Annotation of imach/src/imach.c, revision 1.269
1.269 ! brouard 1: /* $Id: imach.c,v 1.268 2017/05/18 20:09:32 brouard Exp $
1.126 brouard 2: $State: Exp $
1.163 brouard 3: $Log: imach.c,v $
1.269 ! brouard 4: Revision 1.268 2017/05/18 20:09:32 brouard
! 5: Summary: backprojection and confidence intervals of backprevalence
! 6:
1.268 brouard 7: Revision 1.267 2017/05/13 10:25:05 brouard
8: Summary: temporary save for backprojection
9:
1.267 brouard 10: Revision 1.266 2017/05/13 07:26:12 brouard
11: Summary: Version 0.99r13 (improvements and bugs fixed)
12:
1.266 brouard 13: Revision 1.265 2017/04/26 16:22:11 brouard
14: Summary: imach 0.99r13 Some bugs fixed
15:
1.265 brouard 16: Revision 1.264 2017/04/26 06:01:29 brouard
17: Summary: Labels in graphs
18:
1.264 brouard 19: Revision 1.263 2017/04/24 15:23:15 brouard
20: Summary: to save
21:
1.263 brouard 22: Revision 1.262 2017/04/18 16:48:12 brouard
23: *** empty log message ***
24:
1.262 brouard 25: Revision 1.261 2017/04/05 10:14:09 brouard
26: Summary: Bug in E_ as well as in T_ fixed nres-1 vs k1-1
27:
1.261 brouard 28: Revision 1.260 2017/04/04 17:46:59 brouard
29: Summary: Gnuplot indexations fixed (humm)
30:
1.260 brouard 31: Revision 1.259 2017/04/04 13:01:16 brouard
32: Summary: Some errors to warnings only if date of death is unknown but status is death we could set to pi3
33:
1.259 brouard 34: Revision 1.258 2017/04/03 10:17:47 brouard
35: Summary: Version 0.99r12
36:
37: Some cleanings, conformed with updated documentation.
38:
1.258 brouard 39: Revision 1.257 2017/03/29 16:53:30 brouard
40: Summary: Temp
41:
1.257 brouard 42: Revision 1.256 2017/03/27 05:50:23 brouard
43: Summary: Temporary
44:
1.256 brouard 45: Revision 1.255 2017/03/08 16:02:28 brouard
46: Summary: IMaCh version 0.99r10 bugs in gnuplot fixed
47:
1.255 brouard 48: Revision 1.254 2017/03/08 07:13:00 brouard
49: Summary: Fixing data parameter line
50:
1.254 brouard 51: Revision 1.253 2016/12/15 11:59:41 brouard
52: Summary: 0.99 in progress
53:
1.253 brouard 54: Revision 1.252 2016/09/15 21:15:37 brouard
55: *** empty log message ***
56:
1.252 brouard 57: Revision 1.251 2016/09/15 15:01:13 brouard
58: Summary: not working
59:
1.251 brouard 60: Revision 1.250 2016/09/08 16:07:27 brouard
61: Summary: continue
62:
1.250 brouard 63: Revision 1.249 2016/09/07 17:14:18 brouard
64: Summary: Starting values from frequencies
65:
1.249 brouard 66: Revision 1.248 2016/09/07 14:10:18 brouard
67: *** empty log message ***
68:
1.248 brouard 69: Revision 1.247 2016/09/02 11:11:21 brouard
70: *** empty log message ***
71:
1.247 brouard 72: Revision 1.246 2016/09/02 08:49:22 brouard
73: *** empty log message ***
74:
1.246 brouard 75: Revision 1.245 2016/09/02 07:25:01 brouard
76: *** empty log message ***
77:
1.245 brouard 78: Revision 1.244 2016/09/02 07:17:34 brouard
79: *** empty log message ***
80:
1.244 brouard 81: Revision 1.243 2016/09/02 06:45:35 brouard
82: *** empty log message ***
83:
1.243 brouard 84: Revision 1.242 2016/08/30 15:01:20 brouard
85: Summary: Fixing a lots
86:
1.242 brouard 87: Revision 1.241 2016/08/29 17:17:25 brouard
88: Summary: gnuplot problem in Back projection to fix
89:
1.241 brouard 90: Revision 1.240 2016/08/29 07:53:18 brouard
91: Summary: Better
92:
1.240 brouard 93: Revision 1.239 2016/08/26 15:51:03 brouard
94: Summary: Improvement in Powell output in order to copy and paste
95:
96: Author:
97:
1.239 brouard 98: Revision 1.238 2016/08/26 14:23:35 brouard
99: Summary: Starting tests of 0.99
100:
1.238 brouard 101: Revision 1.237 2016/08/26 09:20:19 brouard
102: Summary: to valgrind
103:
1.237 brouard 104: Revision 1.236 2016/08/25 10:50:18 brouard
105: *** empty log message ***
106:
1.236 brouard 107: Revision 1.235 2016/08/25 06:59:23 brouard
108: *** empty log message ***
109:
1.235 brouard 110: Revision 1.234 2016/08/23 16:51:20 brouard
111: *** empty log message ***
112:
1.234 brouard 113: Revision 1.233 2016/08/23 07:40:50 brouard
114: Summary: not working
115:
1.233 brouard 116: Revision 1.232 2016/08/22 14:20:21 brouard
117: Summary: not working
118:
1.232 brouard 119: Revision 1.231 2016/08/22 07:17:15 brouard
120: Summary: not working
121:
1.231 brouard 122: Revision 1.230 2016/08/22 06:55:53 brouard
123: Summary: Not working
124:
1.230 brouard 125: Revision 1.229 2016/07/23 09:45:53 brouard
126: Summary: Completing for func too
127:
1.229 brouard 128: Revision 1.228 2016/07/22 17:45:30 brouard
129: Summary: Fixing some arrays, still debugging
130:
1.227 brouard 131: Revision 1.226 2016/07/12 18:42:34 brouard
132: Summary: temp
133:
1.226 brouard 134: Revision 1.225 2016/07/12 08:40:03 brouard
135: Summary: saving but not running
136:
1.225 brouard 137: Revision 1.224 2016/07/01 13:16:01 brouard
138: Summary: Fixes
139:
1.224 brouard 140: Revision 1.223 2016/02/19 09:23:35 brouard
141: Summary: temporary
142:
1.223 brouard 143: Revision 1.222 2016/02/17 08:14:50 brouard
144: Summary: Probably last 0.98 stable version 0.98r6
145:
1.222 brouard 146: Revision 1.221 2016/02/15 23:35:36 brouard
147: Summary: minor bug
148:
1.220 brouard 149: Revision 1.219 2016/02/15 00:48:12 brouard
150: *** empty log message ***
151:
1.219 brouard 152: Revision 1.218 2016/02/12 11:29:23 brouard
153: Summary: 0.99 Back projections
154:
1.218 brouard 155: Revision 1.217 2015/12/23 17:18:31 brouard
156: Summary: Experimental backcast
157:
1.217 brouard 158: Revision 1.216 2015/12/18 17:32:11 brouard
159: Summary: 0.98r4 Warning and status=-2
160:
161: Version 0.98r4 is now:
162: - displaying an error when status is -1, date of interview unknown and date of death known;
163: - permitting a status -2 when the vital status is unknown at a known date of right truncation.
164: Older changes concerning s=-2, dating from 2005 have been supersed.
165:
1.216 brouard 166: Revision 1.215 2015/12/16 08:52:24 brouard
167: Summary: 0.98r4 working
168:
1.215 brouard 169: Revision 1.214 2015/12/16 06:57:54 brouard
170: Summary: temporary not working
171:
1.214 brouard 172: Revision 1.213 2015/12/11 18:22:17 brouard
173: Summary: 0.98r4
174:
1.213 brouard 175: Revision 1.212 2015/11/21 12:47:24 brouard
176: Summary: minor typo
177:
1.212 brouard 178: Revision 1.211 2015/11/21 12:41:11 brouard
179: Summary: 0.98r3 with some graph of projected cross-sectional
180:
181: Author: Nicolas Brouard
182:
1.211 brouard 183: Revision 1.210 2015/11/18 17:41:20 brouard
1.252 brouard 184: Summary: Start working on projected prevalences Revision 1.209 2015/11/17 22:12:03 brouard
1.210 brouard 185: Summary: Adding ftolpl parameter
186: Author: N Brouard
187:
188: We had difficulties to get smoothed confidence intervals. It was due
189: to the period prevalence which wasn't computed accurately. The inner
190: parameter ftolpl is now an outer parameter of the .imach parameter
191: file after estepm. If ftolpl is small 1.e-4 and estepm too,
192: computation are long.
193:
1.209 brouard 194: Revision 1.208 2015/11/17 14:31:57 brouard
195: Summary: temporary
196:
1.208 brouard 197: Revision 1.207 2015/10/27 17:36:57 brouard
198: *** empty log message ***
199:
1.207 brouard 200: Revision 1.206 2015/10/24 07:14:11 brouard
201: *** empty log message ***
202:
1.206 brouard 203: Revision 1.205 2015/10/23 15:50:53 brouard
204: Summary: 0.98r3 some clarification for graphs on likelihood contributions
205:
1.205 brouard 206: Revision 1.204 2015/10/01 16:20:26 brouard
207: Summary: Some new graphs of contribution to likelihood
208:
1.204 brouard 209: Revision 1.203 2015/09/30 17:45:14 brouard
210: Summary: looking at better estimation of the hessian
211:
212: Also a better criteria for convergence to the period prevalence And
213: therefore adding the number of years needed to converge. (The
214: prevalence in any alive state shold sum to one
215:
1.203 brouard 216: Revision 1.202 2015/09/22 19:45:16 brouard
217: Summary: Adding some overall graph on contribution to likelihood. Might change
218:
1.202 brouard 219: Revision 1.201 2015/09/15 17:34:58 brouard
220: Summary: 0.98r0
221:
222: - Some new graphs like suvival functions
223: - Some bugs fixed like model=1+age+V2.
224:
1.201 brouard 225: Revision 1.200 2015/09/09 16:53:55 brouard
226: Summary: Big bug thanks to Flavia
227:
228: Even model=1+age+V2. did not work anymore
229:
1.200 brouard 230: Revision 1.199 2015/09/07 14:09:23 brouard
231: Summary: 0.98q6 changing default small png format for graph to vectorized svg.
232:
1.199 brouard 233: Revision 1.198 2015/09/03 07:14:39 brouard
234: Summary: 0.98q5 Flavia
235:
1.198 brouard 236: Revision 1.197 2015/09/01 18:24:39 brouard
237: *** empty log message ***
238:
1.197 brouard 239: Revision 1.196 2015/08/18 23:17:52 brouard
240: Summary: 0.98q5
241:
1.196 brouard 242: Revision 1.195 2015/08/18 16:28:39 brouard
243: Summary: Adding a hack for testing purpose
244:
245: After reading the title, ftol and model lines, if the comment line has
246: a q, starting with #q, the answer at the end of the run is quit. It
247: permits to run test files in batch with ctest. The former workaround was
248: $ echo q | imach foo.imach
249:
1.195 brouard 250: Revision 1.194 2015/08/18 13:32:00 brouard
251: Summary: Adding error when the covariance matrix doesn't contain the exact number of lines required by the model line.
252:
1.194 brouard 253: Revision 1.193 2015/08/04 07:17:42 brouard
254: Summary: 0.98q4
255:
1.193 brouard 256: Revision 1.192 2015/07/16 16:49:02 brouard
257: Summary: Fixing some outputs
258:
1.192 brouard 259: Revision 1.191 2015/07/14 10:00:33 brouard
260: Summary: Some fixes
261:
1.191 brouard 262: Revision 1.190 2015/05/05 08:51:13 brouard
263: Summary: Adding digits in output parameters (7 digits instead of 6)
264:
265: Fix 1+age+.
266:
1.190 brouard 267: Revision 1.189 2015/04/30 14:45:16 brouard
268: Summary: 0.98q2
269:
1.189 brouard 270: Revision 1.188 2015/04/30 08:27:53 brouard
271: *** empty log message ***
272:
1.188 brouard 273: Revision 1.187 2015/04/29 09:11:15 brouard
274: *** empty log message ***
275:
1.187 brouard 276: Revision 1.186 2015/04/23 12:01:52 brouard
277: Summary: V1*age is working now, version 0.98q1
278:
279: Some codes had been disabled in order to simplify and Vn*age was
280: working in the optimization phase, ie, giving correct MLE parameters,
281: but, as usual, outputs were not correct and program core dumped.
282:
1.186 brouard 283: Revision 1.185 2015/03/11 13:26:42 brouard
284: Summary: Inclusion of compile and links command line for Intel Compiler
285:
1.185 brouard 286: Revision 1.184 2015/03/11 11:52:39 brouard
287: Summary: Back from Windows 8. Intel Compiler
288:
1.184 brouard 289: Revision 1.183 2015/03/10 20:34:32 brouard
290: Summary: 0.98q0, trying with directest, mnbrak fixed
291:
292: We use directest instead of original Powell test; probably no
293: incidence on the results, but better justifications;
294: We fixed Numerical Recipes mnbrak routine which was wrong and gave
295: wrong results.
296:
1.183 brouard 297: Revision 1.182 2015/02/12 08:19:57 brouard
298: Summary: Trying to keep directest which seems simpler and more general
299: Author: Nicolas Brouard
300:
1.182 brouard 301: Revision 1.181 2015/02/11 23:22:24 brouard
302: Summary: Comments on Powell added
303:
304: Author:
305:
1.181 brouard 306: Revision 1.180 2015/02/11 17:33:45 brouard
307: Summary: Finishing move from main to function (hpijx and prevalence_limit)
308:
1.180 brouard 309: Revision 1.179 2015/01/04 09:57:06 brouard
310: Summary: back to OS/X
311:
1.179 brouard 312: Revision 1.178 2015/01/04 09:35:48 brouard
313: *** empty log message ***
314:
1.178 brouard 315: Revision 1.177 2015/01/03 18:40:56 brouard
316: Summary: Still testing ilc32 on OSX
317:
1.177 brouard 318: Revision 1.176 2015/01/03 16:45:04 brouard
319: *** empty log message ***
320:
1.176 brouard 321: Revision 1.175 2015/01/03 16:33:42 brouard
322: *** empty log message ***
323:
1.175 brouard 324: Revision 1.174 2015/01/03 16:15:49 brouard
325: Summary: Still in cross-compilation
326:
1.174 brouard 327: Revision 1.173 2015/01/03 12:06:26 brouard
328: Summary: trying to detect cross-compilation
329:
1.173 brouard 330: Revision 1.172 2014/12/27 12:07:47 brouard
331: Summary: Back from Visual Studio and Intel, options for compiling for Windows XP
332:
1.172 brouard 333: Revision 1.171 2014/12/23 13:26:59 brouard
334: Summary: Back from Visual C
335:
336: Still problem with utsname.h on Windows
337:
1.171 brouard 338: Revision 1.170 2014/12/23 11:17:12 brouard
339: Summary: Cleaning some \%% back to %%
340:
341: The escape was mandatory for a specific compiler (which one?), but too many warnings.
342:
1.170 brouard 343: Revision 1.169 2014/12/22 23:08:31 brouard
344: Summary: 0.98p
345:
346: Outputs some informations on compiler used, OS etc. Testing on different platforms.
347:
1.169 brouard 348: Revision 1.168 2014/12/22 15:17:42 brouard
1.170 brouard 349: Summary: update
1.169 brouard 350:
1.168 brouard 351: Revision 1.167 2014/12/22 13:50:56 brouard
352: Summary: Testing uname and compiler version and if compiled 32 or 64
353:
354: Testing on Linux 64
355:
1.167 brouard 356: Revision 1.166 2014/12/22 11:40:47 brouard
357: *** empty log message ***
358:
1.166 brouard 359: Revision 1.165 2014/12/16 11:20:36 brouard
360: Summary: After compiling on Visual C
361:
362: * imach.c (Module): Merging 1.61 to 1.162
363:
1.165 brouard 364: Revision 1.164 2014/12/16 10:52:11 brouard
365: Summary: Merging with Visual C after suppressing some warnings for unused variables. Also fixing Saito's bug 0.98Xn
366:
367: * imach.c (Module): Merging 1.61 to 1.162
368:
1.164 brouard 369: Revision 1.163 2014/12/16 10:30:11 brouard
370: * imach.c (Module): Merging 1.61 to 1.162
371:
1.163 brouard 372: Revision 1.162 2014/09/25 11:43:39 brouard
373: Summary: temporary backup 0.99!
374:
1.162 brouard 375: Revision 1.1 2014/09/16 11:06:58 brouard
376: Summary: With some code (wrong) for nlopt
377:
378: Author:
379:
380: Revision 1.161 2014/09/15 20:41:41 brouard
381: Summary: Problem with macro SQR on Intel compiler
382:
1.161 brouard 383: Revision 1.160 2014/09/02 09:24:05 brouard
384: *** empty log message ***
385:
1.160 brouard 386: Revision 1.159 2014/09/01 10:34:10 brouard
387: Summary: WIN32
388: Author: Brouard
389:
1.159 brouard 390: Revision 1.158 2014/08/27 17:11:51 brouard
391: *** empty log message ***
392:
1.158 brouard 393: Revision 1.157 2014/08/27 16:26:55 brouard
394: Summary: Preparing windows Visual studio version
395: Author: Brouard
396:
397: In order to compile on Visual studio, time.h is now correct and time_t
398: and tm struct should be used. difftime should be used but sometimes I
399: just make the differences in raw time format (time(&now).
400: Trying to suppress #ifdef LINUX
401: Add xdg-open for __linux in order to open default browser.
402:
1.157 brouard 403: Revision 1.156 2014/08/25 20:10:10 brouard
404: *** empty log message ***
405:
1.156 brouard 406: Revision 1.155 2014/08/25 18:32:34 brouard
407: Summary: New compile, minor changes
408: Author: Brouard
409:
1.155 brouard 410: Revision 1.154 2014/06/20 17:32:08 brouard
411: Summary: Outputs now all graphs of convergence to period prevalence
412:
1.154 brouard 413: Revision 1.153 2014/06/20 16:45:46 brouard
414: Summary: If 3 live state, convergence to period prevalence on same graph
415: Author: Brouard
416:
1.153 brouard 417: Revision 1.152 2014/06/18 17:54:09 brouard
418: Summary: open browser, use gnuplot on same dir than imach if not found in the path
419:
1.152 brouard 420: Revision 1.151 2014/06/18 16:43:30 brouard
421: *** empty log message ***
422:
1.151 brouard 423: Revision 1.150 2014/06/18 16:42:35 brouard
424: Summary: If gnuplot is not in the path try on same directory than imach binary (OSX)
425: Author: brouard
426:
1.150 brouard 427: Revision 1.149 2014/06/18 15:51:14 brouard
428: Summary: Some fixes in parameter files errors
429: Author: Nicolas Brouard
430:
1.149 brouard 431: Revision 1.148 2014/06/17 17:38:48 brouard
432: Summary: Nothing new
433: Author: Brouard
434:
435: Just a new packaging for OS/X version 0.98nS
436:
1.148 brouard 437: Revision 1.147 2014/06/16 10:33:11 brouard
438: *** empty log message ***
439:
1.147 brouard 440: Revision 1.146 2014/06/16 10:20:28 brouard
441: Summary: Merge
442: Author: Brouard
443:
444: Merge, before building revised version.
445:
1.146 brouard 446: Revision 1.145 2014/06/10 21:23:15 brouard
447: Summary: Debugging with valgrind
448: Author: Nicolas Brouard
449:
450: Lot of changes in order to output the results with some covariates
451: After the Edimburgh REVES conference 2014, it seems mandatory to
452: improve the code.
453: No more memory valgrind error but a lot has to be done in order to
454: continue the work of splitting the code into subroutines.
455: Also, decodemodel has been improved. Tricode is still not
456: optimal. nbcode should be improved. Documentation has been added in
457: the source code.
458:
1.144 brouard 459: Revision 1.143 2014/01/26 09:45:38 brouard
460: Summary: Version 0.98nR (to be improved, but gives same optimization results as 0.98k. Nice, promising
461:
462: * imach.c (Module): Trying to merge old staffs together while being at Tokyo. Not tested...
463: (Module): Version 0.98nR Running ok, but output format still only works for three covariates.
464:
1.143 brouard 465: Revision 1.142 2014/01/26 03:57:36 brouard
466: Summary: gnuplot changed plot w l 1 has to be changed to plot w l lt 2
467:
468: * imach.c (Module): Trying to merge old staffs together while being at Tokyo. Not tested...
469:
1.142 brouard 470: Revision 1.141 2014/01/26 02:42:01 brouard
471: * imach.c (Module): Trying to merge old staffs together while being at Tokyo. Not tested...
472:
1.141 brouard 473: Revision 1.140 2011/09/02 10:37:54 brouard
474: Summary: times.h is ok with mingw32 now.
475:
1.140 brouard 476: Revision 1.139 2010/06/14 07:50:17 brouard
477: After the theft of my laptop, I probably lost some lines of codes which were not uploaded to the CVS tree.
478: I remember having already fixed agemin agemax which are pointers now but not cvs saved.
479:
1.139 brouard 480: Revision 1.138 2010/04/30 18:19:40 brouard
481: *** empty log message ***
482:
1.138 brouard 483: Revision 1.137 2010/04/29 18:11:38 brouard
484: (Module): Checking covariates for more complex models
485: than V1+V2. A lot of change to be done. Unstable.
486:
1.137 brouard 487: Revision 1.136 2010/04/26 20:30:53 brouard
488: (Module): merging some libgsl code. Fixing computation
489: of likelione (using inter/intrapolation if mle = 0) in order to
490: get same likelihood as if mle=1.
491: Some cleaning of code and comments added.
492:
1.136 brouard 493: Revision 1.135 2009/10/29 15:33:14 brouard
494: (Module): Now imach stops if date of birth, at least year of birth, is not given. Some cleaning of the code.
495:
1.135 brouard 496: Revision 1.134 2009/10/29 13:18:53 brouard
497: (Module): Now imach stops if date of birth, at least year of birth, is not given. Some cleaning of the code.
498:
1.134 brouard 499: Revision 1.133 2009/07/06 10:21:25 brouard
500: just nforces
501:
1.133 brouard 502: Revision 1.132 2009/07/06 08:22:05 brouard
503: Many tings
504:
1.132 brouard 505: Revision 1.131 2009/06/20 16:22:47 brouard
506: Some dimensions resccaled
507:
1.131 brouard 508: Revision 1.130 2009/05/26 06:44:34 brouard
509: (Module): Max Covariate is now set to 20 instead of 8. A
510: lot of cleaning with variables initialized to 0. Trying to make
511: V2+V3*age+V1+V4 strb=V3*age+V1+V4 working better.
512:
1.130 brouard 513: Revision 1.129 2007/08/31 13:49:27 lievre
514: Modification of the way of exiting when the covariate is not binary in order to see on the window the error message before exiting
515:
1.129 lievre 516: Revision 1.128 2006/06/30 13:02:05 brouard
517: (Module): Clarifications on computing e.j
518:
1.128 brouard 519: Revision 1.127 2006/04/28 18:11:50 brouard
520: (Module): Yes the sum of survivors was wrong since
521: imach-114 because nhstepm was no more computed in the age
522: loop. Now we define nhstepma in the age loop.
523: (Module): In order to speed up (in case of numerous covariates) we
524: compute health expectancies (without variances) in a first step
525: and then all the health expectancies with variances or standard
526: deviation (needs data from the Hessian matrices) which slows the
527: computation.
528: In the future we should be able to stop the program is only health
529: expectancies and graph are needed without standard deviations.
530:
1.127 brouard 531: Revision 1.126 2006/04/28 17:23:28 brouard
532: (Module): Yes the sum of survivors was wrong since
533: imach-114 because nhstepm was no more computed in the age
534: loop. Now we define nhstepma in the age loop.
535: Version 0.98h
536:
1.126 brouard 537: Revision 1.125 2006/04/04 15:20:31 lievre
538: Errors in calculation of health expectancies. Age was not initialized.
539: Forecasting file added.
540:
541: Revision 1.124 2006/03/22 17:13:53 lievre
542: Parameters are printed with %lf instead of %f (more numbers after the comma).
543: The log-likelihood is printed in the log file
544:
545: Revision 1.123 2006/03/20 10:52:43 brouard
546: * imach.c (Module): <title> changed, corresponds to .htm file
547: name. <head> headers where missing.
548:
549: * imach.c (Module): Weights can have a decimal point as for
550: English (a comma might work with a correct LC_NUMERIC environment,
551: otherwise the weight is truncated).
552: Modification of warning when the covariates values are not 0 or
553: 1.
554: Version 0.98g
555:
556: Revision 1.122 2006/03/20 09:45:41 brouard
557: (Module): Weights can have a decimal point as for
558: English (a comma might work with a correct LC_NUMERIC environment,
559: otherwise the weight is truncated).
560: Modification of warning when the covariates values are not 0 or
561: 1.
562: Version 0.98g
563:
564: Revision 1.121 2006/03/16 17:45:01 lievre
565: * imach.c (Module): Comments concerning covariates added
566:
567: * imach.c (Module): refinements in the computation of lli if
568: status=-2 in order to have more reliable computation if stepm is
569: not 1 month. Version 0.98f
570:
571: Revision 1.120 2006/03/16 15:10:38 lievre
572: (Module): refinements in the computation of lli if
573: status=-2 in order to have more reliable computation if stepm is
574: not 1 month. Version 0.98f
575:
576: Revision 1.119 2006/03/15 17:42:26 brouard
577: (Module): Bug if status = -2, the loglikelihood was
578: computed as likelihood omitting the logarithm. Version O.98e
579:
580: Revision 1.118 2006/03/14 18:20:07 brouard
581: (Module): varevsij Comments added explaining the second
582: table of variances if popbased=1 .
583: (Module): Covariances of eij, ekl added, graphs fixed, new html link.
584: (Module): Function pstamp added
585: (Module): Version 0.98d
586:
587: Revision 1.117 2006/03/14 17:16:22 brouard
588: (Module): varevsij Comments added explaining the second
589: table of variances if popbased=1 .
590: (Module): Covariances of eij, ekl added, graphs fixed, new html link.
591: (Module): Function pstamp added
592: (Module): Version 0.98d
593:
594: Revision 1.116 2006/03/06 10:29:27 brouard
595: (Module): Variance-covariance wrong links and
596: varian-covariance of ej. is needed (Saito).
597:
598: Revision 1.115 2006/02/27 12:17:45 brouard
599: (Module): One freematrix added in mlikeli! 0.98c
600:
601: Revision 1.114 2006/02/26 12:57:58 brouard
602: (Module): Some improvements in processing parameter
603: filename with strsep.
604:
605: Revision 1.113 2006/02/24 14:20:24 brouard
606: (Module): Memory leaks checks with valgrind and:
607: datafile was not closed, some imatrix were not freed and on matrix
608: allocation too.
609:
610: Revision 1.112 2006/01/30 09:55:26 brouard
611: (Module): Back to gnuplot.exe instead of wgnuplot.exe
612:
613: Revision 1.111 2006/01/25 20:38:18 brouard
614: (Module): Lots of cleaning and bugs added (Gompertz)
615: (Module): Comments can be added in data file. Missing date values
616: can be a simple dot '.'.
617:
618: Revision 1.110 2006/01/25 00:51:50 brouard
619: (Module): Lots of cleaning and bugs added (Gompertz)
620:
621: Revision 1.109 2006/01/24 19:37:15 brouard
622: (Module): Comments (lines starting with a #) are allowed in data.
623:
624: Revision 1.108 2006/01/19 18:05:42 lievre
625: Gnuplot problem appeared...
626: To be fixed
627:
628: Revision 1.107 2006/01/19 16:20:37 brouard
629: Test existence of gnuplot in imach path
630:
631: Revision 1.106 2006/01/19 13:24:36 brouard
632: Some cleaning and links added in html output
633:
634: Revision 1.105 2006/01/05 20:23:19 lievre
635: *** empty log message ***
636:
637: Revision 1.104 2005/09/30 16:11:43 lievre
638: (Module): sump fixed, loop imx fixed, and simplifications.
639: (Module): If the status is missing at the last wave but we know
640: that the person is alive, then we can code his/her status as -2
641: (instead of missing=-1 in earlier versions) and his/her
642: contributions to the likelihood is 1 - Prob of dying from last
643: health status (= 1-p13= p11+p12 in the easiest case of somebody in
644: the healthy state at last known wave). Version is 0.98
645:
646: Revision 1.103 2005/09/30 15:54:49 lievre
647: (Module): sump fixed, loop imx fixed, and simplifications.
648:
649: Revision 1.102 2004/09/15 17:31:30 brouard
650: Add the possibility to read data file including tab characters.
651:
652: Revision 1.101 2004/09/15 10:38:38 brouard
653: Fix on curr_time
654:
655: Revision 1.100 2004/07/12 18:29:06 brouard
656: Add version for Mac OS X. Just define UNIX in Makefile
657:
658: Revision 1.99 2004/06/05 08:57:40 brouard
659: *** empty log message ***
660:
661: Revision 1.98 2004/05/16 15:05:56 brouard
662: New version 0.97 . First attempt to estimate force of mortality
663: directly from the data i.e. without the need of knowing the health
664: state at each age, but using a Gompertz model: log u =a + b*age .
665: This is the basic analysis of mortality and should be done before any
666: other analysis, in order to test if the mortality estimated from the
667: cross-longitudinal survey is different from the mortality estimated
668: from other sources like vital statistic data.
669:
670: The same imach parameter file can be used but the option for mle should be -3.
671:
1.133 brouard 672: Agnès, who wrote this part of the code, tried to keep most of the
1.126 brouard 673: former routines in order to include the new code within the former code.
674:
675: The output is very simple: only an estimate of the intercept and of
676: the slope with 95% confident intervals.
677:
678: Current limitations:
679: A) Even if you enter covariates, i.e. with the
680: model= V1+V2 equation for example, the programm does only estimate a unique global model without covariates.
681: B) There is no computation of Life Expectancy nor Life Table.
682:
683: Revision 1.97 2004/02/20 13:25:42 lievre
684: Version 0.96d. Population forecasting command line is (temporarily)
685: suppressed.
686:
687: Revision 1.96 2003/07/15 15:38:55 brouard
688: * imach.c (Repository): Errors in subdirf, 2, 3 while printing tmpout is
689: rewritten within the same printf. Workaround: many printfs.
690:
691: Revision 1.95 2003/07/08 07:54:34 brouard
692: * imach.c (Repository):
693: (Repository): Using imachwizard code to output a more meaningful covariance
694: matrix (cov(a12,c31) instead of numbers.
695:
696: Revision 1.94 2003/06/27 13:00:02 brouard
697: Just cleaning
698:
699: Revision 1.93 2003/06/25 16:33:55 brouard
700: (Module): On windows (cygwin) function asctime_r doesn't
701: exist so I changed back to asctime which exists.
702: (Module): Version 0.96b
703:
704: Revision 1.92 2003/06/25 16:30:45 brouard
705: (Module): On windows (cygwin) function asctime_r doesn't
706: exist so I changed back to asctime which exists.
707:
708: Revision 1.91 2003/06/25 15:30:29 brouard
709: * imach.c (Repository): Duplicated warning errors corrected.
710: (Repository): Elapsed time after each iteration is now output. It
711: helps to forecast when convergence will be reached. Elapsed time
712: is stamped in powell. We created a new html file for the graphs
713: concerning matrix of covariance. It has extension -cov.htm.
714:
715: Revision 1.90 2003/06/24 12:34:15 brouard
716: (Module): Some bugs corrected for windows. Also, when
717: mle=-1 a template is output in file "or"mypar.txt with the design
718: of the covariance matrix to be input.
719:
720: Revision 1.89 2003/06/24 12:30:52 brouard
721: (Module): Some bugs corrected for windows. Also, when
722: mle=-1 a template is output in file "or"mypar.txt with the design
723: of the covariance matrix to be input.
724:
725: Revision 1.88 2003/06/23 17:54:56 brouard
726: * 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.
727:
728: Revision 1.87 2003/06/18 12:26:01 brouard
729: Version 0.96
730:
731: Revision 1.86 2003/06/17 20:04:08 brouard
732: (Module): Change position of html and gnuplot routines and added
733: routine fileappend.
734:
735: Revision 1.85 2003/06/17 13:12:43 brouard
736: * imach.c (Repository): Check when date of death was earlier that
737: current date of interview. It may happen when the death was just
738: prior to the death. In this case, dh was negative and likelihood
739: was wrong (infinity). We still send an "Error" but patch by
740: assuming that the date of death was just one stepm after the
741: interview.
742: (Repository): Because some people have very long ID (first column)
743: we changed int to long in num[] and we added a new lvector for
744: memory allocation. But we also truncated to 8 characters (left
745: truncation)
746: (Repository): No more line truncation errors.
747:
748: Revision 1.84 2003/06/13 21:44:43 brouard
749: * imach.c (Repository): Replace "freqsummary" at a correct
750: place. It differs from routine "prevalence" which may be called
751: many times. Probs is memory consuming and must be used with
752: parcimony.
753: Version 0.95a3 (should output exactly the same maximization than 0.8a2)
754:
755: Revision 1.83 2003/06/10 13:39:11 lievre
756: *** empty log message ***
757:
758: Revision 1.82 2003/06/05 15:57:20 brouard
759: Add log in imach.c and fullversion number is now printed.
760:
761: */
762: /*
763: Interpolated Markov Chain
764:
765: Short summary of the programme:
766:
1.227 brouard 767: This program computes Healthy Life Expectancies or State-specific
768: (if states aren't health statuses) Expectancies from
769: cross-longitudinal data. Cross-longitudinal data consist in:
770:
771: -1- a first survey ("cross") where individuals from different ages
772: are interviewed on their health status or degree of disability (in
773: the case of a health survey which is our main interest)
774:
775: -2- at least a second wave of interviews ("longitudinal") which
776: measure each change (if any) in individual health status. Health
777: expectancies are computed from the time spent in each health state
778: according to a model. More health states you consider, more time is
779: necessary to reach the Maximum Likelihood of the parameters involved
780: in the model. The simplest model is the multinomial logistic model
781: where pij is the probability to be observed in state j at the second
782: wave conditional to be observed in state i at the first
783: wave. Therefore the model is: log(pij/pii)= aij + bij*age+ cij*sex +
784: etc , where 'age' is age and 'sex' is a covariate. If you want to
785: have a more complex model than "constant and age", you should modify
786: the program where the markup *Covariates have to be included here
787: again* invites you to do it. More covariates you add, slower the
1.126 brouard 788: convergence.
789:
790: The advantage of this computer programme, compared to a simple
791: multinomial logistic model, is clear when the delay between waves is not
792: identical for each individual. Also, if a individual missed an
793: intermediate interview, the information is lost, but taken into
794: account using an interpolation or extrapolation.
795:
796: hPijx is the probability to be observed in state i at age x+h
797: conditional to the observed state i at age x. The delay 'h' can be
798: split into an exact number (nh*stepm) of unobserved intermediate
799: states. This elementary transition (by month, quarter,
800: semester or year) is modelled as a multinomial logistic. The hPx
801: matrix is simply the matrix product of nh*stepm elementary matrices
802: and the contribution of each individual to the likelihood is simply
803: hPijx.
804:
805: Also this programme outputs the covariance matrix of the parameters but also
1.218 brouard 806: of the life expectancies. It also computes the period (stable) prevalence.
807:
808: Back prevalence and projections:
1.227 brouard 809:
810: - back_prevalence_limit(double *p, double **bprlim, double ageminpar,
811: double agemaxpar, double ftolpl, int *ncvyearp, double
812: dateprev1,double dateprev2, int firstpass, int lastpass, int
813: mobilavproj)
814:
815: Computes the back prevalence limit for any combination of
816: covariate values k at any age between ageminpar and agemaxpar and
817: returns it in **bprlim. In the loops,
818:
819: - **bprevalim(**bprlim, ***mobaverage, nlstate, *p, age, **oldm,
820: **savm, **dnewm, **doldm, **dsavm, ftolpl, ncvyearp, k);
821:
822: - hBijx Back Probability to be in state i at age x-h being in j at x
1.218 brouard 823: Computes for any combination of covariates k and any age between bage and fage
824: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
825: oldm=oldms;savm=savms;
1.227 brouard 826:
1.267 brouard 827: - hbxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k, nres);
1.218 brouard 828: Computes the transition matrix starting at age 'age' over
829: 'nhstepm*hstepm*stepm' months (i.e. until
830: age (in years) age+nhstepm*hstepm*stepm/12) by multiplying
1.227 brouard 831: nhstepm*hstepm matrices.
832:
833: Returns p3mat[i][j][h] after calling
834: p3mat[i][j][h]=matprod2(newm,
835: bmij(pmmij,cov,ncovmodel,x,nlstate,prevacurrent, dnewm, doldm,
836: dsavm,ij),\ 1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath,
837: oldm);
1.226 brouard 838:
839: Important routines
840:
841: - func (or funcone), computes logit (pij) distinguishing
842: o fixed variables (single or product dummies or quantitative);
843: o varying variables by:
844: (1) wave (single, product dummies, quantitative),
845: (2) by age (can be month) age (done), age*age (done), age*Vn where Vn can be:
846: % fixed dummy (treated) or quantitative (not done because time-consuming);
847: % varying dummy (not done) or quantitative (not done);
848: - Tricode which tests the modality of dummy variables (in order to warn with wrong or empty modalities)
849: and returns the number of efficient covariates cptcoveff and modalities nbcode[Tvar[k]][1]= 0 and nbcode[Tvar[k]][2]= 1 usually.
850: - printinghtml which outputs results like life expectancy in and from a state for a combination of modalities of dummy variables
851: o There are 2*cptcoveff combinations of (0,1) for cptcoveff variables. Outputting only combinations with people, éliminating 1 1 if
852: race White (0 0), Black vs White (1 0), Hispanic (0 1) and 1 1 being meaningless.
1.218 brouard 853:
1.226 brouard 854:
855:
1.133 brouard 856: Authors: Nicolas Brouard (brouard@ined.fr) and Agnès Lièvre (lievre@ined.fr).
857: Institut national d'études démographiques, Paris.
1.126 brouard 858: This software have been partly granted by Euro-REVES, a concerted action
859: from the European Union.
860: It is copyrighted identically to a GNU software product, ie programme and
861: software can be distributed freely for non commercial use. Latest version
862: can be accessed at http://euroreves.ined.fr/imach .
863:
864: Help to debug: LD_PRELOAD=/usr/local/lib/libnjamd.so ./imach foo.imach
865: or better on gdb : set env LD_PRELOAD=/usr/local/lib/libnjamd.so
866:
867: **********************************************************************/
868: /*
869: main
870: read parameterfile
871: read datafile
872: concatwav
873: freqsummary
874: if (mle >= 1)
875: mlikeli
876: print results files
877: if mle==1
878: computes hessian
879: read end of parameter file: agemin, agemax, bage, fage, estepm
880: begin-prev-date,...
881: open gnuplot file
882: open html file
1.145 brouard 883: period (stable) prevalence | pl_nom 1-1 2-2 etc by covariate
884: for age prevalim() | #****** V1=0 V2=1 V3=1 V4=0 ******
885: | 65 1 0 2 1 3 1 4 0 0.96326 0.03674
886: freexexit2 possible for memory heap.
887:
888: h Pij x | pij_nom ficrestpij
889: # Cov Agex agex+h hpijx with i,j= 1-1 1-2 1-3 2-1 2-2 2-3
890: 1 85 85 1.00000 0.00000 0.00000 0.00000 1.00000 0.00000
891: 1 85 86 0.68299 0.22291 0.09410 0.71093 0.00000 0.28907
892:
893: 1 65 99 0.00364 0.00322 0.99314 0.00350 0.00310 0.99340
894: 1 65 100 0.00214 0.00204 0.99581 0.00206 0.00196 0.99597
895: variance of p one-step probabilities varprob | prob_nom ficresprob #One-step probabilities and stand. devi in ()
896: Standard deviation of one-step probabilities | probcor_nom ficresprobcor #One-step probabilities and correlation matrix
897: Matrix of variance covariance of one-step probabilities | probcov_nom ficresprobcov #One-step probabilities and covariance matrix
898:
1.126 brouard 899: forecasting if prevfcast==1 prevforecast call prevalence()
900: health expectancies
901: Variance-covariance of DFLE
902: prevalence()
903: movingaverage()
904: varevsij()
905: if popbased==1 varevsij(,popbased)
906: total life expectancies
907: Variance of period (stable) prevalence
908: end
909: */
910:
1.187 brouard 911: /* #define DEBUG */
912: /* #define DEBUGBRENT */
1.203 brouard 913: /* #define DEBUGLINMIN */
914: /* #define DEBUGHESS */
915: #define DEBUGHESSIJ
1.224 brouard 916: /* #define LINMINORIGINAL /\* Don't use loop on scale in linmin (accepting nan) *\/ */
1.165 brouard 917: #define POWELL /* Instead of NLOPT */
1.224 brouard 918: #define POWELLNOF3INFF1TEST /* Skip test */
1.186 brouard 919: /* #define POWELLORIGINAL /\* Don't use Directest to decide new direction but original Powell test *\/ */
920: /* #define MNBRAKORIGINAL /\* Don't use mnbrak fix *\/ */
1.126 brouard 921:
922: #include <math.h>
923: #include <stdio.h>
924: #include <stdlib.h>
925: #include <string.h>
1.226 brouard 926: #include <ctype.h>
1.159 brouard 927:
928: #ifdef _WIN32
929: #include <io.h>
1.172 brouard 930: #include <windows.h>
931: #include <tchar.h>
1.159 brouard 932: #else
1.126 brouard 933: #include <unistd.h>
1.159 brouard 934: #endif
1.126 brouard 935:
936: #include <limits.h>
937: #include <sys/types.h>
1.171 brouard 938:
939: #if defined(__GNUC__)
940: #include <sys/utsname.h> /* Doesn't work on Windows */
941: #endif
942:
1.126 brouard 943: #include <sys/stat.h>
944: #include <errno.h>
1.159 brouard 945: /* extern int errno; */
1.126 brouard 946:
1.157 brouard 947: /* #ifdef LINUX */
948: /* #include <time.h> */
949: /* #include "timeval.h" */
950: /* #else */
951: /* #include <sys/time.h> */
952: /* #endif */
953:
1.126 brouard 954: #include <time.h>
955:
1.136 brouard 956: #ifdef GSL
957: #include <gsl/gsl_errno.h>
958: #include <gsl/gsl_multimin.h>
959: #endif
960:
1.167 brouard 961:
1.162 brouard 962: #ifdef NLOPT
963: #include <nlopt.h>
964: typedef struct {
965: double (* function)(double [] );
966: } myfunc_data ;
967: #endif
968:
1.126 brouard 969: /* #include <libintl.h> */
970: /* #define _(String) gettext (String) */
971:
1.251 brouard 972: #define MAXLINE 2048 /* Was 256 and 1024. Overflow with 312 with 2 states and 4 covariates. Should be ok */
1.126 brouard 973:
974: #define GNUPLOTPROGRAM "gnuplot"
975: /*#define GNUPLOTPROGRAM "..\\gp37mgw\\wgnuplot"*/
976: #define FILENAMELENGTH 132
977:
978: #define GLOCK_ERROR_NOPATH -1 /* empty path */
979: #define GLOCK_ERROR_GETCWD -2 /* cannot get cwd */
980:
1.144 brouard 981: #define MAXPARM 128 /**< Maximum number of parameters for the optimization */
982: #define NPARMAX 64 /**< (nlstate+ndeath-1)*nlstate*ncovmodel */
1.126 brouard 983:
984: #define NINTERVMAX 8
1.144 brouard 985: #define NLSTATEMAX 8 /**< Maximum number of live states (for func) */
986: #define NDEATHMAX 8 /**< Maximum number of dead states (for func) */
987: #define NCOVMAX 20 /**< Maximum number of covariates, including generated covariates V1*V2 */
1.197 brouard 988: #define codtabm(h,k) (1 & (h-1) >> (k-1))+1
1.211 brouard 989: /*#define decodtabm(h,k,cptcoveff)= (h <= (1<<cptcoveff)?(((h-1) >> (k-1)) & 1) +1 : -1)*/
990: #define decodtabm(h,k,cptcoveff) (((h-1) >> (k-1)) & 1) +1
1.126 brouard 991: #define MAXN 20000
1.144 brouard 992: #define YEARM 12. /**< Number of months per year */
1.218 brouard 993: /* #define AGESUP 130 */
994: #define AGESUP 150
1.268 brouard 995: #define AGEINF 0
1.218 brouard 996: #define AGEMARGE 25 /* Marge for agemin and agemax for(iage=agemin-AGEMARGE; iage <= agemax+3+AGEMARGE; iage++) */
1.126 brouard 997: #define AGEBASE 40
1.194 brouard 998: #define AGEOVERFLOW 1.e20
1.164 brouard 999: #define AGEGOMP 10 /**< Minimal age for Gompertz adjustment */
1.157 brouard 1000: #ifdef _WIN32
1001: #define DIRSEPARATOR '\\'
1002: #define CHARSEPARATOR "\\"
1003: #define ODIRSEPARATOR '/'
1004: #else
1.126 brouard 1005: #define DIRSEPARATOR '/'
1006: #define CHARSEPARATOR "/"
1007: #define ODIRSEPARATOR '\\'
1008: #endif
1009:
1.269 ! brouard 1010: /* $Id: imach.c,v 1.268 2017/05/18 20:09:32 brouard Exp $ */
1.126 brouard 1011: /* $State: Exp $ */
1.196 brouard 1012: #include "version.h"
1013: char version[]=__IMACH_VERSION__;
1.224 brouard 1014: 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";
1.269 ! brouard 1015: char fullversion[]="$Revision: 1.268 $ $Date: 2017/05/18 20:09:32 $";
1.126 brouard 1016: char strstart[80];
1017: char optionfilext[10], optionfilefiname[FILENAMELENGTH];
1.130 brouard 1018: int erreur=0, nberr=0, nbwarn=0; /* Error number, number of errors number of warnings */
1.187 brouard 1019: int nagesqr=0, nforce=0; /* nagesqr=1 if model is including age*age, number of forces */
1.145 brouard 1020: /* Number of covariates model=V2+V1+ V3*age+V2*V4 */
1021: int cptcovn=0; /**< cptcovn number of covariates added in the model (excepting constant and age and age*product) */
1022: int cptcovt=0; /**< cptcovt number of covariates added in the model (excepting constant and age) */
1.225 brouard 1023: int cptcovs=0; /**< cptcovs number of simple covariates in the model V2+V1 =2 */
1024: int cptcovsnq=0; /**< cptcovsnq number of simple covariates in the model but non quantitative V2+V1 =2 */
1.145 brouard 1025: int cptcovage=0; /**< Number of covariates with age: V3*age only =1 */
1026: int cptcovprodnoage=0; /**< Number of covariate products without age */
1027: int cptcoveff=0; /* Total number of covariates to vary for printing results */
1.233 brouard 1028: int ncovf=0; /* Total number of effective fixed covariates (dummy or quantitative) in the model */
1029: int ncovv=0; /* Total number of effective (wave) varying covariates (dummy or quantitative) in the model */
1.232 brouard 1030: int ncova=0; /* Total number of effective (wave and stepm) varying with age covariates (dummy of quantitative) in the model */
1.234 brouard 1031: int nsd=0; /**< Total number of single dummy variables (output) */
1032: int nsq=0; /**< Total number of single quantitative variables (output) */
1.232 brouard 1033: int ncoveff=0; /* Total number of effective fixed dummy covariates in the model */
1.225 brouard 1034: int nqfveff=0; /**< nqfveff Number of Quantitative Fixed Variables Effective */
1.224 brouard 1035: int ntveff=0; /**< ntveff number of effective time varying variables */
1036: int nqtveff=0; /**< ntqveff number of effective time varying quantitative variables */
1.145 brouard 1037: int cptcov=0; /* Working variable */
1.218 brouard 1038: int ncovcombmax=NCOVMAX; /* Maximum calculated number of covariate combination = pow(2, cptcoveff) */
1.126 brouard 1039: int npar=NPARMAX;
1040: int nlstate=2; /* Number of live states */
1041: int ndeath=1; /* Number of dead states */
1.130 brouard 1042: int ncovmodel=0, ncovcol=0; /* Total number of covariables including constant a12*1 +b12*x ncovmodel=2 */
1.223 brouard 1043: int nqv=0, ntv=0, nqtv=0; /* Total number of quantitative variables, time variable (dummy), quantitative and time variable */
1.126 brouard 1044: int popbased=0;
1045:
1046: int *wav; /* Number of waves for this individuual 0 is possible */
1.130 brouard 1047: int maxwav=0; /* Maxim number of waves */
1048: int jmin=0, jmax=0; /* min, max spacing between 2 waves */
1049: int ijmin=0, ijmax=0; /* Individuals having jmin and jmax */
1050: int gipmx=0, gsw=0; /* Global variables on the number of contributions
1.126 brouard 1051: to the likelihood and the sum of weights (done by funcone)*/
1.130 brouard 1052: int mle=1, weightopt=0;
1.126 brouard 1053: int **mw; /* mw[mi][i] is number of the mi wave for this individual */
1054: int **dh; /* dh[mi][i] is number of steps between mi,mi+1 for this individual */
1055: int **bh; /* bh[mi][i] is the bias (+ or -) for this individual if the delay between
1056: * wave mi and wave mi+1 is not an exact multiple of stepm. */
1.162 brouard 1057: int countcallfunc=0; /* Count the number of calls to func */
1.230 brouard 1058: int selected(int kvar); /* Is covariate kvar selected for printing results */
1059:
1.130 brouard 1060: double jmean=1; /* Mean space between 2 waves */
1.145 brouard 1061: double **matprod2(); /* test */
1.126 brouard 1062: double **oldm, **newm, **savm; /* Working pointers to matrices */
1063: double **oldms, **newms, **savms; /* Fixed working pointers to matrices */
1.218 brouard 1064: double **ddnewms, **ddoldms, **ddsavms; /* for freeing later */
1065:
1.136 brouard 1066: /*FILE *fic ; */ /* Used in readdata only */
1.217 brouard 1067: FILE *ficpar, *ficparo,*ficres, *ficresp, *ficresphtm, *ficresphtmfr, *ficrespl, *ficresplb,*ficrespij, *ficrespijb, *ficrest,*ficresf, *ficresfb,*ficrespop;
1.126 brouard 1068: FILE *ficlog, *ficrespow;
1.130 brouard 1069: int globpr=0; /* Global variable for printing or not */
1.126 brouard 1070: double fretone; /* Only one call to likelihood */
1.130 brouard 1071: long ipmx=0; /* Number of contributions */
1.126 brouard 1072: double sw; /* Sum of weights */
1073: char filerespow[FILENAMELENGTH];
1074: char fileresilk[FILENAMELENGTH]; /* File of individual contributions to the likelihood */
1075: FILE *ficresilk;
1076: FILE *ficgp,*ficresprob,*ficpop, *ficresprobcov, *ficresprobcor;
1077: FILE *ficresprobmorprev;
1078: FILE *fichtm, *fichtmcov; /* Html File */
1079: FILE *ficreseij;
1080: char filerese[FILENAMELENGTH];
1081: FILE *ficresstdeij;
1082: char fileresstde[FILENAMELENGTH];
1083: FILE *ficrescveij;
1084: char filerescve[FILENAMELENGTH];
1085: FILE *ficresvij;
1086: char fileresv[FILENAMELENGTH];
1.269 ! brouard 1087:
1.126 brouard 1088: char title[MAXLINE];
1.234 brouard 1089: char model[MAXLINE]; /**< The model line */
1.217 brouard 1090: char optionfile[FILENAMELENGTH], datafile[FILENAMELENGTH], filerespl[FILENAMELENGTH], fileresplb[FILENAMELENGTH];
1.126 brouard 1091: char plotcmd[FILENAMELENGTH], pplotcmd[FILENAMELENGTH];
1092: char tmpout[FILENAMELENGTH], tmpout2[FILENAMELENGTH];
1093: char command[FILENAMELENGTH];
1094: int outcmd=0;
1095:
1.217 brouard 1096: char fileres[FILENAMELENGTH], filerespij[FILENAMELENGTH], filerespijb[FILENAMELENGTH], filereso[FILENAMELENGTH], rfileres[FILENAMELENGTH];
1.202 brouard 1097: char fileresu[FILENAMELENGTH]; /* fileres without r in front */
1.126 brouard 1098: char filelog[FILENAMELENGTH]; /* Log file */
1099: char filerest[FILENAMELENGTH];
1100: char fileregp[FILENAMELENGTH];
1101: char popfile[FILENAMELENGTH];
1102:
1103: char optionfilegnuplot[FILENAMELENGTH], optionfilehtm[FILENAMELENGTH], optionfilehtmcov[FILENAMELENGTH] ;
1104:
1.157 brouard 1105: /* struct timeval start_time, end_time, curr_time, last_time, forecast_time; */
1106: /* struct timezone tzp; */
1107: /* extern int gettimeofday(); */
1108: struct tm tml, *gmtime(), *localtime();
1109:
1110: extern time_t time();
1111:
1112: struct tm start_time, end_time, curr_time, last_time, forecast_time;
1113: time_t rstart_time, rend_time, rcurr_time, rlast_time, rforecast_time; /* raw time */
1114: struct tm tm;
1115:
1.126 brouard 1116: char strcurr[80], strfor[80];
1117:
1118: char *endptr;
1119: long lval;
1120: double dval;
1121:
1122: #define NR_END 1
1123: #define FREE_ARG char*
1124: #define FTOL 1.0e-10
1125:
1126: #define NRANSI
1.240 brouard 1127: #define ITMAX 200
1128: #define ITPOWMAX 20 /* This is now multiplied by the number of parameters */
1.126 brouard 1129:
1130: #define TOL 2.0e-4
1131:
1132: #define CGOLD 0.3819660
1133: #define ZEPS 1.0e-10
1134: #define SHFT(a,b,c,d) (a)=(b);(b)=(c);(c)=(d);
1135:
1136: #define GOLD 1.618034
1137: #define GLIMIT 100.0
1138: #define TINY 1.0e-20
1139:
1140: static double maxarg1,maxarg2;
1141: #define FMAX(a,b) (maxarg1=(a),maxarg2=(b),(maxarg1)>(maxarg2)? (maxarg1):(maxarg2))
1142: #define FMIN(a,b) (maxarg1=(a),maxarg2=(b),(maxarg1)<(maxarg2)? (maxarg1):(maxarg2))
1143:
1144: #define SIGN(a,b) ((b)>0.0 ? fabs(a) : -fabs(a))
1145: #define rint(a) floor(a+0.5)
1.166 brouard 1146: /* http://www.thphys.uni-heidelberg.de/~robbers/cmbeasy/doc/html/myutils_8h-source.html */
1.183 brouard 1147: #define mytinydouble 1.0e-16
1.166 brouard 1148: /* #define DEQUAL(a,b) (fabs((a)-(b))<mytinydouble) */
1149: /* http://www.thphys.uni-heidelberg.de/~robbers/cmbeasy/doc/html/mynrutils_8h-source.html */
1150: /* static double dsqrarg; */
1151: /* #define DSQR(a) (DEQUAL((dsqrarg=(a)),0.0) ? 0.0 : dsqrarg*dsqrarg) */
1.126 brouard 1152: static double sqrarg;
1153: #define SQR(a) ((sqrarg=(a)) == 0.0 ? 0.0 :sqrarg*sqrarg)
1154: #define SWAP(a,b) {temp=(a);(a)=(b);(b)=temp;}
1155: int agegomp= AGEGOMP;
1156:
1157: int imx;
1158: int stepm=1;
1159: /* Stepm, step in month: minimum step interpolation*/
1160:
1161: int estepm;
1162: /* Estepm, step in month to interpolate survival function in order to approximate Life Expectancy*/
1163:
1164: int m,nb;
1165: long *num;
1.197 brouard 1166: int firstpass=0, lastpass=4,*cod, *cens;
1.192 brouard 1167: int *ncodemax; /* ncodemax[j]= Number of modalities of the j th
1168: covariate for which somebody answered excluding
1169: undefined. Usually 2: 0 and 1. */
1170: int *ncodemaxwundef; /* ncodemax[j]= Number of modalities of the j th
1171: covariate for which somebody answered including
1172: undefined. Usually 3: -1, 0 and 1. */
1.126 brouard 1173: double **agev,*moisnais, *annais, *moisdc, *andc,**mint, **anint;
1.218 brouard 1174: double **pmmij, ***probs; /* Global pointer */
1.219 brouard 1175: double ***mobaverage, ***mobaverages; /* New global variable */
1.126 brouard 1176: double *ageexmed,*agecens;
1177: double dateintmean=0;
1178:
1179: double *weight;
1180: int **s; /* Status */
1.141 brouard 1181: double *agedc;
1.145 brouard 1182: double **covar; /**< covar[j,i], value of jth covariate for individual i,
1.141 brouard 1183: * covar=matrix(0,NCOVMAX,1,n);
1.187 brouard 1184: * cov[Tage[kk]+2]=covar[Tvar[Tage[kk]]][i]*age; */
1.268 brouard 1185: double **coqvar; /* Fixed quantitative covariate nqv */
1186: double ***cotvar; /* Time varying covariate ntv */
1.225 brouard 1187: double ***cotqvar; /* Time varying quantitative covariate itqv */
1.141 brouard 1188: double idx;
1189: int **nbcode, *Tvar; /**< model=V2 => Tvar[1]= 2 */
1.234 brouard 1190: /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1191: /*k 1 2 3 4 5 6 7 8 9 */
1192: /*Tvar[k]= 5 4 3 6 5 2 7 1 1 */
1193: /* Tndvar[k] 1 2 3 4 5 */
1194: /*TDvar 4 3 6 7 1 */ /* For outputs only; combination of dummies fixed or varying */
1195: /* Tns[k] 1 2 2 4 5 */ /* Number of single cova */
1196: /* TvarsD[k] 1 2 3 */ /* Number of single dummy cova */
1197: /* TvarsDind 2 3 9 */ /* position K of single dummy cova */
1198: /* TvarsQ[k] 1 2 */ /* Number of single quantitative cova */
1199: /* TvarsQind 1 6 */ /* position K of single quantitative cova */
1200: /* Tprod[i]=k 4 7 */
1201: /* Tage[i]=k 5 8 */
1202: /* */
1203: /* Type */
1204: /* V 1 2 3 4 5 */
1205: /* F F V V V */
1206: /* D Q D D Q */
1207: /* */
1208: int *TvarsD;
1209: int *TvarsDind;
1210: int *TvarsQ;
1211: int *TvarsQind;
1212:
1.235 brouard 1213: #define MAXRESULTLINES 10
1214: int nresult=0;
1.258 brouard 1215: int parameterline=0; /* # of the parameter (type) line */
1.235 brouard 1216: int TKresult[MAXRESULTLINES];
1.237 brouard 1217: int Tresult[MAXRESULTLINES][NCOVMAX];/* For dummy variable , value (output) */
1218: int Tinvresult[MAXRESULTLINES][NCOVMAX];/* For dummy variable , value (output) */
1.235 brouard 1219: int Tvresult[MAXRESULTLINES][NCOVMAX]; /* For dummy variable , variable # (output) */
1220: double Tqresult[MAXRESULTLINES][NCOVMAX]; /* For quantitative variable , value (output) */
1.237 brouard 1221: double Tqinvresult[MAXRESULTLINES][NCOVMAX]; /* For quantitative variable , value (output) */
1.235 brouard 1222: int Tvqresult[MAXRESULTLINES][NCOVMAX]; /* For quantitative variable , variable # (output) */
1223:
1.234 brouard 1224: /* 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 1225: 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 */
1226: 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 */
1227: 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 */
1228: int *TvarVind; /**< TvarVind[1]=1, TvarVind[2]=2 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1229: 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 */
1230: 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 1231: int *TvarFD; /**< TvarFD[1]=V1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1232: int *TvarFDind; /* TvarFDind[1]=9 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1233: int *TvarFQ; /* TvarFQ[1]=V2 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1234: int *TvarFQind; /* TvarFQind[1]=6 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1235: int *TvarVD; /* TvarVD[1]=V5 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1236: int *TvarVDind; /* TvarVDind[1]=1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1237: 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 */
1238: 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 */
1239:
1.230 brouard 1240: int *Tvarsel; /**< Selected covariates for output */
1241: double *Tvalsel; /**< Selected modality value of covariate for output */
1.226 brouard 1242: int *Typevar; /**< 0 for simple covariate (dummy, quantitative, fixed or varying), 1 for age product, 2 for product */
1.227 brouard 1243: int *Fixed; /** Fixed[k] 0=fixed, 1 varying, 2 fixed with age product, 3 varying with age product */
1244: 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 1245: int *DummyV; /** Dummy[v] 0=dummy (0 1), 1 quantitative */
1246: int *FixedV; /** FixedV[v] 0 fixed, 1 varying */
1.197 brouard 1247: int *Tage;
1.227 brouard 1248: int anyvaryingduminmodel=0; /**< Any varying dummy in Model=1 yes, 0 no, to avoid a loop on waves in freq */
1.228 brouard 1249: 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 1250: 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*/
1251: 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 1252: int *Ndum; /** Freq of modality (tricode */
1.200 brouard 1253: /* int **codtab;*/ /**< codtab=imatrix(1,100,1,10); */
1.227 brouard 1254: int **Tvard;
1255: int *Tprod;/**< Gives the k position of the k1 product */
1.238 brouard 1256: /* Tprod[k1=1]=3(=V1*V4) for V2+V1+V1*V4+age*V3 */
1.227 brouard 1257: int *Tposprod; /**< Gives the k1 product from the k position */
1.238 brouard 1258: /* if V2+V1+V1*V4+age*V3+V3*V2 TProd[k1=2]=5 (V3*V2) */
1259: /* Tposprod[k]=k1 , Tposprod[3]=1, Tposprod[5(V3*V2)]=2 (2nd product without age) */
1.227 brouard 1260: int cptcovprod, *Tvaraff, *invalidvarcomb;
1.126 brouard 1261: double *lsurv, *lpop, *tpop;
1262:
1.231 brouard 1263: #define FD 1; /* Fixed dummy covariate */
1264: #define FQ 2; /* Fixed quantitative covariate */
1265: #define FP 3; /* Fixed product covariate */
1266: #define FPDD 7; /* Fixed product dummy*dummy covariate */
1267: #define FPDQ 8; /* Fixed product dummy*quantitative covariate */
1268: #define FPQQ 9; /* Fixed product quantitative*quantitative covariate */
1269: #define VD 10; /* Varying dummy covariate */
1270: #define VQ 11; /* Varying quantitative covariate */
1271: #define VP 12; /* Varying product covariate */
1272: #define VPDD 13; /* Varying product dummy*dummy covariate */
1273: #define VPDQ 14; /* Varying product dummy*quantitative covariate */
1274: #define VPQQ 15; /* Varying product quantitative*quantitative covariate */
1275: #define APFD 16; /* Age product * fixed dummy covariate */
1276: #define APFQ 17; /* Age product * fixed quantitative covariate */
1277: #define APVD 18; /* Age product * varying dummy covariate */
1278: #define APVQ 19; /* Age product * varying quantitative covariate */
1279:
1280: #define FTYPE 1; /* Fixed covariate */
1281: #define VTYPE 2; /* Varying covariate (loop in wave) */
1282: #define ATYPE 2; /* Age product covariate (loop in dh within wave)*/
1283:
1284: struct kmodel{
1285: int maintype; /* main type */
1286: int subtype; /* subtype */
1287: };
1288: struct kmodel modell[NCOVMAX];
1289:
1.143 brouard 1290: double ftol=FTOL; /**< Tolerance for computing Max Likelihood */
1291: double ftolhess; /**< Tolerance for computing hessian */
1.126 brouard 1292:
1293: /**************** split *************************/
1294: static int split( char *path, char *dirc, char *name, char *ext, char *finame )
1295: {
1296: /* From a file name with (full) path (either Unix or Windows) we extract the directory (dirc)
1297: the name of the file (name), its extension only (ext) and its first part of the name (finame)
1298: */
1299: char *ss; /* pointer */
1.186 brouard 1300: int l1=0, l2=0; /* length counters */
1.126 brouard 1301:
1302: l1 = strlen(path ); /* length of path */
1303: if ( l1 == 0 ) return( GLOCK_ERROR_NOPATH );
1304: ss= strrchr( path, DIRSEPARATOR ); /* find last / */
1305: if ( ss == NULL ) { /* no directory, so determine current directory */
1306: strcpy( name, path ); /* we got the fullname name because no directory */
1307: /*if(strrchr(path, ODIRSEPARATOR )==NULL)
1308: printf("Warning you should use %s as a separator\n",DIRSEPARATOR);*/
1309: /* get current working directory */
1310: /* extern char* getcwd ( char *buf , int len);*/
1.184 brouard 1311: #ifdef WIN32
1312: if (_getcwd( dirc, FILENAME_MAX ) == NULL ) {
1313: #else
1314: if (getcwd(dirc, FILENAME_MAX) == NULL) {
1315: #endif
1.126 brouard 1316: return( GLOCK_ERROR_GETCWD );
1317: }
1318: /* got dirc from getcwd*/
1319: printf(" DIRC = %s \n",dirc);
1.205 brouard 1320: } else { /* strip directory from path */
1.126 brouard 1321: ss++; /* after this, the filename */
1322: l2 = strlen( ss ); /* length of filename */
1323: if ( l2 == 0 ) return( GLOCK_ERROR_NOPATH );
1324: strcpy( name, ss ); /* save file name */
1325: strncpy( dirc, path, l1 - l2 ); /* now the directory */
1.186 brouard 1326: dirc[l1-l2] = '\0'; /* add zero */
1.126 brouard 1327: printf(" DIRC2 = %s \n",dirc);
1328: }
1329: /* We add a separator at the end of dirc if not exists */
1330: l1 = strlen( dirc ); /* length of directory */
1331: if( dirc[l1-1] != DIRSEPARATOR ){
1332: dirc[l1] = DIRSEPARATOR;
1333: dirc[l1+1] = 0;
1334: printf(" DIRC3 = %s \n",dirc);
1335: }
1336: ss = strrchr( name, '.' ); /* find last / */
1337: if (ss >0){
1338: ss++;
1339: strcpy(ext,ss); /* save extension */
1340: l1= strlen( name);
1341: l2= strlen(ss)+1;
1342: strncpy( finame, name, l1-l2);
1343: finame[l1-l2]= 0;
1344: }
1345:
1346: return( 0 ); /* we're done */
1347: }
1348:
1349:
1350: /******************************************/
1351:
1352: void replace_back_to_slash(char *s, char*t)
1353: {
1354: int i;
1355: int lg=0;
1356: i=0;
1357: lg=strlen(t);
1358: for(i=0; i<= lg; i++) {
1359: (s[i] = t[i]);
1360: if (t[i]== '\\') s[i]='/';
1361: }
1362: }
1363:
1.132 brouard 1364: char *trimbb(char *out, char *in)
1.137 brouard 1365: { /* Trim multiple blanks in line but keeps first blanks if line starts with blanks */
1.132 brouard 1366: char *s;
1367: s=out;
1368: while (*in != '\0'){
1.137 brouard 1369: while( *in == ' ' && *(in+1) == ' '){ /* && *(in+1) != '\0'){*/
1.132 brouard 1370: in++;
1371: }
1372: *out++ = *in++;
1373: }
1374: *out='\0';
1375: return s;
1376: }
1377:
1.187 brouard 1378: /* char *substrchaine(char *out, char *in, char *chain) */
1379: /* { */
1380: /* /\* Substract chain 'chain' from 'in', return and output 'out' *\/ */
1381: /* char *s, *t; */
1382: /* t=in;s=out; */
1383: /* while ((*in != *chain) && (*in != '\0')){ */
1384: /* *out++ = *in++; */
1385: /* } */
1386:
1387: /* /\* *in matches *chain *\/ */
1388: /* while ((*in++ == *chain++) && (*in != '\0')){ */
1389: /* printf("*in = %c, *out= %c *chain= %c \n", *in, *out, *chain); */
1390: /* } */
1391: /* in--; chain--; */
1392: /* while ( (*in != '\0')){ */
1393: /* printf("Bef *in = %c, *out= %c *chain= %c \n", *in, *out, *chain); */
1394: /* *out++ = *in++; */
1395: /* printf("Aft *in = %c, *out= %c *chain= %c \n", *in, *out, *chain); */
1396: /* } */
1397: /* *out='\0'; */
1398: /* out=s; */
1399: /* return out; */
1400: /* } */
1401: char *substrchaine(char *out, char *in, char *chain)
1402: {
1403: /* Substract chain 'chain' from 'in', return and output 'out' */
1404: /* in="V1+V1*age+age*age+V2", chain="age*age" */
1405:
1406: char *strloc;
1407:
1408: strcpy (out, in);
1409: strloc = strstr(out, chain); /* strloc points to out at age*age+V2 */
1410: printf("Bef strloc=%s chain=%s out=%s \n", strloc, chain, out);
1411: if(strloc != NULL){
1412: /* will affect out */ /* strloc+strlenc(chain)=+V2 */ /* Will also work in Unicode */
1413: memmove(strloc,strloc+strlen(chain), strlen(strloc+strlen(chain))+1);
1414: /* strcpy (strloc, strloc +strlen(chain));*/
1415: }
1416: printf("Aft strloc=%s chain=%s in=%s out=%s \n", strloc, chain, in, out);
1417: return out;
1418: }
1419:
1420:
1.145 brouard 1421: char *cutl(char *blocc, char *alocc, char *in, char occ)
1422: {
1.187 brouard 1423: /* cuts string in into blocc and alocc where blocc ends before FIRST occurence of char 'occ'
1.145 brouard 1424: and alocc starts after first occurence of char 'occ' : ex cutv(blocc,alocc,"abcdef2ghi2j",'2')
1.187 brouard 1425: gives blocc="abcdef" and alocc="ghi2j".
1.145 brouard 1426: If occ is not found blocc is null and alocc is equal to in. Returns blocc
1427: */
1.160 brouard 1428: char *s, *t;
1.145 brouard 1429: t=in;s=in;
1430: while ((*in != occ) && (*in != '\0')){
1431: *alocc++ = *in++;
1432: }
1433: if( *in == occ){
1434: *(alocc)='\0';
1435: s=++in;
1436: }
1437:
1438: if (s == t) {/* occ not found */
1439: *(alocc-(in-s))='\0';
1440: in=s;
1441: }
1442: while ( *in != '\0'){
1443: *blocc++ = *in++;
1444: }
1445:
1446: *blocc='\0';
1447: return t;
1448: }
1.137 brouard 1449: char *cutv(char *blocc, char *alocc, char *in, char occ)
1450: {
1.187 brouard 1451: /* cuts string in into blocc and alocc where blocc ends before LAST occurence of char 'occ'
1.137 brouard 1452: and alocc starts after last occurence of char 'occ' : ex cutv(blocc,alocc,"abcdef2ghi2j",'2')
1453: gives blocc="abcdef2ghi" and alocc="j".
1454: If occ is not found blocc is null and alocc is equal to in. Returns alocc
1455: */
1456: char *s, *t;
1457: t=in;s=in;
1458: while (*in != '\0'){
1459: while( *in == occ){
1460: *blocc++ = *in++;
1461: s=in;
1462: }
1463: *blocc++ = *in++;
1464: }
1465: if (s == t) /* occ not found */
1466: *(blocc-(in-s))='\0';
1467: else
1468: *(blocc-(in-s)-1)='\0';
1469: in=s;
1470: while ( *in != '\0'){
1471: *alocc++ = *in++;
1472: }
1473:
1474: *alocc='\0';
1475: return s;
1476: }
1477:
1.126 brouard 1478: int nbocc(char *s, char occ)
1479: {
1480: int i,j=0;
1481: int lg=20;
1482: i=0;
1483: lg=strlen(s);
1484: for(i=0; i<= lg; i++) {
1.234 brouard 1485: if (s[i] == occ ) j++;
1.126 brouard 1486: }
1487: return j;
1488: }
1489:
1.137 brouard 1490: /* void cutv(char *u,char *v, char*t, char occ) */
1491: /* { */
1492: /* /\* cuts string t into u and v where u ends before last occurence of char 'occ' */
1493: /* and v starts after last occurence of char 'occ' : ex cutv(u,v,"abcdef2ghi2j",'2') */
1494: /* gives u="abcdef2ghi" and v="j" *\/ */
1495: /* int i,lg,j,p=0; */
1496: /* i=0; */
1497: /* lg=strlen(t); */
1498: /* for(j=0; j<=lg-1; j++) { */
1499: /* if((t[j]!= occ) && (t[j+1]== occ)) p=j+1; */
1500: /* } */
1.126 brouard 1501:
1.137 brouard 1502: /* for(j=0; j<p; j++) { */
1503: /* (u[j] = t[j]); */
1504: /* } */
1505: /* u[p]='\0'; */
1.126 brouard 1506:
1.137 brouard 1507: /* for(j=0; j<= lg; j++) { */
1508: /* if (j>=(p+1))(v[j-p-1] = t[j]); */
1509: /* } */
1510: /* } */
1.126 brouard 1511:
1.160 brouard 1512: #ifdef _WIN32
1513: char * strsep(char **pp, const char *delim)
1514: {
1515: char *p, *q;
1516:
1517: if ((p = *pp) == NULL)
1518: return 0;
1519: if ((q = strpbrk (p, delim)) != NULL)
1520: {
1521: *pp = q + 1;
1522: *q = '\0';
1523: }
1524: else
1525: *pp = 0;
1526: return p;
1527: }
1528: #endif
1529:
1.126 brouard 1530: /********************** nrerror ********************/
1531:
1532: void nrerror(char error_text[])
1533: {
1534: fprintf(stderr,"ERREUR ...\n");
1535: fprintf(stderr,"%s\n",error_text);
1536: exit(EXIT_FAILURE);
1537: }
1538: /*********************** vector *******************/
1539: double *vector(int nl, int nh)
1540: {
1541: double *v;
1542: v=(double *) malloc((size_t)((nh-nl+1+NR_END)*sizeof(double)));
1543: if (!v) nrerror("allocation failure in vector");
1544: return v-nl+NR_END;
1545: }
1546:
1547: /************************ free vector ******************/
1548: void free_vector(double*v, int nl, int nh)
1549: {
1550: free((FREE_ARG)(v+nl-NR_END));
1551: }
1552:
1553: /************************ivector *******************************/
1554: int *ivector(long nl,long nh)
1555: {
1556: int *v;
1557: v=(int *) malloc((size_t)((nh-nl+1+NR_END)*sizeof(int)));
1558: if (!v) nrerror("allocation failure in ivector");
1559: return v-nl+NR_END;
1560: }
1561:
1562: /******************free ivector **************************/
1563: void free_ivector(int *v, long nl, long nh)
1564: {
1565: free((FREE_ARG)(v+nl-NR_END));
1566: }
1567:
1568: /************************lvector *******************************/
1569: long *lvector(long nl,long nh)
1570: {
1571: long *v;
1572: v=(long *) malloc((size_t)((nh-nl+1+NR_END)*sizeof(long)));
1573: if (!v) nrerror("allocation failure in ivector");
1574: return v-nl+NR_END;
1575: }
1576:
1577: /******************free lvector **************************/
1578: void free_lvector(long *v, long nl, long nh)
1579: {
1580: free((FREE_ARG)(v+nl-NR_END));
1581: }
1582:
1583: /******************* imatrix *******************************/
1584: int **imatrix(long nrl, long nrh, long ncl, long nch)
1585: /* allocate a int matrix with subscript range m[nrl..nrh][ncl..nch] */
1586: {
1587: long i, nrow=nrh-nrl+1,ncol=nch-ncl+1;
1588: int **m;
1589:
1590: /* allocate pointers to rows */
1591: m=(int **) malloc((size_t)((nrow+NR_END)*sizeof(int*)));
1592: if (!m) nrerror("allocation failure 1 in matrix()");
1593: m += NR_END;
1594: m -= nrl;
1595:
1596:
1597: /* allocate rows and set pointers to them */
1598: m[nrl]=(int *) malloc((size_t)((nrow*ncol+NR_END)*sizeof(int)));
1599: if (!m[nrl]) nrerror("allocation failure 2 in matrix()");
1600: m[nrl] += NR_END;
1601: m[nrl] -= ncl;
1602:
1603: for(i=nrl+1;i<=nrh;i++) m[i]=m[i-1]+ncol;
1604:
1605: /* return pointer to array of pointers to rows */
1606: return m;
1607: }
1608:
1609: /****************** free_imatrix *************************/
1610: void free_imatrix(m,nrl,nrh,ncl,nch)
1611: int **m;
1612: long nch,ncl,nrh,nrl;
1613: /* free an int matrix allocated by imatrix() */
1614: {
1615: free((FREE_ARG) (m[nrl]+ncl-NR_END));
1616: free((FREE_ARG) (m+nrl-NR_END));
1617: }
1618:
1619: /******************* matrix *******************************/
1620: double **matrix(long nrl, long nrh, long ncl, long nch)
1621: {
1622: long i, nrow=nrh-nrl+1, ncol=nch-ncl+1;
1623: double **m;
1624:
1625: m=(double **) malloc((size_t)((nrow+NR_END)*sizeof(double*)));
1626: if (!m) nrerror("allocation failure 1 in matrix()");
1627: m += NR_END;
1628: m -= nrl;
1629:
1630: m[nrl]=(double *) malloc((size_t)((nrow*ncol+NR_END)*sizeof(double)));
1631: if (!m[nrl]) nrerror("allocation failure 2 in matrix()");
1632: m[nrl] += NR_END;
1633: m[nrl] -= ncl;
1634:
1635: for (i=nrl+1; i<=nrh; i++) m[i]=m[i-1]+ncol;
1636: return m;
1.145 brouard 1637: /* print *(*(m+1)+70) or print m[1][70]; print m+1 or print &(m[1]) or &(m[1][0])
1638: m[i] = address of ith row of the table. &(m[i]) is its value which is another adress
1639: that of m[i][0]. In order to get the value p m[i][0] but it is unitialized.
1.126 brouard 1640: */
1641: }
1642:
1643: /*************************free matrix ************************/
1644: void free_matrix(double **m, long nrl, long nrh, long ncl, long nch)
1645: {
1646: free((FREE_ARG)(m[nrl]+ncl-NR_END));
1647: free((FREE_ARG)(m+nrl-NR_END));
1648: }
1649:
1650: /******************* ma3x *******************************/
1651: double ***ma3x(long nrl, long nrh, long ncl, long nch, long nll, long nlh)
1652: {
1653: long i, j, nrow=nrh-nrl+1, ncol=nch-ncl+1, nlay=nlh-nll+1;
1654: double ***m;
1655:
1656: m=(double ***) malloc((size_t)((nrow+NR_END)*sizeof(double*)));
1657: if (!m) nrerror("allocation failure 1 in matrix()");
1658: m += NR_END;
1659: m -= nrl;
1660:
1661: m[nrl]=(double **) malloc((size_t)((nrow*ncol+NR_END)*sizeof(double)));
1662: if (!m[nrl]) nrerror("allocation failure 2 in matrix()");
1663: m[nrl] += NR_END;
1664: m[nrl] -= ncl;
1665:
1666: for (i=nrl+1; i<=nrh; i++) m[i]=m[i-1]+ncol;
1667:
1668: m[nrl][ncl]=(double *) malloc((size_t)((nrow*ncol*nlay+NR_END)*sizeof(double)));
1669: if (!m[nrl][ncl]) nrerror("allocation failure 3 in matrix()");
1670: m[nrl][ncl] += NR_END;
1671: m[nrl][ncl] -= nll;
1672: for (j=ncl+1; j<=nch; j++)
1673: m[nrl][j]=m[nrl][j-1]+nlay;
1674:
1675: for (i=nrl+1; i<=nrh; i++) {
1676: m[i][ncl]=m[i-1l][ncl]+ncol*nlay;
1677: for (j=ncl+1; j<=nch; j++)
1678: m[i][j]=m[i][j-1]+nlay;
1679: }
1680: return m;
1681: /* gdb: p *(m+1) <=> p m[1] and p (m+1) <=> p (m+1) <=> p &(m[1])
1682: &(m[i][j][k]) <=> *((*(m+i) + j)+k)
1683: */
1684: }
1685:
1686: /*************************free ma3x ************************/
1687: void free_ma3x(double ***m, long nrl, long nrh, long ncl, long nch,long nll, long nlh)
1688: {
1689: free((FREE_ARG)(m[nrl][ncl]+ nll-NR_END));
1690: free((FREE_ARG)(m[nrl]+ncl-NR_END));
1691: free((FREE_ARG)(m+nrl-NR_END));
1692: }
1693:
1694: /*************** function subdirf ***********/
1695: char *subdirf(char fileres[])
1696: {
1697: /* Caution optionfilefiname is hidden */
1698: strcpy(tmpout,optionfilefiname);
1699: strcat(tmpout,"/"); /* Add to the right */
1700: strcat(tmpout,fileres);
1701: return tmpout;
1702: }
1703:
1704: /*************** function subdirf2 ***********/
1705: char *subdirf2(char fileres[], char *preop)
1706: {
1707:
1708: /* Caution optionfilefiname is hidden */
1709: strcpy(tmpout,optionfilefiname);
1710: strcat(tmpout,"/");
1711: strcat(tmpout,preop);
1712: strcat(tmpout,fileres);
1713: return tmpout;
1714: }
1715:
1716: /*************** function subdirf3 ***********/
1717: char *subdirf3(char fileres[], char *preop, char *preop2)
1718: {
1719:
1720: /* Caution optionfilefiname is hidden */
1721: strcpy(tmpout,optionfilefiname);
1722: strcat(tmpout,"/");
1723: strcat(tmpout,preop);
1724: strcat(tmpout,preop2);
1725: strcat(tmpout,fileres);
1726: return tmpout;
1727: }
1.213 brouard 1728:
1729: /*************** function subdirfext ***********/
1730: char *subdirfext(char fileres[], char *preop, char *postop)
1731: {
1732:
1733: strcpy(tmpout,preop);
1734: strcat(tmpout,fileres);
1735: strcat(tmpout,postop);
1736: return tmpout;
1737: }
1.126 brouard 1738:
1.213 brouard 1739: /*************** function subdirfext3 ***********/
1740: char *subdirfext3(char fileres[], char *preop, char *postop)
1741: {
1742:
1743: /* Caution optionfilefiname is hidden */
1744: strcpy(tmpout,optionfilefiname);
1745: strcat(tmpout,"/");
1746: strcat(tmpout,preop);
1747: strcat(tmpout,fileres);
1748: strcat(tmpout,postop);
1749: return tmpout;
1750: }
1751:
1.162 brouard 1752: char *asc_diff_time(long time_sec, char ascdiff[])
1753: {
1754: long sec_left, days, hours, minutes;
1755: days = (time_sec) / (60*60*24);
1756: sec_left = (time_sec) % (60*60*24);
1757: hours = (sec_left) / (60*60) ;
1758: sec_left = (sec_left) %(60*60);
1759: minutes = (sec_left) /60;
1760: sec_left = (sec_left) % (60);
1761: sprintf(ascdiff,"%ld day(s) %ld hour(s) %ld minute(s) %ld second(s)",days, hours, minutes, sec_left);
1762: return ascdiff;
1763: }
1764:
1.126 brouard 1765: /***************** f1dim *************************/
1766: extern int ncom;
1767: extern double *pcom,*xicom;
1768: extern double (*nrfunc)(double []);
1769:
1770: double f1dim(double x)
1771: {
1772: int j;
1773: double f;
1774: double *xt;
1775:
1776: xt=vector(1,ncom);
1777: for (j=1;j<=ncom;j++) xt[j]=pcom[j]+x*xicom[j];
1778: f=(*nrfunc)(xt);
1779: free_vector(xt,1,ncom);
1780: return f;
1781: }
1782:
1783: /*****************brent *************************/
1784: double brent(double ax, double bx, double cx, double (*f)(double), double tol, double *xmin)
1.187 brouard 1785: {
1786: /* Given a function f, and given a bracketing triplet of abscissas ax, bx, cx (such that bx is
1787: * between ax and cx, and f(bx) is less than both f(ax) and f(cx) ), this routine isolates
1788: * the minimum to a fractional precision of about tol using Brent’s method. The abscissa of
1789: * the minimum is returned as xmin, and the minimum function value is returned as brent , the
1790: * returned function value.
1791: */
1.126 brouard 1792: int iter;
1793: double a,b,d,etemp;
1.159 brouard 1794: double fu=0,fv,fw,fx;
1.164 brouard 1795: double ftemp=0.;
1.126 brouard 1796: double p,q,r,tol1,tol2,u,v,w,x,xm;
1797: double e=0.0;
1798:
1799: a=(ax < cx ? ax : cx);
1800: b=(ax > cx ? ax : cx);
1801: x=w=v=bx;
1802: fw=fv=fx=(*f)(x);
1803: for (iter=1;iter<=ITMAX;iter++) {
1804: xm=0.5*(a+b);
1805: tol2=2.0*(tol1=tol*fabs(x)+ZEPS);
1806: /* if (2.0*fabs(fp-(*fret)) <= ftol*(fabs(fp)+fabs(*fret)))*/
1807: printf(".");fflush(stdout);
1808: fprintf(ficlog,".");fflush(ficlog);
1.162 brouard 1809: #ifdef DEBUGBRENT
1.126 brouard 1810: 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);
1811: 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);
1812: /* if ((fabs(x-xm) <= (tol2-0.5*(b-a)))||(2.0*fabs(fu-ftemp) <= ftol*1.e-2*(fabs(fu)+fabs(ftemp)))) { */
1813: #endif
1814: if (fabs(x-xm) <= (tol2-0.5*(b-a))){
1815: *xmin=x;
1816: return fx;
1817: }
1818: ftemp=fu;
1819: if (fabs(e) > tol1) {
1820: r=(x-w)*(fx-fv);
1821: q=(x-v)*(fx-fw);
1822: p=(x-v)*q-(x-w)*r;
1823: q=2.0*(q-r);
1824: if (q > 0.0) p = -p;
1825: q=fabs(q);
1826: etemp=e;
1827: e=d;
1828: if (fabs(p) >= fabs(0.5*q*etemp) || p <= q*(a-x) || p >= q*(b-x))
1.224 brouard 1829: d=CGOLD*(e=(x >= xm ? a-x : b-x));
1.126 brouard 1830: else {
1.224 brouard 1831: d=p/q;
1832: u=x+d;
1833: if (u-a < tol2 || b-u < tol2)
1834: d=SIGN(tol1,xm-x);
1.126 brouard 1835: }
1836: } else {
1837: d=CGOLD*(e=(x >= xm ? a-x : b-x));
1838: }
1839: u=(fabs(d) >= tol1 ? x+d : x+SIGN(tol1,d));
1840: fu=(*f)(u);
1841: if (fu <= fx) {
1842: if (u >= x) a=x; else b=x;
1843: SHFT(v,w,x,u)
1.183 brouard 1844: SHFT(fv,fw,fx,fu)
1845: } else {
1846: if (u < x) a=u; else b=u;
1847: if (fu <= fw || w == x) {
1.224 brouard 1848: v=w;
1849: w=u;
1850: fv=fw;
1851: fw=fu;
1.183 brouard 1852: } else if (fu <= fv || v == x || v == w) {
1.224 brouard 1853: v=u;
1854: fv=fu;
1.183 brouard 1855: }
1856: }
1.126 brouard 1857: }
1858: nrerror("Too many iterations in brent");
1859: *xmin=x;
1860: return fx;
1861: }
1862:
1863: /****************** mnbrak ***********************/
1864:
1865: void mnbrak(double *ax, double *bx, double *cx, double *fa, double *fb, double *fc,
1866: double (*func)(double))
1.183 brouard 1867: { /* Given a function func , and given distinct initial points ax and bx , this routine searches in
1868: the downhill direction (defined by the function as evaluated at the initial points) and returns
1869: new points ax , bx , cx that bracket a minimum of the function. Also returned are the function
1870: values at the three points, fa, fb , and fc such that fa > fb and fb < fc.
1871: */
1.126 brouard 1872: double ulim,u,r,q, dum;
1873: double fu;
1.187 brouard 1874:
1875: double scale=10.;
1876: int iterscale=0;
1877:
1878: *fa=(*func)(*ax); /* xta[j]=pcom[j]+(*ax)*xicom[j]; fa=f(xta[j])*/
1879: *fb=(*func)(*bx); /* xtb[j]=pcom[j]+(*bx)*xicom[j]; fb=f(xtb[j]) */
1880:
1881:
1882: /* while(*fb != *fb){ /\* *ax should be ok, reducing distance to *ax *\/ */
1883: /* printf("Warning mnbrak *fb = %lf, *bx=%lf *ax=%lf *fa==%lf iter=%d\n",*fb, *bx, *ax, *fa, iterscale++); */
1884: /* *bx = *ax - (*ax - *bx)/scale; */
1885: /* *fb=(*func)(*bx); /\* xtb[j]=pcom[j]+(*bx)*xicom[j]; fb=f(xtb[j]) *\/ */
1886: /* } */
1887:
1.126 brouard 1888: if (*fb > *fa) {
1889: SHFT(dum,*ax,*bx,dum)
1.183 brouard 1890: SHFT(dum,*fb,*fa,dum)
1891: }
1.126 brouard 1892: *cx=(*bx)+GOLD*(*bx-*ax);
1893: *fc=(*func)(*cx);
1.183 brouard 1894: #ifdef DEBUG
1.224 brouard 1895: printf("mnbrak0 a=%lf *fa=%lf, b=%lf *fb=%lf, c=%lf *fc=%lf\n",*ax,*fa,*bx,*fb,*cx, *fc);
1896: 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 1897: #endif
1.224 brouard 1898: 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 1899: r=(*bx-*ax)*(*fb-*fc);
1.224 brouard 1900: q=(*bx-*cx)*(*fb-*fa); /* What if fa=inf */
1.126 brouard 1901: u=(*bx)-((*bx-*cx)*q-(*bx-*ax)*r)/
1.183 brouard 1902: (2.0*SIGN(FMAX(fabs(q-r),TINY),q-r)); /* Minimum abscissa of a parabolic estimated from (a,fa), (b,fb) and (c,fc). */
1903: ulim=(*bx)+GLIMIT*(*cx-*bx); /* Maximum abscissa where function should be evaluated */
1904: if ((*bx-u)*(u-*cx) > 0.0) { /* if u_p is between b and c */
1.126 brouard 1905: fu=(*func)(u);
1.163 brouard 1906: #ifdef DEBUG
1907: /* f(x)=A(x-u)**2+f(u) */
1908: double A, fparabu;
1909: A= (*fb - *fa)/(*bx-*ax)/(*bx+*ax-2*u);
1910: fparabu= *fa - A*(*ax-u)*(*ax-u);
1.224 brouard 1911: 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);
1912: 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 1913: /* And thus,it can be that fu > *fc even if fparabu < *fc */
1914: /* mnbrak (*ax=7.666299858533, *fa=299039.693133272231), (*bx=8.595447774979, *fb=298976.598289369489),
1915: (*cx=10.098840694817, *fc=298946.631474258087), (*u=9.852501168332, fu=298948.773013752128, fparabu=298945.434711494134) */
1916: /* In that case, there is no bracket in the output! Routine is wrong with many consequences.*/
1.163 brouard 1917: #endif
1.184 brouard 1918: #ifdef MNBRAKORIGINAL
1.183 brouard 1919: #else
1.191 brouard 1920: /* if (fu > *fc) { */
1921: /* #ifdef DEBUG */
1922: /* printf("mnbrak4 fu > fc \n"); */
1923: /* fprintf(ficlog, "mnbrak4 fu > fc\n"); */
1924: /* #endif */
1925: /* /\* 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 *\\/ *\/ */
1926: /* /\* SHFT(*fa,*fc,fu,*fc) /\\* (b, u, c) is a bracket while test fb > fc will be fu > fc will exit *\\/ *\/ */
1927: /* dum=u; /\* Shifting c and u *\/ */
1928: /* u = *cx; */
1929: /* *cx = dum; */
1930: /* dum = fu; */
1931: /* fu = *fc; */
1932: /* *fc =dum; */
1933: /* } else { /\* end *\/ */
1934: /* #ifdef DEBUG */
1935: /* printf("mnbrak3 fu < fc \n"); */
1936: /* fprintf(ficlog, "mnbrak3 fu < fc\n"); */
1937: /* #endif */
1938: /* dum=u; /\* Shifting c and u *\/ */
1939: /* u = *cx; */
1940: /* *cx = dum; */
1941: /* dum = fu; */
1942: /* fu = *fc; */
1943: /* *fc =dum; */
1944: /* } */
1.224 brouard 1945: #ifdef DEBUGMNBRAK
1946: double A, fparabu;
1947: A= (*fb - *fa)/(*bx-*ax)/(*bx+*ax-2*u);
1948: fparabu= *fa - A*(*ax-u)*(*ax-u);
1949: 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);
1950: 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 1951: #endif
1.191 brouard 1952: dum=u; /* Shifting c and u */
1953: u = *cx;
1954: *cx = dum;
1955: dum = fu;
1956: fu = *fc;
1957: *fc =dum;
1.183 brouard 1958: #endif
1.162 brouard 1959: } else if ((*cx-u)*(u-ulim) > 0.0) { /* u is after c but before ulim */
1.183 brouard 1960: #ifdef DEBUG
1.224 brouard 1961: printf("\nmnbrak2 u=%lf after c=%lf but before ulim\n",u,*cx);
1962: fprintf(ficlog,"\nmnbrak2 u=%lf after c=%lf but before ulim\n",u,*cx);
1.183 brouard 1963: #endif
1.126 brouard 1964: fu=(*func)(u);
1965: if (fu < *fc) {
1.183 brouard 1966: #ifdef DEBUG
1.224 brouard 1967: printf("\nmnbrak2 u=%lf after c=%lf but before ulim=%lf AND fu=%lf < %lf=fc\n",u,*cx,ulim,fu, *fc);
1968: fprintf(ficlog,"\nmnbrak2 u=%lf after c=%lf but before ulim=%lf AND fu=%lf < %lf=fc\n",u,*cx,ulim,fu, *fc);
1969: #endif
1970: SHFT(*bx,*cx,u,*cx+GOLD*(*cx-*bx))
1971: SHFT(*fb,*fc,fu,(*func)(u))
1972: #ifdef DEBUG
1973: printf("\nmnbrak2 shift GOLD c=%lf",*cx+GOLD*(*cx-*bx));
1.183 brouard 1974: #endif
1975: }
1.162 brouard 1976: } else if ((u-ulim)*(ulim-*cx) >= 0.0) { /* u outside ulim (verifying that ulim is beyond c) */
1.183 brouard 1977: #ifdef DEBUG
1.224 brouard 1978: printf("\nmnbrak2 u=%lf outside ulim=%lf (verifying that ulim is beyond c=%lf)\n",u,ulim,*cx);
1979: fprintf(ficlog,"\nmnbrak2 u=%lf outside ulim=%lf (verifying that ulim is beyond c=%lf)\n",u,ulim,*cx);
1.183 brouard 1980: #endif
1.126 brouard 1981: u=ulim;
1982: fu=(*func)(u);
1.183 brouard 1983: } else { /* u could be left to b (if r > q parabola has a maximum) */
1984: #ifdef DEBUG
1.224 brouard 1985: printf("\nmnbrak2 u=%lf could be left to b=%lf (if r=%lf > q=%lf parabola has a maximum)\n",u,*bx,r,q);
1986: 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 1987: #endif
1.126 brouard 1988: u=(*cx)+GOLD*(*cx-*bx);
1989: fu=(*func)(u);
1.224 brouard 1990: #ifdef DEBUG
1991: printf("\nmnbrak2 new u=%lf fu=%lf shifted gold left from c=%lf and b=%lf \n",u,fu,*cx,*bx);
1992: fprintf(ficlog,"\nmnbrak2 new u=%lf fu=%lf shifted gold left from c=%lf and b=%lf \n",u,fu,*cx,*bx);
1993: #endif
1.183 brouard 1994: } /* end tests */
1.126 brouard 1995: SHFT(*ax,*bx,*cx,u)
1.183 brouard 1996: SHFT(*fa,*fb,*fc,fu)
1997: #ifdef DEBUG
1.224 brouard 1998: printf("\nmnbrak2 shift (*ax=%.12f, *fa=%.12lf), (*bx=%.12f, *fb=%.12lf), (*cx=%.12f, *fc=%.12lf)\n",*ax,*fa,*bx,*fb,*cx,*fc);
1999: 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 2000: #endif
2001: } /* 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 2002: }
2003:
2004: /*************** linmin ************************/
1.162 brouard 2005: /* Given an n -dimensional point p[1..n] and an n -dimensional direction xi[1..n] , moves and
2006: resets p to where the function func(p) takes on a minimum along the direction xi from p ,
2007: and replaces xi by the actual vector displacement that p was moved. Also returns as fret
2008: the value of func at the returned location p . This is actually all accomplished by calling the
2009: routines mnbrak and brent .*/
1.126 brouard 2010: int ncom;
2011: double *pcom,*xicom;
2012: double (*nrfunc)(double []);
2013:
1.224 brouard 2014: #ifdef LINMINORIGINAL
1.126 brouard 2015: void linmin(double p[], double xi[], int n, double *fret,double (*func)(double []))
1.224 brouard 2016: #else
2017: void linmin(double p[], double xi[], int n, double *fret,double (*func)(double []), int *flat)
2018: #endif
1.126 brouard 2019: {
2020: double brent(double ax, double bx, double cx,
2021: double (*f)(double), double tol, double *xmin);
2022: double f1dim(double x);
2023: void mnbrak(double *ax, double *bx, double *cx, double *fa, double *fb,
2024: double *fc, double (*func)(double));
2025: int j;
2026: double xx,xmin,bx,ax;
2027: double fx,fb,fa;
1.187 brouard 2028:
1.203 brouard 2029: #ifdef LINMINORIGINAL
2030: #else
2031: double scale=10., axs, xxs; /* Scale added for infinity */
2032: #endif
2033:
1.126 brouard 2034: ncom=n;
2035: pcom=vector(1,n);
2036: xicom=vector(1,n);
2037: nrfunc=func;
2038: for (j=1;j<=n;j++) {
2039: pcom[j]=p[j];
1.202 brouard 2040: xicom[j]=xi[j]; /* Former scale xi[j] of currrent direction i */
1.126 brouard 2041: }
1.187 brouard 2042:
1.203 brouard 2043: #ifdef LINMINORIGINAL
2044: xx=1.;
2045: #else
2046: axs=0.0;
2047: xxs=1.;
2048: do{
2049: xx= xxs;
2050: #endif
1.187 brouard 2051: ax=0.;
2052: mnbrak(&ax,&xx,&bx,&fa,&fx,&fb,f1dim); /* Outputs: xtx[j]=pcom[j]+(*xx)*xicom[j]; fx=f(xtx[j]) */
2053: /* brackets with inputs ax=0 and xx=1, but points, pcom=p, and directions values, xicom=xi, are sent via f1dim(x) */
2054: /* 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)) */
2055: /* Outputs: fa=f(p(j)) and fx=f(p(j) + xxs * xi(j) ) and f(bx)= f(p(j)+ bx* xi(j)) */
2056: /* Given input ax=axs and xx=xxs, xx might be too far from ax to get a finite f(xx) */
2057: /* Searches on line, outputs (ax, xx, bx) such that fx < min(fa and fb) */
2058: /* 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 2059: #ifdef LINMINORIGINAL
2060: #else
2061: if (fx != fx){
1.224 brouard 2062: xxs=xxs/scale; /* Trying a smaller xx, closer to initial ax=0 */
2063: printf("|");
2064: fprintf(ficlog,"|");
1.203 brouard 2065: #ifdef DEBUGLINMIN
1.224 brouard 2066: 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 2067: #endif
2068: }
1.224 brouard 2069: }while(fx != fx && xxs > 1.e-5);
1.203 brouard 2070: #endif
2071:
1.191 brouard 2072: #ifdef DEBUGLINMIN
2073: 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 2074: 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 2075: #endif
1.224 brouard 2076: #ifdef LINMINORIGINAL
2077: #else
2078: if(fb == fx){ /* Flat function in the direction */
2079: xmin=xx;
2080: *flat=1;
2081: }else{
2082: *flat=0;
2083: #endif
2084: /*Flat mnbrak2 shift (*ax=0.000000000000, *fa=51626.272983130431), (*bx=-1.618034000000, *fb=51590.149499362531), (*cx=-4.236068025156, *fc=51590.149499362531) */
1.187 brouard 2085: *fret=brent(ax,xx,bx,f1dim,TOL,&xmin); /* Giving a bracketting triplet (ax, xx, bx), find a minimum, xmin, according to f1dim, *fret(xmin),*/
2086: /* fa = f(p[j] + ax * xi[j]), fx = f(p[j] + xx * xi[j]), fb = f(p[j] + bx * xi[j]) */
2087: /* fmin = f(p[j] + xmin * xi[j]) */
2088: /* P+lambda n in that direction (lambdamin), with TOL between abscisses */
2089: /* f1dim(xmin): for (j=1;j<=ncom;j++) xt[j]=pcom[j]+xmin*xicom[j]; */
1.126 brouard 2090: #ifdef DEBUG
1.224 brouard 2091: 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);
2092: 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);
2093: #endif
2094: #ifdef LINMINORIGINAL
2095: #else
2096: }
1.126 brouard 2097: #endif
1.191 brouard 2098: #ifdef DEBUGLINMIN
2099: printf("linmin end ");
1.202 brouard 2100: fprintf(ficlog,"linmin end ");
1.191 brouard 2101: #endif
1.126 brouard 2102: for (j=1;j<=n;j++) {
1.203 brouard 2103: #ifdef LINMINORIGINAL
2104: xi[j] *= xmin;
2105: #else
2106: #ifdef DEBUGLINMIN
2107: if(xxs <1.0)
2108: printf(" before xi[%d]=%12.8f", j,xi[j]);
2109: #endif
2110: 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) */
2111: #ifdef DEBUGLINMIN
2112: if(xxs <1.0)
2113: 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 );
2114: #endif
2115: #endif
1.187 brouard 2116: p[j] += xi[j]; /* Parameters values are updated accordingly */
1.126 brouard 2117: }
1.191 brouard 2118: #ifdef DEBUGLINMIN
1.203 brouard 2119: printf("\n");
1.191 brouard 2120: printf("Comparing last *frec(xmin=%12.8f)=%12.8f from Brent and frec(0.)=%12.8f \n", xmin, *fret, (*func)(p));
1.202 brouard 2121: 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 2122: for (j=1;j<=n;j++) {
1.202 brouard 2123: printf(" xi[%d]= %14.10f p[%d]= %12.7f",j,xi[j],j,p[j]);
2124: fprintf(ficlog," xi[%d]= %14.10f p[%d]= %12.7f",j,xi[j],j,p[j]);
2125: if(j % ncovmodel == 0){
1.191 brouard 2126: printf("\n");
1.202 brouard 2127: fprintf(ficlog,"\n");
2128: }
1.191 brouard 2129: }
1.203 brouard 2130: #else
1.191 brouard 2131: #endif
1.126 brouard 2132: free_vector(xicom,1,n);
2133: free_vector(pcom,1,n);
2134: }
2135:
2136:
2137: /*************** powell ************************/
1.162 brouard 2138: /*
2139: Minimization of a function func of n variables. Input consists of an initial starting point
2140: p[1..n] ; an initial matrix xi[1..n][1..n] , whose columns contain the initial set of di-
2141: rections (usually the n unit vectors); and ftol , the fractional tolerance in the function value
2142: such that failure to decrease by more than this amount on one iteration signals doneness. On
2143: output, p is set to the best point found, xi is the then-current direction set, fret is the returned
2144: function value at p , and iter is the number of iterations taken. The routine linmin is used.
2145: */
1.224 brouard 2146: #ifdef LINMINORIGINAL
2147: #else
2148: int *flatdir; /* Function is vanishing in that direction */
1.225 brouard 2149: int flat=0, flatd=0; /* Function is vanishing in that direction */
1.224 brouard 2150: #endif
1.126 brouard 2151: void powell(double p[], double **xi, int n, double ftol, int *iter, double *fret,
2152: double (*func)(double []))
2153: {
1.224 brouard 2154: #ifdef LINMINORIGINAL
2155: void linmin(double p[], double xi[], int n, double *fret,
1.126 brouard 2156: double (*func)(double []));
1.224 brouard 2157: #else
1.241 brouard 2158: void linmin(double p[], double xi[], int n, double *fret,
2159: double (*func)(double []),int *flat);
1.224 brouard 2160: #endif
1.239 brouard 2161: int i,ibig,j,jk,k;
1.126 brouard 2162: double del,t,*pt,*ptt,*xit;
1.181 brouard 2163: double directest;
1.126 brouard 2164: double fp,fptt;
2165: double *xits;
2166: int niterf, itmp;
1.224 brouard 2167: #ifdef LINMINORIGINAL
2168: #else
2169:
2170: flatdir=ivector(1,n);
2171: for (j=1;j<=n;j++) flatdir[j]=0;
2172: #endif
1.126 brouard 2173:
2174: pt=vector(1,n);
2175: ptt=vector(1,n);
2176: xit=vector(1,n);
2177: xits=vector(1,n);
2178: *fret=(*func)(p);
2179: for (j=1;j<=n;j++) pt[j]=p[j];
1.202 brouard 2180: rcurr_time = time(NULL);
1.126 brouard 2181: for (*iter=1;;++(*iter)) {
1.187 brouard 2182: fp=(*fret); /* From former iteration or initial value */
1.126 brouard 2183: ibig=0;
2184: del=0.0;
1.157 brouard 2185: rlast_time=rcurr_time;
2186: /* (void) gettimeofday(&curr_time,&tzp); */
2187: rcurr_time = time(NULL);
2188: curr_time = *localtime(&rcurr_time);
2189: printf("\nPowell iter=%d -2*LL=%.12f %ld sec. %ld sec.",*iter,*fret, rcurr_time-rlast_time, rcurr_time-rstart_time);fflush(stdout);
2190: fprintf(ficlog,"\nPowell iter=%d -2*LL=%.12f %ld sec. %ld sec.",*iter,*fret,rcurr_time-rlast_time, rcurr_time-rstart_time); fflush(ficlog);
2191: /* fprintf(ficrespow,"%d %.12f %ld",*iter,*fret,curr_time.tm_sec-start_time.tm_sec); */
1.192 brouard 2192: for (i=1;i<=n;i++) {
1.126 brouard 2193: fprintf(ficrespow," %.12lf", p[i]);
2194: }
1.239 brouard 2195: fprintf(ficrespow,"\n");fflush(ficrespow);
2196: printf("\n#model= 1 + age ");
2197: fprintf(ficlog,"\n#model= 1 + age ");
2198: if(nagesqr==1){
1.241 brouard 2199: printf(" + age*age ");
2200: fprintf(ficlog," + age*age ");
1.239 brouard 2201: }
2202: for(j=1;j <=ncovmodel-2;j++){
2203: if(Typevar[j]==0) {
2204: printf(" + V%d ",Tvar[j]);
2205: fprintf(ficlog," + V%d ",Tvar[j]);
2206: }else if(Typevar[j]==1) {
2207: printf(" + V%d*age ",Tvar[j]);
2208: fprintf(ficlog," + V%d*age ",Tvar[j]);
2209: }else if(Typevar[j]==2) {
2210: printf(" + V%d*V%d ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
2211: fprintf(ficlog," + V%d*V%d ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
2212: }
2213: }
1.126 brouard 2214: printf("\n");
1.239 brouard 2215: /* printf("12 47.0114589 0.0154322 33.2424412 0.3279905 2.3731903 */
2216: /* 13 -21.5392400 0.1118147 1.2680506 1.2973408 -1.0663662 */
1.126 brouard 2217: fprintf(ficlog,"\n");
1.239 brouard 2218: for(i=1,jk=1; i <=nlstate; i++){
2219: for(k=1; k <=(nlstate+ndeath); k++){
2220: if (k != i) {
2221: printf("%d%d ",i,k);
2222: fprintf(ficlog,"%d%d ",i,k);
2223: for(j=1; j <=ncovmodel; j++){
2224: printf("%12.7f ",p[jk]);
2225: fprintf(ficlog,"%12.7f ",p[jk]);
2226: jk++;
2227: }
2228: printf("\n");
2229: fprintf(ficlog,"\n");
2230: }
2231: }
2232: }
1.241 brouard 2233: if(*iter <=3 && *iter >1){
1.157 brouard 2234: tml = *localtime(&rcurr_time);
2235: strcpy(strcurr,asctime(&tml));
2236: rforecast_time=rcurr_time;
1.126 brouard 2237: itmp = strlen(strcurr);
2238: if(strcurr[itmp-1]=='\n') /* Windows outputs with a new line */
1.241 brouard 2239: strcurr[itmp-1]='\0';
1.162 brouard 2240: printf("\nConsidering the time needed for the last iteration #%d: %ld seconds,\n",*iter,rcurr_time-rlast_time);
1.157 brouard 2241: fprintf(ficlog,"\nConsidering the time needed for this last iteration #%d: %ld seconds,\n",*iter,rcurr_time-rlast_time);
1.126 brouard 2242: for(niterf=10;niterf<=30;niterf+=10){
1.241 brouard 2243: rforecast_time=rcurr_time+(niterf-*iter)*(rcurr_time-rlast_time);
2244: forecast_time = *localtime(&rforecast_time);
2245: strcpy(strfor,asctime(&forecast_time));
2246: itmp = strlen(strfor);
2247: if(strfor[itmp-1]=='\n')
2248: strfor[itmp-1]='\0';
2249: 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);
2250: 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 2251: }
2252: }
1.187 brouard 2253: for (i=1;i<=n;i++) { /* For each direction i */
2254: for (j=1;j<=n;j++) xit[j]=xi[j][i]; /* Directions stored from previous iteration with previous scales */
1.126 brouard 2255: fptt=(*fret);
2256: #ifdef DEBUG
1.203 brouard 2257: printf("fret=%lf, %lf, %lf \n", *fret, *fret, *fret);
2258: fprintf(ficlog, "fret=%lf, %lf, %lf \n", *fret, *fret, *fret);
1.126 brouard 2259: #endif
1.203 brouard 2260: printf("%d",i);fflush(stdout); /* print direction (parameter) i */
1.126 brouard 2261: fprintf(ficlog,"%d",i);fflush(ficlog);
1.224 brouard 2262: #ifdef LINMINORIGINAL
1.188 brouard 2263: linmin(p,xit,n,fret,func); /* Point p[n]. xit[n] has been loaded for direction i as input.*/
1.224 brouard 2264: #else
2265: linmin(p,xit,n,fret,func,&flat); /* Point p[n]. xit[n] has been loaded for direction i as input.*/
2266: flatdir[i]=flat; /* Function is vanishing in that direction i */
2267: #endif
2268: /* Outputs are fret(new point p) p is updated and xit rescaled */
1.188 brouard 2269: if (fabs(fptt-(*fret)) > del) { /* We are keeping the max gain on each of the n directions */
1.224 brouard 2270: /* because that direction will be replaced unless the gain del is small */
2271: /* in comparison with the 'probable' gain, mu^2, with the last average direction. */
2272: /* Unless the n directions are conjugate some gain in the determinant may be obtained */
2273: /* with the new direction. */
2274: del=fabs(fptt-(*fret));
2275: ibig=i;
1.126 brouard 2276: }
2277: #ifdef DEBUG
2278: printf("%d %.12e",i,(*fret));
2279: fprintf(ficlog,"%d %.12e",i,(*fret));
2280: for (j=1;j<=n;j++) {
1.224 brouard 2281: xits[j]=FMAX(fabs(p[j]-pt[j]),1.e-5);
2282: printf(" x(%d)=%.12e",j,xit[j]);
2283: fprintf(ficlog," x(%d)=%.12e",j,xit[j]);
1.126 brouard 2284: }
2285: for(j=1;j<=n;j++) {
1.225 brouard 2286: printf(" p(%d)=%.12e",j,p[j]);
2287: fprintf(ficlog," p(%d)=%.12e",j,p[j]);
1.126 brouard 2288: }
2289: printf("\n");
2290: fprintf(ficlog,"\n");
2291: #endif
1.187 brouard 2292: } /* end loop on each direction i */
2293: /* Convergence test will use last linmin estimation (fret) and compare former iteration (fp) */
1.188 brouard 2294: /* But p and xit have been updated at the end of linmin, *fret corresponds to new p, xit */
1.187 brouard 2295: /* New value of last point Pn is not computed, P(n-1) */
1.224 brouard 2296: for(j=1;j<=n;j++) {
1.225 brouard 2297: if(flatdir[j] >0){
2298: printf(" p(%d)=%lf flat=%d ",j,p[j],flatdir[j]);
2299: fprintf(ficlog," p(%d)=%lf flat=%d ",j,p[j],flatdir[j]);
2300: }
2301: /* printf("\n"); */
2302: /* fprintf(ficlog,"\n"); */
2303: }
1.243 brouard 2304: /* if (2.0*fabs(fp-(*fret)) <= ftol*(fabs(fp)+fabs(*fret))) { /\* Did we reach enough precision? *\/ */
2305: if (2.0*fabs(fp-(*fret)) <= ftol) { /* Did we reach enough precision? */
1.188 brouard 2306: /* We could compare with a chi^2. chisquare(0.95,ddl=1)=3.84 */
2307: /* By adding age*age in a model, the new -2LL should be lower and the difference follows a */
2308: /* a chisquare statistics with 1 degree. To be significant at the 95% level, it should have */
2309: /* decreased of more than 3.84 */
2310: /* By adding age*age and V1*age the gain (-2LL) should be more than 5.99 (ddl=2) */
2311: /* By using V1+V2+V3, the gain should be 7.82, compared with basic 1+age. */
2312: /* By adding 10 parameters more the gain should be 18.31 */
1.224 brouard 2313:
1.188 brouard 2314: /* Starting the program with initial values given by a former maximization will simply change */
2315: /* the scales of the directions and the directions, because the are reset to canonical directions */
2316: /* Thus the first calls to linmin will give new points and better maximizations until fp-(*fret) is */
2317: /* under the tolerance value. If the tolerance is very small 1.e-9, it could last long. */
1.126 brouard 2318: #ifdef DEBUG
2319: int k[2],l;
2320: k[0]=1;
2321: k[1]=-1;
2322: printf("Max: %.12e",(*func)(p));
2323: fprintf(ficlog,"Max: %.12e",(*func)(p));
2324: for (j=1;j<=n;j++) {
2325: printf(" %.12e",p[j]);
2326: fprintf(ficlog," %.12e",p[j]);
2327: }
2328: printf("\n");
2329: fprintf(ficlog,"\n");
2330: for(l=0;l<=1;l++) {
2331: for (j=1;j<=n;j++) {
2332: ptt[j]=p[j]+(p[j]-pt[j])*k[l];
2333: printf("l=%d j=%d ptt=%.12e, xits=%.12e, p=%.12e, xit=%.12e", l,j,ptt[j],xits[j],p[j],xit[j]);
2334: fprintf(ficlog,"l=%d j=%d ptt=%.12e, xits=%.12e, p=%.12e, xit=%.12e", l,j,ptt[j],xits[j],p[j],xit[j]);
2335: }
2336: printf("func(ptt)=%.12e, deriv=%.12e\n",(*func)(ptt),(ptt[j]-p[j])/((*func)(ptt)-(*func)(p)));
2337: fprintf(ficlog,"func(ptt)=%.12e, deriv=%.12e\n",(*func)(ptt),(ptt[j]-p[j])/((*func)(ptt)-(*func)(p)));
2338: }
2339: #endif
2340:
1.224 brouard 2341: #ifdef LINMINORIGINAL
2342: #else
2343: free_ivector(flatdir,1,n);
2344: #endif
1.126 brouard 2345: free_vector(xit,1,n);
2346: free_vector(xits,1,n);
2347: free_vector(ptt,1,n);
2348: free_vector(pt,1,n);
2349: return;
1.192 brouard 2350: } /* enough precision */
1.240 brouard 2351: if (*iter == ITMAX*n) nrerror("powell exceeding maximum iterations.");
1.181 brouard 2352: for (j=1;j<=n;j++) { /* Computes the extrapolated point P_0 + 2 (P_n-P_0) */
1.126 brouard 2353: ptt[j]=2.0*p[j]-pt[j];
2354: xit[j]=p[j]-pt[j];
2355: pt[j]=p[j];
2356: }
1.181 brouard 2357: fptt=(*func)(ptt); /* f_3 */
1.224 brouard 2358: #ifdef NODIRECTIONCHANGEDUNTILNITER /* No change in drections until some iterations are done */
2359: if (*iter <=4) {
1.225 brouard 2360: #else
2361: #endif
1.224 brouard 2362: #ifdef POWELLNOF3INFF1TEST /* skips test F3 <F1 */
1.192 brouard 2363: #else
1.161 brouard 2364: if (fptt < fp) { /* If extrapolated point is better, decide if we keep that new direction or not */
1.192 brouard 2365: #endif
1.162 brouard 2366: /* (x1 f1=fp), (x2 f2=*fret), (x3 f3=fptt), (xm fm) */
1.161 brouard 2367: /* From x1 (P0) distance of x2 is at h and x3 is 2h */
1.162 brouard 2368: /* Let f"(x2) be the 2nd derivative equal everywhere. */
2369: /* Then the parabolic through (x1,f1), (x2,f2) and (x3,f3) */
2370: /* will reach at f3 = fm + h^2/2 f"m ; f" = (f1 -2f2 +f3 ) / h**2 */
1.224 brouard 2371: /* Conditional for using this new direction is that mu^2 = (f1-2f2+f3)^2 /2 < del or directest <0 */
2372: /* also lamda^2=(f1-f2)^2/mu² is a parasite solution of powell */
2373: /* For powell, inclusion of this average direction is only if t(del)<0 or del inbetween mu^2 and lambda^2 */
1.161 brouard 2374: /* t=2.0*(fp-2.0*(*fret)+fptt)*SQR(fp-(*fret)-del)-del*SQR(fp-fptt); */
1.224 brouard 2375: /* Even if f3 <f1, directest can be negative and t >0 */
2376: /* mu² and del² are equal when f3=f1 */
2377: /* f3 < f1 : mu² < del <= lambda^2 both test are equivalent */
2378: /* f3 < f1 : mu² < lambda^2 < del then directtest is negative and powell t is positive */
2379: /* f3 > f1 : lambda² < mu^2 < del then t is negative and directest >0 */
2380: /* f3 > f1 : lambda² < del < mu^2 then t is positive and directest >0 */
1.183 brouard 2381: #ifdef NRCORIGINAL
2382: t=2.0*(fp-2.0*(*fret)+fptt)*SQR(fp-(*fret)-del)- del*SQR(fp-fptt); /* Original Numerical Recipes in C*/
2383: #else
2384: 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 2385: t= t- del*SQR(fp-fptt);
1.183 brouard 2386: #endif
1.202 brouard 2387: directest = fp-2.0*(*fret)+fptt - 2.0 * del; /* If delta was big enough we change it for a new direction */
1.161 brouard 2388: #ifdef DEBUG
1.181 brouard 2389: 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);
2390: 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 2391: printf("t3= %.12lf, t4= %.12lf, t3*= %.12lf, t4*= %.12lf\n",SQR(fp-(*fret)-del),SQR(fp-fptt),
2392: (fp-(*fret)-del)*(fp-(*fret)-del),(fp-fptt)*(fp-fptt));
2393: fprintf(ficlog,"t3= %.12lf, t4= %.12lf, t3*= %.12lf, t4*= %.12lf\n",SQR(fp-(*fret)-del),SQR(fp-fptt),
2394: (fp-(*fret)-del)*(fp-(*fret)-del),(fp-fptt)*(fp-fptt));
2395: 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);
2396: 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);
2397: #endif
1.183 brouard 2398: #ifdef POWELLORIGINAL
2399: if (t < 0.0) { /* Then we use it for new direction */
2400: #else
1.182 brouard 2401: if (directest*t < 0.0) { /* Contradiction between both tests */
1.224 brouard 2402: 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 2403: 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 2404: 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 2405: fprintf(ficlog,"f1-2f2+f3= %.12lf, f1-f2-del= %.12lf, f1-f3= %.12lf\n",fp-2.0*(*fret)+fptt, fp -(*fret) -del, fp-fptt);
2406: }
1.181 brouard 2407: if (directest < 0.0) { /* Then we use it for new direction */
2408: #endif
1.191 brouard 2409: #ifdef DEBUGLINMIN
1.234 brouard 2410: printf("Before linmin in direction P%d-P0\n",n);
2411: for (j=1;j<=n;j++) {
2412: printf(" Before xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
2413: fprintf(ficlog," Before xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
2414: if(j % ncovmodel == 0){
2415: printf("\n");
2416: fprintf(ficlog,"\n");
2417: }
2418: }
1.224 brouard 2419: #endif
2420: #ifdef LINMINORIGINAL
1.234 brouard 2421: linmin(p,xit,n,fret,func); /* computes minimum on the extrapolated direction: changes p and rescales xit.*/
1.224 brouard 2422: #else
1.234 brouard 2423: linmin(p,xit,n,fret,func,&flat); /* computes minimum on the extrapolated direction: changes p and rescales xit.*/
2424: flatdir[i]=flat; /* Function is vanishing in that direction i */
1.191 brouard 2425: #endif
1.234 brouard 2426:
1.191 brouard 2427: #ifdef DEBUGLINMIN
1.234 brouard 2428: for (j=1;j<=n;j++) {
2429: printf("After xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
2430: fprintf(ficlog,"After xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
2431: if(j % ncovmodel == 0){
2432: printf("\n");
2433: fprintf(ficlog,"\n");
2434: }
2435: }
1.224 brouard 2436: #endif
1.234 brouard 2437: for (j=1;j<=n;j++) {
2438: xi[j][ibig]=xi[j][n]; /* Replace direction with biggest decrease by last direction n */
2439: xi[j][n]=xit[j]; /* and this nth direction by the by the average p_0 p_n */
2440: }
1.224 brouard 2441: #ifdef LINMINORIGINAL
2442: #else
1.234 brouard 2443: for (j=1, flatd=0;j<=n;j++) {
2444: if(flatdir[j]>0)
2445: flatd++;
2446: }
2447: if(flatd >0){
1.255 brouard 2448: printf("%d flat directions: ",flatd);
2449: fprintf(ficlog,"%d flat directions :",flatd);
1.234 brouard 2450: for (j=1;j<=n;j++) {
2451: if(flatdir[j]>0){
2452: printf("%d ",j);
2453: fprintf(ficlog,"%d ",j);
2454: }
2455: }
2456: printf("\n");
2457: fprintf(ficlog,"\n");
2458: }
1.191 brouard 2459: #endif
1.234 brouard 2460: printf("Gaining to use new average direction of P0 P%d instead of biggest increase direction %d :\n",n,ibig);
2461: fprintf(ficlog,"Gaining to use new average direction of P0 P%d instead of biggest increase direction %d :\n",n,ibig);
2462:
1.126 brouard 2463: #ifdef DEBUG
1.234 brouard 2464: printf("Direction changed last moved %d in place of ibig=%d, new last is the average:\n",n,ibig);
2465: fprintf(ficlog,"Direction changed last moved %d in place of ibig=%d, new last is the average:\n",n,ibig);
2466: for(j=1;j<=n;j++){
2467: printf(" %lf",xit[j]);
2468: fprintf(ficlog," %lf",xit[j]);
2469: }
2470: printf("\n");
2471: fprintf(ficlog,"\n");
1.126 brouard 2472: #endif
1.192 brouard 2473: } /* end of t or directest negative */
1.224 brouard 2474: #ifdef POWELLNOF3INFF1TEST
1.192 brouard 2475: #else
1.234 brouard 2476: } /* end if (fptt < fp) */
1.192 brouard 2477: #endif
1.225 brouard 2478: #ifdef NODIRECTIONCHANGEDUNTILNITER /* No change in drections until some iterations are done */
1.234 brouard 2479: } /*NODIRECTIONCHANGEDUNTILNITER No change in drections until some iterations are done */
1.225 brouard 2480: #else
1.224 brouard 2481: #endif
1.234 brouard 2482: } /* loop iteration */
1.126 brouard 2483: }
1.234 brouard 2484:
1.126 brouard 2485: /**** Prevalence limit (stable or period prevalence) ****************/
1.234 brouard 2486:
1.235 brouard 2487: 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 2488: {
1.235 brouard 2489: /* Computes the prevalence limit in each live state at age x and for covariate combination ij
2490: (and selected quantitative values in nres)
2491: by left multiplying the unit
1.234 brouard 2492: matrix by transitions matrix until convergence is reached with precision ftolpl */
1.206 brouard 2493: /* Wx= Wx-1 Px-1= Wx-2 Px-2 Px-1 = Wx-n Px-n ... Px-2 Px-1 I */
2494: /* Wx is row vector: population in state 1, population in state 2, population dead */
2495: /* or prevalence in state 1, prevalence in state 2, 0 */
2496: /* newm is the matrix after multiplications, its rows are identical at a factor */
2497: /* Initial matrix pimij */
2498: /* {0.85204250825084937, 0.13044499163996345, 0.017512500109187184, */
2499: /* 0.090851990222114765, 0.88271245433047185, 0.026435555447413338, */
2500: /* 0, 0 , 1} */
2501: /*
2502: * and after some iteration: */
2503: /* {0.45504275246439968, 0.42731458730878791, 0.11764266022681241, */
2504: /* 0.45201005341706885, 0.42865420071559901, 0.11933574586733192, */
2505: /* 0, 0 , 1} */
2506: /* And prevalence by suppressing the deaths are close to identical rows in prlim: */
2507: /* {0.51571254859325999, 0.4842874514067399, */
2508: /* 0.51326036147820708, 0.48673963852179264} */
2509: /* If we start from prlim again, prlim tends to a constant matrix */
1.234 brouard 2510:
1.126 brouard 2511: int i, ii,j,k;
1.209 brouard 2512: double *min, *max, *meandiff, maxmax,sumnew=0.;
1.145 brouard 2513: /* double **matprod2(); */ /* test */
1.218 brouard 2514: double **out, cov[NCOVMAX+1], **pmij(); /* **pmmij is a global variable feeded with oldms etc */
1.126 brouard 2515: double **newm;
1.209 brouard 2516: double agefin, delaymax=200. ; /* 100 Max number of years to converge */
1.203 brouard 2517: int ncvloop=0;
1.169 brouard 2518:
1.209 brouard 2519: min=vector(1,nlstate);
2520: max=vector(1,nlstate);
2521: meandiff=vector(1,nlstate);
2522:
1.218 brouard 2523: /* Starting with matrix unity */
1.126 brouard 2524: for (ii=1;ii<=nlstate+ndeath;ii++)
2525: for (j=1;j<=nlstate+ndeath;j++){
2526: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
2527: }
1.169 brouard 2528:
2529: cov[1]=1.;
2530:
2531: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
1.202 brouard 2532: /* Start at agefin= age, computes the matrix of passage and loops decreasing agefin until convergence is reached */
1.126 brouard 2533: for(agefin=age-stepm/YEARM; agefin>=age-delaymax; agefin=agefin-stepm/YEARM){
1.202 brouard 2534: ncvloop++;
1.126 brouard 2535: newm=savm;
2536: /* Covariates have to be included here again */
1.138 brouard 2537: cov[2]=agefin;
1.187 brouard 2538: if(nagesqr==1)
2539: cov[3]= agefin*agefin;;
1.234 brouard 2540: for (k=1; k<=nsd;k++) { /* For single dummy covariates only */
2541: /* Here comes the value of the covariate 'ij' after renumbering k with single dummy covariates */
2542: cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,k)];
1.235 brouard 2543: /* 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 2544: }
2545: for (k=1; k<=nsq;k++) { /* For single varying covariates only */
2546: /* Here comes the value of quantitative after renumbering k with single quantitative covariates */
1.235 brouard 2547: cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k];
2548: /* 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 2549: }
1.237 brouard 2550: for (k=1; k<=cptcovage;k++){ /* For product with age */
1.234 brouard 2551: if(Dummy[Tvar[Tage[k]]]){
2552: cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2];
2553: } else{
1.235 brouard 2554: cov[2+nagesqr+Tage[k]]=Tqresult[nres][k];
1.234 brouard 2555: }
1.235 brouard 2556: /* 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 2557: }
1.237 brouard 2558: for (k=1; k<=cptcovprod;k++){ /* For product without age */
1.235 brouard 2559: /* 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 2560: if(Dummy[Tvard[k][1]==0]){
2561: if(Dummy[Tvard[k][2]==0]){
2562: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)];
2563: }else{
2564: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * Tqresult[nres][k];
2565: }
2566: }else{
2567: if(Dummy[Tvard[k][2]==0]){
2568: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][2]][codtabm(ij,k)] * Tqinvresult[nres][Tvard[k][1]];
2569: }else{
2570: cov[2+nagesqr+Tprod[k]]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]];
2571: }
2572: }
1.234 brouard 2573: }
1.138 brouard 2574: /*printf("ij=%d cptcovprod=%d tvar=%d ", ij, cptcovprod, Tvar[1]);*/
2575: /*printf("ij=%d cov[3]=%lf cov[4]=%lf \n",ij, cov[3],cov[4]);*/
2576: /*printf("ij=%d cov[3]=%lf \n",ij, cov[3]);*/
1.145 brouard 2577: /* savm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
2578: /* out=matprod2(newm, pmij(pmmij,cov,ncovmodel,x,nlstate),1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); /\* Bug Valgrind *\/ */
1.218 brouard 2579: /* age and covariate values of ij are in 'cov' */
1.142 brouard 2580: out=matprod2(newm, pmij(pmmij,cov,ncovmodel,x,nlstate),1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); /* Bug Valgrind */
1.138 brouard 2581:
1.126 brouard 2582: savm=oldm;
2583: oldm=newm;
1.209 brouard 2584:
2585: for(j=1; j<=nlstate; j++){
2586: max[j]=0.;
2587: min[j]=1.;
2588: }
2589: for(i=1;i<=nlstate;i++){
2590: sumnew=0;
2591: for(k=1; k<=ndeath; k++) sumnew+=newm[i][nlstate+k];
2592: for(j=1; j<=nlstate; j++){
2593: prlim[i][j]= newm[i][j]/(1-sumnew);
2594: max[j]=FMAX(max[j],prlim[i][j]);
2595: min[j]=FMIN(min[j],prlim[i][j]);
2596: }
2597: }
2598:
1.126 brouard 2599: maxmax=0.;
1.209 brouard 2600: for(j=1; j<=nlstate; j++){
2601: meandiff[j]=(max[j]-min[j])/(max[j]+min[j])*2.; /* mean difference for each column */
2602: maxmax=FMAX(maxmax,meandiff[j]);
2603: /* 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 2604: } /* j loop */
1.203 brouard 2605: *ncvyear= (int)age- (int)agefin;
1.208 brouard 2606: /* 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 2607: if(maxmax < ftolpl){
1.209 brouard 2608: /* printf("maxmax=%lf ncvloop=%ld, age=%d, agefin=%d ncvyear=%d \n", maxmax, ncvloop, (int)age, (int)agefin, *ncvyear); */
2609: free_vector(min,1,nlstate);
2610: free_vector(max,1,nlstate);
2611: free_vector(meandiff,1,nlstate);
1.126 brouard 2612: return prlim;
2613: }
1.169 brouard 2614: } /* age loop */
1.208 brouard 2615: /* After some age loop it doesn't converge */
1.209 brouard 2616: 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 2617: 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 2618: /* 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); */
2619: free_vector(min,1,nlstate);
2620: free_vector(max,1,nlstate);
2621: free_vector(meandiff,1,nlstate);
1.208 brouard 2622:
1.169 brouard 2623: return prlim; /* should not reach here */
1.126 brouard 2624: }
2625:
1.217 brouard 2626:
2627: /**** Back Prevalence limit (stable or period prevalence) ****************/
2628:
1.218 brouard 2629: /* 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) */
2630: /* 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 2631: double **bprevalim(double **bprlim, double ***prevacurrent, int nlstate, double x[], double age, double ftolpl, int *ncvyear, int ij, int nres)
1.217 brouard 2632: {
1.264 brouard 2633: /* 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 2634: matrix by transitions matrix until convergence is reached with precision ftolpl */
2635: /* Wx= Wx-1 Px-1= Wx-2 Px-2 Px-1 = Wx-n Px-n ... Px-2 Px-1 I */
2636: /* Wx is row vector: population in state 1, population in state 2, population dead */
2637: /* or prevalence in state 1, prevalence in state 2, 0 */
2638: /* newm is the matrix after multiplications, its rows are identical at a factor */
2639: /* Initial matrix pimij */
2640: /* {0.85204250825084937, 0.13044499163996345, 0.017512500109187184, */
2641: /* 0.090851990222114765, 0.88271245433047185, 0.026435555447413338, */
2642: /* 0, 0 , 1} */
2643: /*
2644: * and after some iteration: */
2645: /* {0.45504275246439968, 0.42731458730878791, 0.11764266022681241, */
2646: /* 0.45201005341706885, 0.42865420071559901, 0.11933574586733192, */
2647: /* 0, 0 , 1} */
2648: /* And prevalence by suppressing the deaths are close to identical rows in prlim: */
2649: /* {0.51571254859325999, 0.4842874514067399, */
2650: /* 0.51326036147820708, 0.48673963852179264} */
2651: /* If we start from prlim again, prlim tends to a constant matrix */
2652:
2653: int i, ii,j,k;
1.247 brouard 2654: int first=0;
1.217 brouard 2655: double *min, *max, *meandiff, maxmax,sumnew=0.;
2656: /* double **matprod2(); */ /* test */
2657: double **out, cov[NCOVMAX+1], **bmij();
2658: double **newm;
1.218 brouard 2659: double **dnewm, **doldm, **dsavm; /* for use */
2660: double **oldm, **savm; /* for use */
2661:
1.217 brouard 2662: double agefin, delaymax=200. ; /* 100 Max number of years to converge */
2663: int ncvloop=0;
2664:
2665: min=vector(1,nlstate);
2666: max=vector(1,nlstate);
2667: meandiff=vector(1,nlstate);
2668:
1.266 brouard 2669: dnewm=ddnewms; doldm=ddoldms; dsavm=ddsavms;
2670: oldm=oldms; savm=savms;
2671:
2672: /* Starting with matrix unity */
2673: for (ii=1;ii<=nlstate+ndeath;ii++)
2674: for (j=1;j<=nlstate+ndeath;j++){
1.217 brouard 2675: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
2676: }
2677:
2678: cov[1]=1.;
2679:
2680: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
2681: /* Start at agefin= age, computes the matrix of passage and loops decreasing agefin until convergence is reached */
1.218 brouard 2682: /* for(agefin=age+stepm/YEARM; agefin<=age+delaymax; agefin=agefin+stepm/YEARM){ /\* A changer en age *\/ */
2683: for(agefin=age; agefin<AGESUP; agefin=agefin+stepm/YEARM){ /* A changer en age */
1.217 brouard 2684: ncvloop++;
1.218 brouard 2685: newm=savm; /* oldm should be kept from previous iteration or unity at start */
2686: /* newm points to the allocated table savm passed by the function it can be written, savm could be reallocated */
1.217 brouard 2687: /* Covariates have to be included here again */
2688: cov[2]=agefin;
2689: if(nagesqr==1)
2690: cov[3]= agefin*agefin;;
1.242 brouard 2691: for (k=1; k<=nsd;k++) { /* For single dummy covariates only */
2692: /* Here comes the value of the covariate 'ij' after renumbering k with single dummy covariates */
2693: cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,k)];
1.264 brouard 2694: /* 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 2695: }
2696: /* for (k=1; k<=cptcovn;k++) { */
2697: /* /\* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,Tvar[k])]; *\/ */
2698: /* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,k)]; */
2699: /* /\* 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])]); *\/ */
2700: /* } */
2701: for (k=1; k<=nsq;k++) { /* For single varying covariates only */
2702: /* Here comes the value of quantitative after renumbering k with single quantitative covariates */
2703: cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k];
2704: /* 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]); */
2705: }
2706: /* for (k=1; k<=cptcovage;k++) cov[2+nagesqr+Tage[k]]=nbcode[Tvar[k]][codtabm(ij,k)]*cov[2]; */
2707: /* for (k=1; k<=cptcovprod;k++) /\* Useless *\/ */
2708: /* /\* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])]; *\/ */
2709: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)]; */
2710: for (k=1; k<=cptcovage;k++){ /* For product with age */
2711: if(Dummy[Tvar[Tage[k]]]){
2712: cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2];
2713: } else{
2714: cov[2+nagesqr+Tage[k]]=Tqresult[nres][k];
2715: }
2716: /* 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]); */
2717: }
2718: for (k=1; k<=cptcovprod;k++){ /* For product without age */
2719: /* 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]); */
2720: if(Dummy[Tvard[k][1]==0]){
2721: if(Dummy[Tvard[k][2]==0]){
2722: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)];
2723: }else{
2724: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * Tqresult[nres][k];
2725: }
2726: }else{
2727: if(Dummy[Tvard[k][2]==0]){
2728: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][2]][codtabm(ij,k)] * Tqinvresult[nres][Tvard[k][1]];
2729: }else{
2730: cov[2+nagesqr+Tprod[k]]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]];
2731: }
2732: }
1.217 brouard 2733: }
2734:
2735: /*printf("ij=%d cptcovprod=%d tvar=%d ", ij, cptcovprod, Tvar[1]);*/
2736: /*printf("ij=%d cov[3]=%lf cov[4]=%lf \n",ij, cov[3],cov[4]);*/
2737: /*printf("ij=%d cov[3]=%lf \n",ij, cov[3]);*/
2738: /* savm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
2739: /* out=matprod2(newm, pmij(pmmij,cov,ncovmodel,x,nlstate),1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); /\* Bug Valgrind *\/ */
1.218 brouard 2740: /* ij should be linked to the correct index of cov */
2741: /* age and covariate values ij are in 'cov', but we need to pass
2742: * ij for the observed prevalence at age and status and covariate
2743: * number: prevacurrent[(int)agefin][ii][ij]
2744: */
2745: /* 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 *\/ */
2746: /* 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 *\/ */
2747: 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 2748: /* if((int)age == 86 || (int)age == 87){ */
1.266 brouard 2749: /* printf(" Backward prevalim age=%d agefin=%d \n", (int) age, (int) agefin); */
2750: /* for(i=1; i<=nlstate+ndeath; i++) { */
2751: /* printf("%d newm= ",i); */
2752: /* for(j=1;j<=nlstate+ndeath;j++) { */
2753: /* printf("%f ",newm[i][j]); */
2754: /* } */
2755: /* printf("oldm * "); */
2756: /* for(j=1;j<=nlstate+ndeath;j++) { */
2757: /* printf("%f ",oldm[i][j]); */
2758: /* } */
1.268 brouard 2759: /* printf(" bmmij "); */
1.266 brouard 2760: /* for(j=1;j<=nlstate+ndeath;j++) { */
2761: /* printf("%f ",pmmij[i][j]); */
2762: /* } */
2763: /* printf("\n"); */
2764: /* } */
2765: /* } */
1.217 brouard 2766: savm=oldm;
2767: oldm=newm;
1.266 brouard 2768:
1.217 brouard 2769: for(j=1; j<=nlstate; j++){
2770: max[j]=0.;
2771: min[j]=1.;
2772: }
2773: for(j=1; j<=nlstate; j++){
2774: for(i=1;i<=nlstate;i++){
1.234 brouard 2775: /* bprlim[i][j]= newm[i][j]/(1-sumnew); */
2776: bprlim[i][j]= newm[i][j];
2777: max[i]=FMAX(max[i],bprlim[i][j]); /* Max in line */
2778: min[i]=FMIN(min[i],bprlim[i][j]);
1.217 brouard 2779: }
2780: }
1.218 brouard 2781:
1.217 brouard 2782: maxmax=0.;
2783: for(i=1; i<=nlstate; i++){
2784: meandiff[i]=(max[i]-min[i])/(max[i]+min[i])*2.; /* mean difference for each column */
2785: maxmax=FMAX(maxmax,meandiff[i]);
2786: /* 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 2787: } /* i loop */
1.217 brouard 2788: *ncvyear= -( (int)age- (int)agefin);
1.268 brouard 2789: /* printf("Back maxmax=%lf ncvloop=%d, age=%d, agefin=%d ncvyear=%d \n", maxmax, ncvloop, (int)age, (int)agefin, *ncvyear); */
1.217 brouard 2790: if(maxmax < ftolpl){
1.220 brouard 2791: /* printf("OK Back maxmax=%lf ncvloop=%d, age=%d, agefin=%d ncvyear=%d \n", maxmax, ncvloop, (int)age, (int)agefin, *ncvyear); */
1.217 brouard 2792: free_vector(min,1,nlstate);
2793: free_vector(max,1,nlstate);
2794: free_vector(meandiff,1,nlstate);
2795: return bprlim;
2796: }
2797: } /* age loop */
2798: /* After some age loop it doesn't converge */
1.247 brouard 2799: if(first){
2800: first=1;
2801: 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\
2802: 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);
2803: }
2804: 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 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: /* 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); */
2807: free_vector(min,1,nlstate);
2808: free_vector(max,1,nlstate);
2809: free_vector(meandiff,1,nlstate);
2810:
2811: return bprlim; /* should not reach here */
2812: }
2813:
1.126 brouard 2814: /*************** transition probabilities ***************/
2815:
2816: double **pmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate )
2817: {
1.138 brouard 2818: /* According to parameters values stored in x and the covariate's values stored in cov,
1.266 brouard 2819: computes the probability to be observed in state j (after stepm years) being in state i by appying the
1.138 brouard 2820: model to the ncovmodel covariates (including constant and age).
2821: lnpijopii=ln(pij/pii)= aij+bij*age+cij*v1+dij*v2+... = sum_nc=1^ncovmodel xij(nc)*cov[nc]
2822: and, according on how parameters are entered, the position of the coefficient xij(nc) of the
2823: ncth covariate in the global vector x is given by the formula:
2824: j<i nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel
2825: j>=i nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel
2826: Computes ln(pij/pii) (lnpijopii), deduces pij/pii by exponentiation,
2827: sums on j different of i to get 1-pii/pii, deduces pii, and then all pij.
1.266 brouard 2828: Outputs ps[i][j] or probability to be observed in j being in i according to
1.138 brouard 2829: the values of the covariates cov[nc] and corresponding parameter values x[nc+shiftij]
1.266 brouard 2830: Sum on j ps[i][j] should equal to 1.
1.138 brouard 2831: */
2832: double s1, lnpijopii;
1.126 brouard 2833: /*double t34;*/
1.164 brouard 2834: int i,j, nc, ii, jj;
1.126 brouard 2835:
1.223 brouard 2836: for(i=1; i<= nlstate; i++){
2837: for(j=1; j<i;j++){
2838: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
2839: /*lnpijopii += param[i][j][nc]*cov[nc];*/
2840: lnpijopii += x[nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel]*cov[nc];
2841: /* printf("Int j<i s1=%.17e, lnpijopii=%.17e\n",s1,lnpijopii); */
2842: }
2843: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
2844: /* printf("s1=%.17e, lnpijopii=%.17e\n",s1,lnpijopii); */
2845: }
2846: for(j=i+1; j<=nlstate+ndeath;j++){
2847: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
2848: /*lnpijopii += x[(i-1)*nlstate*ncovmodel+(j-2)*ncovmodel+nc+(i-1)*(ndeath-1)*ncovmodel]*cov[nc];*/
2849: lnpijopii += x[nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel]*cov[nc];
2850: /* printf("Int j>i s1=%.17e, lnpijopii=%.17e %lx %lx\n",s1,lnpijopii,s1,lnpijopii); */
2851: }
2852: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
2853: }
2854: }
1.218 brouard 2855:
1.223 brouard 2856: for(i=1; i<= nlstate; i++){
2857: s1=0;
2858: for(j=1; j<i; j++){
2859: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
2860: /*printf("debug1 %d %d ps=%lf exp(ps)=%lf s1+=%lf\n",i,j,ps[i][j],exp(ps[i][j]),s1); */
2861: }
2862: for(j=i+1; j<=nlstate+ndeath; j++){
2863: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
2864: /*printf("debug2 %d %d ps=%lf exp(ps)=%lf s1+=%lf\n",i,j,ps[i][j],exp(ps[i][j]),s1); */
2865: }
2866: /* s1= sum_{j<>i} pij/pii=(1-pii)/pii and thus pii is known from s1 */
2867: ps[i][i]=1./(s1+1.);
2868: /* Computing other pijs */
2869: for(j=1; j<i; j++)
2870: ps[i][j]= exp(ps[i][j])*ps[i][i];
2871: for(j=i+1; j<=nlstate+ndeath; j++)
2872: ps[i][j]= exp(ps[i][j])*ps[i][i];
2873: /* ps[i][nlstate+1]=1.-s1- ps[i][i];*/ /* Sum should be 1 */
2874: } /* end i */
1.218 brouard 2875:
1.223 brouard 2876: for(ii=nlstate+1; ii<= nlstate+ndeath; ii++){
2877: for(jj=1; jj<= nlstate+ndeath; jj++){
2878: ps[ii][jj]=0;
2879: ps[ii][ii]=1;
2880: }
2881: }
1.218 brouard 2882:
2883:
1.223 brouard 2884: /* for(ii=1; ii<= nlstate+ndeath; ii++){ */
2885: /* for(jj=1; jj<= nlstate+ndeath; jj++){ */
2886: /* printf(" pmij ps[%d][%d]=%lf ",ii,jj,ps[ii][jj]); */
2887: /* } */
2888: /* printf("\n "); */
2889: /* } */
2890: /* printf("\n ");printf("%lf ",cov[2]);*/
2891: /*
2892: for(i=1; i<= npar; i++) printf("%f ",x[i]);
1.218 brouard 2893: goto end;*/
1.266 brouard 2894: return ps; /* Pointer is unchanged since its call */
1.126 brouard 2895: }
2896:
1.218 brouard 2897: /*************** backward transition probabilities ***************/
2898:
2899: /* 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 ) */
2900: /* double **bmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate, double ***prevacurrent, double ***dnewm, double **doldm, double **dsavm, int ij ) */
2901: double **bmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate, double ***prevacurrent, int ij )
2902: {
1.266 brouard 2903: /* Computes the backward probability at age agefin and covariate combination ij. In fact cov is already filled and x too.
2904: * 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 2905: */
1.218 brouard 2906: int i, ii, j,k;
1.222 brouard 2907:
2908: double **out, **pmij();
2909: double sumnew=0.;
1.218 brouard 2910: double agefin;
1.268 brouard 2911: 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 2912: double **dnewm, **dsavm, **doldm;
2913: double **bbmij;
2914:
1.218 brouard 2915: doldm=ddoldms; /* global pointers */
1.222 brouard 2916: dnewm=ddnewms;
2917: dsavm=ddsavms;
2918:
2919: agefin=cov[2];
1.268 brouard 2920: /* Bx = Diag(w_x) P_x Diag(Sum_i w^i_x p^ij_x */
1.222 brouard 2921: /* bmij *//* age is cov[2], ij is included in cov, but we need for
1.266 brouard 2922: the observed prevalence (with this covariate ij) at beginning of transition */
2923: /* dsavm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
1.268 brouard 2924:
2925: /* P_x */
1.266 brouard 2926: pmmij=pmij(pmmij,cov,ncovmodel,x,nlstate); /*This is forward probability from agefin to agefin + stepm */
1.268 brouard 2927: /* outputs pmmij which is a stochastic matrix in row */
2928:
2929: /* Diag(w_x) */
2930: /* Problem with prevacurrent which can be zero */
2931: sumnew=0.;
1.269 ! brouard 2932: /*for (ii=1;ii<=nlstate+ndeath;ii++){*/
1.268 brouard 2933: for (ii=1;ii<=nlstate;ii++){ /* Only on live states */
1.269 ! brouard 2934: /* printf(" agefin=%d, ii=%d, ij=%d, prev=%f\n",(int)agefin,ii, ij, prevacurrent[(int)agefin][ii][ij]); */
1.268 brouard 2935: sumnew+=prevacurrent[(int)agefin][ii][ij];
2936: }
2937: if(sumnew >0.01){ /* At least some value in the prevalence */
2938: for (ii=1;ii<=nlstate+ndeath;ii++){
2939: for (j=1;j<=nlstate+ndeath;j++)
1.269 ! brouard 2940: doldm[ii][j]=(ii==j ? prevacurrent[(int)agefin][ii][ij]/sumnew : 0.0);
1.268 brouard 2941: }
2942: }else{
2943: for (ii=1;ii<=nlstate+ndeath;ii++){
2944: for (j=1;j<=nlstate+ndeath;j++)
2945: doldm[ii][j]=(ii==j ? 1./nlstate : 0.0);
2946: }
2947: /* if(sumnew <0.9){ */
2948: /* printf("Problem internal bmij B: sum on i wi <0.9: j=%d, sum_i wi=%lf,agefin=%d\n",j,sumnew, (int)agefin); */
2949: /* } */
2950: }
2951: k3=0.0; /* We put the last diagonal to 0 */
2952: for (ii=nlstate+1;ii<=nlstate+ndeath;ii++){
2953: doldm[ii][ii]= k3;
2954: }
2955: /* End doldm, At the end doldm is diag[(w_i)] */
2956:
2957: /* left Product of this diag matrix by pmmij=Px (dnewm=dsavm*doldm) */
2958: bbmij=matprod2(dnewm, doldm,1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, pmmij); /* Bug Valgrind */
2959:
2960: /* Diag(Sum_i w^i_x p^ij_x */
2961: /* 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 2962: for (j=1;j<=nlstate+ndeath;j++){
1.268 brouard 2963: sumnew=0.;
1.222 brouard 2964: for (ii=1;ii<=nlstate;ii++){
1.266 brouard 2965: /* sumnew+=dsavm[ii][j]*prevacurrent[(int)agefin][ii][ij]; */
1.268 brouard 2966: sumnew+=pmmij[ii][j]*doldm[ii][ii]; /* Yes prevalence at beginning of transition */
1.222 brouard 2967: } /* sumnew is (N11+N21)/N..= N.1/N.. = sum on i of w_i pij */
1.268 brouard 2968: for (ii=1;ii<=nlstate+ndeath;ii++){
1.222 brouard 2969: /* if(agefin >= agemaxpar && agefin <= agemaxpar+stepm/YEARM){ */
1.268 brouard 2970: /* dsavm[ii][j]=(ii==j ? 1./sumnew : 0.0); */
1.222 brouard 2971: /* }else if(agefin >= agemaxpar+stepm/YEARM){ */
1.268 brouard 2972: /* dsavm[ii][j]=(ii==j ? 1./sumnew : 0.0); */
1.222 brouard 2973: /* }else */
1.268 brouard 2974: dsavm[ii][j]=(ii==j ? 1./sumnew : 0.0);
2975: } /*End ii */
2976: } /* 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 */
2977:
2978: ps=matprod2(ps, dnewm,1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, dsavm); /* Bug Valgrind */
2979: /* ps is now diag[w_i] * Px * diag [1/(w_1p1i+w_2 p2i)] */
1.222 brouard 2980: /* end bmij */
1.266 brouard 2981: return ps; /*pointer is unchanged */
1.218 brouard 2982: }
1.217 brouard 2983: /*************** transition probabilities ***************/
2984:
1.218 brouard 2985: double **bpmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate )
1.217 brouard 2986: {
2987: /* According to parameters values stored in x and the covariate's values stored in cov,
2988: computes the probability to be observed in state j being in state i by appying the
2989: model to the ncovmodel covariates (including constant and age).
2990: lnpijopii=ln(pij/pii)= aij+bij*age+cij*v1+dij*v2+... = sum_nc=1^ncovmodel xij(nc)*cov[nc]
2991: and, according on how parameters are entered, the position of the coefficient xij(nc) of the
2992: ncth covariate in the global vector x is given by the formula:
2993: j<i nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel
2994: j>=i nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel
2995: Computes ln(pij/pii) (lnpijopii), deduces pij/pii by exponentiation,
2996: sums on j different of i to get 1-pii/pii, deduces pii, and then all pij.
2997: Outputs ps[i][j] the probability to be observed in j being in j according to
2998: the values of the covariates cov[nc] and corresponding parameter values x[nc+shiftij]
2999: */
3000: double s1, lnpijopii;
3001: /*double t34;*/
3002: int i,j, nc, ii, jj;
3003:
1.234 brouard 3004: for(i=1; i<= nlstate; i++){
3005: for(j=1; j<i;j++){
3006: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
3007: /*lnpijopii += param[i][j][nc]*cov[nc];*/
3008: lnpijopii += x[nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel]*cov[nc];
3009: /* printf("Int j<i s1=%.17e, lnpijopii=%.17e\n",s1,lnpijopii); */
3010: }
3011: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
3012: /* printf("s1=%.17e, lnpijopii=%.17e\n",s1,lnpijopii); */
3013: }
3014: for(j=i+1; j<=nlstate+ndeath;j++){
3015: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
3016: /*lnpijopii += x[(i-1)*nlstate*ncovmodel+(j-2)*ncovmodel+nc+(i-1)*(ndeath-1)*ncovmodel]*cov[nc];*/
3017: lnpijopii += x[nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel]*cov[nc];
3018: /* printf("Int j>i s1=%.17e, lnpijopii=%.17e %lx %lx\n",s1,lnpijopii,s1,lnpijopii); */
3019: }
3020: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
3021: }
3022: }
3023:
3024: for(i=1; i<= nlstate; i++){
3025: s1=0;
3026: for(j=1; j<i; j++){
3027: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
3028: /*printf("debug1 %d %d ps=%lf exp(ps)=%lf s1+=%lf\n",i,j,ps[i][j],exp(ps[i][j]),s1); */
3029: }
3030: for(j=i+1; j<=nlstate+ndeath; j++){
3031: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
3032: /*printf("debug2 %d %d ps=%lf exp(ps)=%lf s1+=%lf\n",i,j,ps[i][j],exp(ps[i][j]),s1); */
3033: }
3034: /* s1= sum_{j<>i} pij/pii=(1-pii)/pii and thus pii is known from s1 */
3035: ps[i][i]=1./(s1+1.);
3036: /* Computing other pijs */
3037: for(j=1; j<i; j++)
3038: ps[i][j]= exp(ps[i][j])*ps[i][i];
3039: for(j=i+1; j<=nlstate+ndeath; j++)
3040: ps[i][j]= exp(ps[i][j])*ps[i][i];
3041: /* ps[i][nlstate+1]=1.-s1- ps[i][i];*/ /* Sum should be 1 */
3042: } /* end i */
3043:
3044: for(ii=nlstate+1; ii<= nlstate+ndeath; ii++){
3045: for(jj=1; jj<= nlstate+ndeath; jj++){
3046: ps[ii][jj]=0;
3047: ps[ii][ii]=1;
3048: }
3049: }
3050: /* Added for backcast */ /* Transposed matrix too */
3051: for(jj=1; jj<= nlstate+ndeath; jj++){
3052: s1=0.;
3053: for(ii=1; ii<= nlstate+ndeath; ii++){
3054: s1+=ps[ii][jj];
3055: }
3056: for(ii=1; ii<= nlstate; ii++){
3057: ps[ii][jj]=ps[ii][jj]/s1;
3058: }
3059: }
3060: /* Transposition */
3061: for(jj=1; jj<= nlstate+ndeath; jj++){
3062: for(ii=jj; ii<= nlstate+ndeath; ii++){
3063: s1=ps[ii][jj];
3064: ps[ii][jj]=ps[jj][ii];
3065: ps[jj][ii]=s1;
3066: }
3067: }
3068: /* for(ii=1; ii<= nlstate+ndeath; ii++){ */
3069: /* for(jj=1; jj<= nlstate+ndeath; jj++){ */
3070: /* printf(" pmij ps[%d][%d]=%lf ",ii,jj,ps[ii][jj]); */
3071: /* } */
3072: /* printf("\n "); */
3073: /* } */
3074: /* printf("\n ");printf("%lf ",cov[2]);*/
3075: /*
3076: for(i=1; i<= npar; i++) printf("%f ",x[i]);
3077: goto end;*/
3078: return ps;
1.217 brouard 3079: }
3080:
3081:
1.126 brouard 3082: /**************** Product of 2 matrices ******************/
3083:
1.145 brouard 3084: double **matprod2(double **out, double **in,int nrl, int nrh, int ncl, int nch, int ncolol, int ncoloh, double **b)
1.126 brouard 3085: {
3086: /* Computes the matrix product of in(1,nrh-nrl+1)(1,nch-ncl+1) times
3087: b(1,nch-ncl+1)(1,ncoloh-ncolol+1) into out(...) */
3088: /* in, b, out are matrice of pointers which should have been initialized
3089: before: only the contents of out is modified. The function returns
3090: a pointer to pointers identical to out */
1.145 brouard 3091: int i, j, k;
1.126 brouard 3092: for(i=nrl; i<= nrh; i++)
1.145 brouard 3093: for(k=ncolol; k<=ncoloh; k++){
3094: out[i][k]=0.;
3095: for(j=ncl; j<=nch; j++)
3096: out[i][k] +=in[i][j]*b[j][k];
3097: }
1.126 brouard 3098: return out;
3099: }
3100:
3101:
3102: /************* Higher Matrix Product ***************/
3103:
1.235 brouard 3104: 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 3105: {
1.218 brouard 3106: /* Computes the transition matrix starting at age 'age' and combination of covariate values corresponding to ij over
1.126 brouard 3107: 'nhstepm*hstepm*stepm' months (i.e. until
3108: age (in years) age+nhstepm*hstepm*stepm/12) by multiplying
3109: nhstepm*hstepm matrices.
3110: Output is stored in matrix po[i][j][h] for h every 'hstepm' step
3111: (typically every 2 years instead of every month which is too big
3112: for the memory).
3113: Model is determined by parameters x and covariates have to be
3114: included manually here.
3115:
3116: */
3117:
3118: int i, j, d, h, k;
1.131 brouard 3119: double **out, cov[NCOVMAX+1];
1.126 brouard 3120: double **newm;
1.187 brouard 3121: double agexact;
1.214 brouard 3122: double agebegin, ageend;
1.126 brouard 3123:
3124: /* Hstepm could be zero and should return the unit matrix */
3125: for (i=1;i<=nlstate+ndeath;i++)
3126: for (j=1;j<=nlstate+ndeath;j++){
3127: oldm[i][j]=(i==j ? 1.0 : 0.0);
3128: po[i][j][0]=(i==j ? 1.0 : 0.0);
3129: }
3130: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
3131: for(h=1; h <=nhstepm; h++){
3132: for(d=1; d <=hstepm; d++){
3133: newm=savm;
3134: /* Covariates have to be included here again */
3135: cov[1]=1.;
1.214 brouard 3136: agexact=age+((h-1)*hstepm + (d-1))*stepm/YEARM; /* age just before transition */
1.187 brouard 3137: cov[2]=agexact;
3138: if(nagesqr==1)
1.227 brouard 3139: cov[3]= agexact*agexact;
1.235 brouard 3140: for (k=1; k<=nsd;k++) { /* For single dummy covariates only */
3141: /* Here comes the value of the covariate 'ij' after renumbering k with single dummy covariates */
3142: cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,k)];
3143: /* 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)); */
3144: }
3145: for (k=1; k<=nsq;k++) { /* For single varying covariates only */
3146: /* Here comes the value of quantitative after renumbering k with single quantitative covariates */
3147: cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k];
3148: /* 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]); */
3149: }
3150: for (k=1; k<=cptcovage;k++){
3151: if(Dummy[Tvar[Tage[k]]]){
3152: cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2];
3153: } else{
3154: cov[2+nagesqr+Tage[k]]=Tqresult[nres][k];
3155: }
3156: /* 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]); */
3157: }
3158: for (k=1; k<=cptcovprod;k++){ /* */
3159: /* 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]); */
3160: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)];
3161: }
3162: /* for (k=1; k<=cptcovn;k++) */
3163: /* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,k)]; */
3164: /* for (k=1; k<=cptcovage;k++) /\* Should start at cptcovn+1 *\/ */
3165: /* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2]; */
3166: /* for (k=1; k<=cptcovprod;k++) /\* Useless because included in cptcovn *\/ */
3167: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)]*nbcode[Tvard[k][2]][codtabm(ij,k)]; */
1.227 brouard 3168:
3169:
1.126 brouard 3170: /*printf("hxi cptcov=%d cptcode=%d\n",cptcov,cptcode);*/
3171: /*printf("h=%d d=%d age=%f cov=%f\n",h,d,age,cov[2]);*/
1.218 brouard 3172: /* right multiplication of oldm by the current matrix */
1.126 brouard 3173: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath,
3174: pmij(pmmij,cov,ncovmodel,x,nlstate));
1.217 brouard 3175: /* if((int)age == 70){ */
3176: /* printf(" Forward hpxij age=%d agexact=%f d=%d nhstepm=%d hstepm=%d\n", (int) age, agexact, d, nhstepm, hstepm); */
3177: /* for(i=1; i<=nlstate+ndeath; i++) { */
3178: /* printf("%d pmmij ",i); */
3179: /* for(j=1;j<=nlstate+ndeath;j++) { */
3180: /* printf("%f ",pmmij[i][j]); */
3181: /* } */
3182: /* printf(" oldm "); */
3183: /* for(j=1;j<=nlstate+ndeath;j++) { */
3184: /* printf("%f ",oldm[i][j]); */
3185: /* } */
3186: /* printf("\n"); */
3187: /* } */
3188: /* } */
1.126 brouard 3189: savm=oldm;
3190: oldm=newm;
3191: }
3192: for(i=1; i<=nlstate+ndeath; i++)
3193: for(j=1;j<=nlstate+ndeath;j++) {
1.267 brouard 3194: po[i][j][h]=newm[i][j];
3195: /*if(h==nhstepm) printf("po[%d][%d][%d]=%f ",i,j,h,po[i][j][h]);*/
1.126 brouard 3196: }
1.128 brouard 3197: /*printf("h=%d ",h);*/
1.126 brouard 3198: } /* end h */
1.267 brouard 3199: /* printf("\n H=%d \n",h); */
1.126 brouard 3200: return po;
3201: }
3202:
1.217 brouard 3203: /************* Higher Back Matrix Product ***************/
1.218 brouard 3204: /* 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 3205: 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 3206: {
1.266 brouard 3207: /* For a combination of dummy covariate ij, computes the transition matrix starting at age 'age' over
1.217 brouard 3208: 'nhstepm*hstepm*stepm' months (i.e. until
1.218 brouard 3209: age (in years) age+nhstepm*hstepm*stepm/12) by multiplying
3210: nhstepm*hstepm matrices.
3211: Output is stored in matrix po[i][j][h] for h every 'hstepm' step
3212: (typically every 2 years instead of every month which is too big
1.217 brouard 3213: for the memory).
1.218 brouard 3214: Model is determined by parameters x and covariates have to be
1.266 brouard 3215: included manually here. Then we use a call to bmij(x and cov)
3216: The addresss of po (p3mat allocated to the dimension of nhstepm) should be stored for output
1.222 brouard 3217: */
1.217 brouard 3218:
3219: int i, j, d, h, k;
1.266 brouard 3220: double **out, cov[NCOVMAX+1], **bmij();
3221: double **newm, ***newmm;
1.217 brouard 3222: double agexact;
3223: double agebegin, ageend;
1.222 brouard 3224: double **oldm, **savm;
1.217 brouard 3225:
1.266 brouard 3226: newmm=po; /* To be saved */
3227: oldm=oldms;savm=savms; /* Global pointers */
1.217 brouard 3228: /* Hstepm could be zero and should return the unit matrix */
3229: for (i=1;i<=nlstate+ndeath;i++)
3230: for (j=1;j<=nlstate+ndeath;j++){
3231: oldm[i][j]=(i==j ? 1.0 : 0.0);
3232: po[i][j][0]=(i==j ? 1.0 : 0.0);
3233: }
3234: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
3235: for(h=1; h <=nhstepm; h++){
3236: for(d=1; d <=hstepm; d++){
3237: newm=savm;
3238: /* Covariates have to be included here again */
3239: cov[1]=1.;
1.266 brouard 3240: agexact=age-((h-1)*hstepm + (d))*stepm/YEARM; /* age just before transition, d or d-1? */
1.217 brouard 3241: /* agexact=age+((h-1)*hstepm + (d-1))*stepm/YEARM; /\* age just before transition *\/ */
3242: cov[2]=agexact;
3243: if(nagesqr==1)
1.222 brouard 3244: cov[3]= agexact*agexact;
1.266 brouard 3245: for (k=1; k<=cptcovn;k++){
3246: /* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,k)]; */
3247: /* /\* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,Tvar[k])]; *\/ */
3248: cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,k)];
3249: /* 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)); */
3250: }
1.267 brouard 3251: for (k=1; k<=nsq;k++) { /* For single varying covariates only */
3252: /* Here comes the value of quantitative after renumbering k with single quantitative covariates */
3253: cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k];
3254: /* 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]); */
3255: }
3256: for (k=1; k<=cptcovage;k++){ /* Should start at cptcovn+1 */
3257: if(Dummy[Tvar[Tage[k]]]){
3258: cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2];
3259: } else{
3260: cov[2+nagesqr+Tage[k]]=Tqresult[nres][k];
3261: }
3262: /* 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]); */
3263: }
3264: for (k=1; k<=cptcovprod;k++){ /* Useless because included in cptcovn */
1.222 brouard 3265: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)]*nbcode[Tvard[k][2]][codtabm(ij,k)];
1.267 brouard 3266: }
1.217 brouard 3267: /*printf("hxi cptcov=%d cptcode=%d\n",cptcov,cptcode);*/
3268: /*printf("h=%d d=%d age=%f cov=%f\n",h,d,age,cov[2]);*/
1.267 brouard 3269:
1.218 brouard 3270: /* Careful transposed matrix */
1.266 brouard 3271: /* age is in cov[2], prevacurrent at beginning of transition. */
1.218 brouard 3272: /* out=matprod2(newm, bmij(pmmij,cov,ncovmodel,x,nlstate,prevacurrent, dnewm, doldm, dsavm,ij),\ */
1.222 brouard 3273: /* 1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); */
1.218 brouard 3274: out=matprod2(newm, bmij(pmmij,cov,ncovmodel,x,nlstate,prevacurrent,ij),\
1.222 brouard 3275: 1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm);
1.217 brouard 3276: /* if((int)age == 70){ */
3277: /* printf(" Backward hbxij age=%d agexact=%f d=%d nhstepm=%d hstepm=%d\n", (int) age, agexact, d, nhstepm, hstepm); */
3278: /* for(i=1; i<=nlstate+ndeath; i++) { */
3279: /* printf("%d pmmij ",i); */
3280: /* for(j=1;j<=nlstate+ndeath;j++) { */
3281: /* printf("%f ",pmmij[i][j]); */
3282: /* } */
3283: /* printf(" oldm "); */
3284: /* for(j=1;j<=nlstate+ndeath;j++) { */
3285: /* printf("%f ",oldm[i][j]); */
3286: /* } */
3287: /* printf("\n"); */
3288: /* } */
3289: /* } */
3290: savm=oldm;
3291: oldm=newm;
3292: }
3293: for(i=1; i<=nlstate+ndeath; i++)
3294: for(j=1;j<=nlstate+ndeath;j++) {
1.222 brouard 3295: po[i][j][h]=newm[i][j];
1.268 brouard 3296: /* if(h==nhstepm) */
3297: /* printf("po[%d][%d][%d]=%f ",i,j,h,po[i][j][h]); */
1.217 brouard 3298: }
1.268 brouard 3299: /* printf("h=%d %.1f ",h, agexact); */
1.217 brouard 3300: } /* end h */
1.268 brouard 3301: /* printf("\n H=%d nhs=%d \n",h, nhstepm); */
1.217 brouard 3302: return po;
3303: }
3304:
3305:
1.162 brouard 3306: #ifdef NLOPT
3307: double myfunc(unsigned n, const double *p1, double *grad, void *pd){
3308: double fret;
3309: double *xt;
3310: int j;
3311: myfunc_data *d2 = (myfunc_data *) pd;
3312: /* xt = (p1-1); */
3313: xt=vector(1,n);
3314: for (j=1;j<=n;j++) xt[j]=p1[j-1]; /* xt[1]=p1[0] */
3315:
3316: fret=(d2->function)(xt); /* p xt[1]@8 is fine */
3317: /* fret=(*func)(xt); /\* p xt[1]@8 is fine *\/ */
3318: printf("Function = %.12lf ",fret);
3319: for (j=1;j<=n;j++) printf(" %d %.8lf", j, xt[j]);
3320: printf("\n");
3321: free_vector(xt,1,n);
3322: return fret;
3323: }
3324: #endif
1.126 brouard 3325:
3326: /*************** log-likelihood *************/
3327: double func( double *x)
3328: {
1.226 brouard 3329: int i, ii, j, k, mi, d, kk;
3330: int ioffset=0;
3331: double l, ll[NLSTATEMAX+1], cov[NCOVMAX+1];
3332: double **out;
3333: double lli; /* Individual log likelihood */
3334: int s1, s2;
1.228 brouard 3335: 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 3336: double bbh, survp;
3337: long ipmx;
3338: double agexact;
3339: /*extern weight */
3340: /* We are differentiating ll according to initial status */
3341: /* for (i=1;i<=npar;i++) printf("%f ", x[i]);*/
3342: /*for(i=1;i<imx;i++)
3343: printf(" %d\n",s[4][i]);
3344: */
1.162 brouard 3345:
1.226 brouard 3346: ++countcallfunc;
1.162 brouard 3347:
1.226 brouard 3348: cov[1]=1.;
1.126 brouard 3349:
1.226 brouard 3350: for(k=1; k<=nlstate; k++) ll[k]=0.;
1.224 brouard 3351: ioffset=0;
1.226 brouard 3352: if(mle==1){
3353: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
3354: /* Computes the values of the ncovmodel covariates of the model
3355: depending if the covariates are fixed or varying (age dependent) and stores them in cov[]
3356: Then computes with function pmij which return a matrix p[i][j] giving the elementary probability
3357: to be observed in j being in i according to the model.
3358: */
1.243 brouard 3359: ioffset=2+nagesqr ;
1.233 brouard 3360: /* Fixed */
1.234 brouard 3361: for (k=1; k<=ncovf;k++){ /* Simple and product fixed covariates without age* products */
3362: 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)*/
3363: }
1.226 brouard 3364: /* In model V2+V1*V4+age*V3+V3*V2 Tvar[1] is V2, Tvar[2=V1*V4]
3365: is 6, Tvar[3=age*V3] should not be computed because of age Tvar[4=V3*V2]
3366: has been calculated etc */
3367: /* For an individual i, wav[i] gives the number of effective waves */
3368: /* We compute the contribution to Likelihood of each effective transition
3369: mw[mi][i] is real wave of the mi th effectve wave */
3370: /* Then statuses are computed at each begin and end of an effective wave s1=s[ mw[mi][i] ][i];
3371: s2=s[mw[mi+1][i]][i];
3372: And the iv th varying covariate is the cotvar[mw[mi+1][i]][iv][i]
3373: But if the variable is not in the model TTvar[iv] is the real variable effective in the model:
3374: meaning that decodemodel should be used cotvar[mw[mi+1][i]][TTvar[iv]][i]
3375: */
3376: for(mi=1; mi<= wav[i]-1; mi++){
1.234 brouard 3377: for(k=1; k <= ncovv ; k++){ /* Varying covariates (single and product but no age )*/
1.242 brouard 3378: /* cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]][i]; */
3379: cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]-ncovcol-nqv][i];
1.234 brouard 3380: }
3381: for (ii=1;ii<=nlstate+ndeath;ii++)
3382: for (j=1;j<=nlstate+ndeath;j++){
3383: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
3384: savm[ii][j]=(ii==j ? 1.0 : 0.0);
3385: }
3386: for(d=0; d<dh[mi][i]; d++){
3387: newm=savm;
3388: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
3389: cov[2]=agexact;
3390: if(nagesqr==1)
3391: cov[3]= agexact*agexact; /* Should be changed here */
3392: for (kk=1; kk<=cptcovage;kk++) {
1.242 brouard 3393: if(!FixedV[Tvar[Tage[kk]]])
1.234 brouard 3394: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact; /* Tage[kk] gives the data-covariate associated with age */
1.242 brouard 3395: else
3396: cov[Tage[kk]+2+nagesqr]=cotvar[mw[mi][i]][Tvar[Tage[kk]]-ncovcol-nqv][i]*agexact;
1.234 brouard 3397: }
3398: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
3399: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
3400: savm=oldm;
3401: oldm=newm;
3402: } /* end mult */
3403:
3404: /*lli=log(out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]);*/ /* Original formula */
3405: /* But now since version 0.9 we anticipate for bias at large stepm.
3406: * If stepm is larger than one month (smallest stepm) and if the exact delay
3407: * (in months) between two waves is not a multiple of stepm, we rounded to
3408: * the nearest (and in case of equal distance, to the lowest) interval but now
3409: * we keep into memory the bias bh[mi][i] and also the previous matrix product
3410: * (i.e to dh[mi][i]-1) saved in 'savm'. Then we inter(extra)polate the
3411: * probability in order to take into account the bias as a fraction of the way
1.231 brouard 3412: * from savm to out if bh is negative or even beyond if bh is positive. bh varies
3413: * -stepm/2 to stepm/2 .
3414: * For stepm=1 the results are the same as for previous versions of Imach.
3415: * For stepm > 1 the results are less biased than in previous versions.
3416: */
1.234 brouard 3417: s1=s[mw[mi][i]][i];
3418: s2=s[mw[mi+1][i]][i];
3419: bbh=(double)bh[mi][i]/(double)stepm;
3420: /* bias bh is positive if real duration
3421: * is higher than the multiple of stepm and negative otherwise.
3422: */
3423: /* lli= (savm[s1][s2]>1.e-8 ?(1.+bbh)*log(out[s1][s2])- bbh*log(savm[s1][s2]):log((1.+bbh)*out[s1][s2]));*/
3424: if( s2 > nlstate){
3425: /* i.e. if s2 is a death state and if the date of death is known
3426: then the contribution to the likelihood is the probability to
3427: die between last step unit time and current step unit time,
3428: which is also equal to probability to die before dh
3429: minus probability to die before dh-stepm .
3430: In version up to 0.92 likelihood was computed
3431: as if date of death was unknown. Death was treated as any other
3432: health state: the date of the interview describes the actual state
3433: and not the date of a change in health state. The former idea was
3434: to consider that at each interview the state was recorded
3435: (healthy, disable or death) and IMaCh was corrected; but when we
3436: introduced the exact date of death then we should have modified
3437: the contribution of an exact death to the likelihood. This new
3438: contribution is smaller and very dependent of the step unit
3439: stepm. It is no more the probability to die between last interview
3440: and month of death but the probability to survive from last
3441: interview up to one month before death multiplied by the
3442: probability to die within a month. Thanks to Chris
3443: Jackson for correcting this bug. Former versions increased
3444: mortality artificially. The bad side is that we add another loop
3445: which slows down the processing. The difference can be up to 10%
3446: lower mortality.
3447: */
3448: /* If, at the beginning of the maximization mostly, the
3449: cumulative probability or probability to be dead is
3450: constant (ie = 1) over time d, the difference is equal to
3451: 0. out[s1][3] = savm[s1][3]: probability, being at state
3452: s1 at precedent wave, to be dead a month before current
3453: wave is equal to probability, being at state s1 at
3454: precedent wave, to be dead at mont of the current
3455: wave. Then the observed probability (that this person died)
3456: is null according to current estimated parameter. In fact,
3457: it should be very low but not zero otherwise the log go to
3458: infinity.
3459: */
1.183 brouard 3460: /* #ifdef INFINITYORIGINAL */
3461: /* lli=log(out[s1][s2] - savm[s1][s2]); */
3462: /* #else */
3463: /* if ((out[s1][s2] - savm[s1][s2]) < mytinydouble) */
3464: /* lli=log(mytinydouble); */
3465: /* else */
3466: /* lli=log(out[s1][s2] - savm[s1][s2]); */
3467: /* #endif */
1.226 brouard 3468: lli=log(out[s1][s2] - savm[s1][s2]);
1.216 brouard 3469:
1.226 brouard 3470: } else if ( s2==-1 ) { /* alive */
3471: for (j=1,survp=0. ; j<=nlstate; j++)
3472: survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j];
3473: /*survp += out[s1][j]; */
3474: lli= log(survp);
3475: }
3476: else if (s2==-4) {
3477: for (j=3,survp=0. ; j<=nlstate; j++)
3478: survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j];
3479: lli= log(survp);
3480: }
3481: else if (s2==-5) {
3482: for (j=1,survp=0. ; j<=2; j++)
3483: survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j];
3484: lli= log(survp);
3485: }
3486: else{
3487: lli= log((1.+bbh)*out[s1][s2]- bbh*savm[s1][s2]); /* linear interpolation */
3488: /* 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 */
3489: }
3490: /*lli=(1.+bbh)*log(out[s1][s2])- bbh*log(savm[s1][s2]);*/
3491: /*if(lli ==000.0)*/
3492: /*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); */
3493: ipmx +=1;
3494: sw += weight[i];
3495: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
3496: /* if (lli < log(mytinydouble)){ */
3497: /* 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); */
3498: /* 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]); */
3499: /* } */
3500: } /* end of wave */
3501: } /* end of individual */
3502: } else if(mle==2){
3503: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
3504: for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i];
3505: for(mi=1; mi<= wav[i]-1; mi++){
3506: for (ii=1;ii<=nlstate+ndeath;ii++)
3507: for (j=1;j<=nlstate+ndeath;j++){
3508: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
3509: savm[ii][j]=(ii==j ? 1.0 : 0.0);
3510: }
3511: for(d=0; d<=dh[mi][i]; d++){
3512: newm=savm;
3513: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
3514: cov[2]=agexact;
3515: if(nagesqr==1)
3516: cov[3]= agexact*agexact;
3517: for (kk=1; kk<=cptcovage;kk++) {
3518: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
3519: }
3520: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
3521: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
3522: savm=oldm;
3523: oldm=newm;
3524: } /* end mult */
3525:
3526: s1=s[mw[mi][i]][i];
3527: s2=s[mw[mi+1][i]][i];
3528: bbh=(double)bh[mi][i]/(double)stepm;
3529: 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 */
3530: ipmx +=1;
3531: sw += weight[i];
3532: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
3533: } /* end of wave */
3534: } /* end of individual */
3535: } else if(mle==3){ /* exponential inter-extrapolation */
3536: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
3537: for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i];
3538: for(mi=1; mi<= wav[i]-1; mi++){
3539: for (ii=1;ii<=nlstate+ndeath;ii++)
3540: for (j=1;j<=nlstate+ndeath;j++){
3541: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
3542: savm[ii][j]=(ii==j ? 1.0 : 0.0);
3543: }
3544: for(d=0; d<dh[mi][i]; d++){
3545: newm=savm;
3546: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
3547: cov[2]=agexact;
3548: if(nagesqr==1)
3549: cov[3]= agexact*agexact;
3550: for (kk=1; kk<=cptcovage;kk++) {
3551: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
3552: }
3553: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
3554: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
3555: savm=oldm;
3556: oldm=newm;
3557: } /* end mult */
3558:
3559: s1=s[mw[mi][i]][i];
3560: s2=s[mw[mi+1][i]][i];
3561: bbh=(double)bh[mi][i]/(double)stepm;
3562: 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 */
3563: ipmx +=1;
3564: sw += weight[i];
3565: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
3566: } /* end of wave */
3567: } /* end of individual */
3568: }else if (mle==4){ /* ml=4 no inter-extrapolation */
3569: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
3570: for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i];
3571: for(mi=1; mi<= wav[i]-1; mi++){
3572: for (ii=1;ii<=nlstate+ndeath;ii++)
3573: for (j=1;j<=nlstate+ndeath;j++){
3574: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
3575: savm[ii][j]=(ii==j ? 1.0 : 0.0);
3576: }
3577: for(d=0; d<dh[mi][i]; d++){
3578: newm=savm;
3579: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
3580: cov[2]=agexact;
3581: if(nagesqr==1)
3582: cov[3]= agexact*agexact;
3583: for (kk=1; kk<=cptcovage;kk++) {
3584: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
3585: }
1.126 brouard 3586:
1.226 brouard 3587: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
3588: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
3589: savm=oldm;
3590: oldm=newm;
3591: } /* end mult */
3592:
3593: s1=s[mw[mi][i]][i];
3594: s2=s[mw[mi+1][i]][i];
3595: if( s2 > nlstate){
3596: lli=log(out[s1][s2] - savm[s1][s2]);
3597: } else if ( s2==-1 ) { /* alive */
3598: for (j=1,survp=0. ; j<=nlstate; j++)
3599: survp += out[s1][j];
3600: lli= log(survp);
3601: }else{
3602: lli=log(out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]); /* Original formula */
3603: }
3604: ipmx +=1;
3605: sw += weight[i];
3606: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
1.126 brouard 3607: /* 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 3608: } /* end of wave */
3609: } /* end of individual */
3610: }else{ /* ml=5 no inter-extrapolation no jackson =0.8a */
3611: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
3612: for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i];
3613: for(mi=1; mi<= wav[i]-1; mi++){
3614: for (ii=1;ii<=nlstate+ndeath;ii++)
3615: for (j=1;j<=nlstate+ndeath;j++){
3616: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
3617: savm[ii][j]=(ii==j ? 1.0 : 0.0);
3618: }
3619: for(d=0; d<dh[mi][i]; d++){
3620: newm=savm;
3621: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
3622: cov[2]=agexact;
3623: if(nagesqr==1)
3624: cov[3]= agexact*agexact;
3625: for (kk=1; kk<=cptcovage;kk++) {
3626: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
3627: }
1.126 brouard 3628:
1.226 brouard 3629: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
3630: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
3631: savm=oldm;
3632: oldm=newm;
3633: } /* end mult */
3634:
3635: s1=s[mw[mi][i]][i];
3636: s2=s[mw[mi+1][i]][i];
3637: lli=log(out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]); /* Original formula */
3638: ipmx +=1;
3639: sw += weight[i];
3640: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
3641: /*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]);*/
3642: } /* end of wave */
3643: } /* end of individual */
3644: } /* End of if */
3645: for(k=1,l=0.; k<=nlstate; k++) l += ll[k];
3646: /* printf("l1=%f l2=%f ",ll[1],ll[2]); */
3647: l= l*ipmx/sw; /* To get the same order of magnitude as if weight=1 for every body */
3648: return -l;
1.126 brouard 3649: }
3650:
3651: /*************** log-likelihood *************/
3652: double funcone( double *x)
3653: {
1.228 brouard 3654: /* Same as func but slower because of a lot of printf and if */
1.126 brouard 3655: int i, ii, j, k, mi, d, kk;
1.228 brouard 3656: int ioffset=0;
1.131 brouard 3657: double l, ll[NLSTATEMAX+1], cov[NCOVMAX+1];
1.126 brouard 3658: double **out;
3659: double lli; /* Individual log likelihood */
3660: double llt;
3661: int s1, s2;
1.228 brouard 3662: int iv=0, iqv=0, itv=0, iqtv=0 ; /* Index of varying covariate, fixed quantitative cov, time varying covariate, quantitative time varying covariate */
3663:
1.126 brouard 3664: double bbh, survp;
1.187 brouard 3665: double agexact;
1.214 brouard 3666: double agebegin, ageend;
1.126 brouard 3667: /*extern weight */
3668: /* We are differentiating ll according to initial status */
3669: /* for (i=1;i<=npar;i++) printf("%f ", x[i]);*/
3670: /*for(i=1;i<imx;i++)
3671: printf(" %d\n",s[4][i]);
3672: */
3673: cov[1]=1.;
3674:
3675: for(k=1; k<=nlstate; k++) ll[k]=0.;
1.224 brouard 3676: ioffset=0;
3677: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
1.243 brouard 3678: /* ioffset=2+nagesqr+cptcovage; */
3679: ioffset=2+nagesqr;
1.232 brouard 3680: /* Fixed */
1.224 brouard 3681: /* for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i]; */
1.232 brouard 3682: /* for (k=1; k<=ncoveff;k++){ /\* Simple and product fixed Dummy covariates without age* products *\/ */
3683: for (k=1; k<=ncovf;k++){ /* Simple and product fixed covariates without age* products */
3684: 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)*/
3685: /* cov[ioffset+TvarFind[1]]=covar[Tvar[TvarFind[1]]][i]; */
3686: /* cov[2+6]=covar[Tvar[6]][i]; */
3687: /* cov[2+6]=covar[2][i]; V2 */
3688: /* cov[TvarFind[2]]=covar[Tvar[TvarFind[2]]][i]; */
3689: /* cov[2+7]=covar[Tvar[7]][i]; */
3690: /* cov[2+7]=covar[7][i]; V7=V1*V2 */
3691: /* cov[TvarFind[3]]=covar[Tvar[TvarFind[3]]][i]; */
3692: /* cov[2+9]=covar[Tvar[9]][i]; */
3693: /* cov[2+9]=covar[1][i]; V1 */
1.225 brouard 3694: }
1.232 brouard 3695: /* for (k=1; k<=nqfveff;k++){ /\* Simple and product fixed Quantitative covariates without age* products *\/ */
3696: /* 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?)*\/ */
3697: /* } */
1.231 brouard 3698: /* for(iqv=1; iqv <= nqfveff; iqv++){ /\* Quantitative fixed covariates *\/ */
3699: /* cov[++ioffset]=coqvar[Tvar[iqv]][i]; /\* Only V2 k=6 and V1*V2 7 *\/ */
3700: /* } */
1.225 brouard 3701:
1.233 brouard 3702:
3703: for(mi=1; mi<= wav[i]-1; mi++){ /* Varying with waves */
1.232 brouard 3704: /* Wave varying (but not age varying) */
3705: for(k=1; k <= ncovv ; k++){ /* Varying covariates (single and product but no age )*/
1.242 brouard 3706: /* cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]][i]; */
3707: cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]-ncovcol-nqv][i];
3708: }
1.232 brouard 3709: /* for(itv=1; itv <= ntveff; itv++){ /\* Varying dummy covariates (single??)*\/ */
1.242 brouard 3710: /* iv= Tvar[Tmodelind[ioffset-2-nagesqr-cptcovage+itv]]-ncovcol-nqv; /\* Counting the # varying covariate from 1 to ntveff *\/ */
3711: /* cov[ioffset+iv]=cotvar[mw[mi][i]][iv][i]; */
3712: /* k=ioffset-2-nagesqr-cptcovage+itv; /\* position in simple model *\/ */
3713: /* cov[ioffset+itv]=cotvar[mw[mi][i]][TmodelInvind[itv]][i]; */
3714: /* 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 3715: /* for(iqtv=1; iqtv <= nqtveff; iqtv++){ /\* Varying quantitatives covariates *\/ */
1.242 brouard 3716: /* iv=TmodelInvQind[iqtv]; /\* Counting the # varying covariate from 1 to ntveff *\/ */
3717: /* /\* 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]); *\/ */
3718: /* cov[ioffset+ntveff+iqtv]=cotqvar[mw[mi][i]][TmodelInvQind[iqtv]][i]; */
1.232 brouard 3719: /* } */
1.126 brouard 3720: for (ii=1;ii<=nlstate+ndeath;ii++)
1.242 brouard 3721: for (j=1;j<=nlstate+ndeath;j++){
3722: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
3723: savm[ii][j]=(ii==j ? 1.0 : 0.0);
3724: }
1.214 brouard 3725:
3726: agebegin=agev[mw[mi][i]][i]; /* Age at beginning of effective wave */
3727: ageend=agev[mw[mi][i]][i] + (dh[mi][i])*stepm/YEARM; /* Age at end of effective wave and at the end of transition */
3728: for(d=0; d<dh[mi][i]; d++){ /* Delay between two effective waves */
1.247 brouard 3729: /* for(d=0; d<=0; d++){ /\* Delay between two effective waves Only one matrix to speed up*\/ */
1.242 brouard 3730: /*dh[m][i] or dh[mw[mi][i]][i] is the delay between two effective waves m=mw[mi][i]
3731: and mw[mi+1][i]. dh depends on stepm.*/
3732: newm=savm;
1.247 brouard 3733: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM; /* Here d is needed */
1.242 brouard 3734: cov[2]=agexact;
3735: if(nagesqr==1)
3736: cov[3]= agexact*agexact;
3737: for (kk=1; kk<=cptcovage;kk++) {
3738: if(!FixedV[Tvar[Tage[kk]]])
3739: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
3740: else
3741: cov[Tage[kk]+2+nagesqr]=cotvar[mw[mi][i]][Tvar[Tage[kk]]-ncovcol-nqv][i]*agexact;
3742: }
3743: /* printf("i=%d,mi=%d,d=%d,mw[mi][i]=%d\n",i, mi,d,mw[mi][i]); */
3744: /* savm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
3745: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
3746: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
3747: /* out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath, */
3748: /* 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate)); */
3749: savm=oldm;
3750: oldm=newm;
1.126 brouard 3751: } /* end mult */
3752:
3753: s1=s[mw[mi][i]][i];
3754: s2=s[mw[mi+1][i]][i];
1.217 brouard 3755: /* if(s2==-1){ */
1.268 brouard 3756: /* printf(" ERROR s1=%d, s2=%d i=%d \n", s1, s2, i); */
1.217 brouard 3757: /* /\* exit(1); *\/ */
3758: /* } */
1.126 brouard 3759: bbh=(double)bh[mi][i]/(double)stepm;
3760: /* bias is positive if real duration
3761: * is higher than the multiple of stepm and negative otherwise.
3762: */
3763: if( s2 > nlstate && (mle <5) ){ /* Jackson */
1.242 brouard 3764: lli=log(out[s1][s2] - savm[s1][s2]);
1.216 brouard 3765: } else if ( s2==-1 ) { /* alive */
1.242 brouard 3766: for (j=1,survp=0. ; j<=nlstate; j++)
3767: survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j];
3768: lli= log(survp);
1.126 brouard 3769: }else if (mle==1){
1.242 brouard 3770: lli= log((1.+bbh)*out[s1][s2]- bbh*savm[s1][s2]); /* linear interpolation */
1.126 brouard 3771: } else if(mle==2){
1.242 brouard 3772: 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 3773: } else if(mle==3){ /* exponential inter-extrapolation */
1.242 brouard 3774: 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 3775: } else if (mle==4){ /* mle=4 no inter-extrapolation */
1.242 brouard 3776: lli=log(out[s1][s2]); /* Original formula */
1.136 brouard 3777: } else{ /* mle=0 back to 1 */
1.242 brouard 3778: lli= log((1.+bbh)*out[s1][s2]- bbh*savm[s1][s2]); /* linear interpolation */
3779: /*lli=log(out[s1][s2]); */ /* Original formula */
1.126 brouard 3780: } /* End of if */
3781: ipmx +=1;
3782: sw += weight[i];
3783: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
1.132 brouard 3784: /*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 3785: if(globpr){
1.246 brouard 3786: fprintf(ficresilk,"%09ld %6.1f %6.1f %6d %2d %2d %2d %2d %3d %15.6f %8.4f %8.3f\
1.126 brouard 3787: %11.6f %11.6f %11.6f ", \
1.242 brouard 3788: 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 3789: 2*weight[i]*lli,(s2==-1? -1: out[s1][s2]),(s2==-1? -1: savm[s1][s2]));
1.242 brouard 3790: for(k=1,llt=0.,l=0.; k<=nlstate; k++){
3791: llt +=ll[k]*gipmx/gsw;
3792: fprintf(ficresilk," %10.6f",-ll[k]*gipmx/gsw);
3793: }
3794: fprintf(ficresilk," %10.6f\n", -llt);
1.126 brouard 3795: }
1.232 brouard 3796: } /* end of wave */
3797: } /* end of individual */
3798: for(k=1,l=0.; k<=nlstate; k++) l += ll[k];
3799: /* printf("l1=%f l2=%f ",ll[1],ll[2]); */
3800: l= l*ipmx/sw; /* To get the same order of magnitude as if weight=1 for every body */
3801: if(globpr==0){ /* First time we count the contributions and weights */
3802: gipmx=ipmx;
3803: gsw=sw;
3804: }
3805: return -l;
1.126 brouard 3806: }
3807:
3808:
3809: /*************** function likelione ***********/
3810: void likelione(FILE *ficres,double p[], int npar, int nlstate, int *globpri, long *ipmx, double *sw, double *fretone, double (*funcone)(double []))
3811: {
3812: /* This routine should help understanding what is done with
3813: the selection of individuals/waves and
3814: to check the exact contribution to the likelihood.
3815: Plotting could be done.
3816: */
3817: int k;
3818:
3819: if(*globpri !=0){ /* Just counts and sums, no printings */
1.201 brouard 3820: strcpy(fileresilk,"ILK_");
1.202 brouard 3821: strcat(fileresilk,fileresu);
1.126 brouard 3822: if((ficresilk=fopen(fileresilk,"w"))==NULL) {
3823: printf("Problem with resultfile: %s\n", fileresilk);
3824: fprintf(ficlog,"Problem with resultfile: %s\n", fileresilk);
3825: }
1.214 brouard 3826: 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");
3827: fprintf(ficresilk, "#num_i ageb agend i s1 s2 mi mw dh likeli weight %%weight 2wlli out sav ");
1.126 brouard 3828: /* i,s1,s2,mi,mw[mi][i],dh[mi][i],exp(lli),weight[i],2*weight[i]*lli,out[s1][s2],savm[s1][s2]); */
3829: for(k=1; k<=nlstate; k++)
3830: fprintf(ficresilk," -2*gipw/gsw*weight*ll[%d]++",k);
3831: fprintf(ficresilk," -2*gipw/gsw*weight*ll(total)\n");
3832: }
3833:
3834: *fretone=(*funcone)(p);
3835: if(*globpri !=0){
3836: fclose(ficresilk);
1.205 brouard 3837: if (mle ==0)
3838: fprintf(fichtm,"\n<br>File of contributions to the likelihood computed with initial parameters and mle = %d.",mle);
3839: else if(mle >=1)
3840: fprintf(fichtm,"\n<br>File of contributions to the likelihood computed with optimized parameters mle = %d.",mle);
3841: 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 3842:
1.208 brouard 3843:
3844: for (k=1; k<= nlstate ; k++) {
1.211 brouard 3845: 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 3846: <img src=\"%s-p%dj.png\">",k,k,subdirf2(optionfilefiname,"ILK_"),k,subdirf2(optionfilefiname,"ILK_"),k,subdirf2(optionfilefiname,"ILK_"),k);
3847: }
1.207 brouard 3848: 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 3849: <img src=\"%s-ori.png\">",subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"));
1.207 brouard 3850: fprintf(fichtm,"<br>- and by state of destination <a href=\"%s-dest.png\">%s-dest.png</a><br> \
1.204 brouard 3851: <img src=\"%s-dest.png\">",subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"));
1.207 brouard 3852: fflush(fichtm);
1.205 brouard 3853: }
1.126 brouard 3854: return;
3855: }
3856:
3857:
3858: /*********** Maximum Likelihood Estimation ***************/
3859:
3860: void mlikeli(FILE *ficres,double p[], int npar, int ncovmodel, int nlstate, double ftol, double (*func)(double []))
3861: {
1.165 brouard 3862: int i,j, iter=0;
1.126 brouard 3863: double **xi;
3864: double fret;
3865: double fretone; /* Only one call to likelihood */
3866: /* char filerespow[FILENAMELENGTH];*/
1.162 brouard 3867:
3868: #ifdef NLOPT
3869: int creturn;
3870: nlopt_opt opt;
3871: /* double lb[9] = { -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL }; /\* lower bounds *\/ */
3872: double *lb;
3873: double minf; /* the minimum objective value, upon return */
3874: double * p1; /* Shifted parameters from 0 instead of 1 */
3875: myfunc_data dinst, *d = &dinst;
3876: #endif
3877:
3878:
1.126 brouard 3879: xi=matrix(1,npar,1,npar);
3880: for (i=1;i<=npar;i++)
3881: for (j=1;j<=npar;j++)
3882: xi[i][j]=(i==j ? 1.0 : 0.0);
3883: printf("Powell\n"); fprintf(ficlog,"Powell\n");
1.201 brouard 3884: strcpy(filerespow,"POW_");
1.126 brouard 3885: strcat(filerespow,fileres);
3886: if((ficrespow=fopen(filerespow,"w"))==NULL) {
3887: printf("Problem with resultfile: %s\n", filerespow);
3888: fprintf(ficlog,"Problem with resultfile: %s\n", filerespow);
3889: }
3890: fprintf(ficrespow,"# Powell\n# iter -2*LL");
3891: for (i=1;i<=nlstate;i++)
3892: for(j=1;j<=nlstate+ndeath;j++)
3893: if(j!=i)fprintf(ficrespow," p%1d%1d",i,j);
3894: fprintf(ficrespow,"\n");
1.162 brouard 3895: #ifdef POWELL
1.126 brouard 3896: powell(p,xi,npar,ftol,&iter,&fret,func);
1.162 brouard 3897: #endif
1.126 brouard 3898:
1.162 brouard 3899: #ifdef NLOPT
3900: #ifdef NEWUOA
3901: opt = nlopt_create(NLOPT_LN_NEWUOA,npar);
3902: #else
3903: opt = nlopt_create(NLOPT_LN_BOBYQA,npar);
3904: #endif
3905: lb=vector(0,npar-1);
3906: for (i=0;i<npar;i++) lb[i]= -HUGE_VAL;
3907: nlopt_set_lower_bounds(opt, lb);
3908: nlopt_set_initial_step1(opt, 0.1);
3909:
3910: p1= (p+1); /* p *(p+1)@8 and p *(p1)@8 are equal p1[0]=p[1] */
3911: d->function = func;
3912: printf(" Func %.12lf \n",myfunc(npar,p1,NULL,d));
3913: nlopt_set_min_objective(opt, myfunc, d);
3914: nlopt_set_xtol_rel(opt, ftol);
3915: if ((creturn=nlopt_optimize(opt, p1, &minf)) < 0) {
3916: printf("nlopt failed! %d\n",creturn);
3917: }
3918: else {
3919: printf("found minimum after %d evaluations (NLOPT=%d)\n", countcallfunc ,NLOPT);
3920: printf("found minimum at f(%g,%g) = %0.10g\n", p[0], p[1], minf);
3921: iter=1; /* not equal */
3922: }
3923: nlopt_destroy(opt);
3924: #endif
1.126 brouard 3925: free_matrix(xi,1,npar,1,npar);
3926: fclose(ficrespow);
1.203 brouard 3927: printf("\n#Number of iterations & function calls = %d & %d, -2 Log likelihood = %.12f\n",iter, countcallfunc,func(p));
3928: fprintf(ficlog,"\n#Number of iterations & function calls = %d & %d, -2 Log likelihood = %.12f\n",iter, countcallfunc,func(p));
1.180 brouard 3929: fprintf(ficres,"#Number of iterations & function calls = %d & %d, -2 Log likelihood = %.12f\n",iter, countcallfunc,func(p));
1.126 brouard 3930:
3931: }
3932:
3933: /**** Computes Hessian and covariance matrix ***/
1.203 brouard 3934: void hesscov(double **matcov, double **hess, double p[], int npar, double delti[], double ftolhess, double (*func)(double []))
1.126 brouard 3935: {
3936: double **a,**y,*x,pd;
1.203 brouard 3937: /* double **hess; */
1.164 brouard 3938: int i, j;
1.126 brouard 3939: int *indx;
3940:
3941: double hessii(double p[], double delta, int theta, double delti[],double (*func)(double []),int npar);
1.203 brouard 3942: double hessij(double p[], double **hess, double delti[], int i, int j,double (*func)(double []),int npar);
1.126 brouard 3943: void lubksb(double **a, int npar, int *indx, double b[]) ;
3944: void ludcmp(double **a, int npar, int *indx, double *d) ;
3945: double gompertz(double p[]);
1.203 brouard 3946: /* hess=matrix(1,npar,1,npar); */
1.126 brouard 3947:
3948: printf("\nCalculation of the hessian matrix. Wait...\n");
3949: fprintf(ficlog,"\nCalculation of the hessian matrix. Wait...\n");
3950: for (i=1;i<=npar;i++){
1.203 brouard 3951: printf("%d-",i);fflush(stdout);
3952: fprintf(ficlog,"%d-",i);fflush(ficlog);
1.126 brouard 3953:
3954: hess[i][i]=hessii(p,ftolhess,i,delti,func,npar);
3955:
3956: /* printf(" %f ",p[i]);
3957: printf(" %lf %lf %lf",hess[i][i],ftolhess,delti[i]);*/
3958: }
3959:
3960: for (i=1;i<=npar;i++) {
3961: for (j=1;j<=npar;j++) {
3962: if (j>i) {
1.203 brouard 3963: printf(".%d-%d",i,j);fflush(stdout);
3964: fprintf(ficlog,".%d-%d",i,j);fflush(ficlog);
3965: hess[i][j]=hessij(p,hess, delti,i,j,func,npar);
1.126 brouard 3966:
3967: hess[j][i]=hess[i][j];
3968: /*printf(" %lf ",hess[i][j]);*/
3969: }
3970: }
3971: }
3972: printf("\n");
3973: fprintf(ficlog,"\n");
3974:
3975: printf("\nInverting the hessian to get the covariance matrix. Wait...\n");
3976: fprintf(ficlog,"\nInverting the hessian to get the covariance matrix. Wait...\n");
3977:
3978: a=matrix(1,npar,1,npar);
3979: y=matrix(1,npar,1,npar);
3980: x=vector(1,npar);
3981: indx=ivector(1,npar);
3982: for (i=1;i<=npar;i++)
3983: for (j=1;j<=npar;j++) a[i][j]=hess[i][j];
3984: ludcmp(a,npar,indx,&pd);
3985:
3986: for (j=1;j<=npar;j++) {
3987: for (i=1;i<=npar;i++) x[i]=0;
3988: x[j]=1;
3989: lubksb(a,npar,indx,x);
3990: for (i=1;i<=npar;i++){
3991: matcov[i][j]=x[i];
3992: }
3993: }
3994:
3995: printf("\n#Hessian matrix#\n");
3996: fprintf(ficlog,"\n#Hessian matrix#\n");
3997: for (i=1;i<=npar;i++) {
3998: for (j=1;j<=npar;j++) {
1.203 brouard 3999: printf("%.6e ",hess[i][j]);
4000: fprintf(ficlog,"%.6e ",hess[i][j]);
1.126 brouard 4001: }
4002: printf("\n");
4003: fprintf(ficlog,"\n");
4004: }
4005:
1.203 brouard 4006: /* printf("\n#Covariance matrix#\n"); */
4007: /* fprintf(ficlog,"\n#Covariance matrix#\n"); */
4008: /* for (i=1;i<=npar;i++) { */
4009: /* for (j=1;j<=npar;j++) { */
4010: /* printf("%.6e ",matcov[i][j]); */
4011: /* fprintf(ficlog,"%.6e ",matcov[i][j]); */
4012: /* } */
4013: /* printf("\n"); */
4014: /* fprintf(ficlog,"\n"); */
4015: /* } */
4016:
1.126 brouard 4017: /* Recompute Inverse */
1.203 brouard 4018: /* for (i=1;i<=npar;i++) */
4019: /* for (j=1;j<=npar;j++) a[i][j]=matcov[i][j]; */
4020: /* ludcmp(a,npar,indx,&pd); */
4021:
4022: /* printf("\n#Hessian matrix recomputed#\n"); */
4023:
4024: /* for (j=1;j<=npar;j++) { */
4025: /* for (i=1;i<=npar;i++) x[i]=0; */
4026: /* x[j]=1; */
4027: /* lubksb(a,npar,indx,x); */
4028: /* for (i=1;i<=npar;i++){ */
4029: /* y[i][j]=x[i]; */
4030: /* printf("%.3e ",y[i][j]); */
4031: /* fprintf(ficlog,"%.3e ",y[i][j]); */
4032: /* } */
4033: /* printf("\n"); */
4034: /* fprintf(ficlog,"\n"); */
4035: /* } */
4036:
4037: /* Verifying the inverse matrix */
4038: #ifdef DEBUGHESS
4039: y=matprod2(y,hess,1,npar,1,npar,1,npar,matcov);
1.126 brouard 4040:
1.203 brouard 4041: printf("\n#Verification: multiplying the matrix of covariance by the Hessian matrix, should be unity:#\n");
4042: fprintf(ficlog,"\n#Verification: multiplying the matrix of covariance by the Hessian matrix. Should be unity:#\n");
1.126 brouard 4043:
4044: for (j=1;j<=npar;j++) {
4045: for (i=1;i<=npar;i++){
1.203 brouard 4046: printf("%.2f ",y[i][j]);
4047: fprintf(ficlog,"%.2f ",y[i][j]);
1.126 brouard 4048: }
4049: printf("\n");
4050: fprintf(ficlog,"\n");
4051: }
1.203 brouard 4052: #endif
1.126 brouard 4053:
4054: free_matrix(a,1,npar,1,npar);
4055: free_matrix(y,1,npar,1,npar);
4056: free_vector(x,1,npar);
4057: free_ivector(indx,1,npar);
1.203 brouard 4058: /* free_matrix(hess,1,npar,1,npar); */
1.126 brouard 4059:
4060:
4061: }
4062:
4063: /*************** hessian matrix ****************/
4064: double hessii(double x[], double delta, int theta, double delti[], double (*func)(double []), int npar)
1.203 brouard 4065: { /* Around values of x, computes the function func and returns the scales delti and hessian */
1.126 brouard 4066: int i;
4067: int l=1, lmax=20;
1.203 brouard 4068: double k1,k2, res, fx;
1.132 brouard 4069: double p2[MAXPARM+1]; /* identical to x */
1.126 brouard 4070: double delt=0.0001, delts, nkhi=10.,nkhif=1., khi=1.e-4;
4071: int k=0,kmax=10;
4072: double l1;
4073:
4074: fx=func(x);
4075: for (i=1;i<=npar;i++) p2[i]=x[i];
1.145 brouard 4076: for(l=0 ; l <=lmax; l++){ /* Enlarging the zone around the Maximum */
1.126 brouard 4077: l1=pow(10,l);
4078: delts=delt;
4079: for(k=1 ; k <kmax; k=k+1){
4080: delt = delta*(l1*k);
4081: p2[theta]=x[theta] +delt;
1.145 brouard 4082: k1=func(p2)-fx; /* Might be negative if too close to the theoretical maximum */
1.126 brouard 4083: p2[theta]=x[theta]-delt;
4084: k2=func(p2)-fx;
4085: /*res= (k1-2.0*fx+k2)/delt/delt; */
1.203 brouard 4086: res= (k1+k2)/delt/delt/2.; /* Divided by 2 because L and not 2*L */
1.126 brouard 4087:
1.203 brouard 4088: #ifdef DEBUGHESSII
1.126 brouard 4089: 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);
4090: 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);
4091: #endif
4092: /*if(fabs(k1-2.0*fx+k2) <1.e-13){ */
4093: if((k1 <khi/nkhi/2.) || (k2 <khi/nkhi/2.)){
4094: k=kmax;
4095: }
4096: else if((k1 >khi/nkhif) || (k2 >khi/nkhif)){ /* Keeps lastvalue before 3.84/2 KHI2 5% 1d.f. */
1.164 brouard 4097: k=kmax; l=lmax*10;
1.126 brouard 4098: }
4099: else if((k1 >khi/nkhi) || (k2 >khi/nkhi)){
4100: delts=delt;
4101: }
1.203 brouard 4102: } /* End loop k */
1.126 brouard 4103: }
4104: delti[theta]=delts;
4105: return res;
4106:
4107: }
4108:
1.203 brouard 4109: double hessij( double x[], double **hess, double delti[], int thetai,int thetaj,double (*func)(double []),int npar)
1.126 brouard 4110: {
4111: int i;
1.164 brouard 4112: int l=1, lmax=20;
1.126 brouard 4113: double k1,k2,k3,k4,res,fx;
1.132 brouard 4114: double p2[MAXPARM+1];
1.203 brouard 4115: int k, kmax=1;
4116: double v1, v2, cv12, lc1, lc2;
1.208 brouard 4117:
4118: int firstime=0;
1.203 brouard 4119:
1.126 brouard 4120: fx=func(x);
1.203 brouard 4121: for (k=1; k<=kmax; k=k+10) {
1.126 brouard 4122: for (i=1;i<=npar;i++) p2[i]=x[i];
1.203 brouard 4123: p2[thetai]=x[thetai]+delti[thetai]*k;
4124: p2[thetaj]=x[thetaj]+delti[thetaj]*k;
1.126 brouard 4125: k1=func(p2)-fx;
4126:
1.203 brouard 4127: p2[thetai]=x[thetai]+delti[thetai]*k;
4128: p2[thetaj]=x[thetaj]-delti[thetaj]*k;
1.126 brouard 4129: k2=func(p2)-fx;
4130:
1.203 brouard 4131: p2[thetai]=x[thetai]-delti[thetai]*k;
4132: p2[thetaj]=x[thetaj]+delti[thetaj]*k;
1.126 brouard 4133: k3=func(p2)-fx;
4134:
1.203 brouard 4135: p2[thetai]=x[thetai]-delti[thetai]*k;
4136: p2[thetaj]=x[thetaj]-delti[thetaj]*k;
1.126 brouard 4137: k4=func(p2)-fx;
1.203 brouard 4138: res=(k1-k2-k3+k4)/4.0/delti[thetai]/k/delti[thetaj]/k/2.; /* Because of L not 2*L */
4139: if(k1*k2*k3*k4 <0.){
1.208 brouard 4140: firstime=1;
1.203 brouard 4141: kmax=kmax+10;
1.208 brouard 4142: }
4143: if(kmax >=10 || firstime ==1){
1.246 brouard 4144: 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);
4145: 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 4146: 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);
4147: 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);
4148: }
4149: #ifdef DEBUGHESSIJ
4150: v1=hess[thetai][thetai];
4151: v2=hess[thetaj][thetaj];
4152: cv12=res;
4153: /* Computing eigen value of Hessian matrix */
4154: lc1=((v1+v2)+sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
4155: lc2=((v1+v2)-sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
4156: if ((lc2 <0) || (lc1 <0) ){
4157: printf("Warning: sub Hessian matrix '%d%d' does not have positive eigen values \n",thetai,thetaj);
4158: fprintf(ficlog, "Warning: sub Hessian matrix '%d%d' does not have positive eigen values \n",thetai,thetaj);
4159: 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);
4160: 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);
4161: }
1.126 brouard 4162: #endif
4163: }
4164: return res;
4165: }
4166:
1.203 brouard 4167: /* Not done yet: Was supposed to fix if not exactly at the maximum */
4168: /* double hessij( double x[], double delti[], int thetai,int thetaj,double (*func)(double []),int npar) */
4169: /* { */
4170: /* int i; */
4171: /* int l=1, lmax=20; */
4172: /* double k1,k2,k3,k4,res,fx; */
4173: /* double p2[MAXPARM+1]; */
4174: /* double delt=0.0001, delts, nkhi=10.,nkhif=1., khi=1.e-4; */
4175: /* int k=0,kmax=10; */
4176: /* double l1; */
4177:
4178: /* fx=func(x); */
4179: /* for(l=0 ; l <=lmax; l++){ /\* Enlarging the zone around the Maximum *\/ */
4180: /* l1=pow(10,l); */
4181: /* delts=delt; */
4182: /* for(k=1 ; k <kmax; k=k+1){ */
4183: /* delt = delti*(l1*k); */
4184: /* for (i=1;i<=npar;i++) p2[i]=x[i]; */
4185: /* p2[thetai]=x[thetai]+delti[thetai]/k; */
4186: /* p2[thetaj]=x[thetaj]+delti[thetaj]/k; */
4187: /* k1=func(p2)-fx; */
4188:
4189: /* p2[thetai]=x[thetai]+delti[thetai]/k; */
4190: /* p2[thetaj]=x[thetaj]-delti[thetaj]/k; */
4191: /* k2=func(p2)-fx; */
4192:
4193: /* p2[thetai]=x[thetai]-delti[thetai]/k; */
4194: /* p2[thetaj]=x[thetaj]+delti[thetaj]/k; */
4195: /* k3=func(p2)-fx; */
4196:
4197: /* p2[thetai]=x[thetai]-delti[thetai]/k; */
4198: /* p2[thetaj]=x[thetaj]-delti[thetaj]/k; */
4199: /* k4=func(p2)-fx; */
4200: /* res=(k1-k2-k3+k4)/4.0/delti[thetai]*k/delti[thetaj]*k/2.; /\* Because of L not 2*L *\/ */
4201: /* #ifdef DEBUGHESSIJ */
4202: /* 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); */
4203: /* 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); */
4204: /* #endif */
4205: /* if((k1 <khi/nkhi/2.) || (k2 <khi/nkhi/2.)|| (k4 <khi/nkhi/2.)|| (k4 <khi/nkhi/2.)){ */
4206: /* k=kmax; */
4207: /* } */
4208: /* else if((k1 >khi/nkhif) || (k2 >khi/nkhif) || (k4 >khi/nkhif) || (k4 >khi/nkhif)){ /\* Keeps lastvalue before 3.84/2 KHI2 5% 1d.f. *\/ */
4209: /* k=kmax; l=lmax*10; */
4210: /* } */
4211: /* else if((k1 >khi/nkhi) || (k2 >khi/nkhi)){ */
4212: /* delts=delt; */
4213: /* } */
4214: /* } /\* End loop k *\/ */
4215: /* } */
4216: /* delti[theta]=delts; */
4217: /* return res; */
4218: /* } */
4219:
4220:
1.126 brouard 4221: /************** Inverse of matrix **************/
4222: void ludcmp(double **a, int n, int *indx, double *d)
4223: {
4224: int i,imax,j,k;
4225: double big,dum,sum,temp;
4226: double *vv;
4227:
4228: vv=vector(1,n);
4229: *d=1.0;
4230: for (i=1;i<=n;i++) {
4231: big=0.0;
4232: for (j=1;j<=n;j++)
4233: if ((temp=fabs(a[i][j])) > big) big=temp;
1.256 brouard 4234: if (big == 0.0){
4235: printf(" Singular Hessian matrix at row %d:\n",i);
4236: for (j=1;j<=n;j++) {
4237: printf(" a[%d][%d]=%f,",i,j,a[i][j]);
4238: fprintf(ficlog," a[%d][%d]=%f,",i,j,a[i][j]);
4239: }
4240: fflush(ficlog);
4241: fclose(ficlog);
4242: nrerror("Singular matrix in routine ludcmp");
4243: }
1.126 brouard 4244: vv[i]=1.0/big;
4245: }
4246: for (j=1;j<=n;j++) {
4247: for (i=1;i<j;i++) {
4248: sum=a[i][j];
4249: for (k=1;k<i;k++) sum -= a[i][k]*a[k][j];
4250: a[i][j]=sum;
4251: }
4252: big=0.0;
4253: for (i=j;i<=n;i++) {
4254: sum=a[i][j];
4255: for (k=1;k<j;k++)
4256: sum -= a[i][k]*a[k][j];
4257: a[i][j]=sum;
4258: if ( (dum=vv[i]*fabs(sum)) >= big) {
4259: big=dum;
4260: imax=i;
4261: }
4262: }
4263: if (j != imax) {
4264: for (k=1;k<=n;k++) {
4265: dum=a[imax][k];
4266: a[imax][k]=a[j][k];
4267: a[j][k]=dum;
4268: }
4269: *d = -(*d);
4270: vv[imax]=vv[j];
4271: }
4272: indx[j]=imax;
4273: if (a[j][j] == 0.0) a[j][j]=TINY;
4274: if (j != n) {
4275: dum=1.0/(a[j][j]);
4276: for (i=j+1;i<=n;i++) a[i][j] *= dum;
4277: }
4278: }
4279: free_vector(vv,1,n); /* Doesn't work */
4280: ;
4281: }
4282:
4283: void lubksb(double **a, int n, int *indx, double b[])
4284: {
4285: int i,ii=0,ip,j;
4286: double sum;
4287:
4288: for (i=1;i<=n;i++) {
4289: ip=indx[i];
4290: sum=b[ip];
4291: b[ip]=b[i];
4292: if (ii)
4293: for (j=ii;j<=i-1;j++) sum -= a[i][j]*b[j];
4294: else if (sum) ii=i;
4295: b[i]=sum;
4296: }
4297: for (i=n;i>=1;i--) {
4298: sum=b[i];
4299: for (j=i+1;j<=n;j++) sum -= a[i][j]*b[j];
4300: b[i]=sum/a[i][i];
4301: }
4302: }
4303:
4304: void pstamp(FILE *fichier)
4305: {
1.196 brouard 4306: fprintf(fichier,"# %s.%s\n#IMaCh version %s, %s\n#%s\n# %s", optionfilefiname,optionfilext,version,copyright, fullversion, strstart);
1.126 brouard 4307: }
4308:
1.253 brouard 4309:
4310:
1.126 brouard 4311: /************ Frequencies ********************/
1.251 brouard 4312: void freqsummary(char fileres[], double p[], double pstart[], int iagemin, int iagemax, int **s, double **agev, int nlstate, int imx, \
1.226 brouard 4313: int *Tvaraff, int *invalidvarcomb, int **nbcode, int *ncodemax,double **mint,double **anint, char strstart[], \
4314: int firstpass, int lastpass, int stepm, int weightopt, char model[])
1.250 brouard 4315: { /* Some frequencies as well as proposing some starting values */
1.226 brouard 4316:
1.265 brouard 4317: int i, m, jk, j1, bool, z1,j, nj, nl, k, iv, jj=0, s1=1, s2=1;
1.226 brouard 4318: int iind=0, iage=0;
4319: int mi; /* Effective wave */
4320: int first;
4321: double ***freq; /* Frequencies */
1.268 brouard 4322: 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 */
4323: 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 4324: double *meanq;
4325: double **meanqt;
4326: double *pp, **prop, *posprop, *pospropt;
4327: double pos=0., posproptt=0., pospropta=0., k2, dateintsum=0,k2cpt=0;
4328: char fileresp[FILENAMELENGTH], fileresphtm[FILENAMELENGTH], fileresphtmfr[FILENAMELENGTH];
4329: double agebegin, ageend;
4330:
4331: pp=vector(1,nlstate);
1.251 brouard 4332: prop=matrix(1,nlstate,iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.226 brouard 4333: posprop=vector(1,nlstate); /* Counting the number of transition starting from a live state per age */
4334: pospropt=vector(1,nlstate); /* Counting the number of transition starting from a live state */
4335: /* prop=matrix(1,nlstate,iagemin,iagemax+3); */
4336: meanq=vector(1,nqfveff); /* Number of Quantitative Fixed Variables Effective */
4337: meanqt=matrix(1,lastpass,1,nqtveff);
4338: strcpy(fileresp,"P_");
4339: strcat(fileresp,fileresu);
4340: /*strcat(fileresphtm,fileresu);*/
4341: if((ficresp=fopen(fileresp,"w"))==NULL) {
4342: printf("Problem with prevalence resultfile: %s\n", fileresp);
4343: fprintf(ficlog,"Problem with prevalence resultfile: %s\n", fileresp);
4344: exit(0);
4345: }
1.240 brouard 4346:
1.226 brouard 4347: strcpy(fileresphtm,subdirfext(optionfilefiname,"PHTM_",".htm"));
4348: if((ficresphtm=fopen(fileresphtm,"w"))==NULL) {
4349: printf("Problem with prevalence HTM resultfile '%s' with errno='%s'\n",fileresphtm,strerror(errno));
4350: fprintf(ficlog,"Problem with prevalence HTM resultfile '%s' with errno='%s'\n",fileresphtm,strerror(errno));
4351: fflush(ficlog);
4352: exit(70);
4353: }
4354: else{
4355: fprintf(ficresphtm,"<html><head>\n<title>IMaCh PHTM_ %s</title></head>\n <body><font size=\"2\">%s <br> %s</font> \
1.240 brouard 4356: <hr size=\"2\" color=\"#EC5E5E\"> \n \
1.214 brouard 4357: Title=%s <br>Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s<br>\n",\
1.226 brouard 4358: fileresphtm,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model);
4359: }
1.237 brouard 4360: 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 4361:
1.226 brouard 4362: strcpy(fileresphtmfr,subdirfext(optionfilefiname,"PHTMFR_",".htm"));
4363: if((ficresphtmfr=fopen(fileresphtmfr,"w"))==NULL) {
4364: printf("Problem with frequency table HTM resultfile '%s' with errno='%s'\n",fileresphtmfr,strerror(errno));
4365: fprintf(ficlog,"Problem with frequency table HTM resultfile '%s' with errno='%s'\n",fileresphtmfr,strerror(errno));
4366: fflush(ficlog);
4367: exit(70);
1.240 brouard 4368: } else{
1.226 brouard 4369: 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 4370: <hr size=\"2\" color=\"#EC5E5E\"> \n \
1.214 brouard 4371: Title=%s <br>Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s<br>\n",\
1.226 brouard 4372: fileresphtmfr,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model);
4373: }
1.240 brouard 4374: 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);
4375:
1.253 brouard 4376: y= vector(iagemin-AGEMARGE,iagemax+4+AGEMARGE);
4377: x= vector(iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.251 brouard 4378: freq= ma3x(-5,nlstate+ndeath,-5,nlstate+ndeath,iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.226 brouard 4379: j1=0;
1.126 brouard 4380:
1.227 brouard 4381: /* j=ncoveff; /\* Only fixed dummy covariates *\/ */
4382: j=cptcoveff; /* Only dummy covariates of the model */
1.226 brouard 4383: if (cptcovn<1) {j=1;ncodemax[1]=1;}
1.240 brouard 4384:
4385:
1.226 brouard 4386: /* Detects if a combination j1 is empty: for a multinomial variable like 3 education levels:
4387: reference=low_education V1=0,V2=0
4388: med_educ V1=1 V2=0,
4389: high_educ V1=0 V2=1
4390: Then V1=1 and V2=1 is a noisy combination that we want to exclude for the list 2**cptcoveff
4391: */
1.249 brouard 4392: dateintsum=0;
4393: k2cpt=0;
4394:
1.253 brouard 4395: if(cptcoveff == 0 )
1.265 brouard 4396: nl=1; /* Constant and age model only */
1.253 brouard 4397: else
4398: nl=2;
1.265 brouard 4399:
4400: /* if a constant only model, one pass to compute frequency tables and to write it on ficresp */
4401: /* Loop on nj=1 or 2 if dummy covariates j!=0
4402: * Loop on j1(1 to 2**cptcoveff) covariate combination
4403: * freq[s1][s2][iage] =0.
4404: * Loop on iind
4405: * ++freq[s1][s2][iage] weighted
4406: * end iind
4407: * if covariate and j!0
4408: * headers Variable on one line
4409: * endif cov j!=0
4410: * header of frequency table by age
4411: * Loop on age
4412: * pp[s1]+=freq[s1][s2][iage] weighted
4413: * pos+=freq[s1][s2][iage] weighted
4414: * Loop on s1 initial state
4415: * fprintf(ficresp
4416: * end s1
4417: * end age
4418: * if j!=0 computes starting values
4419: * end compute starting values
4420: * end j1
4421: * end nl
4422: */
1.253 brouard 4423: for (nj = 1; nj <= nl; nj++){ /* nj= 1 constant model, nl number of loops. */
4424: if(nj==1)
4425: j=0; /* First pass for the constant */
1.265 brouard 4426: else{
1.253 brouard 4427: j=cptcoveff; /* Other passes for the covariate values */
1.265 brouard 4428: }
1.251 brouard 4429: first=1;
1.265 brouard 4430: 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 4431: posproptt=0.;
4432: /*printf("cptcoveff=%d Tvaraff=%d", cptcoveff,Tvaraff[1]);
4433: scanf("%d", i);*/
4434: for (i=-5; i<=nlstate+ndeath; i++)
1.265 brouard 4435: for (s2=-5; s2<=nlstate+ndeath; s2++)
1.251 brouard 4436: for(m=iagemin; m <= iagemax+3; m++)
1.265 brouard 4437: freq[i][s2][m]=0;
1.251 brouard 4438:
4439: for (i=1; i<=nlstate; i++) {
1.240 brouard 4440: for(m=iagemin; m <= iagemax+3; m++)
1.251 brouard 4441: prop[i][m]=0;
4442: posprop[i]=0;
4443: pospropt[i]=0;
4444: }
4445: /* for (z1=1; z1<= nqfveff; z1++) { */
4446: /* meanq[z1]+=0.; */
4447: /* for(m=1;m<=lastpass;m++){ */
4448: /* meanqt[m][z1]=0.; */
4449: /* } */
4450: /* } */
4451:
4452: /* dateintsum=0; */
4453: /* k2cpt=0; */
4454:
1.265 brouard 4455: /* For that combination of covariates j1 (V4=1 V3=0 for example), we count and print the frequencies in one pass */
1.251 brouard 4456: for (iind=1; iind<=imx; iind++) { /* For each individual iind */
4457: bool=1;
4458: if(j !=0){
4459: if(anyvaryingduminmodel==0){ /* If All fixed covariates */
4460: if (cptcoveff >0) { /* Filter is here: Must be looked at for model=V1+V2+V3+V4 */
4461: /* for (z1=1; z1<= nqfveff; z1++) { */
4462: /* meanq[z1]+=coqvar[Tvar[z1]][iind]; /\* Computes mean of quantitative with selected filter *\/ */
4463: /* } */
4464: for (z1=1; z1<=cptcoveff; z1++) { /* loops on covariates in the model */
4465: /* if(Tvaraff[z1] ==-20){ */
4466: /* /\* sumnew+=cotvar[mw[mi][iind]][z1][iind]; *\/ */
4467: /* }else if(Tvaraff[z1] ==-10){ */
4468: /* /\* sumnew+=coqvar[z1][iind]; *\/ */
4469: /* }else */
4470: if (covar[Tvaraff[z1]][iind]!= nbcode[Tvaraff[z1]][codtabm(j1,z1)]){ /* for combination j1 of covariates */
1.265 brouard 4471: /* Tests if the value of the covariate z1 for this individual iind responded to combination j1 (V4=1 V3=0) */
1.251 brouard 4472: bool=0; /* bool should be equal to 1 to be selected, one covariate value failed */
4473: /* 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",
4474: bool,i,z1, z1, Tvaraff[z1],i,covar[Tvaraff[z1]][i],j1,z1,codtabm(j1,z1),
4475: j1,z1,nbcode[Tvaraff[z1]][codtabm(j1,z1)],j1);*/
4476: /* For j1=7 in V1+V2+V3+V4 = 0 1 1 0 and codtabm(7,3)=1 and nbcde[3][?]=1*/
4477: } /* Onlyf fixed */
4478: } /* end z1 */
4479: } /* cptcovn > 0 */
4480: } /* end any */
4481: }/* end j==0 */
1.265 brouard 4482: if (bool==1){ /* We selected an individual iind satisfying combination j1 (V4=1 V3=0) or all fixed covariates */
1.251 brouard 4483: /* for(m=firstpass; m<=lastpass; m++){ */
4484: for(mi=1; mi<wav[iind];mi++){ /* For that wave */
4485: m=mw[mi][iind];
4486: if(j!=0){
4487: if(anyvaryingduminmodel==1){ /* Some are varying covariates */
4488: for (z1=1; z1<=cptcoveff; z1++) {
4489: if( Fixed[Tmodelind[z1]]==1){
4490: iv= Tvar[Tmodelind[z1]]-ncovcol-nqv;
4491: if (cotvar[m][iv][iind]!= nbcode[Tvaraff[z1]][codtabm(j1,z1)]) /* iv=1 to ntv, right modality. If covariate's
4492: value is -1, we don't select. It differs from the
4493: constant and age model which counts them. */
4494: bool=0; /* not selected */
4495: }else if( Fixed[Tmodelind[z1]]== 0) { /* fixed */
4496: if (covar[Tvaraff[z1]][iind]!= nbcode[Tvaraff[z1]][codtabm(j1,z1)]) {
4497: bool=0;
4498: }
4499: }
4500: }
4501: }/* Some are varying covariates, we tried to speed up if all fixed covariates in the model, avoiding waves loop */
4502: } /* end j==0 */
4503: /* bool =0 we keep that guy which corresponds to the combination of dummy values */
4504: if(bool==1){
4505: /* dh[m][iind] or dh[mw[mi][iind]][iind] is the delay between two effective (mi) waves m=mw[mi][iind]
4506: and mw[mi+1][iind]. dh depends on stepm. */
4507: agebegin=agev[m][iind]; /* Age at beginning of wave before transition*/
4508: ageend=agev[m][iind]+(dh[m][iind])*stepm/YEARM; /* Age at end of wave and transition */
4509: if(m >=firstpass && m <=lastpass){
4510: k2=anint[m][iind]+(mint[m][iind]/12.);
4511: /*if ((k2>=dateprev1) && (k2<=dateprev2)) {*/
4512: if(agev[m][iind]==0) agev[m][iind]=iagemax+1; /* All ages equal to 0 are in iagemax+1 */
4513: if(agev[m][iind]==1) agev[m][iind]=iagemax+2; /* All ages equal to 1 are in iagemax+2 */
4514: if (s[m][iind]>0 && s[m][iind]<=nlstate) /* If status at wave m is known and a live state */
4515: prop[s[m][iind]][(int)agev[m][iind]] += weight[iind]; /* At age of beginning of transition, where status is known */
4516: if (m<lastpass) {
4517: /* if(s[m][iind]==4 && s[m+1][iind]==4) */
4518: /* 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]); */
4519: if(s[m][iind]==-1)
4520: 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.));
4521: freq[s[m][iind]][s[m+1][iind]][(int)agev[m][iind]] += weight[iind]; /* At age of beginning of transition, where status is known */
4522: /* if((int)agev[m][iind] == 55) */
4523: /* printf("j=%d, j1=%d Age %d, iind=%d, num=%09ld m=%d\n",j,j1,(int)agev[m][iind],iind, num[iind],m); */
4524: /* freq[s[m][iind]][s[m+1][iind]][(int)((agebegin+ageend)/2.)] += weight[iind]; */
4525: 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 4526: }
1.251 brouard 4527: } /* end if between passes */
4528: if ((agev[m][iind]>1) && (agev[m][iind]< (iagemax+3)) && (anint[m][iind]!=9999) && (mint[m][iind]!=99) && (j==0)) {
4529: dateintsum=dateintsum+k2; /* on all covariates ?*/
4530: k2cpt++;
4531: /* printf("iind=%ld dateintmean = %lf dateintsum=%lf k2cpt=%lf k2=%lf\n",iind, dateintsum/k2cpt, dateintsum,k2cpt, k2); */
1.234 brouard 4532: }
1.251 brouard 4533: }else{
4534: bool=1;
4535: }/* end bool 2 */
4536: } /* end m */
4537: } /* end bool */
4538: } /* end iind = 1 to imx */
4539: /* prop[s][age] is feeded for any initial and valid live state as well as
4540: freq[s1][s2][age] at single age of beginning the transition, for a combination j1 */
4541:
4542:
4543: /* fprintf(ficresp, "#Count between %.lf/%.lf/%.lf and %.lf/%.lf/%.lf\n",jprev1, mprev1,anprev1,jprev2, mprev2,anprev2);*/
1.265 brouard 4544: if(cptcoveff==0 && nj==1) /* no covariate and first pass */
4545: pstamp(ficresp);
1.251 brouard 4546: if (cptcoveff>0 && j!=0){
1.265 brouard 4547: pstamp(ficresp);
1.251 brouard 4548: printf( "\n#********** Variable ");
4549: fprintf(ficresp, "\n#********** Variable ");
4550: fprintf(ficresphtm, "\n<br/><br/><h3>********** Variable ");
4551: fprintf(ficresphtmfr, "\n<br/><br/><h3>********** Variable ");
4552: fprintf(ficlog, "\n#********** Variable ");
4553: for (z1=1; z1<=cptcoveff; z1++){
4554: if(!FixedV[Tvaraff[z1]]){
4555: printf( "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4556: fprintf(ficresp, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4557: fprintf(ficresphtm, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4558: fprintf(ficresphtmfr, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4559: fprintf(ficlog, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
1.250 brouard 4560: }else{
1.251 brouard 4561: printf( "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4562: fprintf(ficresp, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4563: fprintf(ficresphtm, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4564: fprintf(ficresphtmfr, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4565: fprintf(ficlog, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4566: }
4567: }
4568: printf( "**********\n#");
4569: fprintf(ficresp, "**********\n#");
4570: fprintf(ficresphtm, "**********</h3>\n");
4571: fprintf(ficresphtmfr, "**********</h3>\n");
4572: fprintf(ficlog, "**********\n");
4573: }
4574: fprintf(ficresphtm,"<table style=\"text-align:center; border: 1px solid\">");
1.265 brouard 4575: if((cptcoveff==0 && nj==1)|| nj==2 ) /* no covariate and first pass */
4576: fprintf(ficresp, " Age");
4577: 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 4578: for(i=1; i<=nlstate;i++) {
1.265 brouard 4579: if((cptcoveff==0 && nj==1)|| nj==2 ) fprintf(ficresp," Prev(%d) N(%d) N ",i,i);
1.251 brouard 4580: fprintf(ficresphtm, "<th>Age</th><th>Prev(%d)</th><th>N(%d)</th><th>N</th>",i,i);
4581: }
1.265 brouard 4582: if((cptcoveff==0 && nj==1)|| nj==2 ) fprintf(ficresp, "\n");
1.251 brouard 4583: fprintf(ficresphtm, "\n");
4584:
4585: /* Header of frequency table by age */
4586: fprintf(ficresphtmfr,"<table style=\"text-align:center; border: 1px solid\">");
4587: fprintf(ficresphtmfr,"<th>Age</th> ");
1.265 brouard 4588: for(s2=-1; s2 <=nlstate+ndeath; s2++){
1.251 brouard 4589: for(m=-1; m <=nlstate+ndeath; m++){
1.265 brouard 4590: if(s2!=0 && m!=0)
4591: fprintf(ficresphtmfr,"<th>%d%d</th> ",s2,m);
1.240 brouard 4592: }
1.226 brouard 4593: }
1.251 brouard 4594: fprintf(ficresphtmfr, "\n");
4595:
4596: /* For each age */
4597: for(iage=iagemin; iage <= iagemax+3; iage++){
4598: fprintf(ficresphtm,"<tr>");
4599: if(iage==iagemax+1){
4600: fprintf(ficlog,"1");
4601: fprintf(ficresphtmfr,"<tr><th>0</th> ");
4602: }else if(iage==iagemax+2){
4603: fprintf(ficlog,"0");
4604: fprintf(ficresphtmfr,"<tr><th>Unknown</th> ");
4605: }else if(iage==iagemax+3){
4606: fprintf(ficlog,"Total");
4607: fprintf(ficresphtmfr,"<tr><th>Total</th> ");
4608: }else{
1.240 brouard 4609: if(first==1){
1.251 brouard 4610: first=0;
4611: printf("See log file for details...\n");
4612: }
4613: fprintf(ficresphtmfr,"<tr><th>%d</th> ",iage);
4614: fprintf(ficlog,"Age %d", iage);
4615: }
1.265 brouard 4616: for(s1=1; s1 <=nlstate ; s1++){
4617: for(m=-1, pp[s1]=0; m <=nlstate+ndeath ; m++)
4618: pp[s1] += freq[s1][m][iage];
1.251 brouard 4619: }
1.265 brouard 4620: for(s1=1; s1 <=nlstate ; s1++){
1.251 brouard 4621: for(m=-1, pos=0; m <=0 ; m++)
1.265 brouard 4622: pos += freq[s1][m][iage];
4623: if(pp[s1]>=1.e-10){
1.251 brouard 4624: if(first==1){
1.265 brouard 4625: printf(" %d.=%.0f loss[%d]=%.1f%%",s1,pp[s1],s1,100*pos/pp[s1]);
1.251 brouard 4626: }
1.265 brouard 4627: fprintf(ficlog," %d.=%.0f loss[%d]=%.1f%%",s1,pp[s1],s1,100*pos/pp[s1]);
1.251 brouard 4628: }else{
4629: if(first==1)
1.265 brouard 4630: printf(" %d.=%.0f loss[%d]=NaNQ%%",s1,pp[s1],s1);
4631: fprintf(ficlog," %d.=%.0f loss[%d]=NaNQ%%",s1,pp[s1],s1);
1.240 brouard 4632: }
4633: }
4634:
1.265 brouard 4635: for(s1=1; s1 <=nlstate ; s1++){
4636: /* posprop[s1]=0; */
4637: for(m=0, pp[s1]=0; m <=nlstate+ndeath; m++)/* Summing on all ages */
4638: pp[s1] += freq[s1][m][iage];
4639: } /* pp[s1] is the total number of transitions starting from state s1 and any ending status until this age */
4640:
4641: for(s1=1,pos=0, pospropta=0.; s1 <=nlstate ; s1++){
4642: pos += pp[s1]; /* pos is the total number of transitions until this age */
4643: posprop[s1] += prop[s1][iage]; /* prop is the number of transitions from a live state
4644: from s1 at age iage prop[s[m][iind]][(int)agev[m][iind]] += weight[iind] */
4645: pospropta += prop[s1][iage]; /* prop is the number of transitions from a live state
4646: from s1 at age iage prop[s[m][iind]][(int)agev[m][iind]] += weight[iind] */
4647: }
4648:
4649: /* Writing ficresp */
4650: if(cptcoveff==0 && nj==1){ /* no covariate and first pass */
4651: if( iage <= iagemax){
4652: fprintf(ficresp," %d",iage);
4653: }
4654: }else if( nj==2){
4655: if( iage <= iagemax){
4656: fprintf(ficresp," %d",iage);
4657: for (z1=1; z1<=cptcoveff; z1++) fprintf(ficresp, " %d %d",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4658: }
1.240 brouard 4659: }
1.265 brouard 4660: for(s1=1; s1 <=nlstate ; s1++){
1.240 brouard 4661: if(pos>=1.e-5){
1.251 brouard 4662: if(first==1)
1.265 brouard 4663: printf(" %d.=%.0f prev[%d]=%.1f%%",s1,pp[s1],s1,100*pp[s1]/pos);
4664: fprintf(ficlog," %d.=%.0f prev[%d]=%.1f%%",s1,pp[s1],s1,100*pp[s1]/pos);
1.251 brouard 4665: }else{
4666: if(first==1)
1.265 brouard 4667: printf(" %d.=%.0f prev[%d]=NaNQ%%",s1,pp[s1],s1);
4668: fprintf(ficlog," %d.=%.0f prev[%d]=NaNQ%%",s1,pp[s1],s1);
1.251 brouard 4669: }
4670: if( iage <= iagemax){
4671: if(pos>=1.e-5){
1.265 brouard 4672: if(cptcoveff==0 && nj==1){ /* no covariate and first pass */
4673: fprintf(ficresp," %.5f %.0f %.0f",prop[s1][iage]/pospropta, prop[s1][iage],pospropta);
4674: }else if( nj==2){
4675: fprintf(ficresp," %.5f %.0f %.0f",prop[s1][iage]/pospropta, prop[s1][iage],pospropta);
4676: }
4677: fprintf(ficresphtm,"<th>%d</th><td>%.5f</td><td>%.0f</td><td>%.0f</td>",iage,prop[s1][iage]/pospropta, prop[s1][iage],pospropta);
4678: /*probs[iage][s1][j1]= pp[s1]/pos;*/
4679: /*printf("\niage=%d s1=%d j1=%d %.5f %.0f %.0f %f",iage,s1,j1,pp[s1]/pos, pp[s1],pos,probs[iage][s1][j1]);*/
4680: } else{
4681: if((cptcoveff==0 && nj==1)|| nj==2 ) fprintf(ficresp," NaNq %.0f %.0f",prop[s1][iage],pospropta);
4682: fprintf(ficresphtm,"<th>%d</th><td>NaNq</td><td>%.0f</td><td>%.0f</td>",iage, prop[s1][iage],pospropta);
1.251 brouard 4683: }
1.240 brouard 4684: }
1.265 brouard 4685: pospropt[s1] +=posprop[s1];
4686: } /* end loop s1 */
1.251 brouard 4687: /* pospropt=0.; */
1.265 brouard 4688: for(s1=-1; s1 <=nlstate+ndeath; s1++){
1.251 brouard 4689: for(m=-1; m <=nlstate+ndeath; m++){
1.265 brouard 4690: if(freq[s1][m][iage] !=0 ) { /* minimizing output */
1.251 brouard 4691: if(first==1){
1.265 brouard 4692: printf(" %d%d=%.0f",s1,m,freq[s1][m][iage]);
1.251 brouard 4693: }
1.265 brouard 4694: /* printf(" %d%d=%.0f",s1,m,freq[s1][m][iage]); */
4695: fprintf(ficlog," %d%d=%.0f",s1,m,freq[s1][m][iage]);
1.251 brouard 4696: }
1.265 brouard 4697: if(s1!=0 && m!=0)
4698: fprintf(ficresphtmfr,"<td>%.0f</td> ",freq[s1][m][iage]);
1.240 brouard 4699: }
1.265 brouard 4700: } /* end loop s1 */
1.251 brouard 4701: posproptt=0.;
1.265 brouard 4702: for(s1=1; s1 <=nlstate; s1++){
4703: posproptt += pospropt[s1];
1.251 brouard 4704: }
4705: fprintf(ficresphtmfr,"</tr>\n ");
1.265 brouard 4706: fprintf(ficresphtm,"</tr>\n");
4707: if((cptcoveff==0 && nj==1)|| nj==2 ) {
4708: if(iage <= iagemax)
4709: fprintf(ficresp,"\n");
1.240 brouard 4710: }
1.251 brouard 4711: if(first==1)
4712: printf("Others in log...\n");
4713: fprintf(ficlog,"\n");
4714: } /* end loop age iage */
1.265 brouard 4715:
1.251 brouard 4716: fprintf(ficresphtm,"<tr><th>Tot</th>");
1.265 brouard 4717: for(s1=1; s1 <=nlstate ; s1++){
1.251 brouard 4718: if(posproptt < 1.e-5){
1.265 brouard 4719: fprintf(ficresphtm,"<td>Nanq</td><td>%.0f</td><td>%.0f</td>",pospropt[s1],posproptt);
1.251 brouard 4720: }else{
1.265 brouard 4721: fprintf(ficresphtm,"<td>%.5f</td><td>%.0f</td><td>%.0f</td>",pospropt[s1]/posproptt,pospropt[s1],posproptt);
1.240 brouard 4722: }
1.226 brouard 4723: }
1.251 brouard 4724: fprintf(ficresphtm,"</tr>\n");
4725: fprintf(ficresphtm,"</table>\n");
4726: fprintf(ficresphtmfr,"</table>\n");
1.226 brouard 4727: if(posproptt < 1.e-5){
1.251 brouard 4728: fprintf(ficresphtm,"\n <p><b> This combination (%d) is not valid and no result will be produced</b></p>",j1);
4729: fprintf(ficresphtmfr,"\n <p><b> This combination (%d) is not valid and no result will be produced</b></p>",j1);
1.260 brouard 4730: fprintf(ficlog,"# This combination (%d) is not valid and no result will be produced\n",j1);
4731: printf("# This combination (%d) is not valid and no result will be produced\n",j1);
1.251 brouard 4732: invalidvarcomb[j1]=1;
1.226 brouard 4733: }else{
1.251 brouard 4734: fprintf(ficresphtm,"\n <p> This combination (%d) is valid and result will be produced.</p>",j1);
4735: invalidvarcomb[j1]=0;
1.226 brouard 4736: }
1.251 brouard 4737: fprintf(ficresphtmfr,"</table>\n");
4738: fprintf(ficlog,"\n");
4739: if(j!=0){
4740: printf("#Freqsummary: Starting values for combination j1=%d:\n", j1);
1.265 brouard 4741: for(i=1,s1=1; i <=nlstate; i++){
1.251 brouard 4742: for(k=1; k <=(nlstate+ndeath); k++){
4743: if (k != i) {
1.265 brouard 4744: for(jj=1; jj <=ncovmodel; jj++){ /* For counting s1 */
1.253 brouard 4745: if(jj==1){ /* Constant case (in fact cste + age) */
1.251 brouard 4746: if(j1==1){ /* All dummy covariates to zero */
4747: freq[i][k][iagemax+4]=freq[i][k][iagemax+3]; /* Stores case 0 0 0 */
4748: freq[i][i][iagemax+4]=freq[i][i][iagemax+3]; /* Stores case 0 0 0 */
1.252 brouard 4749: printf("%d%d ",i,k);
4750: fprintf(ficlog,"%d%d ",i,k);
1.265 brouard 4751: 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]));
4752: 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]));
4753: pstart[s1]= log(freq[i][k][iagemax+3]/freq[i][i][iagemax+3]);
1.251 brouard 4754: }
1.253 brouard 4755: }else if((j1==1) && (jj==2 || nagesqr==1)){ /* age or age*age parameter without covariate V4*age (to be done later) */
4756: for(iage=iagemin; iage <= iagemax+3; iage++){
4757: x[iage]= (double)iage;
4758: y[iage]= log(freq[i][k][iage]/freq[i][i][iage]);
1.265 brouard 4759: /* 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 4760: }
1.268 brouard 4761: /* Some are not finite, but linreg will ignore these ages */
4762: no=0;
1.253 brouard 4763: linreg(iagemin,iagemax,&no,x,y,&a,&b,&r, &sa, &sb ); /* y= a+b*x with standard errors */
1.265 brouard 4764: pstart[s1]=b;
4765: pstart[s1-1]=a;
1.252 brouard 4766: }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 */
4767: 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]);
4768: 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 4769: 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 4770: printf("%d%d ",i,k);
4771: fprintf(ficlog,"%d%d ",i,k);
1.265 brouard 4772: 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 4773: }else{ /* Other cases, like quantitative fixed or varying covariates */
4774: ;
4775: }
4776: /* printf("%12.7f )", param[i][jj][k]); */
4777: /* fprintf(ficlog,"%12.7f )", param[i][jj][k]); */
1.265 brouard 4778: s1++;
1.251 brouard 4779: } /* end jj */
4780: } /* end k!= i */
4781: } /* end k */
1.265 brouard 4782: } /* end i, s1 */
1.251 brouard 4783: } /* end j !=0 */
4784: } /* end selected combination of covariate j1 */
4785: if(j==0){ /* We can estimate starting values from the occurences in each case */
4786: printf("#Freqsummary: Starting values for the constants:\n");
4787: fprintf(ficlog,"\n");
1.265 brouard 4788: for(i=1,s1=1; i <=nlstate; i++){
1.251 brouard 4789: for(k=1; k <=(nlstate+ndeath); k++){
4790: if (k != i) {
4791: printf("%d%d ",i,k);
4792: fprintf(ficlog,"%d%d ",i,k);
4793: for(jj=1; jj <=ncovmodel; jj++){
1.265 brouard 4794: pstart[s1]=p[s1]; /* Setting pstart to p values by default */
1.253 brouard 4795: if(jj==1){ /* Age has to be done */
1.265 brouard 4796: pstart[s1]= log(freq[i][k][iagemax+3]/freq[i][i][iagemax+3]);
4797: 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]));
4798: 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 4799: }
4800: /* printf("%12.7f )", param[i][jj][k]); */
4801: /* fprintf(ficlog,"%12.7f )", param[i][jj][k]); */
1.265 brouard 4802: s1++;
1.250 brouard 4803: }
1.251 brouard 4804: printf("\n");
4805: fprintf(ficlog,"\n");
1.250 brouard 4806: }
4807: }
4808: }
1.251 brouard 4809: printf("#Freqsummary\n");
4810: fprintf(ficlog,"\n");
1.265 brouard 4811: for(s1=-1; s1 <=nlstate+ndeath; s1++){
4812: for(s2=-1; s2 <=nlstate+ndeath; s2++){
4813: /* param[i]|j][k]= freq[s1][s2][iagemax+3] */
4814: printf(" %d%d=%.0f",s1,s2,freq[s1][s2][iagemax+3]);
4815: fprintf(ficlog," %d%d=%.0f",s1,s2,freq[s1][s2][iagemax+3]);
4816: /* if(freq[s1][s2][iage] !=0 ) { /\* minimizing output *\/ */
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]); */
1.251 brouard 4819: /* } */
4820: }
1.265 brouard 4821: } /* end loop s1 */
1.251 brouard 4822:
4823: printf("\n");
4824: fprintf(ficlog,"\n");
4825: } /* end j=0 */
1.249 brouard 4826: } /* end j */
1.252 brouard 4827:
1.253 brouard 4828: if(mle == -2){ /* We want to use these values as starting values */
1.252 brouard 4829: for(i=1, jk=1; i <=nlstate; i++){
4830: for(j=1; j <=nlstate+ndeath; j++){
4831: if(j!=i){
4832: /*ca[0]= k+'a'-1;ca[1]='\0';*/
4833: printf("%1d%1d",i,j);
4834: fprintf(ficparo,"%1d%1d",i,j);
4835: for(k=1; k<=ncovmodel;k++){
4836: /* printf(" %lf",param[i][j][k]); */
4837: /* fprintf(ficparo," %lf",param[i][j][k]); */
4838: p[jk]=pstart[jk];
4839: printf(" %f ",pstart[jk]);
4840: fprintf(ficparo," %f ",pstart[jk]);
4841: jk++;
4842: }
4843: printf("\n");
4844: fprintf(ficparo,"\n");
4845: }
4846: }
4847: }
4848: } /* end mle=-2 */
1.226 brouard 4849: dateintmean=dateintsum/k2cpt;
1.240 brouard 4850:
1.226 brouard 4851: fclose(ficresp);
4852: fclose(ficresphtm);
4853: fclose(ficresphtmfr);
4854: free_vector(meanq,1,nqfveff);
4855: free_matrix(meanqt,1,lastpass,1,nqtveff);
1.253 brouard 4856: free_vector(x, iagemin-AGEMARGE, iagemax+4+AGEMARGE);
4857: free_vector(y, iagemin-AGEMARGE, iagemax+4+AGEMARGE);
1.251 brouard 4858: free_ma3x(freq,-5,nlstate+ndeath,-5,nlstate+ndeath, iagemin-AGEMARGE, iagemax+4+AGEMARGE);
1.226 brouard 4859: free_vector(pospropt,1,nlstate);
4860: free_vector(posprop,1,nlstate);
1.251 brouard 4861: free_matrix(prop,1,nlstate,iagemin-AGEMARGE, iagemax+4+AGEMARGE);
1.226 brouard 4862: free_vector(pp,1,nlstate);
4863: /* End of freqsummary */
4864: }
1.126 brouard 4865:
1.268 brouard 4866: /* Simple linear regression */
4867: int linreg(int ifi, int ila, int *no, const double x[], const double y[], double* a, double* b, double* r, double* sa, double * sb) {
4868:
4869: /* y=a+bx regression */
4870: double sumx = 0.0; /* sum of x */
4871: double sumx2 = 0.0; /* sum of x**2 */
4872: double sumxy = 0.0; /* sum of x * y */
4873: double sumy = 0.0; /* sum of y */
4874: double sumy2 = 0.0; /* sum of y**2 */
4875: double sume2 = 0.0; /* sum of square or residuals */
4876: double yhat;
4877:
4878: double denom=0;
4879: int i;
4880: int ne=*no;
4881:
4882: for ( i=ifi, ne=0;i<=ila;i++) {
4883: if(!isfinite(x[i]) || !isfinite(y[i])){
4884: /* printf(" x[%d]=%f, y[%d]=%f\n",i,x[i],i,y[i]); */
4885: continue;
4886: }
4887: ne=ne+1;
4888: sumx += x[i];
4889: sumx2 += x[i]*x[i];
4890: sumxy += x[i] * y[i];
4891: sumy += y[i];
4892: sumy2 += y[i]*y[i];
4893: denom = (ne * sumx2 - sumx*sumx);
4894: /* 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); */
4895: }
4896:
4897: denom = (ne * sumx2 - sumx*sumx);
4898: if (denom == 0) {
4899: // vertical, slope m is infinity
4900: *b = INFINITY;
4901: *a = 0;
4902: if (r) *r = 0;
4903: return 1;
4904: }
4905:
4906: *b = (ne * sumxy - sumx * sumy) / denom;
4907: *a = (sumy * sumx2 - sumx * sumxy) / denom;
4908: if (r!=NULL) {
4909: *r = (sumxy - sumx * sumy / ne) / /* compute correlation coeff */
4910: sqrt((sumx2 - sumx*sumx/ne) *
4911: (sumy2 - sumy*sumy/ne));
4912: }
4913: *no=ne;
4914: for ( i=ifi, ne=0;i<=ila;i++) {
4915: if(!isfinite(x[i]) || !isfinite(y[i])){
4916: /* printf(" x[%d]=%f, y[%d]=%f\n",i,x[i],i,y[i]); */
4917: continue;
4918: }
4919: ne=ne+1;
4920: yhat = y[i] - *a -*b* x[i];
4921: sume2 += yhat * yhat ;
4922:
4923: denom = (ne * sumx2 - sumx*sumx);
4924: /* 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); */
4925: }
4926: *sb = sqrt(sume2/(double)(ne-2)/(sumx2 - sumx * sumx /(double)ne));
4927: *sa= *sb * sqrt(sumx2/ne);
4928:
4929: return 0;
4930: }
4931:
1.126 brouard 4932: /************ Prevalence ********************/
1.227 brouard 4933: 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)
4934: {
4935: /* Compute observed prevalence between dateprev1 and dateprev2 by counting the number of people
4936: in each health status at the date of interview (if between dateprev1 and dateprev2).
4937: We still use firstpass and lastpass as another selection.
4938: */
1.126 brouard 4939:
1.227 brouard 4940: int i, m, jk, j1, bool, z1,j, iv;
4941: int mi; /* Effective wave */
4942: int iage;
4943: double agebegin, ageend;
4944:
4945: double **prop;
4946: double posprop;
4947: double y2; /* in fractional years */
4948: int iagemin, iagemax;
4949: int first; /** to stop verbosity which is redirected to log file */
4950:
4951: iagemin= (int) agemin;
4952: iagemax= (int) agemax;
4953: /*pp=vector(1,nlstate);*/
1.251 brouard 4954: prop=matrix(1,nlstate,iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.227 brouard 4955: /* freq=ma3x(-1,nlstate+ndeath,-1,nlstate+ndeath,iagemin,iagemax+3);*/
4956: j1=0;
1.222 brouard 4957:
1.227 brouard 4958: /*j=cptcoveff;*/
4959: if (cptcovn<1) {j=1;ncodemax[1]=1;}
1.222 brouard 4960:
1.227 brouard 4961: first=1;
4962: for(j1=1; j1<= (int) pow(2,cptcoveff);j1++){ /* For each combination of covariate */
4963: for (i=1; i<=nlstate; i++)
1.251 brouard 4964: for(iage=iagemin-AGEMARGE; iage <= iagemax+4+AGEMARGE; iage++)
1.227 brouard 4965: prop[i][iage]=0.0;
4966: printf("Prevalence combination of varying and fixed dummies %d\n",j1);
4967: /* fprintf(ficlog," V%d=%d ",Tvaraff[j1],nbcode[Tvaraff[j1]][codtabm(k,j1)]); */
4968: fprintf(ficlog,"Prevalence combination of varying and fixed dummies %d\n",j1);
4969:
4970: for (i=1; i<=imx; i++) { /* Each individual */
4971: bool=1;
4972: /* for(m=firstpass; m<=lastpass; m++){/\* Other selection (we can limit to certain interviews*\/ */
4973: for(mi=1; mi<wav[i];mi++){ /* For this wave too look where individual can be counted V4=0 V3=0 */
4974: m=mw[mi][i];
4975: /* Tmodelind[z1]=k is the position of the varying covariate in the model, but which # within 1 to ntv? */
4976: /* Tvar[Tmodelind[z1]] is the n of Vn; n-ncovcol-nqv is the first time varying covariate or iv */
4977: for (z1=1; z1<=cptcoveff; z1++){
4978: if( Fixed[Tmodelind[z1]]==1){
4979: iv= Tvar[Tmodelind[z1]]-ncovcol-nqv;
4980: if (cotvar[m][iv][i]!= nbcode[Tvaraff[z1]][codtabm(j1,z1)]) /* iv=1 to ntv, right modality */
4981: bool=0;
4982: }else if( Fixed[Tmodelind[z1]]== 0) /* fixed */
4983: if (covar[Tvaraff[z1]][i]!= nbcode[Tvaraff[z1]][codtabm(j1,z1)]) {
4984: bool=0;
4985: }
4986: }
4987: if(bool==1){ /* Otherwise we skip that wave/person */
4988: agebegin=agev[m][i]; /* Age at beginning of wave before transition*/
4989: /* ageend=agev[m][i]+(dh[m][i])*stepm/YEARM; /\* Age at end of wave and transition *\/ */
4990: if(m >=firstpass && m <=lastpass){
4991: y2=anint[m][i]+(mint[m][i]/12.); /* Fractional date in year */
4992: if ((y2>=dateprev1) && (y2<=dateprev2)) { /* Here is the main selection (fractional years) */
4993: if(agev[m][i]==0) agev[m][i]=iagemax+1;
4994: if(agev[m][i]==1) agev[m][i]=iagemax+2;
1.251 brouard 4995: if((int)agev[m][i] <iagemin-AGEMARGE || (int)agev[m][i] >iagemax+4+AGEMARGE){
1.227 brouard 4996: 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);
4997: exit(1);
4998: }
4999: if (s[m][i]>0 && s[m][i]<=nlstate) {
5000: /*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]]);*/
5001: prop[s[m][i]][(int)agev[m][i]] += weight[i];/* At age of beginning of transition, where status is known */
5002: prop[s[m][i]][iagemax+3] += weight[i];
5003: } /* end valid statuses */
5004: } /* end selection of dates */
5005: } /* end selection of waves */
5006: } /* end bool */
5007: } /* end wave */
5008: } /* end individual */
5009: for(i=iagemin; i <= iagemax+3; i++){
5010: for(jk=1,posprop=0; jk <=nlstate ; jk++) {
5011: posprop += prop[jk][i];
5012: }
5013:
5014: for(jk=1; jk <=nlstate ; jk++){
5015: if( i <= iagemax){
5016: if(posprop>=1.e-5){
5017: probs[i][jk][j1]= prop[jk][i]/posprop;
5018: } else{
5019: if(first==1){
5020: first=0;
1.266 brouard 5021: 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]);
5022: 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]);
5023: }else{
5024: 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 5025: }
5026: }
5027: }
5028: }/* end jk */
5029: }/* end i */
1.222 brouard 5030: /*} *//* end i1 */
1.227 brouard 5031: } /* end j1 */
1.222 brouard 5032:
1.227 brouard 5033: /* free_ma3x(freq,-1,nlstate+ndeath,-1,nlstate+ndeath, iagemin, iagemax+3);*/
5034: /*free_vector(pp,1,nlstate);*/
1.251 brouard 5035: free_matrix(prop,1,nlstate, iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.227 brouard 5036: } /* End of prevalence */
1.126 brouard 5037:
5038: /************* Waves Concatenation ***************/
5039:
5040: 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)
5041: {
5042: /* Concatenates waves: wav[i] is the number of effective (useful waves) of individual i.
5043: Death is a valid wave (if date is known).
5044: mw[mi][i] is the mi (mi=1 to wav[i]) effective wave of individual i
5045: dh[m][i] or dh[mw[mi][i]][i] is the delay between two effective waves m=mw[mi][i]
5046: and mw[mi+1][i]. dh depends on stepm.
1.227 brouard 5047: */
1.126 brouard 5048:
1.224 brouard 5049: int i=0, mi=0, m=0, mli=0;
1.126 brouard 5050: /* int j, k=0,jk, ju, jl,jmin=1e+5, jmax=-1;
5051: double sum=0., jmean=0.;*/
1.224 brouard 5052: int first=0, firstwo=0, firsthree=0, firstfour=0, firstfiv=0;
1.126 brouard 5053: int j, k=0,jk, ju, jl;
5054: double sum=0.;
5055: first=0;
1.214 brouard 5056: firstwo=0;
1.217 brouard 5057: firsthree=0;
1.218 brouard 5058: firstfour=0;
1.164 brouard 5059: jmin=100000;
1.126 brouard 5060: jmax=-1;
5061: jmean=0.;
1.224 brouard 5062:
5063: /* Treating live states */
1.214 brouard 5064: for(i=1; i<=imx; i++){ /* For simple cases and if state is death */
1.224 brouard 5065: mi=0; /* First valid wave */
1.227 brouard 5066: mli=0; /* Last valid wave */
1.126 brouard 5067: m=firstpass;
1.214 brouard 5068: while(s[m][i] <= nlstate){ /* a live state */
1.227 brouard 5069: 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 */
5070: mli=m-1;/* mw[++mi][i]=m-1; */
5071: }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 */
5072: mw[++mi][i]=m;
5073: mli=m;
1.224 brouard 5074: } /* else might be a useless wave -1 and mi is not incremented and mw[mi] not updated */
5075: if(m < lastpass){ /* m < lastpass, standard case */
1.227 brouard 5076: m++; /* mi gives the "effective" current wave, m the current wave, go to next wave by incrementing m */
1.216 brouard 5077: }
1.227 brouard 5078: else{ /* m >= lastpass, eventual special issue with warning */
1.224 brouard 5079: #ifdef UNKNOWNSTATUSNOTCONTRIBUTING
1.227 brouard 5080: break;
1.224 brouard 5081: #else
1.227 brouard 5082: if(s[m][i]==-1 && (int) andc[i] == 9999 && (int)anint[m][i] != 9999){
5083: if(firsthree == 0){
1.262 brouard 5084: 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 5085: firsthree=1;
5086: }
1.262 brouard 5087: 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 5088: mw[++mi][i]=m;
5089: mli=m;
5090: }
5091: if(s[m][i]==-2){ /* Vital status is really unknown */
5092: nbwarn++;
5093: if((int)anint[m][i] == 9999){ /* Has the vital status really been verified? */
5094: 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);
5095: 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);
5096: }
5097: break;
5098: }
5099: break;
1.224 brouard 5100: #endif
1.227 brouard 5101: }/* End m >= lastpass */
1.126 brouard 5102: }/* end while */
1.224 brouard 5103:
1.227 brouard 5104: /* 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 5105: /* After last pass */
1.224 brouard 5106: /* Treating death states */
1.214 brouard 5107: if (s[m][i] > nlstate){ /* In a death state */
1.227 brouard 5108: /* if( mint[m][i]==mdc[m][i] && anint[m][i]==andc[m][i]){ /\* same date of death and date of interview *\/ */
5109: /* } */
1.126 brouard 5110: mi++; /* Death is another wave */
5111: /* if(mi==0) never been interviewed correctly before death */
1.227 brouard 5112: /* Only death is a correct wave */
1.126 brouard 5113: mw[mi][i]=m;
1.257 brouard 5114: } /* else not in a death state */
1.224 brouard 5115: #ifndef DISPATCHINGKNOWNDEATHAFTERLASTWAVE
1.257 brouard 5116: else if ((int) andc[i] != 9999) { /* Date of death is known */
1.218 brouard 5117: if ((int)anint[m][i]!= 9999) { /* date of last interview is known */
1.227 brouard 5118: 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 */
5119: nbwarn++;
5120: if(firstfiv==0){
5121: 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 );
5122: firstfiv=1;
5123: }else{
5124: 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 );
5125: }
5126: }else{ /* Death occured afer last wave potential bias */
5127: nberr++;
5128: if(firstwo==0){
1.257 brouard 5129: 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 5130: firstwo=1;
5131: }
1.257 brouard 5132: 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 5133: }
1.257 brouard 5134: }else{ /* if date of interview is unknown */
1.227 brouard 5135: /* death is known but not confirmed by death status at any wave */
5136: if(firstfour==0){
5137: 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 );
5138: firstfour=1;
5139: }
5140: 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 5141: }
1.224 brouard 5142: } /* end if date of death is known */
5143: #endif
5144: wav[i]=mi; /* mi should be the last effective wave (or mli) */
5145: /* wav[i]=mw[mi][i]; */
1.126 brouard 5146: if(mi==0){
5147: nbwarn++;
5148: if(first==0){
1.227 brouard 5149: printf("Warning! No valid information for individual %ld line=%d (skipped) and may be others, see log file\n",num[i],i);
5150: first=1;
1.126 brouard 5151: }
5152: if(first==1){
1.227 brouard 5153: fprintf(ficlog,"Warning! No valid information for individual %ld line=%d (skipped)\n",num[i],i);
1.126 brouard 5154: }
5155: } /* end mi==0 */
5156: } /* End individuals */
1.214 brouard 5157: /* wav and mw are no more changed */
1.223 brouard 5158:
1.214 brouard 5159:
1.126 brouard 5160: for(i=1; i<=imx; i++){
5161: for(mi=1; mi<wav[i];mi++){
5162: if (stepm <=0)
1.227 brouard 5163: dh[mi][i]=1;
1.126 brouard 5164: else{
1.260 brouard 5165: if (s[mw[mi+1][i]][i] > nlstate) { /* A death, but what if date is unknown? */
1.227 brouard 5166: if (agedc[i] < 2*AGESUP) {
5167: j= rint(agedc[i]*12-agev[mw[mi][i]][i]*12);
5168: if(j==0) j=1; /* Survives at least one month after exam */
5169: else if(j<0){
5170: nberr++;
5171: 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]);
5172: j=1; /* Temporary Dangerous patch */
5173: 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);
5174: 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]);
5175: 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);
5176: }
5177: k=k+1;
5178: if (j >= jmax){
5179: jmax=j;
5180: ijmax=i;
5181: }
5182: if (j <= jmin){
5183: jmin=j;
5184: ijmin=i;
5185: }
5186: sum=sum+j;
5187: /*if (j<0) printf("j=%d num=%d \n",j,i);*/
5188: /* printf("%d %d %d %d\n", s[mw[mi][i]][i] ,s[mw[mi+1][i]][i],j,i);*/
5189: }
5190: }
5191: else{
5192: j= rint( (agev[mw[mi+1][i]][i]*12 - agev[mw[mi][i]][i]*12));
1.126 brouard 5193: /* 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 5194:
1.227 brouard 5195: k=k+1;
5196: if (j >= jmax) {
5197: jmax=j;
5198: ijmax=i;
5199: }
5200: else if (j <= jmin){
5201: jmin=j;
5202: ijmin=i;
5203: }
5204: /* if (j<10) printf("j=%d jmin=%d num=%d ",j,jmin,i); */
5205: /*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]);*/
5206: if(j<0){
5207: nberr++;
5208: 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]);
5209: 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]);
5210: }
5211: sum=sum+j;
5212: }
5213: jk= j/stepm;
5214: jl= j -jk*stepm;
5215: ju= j -(jk+1)*stepm;
5216: if(mle <=1){ /* only if we use a the linear-interpoloation pseudo-likelihood */
5217: if(jl==0){
5218: dh[mi][i]=jk;
5219: bh[mi][i]=0;
5220: }else{ /* We want a negative bias in order to only have interpolation ie
5221: * to avoid the price of an extra matrix product in likelihood */
5222: dh[mi][i]=jk+1;
5223: bh[mi][i]=ju;
5224: }
5225: }else{
5226: if(jl <= -ju){
5227: dh[mi][i]=jk;
5228: bh[mi][i]=jl; /* bias is positive if real duration
5229: * is higher than the multiple of stepm and negative otherwise.
5230: */
5231: }
5232: else{
5233: dh[mi][i]=jk+1;
5234: bh[mi][i]=ju;
5235: }
5236: if(dh[mi][i]==0){
5237: dh[mi][i]=1; /* At least one step */
5238: bh[mi][i]=ju; /* At least one step */
5239: /* 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);*/
5240: }
5241: } /* end if mle */
1.126 brouard 5242: }
5243: } /* end wave */
5244: }
5245: jmean=sum/k;
5246: 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 5247: 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 5248: }
1.126 brouard 5249:
5250: /*********** Tricode ****************************/
1.220 brouard 5251: void tricode(int *cptcov, int *Tvar, int **nbcode, int imx, int *Ndum)
1.242 brouard 5252: {
5253: /**< Uses cptcovn+2*cptcovprod as the number of covariates */
5254: /* Tvar[i]=atoi(stre); find 'n' in Vn and stores in Tvar. If model=V2+V1 Tvar[1]=2 and Tvar[2]=1
5255: * Boring subroutine which should only output nbcode[Tvar[j]][k]
5256: * Tvar[5] in V2+V1+V3*age+V2*V4 is 4 (V4) even it is a time varying or quantitative variable
5257: * nbcode[Tvar[5]][1]= nbcode[4][1]=0, nbcode[4][2]=1 (usually);
5258: */
1.130 brouard 5259:
1.242 brouard 5260: int ij=1, k=0, j=0, i=0, maxncov=NCOVMAX;
5261: int modmaxcovj=0; /* Modality max of covariates j */
5262: int cptcode=0; /* Modality max of covariates j */
5263: int modmincovj=0; /* Modality min of covariates j */
1.145 brouard 5264:
5265:
1.242 brouard 5266: /* cptcoveff=0; */
5267: /* *cptcov=0; */
1.126 brouard 5268:
1.242 brouard 5269: for (k=1; k <= maxncov; k++) ncodemax[k]=0; /* Horrible constant again replaced by NCOVMAX */
1.126 brouard 5270:
1.242 brouard 5271: /* Loop on covariates without age and products and no quantitative variable */
5272: /* for (j=1; j<=(cptcovs); j++) { /\* From model V1 + V2*age+ V3 + V3*V4 keeps V1 + V3 = 2 only *\/ */
5273: for (k=1; k<=cptcovt; k++) { /* From model V1 + V2*age + V3 + V3*V4 keeps V1 + V3 = 2 only */
5274: for (j=-1; (j < maxncov); j++) Ndum[j]=0;
5275: if(Dummy[k]==0 && Typevar[k] !=1){ /* Dummy covariate and not age product */
5276: switch(Fixed[k]) {
5277: case 0: /* Testing on fixed dummy covariate, simple or product of fixed */
5278: 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*/
5279: ij=(int)(covar[Tvar[k]][i]);
5280: /* ij=0 or 1 or -1. Value of the covariate Tvar[j] for individual i
5281: * If product of Vn*Vm, still boolean *:
5282: * If it was coded 1, 2, 3, 4 should be splitted into 3 boolean variables
5283: * 1 => 0 0 0, 2 => 0 0 1, 3 => 0 1 1, 4=1 0 0 */
5284: /* Finds for covariate j, n=Tvar[j] of Vn . ij is the
5285: modality of the nth covariate of individual i. */
5286: if (ij > modmaxcovj)
5287: modmaxcovj=ij;
5288: else if (ij < modmincovj)
5289: modmincovj=ij;
5290: if ((ij < -1) && (ij > NCOVMAX)){
5291: printf( "Error: minimal is less than -1 or maximal is bigger than %d. Exiting. \n", NCOVMAX );
5292: exit(1);
5293: }else
5294: Ndum[ij]++; /*counts and stores the occurence of this modality 0, 1, -1*/
5295: /* If coded 1, 2, 3 , counts the number of 1 Ndum[1], number of 2, Ndum[2], etc */
5296: /*printf("i=%d ij=%d Ndum[ij]=%d imx=%d",i,ij,Ndum[ij],imx);*/
5297: /* getting the maximum value of the modality of the covariate
5298: (should be 0 or 1 now) Tvar[j]. If V=sex and male is coded 0 and
5299: female ies 1, then modmaxcovj=1.
5300: */
5301: } /* end for loop on individuals i */
5302: printf(" Minimal and maximal values of %d th (fixed) covariate V%d: min=%d max=%d \n", k, Tvar[k], modmincovj, modmaxcovj);
5303: fprintf(ficlog," Minimal and maximal values of %d th (fixed) covariate V%d: min=%d max=%d \n", k, Tvar[k], modmincovj, modmaxcovj);
5304: cptcode=modmaxcovj;
5305: /* Ndum[0] = frequency of 0 for model-covariate j, Ndum[1] frequency of 1 etc. */
5306: /*for (i=0; i<=cptcode; i++) {*/
5307: for (j=modmincovj; j<=modmaxcovj; j++) { /* j=-1 ? 0 and 1*//* For each value j of the modality of model-cov k */
5308: printf("Frequencies of (fixed) covariate %d ie V%d with value %d: %d\n", k, Tvar[k], j, Ndum[j]);
5309: fprintf(ficlog, "Frequencies of (fixed) covariate %d ie V%d with value %d: %d\n", k, Tvar[k], j, Ndum[j]);
5310: if( Ndum[j] != 0 ){ /* Counts if nobody answered modality j ie empty modality, we skip it and reorder */
5311: if( j != -1){
5312: ncodemax[k]++; /* ncodemax[k]= Number of modalities of the k th
5313: covariate for which somebody answered excluding
5314: undefined. Usually 2: 0 and 1. */
5315: }
5316: ncodemaxwundef[k]++; /* ncodemax[j]= Number of modalities of the k th
5317: covariate for which somebody answered including
5318: undefined. Usually 3: -1, 0 and 1. */
5319: } /* In fact ncodemax[k]=2 (dichotom. variables only) but it could be more for
5320: * historical reasons: 3 if coded 1, 2, 3 and 4 and Ndum[2]=0 */
5321: } /* Ndum[-1] number of undefined modalities */
1.231 brouard 5322:
1.242 brouard 5323: /* j is a covariate, n=Tvar[j] of Vn; Fills nbcode */
5324: /* For covariate j, modalities could be 1, 2, 3, 4, 5, 6, 7. */
5325: /* If Ndum[1]=0, Ndum[2]=0, Ndum[3]= 635, Ndum[4]=0, Ndum[5]=0, Ndum[6]=27, Ndum[7]=125; */
5326: /* modmincovj=3; modmaxcovj = 7; */
5327: /* There are only 3 modalities non empty 3, 6, 7 (or 2 if 27 is too few) : ncodemax[j]=3; */
5328: /* which will be coded 0, 1, 2 which in binary on 2=3-1 digits are 0=00 1=01, 2=10; */
5329: /* defining two dummy variables: variables V1_1 and V1_2.*/
5330: /* nbcode[Tvar[j]][ij]=k; */
5331: /* nbcode[Tvar[j]][1]=0; */
5332: /* nbcode[Tvar[j]][2]=1; */
5333: /* nbcode[Tvar[j]][3]=2; */
5334: /* To be continued (not working yet). */
5335: ij=0; /* ij is similar to i but can jump over null modalities */
5336: 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*/
5337: if (Ndum[i] == 0) { /* If nobody responded to this modality k */
5338: break;
5339: }
5340: ij++;
5341: 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*/
5342: cptcode = ij; /* New max modality for covar j */
5343: } /* end of loop on modality i=-1 to 1 or more */
5344: break;
5345: case 1: /* Testing on varying covariate, could be simple and
5346: * should look at waves or product of fixed *
5347: * varying. No time to test -1, assuming 0 and 1 only */
5348: ij=0;
5349: for(i=0; i<=1;i++){
5350: nbcode[Tvar[k]][++ij]=i;
5351: }
5352: break;
5353: default:
5354: break;
5355: } /* end switch */
5356: } /* end dummy test */
5357:
5358: /* for (k=0; k<= cptcode; k++) { /\* k=-1 ? k=0 to 1 *\//\* Could be 1 to 4 *\//\* cptcode=modmaxcovj *\/ */
5359: /* /\*recode from 0 *\/ */
5360: /* k is a modality. If we have model=V1+V1*sex */
5361: /* then: nbcode[1][1]=0 ; nbcode[1][2]=1; nbcode[2][1]=0 ; nbcode[2][2]=1; */
5362: /* But if some modality were not used, it is recoded from 0 to a newer modmaxcovj=cptcode *\/ */
5363: /* } */
5364: /* /\* cptcode = ij; *\/ /\* New max modality for covar j *\/ */
5365: /* if (ij > ncodemax[j]) { */
5366: /* printf( " Error ij=%d > ncodemax[%d]=%d\n", ij, j, ncodemax[j]); */
5367: /* fprintf(ficlog, " Error ij=%d > ncodemax[%d]=%d\n", ij, j, ncodemax[j]); */
5368: /* break; */
5369: /* } */
5370: /* } /\* end of loop on modality k *\/ */
5371: } /* end of loop on model-covariate j. nbcode[Tvarj][1]=0 and nbcode[Tvarj][2]=1 sets the value of covariate j*/
5372:
5373: for (k=-1; k< maxncov; k++) Ndum[k]=0;
5374: /* Look at fixed dummy (single or product) covariates to check empty modalities */
5375: for (i=1; i<=ncovmodel-2-nagesqr; i++) { /* -2, cste and age and eventually age*age */
5376: /* Listing of all covariables in statement model to see if some covariates appear twice. For example, V1 appears twice in V1+V1*V2.*/
5377: 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 */
5378: 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 */
5379: /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, {2, 1, 1, 1, 2, 1, 1, 0, 0} */
5380: } /* V4+V3+V5, Ndum[1]@5={0, 0, 1, 1, 1} */
5381:
5382: ij=0;
5383: /* for (i=0; i<= maxncov-1; i++) { /\* modmaxcovj is unknown here. Only Ndum[2(V2),3(age*V3), 5(V3*V2) 6(V1*V4) *\/ */
5384: for (k=1; k<= cptcovt; k++) { /* modmaxcovj is unknown here. Only Ndum[2(V2),3(age*V3), 5(V3*V2) 6(V1*V4) */
5385: /*printf("Ndum[%d]=%d\n",i, Ndum[i]);*/
5386: /* if((Ndum[i]!=0) && (i<=ncovcol)){ /\* Tvar[i] <= ncovmodel ? *\/ */
5387: if(Ndum[Tvar[k]]!=0 && Dummy[k] == 0 && Typevar[k]==0){ /* Only Dummy and non empty in the model */
5388: /* If product not in single variable we don't print results */
5389: /*printf("diff Ndum[%d]=%d\n",i, Ndum[i]);*/
5390: ++ij;/* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, */
5391: 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*/
5392: Tmodelind[ij]=k; /* Tmodelind: index in model of dummies Tmodelind[1]=2 V4: pos=2; V3: pos=3, V1=9 {2, 3, 9, ?, ?,} */
5393: 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 */
5394: if(Fixed[k]!=0)
5395: anyvaryingduminmodel=1;
5396: /* }else if((Ndum[i]!=0) && (i<=ncovcol+nqv)){ */
5397: /* Tvaraff[++ij]=-10; /\* Dont'n know how to treat quantitative variables yet *\/ */
5398: /* }else if((Ndum[i]!=0) && (i<=ncovcol+nqv+ntv)){ */
5399: /* Tvaraff[++ij]=i; /\*For printing (unclear) *\/ */
5400: /* }else if((Ndum[i]!=0) && (i<=ncovcol+nqv+ntv+nqtv)){ */
5401: /* Tvaraff[++ij]=-20; /\* Dont'n know how to treat quantitative variables yet *\/ */
5402: }
5403: } /* Tvaraff[1]@5 {3, 4, -20, 0, 0} Very strange */
5404: /* ij--; */
5405: /* cptcoveff=ij; /\*Number of total covariates*\/ */
5406: *cptcov=ij; /*Number of total real effective covariates: effective
5407: * because they can be excluded from the model and real
5408: * if in the model but excluded because missing values, but how to get k from ij?*/
5409: for(j=ij+1; j<= cptcovt; j++){
5410: Tvaraff[j]=0;
5411: Tmodelind[j]=0;
5412: }
5413: for(j=ntveff+1; j<= cptcovt; j++){
5414: TmodelInvind[j]=0;
5415: }
5416: /* To be sorted */
5417: ;
5418: }
1.126 brouard 5419:
1.145 brouard 5420:
1.126 brouard 5421: /*********** Health Expectancies ****************/
5422:
1.235 brouard 5423: 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 5424:
5425: {
5426: /* Health expectancies, no variances */
1.164 brouard 5427: int i, j, nhstepm, hstepm, h, nstepm;
1.126 brouard 5428: int nhstepma, nstepma; /* Decreasing with age */
5429: double age, agelim, hf;
5430: double ***p3mat;
5431: double eip;
5432:
1.238 brouard 5433: /* pstamp(ficreseij); */
1.126 brouard 5434: fprintf(ficreseij,"# (a) Life expectancies by health status at initial age and (b) health expectancies by health status at initial age\n");
5435: fprintf(ficreseij,"# Age");
5436: for(i=1; i<=nlstate;i++){
5437: for(j=1; j<=nlstate;j++){
5438: fprintf(ficreseij," e%1d%1d ",i,j);
5439: }
5440: fprintf(ficreseij," e%1d. ",i);
5441: }
5442: fprintf(ficreseij,"\n");
5443:
5444:
5445: if(estepm < stepm){
5446: printf ("Problem %d lower than %d\n",estepm, stepm);
5447: }
5448: else hstepm=estepm;
5449: /* We compute the life expectancy from trapezoids spaced every estepm months
5450: * This is mainly to measure the difference between two models: for example
5451: * if stepm=24 months pijx are given only every 2 years and by summing them
5452: * we are calculating an estimate of the Life Expectancy assuming a linear
5453: * progression in between and thus overestimating or underestimating according
5454: * to the curvature of the survival function. If, for the same date, we
5455: * estimate the model with stepm=1 month, we can keep estepm to 24 months
5456: * to compare the new estimate of Life expectancy with the same linear
5457: * hypothesis. A more precise result, taking into account a more precise
5458: * curvature will be obtained if estepm is as small as stepm. */
5459:
5460: /* For example we decided to compute the life expectancy with the smallest unit */
5461: /* hstepm beeing the number of stepms, if hstepm=1 the length of hstepm is stepm.
5462: nhstepm is the number of hstepm from age to agelim
5463: nstepm is the number of stepm from age to agelin.
5464: Look at hpijx to understand the reason of that which relies in memory size
5465: and note for a fixed period like estepm months */
5466: /* We decided (b) to get a life expectancy respecting the most precise curvature of the
5467: survival function given by stepm (the optimization length). Unfortunately it
5468: means that if the survival funtion is printed only each two years of age and if
5469: you sum them up and add 1 year (area under the trapezoids) you won't get the same
5470: results. So we changed our mind and took the option of the best precision.
5471: */
5472: hstepm=hstepm/stepm; /* Typically in stepm units, if stepm=6 & estepm=24 , = 24/6 months = 4 */
5473:
5474: agelim=AGESUP;
5475: /* If stepm=6 months */
5476: /* Computed by stepm unit matrices, product of hstepm matrices, stored
5477: in an array of nhstepm length: nhstepm=10, hstepm=4, stepm=6 months */
5478:
5479: /* nhstepm age range expressed in number of stepm */
5480: nstepm=(int) rint((agelim-bage)*YEARM/stepm); /* Biggest nstepm */
5481: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
5482: /* if (stepm >= YEARM) hstepm=1;*/
5483: nhstepm = nstepm/hstepm;/* Expressed in hstepm, typically nhstepm=40/4=10 */
5484: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
5485:
5486: for (age=bage; age<=fage; age ++){
5487: nstepma=(int) rint((agelim-bage)*YEARM/stepm); /* Biggest nstepm */
5488: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
5489: /* if (stepm >= YEARM) hstepm=1;*/
5490: nhstepma = nstepma/hstepm;/* Expressed in hstepm, typically nhstepma=40/4=10 */
5491:
5492: /* If stepm=6 months */
5493: /* Computed by stepm unit matrices, product of hstepma matrices, stored
5494: in an array of nhstepma length: nhstepma=10, hstepm=4, stepm=6 months */
5495:
1.235 brouard 5496: hpxij(p3mat,nhstepma,age,hstepm,x,nlstate,stepm,oldm, savm, cij, nres);
1.126 brouard 5497:
5498: hf=hstepm*stepm/YEARM; /* Duration of hstepm expressed in year unit. */
5499:
5500: printf("%d|",(int)age);fflush(stdout);
5501: fprintf(ficlog,"%d|",(int)age);fflush(ficlog);
5502:
5503: /* Computing expectancies */
5504: for(i=1; i<=nlstate;i++)
5505: for(j=1; j<=nlstate;j++)
5506: for (h=0, eij[i][j][(int)age]=0; h<=nhstepm-1; h++){
5507: eij[i][j][(int)age] += (p3mat[i][j][h]+p3mat[i][j][h+1])/2.0*hf;
5508:
5509: /* 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]);*/
5510:
5511: }
5512:
5513: fprintf(ficreseij,"%3.0f",age );
5514: for(i=1; i<=nlstate;i++){
5515: eip=0;
5516: for(j=1; j<=nlstate;j++){
5517: eip +=eij[i][j][(int)age];
5518: fprintf(ficreseij,"%9.4f", eij[i][j][(int)age] );
5519: }
5520: fprintf(ficreseij,"%9.4f", eip );
5521: }
5522: fprintf(ficreseij,"\n");
5523:
5524: }
5525: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
5526: printf("\n");
5527: fprintf(ficlog,"\n");
5528:
5529: }
5530:
1.235 brouard 5531: 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 5532:
5533: {
5534: /* Covariances of health expectancies eij and of total life expectancies according
1.222 brouard 5535: to initial status i, ei. .
1.126 brouard 5536: */
5537: int i, j, nhstepm, hstepm, h, nstepm, k, cptj, cptj2, i2, j2, ij, ji;
5538: int nhstepma, nstepma; /* Decreasing with age */
5539: double age, agelim, hf;
5540: double ***p3matp, ***p3matm, ***varhe;
5541: double **dnewm,**doldm;
5542: double *xp, *xm;
5543: double **gp, **gm;
5544: double ***gradg, ***trgradg;
5545: int theta;
5546:
5547: double eip, vip;
5548:
5549: varhe=ma3x(1,nlstate*nlstate,1,nlstate*nlstate,(int) bage, (int) fage);
5550: xp=vector(1,npar);
5551: xm=vector(1,npar);
5552: dnewm=matrix(1,nlstate*nlstate,1,npar);
5553: doldm=matrix(1,nlstate*nlstate,1,nlstate*nlstate);
5554:
5555: pstamp(ficresstdeij);
5556: fprintf(ficresstdeij,"# Health expectancies with standard errors\n");
5557: fprintf(ficresstdeij,"# Age");
5558: for(i=1; i<=nlstate;i++){
5559: for(j=1; j<=nlstate;j++)
5560: fprintf(ficresstdeij," e%1d%1d (SE)",i,j);
5561: fprintf(ficresstdeij," e%1d. ",i);
5562: }
5563: fprintf(ficresstdeij,"\n");
5564:
5565: pstamp(ficrescveij);
5566: fprintf(ficrescveij,"# Subdiagonal matrix of covariances of health expectancies by age: cov(eij,ekl)\n");
5567: fprintf(ficrescveij,"# Age");
5568: for(i=1; i<=nlstate;i++)
5569: for(j=1; j<=nlstate;j++){
5570: cptj= (j-1)*nlstate+i;
5571: for(i2=1; i2<=nlstate;i2++)
5572: for(j2=1; j2<=nlstate;j2++){
5573: cptj2= (j2-1)*nlstate+i2;
5574: if(cptj2 <= cptj)
5575: fprintf(ficrescveij," %1d%1d,%1d%1d",i,j,i2,j2);
5576: }
5577: }
5578: fprintf(ficrescveij,"\n");
5579:
5580: if(estepm < stepm){
5581: printf ("Problem %d lower than %d\n",estepm, stepm);
5582: }
5583: else hstepm=estepm;
5584: /* We compute the life expectancy from trapezoids spaced every estepm months
5585: * This is mainly to measure the difference between two models: for example
5586: * if stepm=24 months pijx are given only every 2 years and by summing them
5587: * we are calculating an estimate of the Life Expectancy assuming a linear
5588: * progression in between and thus overestimating or underestimating according
5589: * to the curvature of the survival function. If, for the same date, we
5590: * estimate the model with stepm=1 month, we can keep estepm to 24 months
5591: * to compare the new estimate of Life expectancy with the same linear
5592: * hypothesis. A more precise result, taking into account a more precise
5593: * curvature will be obtained if estepm is as small as stepm. */
5594:
5595: /* For example we decided to compute the life expectancy with the smallest unit */
5596: /* hstepm beeing the number of stepms, if hstepm=1 the length of hstepm is stepm.
5597: nhstepm is the number of hstepm from age to agelim
5598: nstepm is the number of stepm from age to agelin.
5599: Look at hpijx to understand the reason of that which relies in memory size
5600: and note for a fixed period like estepm months */
5601: /* We decided (b) to get a life expectancy respecting the most precise curvature of the
5602: survival function given by stepm (the optimization length). Unfortunately it
5603: means that if the survival funtion is printed only each two years of age and if
5604: you sum them up and add 1 year (area under the trapezoids) you won't get the same
5605: results. So we changed our mind and took the option of the best precision.
5606: */
5607: hstepm=hstepm/stepm; /* Typically in stepm units, if stepm=6 & estepm=24 , = 24/6 months = 4 */
5608:
5609: /* If stepm=6 months */
5610: /* nhstepm age range expressed in number of stepm */
5611: agelim=AGESUP;
5612: nstepm=(int) rint((agelim-bage)*YEARM/stepm);
5613: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
5614: /* if (stepm >= YEARM) hstepm=1;*/
5615: nhstepm = nstepm/hstepm;/* Expressed in hstepm, typically nhstepm=40/4=10 */
5616:
5617: p3matp=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
5618: p3matm=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
5619: gradg=ma3x(0,nhstepm,1,npar,1,nlstate*nlstate);
5620: trgradg =ma3x(0,nhstepm,1,nlstate*nlstate,1,npar);
5621: gp=matrix(0,nhstepm,1,nlstate*nlstate);
5622: gm=matrix(0,nhstepm,1,nlstate*nlstate);
5623:
5624: for (age=bage; age<=fage; age ++){
5625: nstepma=(int) rint((agelim-bage)*YEARM/stepm); /* Biggest nstepm */
5626: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
5627: /* if (stepm >= YEARM) hstepm=1;*/
5628: nhstepma = nstepma/hstepm;/* Expressed in hstepm, typically nhstepma=40/4=10 */
1.218 brouard 5629:
1.126 brouard 5630: /* If stepm=6 months */
5631: /* Computed by stepm unit matrices, product of hstepma matrices, stored
5632: in an array of nhstepma length: nhstepma=10, hstepm=4, stepm=6 months */
5633:
5634: hf=hstepm*stepm/YEARM; /* Duration of hstepm expressed in year unit. */
1.218 brouard 5635:
1.126 brouard 5636: /* Computing Variances of health expectancies */
5637: /* Gradient is computed with plus gp and minus gm. Code is duplicated in order to
5638: decrease memory allocation */
5639: for(theta=1; theta <=npar; theta++){
5640: for(i=1; i<=npar; i++){
1.222 brouard 5641: xp[i] = x[i] + (i==theta ?delti[theta]:0);
5642: xm[i] = x[i] - (i==theta ?delti[theta]:0);
1.126 brouard 5643: }
1.235 brouard 5644: hpxij(p3matp,nhstepm,age,hstepm,xp,nlstate,stepm,oldm,savm, cij, nres);
5645: hpxij(p3matm,nhstepm,age,hstepm,xm,nlstate,stepm,oldm,savm, cij, nres);
1.218 brouard 5646:
1.126 brouard 5647: for(j=1; j<= nlstate; j++){
1.222 brouard 5648: for(i=1; i<=nlstate; i++){
5649: for(h=0; h<=nhstepm-1; h++){
5650: gp[h][(j-1)*nlstate + i] = (p3matp[i][j][h]+p3matp[i][j][h+1])/2.;
5651: gm[h][(j-1)*nlstate + i] = (p3matm[i][j][h]+p3matm[i][j][h+1])/2.;
5652: }
5653: }
1.126 brouard 5654: }
1.218 brouard 5655:
1.126 brouard 5656: for(ij=1; ij<= nlstate*nlstate; ij++)
1.222 brouard 5657: for(h=0; h<=nhstepm-1; h++){
5658: gradg[h][theta][ij]= (gp[h][ij]-gm[h][ij])/2./delti[theta];
5659: }
1.126 brouard 5660: }/* End theta */
5661:
5662:
5663: for(h=0; h<=nhstepm-1; h++)
5664: for(j=1; j<=nlstate*nlstate;j++)
1.222 brouard 5665: for(theta=1; theta <=npar; theta++)
5666: trgradg[h][j][theta]=gradg[h][theta][j];
1.126 brouard 5667:
1.218 brouard 5668:
1.222 brouard 5669: for(ij=1;ij<=nlstate*nlstate;ij++)
1.126 brouard 5670: for(ji=1;ji<=nlstate*nlstate;ji++)
1.222 brouard 5671: varhe[ij][ji][(int)age] =0.;
1.218 brouard 5672:
1.222 brouard 5673: printf("%d|",(int)age);fflush(stdout);
5674: fprintf(ficlog,"%d|",(int)age);fflush(ficlog);
5675: for(h=0;h<=nhstepm-1;h++){
1.126 brouard 5676: for(k=0;k<=nhstepm-1;k++){
1.222 brouard 5677: matprod2(dnewm,trgradg[h],1,nlstate*nlstate,1,npar,1,npar,matcov);
5678: matprod2(doldm,dnewm,1,nlstate*nlstate,1,npar,1,nlstate*nlstate,gradg[k]);
5679: for(ij=1;ij<=nlstate*nlstate;ij++)
5680: for(ji=1;ji<=nlstate*nlstate;ji++)
5681: varhe[ij][ji][(int)age] += doldm[ij][ji]*hf*hf;
1.126 brouard 5682: }
5683: }
1.218 brouard 5684:
1.126 brouard 5685: /* Computing expectancies */
1.235 brouard 5686: hpxij(p3matm,nhstepm,age,hstepm,x,nlstate,stepm,oldm, savm, cij,nres);
1.126 brouard 5687: for(i=1; i<=nlstate;i++)
5688: for(j=1; j<=nlstate;j++)
1.222 brouard 5689: for (h=0, eij[i][j][(int)age]=0; h<=nhstepm-1; h++){
5690: eij[i][j][(int)age] += (p3matm[i][j][h]+p3matm[i][j][h+1])/2.0*hf;
1.218 brouard 5691:
1.222 brouard 5692: /* 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 5693:
1.222 brouard 5694: }
1.269 ! brouard 5695:
! 5696: /* Standard deviation of expectancies ij */
1.126 brouard 5697: fprintf(ficresstdeij,"%3.0f",age );
5698: for(i=1; i<=nlstate;i++){
5699: eip=0.;
5700: vip=0.;
5701: for(j=1; j<=nlstate;j++){
1.222 brouard 5702: eip += eij[i][j][(int)age];
5703: for(k=1; k<=nlstate;k++) /* Sum on j and k of cov(eij,eik) */
5704: vip += varhe[(j-1)*nlstate+i][(k-1)*nlstate+i][(int)age];
5705: 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 5706: }
5707: fprintf(ficresstdeij," %9.4f (%.4f)", eip, sqrt(vip));
5708: }
5709: fprintf(ficresstdeij,"\n");
1.218 brouard 5710:
1.269 ! brouard 5711: /* Variance of expectancies ij */
1.126 brouard 5712: fprintf(ficrescveij,"%3.0f",age );
5713: for(i=1; i<=nlstate;i++)
5714: for(j=1; j<=nlstate;j++){
1.222 brouard 5715: cptj= (j-1)*nlstate+i;
5716: for(i2=1; i2<=nlstate;i2++)
5717: for(j2=1; j2<=nlstate;j2++){
5718: cptj2= (j2-1)*nlstate+i2;
5719: if(cptj2 <= cptj)
5720: fprintf(ficrescveij," %.4f", varhe[cptj][cptj2][(int)age]);
5721: }
1.126 brouard 5722: }
5723: fprintf(ficrescveij,"\n");
1.218 brouard 5724:
1.126 brouard 5725: }
5726: free_matrix(gm,0,nhstepm,1,nlstate*nlstate);
5727: free_matrix(gp,0,nhstepm,1,nlstate*nlstate);
5728: free_ma3x(gradg,0,nhstepm,1,npar,1,nlstate*nlstate);
5729: free_ma3x(trgradg,0,nhstepm,1,nlstate*nlstate,1,npar);
5730: free_ma3x(p3matm,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
5731: free_ma3x(p3matp,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
5732: printf("\n");
5733: fprintf(ficlog,"\n");
1.218 brouard 5734:
1.126 brouard 5735: free_vector(xm,1,npar);
5736: free_vector(xp,1,npar);
5737: free_matrix(dnewm,1,nlstate*nlstate,1,npar);
5738: free_matrix(doldm,1,nlstate*nlstate,1,nlstate*nlstate);
5739: free_ma3x(varhe,1,nlstate*nlstate,1,nlstate*nlstate,(int) bage, (int)fage);
5740: }
1.218 brouard 5741:
1.126 brouard 5742: /************ Variance ******************/
1.235 brouard 5743: 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 5744: {
5745: /* Variance of health expectancies */
5746: /* double **prevalim(double **prlim, int nlstate, double *xp, double age, double **oldm, double ** savm,double ftolpl);*/
5747: /* double **newm;*/
5748: /* int movingaverage(double ***probs, double bage,double fage, double ***mobaverage, int mobilav)*/
5749:
5750: /* int movingaverage(); */
5751: double **dnewm,**doldm;
5752: double **dnewmp,**doldmp;
5753: int i, j, nhstepm, hstepm, h, nstepm ;
5754: int k;
5755: double *xp;
5756: double **gp, **gm; /* for var eij */
5757: double ***gradg, ***trgradg; /*for var eij */
5758: double **gradgp, **trgradgp; /* for var p point j */
5759: double *gpp, *gmp; /* for var p point j */
5760: double **varppt; /* for var p point j nlstate to nlstate+ndeath */
5761: double ***p3mat;
5762: double age,agelim, hf;
5763: /* double ***mobaverage; */
5764: int theta;
5765: char digit[4];
5766: char digitp[25];
5767:
5768: char fileresprobmorprev[FILENAMELENGTH];
5769:
5770: if(popbased==1){
5771: if(mobilav!=0)
5772: strcpy(digitp,"-POPULBASED-MOBILAV_");
5773: else strcpy(digitp,"-POPULBASED-NOMOBIL_");
5774: }
5775: else
5776: strcpy(digitp,"-STABLBASED_");
1.126 brouard 5777:
1.218 brouard 5778: /* if (mobilav!=0) { */
5779: /* mobaverage= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
5780: /* if (movingaverage(probs, bage, fage, mobaverage,mobilav)!=0){ */
5781: /* fprintf(ficlog," Error in movingaverage mobilav=%d\n",mobilav); */
5782: /* printf(" Error in movingaverage mobilav=%d\n",mobilav); */
5783: /* } */
5784: /* } */
5785:
5786: strcpy(fileresprobmorprev,"PRMORPREV-");
5787: sprintf(digit,"%-d",ij);
5788: /*printf("DIGIT=%s, ij=%d ijr=%-d|\n",digit, ij,ij);*/
5789: strcat(fileresprobmorprev,digit); /* Tvar to be done */
5790: strcat(fileresprobmorprev,digitp); /* Popbased or not, mobilav or not */
5791: strcat(fileresprobmorprev,fileresu);
5792: if((ficresprobmorprev=fopen(fileresprobmorprev,"w"))==NULL) {
5793: printf("Problem with resultfile: %s\n", fileresprobmorprev);
5794: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprobmorprev);
5795: }
5796: printf("Computing total mortality p.j=w1*p1j+w2*p2j+..: result on file '%s' \n",fileresprobmorprev);
5797: fprintf(ficlog,"Computing total mortality p.j=w1*p1j+w2*p2j+..: result on file '%s' \n",fileresprobmorprev);
5798: pstamp(ficresprobmorprev);
5799: 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 5800: fprintf(ficresprobmorprev,"# Selected quantitative variables and dummies");
5801: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
5802: fprintf(ficresprobmorprev," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
5803: }
5804: for(j=1;j<=cptcoveff;j++)
5805: fprintf(ficresprobmorprev,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(ij,j)]);
5806: fprintf(ficresprobmorprev,"\n");
5807:
1.218 brouard 5808: fprintf(ficresprobmorprev,"# Age cov=%-d",ij);
5809: for(j=nlstate+1; j<=(nlstate+ndeath);j++){
5810: fprintf(ficresprobmorprev," p.%-d SE",j);
5811: for(i=1; i<=nlstate;i++)
5812: fprintf(ficresprobmorprev," w%1d p%-d%-d",i,i,j);
5813: }
5814: fprintf(ficresprobmorprev,"\n");
5815:
5816: fprintf(ficgp,"\n# Routine varevsij");
5817: fprintf(ficgp,"\nunset title \n");
5818: /* fprintf(fichtm, "#Local time at start: %s", strstart);*/
5819: 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");
5820: fprintf(fichtm,"\n<br>%s <br>\n",digitp);
5821: /* } */
5822: varppt = matrix(nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
5823: pstamp(ficresvij);
5824: fprintf(ficresvij,"# Variance and covariance of health expectancies e.j \n# (weighted average of eij where weights are ");
5825: if(popbased==1)
5826: 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);
5827: else
5828: fprintf(ficresvij,"the age specific period (stable) prevalences in each health state \n");
5829: fprintf(ficresvij,"# Age");
5830: for(i=1; i<=nlstate;i++)
5831: for(j=1; j<=nlstate;j++)
5832: fprintf(ficresvij," Cov(e.%1d, e.%1d)",i,j);
5833: fprintf(ficresvij,"\n");
5834:
5835: xp=vector(1,npar);
5836: dnewm=matrix(1,nlstate,1,npar);
5837: doldm=matrix(1,nlstate,1,nlstate);
5838: dnewmp= matrix(nlstate+1,nlstate+ndeath,1,npar);
5839: doldmp= matrix(nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
5840:
5841: gradgp=matrix(1,npar,nlstate+1,nlstate+ndeath);
5842: gpp=vector(nlstate+1,nlstate+ndeath);
5843: gmp=vector(nlstate+1,nlstate+ndeath);
5844: trgradgp =matrix(nlstate+1,nlstate+ndeath,1,npar); /* mu or p point j*/
1.126 brouard 5845:
1.218 brouard 5846: if(estepm < stepm){
5847: printf ("Problem %d lower than %d\n",estepm, stepm);
5848: }
5849: else hstepm=estepm;
5850: /* For example we decided to compute the life expectancy with the smallest unit */
5851: /* hstepm beeing the number of stepms, if hstepm=1 the length of hstepm is stepm.
5852: nhstepm is the number of hstepm from age to agelim
5853: nstepm is the number of stepm from age to agelim.
5854: Look at function hpijx to understand why because of memory size limitations,
5855: we decided (b) to get a life expectancy respecting the most precise curvature of the
5856: survival function given by stepm (the optimization length). Unfortunately it
5857: means that if the survival funtion is printed every two years of age and if
5858: you sum them up and add 1 year (area under the trapezoids) you won't get the same
5859: results. So we changed our mind and took the option of the best precision.
5860: */
5861: hstepm=hstepm/stepm; /* Typically in stepm units, if stepm=6 & estepm=24 , = 24/6 months = 4 */
5862: agelim = AGESUP;
5863: for (age=bage; age<=fage; age ++){ /* If stepm=6 months */
5864: nstepm=(int) rint((agelim-age)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
5865: nhstepm = nstepm/hstepm;/* Expressed in hstepm, typically nhstepm=40/4=10 */
5866: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
5867: gradg=ma3x(0,nhstepm,1,npar,1,nlstate);
5868: gp=matrix(0,nhstepm,1,nlstate);
5869: gm=matrix(0,nhstepm,1,nlstate);
5870:
5871:
5872: for(theta=1; theta <=npar; theta++){
5873: for(i=1; i<=npar; i++){ /* Computes gradient x + delta*/
5874: xp[i] = x[i] + (i==theta ?delti[theta]:0);
5875: }
5876:
1.242 brouard 5877: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij, nres);
1.218 brouard 5878:
5879: if (popbased==1) {
5880: if(mobilav ==0){
5881: for(i=1; i<=nlstate;i++)
5882: prlim[i][i]=probs[(int)age][i][ij];
5883: }else{ /* mobilav */
5884: for(i=1; i<=nlstate;i++)
5885: prlim[i][i]=mobaverage[(int)age][i][ij];
5886: }
5887: }
5888:
1.235 brouard 5889: 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 5890: for(j=1; j<= nlstate; j++){
5891: for(h=0; h<=nhstepm; h++){
5892: for(i=1, gp[h][j]=0.;i<=nlstate;i++)
5893: gp[h][j] += prlim[i][i]*p3mat[i][j][h];
5894: }
5895: }
5896: /* Next for computing probability of death (h=1 means
5897: computed over hstepm matrices product = hstepm*stepm months)
5898: as a weighted average of prlim.
5899: */
5900: for(j=nlstate+1;j<=nlstate+ndeath;j++){
5901: for(i=1,gpp[j]=0.; i<= nlstate; i++)
5902: gpp[j] += prlim[i][i]*p3mat[i][j][1];
5903: }
5904: /* end probability of death */
5905:
5906: for(i=1; i<=npar; i++) /* Computes gradient x - delta */
5907: xp[i] = x[i] - (i==theta ?delti[theta]:0);
5908:
1.242 brouard 5909: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp, ij, nres);
1.218 brouard 5910:
5911: if (popbased==1) {
5912: if(mobilav ==0){
5913: for(i=1; i<=nlstate;i++)
5914: prlim[i][i]=probs[(int)age][i][ij];
5915: }else{ /* mobilav */
5916: for(i=1; i<=nlstate;i++)
5917: prlim[i][i]=mobaverage[(int)age][i][ij];
5918: }
5919: }
5920:
1.235 brouard 5921: hpxij(p3mat,nhstepm,age,hstepm,xp,nlstate,stepm,oldm,savm, ij,nres);
1.218 brouard 5922:
5923: for(j=1; j<= nlstate; j++){ /* Sum of wi * eij = e.j */
5924: for(h=0; h<=nhstepm; h++){
5925: for(i=1, gm[h][j]=0.;i<=nlstate;i++)
5926: gm[h][j] += prlim[i][i]*p3mat[i][j][h];
5927: }
5928: }
5929: /* This for computing probability of death (h=1 means
5930: computed over hstepm matrices product = hstepm*stepm months)
5931: as a weighted average of prlim.
5932: */
5933: for(j=nlstate+1;j<=nlstate+ndeath;j++){
5934: for(i=1,gmp[j]=0.; i<= nlstate; i++)
5935: gmp[j] += prlim[i][i]*p3mat[i][j][1];
5936: }
5937: /* end probability of death */
5938:
5939: for(j=1; j<= nlstate; j++) /* vareij */
5940: for(h=0; h<=nhstepm; h++){
5941: gradg[h][theta][j]= (gp[h][j]-gm[h][j])/2./delti[theta];
5942: }
5943:
5944: for(j=nlstate+1; j<= nlstate+ndeath; j++){ /* var mu */
5945: gradgp[theta][j]= (gpp[j]-gmp[j])/2./delti[theta];
5946: }
5947:
5948: } /* End theta */
5949:
5950: trgradg =ma3x(0,nhstepm,1,nlstate,1,npar); /* veij */
5951:
5952: for(h=0; h<=nhstepm; h++) /* veij */
5953: for(j=1; j<=nlstate;j++)
5954: for(theta=1; theta <=npar; theta++)
5955: trgradg[h][j][theta]=gradg[h][theta][j];
5956:
5957: for(j=nlstate+1; j<=nlstate+ndeath;j++) /* mu */
5958: for(theta=1; theta <=npar; theta++)
5959: trgradgp[j][theta]=gradgp[theta][j];
5960:
5961:
5962: hf=hstepm*stepm/YEARM; /* Duration of hstepm expressed in year unit. */
5963: for(i=1;i<=nlstate;i++)
5964: for(j=1;j<=nlstate;j++)
5965: vareij[i][j][(int)age] =0.;
5966:
5967: for(h=0;h<=nhstepm;h++){
5968: for(k=0;k<=nhstepm;k++){
5969: matprod2(dnewm,trgradg[h],1,nlstate,1,npar,1,npar,matcov);
5970: matprod2(doldm,dnewm,1,nlstate,1,npar,1,nlstate,gradg[k]);
5971: for(i=1;i<=nlstate;i++)
5972: for(j=1;j<=nlstate;j++)
5973: vareij[i][j][(int)age] += doldm[i][j]*hf*hf;
5974: }
5975: }
5976:
5977: /* pptj */
5978: matprod2(dnewmp,trgradgp,nlstate+1,nlstate+ndeath,1,npar,1,npar,matcov);
5979: matprod2(doldmp,dnewmp,nlstate+1,nlstate+ndeath,1,npar,nlstate+1,nlstate+ndeath,gradgp);
5980: for(j=nlstate+1;j<=nlstate+ndeath;j++)
5981: for(i=nlstate+1;i<=nlstate+ndeath;i++)
5982: varppt[j][i]=doldmp[j][i];
5983: /* end ppptj */
5984: /* x centered again */
5985:
1.242 brouard 5986: prevalim(prlim,nlstate,x,age,oldm,savm,ftolpl,ncvyearp,ij, nres);
1.218 brouard 5987:
5988: if (popbased==1) {
5989: if(mobilav ==0){
5990: for(i=1; i<=nlstate;i++)
5991: prlim[i][i]=probs[(int)age][i][ij];
5992: }else{ /* mobilav */
5993: for(i=1; i<=nlstate;i++)
5994: prlim[i][i]=mobaverage[(int)age][i][ij];
5995: }
5996: }
5997:
5998: /* This for computing probability of death (h=1 means
5999: computed over hstepm (estepm) matrices product = hstepm*stepm months)
6000: as a weighted average of prlim.
6001: */
1.235 brouard 6002: hpxij(p3mat,nhstepm,age,hstepm,x,nlstate,stepm,oldm,savm, ij, nres);
1.218 brouard 6003: for(j=nlstate+1;j<=nlstate+ndeath;j++){
6004: for(i=1,gmp[j]=0.;i<= nlstate; i++)
6005: gmp[j] += prlim[i][i]*p3mat[i][j][1];
6006: }
6007: /* end probability of death */
6008:
6009: fprintf(ficresprobmorprev,"%3d %d ",(int) age, ij);
6010: for(j=nlstate+1; j<=(nlstate+ndeath);j++){
6011: fprintf(ficresprobmorprev," %11.3e %11.3e",gmp[j], sqrt(varppt[j][j]));
6012: for(i=1; i<=nlstate;i++){
6013: fprintf(ficresprobmorprev," %11.3e %11.3e ",prlim[i][i],p3mat[i][j][1]);
6014: }
6015: }
6016: fprintf(ficresprobmorprev,"\n");
6017:
6018: fprintf(ficresvij,"%.0f ",age );
6019: for(i=1; i<=nlstate;i++)
6020: for(j=1; j<=nlstate;j++){
6021: fprintf(ficresvij," %.4f", vareij[i][j][(int)age]);
6022: }
6023: fprintf(ficresvij,"\n");
6024: free_matrix(gp,0,nhstepm,1,nlstate);
6025: free_matrix(gm,0,nhstepm,1,nlstate);
6026: free_ma3x(gradg,0,nhstepm,1,npar,1,nlstate);
6027: free_ma3x(trgradg,0,nhstepm,1,nlstate,1,npar);
6028: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
6029: } /* End age */
6030: free_vector(gpp,nlstate+1,nlstate+ndeath);
6031: free_vector(gmp,nlstate+1,nlstate+ndeath);
6032: free_matrix(gradgp,1,npar,nlstate+1,nlstate+ndeath);
6033: free_matrix(trgradgp,nlstate+1,nlstate+ndeath,1,npar); /* mu or p point j*/
6034: /* fprintf(ficgp,"\nunset parametric;unset label; set ter png small size 320, 240"); */
6035: fprintf(ficgp,"\nunset parametric;unset label; set ter svg size 640, 480");
6036: /* for(j=nlstate+1; j<= nlstate+ndeath; j++){ *//* Only the first actually */
6037: fprintf(ficgp,"\n set log y; unset log x;set xlabel \"Age\"; set ylabel \"Force of mortality (year-1)\";");
6038: fprintf(ficgp,"\nset out \"%s%s.svg\";",subdirf3(optionfilefiname,"VARMUPTJGR-",digitp),digit);
6039: /* fprintf(ficgp,"\n plot \"%s\" u 1:($3*%6.3f) not w l 1 ",fileresprobmorprev,YEARM/estepm); */
6040: /* fprintf(ficgp,"\n replot \"%s\" u 1:(($3+1.96*$4)*%6.3f) t \"95\%% interval\" w l 2 ",fileresprobmorprev,YEARM/estepm); */
6041: /* fprintf(ficgp,"\n replot \"%s\" u 1:(($3-1.96*$4)*%6.3f) not w l 2 ",fileresprobmorprev,YEARM/estepm); */
6042: fprintf(ficgp,"\n plot \"%s\" u 1:($3) not w l lt 1 ",subdirf(fileresprobmorprev));
6043: fprintf(ficgp,"\n replot \"%s\" u 1:(($3+1.96*$4)) t \"95%% interval\" w l lt 2 ",subdirf(fileresprobmorprev));
6044: fprintf(ficgp,"\n replot \"%s\" u 1:(($3-1.96*$4)) not w l lt 2 ",subdirf(fileresprobmorprev));
6045: fprintf(fichtm,"\n<br> File (multiple files are possible if covariates are present): <A href=\"%s\">%s</a>\n",subdirf(fileresprobmorprev),subdirf(fileresprobmorprev));
6046: 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);
6047: /* 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 6048: */
1.218 brouard 6049: /* fprintf(ficgp,"\nset out \"varmuptjgr%s%s%s.svg\";replot;",digitp,optionfilefiname,digit); */
6050: fprintf(ficgp,"\nset out;\nset out \"%s%s.svg\";replot;set out;\n",subdirf3(optionfilefiname,"VARMUPTJGR-",digitp),digit);
1.126 brouard 6051:
1.218 brouard 6052: free_vector(xp,1,npar);
6053: free_matrix(doldm,1,nlstate,1,nlstate);
6054: free_matrix(dnewm,1,nlstate,1,npar);
6055: free_matrix(doldmp,nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
6056: free_matrix(dnewmp,nlstate+1,nlstate+ndeath,1,npar);
6057: free_matrix(varppt,nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
6058: /* if (mobilav!=0) free_ma3x(mobaverage,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
6059: fclose(ficresprobmorprev);
6060: fflush(ficgp);
6061: fflush(fichtm);
6062: } /* end varevsij */
1.126 brouard 6063:
6064: /************ Variance of prevlim ******************/
1.269 ! brouard 6065: 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 6066: {
1.205 brouard 6067: /* Variance of prevalence limit for each state ij using current parameters x[] and estimates of neighbourhood give by delti*/
1.126 brouard 6068: /* double **prevalim(double **prlim, int nlstate, double *xp, double age, double **oldm, double **savm,double ftolpl);*/
1.164 brouard 6069:
1.268 brouard 6070: double **dnewmpar,**doldm;
1.126 brouard 6071: int i, j, nhstepm, hstepm;
6072: double *xp;
6073: double *gp, *gm;
6074: double **gradg, **trgradg;
1.208 brouard 6075: double **mgm, **mgp;
1.126 brouard 6076: double age,agelim;
6077: int theta;
6078:
6079: pstamp(ficresvpl);
6080: fprintf(ficresvpl,"# Standard deviation of period (stable) prevalences \n");
1.241 brouard 6081: fprintf(ficresvpl,"# Age ");
6082: if(nresult >=1)
6083: fprintf(ficresvpl," Result# ");
1.126 brouard 6084: for(i=1; i<=nlstate;i++)
6085: fprintf(ficresvpl," %1d-%1d",i,i);
6086: fprintf(ficresvpl,"\n");
6087:
6088: xp=vector(1,npar);
1.268 brouard 6089: dnewmpar=matrix(1,nlstate,1,npar);
1.126 brouard 6090: doldm=matrix(1,nlstate,1,nlstate);
6091:
6092: hstepm=1*YEARM; /* Every year of age */
6093: hstepm=hstepm/stepm; /* Typically in stepm units, if j= 2 years, = 2/6 months = 4 */
6094: agelim = AGESUP;
6095: for (age=bage; age<=fage; age ++){ /* If stepm=6 months */
6096: nhstepm=(int) rint((agelim-age)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
6097: if (stepm >= YEARM) hstepm=1;
6098: nhstepm = nhstepm/hstepm; /* Typically 40/4=10 */
6099: gradg=matrix(1,npar,1,nlstate);
1.208 brouard 6100: mgp=matrix(1,npar,1,nlstate);
6101: mgm=matrix(1,npar,1,nlstate);
1.126 brouard 6102: gp=vector(1,nlstate);
6103: gm=vector(1,nlstate);
6104:
6105: for(theta=1; theta <=npar; theta++){
6106: for(i=1; i<=npar; i++){ /* Computes gradient */
6107: xp[i] = x[i] + (i==theta ?delti[theta]:0);
6108: }
1.209 brouard 6109: if((int)age==79 ||(int)age== 80 ||(int)age== 81 )
1.235 brouard 6110: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres);
1.209 brouard 6111: else
1.235 brouard 6112: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres);
1.208 brouard 6113: for(i=1;i<=nlstate;i++){
1.126 brouard 6114: gp[i] = prlim[i][i];
1.208 brouard 6115: mgp[theta][i] = prlim[i][i];
6116: }
1.126 brouard 6117: for(i=1; i<=npar; i++) /* Computes gradient */
6118: xp[i] = x[i] - (i==theta ?delti[theta]:0);
1.209 brouard 6119: if((int)age==79 ||(int)age== 80 ||(int)age== 81 )
1.235 brouard 6120: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres);
1.209 brouard 6121: else
1.235 brouard 6122: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres);
1.208 brouard 6123: for(i=1;i<=nlstate;i++){
1.126 brouard 6124: gm[i] = prlim[i][i];
1.208 brouard 6125: mgm[theta][i] = prlim[i][i];
6126: }
1.126 brouard 6127: for(i=1;i<=nlstate;i++)
6128: gradg[theta][i]= (gp[i]-gm[i])/2./delti[theta];
1.209 brouard 6129: /* gradg[theta][2]= -gradg[theta][1]; */ /* For testing if nlstate=2 */
1.126 brouard 6130: } /* End theta */
6131:
6132: trgradg =matrix(1,nlstate,1,npar);
6133:
6134: for(j=1; j<=nlstate;j++)
6135: for(theta=1; theta <=npar; theta++)
6136: trgradg[j][theta]=gradg[theta][j];
1.209 brouard 6137: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
6138: /* printf("\nmgm mgp %d ",(int)age); */
6139: /* for(j=1; j<=nlstate;j++){ */
6140: /* printf(" %d ",j); */
6141: /* for(theta=1; theta <=npar; theta++) */
6142: /* printf(" %d %lf %lf",theta,mgm[theta][j],mgp[theta][j]); */
6143: /* printf("\n "); */
6144: /* } */
6145: /* } */
6146: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
6147: /* printf("\n gradg %d ",(int)age); */
6148: /* for(j=1; j<=nlstate;j++){ */
6149: /* printf("%d ",j); */
6150: /* for(theta=1; theta <=npar; theta++) */
6151: /* printf("%d %lf ",theta,gradg[theta][j]); */
6152: /* printf("\n "); */
6153: /* } */
6154: /* } */
1.126 brouard 6155:
6156: for(i=1;i<=nlstate;i++)
6157: varpl[i][(int)age] =0.;
1.209 brouard 6158: if((int)age==79 ||(int)age== 80 ||(int)age== 81){
1.268 brouard 6159: matprod2(dnewmpar,trgradg,1,nlstate,1,npar,1,npar,matcov);
6160: matprod2(doldm,dnewmpar,1,nlstate,1,npar,1,nlstate,gradg);
1.205 brouard 6161: }else{
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: }
1.126 brouard 6165: for(i=1;i<=nlstate;i++)
6166: varpl[i][(int)age] = doldm[i][i]; /* Covariances are useless */
6167:
6168: fprintf(ficresvpl,"%.0f ",age );
1.241 brouard 6169: if(nresult >=1)
6170: fprintf(ficresvpl,"%d ",nres );
1.126 brouard 6171: for(i=1; i<=nlstate;i++)
6172: fprintf(ficresvpl," %.5f (%.5f)",prlim[i][i],sqrt(varpl[i][(int)age]));
6173: fprintf(ficresvpl,"\n");
6174: free_vector(gp,1,nlstate);
6175: free_vector(gm,1,nlstate);
1.208 brouard 6176: free_matrix(mgm,1,npar,1,nlstate);
6177: free_matrix(mgp,1,npar,1,nlstate);
1.126 brouard 6178: free_matrix(gradg,1,npar,1,nlstate);
6179: free_matrix(trgradg,1,nlstate,1,npar);
6180: } /* End age */
6181:
6182: free_vector(xp,1,npar);
6183: free_matrix(doldm,1,nlstate,1,npar);
1.268 brouard 6184: free_matrix(dnewmpar,1,nlstate,1,nlstate);
6185:
6186: }
6187:
6188:
6189: /************ Variance of backprevalence limit ******************/
1.269 ! brouard 6190: 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 6191: {
6192: /* Variance of backward prevalence limit for each state ij using current parameters x[] and estimates of neighbourhood give by delti*/
6193: /* double **prevalim(double **prlim, int nlstate, double *xp, double age, double **oldm, double **savm,double ftolpl);*/
6194:
6195: double **dnewmpar,**doldm;
6196: int i, j, nhstepm, hstepm;
6197: double *xp;
6198: double *gp, *gm;
6199: double **gradg, **trgradg;
6200: double **mgm, **mgp;
6201: double age,agelim;
6202: int theta;
6203:
6204: pstamp(ficresvbl);
6205: fprintf(ficresvbl,"# Standard deviation of back (stable) prevalences \n");
6206: fprintf(ficresvbl,"# Age ");
6207: if(nresult >=1)
6208: fprintf(ficresvbl," Result# ");
6209: for(i=1; i<=nlstate;i++)
6210: fprintf(ficresvbl," %1d-%1d",i,i);
6211: fprintf(ficresvbl,"\n");
6212:
6213: xp=vector(1,npar);
6214: dnewmpar=matrix(1,nlstate,1,npar);
6215: doldm=matrix(1,nlstate,1,nlstate);
6216:
6217: hstepm=1*YEARM; /* Every year of age */
6218: hstepm=hstepm/stepm; /* Typically in stepm units, if j= 2 years, = 2/6 months = 4 */
6219: agelim = AGEINF;
6220: for (age=fage; age>=bage; age --){ /* If stepm=6 months */
6221: nhstepm=(int) rint((age-agelim)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
6222: if (stepm >= YEARM) hstepm=1;
6223: nhstepm = nhstepm/hstepm; /* Typically 40/4=10 */
6224: gradg=matrix(1,npar,1,nlstate);
6225: mgp=matrix(1,npar,1,nlstate);
6226: mgm=matrix(1,npar,1,nlstate);
6227: gp=vector(1,nlstate);
6228: gm=vector(1,nlstate);
6229:
6230: for(theta=1; theta <=npar; theta++){
6231: for(i=1; i<=npar; i++){ /* Computes gradient */
6232: xp[i] = x[i] + (i==theta ?delti[theta]:0);
6233: }
6234: if(mobilavproj > 0 )
6235: bprevalim(bprlim, mobaverage,nlstate,xp,age,ftolpl,ncvyearp,ij,nres);
6236: else
6237: bprevalim(bprlim, mobaverage,nlstate,xp,age,ftolpl,ncvyearp,ij,nres);
6238: for(i=1;i<=nlstate;i++){
6239: gp[i] = bprlim[i][i];
6240: mgp[theta][i] = bprlim[i][i];
6241: }
6242: for(i=1; i<=npar; i++) /* Computes gradient */
6243: xp[i] = x[i] - (i==theta ?delti[theta]:0);
6244: if(mobilavproj > 0 )
6245: bprevalim(bprlim, mobaverage,nlstate,xp,age,ftolpl,ncvyearp,ij,nres);
6246: else
6247: bprevalim(bprlim, mobaverage,nlstate,xp,age,ftolpl,ncvyearp,ij,nres);
6248: for(i=1;i<=nlstate;i++){
6249: gm[i] = bprlim[i][i];
6250: mgm[theta][i] = bprlim[i][i];
6251: }
6252: for(i=1;i<=nlstate;i++)
6253: gradg[theta][i]= (gp[i]-gm[i])/2./delti[theta];
6254: /* gradg[theta][2]= -gradg[theta][1]; */ /* For testing if nlstate=2 */
6255: } /* End theta */
6256:
6257: trgradg =matrix(1,nlstate,1,npar);
6258:
6259: for(j=1; j<=nlstate;j++)
6260: for(theta=1; theta <=npar; theta++)
6261: trgradg[j][theta]=gradg[theta][j];
6262: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
6263: /* printf("\nmgm mgp %d ",(int)age); */
6264: /* for(j=1; j<=nlstate;j++){ */
6265: /* printf(" %d ",j); */
6266: /* for(theta=1; theta <=npar; theta++) */
6267: /* printf(" %d %lf %lf",theta,mgm[theta][j],mgp[theta][j]); */
6268: /* printf("\n "); */
6269: /* } */
6270: /* } */
6271: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
6272: /* printf("\n gradg %d ",(int)age); */
6273: /* for(j=1; j<=nlstate;j++){ */
6274: /* printf("%d ",j); */
6275: /* for(theta=1; theta <=npar; theta++) */
6276: /* printf("%d %lf ",theta,gradg[theta][j]); */
6277: /* printf("\n "); */
6278: /* } */
6279: /* } */
6280:
6281: for(i=1;i<=nlstate;i++)
6282: varbpl[i][(int)age] =0.;
6283: if((int)age==79 ||(int)age== 80 ||(int)age== 81){
6284: matprod2(dnewmpar,trgradg,1,nlstate,1,npar,1,npar,matcov);
6285: matprod2(doldm,dnewmpar,1,nlstate,1,npar,1,nlstate,gradg);
6286: }else{
6287: matprod2(dnewmpar,trgradg,1,nlstate,1,npar,1,npar,matcov);
6288: matprod2(doldm,dnewmpar,1,nlstate,1,npar,1,nlstate,gradg);
6289: }
6290: for(i=1;i<=nlstate;i++)
6291: varbpl[i][(int)age] = doldm[i][i]; /* Covariances are useless */
6292:
6293: fprintf(ficresvbl,"%.0f ",age );
6294: if(nresult >=1)
6295: fprintf(ficresvbl,"%d ",nres );
6296: for(i=1; i<=nlstate;i++)
6297: fprintf(ficresvbl," %.5f (%.5f)",bprlim[i][i],sqrt(varbpl[i][(int)age]));
6298: fprintf(ficresvbl,"\n");
6299: free_vector(gp,1,nlstate);
6300: free_vector(gm,1,nlstate);
6301: free_matrix(mgm,1,npar,1,nlstate);
6302: free_matrix(mgp,1,npar,1,nlstate);
6303: free_matrix(gradg,1,npar,1,nlstate);
6304: free_matrix(trgradg,1,nlstate,1,npar);
6305: } /* End age */
6306:
6307: free_vector(xp,1,npar);
6308: free_matrix(doldm,1,nlstate,1,npar);
6309: free_matrix(dnewmpar,1,nlstate,1,nlstate);
1.126 brouard 6310:
6311: }
6312:
6313: /************ Variance of one-step probabilities ******************/
6314: 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 6315: {
6316: int i, j=0, k1, l1, tj;
6317: int k2, l2, j1, z1;
6318: int k=0, l;
6319: int first=1, first1, first2;
6320: double cv12, mu1, mu2, lc1, lc2, v12, v21, v11, v22,v1,v2, c12, tnalp;
6321: double **dnewm,**doldm;
6322: double *xp;
6323: double *gp, *gm;
6324: double **gradg, **trgradg;
6325: double **mu;
6326: double age, cov[NCOVMAX+1];
6327: double std=2.0; /* Number of standard deviation wide of confidence ellipsoids */
6328: int theta;
6329: char fileresprob[FILENAMELENGTH];
6330: char fileresprobcov[FILENAMELENGTH];
6331: char fileresprobcor[FILENAMELENGTH];
6332: double ***varpij;
6333:
6334: strcpy(fileresprob,"PROB_");
6335: strcat(fileresprob,fileres);
6336: if((ficresprob=fopen(fileresprob,"w"))==NULL) {
6337: printf("Problem with resultfile: %s\n", fileresprob);
6338: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprob);
6339: }
6340: strcpy(fileresprobcov,"PROBCOV_");
6341: strcat(fileresprobcov,fileresu);
6342: if((ficresprobcov=fopen(fileresprobcov,"w"))==NULL) {
6343: printf("Problem with resultfile: %s\n", fileresprobcov);
6344: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprobcov);
6345: }
6346: strcpy(fileresprobcor,"PROBCOR_");
6347: strcat(fileresprobcor,fileresu);
6348: if((ficresprobcor=fopen(fileresprobcor,"w"))==NULL) {
6349: printf("Problem with resultfile: %s\n", fileresprobcor);
6350: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprobcor);
6351: }
6352: printf("Computing standard deviation of one-step probabilities: result on file '%s' \n",fileresprob);
6353: fprintf(ficlog,"Computing standard deviation of one-step probabilities: result on file '%s' \n",fileresprob);
6354: printf("Computing matrix of variance covariance of one-step probabilities: result on file '%s' \n",fileresprobcov);
6355: fprintf(ficlog,"Computing matrix of variance covariance of one-step probabilities: result on file '%s' \n",fileresprobcov);
6356: printf("and correlation matrix of one-step probabilities: result on file '%s' \n",fileresprobcor);
6357: fprintf(ficlog,"and correlation matrix of one-step probabilities: result on file '%s' \n",fileresprobcor);
6358: pstamp(ficresprob);
6359: fprintf(ficresprob,"#One-step probabilities and stand. devi in ()\n");
6360: fprintf(ficresprob,"# Age");
6361: pstamp(ficresprobcov);
6362: fprintf(ficresprobcov,"#One-step probabilities and covariance matrix\n");
6363: fprintf(ficresprobcov,"# Age");
6364: pstamp(ficresprobcor);
6365: fprintf(ficresprobcor,"#One-step probabilities and correlation matrix\n");
6366: fprintf(ficresprobcor,"# Age");
1.126 brouard 6367:
6368:
1.222 brouard 6369: for(i=1; i<=nlstate;i++)
6370: for(j=1; j<=(nlstate+ndeath);j++){
6371: fprintf(ficresprob," p%1d-%1d (SE)",i,j);
6372: fprintf(ficresprobcov," p%1d-%1d ",i,j);
6373: fprintf(ficresprobcor," p%1d-%1d ",i,j);
6374: }
6375: /* fprintf(ficresprob,"\n");
6376: fprintf(ficresprobcov,"\n");
6377: fprintf(ficresprobcor,"\n");
6378: */
6379: xp=vector(1,npar);
6380: dnewm=matrix(1,(nlstate)*(nlstate+ndeath),1,npar);
6381: doldm=matrix(1,(nlstate)*(nlstate+ndeath),1,(nlstate)*(nlstate+ndeath));
6382: mu=matrix(1,(nlstate)*(nlstate+ndeath), (int) bage, (int)fage);
6383: varpij=ma3x(1,nlstate*(nlstate+ndeath),1,nlstate*(nlstate+ndeath),(int) bage, (int) fage);
6384: first=1;
6385: fprintf(ficgp,"\n# Routine varprob");
6386: fprintf(fichtm,"\n<li><h4> Computing and drawing one step probabilities with their confidence intervals</h4></li>\n");
6387: fprintf(fichtm,"\n");
6388:
1.266 brouard 6389: 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 6390: 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);
6391: fprintf(fichtmcov,"\nEllipsoids of confidence centered on point (p<inf>ij</inf>, p<inf>kl</inf>) are estimated \
1.126 brouard 6392: and drawn. It helps understanding how is the covariance between two incidences.\
6393: They are expressed in year<sup>-1</sup> in order to be less dependent of stepm.<br>\n");
1.222 brouard 6394: 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 6395: It can be understood this way: if pij and pkl where uncorrelated the (2x2) matrix of covariance \
6396: would have been (1/(var pij), 0 , 0, 1/(var pkl)), and the confidence interval would be 2 \
6397: standard deviations wide on each axis. <br>\
6398: Now, if both incidences are correlated (usual case) we diagonalised the inverse of the covariance matrix\
6399: and made the appropriate rotation to look at the uncorrelated principal directions.<br>\
6400: To be simple, these graphs help to understand the significativity of each parameter in relation to a second other one.<br> \n");
6401:
1.222 brouard 6402: cov[1]=1;
6403: /* tj=cptcoveff; */
1.225 brouard 6404: tj = (int) pow(2,cptcoveff);
1.222 brouard 6405: if (cptcovn<1) {tj=1;ncodemax[1]=1;}
6406: j1=0;
1.224 brouard 6407: for(j1=1; j1<=tj;j1++){ /* For each valid combination of covariates or only once*/
1.222 brouard 6408: if (cptcovn>0) {
6409: fprintf(ficresprob, "\n#********** Variable ");
1.225 brouard 6410: for (z1=1; z1<=cptcoveff; z1++) fprintf(ficresprob, "V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
1.222 brouard 6411: fprintf(ficresprob, "**********\n#\n");
6412: fprintf(ficresprobcov, "\n#********** Variable ");
1.225 brouard 6413: for (z1=1; z1<=cptcoveff; z1++) fprintf(ficresprobcov, "V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
1.222 brouard 6414: fprintf(ficresprobcov, "**********\n#\n");
1.220 brouard 6415:
1.222 brouard 6416: fprintf(ficgp, "\n#********** Variable ");
1.225 brouard 6417: for (z1=1; z1<=cptcoveff; z1++) fprintf(ficgp, " V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
1.222 brouard 6418: fprintf(ficgp, "**********\n#\n");
1.220 brouard 6419:
6420:
1.222 brouard 6421: fprintf(fichtmcov, "\n<hr size=\"2\" color=\"#EC5E5E\">********** Variable ");
1.225 brouard 6422: for (z1=1; z1<=cptcoveff; z1++) fprintf(fichtm, "V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
1.222 brouard 6423: fprintf(fichtmcov, "**********\n<hr size=\"2\" color=\"#EC5E5E\">");
1.220 brouard 6424:
1.222 brouard 6425: fprintf(ficresprobcor, "\n#********** Variable ");
1.225 brouard 6426: for (z1=1; z1<=cptcoveff; z1++) fprintf(ficresprobcor, "V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
1.222 brouard 6427: fprintf(ficresprobcor, "**********\n#");
6428: if(invalidvarcomb[j1]){
6429: fprintf(ficgp,"\n#Combination (%d) ignored because no cases \n",j1);
6430: fprintf(fichtmcov,"\n<h3>Combination (%d) ignored because no cases </h3>\n",j1);
6431: continue;
6432: }
6433: }
6434: gradg=matrix(1,npar,1,(nlstate)*(nlstate+ndeath));
6435: trgradg=matrix(1,(nlstate)*(nlstate+ndeath),1,npar);
6436: gp=vector(1,(nlstate)*(nlstate+ndeath));
6437: gm=vector(1,(nlstate)*(nlstate+ndeath));
6438: for (age=bage; age<=fage; age ++){
6439: cov[2]=age;
6440: if(nagesqr==1)
6441: cov[3]= age*age;
6442: for (k=1; k<=cptcovn;k++) {
6443: cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(j1,k)];
6444: /*cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(j1,Tvar[k])];*//* j1 1 2 3 4
6445: * 1 1 1 1 1
6446: * 2 2 1 1 1
6447: * 3 1 2 1 1
6448: */
6449: /* nbcode[1][1]=0 nbcode[1][2]=1;*/
6450: }
6451: /* for (k=1; k<=cptcovage;k++) cov[2+Tage[k]]=cov[2+Tage[k]]*cov[2]; */
6452: for (k=1; k<=cptcovage;k++) cov[2+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2];
6453: for (k=1; k<=cptcovprod;k++)
6454: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)]*nbcode[Tvard[k][2]][codtabm(ij,k)];
1.220 brouard 6455:
6456:
1.222 brouard 6457: for(theta=1; theta <=npar; theta++){
6458: for(i=1; i<=npar; i++)
6459: xp[i] = x[i] + (i==theta ?delti[theta]:(double)0);
1.220 brouard 6460:
1.222 brouard 6461: pmij(pmmij,cov,ncovmodel,xp,nlstate);
1.220 brouard 6462:
1.222 brouard 6463: k=0;
6464: for(i=1; i<= (nlstate); i++){
6465: for(j=1; j<=(nlstate+ndeath);j++){
6466: k=k+1;
6467: gp[k]=pmmij[i][j];
6468: }
6469: }
1.220 brouard 6470:
1.222 brouard 6471: for(i=1; i<=npar; i++)
6472: xp[i] = x[i] - (i==theta ?delti[theta]:(double)0);
1.220 brouard 6473:
1.222 brouard 6474: pmij(pmmij,cov,ncovmodel,xp,nlstate);
6475: k=0;
6476: for(i=1; i<=(nlstate); i++){
6477: for(j=1; j<=(nlstate+ndeath);j++){
6478: k=k+1;
6479: gm[k]=pmmij[i][j];
6480: }
6481: }
1.220 brouard 6482:
1.222 brouard 6483: for(i=1; i<= (nlstate)*(nlstate+ndeath); i++)
6484: gradg[theta][i]=(gp[i]-gm[i])/(double)2./delti[theta];
6485: }
1.126 brouard 6486:
1.222 brouard 6487: for(j=1; j<=(nlstate)*(nlstate+ndeath);j++)
6488: for(theta=1; theta <=npar; theta++)
6489: trgradg[j][theta]=gradg[theta][j];
1.220 brouard 6490:
1.222 brouard 6491: matprod2(dnewm,trgradg,1,(nlstate)*(nlstate+ndeath),1,npar,1,npar,matcov);
6492: matprod2(doldm,dnewm,1,(nlstate)*(nlstate+ndeath),1,npar,1,(nlstate)*(nlstate+ndeath),gradg);
1.220 brouard 6493:
1.222 brouard 6494: pmij(pmmij,cov,ncovmodel,x,nlstate);
1.220 brouard 6495:
1.222 brouard 6496: k=0;
6497: for(i=1; i<=(nlstate); i++){
6498: for(j=1; j<=(nlstate+ndeath);j++){
6499: k=k+1;
6500: mu[k][(int) age]=pmmij[i][j];
6501: }
6502: }
6503: for(i=1;i<=(nlstate)*(nlstate+ndeath);i++)
6504: for(j=1;j<=(nlstate)*(nlstate+ndeath);j++)
6505: varpij[i][j][(int)age] = doldm[i][j];
1.220 brouard 6506:
1.222 brouard 6507: /*printf("\n%d ",(int)age);
6508: for (i=1; i<=(nlstate)*(nlstate+ndeath);i++){
6509: printf("%e [%e ;%e] ",gm[i],gm[i]-2*sqrt(doldm[i][i]),gm[i]+2*sqrt(doldm[i][i]));
6510: fprintf(ficlog,"%e [%e ;%e] ",gm[i],gm[i]-2*sqrt(doldm[i][i]),gm[i]+2*sqrt(doldm[i][i]));
6511: }*/
1.220 brouard 6512:
1.222 brouard 6513: fprintf(ficresprob,"\n%d ",(int)age);
6514: fprintf(ficresprobcov,"\n%d ",(int)age);
6515: fprintf(ficresprobcor,"\n%d ",(int)age);
1.220 brouard 6516:
1.222 brouard 6517: for (i=1; i<=(nlstate)*(nlstate+ndeath);i++)
6518: fprintf(ficresprob,"%11.3e (%11.3e) ",mu[i][(int) age],sqrt(varpij[i][i][(int)age]));
6519: for (i=1; i<=(nlstate)*(nlstate+ndeath);i++){
6520: fprintf(ficresprobcov,"%11.3e ",mu[i][(int) age]);
6521: fprintf(ficresprobcor,"%11.3e ",mu[i][(int) age]);
6522: }
6523: i=0;
6524: for (k=1; k<=(nlstate);k++){
6525: for (l=1; l<=(nlstate+ndeath);l++){
6526: i++;
6527: fprintf(ficresprobcov,"\n%d %d-%d",(int)age,k,l);
6528: fprintf(ficresprobcor,"\n%d %d-%d",(int)age,k,l);
6529: for (j=1; j<=i;j++){
6530: /* printf(" k=%d l=%d i=%d j=%d\n",k,l,i,j);fflush(stdout); */
6531: fprintf(ficresprobcov," %11.3e",varpij[i][j][(int)age]);
6532: fprintf(ficresprobcor," %11.3e",varpij[i][j][(int) age]/sqrt(varpij[i][i][(int) age])/sqrt(varpij[j][j][(int)age]));
6533: }
6534: }
6535: }/* end of loop for state */
6536: } /* end of loop for age */
6537: free_vector(gp,1,(nlstate+ndeath)*(nlstate+ndeath));
6538: free_vector(gm,1,(nlstate+ndeath)*(nlstate+ndeath));
6539: free_matrix(trgradg,1,(nlstate+ndeath)*(nlstate+ndeath),1,npar);
6540: free_matrix(gradg,1,(nlstate+ndeath)*(nlstate+ndeath),1,npar);
6541:
6542: /* Confidence intervalle of pij */
6543: /*
6544: fprintf(ficgp,"\nunset parametric;unset label");
6545: fprintf(ficgp,"\nset log y;unset log x; set xlabel \"Age\";set ylabel \"probability (year-1)\"");
6546: fprintf(ficgp,"\nset ter png small\nset size 0.65,0.65");
6547: 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);
6548: fprintf(fichtm,"\n<br><img src=\"pijgr%s.png\"> ",optionfilefiname);
6549: fprintf(ficgp,"\nset out \"pijgr%s.png\"",optionfilefiname);
6550: fprintf(ficgp,"\nplot \"%s\" every :::%d::%d u 1:2 \"\%%lf",k1,k2,xfilevarprob);
6551: */
6552:
6553: /* Drawing ellipsoids of confidence of two variables p(k1-l1,k2-l2)*/
6554: first1=1;first2=2;
6555: for (k2=1; k2<=(nlstate);k2++){
6556: for (l2=1; l2<=(nlstate+ndeath);l2++){
6557: if(l2==k2) continue;
6558: j=(k2-1)*(nlstate+ndeath)+l2;
6559: for (k1=1; k1<=(nlstate);k1++){
6560: for (l1=1; l1<=(nlstate+ndeath);l1++){
6561: if(l1==k1) continue;
6562: i=(k1-1)*(nlstate+ndeath)+l1;
6563: if(i<=j) continue;
6564: for (age=bage; age<=fage; age ++){
6565: if ((int)age %5==0){
6566: v1=varpij[i][i][(int)age]/stepm*YEARM/stepm*YEARM;
6567: v2=varpij[j][j][(int)age]/stepm*YEARM/stepm*YEARM;
6568: cv12=varpij[i][j][(int)age]/stepm*YEARM/stepm*YEARM;
6569: mu1=mu[i][(int) age]/stepm*YEARM ;
6570: mu2=mu[j][(int) age]/stepm*YEARM;
6571: c12=cv12/sqrt(v1*v2);
6572: /* Computing eigen value of matrix of covariance */
6573: lc1=((v1+v2)+sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
6574: lc2=((v1+v2)-sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
6575: if ((lc2 <0) || (lc1 <0) ){
6576: if(first2==1){
6577: first1=0;
6578: 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);
6579: }
6580: 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);
6581: /* lc1=fabs(lc1); */ /* If we want to have them positive */
6582: /* lc2=fabs(lc2); */
6583: }
1.220 brouard 6584:
1.222 brouard 6585: /* Eigen vectors */
6586: v11=(1./sqrt(1+(v1-lc1)*(v1-lc1)/cv12/cv12));
6587: /*v21=sqrt(1.-v11*v11); *//* error */
6588: v21=(lc1-v1)/cv12*v11;
6589: v12=-v21;
6590: v22=v11;
6591: tnalp=v21/v11;
6592: if(first1==1){
6593: first1=0;
6594: 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);
6595: }
6596: 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);
6597: /*printf(fignu*/
6598: /* mu1+ v11*lc1*cost + v12*lc2*sin(t) */
6599: /* mu2+ v21*lc1*cost + v22*lc2*sin(t) */
6600: if(first==1){
6601: first=0;
6602: fprintf(ficgp,"\n# Ellipsoids of confidence\n#\n");
6603: fprintf(ficgp,"\nset parametric;unset label");
6604: 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);
6605: fprintf(ficgp,"\nset ter svg size 640, 480");
1.266 brouard 6606: fprintf(fichtmcov,"\n<p><br>Ellipsoids of confidence cov(p%1d%1d,p%1d%1d) expressed in year<sup>-1</sup>\
1.220 brouard 6607: :<a href=\"%s_%d%1d%1d-%1d%1d.svg\"> \
1.201 brouard 6608: %s_%d%1d%1d-%1d%1d.svg</A>, ",k1,l1,k2,l2,\
1.222 brouard 6609: subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2, \
6610: subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
6611: fprintf(fichtmcov,"\n<br><img src=\"%s_%d%1d%1d-%1d%1d.svg\"> ",subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
6612: fprintf(fichtmcov,"\n<br> Correlation at age %d (%.3f),",(int) age, c12);
6613: fprintf(ficgp,"\nset out \"%s_%d%1d%1d-%1d%1d.svg\"",subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
6614: fprintf(ficgp,"\nset label \"%d\" at %11.3e,%11.3e center",(int) age, mu1,mu2);
6615: fprintf(ficgp,"\n# Age %d, p%1d%1d - p%1d%1d",(int) age, k1,l1,k2,l2);
6616: 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 6617: mu1,std,v11,sqrt(lc1),v12,sqrt(fabs(lc2)), \
6618: mu2,std,v21,sqrt(lc1),v22,sqrt(fabs(lc2))); /* For gnuplot only */
1.222 brouard 6619: }else{
6620: first=0;
6621: fprintf(fichtmcov," %d (%.3f),",(int) age, c12);
6622: fprintf(ficgp,"\n# Age %d, p%1d%1d - p%1d%1d",(int) age, k1,l1,k2,l2);
6623: fprintf(ficgp,"\nset label \"%d\" at %11.3e,%11.3e center",(int) age, mu1,mu2);
6624: 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 6625: mu1,std,v11,sqrt(lc1),v12,sqrt(fabs(lc2)), \
6626: mu2,std,v21,sqrt(lc1),v22,sqrt(fabs(lc2)));
1.222 brouard 6627: }/* if first */
6628: } /* age mod 5 */
6629: } /* end loop age */
6630: fprintf(ficgp,"\nset out;\nset out \"%s_%d%1d%1d-%1d%1d.svg\";replot;set out;",subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
6631: first=1;
6632: } /*l12 */
6633: } /* k12 */
6634: } /*l1 */
6635: }/* k1 */
6636: } /* loop on combination of covariates j1 */
6637: free_ma3x(varpij,1,nlstate,1,nlstate+ndeath,(int) bage, (int)fage);
6638: free_matrix(mu,1,(nlstate+ndeath)*(nlstate+ndeath),(int) bage, (int)fage);
6639: free_matrix(doldm,1,(nlstate)*(nlstate+ndeath),1,(nlstate)*(nlstate+ndeath));
6640: free_matrix(dnewm,1,(nlstate)*(nlstate+ndeath),1,npar);
6641: free_vector(xp,1,npar);
6642: fclose(ficresprob);
6643: fclose(ficresprobcov);
6644: fclose(ficresprobcor);
6645: fflush(ficgp);
6646: fflush(fichtmcov);
6647: }
1.126 brouard 6648:
6649:
6650: /******************* Printing html file ***********/
1.201 brouard 6651: void printinghtml(char fileresu[], char title[], char datafile[], int firstpass, \
1.126 brouard 6652: int lastpass, int stepm, int weightopt, char model[],\
6653: int imx,int jmin, int jmax, double jmeanint,char rfileres[],\
1.258 brouard 6654: int popforecast, int mobilav, int prevfcast, int mobilavproj, int backcast, int estepm , \
1.213 brouard 6655: double jprev1, double mprev1,double anprev1, double dateprev1, \
6656: double jprev2, double mprev2,double anprev2, double dateprev2){
1.237 brouard 6657: int jj1, k1, i1, cpt, k4, nres;
1.126 brouard 6658:
6659: fprintf(fichtm,"<ul><li><a href='#firstorder'>Result files (first order: no variance)</a>\n \
6660: <li><a href='#secondorder'>Result files (second order (variance)</a>\n \
6661: </ul>");
1.237 brouard 6662: fprintf(fichtm,"<ul><li> model=1+age+%s\n \
6663: </ul>", model);
1.214 brouard 6664: fprintf(fichtm,"<ul><li><h4><a name='firstorder'>Result files (first order: no variance)</a></h4>\n");
6665: 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",
6666: jprev1, mprev1,anprev1,jprev2, mprev2,anprev2,subdirfext3(optionfilefiname,"PHTMFR_",".htm"),subdirfext3(optionfilefiname,"PHTMFR_",".htm"));
6667: 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 6668: jprev1, mprev1,anprev1,jprev2, mprev2,anprev2,subdirfext3(optionfilefiname,"PHTM_",".htm"),subdirfext3(optionfilefiname,"PHTM_",".htm"));
6669: fprintf(fichtm,", <a href=\"%s\">%s</a> (text file) <br>\n",subdirf2(fileresu,"P_"),subdirf2(fileresu,"P_"));
1.126 brouard 6670: fprintf(fichtm,"\
6671: - Estimated transition probabilities over %d (stepm) months: <a href=\"%s\">%s</a><br>\n ",
1.201 brouard 6672: stepm,subdirf2(fileresu,"PIJ_"),subdirf2(fileresu,"PIJ_"));
1.126 brouard 6673: fprintf(fichtm,"\
1.217 brouard 6674: - Estimated back transition probabilities over %d (stepm) months: <a href=\"%s\">%s</a><br>\n ",
6675: stepm,subdirf2(fileresu,"PIJB_"),subdirf2(fileresu,"PIJB_"));
6676: fprintf(fichtm,"\
1.126 brouard 6677: - Period (stable) prevalence in each health state: <a href=\"%s\">%s</a> <br>\n",
1.201 brouard 6678: subdirf2(fileresu,"PL_"),subdirf2(fileresu,"PL_"));
1.126 brouard 6679: fprintf(fichtm,"\
1.217 brouard 6680: - Period (stable) back prevalence in each health state: <a href=\"%s\">%s</a> <br>\n",
6681: subdirf2(fileresu,"PLB_"),subdirf2(fileresu,"PLB_"));
6682: fprintf(fichtm,"\
1.211 brouard 6683: - (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 6684: <a href=\"%s\">%s</a> <br>\n",
1.201 brouard 6685: estepm,subdirf2(fileresu,"E_"),subdirf2(fileresu,"E_"));
1.211 brouard 6686: if(prevfcast==1){
6687: fprintf(fichtm,"\
6688: - Prevalence projections by age and states: \
1.201 brouard 6689: <a href=\"%s\">%s</a> <br>\n</li>", subdirf2(fileresu,"F_"),subdirf2(fileresu,"F_"));
1.211 brouard 6690: }
1.126 brouard 6691:
6692:
1.225 brouard 6693: m=pow(2,cptcoveff);
1.222 brouard 6694: if (cptcovn < 1) {m=1;ncodemax[1]=1;}
1.126 brouard 6695:
1.264 brouard 6696: fprintf(fichtm," \n<ul><li><b>Graphs</b></li><p>");
6697:
6698: jj1=0;
6699:
6700: fprintf(fichtm," \n<ul>");
6701: for(nres=1; nres <= nresult; nres++) /* For each resultline */
6702: for(k1=1; k1<=m;k1++){ /* For each combination of covariate */
6703: if(m != 1 && TKresult[nres]!= k1)
6704: continue;
6705: jj1++;
6706: if (cptcovn > 0) {
6707: fprintf(fichtm,"\n<li><a size=\"1\" color=\"#EC5E5E\" href=\"#rescov");
6708: for (cpt=1; cpt<=cptcoveff;cpt++){
6709: fprintf(fichtm,"_V%d=%d_",Tvresult[nres][cpt],(int)Tresult[nres][cpt]);
6710: }
6711: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
6712: fprintf(fichtm,"_V%d=%f_",Tvqresult[nres][k4],Tqresult[nres][k4]);
6713: }
6714: fprintf(fichtm,"\">");
6715:
6716: /* if(nqfveff+nqtveff 0) */ /* Test to be done */
6717: fprintf(fichtm,"************ Results for covariates");
6718: for (cpt=1; cpt<=cptcoveff;cpt++){
6719: fprintf(fichtm," V%d=%d ",Tvresult[nres][cpt],(int)Tresult[nres][cpt]);
6720: }
6721: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
6722: fprintf(fichtm," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
6723: }
6724: if(invalidvarcomb[k1]){
6725: fprintf(fichtm," Warning Combination (%d) ignored because no cases ",k1);
6726: continue;
6727: }
6728: fprintf(fichtm,"</a></li>");
6729: } /* cptcovn >0 */
6730: }
6731: fprintf(fichtm," \n</ul>");
6732:
1.222 brouard 6733: jj1=0;
1.237 brouard 6734:
6735: for(nres=1; nres <= nresult; nres++) /* For each resultline */
1.241 brouard 6736: for(k1=1; k1<=m;k1++){ /* For each combination of covariate */
1.253 brouard 6737: if(m != 1 && TKresult[nres]!= k1)
1.237 brouard 6738: continue;
1.220 brouard 6739:
1.222 brouard 6740: /* for(i1=1; i1<=ncodemax[k1];i1++){ */
6741: jj1++;
6742: if (cptcovn > 0) {
1.264 brouard 6743: fprintf(fichtm,"\n<p><a name=\"rescov");
6744: for (cpt=1; cpt<=cptcoveff;cpt++){
6745: fprintf(fichtm,"_V%d=%d_",Tvresult[nres][cpt],(int)Tresult[nres][cpt]);
6746: }
6747: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
6748: fprintf(fichtm,"_V%d=%f_",Tvqresult[nres][k4],Tqresult[nres][k4]);
6749: }
6750: fprintf(fichtm,"\"</a>");
6751:
1.222 brouard 6752: fprintf(fichtm,"<hr size=\"2\" color=\"#EC5E5E\">************ Results for covariates");
1.225 brouard 6753: for (cpt=1; cpt<=cptcoveff;cpt++){
1.237 brouard 6754: fprintf(fichtm," V%d=%d ",Tvresult[nres][cpt],(int)Tresult[nres][cpt]);
6755: printf(" V%d=%d ",Tvresult[nres][cpt],Tresult[nres][cpt]);fflush(stdout);
6756: /* fprintf(fichtm," V%d=%d ",Tvaraff[cpt],nbcode[Tvaraff[cpt]][codtabm(jj1,cpt)]); */
6757: /* printf(" V%d=%d ",Tvaraff[cpt],nbcode[Tvaraff[cpt]][codtabm(jj1,cpt)]);fflush(stdout); */
1.222 brouard 6758: }
1.237 brouard 6759: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
6760: fprintf(fichtm," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
6761: printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);fflush(stdout);
6762: }
6763:
1.230 brouard 6764: /* if(nqfveff+nqtveff 0) */ /* Test to be done */
1.222 brouard 6765: fprintf(fichtm," ************\n<hr size=\"2\" color=\"#EC5E5E\">");
6766: if(invalidvarcomb[k1]){
6767: fprintf(fichtm,"\n<h3>Combination (%d) ignored because no cases </h3>\n",k1);
6768: printf("\nCombination (%d) ignored because no cases \n",k1);
6769: continue;
6770: }
6771: }
6772: /* aij, bij */
1.259 brouard 6773: 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 6774: <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 6775: /* Pij */
1.241 brouard 6776: 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> \
6777: <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 6778: /* Quasi-incidences */
6779: 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 6780: before but expressed in per year i.e. quasi incidences if stepm is small and probabilities too, \
1.211 brouard 6781: 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 6782: 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> \
6783: <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 6784: /* Survival functions (period) in state j */
6785: for(cpt=1; cpt<=nlstate;cpt++){
1.241 brouard 6786: 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> \
6787: <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 6788: }
6789: /* State specific survival functions (period) */
6790: for(cpt=1; cpt<=nlstate;cpt++){
6791: fprintf(fichtm,"<br>\n- Survival functions from state %d in each live state and total.\
1.220 brouard 6792: Or probability to survive in various states (1 to %d) being in state %d at different ages. \
1.241 brouard 6793: <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 6794: }
6795: /* Period (stable) prevalence in each health state */
6796: for(cpt=1; cpt<=nlstate;cpt++){
1.264 brouard 6797: 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> \
6798: <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 6799: }
6800: if(backcast==1){
6801: /* Period (stable) back prevalence in each health state */
6802: for(cpt=1; cpt<=nlstate;cpt++){
1.264 brouard 6803: 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 6804: <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 6805: }
1.217 brouard 6806: }
1.222 brouard 6807: if(prevfcast==1){
6808: /* Projection of prevalence up to period (stable) prevalence in each health state */
6809: for(cpt=1; cpt<=nlstate;cpt++){
1.268 brouard 6810: 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 6811: <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 6812: }
6813: }
1.268 brouard 6814: if(backcast==1){
6815: /* Back projection of prevalence up to stable (mixed) back-prevalence in each health state */
6816: for(cpt=1; cpt<=nlstate;cpt++){
6817: 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> \
6818: <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);
6819: }
6820: }
1.220 brouard 6821:
1.222 brouard 6822: for(cpt=1; cpt<=nlstate;cpt++) {
1.241 brouard 6823: 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> \
6824: <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 6825: }
6826: /* } /\* end i1 *\/ */
6827: }/* End k1 */
6828: fprintf(fichtm,"</ul>");
1.126 brouard 6829:
1.222 brouard 6830: fprintf(fichtm,"\
1.126 brouard 6831: \n<br><li><h4> <a name='secondorder'>Result files (second order: variances)</a></h4>\n\
1.193 brouard 6832: - Parameter file with estimated parameters and covariance matrix: <a href=\"%s\">%s</a> <br> \
1.203 brouard 6833: - 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 6834: But because parameters are usually highly correlated (a higher incidence of disability \
6835: and a higher incidence of recovery can give very close observed transition) it might \
6836: be very useful to look not only at linear confidence intervals estimated from the \
6837: variances but at the covariance matrix. And instead of looking at the estimated coefficients \
6838: (parameters) of the logistic regression, it might be more meaningful to visualize the \
6839: covariance matrix of the one-step probabilities. \
6840: See page 'Matrix of variance-covariance of one-step probabilities' below. \n", rfileres,rfileres);
1.126 brouard 6841:
1.222 brouard 6842: fprintf(fichtm," - Standard deviation of one-step probabilities: <a href=\"%s\">%s</a> <br>\n",
6843: subdirf2(fileresu,"PROB_"),subdirf2(fileresu,"PROB_"));
6844: fprintf(fichtm,"\
1.126 brouard 6845: - Variance-covariance of one-step probabilities: <a href=\"%s\">%s</a> <br>\n",
1.222 brouard 6846: subdirf2(fileresu,"PROBCOV_"),subdirf2(fileresu,"PROBCOV_"));
1.126 brouard 6847:
1.222 brouard 6848: fprintf(fichtm,"\
1.126 brouard 6849: - Correlation matrix of one-step probabilities: <a href=\"%s\">%s</a> <br>\n",
1.222 brouard 6850: subdirf2(fileresu,"PROBCOR_"),subdirf2(fileresu,"PROBCOR_"));
6851: fprintf(fichtm,"\
1.126 brouard 6852: - 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): \
6853: <a href=\"%s\">%s</a> <br>\n</li>",
1.201 brouard 6854: estepm,subdirf2(fileresu,"CVE_"),subdirf2(fileresu,"CVE_"));
1.222 brouard 6855: fprintf(fichtm,"\
1.126 brouard 6856: - (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): \
6857: <a href=\"%s\">%s</a> <br>\n</li>",
1.201 brouard 6858: estepm,subdirf2(fileresu,"STDE_"),subdirf2(fileresu,"STDE_"));
1.222 brouard 6859: fprintf(fichtm,"\
1.128 brouard 6860: - 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 6861: estepm, subdirf2(fileresu,"V_"),subdirf2(fileresu,"V_"));
6862: fprintf(fichtm,"\
1.128 brouard 6863: - 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 6864: estepm, subdirf2(fileresu,"T_"),subdirf2(fileresu,"T_"));
6865: fprintf(fichtm,"\
1.126 brouard 6866: - Standard deviation of period (stable) prevalences: <a href=\"%s\">%s</a> <br>\n",\
1.222 brouard 6867: subdirf2(fileresu,"VPL_"),subdirf2(fileresu,"VPL_"));
1.126 brouard 6868:
6869: /* if(popforecast==1) fprintf(fichtm,"\n */
6870: /* - Prevalences forecasting: <a href=\"f%s\">f%s</a> <br>\n */
6871: /* - Population forecasting (if popforecast=1): <a href=\"pop%s\">pop%s</a> <br>\n */
6872: /* <br>",fileres,fileres,fileres,fileres); */
6873: /* else */
6874: /* 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 6875: fflush(fichtm);
6876: fprintf(fichtm," <ul><li><b>Graphs</b></li><p>");
1.126 brouard 6877:
1.225 brouard 6878: m=pow(2,cptcoveff);
1.222 brouard 6879: if (cptcovn < 1) {m=1;ncodemax[1]=1;}
1.126 brouard 6880:
1.222 brouard 6881: jj1=0;
1.237 brouard 6882:
1.241 brouard 6883: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.222 brouard 6884: for(k1=1; k1<=m;k1++){
1.253 brouard 6885: if(m != 1 && TKresult[nres]!= k1)
1.237 brouard 6886: continue;
1.222 brouard 6887: /* for(i1=1; i1<=ncodemax[k1];i1++){ */
6888: jj1++;
1.126 brouard 6889: if (cptcovn > 0) {
6890: fprintf(fichtm,"<hr size=\"2\" color=\"#EC5E5E\">************ Results for covariates");
1.225 brouard 6891: for (cpt=1; cpt<=cptcoveff;cpt++) /**< cptcoveff number of variables */
1.237 brouard 6892: fprintf(fichtm," V%d=%d ",Tvresult[nres][cpt],Tresult[nres][cpt]);
6893: /* fprintf(fichtm," V%d=%d ",Tvaraff[cpt],nbcode[Tvaraff[cpt]][codtabm(jj1,cpt)]); */
6894: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
6895: fprintf(fichtm," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
6896: }
6897:
1.126 brouard 6898: fprintf(fichtm," ************\n<hr size=\"2\" color=\"#EC5E5E\">");
1.220 brouard 6899:
1.222 brouard 6900: if(invalidvarcomb[k1]){
6901: fprintf(fichtm,"\n<h4>Combination (%d) ignored because no cases </h4>\n",k1);
6902: continue;
6903: }
1.126 brouard 6904: }
6905: for(cpt=1; cpt<=nlstate;cpt++) {
1.258 brouard 6906: fprintf(fichtm,"\n<br>- Observed (cross-sectional with mov_average=%d) and period (incidence based) \
1.241 brouard 6907: 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 6908: <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 6909: }
6910: fprintf(fichtm,"\n<br>- Total life expectancy by age and \
1.128 brouard 6911: health expectancies in states (1) and (2). If popbased=1 the smooth (due to the model) \
6912: true period expectancies (those weighted with period prevalences are also\
6913: drawn in addition to the population based expectancies computed using\
1.241 brouard 6914: observed and cahotic prevalences: <a href=\"%s_%d-%d.svg\">%s_%d-%d.svg</a>\n<br>\
6915: <img src=\"%s_%d-%d.svg\">",subdirf2(optionfilefiname,"E_"),k1,nres,subdirf2(optionfilefiname,"E_"),k1,nres,subdirf2(optionfilefiname,"E_"),k1,nres);
1.222 brouard 6916: /* } /\* end i1 *\/ */
6917: }/* End k1 */
1.241 brouard 6918: }/* End nres */
1.222 brouard 6919: fprintf(fichtm,"</ul>");
6920: fflush(fichtm);
1.126 brouard 6921: }
6922:
6923: /******************* Gnuplot file **************/
1.268 brouard 6924: void printinggnuplot(char fileresu[], char optionfilefiname[], double ageminpar, double agemaxpar, double fage , int prevfcast, int backcast, char pathc[], double p[], int offyear, int offbyear){
1.126 brouard 6925:
6926: char dirfileres[132],optfileres[132];
1.264 brouard 6927: char gplotcondition[132], gplotlabel[132];
1.237 brouard 6928: 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 6929: int lv=0, vlv=0, kl=0;
1.130 brouard 6930: int ng=0;
1.201 brouard 6931: int vpopbased;
1.223 brouard 6932: int ioffset; /* variable offset for columns */
1.235 brouard 6933: int nres=0; /* Index of resultline */
1.266 brouard 6934: int istart=1; /* For starting graphs in projections */
1.219 brouard 6935:
1.126 brouard 6936: /* if((ficgp=fopen(optionfilegnuplot,"a"))==NULL) { */
6937: /* printf("Problem with file %s",optionfilegnuplot); */
6938: /* fprintf(ficlog,"Problem with file %s",optionfilegnuplot); */
6939: /* } */
6940:
6941: /*#ifdef windows */
6942: fprintf(ficgp,"cd \"%s\" \n",pathc);
1.223 brouard 6943: /*#endif */
1.225 brouard 6944: m=pow(2,cptcoveff);
1.126 brouard 6945:
1.202 brouard 6946: /* Contribution to likelihood */
6947: /* Plot the probability implied in the likelihood */
1.223 brouard 6948: fprintf(ficgp,"\n# Contributions to the Likelihood, mle >=1. For mle=4 no interpolation, pure matrix products.\n#\n");
6949: fprintf(ficgp,"\n set log y; unset log x;set xlabel \"Age\"; set ylabel \"Likelihood (-2Log(L))\";");
6950: /* fprintf(ficgp,"\nset ter svg size 640, 480"); */ /* Too big for svg */
6951: fprintf(ficgp,"\nset ter pngcairo size 640, 480");
1.204 brouard 6952: /* nice for mle=4 plot by number of matrix products.
1.202 brouard 6953: replot "rrtest1/toto.txt" u 2:($4 == 1 && $5==2 ? $9 : 1/0):5 t "p12" with point lc 1 */
6954: /* replot exp(p1+p2*x)/(1+exp(p1+p2*x)+exp(p3+p4*x)+exp(p5+p6*x)) t "p12(x)" */
1.223 brouard 6955: /* fprintf(ficgp,"\nset out \"%s.svg\";",subdirf2(optionfilefiname,"ILK_")); */
6956: fprintf(ficgp,"\nset out \"%s-dest.png\";",subdirf2(optionfilefiname,"ILK_"));
6957: 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));
6958: fprintf(ficgp,"\nset out \"%s-ori.png\";",subdirf2(optionfilefiname,"ILK_"));
6959: 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));
6960: for (i=1; i<= nlstate ; i ++) {
6961: fprintf(ficgp,"\nset out \"%s-p%dj.png\";set ylabel \"Probability for each individual/wave\";",subdirf2(optionfilefiname,"ILK_"),i);
6962: fprintf(ficgp,"unset log;\n# plot weighted, mean weight should have point size of 0.5\n plot \"%s\"",subdirf(fileresilk));
6963: 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);
6964: for (j=2; j<= nlstate+ndeath ; j ++) {
6965: 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);
6966: }
6967: fprintf(ficgp,";\nset out; unset ylabel;\n");
6968: }
6969: /* 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 */
6970: /* fprintf(ficgp,"\nset log y;plot \"%s\" u 2:(-$11):3 t \"All sample, all transitions\" with dots lc variable",subdirf(fileresilk)); */
6971: /* fprintf(ficgp,"\nreplot \"%s\" u 2:($3 <= 3 ? -$11 : 1/0):3 t \"First 3 individuals\" with line lc variable", subdirf(fileresilk)); */
6972: fprintf(ficgp,"\nset out;unset log\n");
6973: /* fprintf(ficgp,"\nset out \"%s.svg\"; replot; set out; # bug gnuplot",subdirf2(optionfilefiname,"ILK_")); */
1.202 brouard 6974:
1.126 brouard 6975: strcpy(dirfileres,optionfilefiname);
6976: strcpy(optfileres,"vpl");
1.223 brouard 6977: /* 1eme*/
1.238 brouard 6978: for (cpt=1; cpt<= nlstate ; cpt ++){ /* For each live state */
6979: for (k1=1; k1<= m ; k1 ++){ /* For each valid combination of covariate */
1.236 brouard 6980: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.238 brouard 6981: /* plot [100000000000000000000:-100000000000000000000] "mysbiaspar/vplrmysbiaspar.txt to check */
1.253 brouard 6982: if(m != 1 && TKresult[nres]!= k1)
1.238 brouard 6983: continue;
6984: /* We are interested in selected combination by the resultline */
1.246 brouard 6985: /* printf("\n# 1st: Period (stable) prevalence with CI: 'VPL_' files and live state =%d ", cpt); */
1.238 brouard 6986: fprintf(ficgp,"\n# 1st: Period (stable) prevalence with CI: 'VPL_' files and live state =%d ", cpt);
1.264 brouard 6987: strcpy(gplotlabel,"(");
1.238 brouard 6988: for (k=1; k<=cptcoveff; k++){ /* For each covariate k get corresponding value lv for combination k1 */
6989: lv= decodtabm(k1,k,cptcoveff); /* Should be the value of the covariate corresponding to k1 combination */
6990: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
6991: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
6992: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
6993: vlv= nbcode[Tvaraff[k]][lv]; /* vlv is the value of the covariate lv, 0 or 1 */
6994: /* For each combination of covariate k1 (V1=1, V3=0), we printed the current covariate k and its value vlv */
1.246 brouard 6995: /* printf(" V%d=%d ",Tvaraff[k],vlv); */
1.238 brouard 6996: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 6997: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.238 brouard 6998: }
6999: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
1.246 brouard 7000: /* printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
1.238 brouard 7001: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7002: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
7003: }
7004: strcpy(gplotlabel+strlen(gplotlabel),")");
1.246 brouard 7005: /* printf("\n#\n"); */
1.238 brouard 7006: fprintf(ficgp,"\n#\n");
7007: if(invalidvarcomb[k1]){
1.260 brouard 7008: /*k1=k1-1;*/ /* To be checked */
1.238 brouard 7009: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7010: continue;
7011: }
1.235 brouard 7012:
1.241 brouard 7013: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"V_"),cpt,k1,nres);
7014: fprintf(ficgp,"\n#set out \"V_%s_%d-%d-%d.svg\" \n",optionfilefiname,cpt,k1,nres);
1.264 brouard 7015: 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 7016: 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);
7017: /* 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); */
7018: /* k1-1 error should be nres-1*/
1.238 brouard 7019: for (i=1; i<= nlstate ; i ++) {
7020: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
7021: else fprintf(ficgp," %%*lf (%%*lf)");
7022: }
1.260 brouard 7023: 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 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\"95%% CI\" w l lt 1,\"%s\" every :::%d::%d u 1:($2==%d ? $3-1.96*$4 : 1/0) \"%%lf %%lf",subdirf2(fileresu,"VPL_"),nres-1,nres-1,nres);
1.238 brouard 7029: for (i=1; i<= nlstate ; i ++) {
7030: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
7031: else fprintf(ficgp," %%*lf (%%*lf)");
7032: }
1.265 brouard 7033: /* fprintf(ficgp,"\" t\"\" w l lt 1,\"%s\" every :::%d::%d u 1:($%d) t\"Observed prevalence\" w l lt 2",subdirf2(fileresu,"P_"),k1-1,k1-1,2+4*(cpt-1)); */
7034:
7035: fprintf(ficgp,"\" t\"\" w l lt 1,\"%s\" u 1:((",subdirf2(fileresu,"P_"));
7036: if(cptcoveff ==0){
7037: fprintf(ficgp,"$%d)) t 'Observed prevalence in state %d' with line lt 3", 2+(cpt-1), cpt );
7038: }else{
7039: kl=0;
7040: for (k=1; k<=cptcoveff; k++){ /* For each combination of covariate */
7041: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate value corresponding to k1 combination and kth covariate */
7042: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7043: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7044: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7045: vlv= nbcode[Tvaraff[k]][lv];
7046: kl++;
7047: /* 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 *\/ */
7048: /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */
7049: /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */
7050: /* '' u 6:(($1==1 && $2==0 && $3==2 && $4==0)? $9/(1.-$15) : 1/0):($5==2000? 3:2) t 'p.1' with line lc variable*/
7051: if(k==cptcoveff){
7052: fprintf(ficgp,"$%d==%d && $%d==%d)? $%d : 1/0) t 'Observed prevalence in state %d' w l lt 2",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][lv], \
7053: 2+cptcoveff*2+3*(cpt-1), cpt ); /* 4 or 6 ?*/
7054: }else{
7055: fprintf(ficgp,"$%d==%d && $%d==%d && ",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][lv]);
7056: kl++;
7057: }
7058: } /* end covariate */
7059: } /* end if no covariate */
7060:
1.238 brouard 7061: if(backcast==1){ /* We need to get the corresponding values of the covariates involved in this combination k1 */
7062: /* fprintf(ficgp,",\"%s\" every :::%d::%d u 1:($%d) t\"Backward stable prevalence\" w l lt 3",subdirf2(fileresu,"PLB_"),k1-1,k1-1,1+cpt); */
1.242 brouard 7063: fprintf(ficgp,",\"%s\" u 1:((",subdirf2(fileresu,"PLB_")); /* Age is in 1, nres in 2 to be fixed */
1.238 brouard 7064: if(cptcoveff ==0){
1.245 brouard 7065: fprintf(ficgp,"$%d)) t 'Backward prevalence in state %d' with line lt 3", 2+(cpt-1), cpt );
1.238 brouard 7066: }else{
7067: kl=0;
7068: for (k=1; k<=cptcoveff; k++){ /* For each combination of covariate */
7069: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate value corresponding to k1 combination and kth covariate */
7070: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7071: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7072: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7073: vlv= nbcode[Tvaraff[k]][lv];
1.223 brouard 7074: kl++;
1.238 brouard 7075: /* 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 *\/ */
7076: /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */
7077: /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */
7078: /* '' u 6:(($1==1 && $2==0 && $3==2 && $4==0)? $9/(1.-$15) : 1/0):($5==2000? 3:2) t 'p.1' with line lc variable*/
7079: if(k==cptcoveff){
1.245 brouard 7080: fprintf(ficgp,"$%d==%d && $%d==%d)? $%d : 1/0) t 'Backward prevalence in state %d' w l lt 3",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][lv], \
1.242 brouard 7081: 2+cptcoveff*2+(cpt-1), cpt ); /* 4 or 6 ?*/
1.238 brouard 7082: }else{
7083: fprintf(ficgp,"$%d==%d && $%d==%d && ",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][lv]);
7084: kl++;
7085: }
7086: } /* end covariate */
7087: } /* end if no covariate */
1.268 brouard 7088: if(backcast == 1){
7089: fprintf(ficgp,", \"%s\" every :::%d::%d u 1:($2==%d ? $3:1/0) \"%%lf %%lf",subdirf2(fileresu,"VBL_"),nres-1,nres-1,nres);
7090: /* k1-1 error should be nres-1*/
7091: for (i=1; i<= nlstate ; i ++) {
7092: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
7093: else fprintf(ficgp," %%*lf (%%*lf)");
7094: }
7095: 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);
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\"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);
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\"\" w l lt 1");
7106: } /* end if backprojcast */
1.238 brouard 7107: } /* end if backcast */
1.264 brouard 7108: fprintf(ficgp,"\nset out ;unset label;\n");
1.238 brouard 7109: } /* nres */
1.201 brouard 7110: } /* k1 */
7111: } /* cpt */
1.235 brouard 7112:
7113:
1.126 brouard 7114: /*2 eme*/
1.238 brouard 7115: for (k1=1; k1<= m ; k1 ++){
7116: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 7117: if(m != 1 && TKresult[nres]!= k1)
1.238 brouard 7118: continue;
7119: fprintf(ficgp,"\n# 2nd: Total life expectancy with CI: 't' files ");
1.264 brouard 7120: strcpy(gplotlabel,"(");
1.238 brouard 7121: for (k=1; k<=cptcoveff; k++){ /* For each covariate and each value */
1.225 brouard 7122: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate number corresponding to k1 combination */
1.223 brouard 7123: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7124: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7125: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7126: vlv= nbcode[Tvaraff[k]][lv];
7127: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 7128: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.211 brouard 7129: }
1.237 brouard 7130: /* for(k=1; k <= ncovds; k++){ */
1.236 brouard 7131: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
1.238 brouard 7132: printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.236 brouard 7133: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7134: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.238 brouard 7135: }
1.264 brouard 7136: strcpy(gplotlabel+strlen(gplotlabel),")");
1.211 brouard 7137: fprintf(ficgp,"\n#\n");
1.223 brouard 7138: if(invalidvarcomb[k1]){
7139: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7140: continue;
7141: }
1.219 brouard 7142:
1.241 brouard 7143: fprintf(ficgp,"\nset out \"%s_%d-%d.svg\" \n",subdirf2(optionfilefiname,"E_"),k1,nres);
1.238 brouard 7144: for(vpopbased=0; vpopbased <= popbased; vpopbased++){ /* Done for vpopbased=0 and vpopbased=1 if popbased==1*/
1.264 brouard 7145: fprintf(ficgp,"\nset label \"popbased %d %s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",vpopbased,gplotlabel);
7146: if(vpopbased==0){
1.238 brouard 7147: fprintf(ficgp,"set ylabel \"Years\" \nset ter svg size 640, 480\nplot [%.f:%.f] ",ageminpar,fage);
1.264 brouard 7148: }else
1.238 brouard 7149: fprintf(ficgp,"\nreplot ");
7150: for (i=1; i<= nlstate+1 ; i ++) {
7151: k=2*i;
1.261 brouard 7152: 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 7153: for (j=1; j<= nlstate+1 ; j ++) {
7154: if (j==i) fprintf(ficgp," %%lf (%%lf)");
7155: else fprintf(ficgp," %%*lf (%%*lf)");
7156: }
7157: if (i== 1) fprintf(ficgp,"\" t\"TLE\" w l lt %d, \\\n",i);
7158: else fprintf(ficgp,"\" t\"LE in state (%d)\" w l lt %d, \\\n",i-1,i+1);
1.261 brouard 7159: 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 7160: for (j=1; j<= nlstate+1 ; j ++) {
7161: if (j==i) fprintf(ficgp," %%lf (%%lf)");
7162: else fprintf(ficgp," %%*lf (%%*lf)");
7163: }
7164: fprintf(ficgp,"\" t\"\" w l lt 0,");
1.261 brouard 7165: 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 7166: for (j=1; j<= nlstate+1 ; j ++) {
7167: if (j==i) fprintf(ficgp," %%lf (%%lf)");
7168: else fprintf(ficgp," %%*lf (%%*lf)");
7169: }
7170: if (i== (nlstate+1)) fprintf(ficgp,"\" t\"\" w l lt 0");
7171: else fprintf(ficgp,"\" t\"\" w l lt 0,\\\n");
7172: } /* state */
7173: } /* vpopbased */
1.264 brouard 7174: 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 7175: } /* end nres */
7176: } /* k1 end 2 eme*/
7177:
7178:
7179: /*3eme*/
7180: for (k1=1; k1<= m ; k1 ++){
7181: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 7182: if(m != 1 && TKresult[nres]!= k1)
1.238 brouard 7183: continue;
7184:
7185: for (cpt=1; cpt<= nlstate ; cpt ++) {
1.261 brouard 7186: fprintf(ficgp,"\n\n# 3d: Life expectancy with EXP_ files: combination=%d state=%d",k1, cpt);
1.264 brouard 7187: strcpy(gplotlabel,"(");
1.238 brouard 7188: for (k=1; k<=cptcoveff; k++){ /* For each covariate and each value */
7189: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate number corresponding to k1 combination */
7190: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7191: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7192: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7193: vlv= nbcode[Tvaraff[k]][lv];
7194: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 7195: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.238 brouard 7196: }
7197: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7198: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7199: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.238 brouard 7200: }
1.264 brouard 7201: strcpy(gplotlabel+strlen(gplotlabel),")");
1.238 brouard 7202: fprintf(ficgp,"\n#\n");
7203: if(invalidvarcomb[k1]){
7204: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7205: continue;
7206: }
7207:
7208: /* k=2+nlstate*(2*cpt-2); */
7209: k=2+(nlstate+1)*(cpt-1);
1.241 brouard 7210: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"EXP_"),cpt,k1,nres);
1.264 brouard 7211: fprintf(ficgp,"set label \"%s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",gplotlabel);
1.238 brouard 7212: fprintf(ficgp,"set ter svg size 640, 480\n\
1.261 brouard 7213: 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 7214: /*fprintf(ficgp,",\"e%s\" every :::%d::%d u 1:($%d-2*$%d) \"\%%lf ",fileres,k1-1,k1-1,k,k+1);
7215: for (i=1; i<= nlstate*2 ; i ++) fprintf(ficgp,"\%%lf (\%%lf) ");
7216: fprintf(ficgp,"\" t \"e%d1\" w l",cpt);
7217: fprintf(ficgp,",\"e%s\" every :::%d::%d u 1:($%d+2*$%d) \"\%%lf ",fileres,k1-1,k1-1,k,k+1);
7218: for (i=1; i<= nlstate*2 ; i ++) fprintf(ficgp,"\%%lf (\%%lf) ");
7219: fprintf(ficgp,"\" t \"e%d1\" w l",cpt);
1.219 brouard 7220:
1.238 brouard 7221: */
7222: for (i=1; i< nlstate ; i ++) {
1.261 brouard 7223: 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 7224: /* 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 7225:
1.238 brouard 7226: }
1.261 brouard 7227: 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 7228: }
1.264 brouard 7229: fprintf(ficgp,"\nunset label;\n");
1.238 brouard 7230: } /* end nres */
7231: } /* end kl 3eme */
1.126 brouard 7232:
1.223 brouard 7233: /* 4eme */
1.201 brouard 7234: /* Survival functions (period) from state i in state j by initial state i */
1.238 brouard 7235: for (k1=1; k1<=m; k1++){ /* For each covariate and each value */
7236: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 7237: if(m != 1 && TKresult[nres]!= k1)
1.223 brouard 7238: continue;
1.238 brouard 7239: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state cpt*/
1.264 brouard 7240: strcpy(gplotlabel,"(");
1.238 brouard 7241: fprintf(ficgp,"\n#\n#\n# Survival functions in state j : 'LIJ_' files, cov=%d state=%d",k1, cpt);
7242: for (k=1; k<=cptcoveff; k++){ /* For each covariate and each value */
7243: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate number corresponding to k1 combination */
7244: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7245: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7246: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7247: vlv= nbcode[Tvaraff[k]][lv];
7248: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 7249: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.238 brouard 7250: }
7251: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7252: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7253: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.238 brouard 7254: }
1.264 brouard 7255: strcpy(gplotlabel+strlen(gplotlabel),")");
1.238 brouard 7256: fprintf(ficgp,"\n#\n");
7257: if(invalidvarcomb[k1]){
7258: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7259: continue;
1.223 brouard 7260: }
1.238 brouard 7261:
1.241 brouard 7262: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"LIJ_"),cpt,k1,nres);
1.264 brouard 7263: 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 7264: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability to be alive\" \n\
7265: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
7266: k=3;
7267: for (i=1; i<= nlstate ; i ++){
7268: if(i==1){
7269: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJ_"));
7270: }else{
7271: fprintf(ficgp,", '' ");
7272: }
7273: l=(nlstate+ndeath)*(i-1)+1;
7274: fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d/($%d",k1,k+l+(cpt-1),k+l);
7275: for (j=2; j<= nlstate+ndeath ; j ++)
7276: fprintf(ficgp,"+$%d",k+l+j-1);
7277: fprintf(ficgp,")) t \"l(%d,%d)\" w l",i,cpt);
7278: } /* nlstate */
1.264 brouard 7279: fprintf(ficgp,"\nset out; unset label;\n");
1.238 brouard 7280: } /* end cpt state*/
7281: } /* end nres */
7282: } /* end covariate k1 */
7283:
1.220 brouard 7284: /* 5eme */
1.201 brouard 7285: /* Survival functions (period) from state i in state j by final state j */
1.238 brouard 7286: for (k1=1; k1<= m ; k1++){ /* For each covariate combination if any */
7287: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 7288: if(m != 1 && TKresult[nres]!= k1)
1.227 brouard 7289: continue;
1.238 brouard 7290: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each inital state */
1.264 brouard 7291: strcpy(gplotlabel,"(");
1.238 brouard 7292: 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);
7293: for (k=1; k<=cptcoveff; k++){ /* For each covariate and each value */
7294: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate number corresponding to k1 combination */
7295: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7296: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7297: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7298: vlv= nbcode[Tvaraff[k]][lv];
7299: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 7300: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.238 brouard 7301: }
7302: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7303: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7304: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.238 brouard 7305: }
1.264 brouard 7306: strcpy(gplotlabel+strlen(gplotlabel),")");
1.238 brouard 7307: fprintf(ficgp,"\n#\n");
7308: if(invalidvarcomb[k1]){
7309: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7310: continue;
7311: }
1.227 brouard 7312:
1.241 brouard 7313: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"LIJT_"),cpt,k1,nres);
1.264 brouard 7314: 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 7315: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability to be alive\" \n\
7316: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
7317: k=3;
7318: for (j=1; j<= nlstate ; j ++){ /* Lived in state j */
7319: if(j==1)
7320: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJ_"));
7321: else
7322: fprintf(ficgp,", '' ");
7323: l=(nlstate+ndeath)*(cpt-1) +j;
7324: fprintf(ficgp," u (($1==%d && (floor($2)%%5 == 0)) ? ($3):1/0):($%d",k1,k+l);
7325: /* for (i=2; i<= nlstate+ndeath ; i ++) */
7326: /* fprintf(ficgp,"+$%d",k+l+i-1); */
7327: fprintf(ficgp,") t \"l(%d,%d)\" w l",cpt,j);
7328: } /* nlstate */
7329: fprintf(ficgp,", '' ");
7330: fprintf(ficgp," u (($1==%d && (floor($2)%%5 == 0)) ? ($3):1/0):(",k1);
7331: for (j=1; j<= nlstate ; j ++){ /* Lived in state j */
7332: l=(nlstate+ndeath)*(cpt-1) +j;
7333: if(j < nlstate)
7334: fprintf(ficgp,"$%d +",k+l);
7335: else
7336: fprintf(ficgp,"$%d) t\"l(%d,.)\" w l",k+l,cpt);
7337: }
1.264 brouard 7338: fprintf(ficgp,"\nset out; unset label;\n");
1.238 brouard 7339: } /* end cpt state*/
7340: } /* end covariate */
7341: } /* end nres */
1.227 brouard 7342:
1.220 brouard 7343: /* 6eme */
1.202 brouard 7344: /* CV preval stable (period) for each covariate */
1.237 brouard 7345: for (k1=1; k1<= m ; k1 ++) /* For each covariate combination if any */
7346: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 7347: if(m != 1 && TKresult[nres]!= k1)
1.237 brouard 7348: continue;
1.255 brouard 7349: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state of arrival */
1.264 brouard 7350: strcpy(gplotlabel,"(");
1.211 brouard 7351: fprintf(ficgp,"\n#\n#\n#CV preval stable (period): 'pij' files, covariatecombination#=%d state=%d",k1, cpt);
1.225 brouard 7352: for (k=1; k<=cptcoveff; k++){ /* For each covariate and each value */
1.227 brouard 7353: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate number corresponding to k1 combination */
7354: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7355: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7356: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7357: vlv= nbcode[Tvaraff[k]][lv];
7358: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 7359: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.211 brouard 7360: }
1.237 brouard 7361: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7362: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7363: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.237 brouard 7364: }
1.264 brouard 7365: strcpy(gplotlabel+strlen(gplotlabel),")");
1.211 brouard 7366: fprintf(ficgp,"\n#\n");
1.223 brouard 7367: if(invalidvarcomb[k1]){
1.227 brouard 7368: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7369: continue;
1.223 brouard 7370: }
1.227 brouard 7371:
1.241 brouard 7372: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"P_"),cpt,k1,nres);
1.264 brouard 7373: 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 7374: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability\" \n\
1.238 brouard 7375: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
1.211 brouard 7376: k=3; /* Offset */
1.255 brouard 7377: for (i=1; i<= nlstate ; i ++){ /* State of origin */
1.227 brouard 7378: if(i==1)
7379: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJ_"));
7380: else
7381: fprintf(ficgp,", '' ");
1.255 brouard 7382: l=(nlstate+ndeath)*(i-1)+1; /* 1, 1+ nlstate+ndeath, 1+2*(nlstate+ndeath) */
1.227 brouard 7383: fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d/($%d",k1,k+l+(cpt-1),k+l);
7384: for (j=2; j<= nlstate ; j ++)
7385: fprintf(ficgp,"+$%d",k+l+j-1);
7386: fprintf(ficgp,")) t \"prev(%d,%d)\" w l",i,cpt);
1.153 brouard 7387: } /* nlstate */
1.264 brouard 7388: fprintf(ficgp,"\nset out; unset label;\n");
1.153 brouard 7389: } /* end cpt state*/
7390: } /* end covariate */
1.227 brouard 7391:
7392:
1.220 brouard 7393: /* 7eme */
1.218 brouard 7394: if(backcast == 1){
1.217 brouard 7395: /* CV back preval stable (period) for each covariate */
1.237 brouard 7396: for (k1=1; k1<= m ; k1 ++) /* For each covariate combination if any */
7397: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 7398: if(m != 1 && TKresult[nres]!= k1)
1.237 brouard 7399: continue;
1.268 brouard 7400: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life origin state */
1.264 brouard 7401: strcpy(gplotlabel,"(");
7402: fprintf(ficgp,"\n#\n#\n#CV Back preval stable (period): 'pijb' files, covariatecombination#=%d state=%d",k1, cpt);
1.227 brouard 7403: for (k=1; k<=cptcoveff; k++){ /* For each covariate and each value */
7404: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate number corresponding to k1 combination */
7405: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7406: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
1.223 brouard 7407: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
1.227 brouard 7408: vlv= nbcode[Tvaraff[k]][lv];
7409: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 7410: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.227 brouard 7411: }
1.237 brouard 7412: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7413: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7414: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.237 brouard 7415: }
1.264 brouard 7416: strcpy(gplotlabel+strlen(gplotlabel),")");
1.227 brouard 7417: fprintf(ficgp,"\n#\n");
7418: if(invalidvarcomb[k1]){
7419: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7420: continue;
7421: }
7422:
1.241 brouard 7423: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"PB_"),cpt,k1,nres);
1.268 brouard 7424: 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 7425: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability\" \n\
1.238 brouard 7426: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
1.227 brouard 7427: k=3; /* Offset */
1.268 brouard 7428: for (i=1; i<= nlstate ; i ++){ /* State of arrival */
1.227 brouard 7429: if(i==1)
7430: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJB_"));
7431: else
7432: fprintf(ficgp,", '' ");
7433: /* l=(nlstate+ndeath)*(i-1)+1; */
1.255 brouard 7434: l=(nlstate+ndeath)*(cpt-1)+1; /* fixed for i; cpt=1 1, cpt=2 1+ nlstate+ndeath, 1+2*(nlstate+ndeath) */
1.227 brouard 7435: /* fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d/($%d",k1,k+l+(cpt-1),k+l); /\* a vérifier *\/ */
7436: /* 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 7437: fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d",k1,k+l+i-1); /* To be verified */
1.227 brouard 7438: /* for (j=2; j<= nlstate ; j ++) */
7439: /* fprintf(ficgp,"+$%d",k+l+j-1); */
7440: /* /\* fprintf(ficgp,"+$%d",k+l+j-1); *\/ */
1.268 brouard 7441: fprintf(ficgp,") t \"bprev(%d,%d)\" w l",cpt,i);
1.227 brouard 7442: } /* nlstate */
1.264 brouard 7443: fprintf(ficgp,"\nset out; unset label;\n");
1.218 brouard 7444: } /* end cpt state*/
7445: } /* end covariate */
7446: } /* End if backcast */
7447:
1.223 brouard 7448: /* 8eme */
1.218 brouard 7449: if(prevfcast==1){
7450: /* Projection from cross-sectional to stable (period) for each covariate */
7451:
1.237 brouard 7452: for (k1=1; k1<= m ; k1 ++) /* For each covariate combination if any */
7453: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 7454: if(m != 1 && TKresult[nres]!= k1)
1.237 brouard 7455: continue;
1.211 brouard 7456: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state */
1.264 brouard 7457: strcpy(gplotlabel,"(");
1.227 brouard 7458: fprintf(ficgp,"\n#\n#\n#Projection of prevalence to stable (period): 'PROJ_' files, covariatecombination#=%d state=%d",k1, cpt);
7459: for (k=1; k<=cptcoveff; k++){ /* For each correspondig covariate value */
7460: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate value corresponding to k1 combination and kth covariate */
7461: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7462: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7463: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7464: vlv= nbcode[Tvaraff[k]][lv];
7465: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 7466: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.227 brouard 7467: }
1.237 brouard 7468: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7469: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7470: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.237 brouard 7471: }
1.264 brouard 7472: strcpy(gplotlabel+strlen(gplotlabel),")");
1.227 brouard 7473: fprintf(ficgp,"\n#\n");
7474: if(invalidvarcomb[k1]){
7475: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7476: continue;
7477: }
7478:
7479: fprintf(ficgp,"# hpijx=probability over h years, hp.jx is weighted by observed prev\n ");
1.241 brouard 7480: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"PROJ_"),cpt,k1,nres);
1.264 brouard 7481: 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 7482: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Prevalence\" \n\
1.238 brouard 7483: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
1.266 brouard 7484:
7485: /* for (i=1; i<= nlstate+1 ; i ++){ /\* nlstate +1 p11 p21 p.1 *\/ */
7486: istart=nlstate+1; /* Could be one if by state, but nlstate+1 is w.i projection only */
7487: /*istart=1;*/ /* Could be one if by state, but nlstate+1 is w.i projection only */
7488: for (i=istart; i<= nlstate+1 ; i ++){ /* nlstate +1 p11 p21 p.1 */
1.227 brouard 7489: /*# V1 = 1 V2 = 0 yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
7490: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
7491: /*# yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
7492: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
1.266 brouard 7493: if(i==istart){
1.227 brouard 7494: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"F_"));
7495: }else{
7496: fprintf(ficgp,",\\\n '' ");
7497: }
7498: if(cptcoveff ==0){ /* No covariate */
7499: ioffset=2; /* Age is in 2 */
7500: /*# yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/
7501: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */
7502: /*# V1 = 1 yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/
7503: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */
7504: fprintf(ficgp," u %d:(", ioffset);
1.266 brouard 7505: if(i==nlstate+1){
7506: fprintf(ficgp," $%d/(1.-$%d)):5 t 'pw.%d' with line lc variable ", \
7507: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,cpt );
7508: fprintf(ficgp,",\\\n '' ");
7509: fprintf(ficgp," u %d:(",ioffset);
7510: fprintf(ficgp," (($5-$6) == %d ) ? $%d/(1.-$%d) : 1/0):5 with labels center not ", \
7511: offyear, \
1.268 brouard 7512: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate );
1.266 brouard 7513: }else
1.227 brouard 7514: fprintf(ficgp," $%d/(1.-$%d)) t 'p%d%d' with line ", \
7515: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,i,cpt );
7516: }else{ /* more than 2 covariates */
7517: if(cptcoveff ==1){
7518: ioffset=4; /* Age is in 4 */
7519: }else{
7520: ioffset=6; /* Age is in 6 */
7521: /*# V1 = 1 V2 = 0 yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
7522: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
7523: }
7524: fprintf(ficgp," u %d:(",ioffset);
7525: kl=0;
7526: strcpy(gplotcondition,"(");
7527: for (k=1; k<=cptcoveff; k++){ /* For each covariate writing the chain of conditions */
7528: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate value corresponding to combination k1 and covariate k */
7529: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7530: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7531: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7532: vlv= nbcode[Tvaraff[k]][lv]; /* Value of the modality of Tvaraff[k] */
7533: kl++;
7534: sprintf(gplotcondition+strlen(gplotcondition),"$%d==%d && $%d==%d " ,kl,Tvaraff[k], kl+1, nbcode[Tvaraff[k]][lv]);
7535: kl++;
7536: if(k <cptcoveff && cptcoveff>1)
7537: sprintf(gplotcondition+strlen(gplotcondition)," && ");
7538: }
7539: strcpy(gplotcondition+strlen(gplotcondition),")");
7540: /* 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 *\/ */
7541: /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */
7542: /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */
7543: /* '' 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*/
7544: if(i==nlstate+1){
1.266 brouard 7545: fprintf(ficgp,"%s ? $%d/(1.-$%d) : 1/0):5 t 'p.%d' with line lc variable", gplotcondition, \
7546: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,cpt );
7547: fprintf(ficgp,",\\\n '' ");
7548: fprintf(ficgp," u %d:(",ioffset);
7549: fprintf(ficgp,"%s && (($5-$6) == %d ) ? $%d/(1.-$%d) : 1/0):5 with labels center not ", gplotcondition, \
7550: offyear, \
1.268 brouard 7551: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate );
1.266 brouard 7552: /* '' 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 7553: }else{
7554: fprintf(ficgp,"%s ? $%d/(1.-$%d) : 1/0) t 'p%d%d' with line ", gplotcondition, \
7555: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset +1+(i-1)+(nlstate+1)*nlstate,i,cpt );
7556: }
7557: } /* end if covariate */
7558: } /* nlstate */
1.264 brouard 7559: fprintf(ficgp,"\nset out; unset label;\n");
1.223 brouard 7560: } /* end cpt state*/
7561: } /* end covariate */
7562: } /* End if prevfcast */
1.227 brouard 7563:
1.268 brouard 7564: if(backcast==1){
7565: /* Back projection from cross-sectional to stable (mixed) for each covariate */
7566:
7567: for (k1=1; k1<= m ; k1 ++) /* For each covariate combination if any */
7568: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
7569: if(m != 1 && TKresult[nres]!= k1)
7570: continue;
7571: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state */
7572: strcpy(gplotlabel,"(");
7573: fprintf(ficgp,"\n#\n#\n#Back projection of prevalence to stable (mixed) back prevalence: 'BPROJ_' files, covariatecombination#=%d originstate=%d",k1, cpt);
7574: for (k=1; k<=cptcoveff; k++){ /* For each correspondig covariate value */
7575: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate value corresponding to k1 combination and kth covariate */
7576: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7577: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7578: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7579: vlv= nbcode[Tvaraff[k]][lv];
7580: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
7581: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
7582: }
7583: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7584: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
7585: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
7586: }
7587: strcpy(gplotlabel+strlen(gplotlabel),")");
7588: fprintf(ficgp,"\n#\n");
7589: if(invalidvarcomb[k1]){
7590: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7591: continue;
7592: }
7593:
7594: fprintf(ficgp,"# hbijx=backprobability over h years, hb.jx is weighted by observed prev at destination state\n ");
7595: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"PROJB_"),cpt,k1,nres);
7596: fprintf(ficgp,"set label \"Origin alive state %d %s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",cpt,gplotlabel);
7597: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Prevalence\" \n\
7598: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
7599:
7600: /* for (i=1; i<= nlstate+1 ; i ++){ /\* nlstate +1 p11 p21 p.1 *\/ */
7601: istart=nlstate+1; /* Could be one if by state, but nlstate+1 is w.i projection only */
7602: /*istart=1;*/ /* Could be one if by state, but nlstate+1 is w.i projection only */
7603: for (i=istart; i<= nlstate+1 ; i ++){ /* nlstate +1 p11 p21 p.1 */
7604: /*# V1 = 1 V2 = 0 yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
7605: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
7606: /*# yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
7607: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
7608: if(i==istart){
7609: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"FB_"));
7610: }else{
7611: fprintf(ficgp,",\\\n '' ");
7612: }
7613: if(cptcoveff ==0){ /* No covariate */
7614: ioffset=2; /* Age is in 2 */
7615: /*# yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/
7616: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */
7617: /*# V1 = 1 yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/
7618: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */
7619: fprintf(ficgp," u %d:(", ioffset);
7620: if(i==nlstate+1){
7621: fprintf(ficgp," $%d/(1.-$%d)):5 t 'bw%d' with line lc variable ", \
7622: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,cpt );
7623: fprintf(ficgp,",\\\n '' ");
7624: fprintf(ficgp," u %d:(",ioffset);
7625: fprintf(ficgp," (($5-$6) == %d ) ? $%d : 1/0):5 with labels center not ", \
7626: offbyear, \
7627: ioffset+(cpt-1)*(nlstate+1)+1+(i-1) );
7628: }else
7629: fprintf(ficgp," $%d/(1.-$%d)) t 'b%d%d' with line ", \
7630: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,cpt,i );
7631: }else{ /* more than 2 covariates */
7632: if(cptcoveff ==1){
7633: ioffset=4; /* Age is in 4 */
7634: }else{
7635: ioffset=6; /* Age is in 6 */
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: }
7639: fprintf(ficgp," u %d:(",ioffset);
7640: kl=0;
7641: strcpy(gplotcondition,"(");
7642: for (k=1; k<=cptcoveff; k++){ /* For each covariate writing the chain of conditions */
7643: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate value corresponding to combination k1 and covariate k */
7644: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7645: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7646: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7647: vlv= nbcode[Tvaraff[k]][lv]; /* Value of the modality of Tvaraff[k] */
7648: kl++;
7649: sprintf(gplotcondition+strlen(gplotcondition),"$%d==%d && $%d==%d " ,kl,Tvaraff[k], kl+1, nbcode[Tvaraff[k]][lv]);
7650: kl++;
7651: if(k <cptcoveff && cptcoveff>1)
7652: sprintf(gplotcondition+strlen(gplotcondition)," && ");
7653: }
7654: strcpy(gplotcondition+strlen(gplotcondition),")");
7655: /* 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 *\/ */
7656: /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */
7657: /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */
7658: /* '' 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*/
7659: if(i==nlstate+1){
7660: fprintf(ficgp,"%s ? $%d : 1/0):5 t 'bw%d' with line lc variable", gplotcondition, \
7661: ioffset+(cpt-1)*(nlstate+1)+1+(i-1),cpt );
7662: fprintf(ficgp,",\\\n '' ");
7663: fprintf(ficgp," u %d:(",ioffset);
7664: /* fprintf(ficgp,"%s && (($5-$6) == %d ) ? $%d/(1.-$%d) : 1/0):5 with labels center not ", gplotcondition, \ */
7665: fprintf(ficgp,"%s && (($5-$6) == %d ) ? $%d : 1/0):5 with labels center not ", gplotcondition, \
7666: offbyear, \
7667: ioffset+(cpt-1)*(nlstate+1)+1+(i-1) );
7668: /* '' u 6:(($1==1 && $2==0 && $3==2 && $4==0) && (($5-$6) == 1947) ? $10/(1.-$22) : 1/0):5 with labels center boxed not*/
7669: }else{
7670: /* fprintf(ficgp,"%s ? $%d/(1.-$%d) : 1/0) t 'p%d%d' with line ", gplotcondition, \ */
7671: fprintf(ficgp,"%s ? $%d : 1/0) t 'b%d%d' with line ", gplotcondition, \
7672: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), cpt,i );
7673: }
7674: } /* end if covariate */
7675: } /* nlstate */
7676: fprintf(ficgp,"\nset out; unset label;\n");
7677: } /* end cpt state*/
7678: } /* end covariate */
7679: } /* End if backcast */
7680:
1.227 brouard 7681:
1.238 brouard 7682: /* 9eme writing MLE parameters */
7683: fprintf(ficgp,"\n##############\n#9eme MLE estimated parameters\n#############\n");
1.126 brouard 7684: for(i=1,jk=1; i <=nlstate; i++){
1.187 brouard 7685: fprintf(ficgp,"# initial state %d\n",i);
1.126 brouard 7686: for(k=1; k <=(nlstate+ndeath); k++){
7687: if (k != i) {
1.227 brouard 7688: fprintf(ficgp,"# current state %d\n",k);
7689: for(j=1; j <=ncovmodel; j++){
7690: fprintf(ficgp,"p%d=%f; ",jk,p[jk]);
7691: jk++;
7692: }
7693: fprintf(ficgp,"\n");
1.126 brouard 7694: }
7695: }
1.223 brouard 7696: }
1.187 brouard 7697: fprintf(ficgp,"##############\n#\n");
1.227 brouard 7698:
1.145 brouard 7699: /*goto avoid;*/
1.238 brouard 7700: /* 10eme Graphics of probabilities or incidences using written MLE parameters */
7701: fprintf(ficgp,"\n##############\n#10eme Graphics of probabilities or incidences\n#############\n");
1.187 brouard 7702: fprintf(ficgp,"# logi(p12/p11)=a12+b12*age+c12age*age+d12*V1+e12*V1*age\n");
7703: fprintf(ficgp,"# logi(p12/p11)=p1 +p2*age +p3*age*age+ p4*V1+ p5*V1*age\n");
7704: fprintf(ficgp,"# logi(p13/p11)=a13+b13*age+c13age*age+d13*V1+e13*V1*age\n");
7705: fprintf(ficgp,"# logi(p13/p11)=p6 +p7*age +p8*age*age+ p9*V1+ p10*V1*age\n");
7706: fprintf(ficgp,"# p12+p13+p14+p11=1=p11(1+exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)\n");
7707: fprintf(ficgp,"# +exp(a13+b13*age+c13age*age+d13*V1+e13*V1*age)+...)\n");
7708: fprintf(ficgp,"# p11=1/(1+exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)\n");
7709: fprintf(ficgp,"# +exp(a13+b13*age+c13age*age+d13*V1+e13*V1*age)+...)\n");
7710: fprintf(ficgp,"# p12=exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)/\n");
7711: fprintf(ficgp,"# (1+exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)\n");
7712: fprintf(ficgp,"# +exp(a13+b13*age+c13age*age+d13*V1+e13*V1*age))\n");
7713: fprintf(ficgp,"# +exp(a14+b14*age+c14age*age+d14*V1+e14*V1*age)+...)\n");
7714: fprintf(ficgp,"#\n");
1.223 brouard 7715: for(ng=1; ng<=3;ng++){ /* Number of graphics: first is logit, 2nd is probabilities, third is incidences per year*/
1.238 brouard 7716: fprintf(ficgp,"#Number of graphics: first is logit, 2nd is probabilities, third is incidences per year\n");
1.237 brouard 7717: fprintf(ficgp,"#model=%s \n",model);
1.238 brouard 7718: fprintf(ficgp,"# Type of graphic ng=%d\n",ng);
1.264 brouard 7719: fprintf(ficgp,"# k1=1 to 2^%d=%d\n",cptcoveff,m);/* to be checked */
7720: for(k1=1; k1 <=m; k1++) /* For each combination of covariate */
1.237 brouard 7721: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.264 brouard 7722: if(m != 1 && TKresult[nres]!= k1)
1.237 brouard 7723: continue;
1.264 brouard 7724: fprintf(ficgp,"\n\n# Combination of dummy k1=%d which is ",k1);
7725: strcpy(gplotlabel,"(");
7726: sprintf(gplotlabel+strlen(gplotlabel)," Dummy combination %d ",k1);
7727: for (k=1; k<=cptcoveff; k++){ /* For each correspondig covariate value */
7728: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate value corresponding to k1 combination and kth covariate */
7729: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7730: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7731: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7732: vlv= nbcode[Tvaraff[k]][lv];
7733: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
7734: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
7735: }
1.237 brouard 7736: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7737: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7738: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.237 brouard 7739: }
1.264 brouard 7740: strcpy(gplotlabel+strlen(gplotlabel),")");
1.237 brouard 7741: fprintf(ficgp,"\n#\n");
1.264 brouard 7742: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" ",subdirf2(optionfilefiname,"PE_"),k1,ng,nres);
7743: fprintf(ficgp,"\nset label \"%s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",gplotlabel);
1.223 brouard 7744: fprintf(ficgp,"\nset ter svg size 640, 480 ");
7745: if (ng==1){
7746: fprintf(ficgp,"\nset ylabel \"Value of the logit of the model\"\n"); /* exp(a12+b12*x) could be nice */
7747: fprintf(ficgp,"\nunset log y");
7748: }else if (ng==2){
7749: fprintf(ficgp,"\nset ylabel \"Probability\"\n");
7750: fprintf(ficgp,"\nset log y");
7751: }else if (ng==3){
7752: fprintf(ficgp,"\nset ylabel \"Quasi-incidence per year\"\n");
7753: fprintf(ficgp,"\nset log y");
7754: }else
7755: fprintf(ficgp,"\nunset title ");
7756: fprintf(ficgp,"\nplot [%.f:%.f] ",ageminpar,agemaxpar);
7757: i=1;
7758: for(k2=1; k2<=nlstate; k2++) {
7759: k3=i;
7760: for(k=1; k<=(nlstate+ndeath); k++) {
7761: if (k != k2){
7762: switch( ng) {
7763: case 1:
7764: if(nagesqr==0)
7765: fprintf(ficgp," p%d+p%d*x",i,i+1);
7766: else /* nagesqr =1 */
7767: fprintf(ficgp," p%d+p%d*x+p%d*x*x",i,i+1,i+1+nagesqr);
7768: break;
7769: case 2: /* ng=2 */
7770: if(nagesqr==0)
7771: fprintf(ficgp," exp(p%d+p%d*x",i,i+1);
7772: else /* nagesqr =1 */
7773: fprintf(ficgp," exp(p%d+p%d*x+p%d*x*x",i,i+1,i+1+nagesqr);
7774: break;
7775: case 3:
7776: if(nagesqr==0)
7777: fprintf(ficgp," %f*exp(p%d+p%d*x",YEARM/stepm,i,i+1);
7778: else /* nagesqr =1 */
7779: fprintf(ficgp," %f*exp(p%d+p%d*x+p%d*x*x",YEARM/stepm,i,i+1,i+1+nagesqr);
7780: break;
7781: }
7782: ij=1;/* To be checked else nbcode[0][0] wrong */
1.237 brouard 7783: ijp=1; /* product no age */
7784: /* for(j=3; j <=ncovmodel-nagesqr; j++) { */
7785: for(j=1; j <=cptcovt; j++) { /* For each covariate of the simplified model */
1.223 brouard 7786: /* printf("Tage[%d]=%d, j=%d\n", ij, Tage[ij], j); */
1.268 brouard 7787: if(cptcovage >0){ /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, 2 V5 and V1 */
7788: if(j==Tage[ij]) { /* Product by age To be looked at!!*/
7789: if(ij <=cptcovage) { /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, 2 V5 and V1 */
7790: if(DummyV[j]==0){
7791: fprintf(ficgp,"+p%d*%d*x",i+j+2+nagesqr-1,Tinvresult[nres][Tvar[j]]);;
7792: }else{ /* quantitative */
7793: fprintf(ficgp,"+p%d*%f*x",i+j+2+nagesqr-1,Tqinvresult[nres][Tvar[j]]); /* Tqinvresult in decoderesult */
7794: /* fprintf(ficgp,"+p%d*%d*x",i+j+nagesqr-1,nbcode[Tvar[j-2]][codtabm(k1,Tvar[j-2])]); */
7795: }
7796: ij++;
1.237 brouard 7797: }
1.268 brouard 7798: }
7799: }else if(cptcovprod >0){
7800: if(j==Tprod[ijp]) { /* */
7801: /* printf("Tprod[%d]=%d, j=%d\n", ij, Tprod[ijp], j); */
7802: if(ijp <=cptcovprod) { /* Product */
7803: if(DummyV[Tvard[ijp][1]]==0){/* Vn is dummy */
7804: if(DummyV[Tvard[ijp][2]]==0){/* Vn and Vm are dummy */
7805: /* 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)]); */
7806: fprintf(ficgp,"+p%d*%d*%d",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tinvresult[nres][Tvard[ijp][2]]);
7807: }else{ /* Vn is dummy and Vm is quanti */
7808: /* fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,nbcode[Tvard[ijp][1]][codtabm(k1,j)],Tqinvresult[nres][Tvard[ijp][2]]); */
7809: fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]);
7810: }
7811: }else{ /* Vn*Vm Vn is quanti */
7812: if(DummyV[Tvard[ijp][2]]==0){
7813: fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][2]],Tqinvresult[nres][Tvard[ijp][1]]);
7814: }else{ /* Both quanti */
7815: fprintf(ficgp,"+p%d*%f*%f",i+j+2+nagesqr-1,Tqinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]);
7816: }
1.237 brouard 7817: }
1.268 brouard 7818: ijp++;
1.237 brouard 7819: }
1.268 brouard 7820: } /* end Tprod */
1.237 brouard 7821: } else{ /* simple covariate */
1.264 brouard 7822: /* fprintf(ficgp,"+p%d*%d",i+j+2+nagesqr-1,nbcode[Tvar[j]][codtabm(k1,j)]); /\* Valgrind bug nbcode *\/ */
1.237 brouard 7823: if(Dummy[j]==0){
7824: fprintf(ficgp,"+p%d*%d",i+j+2+nagesqr-1,Tinvresult[nres][Tvar[j]]); /* */
7825: }else{ /* quantitative */
7826: fprintf(ficgp,"+p%d*%f",i+j+2+nagesqr-1,Tqinvresult[nres][Tvar[j]]); /* */
1.264 brouard 7827: /* fprintf(ficgp,"+p%d*%d*x",i+j+nagesqr-1,nbcode[Tvar[j-2]][codtabm(k1,Tvar[j-2])]); */
1.223 brouard 7828: }
1.237 brouard 7829: } /* end simple */
7830: } /* end j */
1.223 brouard 7831: }else{
7832: i=i-ncovmodel;
7833: if(ng !=1 ) /* For logit formula of log p11 is more difficult to get */
7834: fprintf(ficgp," (1.");
7835: }
1.227 brouard 7836:
1.223 brouard 7837: if(ng != 1){
7838: fprintf(ficgp,")/(1");
1.227 brouard 7839:
1.264 brouard 7840: for(cpt=1; cpt <=nlstate; cpt++){
1.223 brouard 7841: if(nagesqr==0)
1.264 brouard 7842: fprintf(ficgp,"+exp(p%d+p%d*x",k3+(cpt-1)*ncovmodel,k3+(cpt-1)*ncovmodel+1);
1.223 brouard 7843: else /* nagesqr =1 */
1.264 brouard 7844: 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 7845:
1.223 brouard 7846: ij=1;
7847: for(j=3; j <=ncovmodel-nagesqr; j++){
1.268 brouard 7848: if(cptcovage >0){
7849: if((j-2)==Tage[ij]) { /* Bug valgrind */
7850: if(ij <=cptcovage) { /* Bug valgrind */
7851: fprintf(ficgp,"+p%d*%d*x",k3+(cpt-1)*ncovmodel+1+j-2+nagesqr,nbcode[Tvar[j-2]][codtabm(k1,j-2)]);
7852: /* fprintf(ficgp,"+p%d*%d*x",k3+(cpt-1)*ncovmodel+1+j-2+nagesqr,nbcode[Tvar[j-2]][codtabm(k1,Tvar[j-2])]); */
7853: ij++;
7854: }
7855: }
7856: }else
7857: 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 7858: }
7859: fprintf(ficgp,")");
7860: }
7861: fprintf(ficgp,")");
7862: if(ng ==2)
7863: fprintf(ficgp," t \"p%d%d\" ", k2,k);
7864: else /* ng= 3 */
7865: fprintf(ficgp," t \"i%d%d\" ", k2,k);
7866: }else{ /* end ng <> 1 */
7867: if( k !=k2) /* logit p11 is hard to draw */
7868: fprintf(ficgp," t \"logit(p%d%d)\" ", k2,k);
7869: }
7870: if ((k+k2)!= (nlstate*2+ndeath) && ng != 1)
7871: fprintf(ficgp,",");
7872: if (ng == 1 && k!=k2 && (k+k2)!= (nlstate*2+ndeath))
7873: fprintf(ficgp,",");
7874: i=i+ncovmodel;
7875: } /* end k */
7876: } /* end k2 */
1.264 brouard 7877: fprintf(ficgp,"\n set out; unset label;\n");
7878: } /* end k1 */
1.223 brouard 7879: } /* end ng */
7880: /* avoid: */
7881: fflush(ficgp);
1.126 brouard 7882: } /* end gnuplot */
7883:
7884:
7885: /*************** Moving average **************/
1.219 brouard 7886: /* int movingaverage(double ***probs, double bage, double fage, double ***mobaverage, int mobilav, double bageout, double fageout){ */
1.222 brouard 7887: int movingaverage(double ***probs, double bage, double fage, double ***mobaverage, int mobilav){
1.218 brouard 7888:
1.222 brouard 7889: int i, cpt, cptcod;
7890: int modcovmax =1;
7891: int mobilavrange, mob;
7892: int iage=0;
7893:
1.266 brouard 7894: double sum=0., sumr=0.;
1.222 brouard 7895: double age;
1.266 brouard 7896: double *sumnewp, *sumnewm, *sumnewmr;
7897: double *agemingood, *agemaxgood;
7898: double *agemingoodr, *agemaxgoodr;
1.222 brouard 7899:
7900:
1.225 brouard 7901: /* modcovmax=2*cptcoveff;/\* Max number of modalities. We suppose */
1.222 brouard 7902: /* a covariate has 2 modalities, should be equal to ncovcombmax *\/ */
7903:
7904: sumnewp = vector(1,ncovcombmax);
7905: sumnewm = vector(1,ncovcombmax);
1.266 brouard 7906: sumnewmr = vector(1,ncovcombmax);
1.222 brouard 7907: agemingood = vector(1,ncovcombmax);
1.266 brouard 7908: agemingoodr = vector(1,ncovcombmax);
1.222 brouard 7909: agemaxgood = vector(1,ncovcombmax);
1.266 brouard 7910: agemaxgoodr = vector(1,ncovcombmax);
1.222 brouard 7911:
7912: for (cptcod=1;cptcod<=ncovcombmax;cptcod++){
1.266 brouard 7913: sumnewm[cptcod]=0.; sumnewmr[cptcod]=0.;
1.222 brouard 7914: sumnewp[cptcod]=0.;
1.266 brouard 7915: agemingood[cptcod]=0, agemingoodr[cptcod]=0;
7916: agemaxgood[cptcod]=0, agemaxgoodr[cptcod]=0;
1.222 brouard 7917: }
7918: if (cptcovn<1) ncovcombmax=1; /* At least 1 pass */
7919:
1.266 brouard 7920: if(mobilav==-1 || mobilav==1||mobilav ==3 ||mobilav==5 ||mobilav== 7){
7921: if(mobilav==1 || mobilav==-1) mobilavrange=5; /* default */
1.222 brouard 7922: else mobilavrange=mobilav;
7923: for (age=bage; age<=fage; age++)
7924: for (i=1; i<=nlstate;i++)
7925: for (cptcod=1;cptcod<=ncovcombmax;cptcod++)
7926: mobaverage[(int)age][i][cptcod]=probs[(int)age][i][cptcod];
7927: /* We keep the original values on the extreme ages bage, fage and for
7928: fage+1 and bage-1 we use a 3 terms moving average; for fage+2 bage+2
7929: we use a 5 terms etc. until the borders are no more concerned.
7930: */
7931: for (mob=3;mob <=mobilavrange;mob=mob+2){
7932: for (age=bage+(mob-1)/2; age<=fage-(mob-1)/2; age++){
1.266 brouard 7933: for (cptcod=1;cptcod<=ncovcombmax;cptcod++){
7934: sumnewm[cptcod]=0.;
7935: for (i=1; i<=nlstate;i++){
1.222 brouard 7936: mobaverage[(int)age][i][cptcod] =probs[(int)age][i][cptcod];
7937: for (cpt=1;cpt<=(mob-1)/2;cpt++){
7938: mobaverage[(int)age][i][cptcod] +=probs[(int)age-cpt][i][cptcod];
7939: mobaverage[(int)age][i][cptcod] +=probs[(int)age+cpt][i][cptcod];
7940: }
7941: mobaverage[(int)age][i][cptcod]=mobaverage[(int)age][i][cptcod]/mob;
1.266 brouard 7942: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
7943: } /* end i */
7944: if(sumnewm[cptcod] >1.e-3) mobaverage[(int)age][i][cptcod]=mobaverage[(int)age][i][cptcod]/sumnewm[cptcod]; /* Rescaling to sum one */
7945: } /* end cptcod */
1.222 brouard 7946: }/* end age */
7947: }/* end mob */
1.266 brouard 7948: }else{
7949: printf("Error internal in movingaverage, mobilav=%d.\n",mobilav);
1.222 brouard 7950: return -1;
1.266 brouard 7951: }
7952:
7953: for (cptcod=1;cptcod<=ncovcombmax;cptcod++){ /* for each combination */
1.222 brouard 7954: /* for (age=bage+(mob-1)/2; age<=fage-(mob-1)/2; age++){ */
7955: if(invalidvarcomb[cptcod]){
7956: printf("\nCombination (%d) ignored because no cases \n",cptcod);
7957: continue;
7958: }
1.219 brouard 7959:
1.266 brouard 7960: for (age=fage-(mob-1)/2; age>=bage+(mob-1)/2; age--){ /*looking for the youngest and oldest good age */
7961: sumnewm[cptcod]=0.;
7962: sumnewmr[cptcod]=0.;
7963: for (i=1; i<=nlstate;i++){
7964: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
7965: sumnewmr[cptcod]+=probs[(int)age][i][cptcod];
7966: }
7967: if(fabs(sumnewmr[cptcod] - 1.) <= 1.e-3) { /* good without smoothing */
7968: agemingoodr[cptcod]=age;
7969: }
7970: if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
7971: agemingood[cptcod]=age;
7972: }
7973: } /* age */
7974: for (age=bage+(mob-1)/2; age<=fage-(mob-1)/2; age++){ /*looking for the youngest and oldest good age */
1.222 brouard 7975: sumnewm[cptcod]=0.;
1.266 brouard 7976: sumnewmr[cptcod]=0.;
1.222 brouard 7977: for (i=1; i<=nlstate;i++){
7978: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
1.266 brouard 7979: sumnewmr[cptcod]+=probs[(int)age][i][cptcod];
7980: }
7981: if(fabs(sumnewmr[cptcod] - 1.) <= 1.e-3) { /* good without smoothing */
7982: agemaxgoodr[cptcod]=age;
1.222 brouard 7983: }
7984: if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
1.266 brouard 7985: agemaxgood[cptcod]=age;
7986: }
7987: } /* age */
7988: /* Thus we have agemingood and agemaxgood as well as goodr for raw (preobs) */
7989: /* but they will change */
7990: for (age=fage-(mob-1)/2; age>=bage; age--){/* From oldest to youngest, filling up to the youngest */
7991: sumnewm[cptcod]=0.;
7992: sumnewmr[cptcod]=0.;
7993: for (i=1; i<=nlstate;i++){
7994: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
7995: sumnewmr[cptcod]+=probs[(int)age][i][cptcod];
7996: }
7997: if(mobilav==-1){ /* Forcing raw ages if good else agemingood */
7998: if(fabs(sumnewmr[cptcod] - 1.) <= 1.e-3) { /* good without smoothing */
7999: agemaxgoodr[cptcod]=age; /* age min */
8000: for (i=1; i<=nlstate;i++)
8001: mobaverage[(int)age][i][cptcod]=probs[(int)age][i][cptcod];
8002: }else{ /* bad we change the value with the values of good ages */
8003: for (i=1; i<=nlstate;i++){
8004: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemaxgoodr[cptcod]][i][cptcod];
8005: } /* i */
8006: } /* end bad */
8007: }else{
8008: if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
8009: agemaxgood[cptcod]=age;
8010: }else{ /* bad we change the value with the values of good ages */
8011: for (i=1; i<=nlstate;i++){
8012: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemaxgood[cptcod]][i][cptcod];
8013: } /* i */
8014: } /* end bad */
8015: }/* end else */
8016: sum=0.;sumr=0.;
8017: for (i=1; i<=nlstate;i++){
8018: sum+=mobaverage[(int)age][i][cptcod];
8019: sumr+=probs[(int)age][i][cptcod];
8020: }
8021: if(fabs(sum - 1.) > 1.e-3) { /* bad */
1.268 brouard 8022: 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 8023: } /* end bad */
8024: /* else{ /\* We found some ages summing to one, we will smooth the oldest *\/ */
8025: if(fabs(sumr - 1.) > 1.e-3) { /* bad */
1.268 brouard 8026: 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 8027: } /* end bad */
8028: }/* age */
1.266 brouard 8029:
8030: for (age=bage+(mob-1)/2; age<=fage; age++){/* From youngest, finding the oldest wrong */
1.222 brouard 8031: sumnewm[cptcod]=0.;
1.266 brouard 8032: sumnewmr[cptcod]=0.;
1.222 brouard 8033: for (i=1; i<=nlstate;i++){
8034: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
1.266 brouard 8035: sumnewmr[cptcod]+=probs[(int)age][i][cptcod];
8036: }
8037: if(mobilav==-1){ /* Forcing raw ages if good else agemingood */
8038: if(fabs(sumnewmr[cptcod] - 1.) <= 1.e-3) { /* good */
8039: agemingoodr[cptcod]=age;
8040: for (i=1; i<=nlstate;i++)
8041: mobaverage[(int)age][i][cptcod]=probs[(int)age][i][cptcod];
8042: }else{ /* bad we change the value with the values of good ages */
8043: for (i=1; i<=nlstate;i++){
8044: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemingoodr[cptcod]][i][cptcod];
8045: } /* i */
8046: } /* end bad */
8047: }else{
8048: if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
8049: agemingood[cptcod]=age;
8050: }else{ /* bad */
8051: for (i=1; i<=nlstate;i++){
8052: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemingood[cptcod]][i][cptcod];
8053: } /* i */
8054: } /* end bad */
8055: }/* end else */
8056: sum=0.;sumr=0.;
8057: for (i=1; i<=nlstate;i++){
8058: sum+=mobaverage[(int)age][i][cptcod];
8059: sumr+=mobaverage[(int)age][i][cptcod];
1.222 brouard 8060: }
1.266 brouard 8061: if(fabs(sum - 1.) > 1.e-3) { /* bad */
1.268 brouard 8062: 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 8063: } /* end bad */
8064: /* else{ /\* We found some ages summing to one, we will smooth the oldest *\/ */
8065: if(fabs(sumr - 1.) > 1.e-3) { /* bad */
1.268 brouard 8066: 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 8067: } /* end bad */
8068: }/* age */
1.266 brouard 8069:
1.222 brouard 8070:
8071: for (age=bage; age<=fage; age++){
1.235 brouard 8072: /* printf("%d %d ", cptcod, (int)age); */
1.222 brouard 8073: sumnewp[cptcod]=0.;
8074: sumnewm[cptcod]=0.;
8075: for (i=1; i<=nlstate;i++){
8076: sumnewp[cptcod]+=probs[(int)age][i][cptcod];
8077: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
8078: /* printf("%.4f %.4f ",probs[(int)age][i][cptcod], mobaverage[(int)age][i][cptcod]); */
8079: }
8080: /* printf("%.4f %.4f \n",sumnewp[cptcod], sumnewm[cptcod]); */
8081: }
8082: /* printf("\n"); */
8083: /* } */
1.266 brouard 8084:
1.222 brouard 8085: /* brutal averaging */
1.266 brouard 8086: /* for (i=1; i<=nlstate;i++){ */
8087: /* for (age=1; age<=bage; age++){ */
8088: /* mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemingood[cptcod]][i][cptcod]; */
8089: /* /\* printf("age=%d i=%d cptcod=%d mobaverage=%.4f \n",(int)age,i, cptcod, mobaverage[(int)age][i][cptcod]); *\/ */
8090: /* } */
8091: /* for (age=fage; age<=AGESUP; age++){ */
8092: /* mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemaxgood[cptcod]][i][cptcod]; */
8093: /* /\* printf("age=%d i=%d cptcod=%d mobaverage=%.4f \n",(int)age,i, cptcod, mobaverage[(int)age][i][cptcod]); *\/ */
8094: /* } */
8095: /* } /\* end i status *\/ */
8096: /* for (i=nlstate+1; i<=nlstate+ndeath;i++){ */
8097: /* for (age=1; age<=AGESUP; age++){ */
8098: /* /\*printf("i=%d, age=%d, cptcod=%d\n",i, (int)age, cptcod);*\/ */
8099: /* mobaverage[(int)age][i][cptcod]=0.; */
8100: /* } */
8101: /* } */
1.222 brouard 8102: }/* end cptcod */
1.266 brouard 8103: free_vector(agemaxgoodr,1, ncovcombmax);
8104: free_vector(agemaxgood,1, ncovcombmax);
8105: free_vector(agemingood,1, ncovcombmax);
8106: free_vector(agemingoodr,1, ncovcombmax);
8107: free_vector(sumnewmr,1, ncovcombmax);
1.222 brouard 8108: free_vector(sumnewm,1, ncovcombmax);
8109: free_vector(sumnewp,1, ncovcombmax);
8110: return 0;
8111: }/* End movingaverage */
1.218 brouard 8112:
1.126 brouard 8113:
8114: /************** Forecasting ******************/
1.269 ! brouard 8115: 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 8116: /* proj1, year, month, day of starting projection
8117: agemin, agemax range of age
8118: dateprev1 dateprev2 range of dates during which prevalence is computed
8119: anproj2 year of en of projection (same day and month as proj1).
8120: */
1.267 brouard 8121: int yearp, stepsize, hstepm, nhstepm, j, k, cptcod, i, h, i1, k4, nres=0;
1.126 brouard 8122: double agec; /* generic age */
8123: double agelim, ppij, yp,yp1,yp2,jprojmean,mprojmean,anprojmean;
8124: double *popeffectif,*popcount;
8125: double ***p3mat;
1.218 brouard 8126: /* double ***mobaverage; */
1.126 brouard 8127: char fileresf[FILENAMELENGTH];
8128:
8129: agelim=AGESUP;
1.211 brouard 8130: /* Compute observed prevalence between dateprev1 and dateprev2 by counting the number of people
8131: in each health status at the date of interview (if between dateprev1 and dateprev2).
8132: We still use firstpass and lastpass as another selection.
8133: */
1.214 brouard 8134: /* freqsummary(fileres, agemin, agemax, s, agev, nlstate, imx,Tvaraff,nbcode, ncodemax,mint,anint,strstart,\ */
8135: /* firstpass, lastpass, stepm, weightopt, model); */
1.126 brouard 8136:
1.201 brouard 8137: strcpy(fileresf,"F_");
8138: strcat(fileresf,fileresu);
1.126 brouard 8139: if((ficresf=fopen(fileresf,"w"))==NULL) {
8140: printf("Problem with forecast resultfile: %s\n", fileresf);
8141: fprintf(ficlog,"Problem with forecast resultfile: %s\n", fileresf);
8142: }
1.235 brouard 8143: printf("\nComputing forecasting: result on file '%s', please wait... \n", fileresf);
8144: fprintf(ficlog,"\nComputing forecasting: result on file '%s', please wait... \n", fileresf);
1.126 brouard 8145:
1.225 brouard 8146: if (cptcoveff==0) ncodemax[cptcoveff]=1;
1.126 brouard 8147:
8148:
8149: stepsize=(int) (stepm+YEARM-1)/YEARM;
8150: if (stepm<=12) stepsize=1;
8151: if(estepm < stepm){
8152: printf ("Problem %d lower than %d\n",estepm, stepm);
8153: }
8154: else hstepm=estepm;
8155:
8156: hstepm=hstepm/stepm;
8157: yp1=modf(dateintmean,&yp);/* extracts integral of datemean in yp and
8158: fractional in yp1 */
8159: anprojmean=yp;
8160: yp2=modf((yp1*12),&yp);
8161: mprojmean=yp;
8162: yp1=modf((yp2*30.5),&yp);
8163: jprojmean=yp;
8164: if(jprojmean==0) jprojmean=1;
8165: if(mprojmean==0) jprojmean=1;
8166:
1.227 brouard 8167: i1=pow(2,cptcoveff);
1.126 brouard 8168: if (cptcovn < 1){i1=1;}
8169:
8170: fprintf(ficresf,"# Mean day of interviews %.lf/%.lf/%.lf (%.2f) between %.2f and %.2f \n",jprojmean,mprojmean,anprojmean,dateintmean,dateprev1,dateprev2);
8171:
8172: fprintf(ficresf,"#****** Routine prevforecast **\n");
1.227 brouard 8173:
1.126 brouard 8174: /* if (h==(int)(YEARM*yearp)){ */
1.235 brouard 8175: for(nres=1; nres <= nresult; nres++) /* For each resultline */
8176: for(k=1; k<=i1;k++){
1.253 brouard 8177: if(i1 != 1 && TKresult[nres]!= k)
1.235 brouard 8178: continue;
1.227 brouard 8179: if(invalidvarcomb[k]){
8180: printf("\nCombination (%d) projection ignored because no cases \n",k);
8181: continue;
8182: }
8183: fprintf(ficresf,"\n#****** hpijx=probability over h years, hp.jx is weighted by observed prev \n#");
8184: for(j=1;j<=cptcoveff;j++) {
8185: fprintf(ficresf," V%d (=) %d",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
8186: }
1.235 brouard 8187: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
1.238 brouard 8188: fprintf(ficresf," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.235 brouard 8189: }
1.227 brouard 8190: fprintf(ficresf," yearproj age");
8191: for(j=1; j<=nlstate+ndeath;j++){
8192: for(i=1; i<=nlstate;i++)
8193: fprintf(ficresf," p%d%d",i,j);
8194: fprintf(ficresf," wp.%d",j);
8195: }
8196: for (yearp=0; yearp<=(anproj2-anproj1);yearp +=stepsize) {
8197: fprintf(ficresf,"\n");
8198: fprintf(ficresf,"\n# Forecasting at date %.lf/%.lf/%.lf ",jproj1,mproj1,anproj1+yearp);
8199: for (agec=fage; agec>=(ageminpar-1); agec--){
8200: nhstepm=(int) rint((agelim-agec)*YEARM/stepm);
8201: nhstepm = nhstepm/hstepm;
8202: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
8203: oldm=oldms;savm=savms;
1.268 brouard 8204: /* We compute pii at age agec over nhstepm);*/
1.235 brouard 8205: hpxij(p3mat,nhstepm,agec,hstepm,p,nlstate,stepm,oldm,savm, k,nres);
1.268 brouard 8206: /* Then we print p3mat for h corresponding to the right agec+h*stepms=yearp */
1.227 brouard 8207: for (h=0; h<=nhstepm; h++){
8208: if (h*hstepm/YEARM*stepm ==yearp) {
1.268 brouard 8209: break;
8210: }
8211: }
8212: fprintf(ficresf,"\n");
8213: for(j=1;j<=cptcoveff;j++)
8214: fprintf(ficresf,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
8215: fprintf(ficresf,"%.f %.f ",anproj1+yearp,agec+h*hstepm/YEARM*stepm);
8216:
8217: for(j=1; j<=nlstate+ndeath;j++) {
8218: ppij=0.;
8219: for(i=1; i<=nlstate;i++) {
8220: /* if (mobilav>=1) */
1.269 ! brouard 8221: ppij=ppij+p3mat[i][j][h]*prev[(int)agec][i][k];
1.268 brouard 8222: /* else { */ /* even if mobilav==-1 we use mobaverage */
8223: /* ppij=ppij+p3mat[i][j][h]*probs[(int)(agec)][i][k]; */
8224: /* } */
8225: fprintf(ficresf," %.3f", p3mat[i][j][h]);
8226: } /* end i */
8227: fprintf(ficresf," %.3f", ppij);
8228: }/* end j */
1.227 brouard 8229: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
8230: } /* end agec */
1.266 brouard 8231: /* diffyear=(int) anproj1+yearp-ageminpar-1; */
8232: /*printf("Prevforecast %d+%d-%d=diffyear=%d\n",(int) anproj1, (int)yearp,(int)ageminpar,(int) anproj1-(int)ageminpar);*/
1.227 brouard 8233: } /* end yearp */
8234: } /* end k */
1.219 brouard 8235:
1.126 brouard 8236: fclose(ficresf);
1.215 brouard 8237: printf("End of Computing forecasting \n");
8238: fprintf(ficlog,"End of Computing forecasting\n");
8239:
1.126 brouard 8240: }
8241:
1.269 ! brouard 8242: /************** Back Forecasting ******************/
! 8243: 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 8244: /* back1, year, month, day of starting backection
8245: agemin, agemax range of age
8246: dateprev1 dateprev2 range of dates during which prevalence is computed
1.269 ! brouard 8247: anback2 year of end of backprojection (same day and month as back1).
! 8248: prevacurrent and prev are prevalences.
1.267 brouard 8249: */
8250: int yearp, stepsize, hstepm, nhstepm, j, k, cptcod, i, h, i1, k4, nres=0;
8251: double agec; /* generic age */
1.268 brouard 8252: double agelim, ppij, ppi, yp,yp1,yp2,jprojmean,mprojmean,anprojmean;
1.267 brouard 8253: double *popeffectif,*popcount;
8254: double ***p3mat;
8255: /* double ***mobaverage; */
8256: char fileresfb[FILENAMELENGTH];
8257:
1.268 brouard 8258: agelim=AGEINF;
1.267 brouard 8259: /* Compute observed prevalence between dateprev1 and dateprev2 by counting the number of people
8260: in each health status at the date of interview (if between dateprev1 and dateprev2).
8261: We still use firstpass and lastpass as another selection.
8262: */
8263: /* freqsummary(fileres, agemin, agemax, s, agev, nlstate, imx,Tvaraff,nbcode, ncodemax,mint,anint,strstart,\ */
8264: /* firstpass, lastpass, stepm, weightopt, model); */
8265:
8266: /*Do we need to compute prevalence again?*/
8267:
8268: /* prevalence(probs, ageminpar, agemax, s, agev, nlstate, imx, Tvar, nbcode, ncodemax, mint, anint, dateprev1, dateprev2, firstpass, lastpass); */
8269:
8270: strcpy(fileresfb,"FB_");
8271: strcat(fileresfb,fileresu);
8272: if((ficresfb=fopen(fileresfb,"w"))==NULL) {
8273: printf("Problem with back forecast resultfile: %s\n", fileresfb);
8274: fprintf(ficlog,"Problem with back forecast resultfile: %s\n", fileresfb);
8275: }
8276: printf("\nComputing back forecasting: result on file '%s', please wait... \n", fileresfb);
8277: fprintf(ficlog,"\nComputing back forecasting: result on file '%s', please wait... \n", fileresfb);
8278:
8279: if (cptcoveff==0) ncodemax[cptcoveff]=1;
8280:
8281:
8282: stepsize=(int) (stepm+YEARM-1)/YEARM;
8283: if (stepm<=12) stepsize=1;
8284: if(estepm < stepm){
8285: printf ("Problem %d lower than %d\n",estepm, stepm);
8286: }
8287: else hstepm=estepm;
8288:
8289: hstepm=hstepm/stepm;
8290: yp1=modf(dateintmean,&yp);/* extracts integral of datemean in yp and
8291: fractional in yp1 */
8292: anprojmean=yp;
8293: yp2=modf((yp1*12),&yp);
8294: mprojmean=yp;
8295: yp1=modf((yp2*30.5),&yp);
8296: jprojmean=yp;
8297: if(jprojmean==0) jprojmean=1;
8298: if(mprojmean==0) jprojmean=1;
8299:
8300: i1=pow(2,cptcoveff);
8301: if (cptcovn < 1){i1=1;}
8302:
8303: fprintf(ficresfb,"# Mean day of interviews %.lf/%.lf/%.lf (%.2f) between %.2f and %.2f \n",jprojmean,mprojmean,anprojmean,dateintmean,dateprev1,dateprev2);
1.268 brouard 8304: printf("# Mean day of interviews %.lf/%.lf/%.lf (%.2f) between %.2f and %.2f \n",jprojmean,mprojmean,anprojmean,dateintmean,dateprev1,dateprev2);
1.267 brouard 8305:
8306: fprintf(ficresfb,"#****** Routine prevbackforecast **\n");
8307:
8308: for(nres=1; nres <= nresult; nres++) /* For each resultline */
8309: for(k=1; k<=i1;k++){
8310: if(i1 != 1 && TKresult[nres]!= k)
8311: continue;
8312: if(invalidvarcomb[k]){
8313: printf("\nCombination (%d) projection ignored because no cases \n",k);
8314: continue;
8315: }
1.268 brouard 8316: fprintf(ficresfb,"\n#****** hbijx=probability over h years, hb.jx is weighted by observed prev \n#");
1.267 brouard 8317: for(j=1;j<=cptcoveff;j++) {
8318: fprintf(ficresfb," V%d (=) %d",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
8319: }
8320: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
8321: fprintf(ficresf," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
8322: }
8323: fprintf(ficresfb," yearbproj age");
8324: for(j=1; j<=nlstate+ndeath;j++){
8325: for(i=1; i<=nlstate;i++)
1.268 brouard 8326: fprintf(ficresfb," b%d%d",i,j);
8327: fprintf(ficresfb," b.%d",j);
1.267 brouard 8328: }
8329: for (yearp=0; yearp>=(anback2-anback1);yearp -=stepsize) {
8330: /* for (yearp=0; yearp<=(anproj2-anproj1);yearp +=stepsize) { */
8331: fprintf(ficresfb,"\n");
8332: fprintf(ficresfb,"\n# Back Forecasting at date %.lf/%.lf/%.lf ",jback1,mback1,anback1+yearp);
1.269 ! brouard 8333: /* printf("\n# Back Forecasting at date %.lf/%.lf/%.lf ",jback1,mback1,anback1+yearp); */
1.268 brouard 8334: for (agec=bage; agec<=agemax-1; agec++){ /* testing */
8335: /* We compute bij at age agec over nhstepm, nhstepm decreases when agec increases because of agemax;*/
8336: nhstepm=(int) rint((agec-agelim)*YEARM/stepm);
1.267 brouard 8337: nhstepm = nhstepm/hstepm;
8338: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
8339: oldm=oldms;savm=savms;
1.268 brouard 8340: /* computes hbxij at age agec over 1 to nhstepm */
1.267 brouard 8341: hbxij(p3mat,nhstepm,agec,hstepm,p,prevacurrent,nlstate,stepm, k, nres);
1.268 brouard 8342: /* hpxij(p3mat,nhstepm,agec,hstepm,p, nlstate,stepm,oldm,savm, k,nres); */
8343: /* Then we print p3mat for h corresponding to the right agec+h*stepms=yearp */
8344: /* printf(" agec=%.2f\n",agec);fflush(stdout); */
1.267 brouard 8345: for (h=0; h<=nhstepm; h++){
1.268 brouard 8346: if (h*hstepm/YEARM*stepm ==-yearp) {
8347: break;
8348: }
8349: }
8350: fprintf(ficresfb,"\n");
8351: for(j=1;j<=cptcoveff;j++)
8352: fprintf(ficresfb,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
8353: fprintf(ficresfb,"%.f %.f ",anback1+yearp,agec-h*hstepm/YEARM*stepm);
8354: for(i=1; i<=nlstate+ndeath;i++) {
8355: ppij=0.;ppi=0.;
8356: for(j=1; j<=nlstate;j++) {
8357: /* if (mobilav==1) */
1.269 ! brouard 8358: ppij=ppij+p3mat[i][j][h]*prevacurrent[(int)agec][j][k];
! 8359: ppi=ppi+prevacurrent[(int)agec][j][k];
! 8360: /* ppij=ppij+p3mat[i][j][h]*mobaverage[(int)agec][j][k]; */
! 8361: /* ppi=ppi+mobaverage[(int)agec][j][k]; */
1.267 brouard 8362: /* else { */
8363: /* ppij=ppij+p3mat[i][j][h]*probs[(int)(agec)][i][k]; */
8364: /* } */
1.268 brouard 8365: fprintf(ficresfb," %.3f", p3mat[i][j][h]);
8366: } /* end j */
8367: if(ppi <0.99){
8368: printf("Error in prevbackforecast, prevalence doesn't sum to 1 for state %d: %3f\n",i, ppi);
8369: fprintf(ficlog,"Error in prevbackforecast, prevalence doesn't sum to 1 for state %d: %3f\n",i, ppi);
8370: }
8371: fprintf(ficresfb," %.3f", ppij);
8372: }/* end j */
1.267 brouard 8373: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
8374: } /* end agec */
8375: } /* end yearp */
8376: } /* end k */
1.217 brouard 8377:
1.267 brouard 8378: /* if (mobilav!=0) free_ma3x(mobaverage,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
1.217 brouard 8379:
1.267 brouard 8380: fclose(ficresfb);
8381: printf("End of Computing Back forecasting \n");
8382: fprintf(ficlog,"End of Computing Back forecasting\n");
1.218 brouard 8383:
1.267 brouard 8384: }
1.217 brouard 8385:
1.269 ! brouard 8386: /* Variance of prevalence limit: varprlim */
! 8387: 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){
! 8388: /*------- Variance of period (stable) prevalence------*/
! 8389:
! 8390: char fileresvpl[FILENAMELENGTH];
! 8391: FILE *ficresvpl;
! 8392: double **oldm, **savm;
! 8393: double **varpl; /* Variances of prevalence limits by age */
! 8394: int i1, k, nres, j ;
! 8395:
! 8396: strcpy(fileresvpl,"VPL_");
! 8397: strcat(fileresvpl,fileresu);
! 8398: if((ficresvpl=fopen(fileresvpl,"w"))==NULL) {
! 8399: printf("Problem with variance of period (stable) prevalence resultfile: %s\n", fileresvpl);
! 8400: exit(0);
! 8401: }
! 8402: printf("Computing Variance-covariance of period (stable) prevalence: file '%s' ...", fileresvpl);fflush(stdout);
! 8403: fprintf(ficlog, "Computing Variance-covariance of period (stable) prevalence: file '%s' ...", fileresvpl);fflush(ficlog);
! 8404:
! 8405: /*for(cptcov=1,k=0;cptcov<=i1;cptcov++){
! 8406: for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){*/
! 8407:
! 8408: i1=pow(2,cptcoveff);
! 8409: if (cptcovn < 1){i1=1;}
! 8410:
! 8411: for(nres=1; nres <= nresult; nres++) /* For each resultline */
! 8412: for(k=1; k<=i1;k++){
! 8413: if(i1 != 1 && TKresult[nres]!= k)
! 8414: continue;
! 8415: fprintf(ficresvpl,"\n#****** ");
! 8416: printf("\n#****** ");
! 8417: fprintf(ficlog,"\n#****** ");
! 8418: for(j=1;j<=cptcoveff;j++) {
! 8419: fprintf(ficresvpl,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
! 8420: fprintf(ficlog,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
! 8421: printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
! 8422: }
! 8423: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
! 8424: printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
! 8425: fprintf(ficresvpl," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
! 8426: fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
! 8427: }
! 8428: fprintf(ficresvpl,"******\n");
! 8429: printf("******\n");
! 8430: fprintf(ficlog,"******\n");
! 8431:
! 8432: varpl=matrix(1,nlstate,(int) bage, (int) fage);
! 8433: oldm=oldms;savm=savms;
! 8434: varprevlim(fileresvpl, ficresvpl, varpl, matcov, p, delti, nlstate, stepm, (int) bage, (int) fage, oldm, savm, prlim, ftolpl, ncvyearp, k, strstart, nres);
! 8435: free_matrix(varpl,1,nlstate,(int) bage, (int)fage);
! 8436: /*}*/
! 8437: }
! 8438:
! 8439: fclose(ficresvpl);
! 8440: printf("done variance-covariance of period prevalence\n");fflush(stdout);
! 8441: fprintf(ficlog,"done variance-covariance of period prevalence\n");fflush(ficlog);
! 8442:
! 8443: }
! 8444: /* Variance of back prevalence: varbprlim */
! 8445: 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){
! 8446: /*------- Variance of back (stable) prevalence------*/
! 8447:
! 8448: char fileresvbl[FILENAMELENGTH];
! 8449: FILE *ficresvbl;
! 8450:
! 8451: double **oldm, **savm;
! 8452: double **varbpl; /* Variances of back prevalence limits by age */
! 8453: int i1, k, nres, j ;
! 8454:
! 8455: strcpy(fileresvbl,"VBL_");
! 8456: strcat(fileresvbl,fileresu);
! 8457: if((ficresvbl=fopen(fileresvbl,"w"))==NULL) {
! 8458: printf("Problem with variance of back (stable) prevalence resultfile: %s\n", fileresvbl);
! 8459: exit(0);
! 8460: }
! 8461: printf("Computing Variance-covariance of back (stable) prevalence: file '%s' ...", fileresvbl);fflush(stdout);
! 8462: fprintf(ficlog, "Computing Variance-covariance of back (stable) prevalence: file '%s' ...", fileresvbl);fflush(ficlog);
! 8463:
! 8464:
! 8465: i1=pow(2,cptcoveff);
! 8466: if (cptcovn < 1){i1=1;}
! 8467:
! 8468: for(nres=1; nres <= nresult; nres++) /* For each resultline */
! 8469: for(k=1; k<=i1;k++){
! 8470: if(i1 != 1 && TKresult[nres]!= k)
! 8471: continue;
! 8472: fprintf(ficresvbl,"\n#****** ");
! 8473: printf("\n#****** ");
! 8474: fprintf(ficlog,"\n#****** ");
! 8475: for(j=1;j<=cptcoveff;j++) {
! 8476: fprintf(ficresvbl,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
! 8477: fprintf(ficlog,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
! 8478: printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
! 8479: }
! 8480: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
! 8481: printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
! 8482: fprintf(ficresvbl," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
! 8483: fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
! 8484: }
! 8485: fprintf(ficresvbl,"******\n");
! 8486: printf("******\n");
! 8487: fprintf(ficlog,"******\n");
! 8488:
! 8489: varbpl=matrix(1,nlstate,(int) bage, (int) fage);
! 8490: oldm=oldms;savm=savms;
! 8491:
! 8492: varbrevlim(fileresvbl, ficresvbl, varbpl, matcov, p, delti, nlstate, stepm, (int) bage, (int) fage, oldm, savm, bprlim, ftolpl, mobilavproj, ncvyearp, k, strstart, nres);
! 8493: free_matrix(varbpl,1,nlstate,(int) bage, (int)fage);
! 8494: /*}*/
! 8495: }
! 8496:
! 8497: fclose(ficresvbl);
! 8498: printf("done variance-covariance of back prevalence\n");fflush(stdout);
! 8499: fprintf(ficlog,"done variance-covariance of back prevalence\n");fflush(ficlog);
! 8500:
! 8501: } /* End of varbprlim */
! 8502:
1.126 brouard 8503: /************** Forecasting *****not tested NB*************/
1.227 brouard 8504: /* 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 8505:
1.227 brouard 8506: /* int cpt, stepsize, hstepm, nhstepm, j,k,c, cptcod, i,h; */
8507: /* int *popage; */
8508: /* double calagedatem, agelim, kk1, kk2; */
8509: /* double *popeffectif,*popcount; */
8510: /* double ***p3mat,***tabpop,***tabpopprev; */
8511: /* /\* double ***mobaverage; *\/ */
8512: /* char filerespop[FILENAMELENGTH]; */
1.126 brouard 8513:
1.227 brouard 8514: /* tabpop= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
8515: /* tabpopprev= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
8516: /* agelim=AGESUP; */
8517: /* calagedatem=(anpyram+mpyram/12.+jpyram/365.-dateintmean)*YEARM; */
1.126 brouard 8518:
1.227 brouard 8519: /* prevalence(probs, ageminpar, agemax, s, agev, nlstate, imx, Tvar, nbcode, ncodemax, mint, anint, dateprev1, dateprev2, firstpass, lastpass); */
1.126 brouard 8520:
8521:
1.227 brouard 8522: /* strcpy(filerespop,"POP_"); */
8523: /* strcat(filerespop,fileresu); */
8524: /* if((ficrespop=fopen(filerespop,"w"))==NULL) { */
8525: /* printf("Problem with forecast resultfile: %s\n", filerespop); */
8526: /* fprintf(ficlog,"Problem with forecast resultfile: %s\n", filerespop); */
8527: /* } */
8528: /* printf("Computing forecasting: result on file '%s' \n", filerespop); */
8529: /* fprintf(ficlog,"Computing forecasting: result on file '%s' \n", filerespop); */
1.126 brouard 8530:
1.227 brouard 8531: /* if (cptcoveff==0) ncodemax[cptcoveff]=1; */
1.126 brouard 8532:
1.227 brouard 8533: /* /\* if (mobilav!=0) { *\/ */
8534: /* /\* mobaverage= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); *\/ */
8535: /* /\* if (movingaverage(probs, ageminpar, fage, mobaverage,mobilav)!=0){ *\/ */
8536: /* /\* fprintf(ficlog," Error in movingaverage mobilav=%d\n",mobilav); *\/ */
8537: /* /\* printf(" Error in movingaverage mobilav=%d\n",mobilav); *\/ */
8538: /* /\* } *\/ */
8539: /* /\* } *\/ */
1.126 brouard 8540:
1.227 brouard 8541: /* stepsize=(int) (stepm+YEARM-1)/YEARM; */
8542: /* if (stepm<=12) stepsize=1; */
1.126 brouard 8543:
1.227 brouard 8544: /* agelim=AGESUP; */
1.126 brouard 8545:
1.227 brouard 8546: /* hstepm=1; */
8547: /* hstepm=hstepm/stepm; */
1.218 brouard 8548:
1.227 brouard 8549: /* if (popforecast==1) { */
8550: /* if((ficpop=fopen(popfile,"r"))==NULL) { */
8551: /* printf("Problem with population file : %s\n",popfile);exit(0); */
8552: /* fprintf(ficlog,"Problem with population file : %s\n",popfile);exit(0); */
8553: /* } */
8554: /* popage=ivector(0,AGESUP); */
8555: /* popeffectif=vector(0,AGESUP); */
8556: /* popcount=vector(0,AGESUP); */
1.126 brouard 8557:
1.227 brouard 8558: /* i=1; */
8559: /* while ((c=fscanf(ficpop,"%d %lf\n",&popage[i],&popcount[i])) != EOF) i=i+1; */
1.218 brouard 8560:
1.227 brouard 8561: /* imx=i; */
8562: /* for (i=1; i<imx;i++) popeffectif[popage[i]]=popcount[i]; */
8563: /* } */
1.218 brouard 8564:
1.227 brouard 8565: /* for(cptcov=1,k=0;cptcov<=i2;cptcov++){ */
8566: /* for(cptcod=1;cptcod<=ncodemax[cptcoveff];cptcod++){ */
8567: /* k=k+1; */
8568: /* fprintf(ficrespop,"\n#******"); */
8569: /* for(j=1;j<=cptcoveff;j++) { */
8570: /* fprintf(ficrespop," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]); */
8571: /* } */
8572: /* fprintf(ficrespop,"******\n"); */
8573: /* fprintf(ficrespop,"# Age"); */
8574: /* for(j=1; j<=nlstate+ndeath;j++) fprintf(ficrespop," P.%d",j); */
8575: /* if (popforecast==1) fprintf(ficrespop," [Population]"); */
1.126 brouard 8576:
1.227 brouard 8577: /* for (cpt=0; cpt<=0;cpt++) { */
8578: /* fprintf(ficrespop,"\n\n# Forecasting at date %.lf/%.lf/%.lf ",jpyram,mpyram,anpyram+cpt); */
1.126 brouard 8579:
1.227 brouard 8580: /* for (agedeb=(fage-((int)calagedatem %12/12.)); agedeb>=(ageminpar-((int)calagedatem %12)/12.); agedeb--){ */
8581: /* nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); */
8582: /* nhstepm = nhstepm/hstepm; */
1.126 brouard 8583:
1.227 brouard 8584: /* p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
8585: /* oldm=oldms;savm=savms; */
8586: /* hpxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k); */
1.218 brouard 8587:
1.227 brouard 8588: /* for (h=0; h<=nhstepm; h++){ */
8589: /* if (h==(int) (calagedatem+YEARM*cpt)) { */
8590: /* fprintf(ficrespop,"\n %3.f ",agedeb+h*hstepm/YEARM*stepm); */
8591: /* } */
8592: /* for(j=1; j<=nlstate+ndeath;j++) { */
8593: /* kk1=0.;kk2=0; */
8594: /* for(i=1; i<=nlstate;i++) { */
8595: /* if (mobilav==1) */
8596: /* kk1=kk1+p3mat[i][j][h]*mobaverage[(int)agedeb+1][i][cptcod]; */
8597: /* else { */
8598: /* kk1=kk1+p3mat[i][j][h]*probs[(int)(agedeb+1)][i][cptcod]; */
8599: /* } */
8600: /* } */
8601: /* if (h==(int)(calagedatem+12*cpt)){ */
8602: /* tabpop[(int)(agedeb)][j][cptcod]=kk1; */
8603: /* /\*fprintf(ficrespop," %.3f", kk1); */
8604: /* if (popforecast==1) fprintf(ficrespop," [%.f]", kk1*popeffectif[(int)agedeb+1]);*\/ */
8605: /* } */
8606: /* } */
8607: /* for(i=1; i<=nlstate;i++){ */
8608: /* kk1=0.; */
8609: /* for(j=1; j<=nlstate;j++){ */
8610: /* kk1= kk1+tabpop[(int)(agedeb)][j][cptcod]; */
8611: /* } */
8612: /* tabpopprev[(int)(agedeb)][i][cptcod]=tabpop[(int)(agedeb)][i][cptcod]/kk1*popeffectif[(int)(agedeb+(calagedatem+12*cpt)*hstepm/YEARM*stepm-1)]; */
8613: /* } */
1.218 brouard 8614:
1.227 brouard 8615: /* if (h==(int)(calagedatem+12*cpt)) */
8616: /* for(j=1; j<=nlstate;j++) */
8617: /* fprintf(ficrespop," %15.2f",tabpopprev[(int)(agedeb+1)][j][cptcod]); */
8618: /* } */
8619: /* free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
8620: /* } */
8621: /* } */
1.218 brouard 8622:
1.227 brouard 8623: /* /\******\/ */
1.218 brouard 8624:
1.227 brouard 8625: /* for (cpt=1; cpt<=(anpyram1-anpyram);cpt++) { */
8626: /* fprintf(ficrespop,"\n\n# Forecasting at date %.lf/%.lf/%.lf ",jpyram,mpyram,anpyram+cpt); */
8627: /* for (agedeb=(fage-((int)calagedatem %12/12.)); agedeb>=(ageminpar-((int)calagedatem %12)/12.); agedeb--){ */
8628: /* nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); */
8629: /* nhstepm = nhstepm/hstepm; */
1.126 brouard 8630:
1.227 brouard 8631: /* p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
8632: /* oldm=oldms;savm=savms; */
8633: /* hpxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k); */
8634: /* for (h=0; h<=nhstepm; h++){ */
8635: /* if (h==(int) (calagedatem+YEARM*cpt)) { */
8636: /* fprintf(ficresf,"\n %3.f ",agedeb+h*hstepm/YEARM*stepm); */
8637: /* } */
8638: /* for(j=1; j<=nlstate+ndeath;j++) { */
8639: /* kk1=0.;kk2=0; */
8640: /* for(i=1; i<=nlstate;i++) { */
8641: /* kk1=kk1+p3mat[i][j][h]*tabpopprev[(int)agedeb+1][i][cptcod]; */
8642: /* } */
8643: /* if (h==(int)(calagedatem+12*cpt)) fprintf(ficresf," %15.2f", kk1); */
8644: /* } */
8645: /* } */
8646: /* free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
8647: /* } */
8648: /* } */
8649: /* } */
8650: /* } */
1.218 brouard 8651:
1.227 brouard 8652: /* /\* if (mobilav!=0) free_ma3x(mobaverage,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); *\/ */
1.218 brouard 8653:
1.227 brouard 8654: /* if (popforecast==1) { */
8655: /* free_ivector(popage,0,AGESUP); */
8656: /* free_vector(popeffectif,0,AGESUP); */
8657: /* free_vector(popcount,0,AGESUP); */
8658: /* } */
8659: /* free_ma3x(tabpop,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
8660: /* free_ma3x(tabpopprev,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
8661: /* fclose(ficrespop); */
8662: /* } /\* End of popforecast *\/ */
1.218 brouard 8663:
1.126 brouard 8664: int fileappend(FILE *fichier, char *optionfich)
8665: {
8666: if((fichier=fopen(optionfich,"a"))==NULL) {
8667: printf("Problem with file: %s\n", optionfich);
8668: fprintf(ficlog,"Problem with file: %s\n", optionfich);
8669: return (0);
8670: }
8671: fflush(fichier);
8672: return (1);
8673: }
8674:
8675:
8676: /**************** function prwizard **********************/
8677: void prwizard(int ncovmodel, int nlstate, int ndeath, char model[], FILE *ficparo)
8678: {
8679:
8680: /* Wizard to print covariance matrix template */
8681:
1.164 brouard 8682: char ca[32], cb[32];
8683: int i,j, k, li, lj, lk, ll, jj, npar, itimes;
1.126 brouard 8684: int numlinepar;
8685:
8686: printf("# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
8687: fprintf(ficparo,"# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
8688: for(i=1; i <=nlstate; i++){
8689: jj=0;
8690: for(j=1; j <=nlstate+ndeath; j++){
8691: if(j==i) continue;
8692: jj++;
8693: /*ca[0]= k+'a'-1;ca[1]='\0';*/
8694: printf("%1d%1d",i,j);
8695: fprintf(ficparo,"%1d%1d",i,j);
8696: for(k=1; k<=ncovmodel;k++){
8697: /* printf(" %lf",param[i][j][k]); */
8698: /* fprintf(ficparo," %lf",param[i][j][k]); */
8699: printf(" 0.");
8700: fprintf(ficparo," 0.");
8701: }
8702: printf("\n");
8703: fprintf(ficparo,"\n");
8704: }
8705: }
8706: printf("# Scales (for hessian or gradient estimation)\n");
8707: fprintf(ficparo,"# Scales (for hessian or gradient estimation)\n");
8708: npar= (nlstate+ndeath-1)*nlstate*ncovmodel; /* Number of parameters*/
8709: for(i=1; i <=nlstate; i++){
8710: jj=0;
8711: for(j=1; j <=nlstate+ndeath; j++){
8712: if(j==i) continue;
8713: jj++;
8714: fprintf(ficparo,"%1d%1d",i,j);
8715: printf("%1d%1d",i,j);
8716: fflush(stdout);
8717: for(k=1; k<=ncovmodel;k++){
8718: /* printf(" %le",delti3[i][j][k]); */
8719: /* fprintf(ficparo," %le",delti3[i][j][k]); */
8720: printf(" 0.");
8721: fprintf(ficparo," 0.");
8722: }
8723: numlinepar++;
8724: printf("\n");
8725: fprintf(ficparo,"\n");
8726: }
8727: }
8728: printf("# Covariance matrix\n");
8729: /* # 121 Var(a12)\n\ */
8730: /* # 122 Cov(b12,a12) Var(b12)\n\ */
8731: /* # 131 Cov(a13,a12) Cov(a13,b12, Var(a13)\n\ */
8732: /* # 132 Cov(b13,a12) Cov(b13,b12, Cov(b13,a13) Var(b13)\n\ */
8733: /* # 212 Cov(a21,a12) Cov(a21,b12, Cov(a21,a13) Cov(a21,b13) Var(a21)\n\ */
8734: /* # 212 Cov(b21,a12) Cov(b21,b12, Cov(b21,a13) Cov(b21,b13) Cov(b21,a21) Var(b21)\n\ */
8735: /* # 232 Cov(a23,a12) Cov(a23,b12, Cov(a23,a13) Cov(a23,b13) Cov(a23,a21) Cov(a23,b21) Var(a23)\n\ */
8736: /* # 232 Cov(b23,a12) Cov(b23,b12) ... Var (b23)\n" */
8737: fflush(stdout);
8738: fprintf(ficparo,"# Covariance matrix\n");
8739: /* # 121 Var(a12)\n\ */
8740: /* # 122 Cov(b12,a12) Var(b12)\n\ */
8741: /* # ...\n\ */
8742: /* # 232 Cov(b23,a12) Cov(b23,b12) ... Var (b23)\n" */
8743:
8744: for(itimes=1;itimes<=2;itimes++){
8745: jj=0;
8746: for(i=1; i <=nlstate; i++){
8747: for(j=1; j <=nlstate+ndeath; j++){
8748: if(j==i) continue;
8749: for(k=1; k<=ncovmodel;k++){
8750: jj++;
8751: ca[0]= k+'a'-1;ca[1]='\0';
8752: if(itimes==1){
8753: printf("#%1d%1d%d",i,j,k);
8754: fprintf(ficparo,"#%1d%1d%d",i,j,k);
8755: }else{
8756: printf("%1d%1d%d",i,j,k);
8757: fprintf(ficparo,"%1d%1d%d",i,j,k);
8758: /* printf(" %.5le",matcov[i][j]); */
8759: }
8760: ll=0;
8761: for(li=1;li <=nlstate; li++){
8762: for(lj=1;lj <=nlstate+ndeath; lj++){
8763: if(lj==li) continue;
8764: for(lk=1;lk<=ncovmodel;lk++){
8765: ll++;
8766: if(ll<=jj){
8767: cb[0]= lk +'a'-1;cb[1]='\0';
8768: if(ll<jj){
8769: if(itimes==1){
8770: printf(" Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
8771: fprintf(ficparo," Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
8772: }else{
8773: printf(" 0.");
8774: fprintf(ficparo," 0.");
8775: }
8776: }else{
8777: if(itimes==1){
8778: printf(" Var(%s%1d%1d)",ca,i,j);
8779: fprintf(ficparo," Var(%s%1d%1d)",ca,i,j);
8780: }else{
8781: printf(" 0.");
8782: fprintf(ficparo," 0.");
8783: }
8784: }
8785: }
8786: } /* end lk */
8787: } /* end lj */
8788: } /* end li */
8789: printf("\n");
8790: fprintf(ficparo,"\n");
8791: numlinepar++;
8792: } /* end k*/
8793: } /*end j */
8794: } /* end i */
8795: } /* end itimes */
8796:
8797: } /* end of prwizard */
8798: /******************* Gompertz Likelihood ******************************/
8799: double gompertz(double x[])
8800: {
8801: double A,B,L=0.0,sump=0.,num=0.;
8802: int i,n=0; /* n is the size of the sample */
8803:
1.220 brouard 8804: for (i=1;i<=imx ; i++) {
1.126 brouard 8805: sump=sump+weight[i];
8806: /* sump=sump+1;*/
8807: num=num+1;
8808: }
8809:
8810:
8811: /* for (i=0; i<=imx; i++)
8812: 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]);*/
8813:
8814: for (i=1;i<=imx ; i++)
8815: {
8816: if (cens[i] == 1 && wav[i]>1)
8817: A=-x[1]/(x[2])*(exp(x[2]*(agecens[i]-agegomp))-exp(x[2]*(ageexmed[i]-agegomp)));
8818:
8819: if (cens[i] == 0 && wav[i]>1)
8820: A=-x[1]/(x[2])*(exp(x[2]*(agedc[i]-agegomp))-exp(x[2]*(ageexmed[i]-agegomp)))
8821: +log(x[1]/YEARM)+x[2]*(agedc[i]-agegomp)+log(YEARM);
8822:
8823: /*if (wav[i] > 1 && agecens[i] > 15) {*/ /* ??? */
8824: if (wav[i] > 1 ) { /* ??? */
8825: L=L+A*weight[i];
8826: /* 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]);*/
8827: }
8828: }
8829:
8830: /*printf("x1=%2.9f x2=%2.9f x3=%2.9f L=%f\n",x[1],x[2],x[3],L);*/
8831:
8832: return -2*L*num/sump;
8833: }
8834:
1.136 brouard 8835: #ifdef GSL
8836: /******************* Gompertz_f Likelihood ******************************/
8837: double gompertz_f(const gsl_vector *v, void *params)
8838: {
8839: double A,B,LL=0.0,sump=0.,num=0.;
8840: double *x= (double *) v->data;
8841: int i,n=0; /* n is the size of the sample */
8842:
8843: for (i=0;i<=imx-1 ; i++) {
8844: sump=sump+weight[i];
8845: /* sump=sump+1;*/
8846: num=num+1;
8847: }
8848:
8849:
8850: /* for (i=0; i<=imx; i++)
8851: 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]);*/
8852: printf("x[0]=%lf x[1]=%lf\n",x[0],x[1]);
8853: for (i=1;i<=imx ; i++)
8854: {
8855: if (cens[i] == 1 && wav[i]>1)
8856: A=-x[0]/(x[1])*(exp(x[1]*(agecens[i]-agegomp))-exp(x[1]*(ageexmed[i]-agegomp)));
8857:
8858: if (cens[i] == 0 && wav[i]>1)
8859: A=-x[0]/(x[1])*(exp(x[1]*(agedc[i]-agegomp))-exp(x[1]*(ageexmed[i]-agegomp)))
8860: +log(x[0]/YEARM)+x[1]*(agedc[i]-agegomp)+log(YEARM);
8861:
8862: /*if (wav[i] > 1 && agecens[i] > 15) {*/ /* ??? */
8863: if (wav[i] > 1 ) { /* ??? */
8864: LL=LL+A*weight[i];
8865: /* 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]);*/
8866: }
8867: }
8868:
8869: /*printf("x1=%2.9f x2=%2.9f x3=%2.9f L=%f\n",x[1],x[2],x[3],L);*/
8870: printf("x[0]=%lf x[1]=%lf -2*LL*num/sump=%lf\n",x[0],x[1],-2*LL*num/sump);
8871:
8872: return -2*LL*num/sump;
8873: }
8874: #endif
8875:
1.126 brouard 8876: /******************* Printing html file ***********/
1.201 brouard 8877: void printinghtmlmort(char fileresu[], char title[], char datafile[], int firstpass, \
1.126 brouard 8878: int lastpass, int stepm, int weightopt, char model[],\
8879: int imx, double p[],double **matcov,double agemortsup){
8880: int i,k;
8881:
8882: fprintf(fichtm,"<ul><li><h4>Result files </h4>\n Force of mortality. Parameters of the Gompertz fit (with confidence interval in brackets):<br>");
8883: fprintf(fichtm," mu(age) =%lf*exp(%lf*(age-%d)) per year<br><br>",p[1],p[2],agegomp);
8884: for (i=1;i<=2;i++)
8885: 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 8886: fprintf(fichtm,"<br><br><img src=\"graphmort.svg\">");
1.126 brouard 8887: fprintf(fichtm,"</ul>");
8888:
8889: fprintf(fichtm,"<ul><li><h4>Life table</h4>\n <br>");
8890:
8891: 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>");
8892:
8893: for (k=agegomp;k<(agemortsup-2);k++)
8894: 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]);
8895:
8896:
8897: fflush(fichtm);
8898: }
8899:
8900: /******************* Gnuplot file **************/
1.201 brouard 8901: void printinggnuplotmort(char fileresu[], char optionfilefiname[], double ageminpar, double agemaxpar, double fage , char pathc[], double p[]){
1.126 brouard 8902:
8903: char dirfileres[132],optfileres[132];
1.164 brouard 8904:
1.126 brouard 8905: int ng;
8906:
8907:
8908: /*#ifdef windows */
8909: fprintf(ficgp,"cd \"%s\" \n",pathc);
8910: /*#endif */
8911:
8912:
8913: strcpy(dirfileres,optionfilefiname);
8914: strcpy(optfileres,"vpl");
1.199 brouard 8915: fprintf(ficgp,"set out \"graphmort.svg\"\n ");
1.126 brouard 8916: fprintf(ficgp,"set xlabel \"Age\"\n set ylabel \"Force of mortality (per year)\" \n ");
1.199 brouard 8917: fprintf(ficgp, "set ter svg size 640, 480\n set log y\n");
1.145 brouard 8918: /* fprintf(ficgp, "set size 0.65,0.65\n"); */
1.126 brouard 8919: fprintf(ficgp,"plot [%d:100] %lf*exp(%lf*(x-%d))",agegomp,p[1],p[2],agegomp);
8920:
8921: }
8922:
1.136 brouard 8923: int readdata(char datafile[], int firstobs, int lastobs, int *imax)
8924: {
1.126 brouard 8925:
1.136 brouard 8926: /*-------- data file ----------*/
8927: FILE *fic;
8928: char dummy[]=" ";
1.240 brouard 8929: int i=0, j=0, n=0, iv=0, v;
1.223 brouard 8930: int lstra;
1.136 brouard 8931: int linei, month, year,iout;
8932: char line[MAXLINE], linetmp[MAXLINE];
1.164 brouard 8933: char stra[MAXLINE], strb[MAXLINE];
1.136 brouard 8934: char *stratrunc;
1.223 brouard 8935:
1.240 brouard 8936: DummyV=ivector(1,NCOVMAX); /* 1 to 3 */
8937: FixedV=ivector(1,NCOVMAX); /* 1 to 3 */
1.126 brouard 8938:
1.240 brouard 8939: for(v=1; v <=ncovcol;v++){
8940: DummyV[v]=0;
8941: FixedV[v]=0;
8942: }
8943: for(v=ncovcol+1; v <=ncovcol+nqv;v++){
8944: DummyV[v]=1;
8945: FixedV[v]=0;
8946: }
8947: for(v=ncovcol+nqv+1; v <=ncovcol+nqv+ntv;v++){
8948: DummyV[v]=0;
8949: FixedV[v]=1;
8950: }
8951: for(v=ncovcol+nqv+ntv+1; v <=ncovcol+nqv+ntv+nqtv;v++){
8952: DummyV[v]=1;
8953: FixedV[v]=1;
8954: }
8955: for(v=1; v <=ncovcol+nqv+ntv+nqtv;v++){
8956: printf("Covariate type in the data: V%d, DummyV(V%d)=%d, FixedV(V%d)=%d\n",v,v,DummyV[v],v,FixedV[v]);
8957: 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]);
8958: }
1.126 brouard 8959:
1.136 brouard 8960: if((fic=fopen(datafile,"r"))==NULL) {
1.218 brouard 8961: printf("Problem while opening datafile: %s with errno='%s'\n", datafile,strerror(errno));fflush(stdout);
8962: fprintf(ficlog,"Problem while opening datafile: %s with errno='%s'\n", datafile,strerror(errno));fflush(ficlog);return 1;
1.136 brouard 8963: }
1.126 brouard 8964:
1.136 brouard 8965: i=1;
8966: linei=0;
8967: while ((fgets(line, MAXLINE, fic) != NULL) &&((i >= firstobs) && (i <=lastobs))) {
8968: linei=linei+1;
8969: for(j=strlen(line); j>=0;j--){ /* Untabifies line */
8970: if(line[j] == '\t')
8971: line[j] = ' ';
8972: }
8973: for(j=strlen(line)-1; (line[j]==' ')||(line[j]==10)||(line[j]==13);j--){
8974: ;
8975: };
8976: line[j+1]=0; /* Trims blanks at end of line */
8977: if(line[0]=='#'){
8978: fprintf(ficlog,"Comment line\n%s\n",line);
8979: printf("Comment line\n%s\n",line);
8980: continue;
8981: }
8982: trimbb(linetmp,line); /* Trims multiple blanks in line */
1.164 brouard 8983: strcpy(line, linetmp);
1.223 brouard 8984:
8985: /* Loops on waves */
8986: for (j=maxwav;j>=1;j--){
8987: for (iv=nqtv;iv>=1;iv--){ /* Loop on time varying quantitative variables */
1.238 brouard 8988: cutv(stra, strb, line, ' ');
8989: if(strb[0]=='.') { /* Missing value */
8990: lval=-1;
8991: cotqvar[j][iv][i]=-1; /* 0.0/0.0 */
8992: cotvar[j][ntv+iv][i]=-1; /* For performance reasons */
8993: if(isalpha(strb[1])) { /* .m or .d Really Missing value */
8994: 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);
8995: 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);
8996: return 1;
8997: }
8998: }else{
8999: errno=0;
9000: /* what_kind_of_number(strb); */
9001: dval=strtod(strb,&endptr);
9002: /* if( strb[0]=='\0' || (*endptr != '\0')){ */
9003: /* if(strb != endptr && *endptr == '\0') */
9004: /* dval=dlval; */
9005: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN)) */
9006: if( strb[0]=='\0' || (*endptr != '\0')){
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. Setting maxwav=%d might be wrong. Exiting.\n", strb, linei,i,line,iv, nqtv, j,maxwav);
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. Setting maxwav=%d might be wrong. Exiting.\n", strb, linei,i,line, iv, nqtv, j,maxwav);fflush(ficlog);
9009: return 1;
9010: }
9011: cotqvar[j][iv][i]=dval;
9012: cotvar[j][ntv+iv][i]=dval;
9013: }
9014: strcpy(line,stra);
1.223 brouard 9015: }/* end loop ntqv */
1.225 brouard 9016:
1.223 brouard 9017: for (iv=ntv;iv>=1;iv--){ /* Loop on time varying dummies */
1.238 brouard 9018: cutv(stra, strb, line, ' ');
9019: if(strb[0]=='.') { /* Missing value */
9020: lval=-1;
9021: }else{
9022: errno=0;
9023: lval=strtol(strb,&endptr,10);
9024: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN))*/
9025: if( strb[0]=='\0' || (*endptr != '\0')){
9026: 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);
9027: 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);
9028: return 1;
9029: }
9030: }
9031: if(lval <-1 || lval >1){
9032: printf("Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.223 brouard 9033: Should be a value of %d(nth) covariate (0 should be the value for the reference and 1\n \
9034: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.238 brouard 9035: For example, for multinomial values like 1, 2 and 3,\n \
9036: build V1=0 V2=0 for the reference value (1),\n \
9037: V1=1 V2=0 for (2) \n \
1.223 brouard 9038: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.238 brouard 9039: output of IMaCh is often meaningless.\n \
1.223 brouard 9040: Exiting.\n",lval,linei, i,line,j);
1.238 brouard 9041: fprintf(ficlog,"Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.223 brouard 9042: Should be a value of %d(nth) covariate (0 should be the value for the reference and 1\n \
9043: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.238 brouard 9044: For example, for multinomial values like 1, 2 and 3,\n \
9045: build V1=0 V2=0 for the reference value (1),\n \
9046: V1=1 V2=0 for (2) \n \
1.223 brouard 9047: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.238 brouard 9048: output of IMaCh is often meaningless.\n \
1.223 brouard 9049: Exiting.\n",lval,linei, i,line,j);fflush(ficlog);
1.238 brouard 9050: return 1;
9051: }
9052: cotvar[j][iv][i]=(double)(lval);
9053: strcpy(line,stra);
1.223 brouard 9054: }/* end loop ntv */
1.225 brouard 9055:
1.223 brouard 9056: /* Statuses at wave */
1.137 brouard 9057: cutv(stra, strb, line, ' ');
1.223 brouard 9058: if(strb[0]=='.') { /* Missing value */
1.238 brouard 9059: lval=-1;
1.136 brouard 9060: }else{
1.238 brouard 9061: errno=0;
9062: lval=strtol(strb,&endptr,10);
9063: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN))*/
9064: if( strb[0]=='\0' || (*endptr != '\0')){
9065: 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);
9066: 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);
9067: return 1;
9068: }
1.136 brouard 9069: }
1.225 brouard 9070:
1.136 brouard 9071: s[j][i]=lval;
1.225 brouard 9072:
1.223 brouard 9073: /* Date of Interview */
1.136 brouard 9074: strcpy(line,stra);
9075: cutv(stra, strb,line,' ');
1.169 brouard 9076: if( (iout=sscanf(strb,"%d/%d",&month, &year)) != 0){
1.136 brouard 9077: }
1.169 brouard 9078: else if( (iout=sscanf(strb,"%s.",dummy)) != 0){
1.225 brouard 9079: month=99;
9080: year=9999;
1.136 brouard 9081: }else{
1.225 brouard 9082: 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);
9083: 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);
9084: return 1;
1.136 brouard 9085: }
9086: anint[j][i]= (double) year;
9087: mint[j][i]= (double)month;
9088: strcpy(line,stra);
1.223 brouard 9089: } /* End loop on waves */
1.225 brouard 9090:
1.223 brouard 9091: /* Date of death */
1.136 brouard 9092: cutv(stra, strb,line,' ');
1.169 brouard 9093: if( (iout=sscanf(strb,"%d/%d",&month, &year)) != 0){
1.136 brouard 9094: }
1.169 brouard 9095: else if( (iout=sscanf(strb,"%s.",dummy)) != 0){
1.136 brouard 9096: month=99;
9097: year=9999;
9098: }else{
1.141 brouard 9099: 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 9100: 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);
9101: return 1;
1.136 brouard 9102: }
9103: andc[i]=(double) year;
9104: moisdc[i]=(double) month;
9105: strcpy(line,stra);
9106:
1.223 brouard 9107: /* Date of birth */
1.136 brouard 9108: cutv(stra, strb,line,' ');
1.169 brouard 9109: if( (iout=sscanf(strb,"%d/%d",&month, &year)) != 0){
1.136 brouard 9110: }
1.169 brouard 9111: else if( (iout=sscanf(strb,"%s.", dummy)) != 0){
1.136 brouard 9112: month=99;
9113: year=9999;
9114: }else{
1.141 brouard 9115: 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);
9116: 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 9117: return 1;
1.136 brouard 9118: }
9119: if (year==9999) {
1.141 brouard 9120: 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);
9121: 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 9122: return 1;
9123:
1.136 brouard 9124: }
9125: annais[i]=(double)(year);
9126: moisnais[i]=(double)(month);
9127: strcpy(line,stra);
1.225 brouard 9128:
1.223 brouard 9129: /* Sample weight */
1.136 brouard 9130: cutv(stra, strb,line,' ');
9131: errno=0;
9132: dval=strtod(strb,&endptr);
9133: if( strb[0]=='\0' || (*endptr != '\0')){
1.141 brouard 9134: printf("Error reading data around '%f' at line number %d, \"%s\" for individual %d\nShould be a weight. Exiting.\n",dval, i,line,linei);
9135: 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 9136: fflush(ficlog);
9137: return 1;
9138: }
9139: weight[i]=dval;
9140: strcpy(line,stra);
1.225 brouard 9141:
1.223 brouard 9142: for (iv=nqv;iv>=1;iv--){ /* Loop on fixed quantitative variables */
9143: cutv(stra, strb, line, ' ');
9144: if(strb[0]=='.') { /* Missing value */
1.225 brouard 9145: lval=-1;
1.223 brouard 9146: }else{
1.225 brouard 9147: errno=0;
9148: /* what_kind_of_number(strb); */
9149: dval=strtod(strb,&endptr);
9150: /* if(strb != endptr && *endptr == '\0') */
9151: /* dval=dlval; */
9152: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN)) */
9153: if( strb[0]=='\0' || (*endptr != '\0')){
9154: 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);
9155: 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);
9156: return 1;
9157: }
9158: coqvar[iv][i]=dval;
1.226 brouard 9159: covar[ncovcol+iv][i]=dval; /* including qvar in standard covar for performance reasons */
1.223 brouard 9160: }
9161: strcpy(line,stra);
9162: }/* end loop nqv */
1.136 brouard 9163:
1.223 brouard 9164: /* Covariate values */
1.136 brouard 9165: for (j=ncovcol;j>=1;j--){
9166: cutv(stra, strb,line,' ');
1.223 brouard 9167: if(strb[0]=='.') { /* Missing covariate value */
1.225 brouard 9168: lval=-1;
1.136 brouard 9169: }else{
1.225 brouard 9170: errno=0;
9171: lval=strtol(strb,&endptr,10);
9172: if( strb[0]=='\0' || (*endptr != '\0')){
9173: 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);
9174: 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);
9175: return 1;
9176: }
1.136 brouard 9177: }
9178: if(lval <-1 || lval >1){
1.225 brouard 9179: printf("Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.136 brouard 9180: Should be a value of %d(nth) covariate (0 should be the value for the reference and 1\n \
9181: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.225 brouard 9182: For example, for multinomial values like 1, 2 and 3,\n \
9183: build V1=0 V2=0 for the reference value (1),\n \
9184: V1=1 V2=0 for (2) \n \
1.136 brouard 9185: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.225 brouard 9186: output of IMaCh is often meaningless.\n \
1.136 brouard 9187: Exiting.\n",lval,linei, i,line,j);
1.225 brouard 9188: fprintf(ficlog,"Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.136 brouard 9189: Should be a value of %d(nth) covariate (0 should be the value for the reference and 1\n \
9190: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.225 brouard 9191: For example, for multinomial values like 1, 2 and 3,\n \
9192: build V1=0 V2=0 for the reference value (1),\n \
9193: V1=1 V2=0 for (2) \n \
1.136 brouard 9194: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.225 brouard 9195: output of IMaCh is often meaningless.\n \
1.136 brouard 9196: Exiting.\n",lval,linei, i,line,j);fflush(ficlog);
1.225 brouard 9197: return 1;
1.136 brouard 9198: }
9199: covar[j][i]=(double)(lval);
9200: strcpy(line,stra);
9201: }
9202: lstra=strlen(stra);
1.225 brouard 9203:
1.136 brouard 9204: if(lstra > 9){ /* More than 2**32 or max of what printf can write with %ld */
9205: stratrunc = &(stra[lstra-9]);
9206: num[i]=atol(stratrunc);
9207: }
9208: else
9209: num[i]=atol(stra);
9210: /*if((s[2][i]==2) && (s[3][i]==-1)&&(s[4][i]==9)){
9211: 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;}*/
9212:
9213: i=i+1;
9214: } /* End loop reading data */
1.225 brouard 9215:
1.136 brouard 9216: *imax=i-1; /* Number of individuals */
9217: fclose(fic);
1.225 brouard 9218:
1.136 brouard 9219: return (0);
1.164 brouard 9220: /* endread: */
1.225 brouard 9221: printf("Exiting readdata: ");
9222: fclose(fic);
9223: return (1);
1.223 brouard 9224: }
1.126 brouard 9225:
1.234 brouard 9226: void removefirstspace(char **stri){/*, char stro[]) {*/
1.230 brouard 9227: char *p1 = *stri, *p2 = *stri;
1.235 brouard 9228: while (*p2 == ' ')
1.234 brouard 9229: p2++;
9230: /* while ((*p1++ = *p2++) !=0) */
9231: /* ; */
9232: /* do */
9233: /* while (*p2 == ' ') */
9234: /* p2++; */
9235: /* while (*p1++ == *p2++); */
9236: *stri=p2;
1.145 brouard 9237: }
9238:
1.235 brouard 9239: int decoderesult ( char resultline[], int nres)
1.230 brouard 9240: /**< This routine decode one result line and returns the combination # of dummy covariates only **/
9241: {
1.235 brouard 9242: int j=0, k=0, k1=0, k2=0, k3=0, k4=0, match=0, k2q=0, k3q=0, k4q=0;
1.230 brouard 9243: char resultsav[MAXLINE];
1.234 brouard 9244: int resultmodel[MAXLINE];
9245: int modelresult[MAXLINE];
1.230 brouard 9246: char stra[80], strb[80], strc[80], strd[80],stre[80];
9247:
1.234 brouard 9248: removefirstspace(&resultline);
1.233 brouard 9249: printf("decoderesult:%s\n",resultline);
1.230 brouard 9250:
9251: if (strstr(resultline,"v") !=0){
9252: printf("Error. 'v' must be in upper case 'V' result: %s ",resultline);
9253: fprintf(ficlog,"Error. 'v' must be in upper case result: %s ",resultline);fflush(ficlog);
9254: return 1;
9255: }
9256: trimbb(resultsav, resultline);
9257: if (strlen(resultsav) >1){
9258: j=nbocc(resultsav,'='); /**< j=Number of covariate values'=' */
9259: }
1.253 brouard 9260: if(j == 0){ /* Resultline but no = */
9261: TKresult[nres]=0; /* Combination for the nresult and the model */
9262: return (0);
9263: }
9264:
1.234 brouard 9265: if( j != cptcovs ){ /* Be careful if a variable is in a product but not single */
9266: 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);
9267: 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);
9268: }
9269: for(k=1; k<=j;k++){ /* Loop on any covariate of the result line */
9270: if(nbocc(resultsav,'=') >1){
9271: cutl(stra,strb,resultsav,' '); /* keeps in strb after the first ' '
9272: resultsav= V4=1 V5=25.1 V3=0 strb=V3=0 stra= V4=1 V5=25.1 */
9273: cutl(strc,strd,strb,'='); /* strb:V4=1 strc=1 strd=V4 */
9274: }else
9275: cutl(strc,strd,resultsav,'=');
1.230 brouard 9276: Tvalsel[k]=atof(strc); /* 1 */
1.234 brouard 9277:
1.230 brouard 9278: cutl(strc,stre,strd,'V'); /* strd='V4' strc=4 stre='V' */;
9279: Tvarsel[k]=atoi(strc);
9280: /* Typevarsel[k]=1; /\* 1 for age product *\/ */
9281: /* cptcovsel++; */
9282: if (nbocc(stra,'=') >0)
9283: strcpy(resultsav,stra); /* and analyzes it */
9284: }
1.235 brouard 9285: /* Checking for missing or useless values in comparison of current model needs */
1.236 brouard 9286: for(k1=1; k1<= cptcovt ;k1++){ /* model line V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
9287: if(Typevar[k1]==0){ /* Single covariate in model */
1.234 brouard 9288: match=0;
1.236 brouard 9289: for(k2=1; k2 <=j;k2++){/* result line V4=1 V5=24.1 V3=1 V2=8 V1=0 */
1.237 brouard 9290: if(Tvar[k1]==Tvarsel[k2]) {/* Tvar[1]=5 == Tvarsel[2]=5 */
1.236 brouard 9291: modelresult[k2]=k1;/* modelresult[2]=1 modelresult[1]=2 modelresult[3]=3 modelresult[6]=4 modelresult[9]=5 */
1.234 brouard 9292: match=1;
9293: break;
9294: }
9295: }
9296: if(match == 0){
9297: printf("Error in result line: %d value missing; result: %s, model=%s\n",k1, resultline, model);
9298: }
9299: }
9300: }
1.235 brouard 9301: /* Checking for missing or useless values in comparison of current model needs */
9302: for(k2=1; k2 <=j;k2++){ /* result line V4=1 V5=24.1 V3=1 V2=8 V1=0 */
1.234 brouard 9303: match=0;
1.235 brouard 9304: for(k1=1; k1<= cptcovt ;k1++){ /* model line V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
9305: if(Typevar[k1]==0){ /* Single */
1.237 brouard 9306: if(Tvar[k1]==Tvarsel[k2]) { /* Tvar[2]=4 == Tvarsel[1]=4 */
1.235 brouard 9307: resultmodel[k1]=k2; /* resultmodel[2]=1 resultmodel[1]=2 resultmodel[3]=3 resultmodel[6]=4 resultmodel[9]=5 */
1.234 brouard 9308: ++match;
9309: }
9310: }
9311: }
9312: if(match == 0){
9313: printf("Error in result line: %d value missing; result: %s, model=%s\n",k1, resultline, model);
9314: }else if(match > 1){
9315: printf("Error in result line: %d doubled; result: %s, model=%s\n",k2, resultline, model);
9316: }
9317: }
1.235 brouard 9318:
1.234 brouard 9319: /* We need to deduce which combination number is chosen and save quantitative values */
1.235 brouard 9320: /* model line V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
9321: /* result line V4=1 V5=25.1 V3=0 V2=8 V1=1 */
9322: /* should give a combination of dummy V4=1, V3=0, V1=1 => V4*2**(0) + V3*2**(1) + V1*2**(2) = 5 + (1offset) = 6*/
9323: /* result line V4=1 V5=24.1 V3=1 V2=8 V1=0 */
9324: /* should give a combination of dummy V4=1, V3=1, V1=0 => V4*2**(0) + V3*2**(1) + V1*2**(2) = 3 + (1offset) = 4*/
9325: /* 1 0 0 0 */
9326: /* 2 1 0 0 */
9327: /* 3 0 1 0 */
9328: /* 4 1 1 0 */ /* V4=1, V3=1, V1=0 */
9329: /* 5 0 0 1 */
9330: /* 6 1 0 1 */ /* V4=1, V3=0, V1=1 */
9331: /* 7 0 1 1 */
9332: /* 8 1 1 1 */
1.237 brouard 9333: /* V(Tvresult)=Tresult V4=1 V3=0 V1=1 Tresult[nres=1][2]=0 */
9334: /* V(Tvqresult)=Tqresult V5=25.1 V2=8 Tqresult[nres=1][1]=25.1 */
9335: /* V5*age V5 known which value for nres? */
9336: /* Tqinvresult[2]=8 Tqinvresult[1]=25.1 */
1.235 brouard 9337: for(k1=1, k=0, k4=0, k4q=0; k1 <=cptcovt;k1++){ /* model line */
9338: if( Dummy[k1]==0 && Typevar[k1]==0 ){ /* Single dummy */
1.237 brouard 9339: k3= resultmodel[k1]; /* resultmodel[2(V4)] = 1=k3 */
1.235 brouard 9340: k2=(int)Tvarsel[k3]; /* Tvarsel[resultmodel[2]]= Tvarsel[1] = 4=k2 */
9341: k+=Tvalsel[k3]*pow(2,k4); /* Tvalsel[1]=1 */
1.237 brouard 9342: Tresult[nres][k4+1]=Tvalsel[k3];/* Tresult[nres][1]=1(V4=1) Tresult[nres][2]=0(V3=0) */
9343: Tvresult[nres][k4+1]=(int)Tvarsel[k3];/* Tvresult[nres][1]=4 Tvresult[nres][3]=1 */
9344: Tinvresult[nres][(int)Tvarsel[k3]]=Tvalsel[k3]; /* Tinvresult[nres][4]=1 */
1.235 brouard 9345: printf("Decoderesult Dummy k=%d, V(k2=V%d)= Tvalsel[%d]=%d, 2**(%d)\n",k, k2, k3, (int)Tvalsel[k3], k4);
9346: k4++;;
9347: } else if( Dummy[k1]==1 && Typevar[k1]==0 ){ /* Single quantitative */
9348: k3q= resultmodel[k1]; /* resultmodel[2] = 1=k3 */
9349: k2q=(int)Tvarsel[k3q]; /* Tvarsel[resultmodel[2]]= Tvarsel[1] = 4=k2 */
1.237 brouard 9350: Tqresult[nres][k4q+1]=Tvalsel[k3q]; /* Tqresult[nres][1]=25.1 */
9351: Tvqresult[nres][k4q+1]=(int)Tvarsel[k3q]; /* Tvqresult[nres][1]=5 */
9352: Tqinvresult[nres][(int)Tvarsel[k3q]]=Tvalsel[k3q]; /* Tqinvresult[nres][5]=25.1 */
1.235 brouard 9353: printf("Decoderesult Quantitative nres=%d, V(k2q=V%d)= Tvalsel[%d]=%d, Tvarsel[%d]=%f\n",nres, k2q, k3q, Tvarsel[k3q], k3q, Tvalsel[k3q]);
9354: k4q++;;
9355: }
9356: }
1.234 brouard 9357:
1.235 brouard 9358: TKresult[nres]=++k; /* Combination for the nresult and the model */
1.230 brouard 9359: return (0);
9360: }
1.235 brouard 9361:
1.230 brouard 9362: int decodemodel( char model[], int lastobs)
9363: /**< This routine decodes the model and returns:
1.224 brouard 9364: * Model V1+V2+V3+V8+V7*V8+V5*V6+V8*age+V3*age+age*age
9365: * - nagesqr = 1 if age*age in the model, otherwise 0.
9366: * - cptcovt total number of covariates of the model nbocc(+)+1 = 8 excepting constant and age and age*age
9367: * - cptcovn or number of covariates k of the models excluding age*products =6 and age*age
9368: * - cptcovage number of covariates with age*products =2
9369: * - cptcovs number of simple covariates
9370: * - 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
9371: * which is a new column after the 9 (ncovcol) variables.
9372: * - if k is a product Vn*Vm covar[k][i] is filled with correct values for each individual
9373: * - Tprod[l] gives the kth covariates of the product Vn*Vm l=1 to cptcovprod-cptcovage
9374: * Tprod[1]@2 {5, 6}: position of first product V7*V8 is 5, and second V5*V6 is 6.
9375: * - Tvard[k] p Tvard[1][1]@4 {7, 8, 5, 6} for V7*V8 and V5*V6 .
9376: */
1.136 brouard 9377: {
1.238 brouard 9378: int i, j, k, ks, v;
1.227 brouard 9379: int j1, k1, k2, k3, k4;
1.136 brouard 9380: char modelsav[80];
1.145 brouard 9381: char stra[80], strb[80], strc[80], strd[80],stre[80];
1.187 brouard 9382: char *strpt;
1.136 brouard 9383:
1.145 brouard 9384: /*removespace(model);*/
1.136 brouard 9385: if (strlen(model) >1){ /* If there is at least 1 covariate */
1.145 brouard 9386: j=0, j1=0, k1=0, k2=-1, ks=0, cptcovn=0;
1.137 brouard 9387: if (strstr(model,"AGE") !=0){
1.192 brouard 9388: printf("Error. AGE must be in lower case 'age' model=1+age+%s. ",model);
9389: fprintf(ficlog,"Error. AGE must be in lower case model=1+age+%s. ",model);fflush(ficlog);
1.136 brouard 9390: return 1;
9391: }
1.141 brouard 9392: if (strstr(model,"v") !=0){
9393: printf("Error. 'v' must be in upper case 'V' model=%s ",model);
9394: fprintf(ficlog,"Error. 'v' must be in upper case model=%s ",model);fflush(ficlog);
9395: return 1;
9396: }
1.187 brouard 9397: strcpy(modelsav,model);
9398: if ((strpt=strstr(model,"age*age")) !=0){
9399: printf(" strpt=%s, model=%s\n",strpt, model);
9400: if(strpt != model){
1.234 brouard 9401: printf("Error in model: 'model=%s'; 'age*age' should in first place before other covariates\n \
1.192 brouard 9402: 'model=1+age+age*age+V1.' or 'model=1+age+age*age+V1+V1*age.', please swap as well as \n \
1.187 brouard 9403: corresponding column of parameters.\n",model);
1.234 brouard 9404: fprintf(ficlog,"Error in model: 'model=%s'; 'age*age' should in first place before other covariates\n \
1.192 brouard 9405: 'model=1+age+age*age+V1.' or 'model=1+age+age*age+V1+V1*age.', please swap as well as \n \
1.187 brouard 9406: corresponding column of parameters.\n",model); fflush(ficlog);
1.234 brouard 9407: return 1;
1.225 brouard 9408: }
1.187 brouard 9409: nagesqr=1;
9410: if (strstr(model,"+age*age") !=0)
1.234 brouard 9411: substrchaine(modelsav, model, "+age*age");
1.187 brouard 9412: else if (strstr(model,"age*age+") !=0)
1.234 brouard 9413: substrchaine(modelsav, model, "age*age+");
1.187 brouard 9414: else
1.234 brouard 9415: substrchaine(modelsav, model, "age*age");
1.187 brouard 9416: }else
9417: nagesqr=0;
9418: if (strlen(modelsav) >1){
9419: j=nbocc(modelsav,'+'); /**< j=Number of '+' */
9420: j1=nbocc(modelsav,'*'); /**< j1=Number of '*' */
1.224 brouard 9421: cptcovs=j+1-j1; /**< Number of simple covariates V1+V1*age+V3 +V3*V4+age*age=> V1 + V3 =5-3=2 */
1.187 brouard 9422: cptcovt= j+1; /* Number of total covariates in the model, not including
1.225 brouard 9423: * cst, age and age*age
9424: * V1+V1*age+ V3 + V3*V4+age*age=> 3+1=4*/
9425: /* including age products which are counted in cptcovage.
9426: * but the covariates which are products must be treated
9427: * separately: ncovn=4- 2=2 (V1+V3). */
1.187 brouard 9428: cptcovprod=j1; /**< Number of products V1*V2 +v3*age = 2 */
9429: cptcovprodnoage=0; /**< Number of covariate products without age: V3*V4 =1 */
1.225 brouard 9430:
9431:
1.187 brouard 9432: /* Design
9433: * V1 V2 V3 V4 V5 V6 V7 V8 V9 Weight
9434: * < ncovcol=8 >
9435: * Model V2 + V1 + V3*age + V3 + V5*V6 + V7*V8 + V8*age + V8
9436: * k= 1 2 3 4 5 6 7 8
9437: * cptcovn number of covariates (not including constant and age ) = # of + plus 1 = 7+1=8
9438: * covar[k,i], value of kth covariate if not including age for individual i:
1.224 brouard 9439: * covar[1][i]= (V1), covar[4][i]=(V4), covar[8][i]=(V8)
9440: * Tvar[k] # of the kth covariate: Tvar[1]=2 Tvar[2]=1 Tvar[4]=3 Tvar[8]=8
1.187 brouard 9441: * if multiplied by age: V3*age Tvar[3=V3*age]=3 (V3) Tvar[7]=8 and
9442: * Tage[++cptcovage]=k
9443: * if products, new covar are created after ncovcol with k1
9444: * Tvar[k]=ncovcol+k1; # of the kth covariate product: Tvar[5]=ncovcol+1=10 Tvar[6]=ncovcol+1=11
9445: * Tprod[k1]=k; Tprod[1]=5 Tprod[2]= 6; gives the position of the k1th product
9446: * 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
9447: * Tvar[cptcovn+k2]=Tvard[k1][1];Tvar[cptcovn+k2+1]=Tvard[k1][2];
9448: * Tvar[8+1]=5;Tvar[8+2]=6;Tvar[8+3]=7;Tvar[8+4]=8 inverted
9449: * V1 V2 V3 V4 V5 V6 V7 V8 V9 V10 V11
9450: * < ncovcol=8 >
9451: * Model V2 + V1 + V3*age + V3 + V5*V6 + V7*V8 + V8*age + V8 d1 d1 d2 d2
9452: * k= 1 2 3 4 5 6 7 8 9 10 11 12
9453: * Tvar[k]= 2 1 3 3 10 11 8 8 5 6 7 8
9454: * p Tvar[1]@12={2, 1, 3, 3, 11, 10, 8, 8, 7, 8, 5, 6}
9455: * p Tprod[1]@2={ 6, 5}
9456: *p Tvard[1][1]@4= {7, 8, 5, 6}
9457: * covar[k][i]= V2 V1 ? V3 V5*V6? V7*V8? ? V8
9458: * cov[Tage[kk]+2]=covar[Tvar[Tage[kk]]][i]*cov[2];
9459: *How to reorganize?
9460: * Model V1 + V2 + V3 + V8 + V5*V6 + V7*V8 + V3*age + V8*age
9461: * Tvars {2, 1, 3, 3, 11, 10, 8, 8, 7, 8, 5, 6}
9462: * {2, 1, 4, 8, 5, 6, 3, 7}
9463: * Struct []
9464: */
1.225 brouard 9465:
1.187 brouard 9466: /* This loop fills the array Tvar from the string 'model'.*/
9467: /* j is the number of + signs in the model V1+V2+V3 j=2 i=3 to 1 */
9468: /* modelsav=V2+V1+V4+age*V3 strb=age*V3 stra=V2+V1+V4 */
9469: /* k=4 (age*V3) Tvar[k=4]= 3 (from V3) Tage[cptcovage=1]=4 */
9470: /* k=3 V4 Tvar[k=3]= 4 (from V4) */
9471: /* k=2 V1 Tvar[k=2]= 1 (from V1) */
9472: /* k=1 Tvar[1]=2 (from V2) */
9473: /* k=5 Tvar[5] */
9474: /* for (k=1; k<=cptcovn;k++) { */
1.198 brouard 9475: /* cov[2+k]=nbcode[Tvar[k]][codtabm(ij,Tvar[k])]; */
1.187 brouard 9476: /* } */
1.198 brouard 9477: /* for (k=1; k<=cptcovage;k++) cov[2+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,Tvar[Tage[k])]]*cov[2]; */
1.187 brouard 9478: /*
9479: * Treating invertedly V2+V1+V3*age+V2*V4 is as if written V2*V4 +V3*age + V1 + V2 */
1.227 brouard 9480: for(k=cptcovt; k>=1;k--){ /**< Number of covariates not including constant and age, neither age*age*/
9481: Tvar[k]=0; Tprod[k]=0; Tposprod[k]=0;
9482: }
1.187 brouard 9483: cptcovage=0;
9484: for(k=1; k<=cptcovt;k++){ /* Loop on total covariates of the model */
1.234 brouard 9485: cutl(stra,strb,modelsav,'+'); /* keeps in strb after the first '+'
1.225 brouard 9486: modelsav==V2+V1+V4+V3*age strb=V3*age stra=V2+V1+V4 */
1.234 brouard 9487: if (nbocc(modelsav,'+')==0) strcpy(strb,modelsav); /* and analyzes it */
9488: /* printf("i=%d a=%s b=%s sav=%s\n",i, stra,strb,modelsav);*/
9489: /*scanf("%d",i);*/
9490: if (strchr(strb,'*')) { /**< Model includes a product V2+V1+V4+V3*age strb=V3*age */
9491: cutl(strc,strd,strb,'*'); /**< strd*strc Vm*Vn: strb=V3*age(input) strc=age strd=V3 ; V3*V2 strc=V2, strd=V3 */
9492: if (strcmp(strc,"age")==0) { /**< Model includes age: Vn*age */
9493: /* covar is not filled and then is empty */
9494: cptcovprod--;
9495: cutl(stre,strb,strd,'V'); /* strd=V3(input): stre="3" */
9496: Tvar[k]=atoi(stre); /* V2+V1+V4+V3*age Tvar[4]=3 ; V1+V2*age Tvar[2]=2; V1+V1*age Tvar[2]=1 */
9497: Typevar[k]=1; /* 1 for age product */
9498: cptcovage++; /* Sums the number of covariates which include age as a product */
9499: Tage[cptcovage]=k; /* Tvar[4]=3, Tage[1] = 4 or V1+V1*age Tvar[2]=1, Tage[1]=2 */
9500: /*printf("stre=%s ", stre);*/
9501: } else if (strcmp(strd,"age")==0) { /* or age*Vn */
9502: cptcovprod--;
9503: cutl(stre,strb,strc,'V');
9504: Tvar[k]=atoi(stre);
9505: Typevar[k]=1; /* 1 for age product */
9506: cptcovage++;
9507: Tage[cptcovage]=k;
9508: } else { /* Age is not in the model product V2+V1+V1*V4+V3*age+V3*V2 strb=V3*V2*/
9509: /* loops on k1=1 (V3*V2) and k1=2 V4*V3 */
9510: cptcovn++;
9511: cptcovprodnoage++;k1++;
9512: cutl(stre,strb,strc,'V'); /* strc= Vn, stre is n; strb=V3*V2 stre=3 strc=*/
9513: Tvar[k]=ncovcol+nqv+ntv+nqtv+k1; /* For model-covariate k tells which data-covariate to use but
9514: because this model-covariate is a construction we invent a new column
9515: which is after existing variables ncovcol+nqv+ntv+nqtv + k1
9516: If already ncovcol=4 and model=V2+V1+V1*V4+age*V3+V3*V2
9517: Tvar[3=V1*V4]=4+1 Tvar[5=V3*V2]=4 + 2= 6, etc */
9518: Typevar[k]=2; /* 2 for double fixed dummy covariates */
9519: cutl(strc,strb,strd,'V'); /* strd was Vm, strc is m */
9520: Tprod[k1]=k; /* Tprod[1]=3(=V1*V4) for V2+V1+V1*V4+age*V3+V3*V2 */
9521: Tposprod[k]=k1; /* Tpsprod[3]=1, Tposprod[2]=5 */
9522: Tvard[k1][1] =atoi(strc); /* m 1 for V1*/
9523: Tvard[k1][2] =atoi(stre); /* n 4 for V4*/
9524: k2=k2+2; /* k2 is initialize to -1, We want to store the n and m in Vn*Vm at the end of Tvar */
9525: /* Tvar[cptcovt+k2]=Tvard[k1][1]; /\* Tvar[(cptcovt=4+k2=1)=5]= 1 (V1) *\/ */
9526: /* Tvar[cptcovt+k2+1]=Tvard[k1][2]; /\* Tvar[(cptcovt=4+(k2=1)+1)=6]= 4 (V4) *\/ */
1.225 brouard 9527: /*ncovcol=4 and model=V2+V1+V1*V4+age*V3+V3*V2, Tvar[3]=5, Tvar[4]=6, cptcovt=5 */
1.234 brouard 9528: /* 1 2 3 4 5 | Tvar[5+1)=1, Tvar[7]=2 */
9529: for (i=1; i<=lastobs;i++){
9530: /* Computes the new covariate which is a product of
9531: covar[n][i]* covar[m][i] and stores it at ncovol+k1 May not be defined */
9532: covar[ncovcol+k1][i]=covar[atoi(stre)][i]*covar[atoi(strc)][i];
9533: }
9534: } /* End age is not in the model */
9535: } /* End if model includes a product */
9536: else { /* no more sum */
9537: /*printf("d=%s c=%s b=%s\n", strd,strc,strb);*/
9538: /* scanf("%d",i);*/
9539: cutl(strd,strc,strb,'V');
9540: ks++; /**< Number of simple covariates dummy or quantitative, fixe or varying */
9541: cptcovn++; /** V4+V3+V5: V4 and V3 timevarying dummy covariates, V5 timevarying quantitative */
9542: Tvar[k]=atoi(strd);
9543: Typevar[k]=0; /* 0 for simple covariates */
9544: }
9545: strcpy(modelsav,stra); /* modelsav=V2+V1+V4 stra=V2+V1+V4 */
1.223 brouard 9546: /*printf("a=%s b=%s sav=%s\n", stra,strb,modelsav);
1.225 brouard 9547: scanf("%d",i);*/
1.187 brouard 9548: } /* end of loop + on total covariates */
9549: } /* end if strlen(modelsave == 0) age*age might exist */
9550: } /* end if strlen(model == 0) */
1.136 brouard 9551:
9552: /*The number n of Vn is stored in Tvar. cptcovage =number of age covariate. Tage gives the position of age. cptcovprod= number of products.
9553: If model=V1+V1*age then Tvar[1]=1 Tvar[2]=1 cptcovage=1 Tage[1]=2 cptcovprod=0*/
1.225 brouard 9554:
1.136 brouard 9555: /* printf("tvar1=%d tvar2=%d tvar3=%d cptcovage=%d Tage=%d",Tvar[1],Tvar[2],Tvar[3],cptcovage,Tage[1]);
1.225 brouard 9556: printf("cptcovprod=%d ", cptcovprod);
9557: fprintf(ficlog,"cptcovprod=%d ", cptcovprod);
9558: scanf("%d ",i);*/
9559:
9560:
1.230 brouard 9561: /* Until here, decodemodel knows only the grammar (simple, product, age*) of the model but not what kind
9562: of variable (dummy vs quantitative, fixed vs time varying) is behind. But we know the # of each. */
1.226 brouard 9563: /* ncovcol= 1, nqv=1 | ntv=2, nqtv= 1 = 5 possible variables data: 2 fixed 3, varying
9564: model= V5 + V4 +V3 + V4*V3 + V5*age + V2 + V1*V2 + V1*age + V5*age, V1 is not used saving its place
9565: k = 1 2 3 4 5 6 7 8 9
9566: Tvar[k]= 5 4 3 1+1+2+1+1=6 5 2 7 1 5
9567: Typevar[k]= 0 0 0 2 1 0 2 1 1
1.227 brouard 9568: Fixed[k] 1 1 1 1 3 0 0 or 2 2 3
9569: Dummy[k] 1 0 0 0 3 1 1 2 3
9570: Tmodelind[combination of covar]=k;
1.225 brouard 9571: */
9572: /* Dispatching between quantitative and time varying covariates */
1.226 brouard 9573: /* If Tvar[k] >ncovcol it is a product */
1.225 brouard 9574: /* 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 9575: /* Computing effective variables, ie used by the model, that is from the cptcovt variables */
1.227 brouard 9576: printf("Model=%s\n\
9577: Typevar: 0 for simple covariate (dummy, quantitative, fixed or varying), 1 for age product, 2 for product \n\
9578: Fixed[k] 0=fixed (product or simple), 1 varying, 2 fixed with age product, 3 varying with age product \n\
9579: 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);
9580: fprintf(ficlog,"Model=%s\n\
9581: Typevar: 0 for simple covariate (dummy, quantitative, fixed or varying), 1 for age product, 2 for product \n\
9582: Fixed[k] 0=fixed (product or simple), 1 varying, 2 fixed with age product, 3 varying with age product \n\
9583: 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 9584: for(k=1;k<=cptcovt; k++){ Fixed[k]=0; Dummy[k]=0;}
1.234 brouard 9585: 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 */
9586: if (Tvar[k] <=ncovcol && Typevar[k]==0 ){ /* Simple fixed dummy (<=ncovcol) covariates */
1.227 brouard 9587: Fixed[k]= 0;
9588: Dummy[k]= 0;
1.225 brouard 9589: ncoveff++;
1.232 brouard 9590: ncovf++;
1.234 brouard 9591: nsd++;
9592: modell[k].maintype= FTYPE;
9593: TvarsD[nsd]=Tvar[k];
9594: TvarsDind[nsd]=k;
9595: TvarF[ncovf]=Tvar[k];
9596: TvarFind[ncovf]=k;
9597: TvarFD[ncoveff]=Tvar[k]; /* TvarFD[1]=V1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
9598: TvarFDind[ncoveff]=k; /* TvarFDind[1]=9 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
9599: }else if( Tvar[k] <=ncovcol && Typevar[k]==2){ /* Product of fixed dummy (<=ncovcol) covariates */
9600: Fixed[k]= 0;
9601: Dummy[k]= 0;
9602: ncoveff++;
9603: ncovf++;
9604: modell[k].maintype= FTYPE;
9605: TvarF[ncovf]=Tvar[k];
9606: TvarFind[ncovf]=k;
1.230 brouard 9607: TvarFD[ncoveff]=Tvar[k]; /* TvarFD[1]=V1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1.231 brouard 9608: TvarFDind[ncoveff]=k; /* TvarFDind[1]=9 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1.240 brouard 9609: }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 9610: Fixed[k]= 0;
9611: Dummy[k]= 1;
1.230 brouard 9612: nqfveff++;
1.234 brouard 9613: modell[k].maintype= FTYPE;
9614: modell[k].subtype= FQ;
9615: nsq++;
9616: TvarsQ[nsq]=Tvar[k];
9617: TvarsQind[nsq]=k;
1.232 brouard 9618: ncovf++;
1.234 brouard 9619: TvarF[ncovf]=Tvar[k];
9620: TvarFind[ncovf]=k;
1.231 brouard 9621: 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 9622: 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 9623: }else if( Tvar[k] <=ncovcol+nqv+ntv && Typevar[k]==0){/* Only simple time varying dummy variables */
1.227 brouard 9624: Fixed[k]= 1;
9625: Dummy[k]= 0;
1.225 brouard 9626: ntveff++; /* Only simple time varying dummy variable */
1.234 brouard 9627: modell[k].maintype= VTYPE;
9628: modell[k].subtype= VD;
9629: nsd++;
9630: TvarsD[nsd]=Tvar[k];
9631: TvarsDind[nsd]=k;
9632: ncovv++; /* Only simple time varying variables */
9633: TvarV[ncovv]=Tvar[k];
1.242 brouard 9634: 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 9635: 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 */
9636: 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 9637: 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);
9638: printf("Quasi TmodelInvind[%d]=%d\n",k,Tvar[k]- ncovcol-nqv);
1.231 brouard 9639: }else if( Tvar[k] <=ncovcol+nqv+ntv+nqtv && Typevar[k]==0){ /* Only simple time varying quantitative variable V5*/
1.234 brouard 9640: Fixed[k]= 1;
9641: Dummy[k]= 1;
9642: nqtveff++;
9643: modell[k].maintype= VTYPE;
9644: modell[k].subtype= VQ;
9645: ncovv++; /* Only simple time varying variables */
9646: nsq++;
9647: TvarsQ[nsq]=Tvar[k];
9648: TvarsQind[nsq]=k;
9649: TvarV[ncovv]=Tvar[k];
1.242 brouard 9650: 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 9651: 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 */
9652: 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 9653: TmodelInvQind[nqtveff]=Tvar[k]- ncovcol-nqv-ntv;/* Only simple time varying quantitative variable */
9654: /* Tmodeliqind[k]=nqtveff;/\* Only simple time varying quantitative variable *\/ */
9655: 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 9656: printf("Quasi TmodelInvQind[%d]=%d\n",k,Tvar[k]- ncovcol-nqv-ntv);
1.227 brouard 9657: }else if (Typevar[k] == 1) { /* product with age */
1.234 brouard 9658: ncova++;
9659: TvarA[ncova]=Tvar[k];
9660: TvarAind[ncova]=k;
1.231 brouard 9661: if (Tvar[k] <=ncovcol ){ /* Product age with fixed dummy covariatee */
1.240 brouard 9662: Fixed[k]= 2;
9663: Dummy[k]= 2;
9664: modell[k].maintype= ATYPE;
9665: modell[k].subtype= APFD;
9666: /* ncoveff++; */
1.227 brouard 9667: }else if( Tvar[k] <=ncovcol+nqv) { /* Remind that product Vn*Vm are added in k*/
1.240 brouard 9668: Fixed[k]= 2;
9669: Dummy[k]= 3;
9670: modell[k].maintype= ATYPE;
9671: modell[k].subtype= APFQ; /* Product age * fixed quantitative */
9672: /* nqfveff++; /\* Only simple fixed quantitative variable *\/ */
1.227 brouard 9673: }else if( Tvar[k] <=ncovcol+nqv+ntv ){
1.240 brouard 9674: Fixed[k]= 3;
9675: Dummy[k]= 2;
9676: modell[k].maintype= ATYPE;
9677: modell[k].subtype= APVD; /* Product age * varying dummy */
9678: /* ntveff++; /\* Only simple time varying dummy variable *\/ */
1.227 brouard 9679: }else if( Tvar[k] <=ncovcol+nqv+ntv+nqtv){
1.240 brouard 9680: Fixed[k]= 3;
9681: Dummy[k]= 3;
9682: modell[k].maintype= ATYPE;
9683: modell[k].subtype= APVQ; /* Product age * varying quantitative */
9684: /* nqtveff++;/\* Only simple time varying quantitative variable *\/ */
1.227 brouard 9685: }
9686: }else if (Typevar[k] == 2) { /* product without age */
9687: k1=Tposprod[k];
9688: if(Tvard[k1][1] <=ncovcol){
1.240 brouard 9689: if(Tvard[k1][2] <=ncovcol){
9690: Fixed[k]= 1;
9691: Dummy[k]= 0;
9692: modell[k].maintype= FTYPE;
9693: modell[k].subtype= FPDD; /* Product fixed dummy * fixed dummy */
9694: ncovf++; /* Fixed variables without age */
9695: TvarF[ncovf]=Tvar[k];
9696: TvarFind[ncovf]=k;
9697: }else if(Tvard[k1][2] <=ncovcol+nqv){
9698: Fixed[k]= 0; /* or 2 ?*/
9699: Dummy[k]= 1;
9700: modell[k].maintype= FTYPE;
9701: modell[k].subtype= FPDQ; /* Product fixed dummy * fixed quantitative */
9702: ncovf++; /* Varying variables without age */
9703: TvarF[ncovf]=Tvar[k];
9704: TvarFind[ncovf]=k;
9705: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){
9706: Fixed[k]= 1;
9707: Dummy[k]= 0;
9708: modell[k].maintype= VTYPE;
9709: modell[k].subtype= VPDD; /* Product fixed dummy * varying dummy */
9710: ncovv++; /* Varying variables without age */
9711: TvarV[ncovv]=Tvar[k];
9712: TvarVind[ncovv]=k;
9713: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){
9714: Fixed[k]= 1;
9715: Dummy[k]= 1;
9716: modell[k].maintype= VTYPE;
9717: modell[k].subtype= VPDQ; /* Product fixed dummy * varying quantitative */
9718: ncovv++; /* Varying variables without age */
9719: TvarV[ncovv]=Tvar[k];
9720: TvarVind[ncovv]=k;
9721: }
1.227 brouard 9722: }else if(Tvard[k1][1] <=ncovcol+nqv){
1.240 brouard 9723: if(Tvard[k1][2] <=ncovcol){
9724: Fixed[k]= 0; /* or 2 ?*/
9725: Dummy[k]= 1;
9726: modell[k].maintype= FTYPE;
9727: modell[k].subtype= FPDQ; /* Product fixed quantitative * fixed dummy */
9728: ncovf++; /* Fixed variables without age */
9729: TvarF[ncovf]=Tvar[k];
9730: TvarFind[ncovf]=k;
9731: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){
9732: Fixed[k]= 1;
9733: Dummy[k]= 1;
9734: modell[k].maintype= VTYPE;
9735: modell[k].subtype= VPDQ; /* Product fixed quantitative * varying dummy */
9736: ncovv++; /* Varying variables without age */
9737: TvarV[ncovv]=Tvar[k];
9738: TvarVind[ncovv]=k;
9739: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){
9740: Fixed[k]= 1;
9741: Dummy[k]= 1;
9742: modell[k].maintype= VTYPE;
9743: modell[k].subtype= VPQQ; /* Product fixed quantitative * varying quantitative */
9744: ncovv++; /* Varying variables without age */
9745: TvarV[ncovv]=Tvar[k];
9746: TvarVind[ncovv]=k;
9747: ncovv++; /* Varying variables without age */
9748: TvarV[ncovv]=Tvar[k];
9749: TvarVind[ncovv]=k;
9750: }
1.227 brouard 9751: }else if(Tvard[k1][1] <=ncovcol+nqv+ntv){
1.240 brouard 9752: if(Tvard[k1][2] <=ncovcol){
9753: Fixed[k]= 1;
9754: Dummy[k]= 1;
9755: modell[k].maintype= VTYPE;
9756: modell[k].subtype= VPDD; /* Product time varying dummy * fixed dummy */
9757: ncovv++; /* Varying variables without age */
9758: TvarV[ncovv]=Tvar[k];
9759: TvarVind[ncovv]=k;
9760: }else if(Tvard[k1][2] <=ncovcol+nqv){
9761: Fixed[k]= 1;
9762: Dummy[k]= 1;
9763: modell[k].maintype= VTYPE;
9764: modell[k].subtype= VPDQ; /* Product time varying dummy * fixed quantitative */
9765: ncovv++; /* Varying variables without age */
9766: TvarV[ncovv]=Tvar[k];
9767: TvarVind[ncovv]=k;
9768: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){
9769: Fixed[k]= 1;
9770: Dummy[k]= 0;
9771: modell[k].maintype= VTYPE;
9772: modell[k].subtype= VPDD; /* Product time varying dummy * time varying dummy */
9773: ncovv++; /* Varying variables without age */
9774: TvarV[ncovv]=Tvar[k];
9775: TvarVind[ncovv]=k;
9776: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){
9777: Fixed[k]= 1;
9778: Dummy[k]= 1;
9779: modell[k].maintype= VTYPE;
9780: modell[k].subtype= VPDQ; /* Product time varying dummy * time varying quantitative */
9781: ncovv++; /* Varying variables without age */
9782: TvarV[ncovv]=Tvar[k];
9783: TvarVind[ncovv]=k;
9784: }
1.227 brouard 9785: }else if(Tvard[k1][1] <=ncovcol+nqv+ntv+nqtv){
1.240 brouard 9786: if(Tvard[k1][2] <=ncovcol){
9787: Fixed[k]= 1;
9788: Dummy[k]= 1;
9789: modell[k].maintype= VTYPE;
9790: modell[k].subtype= VPDQ; /* Product time varying quantitative * fixed dummy */
9791: ncovv++; /* Varying variables without age */
9792: TvarV[ncovv]=Tvar[k];
9793: TvarVind[ncovv]=k;
9794: }else if(Tvard[k1][2] <=ncovcol+nqv){
9795: Fixed[k]= 1;
9796: Dummy[k]= 1;
9797: modell[k].maintype= VTYPE;
9798: modell[k].subtype= VPQQ; /* Product time varying quantitative * fixed quantitative */
9799: ncovv++; /* Varying variables without age */
9800: TvarV[ncovv]=Tvar[k];
9801: TvarVind[ncovv]=k;
9802: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){
9803: Fixed[k]= 1;
9804: Dummy[k]= 1;
9805: modell[k].maintype= VTYPE;
9806: modell[k].subtype= VPDQ; /* Product time varying quantitative * time varying dummy */
9807: ncovv++; /* Varying variables without age */
9808: TvarV[ncovv]=Tvar[k];
9809: TvarVind[ncovv]=k;
9810: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){
9811: Fixed[k]= 1;
9812: Dummy[k]= 1;
9813: modell[k].maintype= VTYPE;
9814: modell[k].subtype= VPQQ; /* Product time varying quantitative * time varying quantitative */
9815: ncovv++; /* Varying variables without age */
9816: TvarV[ncovv]=Tvar[k];
9817: TvarVind[ncovv]=k;
9818: }
1.227 brouard 9819: }else{
1.240 brouard 9820: printf("Error unknown type of covariate: Tvard[%d][1]=%d,Tvard[%d][2]=%d\n",k1,Tvard[k1][1],k1,Tvard[k1][2]);
9821: fprintf(ficlog,"Error unknown type of covariate: Tvard[%d][1]=%d,Tvard[%d][2]=%d\n",k1,Tvard[k1][1],k1,Tvard[k1][2]);
9822: } /*end k1*/
1.225 brouard 9823: }else{
1.226 brouard 9824: printf("Error, current version can't treat for performance reasons, Tvar[%d]=%d, Typevar[%d]=%d\n", k, Tvar[k], k, Typevar[k]);
9825: 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 9826: }
1.227 brouard 9827: 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 9828: printf(" modell[%d].maintype=%d, modell[%d].subtype=%d\n",k,modell[k].maintype,k,modell[k].subtype);
1.227 brouard 9829: 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]);
9830: }
9831: /* Searching for doublons in the model */
9832: for(k1=1; k1<= cptcovt;k1++){
9833: for(k2=1; k2 <k1;k2++){
9834: if((Typevar[k1]==Typevar[k2]) && (Fixed[Tvar[k1]]==Fixed[Tvar[k2]]) && (Dummy[Tvar[k1]]==Dummy[Tvar[k2]] )){
1.234 brouard 9835: if((Typevar[k1] == 0 || Typevar[k1] == 1)){ /* Simple or age product */
9836: if(Tvar[k1]==Tvar[k2]){
9837: 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]]);
9838: 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);
9839: return(1);
9840: }
9841: }else if (Typevar[k1] ==2){
9842: k3=Tposprod[k1];
9843: k4=Tposprod[k2];
9844: 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])) ){
9845: 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]]);
9846: 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);
9847: return(1);
9848: }
9849: }
1.227 brouard 9850: }
9851: }
1.225 brouard 9852: }
9853: printf("ncoveff=%d, nqfveff=%d, ntveff=%d, nqtveff=%d, cptcovn=%d\n",ncoveff,nqfveff,ntveff,nqtveff,cptcovn);
9854: fprintf(ficlog,"ncoveff=%d, nqfveff=%d, ntveff=%d, nqtveff=%d, cptcovn=%d\n",ncoveff,nqfveff,ntveff,nqtveff,cptcovn);
1.234 brouard 9855: printf("ncovf=%d, ncovv=%d, ncova=%d, nsd=%d, nsq=%d\n",ncovf,ncovv,ncova,nsd,nsq);
9856: fprintf(ficlog,"ncovf=%d, ncovv=%d, ncova=%d, nsd=%d, nsq=%d\n",ncovf,ncovv,ncova,nsd, nsq);
1.137 brouard 9857: return (0); /* with covar[new additional covariate if product] and Tage if age */
1.164 brouard 9858: /*endread:*/
1.225 brouard 9859: printf("Exiting decodemodel: ");
9860: return (1);
1.136 brouard 9861: }
9862:
1.169 brouard 9863: int calandcheckages(int imx, int maxwav, double *agemin, double *agemax, int *nberr, int *nbwarn )
1.248 brouard 9864: {/* Check ages at death */
1.136 brouard 9865: int i, m;
1.218 brouard 9866: int firstone=0;
9867:
1.136 brouard 9868: for (i=1; i<=imx; i++) {
9869: for(m=2; (m<= maxwav); m++) {
9870: if (((int)mint[m][i]== 99) && (s[m][i] <= nlstate)){
9871: anint[m][i]=9999;
1.216 brouard 9872: if (s[m][i] != -2) /* Keeping initial status of unknown vital status */
9873: s[m][i]=-1;
1.136 brouard 9874: }
9875: if((int)moisdc[i]==99 && (int)andc[i]==9999 && s[m][i]>nlstate){
1.260 brouard 9876: *nberr = *nberr + 1;
1.218 brouard 9877: if(firstone == 0){
9878: firstone=1;
1.260 brouard 9879: 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 9880: }
1.262 brouard 9881: 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 9882: s[m][i]=-1; /* Droping the death status */
1.136 brouard 9883: }
9884: if((int)moisdc[i]==99 && (int)andc[i]!=9999 && s[m][i]>nlstate){
1.169 brouard 9885: (*nberr)++;
1.259 brouard 9886: 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 9887: 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 9888: s[m][i]=-2; /* We prefer to skip it (and to skip it in version 0.8a1 too */
1.136 brouard 9889: }
9890: }
9891: }
9892:
9893: for (i=1; i<=imx; i++) {
9894: agedc[i]=(moisdc[i]/12.+andc[i])-(moisnais[i]/12.+annais[i]);
9895: for(m=firstpass; (m<= lastpass); m++){
1.214 brouard 9896: 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 9897: if (s[m][i] >= nlstate+1) {
1.169 brouard 9898: if(agedc[i]>0){
9899: if((int)moisdc[i]!=99 && (int)andc[i]!=9999){
1.136 brouard 9900: agev[m][i]=agedc[i];
1.214 brouard 9901: /*if(moisdc[i]==99 && andc[i]==9999) s[m][i]=-1;*/
1.169 brouard 9902: }else {
1.136 brouard 9903: if ((int)andc[i]!=9999){
9904: nbwarn++;
9905: printf("Warning negative age at death: %ld line:%d\n",num[i],i);
9906: fprintf(ficlog,"Warning negative age at death: %ld line:%d\n",num[i],i);
9907: agev[m][i]=-1;
9908: }
9909: }
1.169 brouard 9910: } /* agedc > 0 */
1.214 brouard 9911: } /* end if */
1.136 brouard 9912: else if(s[m][i] !=9){ /* Standard case, age in fractional
9913: years but with the precision of a month */
9914: agev[m][i]=(mint[m][i]/12.+1./24.+anint[m][i])-(moisnais[i]/12.+1./24.+annais[i]);
9915: if((int)mint[m][i]==99 || (int)anint[m][i]==9999)
9916: agev[m][i]=1;
9917: else if(agev[m][i] < *agemin){
9918: *agemin=agev[m][i];
9919: printf(" Min anint[%d][%d]=%.2f annais[%d]=%.2f, agemin=%.2f\n",m,i,anint[m][i], i,annais[i], *agemin);
9920: }
9921: else if(agev[m][i] >*agemax){
9922: *agemax=agev[m][i];
1.156 brouard 9923: /* printf(" Max anint[%d][%d]=%.0f annais[%d]=%.0f, agemax=%.2f\n",m,i,anint[m][i], i,annais[i], *agemax);*/
1.136 brouard 9924: }
9925: /*agev[m][i]=anint[m][i]-annais[i];*/
9926: /* agev[m][i] = age[i]+2*m;*/
1.214 brouard 9927: } /* en if 9*/
1.136 brouard 9928: else { /* =9 */
1.214 brouard 9929: /* printf("Debug num[%d]=%ld s[%d][%d]=%d\n",i,num[i], m,i, s[m][i]); */
1.136 brouard 9930: agev[m][i]=1;
9931: s[m][i]=-1;
9932: }
9933: }
1.214 brouard 9934: else if(s[m][i]==0) /*= 0 Unknown */
1.136 brouard 9935: agev[m][i]=1;
1.214 brouard 9936: else{
9937: printf("Warning, num[%d]=%ld, s[%d][%d]=%d\n", i, num[i], m, i,s[m][i]);
9938: fprintf(ficlog, "Warning, num[%d]=%ld, s[%d][%d]=%d\n", i, num[i], m, i,s[m][i]);
9939: agev[m][i]=0;
9940: }
9941: } /* End for lastpass */
9942: }
1.136 brouard 9943:
9944: for (i=1; i<=imx; i++) {
9945: for(m=firstpass; (m<=lastpass); m++){
9946: if (s[m][i] > (nlstate+ndeath)) {
1.169 brouard 9947: (*nberr)++;
1.136 brouard 9948: 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);
9949: 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);
9950: return 1;
9951: }
9952: }
9953: }
9954:
9955: /*for (i=1; i<=imx; i++){
9956: for (m=firstpass; (m<lastpass); m++){
9957: printf("%ld %d %.lf %d %d\n", num[i],(covar[1][i]),agev[m][i],s[m][i],s[m+1][i]);
9958: }
9959:
9960: }*/
9961:
9962:
1.139 brouard 9963: printf("Total number of individuals= %d, Agemin = %.2f, Agemax= %.2f\n\n", imx, *agemin, *agemax);
9964: fprintf(ficlog,"Total number of individuals= %d, Agemin = %.2f, Agemax= %.2f\n\n", imx, *agemin, *agemax);
1.136 brouard 9965:
9966: return (0);
1.164 brouard 9967: /* endread:*/
1.136 brouard 9968: printf("Exiting calandcheckages: ");
9969: return (1);
9970: }
9971:
1.172 brouard 9972: #if defined(_MSC_VER)
9973: /*printf("Visual C++ compiler: %s \n;", _MSC_FULL_VER);*/
9974: /*fprintf(ficlog, "Visual C++ compiler: %s \n;", _MSC_FULL_VER);*/
9975: //#include "stdafx.h"
9976: //#include <stdio.h>
9977: //#include <tchar.h>
9978: //#include <windows.h>
9979: //#include <iostream>
9980: typedef BOOL(WINAPI *LPFN_ISWOW64PROCESS) (HANDLE, PBOOL);
9981:
9982: LPFN_ISWOW64PROCESS fnIsWow64Process;
9983:
9984: BOOL IsWow64()
9985: {
9986: BOOL bIsWow64 = FALSE;
9987:
9988: //typedef BOOL (APIENTRY *LPFN_ISWOW64PROCESS)
9989: // (HANDLE, PBOOL);
9990:
9991: //LPFN_ISWOW64PROCESS fnIsWow64Process;
9992:
9993: HMODULE module = GetModuleHandle(_T("kernel32"));
9994: const char funcName[] = "IsWow64Process";
9995: fnIsWow64Process = (LPFN_ISWOW64PROCESS)
9996: GetProcAddress(module, funcName);
9997:
9998: if (NULL != fnIsWow64Process)
9999: {
10000: if (!fnIsWow64Process(GetCurrentProcess(),
10001: &bIsWow64))
10002: //throw std::exception("Unknown error");
10003: printf("Unknown error\n");
10004: }
10005: return bIsWow64 != FALSE;
10006: }
10007: #endif
1.177 brouard 10008:
1.191 brouard 10009: void syscompilerinfo(int logged)
1.167 brouard 10010: {
10011: /* #include "syscompilerinfo.h"*/
1.185 brouard 10012: /* command line Intel compiler 32bit windows, XP compatible:*/
10013: /* /GS /W3 /Gy
10014: /Zc:wchar_t /Zi /O2 /Fd"Release\vc120.pdb" /D "WIN32" /D "NDEBUG" /D
10015: "_CONSOLE" /D "_LIB" /D "_USING_V110_SDK71_" /D "_UNICODE" /D
10016: "UNICODE" /Qipo /Zc:forScope /Gd /Oi /MT /Fa"Release\" /EHsc /nologo
1.186 brouard 10017: /Fo"Release\" /Qprof-dir "Release\" /Fp"Release\IMaCh.pch"
10018: */
10019: /* 64 bits */
1.185 brouard 10020: /*
10021: /GS /W3 /Gy
10022: /Zc:wchar_t /Zi /O2 /Fd"x64\Release\vc120.pdb" /D "WIN32" /D "NDEBUG"
10023: /D "_CONSOLE" /D "_LIB" /D "_UNICODE" /D "UNICODE" /Qipo /Zc:forScope
10024: /Oi /MD /Fa"x64\Release\" /EHsc /nologo /Fo"x64\Release\" /Qprof-dir
10025: "x64\Release\" /Fp"x64\Release\IMaCh.pch" */
10026: /* Optimization are useless and O3 is slower than O2 */
10027: /*
10028: /GS /W3 /Gy /Zc:wchar_t /Zi /O3 /Fd"x64\Release\vc120.pdb" /D "WIN32"
10029: /D "NDEBUG" /D "_CONSOLE" /D "_LIB" /D "_UNICODE" /D "UNICODE" /Qipo
10030: /Zc:forScope /Oi /MD /Fa"x64\Release\" /EHsc /nologo /Qparallel
10031: /Fo"x64\Release\" /Qprof-dir "x64\Release\" /Fp"x64\Release\IMaCh.pch"
10032: */
1.186 brouard 10033: /* Link is */ /* /OUT:"visual studio
1.185 brouard 10034: 2013\Projects\IMaCh\Release\IMaCh.exe" /MANIFEST /NXCOMPAT
10035: /PDB:"visual studio
10036: 2013\Projects\IMaCh\Release\IMaCh.pdb" /DYNAMICBASE
10037: "kernel32.lib" "user32.lib" "gdi32.lib" "winspool.lib"
10038: "comdlg32.lib" "advapi32.lib" "shell32.lib" "ole32.lib"
10039: "oleaut32.lib" "uuid.lib" "odbc32.lib" "odbccp32.lib"
10040: /MACHINE:X86 /OPT:REF /SAFESEH /INCREMENTAL:NO
10041: /SUBSYSTEM:CONSOLE",5.01" /MANIFESTUAC:"level='asInvoker'
10042: uiAccess='false'"
10043: /ManifestFile:"Release\IMaCh.exe.intermediate.manifest" /OPT:ICF
10044: /NOLOGO /TLBID:1
10045: */
1.177 brouard 10046: #if defined __INTEL_COMPILER
1.178 brouard 10047: #if defined(__GNUC__)
10048: struct utsname sysInfo; /* For Intel on Linux and OS/X */
10049: #endif
1.177 brouard 10050: #elif defined(__GNUC__)
1.179 brouard 10051: #ifndef __APPLE__
1.174 brouard 10052: #include <gnu/libc-version.h> /* Only on gnu */
1.179 brouard 10053: #endif
1.177 brouard 10054: struct utsname sysInfo;
1.178 brouard 10055: int cross = CROSS;
10056: if (cross){
10057: printf("Cross-");
1.191 brouard 10058: if(logged) fprintf(ficlog, "Cross-");
1.178 brouard 10059: }
1.174 brouard 10060: #endif
10061:
1.171 brouard 10062: #include <stdint.h>
1.178 brouard 10063:
1.191 brouard 10064: printf("Compiled with:");if(logged)fprintf(ficlog,"Compiled with:");
1.169 brouard 10065: #if defined(__clang__)
1.191 brouard 10066: printf(" Clang/LLVM");if(logged)fprintf(ficlog," Clang/LLVM"); /* Clang/LLVM. ---------------------------------------------- */
1.169 brouard 10067: #endif
10068: #if defined(__ICC) || defined(__INTEL_COMPILER)
1.191 brouard 10069: printf(" Intel ICC/ICPC");if(logged)fprintf(ficlog," Intel ICC/ICPC");/* Intel ICC/ICPC. ------------------------------------------ */
1.169 brouard 10070: #endif
10071: #if defined(__GNUC__) || defined(__GNUG__)
1.191 brouard 10072: printf(" GNU GCC/G++");if(logged)fprintf(ficlog," GNU GCC/G++");/* GNU GCC/G++. --------------------------------------------- */
1.169 brouard 10073: #endif
10074: #if defined(__HP_cc) || defined(__HP_aCC)
1.191 brouard 10075: printf(" Hewlett-Packard C/aC++");if(logged)fprintf(fcilog," Hewlett-Packard C/aC++"); /* Hewlett-Packard C/aC++. ---------------------------------- */
1.169 brouard 10076: #endif
10077: #if defined(__IBMC__) || defined(__IBMCPP__)
1.191 brouard 10078: printf(" IBM XL C/C++"); if(logged) fprintf(ficlog," IBM XL C/C++");/* IBM XL C/C++. -------------------------------------------- */
1.169 brouard 10079: #endif
10080: #if defined(_MSC_VER)
1.191 brouard 10081: printf(" Microsoft Visual Studio");if(logged)fprintf(ficlog," Microsoft Visual Studio");/* Microsoft Visual Studio. --------------------------------- */
1.169 brouard 10082: #endif
10083: #if defined(__PGI)
1.191 brouard 10084: printf(" Portland Group PGCC/PGCPP");if(logged) fprintf(ficlog," Portland Group PGCC/PGCPP");/* Portland Group PGCC/PGCPP. ------------------------------- */
1.169 brouard 10085: #endif
10086: #if defined(__SUNPRO_C) || defined(__SUNPRO_CC)
1.191 brouard 10087: printf(" Oracle Solaris Studio");if(logged)fprintf(ficlog," Oracle Solaris Studio\n");/* Oracle Solaris Studio. ----------------------------------- */
1.167 brouard 10088: #endif
1.191 brouard 10089: printf(" for "); if (logged) fprintf(ficlog, " for ");
1.169 brouard 10090:
1.167 brouard 10091: // http://stackoverflow.com/questions/4605842/how-to-identify-platform-compiler-from-preprocessor-macros
10092: #ifdef _WIN32 // note the underscore: without it, it's not msdn official!
10093: // Windows (x64 and x86)
1.191 brouard 10094: printf("Windows (x64 and x86) ");if(logged) fprintf(ficlog,"Windows (x64 and x86) ");
1.167 brouard 10095: #elif __unix__ // all unices, not all compilers
10096: // Unix
1.191 brouard 10097: printf("Unix ");if(logged) fprintf(ficlog,"Unix ");
1.167 brouard 10098: #elif __linux__
10099: // linux
1.191 brouard 10100: printf("linux ");if(logged) fprintf(ficlog,"linux ");
1.167 brouard 10101: #elif __APPLE__
1.174 brouard 10102: // Mac OS, not sure if this is covered by __posix__ and/or __unix__ though..
1.191 brouard 10103: printf("Mac OS ");if(logged) fprintf(ficlog,"Mac OS ");
1.167 brouard 10104: #endif
10105:
10106: /* __MINGW32__ */
10107: /* __CYGWIN__ */
10108: /* __MINGW64__ */
10109: // http://msdn.microsoft.com/en-us/library/b0084kay.aspx
10110: /* _MSC_VER //the Visual C++ compiler is 17.00.51106.1, the _MSC_VER macro evaluates to 1700. Type cl /? */
10111: /* _MSC_FULL_VER //the Visual C++ compiler is 15.00.20706.01, the _MSC_FULL_VER macro evaluates to 150020706 */
10112: /* _WIN64 // Defined for applications for Win64. */
10113: /* _M_X64 // Defined for compilations that target x64 processors. */
10114: /* _DEBUG // Defined when you compile with /LDd, /MDd, and /MTd. */
1.171 brouard 10115:
1.167 brouard 10116: #if UINTPTR_MAX == 0xffffffff
1.191 brouard 10117: printf(" 32-bit"); if(logged) fprintf(ficlog," 32-bit");/* 32-bit */
1.167 brouard 10118: #elif UINTPTR_MAX == 0xffffffffffffffff
1.191 brouard 10119: printf(" 64-bit"); if(logged) fprintf(ficlog," 64-bit");/* 64-bit */
1.167 brouard 10120: #else
1.191 brouard 10121: printf(" wtf-bit"); if(logged) fprintf(ficlog," wtf-bit");/* wtf */
1.167 brouard 10122: #endif
10123:
1.169 brouard 10124: #if defined(__GNUC__)
10125: # if defined(__GNUC_PATCHLEVEL__)
10126: # define __GNUC_VERSION__ (__GNUC__ * 10000 \
10127: + __GNUC_MINOR__ * 100 \
10128: + __GNUC_PATCHLEVEL__)
10129: # else
10130: # define __GNUC_VERSION__ (__GNUC__ * 10000 \
10131: + __GNUC_MINOR__ * 100)
10132: # endif
1.174 brouard 10133: printf(" using GNU C version %d.\n", __GNUC_VERSION__);
1.191 brouard 10134: if(logged) fprintf(ficlog, " using GNU C version %d.\n", __GNUC_VERSION__);
1.176 brouard 10135:
10136: if (uname(&sysInfo) != -1) {
10137: printf("Running on: %s %s %s %s %s\n",sysInfo.sysname, sysInfo.nodename, sysInfo.release, sysInfo.version, sysInfo.machine);
1.191 brouard 10138: 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 10139: }
10140: else
10141: perror("uname() error");
1.179 brouard 10142: //#ifndef __INTEL_COMPILER
10143: #if !defined (__INTEL_COMPILER) && !defined(__APPLE__)
1.174 brouard 10144: printf("GNU libc version: %s\n", gnu_get_libc_version());
1.191 brouard 10145: if(logged) fprintf(ficlog,"GNU libc version: %s\n", gnu_get_libc_version());
1.177 brouard 10146: #endif
1.169 brouard 10147: #endif
1.172 brouard 10148:
10149: // void main()
10150: // {
1.169 brouard 10151: #if defined(_MSC_VER)
1.174 brouard 10152: if (IsWow64()){
1.191 brouard 10153: printf("\nThe program (probably compiled for 32bit) is running under WOW64 (64bit) emulation.\n");
10154: if (logged) fprintf(ficlog, "\nThe program (probably compiled for 32bit) is running under WOW64 (64bit) emulation.\n");
1.174 brouard 10155: }
10156: else{
1.191 brouard 10157: printf("\nThe program is not running under WOW64 (i.e probably on a 64bit Windows).\n");
10158: if (logged) fprintf(ficlog, "\nThe programm is not running under WOW64 (i.e probably on a 64bit Windows).\n");
1.174 brouard 10159: }
1.172 brouard 10160: // printf("\nPress Enter to continue...");
10161: // getchar();
10162: // }
10163:
1.169 brouard 10164: #endif
10165:
1.167 brouard 10166:
1.219 brouard 10167: }
1.136 brouard 10168:
1.219 brouard 10169: int prevalence_limit(double *p, double **prlim, double ageminpar, double agemaxpar, double ftolpl, int *ncvyearp){
1.180 brouard 10170: /*--------------- Prevalence limit (period or stable prevalence) --------------*/
1.235 brouard 10171: int i, j, k, i1, k4=0, nres=0 ;
1.202 brouard 10172: /* double ftolpl = 1.e-10; */
1.180 brouard 10173: double age, agebase, agelim;
1.203 brouard 10174: double tot;
1.180 brouard 10175:
1.202 brouard 10176: strcpy(filerespl,"PL_");
10177: strcat(filerespl,fileresu);
10178: if((ficrespl=fopen(filerespl,"w"))==NULL) {
10179: printf("Problem with period (stable) prevalence resultfile: %s\n", filerespl);return 1;
10180: fprintf(ficlog,"Problem with period (stable) prevalence resultfile: %s\n", filerespl);return 1;
10181: }
1.227 brouard 10182: printf("\nComputing period (stable) prevalence: result on file '%s' \n", filerespl);
10183: fprintf(ficlog,"\nComputing period (stable) prevalence: result on file '%s' \n", filerespl);
1.202 brouard 10184: pstamp(ficrespl);
1.203 brouard 10185: fprintf(ficrespl,"# Period (stable) prevalence. Precision given by ftolpl=%g \n", ftolpl);
1.202 brouard 10186: fprintf(ficrespl,"#Age ");
10187: for(i=1; i<=nlstate;i++) fprintf(ficrespl,"%d-%d ",i,i);
10188: fprintf(ficrespl,"\n");
1.180 brouard 10189:
1.219 brouard 10190: /* prlim=matrix(1,nlstate,1,nlstate);*/ /* back in main */
1.180 brouard 10191:
1.219 brouard 10192: agebase=ageminpar;
10193: agelim=agemaxpar;
1.180 brouard 10194:
1.227 brouard 10195: /* i1=pow(2,ncoveff); */
1.234 brouard 10196: i1=pow(2,cptcoveff); /* Number of combination of dummy covariates */
1.219 brouard 10197: if (cptcovn < 1){i1=1;}
1.180 brouard 10198:
1.238 brouard 10199: for(k=1; k<=i1;k++){ /* For each combination k of dummy covariates in the model */
10200: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 10201: if(i1 != 1 && TKresult[nres]!= k)
1.238 brouard 10202: continue;
1.235 brouard 10203:
1.238 brouard 10204: /* for(cptcov=1,k=0;cptcov<=i1;cptcov++){ */
10205: /* for(cptcov=1,k=0;cptcov<=1;cptcov++){ */
10206: //for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){
10207: /* k=k+1; */
10208: /* to clean */
10209: //printf("cptcov=%d cptcod=%d codtab=%d\n",cptcov, cptcod,codtabm(cptcod,cptcov));
10210: fprintf(ficrespl,"#******");
10211: printf("#******");
10212: fprintf(ficlog,"#******");
10213: for(j=1;j<=cptcoveff ;j++) {/* all covariates */
10214: fprintf(ficrespl," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]); /* Here problem for varying dummy*/
10215: printf(" V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10216: fprintf(ficlog," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10217: }
10218: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
10219: printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
10220: fprintf(ficrespl," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
10221: fprintf(ficlog," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
10222: }
10223: fprintf(ficrespl,"******\n");
10224: printf("******\n");
10225: fprintf(ficlog,"******\n");
10226: if(invalidvarcomb[k]){
10227: printf("\nCombination (%d) ignored because no case \n",k);
10228: fprintf(ficrespl,"#Combination (%d) ignored because no case \n",k);
10229: fprintf(ficlog,"\nCombination (%d) ignored because no case \n",k);
10230: continue;
10231: }
1.219 brouard 10232:
1.238 brouard 10233: fprintf(ficrespl,"#Age ");
10234: for(j=1;j<=cptcoveff;j++) {
10235: fprintf(ficrespl,"V%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10236: }
10237: for(i=1; i<=nlstate;i++) fprintf(ficrespl," %d-%d ",i,i);
10238: fprintf(ficrespl,"Total Years_to_converge\n");
1.227 brouard 10239:
1.238 brouard 10240: for (age=agebase; age<=agelim; age++){
10241: /* for (age=agebase; age<=agebase; age++){ */
10242: prevalim(prlim, nlstate, p, age, oldm, savm, ftolpl, ncvyearp, k, nres);
10243: fprintf(ficrespl,"%.0f ",age );
10244: for(j=1;j<=cptcoveff;j++)
10245: fprintf(ficrespl,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10246: tot=0.;
10247: for(i=1; i<=nlstate;i++){
10248: tot += prlim[i][i];
10249: fprintf(ficrespl," %.5f", prlim[i][i]);
10250: }
10251: fprintf(ficrespl," %.3f %d\n", tot, *ncvyearp);
10252: } /* Age */
10253: /* was end of cptcod */
10254: } /* cptcov */
10255: } /* nres */
1.219 brouard 10256: return 0;
1.180 brouard 10257: }
10258:
1.218 brouard 10259: 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){
10260: /*--------------- Back Prevalence limit (period or stable prevalence) --------------*/
10261:
10262: /* Computes the back prevalence limit for any combination of covariate values
10263: * at any age between ageminpar and agemaxpar
10264: */
1.235 brouard 10265: int i, j, k, i1, nres=0 ;
1.217 brouard 10266: /* double ftolpl = 1.e-10; */
10267: double age, agebase, agelim;
10268: double tot;
1.218 brouard 10269: /* double ***mobaverage; */
10270: /* double **dnewm, **doldm, **dsavm; /\* for use *\/ */
1.217 brouard 10271:
10272: strcpy(fileresplb,"PLB_");
10273: strcat(fileresplb,fileresu);
10274: if((ficresplb=fopen(fileresplb,"w"))==NULL) {
10275: printf("Problem with period (stable) back prevalence resultfile: %s\n", fileresplb);return 1;
10276: fprintf(ficlog,"Problem with period (stable) back prevalence resultfile: %s\n", fileresplb);return 1;
10277: }
10278: printf("Computing period (stable) back prevalence: result on file '%s' \n", fileresplb);
10279: fprintf(ficlog,"Computing period (stable) back prevalence: result on file '%s' \n", fileresplb);
10280: pstamp(ficresplb);
10281: fprintf(ficresplb,"# Period (stable) back prevalence. Precision given by ftolpl=%g \n", ftolpl);
10282: fprintf(ficresplb,"#Age ");
10283: for(i=1; i<=nlstate;i++) fprintf(ficresplb,"%d-%d ",i,i);
10284: fprintf(ficresplb,"\n");
10285:
1.218 brouard 10286:
10287: /* prlim=matrix(1,nlstate,1,nlstate);*/ /* back in main */
10288:
10289: agebase=ageminpar;
10290: agelim=agemaxpar;
10291:
10292:
1.227 brouard 10293: i1=pow(2,cptcoveff);
1.218 brouard 10294: if (cptcovn < 1){i1=1;}
1.227 brouard 10295:
1.238 brouard 10296: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
10297: for(k=1; k<=i1;k++){ /* For any combination of dummy covariates, fixed and varying */
1.253 brouard 10298: if(i1 != 1 && TKresult[nres]!= k)
1.238 brouard 10299: continue;
10300: //printf("cptcov=%d cptcod=%d codtab=%d\n",cptcov, cptcod,codtabm(cptcod,cptcov));
10301: fprintf(ficresplb,"#******");
10302: printf("#******");
10303: fprintf(ficlog,"#******");
10304: for(j=1;j<=cptcoveff ;j++) {/* all covariates */
10305: fprintf(ficresplb," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10306: printf(" V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10307: fprintf(ficlog," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10308: }
10309: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
10310: printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
10311: fprintf(ficresplb," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
10312: fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
10313: }
10314: fprintf(ficresplb,"******\n");
10315: printf("******\n");
10316: fprintf(ficlog,"******\n");
10317: if(invalidvarcomb[k]){
10318: printf("\nCombination (%d) ignored because no cases \n",k);
10319: fprintf(ficresplb,"#Combination (%d) ignored because no cases \n",k);
10320: fprintf(ficlog,"\nCombination (%d) ignored because no cases \n",k);
10321: continue;
10322: }
1.218 brouard 10323:
1.238 brouard 10324: fprintf(ficresplb,"#Age ");
10325: for(j=1;j<=cptcoveff;j++) {
10326: fprintf(ficresplb,"V%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10327: }
10328: for(i=1; i<=nlstate;i++) fprintf(ficresplb," %d-%d ",i,i);
10329: fprintf(ficresplb,"Total Years_to_converge\n");
1.218 brouard 10330:
10331:
1.238 brouard 10332: for (age=agebase; age<=agelim; age++){
10333: /* for (age=agebase; age<=agebase; age++){ */
10334: if(mobilavproj > 0){
10335: /* bprevalim(bprlim, mobaverage, nlstate, p, age, ageminpar, agemaxpar, oldm, savm, doldm, dsavm, ftolpl, ncvyearp, k); */
10336: /* bprevalim(bprlim, mobaverage, nlstate, p, age, oldm, savm, dnewm, doldm, dsavm, ftolpl, ncvyearp, k); */
1.242 brouard 10337: bprevalim(bprlim, mobaverage, nlstate, p, age, ftolpl, ncvyearp, k, nres);
1.238 brouard 10338: }else if (mobilavproj == 0){
10339: 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);
10340: 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);
10341: exit(1);
10342: }else{
10343: /* bprevalim(bprlim, probs, nlstate, p, age, oldm, savm, dnewm, doldm, dsavm, ftolpl, ncvyearp, k); */
1.242 brouard 10344: bprevalim(bprlim, probs, nlstate, p, age, ftolpl, ncvyearp, k,nres);
1.266 brouard 10345: /* printf("TOTOT\n"); */
10346: /* exit(1); */
1.238 brouard 10347: }
10348: fprintf(ficresplb,"%.0f ",age );
10349: for(j=1;j<=cptcoveff;j++)
10350: fprintf(ficresplb,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10351: tot=0.;
10352: for(i=1; i<=nlstate;i++){
10353: tot += bprlim[i][i];
10354: fprintf(ficresplb," %.5f", bprlim[i][i]);
10355: }
10356: fprintf(ficresplb," %.3f %d\n", tot, *ncvyearp);
10357: } /* Age */
10358: /* was end of cptcod */
1.255 brouard 10359: /*fprintf(ficresplb,"\n");*/ /* Seems to be necessary for gnuplot only if two result lines and no covariate. */
1.238 brouard 10360: } /* end of any combination */
10361: } /* end of nres */
1.218 brouard 10362: /* hBijx(p, bage, fage); */
10363: /* fclose(ficrespijb); */
10364:
10365: return 0;
1.217 brouard 10366: }
1.218 brouard 10367:
1.180 brouard 10368: int hPijx(double *p, int bage, int fage){
10369: /*------------- h Pij x at various ages ------------*/
10370:
10371: int stepsize;
10372: int agelim;
10373: int hstepm;
10374: int nhstepm;
1.235 brouard 10375: int h, i, i1, j, k, k4, nres=0;
1.180 brouard 10376:
10377: double agedeb;
10378: double ***p3mat;
10379:
1.201 brouard 10380: strcpy(filerespij,"PIJ_"); strcat(filerespij,fileresu);
1.180 brouard 10381: if((ficrespij=fopen(filerespij,"w"))==NULL) {
10382: printf("Problem with Pij resultfile: %s\n", filerespij); return 1;
10383: fprintf(ficlog,"Problem with Pij resultfile: %s\n", filerespij); return 1;
10384: }
10385: printf("Computing pij: result on file '%s' \n", filerespij);
10386: fprintf(ficlog,"Computing pij: result on file '%s' \n", filerespij);
10387:
10388: stepsize=(int) (stepm+YEARM-1)/YEARM;
10389: /*if (stepm<=24) stepsize=2;*/
10390:
10391: agelim=AGESUP;
10392: hstepm=stepsize*YEARM; /* Every year of age */
10393: hstepm=hstepm/stepm; /* Typically 2 years, = 2/6 months = 4 */
1.218 brouard 10394:
1.180 brouard 10395: /* hstepm=1; aff par mois*/
10396: pstamp(ficrespij);
10397: fprintf(ficrespij,"#****** h Pij x Probability to be in state j at age x+h being in i at x ");
1.227 brouard 10398: i1= pow(2,cptcoveff);
1.218 brouard 10399: /* for(cptcov=1,k=0;cptcov<=i1;cptcov++){ */
10400: /* /\*for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){*\/ */
10401: /* k=k+1; */
1.235 brouard 10402: for(nres=1; nres <= nresult; nres++) /* For each resultline */
10403: for(k=1; k<=i1;k++){
1.253 brouard 10404: if(i1 != 1 && TKresult[nres]!= k)
1.235 brouard 10405: continue;
1.183 brouard 10406: fprintf(ficrespij,"\n#****** ");
1.227 brouard 10407: for(j=1;j<=cptcoveff;j++)
1.198 brouard 10408: fprintf(ficrespij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
1.235 brouard 10409: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
10410: printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
10411: fprintf(ficrespij," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
10412: }
1.183 brouard 10413: fprintf(ficrespij,"******\n");
10414:
10415: for (agedeb=fage; agedeb>=bage; agedeb--){ /* If stepm=6 months */
10416: nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
10417: nhstepm = nhstepm/hstepm; /* Typically 40/4=10 */
10418:
10419: /* nhstepm=nhstepm*YEARM; aff par mois*/
1.180 brouard 10420:
1.183 brouard 10421: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
10422: oldm=oldms;savm=savms;
1.235 brouard 10423: hpxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k, nres);
1.183 brouard 10424: fprintf(ficrespij,"# Cov Agex agex+h hpijx with i,j=");
10425: for(i=1; i<=nlstate;i++)
10426: for(j=1; j<=nlstate+ndeath;j++)
10427: fprintf(ficrespij," %1d-%1d",i,j);
10428: fprintf(ficrespij,"\n");
10429: for (h=0; h<=nhstepm; h++){
10430: /*agedebphstep = agedeb + h*hstepm/YEARM*stepm;*/
10431: fprintf(ficrespij,"%d %3.f %3.f",k, agedeb, agedeb + h*hstepm/YEARM*stepm );
1.180 brouard 10432: for(i=1; i<=nlstate;i++)
10433: for(j=1; j<=nlstate+ndeath;j++)
1.183 brouard 10434: fprintf(ficrespij," %.5f", p3mat[i][j][h]);
1.180 brouard 10435: fprintf(ficrespij,"\n");
10436: }
1.183 brouard 10437: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
10438: fprintf(ficrespij,"\n");
10439: }
1.180 brouard 10440: /*}*/
10441: }
1.218 brouard 10442: return 0;
1.180 brouard 10443: }
1.218 brouard 10444:
10445: int hBijx(double *p, int bage, int fage, double ***prevacurrent){
1.217 brouard 10446: /*------------- h Bij x at various ages ------------*/
10447:
10448: int stepsize;
1.218 brouard 10449: /* int agelim; */
10450: int ageminl;
1.217 brouard 10451: int hstepm;
10452: int nhstepm;
1.238 brouard 10453: int h, i, i1, j, k, nres;
1.218 brouard 10454:
1.217 brouard 10455: double agedeb;
10456: double ***p3mat;
1.218 brouard 10457:
10458: strcpy(filerespijb,"PIJB_"); strcat(filerespijb,fileresu);
10459: if((ficrespijb=fopen(filerespijb,"w"))==NULL) {
10460: printf("Problem with Pij back resultfile: %s\n", filerespijb); return 1;
10461: fprintf(ficlog,"Problem with Pij back resultfile: %s\n", filerespijb); return 1;
10462: }
10463: printf("Computing pij back: result on file '%s' \n", filerespijb);
10464: fprintf(ficlog,"Computing pij back: result on file '%s' \n", filerespijb);
10465:
10466: stepsize=(int) (stepm+YEARM-1)/YEARM;
10467: /*if (stepm<=24) stepsize=2;*/
1.217 brouard 10468:
1.218 brouard 10469: /* agelim=AGESUP; */
10470: ageminl=30;
10471: hstepm=stepsize*YEARM; /* Every year of age */
10472: hstepm=hstepm/stepm; /* Typically 2 years, = 2/6 months = 4 */
10473:
10474: /* hstepm=1; aff par mois*/
10475: pstamp(ficrespijb);
1.255 brouard 10476: 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 10477: i1= pow(2,cptcoveff);
1.218 brouard 10478: /* for(cptcov=1,k=0;cptcov<=i1;cptcov++){ */
10479: /* /\*for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){*\/ */
10480: /* k=k+1; */
1.238 brouard 10481: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
10482: for(k=1; k<=i1;k++){ /* For any combination of dummy covariates, fixed and varying */
1.253 brouard 10483: if(i1 != 1 && TKresult[nres]!= k)
1.238 brouard 10484: continue;
10485: fprintf(ficrespijb,"\n#****** ");
10486: for(j=1;j<=cptcoveff;j++)
10487: fprintf(ficrespijb,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10488: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
10489: fprintf(ficrespijb," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
10490: }
10491: fprintf(ficrespijb,"******\n");
1.264 brouard 10492: if(invalidvarcomb[k]){ /* Is it necessary here? */
1.238 brouard 10493: fprintf(ficrespijb,"\n#Combination (%d) ignored because no cases \n",k);
10494: continue;
10495: }
10496:
10497: /* for (agedeb=fage; agedeb>=bage; agedeb--){ /\* If stepm=6 months *\/ */
10498: for (agedeb=bage; agedeb<=fage; agedeb++){ /* If stepm=6 months and estepm=24 (2 years) */
10499: /* nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); /\* Typically 20 years = 20*12/6=40 *\/ */
10500: nhstepm=(int) rint((agedeb-ageminl)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
10501: nhstepm = nhstepm/hstepm; /* Typically 40/4=10, because estepm=24 stepm=6 => hstepm=24/6=4 */
10502:
10503: /* nhstepm=nhstepm*YEARM; aff par mois*/
10504:
1.266 brouard 10505: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); /* We can't have it at an upper level because of nhstepm */
10506: /* and memory limitations if stepm is small */
10507:
1.238 brouard 10508: /* oldm=oldms;savm=savms; */
10509: /* hbxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k); */
1.267 brouard 10510: hbxij(p3mat,nhstepm,agedeb,hstepm,p,prevacurrent,nlstate,stepm, k, nres);
1.238 brouard 10511: /* hbxij(p3mat,nhstepm,agedeb,hstepm,p,prevacurrent,nlstate,stepm,oldm,savm, dnewm, doldm, dsavm, k); */
1.255 brouard 10512: fprintf(ficrespijb,"# Cov Agex agex-h hbijx with i,j=");
1.217 brouard 10513: for(i=1; i<=nlstate;i++)
10514: for(j=1; j<=nlstate+ndeath;j++)
1.238 brouard 10515: fprintf(ficrespijb," %1d-%1d",i,j);
1.217 brouard 10516: fprintf(ficrespijb,"\n");
1.238 brouard 10517: for (h=0; h<=nhstepm; h++){
10518: /*agedebphstep = agedeb + h*hstepm/YEARM*stepm;*/
10519: fprintf(ficrespijb,"%d %3.f %3.f",k, agedeb, agedeb - h*hstepm/YEARM*stepm );
10520: /* fprintf(ficrespijb,"%d %3.f %3.f",k, agedeb, agedeb + h*hstepm/YEARM*stepm ); */
10521: for(i=1; i<=nlstate;i++)
10522: for(j=1; j<=nlstate+ndeath;j++)
10523: fprintf(ficrespijb," %.5f", p3mat[i][j][h]);
10524: fprintf(ficrespijb,"\n");
10525: }
10526: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
10527: fprintf(ficrespijb,"\n");
10528: } /* end age deb */
10529: } /* end combination */
10530: } /* end nres */
1.218 brouard 10531: return 0;
10532: } /* hBijx */
1.217 brouard 10533:
1.180 brouard 10534:
1.136 brouard 10535: /***********************************************/
10536: /**************** Main Program *****************/
10537: /***********************************************/
10538:
10539: int main(int argc, char *argv[])
10540: {
10541: #ifdef GSL
10542: const gsl_multimin_fminimizer_type *T;
10543: size_t iteri = 0, it;
10544: int rval = GSL_CONTINUE;
10545: int status = GSL_SUCCESS;
10546: double ssval;
10547: #endif
10548: int movingaverage(double ***probs, double bage,double fage, double ***mobaverage, int mobilav);
1.164 brouard 10549: int i,j, k, n=MAXN,iter=0,m,size=100, cptcod;
1.209 brouard 10550: int ncvyear=0; /* Number of years needed for the period prevalence to converge */
1.164 brouard 10551: int jj, ll, li, lj, lk;
1.136 brouard 10552: int numlinepar=0; /* Current linenumber of parameter file */
1.197 brouard 10553: int num_filled;
1.136 brouard 10554: int itimes;
10555: int NDIM=2;
10556: int vpopbased=0;
1.235 brouard 10557: int nres=0;
1.258 brouard 10558: int endishere=0;
1.136 brouard 10559:
1.164 brouard 10560: char ca[32], cb[32];
1.136 brouard 10561: /* FILE *fichtm; *//* Html File */
10562: /* FILE *ficgp;*/ /*Gnuplot File */
10563: struct stat info;
1.191 brouard 10564: double agedeb=0.;
1.194 brouard 10565:
10566: double ageminpar=AGEOVERFLOW,agemin=AGEOVERFLOW, agemaxpar=-AGEOVERFLOW, agemax=-AGEOVERFLOW;
1.219 brouard 10567: double ageminout=-AGEOVERFLOW,agemaxout=AGEOVERFLOW; /* Smaller Age range redefined after movingaverage */
1.136 brouard 10568:
1.165 brouard 10569: double fret;
1.191 brouard 10570: double dum=0.; /* Dummy variable */
1.136 brouard 10571: double ***p3mat;
1.218 brouard 10572: /* double ***mobaverage; */
1.164 brouard 10573:
10574: char line[MAXLINE];
1.197 brouard 10575: char path[MAXLINE],pathc[MAXLINE],pathcd[MAXLINE],pathtot[MAXLINE];
10576:
1.234 brouard 10577: char modeltemp[MAXLINE];
1.230 brouard 10578: char resultline[MAXLINE];
10579:
1.136 brouard 10580: char pathr[MAXLINE], pathimach[MAXLINE];
1.164 brouard 10581: char *tok, *val; /* pathtot */
1.136 brouard 10582: int firstobs=1, lastobs=10;
1.195 brouard 10583: int c, h , cpt, c2;
1.191 brouard 10584: int jl=0;
10585: int i1, j1, jk, stepsize=0;
1.194 brouard 10586: int count=0;
10587:
1.164 brouard 10588: int *tab;
1.136 brouard 10589: int mobilavproj=0 , prevfcast=0 ; /* moving average of prev, If prevfcast=1 prevalence projection */
1.217 brouard 10590: int backcast=0;
1.136 brouard 10591: int mobilav=0,popforecast=0;
1.191 brouard 10592: int hstepm=0, nhstepm=0;
1.136 brouard 10593: int agemortsup;
10594: float sumlpop=0.;
10595: double jprev1=1, mprev1=1,anprev1=2000,jprev2=1, mprev2=1,anprev2=2000;
10596: double jpyram=1, mpyram=1,anpyram=2000,jpyram1=1, mpyram1=1,anpyram1=2000;
10597:
1.191 brouard 10598: double bage=0, fage=110., age, agelim=0., agebase=0.;
1.136 brouard 10599: double ftolpl=FTOL;
10600: double **prlim;
1.217 brouard 10601: double **bprlim;
1.136 brouard 10602: double ***param; /* Matrix of parameters */
1.251 brouard 10603: double ***paramstart; /* Matrix of starting parameter values */
10604: double *p, *pstart; /* p=param[1][1] pstart is for starting values guessed by freqsummary */
1.136 brouard 10605: double **matcov; /* Matrix of covariance */
1.203 brouard 10606: double **hess; /* Hessian matrix */
1.136 brouard 10607: double ***delti3; /* Scale */
10608: double *delti; /* Scale */
10609: double ***eij, ***vareij;
10610: double **varpl; /* Variances of prevalence limits by age */
1.269 ! brouard 10611:
1.136 brouard 10612: double *epj, vepp;
1.164 brouard 10613:
1.136 brouard 10614: double dateprev1, dateprev2,jproj1=1,mproj1=1,anproj1=2000,jproj2=1,mproj2=1,anproj2=2000;
1.217 brouard 10615: double jback1=1,mback1=1,anback1=2000,jback2=1,mback2=1,anback2=2000;
10616:
1.136 brouard 10617: double **ximort;
1.145 brouard 10618: char *alph[]={"a","a","b","c","d","e"}, str[4]="1234";
1.136 brouard 10619: int *dcwave;
10620:
1.164 brouard 10621: char z[1]="c";
1.136 brouard 10622:
10623: /*char *strt;*/
10624: char strtend[80];
1.126 brouard 10625:
1.164 brouard 10626:
1.126 brouard 10627: /* setlocale (LC_ALL, ""); */
10628: /* bindtextdomain (PACKAGE, LOCALEDIR); */
10629: /* textdomain (PACKAGE); */
10630: /* setlocale (LC_CTYPE, ""); */
10631: /* setlocale (LC_MESSAGES, ""); */
10632:
10633: /* gettimeofday(&start_time, (struct timezone*)0); */ /* at first time */
1.157 brouard 10634: rstart_time = time(NULL);
10635: /* (void) gettimeofday(&start_time,&tzp);*/
10636: start_time = *localtime(&rstart_time);
1.126 brouard 10637: curr_time=start_time;
1.157 brouard 10638: /*tml = *localtime(&start_time.tm_sec);*/
10639: /* strcpy(strstart,asctime(&tml)); */
10640: strcpy(strstart,asctime(&start_time));
1.126 brouard 10641:
10642: /* printf("Localtime (at start)=%s",strstart); */
1.157 brouard 10643: /* tp.tm_sec = tp.tm_sec +86400; */
10644: /* tm = *localtime(&start_time.tm_sec); */
1.126 brouard 10645: /* tmg.tm_year=tmg.tm_year +dsign*dyear; */
10646: /* tmg.tm_mon=tmg.tm_mon +dsign*dmonth; */
10647: /* tmg.tm_hour=tmg.tm_hour + 1; */
1.157 brouard 10648: /* tp.tm_sec = mktime(&tmg); */
1.126 brouard 10649: /* strt=asctime(&tmg); */
10650: /* printf("Time(after) =%s",strstart); */
10651: /* (void) time (&time_value);
10652: * printf("time=%d,t-=%d\n",time_value,time_value-86400);
10653: * tm = *localtime(&time_value);
10654: * strstart=asctime(&tm);
10655: * printf("tim_value=%d,asctime=%s\n",time_value,strstart);
10656: */
10657:
10658: nberr=0; /* Number of errors and warnings */
10659: nbwarn=0;
1.184 brouard 10660: #ifdef WIN32
10661: _getcwd(pathcd, size);
10662: #else
1.126 brouard 10663: getcwd(pathcd, size);
1.184 brouard 10664: #endif
1.191 brouard 10665: syscompilerinfo(0);
1.196 brouard 10666: printf("\nIMaCh version %s, %s\n%s",version, copyright, fullversion);
1.126 brouard 10667: if(argc <=1){
10668: printf("\nEnter the parameter file name: ");
1.205 brouard 10669: if(!fgets(pathr,FILENAMELENGTH,stdin)){
10670: printf("ERROR Empty parameter file name\n");
10671: goto end;
10672: }
1.126 brouard 10673: i=strlen(pathr);
10674: if(pathr[i-1]=='\n')
10675: pathr[i-1]='\0';
1.156 brouard 10676: i=strlen(pathr);
1.205 brouard 10677: if(i >= 1 && pathr[i-1]==' ') {/* This may happen when dragging on oS/X! */
1.156 brouard 10678: pathr[i-1]='\0';
1.205 brouard 10679: }
10680: i=strlen(pathr);
10681: if( i==0 ){
10682: printf("ERROR Empty parameter file name\n");
10683: goto end;
10684: }
10685: for (tok = pathr; tok != NULL; ){
1.126 brouard 10686: printf("Pathr |%s|\n",pathr);
10687: while ((val = strsep(&tok, "\"" )) != NULL && *val == '\0');
10688: printf("val= |%s| pathr=%s\n",val,pathr);
10689: strcpy (pathtot, val);
10690: if(pathr[0] == '\0') break; /* Dirty */
10691: }
10692: }
10693: else{
10694: strcpy(pathtot,argv[1]);
10695: }
10696: /*if(getcwd(pathcd, MAXLINE)!= NULL)printf ("Error pathcd\n");*/
10697: /*cygwin_split_path(pathtot,path,optionfile);
10698: printf("pathtot=%s, path=%s, optionfile=%s\n",pathtot,path,optionfile);*/
10699: /* cutv(path,optionfile,pathtot,'\\');*/
10700:
10701: /* Split argv[0], imach program to get pathimach */
10702: printf("\nargv[0]=%s argv[1]=%s, \n",argv[0],argv[1]);
10703: split(argv[0],pathimach,optionfile,optionfilext,optionfilefiname);
10704: printf("\nargv[0]=%s pathimach=%s, \noptionfile=%s \noptionfilext=%s \noptionfilefiname=%s\n",argv[0],pathimach,optionfile,optionfilext,optionfilefiname);
10705: /* strcpy(pathimach,argv[0]); */
10706: /* Split argv[1]=pathtot, parameter file name to get path, optionfile, extension and name */
10707: split(pathtot,path,optionfile,optionfilext,optionfilefiname);
10708: printf("\npathtot=%s,\npath=%s,\noptionfile=%s \noptionfilext=%s \noptionfilefiname=%s\n",pathtot,path,optionfile,optionfilext,optionfilefiname);
1.184 brouard 10709: #ifdef WIN32
10710: _chdir(path); /* Can be a relative path */
10711: if(_getcwd(pathcd,MAXLINE) > 0) /* So pathcd is the full path */
10712: #else
1.126 brouard 10713: chdir(path); /* Can be a relative path */
1.184 brouard 10714: if (getcwd(pathcd, MAXLINE) > 0) /* So pathcd is the full path */
10715: #endif
10716: printf("Current directory %s!\n",pathcd);
1.126 brouard 10717: strcpy(command,"mkdir ");
10718: strcat(command,optionfilefiname);
10719: if((outcmd=system(command)) != 0){
1.169 brouard 10720: printf("Directory already exists (or can't create it) %s%s, err=%d\n",path,optionfilefiname,outcmd);
1.126 brouard 10721: /* fprintf(ficlog,"Problem creating directory %s%s\n",path,optionfilefiname); */
10722: /* fclose(ficlog); */
10723: /* exit(1); */
10724: }
10725: /* if((imk=mkdir(optionfilefiname))<0){ */
10726: /* perror("mkdir"); */
10727: /* } */
10728:
10729: /*-------- arguments in the command line --------*/
10730:
1.186 brouard 10731: /* Main Log file */
1.126 brouard 10732: strcat(filelog, optionfilefiname);
10733: strcat(filelog,".log"); /* */
10734: if((ficlog=fopen(filelog,"w"))==NULL) {
10735: printf("Problem with logfile %s\n",filelog);
10736: goto end;
10737: }
10738: fprintf(ficlog,"Log filename:%s\n",filelog);
1.197 brouard 10739: fprintf(ficlog,"Version %s %s",version,fullversion);
1.126 brouard 10740: fprintf(ficlog,"\nEnter the parameter file name: \n");
10741: fprintf(ficlog,"pathimach=%s\npathtot=%s\n\
10742: path=%s \n\
10743: optionfile=%s\n\
10744: optionfilext=%s\n\
1.156 brouard 10745: optionfilefiname='%s'\n",pathimach,pathtot,path,optionfile,optionfilext,optionfilefiname);
1.126 brouard 10746:
1.197 brouard 10747: syscompilerinfo(1);
1.167 brouard 10748:
1.126 brouard 10749: printf("Local time (at start):%s",strstart);
10750: fprintf(ficlog,"Local time (at start): %s",strstart);
10751: fflush(ficlog);
10752: /* (void) gettimeofday(&curr_time,&tzp); */
1.157 brouard 10753: /* printf("Elapsed time %d\n", asc_diff_time(curr_time.tm_sec-start_time.tm_sec,tmpout)); */
1.126 brouard 10754:
10755: /* */
10756: strcpy(fileres,"r");
10757: strcat(fileres, optionfilefiname);
1.201 brouard 10758: strcat(fileresu, optionfilefiname); /* Without r in front */
1.126 brouard 10759: strcat(fileres,".txt"); /* Other files have txt extension */
1.201 brouard 10760: strcat(fileresu,".txt"); /* Other files have txt extension */
1.126 brouard 10761:
1.186 brouard 10762: /* Main ---------arguments file --------*/
1.126 brouard 10763:
10764: if((ficpar=fopen(optionfile,"r"))==NULL) {
1.155 brouard 10765: printf("Problem with optionfile '%s' with errno='%s'\n",optionfile,strerror(errno));
10766: fprintf(ficlog,"Problem with optionfile '%s' with errno='%s'\n",optionfile,strerror(errno));
1.126 brouard 10767: fflush(ficlog);
1.149 brouard 10768: /* goto end; */
10769: exit(70);
1.126 brouard 10770: }
10771:
10772:
10773:
10774: strcpy(filereso,"o");
1.201 brouard 10775: strcat(filereso,fileresu);
1.126 brouard 10776: if((ficparo=fopen(filereso,"w"))==NULL) { /* opened on subdirectory */
10777: printf("Problem with Output resultfile: %s\n", filereso);
10778: fprintf(ficlog,"Problem with Output resultfile: %s\n", filereso);
10779: fflush(ficlog);
10780: goto end;
10781: }
10782:
10783: /* Reads comments: lines beginning with '#' */
10784: numlinepar=0;
1.197 brouard 10785:
10786: /* First parameter line */
10787: while(fgets(line, MAXLINE, ficpar)) {
10788: /* If line starts with a # it is a comment */
10789: if (line[0] == '#') {
10790: numlinepar++;
10791: fputs(line,stdout);
10792: fputs(line,ficparo);
10793: fputs(line,ficlog);
10794: continue;
10795: }else
10796: break;
10797: }
10798: if((num_filled=sscanf(line,"title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", \
10799: title, datafile, &lastobs, &firstpass,&lastpass)) !=EOF){
10800: if (num_filled != 5) {
10801: printf("Should be 5 parameters\n");
10802: }
1.126 brouard 10803: numlinepar++;
1.197 brouard 10804: printf("title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", title, datafile, lastobs, firstpass,lastpass);
10805: }
10806: /* Second parameter line */
10807: while(fgets(line, MAXLINE, ficpar)) {
10808: /* If line starts with a # it is a comment */
10809: if (line[0] == '#') {
10810: numlinepar++;
10811: fputs(line,stdout);
10812: fputs(line,ficparo);
10813: fputs(line,ficlog);
10814: continue;
10815: }else
10816: break;
10817: }
1.223 brouard 10818: 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", \
10819: &ftol, &stepm, &ncovcol, &nqv, &ntv, &nqtv, &nlstate, &ndeath, &maxwav, &mle, &weightopt)) !=EOF){
10820: if (num_filled != 11) {
10821: 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 10822: printf("but line=%s\n",line);
1.197 brouard 10823: }
1.223 brouard 10824: 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 10825: }
1.203 brouard 10826: /* ftolpl=6*ftol*1.e5; /\* 6.e-3 make convergences in less than 80 loops for the prevalence limit *\/ */
1.209 brouard 10827: /*ftolpl=6.e-4; *//* 6.e-3 make convergences in less than 80 loops for the prevalence limit */
1.197 brouard 10828: /* Third parameter line */
10829: while(fgets(line, MAXLINE, ficpar)) {
10830: /* If line starts with a # it is a comment */
10831: if (line[0] == '#') {
10832: numlinepar++;
10833: fputs(line,stdout);
10834: fputs(line,ficparo);
10835: fputs(line,ficlog);
10836: continue;
10837: }else
10838: break;
10839: }
1.201 brouard 10840: if((num_filled=sscanf(line,"model=1+age%[^.\n]", model)) !=EOF){
1.263 brouard 10841: if (num_filled == 0){
10842: printf("ERROR %d: Model should be at minimum 'model=1+age.' WITHOUT space:'%s'\n",num_filled, line);
10843: fprintf(ficlog,"ERROR %d: Model should be at minimum 'model=1+age.' WITHOUT space:'%s'\n",num_filled, line);
10844: model[0]='\0';
10845: goto end;
10846: } else if (num_filled != 1){
1.197 brouard 10847: printf("ERROR %d: Model should be at minimum 'model=1+age.' %s\n",num_filled, line);
10848: fprintf(ficlog,"ERROR %d: Model should be at minimum 'model=1+age.' %s\n",num_filled, line);
10849: model[0]='\0';
10850: goto end;
10851: }
10852: else{
10853: if (model[0]=='+'){
10854: for(i=1; i<=strlen(model);i++)
10855: modeltemp[i-1]=model[i];
1.201 brouard 10856: strcpy(model,modeltemp);
1.197 brouard 10857: }
10858: }
1.199 brouard 10859: /* printf(" model=1+age%s modeltemp= %s, model=%s\n",model, modeltemp, model);fflush(stdout); */
1.203 brouard 10860: printf("model=1+age+%s\n",model);fflush(stdout);
1.197 brouard 10861: }
10862: /* 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); */
10863: /* numlinepar=numlinepar+3; /\* In general *\/ */
10864: /* 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 10865: 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);
10866: 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 10867: fflush(ficlog);
1.190 brouard 10868: /* if(model[0]=='#'|| model[0]== '\0'){ */
10869: if(model[0]=='#'){
1.187 brouard 10870: printf("Error in 'model' line: model should start with 'model=1+age+' and end with '.' \n \
10871: 'model=1+age+.' or 'model=1+age+V1.' or 'model=1+age+age*age+V1+V1*age.' or \n \
10872: 'model=1+age+V1+V2.' or 'model=1+age+V1+V2+V1*V2.' etc. \n"); \
10873: if(mle != -1){
10874: printf("Fix the model line and run imach with mle=-1 to get a correct template of the parameter file.\n");
10875: exit(1);
10876: }
10877: }
1.126 brouard 10878: while((c=getc(ficpar))=='#' && c!= EOF){
10879: ungetc(c,ficpar);
10880: fgets(line, MAXLINE, ficpar);
10881: numlinepar++;
1.195 brouard 10882: if(line[1]=='q'){ /* This #q will quit imach (the answer is q) */
10883: z[0]=line[1];
10884: }
10885: /* printf("****line [1] = %c \n",line[1]); */
1.141 brouard 10886: fputs(line, stdout);
10887: //puts(line);
1.126 brouard 10888: fputs(line,ficparo);
10889: fputs(line,ficlog);
10890: }
10891: ungetc(c,ficpar);
10892:
10893:
1.145 brouard 10894: covar=matrix(0,NCOVMAX,1,n); /**< used in readdata */
1.268 brouard 10895: if(nqv>=1)coqvar=matrix(1,nqv,1,n); /**< Fixed quantitative covariate */
10896: if(nqtv>=1)cotqvar=ma3x(1,maxwav,1,nqtv,1,n); /**< Time varying quantitative covariate */
10897: if(ntv+nqtv>=1)cotvar=ma3x(1,maxwav,1,ntv+nqtv,1,n); /**< Time varying covariate (dummy and quantitative)*/
1.136 brouard 10898: cptcovn=0; /*Number of covariates, i.e. number of '+' in model statement plus one, indepently of n in Vn*/
10899: /* v1+v2+v3+v2*v4+v5*age makes cptcovn = 5
10900: v1+v2*age+v2*v3 makes cptcovn = 3
10901: */
10902: if (strlen(model)>1)
1.187 brouard 10903: 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 10904: else
1.187 brouard 10905: ncovmodel=2; /* Constant and age */
1.133 brouard 10906: nforce= (nlstate+ndeath-1)*nlstate; /* Number of forces ij from state i to j */
10907: npar= nforce*ncovmodel; /* Number of parameters like aij*/
1.131 brouard 10908: if(npar >MAXPARM || nlstate >NLSTATEMAX || ndeath >NDEATHMAX || ncovmodel>NCOVMAX){
10909: 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);
10910: 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);
10911: fflush(stdout);
10912: fclose (ficlog);
10913: goto end;
10914: }
1.126 brouard 10915: delti3= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
10916: delti=delti3[1][1];
10917: /*delti=vector(1,npar); *//* Scale of each paramater (output from hesscov)*/
10918: if(mle==-1){ /* Print a wizard for help writing covariance matrix */
1.247 brouard 10919: /* We could also provide initial parameters values giving by simple logistic regression
10920: * only one way, that is without matrix product. We will have nlstate maximizations */
10921: /* for(i=1;i<nlstate;i++){ */
10922: /* /\*reducing xi for 1 to npar to 1 to ncovmodel; *\/ */
10923: /* mlikeli(ficres,p, ncovmodel, ncovmodel, nlstate, ftol, funcnoprod); */
10924: /* } */
1.126 brouard 10925: prwizard(ncovmodel, nlstate, ndeath, model, ficparo);
1.191 brouard 10926: printf(" You chose mle=-1, look at file %s for a template of covariance matrix \n",filereso);
10927: fprintf(ficlog," You chose mle=-1, look at file %s for a template of covariance matrix \n",filereso);
1.126 brouard 10928: free_ma3x(delti3,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
10929: fclose (ficparo);
10930: fclose (ficlog);
10931: goto end;
10932: exit(0);
1.220 brouard 10933: } else if(mle==-5) { /* Main Wizard */
1.126 brouard 10934: prwizard(ncovmodel, nlstate, ndeath, model, ficparo);
1.192 brouard 10935: printf(" You chose mle=-3, look at file %s for a template of covariance matrix \n",filereso);
10936: fprintf(ficlog," You chose mle=-3, look at file %s for a template of covariance matrix \n",filereso);
1.126 brouard 10937: param= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
10938: matcov=matrix(1,npar,1,npar);
1.203 brouard 10939: hess=matrix(1,npar,1,npar);
1.220 brouard 10940: } else{ /* Begin of mle != -1 or -5 */
1.145 brouard 10941: /* Read guessed parameters */
1.126 brouard 10942: /* Reads comments: lines beginning with '#' */
10943: while((c=getc(ficpar))=='#' && c!= EOF){
10944: ungetc(c,ficpar);
10945: fgets(line, MAXLINE, ficpar);
10946: numlinepar++;
1.141 brouard 10947: fputs(line,stdout);
1.126 brouard 10948: fputs(line,ficparo);
10949: fputs(line,ficlog);
10950: }
10951: ungetc(c,ficpar);
10952:
10953: param= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
1.251 brouard 10954: paramstart= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
1.126 brouard 10955: for(i=1; i <=nlstate; i++){
1.234 brouard 10956: j=0;
1.126 brouard 10957: for(jj=1; jj <=nlstate+ndeath; jj++){
1.234 brouard 10958: if(jj==i) continue;
10959: j++;
10960: fscanf(ficpar,"%1d%1d",&i1,&j1);
10961: if ((i1 != i) || (j1 != jj)){
10962: printf("Error in line parameters number %d, %1d%1d instead of %1d%1d \n \
1.126 brouard 10963: It might be a problem of design; if ncovcol and the model are correct\n \
10964: run imach with mle=-1 to get a correct template of the parameter file.\n",numlinepar, i,j, i1, j1);
1.234 brouard 10965: exit(1);
10966: }
10967: fprintf(ficparo,"%1d%1d",i1,j1);
10968: if(mle==1)
10969: printf("%1d%1d",i,jj);
10970: fprintf(ficlog,"%1d%1d",i,jj);
10971: for(k=1; k<=ncovmodel;k++){
10972: fscanf(ficpar," %lf",¶m[i][j][k]);
10973: if(mle==1){
10974: printf(" %lf",param[i][j][k]);
10975: fprintf(ficlog," %lf",param[i][j][k]);
10976: }
10977: else
10978: fprintf(ficlog," %lf",param[i][j][k]);
10979: fprintf(ficparo," %lf",param[i][j][k]);
10980: }
10981: fscanf(ficpar,"\n");
10982: numlinepar++;
10983: if(mle==1)
10984: printf("\n");
10985: fprintf(ficlog,"\n");
10986: fprintf(ficparo,"\n");
1.126 brouard 10987: }
10988: }
10989: fflush(ficlog);
1.234 brouard 10990:
1.251 brouard 10991: /* Reads parameters values */
1.126 brouard 10992: p=param[1][1];
1.251 brouard 10993: pstart=paramstart[1][1];
1.126 brouard 10994:
10995: /* Reads comments: lines beginning with '#' */
10996: while((c=getc(ficpar))=='#' && c!= EOF){
10997: ungetc(c,ficpar);
10998: fgets(line, MAXLINE, ficpar);
10999: numlinepar++;
1.141 brouard 11000: fputs(line,stdout);
1.126 brouard 11001: fputs(line,ficparo);
11002: fputs(line,ficlog);
11003: }
11004: ungetc(c,ficpar);
11005:
11006: for(i=1; i <=nlstate; i++){
11007: for(j=1; j <=nlstate+ndeath-1; j++){
1.234 brouard 11008: fscanf(ficpar,"%1d%1d",&i1,&j1);
11009: if ( (i1-i) * (j1-j) != 0){
11010: printf("Error in line parameters number %d, %1d%1d instead of %1d%1d \n",numlinepar, i,j, i1, j1);
11011: exit(1);
11012: }
11013: printf("%1d%1d",i,j);
11014: fprintf(ficparo,"%1d%1d",i1,j1);
11015: fprintf(ficlog,"%1d%1d",i1,j1);
11016: for(k=1; k<=ncovmodel;k++){
11017: fscanf(ficpar,"%le",&delti3[i][j][k]);
11018: printf(" %le",delti3[i][j][k]);
11019: fprintf(ficparo," %le",delti3[i][j][k]);
11020: fprintf(ficlog," %le",delti3[i][j][k]);
11021: }
11022: fscanf(ficpar,"\n");
11023: numlinepar++;
11024: printf("\n");
11025: fprintf(ficparo,"\n");
11026: fprintf(ficlog,"\n");
1.126 brouard 11027: }
11028: }
11029: fflush(ficlog);
1.234 brouard 11030:
1.145 brouard 11031: /* Reads covariance matrix */
1.126 brouard 11032: delti=delti3[1][1];
1.220 brouard 11033:
11034:
1.126 brouard 11035: /* 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 11036:
1.126 brouard 11037: /* Reads comments: lines beginning with '#' */
11038: while((c=getc(ficpar))=='#' && c!= EOF){
11039: ungetc(c,ficpar);
11040: fgets(line, MAXLINE, ficpar);
11041: numlinepar++;
1.141 brouard 11042: fputs(line,stdout);
1.126 brouard 11043: fputs(line,ficparo);
11044: fputs(line,ficlog);
11045: }
11046: ungetc(c,ficpar);
1.220 brouard 11047:
1.126 brouard 11048: matcov=matrix(1,npar,1,npar);
1.203 brouard 11049: hess=matrix(1,npar,1,npar);
1.131 brouard 11050: for(i=1; i <=npar; i++)
11051: for(j=1; j <=npar; j++) matcov[i][j]=0.;
1.220 brouard 11052:
1.194 brouard 11053: /* Scans npar lines */
1.126 brouard 11054: for(i=1; i <=npar; i++){
1.226 brouard 11055: count=fscanf(ficpar,"%1d%1d%d",&i1,&j1,&jk);
1.194 brouard 11056: if(count != 3){
1.226 brouard 11057: printf("Error! Error in parameter file %s at line %d after line starting with %1d%1d%1d\n\
1.194 brouard 11058: This is probably because your covariance matrix doesn't \n contain exactly %d lines corresponding to your model line '1+age+%s'.\n\
11059: Please run with mle=-1 to get a correct covariance matrix.\n",optionfile,numlinepar, i1,j1,jk, npar, model);
1.226 brouard 11060: fprintf(ficlog,"Error! Error in parameter file %s at line %d after line starting with %1d%1d%1d\n\
1.194 brouard 11061: This is probably because your covariance matrix doesn't \n contain exactly %d lines corresponding to your model line '1+age+%s'.\n\
11062: Please run with mle=-1 to get a correct covariance matrix.\n",optionfile,numlinepar, i1,j1,jk, npar, model);
1.226 brouard 11063: exit(1);
1.220 brouard 11064: }else{
1.226 brouard 11065: if(mle==1)
11066: printf("%1d%1d%d",i1,j1,jk);
11067: }
11068: fprintf(ficlog,"%1d%1d%d",i1,j1,jk);
11069: fprintf(ficparo,"%1d%1d%d",i1,j1,jk);
1.126 brouard 11070: for(j=1; j <=i; j++){
1.226 brouard 11071: fscanf(ficpar," %le",&matcov[i][j]);
11072: if(mle==1){
11073: printf(" %.5le",matcov[i][j]);
11074: }
11075: fprintf(ficlog," %.5le",matcov[i][j]);
11076: fprintf(ficparo," %.5le",matcov[i][j]);
1.126 brouard 11077: }
11078: fscanf(ficpar,"\n");
11079: numlinepar++;
11080: if(mle==1)
1.220 brouard 11081: printf("\n");
1.126 brouard 11082: fprintf(ficlog,"\n");
11083: fprintf(ficparo,"\n");
11084: }
1.194 brouard 11085: /* End of read covariance matrix npar lines */
1.126 brouard 11086: for(i=1; i <=npar; i++)
11087: for(j=i+1;j<=npar;j++)
1.226 brouard 11088: matcov[i][j]=matcov[j][i];
1.126 brouard 11089:
11090: if(mle==1)
11091: printf("\n");
11092: fprintf(ficlog,"\n");
11093:
11094: fflush(ficlog);
11095:
11096: /*-------- Rewriting parameter file ----------*/
11097: strcpy(rfileres,"r"); /* "Rparameterfile */
11098: strcat(rfileres,optionfilefiname); /* Parameter file first name*/
11099: strcat(rfileres,"."); /* */
11100: strcat(rfileres,optionfilext); /* Other files have txt extension */
11101: if((ficres =fopen(rfileres,"w"))==NULL) {
1.201 brouard 11102: printf("Problem writing new parameter file: %s\n", rfileres);goto end;
11103: fprintf(ficlog,"Problem writing new parameter file: %s\n", rfileres);goto end;
1.126 brouard 11104: }
11105: fprintf(ficres,"#%s\n",version);
11106: } /* End of mle != -3 */
1.218 brouard 11107:
1.186 brouard 11108: /* Main data
11109: */
1.126 brouard 11110: n= lastobs;
11111: num=lvector(1,n);
11112: moisnais=vector(1,n);
11113: annais=vector(1,n);
11114: moisdc=vector(1,n);
11115: andc=vector(1,n);
1.220 brouard 11116: weight=vector(1,n);
1.126 brouard 11117: agedc=vector(1,n);
11118: cod=ivector(1,n);
1.220 brouard 11119: for(i=1;i<=n;i++){
1.234 brouard 11120: num[i]=0;
11121: moisnais[i]=0;
11122: annais[i]=0;
11123: moisdc[i]=0;
11124: andc[i]=0;
11125: agedc[i]=0;
11126: cod[i]=0;
11127: weight[i]=1.0; /* Equal weights, 1 by default */
11128: }
1.126 brouard 11129: mint=matrix(1,maxwav,1,n);
11130: anint=matrix(1,maxwav,1,n);
1.131 brouard 11131: s=imatrix(1,maxwav+1,1,n); /* s[i][j] health state for wave i and individual j */
1.126 brouard 11132: tab=ivector(1,NCOVMAX);
1.144 brouard 11133: ncodemax=ivector(1,NCOVMAX); /* Number of code per covariate; if O and 1 only, 2**ncov; V1+V2+V3+V4=>16 */
1.192 brouard 11134: 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 11135:
1.136 brouard 11136: /* Reads data from file datafile */
11137: if (readdata(datafile, firstobs, lastobs, &imx)==1)
11138: goto end;
11139:
11140: /* Calculation of the number of parameters from char model */
1.234 brouard 11141: /* modelsav=V2+V1+V4+age*V3 strb=age*V3 stra=V2+V1+V4
1.137 brouard 11142: k=4 (age*V3) Tvar[k=4]= 3 (from V3) Tag[cptcovage=1]=4
11143: k=3 V4 Tvar[k=3]= 4 (from V4)
11144: k=2 V1 Tvar[k=2]= 1 (from V1)
11145: k=1 Tvar[1]=2 (from V2)
1.234 brouard 11146: */
11147:
11148: Tvar=ivector(1,NCOVMAX); /* Was 15 changed to NCOVMAX. */
11149: TvarsDind=ivector(1,NCOVMAX); /* */
11150: TvarsD=ivector(1,NCOVMAX); /* */
11151: TvarsQind=ivector(1,NCOVMAX); /* */
11152: TvarsQ=ivector(1,NCOVMAX); /* */
1.232 brouard 11153: TvarF=ivector(1,NCOVMAX); /* */
11154: TvarFind=ivector(1,NCOVMAX); /* */
11155: TvarV=ivector(1,NCOVMAX); /* */
11156: TvarVind=ivector(1,NCOVMAX); /* */
11157: TvarA=ivector(1,NCOVMAX); /* */
11158: TvarAind=ivector(1,NCOVMAX); /* */
1.231 brouard 11159: TvarFD=ivector(1,NCOVMAX); /* */
11160: TvarFDind=ivector(1,NCOVMAX); /* */
11161: TvarFQ=ivector(1,NCOVMAX); /* */
11162: TvarFQind=ivector(1,NCOVMAX); /* */
11163: TvarVD=ivector(1,NCOVMAX); /* */
11164: TvarVDind=ivector(1,NCOVMAX); /* */
11165: TvarVQ=ivector(1,NCOVMAX); /* */
11166: TvarVQind=ivector(1,NCOVMAX); /* */
11167:
1.230 brouard 11168: Tvalsel=vector(1,NCOVMAX); /* */
1.233 brouard 11169: Tvarsel=ivector(1,NCOVMAX); /* */
1.226 brouard 11170: Typevar=ivector(-1,NCOVMAX); /* -1 to 2 */
11171: Fixed=ivector(-1,NCOVMAX); /* -1 to 3 */
11172: Dummy=ivector(-1,NCOVMAX); /* -1 to 3 */
1.137 brouard 11173: /* V2+V1+V4+age*V3 is a model with 4 covariates (3 plus signs).
11174: For each model-covariate stores the data-covariate id. Tvar[1]=2, Tvar[2]=1, Tvar[3]=4,
11175: Tvar[4=age*V3] is 3 and 'age' is recorded in Tage.
11176: */
11177: /* For model-covariate k tells which data-covariate to use but
11178: because this model-covariate is a construction we invent a new column
11179: ncovcol + k1
11180: If already ncovcol=4 and model=V2+V1+V1*V4+age*V3
11181: Tvar[3=V1*V4]=4+1 etc */
1.227 brouard 11182: Tprod=ivector(1,NCOVMAX); /* Gives the k position of the k1 product */
11183: Tposprod=ivector(1,NCOVMAX); /* Gives the k1 product from the k position */
1.137 brouard 11184: /* Tprod[k1=1]=3(=V1*V4) for V2+V1+V1*V4+age*V3
11185: if V2+V1+V1*V4+age*V3+V3*V2 TProd[k1=2]=5 (V3*V2)
1.227 brouard 11186: Tposprod[k]=k1 , Tposprod[3]=1, Tposprod[5]=2
1.137 brouard 11187: */
1.145 brouard 11188: Tvaraff=ivector(1,NCOVMAX); /* Unclear */
11189: 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 11190: * For V3*V2 (in V2+V1+V1*V4+age*V3+V3*V2), V3*V2 position is 2nd.
11191: * Tvard[k1=2][1]=3 (V3) Tvard[k1=2][2]=2(V2) */
1.145 brouard 11192: Tage=ivector(1,NCOVMAX); /* Gives the covariate id of covariates associated with age: V2 + V1 + age*V4 + V3*age
1.137 brouard 11193: 4 covariates (3 plus signs)
11194: Tage[1=V3*age]= 4; Tage[2=age*V4] = 3
11195: */
1.230 brouard 11196: Tmodelind=ivector(1,NCOVMAX);/** gives the k model position of an
1.227 brouard 11197: * individual dummy, fixed or varying:
11198: * Tmodelind[Tvaraff[3]]=9,Tvaraff[1]@9={4,
11199: * 3, 1, 0, 0, 0, 0, 0, 0},
1.230 brouard 11200: * model=V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 ,
11201: * V1 df, V2 qf, V3 & V4 dv, V5 qv
11202: * Tmodelind[1]@9={9,0,3,2,}*/
11203: TmodelInvind=ivector(1,NCOVMAX); /* TmodelInvind=Tvar[k]- ncovcol-nqv={5-2-1=2,*/
11204: TmodelInvQind=ivector(1,NCOVMAX);/** gives the k model position of an
1.228 brouard 11205: * individual quantitative, fixed or varying:
11206: * Tmodelqind[1]=1,Tvaraff[1]@9={4,
11207: * 3, 1, 0, 0, 0, 0, 0, 0},
11208: * model=V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1*/
1.186 brouard 11209: /* Main decodemodel */
11210:
1.187 brouard 11211:
1.223 brouard 11212: if(decodemodel(model, lastobs) == 1) /* In order to get Tvar[k] V4+V3+V5 p Tvar[1]@3 = {4, 3, 5}*/
1.136 brouard 11213: goto end;
11214:
1.137 brouard 11215: if((double)(lastobs-imx)/(double)imx > 1.10){
11216: nbwarn++;
11217: 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);
11218: 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);
11219: }
1.136 brouard 11220: /* if(mle==1){*/
1.137 brouard 11221: if (weightopt != 1) { /* Maximisation without weights. We can have weights different from 1 but want no weight*/
11222: for(i=1;i<=imx;i++) weight[i]=1.0; /* changed to imx */
1.136 brouard 11223: }
11224:
11225: /*-calculation of age at interview from date of interview and age at death -*/
11226: agev=matrix(1,maxwav,1,imx);
11227:
11228: if(calandcheckages(imx, maxwav, &agemin, &agemax, &nberr, &nbwarn) == 1)
11229: goto end;
11230:
1.126 brouard 11231:
1.136 brouard 11232: agegomp=(int)agemin;
11233: free_vector(moisnais,1,n);
11234: free_vector(annais,1,n);
1.126 brouard 11235: /* free_matrix(mint,1,maxwav,1,n);
11236: free_matrix(anint,1,maxwav,1,n);*/
1.215 brouard 11237: /* free_vector(moisdc,1,n); */
11238: /* free_vector(andc,1,n); */
1.145 brouard 11239: /* */
11240:
1.126 brouard 11241: wav=ivector(1,imx);
1.214 brouard 11242: /* dh=imatrix(1,lastpass-firstpass+1,1,imx); */
11243: /* bh=imatrix(1,lastpass-firstpass+1,1,imx); */
11244: /* mw=imatrix(1,lastpass-firstpass+1,1,imx); */
11245: 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.*/
11246: bh=imatrix(1,lastpass-firstpass+2,1,imx);
11247: mw=imatrix(1,lastpass-firstpass+2,1,imx);
1.126 brouard 11248:
11249: /* Concatenates waves */
1.214 brouard 11250: /* Concatenates waves: wav[i] is the number of effective (useful waves) of individual i.
11251: Death is a valid wave (if date is known).
11252: mw[mi][i] is the number of (mi=1 to wav[i]) effective wave out of mi of individual i
11253: dh[m][i] or dh[mw[mi][i]][i] is the delay between two effective waves m=mw[mi][i]
11254: and mw[mi+1][i]. dh depends on stepm.
11255: */
11256:
1.126 brouard 11257: concatwav(wav, dh, bh, mw, s, agedc, agev, firstpass, lastpass, imx, nlstate, stepm);
1.248 brouard 11258: /* Concatenates waves */
1.145 brouard 11259:
1.215 brouard 11260: free_vector(moisdc,1,n);
11261: free_vector(andc,1,n);
11262:
1.126 brouard 11263: /* Routine tricode is to calculate cptcoveff (real number of unique covariates) and to associate covariable number and modality */
11264: nbcode=imatrix(0,NCOVMAX,0,NCOVMAX);
11265: ncodemax[1]=1;
1.145 brouard 11266: Ndum =ivector(-1,NCOVMAX);
1.225 brouard 11267: cptcoveff=0;
1.220 brouard 11268: if (ncovmodel-nagesqr > 2 ){ /* That is if covariate other than cst, age and age*age */
11269: tricode(&cptcoveff,Tvar,nbcode,imx, Ndum); /**< Fills nbcode[Tvar[j]][l]; */
1.227 brouard 11270: }
11271:
11272: ncovcombmax=pow(2,cptcoveff);
11273: invalidvarcomb=ivector(1, ncovcombmax);
11274: for(i=1;i<ncovcombmax;i++)
11275: invalidvarcomb[i]=0;
11276:
1.211 brouard 11277: /* Nbcode gives the value of the lth modality (currently 1 to 2) of jth covariate, in
1.186 brouard 11278: V2+V1*age, there are 3 covariates Tvar[2]=1 (V1).*/
1.211 brouard 11279: /* 1 to ncodemax[j] which is the maximum value of this jth covariate */
1.227 brouard 11280:
1.200 brouard 11281: /* codtab=imatrix(1,100,1,10);*/ /* codtab[h,k]=( (h-1) - mod(k-1,2**(k-1) )/2**(k-1) */
1.198 brouard 11282: /*printf(" codtab[1,1],codtab[100,10]=%d,%d\n", codtab[1][1],codtabm(100,10));*/
1.186 brouard 11283: /* codtab gives the value 1 or 2 of the hth combination of k covariates (1 or 2).*/
1.211 brouard 11284: /* nbcode[Tvaraff[j]][codtabm(h,j)]) : if there are only 2 modalities for a covariate j,
11285: * codtabm(h,j) gives its value classified at position h and nbcode gives how it is coded
11286: * (currently 0 or 1) in the data.
11287: * In a loop on h=1 to 2**k, and a loop on j (=1 to k), we get the value of
11288: * corresponding modality (h,j).
11289: */
11290:
1.145 brouard 11291: h=0;
11292: /*if (cptcovn > 0) */
1.126 brouard 11293: m=pow(2,cptcoveff);
11294:
1.144 brouard 11295: /**< codtab(h,k) k = codtab[h,k]=( (h-1) - mod(k-1,2**(k-1) )/2**(k-1) + 1
1.211 brouard 11296: * For k=4 covariates, h goes from 1 to m=2**k
11297: * codtabm(h,k)= (1 & (h-1) >> (k-1)) + 1;
11298: * #define codtabm(h,k) (1 & (h-1) >> (k-1))+1
1.186 brouard 11299: * h\k 1 2 3 4
1.143 brouard 11300: *______________________________
11301: * 1 i=1 1 i=1 1 i=1 1 i=1 1
11302: * 2 2 1 1 1
11303: * 3 i=2 1 2 1 1
11304: * 4 2 2 1 1
11305: * 5 i=3 1 i=2 1 2 1
11306: * 6 2 1 2 1
11307: * 7 i=4 1 2 2 1
11308: * 8 2 2 2 1
1.197 brouard 11309: * 9 i=5 1 i=3 1 i=2 1 2
11310: * 10 2 1 1 2
11311: * 11 i=6 1 2 1 2
11312: * 12 2 2 1 2
11313: * 13 i=7 1 i=4 1 2 2
11314: * 14 2 1 2 2
11315: * 15 i=8 1 2 2 2
11316: * 16 2 2 2 2
1.143 brouard 11317: */
1.212 brouard 11318: /* How to do the opposite? From combination h (=1 to 2**k) how to get the value on the covariates? */
1.211 brouard 11319: /* from h=5 and m, we get then number of covariates k=log(m)/log(2)=4
11320: * and the value of each covariate?
11321: * V1=1, V2=1, V3=2, V4=1 ?
11322: * h-1=4 and 4 is 0100 or reverse 0010, and +1 is 1121 ok.
11323: * h=6, 6-1=5, 5 is 0101, 1010, 2121, V1=2nd, V2=1st, V3=2nd, V4=1st.
11324: * In order to get the real value in the data, we use nbcode
11325: * nbcode[Tvar[3][2nd]]=1 and nbcode[Tvar[4][1]]=0
11326: * We are keeping this crazy system in order to be able (in the future?)
11327: * to have more than 2 values (0 or 1) for a covariate.
11328: * #define codtabm(h,k) (1 & (h-1) >> (k-1))+1
11329: * h=6, k=2? h-1=5=0101, reverse 1010, +1=2121, k=2nd position: value is 1: codtabm(6,2)=1
11330: * bbbbbbbb
11331: * 76543210
11332: * h-1 00000101 (6-1=5)
1.219 brouard 11333: *(h-1)>>(k-1)= 00000010 >> (2-1) = 1 right shift
1.211 brouard 11334: * &
11335: * 1 00000001 (1)
1.219 brouard 11336: * 00000000 = 1 & ((h-1) >> (k-1))
11337: * +1= 00000001 =1
1.211 brouard 11338: *
11339: * h=14, k=3 => h'=h-1=13, k'=k-1=2
11340: * h' 1101 =2^3+2^2+0x2^1+2^0
11341: * >>k' 11
11342: * & 00000001
11343: * = 00000001
11344: * +1 = 00000010=2 = codtabm(14,3)
11345: * Reverse h=6 and m=16?
11346: * cptcoveff=log(16)/log(2)=4 covariate: 6-1=5=0101 reversed=1010 +1=2121 =>V1=2, V2=1, V3=2, V4=1.
11347: * for (j=1 to cptcoveff) Vj=decodtabm(j,h,cptcoveff)
11348: * decodtabm(h,j,cptcoveff)= (((h-1) >> (j-1)) & 1) +1
11349: * decodtabm(h,j,cptcoveff)= (h <= (1<<cptcoveff)?(((h-1) >> (j-1)) & 1) +1 : -1)
11350: * V3=decodtabm(14,3,2**4)=2
11351: * h'=13 1101 =2^3+2^2+0x2^1+2^0
11352: *(h-1) >> (j-1) 0011 =13 >> 2
11353: * &1 000000001
11354: * = 000000001
11355: * +1= 000000010 =2
11356: * 2211
11357: * V1=1+1, V2=0+1, V3=1+1, V4=1+1
11358: * V3=2
1.220 brouard 11359: * codtabm and decodtabm are identical
1.211 brouard 11360: */
11361:
1.145 brouard 11362:
11363: free_ivector(Ndum,-1,NCOVMAX);
11364:
11365:
1.126 brouard 11366:
1.186 brouard 11367: /* Initialisation of ----------- gnuplot -------------*/
1.126 brouard 11368: strcpy(optionfilegnuplot,optionfilefiname);
11369: if(mle==-3)
1.201 brouard 11370: strcat(optionfilegnuplot,"-MORT_");
1.126 brouard 11371: strcat(optionfilegnuplot,".gp");
11372:
11373: if((ficgp=fopen(optionfilegnuplot,"w"))==NULL) {
11374: printf("Problem with file %s",optionfilegnuplot);
11375: }
11376: else{
1.204 brouard 11377: fprintf(ficgp,"\n# IMaCh-%s\n", version);
1.126 brouard 11378: fprintf(ficgp,"# %s\n", optionfilegnuplot);
1.141 brouard 11379: //fprintf(ficgp,"set missing 'NaNq'\n");
11380: fprintf(ficgp,"set datafile missing 'NaNq'\n");
1.126 brouard 11381: }
11382: /* fclose(ficgp);*/
1.186 brouard 11383:
11384:
11385: /* Initialisation of --------- index.htm --------*/
1.126 brouard 11386:
11387: strcpy(optionfilehtm,optionfilefiname); /* Main html file */
11388: if(mle==-3)
1.201 brouard 11389: strcat(optionfilehtm,"-MORT_");
1.126 brouard 11390: strcat(optionfilehtm,".htm");
11391: if((fichtm=fopen(optionfilehtm,"w"))==NULL) {
1.131 brouard 11392: printf("Problem with %s \n",optionfilehtm);
11393: exit(0);
1.126 brouard 11394: }
11395:
11396: strcpy(optionfilehtmcov,optionfilefiname); /* Only for matrix of covariance */
11397: strcat(optionfilehtmcov,"-cov.htm");
11398: if((fichtmcov=fopen(optionfilehtmcov,"w"))==NULL) {
11399: printf("Problem with %s \n",optionfilehtmcov), exit(0);
11400: }
11401: else{
11402: fprintf(fichtmcov,"<html><head>\n<title>IMaCh Cov %s</title></head>\n <body><font size=\"2\">%s <br> %s</font> \
11403: <hr size=\"2\" color=\"#EC5E5E\"> \n\
1.204 brouard 11404: Title=%s <br>Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s<br>\n",\
1.126 brouard 11405: optionfilehtmcov,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model);
11406: }
11407:
1.213 brouard 11408: 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 11409: <hr size=\"2\" color=\"#EC5E5E\"> \n\
11410: <font size=\"2\">IMaCh-%s <br> %s</font> \
1.126 brouard 11411: <hr size=\"2\" color=\"#EC5E5E\"> \n\
1.204 brouard 11412: Title=%s <br>Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s<br>\n\
1.126 brouard 11413: \n\
11414: <hr size=\"2\" color=\"#EC5E5E\">\
11415: <ul><li><h4>Parameter files</h4>\n\
11416: - Parameter file: <a href=\"%s.%s\">%s.%s</a><br>\n\
11417: - Copy of the parameter file: <a href=\"o%s\">o%s</a><br>\n\
11418: - Log file of the run: <a href=\"%s\">%s</a><br>\n\
11419: - Gnuplot file name: <a href=\"%s\">%s</a><br>\n\
11420: - Date and time at start: %s</ul>\n",\
11421: optionfilehtm,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model,\
11422: optionfilefiname,optionfilext,optionfilefiname,optionfilext,\
11423: fileres,fileres,\
11424: filelog,filelog,optionfilegnuplot,optionfilegnuplot,strstart);
11425: fflush(fichtm);
11426:
11427: strcpy(pathr,path);
11428: strcat(pathr,optionfilefiname);
1.184 brouard 11429: #ifdef WIN32
11430: _chdir(optionfilefiname); /* Move to directory named optionfile */
11431: #else
1.126 brouard 11432: chdir(optionfilefiname); /* Move to directory named optionfile */
1.184 brouard 11433: #endif
11434:
1.126 brouard 11435:
1.220 brouard 11436: /* Calculates basic frequencies. Computes observed prevalence at single age
11437: and for any valid combination of covariates
1.126 brouard 11438: and prints on file fileres'p'. */
1.251 brouard 11439: freqsummary(fileres, p, pstart, agemin, agemax, s, agev, nlstate, imx, Tvaraff, invalidvarcomb, nbcode, ncodemax,mint,anint,strstart, \
1.227 brouard 11440: firstpass, lastpass, stepm, weightopt, model);
1.126 brouard 11441:
11442: fprintf(fichtm,"\n");
11443: fprintf(fichtm,"<br>Total number of observations=%d <br>\n\
11444: Youngest age at first (selected) pass %.2f, oldest age %.2f<br>\n\
11445: Interval (in months) between two waves: Min=%d Max=%d Mean=%.2lf<br>\n",\
11446: imx,agemin,agemax,jmin,jmax,jmean);
11447: pmmij= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
1.268 brouard 11448: oldms= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
11449: newms= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
11450: savms= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
11451: oldm=oldms; newm=newms; savm=savms; /* Keeps fixed addresses to free */
1.218 brouard 11452:
1.126 brouard 11453: /* For Powell, parameters are in a vector p[] starting at p[1]
11454: so we point p on param[1][1] so that p[1] maps on param[1][1][1] */
11455: p=param[1][1]; /* *(*(*(param +1)+1)+0) */
11456:
11457: globpr=0; /* To get the number ipmx of contributions and the sum of weights*/
1.186 brouard 11458: /* For mortality only */
1.126 brouard 11459: if (mle==-3){
1.136 brouard 11460: ximort=matrix(1,NDIM,1,NDIM);
1.248 brouard 11461: for(i=1;i<=NDIM;i++)
11462: for(j=1;j<=NDIM;j++)
11463: ximort[i][j]=0.;
1.186 brouard 11464: /* ximort=gsl_matrix_alloc(1,NDIM,1,NDIM); */
1.126 brouard 11465: cens=ivector(1,n);
11466: ageexmed=vector(1,n);
11467: agecens=vector(1,n);
11468: dcwave=ivector(1,n);
1.223 brouard 11469:
1.126 brouard 11470: for (i=1; i<=imx; i++){
11471: dcwave[i]=-1;
11472: for (m=firstpass; m<=lastpass; m++)
1.226 brouard 11473: if (s[m][i]>nlstate) {
11474: dcwave[i]=m;
11475: /* printf("i=%d j=%d s=%d dcwave=%d\n",i,j, s[j][i],dcwave[i]);*/
11476: break;
11477: }
1.126 brouard 11478: }
1.226 brouard 11479:
1.126 brouard 11480: for (i=1; i<=imx; i++) {
11481: if (wav[i]>0){
1.226 brouard 11482: ageexmed[i]=agev[mw[1][i]][i];
11483: j=wav[i];
11484: agecens[i]=1.;
11485:
11486: if (ageexmed[i]> 1 && wav[i] > 0){
11487: agecens[i]=agev[mw[j][i]][i];
11488: cens[i]= 1;
11489: }else if (ageexmed[i]< 1)
11490: cens[i]= -1;
11491: if (agedc[i]< AGESUP && agedc[i]>1 && dcwave[i]>firstpass && dcwave[i]<=lastpass)
11492: cens[i]=0 ;
1.126 brouard 11493: }
11494: else cens[i]=-1;
11495: }
11496:
11497: for (i=1;i<=NDIM;i++) {
11498: for (j=1;j<=NDIM;j++)
1.226 brouard 11499: ximort[i][j]=(i == j ? 1.0 : 0.0);
1.126 brouard 11500: }
11501:
1.145 brouard 11502: /*p[1]=0.0268; p[NDIM]=0.083;*/
1.126 brouard 11503: /*printf("%lf %lf", p[1], p[2]);*/
11504:
11505:
1.136 brouard 11506: #ifdef GSL
11507: printf("GSL optimization\n"); fprintf(ficlog,"Powell\n");
1.162 brouard 11508: #else
1.126 brouard 11509: printf("Powell\n"); fprintf(ficlog,"Powell\n");
1.136 brouard 11510: #endif
1.201 brouard 11511: strcpy(filerespow,"POW-MORT_");
11512: strcat(filerespow,fileresu);
1.126 brouard 11513: if((ficrespow=fopen(filerespow,"w"))==NULL) {
11514: printf("Problem with resultfile: %s\n", filerespow);
11515: fprintf(ficlog,"Problem with resultfile: %s\n", filerespow);
11516: }
1.136 brouard 11517: #ifdef GSL
11518: fprintf(ficrespow,"# GSL optimization\n# iter -2*LL");
1.162 brouard 11519: #else
1.126 brouard 11520: fprintf(ficrespow,"# Powell\n# iter -2*LL");
1.136 brouard 11521: #endif
1.126 brouard 11522: /* for (i=1;i<=nlstate;i++)
11523: for(j=1;j<=nlstate+ndeath;j++)
11524: if(j!=i)fprintf(ficrespow," p%1d%1d",i,j);
11525: */
11526: fprintf(ficrespow,"\n");
1.136 brouard 11527: #ifdef GSL
11528: /* gsl starts here */
11529: T = gsl_multimin_fminimizer_nmsimplex;
11530: gsl_multimin_fminimizer *sfm = NULL;
11531: gsl_vector *ss, *x;
11532: gsl_multimin_function minex_func;
11533:
11534: /* Initial vertex size vector */
11535: ss = gsl_vector_alloc (NDIM);
11536:
11537: if (ss == NULL){
11538: GSL_ERROR_VAL ("failed to allocate space for ss", GSL_ENOMEM, 0);
11539: }
11540: /* Set all step sizes to 1 */
11541: gsl_vector_set_all (ss, 0.001);
11542:
11543: /* Starting point */
1.126 brouard 11544:
1.136 brouard 11545: x = gsl_vector_alloc (NDIM);
11546:
11547: if (x == NULL){
11548: gsl_vector_free(ss);
11549: GSL_ERROR_VAL ("failed to allocate space for x", GSL_ENOMEM, 0);
11550: }
11551:
11552: /* Initialize method and iterate */
11553: /* p[1]=0.0268; p[NDIM]=0.083; */
1.186 brouard 11554: /* gsl_vector_set(x, 0, 0.0268); */
11555: /* gsl_vector_set(x, 1, 0.083); */
1.136 brouard 11556: gsl_vector_set(x, 0, p[1]);
11557: gsl_vector_set(x, 1, p[2]);
11558:
11559: minex_func.f = &gompertz_f;
11560: minex_func.n = NDIM;
11561: minex_func.params = (void *)&p; /* ??? */
11562:
11563: sfm = gsl_multimin_fminimizer_alloc (T, NDIM);
11564: gsl_multimin_fminimizer_set (sfm, &minex_func, x, ss);
11565:
11566: printf("Iterations beginning .....\n\n");
11567: printf("Iter. # Intercept Slope -Log Likelihood Simplex size\n");
11568:
11569: iteri=0;
11570: while (rval == GSL_CONTINUE){
11571: iteri++;
11572: status = gsl_multimin_fminimizer_iterate(sfm);
11573:
11574: if (status) printf("error: %s\n", gsl_strerror (status));
11575: fflush(0);
11576:
11577: if (status)
11578: break;
11579:
11580: rval = gsl_multimin_test_size (gsl_multimin_fminimizer_size (sfm), 1e-6);
11581: ssval = gsl_multimin_fminimizer_size (sfm);
11582:
11583: if (rval == GSL_SUCCESS)
11584: printf ("converged to a local maximum at\n");
11585:
11586: printf("%5d ", iteri);
11587: for (it = 0; it < NDIM; it++){
11588: printf ("%10.5f ", gsl_vector_get (sfm->x, it));
11589: }
11590: printf("f() = %-10.5f ssize = %.7f\n", sfm->fval, ssval);
11591: }
11592:
11593: printf("\n\n Please note: Program should be run many times with varying starting points to detemine global maximum\n\n");
11594:
11595: gsl_vector_free(x); /* initial values */
11596: gsl_vector_free(ss); /* inital step size */
11597: for (it=0; it<NDIM; it++){
11598: p[it+1]=gsl_vector_get(sfm->x,it);
11599: fprintf(ficrespow," %.12lf", p[it]);
11600: }
11601: gsl_multimin_fminimizer_free (sfm); /* p *(sfm.x.data) et p *(sfm.x.data+1) */
11602: #endif
11603: #ifdef POWELL
11604: powell(p,ximort,NDIM,ftol,&iter,&fret,gompertz);
11605: #endif
1.126 brouard 11606: fclose(ficrespow);
11607:
1.203 brouard 11608: hesscov(matcov, hess, p, NDIM, delti, 1e-4, gompertz);
1.126 brouard 11609:
11610: for(i=1; i <=NDIM; i++)
11611: for(j=i+1;j<=NDIM;j++)
1.220 brouard 11612: matcov[i][j]=matcov[j][i];
1.126 brouard 11613:
11614: printf("\nCovariance matrix\n ");
1.203 brouard 11615: fprintf(ficlog,"\nCovariance matrix\n ");
1.126 brouard 11616: for(i=1; i <=NDIM; i++) {
11617: for(j=1;j<=NDIM;j++){
1.220 brouard 11618: printf("%f ",matcov[i][j]);
11619: fprintf(ficlog,"%f ",matcov[i][j]);
1.126 brouard 11620: }
1.203 brouard 11621: printf("\n "); fprintf(ficlog,"\n ");
1.126 brouard 11622: }
11623:
11624: printf("iter=%d MLE=%f Eq=%lf*exp(%lf*(age-%d))\n",iter,-gompertz(p),p[1],p[2],agegomp);
1.193 brouard 11625: for (i=1;i<=NDIM;i++) {
1.126 brouard 11626: printf("%f [%f ; %f]\n",p[i],p[i]-2*sqrt(matcov[i][i]),p[i]+2*sqrt(matcov[i][i]));
1.193 brouard 11627: fprintf(ficlog,"%f [%f ; %f]\n",p[i],p[i]-2*sqrt(matcov[i][i]),p[i]+2*sqrt(matcov[i][i]));
11628: }
1.126 brouard 11629: lsurv=vector(1,AGESUP);
11630: lpop=vector(1,AGESUP);
11631: tpop=vector(1,AGESUP);
11632: lsurv[agegomp]=100000;
11633:
11634: for (k=agegomp;k<=AGESUP;k++) {
11635: agemortsup=k;
11636: if (p[1]*exp(p[2]*(k-agegomp))>1) break;
11637: }
11638:
11639: for (k=agegomp;k<agemortsup;k++)
11640: lsurv[k+1]=lsurv[k]-lsurv[k]*(p[1]*exp(p[2]*(k-agegomp)));
11641:
11642: for (k=agegomp;k<agemortsup;k++){
11643: lpop[k]=(lsurv[k]+lsurv[k+1])/2.;
11644: sumlpop=sumlpop+lpop[k];
11645: }
11646:
11647: tpop[agegomp]=sumlpop;
11648: for (k=agegomp;k<(agemortsup-3);k++){
11649: /* tpop[k+1]=2;*/
11650: tpop[k+1]=tpop[k]-lpop[k];
11651: }
11652:
11653:
11654: printf("\nAge lx qx dx Lx Tx e(x)\n");
11655: for (k=agegomp;k<(agemortsup-2);k++)
11656: 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]);
11657:
11658:
11659: replace_back_to_slash(pathc,pathcd); /* Even gnuplot wants a / */
1.220 brouard 11660: ageminpar=50;
11661: agemaxpar=100;
1.194 brouard 11662: if(ageminpar == AGEOVERFLOW ||agemaxpar == AGEOVERFLOW){
11663: printf("Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
11664: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
11665: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
11666: fprintf(ficlog,"Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
11667: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
11668: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
1.220 brouard 11669: }else{
11670: printf("Warning! ageminpar %f and agemaxpar %f have been fixed because for simplification until it is fixed...\n\n",ageminpar,agemaxpar);
11671: 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 11672: printinggnuplotmort(fileresu, optionfilefiname,ageminpar,agemaxpar,fage, pathc,p);
1.220 brouard 11673: }
1.201 brouard 11674: printinghtmlmort(fileresu,title,datafile, firstpass, lastpass, \
1.126 brouard 11675: stepm, weightopt,\
11676: model,imx,p,matcov,agemortsup);
11677:
11678: free_vector(lsurv,1,AGESUP);
11679: free_vector(lpop,1,AGESUP);
11680: free_vector(tpop,1,AGESUP);
1.220 brouard 11681: free_matrix(ximort,1,NDIM,1,NDIM);
1.136 brouard 11682: free_ivector(cens,1,n);
11683: free_vector(agecens,1,n);
11684: free_ivector(dcwave,1,n);
1.220 brouard 11685: #ifdef GSL
1.136 brouard 11686: #endif
1.186 brouard 11687: } /* Endof if mle==-3 mortality only */
1.205 brouard 11688: /* Standard */
11689: else{ /* For mle !=- 3, could be 0 or 1 or 4 etc. */
11690: globpr=0;/* Computes sum of likelihood for globpr=1 and funcone */
11691: /* Computes likelihood for initial parameters, uses funcone to compute gpimx and gsw */
1.132 brouard 11692: likelione(ficres, p, npar, nlstate, &globpr, &ipmx, &sw, &fretone, funcone); /* Prints the contributions to the likelihood */
1.126 brouard 11693: printf("First Likeli=%12.6f ipmx=%ld sw=%12.6f",fretone,ipmx,sw);
11694: for (k=1; k<=npar;k++)
11695: printf(" %d %8.5f",k,p[k]);
11696: printf("\n");
1.205 brouard 11697: if(mle>=1){ /* Could be 1 or 2, Real Maximization */
11698: /* mlikeli uses func not funcone */
1.247 brouard 11699: /* for(i=1;i<nlstate;i++){ */
11700: /* /\*reducing xi for 1 to npar to 1 to ncovmodel; *\/ */
11701: /* mlikeli(ficres,p, ncovmodel, ncovmodel, nlstate, ftol, funcnoprod); */
11702: /* } */
1.205 brouard 11703: mlikeli(ficres,p, npar, ncovmodel, nlstate, ftol, func);
11704: }
11705: if(mle==0) {/* No optimization, will print the likelihoods for the datafile */
11706: globpr=0;/* Computes sum of likelihood for globpr=1 and funcone */
11707: /* Computes likelihood for initial parameters, uses funcone to compute gpimx and gsw */
11708: likelione(ficres, p, npar, nlstate, &globpr, &ipmx, &sw, &fretone, funcone); /* Prints the contributions to the likelihood */
11709: }
11710: globpr=1; /* again, to print the individual contributions using computed gpimx and gsw */
1.126 brouard 11711: likelione(ficres, p, npar, nlstate, &globpr, &ipmx, &sw, &fretone, funcone); /* Prints the contributions to the likelihood */
11712: printf("Second Likeli=%12.6f ipmx=%ld sw=%12.6f",fretone,ipmx,sw);
11713: for (k=1; k<=npar;k++)
11714: printf(" %d %8.5f",k,p[k]);
11715: printf("\n");
11716:
11717: /*--------- results files --------------*/
1.224 brouard 11718: 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 11719:
11720:
11721: fprintf(ficres,"# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
11722: printf("# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
11723: fprintf(ficlog,"# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
11724: for(i=1,jk=1; i <=nlstate; i++){
11725: for(k=1; k <=(nlstate+ndeath); k++){
1.225 brouard 11726: if (k != i) {
11727: printf("%d%d ",i,k);
11728: fprintf(ficlog,"%d%d ",i,k);
11729: fprintf(ficres,"%1d%1d ",i,k);
11730: for(j=1; j <=ncovmodel; j++){
11731: printf("%12.7f ",p[jk]);
11732: fprintf(ficlog,"%12.7f ",p[jk]);
11733: fprintf(ficres,"%12.7f ",p[jk]);
11734: jk++;
11735: }
11736: printf("\n");
11737: fprintf(ficlog,"\n");
11738: fprintf(ficres,"\n");
11739: }
1.126 brouard 11740: }
11741: }
1.203 brouard 11742: if(mle != 0){
11743: /* Computing hessian and covariance matrix only at a peak of the Likelihood, that is after optimization */
1.126 brouard 11744: ftolhess=ftol; /* Usually correct */
1.203 brouard 11745: hesscov(matcov, hess, p, npar, delti, ftolhess, func);
11746: 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");
11747: 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");
11748: for(i=1,jk=1; i <=nlstate; i++){
1.225 brouard 11749: for(k=1; k <=(nlstate+ndeath); k++){
11750: if (k != i) {
11751: printf("%d%d ",i,k);
11752: fprintf(ficlog,"%d%d ",i,k);
11753: for(j=1; j <=ncovmodel; j++){
11754: 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]));
11755: 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]));
11756: jk++;
11757: }
11758: printf("\n");
11759: fprintf(ficlog,"\n");
11760: }
11761: }
1.193 brouard 11762: }
1.203 brouard 11763: } /* end of hesscov and Wald tests */
1.225 brouard 11764:
1.203 brouard 11765: /* */
1.126 brouard 11766: fprintf(ficres,"# Scales (for hessian or gradient estimation)\n");
11767: printf("# Scales (for hessian or gradient estimation)\n");
11768: fprintf(ficlog,"# Scales (for hessian or gradient estimation)\n");
11769: for(i=1,jk=1; i <=nlstate; i++){
11770: for(j=1; j <=nlstate+ndeath; j++){
1.225 brouard 11771: if (j!=i) {
11772: fprintf(ficres,"%1d%1d",i,j);
11773: printf("%1d%1d",i,j);
11774: fprintf(ficlog,"%1d%1d",i,j);
11775: for(k=1; k<=ncovmodel;k++){
11776: printf(" %.5e",delti[jk]);
11777: fprintf(ficlog," %.5e",delti[jk]);
11778: fprintf(ficres," %.5e",delti[jk]);
11779: jk++;
11780: }
11781: printf("\n");
11782: fprintf(ficlog,"\n");
11783: fprintf(ficres,"\n");
11784: }
1.126 brouard 11785: }
11786: }
11787:
11788: 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 11789: if(mle >= 1) /* To big for the screen */
1.126 brouard 11790: 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");
11791: 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");
11792: /* # 121 Var(a12)\n\ */
11793: /* # 122 Cov(b12,a12) Var(b12)\n\ */
11794: /* # 131 Cov(a13,a12) Cov(a13,b12, Var(a13)\n\ */
11795: /* # 132 Cov(b13,a12) Cov(b13,b12, Cov(b13,a13) Var(b13)\n\ */
11796: /* # 212 Cov(a21,a12) Cov(a21,b12, Cov(a21,a13) Cov(a21,b13) Var(a21)\n\ */
11797: /* # 212 Cov(b21,a12) Cov(b21,b12, Cov(b21,a13) Cov(b21,b13) Cov(b21,a21) Var(b21)\n\ */
11798: /* # 232 Cov(a23,a12) Cov(a23,b12, Cov(a23,a13) Cov(a23,b13) Cov(a23,a21) Cov(a23,b21) Var(a23)\n\ */
11799: /* # 232 Cov(b23,a12) Cov(b23,b12) ... Var (b23)\n" */
11800:
11801:
11802: /* Just to have a covariance matrix which will be more understandable
11803: even is we still don't want to manage dictionary of variables
11804: */
11805: for(itimes=1;itimes<=2;itimes++){
11806: jj=0;
11807: for(i=1; i <=nlstate; i++){
1.225 brouard 11808: for(j=1; j <=nlstate+ndeath; j++){
11809: if(j==i) continue;
11810: for(k=1; k<=ncovmodel;k++){
11811: jj++;
11812: ca[0]= k+'a'-1;ca[1]='\0';
11813: if(itimes==1){
11814: if(mle>=1)
11815: printf("#%1d%1d%d",i,j,k);
11816: fprintf(ficlog,"#%1d%1d%d",i,j,k);
11817: fprintf(ficres,"#%1d%1d%d",i,j,k);
11818: }else{
11819: if(mle>=1)
11820: printf("%1d%1d%d",i,j,k);
11821: fprintf(ficlog,"%1d%1d%d",i,j,k);
11822: fprintf(ficres,"%1d%1d%d",i,j,k);
11823: }
11824: ll=0;
11825: for(li=1;li <=nlstate; li++){
11826: for(lj=1;lj <=nlstate+ndeath; lj++){
11827: if(lj==li) continue;
11828: for(lk=1;lk<=ncovmodel;lk++){
11829: ll++;
11830: if(ll<=jj){
11831: cb[0]= lk +'a'-1;cb[1]='\0';
11832: if(ll<jj){
11833: if(itimes==1){
11834: if(mle>=1)
11835: printf(" Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
11836: fprintf(ficlog," Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
11837: fprintf(ficres," Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
11838: }else{
11839: if(mle>=1)
11840: printf(" %.5e",matcov[jj][ll]);
11841: fprintf(ficlog," %.5e",matcov[jj][ll]);
11842: fprintf(ficres," %.5e",matcov[jj][ll]);
11843: }
11844: }else{
11845: if(itimes==1){
11846: if(mle>=1)
11847: printf(" Var(%s%1d%1d)",ca,i,j);
11848: fprintf(ficlog," Var(%s%1d%1d)",ca,i,j);
11849: fprintf(ficres," Var(%s%1d%1d)",ca,i,j);
11850: }else{
11851: if(mle>=1)
11852: printf(" %.7e",matcov[jj][ll]);
11853: fprintf(ficlog," %.7e",matcov[jj][ll]);
11854: fprintf(ficres," %.7e",matcov[jj][ll]);
11855: }
11856: }
11857: }
11858: } /* end lk */
11859: } /* end lj */
11860: } /* end li */
11861: if(mle>=1)
11862: printf("\n");
11863: fprintf(ficlog,"\n");
11864: fprintf(ficres,"\n");
11865: numlinepar++;
11866: } /* end k*/
11867: } /*end j */
1.126 brouard 11868: } /* end i */
11869: } /* end itimes */
11870:
11871: fflush(ficlog);
11872: fflush(ficres);
1.225 brouard 11873: while(fgets(line, MAXLINE, ficpar)) {
11874: /* If line starts with a # it is a comment */
11875: if (line[0] == '#') {
11876: numlinepar++;
11877: fputs(line,stdout);
11878: fputs(line,ficparo);
11879: fputs(line,ficlog);
11880: continue;
11881: }else
11882: break;
11883: }
11884:
1.209 brouard 11885: /* while((c=getc(ficpar))=='#' && c!= EOF){ */
11886: /* ungetc(c,ficpar); */
11887: /* fgets(line, MAXLINE, ficpar); */
11888: /* fputs(line,stdout); */
11889: /* fputs(line,ficparo); */
11890: /* } */
11891: /* ungetc(c,ficpar); */
1.126 brouard 11892:
11893: estepm=0;
1.209 brouard 11894: 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 11895:
11896: if (num_filled != 6) {
11897: 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);
11898: 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);
11899: goto end;
11900: }
11901: printf("agemin=%lf agemax=%lf bage=%lf fage=%lf estepm=%d ftolpl=%lf\n",ageminpar,agemaxpar, bage, fage, estepm, ftolpl);
11902: }
11903: /* ftolpl=6*ftol*1.e5; /\* 6.e-3 make convergences in less than 80 loops for the prevalence limit *\/ */
11904: /*ftolpl=6.e-4;*/ /* 6.e-3 make convergences in less than 80 loops for the prevalence limit */
11905:
1.209 brouard 11906: /* fscanf(ficpar,"agemin=%lf agemax=%lf bage=%lf fage=%lf estepm=%d ftolpl=%\n",&ageminpar,&agemaxpar, &bage, &fage, &estepm); */
1.126 brouard 11907: if (estepm==0 || estepm < stepm) estepm=stepm;
11908: if (fage <= 2) {
11909: bage = ageminpar;
11910: fage = agemaxpar;
11911: }
11912:
11913: fprintf(ficres,"# agemin agemax for life expectancy, bage fage (if mle==0 ie no data nor Max likelihood).\n");
1.211 brouard 11914: fprintf(ficres,"agemin=%.0f agemax=%.0f bage=%.0f fage=%.0f estepm=%d ftolpl=%e\n",ageminpar,agemaxpar,bage,fage, estepm, ftolpl);
11915: fprintf(ficparo,"agemin=%.0f agemax=%.0f bage=%.0f fage=%.0f estepm=%d, ftolpl=%e\n",ageminpar,agemaxpar,bage,fage, estepm, ftolpl);
1.220 brouard 11916:
1.186 brouard 11917: /* Other stuffs, more or less useful */
1.254 brouard 11918: while(fgets(line, MAXLINE, ficpar)) {
11919: /* If line starts with a # it is a comment */
11920: if (line[0] == '#') {
11921: numlinepar++;
11922: fputs(line,stdout);
11923: fputs(line,ficparo);
11924: fputs(line,ficlog);
11925: continue;
11926: }else
11927: break;
11928: }
11929:
11930: 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){
11931:
11932: if (num_filled != 7) {
11933: 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);
11934: 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);
11935: goto end;
11936: }
11937: printf("begin-prev-date=%.lf/%.lf/%.lf end-prev-date=%.lf/%.lf/%.lf mov_average=%d\n",jprev1, mprev1,anprev1,jprev2, mprev2,anprev2,mobilav);
11938: 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);
11939: 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);
11940: 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 11941: }
1.254 brouard 11942:
11943: while(fgets(line, MAXLINE, ficpar)) {
11944: /* If line starts with a # it is a comment */
11945: if (line[0] == '#') {
11946: numlinepar++;
11947: fputs(line,stdout);
11948: fputs(line,ficparo);
11949: fputs(line,ficlog);
11950: continue;
11951: }else
11952: break;
1.126 brouard 11953: }
11954:
11955:
11956: dateprev1=anprev1+(mprev1-1)/12.+(jprev1-1)/365.;
11957: dateprev2=anprev2+(mprev2-1)/12.+(jprev2-1)/365.;
11958:
1.254 brouard 11959: if((num_filled=sscanf(line,"pop_based=%d\n",&popbased)) !=EOF){
11960: if (num_filled != 1) {
11961: 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);
11962: 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);
11963: goto end;
11964: }
11965: printf("pop_based=%d\n",popbased);
11966: fprintf(ficlog,"pop_based=%d\n",popbased);
11967: fprintf(ficparo,"pop_based=%d\n",popbased);
11968: fprintf(ficres,"pop_based=%d\n",popbased);
11969: }
11970:
1.258 brouard 11971: /* Results */
11972: nresult=0;
11973: do{
11974: if(!fgets(line, MAXLINE, ficpar)){
11975: endishere=1;
11976: parameterline=14;
11977: }else if (line[0] == '#') {
11978: /* If line starts with a # it is a comment */
1.254 brouard 11979: numlinepar++;
11980: fputs(line,stdout);
11981: fputs(line,ficparo);
11982: fputs(line,ficlog);
11983: continue;
1.258 brouard 11984: }else if(sscanf(line,"prevforecast=%[^\n]\n",modeltemp))
11985: parameterline=11;
11986: else if(sscanf(line,"backcast=%[^\n]\n",modeltemp))
11987: parameterline=12;
11988: else if(sscanf(line,"result:%[^\n]\n",modeltemp))
11989: parameterline=13;
11990: else{
11991: parameterline=14;
1.254 brouard 11992: }
1.258 brouard 11993: switch (parameterline){
11994: case 11:
11995: 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){
11996: if (num_filled != 8) {
11997: 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);
11998: 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);
11999: goto end;
12000: }
12001: 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);
12002: 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);
12003: 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);
12004: 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);
12005: /* day and month of proj2 are not used but only year anproj2.*/
12006: }
1.254 brouard 12007: break;
1.258 brouard 12008: case 12:
12009: /*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);*/
12010: 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){
12011: if (num_filled != 8) {
1.262 brouard 12012: 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);
12013: 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 12014: goto end;
12015: }
12016: 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);
12017: 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);
12018: 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);
12019: 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);
12020: /* day and month of proj2 are not used but only year anproj2.*/
12021: }
1.230 brouard 12022: break;
1.258 brouard 12023: case 13:
12024: if((num_filled=sscanf(line,"result:%[^\n]\n",resultline)) !=EOF){
12025: if (num_filled == 0){
12026: resultline[0]='\0';
12027: printf("Warning %d: no result line! It should be at minimum 'result: V2=0 V1=1 or result:.\n%s\n", num_filled, line);
12028: 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);
12029: break;
12030: } else if (num_filled != 1){
12031: printf("ERROR %d: result line! It should be at minimum 'result: V2=0 V1=1 or result:.' %s\n",num_filled, line);
12032: fprintf(ficlog,"ERROR %d: result line! It should be at minimum 'result: V2=0 V1=1 or result:.' %s\n",num_filled, line);
12033: }
12034: nresult++; /* Sum of resultlines */
12035: printf("Result %d: result=%s\n",nresult, resultline);
12036: if(nresult > MAXRESULTLINES){
12037: printf("ERROR: Current version of IMaCh limits the number of resultlines to %d, you used %d\n",MAXRESULTLINES,nresult);
12038: fprintf(ficlog,"ERROR: Current version of IMaCh limits the number of resultlines to %d, you used %d\n",MAXRESULTLINES,nresult);
12039: goto end;
12040: }
12041: decoderesult(resultline, nresult); /* Fills TKresult[nresult] combination and Tresult[nresult][k4+1] combination values */
12042: fprintf(ficparo,"result: %s\n",resultline);
12043: fprintf(ficres,"result: %s\n",resultline);
12044: fprintf(ficlog,"result: %s\n",resultline);
1.230 brouard 12045: break;
1.258 brouard 12046: case 14:
1.259 brouard 12047: if(ncovmodel >2 && nresult==0 ){
12048: printf("ERROR: no result lines! It should be at minimum 'result: V2=0 V1=1 or result:.' %s\n",line);
1.258 brouard 12049: goto end;
12050: }
1.259 brouard 12051: break;
1.258 brouard 12052: default:
12053: nresult=1;
12054: decoderesult(".",nresult ); /* No covariate */
12055: }
12056: } /* End switch parameterline */
12057: }while(endishere==0); /* End do */
1.126 brouard 12058:
1.230 brouard 12059: /* freqsummary(fileres, agemin, agemax, s, agev, nlstate, imx,Tvaraff,nbcode, ncodemax,mint,anint); */
1.145 brouard 12060: /* ,dateprev1,dateprev2,jprev1, mprev1,anprev1,jprev2, mprev2,anprev2); */
1.126 brouard 12061:
12062: replace_back_to_slash(pathc,pathcd); /* Even gnuplot wants a / */
1.194 brouard 12063: if(ageminpar == AGEOVERFLOW ||agemaxpar == -AGEOVERFLOW){
1.230 brouard 12064: printf("Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
1.194 brouard 12065: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
12066: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
1.230 brouard 12067: fprintf(ficlog,"Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
1.194 brouard 12068: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
12069: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
1.220 brouard 12070: }else{
1.268 brouard 12071: printinggnuplot(fileresu, optionfilefiname,ageminpar,agemaxpar,fage, prevfcast, backcast, pathc,p, (int)anproj1-(int)agemin, (int)anback1-(int)agemax+1);
1.220 brouard 12072: }
12073: printinghtml(fileresu,title,datafile, firstpass, lastpass, stepm, weightopt, \
1.258 brouard 12074: model,imx,jmin,jmax,jmean,rfileres,popforecast,mobilav,prevfcast,mobilavproj,backcast, estepm, \
1.225 brouard 12075: jprev1,mprev1,anprev1,dateprev1,jprev2,mprev2,anprev2,dateprev2);
1.220 brouard 12076:
1.225 brouard 12077: /*------------ free_vector -------------*/
12078: /* chdir(path); */
1.220 brouard 12079:
1.215 brouard 12080: /* free_ivector(wav,1,imx); */ /* Moved after last prevalence call */
12081: /* free_imatrix(dh,1,lastpass-firstpass+2,1,imx); */
12082: /* free_imatrix(bh,1,lastpass-firstpass+2,1,imx); */
12083: /* free_imatrix(mw,1,lastpass-firstpass+2,1,imx); */
1.126 brouard 12084: free_lvector(num,1,n);
12085: free_vector(agedc,1,n);
12086: /*free_matrix(covar,0,NCOVMAX,1,n);*/
12087: /*free_matrix(covar,1,NCOVMAX,1,n);*/
12088: fclose(ficparo);
12089: fclose(ficres);
1.220 brouard 12090:
12091:
1.186 brouard 12092: /* Other results (useful)*/
1.220 brouard 12093:
12094:
1.126 brouard 12095: /*--------------- Prevalence limit (period or stable prevalence) --------------*/
1.180 brouard 12096: /*#include "prevlim.h"*/ /* Use ficrespl, ficlog */
12097: prlim=matrix(1,nlstate,1,nlstate);
1.209 brouard 12098: prevalence_limit(p, prlim, ageminpar, agemaxpar, ftolpl, &ncvyear);
1.126 brouard 12099: fclose(ficrespl);
12100:
12101: /*------------- h Pij x at various ages ------------*/
1.180 brouard 12102: /*#include "hpijx.h"*/
12103: hPijx(p, bage, fage);
1.145 brouard 12104: fclose(ficrespij);
1.227 brouard 12105:
1.220 brouard 12106: /* ncovcombmax= pow(2,cptcoveff); */
1.219 brouard 12107: /*-------------- Variance of one-step probabilities---*/
1.145 brouard 12108: k=1;
1.126 brouard 12109: varprob(optionfilefiname, matcov, p, delti, nlstate, bage, fage,k,Tvar,nbcode, ncodemax,strstart);
1.227 brouard 12110:
1.269 ! brouard 12111: /* Prevalence for each covariate combination in probs[age][status][cov] */
! 12112: probs= ma3x(AGEINF,AGESUP,1,nlstate+ndeath, 1,ncovcombmax);
! 12113: for(i=AGEINF;i<=AGESUP;i++)
1.219 brouard 12114: for(j=1;j<=nlstate+ndeath;j++) /* ndeath is useless but a necessity to be compared with mobaverages */
1.225 brouard 12115: for(k=1;k<=ncovcombmax;k++)
12116: probs[i][j][k]=0.;
1.269 ! brouard 12117: prevalence(probs, ageminpar, agemaxpar, s, agev, nlstate, imx, Tvar, nbcode,
! 12118: ncodemax, mint, anint, dateprev1, dateprev2, firstpass, lastpass);
1.219 brouard 12119: if (mobilav!=0 ||mobilavproj !=0 ) {
1.269 ! brouard 12120: mobaverages= ma3x(AGEINF, AGESUP,1,nlstate+ndeath, 1,ncovcombmax);
! 12121: for(i=AGEINF;i<=AGESUP;i++)
1.268 brouard 12122: for(j=1;j<=nlstate+ndeath;j++)
1.227 brouard 12123: for(k=1;k<=ncovcombmax;k++)
12124: mobaverages[i][j][k]=0.;
1.219 brouard 12125: mobaverage=mobaverages;
12126: if (mobilav!=0) {
1.235 brouard 12127: printf("Movingaveraging observed prevalence\n");
1.258 brouard 12128: fprintf(ficlog,"Movingaveraging observed prevalence\n");
1.227 brouard 12129: if (movingaverage(probs, ageminpar, agemaxpar, mobaverage, mobilav)!=0){
12130: fprintf(ficlog," Error in movingaverage mobilav=%d\n",mobilav);
12131: printf(" Error in movingaverage mobilav=%d\n",mobilav);
12132: }
1.269 ! brouard 12133: } else if (mobilavproj !=0) {
1.235 brouard 12134: printf("Movingaveraging projected observed prevalence\n");
1.258 brouard 12135: fprintf(ficlog,"Movingaveraging projected observed prevalence\n");
1.227 brouard 12136: if (movingaverage(probs, ageminpar, agemaxpar, mobaverage, mobilavproj)!=0){
12137: fprintf(ficlog," Error in movingaverage mobilavproj=%d\n",mobilavproj);
12138: printf(" Error in movingaverage mobilavproj=%d\n",mobilavproj);
12139: }
1.269 ! brouard 12140: }else{
! 12141: printf("Internal error moving average\n");
! 12142: fflush(stdout);
! 12143: exit(1);
1.219 brouard 12144: }
12145: }/* end if moving average */
1.227 brouard 12146:
1.126 brouard 12147: /*---------- Forecasting ------------------*/
12148: if(prevfcast==1){
12149: /* if(stepm ==1){*/
1.269 ! brouard 12150: prevforecast(fileresu, anproj1, mproj1, jproj1, agemin, agemax, dateprev1, dateprev2, mobilavproj, mobaverage, bage, fage, firstpass, lastpass, anproj2, p, cptcoveff);
1.126 brouard 12151: }
1.269 ! brouard 12152:
! 12153: /* Backcasting */
1.217 brouard 12154: if(backcast==1){
1.219 brouard 12155: ddnewms=matrix(1,nlstate+ndeath,1,nlstate+ndeath);
12156: ddoldms=matrix(1,nlstate+ndeath,1,nlstate+ndeath);
12157: ddsavms=matrix(1,nlstate+ndeath,1,nlstate+ndeath);
12158:
12159: /*--------------- Back Prevalence limit (period or stable prevalence) --------------*/
12160:
12161: bprlim=matrix(1,nlstate,1,nlstate);
1.269 ! brouard 12162:
1.219 brouard 12163: back_prevalence_limit(p, bprlim, ageminpar, agemaxpar, ftolpl, &ncvyear, dateprev1, dateprev2, firstpass, lastpass, mobilavproj);
12164: fclose(ficresplb);
12165:
1.222 brouard 12166: hBijx(p, bage, fage, mobaverage);
12167: fclose(ficrespijb);
1.219 brouard 12168:
1.269 ! brouard 12169: prevbackforecast(fileresu, mobaverage, anback1, mback1, jback1, agemin, agemax, dateprev1, dateprev2,
! 12170: mobilavproj, bage, fage, firstpass, lastpass, anback2, p, cptcoveff);
! 12171: varbprlim(fileresu, nresult, mobaverage, mobilavproj, bage, fage, bprlim, &ncvyear, ftolpl, p, matcov, delti, stepm, cptcoveff);
1.268 brouard 12172:
12173:
1.269 ! brouard 12174: free_matrix(bprlim,1,nlstate,1,nlstate); /*here or after loop ? */
1.219 brouard 12175: free_matrix(ddnewms, 1, nlstate+ndeath, 1, nlstate+ndeath);
12176: free_matrix(ddsavms, 1, nlstate+ndeath, 1, nlstate+ndeath);
12177: free_matrix(ddoldms, 1, nlstate+ndeath, 1, nlstate+ndeath);
1.269 ! brouard 12178: } /* end Backcasting */
1.268 brouard 12179:
1.186 brouard 12180:
12181: /* ------ Other prevalence ratios------------ */
1.126 brouard 12182:
1.215 brouard 12183: free_ivector(wav,1,imx);
12184: free_imatrix(dh,1,lastpass-firstpass+2,1,imx);
12185: free_imatrix(bh,1,lastpass-firstpass+2,1,imx);
12186: free_imatrix(mw,1,lastpass-firstpass+2,1,imx);
1.218 brouard 12187:
12188:
1.127 brouard 12189: /*---------- Health expectancies, no variances ------------*/
1.218 brouard 12190:
1.201 brouard 12191: strcpy(filerese,"E_");
12192: strcat(filerese,fileresu);
1.126 brouard 12193: if((ficreseij=fopen(filerese,"w"))==NULL) {
12194: printf("Problem with Health Exp. resultfile: %s\n", filerese); exit(0);
12195: fprintf(ficlog,"Problem with Health Exp. resultfile: %s\n", filerese); exit(0);
12196: }
1.208 brouard 12197: printf("Computing Health Expectancies: result on file '%s' ...", filerese);fflush(stdout);
12198: fprintf(ficlog,"Computing Health Expectancies: result on file '%s' ...", filerese);fflush(ficlog);
1.238 brouard 12199:
12200: pstamp(ficreseij);
1.219 brouard 12201:
1.235 brouard 12202: i1=pow(2,cptcoveff); /* Number of combination of dummy covariates */
12203: if (cptcovn < 1){i1=1;}
12204:
12205: for(nres=1; nres <= nresult; nres++) /* For each resultline */
12206: for(k=1; k<=i1;k++){ /* For any combination of dummy covariates, fixed and varying */
1.253 brouard 12207: if(i1 != 1 && TKresult[nres]!= k)
1.235 brouard 12208: continue;
1.219 brouard 12209: fprintf(ficreseij,"\n#****** ");
1.235 brouard 12210: printf("\n#****** ");
1.225 brouard 12211: for(j=1;j<=cptcoveff;j++) {
1.227 brouard 12212: fprintf(ficreseij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
1.235 brouard 12213: printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
12214: }
12215: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
12216: printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
12217: fprintf(ficreseij," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
1.219 brouard 12218: }
12219: fprintf(ficreseij,"******\n");
1.235 brouard 12220: printf("******\n");
1.219 brouard 12221:
12222: eij=ma3x(1,nlstate,1,nlstate,(int) bage, (int) fage);
12223: oldm=oldms;savm=savms;
1.235 brouard 12224: evsij(eij, p, nlstate, stepm, (int) bage, (int)fage, oldm, savm, k, estepm, strstart, nres);
1.127 brouard 12225:
1.219 brouard 12226: free_ma3x(eij,1,nlstate,1,nlstate,(int) bage, (int)fage);
1.127 brouard 12227: }
12228: fclose(ficreseij);
1.208 brouard 12229: printf("done evsij\n");fflush(stdout);
12230: fprintf(ficlog,"done evsij\n");fflush(ficlog);
1.269 ! brouard 12231:
1.218 brouard 12232:
1.227 brouard 12233: /*---------- State-specific expectancies and variances ------------*/
1.218 brouard 12234:
1.201 brouard 12235: strcpy(filerest,"T_");
12236: strcat(filerest,fileresu);
1.127 brouard 12237: if((ficrest=fopen(filerest,"w"))==NULL) {
12238: printf("Problem with total LE resultfile: %s\n", filerest);goto end;
12239: fprintf(ficlog,"Problem with total LE resultfile: %s\n", filerest);goto end;
12240: }
1.208 brouard 12241: printf("Computing Total Life expectancies with their standard errors: file '%s' ...\n", filerest); fflush(stdout);
12242: fprintf(ficlog,"Computing Total Life expectancies with their standard errors: file '%s' ...\n", filerest); fflush(ficlog);
1.201 brouard 12243: strcpy(fileresstde,"STDE_");
12244: strcat(fileresstde,fileresu);
1.126 brouard 12245: if((ficresstdeij=fopen(fileresstde,"w"))==NULL) {
1.227 brouard 12246: printf("Problem with State specific Exp. and std errors resultfile: %s\n", fileresstde); exit(0);
12247: fprintf(ficlog,"Problem with State specific Exp. and std errors resultfile: %s\n", fileresstde); exit(0);
1.126 brouard 12248: }
1.227 brouard 12249: printf(" Computing State-specific Expectancies and standard errors: result on file '%s' \n", fileresstde);
12250: fprintf(ficlog," Computing State-specific Expectancies and standard errors: result on file '%s' \n", fileresstde);
1.126 brouard 12251:
1.201 brouard 12252: strcpy(filerescve,"CVE_");
12253: strcat(filerescve,fileresu);
1.126 brouard 12254: if((ficrescveij=fopen(filerescve,"w"))==NULL) {
1.227 brouard 12255: printf("Problem with Covar. State-specific Exp. resultfile: %s\n", filerescve); exit(0);
12256: fprintf(ficlog,"Problem with Covar. State-specific Exp. resultfile: %s\n", filerescve); exit(0);
1.126 brouard 12257: }
1.227 brouard 12258: printf(" Computing Covar. of State-specific Expectancies: result on file '%s' \n", filerescve);
12259: fprintf(ficlog," Computing Covar. of State-specific Expectancies: result on file '%s' \n", filerescve);
1.126 brouard 12260:
1.201 brouard 12261: strcpy(fileresv,"V_");
12262: strcat(fileresv,fileresu);
1.126 brouard 12263: if((ficresvij=fopen(fileresv,"w"))==NULL) {
12264: printf("Problem with variance resultfile: %s\n", fileresv);exit(0);
12265: fprintf(ficlog,"Problem with variance resultfile: %s\n", fileresv);exit(0);
12266: }
1.227 brouard 12267: printf(" Computing Variance-covariance of State-specific Expectancies: file '%s' ... ", fileresv);fflush(stdout);
12268: fprintf(ficlog," Computing Variance-covariance of State-specific Expectancies: file '%s' ... ", fileresv);fflush(ficlog);
1.126 brouard 12269:
1.235 brouard 12270: i1=pow(2,cptcoveff); /* Number of combination of dummy covariates */
12271: if (cptcovn < 1){i1=1;}
12272:
12273: for(nres=1; nres <= nresult; nres++) /* For each resultline */
12274: for(k=1; k<=i1;k++){ /* For any combination of dummy covariates, fixed and varying */
1.253 brouard 12275: if(i1 != 1 && TKresult[nres]!= k)
1.235 brouard 12276: continue;
1.242 brouard 12277: printf("\n#****** Result for:");
12278: fprintf(ficrest,"\n#****** Result for:");
12279: fprintf(ficlog,"\n#****** Result for:");
1.227 brouard 12280: for(j=1;j<=cptcoveff;j++){
12281: printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
12282: fprintf(ficrest,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
12283: fprintf(ficlog,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
12284: }
1.235 brouard 12285: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
12286: printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
12287: fprintf(ficrest," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
12288: fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
12289: }
1.208 brouard 12290: fprintf(ficrest,"******\n");
1.227 brouard 12291: fprintf(ficlog,"******\n");
12292: printf("******\n");
1.208 brouard 12293:
12294: fprintf(ficresstdeij,"\n#****** ");
12295: fprintf(ficrescveij,"\n#****** ");
1.225 brouard 12296: for(j=1;j<=cptcoveff;j++) {
1.227 brouard 12297: fprintf(ficresstdeij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
12298: fprintf(ficrescveij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
1.208 brouard 12299: }
1.235 brouard 12300: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
12301: fprintf(ficresstdeij," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
12302: fprintf(ficrescveij," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
12303: }
1.208 brouard 12304: fprintf(ficresstdeij,"******\n");
12305: fprintf(ficrescveij,"******\n");
12306:
12307: fprintf(ficresvij,"\n#****** ");
1.238 brouard 12308: /* pstamp(ficresvij); */
1.225 brouard 12309: for(j=1;j<=cptcoveff;j++)
1.227 brouard 12310: fprintf(ficresvij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
1.235 brouard 12311: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
12312: fprintf(ficresvij," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
12313: }
1.208 brouard 12314: fprintf(ficresvij,"******\n");
12315:
12316: eij=ma3x(1,nlstate,1,nlstate,(int) bage, (int) fage);
12317: oldm=oldms;savm=savms;
1.235 brouard 12318: printf(" cvevsij ");
12319: fprintf(ficlog, " cvevsij ");
12320: cvevsij(eij, p, nlstate, stepm, (int) bage, (int)fage, oldm, savm, k, estepm, delti, matcov, strstart, nres);
1.208 brouard 12321: printf(" end cvevsij \n ");
12322: fprintf(ficlog, " end cvevsij \n ");
12323:
12324: /*
12325: */
12326: /* goto endfree; */
12327:
12328: vareij=ma3x(1,nlstate,1,nlstate,(int) bage, (int) fage);
12329: pstamp(ficrest);
12330:
1.269 ! brouard 12331: epj=vector(1,nlstate+1);
1.208 brouard 12332: for(vpopbased=0; vpopbased <= popbased; vpopbased++){ /* Done for vpopbased=0 and vpopbased=1 if popbased==1*/
1.227 brouard 12333: oldm=oldms;savm=savms; /* ZZ Segmentation fault */
12334: cptcod= 0; /* To be deleted */
12335: printf("varevsij vpopbased=%d \n",vpopbased);
12336: fprintf(ficlog, "varevsij vpopbased=%d \n",vpopbased);
1.235 brouard 12337: 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 12338: 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 ");
12339: if(vpopbased==1)
12340: 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);
12341: else
12342: fprintf(ficrest,"the age specific period (stable) prevalences in each health state \n");
12343: fprintf(ficrest,"# Age popbased mobilav e.. (std) ");
12344: for (i=1;i<=nlstate;i++) fprintf(ficrest,"e.%d (std) ",i);
12345: fprintf(ficrest,"\n");
12346: /* printf("Which p?\n"); for(i=1;i<=npar;i++)printf("p[i=%d]=%lf,",i,p[i]);printf("\n"); */
12347: printf("Computing age specific period (stable) prevalences in each health state \n");
12348: fprintf(ficlog,"Computing age specific period (stable) prevalences in each health state \n");
12349: for(age=bage; age <=fage ;age++){
1.235 brouard 12350: prevalim(prlim, nlstate, p, age, oldm, savm, ftolpl, &ncvyear, k, nres); /*ZZ Is it the correct prevalim */
1.227 brouard 12351: if (vpopbased==1) {
12352: if(mobilav ==0){
12353: for(i=1; i<=nlstate;i++)
12354: prlim[i][i]=probs[(int)age][i][k];
12355: }else{ /* mobilav */
12356: for(i=1; i<=nlstate;i++)
12357: prlim[i][i]=mobaverage[(int)age][i][k];
12358: }
12359: }
1.219 brouard 12360:
1.227 brouard 12361: fprintf(ficrest," %4.0f %d %d",age, vpopbased, mobilav);
12362: /* fprintf(ficrest," %4.0f %d %d %d %d",age, vpopbased, mobilav,Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]); */ /* to be done */
12363: /* printf(" age %4.0f ",age); */
12364: for(j=1, epj[nlstate+1]=0.;j <=nlstate;j++){
12365: for(i=1, epj[j]=0.;i <=nlstate;i++) {
12366: epj[j] += prlim[i][i]*eij[i][j][(int)age];
12367: /*ZZZ printf("%lf %lf ", prlim[i][i] ,eij[i][j][(int)age]);*/
12368: /* printf("%lf %lf ", prlim[i][i] ,eij[i][j][(int)age]); */
12369: }
12370: epj[nlstate+1] +=epj[j];
12371: }
12372: /* printf(" age %4.0f \n",age); */
1.219 brouard 12373:
1.227 brouard 12374: for(i=1, vepp=0.;i <=nlstate;i++)
12375: for(j=1;j <=nlstate;j++)
12376: vepp += vareij[i][j][(int)age];
12377: fprintf(ficrest," %7.3f (%7.3f)", epj[nlstate+1],sqrt(vepp));
12378: for(j=1;j <=nlstate;j++){
12379: fprintf(ficrest," %7.3f (%7.3f)", epj[j],sqrt(vareij[j][j][(int)age]));
12380: }
12381: fprintf(ficrest,"\n");
12382: }
1.208 brouard 12383: } /* End vpopbased */
1.269 ! brouard 12384: free_vector(epj,1,nlstate+1);
1.208 brouard 12385: free_ma3x(eij,1,nlstate,1,nlstate,(int) bage, (int)fage);
12386: free_ma3x(vareij,1,nlstate,1,nlstate,(int) bage, (int)fage);
1.235 brouard 12387: printf("done selection\n");fflush(stdout);
12388: fprintf(ficlog,"done selection\n");fflush(ficlog);
1.208 brouard 12389:
1.235 brouard 12390: } /* End k selection */
1.227 brouard 12391:
12392: printf("done State-specific expectancies\n");fflush(stdout);
12393: fprintf(ficlog,"done State-specific expectancies\n");fflush(ficlog);
12394:
1.269 ! brouard 12395: /* variance-covariance of period prevalence*/
! 12396: varprlim(fileresu, nresult, mobaverage, mobilavproj, bage, fage, prlim, &ncvyear, ftolpl, p, matcov, delti, stepm, cptcoveff);
1.268 brouard 12397:
1.227 brouard 12398:
12399: free_vector(weight,1,n);
12400: free_imatrix(Tvard,1,NCOVMAX,1,2);
12401: free_imatrix(s,1,maxwav+1,1,n);
12402: free_matrix(anint,1,maxwav,1,n);
12403: free_matrix(mint,1,maxwav,1,n);
12404: free_ivector(cod,1,n);
12405: free_ivector(tab,1,NCOVMAX);
12406: fclose(ficresstdeij);
12407: fclose(ficrescveij);
12408: fclose(ficresvij);
12409: fclose(ficrest);
12410: fclose(ficpar);
12411:
12412:
1.126 brouard 12413: /*---------- End : free ----------------*/
1.219 brouard 12414: if (mobilav!=0 ||mobilavproj !=0)
1.269 ! brouard 12415: free_ma3x(mobaverages,AGEINF, AGESUP,1,nlstate+ndeath, 1,ncovcombmax); /* We need to have a squared matrix with prevalence of the dead! */
! 12416: free_ma3x(probs,AGEINF,AGESUP,1,nlstate+ndeath, 1,ncovcombmax);
1.220 brouard 12417: free_matrix(prlim,1,nlstate,1,nlstate); /*here or after loop ? */
12418: free_matrix(pmmij,1,nlstate+ndeath,1,nlstate+ndeath);
1.126 brouard 12419: } /* mle==-3 arrives here for freeing */
1.227 brouard 12420: /* endfree:*/
12421: free_matrix(oldms, 1,nlstate+ndeath,1,nlstate+ndeath);
12422: free_matrix(newms, 1,nlstate+ndeath,1,nlstate+ndeath);
12423: free_matrix(savms, 1,nlstate+ndeath,1,nlstate+ndeath);
1.268 brouard 12424: if(ntv+nqtv>=1)free_ma3x(cotvar,1,maxwav,1,ntv+nqtv,1,n);
12425: if(nqtv>=1)free_ma3x(cotqvar,1,maxwav,1,nqtv,1,n);
12426: if(nqv>=1)free_matrix(coqvar,1,nqv,1,n);
1.227 brouard 12427: free_matrix(covar,0,NCOVMAX,1,n);
12428: free_matrix(matcov,1,npar,1,npar);
12429: free_matrix(hess,1,npar,1,npar);
12430: /*free_vector(delti,1,npar);*/
12431: free_ma3x(delti3,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
12432: free_matrix(agev,1,maxwav,1,imx);
1.269 ! brouard 12433: free_ma3x(paramstart,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
1.227 brouard 12434: free_ma3x(param,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
12435:
12436: free_ivector(ncodemax,1,NCOVMAX);
12437: free_ivector(ncodemaxwundef,1,NCOVMAX);
12438: free_ivector(Dummy,-1,NCOVMAX);
12439: free_ivector(Fixed,-1,NCOVMAX);
1.238 brouard 12440: free_ivector(DummyV,1,NCOVMAX);
12441: free_ivector(FixedV,1,NCOVMAX);
1.227 brouard 12442: free_ivector(Typevar,-1,NCOVMAX);
12443: free_ivector(Tvar,1,NCOVMAX);
1.234 brouard 12444: free_ivector(TvarsQ,1,NCOVMAX);
12445: free_ivector(TvarsQind,1,NCOVMAX);
12446: free_ivector(TvarsD,1,NCOVMAX);
12447: free_ivector(TvarsDind,1,NCOVMAX);
1.231 brouard 12448: free_ivector(TvarFD,1,NCOVMAX);
12449: free_ivector(TvarFDind,1,NCOVMAX);
1.232 brouard 12450: free_ivector(TvarF,1,NCOVMAX);
12451: free_ivector(TvarFind,1,NCOVMAX);
12452: free_ivector(TvarV,1,NCOVMAX);
12453: free_ivector(TvarVind,1,NCOVMAX);
12454: free_ivector(TvarA,1,NCOVMAX);
12455: free_ivector(TvarAind,1,NCOVMAX);
1.231 brouard 12456: free_ivector(TvarFQ,1,NCOVMAX);
12457: free_ivector(TvarFQind,1,NCOVMAX);
12458: free_ivector(TvarVD,1,NCOVMAX);
12459: free_ivector(TvarVDind,1,NCOVMAX);
12460: free_ivector(TvarVQ,1,NCOVMAX);
12461: free_ivector(TvarVQind,1,NCOVMAX);
1.230 brouard 12462: free_ivector(Tvarsel,1,NCOVMAX);
12463: free_vector(Tvalsel,1,NCOVMAX);
1.227 brouard 12464: free_ivector(Tposprod,1,NCOVMAX);
12465: free_ivector(Tprod,1,NCOVMAX);
12466: free_ivector(Tvaraff,1,NCOVMAX);
12467: free_ivector(invalidvarcomb,1,ncovcombmax);
12468: free_ivector(Tage,1,NCOVMAX);
12469: free_ivector(Tmodelind,1,NCOVMAX);
1.228 brouard 12470: free_ivector(TmodelInvind,1,NCOVMAX);
12471: free_ivector(TmodelInvQind,1,NCOVMAX);
1.227 brouard 12472:
12473: free_imatrix(nbcode,0,NCOVMAX,0,NCOVMAX);
12474: /* free_imatrix(codtab,1,100,1,10); */
1.126 brouard 12475: fflush(fichtm);
12476: fflush(ficgp);
12477:
1.227 brouard 12478:
1.126 brouard 12479: if((nberr >0) || (nbwarn>0)){
1.216 brouard 12480: printf("End of Imach with %d errors and/or %d warnings. Please look at the log file for details.\n",nberr,nbwarn);
12481: 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 12482: }else{
12483: printf("End of Imach\n");
12484: fprintf(ficlog,"End of Imach\n");
12485: }
12486: printf("See log file on %s\n",filelog);
12487: /* gettimeofday(&end_time, (struct timezone*)0);*/ /* after time */
1.157 brouard 12488: /*(void) gettimeofday(&end_time,&tzp);*/
12489: rend_time = time(NULL);
12490: end_time = *localtime(&rend_time);
12491: /* tml = *localtime(&end_time.tm_sec); */
12492: strcpy(strtend,asctime(&end_time));
1.126 brouard 12493: printf("Local time at start %s\nLocal time at end %s",strstart, strtend);
12494: fprintf(ficlog,"Local time at start %s\nLocal time at end %s\n",strstart, strtend);
1.157 brouard 12495: printf("Total time used %s\n", asc_diff_time(rend_time -rstart_time,tmpout));
1.227 brouard 12496:
1.157 brouard 12497: printf("Total time was %.0lf Sec.\n", difftime(rend_time,rstart_time));
12498: fprintf(ficlog,"Total time used %s\n", asc_diff_time(rend_time -rstart_time,tmpout));
12499: fprintf(ficlog,"Total time was %.0lf Sec.\n", difftime(rend_time,rstart_time));
1.126 brouard 12500: /* printf("Total time was %d uSec.\n", total_usecs);*/
12501: /* if(fileappend(fichtm,optionfilehtm)){ */
12502: fprintf(fichtm,"<br>Local time at start %s<br>Local time at end %s<br>\n</body></html>",strstart, strtend);
12503: fclose(fichtm);
12504: fprintf(fichtmcov,"<br>Local time at start %s<br>Local time at end %s<br>\n</body></html>",strstart, strtend);
12505: fclose(fichtmcov);
12506: fclose(ficgp);
12507: fclose(ficlog);
12508: /*------ End -----------*/
1.227 brouard 12509:
12510:
12511: printf("Before Current directory %s!\n",pathcd);
1.184 brouard 12512: #ifdef WIN32
1.227 brouard 12513: if (_chdir(pathcd) != 0)
12514: printf("Can't move to directory %s!\n",path);
12515: if(_getcwd(pathcd,MAXLINE) > 0)
1.184 brouard 12516: #else
1.227 brouard 12517: if(chdir(pathcd) != 0)
12518: printf("Can't move to directory %s!\n", path);
12519: if (getcwd(pathcd, MAXLINE) > 0)
1.184 brouard 12520: #endif
1.126 brouard 12521: printf("Current directory %s!\n",pathcd);
12522: /*strcat(plotcmd,CHARSEPARATOR);*/
12523: sprintf(plotcmd,"gnuplot");
1.157 brouard 12524: #ifdef _WIN32
1.126 brouard 12525: sprintf(plotcmd,"\"%sgnuplot.exe\"",pathimach);
12526: #endif
12527: if(!stat(plotcmd,&info)){
1.158 brouard 12528: printf("Error or gnuplot program not found: '%s'\n",plotcmd);fflush(stdout);
1.126 brouard 12529: if(!stat(getenv("GNUPLOTBIN"),&info)){
1.158 brouard 12530: printf("Error or gnuplot program not found: '%s' Environment GNUPLOTBIN not set.\n",plotcmd);fflush(stdout);
1.126 brouard 12531: }else
12532: strcpy(pplotcmd,plotcmd);
1.157 brouard 12533: #ifdef __unix
1.126 brouard 12534: strcpy(plotcmd,GNUPLOTPROGRAM);
12535: if(!stat(plotcmd,&info)){
1.158 brouard 12536: printf("Error gnuplot program not found: '%s'\n",plotcmd);fflush(stdout);
1.126 brouard 12537: }else
12538: strcpy(pplotcmd,plotcmd);
12539: #endif
12540: }else
12541: strcpy(pplotcmd,plotcmd);
12542:
12543: sprintf(plotcmd,"%s %s",pplotcmd, optionfilegnuplot);
1.158 brouard 12544: printf("Starting graphs with: '%s'\n",plotcmd);fflush(stdout);
1.227 brouard 12545:
1.126 brouard 12546: if((outcmd=system(plotcmd)) != 0){
1.158 brouard 12547: printf("gnuplot command might not be in your path: '%s', err=%d\n", plotcmd, outcmd);
1.154 brouard 12548: printf("\n Trying if gnuplot resides on the same directory that IMaCh\n");
1.152 brouard 12549: sprintf(plotcmd,"%sgnuplot %s", pathimach, optionfilegnuplot);
1.150 brouard 12550: if((outcmd=system(plotcmd)) != 0)
1.153 brouard 12551: printf("\n Still a problem with gnuplot command %s, err=%d\n", plotcmd, outcmd);
1.126 brouard 12552: }
1.158 brouard 12553: printf(" Successful, please wait...");
1.126 brouard 12554: while (z[0] != 'q') {
12555: /* chdir(path); */
1.154 brouard 12556: printf("\nType e to edit results with your browser, g to graph again and q for exit: ");
1.126 brouard 12557: scanf("%s",z);
12558: /* if (z[0] == 'c') system("./imach"); */
12559: if (z[0] == 'e') {
1.158 brouard 12560: #ifdef __APPLE__
1.152 brouard 12561: sprintf(pplotcmd, "open %s", optionfilehtm);
1.157 brouard 12562: #elif __linux
12563: sprintf(pplotcmd, "xdg-open %s", optionfilehtm);
1.153 brouard 12564: #else
1.152 brouard 12565: sprintf(pplotcmd, "%s", optionfilehtm);
1.153 brouard 12566: #endif
12567: printf("Starting browser with: %s",pplotcmd);fflush(stdout);
12568: system(pplotcmd);
1.126 brouard 12569: }
12570: else if (z[0] == 'g') system(plotcmd);
12571: else if (z[0] == 'q') exit(0);
12572: }
1.227 brouard 12573: end:
1.126 brouard 12574: while (z[0] != 'q') {
1.195 brouard 12575: printf("\nType q for exiting: "); fflush(stdout);
1.126 brouard 12576: scanf("%s",z);
12577: }
12578: }
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