,1,lastpass-firstpass+2,1,imx); */
12097: /* free_imatrix(mw,1,lastpass-firstpass+2,1,imx); */
1.126 brouard 12098: free_lvector(num,1,n);
12099: free_vector(agedc,1,n);
12100: /*free_matrix(covar,0,NCOVMAX,1,n);*/
12101: /*free_matrix(covar,1,NCOVMAX,1,n);*/
12102: fclose(ficparo);
12103: fclose(ficres);
1.220 brouard 12104:
12105:
1.186 brouard 12106: /* Other results (useful)*/
1.220 brouard 12107:
12108:
1.126 brouard 12109: /*--------------- Prevalence limit (period or stable prevalence) --------------*/
1.180 brouard 12110: /*#include "prevlim.h"*/ /* Use ficrespl, ficlog */
12111: prlim=matrix(1,nlstate,1,nlstate);
1.209 brouard 12112: prevalence_limit(p, prlim, ageminpar, agemaxpar, ftolpl, &ncvyear);
1.126 brouard 12113: fclose(ficrespl);
12114:
12115: /*------------- h Pij x at various ages ------------*/
1.180 brouard 12116: /*#include "hpijx.h"*/
12117: hPijx(p, bage, fage);
1.145 brouard 12118: fclose(ficrespij);
1.227 brouard 12119:
1.220 brouard 12120: /* ncovcombmax= pow(2,cptcoveff); */
1.219 brouard 12121: /*-------------- Variance of one-step probabilities---*/
1.145 brouard 12122: k=1;
1.126 brouard 12123: varprob(optionfilefiname, matcov, p, delti, nlstate, bage, fage,k,Tvar,nbcode, ncodemax,strstart);
1.227 brouard 12124:
1.269 brouard 12125: /* Prevalence for each covariate combination in probs[age][status][cov] */
12126: probs= ma3x(AGEINF,AGESUP,1,nlstate+ndeath, 1,ncovcombmax);
12127: for(i=AGEINF;i<=AGESUP;i++)
1.219 brouard 12128: for(j=1;j<=nlstate+ndeath;j++) /* ndeath is useless but a necessity to be compared with mobaverages */
1.225 brouard 12129: for(k=1;k<=ncovcombmax;k++)
12130: probs[i][j][k]=0.;
1.269 brouard 12131: prevalence(probs, ageminpar, agemaxpar, s, agev, nlstate, imx, Tvar, nbcode,
12132: ncodemax, mint, anint, dateprev1, dateprev2, firstpass, lastpass);
1.219 brouard 12133: if (mobilav!=0 ||mobilavproj !=0 ) {
1.269 brouard 12134: mobaverages= ma3x(AGEINF, AGESUP,1,nlstate+ndeath, 1,ncovcombmax);
12135: for(i=AGEINF;i<=AGESUP;i++)
1.268 brouard 12136: for(j=1;j<=nlstate+ndeath;j++)
1.227 brouard 12137: for(k=1;k<=ncovcombmax;k++)
12138: mobaverages[i][j][k]=0.;
1.219 brouard 12139: mobaverage=mobaverages;
12140: if (mobilav!=0) {
1.235 brouard 12141: printf("Movingaveraging observed prevalence\n");
1.258 brouard 12142: fprintf(ficlog,"Movingaveraging observed prevalence\n");
1.227 brouard 12143: if (movingaverage(probs, ageminpar, agemaxpar, mobaverage, mobilav)!=0){
12144: fprintf(ficlog," Error in movingaverage mobilav=%d\n",mobilav);
12145: printf(" Error in movingaverage mobilav=%d\n",mobilav);
12146: }
1.269 brouard 12147: } else if (mobilavproj !=0) {
1.235 brouard 12148: printf("Movingaveraging projected observed prevalence\n");
1.258 brouard 12149: fprintf(ficlog,"Movingaveraging projected observed prevalence\n");
1.227 brouard 12150: if (movingaverage(probs, ageminpar, agemaxpar, mobaverage, mobilavproj)!=0){
12151: fprintf(ficlog," Error in movingaverage mobilavproj=%d\n",mobilavproj);
12152: printf(" Error in movingaverage mobilavproj=%d\n",mobilavproj);
12153: }
1.269 brouard 12154: }else{
12155: printf("Internal error moving average\n");
12156: fflush(stdout);
12157: exit(1);
1.219 brouard 12158: }
12159: }/* end if moving average */
1.227 brouard 12160:
1.126 brouard 12161: /*---------- Forecasting ------------------*/
12162: if(prevfcast==1){
12163: /* if(stepm ==1){*/
1.269 brouard 12164: prevforecast(fileresu, anproj1, mproj1, jproj1, agemin, agemax, dateprev1, dateprev2, mobilavproj, mobaverage, bage, fage, firstpass, lastpass, anproj2, p, cptcoveff);
1.126 brouard 12165: }
1.269 brouard 12166:
12167: /* Backcasting */
1.217 brouard 12168: if(backcast==1){
1.219 brouard 12169: ddnewms=matrix(1,nlstate+ndeath,1,nlstate+ndeath);
12170: ddoldms=matrix(1,nlstate+ndeath,1,nlstate+ndeath);
12171: ddsavms=matrix(1,nlstate+ndeath,1,nlstate+ndeath);
12172:
12173: /*--------------- Back Prevalence limit (period or stable prevalence) --------------*/
12174:
12175: bprlim=matrix(1,nlstate,1,nlstate);
1.269 brouard 12176:
1.219 brouard 12177: back_prevalence_limit(p, bprlim, ageminpar, agemaxpar, ftolpl, &ncvyear, dateprev1, dateprev2, firstpass, lastpass, mobilavproj);
12178: fclose(ficresplb);
12179:
1.222 brouard 12180: hBijx(p, bage, fage, mobaverage);
12181: fclose(ficrespijb);
1.219 brouard 12182:
1.269 brouard 12183: prevbackforecast(fileresu, mobaverage, anback1, mback1, jback1, agemin, agemax, dateprev1, dateprev2,
12184: mobilavproj, bage, fage, firstpass, lastpass, anback2, p, cptcoveff);
12185: varbprlim(fileresu, nresult, mobaverage, mobilavproj, bage, fage, bprlim, &ncvyear, ftolpl, p, matcov, delti, stepm, cptcoveff);
1.268 brouard 12186:
12187:
1.269 brouard 12188: free_matrix(bprlim,1,nlstate,1,nlstate); /*here or after loop ? */
1.219 brouard 12189: free_matrix(ddnewms, 1, nlstate+ndeath, 1, nlstate+ndeath);
12190: free_matrix(ddsavms, 1, nlstate+ndeath, 1, nlstate+ndeath);
12191: free_matrix(ddoldms, 1, nlstate+ndeath, 1, nlstate+ndeath);
1.269 brouard 12192: } /* end Backcasting */
1.268 brouard 12193:
1.186 brouard 12194:
12195: /* ------ Other prevalence ratios------------ */
1.126 brouard 12196:
1.215 brouard 12197: free_ivector(wav,1,imx);
12198: free_imatrix(dh,1,lastpass-firstpass+2,1,imx);
12199: free_imatrix(bh,1,lastpass-firstpass+2,1,imx);
12200: free_imatrix(mw,1,lastpass-firstpass+2,1,imx);
1.218 brouard 12201:
12202:
1.127 brouard 12203: /*---------- Health expectancies, no variances ------------*/
1.218 brouard 12204:
1.201 brouard 12205: strcpy(filerese,"E_");
12206: strcat(filerese,fileresu);
1.126 brouard 12207: if((ficreseij=fopen(filerese,"w"))==NULL) {
12208: printf("Problem with Health Exp. resultfile: %s\n", filerese); exit(0);
12209: fprintf(ficlog,"Problem with Health Exp. resultfile: %s\n", filerese); exit(0);
12210: }
1.208 brouard 12211: printf("Computing Health Expectancies: result on file '%s' ...", filerese);fflush(stdout);
12212: fprintf(ficlog,"Computing Health Expectancies: result on file '%s' ...", filerese);fflush(ficlog);
1.238 brouard 12213:
12214: pstamp(ficreseij);
1.219 brouard 12215:
1.235 brouard 12216: i1=pow(2,cptcoveff); /* Number of combination of dummy covariates */
12217: if (cptcovn < 1){i1=1;}
12218:
12219: for(nres=1; nres <= nresult; nres++) /* For each resultline */
12220: for(k=1; k<=i1;k++){ /* For any combination of dummy covariates, fixed and varying */
1.253 brouard 12221: if(i1 != 1 && TKresult[nres]!= k)
1.235 brouard 12222: continue;
1.219 brouard 12223: fprintf(ficreseij,"\n#****** ");
1.235 brouard 12224: printf("\n#****** ");
1.225 brouard 12225: for(j=1;j<=cptcoveff;j++) {
1.227 brouard 12226: fprintf(ficreseij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
1.235 brouard 12227: printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
12228: }
12229: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
12230: printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
12231: fprintf(ficreseij," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
1.219 brouard 12232: }
12233: fprintf(ficreseij,"******\n");
1.235 brouard 12234: printf("******\n");
1.219 brouard 12235:
12236: eij=ma3x(1,nlstate,1,nlstate,(int) bage, (int) fage);
12237: oldm=oldms;savm=savms;
1.235 brouard 12238: evsij(eij, p, nlstate, stepm, (int) bage, (int)fage, oldm, savm, k, estepm, strstart, nres);
1.127 brouard 12239:
1.219 brouard 12240: free_ma3x(eij,1,nlstate,1,nlstate,(int) bage, (int)fage);
1.127 brouard 12241: }
12242: fclose(ficreseij);
1.208 brouard 12243: printf("done evsij\n");fflush(stdout);
12244: fprintf(ficlog,"done evsij\n");fflush(ficlog);
1.269 brouard 12245:
1.218 brouard 12246:
1.227 brouard 12247: /*---------- State-specific expectancies and variances ------------*/
1.218 brouard 12248:
1.201 brouard 12249: strcpy(filerest,"T_");
12250: strcat(filerest,fileresu);
1.127 brouard 12251: if((ficrest=fopen(filerest,"w"))==NULL) {
12252: printf("Problem with total LE resultfile: %s\n", filerest);goto end;
12253: fprintf(ficlog,"Problem with total LE resultfile: %s\n", filerest);goto end;
12254: }
1.208 brouard 12255: printf("Computing Total Life expectancies with their standard errors: file '%s' ...\n", filerest); fflush(stdout);
12256: fprintf(ficlog,"Computing Total Life expectancies with their standard errors: file '%s' ...\n", filerest); fflush(ficlog);
1.201 brouard 12257: strcpy(fileresstde,"STDE_");
12258: strcat(fileresstde,fileresu);
1.126 brouard 12259: if((ficresstdeij=fopen(fileresstde,"w"))==NULL) {
1.227 brouard 12260: printf("Problem with State specific Exp. and std errors resultfile: %s\n", fileresstde); exit(0);
12261: fprintf(ficlog,"Problem with State specific Exp. and std errors resultfile: %s\n", fileresstde); exit(0);
1.126 brouard 12262: }
1.227 brouard 12263: printf(" Computing State-specific Expectancies and standard errors: result on file '%s' \n", fileresstde);
12264: fprintf(ficlog," Computing State-specific Expectancies and standard errors: result on file '%s' \n", fileresstde);
1.126 brouard 12265:
1.201 brouard 12266: strcpy(filerescve,"CVE_");
12267: strcat(filerescve,fileresu);
1.126 brouard 12268: if((ficrescveij=fopen(filerescve,"w"))==NULL) {
1.227 brouard 12269: printf("Problem with Covar. State-specific Exp. resultfile: %s\n", filerescve); exit(0);
12270: fprintf(ficlog,"Problem with Covar. State-specific Exp. resultfile: %s\n", filerescve); exit(0);
1.126 brouard 12271: }
1.227 brouard 12272: printf(" Computing Covar. of State-specific Expectancies: result on file '%s' \n", filerescve);
12273: fprintf(ficlog," Computing Covar. of State-specific Expectancies: result on file '%s' \n", filerescve);
1.126 brouard 12274:
1.201 brouard 12275: strcpy(fileresv,"V_");
12276: strcat(fileresv,fileresu);
1.126 brouard 12277: if((ficresvij=fopen(fileresv,"w"))==NULL) {
12278: printf("Problem with variance resultfile: %s\n", fileresv);exit(0);
12279: fprintf(ficlog,"Problem with variance resultfile: %s\n", fileresv);exit(0);
12280: }
1.227 brouard 12281: printf(" Computing Variance-covariance of State-specific Expectancies: file '%s' ... ", fileresv);fflush(stdout);
12282: fprintf(ficlog," Computing Variance-covariance of State-specific Expectancies: file '%s' ... ", fileresv);fflush(ficlog);
1.126 brouard 12283:
1.235 brouard 12284: i1=pow(2,cptcoveff); /* Number of combination of dummy covariates */
12285: if (cptcovn < 1){i1=1;}
12286:
12287: for(nres=1; nres <= nresult; nres++) /* For each resultline */
12288: for(k=1; k<=i1;k++){ /* For any combination of dummy covariates, fixed and varying */
1.253 brouard 12289: if(i1 != 1 && TKresult[nres]!= k)
1.235 brouard 12290: continue;
1.242 brouard 12291: printf("\n#****** Result for:");
12292: fprintf(ficrest,"\n#****** Result for:");
12293: fprintf(ficlog,"\n#****** Result for:");
1.227 brouard 12294: for(j=1;j<=cptcoveff;j++){
12295: printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
12296: fprintf(ficrest,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
12297: fprintf(ficlog,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
12298: }
1.235 brouard 12299: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
12300: printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
12301: fprintf(ficrest," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
12302: fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
12303: }
1.208 brouard 12304: fprintf(ficrest,"******\n");
1.227 brouard 12305: fprintf(ficlog,"******\n");
12306: printf("******\n");
1.208 brouard 12307:
12308: fprintf(ficresstdeij,"\n#****** ");
12309: fprintf(ficrescveij,"\n#****** ");
1.225 brouard 12310: for(j=1;j<=cptcoveff;j++) {
1.227 brouard 12311: fprintf(ficresstdeij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
12312: fprintf(ficrescveij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
1.208 brouard 12313: }
1.235 brouard 12314: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
12315: fprintf(ficresstdeij," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
12316: fprintf(ficrescveij," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
12317: }
1.208 brouard 12318: fprintf(ficresstdeij,"******\n");
12319: fprintf(ficrescveij,"******\n");
12320:
12321: fprintf(ficresvij,"\n#****** ");
1.238 brouard 12322: /* pstamp(ficresvij); */
1.225 brouard 12323: for(j=1;j<=cptcoveff;j++)
1.227 brouard 12324: fprintf(ficresvij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
1.235 brouard 12325: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
12326: fprintf(ficresvij," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
12327: }
1.208 brouard 12328: fprintf(ficresvij,"******\n");
12329:
12330: eij=ma3x(1,nlstate,1,nlstate,(int) bage, (int) fage);
12331: oldm=oldms;savm=savms;
1.235 brouard 12332: printf(" cvevsij ");
12333: fprintf(ficlog, " cvevsij ");
12334: cvevsij(eij, p, nlstate, stepm, (int) bage, (int)fage, oldm, savm, k, estepm, delti, matcov, strstart, nres);
1.208 brouard 12335: printf(" end cvevsij \n ");
12336: fprintf(ficlog, " end cvevsij \n ");
12337:
12338: /*
12339: */
12340: /* goto endfree; */
12341:
12342: vareij=ma3x(1,nlstate,1,nlstate,(int) bage, (int) fage);
12343: pstamp(ficrest);
12344:
1.269 brouard 12345: epj=vector(1,nlstate+1);
1.208 brouard 12346: for(vpopbased=0; vpopbased <= popbased; vpopbased++){ /* Done for vpopbased=0 and vpopbased=1 if popbased==1*/
1.227 brouard 12347: oldm=oldms;savm=savms; /* ZZ Segmentation fault */
12348: cptcod= 0; /* To be deleted */
12349: printf("varevsij vpopbased=%d \n",vpopbased);
12350: fprintf(ficlog, "varevsij vpopbased=%d \n",vpopbased);
1.235 brouard 12351: 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 12352: 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 ");
12353: if(vpopbased==1)
12354: 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);
12355: else
12356: fprintf(ficrest,"the age specific period (stable) prevalences in each health state \n");
12357: fprintf(ficrest,"# Age popbased mobilav e.. (std) ");
12358: for (i=1;i<=nlstate;i++) fprintf(ficrest,"e.%d (std) ",i);
12359: fprintf(ficrest,"\n");
12360: /* printf("Which p?\n"); for(i=1;i<=npar;i++)printf("p[i=%d]=%lf,",i,p[i]);printf("\n"); */
12361: printf("Computing age specific period (stable) prevalences in each health state \n");
12362: fprintf(ficlog,"Computing age specific period (stable) prevalences in each health state \n");
12363: for(age=bage; age <=fage ;age++){
1.235 brouard 12364: prevalim(prlim, nlstate, p, age, oldm, savm, ftolpl, &ncvyear, k, nres); /*ZZ Is it the correct prevalim */
1.227 brouard 12365: if (vpopbased==1) {
12366: if(mobilav ==0){
12367: for(i=1; i<=nlstate;i++)
12368: prlim[i][i]=probs[(int)age][i][k];
12369: }else{ /* mobilav */
12370: for(i=1; i<=nlstate;i++)
12371: prlim[i][i]=mobaverage[(int)age][i][k];
12372: }
12373: }
1.219 brouard 12374:
1.227 brouard 12375: fprintf(ficrest," %4.0f %d %d",age, vpopbased, mobilav);
12376: /* fprintf(ficrest," %4.0f %d %d %d %d",age, vpopbased, mobilav,Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]); */ /* to be done */
12377: /* printf(" age %4.0f ",age); */
12378: for(j=1, epj[nlstate+1]=0.;j <=nlstate;j++){
12379: for(i=1, epj[j]=0.;i <=nlstate;i++) {
12380: epj[j] += prlim[i][i]*eij[i][j][(int)age];
12381: /*ZZZ printf("%lf %lf ", prlim[i][i] ,eij[i][j][(int)age]);*/
12382: /* printf("%lf %lf ", prlim[i][i] ,eij[i][j][(int)age]); */
12383: }
12384: epj[nlstate+1] +=epj[j];
12385: }
12386: /* printf(" age %4.0f \n",age); */
1.219 brouard 12387:
1.227 brouard 12388: for(i=1, vepp=0.;i <=nlstate;i++)
12389: for(j=1;j <=nlstate;j++)
12390: vepp += vareij[i][j][(int)age];
12391: fprintf(ficrest," %7.3f (%7.3f)", epj[nlstate+1],sqrt(vepp));
12392: for(j=1;j <=nlstate;j++){
12393: fprintf(ficrest," %7.3f (%7.3f)", epj[j],sqrt(vareij[j][j][(int)age]));
12394: }
12395: fprintf(ficrest,"\n");
12396: }
1.208 brouard 12397: } /* End vpopbased */
1.269 brouard 12398: free_vector(epj,1,nlstate+1);
1.208 brouard 12399: free_ma3x(eij,1,nlstate,1,nlstate,(int) bage, (int)fage);
12400: free_ma3x(vareij,1,nlstate,1,nlstate,(int) bage, (int)fage);
1.235 brouard 12401: printf("done selection\n");fflush(stdout);
12402: fprintf(ficlog,"done selection\n");fflush(ficlog);
1.208 brouard 12403:
1.235 brouard 12404: } /* End k selection */
1.227 brouard 12405:
12406: printf("done State-specific expectancies\n");fflush(stdout);
12407: fprintf(ficlog,"done State-specific expectancies\n");fflush(ficlog);
12408:
1.269 brouard 12409: /* variance-covariance of period prevalence*/
12410: varprlim(fileresu, nresult, mobaverage, mobilavproj, bage, fage, prlim, &ncvyear, ftolpl, p, matcov, delti, stepm, cptcoveff);
1.268 brouard 12411:
1.227 brouard 12412:
12413: free_vector(weight,1,n);
12414: free_imatrix(Tvard,1,NCOVMAX,1,2);
12415: free_imatrix(s,1,maxwav+1,1,n);
12416: free_matrix(anint,1,maxwav,1,n);
12417: free_matrix(mint,1,maxwav,1,n);
12418: free_ivector(cod,1,n);
12419: free_ivector(tab,1,NCOVMAX);
12420: fclose(ficresstdeij);
12421: fclose(ficrescveij);
12422: fclose(ficresvij);
12423: fclose(ficrest);
12424: fclose(ficpar);
12425:
12426:
1.126 brouard 12427: /*---------- End : free ----------------*/
1.219 brouard 12428: if (mobilav!=0 ||mobilavproj !=0)
1.269 brouard 12429: free_ma3x(mobaverages,AGEINF, AGESUP,1,nlstate+ndeath, 1,ncovcombmax); /* We need to have a squared matrix with prevalence of the dead! */
12430: free_ma3x(probs,AGEINF,AGESUP,1,nlstate+ndeath, 1,ncovcombmax);
1.220 brouard 12431: free_matrix(prlim,1,nlstate,1,nlstate); /*here or after loop ? */
12432: free_matrix(pmmij,1,nlstate+ndeath,1,nlstate+ndeath);
1.126 brouard 12433: } /* mle==-3 arrives here for freeing */
1.227 brouard 12434: /* endfree:*/
12435: free_matrix(oldms, 1,nlstate+ndeath,1,nlstate+ndeath);
12436: free_matrix(newms, 1,nlstate+ndeath,1,nlstate+ndeath);
12437: free_matrix(savms, 1,nlstate+ndeath,1,nlstate+ndeath);
1.268 brouard 12438: if(ntv+nqtv>=1)free_ma3x(cotvar,1,maxwav,1,ntv+nqtv,1,n);
12439: if(nqtv>=1)free_ma3x(cotqvar,1,maxwav,1,nqtv,1,n);
12440: if(nqv>=1)free_matrix(coqvar,1,nqv,1,n);
1.227 brouard 12441: free_matrix(covar,0,NCOVMAX,1,n);
12442: free_matrix(matcov,1,npar,1,npar);
12443: free_matrix(hess,1,npar,1,npar);
12444: /*free_vector(delti,1,npar);*/
12445: free_ma3x(delti3,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
12446: free_matrix(agev,1,maxwav,1,imx);
1.269 brouard 12447: free_ma3x(paramstart,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
1.227 brouard 12448: free_ma3x(param,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
12449:
12450: free_ivector(ncodemax,1,NCOVMAX);
12451: free_ivector(ncodemaxwundef,1,NCOVMAX);
12452: free_ivector(Dummy,-1,NCOVMAX);
12453: free_ivector(Fixed,-1,NCOVMAX);
1.238 brouard 12454: free_ivector(DummyV,1,NCOVMAX);
12455: free_ivector(FixedV,1,NCOVMAX);
1.227 brouard 12456: free_ivector(Typevar,-1,NCOVMAX);
12457: free_ivector(Tvar,1,NCOVMAX);
1.234 brouard 12458: free_ivector(TvarsQ,1,NCOVMAX);
12459: free_ivector(TvarsQind,1,NCOVMAX);
12460: free_ivector(TvarsD,1,NCOVMAX);
12461: free_ivector(TvarsDind,1,NCOVMAX);
1.231 brouard 12462: free_ivector(TvarFD,1,NCOVMAX);
12463: free_ivector(TvarFDind,1,NCOVMAX);
1.232 brouard 12464: free_ivector(TvarF,1,NCOVMAX);
12465: free_ivector(TvarFind,1,NCOVMAX);
12466: free_ivector(TvarV,1,NCOVMAX);
12467: free_ivector(TvarVind,1,NCOVMAX);
12468: free_ivector(TvarA,1,NCOVMAX);
12469: free_ivector(TvarAind,1,NCOVMAX);
1.231 brouard 12470: free_ivector(TvarFQ,1,NCOVMAX);
12471: free_ivector(TvarFQind,1,NCOVMAX);
12472: free_ivector(TvarVD,1,NCOVMAX);
12473: free_ivector(TvarVDind,1,NCOVMAX);
12474: free_ivector(TvarVQ,1,NCOVMAX);
12475: free_ivector(TvarVQind,1,NCOVMAX);
1.230 brouard 12476: free_ivector(Tvarsel,1,NCOVMAX);
12477: free_vector(Tvalsel,1,NCOVMAX);
1.227 brouard 12478: free_ivector(Tposprod,1,NCOVMAX);
12479: free_ivector(Tprod,1,NCOVMAX);
12480: free_ivector(Tvaraff,1,NCOVMAX);
12481: free_ivector(invalidvarcomb,1,ncovcombmax);
12482: free_ivector(Tage,1,NCOVMAX);
12483: free_ivector(Tmodelind,1,NCOVMAX);
1.228 brouard 12484: free_ivector(TmodelInvind,1,NCOVMAX);
12485: free_ivector(TmodelInvQind,1,NCOVMAX);
1.227 brouard 12486:
12487: free_imatrix(nbcode,0,NCOVMAX,0,NCOVMAX);
12488: /* free_imatrix(codtab,1,100,1,10); */
1.126 brouard 12489: fflush(fichtm);
12490: fflush(ficgp);
12491:
1.227 brouard 12492:
1.126 brouard 12493: if((nberr >0) || (nbwarn>0)){
1.216 brouard 12494: printf("End of Imach with %d errors and/or %d warnings. Please look at the log file for details.\n",nberr,nbwarn);
12495: 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 12496: }else{
12497: printf("End of Imach\n");
12498: fprintf(ficlog,"End of Imach\n");
12499: }
12500: printf("See log file on %s\n",filelog);
12501: /* gettimeofday(&end_time, (struct timezone*)0);*/ /* after time */
1.157 brouard 12502: /*(void) gettimeofday(&end_time,&tzp);*/
12503: rend_time = time(NULL);
12504: end_time = *localtime(&rend_time);
12505: /* tml = *localtime(&end_time.tm_sec); */
12506: strcpy(strtend,asctime(&end_time));
1.126 brouard 12507: printf("Local time at start %s\nLocal time at end %s",strstart, strtend);
12508: fprintf(ficlog,"Local time at start %s\nLocal time at end %s\n",strstart, strtend);
1.157 brouard 12509: printf("Total time used %s\n", asc_diff_time(rend_time -rstart_time,tmpout));
1.227 brouard 12510:
1.157 brouard 12511: printf("Total time was %.0lf Sec.\n", difftime(rend_time,rstart_time));
12512: fprintf(ficlog,"Total time used %s\n", asc_diff_time(rend_time -rstart_time,tmpout));
12513: fprintf(ficlog,"Total time was %.0lf Sec.\n", difftime(rend_time,rstart_time));
1.126 brouard 12514: /* printf("Total time was %d uSec.\n", total_usecs);*/
12515: /* if(fileappend(fichtm,optionfilehtm)){ */
12516: fprintf(fichtm,"<br>Local time at start %s<br>Local time at end %s<br>\n</body></html>",strstart, strtend);
12517: fclose(fichtm);
12518: fprintf(fichtmcov,"<br>Local time at start %s<br>Local time at end %s<br>\n</body></html>",strstart, strtend);
12519: fclose(fichtmcov);
12520: fclose(ficgp);
12521: fclose(ficlog);
12522: /*------ End -----------*/
1.227 brouard 12523:
12524:
12525: printf("Before Current directory %s!\n",pathcd);
1.184 brouard 12526: #ifdef WIN32
1.227 brouard 12527: if (_chdir(pathcd) != 0)
12528: printf("Can't move to directory %s!\n",path);
12529: if(_getcwd(pathcd,MAXLINE) > 0)
1.184 brouard 12530: #else
1.227 brouard 12531: if(chdir(pathcd) != 0)
12532: printf("Can't move to directory %s!\n", path);
12533: if (getcwd(pathcd, MAXLINE) > 0)
1.184 brouard 12534: #endif
1.126 brouard 12535: printf("Current directory %s!\n",pathcd);
12536: /*strcat(plotcmd,CHARSEPARATOR);*/
12537: sprintf(plotcmd,"gnuplot");
1.157 brouard 12538: #ifdef _WIN32
1.126 brouard 12539: sprintf(plotcmd,"\"%sgnuplot.exe\"",pathimach);
12540: #endif
12541: if(!stat(plotcmd,&info)){
1.158 brouard 12542: printf("Error or gnuplot program not found: '%s'\n",plotcmd);fflush(stdout);
1.126 brouard 12543: if(!stat(getenv("GNUPLOTBIN"),&info)){
1.158 brouard 12544: printf("Error or gnuplot program not found: '%s' Environment GNUPLOTBIN not set.\n",plotcmd);fflush(stdout);
1.126 brouard 12545: }else
12546: strcpy(pplotcmd,plotcmd);
1.157 brouard 12547: #ifdef __unix
1.126 brouard 12548: strcpy(plotcmd,GNUPLOTPROGRAM);
12549: if(!stat(plotcmd,&info)){
1.158 brouard 12550: printf("Error gnuplot program not found: '%s'\n",plotcmd);fflush(stdout);
1.126 brouard 12551: }else
12552: strcpy(pplotcmd,plotcmd);
12553: #endif
12554: }else
12555: strcpy(pplotcmd,plotcmd);
12556:
12557: sprintf(plotcmd,"%s %s",pplotcmd, optionfilegnuplot);
1.158 brouard 12558: printf("Starting graphs with: '%s'\n",plotcmd);fflush(stdout);
1.227 brouard 12559:
1.126 brouard 12560: if((outcmd=system(plotcmd)) != 0){
1.158 brouard 12561: printf("gnuplot command might not be in your path: '%s', err=%d\n", plotcmd, outcmd);
1.154 brouard 12562: printf("\n Trying if gnuplot resides on the same directory that IMaCh\n");
1.152 brouard 12563: sprintf(plotcmd,"%sgnuplot %s", pathimach, optionfilegnuplot);
1.150 brouard 12564: if((outcmd=system(plotcmd)) != 0)
1.153 brouard 12565: printf("\n Still a problem with gnuplot command %s, err=%d\n", plotcmd, outcmd);
1.126 brouard 12566: }
1.158 brouard 12567: printf(" Successful, please wait...");
1.126 brouard 12568: while (z[0] != 'q') {
12569: /* chdir(path); */
1.154 brouard 12570: printf("\nType e to edit results with your browser, g to graph again and q for exit: ");
1.126 brouard 12571: scanf("%s",z);
12572: /* if (z[0] == 'c') system("./imach"); */
12573: if (z[0] == 'e') {
1.158 brouard 12574: #ifdef __APPLE__
1.152 brouard 12575: sprintf(pplotcmd, "open %s", optionfilehtm);
1.157 brouard 12576: #elif __linux
12577: sprintf(pplotcmd, "xdg-open %s", optionfilehtm);
1.153 brouard 12578: #else
1.152 brouard 12579: sprintf(pplotcmd, "%s", optionfilehtm);
1.153 brouard 12580: #endif
12581: printf("Starting browser with: %s",pplotcmd);fflush(stdout);
12582: system(pplotcmd);
1.126 brouard 12583: }
12584: else if (z[0] == 'g') system(plotcmd);
12585: else if (z[0] == 'q') exit(0);
12586: }
1.227 brouard 12587: end:
1.126 brouard 12588: while (z[0] != 'q') {
1.195 brouard 12589: printf("\nType q for exiting: "); fflush(stdout);
1.126 brouard 12590: scanf("%s",z);
12591: }
12592: }
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