Annotation of imach/src/imach.c, revision 1.243
1.243 ! brouard 1: /* $Id: imach.c,v 1.242 2016/08/30 15:01:20 brouard Exp $
1.126 brouard 2: $State: Exp $
1.163 brouard 3: $Log: imach.c,v $
1.243 ! brouard 4: Revision 1.242 2016/08/30 15:01:20 brouard
! 5: Summary: Fixing a lots
! 6:
1.242 brouard 7: Revision 1.241 2016/08/29 17:17:25 brouard
8: Summary: gnuplot problem in Back projection to fix
9:
1.241 brouard 10: Revision 1.240 2016/08/29 07:53:18 brouard
11: Summary: Better
12:
1.240 brouard 13: Revision 1.239 2016/08/26 15:51:03 brouard
14: Summary: Improvement in Powell output in order to copy and paste
15:
16: Author:
17:
1.239 brouard 18: Revision 1.238 2016/08/26 14:23:35 brouard
19: Summary: Starting tests of 0.99
20:
1.238 brouard 21: Revision 1.237 2016/08/26 09:20:19 brouard
22: Summary: to valgrind
23:
1.237 brouard 24: Revision 1.236 2016/08/25 10:50:18 brouard
25: *** empty log message ***
26:
1.236 brouard 27: Revision 1.235 2016/08/25 06:59:23 brouard
28: *** empty log message ***
29:
1.235 brouard 30: Revision 1.234 2016/08/23 16:51:20 brouard
31: *** empty log message ***
32:
1.234 brouard 33: Revision 1.233 2016/08/23 07:40:50 brouard
34: Summary: not working
35:
1.233 brouard 36: Revision 1.232 2016/08/22 14:20:21 brouard
37: Summary: not working
38:
1.232 brouard 39: Revision 1.231 2016/08/22 07:17:15 brouard
40: Summary: not working
41:
1.231 brouard 42: Revision 1.230 2016/08/22 06:55:53 brouard
43: Summary: Not working
44:
1.230 brouard 45: Revision 1.229 2016/07/23 09:45:53 brouard
46: Summary: Completing for func too
47:
1.229 brouard 48: Revision 1.228 2016/07/22 17:45:30 brouard
49: Summary: Fixing some arrays, still debugging
50:
1.227 brouard 51: Revision 1.226 2016/07/12 18:42:34 brouard
52: Summary: temp
53:
1.226 brouard 54: Revision 1.225 2016/07/12 08:40:03 brouard
55: Summary: saving but not running
56:
1.225 brouard 57: Revision 1.224 2016/07/01 13:16:01 brouard
58: Summary: Fixes
59:
1.224 brouard 60: Revision 1.223 2016/02/19 09:23:35 brouard
61: Summary: temporary
62:
1.223 brouard 63: Revision 1.222 2016/02/17 08:14:50 brouard
64: Summary: Probably last 0.98 stable version 0.98r6
65:
1.222 brouard 66: Revision 1.221 2016/02/15 23:35:36 brouard
67: Summary: minor bug
68:
1.220 brouard 69: Revision 1.219 2016/02/15 00:48:12 brouard
70: *** empty log message ***
71:
1.219 brouard 72: Revision 1.218 2016/02/12 11:29:23 brouard
73: Summary: 0.99 Back projections
74:
1.218 brouard 75: Revision 1.217 2015/12/23 17:18:31 brouard
76: Summary: Experimental backcast
77:
1.217 brouard 78: Revision 1.216 2015/12/18 17:32:11 brouard
79: Summary: 0.98r4 Warning and status=-2
80:
81: Version 0.98r4 is now:
82: - displaying an error when status is -1, date of interview unknown and date of death known;
83: - permitting a status -2 when the vital status is unknown at a known date of right truncation.
84: Older changes concerning s=-2, dating from 2005 have been supersed.
85:
1.216 brouard 86: Revision 1.215 2015/12/16 08:52:24 brouard
87: Summary: 0.98r4 working
88:
1.215 brouard 89: Revision 1.214 2015/12/16 06:57:54 brouard
90: Summary: temporary not working
91:
1.214 brouard 92: Revision 1.213 2015/12/11 18:22:17 brouard
93: Summary: 0.98r4
94:
1.213 brouard 95: Revision 1.212 2015/11/21 12:47:24 brouard
96: Summary: minor typo
97:
1.212 brouard 98: Revision 1.211 2015/11/21 12:41:11 brouard
99: Summary: 0.98r3 with some graph of projected cross-sectional
100:
101: Author: Nicolas Brouard
102:
1.211 brouard 103: Revision 1.210 2015/11/18 17:41:20 brouard
104: Summary: Start working on projected prevalences
105:
1.210 brouard 106: Revision 1.209 2015/11/17 22:12:03 brouard
107: Summary: Adding ftolpl parameter
108: Author: N Brouard
109:
110: We had difficulties to get smoothed confidence intervals. It was due
111: to the period prevalence which wasn't computed accurately. The inner
112: parameter ftolpl is now an outer parameter of the .imach parameter
113: file after estepm. If ftolpl is small 1.e-4 and estepm too,
114: computation are long.
115:
1.209 brouard 116: Revision 1.208 2015/11/17 14:31:57 brouard
117: Summary: temporary
118:
1.208 brouard 119: Revision 1.207 2015/10/27 17:36:57 brouard
120: *** empty log message ***
121:
1.207 brouard 122: Revision 1.206 2015/10/24 07:14:11 brouard
123: *** empty log message ***
124:
1.206 brouard 125: Revision 1.205 2015/10/23 15:50:53 brouard
126: Summary: 0.98r3 some clarification for graphs on likelihood contributions
127:
1.205 brouard 128: Revision 1.204 2015/10/01 16:20:26 brouard
129: Summary: Some new graphs of contribution to likelihood
130:
1.204 brouard 131: Revision 1.203 2015/09/30 17:45:14 brouard
132: Summary: looking at better estimation of the hessian
133:
134: Also a better criteria for convergence to the period prevalence And
135: therefore adding the number of years needed to converge. (The
136: prevalence in any alive state shold sum to one
137:
1.203 brouard 138: Revision 1.202 2015/09/22 19:45:16 brouard
139: Summary: Adding some overall graph on contribution to likelihood. Might change
140:
1.202 brouard 141: Revision 1.201 2015/09/15 17:34:58 brouard
142: Summary: 0.98r0
143:
144: - Some new graphs like suvival functions
145: - Some bugs fixed like model=1+age+V2.
146:
1.201 brouard 147: Revision 1.200 2015/09/09 16:53:55 brouard
148: Summary: Big bug thanks to Flavia
149:
150: Even model=1+age+V2. did not work anymore
151:
1.200 brouard 152: Revision 1.199 2015/09/07 14:09:23 brouard
153: Summary: 0.98q6 changing default small png format for graph to vectorized svg.
154:
1.199 brouard 155: Revision 1.198 2015/09/03 07:14:39 brouard
156: Summary: 0.98q5 Flavia
157:
1.198 brouard 158: Revision 1.197 2015/09/01 18:24:39 brouard
159: *** empty log message ***
160:
1.197 brouard 161: Revision 1.196 2015/08/18 23:17:52 brouard
162: Summary: 0.98q5
163:
1.196 brouard 164: Revision 1.195 2015/08/18 16:28:39 brouard
165: Summary: Adding a hack for testing purpose
166:
167: After reading the title, ftol and model lines, if the comment line has
168: a q, starting with #q, the answer at the end of the run is quit. It
169: permits to run test files in batch with ctest. The former workaround was
170: $ echo q | imach foo.imach
171:
1.195 brouard 172: Revision 1.194 2015/08/18 13:32:00 brouard
173: Summary: Adding error when the covariance matrix doesn't contain the exact number of lines required by the model line.
174:
1.194 brouard 175: Revision 1.193 2015/08/04 07:17:42 brouard
176: Summary: 0.98q4
177:
1.193 brouard 178: Revision 1.192 2015/07/16 16:49:02 brouard
179: Summary: Fixing some outputs
180:
1.192 brouard 181: Revision 1.191 2015/07/14 10:00:33 brouard
182: Summary: Some fixes
183:
1.191 brouard 184: Revision 1.190 2015/05/05 08:51:13 brouard
185: Summary: Adding digits in output parameters (7 digits instead of 6)
186:
187: Fix 1+age+.
188:
1.190 brouard 189: Revision 1.189 2015/04/30 14:45:16 brouard
190: Summary: 0.98q2
191:
1.189 brouard 192: Revision 1.188 2015/04/30 08:27:53 brouard
193: *** empty log message ***
194:
1.188 brouard 195: Revision 1.187 2015/04/29 09:11:15 brouard
196: *** empty log message ***
197:
1.187 brouard 198: Revision 1.186 2015/04/23 12:01:52 brouard
199: Summary: V1*age is working now, version 0.98q1
200:
201: Some codes had been disabled in order to simplify and Vn*age was
202: working in the optimization phase, ie, giving correct MLE parameters,
203: but, as usual, outputs were not correct and program core dumped.
204:
1.186 brouard 205: Revision 1.185 2015/03/11 13:26:42 brouard
206: Summary: Inclusion of compile and links command line for Intel Compiler
207:
1.185 brouard 208: Revision 1.184 2015/03/11 11:52:39 brouard
209: Summary: Back from Windows 8. Intel Compiler
210:
1.184 brouard 211: Revision 1.183 2015/03/10 20:34:32 brouard
212: Summary: 0.98q0, trying with directest, mnbrak fixed
213:
214: We use directest instead of original Powell test; probably no
215: incidence on the results, but better justifications;
216: We fixed Numerical Recipes mnbrak routine which was wrong and gave
217: wrong results.
218:
1.183 brouard 219: Revision 1.182 2015/02/12 08:19:57 brouard
220: Summary: Trying to keep directest which seems simpler and more general
221: Author: Nicolas Brouard
222:
1.182 brouard 223: Revision 1.181 2015/02/11 23:22:24 brouard
224: Summary: Comments on Powell added
225:
226: Author:
227:
1.181 brouard 228: Revision 1.180 2015/02/11 17:33:45 brouard
229: Summary: Finishing move from main to function (hpijx and prevalence_limit)
230:
1.180 brouard 231: Revision 1.179 2015/01/04 09:57:06 brouard
232: Summary: back to OS/X
233:
1.179 brouard 234: Revision 1.178 2015/01/04 09:35:48 brouard
235: *** empty log message ***
236:
1.178 brouard 237: Revision 1.177 2015/01/03 18:40:56 brouard
238: Summary: Still testing ilc32 on OSX
239:
1.177 brouard 240: Revision 1.176 2015/01/03 16:45:04 brouard
241: *** empty log message ***
242:
1.176 brouard 243: Revision 1.175 2015/01/03 16:33:42 brouard
244: *** empty log message ***
245:
1.175 brouard 246: Revision 1.174 2015/01/03 16:15:49 brouard
247: Summary: Still in cross-compilation
248:
1.174 brouard 249: Revision 1.173 2015/01/03 12:06:26 brouard
250: Summary: trying to detect cross-compilation
251:
1.173 brouard 252: Revision 1.172 2014/12/27 12:07:47 brouard
253: Summary: Back from Visual Studio and Intel, options for compiling for Windows XP
254:
1.172 brouard 255: Revision 1.171 2014/12/23 13:26:59 brouard
256: Summary: Back from Visual C
257:
258: Still problem with utsname.h on Windows
259:
1.171 brouard 260: Revision 1.170 2014/12/23 11:17:12 brouard
261: Summary: Cleaning some \%% back to %%
262:
263: The escape was mandatory for a specific compiler (which one?), but too many warnings.
264:
1.170 brouard 265: Revision 1.169 2014/12/22 23:08:31 brouard
266: Summary: 0.98p
267:
268: Outputs some informations on compiler used, OS etc. Testing on different platforms.
269:
1.169 brouard 270: Revision 1.168 2014/12/22 15:17:42 brouard
1.170 brouard 271: Summary: update
1.169 brouard 272:
1.168 brouard 273: Revision 1.167 2014/12/22 13:50:56 brouard
274: Summary: Testing uname and compiler version and if compiled 32 or 64
275:
276: Testing on Linux 64
277:
1.167 brouard 278: Revision 1.166 2014/12/22 11:40:47 brouard
279: *** empty log message ***
280:
1.166 brouard 281: Revision 1.165 2014/12/16 11:20:36 brouard
282: Summary: After compiling on Visual C
283:
284: * imach.c (Module): Merging 1.61 to 1.162
285:
1.165 brouard 286: Revision 1.164 2014/12/16 10:52:11 brouard
287: Summary: Merging with Visual C after suppressing some warnings for unused variables. Also fixing Saito's bug 0.98Xn
288:
289: * imach.c (Module): Merging 1.61 to 1.162
290:
1.164 brouard 291: Revision 1.163 2014/12/16 10:30:11 brouard
292: * imach.c (Module): Merging 1.61 to 1.162
293:
1.163 brouard 294: Revision 1.162 2014/09/25 11:43:39 brouard
295: Summary: temporary backup 0.99!
296:
1.162 brouard 297: Revision 1.1 2014/09/16 11:06:58 brouard
298: Summary: With some code (wrong) for nlopt
299:
300: Author:
301:
302: Revision 1.161 2014/09/15 20:41:41 brouard
303: Summary: Problem with macro SQR on Intel compiler
304:
1.161 brouard 305: Revision 1.160 2014/09/02 09:24:05 brouard
306: *** empty log message ***
307:
1.160 brouard 308: Revision 1.159 2014/09/01 10:34:10 brouard
309: Summary: WIN32
310: Author: Brouard
311:
1.159 brouard 312: Revision 1.158 2014/08/27 17:11:51 brouard
313: *** empty log message ***
314:
1.158 brouard 315: Revision 1.157 2014/08/27 16:26:55 brouard
316: Summary: Preparing windows Visual studio version
317: Author: Brouard
318:
319: In order to compile on Visual studio, time.h is now correct and time_t
320: and tm struct should be used. difftime should be used but sometimes I
321: just make the differences in raw time format (time(&now).
322: Trying to suppress #ifdef LINUX
323: Add xdg-open for __linux in order to open default browser.
324:
1.157 brouard 325: Revision 1.156 2014/08/25 20:10:10 brouard
326: *** empty log message ***
327:
1.156 brouard 328: Revision 1.155 2014/08/25 18:32:34 brouard
329: Summary: New compile, minor changes
330: Author: Brouard
331:
1.155 brouard 332: Revision 1.154 2014/06/20 17:32:08 brouard
333: Summary: Outputs now all graphs of convergence to period prevalence
334:
1.154 brouard 335: Revision 1.153 2014/06/20 16:45:46 brouard
336: Summary: If 3 live state, convergence to period prevalence on same graph
337: Author: Brouard
338:
1.153 brouard 339: Revision 1.152 2014/06/18 17:54:09 brouard
340: Summary: open browser, use gnuplot on same dir than imach if not found in the path
341:
1.152 brouard 342: Revision 1.151 2014/06/18 16:43:30 brouard
343: *** empty log message ***
344:
1.151 brouard 345: Revision 1.150 2014/06/18 16:42:35 brouard
346: Summary: If gnuplot is not in the path try on same directory than imach binary (OSX)
347: Author: brouard
348:
1.150 brouard 349: Revision 1.149 2014/06/18 15:51:14 brouard
350: Summary: Some fixes in parameter files errors
351: Author: Nicolas Brouard
352:
1.149 brouard 353: Revision 1.148 2014/06/17 17:38:48 brouard
354: Summary: Nothing new
355: Author: Brouard
356:
357: Just a new packaging for OS/X version 0.98nS
358:
1.148 brouard 359: Revision 1.147 2014/06/16 10:33:11 brouard
360: *** empty log message ***
361:
1.147 brouard 362: Revision 1.146 2014/06/16 10:20:28 brouard
363: Summary: Merge
364: Author: Brouard
365:
366: Merge, before building revised version.
367:
1.146 brouard 368: Revision 1.145 2014/06/10 21:23:15 brouard
369: Summary: Debugging with valgrind
370: Author: Nicolas Brouard
371:
372: Lot of changes in order to output the results with some covariates
373: After the Edimburgh REVES conference 2014, it seems mandatory to
374: improve the code.
375: No more memory valgrind error but a lot has to be done in order to
376: continue the work of splitting the code into subroutines.
377: Also, decodemodel has been improved. Tricode is still not
378: optimal. nbcode should be improved. Documentation has been added in
379: the source code.
380:
1.144 brouard 381: Revision 1.143 2014/01/26 09:45:38 brouard
382: Summary: Version 0.98nR (to be improved, but gives same optimization results as 0.98k. Nice, promising
383:
384: * imach.c (Module): Trying to merge old staffs together while being at Tokyo. Not tested...
385: (Module): Version 0.98nR Running ok, but output format still only works for three covariates.
386:
1.143 brouard 387: Revision 1.142 2014/01/26 03:57:36 brouard
388: Summary: gnuplot changed plot w l 1 has to be changed to plot w l lt 2
389:
390: * imach.c (Module): Trying to merge old staffs together while being at Tokyo. Not tested...
391:
1.142 brouard 392: Revision 1.141 2014/01/26 02:42:01 brouard
393: * imach.c (Module): Trying to merge old staffs together while being at Tokyo. Not tested...
394:
1.141 brouard 395: Revision 1.140 2011/09/02 10:37:54 brouard
396: Summary: times.h is ok with mingw32 now.
397:
1.140 brouard 398: Revision 1.139 2010/06/14 07:50:17 brouard
399: After the theft of my laptop, I probably lost some lines of codes which were not uploaded to the CVS tree.
400: I remember having already fixed agemin agemax which are pointers now but not cvs saved.
401:
1.139 brouard 402: Revision 1.138 2010/04/30 18:19:40 brouard
403: *** empty log message ***
404:
1.138 brouard 405: Revision 1.137 2010/04/29 18:11:38 brouard
406: (Module): Checking covariates for more complex models
407: than V1+V2. A lot of change to be done. Unstable.
408:
1.137 brouard 409: Revision 1.136 2010/04/26 20:30:53 brouard
410: (Module): merging some libgsl code. Fixing computation
411: of likelione (using inter/intrapolation if mle = 0) in order to
412: get same likelihood as if mle=1.
413: Some cleaning of code and comments added.
414:
1.136 brouard 415: Revision 1.135 2009/10/29 15:33:14 brouard
416: (Module): Now imach stops if date of birth, at least year of birth, is not given. Some cleaning of the code.
417:
1.135 brouard 418: Revision 1.134 2009/10/29 13:18:53 brouard
419: (Module): Now imach stops if date of birth, at least year of birth, is not given. Some cleaning of the code.
420:
1.134 brouard 421: Revision 1.133 2009/07/06 10:21:25 brouard
422: just nforces
423:
1.133 brouard 424: Revision 1.132 2009/07/06 08:22:05 brouard
425: Many tings
426:
1.132 brouard 427: Revision 1.131 2009/06/20 16:22:47 brouard
428: Some dimensions resccaled
429:
1.131 brouard 430: Revision 1.130 2009/05/26 06:44:34 brouard
431: (Module): Max Covariate is now set to 20 instead of 8. A
432: lot of cleaning with variables initialized to 0. Trying to make
433: V2+V3*age+V1+V4 strb=V3*age+V1+V4 working better.
434:
1.130 brouard 435: Revision 1.129 2007/08/31 13:49:27 lievre
436: Modification of the way of exiting when the covariate is not binary in order to see on the window the error message before exiting
437:
1.129 lievre 438: Revision 1.128 2006/06/30 13:02:05 brouard
439: (Module): Clarifications on computing e.j
440:
1.128 brouard 441: Revision 1.127 2006/04/28 18:11:50 brouard
442: (Module): Yes the sum of survivors was wrong since
443: imach-114 because nhstepm was no more computed in the age
444: loop. Now we define nhstepma in the age loop.
445: (Module): In order to speed up (in case of numerous covariates) we
446: compute health expectancies (without variances) in a first step
447: and then all the health expectancies with variances or standard
448: deviation (needs data from the Hessian matrices) which slows the
449: computation.
450: In the future we should be able to stop the program is only health
451: expectancies and graph are needed without standard deviations.
452:
1.127 brouard 453: Revision 1.126 2006/04/28 17:23:28 brouard
454: (Module): Yes the sum of survivors was wrong since
455: imach-114 because nhstepm was no more computed in the age
456: loop. Now we define nhstepma in the age loop.
457: Version 0.98h
458:
1.126 brouard 459: Revision 1.125 2006/04/04 15:20:31 lievre
460: Errors in calculation of health expectancies. Age was not initialized.
461: Forecasting file added.
462:
463: Revision 1.124 2006/03/22 17:13:53 lievre
464: Parameters are printed with %lf instead of %f (more numbers after the comma).
465: The log-likelihood is printed in the log file
466:
467: Revision 1.123 2006/03/20 10:52:43 brouard
468: * imach.c (Module): <title> changed, corresponds to .htm file
469: name. <head> headers where missing.
470:
471: * imach.c (Module): Weights can have a decimal point as for
472: English (a comma might work with a correct LC_NUMERIC environment,
473: otherwise the weight is truncated).
474: Modification of warning when the covariates values are not 0 or
475: 1.
476: Version 0.98g
477:
478: Revision 1.122 2006/03/20 09:45:41 brouard
479: (Module): Weights can have a decimal point as for
480: English (a comma might work with a correct LC_NUMERIC environment,
481: otherwise the weight is truncated).
482: Modification of warning when the covariates values are not 0 or
483: 1.
484: Version 0.98g
485:
486: Revision 1.121 2006/03/16 17:45:01 lievre
487: * imach.c (Module): Comments concerning covariates added
488:
489: * imach.c (Module): refinements in the computation of lli if
490: status=-2 in order to have more reliable computation if stepm is
491: not 1 month. Version 0.98f
492:
493: Revision 1.120 2006/03/16 15:10:38 lievre
494: (Module): refinements in the computation of lli if
495: status=-2 in order to have more reliable computation if stepm is
496: not 1 month. Version 0.98f
497:
498: Revision 1.119 2006/03/15 17:42:26 brouard
499: (Module): Bug if status = -2, the loglikelihood was
500: computed as likelihood omitting the logarithm. Version O.98e
501:
502: Revision 1.118 2006/03/14 18:20:07 brouard
503: (Module): varevsij Comments added explaining the second
504: table of variances if popbased=1 .
505: (Module): Covariances of eij, ekl added, graphs fixed, new html link.
506: (Module): Function pstamp added
507: (Module): Version 0.98d
508:
509: Revision 1.117 2006/03/14 17:16:22 brouard
510: (Module): varevsij Comments added explaining the second
511: table of variances if popbased=1 .
512: (Module): Covariances of eij, ekl added, graphs fixed, new html link.
513: (Module): Function pstamp added
514: (Module): Version 0.98d
515:
516: Revision 1.116 2006/03/06 10:29:27 brouard
517: (Module): Variance-covariance wrong links and
518: varian-covariance of ej. is needed (Saito).
519:
520: Revision 1.115 2006/02/27 12:17:45 brouard
521: (Module): One freematrix added in mlikeli! 0.98c
522:
523: Revision 1.114 2006/02/26 12:57:58 brouard
524: (Module): Some improvements in processing parameter
525: filename with strsep.
526:
527: Revision 1.113 2006/02/24 14:20:24 brouard
528: (Module): Memory leaks checks with valgrind and:
529: datafile was not closed, some imatrix were not freed and on matrix
530: allocation too.
531:
532: Revision 1.112 2006/01/30 09:55:26 brouard
533: (Module): Back to gnuplot.exe instead of wgnuplot.exe
534:
535: Revision 1.111 2006/01/25 20:38:18 brouard
536: (Module): Lots of cleaning and bugs added (Gompertz)
537: (Module): Comments can be added in data file. Missing date values
538: can be a simple dot '.'.
539:
540: Revision 1.110 2006/01/25 00:51:50 brouard
541: (Module): Lots of cleaning and bugs added (Gompertz)
542:
543: Revision 1.109 2006/01/24 19:37:15 brouard
544: (Module): Comments (lines starting with a #) are allowed in data.
545:
546: Revision 1.108 2006/01/19 18:05:42 lievre
547: Gnuplot problem appeared...
548: To be fixed
549:
550: Revision 1.107 2006/01/19 16:20:37 brouard
551: Test existence of gnuplot in imach path
552:
553: Revision 1.106 2006/01/19 13:24:36 brouard
554: Some cleaning and links added in html output
555:
556: Revision 1.105 2006/01/05 20:23:19 lievre
557: *** empty log message ***
558:
559: Revision 1.104 2005/09/30 16:11:43 lievre
560: (Module): sump fixed, loop imx fixed, and simplifications.
561: (Module): If the status is missing at the last wave but we know
562: that the person is alive, then we can code his/her status as -2
563: (instead of missing=-1 in earlier versions) and his/her
564: contributions to the likelihood is 1 - Prob of dying from last
565: health status (= 1-p13= p11+p12 in the easiest case of somebody in
566: the healthy state at last known wave). Version is 0.98
567:
568: Revision 1.103 2005/09/30 15:54:49 lievre
569: (Module): sump fixed, loop imx fixed, and simplifications.
570:
571: Revision 1.102 2004/09/15 17:31:30 brouard
572: Add the possibility to read data file including tab characters.
573:
574: Revision 1.101 2004/09/15 10:38:38 brouard
575: Fix on curr_time
576:
577: Revision 1.100 2004/07/12 18:29:06 brouard
578: Add version for Mac OS X. Just define UNIX in Makefile
579:
580: Revision 1.99 2004/06/05 08:57:40 brouard
581: *** empty log message ***
582:
583: Revision 1.98 2004/05/16 15:05:56 brouard
584: New version 0.97 . First attempt to estimate force of mortality
585: directly from the data i.e. without the need of knowing the health
586: state at each age, but using a Gompertz model: log u =a + b*age .
587: This is the basic analysis of mortality and should be done before any
588: other analysis, in order to test if the mortality estimated from the
589: cross-longitudinal survey is different from the mortality estimated
590: from other sources like vital statistic data.
591:
592: The same imach parameter file can be used but the option for mle should be -3.
593:
1.133 brouard 594: Agnès, who wrote this part of the code, tried to keep most of the
1.126 brouard 595: former routines in order to include the new code within the former code.
596:
597: The output is very simple: only an estimate of the intercept and of
598: the slope with 95% confident intervals.
599:
600: Current limitations:
601: A) Even if you enter covariates, i.e. with the
602: model= V1+V2 equation for example, the programm does only estimate a unique global model without covariates.
603: B) There is no computation of Life Expectancy nor Life Table.
604:
605: Revision 1.97 2004/02/20 13:25:42 lievre
606: Version 0.96d. Population forecasting command line is (temporarily)
607: suppressed.
608:
609: Revision 1.96 2003/07/15 15:38:55 brouard
610: * imach.c (Repository): Errors in subdirf, 2, 3 while printing tmpout is
611: rewritten within the same printf. Workaround: many printfs.
612:
613: Revision 1.95 2003/07/08 07:54:34 brouard
614: * imach.c (Repository):
615: (Repository): Using imachwizard code to output a more meaningful covariance
616: matrix (cov(a12,c31) instead of numbers.
617:
618: Revision 1.94 2003/06/27 13:00:02 brouard
619: Just cleaning
620:
621: Revision 1.93 2003/06/25 16:33:55 brouard
622: (Module): On windows (cygwin) function asctime_r doesn't
623: exist so I changed back to asctime which exists.
624: (Module): Version 0.96b
625:
626: Revision 1.92 2003/06/25 16:30:45 brouard
627: (Module): On windows (cygwin) function asctime_r doesn't
628: exist so I changed back to asctime which exists.
629:
630: Revision 1.91 2003/06/25 15:30:29 brouard
631: * imach.c (Repository): Duplicated warning errors corrected.
632: (Repository): Elapsed time after each iteration is now output. It
633: helps to forecast when convergence will be reached. Elapsed time
634: is stamped in powell. We created a new html file for the graphs
635: concerning matrix of covariance. It has extension -cov.htm.
636:
637: Revision 1.90 2003/06/24 12:34:15 brouard
638: (Module): Some bugs corrected for windows. Also, when
639: mle=-1 a template is output in file "or"mypar.txt with the design
640: of the covariance matrix to be input.
641:
642: Revision 1.89 2003/06/24 12:30:52 brouard
643: (Module): Some bugs corrected for windows. Also, when
644: mle=-1 a template is output in file "or"mypar.txt with the design
645: of the covariance matrix to be input.
646:
647: Revision 1.88 2003/06/23 17:54:56 brouard
648: * 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.
649:
650: Revision 1.87 2003/06/18 12:26:01 brouard
651: Version 0.96
652:
653: Revision 1.86 2003/06/17 20:04:08 brouard
654: (Module): Change position of html and gnuplot routines and added
655: routine fileappend.
656:
657: Revision 1.85 2003/06/17 13:12:43 brouard
658: * imach.c (Repository): Check when date of death was earlier that
659: current date of interview. It may happen when the death was just
660: prior to the death. In this case, dh was negative and likelihood
661: was wrong (infinity). We still send an "Error" but patch by
662: assuming that the date of death was just one stepm after the
663: interview.
664: (Repository): Because some people have very long ID (first column)
665: we changed int to long in num[] and we added a new lvector for
666: memory allocation. But we also truncated to 8 characters (left
667: truncation)
668: (Repository): No more line truncation errors.
669:
670: Revision 1.84 2003/06/13 21:44:43 brouard
671: * imach.c (Repository): Replace "freqsummary" at a correct
672: place. It differs from routine "prevalence" which may be called
673: many times. Probs is memory consuming and must be used with
674: parcimony.
675: Version 0.95a3 (should output exactly the same maximization than 0.8a2)
676:
677: Revision 1.83 2003/06/10 13:39:11 lievre
678: *** empty log message ***
679:
680: Revision 1.82 2003/06/05 15:57:20 brouard
681: Add log in imach.c and fullversion number is now printed.
682:
683: */
684: /*
685: Interpolated Markov Chain
686:
687: Short summary of the programme:
688:
1.227 brouard 689: This program computes Healthy Life Expectancies or State-specific
690: (if states aren't health statuses) Expectancies from
691: cross-longitudinal data. Cross-longitudinal data consist in:
692:
693: -1- a first survey ("cross") where individuals from different ages
694: are interviewed on their health status or degree of disability (in
695: the case of a health survey which is our main interest)
696:
697: -2- at least a second wave of interviews ("longitudinal") which
698: measure each change (if any) in individual health status. Health
699: expectancies are computed from the time spent in each health state
700: according to a model. More health states you consider, more time is
701: necessary to reach the Maximum Likelihood of the parameters involved
702: in the model. The simplest model is the multinomial logistic model
703: where pij is the probability to be observed in state j at the second
704: wave conditional to be observed in state i at the first
705: wave. Therefore the model is: log(pij/pii)= aij + bij*age+ cij*sex +
706: etc , where 'age' is age and 'sex' is a covariate. If you want to
707: have a more complex model than "constant and age", you should modify
708: the program where the markup *Covariates have to be included here
709: again* invites you to do it. More covariates you add, slower the
1.126 brouard 710: convergence.
711:
712: The advantage of this computer programme, compared to a simple
713: multinomial logistic model, is clear when the delay between waves is not
714: identical for each individual. Also, if a individual missed an
715: intermediate interview, the information is lost, but taken into
716: account using an interpolation or extrapolation.
717:
718: hPijx is the probability to be observed in state i at age x+h
719: conditional to the observed state i at age x. The delay 'h' can be
720: split into an exact number (nh*stepm) of unobserved intermediate
721: states. This elementary transition (by month, quarter,
722: semester or year) is modelled as a multinomial logistic. The hPx
723: matrix is simply the matrix product of nh*stepm elementary matrices
724: and the contribution of each individual to the likelihood is simply
725: hPijx.
726:
727: Also this programme outputs the covariance matrix of the parameters but also
1.218 brouard 728: of the life expectancies. It also computes the period (stable) prevalence.
729:
730: Back prevalence and projections:
1.227 brouard 731:
732: - back_prevalence_limit(double *p, double **bprlim, double ageminpar,
733: double agemaxpar, double ftolpl, int *ncvyearp, double
734: dateprev1,double dateprev2, int firstpass, int lastpass, int
735: mobilavproj)
736:
737: Computes the back prevalence limit for any combination of
738: covariate values k at any age between ageminpar and agemaxpar and
739: returns it in **bprlim. In the loops,
740:
741: - **bprevalim(**bprlim, ***mobaverage, nlstate, *p, age, **oldm,
742: **savm, **dnewm, **doldm, **dsavm, ftolpl, ncvyearp, k);
743:
744: - hBijx Back Probability to be in state i at age x-h being in j at x
1.218 brouard 745: Computes for any combination of covariates k and any age between bage and fage
746: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
747: oldm=oldms;savm=savms;
1.227 brouard 748:
749: - hbxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k);
1.218 brouard 750: Computes the transition matrix starting at age 'age' over
751: 'nhstepm*hstepm*stepm' months (i.e. until
752: age (in years) age+nhstepm*hstepm*stepm/12) by multiplying
1.227 brouard 753: nhstepm*hstepm matrices.
754:
755: Returns p3mat[i][j][h] after calling
756: p3mat[i][j][h]=matprod2(newm,
757: bmij(pmmij,cov,ncovmodel,x,nlstate,prevacurrent, dnewm, doldm,
758: dsavm,ij),\ 1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath,
759: oldm);
1.226 brouard 760:
761: Important routines
762:
763: - func (or funcone), computes logit (pij) distinguishing
764: o fixed variables (single or product dummies or quantitative);
765: o varying variables by:
766: (1) wave (single, product dummies, quantitative),
767: (2) by age (can be month) age (done), age*age (done), age*Vn where Vn can be:
768: % fixed dummy (treated) or quantitative (not done because time-consuming);
769: % varying dummy (not done) or quantitative (not done);
770: - Tricode which tests the modality of dummy variables (in order to warn with wrong or empty modalities)
771: and returns the number of efficient covariates cptcoveff and modalities nbcode[Tvar[k]][1]= 0 and nbcode[Tvar[k]][2]= 1 usually.
772: - printinghtml which outputs results like life expectancy in and from a state for a combination of modalities of dummy variables
773: o There are 2*cptcoveff combinations of (0,1) for cptcoveff variables. Outputting only combinations with people, éliminating 1 1 if
774: race White (0 0), Black vs White (1 0), Hispanic (0 1) and 1 1 being meaningless.
1.218 brouard 775:
1.226 brouard 776:
777:
1.133 brouard 778: Authors: Nicolas Brouard (brouard@ined.fr) and Agnès Lièvre (lievre@ined.fr).
779: Institut national d'études démographiques, Paris.
1.126 brouard 780: This software have been partly granted by Euro-REVES, a concerted action
781: from the European Union.
782: It is copyrighted identically to a GNU software product, ie programme and
783: software can be distributed freely for non commercial use. Latest version
784: can be accessed at http://euroreves.ined.fr/imach .
785:
786: Help to debug: LD_PRELOAD=/usr/local/lib/libnjamd.so ./imach foo.imach
787: or better on gdb : set env LD_PRELOAD=/usr/local/lib/libnjamd.so
788:
789: **********************************************************************/
790: /*
791: main
792: read parameterfile
793: read datafile
794: concatwav
795: freqsummary
796: if (mle >= 1)
797: mlikeli
798: print results files
799: if mle==1
800: computes hessian
801: read end of parameter file: agemin, agemax, bage, fage, estepm
802: begin-prev-date,...
803: open gnuplot file
804: open html file
1.145 brouard 805: period (stable) prevalence | pl_nom 1-1 2-2 etc by covariate
806: for age prevalim() | #****** V1=0 V2=1 V3=1 V4=0 ******
807: | 65 1 0 2 1 3 1 4 0 0.96326 0.03674
808: freexexit2 possible for memory heap.
809:
810: h Pij x | pij_nom ficrestpij
811: # Cov Agex agex+h hpijx with i,j= 1-1 1-2 1-3 2-1 2-2 2-3
812: 1 85 85 1.00000 0.00000 0.00000 0.00000 1.00000 0.00000
813: 1 85 86 0.68299 0.22291 0.09410 0.71093 0.00000 0.28907
814:
815: 1 65 99 0.00364 0.00322 0.99314 0.00350 0.00310 0.99340
816: 1 65 100 0.00214 0.00204 0.99581 0.00206 0.00196 0.99597
817: variance of p one-step probabilities varprob | prob_nom ficresprob #One-step probabilities and stand. devi in ()
818: Standard deviation of one-step probabilities | probcor_nom ficresprobcor #One-step probabilities and correlation matrix
819: Matrix of variance covariance of one-step probabilities | probcov_nom ficresprobcov #One-step probabilities and covariance matrix
820:
1.126 brouard 821: forecasting if prevfcast==1 prevforecast call prevalence()
822: health expectancies
823: Variance-covariance of DFLE
824: prevalence()
825: movingaverage()
826: varevsij()
827: if popbased==1 varevsij(,popbased)
828: total life expectancies
829: Variance of period (stable) prevalence
830: end
831: */
832:
1.187 brouard 833: /* #define DEBUG */
834: /* #define DEBUGBRENT */
1.203 brouard 835: /* #define DEBUGLINMIN */
836: /* #define DEBUGHESS */
837: #define DEBUGHESSIJ
1.224 brouard 838: /* #define LINMINORIGINAL /\* Don't use loop on scale in linmin (accepting nan) *\/ */
1.165 brouard 839: #define POWELL /* Instead of NLOPT */
1.224 brouard 840: #define POWELLNOF3INFF1TEST /* Skip test */
1.186 brouard 841: /* #define POWELLORIGINAL /\* Don't use Directest to decide new direction but original Powell test *\/ */
842: /* #define MNBRAKORIGINAL /\* Don't use mnbrak fix *\/ */
1.126 brouard 843:
844: #include <math.h>
845: #include <stdio.h>
846: #include <stdlib.h>
847: #include <string.h>
1.226 brouard 848: #include <ctype.h>
1.159 brouard 849:
850: #ifdef _WIN32
851: #include <io.h>
1.172 brouard 852: #include <windows.h>
853: #include <tchar.h>
1.159 brouard 854: #else
1.126 brouard 855: #include <unistd.h>
1.159 brouard 856: #endif
1.126 brouard 857:
858: #include <limits.h>
859: #include <sys/types.h>
1.171 brouard 860:
861: #if defined(__GNUC__)
862: #include <sys/utsname.h> /* Doesn't work on Windows */
863: #endif
864:
1.126 brouard 865: #include <sys/stat.h>
866: #include <errno.h>
1.159 brouard 867: /* extern int errno; */
1.126 brouard 868:
1.157 brouard 869: /* #ifdef LINUX */
870: /* #include <time.h> */
871: /* #include "timeval.h" */
872: /* #else */
873: /* #include <sys/time.h> */
874: /* #endif */
875:
1.126 brouard 876: #include <time.h>
877:
1.136 brouard 878: #ifdef GSL
879: #include <gsl/gsl_errno.h>
880: #include <gsl/gsl_multimin.h>
881: #endif
882:
1.167 brouard 883:
1.162 brouard 884: #ifdef NLOPT
885: #include <nlopt.h>
886: typedef struct {
887: double (* function)(double [] );
888: } myfunc_data ;
889: #endif
890:
1.126 brouard 891: /* #include <libintl.h> */
892: /* #define _(String) gettext (String) */
893:
1.141 brouard 894: #define MAXLINE 1024 /* Was 256. Overflow with 312 with 2 states and 4 covariates. Should be ok */
1.126 brouard 895:
896: #define GNUPLOTPROGRAM "gnuplot"
897: /*#define GNUPLOTPROGRAM "..\\gp37mgw\\wgnuplot"*/
898: #define FILENAMELENGTH 132
899:
900: #define GLOCK_ERROR_NOPATH -1 /* empty path */
901: #define GLOCK_ERROR_GETCWD -2 /* cannot get cwd */
902:
1.144 brouard 903: #define MAXPARM 128 /**< Maximum number of parameters for the optimization */
904: #define NPARMAX 64 /**< (nlstate+ndeath-1)*nlstate*ncovmodel */
1.126 brouard 905:
906: #define NINTERVMAX 8
1.144 brouard 907: #define NLSTATEMAX 8 /**< Maximum number of live states (for func) */
908: #define NDEATHMAX 8 /**< Maximum number of dead states (for func) */
909: #define NCOVMAX 20 /**< Maximum number of covariates, including generated covariates V1*V2 */
1.197 brouard 910: #define codtabm(h,k) (1 & (h-1) >> (k-1))+1
1.211 brouard 911: /*#define decodtabm(h,k,cptcoveff)= (h <= (1<<cptcoveff)?(((h-1) >> (k-1)) & 1) +1 : -1)*/
912: #define decodtabm(h,k,cptcoveff) (((h-1) >> (k-1)) & 1) +1
1.126 brouard 913: #define MAXN 20000
1.144 brouard 914: #define YEARM 12. /**< Number of months per year */
1.218 brouard 915: /* #define AGESUP 130 */
916: #define AGESUP 150
917: #define AGEMARGE 25 /* Marge for agemin and agemax for(iage=agemin-AGEMARGE; iage <= agemax+3+AGEMARGE; iage++) */
1.126 brouard 918: #define AGEBASE 40
1.194 brouard 919: #define AGEOVERFLOW 1.e20
1.164 brouard 920: #define AGEGOMP 10 /**< Minimal age for Gompertz adjustment */
1.157 brouard 921: #ifdef _WIN32
922: #define DIRSEPARATOR '\\'
923: #define CHARSEPARATOR "\\"
924: #define ODIRSEPARATOR '/'
925: #else
1.126 brouard 926: #define DIRSEPARATOR '/'
927: #define CHARSEPARATOR "/"
928: #define ODIRSEPARATOR '\\'
929: #endif
930:
1.243 ! brouard 931: /* $Id: imach.c,v 1.242 2016/08/30 15:01:20 brouard Exp $ */
1.126 brouard 932: /* $State: Exp $ */
1.196 brouard 933: #include "version.h"
934: char version[]=__IMACH_VERSION__;
1.224 brouard 935: 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";
1.243 ! brouard 936: char fullversion[]="$Revision: 1.242 $ $Date: 2016/08/30 15:01:20 $";
1.126 brouard 937: char strstart[80];
938: char optionfilext[10], optionfilefiname[FILENAMELENGTH];
1.130 brouard 939: int erreur=0, nberr=0, nbwarn=0; /* Error number, number of errors number of warnings */
1.187 brouard 940: int nagesqr=0, nforce=0; /* nagesqr=1 if model is including age*age, number of forces */
1.145 brouard 941: /* Number of covariates model=V2+V1+ V3*age+V2*V4 */
942: int cptcovn=0; /**< cptcovn number of covariates added in the model (excepting constant and age and age*product) */
943: int cptcovt=0; /**< cptcovt number of covariates added in the model (excepting constant and age) */
1.225 brouard 944: int cptcovs=0; /**< cptcovs number of simple covariates in the model V2+V1 =2 */
945: int cptcovsnq=0; /**< cptcovsnq number of simple covariates in the model but non quantitative V2+V1 =2 */
1.145 brouard 946: int cptcovage=0; /**< Number of covariates with age: V3*age only =1 */
947: int cptcovprodnoage=0; /**< Number of covariate products without age */
948: int cptcoveff=0; /* Total number of covariates to vary for printing results */
1.233 brouard 949: int ncovf=0; /* Total number of effective fixed covariates (dummy or quantitative) in the model */
950: int ncovv=0; /* Total number of effective (wave) varying covariates (dummy or quantitative) in the model */
1.232 brouard 951: int ncova=0; /* Total number of effective (wave and stepm) varying with age covariates (dummy of quantitative) in the model */
1.234 brouard 952: int nsd=0; /**< Total number of single dummy variables (output) */
953: int nsq=0; /**< Total number of single quantitative variables (output) */
1.232 brouard 954: int ncoveff=0; /* Total number of effective fixed dummy covariates in the model */
1.225 brouard 955: int nqfveff=0; /**< nqfveff Number of Quantitative Fixed Variables Effective */
1.224 brouard 956: int ntveff=0; /**< ntveff number of effective time varying variables */
957: int nqtveff=0; /**< ntqveff number of effective time varying quantitative variables */
1.145 brouard 958: int cptcov=0; /* Working variable */
1.218 brouard 959: int ncovcombmax=NCOVMAX; /* Maximum calculated number of covariate combination = pow(2, cptcoveff) */
1.126 brouard 960: int npar=NPARMAX;
961: int nlstate=2; /* Number of live states */
962: int ndeath=1; /* Number of dead states */
1.130 brouard 963: int ncovmodel=0, ncovcol=0; /* Total number of covariables including constant a12*1 +b12*x ncovmodel=2 */
1.223 brouard 964: int nqv=0, ntv=0, nqtv=0; /* Total number of quantitative variables, time variable (dummy), quantitative and time variable */
1.126 brouard 965: int popbased=0;
966:
967: int *wav; /* Number of waves for this individuual 0 is possible */
1.130 brouard 968: int maxwav=0; /* Maxim number of waves */
969: int jmin=0, jmax=0; /* min, max spacing between 2 waves */
970: int ijmin=0, ijmax=0; /* Individuals having jmin and jmax */
971: int gipmx=0, gsw=0; /* Global variables on the number of contributions
1.126 brouard 972: to the likelihood and the sum of weights (done by funcone)*/
1.130 brouard 973: int mle=1, weightopt=0;
1.126 brouard 974: int **mw; /* mw[mi][i] is number of the mi wave for this individual */
975: int **dh; /* dh[mi][i] is number of steps between mi,mi+1 for this individual */
976: int **bh; /* bh[mi][i] is the bias (+ or -) for this individual if the delay between
977: * wave mi and wave mi+1 is not an exact multiple of stepm. */
1.162 brouard 978: int countcallfunc=0; /* Count the number of calls to func */
1.230 brouard 979: int selected(int kvar); /* Is covariate kvar selected for printing results */
980:
1.130 brouard 981: double jmean=1; /* Mean space between 2 waves */
1.145 brouard 982: double **matprod2(); /* test */
1.126 brouard 983: double **oldm, **newm, **savm; /* Working pointers to matrices */
984: double **oldms, **newms, **savms; /* Fixed working pointers to matrices */
1.218 brouard 985: double **ddnewms, **ddoldms, **ddsavms; /* for freeing later */
986:
1.136 brouard 987: /*FILE *fic ; */ /* Used in readdata only */
1.217 brouard 988: FILE *ficpar, *ficparo,*ficres, *ficresp, *ficresphtm, *ficresphtmfr, *ficrespl, *ficresplb,*ficrespij, *ficrespijb, *ficrest,*ficresf, *ficresfb,*ficrespop;
1.126 brouard 989: FILE *ficlog, *ficrespow;
1.130 brouard 990: int globpr=0; /* Global variable for printing or not */
1.126 brouard 991: double fretone; /* Only one call to likelihood */
1.130 brouard 992: long ipmx=0; /* Number of contributions */
1.126 brouard 993: double sw; /* Sum of weights */
994: char filerespow[FILENAMELENGTH];
995: char fileresilk[FILENAMELENGTH]; /* File of individual contributions to the likelihood */
996: FILE *ficresilk;
997: FILE *ficgp,*ficresprob,*ficpop, *ficresprobcov, *ficresprobcor;
998: FILE *ficresprobmorprev;
999: FILE *fichtm, *fichtmcov; /* Html File */
1000: FILE *ficreseij;
1001: char filerese[FILENAMELENGTH];
1002: FILE *ficresstdeij;
1003: char fileresstde[FILENAMELENGTH];
1004: FILE *ficrescveij;
1005: char filerescve[FILENAMELENGTH];
1006: FILE *ficresvij;
1007: char fileresv[FILENAMELENGTH];
1008: FILE *ficresvpl;
1009: char fileresvpl[FILENAMELENGTH];
1010: char title[MAXLINE];
1.234 brouard 1011: char model[MAXLINE]; /**< The model line */
1.217 brouard 1012: char optionfile[FILENAMELENGTH], datafile[FILENAMELENGTH], filerespl[FILENAMELENGTH], fileresplb[FILENAMELENGTH];
1.126 brouard 1013: char plotcmd[FILENAMELENGTH], pplotcmd[FILENAMELENGTH];
1014: char tmpout[FILENAMELENGTH], tmpout2[FILENAMELENGTH];
1015: char command[FILENAMELENGTH];
1016: int outcmd=0;
1017:
1.217 brouard 1018: char fileres[FILENAMELENGTH], filerespij[FILENAMELENGTH], filerespijb[FILENAMELENGTH], filereso[FILENAMELENGTH], rfileres[FILENAMELENGTH];
1.202 brouard 1019: char fileresu[FILENAMELENGTH]; /* fileres without r in front */
1.126 brouard 1020: char filelog[FILENAMELENGTH]; /* Log file */
1021: char filerest[FILENAMELENGTH];
1022: char fileregp[FILENAMELENGTH];
1023: char popfile[FILENAMELENGTH];
1024:
1025: char optionfilegnuplot[FILENAMELENGTH], optionfilehtm[FILENAMELENGTH], optionfilehtmcov[FILENAMELENGTH] ;
1026:
1.157 brouard 1027: /* struct timeval start_time, end_time, curr_time, last_time, forecast_time; */
1028: /* struct timezone tzp; */
1029: /* extern int gettimeofday(); */
1030: struct tm tml, *gmtime(), *localtime();
1031:
1032: extern time_t time();
1033:
1034: struct tm start_time, end_time, curr_time, last_time, forecast_time;
1035: time_t rstart_time, rend_time, rcurr_time, rlast_time, rforecast_time; /* raw time */
1036: struct tm tm;
1037:
1.126 brouard 1038: char strcurr[80], strfor[80];
1039:
1040: char *endptr;
1041: long lval;
1042: double dval;
1043:
1044: #define NR_END 1
1045: #define FREE_ARG char*
1046: #define FTOL 1.0e-10
1047:
1048: #define NRANSI
1.240 brouard 1049: #define ITMAX 200
1050: #define ITPOWMAX 20 /* This is now multiplied by the number of parameters */
1.126 brouard 1051:
1052: #define TOL 2.0e-4
1053:
1054: #define CGOLD 0.3819660
1055: #define ZEPS 1.0e-10
1056: #define SHFT(a,b,c,d) (a)=(b);(b)=(c);(c)=(d);
1057:
1058: #define GOLD 1.618034
1059: #define GLIMIT 100.0
1060: #define TINY 1.0e-20
1061:
1062: static double maxarg1,maxarg2;
1063: #define FMAX(a,b) (maxarg1=(a),maxarg2=(b),(maxarg1)>(maxarg2)? (maxarg1):(maxarg2))
1064: #define FMIN(a,b) (maxarg1=(a),maxarg2=(b),(maxarg1)<(maxarg2)? (maxarg1):(maxarg2))
1065:
1066: #define SIGN(a,b) ((b)>0.0 ? fabs(a) : -fabs(a))
1067: #define rint(a) floor(a+0.5)
1.166 brouard 1068: /* http://www.thphys.uni-heidelberg.de/~robbers/cmbeasy/doc/html/myutils_8h-source.html */
1.183 brouard 1069: #define mytinydouble 1.0e-16
1.166 brouard 1070: /* #define DEQUAL(a,b) (fabs((a)-(b))<mytinydouble) */
1071: /* http://www.thphys.uni-heidelberg.de/~robbers/cmbeasy/doc/html/mynrutils_8h-source.html */
1072: /* static double dsqrarg; */
1073: /* #define DSQR(a) (DEQUAL((dsqrarg=(a)),0.0) ? 0.0 : dsqrarg*dsqrarg) */
1.126 brouard 1074: static double sqrarg;
1075: #define SQR(a) ((sqrarg=(a)) == 0.0 ? 0.0 :sqrarg*sqrarg)
1076: #define SWAP(a,b) {temp=(a);(a)=(b);(b)=temp;}
1077: int agegomp= AGEGOMP;
1078:
1079: int imx;
1080: int stepm=1;
1081: /* Stepm, step in month: minimum step interpolation*/
1082:
1083: int estepm;
1084: /* Estepm, step in month to interpolate survival function in order to approximate Life Expectancy*/
1085:
1086: int m,nb;
1087: long *num;
1.197 brouard 1088: int firstpass=0, lastpass=4,*cod, *cens;
1.192 brouard 1089: int *ncodemax; /* ncodemax[j]= Number of modalities of the j th
1090: covariate for which somebody answered excluding
1091: undefined. Usually 2: 0 and 1. */
1092: int *ncodemaxwundef; /* ncodemax[j]= Number of modalities of the j th
1093: covariate for which somebody answered including
1094: undefined. Usually 3: -1, 0 and 1. */
1.126 brouard 1095: double **agev,*moisnais, *annais, *moisdc, *andc,**mint, **anint;
1.218 brouard 1096: double **pmmij, ***probs; /* Global pointer */
1.219 brouard 1097: double ***mobaverage, ***mobaverages; /* New global variable */
1.126 brouard 1098: double *ageexmed,*agecens;
1099: double dateintmean=0;
1100:
1101: double *weight;
1102: int **s; /* Status */
1.141 brouard 1103: double *agedc;
1.145 brouard 1104: double **covar; /**< covar[j,i], value of jth covariate for individual i,
1.141 brouard 1105: * covar=matrix(0,NCOVMAX,1,n);
1.187 brouard 1106: * cov[Tage[kk]+2]=covar[Tvar[Tage[kk]]][i]*age; */
1.225 brouard 1107: double **coqvar; /* Fixed quantitative covariate iqv */
1108: double ***cotvar; /* Time varying covariate itv */
1109: double ***cotqvar; /* Time varying quantitative covariate itqv */
1.141 brouard 1110: double idx;
1111: int **nbcode, *Tvar; /**< model=V2 => Tvar[1]= 2 */
1.234 brouard 1112: /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1113: /*k 1 2 3 4 5 6 7 8 9 */
1114: /*Tvar[k]= 5 4 3 6 5 2 7 1 1 */
1115: /* Tndvar[k] 1 2 3 4 5 */
1116: /*TDvar 4 3 6 7 1 */ /* For outputs only; combination of dummies fixed or varying */
1117: /* Tns[k] 1 2 2 4 5 */ /* Number of single cova */
1118: /* TvarsD[k] 1 2 3 */ /* Number of single dummy cova */
1119: /* TvarsDind 2 3 9 */ /* position K of single dummy cova */
1120: /* TvarsQ[k] 1 2 */ /* Number of single quantitative cova */
1121: /* TvarsQind 1 6 */ /* position K of single quantitative cova */
1122: /* Tprod[i]=k 4 7 */
1123: /* Tage[i]=k 5 8 */
1124: /* */
1125: /* Type */
1126: /* V 1 2 3 4 5 */
1127: /* F F V V V */
1128: /* D Q D D Q */
1129: /* */
1130: int *TvarsD;
1131: int *TvarsDind;
1132: int *TvarsQ;
1133: int *TvarsQind;
1134:
1.235 brouard 1135: #define MAXRESULTLINES 10
1136: int nresult=0;
1137: int TKresult[MAXRESULTLINES];
1.237 brouard 1138: int Tresult[MAXRESULTLINES][NCOVMAX];/* For dummy variable , value (output) */
1139: int Tinvresult[MAXRESULTLINES][NCOVMAX];/* For dummy variable , value (output) */
1.235 brouard 1140: int Tvresult[MAXRESULTLINES][NCOVMAX]; /* For dummy variable , variable # (output) */
1141: double Tqresult[MAXRESULTLINES][NCOVMAX]; /* For quantitative variable , value (output) */
1.237 brouard 1142: double Tqinvresult[MAXRESULTLINES][NCOVMAX]; /* For quantitative variable , value (output) */
1.235 brouard 1143: int Tvqresult[MAXRESULTLINES][NCOVMAX]; /* For quantitative variable , variable # (output) */
1144:
1.234 brouard 1145: /* 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 1146: 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 */
1147: 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 */
1148: 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 */
1149: int *TvarVind; /**< TvarVind[1]=1, TvarVind[2]=2 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1150: 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 */
1151: 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 1152: int *TvarFD; /**< TvarFD[1]=V1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1153: int *TvarFDind; /* TvarFDind[1]=9 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1154: int *TvarFQ; /* TvarFQ[1]=V2 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1155: int *TvarFQind; /* TvarFQind[1]=6 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1156: int *TvarVD; /* TvarVD[1]=V5 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1157: int *TvarVDind; /* TvarVDind[1]=1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1158: 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 */
1159: 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 */
1160:
1.230 brouard 1161: int *Tvarsel; /**< Selected covariates for output */
1162: double *Tvalsel; /**< Selected modality value of covariate for output */
1.226 brouard 1163: int *Typevar; /**< 0 for simple covariate (dummy, quantitative, fixed or varying), 1 for age product, 2 for product */
1.227 brouard 1164: int *Fixed; /** Fixed[k] 0=fixed, 1 varying, 2 fixed with age product, 3 varying with age product */
1165: 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 1166: int *DummyV; /** Dummy[v] 0=dummy (0 1), 1 quantitative */
1167: int *FixedV; /** FixedV[v] 0 fixed, 1 varying */
1.197 brouard 1168: int *Tage;
1.227 brouard 1169: int anyvaryingduminmodel=0; /**< Any varying dummy in Model=1 yes, 0 no, to avoid a loop on waves in freq */
1.228 brouard 1170: 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 1171: 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*/
1172: 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 1173: int *Ndum; /** Freq of modality (tricode */
1.200 brouard 1174: /* int **codtab;*/ /**< codtab=imatrix(1,100,1,10); */
1.227 brouard 1175: int **Tvard;
1176: int *Tprod;/**< Gives the k position of the k1 product */
1.238 brouard 1177: /* Tprod[k1=1]=3(=V1*V4) for V2+V1+V1*V4+age*V3 */
1.227 brouard 1178: int *Tposprod; /**< Gives the k1 product from the k position */
1.238 brouard 1179: /* if V2+V1+V1*V4+age*V3+V3*V2 TProd[k1=2]=5 (V3*V2) */
1180: /* Tposprod[k]=k1 , Tposprod[3]=1, Tposprod[5(V3*V2)]=2 (2nd product without age) */
1.227 brouard 1181: int cptcovprod, *Tvaraff, *invalidvarcomb;
1.126 brouard 1182: double *lsurv, *lpop, *tpop;
1183:
1.231 brouard 1184: #define FD 1; /* Fixed dummy covariate */
1185: #define FQ 2; /* Fixed quantitative covariate */
1186: #define FP 3; /* Fixed product covariate */
1187: #define FPDD 7; /* Fixed product dummy*dummy covariate */
1188: #define FPDQ 8; /* Fixed product dummy*quantitative covariate */
1189: #define FPQQ 9; /* Fixed product quantitative*quantitative covariate */
1190: #define VD 10; /* Varying dummy covariate */
1191: #define VQ 11; /* Varying quantitative covariate */
1192: #define VP 12; /* Varying product covariate */
1193: #define VPDD 13; /* Varying product dummy*dummy covariate */
1194: #define VPDQ 14; /* Varying product dummy*quantitative covariate */
1195: #define VPQQ 15; /* Varying product quantitative*quantitative covariate */
1196: #define APFD 16; /* Age product * fixed dummy covariate */
1197: #define APFQ 17; /* Age product * fixed quantitative covariate */
1198: #define APVD 18; /* Age product * varying dummy covariate */
1199: #define APVQ 19; /* Age product * varying quantitative covariate */
1200:
1201: #define FTYPE 1; /* Fixed covariate */
1202: #define VTYPE 2; /* Varying covariate (loop in wave) */
1203: #define ATYPE 2; /* Age product covariate (loop in dh within wave)*/
1204:
1205: struct kmodel{
1206: int maintype; /* main type */
1207: int subtype; /* subtype */
1208: };
1209: struct kmodel modell[NCOVMAX];
1210:
1.143 brouard 1211: double ftol=FTOL; /**< Tolerance for computing Max Likelihood */
1212: double ftolhess; /**< Tolerance for computing hessian */
1.126 brouard 1213:
1214: /**************** split *************************/
1215: static int split( char *path, char *dirc, char *name, char *ext, char *finame )
1216: {
1217: /* From a file name with (full) path (either Unix or Windows) we extract the directory (dirc)
1218: the name of the file (name), its extension only (ext) and its first part of the name (finame)
1219: */
1220: char *ss; /* pointer */
1.186 brouard 1221: int l1=0, l2=0; /* length counters */
1.126 brouard 1222:
1223: l1 = strlen(path ); /* length of path */
1224: if ( l1 == 0 ) return( GLOCK_ERROR_NOPATH );
1225: ss= strrchr( path, DIRSEPARATOR ); /* find last / */
1226: if ( ss == NULL ) { /* no directory, so determine current directory */
1227: strcpy( name, path ); /* we got the fullname name because no directory */
1228: /*if(strrchr(path, ODIRSEPARATOR )==NULL)
1229: printf("Warning you should use %s as a separator\n",DIRSEPARATOR);*/
1230: /* get current working directory */
1231: /* extern char* getcwd ( char *buf , int len);*/
1.184 brouard 1232: #ifdef WIN32
1233: if (_getcwd( dirc, FILENAME_MAX ) == NULL ) {
1234: #else
1235: if (getcwd(dirc, FILENAME_MAX) == NULL) {
1236: #endif
1.126 brouard 1237: return( GLOCK_ERROR_GETCWD );
1238: }
1239: /* got dirc from getcwd*/
1240: printf(" DIRC = %s \n",dirc);
1.205 brouard 1241: } else { /* strip directory from path */
1.126 brouard 1242: ss++; /* after this, the filename */
1243: l2 = strlen( ss ); /* length of filename */
1244: if ( l2 == 0 ) return( GLOCK_ERROR_NOPATH );
1245: strcpy( name, ss ); /* save file name */
1246: strncpy( dirc, path, l1 - l2 ); /* now the directory */
1.186 brouard 1247: dirc[l1-l2] = '\0'; /* add zero */
1.126 brouard 1248: printf(" DIRC2 = %s \n",dirc);
1249: }
1250: /* We add a separator at the end of dirc if not exists */
1251: l1 = strlen( dirc ); /* length of directory */
1252: if( dirc[l1-1] != DIRSEPARATOR ){
1253: dirc[l1] = DIRSEPARATOR;
1254: dirc[l1+1] = 0;
1255: printf(" DIRC3 = %s \n",dirc);
1256: }
1257: ss = strrchr( name, '.' ); /* find last / */
1258: if (ss >0){
1259: ss++;
1260: strcpy(ext,ss); /* save extension */
1261: l1= strlen( name);
1262: l2= strlen(ss)+1;
1263: strncpy( finame, name, l1-l2);
1264: finame[l1-l2]= 0;
1265: }
1266:
1267: return( 0 ); /* we're done */
1268: }
1269:
1270:
1271: /******************************************/
1272:
1273: void replace_back_to_slash(char *s, char*t)
1274: {
1275: int i;
1276: int lg=0;
1277: i=0;
1278: lg=strlen(t);
1279: for(i=0; i<= lg; i++) {
1280: (s[i] = t[i]);
1281: if (t[i]== '\\') s[i]='/';
1282: }
1283: }
1284:
1.132 brouard 1285: char *trimbb(char *out, char *in)
1.137 brouard 1286: { /* Trim multiple blanks in line but keeps first blanks if line starts with blanks */
1.132 brouard 1287: char *s;
1288: s=out;
1289: while (*in != '\0'){
1.137 brouard 1290: while( *in == ' ' && *(in+1) == ' '){ /* && *(in+1) != '\0'){*/
1.132 brouard 1291: in++;
1292: }
1293: *out++ = *in++;
1294: }
1295: *out='\0';
1296: return s;
1297: }
1298:
1.187 brouard 1299: /* char *substrchaine(char *out, char *in, char *chain) */
1300: /* { */
1301: /* /\* Substract chain 'chain' from 'in', return and output 'out' *\/ */
1302: /* char *s, *t; */
1303: /* t=in;s=out; */
1304: /* while ((*in != *chain) && (*in != '\0')){ */
1305: /* *out++ = *in++; */
1306: /* } */
1307:
1308: /* /\* *in matches *chain *\/ */
1309: /* while ((*in++ == *chain++) && (*in != '\0')){ */
1310: /* printf("*in = %c, *out= %c *chain= %c \n", *in, *out, *chain); */
1311: /* } */
1312: /* in--; chain--; */
1313: /* while ( (*in != '\0')){ */
1314: /* printf("Bef *in = %c, *out= %c *chain= %c \n", *in, *out, *chain); */
1315: /* *out++ = *in++; */
1316: /* printf("Aft *in = %c, *out= %c *chain= %c \n", *in, *out, *chain); */
1317: /* } */
1318: /* *out='\0'; */
1319: /* out=s; */
1320: /* return out; */
1321: /* } */
1322: char *substrchaine(char *out, char *in, char *chain)
1323: {
1324: /* Substract chain 'chain' from 'in', return and output 'out' */
1325: /* in="V1+V1*age+age*age+V2", chain="age*age" */
1326:
1327: char *strloc;
1328:
1329: strcpy (out, in);
1330: strloc = strstr(out, chain); /* strloc points to out at age*age+V2 */
1331: printf("Bef strloc=%s chain=%s out=%s \n", strloc, chain, out);
1332: if(strloc != NULL){
1333: /* will affect out */ /* strloc+strlenc(chain)=+V2 */ /* Will also work in Unicode */
1334: memmove(strloc,strloc+strlen(chain), strlen(strloc+strlen(chain))+1);
1335: /* strcpy (strloc, strloc +strlen(chain));*/
1336: }
1337: printf("Aft strloc=%s chain=%s in=%s out=%s \n", strloc, chain, in, out);
1338: return out;
1339: }
1340:
1341:
1.145 brouard 1342: char *cutl(char *blocc, char *alocc, char *in, char occ)
1343: {
1.187 brouard 1344: /* cuts string in into blocc and alocc where blocc ends before FIRST occurence of char 'occ'
1.145 brouard 1345: and alocc starts after first occurence of char 'occ' : ex cutv(blocc,alocc,"abcdef2ghi2j",'2')
1.187 brouard 1346: gives blocc="abcdef" and alocc="ghi2j".
1.145 brouard 1347: If occ is not found blocc is null and alocc is equal to in. Returns blocc
1348: */
1.160 brouard 1349: char *s, *t;
1.145 brouard 1350: t=in;s=in;
1351: while ((*in != occ) && (*in != '\0')){
1352: *alocc++ = *in++;
1353: }
1354: if( *in == occ){
1355: *(alocc)='\0';
1356: s=++in;
1357: }
1358:
1359: if (s == t) {/* occ not found */
1360: *(alocc-(in-s))='\0';
1361: in=s;
1362: }
1363: while ( *in != '\0'){
1364: *blocc++ = *in++;
1365: }
1366:
1367: *blocc='\0';
1368: return t;
1369: }
1.137 brouard 1370: char *cutv(char *blocc, char *alocc, char *in, char occ)
1371: {
1.187 brouard 1372: /* cuts string in into blocc and alocc where blocc ends before LAST occurence of char 'occ'
1.137 brouard 1373: and alocc starts after last occurence of char 'occ' : ex cutv(blocc,alocc,"abcdef2ghi2j",'2')
1374: gives blocc="abcdef2ghi" and alocc="j".
1375: If occ is not found blocc is null and alocc is equal to in. Returns alocc
1376: */
1377: char *s, *t;
1378: t=in;s=in;
1379: while (*in != '\0'){
1380: while( *in == occ){
1381: *blocc++ = *in++;
1382: s=in;
1383: }
1384: *blocc++ = *in++;
1385: }
1386: if (s == t) /* occ not found */
1387: *(blocc-(in-s))='\0';
1388: else
1389: *(blocc-(in-s)-1)='\0';
1390: in=s;
1391: while ( *in != '\0'){
1392: *alocc++ = *in++;
1393: }
1394:
1395: *alocc='\0';
1396: return s;
1397: }
1398:
1.126 brouard 1399: int nbocc(char *s, char occ)
1400: {
1401: int i,j=0;
1402: int lg=20;
1403: i=0;
1404: lg=strlen(s);
1405: for(i=0; i<= lg; i++) {
1.234 brouard 1406: if (s[i] == occ ) j++;
1.126 brouard 1407: }
1408: return j;
1409: }
1410:
1.137 brouard 1411: /* void cutv(char *u,char *v, char*t, char occ) */
1412: /* { */
1413: /* /\* cuts string t into u and v where u ends before last occurence of char 'occ' */
1414: /* and v starts after last occurence of char 'occ' : ex cutv(u,v,"abcdef2ghi2j",'2') */
1415: /* gives u="abcdef2ghi" and v="j" *\/ */
1416: /* int i,lg,j,p=0; */
1417: /* i=0; */
1418: /* lg=strlen(t); */
1419: /* for(j=0; j<=lg-1; j++) { */
1420: /* if((t[j]!= occ) && (t[j+1]== occ)) p=j+1; */
1421: /* } */
1.126 brouard 1422:
1.137 brouard 1423: /* for(j=0; j<p; j++) { */
1424: /* (u[j] = t[j]); */
1425: /* } */
1426: /* u[p]='\0'; */
1.126 brouard 1427:
1.137 brouard 1428: /* for(j=0; j<= lg; j++) { */
1429: /* if (j>=(p+1))(v[j-p-1] = t[j]); */
1430: /* } */
1431: /* } */
1.126 brouard 1432:
1.160 brouard 1433: #ifdef _WIN32
1434: char * strsep(char **pp, const char *delim)
1435: {
1436: char *p, *q;
1437:
1438: if ((p = *pp) == NULL)
1439: return 0;
1440: if ((q = strpbrk (p, delim)) != NULL)
1441: {
1442: *pp = q + 1;
1443: *q = '\0';
1444: }
1445: else
1446: *pp = 0;
1447: return p;
1448: }
1449: #endif
1450:
1.126 brouard 1451: /********************** nrerror ********************/
1452:
1453: void nrerror(char error_text[])
1454: {
1455: fprintf(stderr,"ERREUR ...\n");
1456: fprintf(stderr,"%s\n",error_text);
1457: exit(EXIT_FAILURE);
1458: }
1459: /*********************** vector *******************/
1460: double *vector(int nl, int nh)
1461: {
1462: double *v;
1463: v=(double *) malloc((size_t)((nh-nl+1+NR_END)*sizeof(double)));
1464: if (!v) nrerror("allocation failure in vector");
1465: return v-nl+NR_END;
1466: }
1467:
1468: /************************ free vector ******************/
1469: void free_vector(double*v, int nl, int nh)
1470: {
1471: free((FREE_ARG)(v+nl-NR_END));
1472: }
1473:
1474: /************************ivector *******************************/
1475: int *ivector(long nl,long nh)
1476: {
1477: int *v;
1478: v=(int *) malloc((size_t)((nh-nl+1+NR_END)*sizeof(int)));
1479: if (!v) nrerror("allocation failure in ivector");
1480: return v-nl+NR_END;
1481: }
1482:
1483: /******************free ivector **************************/
1484: void free_ivector(int *v, long nl, long nh)
1485: {
1486: free((FREE_ARG)(v+nl-NR_END));
1487: }
1488:
1489: /************************lvector *******************************/
1490: long *lvector(long nl,long nh)
1491: {
1492: long *v;
1493: v=(long *) malloc((size_t)((nh-nl+1+NR_END)*sizeof(long)));
1494: if (!v) nrerror("allocation failure in ivector");
1495: return v-nl+NR_END;
1496: }
1497:
1498: /******************free lvector **************************/
1499: void free_lvector(long *v, long nl, long nh)
1500: {
1501: free((FREE_ARG)(v+nl-NR_END));
1502: }
1503:
1504: /******************* imatrix *******************************/
1505: int **imatrix(long nrl, long nrh, long ncl, long nch)
1506: /* allocate a int matrix with subscript range m[nrl..nrh][ncl..nch] */
1507: {
1508: long i, nrow=nrh-nrl+1,ncol=nch-ncl+1;
1509: int **m;
1510:
1511: /* allocate pointers to rows */
1512: m=(int **) malloc((size_t)((nrow+NR_END)*sizeof(int*)));
1513: if (!m) nrerror("allocation failure 1 in matrix()");
1514: m += NR_END;
1515: m -= nrl;
1516:
1517:
1518: /* allocate rows and set pointers to them */
1519: m[nrl]=(int *) malloc((size_t)((nrow*ncol+NR_END)*sizeof(int)));
1520: if (!m[nrl]) nrerror("allocation failure 2 in matrix()");
1521: m[nrl] += NR_END;
1522: m[nrl] -= ncl;
1523:
1524: for(i=nrl+1;i<=nrh;i++) m[i]=m[i-1]+ncol;
1525:
1526: /* return pointer to array of pointers to rows */
1527: return m;
1528: }
1529:
1530: /****************** free_imatrix *************************/
1531: void free_imatrix(m,nrl,nrh,ncl,nch)
1532: int **m;
1533: long nch,ncl,nrh,nrl;
1534: /* free an int matrix allocated by imatrix() */
1535: {
1536: free((FREE_ARG) (m[nrl]+ncl-NR_END));
1537: free((FREE_ARG) (m+nrl-NR_END));
1538: }
1539:
1540: /******************* matrix *******************************/
1541: double **matrix(long nrl, long nrh, long ncl, long nch)
1542: {
1543: long i, nrow=nrh-nrl+1, ncol=nch-ncl+1;
1544: double **m;
1545:
1546: m=(double **) malloc((size_t)((nrow+NR_END)*sizeof(double*)));
1547: if (!m) nrerror("allocation failure 1 in matrix()");
1548: m += NR_END;
1549: m -= nrl;
1550:
1551: m[nrl]=(double *) malloc((size_t)((nrow*ncol+NR_END)*sizeof(double)));
1552: if (!m[nrl]) nrerror("allocation failure 2 in matrix()");
1553: m[nrl] += NR_END;
1554: m[nrl] -= ncl;
1555:
1556: for (i=nrl+1; i<=nrh; i++) m[i]=m[i-1]+ncol;
1557: return m;
1.145 brouard 1558: /* print *(*(m+1)+70) or print m[1][70]; print m+1 or print &(m[1]) or &(m[1][0])
1559: m[i] = address of ith row of the table. &(m[i]) is its value which is another adress
1560: that of m[i][0]. In order to get the value p m[i][0] but it is unitialized.
1.126 brouard 1561: */
1562: }
1563:
1564: /*************************free matrix ************************/
1565: void free_matrix(double **m, long nrl, long nrh, long ncl, long nch)
1566: {
1567: free((FREE_ARG)(m[nrl]+ncl-NR_END));
1568: free((FREE_ARG)(m+nrl-NR_END));
1569: }
1570:
1571: /******************* ma3x *******************************/
1572: double ***ma3x(long nrl, long nrh, long ncl, long nch, long nll, long nlh)
1573: {
1574: long i, j, nrow=nrh-nrl+1, ncol=nch-ncl+1, nlay=nlh-nll+1;
1575: double ***m;
1576:
1577: m=(double ***) malloc((size_t)((nrow+NR_END)*sizeof(double*)));
1578: if (!m) nrerror("allocation failure 1 in matrix()");
1579: m += NR_END;
1580: m -= nrl;
1581:
1582: m[nrl]=(double **) malloc((size_t)((nrow*ncol+NR_END)*sizeof(double)));
1583: if (!m[nrl]) nrerror("allocation failure 2 in matrix()");
1584: m[nrl] += NR_END;
1585: m[nrl] -= ncl;
1586:
1587: for (i=nrl+1; i<=nrh; i++) m[i]=m[i-1]+ncol;
1588:
1589: m[nrl][ncl]=(double *) malloc((size_t)((nrow*ncol*nlay+NR_END)*sizeof(double)));
1590: if (!m[nrl][ncl]) nrerror("allocation failure 3 in matrix()");
1591: m[nrl][ncl] += NR_END;
1592: m[nrl][ncl] -= nll;
1593: for (j=ncl+1; j<=nch; j++)
1594: m[nrl][j]=m[nrl][j-1]+nlay;
1595:
1596: for (i=nrl+1; i<=nrh; i++) {
1597: m[i][ncl]=m[i-1l][ncl]+ncol*nlay;
1598: for (j=ncl+1; j<=nch; j++)
1599: m[i][j]=m[i][j-1]+nlay;
1600: }
1601: return m;
1602: /* gdb: p *(m+1) <=> p m[1] and p (m+1) <=> p (m+1) <=> p &(m[1])
1603: &(m[i][j][k]) <=> *((*(m+i) + j)+k)
1604: */
1605: }
1606:
1607: /*************************free ma3x ************************/
1608: void free_ma3x(double ***m, long nrl, long nrh, long ncl, long nch,long nll, long nlh)
1609: {
1610: free((FREE_ARG)(m[nrl][ncl]+ nll-NR_END));
1611: free((FREE_ARG)(m[nrl]+ncl-NR_END));
1612: free((FREE_ARG)(m+nrl-NR_END));
1613: }
1614:
1615: /*************** function subdirf ***********/
1616: char *subdirf(char fileres[])
1617: {
1618: /* Caution optionfilefiname is hidden */
1619: strcpy(tmpout,optionfilefiname);
1620: strcat(tmpout,"/"); /* Add to the right */
1621: strcat(tmpout,fileres);
1622: return tmpout;
1623: }
1624:
1625: /*************** function subdirf2 ***********/
1626: char *subdirf2(char fileres[], char *preop)
1627: {
1628:
1629: /* Caution optionfilefiname is hidden */
1630: strcpy(tmpout,optionfilefiname);
1631: strcat(tmpout,"/");
1632: strcat(tmpout,preop);
1633: strcat(tmpout,fileres);
1634: return tmpout;
1635: }
1636:
1637: /*************** function subdirf3 ***********/
1638: char *subdirf3(char fileres[], char *preop, char *preop2)
1639: {
1640:
1641: /* Caution optionfilefiname is hidden */
1642: strcpy(tmpout,optionfilefiname);
1643: strcat(tmpout,"/");
1644: strcat(tmpout,preop);
1645: strcat(tmpout,preop2);
1646: strcat(tmpout,fileres);
1647: return tmpout;
1648: }
1.213 brouard 1649:
1650: /*************** function subdirfext ***********/
1651: char *subdirfext(char fileres[], char *preop, char *postop)
1652: {
1653:
1654: strcpy(tmpout,preop);
1655: strcat(tmpout,fileres);
1656: strcat(tmpout,postop);
1657: return tmpout;
1658: }
1.126 brouard 1659:
1.213 brouard 1660: /*************** function subdirfext3 ***********/
1661: char *subdirfext3(char fileres[], char *preop, char *postop)
1662: {
1663:
1664: /* Caution optionfilefiname is hidden */
1665: strcpy(tmpout,optionfilefiname);
1666: strcat(tmpout,"/");
1667: strcat(tmpout,preop);
1668: strcat(tmpout,fileres);
1669: strcat(tmpout,postop);
1670: return tmpout;
1671: }
1672:
1.162 brouard 1673: char *asc_diff_time(long time_sec, char ascdiff[])
1674: {
1675: long sec_left, days, hours, minutes;
1676: days = (time_sec) / (60*60*24);
1677: sec_left = (time_sec) % (60*60*24);
1678: hours = (sec_left) / (60*60) ;
1679: sec_left = (sec_left) %(60*60);
1680: minutes = (sec_left) /60;
1681: sec_left = (sec_left) % (60);
1682: sprintf(ascdiff,"%ld day(s) %ld hour(s) %ld minute(s) %ld second(s)",days, hours, minutes, sec_left);
1683: return ascdiff;
1684: }
1685:
1.126 brouard 1686: /***************** f1dim *************************/
1687: extern int ncom;
1688: extern double *pcom,*xicom;
1689: extern double (*nrfunc)(double []);
1690:
1691: double f1dim(double x)
1692: {
1693: int j;
1694: double f;
1695: double *xt;
1696:
1697: xt=vector(1,ncom);
1698: for (j=1;j<=ncom;j++) xt[j]=pcom[j]+x*xicom[j];
1699: f=(*nrfunc)(xt);
1700: free_vector(xt,1,ncom);
1701: return f;
1702: }
1703:
1704: /*****************brent *************************/
1705: double brent(double ax, double bx, double cx, double (*f)(double), double tol, double *xmin)
1.187 brouard 1706: {
1707: /* Given a function f, and given a bracketing triplet of abscissas ax, bx, cx (such that bx is
1708: * between ax and cx, and f(bx) is less than both f(ax) and f(cx) ), this routine isolates
1709: * the minimum to a fractional precision of about tol using Brent’s method. The abscissa of
1710: * the minimum is returned as xmin, and the minimum function value is returned as brent , the
1711: * returned function value.
1712: */
1.126 brouard 1713: int iter;
1714: double a,b,d,etemp;
1.159 brouard 1715: double fu=0,fv,fw,fx;
1.164 brouard 1716: double ftemp=0.;
1.126 brouard 1717: double p,q,r,tol1,tol2,u,v,w,x,xm;
1718: double e=0.0;
1719:
1720: a=(ax < cx ? ax : cx);
1721: b=(ax > cx ? ax : cx);
1722: x=w=v=bx;
1723: fw=fv=fx=(*f)(x);
1724: for (iter=1;iter<=ITMAX;iter++) {
1725: xm=0.5*(a+b);
1726: tol2=2.0*(tol1=tol*fabs(x)+ZEPS);
1727: /* if (2.0*fabs(fp-(*fret)) <= ftol*(fabs(fp)+fabs(*fret)))*/
1728: printf(".");fflush(stdout);
1729: fprintf(ficlog,".");fflush(ficlog);
1.162 brouard 1730: #ifdef DEBUGBRENT
1.126 brouard 1731: 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);
1732: 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);
1733: /* if ((fabs(x-xm) <= (tol2-0.5*(b-a)))||(2.0*fabs(fu-ftemp) <= ftol*1.e-2*(fabs(fu)+fabs(ftemp)))) { */
1734: #endif
1735: if (fabs(x-xm) <= (tol2-0.5*(b-a))){
1736: *xmin=x;
1737: return fx;
1738: }
1739: ftemp=fu;
1740: if (fabs(e) > tol1) {
1741: r=(x-w)*(fx-fv);
1742: q=(x-v)*(fx-fw);
1743: p=(x-v)*q-(x-w)*r;
1744: q=2.0*(q-r);
1745: if (q > 0.0) p = -p;
1746: q=fabs(q);
1747: etemp=e;
1748: e=d;
1749: if (fabs(p) >= fabs(0.5*q*etemp) || p <= q*(a-x) || p >= q*(b-x))
1.224 brouard 1750: d=CGOLD*(e=(x >= xm ? a-x : b-x));
1.126 brouard 1751: else {
1.224 brouard 1752: d=p/q;
1753: u=x+d;
1754: if (u-a < tol2 || b-u < tol2)
1755: d=SIGN(tol1,xm-x);
1.126 brouard 1756: }
1757: } else {
1758: d=CGOLD*(e=(x >= xm ? a-x : b-x));
1759: }
1760: u=(fabs(d) >= tol1 ? x+d : x+SIGN(tol1,d));
1761: fu=(*f)(u);
1762: if (fu <= fx) {
1763: if (u >= x) a=x; else b=x;
1764: SHFT(v,w,x,u)
1.183 brouard 1765: SHFT(fv,fw,fx,fu)
1766: } else {
1767: if (u < x) a=u; else b=u;
1768: if (fu <= fw || w == x) {
1.224 brouard 1769: v=w;
1770: w=u;
1771: fv=fw;
1772: fw=fu;
1.183 brouard 1773: } else if (fu <= fv || v == x || v == w) {
1.224 brouard 1774: v=u;
1775: fv=fu;
1.183 brouard 1776: }
1777: }
1.126 brouard 1778: }
1779: nrerror("Too many iterations in brent");
1780: *xmin=x;
1781: return fx;
1782: }
1783:
1784: /****************** mnbrak ***********************/
1785:
1786: void mnbrak(double *ax, double *bx, double *cx, double *fa, double *fb, double *fc,
1787: double (*func)(double))
1.183 brouard 1788: { /* Given a function func , and given distinct initial points ax and bx , this routine searches in
1789: the downhill direction (defined by the function as evaluated at the initial points) and returns
1790: new points ax , bx , cx that bracket a minimum of the function. Also returned are the function
1791: values at the three points, fa, fb , and fc such that fa > fb and fb < fc.
1792: */
1.126 brouard 1793: double ulim,u,r,q, dum;
1794: double fu;
1.187 brouard 1795:
1796: double scale=10.;
1797: int iterscale=0;
1798:
1799: *fa=(*func)(*ax); /* xta[j]=pcom[j]+(*ax)*xicom[j]; fa=f(xta[j])*/
1800: *fb=(*func)(*bx); /* xtb[j]=pcom[j]+(*bx)*xicom[j]; fb=f(xtb[j]) */
1801:
1802:
1803: /* while(*fb != *fb){ /\* *ax should be ok, reducing distance to *ax *\/ */
1804: /* printf("Warning mnbrak *fb = %lf, *bx=%lf *ax=%lf *fa==%lf iter=%d\n",*fb, *bx, *ax, *fa, iterscale++); */
1805: /* *bx = *ax - (*ax - *bx)/scale; */
1806: /* *fb=(*func)(*bx); /\* xtb[j]=pcom[j]+(*bx)*xicom[j]; fb=f(xtb[j]) *\/ */
1807: /* } */
1808:
1.126 brouard 1809: if (*fb > *fa) {
1810: SHFT(dum,*ax,*bx,dum)
1.183 brouard 1811: SHFT(dum,*fb,*fa,dum)
1812: }
1.126 brouard 1813: *cx=(*bx)+GOLD*(*bx-*ax);
1814: *fc=(*func)(*cx);
1.183 brouard 1815: #ifdef DEBUG
1.224 brouard 1816: printf("mnbrak0 a=%lf *fa=%lf, b=%lf *fb=%lf, c=%lf *fc=%lf\n",*ax,*fa,*bx,*fb,*cx, *fc);
1817: 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 1818: #endif
1.224 brouard 1819: 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 1820: r=(*bx-*ax)*(*fb-*fc);
1.224 brouard 1821: q=(*bx-*cx)*(*fb-*fa); /* What if fa=inf */
1.126 brouard 1822: u=(*bx)-((*bx-*cx)*q-(*bx-*ax)*r)/
1.183 brouard 1823: (2.0*SIGN(FMAX(fabs(q-r),TINY),q-r)); /* Minimum abscissa of a parabolic estimated from (a,fa), (b,fb) and (c,fc). */
1824: ulim=(*bx)+GLIMIT*(*cx-*bx); /* Maximum abscissa where function should be evaluated */
1825: if ((*bx-u)*(u-*cx) > 0.0) { /* if u_p is between b and c */
1.126 brouard 1826: fu=(*func)(u);
1.163 brouard 1827: #ifdef DEBUG
1828: /* f(x)=A(x-u)**2+f(u) */
1829: double A, fparabu;
1830: A= (*fb - *fa)/(*bx-*ax)/(*bx+*ax-2*u);
1831: fparabu= *fa - A*(*ax-u)*(*ax-u);
1.224 brouard 1832: 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);
1833: 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 1834: /* And thus,it can be that fu > *fc even if fparabu < *fc */
1835: /* mnbrak (*ax=7.666299858533, *fa=299039.693133272231), (*bx=8.595447774979, *fb=298976.598289369489),
1836: (*cx=10.098840694817, *fc=298946.631474258087), (*u=9.852501168332, fu=298948.773013752128, fparabu=298945.434711494134) */
1837: /* In that case, there is no bracket in the output! Routine is wrong with many consequences.*/
1.163 brouard 1838: #endif
1.184 brouard 1839: #ifdef MNBRAKORIGINAL
1.183 brouard 1840: #else
1.191 brouard 1841: /* if (fu > *fc) { */
1842: /* #ifdef DEBUG */
1843: /* printf("mnbrak4 fu > fc \n"); */
1844: /* fprintf(ficlog, "mnbrak4 fu > fc\n"); */
1845: /* #endif */
1846: /* /\* 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 *\\/ *\/ */
1847: /* /\* SHFT(*fa,*fc,fu,*fc) /\\* (b, u, c) is a bracket while test fb > fc will be fu > fc will exit *\\/ *\/ */
1848: /* dum=u; /\* Shifting c and u *\/ */
1849: /* u = *cx; */
1850: /* *cx = dum; */
1851: /* dum = fu; */
1852: /* fu = *fc; */
1853: /* *fc =dum; */
1854: /* } else { /\* end *\/ */
1855: /* #ifdef DEBUG */
1856: /* printf("mnbrak3 fu < fc \n"); */
1857: /* fprintf(ficlog, "mnbrak3 fu < fc\n"); */
1858: /* #endif */
1859: /* dum=u; /\* Shifting c and u *\/ */
1860: /* u = *cx; */
1861: /* *cx = dum; */
1862: /* dum = fu; */
1863: /* fu = *fc; */
1864: /* *fc =dum; */
1865: /* } */
1.224 brouard 1866: #ifdef DEBUGMNBRAK
1867: double A, fparabu;
1868: A= (*fb - *fa)/(*bx-*ax)/(*bx+*ax-2*u);
1869: fparabu= *fa - A*(*ax-u)*(*ax-u);
1870: 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);
1871: 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 1872: #endif
1.191 brouard 1873: dum=u; /* Shifting c and u */
1874: u = *cx;
1875: *cx = dum;
1876: dum = fu;
1877: fu = *fc;
1878: *fc =dum;
1.183 brouard 1879: #endif
1.162 brouard 1880: } else if ((*cx-u)*(u-ulim) > 0.0) { /* u is after c but before ulim */
1.183 brouard 1881: #ifdef DEBUG
1.224 brouard 1882: printf("\nmnbrak2 u=%lf after c=%lf but before ulim\n",u,*cx);
1883: fprintf(ficlog,"\nmnbrak2 u=%lf after c=%lf but before ulim\n",u,*cx);
1.183 brouard 1884: #endif
1.126 brouard 1885: fu=(*func)(u);
1886: if (fu < *fc) {
1.183 brouard 1887: #ifdef DEBUG
1.224 brouard 1888: printf("\nmnbrak2 u=%lf after c=%lf but before ulim=%lf AND fu=%lf < %lf=fc\n",u,*cx,ulim,fu, *fc);
1889: fprintf(ficlog,"\nmnbrak2 u=%lf after c=%lf but before ulim=%lf AND fu=%lf < %lf=fc\n",u,*cx,ulim,fu, *fc);
1890: #endif
1891: SHFT(*bx,*cx,u,*cx+GOLD*(*cx-*bx))
1892: SHFT(*fb,*fc,fu,(*func)(u))
1893: #ifdef DEBUG
1894: printf("\nmnbrak2 shift GOLD c=%lf",*cx+GOLD*(*cx-*bx));
1.183 brouard 1895: #endif
1896: }
1.162 brouard 1897: } else if ((u-ulim)*(ulim-*cx) >= 0.0) { /* u outside ulim (verifying that ulim is beyond c) */
1.183 brouard 1898: #ifdef DEBUG
1.224 brouard 1899: printf("\nmnbrak2 u=%lf outside ulim=%lf (verifying that ulim is beyond c=%lf)\n",u,ulim,*cx);
1900: fprintf(ficlog,"\nmnbrak2 u=%lf outside ulim=%lf (verifying that ulim is beyond c=%lf)\n",u,ulim,*cx);
1.183 brouard 1901: #endif
1.126 brouard 1902: u=ulim;
1903: fu=(*func)(u);
1.183 brouard 1904: } else { /* u could be left to b (if r > q parabola has a maximum) */
1905: #ifdef DEBUG
1.224 brouard 1906: printf("\nmnbrak2 u=%lf could be left to b=%lf (if r=%lf > q=%lf parabola has a maximum)\n",u,*bx,r,q);
1907: 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 1908: #endif
1.126 brouard 1909: u=(*cx)+GOLD*(*cx-*bx);
1910: fu=(*func)(u);
1.224 brouard 1911: #ifdef DEBUG
1912: printf("\nmnbrak2 new u=%lf fu=%lf shifted gold left from c=%lf and b=%lf \n",u,fu,*cx,*bx);
1913: fprintf(ficlog,"\nmnbrak2 new u=%lf fu=%lf shifted gold left from c=%lf and b=%lf \n",u,fu,*cx,*bx);
1914: #endif
1.183 brouard 1915: } /* end tests */
1.126 brouard 1916: SHFT(*ax,*bx,*cx,u)
1.183 brouard 1917: SHFT(*fa,*fb,*fc,fu)
1918: #ifdef DEBUG
1.224 brouard 1919: printf("\nmnbrak2 shift (*ax=%.12f, *fa=%.12lf), (*bx=%.12f, *fb=%.12lf), (*cx=%.12f, *fc=%.12lf)\n",*ax,*fa,*bx,*fb,*cx,*fc);
1920: 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 1921: #endif
1922: } /* 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 1923: }
1924:
1925: /*************** linmin ************************/
1.162 brouard 1926: /* Given an n -dimensional point p[1..n] and an n -dimensional direction xi[1..n] , moves and
1927: resets p to where the function func(p) takes on a minimum along the direction xi from p ,
1928: and replaces xi by the actual vector displacement that p was moved. Also returns as fret
1929: the value of func at the returned location p . This is actually all accomplished by calling the
1930: routines mnbrak and brent .*/
1.126 brouard 1931: int ncom;
1932: double *pcom,*xicom;
1933: double (*nrfunc)(double []);
1934:
1.224 brouard 1935: #ifdef LINMINORIGINAL
1.126 brouard 1936: void linmin(double p[], double xi[], int n, double *fret,double (*func)(double []))
1.224 brouard 1937: #else
1938: void linmin(double p[], double xi[], int n, double *fret,double (*func)(double []), int *flat)
1939: #endif
1.126 brouard 1940: {
1941: double brent(double ax, double bx, double cx,
1942: double (*f)(double), double tol, double *xmin);
1943: double f1dim(double x);
1944: void mnbrak(double *ax, double *bx, double *cx, double *fa, double *fb,
1945: double *fc, double (*func)(double));
1946: int j;
1947: double xx,xmin,bx,ax;
1948: double fx,fb,fa;
1.187 brouard 1949:
1.203 brouard 1950: #ifdef LINMINORIGINAL
1951: #else
1952: double scale=10., axs, xxs; /* Scale added for infinity */
1953: #endif
1954:
1.126 brouard 1955: ncom=n;
1956: pcom=vector(1,n);
1957: xicom=vector(1,n);
1958: nrfunc=func;
1959: for (j=1;j<=n;j++) {
1960: pcom[j]=p[j];
1.202 brouard 1961: xicom[j]=xi[j]; /* Former scale xi[j] of currrent direction i */
1.126 brouard 1962: }
1.187 brouard 1963:
1.203 brouard 1964: #ifdef LINMINORIGINAL
1965: xx=1.;
1966: #else
1967: axs=0.0;
1968: xxs=1.;
1969: do{
1970: xx= xxs;
1971: #endif
1.187 brouard 1972: ax=0.;
1973: mnbrak(&ax,&xx,&bx,&fa,&fx,&fb,f1dim); /* Outputs: xtx[j]=pcom[j]+(*xx)*xicom[j]; fx=f(xtx[j]) */
1974: /* brackets with inputs ax=0 and xx=1, but points, pcom=p, and directions values, xicom=xi, are sent via f1dim(x) */
1975: /* 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)) */
1976: /* Outputs: fa=f(p(j)) and fx=f(p(j) + xxs * xi(j) ) and f(bx)= f(p(j)+ bx* xi(j)) */
1977: /* Given input ax=axs and xx=xxs, xx might be too far from ax to get a finite f(xx) */
1978: /* Searches on line, outputs (ax, xx, bx) such that fx < min(fa and fb) */
1979: /* 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 1980: #ifdef LINMINORIGINAL
1981: #else
1982: if (fx != fx){
1.224 brouard 1983: xxs=xxs/scale; /* Trying a smaller xx, closer to initial ax=0 */
1984: printf("|");
1985: fprintf(ficlog,"|");
1.203 brouard 1986: #ifdef DEBUGLINMIN
1.224 brouard 1987: 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 1988: #endif
1989: }
1.224 brouard 1990: }while(fx != fx && xxs > 1.e-5);
1.203 brouard 1991: #endif
1992:
1.191 brouard 1993: #ifdef DEBUGLINMIN
1994: 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 1995: 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 1996: #endif
1.224 brouard 1997: #ifdef LINMINORIGINAL
1998: #else
1999: if(fb == fx){ /* Flat function in the direction */
2000: xmin=xx;
2001: *flat=1;
2002: }else{
2003: *flat=0;
2004: #endif
2005: /*Flat mnbrak2 shift (*ax=0.000000000000, *fa=51626.272983130431), (*bx=-1.618034000000, *fb=51590.149499362531), (*cx=-4.236068025156, *fc=51590.149499362531) */
1.187 brouard 2006: *fret=brent(ax,xx,bx,f1dim,TOL,&xmin); /* Giving a bracketting triplet (ax, xx, bx), find a minimum, xmin, according to f1dim, *fret(xmin),*/
2007: /* fa = f(p[j] + ax * xi[j]), fx = f(p[j] + xx * xi[j]), fb = f(p[j] + bx * xi[j]) */
2008: /* fmin = f(p[j] + xmin * xi[j]) */
2009: /* P+lambda n in that direction (lambdamin), with TOL between abscisses */
2010: /* f1dim(xmin): for (j=1;j<=ncom;j++) xt[j]=pcom[j]+xmin*xicom[j]; */
1.126 brouard 2011: #ifdef DEBUG
1.224 brouard 2012: 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);
2013: 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);
2014: #endif
2015: #ifdef LINMINORIGINAL
2016: #else
2017: }
1.126 brouard 2018: #endif
1.191 brouard 2019: #ifdef DEBUGLINMIN
2020: printf("linmin end ");
1.202 brouard 2021: fprintf(ficlog,"linmin end ");
1.191 brouard 2022: #endif
1.126 brouard 2023: for (j=1;j<=n;j++) {
1.203 brouard 2024: #ifdef LINMINORIGINAL
2025: xi[j] *= xmin;
2026: #else
2027: #ifdef DEBUGLINMIN
2028: if(xxs <1.0)
2029: printf(" before xi[%d]=%12.8f", j,xi[j]);
2030: #endif
2031: 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) */
2032: #ifdef DEBUGLINMIN
2033: if(xxs <1.0)
2034: 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 );
2035: #endif
2036: #endif
1.187 brouard 2037: p[j] += xi[j]; /* Parameters values are updated accordingly */
1.126 brouard 2038: }
1.191 brouard 2039: #ifdef DEBUGLINMIN
1.203 brouard 2040: printf("\n");
1.191 brouard 2041: printf("Comparing last *frec(xmin=%12.8f)=%12.8f from Brent and frec(0.)=%12.8f \n", xmin, *fret, (*func)(p));
1.202 brouard 2042: 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 2043: for (j=1;j<=n;j++) {
1.202 brouard 2044: printf(" xi[%d]= %14.10f p[%d]= %12.7f",j,xi[j],j,p[j]);
2045: fprintf(ficlog," xi[%d]= %14.10f p[%d]= %12.7f",j,xi[j],j,p[j]);
2046: if(j % ncovmodel == 0){
1.191 brouard 2047: printf("\n");
1.202 brouard 2048: fprintf(ficlog,"\n");
2049: }
1.191 brouard 2050: }
1.203 brouard 2051: #else
1.191 brouard 2052: #endif
1.126 brouard 2053: free_vector(xicom,1,n);
2054: free_vector(pcom,1,n);
2055: }
2056:
2057:
2058: /*************** powell ************************/
1.162 brouard 2059: /*
2060: Minimization of a function func of n variables. Input consists of an initial starting point
2061: p[1..n] ; an initial matrix xi[1..n][1..n] , whose columns contain the initial set of di-
2062: rections (usually the n unit vectors); and ftol , the fractional tolerance in the function value
2063: such that failure to decrease by more than this amount on one iteration signals doneness. On
2064: output, p is set to the best point found, xi is the then-current direction set, fret is the returned
2065: function value at p , and iter is the number of iterations taken. The routine linmin is used.
2066: */
1.224 brouard 2067: #ifdef LINMINORIGINAL
2068: #else
2069: int *flatdir; /* Function is vanishing in that direction */
1.225 brouard 2070: int flat=0, flatd=0; /* Function is vanishing in that direction */
1.224 brouard 2071: #endif
1.126 brouard 2072: void powell(double p[], double **xi, int n, double ftol, int *iter, double *fret,
2073: double (*func)(double []))
2074: {
1.224 brouard 2075: #ifdef LINMINORIGINAL
2076: void linmin(double p[], double xi[], int n, double *fret,
1.126 brouard 2077: double (*func)(double []));
1.224 brouard 2078: #else
1.241 brouard 2079: void linmin(double p[], double xi[], int n, double *fret,
2080: double (*func)(double []),int *flat);
1.224 brouard 2081: #endif
1.239 brouard 2082: int i,ibig,j,jk,k;
1.126 brouard 2083: double del,t,*pt,*ptt,*xit;
1.181 brouard 2084: double directest;
1.126 brouard 2085: double fp,fptt;
2086: double *xits;
2087: int niterf, itmp;
1.224 brouard 2088: #ifdef LINMINORIGINAL
2089: #else
2090:
2091: flatdir=ivector(1,n);
2092: for (j=1;j<=n;j++) flatdir[j]=0;
2093: #endif
1.126 brouard 2094:
2095: pt=vector(1,n);
2096: ptt=vector(1,n);
2097: xit=vector(1,n);
2098: xits=vector(1,n);
2099: *fret=(*func)(p);
2100: for (j=1;j<=n;j++) pt[j]=p[j];
1.202 brouard 2101: rcurr_time = time(NULL);
1.126 brouard 2102: for (*iter=1;;++(*iter)) {
1.187 brouard 2103: fp=(*fret); /* From former iteration or initial value */
1.126 brouard 2104: ibig=0;
2105: del=0.0;
1.157 brouard 2106: rlast_time=rcurr_time;
2107: /* (void) gettimeofday(&curr_time,&tzp); */
2108: rcurr_time = time(NULL);
2109: curr_time = *localtime(&rcurr_time);
2110: printf("\nPowell iter=%d -2*LL=%.12f %ld sec. %ld sec.",*iter,*fret, rcurr_time-rlast_time, rcurr_time-rstart_time);fflush(stdout);
2111: fprintf(ficlog,"\nPowell iter=%d -2*LL=%.12f %ld sec. %ld sec.",*iter,*fret,rcurr_time-rlast_time, rcurr_time-rstart_time); fflush(ficlog);
2112: /* fprintf(ficrespow,"%d %.12f %ld",*iter,*fret,curr_time.tm_sec-start_time.tm_sec); */
1.192 brouard 2113: for (i=1;i<=n;i++) {
1.126 brouard 2114: fprintf(ficrespow," %.12lf", p[i]);
2115: }
1.239 brouard 2116: fprintf(ficrespow,"\n");fflush(ficrespow);
2117: printf("\n#model= 1 + age ");
2118: fprintf(ficlog,"\n#model= 1 + age ");
2119: if(nagesqr==1){
1.241 brouard 2120: printf(" + age*age ");
2121: fprintf(ficlog," + age*age ");
1.239 brouard 2122: }
2123: for(j=1;j <=ncovmodel-2;j++){
2124: if(Typevar[j]==0) {
2125: printf(" + V%d ",Tvar[j]);
2126: fprintf(ficlog," + V%d ",Tvar[j]);
2127: }else if(Typevar[j]==1) {
2128: printf(" + V%d*age ",Tvar[j]);
2129: fprintf(ficlog," + V%d*age ",Tvar[j]);
2130: }else if(Typevar[j]==2) {
2131: printf(" + V%d*V%d ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
2132: fprintf(ficlog," + V%d*V%d ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
2133: }
2134: }
1.126 brouard 2135: printf("\n");
1.239 brouard 2136: /* printf("12 47.0114589 0.0154322 33.2424412 0.3279905 2.3731903 */
2137: /* 13 -21.5392400 0.1118147 1.2680506 1.2973408 -1.0663662 */
1.126 brouard 2138: fprintf(ficlog,"\n");
1.239 brouard 2139: for(i=1,jk=1; i <=nlstate; i++){
2140: for(k=1; k <=(nlstate+ndeath); k++){
2141: if (k != i) {
2142: printf("%d%d ",i,k);
2143: fprintf(ficlog,"%d%d ",i,k);
2144: for(j=1; j <=ncovmodel; j++){
2145: printf("%12.7f ",p[jk]);
2146: fprintf(ficlog,"%12.7f ",p[jk]);
2147: jk++;
2148: }
2149: printf("\n");
2150: fprintf(ficlog,"\n");
2151: }
2152: }
2153: }
1.241 brouard 2154: if(*iter <=3 && *iter >1){
1.157 brouard 2155: tml = *localtime(&rcurr_time);
2156: strcpy(strcurr,asctime(&tml));
2157: rforecast_time=rcurr_time;
1.126 brouard 2158: itmp = strlen(strcurr);
2159: if(strcurr[itmp-1]=='\n') /* Windows outputs with a new line */
1.241 brouard 2160: strcurr[itmp-1]='\0';
1.162 brouard 2161: printf("\nConsidering the time needed for the last iteration #%d: %ld seconds,\n",*iter,rcurr_time-rlast_time);
1.157 brouard 2162: fprintf(ficlog,"\nConsidering the time needed for this last iteration #%d: %ld seconds,\n",*iter,rcurr_time-rlast_time);
1.126 brouard 2163: for(niterf=10;niterf<=30;niterf+=10){
1.241 brouard 2164: rforecast_time=rcurr_time+(niterf-*iter)*(rcurr_time-rlast_time);
2165: forecast_time = *localtime(&rforecast_time);
2166: strcpy(strfor,asctime(&forecast_time));
2167: itmp = strlen(strfor);
2168: if(strfor[itmp-1]=='\n')
2169: strfor[itmp-1]='\0';
2170: 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);
2171: 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 2172: }
2173: }
1.187 brouard 2174: for (i=1;i<=n;i++) { /* For each direction i */
2175: for (j=1;j<=n;j++) xit[j]=xi[j][i]; /* Directions stored from previous iteration with previous scales */
1.126 brouard 2176: fptt=(*fret);
2177: #ifdef DEBUG
1.203 brouard 2178: printf("fret=%lf, %lf, %lf \n", *fret, *fret, *fret);
2179: fprintf(ficlog, "fret=%lf, %lf, %lf \n", *fret, *fret, *fret);
1.126 brouard 2180: #endif
1.203 brouard 2181: printf("%d",i);fflush(stdout); /* print direction (parameter) i */
1.126 brouard 2182: fprintf(ficlog,"%d",i);fflush(ficlog);
1.224 brouard 2183: #ifdef LINMINORIGINAL
1.188 brouard 2184: linmin(p,xit,n,fret,func); /* Point p[n]. xit[n] has been loaded for direction i as input.*/
1.224 brouard 2185: #else
2186: linmin(p,xit,n,fret,func,&flat); /* Point p[n]. xit[n] has been loaded for direction i as input.*/
2187: flatdir[i]=flat; /* Function is vanishing in that direction i */
2188: #endif
2189: /* Outputs are fret(new point p) p is updated and xit rescaled */
1.188 brouard 2190: if (fabs(fptt-(*fret)) > del) { /* We are keeping the max gain on each of the n directions */
1.224 brouard 2191: /* because that direction will be replaced unless the gain del is small */
2192: /* in comparison with the 'probable' gain, mu^2, with the last average direction. */
2193: /* Unless the n directions are conjugate some gain in the determinant may be obtained */
2194: /* with the new direction. */
2195: del=fabs(fptt-(*fret));
2196: ibig=i;
1.126 brouard 2197: }
2198: #ifdef DEBUG
2199: printf("%d %.12e",i,(*fret));
2200: fprintf(ficlog,"%d %.12e",i,(*fret));
2201: for (j=1;j<=n;j++) {
1.224 brouard 2202: xits[j]=FMAX(fabs(p[j]-pt[j]),1.e-5);
2203: printf(" x(%d)=%.12e",j,xit[j]);
2204: fprintf(ficlog," x(%d)=%.12e",j,xit[j]);
1.126 brouard 2205: }
2206: for(j=1;j<=n;j++) {
1.225 brouard 2207: printf(" p(%d)=%.12e",j,p[j]);
2208: fprintf(ficlog," p(%d)=%.12e",j,p[j]);
1.126 brouard 2209: }
2210: printf("\n");
2211: fprintf(ficlog,"\n");
2212: #endif
1.187 brouard 2213: } /* end loop on each direction i */
2214: /* Convergence test will use last linmin estimation (fret) and compare former iteration (fp) */
1.188 brouard 2215: /* But p and xit have been updated at the end of linmin, *fret corresponds to new p, xit */
1.187 brouard 2216: /* New value of last point Pn is not computed, P(n-1) */
1.224 brouard 2217: for(j=1;j<=n;j++) {
1.225 brouard 2218: if(flatdir[j] >0){
2219: printf(" p(%d)=%lf flat=%d ",j,p[j],flatdir[j]);
2220: fprintf(ficlog," p(%d)=%lf flat=%d ",j,p[j],flatdir[j]);
2221: }
2222: /* printf("\n"); */
2223: /* fprintf(ficlog,"\n"); */
2224: }
1.243 ! brouard 2225: /* if (2.0*fabs(fp-(*fret)) <= ftol*(fabs(fp)+fabs(*fret))) { /\* Did we reach enough precision? *\/ */
! 2226: if (2.0*fabs(fp-(*fret)) <= ftol) { /* Did we reach enough precision? */
1.188 brouard 2227: /* We could compare with a chi^2. chisquare(0.95,ddl=1)=3.84 */
2228: /* By adding age*age in a model, the new -2LL should be lower and the difference follows a */
2229: /* a chisquare statistics with 1 degree. To be significant at the 95% level, it should have */
2230: /* decreased of more than 3.84 */
2231: /* By adding age*age and V1*age the gain (-2LL) should be more than 5.99 (ddl=2) */
2232: /* By using V1+V2+V3, the gain should be 7.82, compared with basic 1+age. */
2233: /* By adding 10 parameters more the gain should be 18.31 */
1.224 brouard 2234:
1.188 brouard 2235: /* Starting the program with initial values given by a former maximization will simply change */
2236: /* the scales of the directions and the directions, because the are reset to canonical directions */
2237: /* Thus the first calls to linmin will give new points and better maximizations until fp-(*fret) is */
2238: /* under the tolerance value. If the tolerance is very small 1.e-9, it could last long. */
1.126 brouard 2239: #ifdef DEBUG
2240: int k[2],l;
2241: k[0]=1;
2242: k[1]=-1;
2243: printf("Max: %.12e",(*func)(p));
2244: fprintf(ficlog,"Max: %.12e",(*func)(p));
2245: for (j=1;j<=n;j++) {
2246: printf(" %.12e",p[j]);
2247: fprintf(ficlog," %.12e",p[j]);
2248: }
2249: printf("\n");
2250: fprintf(ficlog,"\n");
2251: for(l=0;l<=1;l++) {
2252: for (j=1;j<=n;j++) {
2253: ptt[j]=p[j]+(p[j]-pt[j])*k[l];
2254: printf("l=%d j=%d ptt=%.12e, xits=%.12e, p=%.12e, xit=%.12e", l,j,ptt[j],xits[j],p[j],xit[j]);
2255: fprintf(ficlog,"l=%d j=%d ptt=%.12e, xits=%.12e, p=%.12e, xit=%.12e", l,j,ptt[j],xits[j],p[j],xit[j]);
2256: }
2257: printf("func(ptt)=%.12e, deriv=%.12e\n",(*func)(ptt),(ptt[j]-p[j])/((*func)(ptt)-(*func)(p)));
2258: fprintf(ficlog,"func(ptt)=%.12e, deriv=%.12e\n",(*func)(ptt),(ptt[j]-p[j])/((*func)(ptt)-(*func)(p)));
2259: }
2260: #endif
2261:
1.224 brouard 2262: #ifdef LINMINORIGINAL
2263: #else
2264: free_ivector(flatdir,1,n);
2265: #endif
1.126 brouard 2266: free_vector(xit,1,n);
2267: free_vector(xits,1,n);
2268: free_vector(ptt,1,n);
2269: free_vector(pt,1,n);
2270: return;
1.192 brouard 2271: } /* enough precision */
1.240 brouard 2272: if (*iter == ITMAX*n) nrerror("powell exceeding maximum iterations.");
1.181 brouard 2273: for (j=1;j<=n;j++) { /* Computes the extrapolated point P_0 + 2 (P_n-P_0) */
1.126 brouard 2274: ptt[j]=2.0*p[j]-pt[j];
2275: xit[j]=p[j]-pt[j];
2276: pt[j]=p[j];
2277: }
1.181 brouard 2278: fptt=(*func)(ptt); /* f_3 */
1.224 brouard 2279: #ifdef NODIRECTIONCHANGEDUNTILNITER /* No change in drections until some iterations are done */
2280: if (*iter <=4) {
1.225 brouard 2281: #else
2282: #endif
1.224 brouard 2283: #ifdef POWELLNOF3INFF1TEST /* skips test F3 <F1 */
1.192 brouard 2284: #else
1.161 brouard 2285: if (fptt < fp) { /* If extrapolated point is better, decide if we keep that new direction or not */
1.192 brouard 2286: #endif
1.162 brouard 2287: /* (x1 f1=fp), (x2 f2=*fret), (x3 f3=fptt), (xm fm) */
1.161 brouard 2288: /* From x1 (P0) distance of x2 is at h and x3 is 2h */
1.162 brouard 2289: /* Let f"(x2) be the 2nd derivative equal everywhere. */
2290: /* Then the parabolic through (x1,f1), (x2,f2) and (x3,f3) */
2291: /* will reach at f3 = fm + h^2/2 f"m ; f" = (f1 -2f2 +f3 ) / h**2 */
1.224 brouard 2292: /* Conditional for using this new direction is that mu^2 = (f1-2f2+f3)^2 /2 < del or directest <0 */
2293: /* also lamda^2=(f1-f2)^2/mu² is a parasite solution of powell */
2294: /* For powell, inclusion of this average direction is only if t(del)<0 or del inbetween mu^2 and lambda^2 */
1.161 brouard 2295: /* t=2.0*(fp-2.0*(*fret)+fptt)*SQR(fp-(*fret)-del)-del*SQR(fp-fptt); */
1.224 brouard 2296: /* Even if f3 <f1, directest can be negative and t >0 */
2297: /* mu² and del² are equal when f3=f1 */
2298: /* f3 < f1 : mu² < del <= lambda^2 both test are equivalent */
2299: /* f3 < f1 : mu² < lambda^2 < del then directtest is negative and powell t is positive */
2300: /* f3 > f1 : lambda² < mu^2 < del then t is negative and directest >0 */
2301: /* f3 > f1 : lambda² < del < mu^2 then t is positive and directest >0 */
1.183 brouard 2302: #ifdef NRCORIGINAL
2303: t=2.0*(fp-2.0*(*fret)+fptt)*SQR(fp-(*fret)-del)- del*SQR(fp-fptt); /* Original Numerical Recipes in C*/
2304: #else
2305: 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 2306: t= t- del*SQR(fp-fptt);
1.183 brouard 2307: #endif
1.202 brouard 2308: directest = fp-2.0*(*fret)+fptt - 2.0 * del; /* If delta was big enough we change it for a new direction */
1.161 brouard 2309: #ifdef DEBUG
1.181 brouard 2310: 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);
2311: 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 2312: printf("t3= %.12lf, t4= %.12lf, t3*= %.12lf, t4*= %.12lf\n",SQR(fp-(*fret)-del),SQR(fp-fptt),
2313: (fp-(*fret)-del)*(fp-(*fret)-del),(fp-fptt)*(fp-fptt));
2314: fprintf(ficlog,"t3= %.12lf, t4= %.12lf, t3*= %.12lf, t4*= %.12lf\n",SQR(fp-(*fret)-del),SQR(fp-fptt),
2315: (fp-(*fret)-del)*(fp-(*fret)-del),(fp-fptt)*(fp-fptt));
2316: 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);
2317: 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);
2318: #endif
1.183 brouard 2319: #ifdef POWELLORIGINAL
2320: if (t < 0.0) { /* Then we use it for new direction */
2321: #else
1.182 brouard 2322: if (directest*t < 0.0) { /* Contradiction between both tests */
1.224 brouard 2323: 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 2324: 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 2325: 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 2326: fprintf(ficlog,"f1-2f2+f3= %.12lf, f1-f2-del= %.12lf, f1-f3= %.12lf\n",fp-2.0*(*fret)+fptt, fp -(*fret) -del, fp-fptt);
2327: }
1.181 brouard 2328: if (directest < 0.0) { /* Then we use it for new direction */
2329: #endif
1.191 brouard 2330: #ifdef DEBUGLINMIN
1.234 brouard 2331: printf("Before linmin in direction P%d-P0\n",n);
2332: for (j=1;j<=n;j++) {
2333: printf(" Before xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
2334: fprintf(ficlog," Before xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
2335: if(j % ncovmodel == 0){
2336: printf("\n");
2337: fprintf(ficlog,"\n");
2338: }
2339: }
1.224 brouard 2340: #endif
2341: #ifdef LINMINORIGINAL
1.234 brouard 2342: linmin(p,xit,n,fret,func); /* computes minimum on the extrapolated direction: changes p and rescales xit.*/
1.224 brouard 2343: #else
1.234 brouard 2344: linmin(p,xit,n,fret,func,&flat); /* computes minimum on the extrapolated direction: changes p and rescales xit.*/
2345: flatdir[i]=flat; /* Function is vanishing in that direction i */
1.191 brouard 2346: #endif
1.234 brouard 2347:
1.191 brouard 2348: #ifdef DEBUGLINMIN
1.234 brouard 2349: for (j=1;j<=n;j++) {
2350: printf("After xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
2351: fprintf(ficlog,"After xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
2352: if(j % ncovmodel == 0){
2353: printf("\n");
2354: fprintf(ficlog,"\n");
2355: }
2356: }
1.224 brouard 2357: #endif
1.234 brouard 2358: for (j=1;j<=n;j++) {
2359: xi[j][ibig]=xi[j][n]; /* Replace direction with biggest decrease by last direction n */
2360: xi[j][n]=xit[j]; /* and this nth direction by the by the average p_0 p_n */
2361: }
1.224 brouard 2362: #ifdef LINMINORIGINAL
2363: #else
1.234 brouard 2364: for (j=1, flatd=0;j<=n;j++) {
2365: if(flatdir[j]>0)
2366: flatd++;
2367: }
2368: if(flatd >0){
2369: printf("%d flat directions\n",flatd);
2370: fprintf(ficlog,"%d flat directions\n",flatd);
2371: for (j=1;j<=n;j++) {
2372: if(flatdir[j]>0){
2373: printf("%d ",j);
2374: fprintf(ficlog,"%d ",j);
2375: }
2376: }
2377: printf("\n");
2378: fprintf(ficlog,"\n");
2379: }
1.191 brouard 2380: #endif
1.234 brouard 2381: printf("Gaining to use new average direction of P0 P%d instead of biggest increase direction %d :\n",n,ibig);
2382: fprintf(ficlog,"Gaining to use new average direction of P0 P%d instead of biggest increase direction %d :\n",n,ibig);
2383:
1.126 brouard 2384: #ifdef DEBUG
1.234 brouard 2385: printf("Direction changed last moved %d in place of ibig=%d, new last is the average:\n",n,ibig);
2386: fprintf(ficlog,"Direction changed last moved %d in place of ibig=%d, new last is the average:\n",n,ibig);
2387: for(j=1;j<=n;j++){
2388: printf(" %lf",xit[j]);
2389: fprintf(ficlog," %lf",xit[j]);
2390: }
2391: printf("\n");
2392: fprintf(ficlog,"\n");
1.126 brouard 2393: #endif
1.192 brouard 2394: } /* end of t or directest negative */
1.224 brouard 2395: #ifdef POWELLNOF3INFF1TEST
1.192 brouard 2396: #else
1.234 brouard 2397: } /* end if (fptt < fp) */
1.192 brouard 2398: #endif
1.225 brouard 2399: #ifdef NODIRECTIONCHANGEDUNTILNITER /* No change in drections until some iterations are done */
1.234 brouard 2400: } /*NODIRECTIONCHANGEDUNTILNITER No change in drections until some iterations are done */
1.225 brouard 2401: #else
1.224 brouard 2402: #endif
1.234 brouard 2403: } /* loop iteration */
1.126 brouard 2404: }
1.234 brouard 2405:
1.126 brouard 2406: /**** Prevalence limit (stable or period prevalence) ****************/
1.234 brouard 2407:
1.235 brouard 2408: 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 2409: {
1.235 brouard 2410: /* Computes the prevalence limit in each live state at age x and for covariate combination ij
2411: (and selected quantitative values in nres)
2412: by left multiplying the unit
1.234 brouard 2413: matrix by transitions matrix until convergence is reached with precision ftolpl */
1.206 brouard 2414: /* Wx= Wx-1 Px-1= Wx-2 Px-2 Px-1 = Wx-n Px-n ... Px-2 Px-1 I */
2415: /* Wx is row vector: population in state 1, population in state 2, population dead */
2416: /* or prevalence in state 1, prevalence in state 2, 0 */
2417: /* newm is the matrix after multiplications, its rows are identical at a factor */
2418: /* Initial matrix pimij */
2419: /* {0.85204250825084937, 0.13044499163996345, 0.017512500109187184, */
2420: /* 0.090851990222114765, 0.88271245433047185, 0.026435555447413338, */
2421: /* 0, 0 , 1} */
2422: /*
2423: * and after some iteration: */
2424: /* {0.45504275246439968, 0.42731458730878791, 0.11764266022681241, */
2425: /* 0.45201005341706885, 0.42865420071559901, 0.11933574586733192, */
2426: /* 0, 0 , 1} */
2427: /* And prevalence by suppressing the deaths are close to identical rows in prlim: */
2428: /* {0.51571254859325999, 0.4842874514067399, */
2429: /* 0.51326036147820708, 0.48673963852179264} */
2430: /* If we start from prlim again, prlim tends to a constant matrix */
1.234 brouard 2431:
1.126 brouard 2432: int i, ii,j,k;
1.209 brouard 2433: double *min, *max, *meandiff, maxmax,sumnew=0.;
1.145 brouard 2434: /* double **matprod2(); */ /* test */
1.218 brouard 2435: double **out, cov[NCOVMAX+1], **pmij(); /* **pmmij is a global variable feeded with oldms etc */
1.126 brouard 2436: double **newm;
1.209 brouard 2437: double agefin, delaymax=200. ; /* 100 Max number of years to converge */
1.203 brouard 2438: int ncvloop=0;
1.169 brouard 2439:
1.209 brouard 2440: min=vector(1,nlstate);
2441: max=vector(1,nlstate);
2442: meandiff=vector(1,nlstate);
2443:
1.218 brouard 2444: /* Starting with matrix unity */
1.126 brouard 2445: for (ii=1;ii<=nlstate+ndeath;ii++)
2446: for (j=1;j<=nlstate+ndeath;j++){
2447: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
2448: }
1.169 brouard 2449:
2450: cov[1]=1.;
2451:
2452: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
1.202 brouard 2453: /* Start at agefin= age, computes the matrix of passage and loops decreasing agefin until convergence is reached */
1.126 brouard 2454: for(agefin=age-stepm/YEARM; agefin>=age-delaymax; agefin=agefin-stepm/YEARM){
1.202 brouard 2455: ncvloop++;
1.126 brouard 2456: newm=savm;
2457: /* Covariates have to be included here again */
1.138 brouard 2458: cov[2]=agefin;
1.187 brouard 2459: if(nagesqr==1)
2460: cov[3]= agefin*agefin;;
1.234 brouard 2461: for (k=1; k<=nsd;k++) { /* For single dummy covariates only */
2462: /* Here comes the value of the covariate 'ij' after renumbering k with single dummy covariates */
2463: cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,k)];
1.235 brouard 2464: /* 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 2465: }
2466: for (k=1; k<=nsq;k++) { /* For single varying covariates only */
2467: /* Here comes the value of quantitative after renumbering k with single quantitative covariates */
1.235 brouard 2468: cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k];
2469: /* 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 2470: }
1.237 brouard 2471: for (k=1; k<=cptcovage;k++){ /* For product with age */
1.234 brouard 2472: if(Dummy[Tvar[Tage[k]]]){
2473: cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2];
2474: } else{
1.235 brouard 2475: cov[2+nagesqr+Tage[k]]=Tqresult[nres][k];
1.234 brouard 2476: }
1.235 brouard 2477: /* 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 2478: }
1.237 brouard 2479: for (k=1; k<=cptcovprod;k++){ /* For product without age */
1.235 brouard 2480: /* 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 2481: if(Dummy[Tvard[k][1]==0]){
2482: if(Dummy[Tvard[k][2]==0]){
2483: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)];
2484: }else{
2485: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * Tqresult[nres][k];
2486: }
2487: }else{
2488: if(Dummy[Tvard[k][2]==0]){
2489: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][2]][codtabm(ij,k)] * Tqinvresult[nres][Tvard[k][1]];
2490: }else{
2491: cov[2+nagesqr+Tprod[k]]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]];
2492: }
2493: }
1.234 brouard 2494: }
1.138 brouard 2495: /*printf("ij=%d cptcovprod=%d tvar=%d ", ij, cptcovprod, Tvar[1]);*/
2496: /*printf("ij=%d cov[3]=%lf cov[4]=%lf \n",ij, cov[3],cov[4]);*/
2497: /*printf("ij=%d cov[3]=%lf \n",ij, cov[3]);*/
1.145 brouard 2498: /* savm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
2499: /* out=matprod2(newm, pmij(pmmij,cov,ncovmodel,x,nlstate),1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); /\* Bug Valgrind *\/ */
1.218 brouard 2500: /* age and covariate values of ij are in 'cov' */
1.142 brouard 2501: out=matprod2(newm, pmij(pmmij,cov,ncovmodel,x,nlstate),1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); /* Bug Valgrind */
1.138 brouard 2502:
1.126 brouard 2503: savm=oldm;
2504: oldm=newm;
1.209 brouard 2505:
2506: for(j=1; j<=nlstate; j++){
2507: max[j]=0.;
2508: min[j]=1.;
2509: }
2510: for(i=1;i<=nlstate;i++){
2511: sumnew=0;
2512: for(k=1; k<=ndeath; k++) sumnew+=newm[i][nlstate+k];
2513: for(j=1; j<=nlstate; j++){
2514: prlim[i][j]= newm[i][j]/(1-sumnew);
2515: max[j]=FMAX(max[j],prlim[i][j]);
2516: min[j]=FMIN(min[j],prlim[i][j]);
2517: }
2518: }
2519:
1.126 brouard 2520: maxmax=0.;
1.209 brouard 2521: for(j=1; j<=nlstate; j++){
2522: meandiff[j]=(max[j]-min[j])/(max[j]+min[j])*2.; /* mean difference for each column */
2523: maxmax=FMAX(maxmax,meandiff[j]);
2524: /* 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 2525: } /* j loop */
1.203 brouard 2526: *ncvyear= (int)age- (int)agefin;
1.208 brouard 2527: /* 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 2528: if(maxmax < ftolpl){
1.209 brouard 2529: /* printf("maxmax=%lf ncvloop=%ld, age=%d, agefin=%d ncvyear=%d \n", maxmax, ncvloop, (int)age, (int)agefin, *ncvyear); */
2530: free_vector(min,1,nlstate);
2531: free_vector(max,1,nlstate);
2532: free_vector(meandiff,1,nlstate);
1.126 brouard 2533: return prlim;
2534: }
1.169 brouard 2535: } /* age loop */
1.208 brouard 2536: /* After some age loop it doesn't converge */
1.209 brouard 2537: 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 2538: 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 2539: /* 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); */
2540: free_vector(min,1,nlstate);
2541: free_vector(max,1,nlstate);
2542: free_vector(meandiff,1,nlstate);
1.208 brouard 2543:
1.169 brouard 2544: return prlim; /* should not reach here */
1.126 brouard 2545: }
2546:
1.217 brouard 2547:
2548: /**** Back Prevalence limit (stable or period prevalence) ****************/
2549:
1.218 brouard 2550: /* 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) */
2551: /* 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 2552: double **bprevalim(double **bprlim, double ***prevacurrent, int nlstate, double x[], double age, double ftolpl, int *ncvyear, int ij, int nres)
1.217 brouard 2553: {
1.218 brouard 2554: /* Computes the prevalence limit in each live state at age x and covariate ij by left multiplying the unit
1.217 brouard 2555: matrix by transitions matrix until convergence is reached with precision ftolpl */
2556: /* Wx= Wx-1 Px-1= Wx-2 Px-2 Px-1 = Wx-n Px-n ... Px-2 Px-1 I */
2557: /* Wx is row vector: population in state 1, population in state 2, population dead */
2558: /* or prevalence in state 1, prevalence in state 2, 0 */
2559: /* newm is the matrix after multiplications, its rows are identical at a factor */
2560: /* Initial matrix pimij */
2561: /* {0.85204250825084937, 0.13044499163996345, 0.017512500109187184, */
2562: /* 0.090851990222114765, 0.88271245433047185, 0.026435555447413338, */
2563: /* 0, 0 , 1} */
2564: /*
2565: * and after some iteration: */
2566: /* {0.45504275246439968, 0.42731458730878791, 0.11764266022681241, */
2567: /* 0.45201005341706885, 0.42865420071559901, 0.11933574586733192, */
2568: /* 0, 0 , 1} */
2569: /* And prevalence by suppressing the deaths are close to identical rows in prlim: */
2570: /* {0.51571254859325999, 0.4842874514067399, */
2571: /* 0.51326036147820708, 0.48673963852179264} */
2572: /* If we start from prlim again, prlim tends to a constant matrix */
2573:
2574: int i, ii,j,k;
2575: double *min, *max, *meandiff, maxmax,sumnew=0.;
2576: /* double **matprod2(); */ /* test */
2577: double **out, cov[NCOVMAX+1], **bmij();
2578: double **newm;
1.218 brouard 2579: double **dnewm, **doldm, **dsavm; /* for use */
2580: double **oldm, **savm; /* for use */
2581:
1.217 brouard 2582: double agefin, delaymax=200. ; /* 100 Max number of years to converge */
2583: int ncvloop=0;
2584:
2585: min=vector(1,nlstate);
2586: max=vector(1,nlstate);
2587: meandiff=vector(1,nlstate);
2588:
1.218 brouard 2589: dnewm=ddnewms; doldm=ddoldms; dsavm=ddsavms;
2590: oldm=oldms; savm=savms;
2591:
2592: /* Starting with matrix unity */
2593: for (ii=1;ii<=nlstate+ndeath;ii++)
2594: for (j=1;j<=nlstate+ndeath;j++){
1.217 brouard 2595: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
2596: }
2597:
2598: cov[1]=1.;
2599:
2600: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
2601: /* Start at agefin= age, computes the matrix of passage and loops decreasing agefin until convergence is reached */
1.218 brouard 2602: /* for(agefin=age+stepm/YEARM; agefin<=age+delaymax; agefin=agefin+stepm/YEARM){ /\* A changer en age *\/ */
2603: for(agefin=age; agefin<AGESUP; agefin=agefin+stepm/YEARM){ /* A changer en age */
1.217 brouard 2604: ncvloop++;
1.218 brouard 2605: newm=savm; /* oldm should be kept from previous iteration or unity at start */
2606: /* newm points to the allocated table savm passed by the function it can be written, savm could be reallocated */
1.217 brouard 2607: /* Covariates have to be included here again */
2608: cov[2]=agefin;
2609: if(nagesqr==1)
2610: cov[3]= agefin*agefin;;
1.242 brouard 2611: for (k=1; k<=nsd;k++) { /* For single dummy covariates only */
2612: /* Here comes the value of the covariate 'ij' after renumbering k with single dummy covariates */
2613: cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,k)];
2614: /* printf("bprevalim 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)); */
2615: }
2616: /* for (k=1; k<=cptcovn;k++) { */
2617: /* /\* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,Tvar[k])]; *\/ */
2618: /* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,k)]; */
2619: /* /\* 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])]); *\/ */
2620: /* } */
2621: for (k=1; k<=nsq;k++) { /* For single varying covariates only */
2622: /* Here comes the value of quantitative after renumbering k with single quantitative covariates */
2623: cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k];
2624: /* 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]); */
2625: }
2626: /* for (k=1; k<=cptcovage;k++) cov[2+nagesqr+Tage[k]]=nbcode[Tvar[k]][codtabm(ij,k)]*cov[2]; */
2627: /* for (k=1; k<=cptcovprod;k++) /\* Useless *\/ */
2628: /* /\* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])]; *\/ */
2629: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)]; */
2630: for (k=1; k<=cptcovage;k++){ /* For product with age */
2631: if(Dummy[Tvar[Tage[k]]]){
2632: cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2];
2633: } else{
2634: cov[2+nagesqr+Tage[k]]=Tqresult[nres][k];
2635: }
2636: /* 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]); */
2637: }
2638: for (k=1; k<=cptcovprod;k++){ /* For product without age */
2639: /* 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]); */
2640: if(Dummy[Tvard[k][1]==0]){
2641: if(Dummy[Tvard[k][2]==0]){
2642: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)];
2643: }else{
2644: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * Tqresult[nres][k];
2645: }
2646: }else{
2647: if(Dummy[Tvard[k][2]==0]){
2648: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][2]][codtabm(ij,k)] * Tqinvresult[nres][Tvard[k][1]];
2649: }else{
2650: cov[2+nagesqr+Tprod[k]]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]];
2651: }
2652: }
1.217 brouard 2653: }
2654:
2655: /*printf("ij=%d cptcovprod=%d tvar=%d ", ij, cptcovprod, Tvar[1]);*/
2656: /*printf("ij=%d cov[3]=%lf cov[4]=%lf \n",ij, cov[3],cov[4]);*/
2657: /*printf("ij=%d cov[3]=%lf \n",ij, cov[3]);*/
2658: /* savm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
2659: /* out=matprod2(newm, pmij(pmmij,cov,ncovmodel,x,nlstate),1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); /\* Bug Valgrind *\/ */
1.218 brouard 2660: /* ij should be linked to the correct index of cov */
2661: /* age and covariate values ij are in 'cov', but we need to pass
2662: * ij for the observed prevalence at age and status and covariate
2663: * number: prevacurrent[(int)agefin][ii][ij]
2664: */
2665: /* 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 *\/ */
2666: /* 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 *\/ */
2667: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, bmij(pmmij,cov,ncovmodel,x,nlstate,prevacurrent,ij)); /* Bug Valgrind */
1.217 brouard 2668: savm=oldm;
2669: oldm=newm;
2670: for(j=1; j<=nlstate; j++){
2671: max[j]=0.;
2672: min[j]=1.;
2673: }
2674: for(j=1; j<=nlstate; j++){
2675: for(i=1;i<=nlstate;i++){
1.234 brouard 2676: /* bprlim[i][j]= newm[i][j]/(1-sumnew); */
2677: bprlim[i][j]= newm[i][j];
2678: max[i]=FMAX(max[i],bprlim[i][j]); /* Max in line */
2679: min[i]=FMIN(min[i],bprlim[i][j]);
1.217 brouard 2680: }
2681: }
1.218 brouard 2682:
1.217 brouard 2683: maxmax=0.;
2684: for(i=1; i<=nlstate; i++){
2685: meandiff[i]=(max[i]-min[i])/(max[i]+min[i])*2.; /* mean difference for each column */
2686: maxmax=FMAX(maxmax,meandiff[i]);
2687: /* 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); */
2688: } /* j loop */
2689: *ncvyear= -( (int)age- (int)agefin);
1.218 brouard 2690: /* printf("Back maxmax=%lf ncvloop=%d, age=%d, agefin=%d ncvyear=%d \n", maxmax, ncvloop, (int)age, (int)agefin, *ncvyear);*/
1.217 brouard 2691: if(maxmax < ftolpl){
1.220 brouard 2692: /* printf("OK Back maxmax=%lf ncvloop=%d, age=%d, agefin=%d ncvyear=%d \n", maxmax, ncvloop, (int)age, (int)agefin, *ncvyear); */
1.217 brouard 2693: free_vector(min,1,nlstate);
2694: free_vector(max,1,nlstate);
2695: free_vector(meandiff,1,nlstate);
2696: return bprlim;
2697: }
2698: } /* age loop */
2699: /* After some age loop it doesn't converge */
2700: 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'. \n\
2701: 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);
2702: /* 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); */
2703: free_vector(min,1,nlstate);
2704: free_vector(max,1,nlstate);
2705: free_vector(meandiff,1,nlstate);
2706:
2707: return bprlim; /* should not reach here */
2708: }
2709:
1.126 brouard 2710: /*************** transition probabilities ***************/
2711:
2712: double **pmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate )
2713: {
1.138 brouard 2714: /* According to parameters values stored in x and the covariate's values stored in cov,
2715: computes the probability to be observed in state j being in state i by appying the
2716: model to the ncovmodel covariates (including constant and age).
2717: lnpijopii=ln(pij/pii)= aij+bij*age+cij*v1+dij*v2+... = sum_nc=1^ncovmodel xij(nc)*cov[nc]
2718: and, according on how parameters are entered, the position of the coefficient xij(nc) of the
2719: ncth covariate in the global vector x is given by the formula:
2720: j<i nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel
2721: j>=i nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel
2722: Computes ln(pij/pii) (lnpijopii), deduces pij/pii by exponentiation,
2723: sums on j different of i to get 1-pii/pii, deduces pii, and then all pij.
2724: Outputs ps[i][j] the probability to be observed in j being in j according to
2725: the values of the covariates cov[nc] and corresponding parameter values x[nc+shiftij]
2726: */
2727: double s1, lnpijopii;
1.126 brouard 2728: /*double t34;*/
1.164 brouard 2729: int i,j, nc, ii, jj;
1.126 brouard 2730:
1.223 brouard 2731: for(i=1; i<= nlstate; i++){
2732: for(j=1; j<i;j++){
2733: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
2734: /*lnpijopii += param[i][j][nc]*cov[nc];*/
2735: lnpijopii += x[nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel]*cov[nc];
2736: /* printf("Int j<i s1=%.17e, lnpijopii=%.17e\n",s1,lnpijopii); */
2737: }
2738: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
2739: /* printf("s1=%.17e, lnpijopii=%.17e\n",s1,lnpijopii); */
2740: }
2741: for(j=i+1; j<=nlstate+ndeath;j++){
2742: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
2743: /*lnpijopii += x[(i-1)*nlstate*ncovmodel+(j-2)*ncovmodel+nc+(i-1)*(ndeath-1)*ncovmodel]*cov[nc];*/
2744: lnpijopii += x[nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel]*cov[nc];
2745: /* printf("Int j>i s1=%.17e, lnpijopii=%.17e %lx %lx\n",s1,lnpijopii,s1,lnpijopii); */
2746: }
2747: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
2748: }
2749: }
1.218 brouard 2750:
1.223 brouard 2751: for(i=1; i<= nlstate; i++){
2752: s1=0;
2753: for(j=1; j<i; j++){
2754: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
2755: /*printf("debug1 %d %d ps=%lf exp(ps)=%lf s1+=%lf\n",i,j,ps[i][j],exp(ps[i][j]),s1); */
2756: }
2757: for(j=i+1; j<=nlstate+ndeath; j++){
2758: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
2759: /*printf("debug2 %d %d ps=%lf exp(ps)=%lf s1+=%lf\n",i,j,ps[i][j],exp(ps[i][j]),s1); */
2760: }
2761: /* s1= sum_{j<>i} pij/pii=(1-pii)/pii and thus pii is known from s1 */
2762: ps[i][i]=1./(s1+1.);
2763: /* Computing other pijs */
2764: for(j=1; j<i; j++)
2765: ps[i][j]= exp(ps[i][j])*ps[i][i];
2766: for(j=i+1; j<=nlstate+ndeath; j++)
2767: ps[i][j]= exp(ps[i][j])*ps[i][i];
2768: /* ps[i][nlstate+1]=1.-s1- ps[i][i];*/ /* Sum should be 1 */
2769: } /* end i */
1.218 brouard 2770:
1.223 brouard 2771: for(ii=nlstate+1; ii<= nlstate+ndeath; ii++){
2772: for(jj=1; jj<= nlstate+ndeath; jj++){
2773: ps[ii][jj]=0;
2774: ps[ii][ii]=1;
2775: }
2776: }
1.218 brouard 2777:
2778:
1.223 brouard 2779: /* for(ii=1; ii<= nlstate+ndeath; ii++){ */
2780: /* for(jj=1; jj<= nlstate+ndeath; jj++){ */
2781: /* printf(" pmij ps[%d][%d]=%lf ",ii,jj,ps[ii][jj]); */
2782: /* } */
2783: /* printf("\n "); */
2784: /* } */
2785: /* printf("\n ");printf("%lf ",cov[2]);*/
2786: /*
2787: for(i=1; i<= npar; i++) printf("%f ",x[i]);
1.218 brouard 2788: goto end;*/
1.223 brouard 2789: return ps;
1.126 brouard 2790: }
2791:
1.218 brouard 2792: /*************** backward transition probabilities ***************/
2793:
2794: /* 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 ) */
2795: /* double **bmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate, double ***prevacurrent, double ***dnewm, double **doldm, double **dsavm, int ij ) */
2796: double **bmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate, double ***prevacurrent, int ij )
2797: {
1.222 brouard 2798: /* Computes the backward probability at age agefin and covariate ij
2799: * and returns in **ps as well as **bmij.
2800: */
1.218 brouard 2801: int i, ii, j,k;
1.222 brouard 2802:
2803: double **out, **pmij();
2804: double sumnew=0.;
1.218 brouard 2805: double agefin;
1.222 brouard 2806:
2807: double **dnewm, **dsavm, **doldm;
2808: double **bbmij;
2809:
1.218 brouard 2810: doldm=ddoldms; /* global pointers */
1.222 brouard 2811: dnewm=ddnewms;
2812: dsavm=ddsavms;
2813:
2814: agefin=cov[2];
2815: /* bmij *//* age is cov[2], ij is included in cov, but we need for
2816: the observed prevalence (with this covariate ij) */
2817: dsavm=pmij(pmmij,cov,ncovmodel,x,nlstate);
2818: /* We do have the matrix Px in savm and we need pij */
2819: for (j=1;j<=nlstate+ndeath;j++){
2820: sumnew=0.; /* w1 p11 + w2 p21 only on live states */
2821: for (ii=1;ii<=nlstate;ii++){
2822: sumnew+=dsavm[ii][j]*prevacurrent[(int)agefin][ii][ij];
2823: } /* sumnew is (N11+N21)/N..= N.1/N.. = sum on i of w_i pij */
2824: for (ii=1;ii<=nlstate+ndeath;ii++){
2825: if(sumnew >= 1.e-10){
2826: /* if(agefin >= agemaxpar && agefin <= agemaxpar+stepm/YEARM){ */
2827: /* doldm[ii][j]=(ii==j ? 1./sumnew : 0.0); */
2828: /* }else if(agefin >= agemaxpar+stepm/YEARM){ */
2829: /* doldm[ii][j]=(ii==j ? 1./sumnew : 0.0); */
2830: /* }else */
2831: doldm[ii][j]=(ii==j ? 1./sumnew : 0.0);
2832: }else{
1.242 brouard 2833: ;
2834: /* printf("ii=%d, i=%d, doldm=%lf dsavm=%lf, probs=%lf, sumnew=%lf,agefin=%d\n",ii,j,doldm[ii][j],dsavm[ii][j],prevacurrent[(int)agefin][ii][ij],sumnew, (int)agefin); */
1.222 brouard 2835: }
2836: } /*End ii */
2837: } /* End j, At the end doldm is diag[1/(w_1p1i+w_2 p2i)] */
2838: /* left Product of this diag matrix by dsavm=Px (newm=dsavm*doldm) */
2839: bbmij=matprod2(dnewm, dsavm,1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, doldm); /* Bug Valgrind */
2840: /* dsavm=doldm; /\* dsavm is now diag [1/(w_1p1i+w_2 p2i)] but can be overwritten*\/ */
2841: /* doldm=dnewm; /\* doldm is now Px * diag [1/(w_1p1i+w_2 p2i)] *\/ */
2842: /* dnewm=dsavm; /\* doldm is now Px * diag [1/(w_1p1i+w_2 p2i)] *\/ */
2843: /* left Product of this matrix by diag matrix of prevalences (savm) */
2844: for (j=1;j<=nlstate+ndeath;j++){
2845: for (ii=1;ii<=nlstate+ndeath;ii++){
2846: dsavm[ii][j]=(ii==j ? prevacurrent[(int)agefin][ii][ij] : 0.0);
2847: }
2848: } /* End j, At the end oldm is diag[1/(w_1p1i+w_2 p2i)] */
2849: ps=matprod2(doldm, dsavm,1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, dnewm); /* Bug Valgrind */
2850: /* newm or out is now diag[w_i] * Px * diag [1/(w_1p1i+w_2 p2i)] */
2851: /* end bmij */
2852: return ps;
1.218 brouard 2853: }
1.217 brouard 2854: /*************** transition probabilities ***************/
2855:
1.218 brouard 2856: double **bpmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate )
1.217 brouard 2857: {
2858: /* According to parameters values stored in x and the covariate's values stored in cov,
2859: computes the probability to be observed in state j being in state i by appying the
2860: model to the ncovmodel covariates (including constant and age).
2861: lnpijopii=ln(pij/pii)= aij+bij*age+cij*v1+dij*v2+... = sum_nc=1^ncovmodel xij(nc)*cov[nc]
2862: and, according on how parameters are entered, the position of the coefficient xij(nc) of the
2863: ncth covariate in the global vector x is given by the formula:
2864: j<i nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel
2865: j>=i nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel
2866: Computes ln(pij/pii) (lnpijopii), deduces pij/pii by exponentiation,
2867: sums on j different of i to get 1-pii/pii, deduces pii, and then all pij.
2868: Outputs ps[i][j] the probability to be observed in j being in j according to
2869: the values of the covariates cov[nc] and corresponding parameter values x[nc+shiftij]
2870: */
2871: double s1, lnpijopii;
2872: /*double t34;*/
2873: int i,j, nc, ii, jj;
2874:
1.234 brouard 2875: for(i=1; i<= nlstate; i++){
2876: for(j=1; j<i;j++){
2877: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
2878: /*lnpijopii += param[i][j][nc]*cov[nc];*/
2879: lnpijopii += x[nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel]*cov[nc];
2880: /* printf("Int j<i s1=%.17e, lnpijopii=%.17e\n",s1,lnpijopii); */
2881: }
2882: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
2883: /* printf("s1=%.17e, lnpijopii=%.17e\n",s1,lnpijopii); */
2884: }
2885: for(j=i+1; j<=nlstate+ndeath;j++){
2886: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
2887: /*lnpijopii += x[(i-1)*nlstate*ncovmodel+(j-2)*ncovmodel+nc+(i-1)*(ndeath-1)*ncovmodel]*cov[nc];*/
2888: lnpijopii += x[nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel]*cov[nc];
2889: /* printf("Int j>i s1=%.17e, lnpijopii=%.17e %lx %lx\n",s1,lnpijopii,s1,lnpijopii); */
2890: }
2891: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
2892: }
2893: }
2894:
2895: for(i=1; i<= nlstate; i++){
2896: s1=0;
2897: for(j=1; j<i; j++){
2898: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
2899: /*printf("debug1 %d %d ps=%lf exp(ps)=%lf s1+=%lf\n",i,j,ps[i][j],exp(ps[i][j]),s1); */
2900: }
2901: for(j=i+1; j<=nlstate+ndeath; j++){
2902: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
2903: /*printf("debug2 %d %d ps=%lf exp(ps)=%lf s1+=%lf\n",i,j,ps[i][j],exp(ps[i][j]),s1); */
2904: }
2905: /* s1= sum_{j<>i} pij/pii=(1-pii)/pii and thus pii is known from s1 */
2906: ps[i][i]=1./(s1+1.);
2907: /* Computing other pijs */
2908: for(j=1; j<i; j++)
2909: ps[i][j]= exp(ps[i][j])*ps[i][i];
2910: for(j=i+1; j<=nlstate+ndeath; j++)
2911: ps[i][j]= exp(ps[i][j])*ps[i][i];
2912: /* ps[i][nlstate+1]=1.-s1- ps[i][i];*/ /* Sum should be 1 */
2913: } /* end i */
2914:
2915: for(ii=nlstate+1; ii<= nlstate+ndeath; ii++){
2916: for(jj=1; jj<= nlstate+ndeath; jj++){
2917: ps[ii][jj]=0;
2918: ps[ii][ii]=1;
2919: }
2920: }
2921: /* Added for backcast */ /* Transposed matrix too */
2922: for(jj=1; jj<= nlstate+ndeath; jj++){
2923: s1=0.;
2924: for(ii=1; ii<= nlstate+ndeath; ii++){
2925: s1+=ps[ii][jj];
2926: }
2927: for(ii=1; ii<= nlstate; ii++){
2928: ps[ii][jj]=ps[ii][jj]/s1;
2929: }
2930: }
2931: /* Transposition */
2932: for(jj=1; jj<= nlstate+ndeath; jj++){
2933: for(ii=jj; ii<= nlstate+ndeath; ii++){
2934: s1=ps[ii][jj];
2935: ps[ii][jj]=ps[jj][ii];
2936: ps[jj][ii]=s1;
2937: }
2938: }
2939: /* for(ii=1; ii<= nlstate+ndeath; ii++){ */
2940: /* for(jj=1; jj<= nlstate+ndeath; jj++){ */
2941: /* printf(" pmij ps[%d][%d]=%lf ",ii,jj,ps[ii][jj]); */
2942: /* } */
2943: /* printf("\n "); */
2944: /* } */
2945: /* printf("\n ");printf("%lf ",cov[2]);*/
2946: /*
2947: for(i=1; i<= npar; i++) printf("%f ",x[i]);
2948: goto end;*/
2949: return ps;
1.217 brouard 2950: }
2951:
2952:
1.126 brouard 2953: /**************** Product of 2 matrices ******************/
2954:
1.145 brouard 2955: double **matprod2(double **out, double **in,int nrl, int nrh, int ncl, int nch, int ncolol, int ncoloh, double **b)
1.126 brouard 2956: {
2957: /* Computes the matrix product of in(1,nrh-nrl+1)(1,nch-ncl+1) times
2958: b(1,nch-ncl+1)(1,ncoloh-ncolol+1) into out(...) */
2959: /* in, b, out are matrice of pointers which should have been initialized
2960: before: only the contents of out is modified. The function returns
2961: a pointer to pointers identical to out */
1.145 brouard 2962: int i, j, k;
1.126 brouard 2963: for(i=nrl; i<= nrh; i++)
1.145 brouard 2964: for(k=ncolol; k<=ncoloh; k++){
2965: out[i][k]=0.;
2966: for(j=ncl; j<=nch; j++)
2967: out[i][k] +=in[i][j]*b[j][k];
2968: }
1.126 brouard 2969: return out;
2970: }
2971:
2972:
2973: /************* Higher Matrix Product ***************/
2974:
1.235 brouard 2975: 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 2976: {
1.218 brouard 2977: /* Computes the transition matrix starting at age 'age' and combination of covariate values corresponding to ij over
1.126 brouard 2978: 'nhstepm*hstepm*stepm' months (i.e. until
2979: age (in years) age+nhstepm*hstepm*stepm/12) by multiplying
2980: nhstepm*hstepm matrices.
2981: Output is stored in matrix po[i][j][h] for h every 'hstepm' step
2982: (typically every 2 years instead of every month which is too big
2983: for the memory).
2984: Model is determined by parameters x and covariates have to be
2985: included manually here.
2986:
2987: */
2988:
2989: int i, j, d, h, k;
1.131 brouard 2990: double **out, cov[NCOVMAX+1];
1.126 brouard 2991: double **newm;
1.187 brouard 2992: double agexact;
1.214 brouard 2993: double agebegin, ageend;
1.126 brouard 2994:
2995: /* Hstepm could be zero and should return the unit matrix */
2996: for (i=1;i<=nlstate+ndeath;i++)
2997: for (j=1;j<=nlstate+ndeath;j++){
2998: oldm[i][j]=(i==j ? 1.0 : 0.0);
2999: po[i][j][0]=(i==j ? 1.0 : 0.0);
3000: }
3001: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
3002: for(h=1; h <=nhstepm; h++){
3003: for(d=1; d <=hstepm; d++){
3004: newm=savm;
3005: /* Covariates have to be included here again */
3006: cov[1]=1.;
1.214 brouard 3007: agexact=age+((h-1)*hstepm + (d-1))*stepm/YEARM; /* age just before transition */
1.187 brouard 3008: cov[2]=agexact;
3009: if(nagesqr==1)
1.227 brouard 3010: cov[3]= agexact*agexact;
1.235 brouard 3011: for (k=1; k<=nsd;k++) { /* For single dummy covariates only */
3012: /* Here comes the value of the covariate 'ij' after renumbering k with single dummy covariates */
3013: cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,k)];
3014: /* 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)); */
3015: }
3016: for (k=1; k<=nsq;k++) { /* For single varying covariates only */
3017: /* Here comes the value of quantitative after renumbering k with single quantitative covariates */
3018: cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k];
3019: /* 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]); */
3020: }
3021: for (k=1; k<=cptcovage;k++){
3022: if(Dummy[Tvar[Tage[k]]]){
3023: cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2];
3024: } else{
3025: cov[2+nagesqr+Tage[k]]=Tqresult[nres][k];
3026: }
3027: /* 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]); */
3028: }
3029: for (k=1; k<=cptcovprod;k++){ /* */
3030: /* 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]); */
3031: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)];
3032: }
3033: /* for (k=1; k<=cptcovn;k++) */
3034: /* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,k)]; */
3035: /* for (k=1; k<=cptcovage;k++) /\* Should start at cptcovn+1 *\/ */
3036: /* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2]; */
3037: /* for (k=1; k<=cptcovprod;k++) /\* Useless because included in cptcovn *\/ */
3038: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)]*nbcode[Tvard[k][2]][codtabm(ij,k)]; */
1.227 brouard 3039:
3040:
1.126 brouard 3041: /*printf("hxi cptcov=%d cptcode=%d\n",cptcov,cptcode);*/
3042: /*printf("h=%d d=%d age=%f cov=%f\n",h,d,age,cov[2]);*/
1.218 brouard 3043: /* right multiplication of oldm by the current matrix */
1.126 brouard 3044: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath,
3045: pmij(pmmij,cov,ncovmodel,x,nlstate));
1.217 brouard 3046: /* if((int)age == 70){ */
3047: /* printf(" Forward hpxij age=%d agexact=%f d=%d nhstepm=%d hstepm=%d\n", (int) age, agexact, d, nhstepm, hstepm); */
3048: /* for(i=1; i<=nlstate+ndeath; i++) { */
3049: /* printf("%d pmmij ",i); */
3050: /* for(j=1;j<=nlstate+ndeath;j++) { */
3051: /* printf("%f ",pmmij[i][j]); */
3052: /* } */
3053: /* printf(" oldm "); */
3054: /* for(j=1;j<=nlstate+ndeath;j++) { */
3055: /* printf("%f ",oldm[i][j]); */
3056: /* } */
3057: /* printf("\n"); */
3058: /* } */
3059: /* } */
1.126 brouard 3060: savm=oldm;
3061: oldm=newm;
3062: }
3063: for(i=1; i<=nlstate+ndeath; i++)
3064: for(j=1;j<=nlstate+ndeath;j++) {
1.218 brouard 3065: po[i][j][h]=newm[i][j];
3066: /*if(h==nhstepm) printf("po[%d][%d][%d]=%f ",i,j,h,po[i][j][h]);*/
1.126 brouard 3067: }
1.128 brouard 3068: /*printf("h=%d ",h);*/
1.126 brouard 3069: } /* end h */
1.218 brouard 3070: /* printf("\n H=%d \n",h); */
1.126 brouard 3071: return po;
3072: }
3073:
1.217 brouard 3074: /************* Higher Back Matrix Product ***************/
1.218 brouard 3075: /* double ***hbxij(double ***po, int nhstepm, double age, int hstepm, double *x, double ***prevacurrent, int nlstate, int stepm, double **oldm, double **savm, double **dnewm, double **doldm, double **dsavm, int ij ) */
1.222 brouard 3076: double ***hbxij(double ***po, int nhstepm, double age, int hstepm, double *x, double ***prevacurrent, int nlstate, int stepm, int ij )
1.217 brouard 3077: {
1.218 brouard 3078: /* Computes the transition matrix starting at age 'age' over
1.217 brouard 3079: 'nhstepm*hstepm*stepm' months (i.e. until
1.218 brouard 3080: age (in years) age+nhstepm*hstepm*stepm/12) by multiplying
3081: nhstepm*hstepm matrices.
3082: Output is stored in matrix po[i][j][h] for h every 'hstepm' step
3083: (typically every 2 years instead of every month which is too big
1.217 brouard 3084: for the memory).
1.218 brouard 3085: Model is determined by parameters x and covariates have to be
3086: included manually here.
1.217 brouard 3087:
1.222 brouard 3088: */
1.217 brouard 3089:
3090: int i, j, d, h, k;
3091: double **out, cov[NCOVMAX+1];
3092: double **newm;
3093: double agexact;
3094: double agebegin, ageend;
1.222 brouard 3095: double **oldm, **savm;
1.217 brouard 3096:
1.222 brouard 3097: oldm=oldms;savm=savms;
1.217 brouard 3098: /* Hstepm could be zero and should return the unit matrix */
3099: for (i=1;i<=nlstate+ndeath;i++)
3100: for (j=1;j<=nlstate+ndeath;j++){
3101: oldm[i][j]=(i==j ? 1.0 : 0.0);
3102: po[i][j][0]=(i==j ? 1.0 : 0.0);
3103: }
3104: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
3105: for(h=1; h <=nhstepm; h++){
3106: for(d=1; d <=hstepm; d++){
3107: newm=savm;
3108: /* Covariates have to be included here again */
3109: cov[1]=1.;
3110: agexact=age-((h-1)*hstepm + (d-1))*stepm/YEARM; /* age just before transition */
3111: /* agexact=age+((h-1)*hstepm + (d-1))*stepm/YEARM; /\* age just before transition *\/ */
3112: cov[2]=agexact;
3113: if(nagesqr==1)
1.222 brouard 3114: cov[3]= agexact*agexact;
1.218 brouard 3115: for (k=1; k<=cptcovn;k++)
1.222 brouard 3116: cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,k)];
3117: /* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,Tvar[k])]; */
1.217 brouard 3118: for (k=1; k<=cptcovage;k++) /* Should start at cptcovn+1 */
1.222 brouard 3119: /* cov[2+Tage[k]]=cov[2+Tage[k]]*cov[2]; */
3120: cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2];
3121: /* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,Tvar[Tage[k]])]*cov[2]; */
1.217 brouard 3122: for (k=1; k<=cptcovprod;k++) /* Useless because included in cptcovn */
1.222 brouard 3123: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)]*nbcode[Tvard[k][2]][codtabm(ij,k)];
3124: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])]*nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])]; */
1.218 brouard 3125:
3126:
1.217 brouard 3127: /*printf("hxi cptcov=%d cptcode=%d\n",cptcov,cptcode);*/
3128: /*printf("h=%d d=%d age=%f cov=%f\n",h,d,age,cov[2]);*/
1.218 brouard 3129: /* Careful transposed matrix */
1.222 brouard 3130: /* age is in cov[2] */
1.218 brouard 3131: /* out=matprod2(newm, bmij(pmmij,cov,ncovmodel,x,nlstate,prevacurrent, dnewm, doldm, dsavm,ij),\ */
1.222 brouard 3132: /* 1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); */
1.218 brouard 3133: out=matprod2(newm, bmij(pmmij,cov,ncovmodel,x,nlstate,prevacurrent,ij),\
1.222 brouard 3134: 1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm);
1.217 brouard 3135: /* if((int)age == 70){ */
3136: /* printf(" Backward hbxij age=%d agexact=%f d=%d nhstepm=%d hstepm=%d\n", (int) age, agexact, d, nhstepm, hstepm); */
3137: /* for(i=1; i<=nlstate+ndeath; i++) { */
3138: /* printf("%d pmmij ",i); */
3139: /* for(j=1;j<=nlstate+ndeath;j++) { */
3140: /* printf("%f ",pmmij[i][j]); */
3141: /* } */
3142: /* printf(" oldm "); */
3143: /* for(j=1;j<=nlstate+ndeath;j++) { */
3144: /* printf("%f ",oldm[i][j]); */
3145: /* } */
3146: /* printf("\n"); */
3147: /* } */
3148: /* } */
3149: savm=oldm;
3150: oldm=newm;
3151: }
3152: for(i=1; i<=nlstate+ndeath; i++)
3153: for(j=1;j<=nlstate+ndeath;j++) {
1.222 brouard 3154: po[i][j][h]=newm[i][j];
3155: /*if(h==nhstepm) printf("po[%d][%d][%d]=%f ",i,j,h,po[i][j][h]);*/
1.217 brouard 3156: }
3157: /*printf("h=%d ",h);*/
3158: } /* end h */
1.222 brouard 3159: /* printf("\n H=%d \n",h); */
1.217 brouard 3160: return po;
3161: }
3162:
3163:
1.162 brouard 3164: #ifdef NLOPT
3165: double myfunc(unsigned n, const double *p1, double *grad, void *pd){
3166: double fret;
3167: double *xt;
3168: int j;
3169: myfunc_data *d2 = (myfunc_data *) pd;
3170: /* xt = (p1-1); */
3171: xt=vector(1,n);
3172: for (j=1;j<=n;j++) xt[j]=p1[j-1]; /* xt[1]=p1[0] */
3173:
3174: fret=(d2->function)(xt); /* p xt[1]@8 is fine */
3175: /* fret=(*func)(xt); /\* p xt[1]@8 is fine *\/ */
3176: printf("Function = %.12lf ",fret);
3177: for (j=1;j<=n;j++) printf(" %d %.8lf", j, xt[j]);
3178: printf("\n");
3179: free_vector(xt,1,n);
3180: return fret;
3181: }
3182: #endif
1.126 brouard 3183:
3184: /*************** log-likelihood *************/
3185: double func( double *x)
3186: {
1.226 brouard 3187: int i, ii, j, k, mi, d, kk;
3188: int ioffset=0;
3189: double l, ll[NLSTATEMAX+1], cov[NCOVMAX+1];
3190: double **out;
3191: double lli; /* Individual log likelihood */
3192: int s1, s2;
1.228 brouard 3193: 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 3194: double bbh, survp;
3195: long ipmx;
3196: double agexact;
3197: /*extern weight */
3198: /* We are differentiating ll according to initial status */
3199: /* for (i=1;i<=npar;i++) printf("%f ", x[i]);*/
3200: /*for(i=1;i<imx;i++)
3201: printf(" %d\n",s[4][i]);
3202: */
1.162 brouard 3203:
1.226 brouard 3204: ++countcallfunc;
1.162 brouard 3205:
1.226 brouard 3206: cov[1]=1.;
1.126 brouard 3207:
1.226 brouard 3208: for(k=1; k<=nlstate; k++) ll[k]=0.;
1.224 brouard 3209: ioffset=0;
1.226 brouard 3210: if(mle==1){
3211: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
3212: /* Computes the values of the ncovmodel covariates of the model
3213: depending if the covariates are fixed or varying (age dependent) and stores them in cov[]
3214: Then computes with function pmij which return a matrix p[i][j] giving the elementary probability
3215: to be observed in j being in i according to the model.
3216: */
1.243 ! brouard 3217: ioffset=2+nagesqr ;
1.233 brouard 3218: /* Fixed */
1.234 brouard 3219: for (k=1; k<=ncovf;k++){ /* Simple and product fixed covariates without age* products */
3220: 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)*/
3221: }
1.226 brouard 3222: /* In model V2+V1*V4+age*V3+V3*V2 Tvar[1] is V2, Tvar[2=V1*V4]
3223: is 6, Tvar[3=age*V3] should not be computed because of age Tvar[4=V3*V2]
3224: has been calculated etc */
3225: /* For an individual i, wav[i] gives the number of effective waves */
3226: /* We compute the contribution to Likelihood of each effective transition
3227: mw[mi][i] is real wave of the mi th effectve wave */
3228: /* Then statuses are computed at each begin and end of an effective wave s1=s[ mw[mi][i] ][i];
3229: s2=s[mw[mi+1][i]][i];
3230: And the iv th varying covariate is the cotvar[mw[mi+1][i]][iv][i]
3231: But if the variable is not in the model TTvar[iv] is the real variable effective in the model:
3232: meaning that decodemodel should be used cotvar[mw[mi+1][i]][TTvar[iv]][i]
3233: */
3234: for(mi=1; mi<= wav[i]-1; mi++){
1.234 brouard 3235: for(k=1; k <= ncovv ; k++){ /* Varying covariates (single and product but no age )*/
1.242 brouard 3236: /* cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]][i]; */
3237: cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]-ncovcol-nqv][i];
1.234 brouard 3238: }
3239: for (ii=1;ii<=nlstate+ndeath;ii++)
3240: for (j=1;j<=nlstate+ndeath;j++){
3241: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
3242: savm[ii][j]=(ii==j ? 1.0 : 0.0);
3243: }
3244: for(d=0; d<dh[mi][i]; d++){
3245: newm=savm;
3246: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
3247: cov[2]=agexact;
3248: if(nagesqr==1)
3249: cov[3]= agexact*agexact; /* Should be changed here */
3250: for (kk=1; kk<=cptcovage;kk++) {
1.242 brouard 3251: if(!FixedV[Tvar[Tage[kk]]])
1.234 brouard 3252: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact; /* Tage[kk] gives the data-covariate associated with age */
1.242 brouard 3253: else
3254: cov[Tage[kk]+2+nagesqr]=cotvar[mw[mi][i]][Tvar[Tage[kk]]-ncovcol-nqv][i]*agexact;
1.234 brouard 3255: }
3256: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
3257: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
3258: savm=oldm;
3259: oldm=newm;
3260: } /* end mult */
3261:
3262: /*lli=log(out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]);*/ /* Original formula */
3263: /* But now since version 0.9 we anticipate for bias at large stepm.
3264: * If stepm is larger than one month (smallest stepm) and if the exact delay
3265: * (in months) between two waves is not a multiple of stepm, we rounded to
3266: * the nearest (and in case of equal distance, to the lowest) interval but now
3267: * we keep into memory the bias bh[mi][i] and also the previous matrix product
3268: * (i.e to dh[mi][i]-1) saved in 'savm'. Then we inter(extra)polate the
3269: * probability in order to take into account the bias as a fraction of the way
1.231 brouard 3270: * from savm to out if bh is negative or even beyond if bh is positive. bh varies
3271: * -stepm/2 to stepm/2 .
3272: * For stepm=1 the results are the same as for previous versions of Imach.
3273: * For stepm > 1 the results are less biased than in previous versions.
3274: */
1.234 brouard 3275: s1=s[mw[mi][i]][i];
3276: s2=s[mw[mi+1][i]][i];
3277: bbh=(double)bh[mi][i]/(double)stepm;
3278: /* bias bh is positive if real duration
3279: * is higher than the multiple of stepm and negative otherwise.
3280: */
3281: /* lli= (savm[s1][s2]>1.e-8 ?(1.+bbh)*log(out[s1][s2])- bbh*log(savm[s1][s2]):log((1.+bbh)*out[s1][s2]));*/
3282: if( s2 > nlstate){
3283: /* i.e. if s2 is a death state and if the date of death is known
3284: then the contribution to the likelihood is the probability to
3285: die between last step unit time and current step unit time,
3286: which is also equal to probability to die before dh
3287: minus probability to die before dh-stepm .
3288: In version up to 0.92 likelihood was computed
3289: as if date of death was unknown. Death was treated as any other
3290: health state: the date of the interview describes the actual state
3291: and not the date of a change in health state. The former idea was
3292: to consider that at each interview the state was recorded
3293: (healthy, disable or death) and IMaCh was corrected; but when we
3294: introduced the exact date of death then we should have modified
3295: the contribution of an exact death to the likelihood. This new
3296: contribution is smaller and very dependent of the step unit
3297: stepm. It is no more the probability to die between last interview
3298: and month of death but the probability to survive from last
3299: interview up to one month before death multiplied by the
3300: probability to die within a month. Thanks to Chris
3301: Jackson for correcting this bug. Former versions increased
3302: mortality artificially. The bad side is that we add another loop
3303: which slows down the processing. The difference can be up to 10%
3304: lower mortality.
3305: */
3306: /* If, at the beginning of the maximization mostly, the
3307: cumulative probability or probability to be dead is
3308: constant (ie = 1) over time d, the difference is equal to
3309: 0. out[s1][3] = savm[s1][3]: probability, being at state
3310: s1 at precedent wave, to be dead a month before current
3311: wave is equal to probability, being at state s1 at
3312: precedent wave, to be dead at mont of the current
3313: wave. Then the observed probability (that this person died)
3314: is null according to current estimated parameter. In fact,
3315: it should be very low but not zero otherwise the log go to
3316: infinity.
3317: */
1.183 brouard 3318: /* #ifdef INFINITYORIGINAL */
3319: /* lli=log(out[s1][s2] - savm[s1][s2]); */
3320: /* #else */
3321: /* if ((out[s1][s2] - savm[s1][s2]) < mytinydouble) */
3322: /* lli=log(mytinydouble); */
3323: /* else */
3324: /* lli=log(out[s1][s2] - savm[s1][s2]); */
3325: /* #endif */
1.226 brouard 3326: lli=log(out[s1][s2] - savm[s1][s2]);
1.216 brouard 3327:
1.226 brouard 3328: } else if ( s2==-1 ) { /* alive */
3329: for (j=1,survp=0. ; j<=nlstate; j++)
3330: survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j];
3331: /*survp += out[s1][j]; */
3332: lli= log(survp);
3333: }
3334: else if (s2==-4) {
3335: for (j=3,survp=0. ; j<=nlstate; j++)
3336: survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j];
3337: lli= log(survp);
3338: }
3339: else if (s2==-5) {
3340: for (j=1,survp=0. ; j<=2; j++)
3341: survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j];
3342: lli= log(survp);
3343: }
3344: else{
3345: lli= log((1.+bbh)*out[s1][s2]- bbh*savm[s1][s2]); /* linear interpolation */
3346: /* 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 */
3347: }
3348: /*lli=(1.+bbh)*log(out[s1][s2])- bbh*log(savm[s1][s2]);*/
3349: /*if(lli ==000.0)*/
3350: /*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); */
3351: ipmx +=1;
3352: sw += weight[i];
3353: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
3354: /* if (lli < log(mytinydouble)){ */
3355: /* 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); */
3356: /* 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]); */
3357: /* } */
3358: } /* end of wave */
3359: } /* end of individual */
3360: } else if(mle==2){
3361: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
3362: for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i];
3363: for(mi=1; mi<= wav[i]-1; mi++){
3364: for (ii=1;ii<=nlstate+ndeath;ii++)
3365: for (j=1;j<=nlstate+ndeath;j++){
3366: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
3367: savm[ii][j]=(ii==j ? 1.0 : 0.0);
3368: }
3369: for(d=0; d<=dh[mi][i]; d++){
3370: newm=savm;
3371: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
3372: cov[2]=agexact;
3373: if(nagesqr==1)
3374: cov[3]= agexact*agexact;
3375: for (kk=1; kk<=cptcovage;kk++) {
3376: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
3377: }
3378: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
3379: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
3380: savm=oldm;
3381: oldm=newm;
3382: } /* end mult */
3383:
3384: s1=s[mw[mi][i]][i];
3385: s2=s[mw[mi+1][i]][i];
3386: bbh=(double)bh[mi][i]/(double)stepm;
3387: 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 */
3388: ipmx +=1;
3389: sw += weight[i];
3390: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
3391: } /* end of wave */
3392: } /* end of individual */
3393: } else if(mle==3){ /* exponential inter-extrapolation */
3394: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
3395: for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i];
3396: for(mi=1; mi<= wav[i]-1; mi++){
3397: for (ii=1;ii<=nlstate+ndeath;ii++)
3398: for (j=1;j<=nlstate+ndeath;j++){
3399: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
3400: savm[ii][j]=(ii==j ? 1.0 : 0.0);
3401: }
3402: for(d=0; d<dh[mi][i]; d++){
3403: newm=savm;
3404: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
3405: cov[2]=agexact;
3406: if(nagesqr==1)
3407: cov[3]= agexact*agexact;
3408: for (kk=1; kk<=cptcovage;kk++) {
3409: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
3410: }
3411: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
3412: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
3413: savm=oldm;
3414: oldm=newm;
3415: } /* end mult */
3416:
3417: s1=s[mw[mi][i]][i];
3418: s2=s[mw[mi+1][i]][i];
3419: bbh=(double)bh[mi][i]/(double)stepm;
3420: 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 */
3421: ipmx +=1;
3422: sw += weight[i];
3423: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
3424: } /* end of wave */
3425: } /* end of individual */
3426: }else if (mle==4){ /* ml=4 no inter-extrapolation */
3427: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
3428: for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i];
3429: for(mi=1; mi<= wav[i]-1; mi++){
3430: for (ii=1;ii<=nlstate+ndeath;ii++)
3431: for (j=1;j<=nlstate+ndeath;j++){
3432: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
3433: savm[ii][j]=(ii==j ? 1.0 : 0.0);
3434: }
3435: for(d=0; d<dh[mi][i]; d++){
3436: newm=savm;
3437: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
3438: cov[2]=agexact;
3439: if(nagesqr==1)
3440: cov[3]= agexact*agexact;
3441: for (kk=1; kk<=cptcovage;kk++) {
3442: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
3443: }
1.126 brouard 3444:
1.226 brouard 3445: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
3446: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
3447: savm=oldm;
3448: oldm=newm;
3449: } /* end mult */
3450:
3451: s1=s[mw[mi][i]][i];
3452: s2=s[mw[mi+1][i]][i];
3453: if( s2 > nlstate){
3454: lli=log(out[s1][s2] - savm[s1][s2]);
3455: } else if ( s2==-1 ) { /* alive */
3456: for (j=1,survp=0. ; j<=nlstate; j++)
3457: survp += out[s1][j];
3458: lli= log(survp);
3459: }else{
3460: lli=log(out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]); /* Original formula */
3461: }
3462: ipmx +=1;
3463: sw += weight[i];
3464: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
1.126 brouard 3465: /* 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 3466: } /* end of wave */
3467: } /* end of individual */
3468: }else{ /* ml=5 no inter-extrapolation no jackson =0.8a */
3469: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
3470: for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i];
3471: for(mi=1; mi<= wav[i]-1; mi++){
3472: for (ii=1;ii<=nlstate+ndeath;ii++)
3473: for (j=1;j<=nlstate+ndeath;j++){
3474: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
3475: savm[ii][j]=(ii==j ? 1.0 : 0.0);
3476: }
3477: for(d=0; d<dh[mi][i]; d++){
3478: newm=savm;
3479: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
3480: cov[2]=agexact;
3481: if(nagesqr==1)
3482: cov[3]= agexact*agexact;
3483: for (kk=1; kk<=cptcovage;kk++) {
3484: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
3485: }
1.126 brouard 3486:
1.226 brouard 3487: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
3488: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
3489: savm=oldm;
3490: oldm=newm;
3491: } /* end mult */
3492:
3493: s1=s[mw[mi][i]][i];
3494: s2=s[mw[mi+1][i]][i];
3495: lli=log(out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]); /* Original formula */
3496: ipmx +=1;
3497: sw += weight[i];
3498: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
3499: /*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]);*/
3500: } /* end of wave */
3501: } /* end of individual */
3502: } /* End of if */
3503: for(k=1,l=0.; k<=nlstate; k++) l += ll[k];
3504: /* printf("l1=%f l2=%f ",ll[1],ll[2]); */
3505: l= l*ipmx/sw; /* To get the same order of magnitude as if weight=1 for every body */
3506: return -l;
1.126 brouard 3507: }
3508:
3509: /*************** log-likelihood *************/
3510: double funcone( double *x)
3511: {
1.228 brouard 3512: /* Same as func but slower because of a lot of printf and if */
1.126 brouard 3513: int i, ii, j, k, mi, d, kk;
1.228 brouard 3514: int ioffset=0;
1.131 brouard 3515: double l, ll[NLSTATEMAX+1], cov[NCOVMAX+1];
1.126 brouard 3516: double **out;
3517: double lli; /* Individual log likelihood */
3518: double llt;
3519: int s1, s2;
1.228 brouard 3520: int iv=0, iqv=0, itv=0, iqtv=0 ; /* Index of varying covariate, fixed quantitative cov, time varying covariate, quantitative time varying covariate */
3521:
1.126 brouard 3522: double bbh, survp;
1.187 brouard 3523: double agexact;
1.214 brouard 3524: double agebegin, ageend;
1.126 brouard 3525: /*extern weight */
3526: /* We are differentiating ll according to initial status */
3527: /* for (i=1;i<=npar;i++) printf("%f ", x[i]);*/
3528: /*for(i=1;i<imx;i++)
3529: printf(" %d\n",s[4][i]);
3530: */
3531: cov[1]=1.;
3532:
3533: for(k=1; k<=nlstate; k++) ll[k]=0.;
1.224 brouard 3534: ioffset=0;
3535: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
1.243 ! brouard 3536: /* ioffset=2+nagesqr+cptcovage; */
! 3537: ioffset=2+nagesqr;
1.232 brouard 3538: /* Fixed */
1.224 brouard 3539: /* for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i]; */
1.232 brouard 3540: /* for (k=1; k<=ncoveff;k++){ /\* Simple and product fixed Dummy covariates without age* products *\/ */
3541: for (k=1; k<=ncovf;k++){ /* Simple and product fixed covariates without age* products */
3542: 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)*/
3543: /* cov[ioffset+TvarFind[1]]=covar[Tvar[TvarFind[1]]][i]; */
3544: /* cov[2+6]=covar[Tvar[6]][i]; */
3545: /* cov[2+6]=covar[2][i]; V2 */
3546: /* cov[TvarFind[2]]=covar[Tvar[TvarFind[2]]][i]; */
3547: /* cov[2+7]=covar[Tvar[7]][i]; */
3548: /* cov[2+7]=covar[7][i]; V7=V1*V2 */
3549: /* cov[TvarFind[3]]=covar[Tvar[TvarFind[3]]][i]; */
3550: /* cov[2+9]=covar[Tvar[9]][i]; */
3551: /* cov[2+9]=covar[1][i]; V1 */
1.225 brouard 3552: }
1.232 brouard 3553: /* for (k=1; k<=nqfveff;k++){ /\* Simple and product fixed Quantitative covariates without age* products *\/ */
3554: /* 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?)*\/ */
3555: /* } */
1.231 brouard 3556: /* for(iqv=1; iqv <= nqfveff; iqv++){ /\* Quantitative fixed covariates *\/ */
3557: /* cov[++ioffset]=coqvar[Tvar[iqv]][i]; /\* Only V2 k=6 and V1*V2 7 *\/ */
3558: /* } */
1.225 brouard 3559:
1.233 brouard 3560:
3561: for(mi=1; mi<= wav[i]-1; mi++){ /* Varying with waves */
1.232 brouard 3562: /* Wave varying (but not age varying) */
3563: for(k=1; k <= ncovv ; k++){ /* Varying covariates (single and product but no age )*/
1.242 brouard 3564: /* cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]][i]; */
3565: cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]-ncovcol-nqv][i];
3566: }
1.232 brouard 3567: /* for(itv=1; itv <= ntveff; itv++){ /\* Varying dummy covariates (single??)*\/ */
1.242 brouard 3568: /* iv= Tvar[Tmodelind[ioffset-2-nagesqr-cptcovage+itv]]-ncovcol-nqv; /\* Counting the # varying covariate from 1 to ntveff *\/ */
3569: /* cov[ioffset+iv]=cotvar[mw[mi][i]][iv][i]; */
3570: /* k=ioffset-2-nagesqr-cptcovage+itv; /\* position in simple model *\/ */
3571: /* cov[ioffset+itv]=cotvar[mw[mi][i]][TmodelInvind[itv]][i]; */
3572: /* 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 3573: /* for(iqtv=1; iqtv <= nqtveff; iqtv++){ /\* Varying quantitatives covariates *\/ */
1.242 brouard 3574: /* iv=TmodelInvQind[iqtv]; /\* Counting the # varying covariate from 1 to ntveff *\/ */
3575: /* /\* 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]); *\/ */
3576: /* cov[ioffset+ntveff+iqtv]=cotqvar[mw[mi][i]][TmodelInvQind[iqtv]][i]; */
1.232 brouard 3577: /* } */
1.126 brouard 3578: for (ii=1;ii<=nlstate+ndeath;ii++)
1.242 brouard 3579: for (j=1;j<=nlstate+ndeath;j++){
3580: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
3581: savm[ii][j]=(ii==j ? 1.0 : 0.0);
3582: }
1.214 brouard 3583:
3584: agebegin=agev[mw[mi][i]][i]; /* Age at beginning of effective wave */
3585: ageend=agev[mw[mi][i]][i] + (dh[mi][i])*stepm/YEARM; /* Age at end of effective wave and at the end of transition */
3586: for(d=0; d<dh[mi][i]; d++){ /* Delay between two effective waves */
1.242 brouard 3587: /*dh[m][i] or dh[mw[mi][i]][i] is the delay between two effective waves m=mw[mi][i]
3588: and mw[mi+1][i]. dh depends on stepm.*/
3589: newm=savm;
3590: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
3591: cov[2]=agexact;
3592: if(nagesqr==1)
3593: cov[3]= agexact*agexact;
3594: for (kk=1; kk<=cptcovage;kk++) {
3595: if(!FixedV[Tvar[Tage[kk]]])
3596: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
3597: else
3598: cov[Tage[kk]+2+nagesqr]=cotvar[mw[mi][i]][Tvar[Tage[kk]]-ncovcol-nqv][i]*agexact;
3599: }
3600: /* printf("i=%d,mi=%d,d=%d,mw[mi][i]=%d\n",i, mi,d,mw[mi][i]); */
3601: /* savm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
3602: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
3603: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
3604: /* out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath, */
3605: /* 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate)); */
3606: savm=oldm;
3607: oldm=newm;
1.126 brouard 3608: } /* end mult */
3609:
3610: s1=s[mw[mi][i]][i];
3611: s2=s[mw[mi+1][i]][i];
1.217 brouard 3612: /* if(s2==-1){ */
3613: /* printf(" s1=%d, s2=%d i=%d \n", s1, s2, i); */
3614: /* /\* exit(1); *\/ */
3615: /* } */
1.126 brouard 3616: bbh=(double)bh[mi][i]/(double)stepm;
3617: /* bias is positive if real duration
3618: * is higher than the multiple of stepm and negative otherwise.
3619: */
3620: if( s2 > nlstate && (mle <5) ){ /* Jackson */
1.242 brouard 3621: lli=log(out[s1][s2] - savm[s1][s2]);
1.216 brouard 3622: } else if ( s2==-1 ) { /* alive */
1.242 brouard 3623: for (j=1,survp=0. ; j<=nlstate; j++)
3624: survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j];
3625: lli= log(survp);
1.126 brouard 3626: }else if (mle==1){
1.242 brouard 3627: lli= log((1.+bbh)*out[s1][s2]- bbh*savm[s1][s2]); /* linear interpolation */
1.126 brouard 3628: } else if(mle==2){
1.242 brouard 3629: 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 3630: } else if(mle==3){ /* exponential inter-extrapolation */
1.242 brouard 3631: 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 3632: } else if (mle==4){ /* mle=4 no inter-extrapolation */
1.242 brouard 3633: lli=log(out[s1][s2]); /* Original formula */
1.136 brouard 3634: } else{ /* mle=0 back to 1 */
1.242 brouard 3635: lli= log((1.+bbh)*out[s1][s2]- bbh*savm[s1][s2]); /* linear interpolation */
3636: /*lli=log(out[s1][s2]); */ /* Original formula */
1.126 brouard 3637: } /* End of if */
3638: ipmx +=1;
3639: sw += weight[i];
3640: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
1.132 brouard 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]); */
1.126 brouard 3642: if(globpr){
1.242 brouard 3643: fprintf(ficresilk,"%9ld %6.1f %6.1f %6d %2d %2d %2d %2d %3d %15.6f %8.4f %8.3f\
1.126 brouard 3644: %11.6f %11.6f %11.6f ", \
1.242 brouard 3645: num[i], agebegin, ageend, i,s1,s2,mi,mw[mi][i],dh[mi][i],exp(lli),weight[i],weight[i]*gipmx/gsw,
3646: 2*weight[i]*lli,out[s1][s2],savm[s1][s2]);
3647: for(k=1,llt=0.,l=0.; k<=nlstate; k++){
3648: llt +=ll[k]*gipmx/gsw;
3649: fprintf(ficresilk," %10.6f",-ll[k]*gipmx/gsw);
3650: }
3651: fprintf(ficresilk," %10.6f\n", -llt);
1.126 brouard 3652: }
1.232 brouard 3653: } /* end of wave */
3654: } /* end of individual */
3655: for(k=1,l=0.; k<=nlstate; k++) l += ll[k];
3656: /* printf("l1=%f l2=%f ",ll[1],ll[2]); */
3657: l= l*ipmx/sw; /* To get the same order of magnitude as if weight=1 for every body */
3658: if(globpr==0){ /* First time we count the contributions and weights */
3659: gipmx=ipmx;
3660: gsw=sw;
3661: }
3662: return -l;
1.126 brouard 3663: }
3664:
3665:
3666: /*************** function likelione ***********/
3667: void likelione(FILE *ficres,double p[], int npar, int nlstate, int *globpri, long *ipmx, double *sw, double *fretone, double (*funcone)(double []))
3668: {
3669: /* This routine should help understanding what is done with
3670: the selection of individuals/waves and
3671: to check the exact contribution to the likelihood.
3672: Plotting could be done.
3673: */
3674: int k;
3675:
3676: if(*globpri !=0){ /* Just counts and sums, no printings */
1.201 brouard 3677: strcpy(fileresilk,"ILK_");
1.202 brouard 3678: strcat(fileresilk,fileresu);
1.126 brouard 3679: if((ficresilk=fopen(fileresilk,"w"))==NULL) {
3680: printf("Problem with resultfile: %s\n", fileresilk);
3681: fprintf(ficlog,"Problem with resultfile: %s\n", fileresilk);
3682: }
1.214 brouard 3683: 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");
3684: fprintf(ficresilk, "#num_i ageb agend i s1 s2 mi mw dh likeli weight %%weight 2wlli out sav ");
1.126 brouard 3685: /* i,s1,s2,mi,mw[mi][i],dh[mi][i],exp(lli),weight[i],2*weight[i]*lli,out[s1][s2],savm[s1][s2]); */
3686: for(k=1; k<=nlstate; k++)
3687: fprintf(ficresilk," -2*gipw/gsw*weight*ll[%d]++",k);
3688: fprintf(ficresilk," -2*gipw/gsw*weight*ll(total)\n");
3689: }
3690:
3691: *fretone=(*funcone)(p);
3692: if(*globpri !=0){
3693: fclose(ficresilk);
1.205 brouard 3694: if (mle ==0)
3695: fprintf(fichtm,"\n<br>File of contributions to the likelihood computed with initial parameters and mle = %d.",mle);
3696: else if(mle >=1)
3697: fprintf(fichtm,"\n<br>File of contributions to the likelihood computed with optimized parameters mle = %d.",mle);
3698: 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 3699:
1.208 brouard 3700:
3701: for (k=1; k<= nlstate ; k++) {
1.211 brouard 3702: 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 3703: <img src=\"%s-p%dj.png\">",k,k,subdirf2(optionfilefiname,"ILK_"),k,subdirf2(optionfilefiname,"ILK_"),k,subdirf2(optionfilefiname,"ILK_"),k);
3704: }
1.207 brouard 3705: 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 3706: <img src=\"%s-ori.png\">",subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"));
1.207 brouard 3707: fprintf(fichtm,"<br>- and by state of destination <a href=\"%s-dest.png\">%s-dest.png</a><br> \
1.204 brouard 3708: <img src=\"%s-dest.png\">",subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"));
1.207 brouard 3709: fflush(fichtm);
1.205 brouard 3710: }
1.126 brouard 3711: return;
3712: }
3713:
3714:
3715: /*********** Maximum Likelihood Estimation ***************/
3716:
3717: void mlikeli(FILE *ficres,double p[], int npar, int ncovmodel, int nlstate, double ftol, double (*func)(double []))
3718: {
1.165 brouard 3719: int i,j, iter=0;
1.126 brouard 3720: double **xi;
3721: double fret;
3722: double fretone; /* Only one call to likelihood */
3723: /* char filerespow[FILENAMELENGTH];*/
1.162 brouard 3724:
3725: #ifdef NLOPT
3726: int creturn;
3727: nlopt_opt opt;
3728: /* double lb[9] = { -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL }; /\* lower bounds *\/ */
3729: double *lb;
3730: double minf; /* the minimum objective value, upon return */
3731: double * p1; /* Shifted parameters from 0 instead of 1 */
3732: myfunc_data dinst, *d = &dinst;
3733: #endif
3734:
3735:
1.126 brouard 3736: xi=matrix(1,npar,1,npar);
3737: for (i=1;i<=npar;i++)
3738: for (j=1;j<=npar;j++)
3739: xi[i][j]=(i==j ? 1.0 : 0.0);
3740: printf("Powell\n"); fprintf(ficlog,"Powell\n");
1.201 brouard 3741: strcpy(filerespow,"POW_");
1.126 brouard 3742: strcat(filerespow,fileres);
3743: if((ficrespow=fopen(filerespow,"w"))==NULL) {
3744: printf("Problem with resultfile: %s\n", filerespow);
3745: fprintf(ficlog,"Problem with resultfile: %s\n", filerespow);
3746: }
3747: fprintf(ficrespow,"# Powell\n# iter -2*LL");
3748: for (i=1;i<=nlstate;i++)
3749: for(j=1;j<=nlstate+ndeath;j++)
3750: if(j!=i)fprintf(ficrespow," p%1d%1d",i,j);
3751: fprintf(ficrespow,"\n");
1.162 brouard 3752: #ifdef POWELL
1.126 brouard 3753: powell(p,xi,npar,ftol,&iter,&fret,func);
1.162 brouard 3754: #endif
1.126 brouard 3755:
1.162 brouard 3756: #ifdef NLOPT
3757: #ifdef NEWUOA
3758: opt = nlopt_create(NLOPT_LN_NEWUOA,npar);
3759: #else
3760: opt = nlopt_create(NLOPT_LN_BOBYQA,npar);
3761: #endif
3762: lb=vector(0,npar-1);
3763: for (i=0;i<npar;i++) lb[i]= -HUGE_VAL;
3764: nlopt_set_lower_bounds(opt, lb);
3765: nlopt_set_initial_step1(opt, 0.1);
3766:
3767: p1= (p+1); /* p *(p+1)@8 and p *(p1)@8 are equal p1[0]=p[1] */
3768: d->function = func;
3769: printf(" Func %.12lf \n",myfunc(npar,p1,NULL,d));
3770: nlopt_set_min_objective(opt, myfunc, d);
3771: nlopt_set_xtol_rel(opt, ftol);
3772: if ((creturn=nlopt_optimize(opt, p1, &minf)) < 0) {
3773: printf("nlopt failed! %d\n",creturn);
3774: }
3775: else {
3776: printf("found minimum after %d evaluations (NLOPT=%d)\n", countcallfunc ,NLOPT);
3777: printf("found minimum at f(%g,%g) = %0.10g\n", p[0], p[1], minf);
3778: iter=1; /* not equal */
3779: }
3780: nlopt_destroy(opt);
3781: #endif
1.126 brouard 3782: free_matrix(xi,1,npar,1,npar);
3783: fclose(ficrespow);
1.203 brouard 3784: printf("\n#Number of iterations & function calls = %d & %d, -2 Log likelihood = %.12f\n",iter, countcallfunc,func(p));
3785: fprintf(ficlog,"\n#Number of iterations & function calls = %d & %d, -2 Log likelihood = %.12f\n",iter, countcallfunc,func(p));
1.180 brouard 3786: fprintf(ficres,"#Number of iterations & function calls = %d & %d, -2 Log likelihood = %.12f\n",iter, countcallfunc,func(p));
1.126 brouard 3787:
3788: }
3789:
3790: /**** Computes Hessian and covariance matrix ***/
1.203 brouard 3791: void hesscov(double **matcov, double **hess, double p[], int npar, double delti[], double ftolhess, double (*func)(double []))
1.126 brouard 3792: {
3793: double **a,**y,*x,pd;
1.203 brouard 3794: /* double **hess; */
1.164 brouard 3795: int i, j;
1.126 brouard 3796: int *indx;
3797:
3798: double hessii(double p[], double delta, int theta, double delti[],double (*func)(double []),int npar);
1.203 brouard 3799: double hessij(double p[], double **hess, double delti[], int i, int j,double (*func)(double []),int npar);
1.126 brouard 3800: void lubksb(double **a, int npar, int *indx, double b[]) ;
3801: void ludcmp(double **a, int npar, int *indx, double *d) ;
3802: double gompertz(double p[]);
1.203 brouard 3803: /* hess=matrix(1,npar,1,npar); */
1.126 brouard 3804:
3805: printf("\nCalculation of the hessian matrix. Wait...\n");
3806: fprintf(ficlog,"\nCalculation of the hessian matrix. Wait...\n");
3807: for (i=1;i<=npar;i++){
1.203 brouard 3808: printf("%d-",i);fflush(stdout);
3809: fprintf(ficlog,"%d-",i);fflush(ficlog);
1.126 brouard 3810:
3811: hess[i][i]=hessii(p,ftolhess,i,delti,func,npar);
3812:
3813: /* printf(" %f ",p[i]);
3814: printf(" %lf %lf %lf",hess[i][i],ftolhess,delti[i]);*/
3815: }
3816:
3817: for (i=1;i<=npar;i++) {
3818: for (j=1;j<=npar;j++) {
3819: if (j>i) {
1.203 brouard 3820: printf(".%d-%d",i,j);fflush(stdout);
3821: fprintf(ficlog,".%d-%d",i,j);fflush(ficlog);
3822: hess[i][j]=hessij(p,hess, delti,i,j,func,npar);
1.126 brouard 3823:
3824: hess[j][i]=hess[i][j];
3825: /*printf(" %lf ",hess[i][j]);*/
3826: }
3827: }
3828: }
3829: printf("\n");
3830: fprintf(ficlog,"\n");
3831:
3832: printf("\nInverting the hessian to get the covariance matrix. Wait...\n");
3833: fprintf(ficlog,"\nInverting the hessian to get the covariance matrix. Wait...\n");
3834:
3835: a=matrix(1,npar,1,npar);
3836: y=matrix(1,npar,1,npar);
3837: x=vector(1,npar);
3838: indx=ivector(1,npar);
3839: for (i=1;i<=npar;i++)
3840: for (j=1;j<=npar;j++) a[i][j]=hess[i][j];
3841: ludcmp(a,npar,indx,&pd);
3842:
3843: for (j=1;j<=npar;j++) {
3844: for (i=1;i<=npar;i++) x[i]=0;
3845: x[j]=1;
3846: lubksb(a,npar,indx,x);
3847: for (i=1;i<=npar;i++){
3848: matcov[i][j]=x[i];
3849: }
3850: }
3851:
3852: printf("\n#Hessian matrix#\n");
3853: fprintf(ficlog,"\n#Hessian matrix#\n");
3854: for (i=1;i<=npar;i++) {
3855: for (j=1;j<=npar;j++) {
1.203 brouard 3856: printf("%.6e ",hess[i][j]);
3857: fprintf(ficlog,"%.6e ",hess[i][j]);
1.126 brouard 3858: }
3859: printf("\n");
3860: fprintf(ficlog,"\n");
3861: }
3862:
1.203 brouard 3863: /* printf("\n#Covariance matrix#\n"); */
3864: /* fprintf(ficlog,"\n#Covariance matrix#\n"); */
3865: /* for (i=1;i<=npar;i++) { */
3866: /* for (j=1;j<=npar;j++) { */
3867: /* printf("%.6e ",matcov[i][j]); */
3868: /* fprintf(ficlog,"%.6e ",matcov[i][j]); */
3869: /* } */
3870: /* printf("\n"); */
3871: /* fprintf(ficlog,"\n"); */
3872: /* } */
3873:
1.126 brouard 3874: /* Recompute Inverse */
1.203 brouard 3875: /* for (i=1;i<=npar;i++) */
3876: /* for (j=1;j<=npar;j++) a[i][j]=matcov[i][j]; */
3877: /* ludcmp(a,npar,indx,&pd); */
3878:
3879: /* printf("\n#Hessian matrix recomputed#\n"); */
3880:
3881: /* for (j=1;j<=npar;j++) { */
3882: /* for (i=1;i<=npar;i++) x[i]=0; */
3883: /* x[j]=1; */
3884: /* lubksb(a,npar,indx,x); */
3885: /* for (i=1;i<=npar;i++){ */
3886: /* y[i][j]=x[i]; */
3887: /* printf("%.3e ",y[i][j]); */
3888: /* fprintf(ficlog,"%.3e ",y[i][j]); */
3889: /* } */
3890: /* printf("\n"); */
3891: /* fprintf(ficlog,"\n"); */
3892: /* } */
3893:
3894: /* Verifying the inverse matrix */
3895: #ifdef DEBUGHESS
3896: y=matprod2(y,hess,1,npar,1,npar,1,npar,matcov);
1.126 brouard 3897:
1.203 brouard 3898: printf("\n#Verification: multiplying the matrix of covariance by the Hessian matrix, should be unity:#\n");
3899: fprintf(ficlog,"\n#Verification: multiplying the matrix of covariance by the Hessian matrix. Should be unity:#\n");
1.126 brouard 3900:
3901: for (j=1;j<=npar;j++) {
3902: for (i=1;i<=npar;i++){
1.203 brouard 3903: printf("%.2f ",y[i][j]);
3904: fprintf(ficlog,"%.2f ",y[i][j]);
1.126 brouard 3905: }
3906: printf("\n");
3907: fprintf(ficlog,"\n");
3908: }
1.203 brouard 3909: #endif
1.126 brouard 3910:
3911: free_matrix(a,1,npar,1,npar);
3912: free_matrix(y,1,npar,1,npar);
3913: free_vector(x,1,npar);
3914: free_ivector(indx,1,npar);
1.203 brouard 3915: /* free_matrix(hess,1,npar,1,npar); */
1.126 brouard 3916:
3917:
3918: }
3919:
3920: /*************** hessian matrix ****************/
3921: double hessii(double x[], double delta, int theta, double delti[], double (*func)(double []), int npar)
1.203 brouard 3922: { /* Around values of x, computes the function func and returns the scales delti and hessian */
1.126 brouard 3923: int i;
3924: int l=1, lmax=20;
1.203 brouard 3925: double k1,k2, res, fx;
1.132 brouard 3926: double p2[MAXPARM+1]; /* identical to x */
1.126 brouard 3927: double delt=0.0001, delts, nkhi=10.,nkhif=1., khi=1.e-4;
3928: int k=0,kmax=10;
3929: double l1;
3930:
3931: fx=func(x);
3932: for (i=1;i<=npar;i++) p2[i]=x[i];
1.145 brouard 3933: for(l=0 ; l <=lmax; l++){ /* Enlarging the zone around the Maximum */
1.126 brouard 3934: l1=pow(10,l);
3935: delts=delt;
3936: for(k=1 ; k <kmax; k=k+1){
3937: delt = delta*(l1*k);
3938: p2[theta]=x[theta] +delt;
1.145 brouard 3939: k1=func(p2)-fx; /* Might be negative if too close to the theoretical maximum */
1.126 brouard 3940: p2[theta]=x[theta]-delt;
3941: k2=func(p2)-fx;
3942: /*res= (k1-2.0*fx+k2)/delt/delt; */
1.203 brouard 3943: res= (k1+k2)/delt/delt/2.; /* Divided by 2 because L and not 2*L */
1.126 brouard 3944:
1.203 brouard 3945: #ifdef DEBUGHESSII
1.126 brouard 3946: 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);
3947: 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);
3948: #endif
3949: /*if(fabs(k1-2.0*fx+k2) <1.e-13){ */
3950: if((k1 <khi/nkhi/2.) || (k2 <khi/nkhi/2.)){
3951: k=kmax;
3952: }
3953: else if((k1 >khi/nkhif) || (k2 >khi/nkhif)){ /* Keeps lastvalue before 3.84/2 KHI2 5% 1d.f. */
1.164 brouard 3954: k=kmax; l=lmax*10;
1.126 brouard 3955: }
3956: else if((k1 >khi/nkhi) || (k2 >khi/nkhi)){
3957: delts=delt;
3958: }
1.203 brouard 3959: } /* End loop k */
1.126 brouard 3960: }
3961: delti[theta]=delts;
3962: return res;
3963:
3964: }
3965:
1.203 brouard 3966: double hessij( double x[], double **hess, double delti[], int thetai,int thetaj,double (*func)(double []),int npar)
1.126 brouard 3967: {
3968: int i;
1.164 brouard 3969: int l=1, lmax=20;
1.126 brouard 3970: double k1,k2,k3,k4,res,fx;
1.132 brouard 3971: double p2[MAXPARM+1];
1.203 brouard 3972: int k, kmax=1;
3973: double v1, v2, cv12, lc1, lc2;
1.208 brouard 3974:
3975: int firstime=0;
1.203 brouard 3976:
1.126 brouard 3977: fx=func(x);
1.203 brouard 3978: for (k=1; k<=kmax; k=k+10) {
1.126 brouard 3979: for (i=1;i<=npar;i++) p2[i]=x[i];
1.203 brouard 3980: p2[thetai]=x[thetai]+delti[thetai]*k;
3981: p2[thetaj]=x[thetaj]+delti[thetaj]*k;
1.126 brouard 3982: k1=func(p2)-fx;
3983:
1.203 brouard 3984: p2[thetai]=x[thetai]+delti[thetai]*k;
3985: p2[thetaj]=x[thetaj]-delti[thetaj]*k;
1.126 brouard 3986: k2=func(p2)-fx;
3987:
1.203 brouard 3988: p2[thetai]=x[thetai]-delti[thetai]*k;
3989: p2[thetaj]=x[thetaj]+delti[thetaj]*k;
1.126 brouard 3990: k3=func(p2)-fx;
3991:
1.203 brouard 3992: p2[thetai]=x[thetai]-delti[thetai]*k;
3993: p2[thetaj]=x[thetaj]-delti[thetaj]*k;
1.126 brouard 3994: k4=func(p2)-fx;
1.203 brouard 3995: res=(k1-k2-k3+k4)/4.0/delti[thetai]/k/delti[thetaj]/k/2.; /* Because of L not 2*L */
3996: if(k1*k2*k3*k4 <0.){
1.208 brouard 3997: firstime=1;
1.203 brouard 3998: kmax=kmax+10;
1.208 brouard 3999: }
4000: if(kmax >=10 || firstime ==1){
1.218 brouard 4001: printf("Warning: directions %d-%d, you are not estimating the Hessian at the exact maximum likelihood; you may increase ftol=%.2e\n",thetai,thetaj, ftol);
4002: fprintf(ficlog,"Warning: directions %d-%d, you are not estimating the Hessian at the exact maximum likelihood; you may increase ftol=%.2e\n",thetai,thetaj, ftol);
1.203 brouard 4003: 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);
4004: 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);
4005: }
4006: #ifdef DEBUGHESSIJ
4007: v1=hess[thetai][thetai];
4008: v2=hess[thetaj][thetaj];
4009: cv12=res;
4010: /* Computing eigen value of Hessian matrix */
4011: lc1=((v1+v2)+sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
4012: lc2=((v1+v2)-sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
4013: if ((lc2 <0) || (lc1 <0) ){
4014: printf("Warning: sub Hessian matrix '%d%d' does not have positive eigen values \n",thetai,thetaj);
4015: fprintf(ficlog, "Warning: sub Hessian matrix '%d%d' does not have positive eigen values \n",thetai,thetaj);
4016: 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);
4017: 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);
4018: }
1.126 brouard 4019: #endif
4020: }
4021: return res;
4022: }
4023:
1.203 brouard 4024: /* Not done yet: Was supposed to fix if not exactly at the maximum */
4025: /* double hessij( double x[], double delti[], int thetai,int thetaj,double (*func)(double []),int npar) */
4026: /* { */
4027: /* int i; */
4028: /* int l=1, lmax=20; */
4029: /* double k1,k2,k3,k4,res,fx; */
4030: /* double p2[MAXPARM+1]; */
4031: /* double delt=0.0001, delts, nkhi=10.,nkhif=1., khi=1.e-4; */
4032: /* int k=0,kmax=10; */
4033: /* double l1; */
4034:
4035: /* fx=func(x); */
4036: /* for(l=0 ; l <=lmax; l++){ /\* Enlarging the zone around the Maximum *\/ */
4037: /* l1=pow(10,l); */
4038: /* delts=delt; */
4039: /* for(k=1 ; k <kmax; k=k+1){ */
4040: /* delt = delti*(l1*k); */
4041: /* for (i=1;i<=npar;i++) p2[i]=x[i]; */
4042: /* p2[thetai]=x[thetai]+delti[thetai]/k; */
4043: /* p2[thetaj]=x[thetaj]+delti[thetaj]/k; */
4044: /* k1=func(p2)-fx; */
4045:
4046: /* p2[thetai]=x[thetai]+delti[thetai]/k; */
4047: /* p2[thetaj]=x[thetaj]-delti[thetaj]/k; */
4048: /* k2=func(p2)-fx; */
4049:
4050: /* p2[thetai]=x[thetai]-delti[thetai]/k; */
4051: /* p2[thetaj]=x[thetaj]+delti[thetaj]/k; */
4052: /* k3=func(p2)-fx; */
4053:
4054: /* p2[thetai]=x[thetai]-delti[thetai]/k; */
4055: /* p2[thetaj]=x[thetaj]-delti[thetaj]/k; */
4056: /* k4=func(p2)-fx; */
4057: /* res=(k1-k2-k3+k4)/4.0/delti[thetai]*k/delti[thetaj]*k/2.; /\* Because of L not 2*L *\/ */
4058: /* #ifdef DEBUGHESSIJ */
4059: /* 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); */
4060: /* 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); */
4061: /* #endif */
4062: /* if((k1 <khi/nkhi/2.) || (k2 <khi/nkhi/2.)|| (k4 <khi/nkhi/2.)|| (k4 <khi/nkhi/2.)){ */
4063: /* k=kmax; */
4064: /* } */
4065: /* else if((k1 >khi/nkhif) || (k2 >khi/nkhif) || (k4 >khi/nkhif) || (k4 >khi/nkhif)){ /\* Keeps lastvalue before 3.84/2 KHI2 5% 1d.f. *\/ */
4066: /* k=kmax; l=lmax*10; */
4067: /* } */
4068: /* else if((k1 >khi/nkhi) || (k2 >khi/nkhi)){ */
4069: /* delts=delt; */
4070: /* } */
4071: /* } /\* End loop k *\/ */
4072: /* } */
4073: /* delti[theta]=delts; */
4074: /* return res; */
4075: /* } */
4076:
4077:
1.126 brouard 4078: /************** Inverse of matrix **************/
4079: void ludcmp(double **a, int n, int *indx, double *d)
4080: {
4081: int i,imax,j,k;
4082: double big,dum,sum,temp;
4083: double *vv;
4084:
4085: vv=vector(1,n);
4086: *d=1.0;
4087: for (i=1;i<=n;i++) {
4088: big=0.0;
4089: for (j=1;j<=n;j++)
4090: if ((temp=fabs(a[i][j])) > big) big=temp;
4091: if (big == 0.0) nrerror("Singular matrix in routine ludcmp");
4092: vv[i]=1.0/big;
4093: }
4094: for (j=1;j<=n;j++) {
4095: for (i=1;i<j;i++) {
4096: sum=a[i][j];
4097: for (k=1;k<i;k++) sum -= a[i][k]*a[k][j];
4098: a[i][j]=sum;
4099: }
4100: big=0.0;
4101: for (i=j;i<=n;i++) {
4102: sum=a[i][j];
4103: for (k=1;k<j;k++)
4104: sum -= a[i][k]*a[k][j];
4105: a[i][j]=sum;
4106: if ( (dum=vv[i]*fabs(sum)) >= big) {
4107: big=dum;
4108: imax=i;
4109: }
4110: }
4111: if (j != imax) {
4112: for (k=1;k<=n;k++) {
4113: dum=a[imax][k];
4114: a[imax][k]=a[j][k];
4115: a[j][k]=dum;
4116: }
4117: *d = -(*d);
4118: vv[imax]=vv[j];
4119: }
4120: indx[j]=imax;
4121: if (a[j][j] == 0.0) a[j][j]=TINY;
4122: if (j != n) {
4123: dum=1.0/(a[j][j]);
4124: for (i=j+1;i<=n;i++) a[i][j] *= dum;
4125: }
4126: }
4127: free_vector(vv,1,n); /* Doesn't work */
4128: ;
4129: }
4130:
4131: void lubksb(double **a, int n, int *indx, double b[])
4132: {
4133: int i,ii=0,ip,j;
4134: double sum;
4135:
4136: for (i=1;i<=n;i++) {
4137: ip=indx[i];
4138: sum=b[ip];
4139: b[ip]=b[i];
4140: if (ii)
4141: for (j=ii;j<=i-1;j++) sum -= a[i][j]*b[j];
4142: else if (sum) ii=i;
4143: b[i]=sum;
4144: }
4145: for (i=n;i>=1;i--) {
4146: sum=b[i];
4147: for (j=i+1;j<=n;j++) sum -= a[i][j]*b[j];
4148: b[i]=sum/a[i][i];
4149: }
4150: }
4151:
4152: void pstamp(FILE *fichier)
4153: {
1.196 brouard 4154: fprintf(fichier,"# %s.%s\n#IMaCh version %s, %s\n#%s\n# %s", optionfilefiname,optionfilext,version,copyright, fullversion, strstart);
1.126 brouard 4155: }
4156:
4157: /************ Frequencies ********************/
1.226 brouard 4158: void freqsummary(char fileres[], int iagemin, int iagemax, int **s, double **agev, int nlstate, int imx, \
4159: int *Tvaraff, int *invalidvarcomb, int **nbcode, int *ncodemax,double **mint,double **anint, char strstart[], \
4160: int firstpass, int lastpass, int stepm, int weightopt, char model[])
4161: { /* Some frequencies */
4162:
1.227 brouard 4163: int i, m, jk, j1, bool, z1,j, k, iv;
1.226 brouard 4164: int iind=0, iage=0;
4165: int mi; /* Effective wave */
4166: int first;
4167: double ***freq; /* Frequencies */
4168: double *meanq;
4169: double **meanqt;
4170: double *pp, **prop, *posprop, *pospropt;
4171: double pos=0., posproptt=0., pospropta=0., k2, dateintsum=0,k2cpt=0;
4172: char fileresp[FILENAMELENGTH], fileresphtm[FILENAMELENGTH], fileresphtmfr[FILENAMELENGTH];
4173: double agebegin, ageend;
4174:
4175: pp=vector(1,nlstate);
4176: prop=matrix(1,nlstate,iagemin-AGEMARGE,iagemax+3+AGEMARGE);
4177: posprop=vector(1,nlstate); /* Counting the number of transition starting from a live state per age */
4178: pospropt=vector(1,nlstate); /* Counting the number of transition starting from a live state */
4179: /* prop=matrix(1,nlstate,iagemin,iagemax+3); */
4180: meanq=vector(1,nqfveff); /* Number of Quantitative Fixed Variables Effective */
4181: meanqt=matrix(1,lastpass,1,nqtveff);
4182: strcpy(fileresp,"P_");
4183: strcat(fileresp,fileresu);
4184: /*strcat(fileresphtm,fileresu);*/
4185: if((ficresp=fopen(fileresp,"w"))==NULL) {
4186: printf("Problem with prevalence resultfile: %s\n", fileresp);
4187: fprintf(ficlog,"Problem with prevalence resultfile: %s\n", fileresp);
4188: exit(0);
4189: }
1.240 brouard 4190:
1.226 brouard 4191: strcpy(fileresphtm,subdirfext(optionfilefiname,"PHTM_",".htm"));
4192: if((ficresphtm=fopen(fileresphtm,"w"))==NULL) {
4193: printf("Problem with prevalence HTM resultfile '%s' with errno='%s'\n",fileresphtm,strerror(errno));
4194: fprintf(ficlog,"Problem with prevalence HTM resultfile '%s' with errno='%s'\n",fileresphtm,strerror(errno));
4195: fflush(ficlog);
4196: exit(70);
4197: }
4198: else{
4199: fprintf(ficresphtm,"<html><head>\n<title>IMaCh PHTM_ %s</title></head>\n <body><font size=\"2\">%s <br> %s</font> \
1.240 brouard 4200: <hr size=\"2\" color=\"#EC5E5E\"> \n \
1.214 brouard 4201: Title=%s <br>Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s<br>\n",\
1.226 brouard 4202: fileresphtm,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model);
4203: }
1.237 brouard 4204: 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 4205:
1.226 brouard 4206: strcpy(fileresphtmfr,subdirfext(optionfilefiname,"PHTMFR_",".htm"));
4207: if((ficresphtmfr=fopen(fileresphtmfr,"w"))==NULL) {
4208: printf("Problem with frequency table HTM resultfile '%s' with errno='%s'\n",fileresphtmfr,strerror(errno));
4209: fprintf(ficlog,"Problem with frequency table HTM resultfile '%s' with errno='%s'\n",fileresphtmfr,strerror(errno));
4210: fflush(ficlog);
4211: exit(70);
1.240 brouard 4212: } else{
1.226 brouard 4213: 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 4214: <hr size=\"2\" color=\"#EC5E5E\"> \n \
1.214 brouard 4215: Title=%s <br>Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s<br>\n",\
1.226 brouard 4216: fileresphtmfr,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model);
4217: }
1.240 brouard 4218: 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);
4219:
1.226 brouard 4220: freq= ma3x(-5,nlstate+ndeath,-5,nlstate+ndeath,iagemin-AGEMARGE,iagemax+3+AGEMARGE);
4221: j1=0;
1.126 brouard 4222:
1.227 brouard 4223: /* j=ncoveff; /\* Only fixed dummy covariates *\/ */
4224: j=cptcoveff; /* Only dummy covariates of the model */
1.226 brouard 4225: if (cptcovn<1) {j=1;ncodemax[1]=1;}
1.240 brouard 4226:
1.226 brouard 4227: first=1;
1.240 brouard 4228:
1.226 brouard 4229: /* Detects if a combination j1 is empty: for a multinomial variable like 3 education levels:
4230: reference=low_education V1=0,V2=0
4231: med_educ V1=1 V2=0,
4232: high_educ V1=0 V2=1
4233: Then V1=1 and V2=1 is a noisy combination that we want to exclude for the list 2**cptcoveff
4234: */
1.240 brouard 4235:
1.227 brouard 4236: for (j1 = 1; j1 <= (int) pow(2,j); j1++){ /* Loop on covariates combination in order of model, excluding quantitatives V4=0, V3=0 for example, fixed or varying covariates */
1.226 brouard 4237: posproptt=0.;
4238: /*printf("cptcoveff=%d Tvaraff=%d", cptcoveff,Tvaraff[1]);
4239: scanf("%d", i);*/
4240: for (i=-5; i<=nlstate+ndeath; i++)
4241: for (jk=-5; jk<=nlstate+ndeath; jk++)
1.240 brouard 4242: for(m=iagemin; m <= iagemax+3; m++)
4243: freq[i][jk][m]=0;
4244:
1.226 brouard 4245: for (i=1; i<=nlstate; i++) {
4246: for(m=iagemin; m <= iagemax+3; m++)
1.240 brouard 4247: prop[i][m]=0;
1.226 brouard 4248: posprop[i]=0;
4249: pospropt[i]=0;
4250: }
1.227 brouard 4251: /* for (z1=1; z1<= nqfveff; z1++) { */
4252: /* meanq[z1]+=0.; */
4253: /* for(m=1;m<=lastpass;m++){ */
4254: /* meanqt[m][z1]=0.; */
4255: /* } */
4256: /* } */
1.240 brouard 4257:
1.226 brouard 4258: dateintsum=0;
4259: k2cpt=0;
1.227 brouard 4260: /* For that combination of covariate j1, we count and print the frequencies in one pass */
1.226 brouard 4261: for (iind=1; iind<=imx; iind++) { /* For each individual iind */
4262: bool=1;
1.227 brouard 4263: if(anyvaryingduminmodel==0){ /* If All fixed covariates */
1.234 brouard 4264: if (cptcoveff >0) { /* Filter is here: Must be looked at for model=V1+V2+V3+V4 */
1.227 brouard 4265: /* for (z1=1; z1<= nqfveff; z1++) { */
4266: /* meanq[z1]+=coqvar[Tvar[z1]][iind]; /\* Computes mean of quantitative with selected filter *\/ */
4267: /* } */
1.234 brouard 4268: for (z1=1; z1<=cptcoveff; z1++) {
4269: /* if(Tvaraff[z1] ==-20){ */
4270: /* /\* sumnew+=cotvar[mw[mi][iind]][z1][iind]; *\/ */
4271: /* }else if(Tvaraff[z1] ==-10){ */
4272: /* /\* sumnew+=coqvar[z1][iind]; *\/ */
4273: /* }else */
4274: if (covar[Tvaraff[z1]][iind]!= nbcode[Tvaraff[z1]][codtabm(j1,z1)]){
4275: /* Tests if this individual iind responded to j1 (V4=1 V3=0) */
4276: bool=0;
4277: /* 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",
4278: bool,i,z1, z1, Tvaraff[z1],i,covar[Tvaraff[z1]][i],j1,z1,codtabm(j1,z1),
4279: j1,z1,nbcode[Tvaraff[z1]][codtabm(j1,z1)],j1);*/
4280: /* For j1=7 in V1+V2+V3+V4 = 0 1 1 0 and codtabm(7,3)=1 and nbcde[3][?]=1*/
4281: } /* Onlyf fixed */
4282: } /* end z1 */
4283: } /* cptcovn > 0 */
1.227 brouard 4284: } /* end any */
4285: if (bool==1){ /* We selected an individual iind satisfying combination j1 or all fixed */
1.234 brouard 4286: /* for(m=firstpass; m<=lastpass; m++){ */
4287: for(mi=1; mi<wav[iind];mi++){ /* For that wave */
4288: m=mw[mi][iind];
4289: if(anyvaryingduminmodel==1){ /* Some are varying covariates */
4290: for (z1=1; z1<=cptcoveff; z1++) {
4291: if( Fixed[Tmodelind[z1]]==1){
4292: iv= Tvar[Tmodelind[z1]]-ncovcol-nqv;
4293: if (cotvar[m][iv][iind]!= nbcode[Tvaraff[z1]][codtabm(j1,z1)]) /* iv=1 to ntv, right modality */
4294: bool=0;
4295: }else if( Fixed[Tmodelind[z1]]== 0) { /* fixed */
4296: if (covar[Tvaraff[z1]][iind]!= nbcode[Tvaraff[z1]][codtabm(j1,z1)]) {
4297: bool=0;
4298: }
4299: }
4300: }
4301: }/* Some are varying covariates, we tried to speed up if all fixed covariates in the model, avoiding waves loop */
4302: /* bool =0 we keep that guy which corresponds to the combination of dummy values */
4303: if(bool==1){
4304: /* dh[m][iind] or dh[mw[mi][iind]][iind] is the delay between two effective (mi) waves m=mw[mi][iind]
4305: and mw[mi+1][iind]. dh depends on stepm. */
4306: agebegin=agev[m][iind]; /* Age at beginning of wave before transition*/
4307: ageend=agev[m][iind]+(dh[m][iind])*stepm/YEARM; /* Age at end of wave and transition */
4308: if(m >=firstpass && m <=lastpass){
4309: k2=anint[m][iind]+(mint[m][iind]/12.);
4310: /*if ((k2>=dateprev1) && (k2<=dateprev2)) {*/
4311: if(agev[m][iind]==0) agev[m][iind]=iagemax+1; /* All ages equal to 0 are in iagemax+1 */
4312: if(agev[m][iind]==1) agev[m][iind]=iagemax+2; /* All ages equal to 1 are in iagemax+2 */
4313: if (s[m][iind]>0 && s[m][iind]<=nlstate) /* If status at wave m is known and a live state */
4314: prop[s[m][iind]][(int)agev[m][iind]] += weight[iind]; /* At age of beginning of transition, where status is known */
4315: if (m<lastpass) {
4316: /* if(s[m][iind]==4 && s[m+1][iind]==4) */
4317: /* 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]); */
4318: if(s[m][iind]==-1)
4319: 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.));
4320: freq[s[m][iind]][s[m+1][iind]][(int)agev[m][iind]] += weight[iind]; /* At age of beginning of transition, where status is known */
4321: /* freq[s[m][iind]][s[m+1][iind]][(int)((agebegin+ageend)/2.)] += weight[iind]; */
4322: 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 */
4323: }
4324: } /* end if between passes */
4325: if ((agev[m][iind]>1) && (agev[m][iind]< (iagemax+3)) && (anint[m][iind]!=9999) && (mint[m][iind]!=99)) {
4326: dateintsum=dateintsum+k2;
4327: k2cpt++;
4328: /* printf("iind=%ld dateintmean = %lf dateintsum=%lf k2cpt=%lf k2=%lf\n",iind, dateintsum/k2cpt, dateintsum,k2cpt, k2); */
4329: }
4330: } /* end bool 2 */
4331: } /* end m */
1.226 brouard 4332: } /* end bool */
4333: } /* end iind = 1 to imx */
4334: /* prop[s][age] is feeded for any initial and valid live state as well as
4335: freq[s1][s2][age] at single age of beginning the transition, for a combination j1 */
1.240 brouard 4336:
4337:
1.226 brouard 4338: /* fprintf(ficresp, "#Count between %.lf/%.lf/%.lf and %.lf/%.lf/%.lf\n",jprev1, mprev1,anprev1,jprev2, mprev2,anprev2);*/
4339: pstamp(ficresp);
1.240 brouard 4340: if (cptcoveff>0){
1.226 brouard 4341: fprintf(ficresp, "\n#********** Variable ");
4342: fprintf(ficresphtm, "\n<br/><br/><h3>********** Variable ");
4343: fprintf(ficresphtmfr, "\n<br/><br/><h3>********** Variable ");
1.240 brouard 4344: fprintf(ficlog, "\n#********** Variable ");
1.227 brouard 4345: for (z1=1; z1<=cptcoveff; z1++){
1.240 brouard 4346: if(DummyV[z1]){
4347: fprintf(ficresp, "V%d (fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4348: fprintf(ficresphtm, "V%d (fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4349: fprintf(ficresphtmfr, "V%d (fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4350: fprintf(ficlog, "V%d (fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4351: }else{
4352: fprintf(ficresp, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4353: fprintf(ficresphtm, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4354: fprintf(ficresphtmfr, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4355: fprintf(ficlog, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4356: }
1.226 brouard 4357: }
4358: fprintf(ficresp, "**********\n#");
4359: fprintf(ficresphtm, "**********</h3>\n");
4360: fprintf(ficresphtmfr, "**********</h3>\n");
4361: fprintf(ficlog, "**********\n");
4362: }
4363: fprintf(ficresphtm,"<table style=\"text-align:center; border: 1px solid\">");
4364: for(i=1; i<=nlstate;i++) {
1.240 brouard 4365: fprintf(ficresp, " Age Prev(%d) N(%d) N ",i,i);
1.226 brouard 4366: fprintf(ficresphtm, "<th>Age</th><th>Prev(%d)</th><th>N(%d)</th><th>N</th>",i,i);
4367: }
4368: fprintf(ficresp, "\n");
4369: fprintf(ficresphtm, "\n");
1.240 brouard 4370:
1.226 brouard 4371: /* Header of frequency table by age */
4372: fprintf(ficresphtmfr,"<table style=\"text-align:center; border: 1px solid\">");
4373: fprintf(ficresphtmfr,"<th>Age</th> ");
4374: for(jk=-1; jk <=nlstate+ndeath; jk++){
4375: for(m=-1; m <=nlstate+ndeath; m++){
1.234 brouard 4376: if(jk!=0 && m!=0)
4377: fprintf(ficresphtmfr,"<th>%d%d</th> ",jk,m);
1.226 brouard 4378: }
4379: }
4380: fprintf(ficresphtmfr, "\n");
1.240 brouard 4381:
1.226 brouard 4382: /* For each age */
4383: for(iage=iagemin; iage <= iagemax+3; iage++){
4384: fprintf(ficresphtm,"<tr>");
4385: if(iage==iagemax+1){
1.240 brouard 4386: fprintf(ficlog,"1");
4387: fprintf(ficresphtmfr,"<tr><th>0</th> ");
1.226 brouard 4388: }else if(iage==iagemax+2){
1.240 brouard 4389: fprintf(ficlog,"0");
4390: fprintf(ficresphtmfr,"<tr><th>Unknown</th> ");
1.226 brouard 4391: }else if(iage==iagemax+3){
1.240 brouard 4392: fprintf(ficlog,"Total");
4393: fprintf(ficresphtmfr,"<tr><th>Total</th> ");
1.226 brouard 4394: }else{
1.240 brouard 4395: if(first==1){
4396: first=0;
4397: printf("See log file for details...\n");
4398: }
4399: fprintf(ficresphtmfr,"<tr><th>%d</th> ",iage);
4400: fprintf(ficlog,"Age %d", iage);
1.226 brouard 4401: }
4402: for(jk=1; jk <=nlstate ; jk++){
1.240 brouard 4403: for(m=-1, pp[jk]=0; m <=nlstate+ndeath ; m++)
4404: pp[jk] += freq[jk][m][iage];
1.226 brouard 4405: }
4406: for(jk=1; jk <=nlstate ; jk++){
1.240 brouard 4407: for(m=-1, pos=0; m <=0 ; m++)
4408: pos += freq[jk][m][iage];
4409: if(pp[jk]>=1.e-10){
4410: if(first==1){
4411: printf(" %d.=%.0f loss[%d]=%.1f%%",jk,pp[jk],jk,100*pos/pp[jk]);
4412: }
4413: fprintf(ficlog," %d.=%.0f loss[%d]=%.1f%%",jk,pp[jk],jk,100*pos/pp[jk]);
4414: }else{
4415: if(first==1)
4416: printf(" %d.=%.0f loss[%d]=NaNQ%%",jk,pp[jk],jk);
4417: fprintf(ficlog," %d.=%.0f loss[%d]=NaNQ%%",jk,pp[jk],jk);
4418: }
1.226 brouard 4419: }
1.240 brouard 4420:
1.226 brouard 4421: for(jk=1; jk <=nlstate ; jk++){
1.240 brouard 4422: /* posprop[jk]=0; */
4423: for(m=0, pp[jk]=0; m <=nlstate+ndeath; m++)/* Summing on all ages */
4424: pp[jk] += freq[jk][m][iage];
1.226 brouard 4425: } /* pp[jk] is the total number of transitions starting from state jk and any ending status until this age */
1.240 brouard 4426:
1.226 brouard 4427: for(jk=1,pos=0, pospropta=0.; jk <=nlstate ; jk++){
1.240 brouard 4428: pos += pp[jk]; /* pos is the total number of transitions until this age */
4429: posprop[jk] += prop[jk][iage]; /* prop is the number of transitions from a live state
4430: from jk at age iage prop[s[m][iind]][(int)agev[m][iind]] += weight[iind] */
4431: pospropta += prop[jk][iage]; /* prop is the number of transitions from a live state
4432: from jk at age iage prop[s[m][iind]][(int)agev[m][iind]] += weight[iind] */
1.226 brouard 4433: }
4434: for(jk=1; jk <=nlstate ; jk++){
1.240 brouard 4435: if(pos>=1.e-5){
4436: if(first==1)
4437: printf(" %d.=%.0f prev[%d]=%.1f%%",jk,pp[jk],jk,100*pp[jk]/pos);
4438: fprintf(ficlog," %d.=%.0f prev[%d]=%.1f%%",jk,pp[jk],jk,100*pp[jk]/pos);
4439: }else{
4440: if(first==1)
4441: printf(" %d.=%.0f prev[%d]=NaNQ%%",jk,pp[jk],jk);
4442: fprintf(ficlog," %d.=%.0f prev[%d]=NaNQ%%",jk,pp[jk],jk);
4443: }
4444: if( iage <= iagemax){
4445: if(pos>=1.e-5){
4446: fprintf(ficresp," %d %.5f %.0f %.0f",iage,prop[jk][iage]/pospropta, prop[jk][iage],pospropta);
4447: fprintf(ficresphtm,"<th>%d</th><td>%.5f</td><td>%.0f</td><td>%.0f</td>",iage,prop[jk][iage]/pospropta, prop[jk][iage],pospropta);
4448: /*probs[iage][jk][j1]= pp[jk]/pos;*/
4449: /*printf("\niage=%d jk=%d j1=%d %.5f %.0f %.0f %f",iage,jk,j1,pp[jk]/pos, pp[jk],pos,probs[iage][jk][j1]);*/
4450: }
4451: else{
4452: fprintf(ficresp," %d NaNq %.0f %.0f",iage,prop[jk][iage],pospropta);
4453: fprintf(ficresphtm,"<th>%d</th><td>NaNq</td><td>%.0f</td><td>%.0f</td>",iage, prop[jk][iage],pospropta);
4454: }
4455: }
4456: pospropt[jk] +=posprop[jk];
1.226 brouard 4457: } /* end loop jk */
4458: /* pospropt=0.; */
4459: for(jk=-1; jk <=nlstate+ndeath; jk++){
1.240 brouard 4460: for(m=-1; m <=nlstate+ndeath; m++){
4461: if(freq[jk][m][iage] !=0 ) { /* minimizing output */
4462: if(first==1){
4463: printf(" %d%d=%.0f",jk,m,freq[jk][m][iage]);
4464: }
4465: fprintf(ficlog," %d%d=%.0f",jk,m,freq[jk][m][iage]);
4466: }
4467: if(jk!=0 && m!=0)
4468: fprintf(ficresphtmfr,"<td>%.0f</td> ",freq[jk][m][iage]);
4469: }
1.226 brouard 4470: } /* end loop jk */
4471: posproptt=0.;
4472: for(jk=1; jk <=nlstate; jk++){
1.240 brouard 4473: posproptt += pospropt[jk];
1.226 brouard 4474: }
4475: fprintf(ficresphtmfr,"</tr>\n ");
4476: if(iage <= iagemax){
1.240 brouard 4477: fprintf(ficresp,"\n");
4478: fprintf(ficresphtm,"</tr>\n");
1.226 brouard 4479: }
4480: if(first==1)
1.240 brouard 4481: printf("Others in log...\n");
1.226 brouard 4482: fprintf(ficlog,"\n");
4483: } /* end loop age iage */
4484: fprintf(ficresphtm,"<tr><th>Tot</th>");
4485: for(jk=1; jk <=nlstate ; jk++){
4486: if(posproptt < 1.e-5){
1.240 brouard 4487: fprintf(ficresphtm,"<td>Nanq</td><td>%.0f</td><td>%.0f</td>",pospropt[jk],posproptt);
1.226 brouard 4488: }else{
1.240 brouard 4489: fprintf(ficresphtm,"<td>%.5f</td><td>%.0f</td><td>%.0f</td>",pospropt[jk]/posproptt,pospropt[jk],posproptt);
1.226 brouard 4490: }
4491: }
4492: fprintf(ficresphtm,"</tr>\n");
4493: fprintf(ficresphtm,"</table>\n");
4494: fprintf(ficresphtmfr,"</table>\n");
4495: if(posproptt < 1.e-5){
4496: fprintf(ficresphtm,"\n <p><b> This combination (%d) is not valid and no result will be produced</b></p>",j1);
4497: fprintf(ficresphtmfr,"\n <p><b> This combination (%d) is not valid and no result will be produced</b></p>",j1);
4498: fprintf(ficres,"\n This combination (%d) is not valid and no result will be produced\n\n",j1);
4499: invalidvarcomb[j1]=1;
4500: }else{
4501: fprintf(ficresphtm,"\n <p> This combination (%d) is valid and result will be produced.</p>",j1);
4502: invalidvarcomb[j1]=0;
4503: }
4504: fprintf(ficresphtmfr,"</table>\n");
4505: } /* end selected combination of covariate j1 */
4506: dateintmean=dateintsum/k2cpt;
1.240 brouard 4507:
1.226 brouard 4508: fclose(ficresp);
4509: fclose(ficresphtm);
4510: fclose(ficresphtmfr);
4511: free_vector(meanq,1,nqfveff);
4512: free_matrix(meanqt,1,lastpass,1,nqtveff);
4513: free_ma3x(freq,-5,nlstate+ndeath,-5,nlstate+ndeath, iagemin-AGEMARGE, iagemax+3+AGEMARGE);
4514: free_vector(pospropt,1,nlstate);
4515: free_vector(posprop,1,nlstate);
4516: free_matrix(prop,1,nlstate,iagemin-AGEMARGE, iagemax+3+AGEMARGE);
4517: free_vector(pp,1,nlstate);
4518: /* End of freqsummary */
4519: }
1.126 brouard 4520:
4521: /************ Prevalence ********************/
1.227 brouard 4522: 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)
4523: {
4524: /* Compute observed prevalence between dateprev1 and dateprev2 by counting the number of people
4525: in each health status at the date of interview (if between dateprev1 and dateprev2).
4526: We still use firstpass and lastpass as another selection.
4527: */
1.126 brouard 4528:
1.227 brouard 4529: int i, m, jk, j1, bool, z1,j, iv;
4530: int mi; /* Effective wave */
4531: int iage;
4532: double agebegin, ageend;
4533:
4534: double **prop;
4535: double posprop;
4536: double y2; /* in fractional years */
4537: int iagemin, iagemax;
4538: int first; /** to stop verbosity which is redirected to log file */
4539:
4540: iagemin= (int) agemin;
4541: iagemax= (int) agemax;
4542: /*pp=vector(1,nlstate);*/
4543: prop=matrix(1,nlstate,iagemin-AGEMARGE,iagemax+3+AGEMARGE);
4544: /* freq=ma3x(-1,nlstate+ndeath,-1,nlstate+ndeath,iagemin,iagemax+3);*/
4545: j1=0;
1.222 brouard 4546:
1.227 brouard 4547: /*j=cptcoveff;*/
4548: if (cptcovn<1) {j=1;ncodemax[1]=1;}
1.222 brouard 4549:
1.227 brouard 4550: first=1;
4551: for(j1=1; j1<= (int) pow(2,cptcoveff);j1++){ /* For each combination of covariate */
4552: for (i=1; i<=nlstate; i++)
4553: for(iage=iagemin-AGEMARGE; iage <= iagemax+3+AGEMARGE; iage++)
4554: prop[i][iage]=0.0;
4555: printf("Prevalence combination of varying and fixed dummies %d\n",j1);
4556: /* fprintf(ficlog," V%d=%d ",Tvaraff[j1],nbcode[Tvaraff[j1]][codtabm(k,j1)]); */
4557: fprintf(ficlog,"Prevalence combination of varying and fixed dummies %d\n",j1);
4558:
4559: for (i=1; i<=imx; i++) { /* Each individual */
4560: bool=1;
4561: /* for(m=firstpass; m<=lastpass; m++){/\* Other selection (we can limit to certain interviews*\/ */
4562: for(mi=1; mi<wav[i];mi++){ /* For this wave too look where individual can be counted V4=0 V3=0 */
4563: m=mw[mi][i];
4564: /* Tmodelind[z1]=k is the position of the varying covariate in the model, but which # within 1 to ntv? */
4565: /* Tvar[Tmodelind[z1]] is the n of Vn; n-ncovcol-nqv is the first time varying covariate or iv */
4566: for (z1=1; z1<=cptcoveff; z1++){
4567: if( Fixed[Tmodelind[z1]]==1){
4568: iv= Tvar[Tmodelind[z1]]-ncovcol-nqv;
4569: if (cotvar[m][iv][i]!= nbcode[Tvaraff[z1]][codtabm(j1,z1)]) /* iv=1 to ntv, right modality */
4570: bool=0;
4571: }else if( Fixed[Tmodelind[z1]]== 0) /* fixed */
4572: if (covar[Tvaraff[z1]][i]!= nbcode[Tvaraff[z1]][codtabm(j1,z1)]) {
4573: bool=0;
4574: }
4575: }
4576: if(bool==1){ /* Otherwise we skip that wave/person */
4577: agebegin=agev[m][i]; /* Age at beginning of wave before transition*/
4578: /* ageend=agev[m][i]+(dh[m][i])*stepm/YEARM; /\* Age at end of wave and transition *\/ */
4579: if(m >=firstpass && m <=lastpass){
4580: y2=anint[m][i]+(mint[m][i]/12.); /* Fractional date in year */
4581: if ((y2>=dateprev1) && (y2<=dateprev2)) { /* Here is the main selection (fractional years) */
4582: if(agev[m][i]==0) agev[m][i]=iagemax+1;
4583: if(agev[m][i]==1) agev[m][i]=iagemax+2;
4584: if((int)agev[m][i] <iagemin-AGEMARGE || (int)agev[m][i] >iagemax+3+AGEMARGE){
4585: 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);
4586: exit(1);
4587: }
4588: if (s[m][i]>0 && s[m][i]<=nlstate) {
4589: /*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]]);*/
4590: prop[s[m][i]][(int)agev[m][i]] += weight[i];/* At age of beginning of transition, where status is known */
4591: prop[s[m][i]][iagemax+3] += weight[i];
4592: } /* end valid statuses */
4593: } /* end selection of dates */
4594: } /* end selection of waves */
4595: } /* end bool */
4596: } /* end wave */
4597: } /* end individual */
4598: for(i=iagemin; i <= iagemax+3; i++){
4599: for(jk=1,posprop=0; jk <=nlstate ; jk++) {
4600: posprop += prop[jk][i];
4601: }
4602:
4603: for(jk=1; jk <=nlstate ; jk++){
4604: if( i <= iagemax){
4605: if(posprop>=1.e-5){
4606: probs[i][jk][j1]= prop[jk][i]/posprop;
4607: } else{
4608: if(first==1){
4609: first=0;
4610: printf("Warning Observed prevalence probs[%d][%d][%d]=%lf because of lack of cases\nSee others in log file...\n",jk,i,j1,probs[i][jk][j1]);
4611: }
4612: }
4613: }
4614: }/* end jk */
4615: }/* end i */
1.222 brouard 4616: /*} *//* end i1 */
1.227 brouard 4617: } /* end j1 */
1.222 brouard 4618:
1.227 brouard 4619: /* free_ma3x(freq,-1,nlstate+ndeath,-1,nlstate+ndeath, iagemin, iagemax+3);*/
4620: /*free_vector(pp,1,nlstate);*/
4621: free_matrix(prop,1,nlstate, iagemin-AGEMARGE,iagemax+3+AGEMARGE);
4622: } /* End of prevalence */
1.126 brouard 4623:
4624: /************* Waves Concatenation ***************/
4625:
4626: 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)
4627: {
4628: /* Concatenates waves: wav[i] is the number of effective (useful waves) of individual i.
4629: Death is a valid wave (if date is known).
4630: mw[mi][i] is the mi (mi=1 to wav[i]) effective wave of individual i
4631: dh[m][i] or dh[mw[mi][i]][i] is the delay between two effective waves m=mw[mi][i]
4632: and mw[mi+1][i]. dh depends on stepm.
1.227 brouard 4633: */
1.126 brouard 4634:
1.224 brouard 4635: int i=0, mi=0, m=0, mli=0;
1.126 brouard 4636: /* int j, k=0,jk, ju, jl,jmin=1e+5, jmax=-1;
4637: double sum=0., jmean=0.;*/
1.224 brouard 4638: int first=0, firstwo=0, firsthree=0, firstfour=0, firstfiv=0;
1.126 brouard 4639: int j, k=0,jk, ju, jl;
4640: double sum=0.;
4641: first=0;
1.214 brouard 4642: firstwo=0;
1.217 brouard 4643: firsthree=0;
1.218 brouard 4644: firstfour=0;
1.164 brouard 4645: jmin=100000;
1.126 brouard 4646: jmax=-1;
4647: jmean=0.;
1.224 brouard 4648:
4649: /* Treating live states */
1.214 brouard 4650: for(i=1; i<=imx; i++){ /* For simple cases and if state is death */
1.224 brouard 4651: mi=0; /* First valid wave */
1.227 brouard 4652: mli=0; /* Last valid wave */
1.126 brouard 4653: m=firstpass;
1.214 brouard 4654: while(s[m][i] <= nlstate){ /* a live state */
1.227 brouard 4655: 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 */
4656: mli=m-1;/* mw[++mi][i]=m-1; */
4657: }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 */
4658: mw[++mi][i]=m;
4659: mli=m;
1.224 brouard 4660: } /* else might be a useless wave -1 and mi is not incremented and mw[mi] not updated */
4661: if(m < lastpass){ /* m < lastpass, standard case */
1.227 brouard 4662: m++; /* mi gives the "effective" current wave, m the current wave, go to next wave by incrementing m */
1.216 brouard 4663: }
1.227 brouard 4664: else{ /* m >= lastpass, eventual special issue with warning */
1.224 brouard 4665: #ifdef UNKNOWNSTATUSNOTCONTRIBUTING
1.227 brouard 4666: break;
1.224 brouard 4667: #else
1.227 brouard 4668: if(s[m][i]==-1 && (int) andc[i] == 9999 && (int)anint[m][i] != 9999){
4669: if(firsthree == 0){
4670: 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 pi. .\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);
4671: firsthree=1;
4672: }
4673: 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 pi. .\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);
4674: mw[++mi][i]=m;
4675: mli=m;
4676: }
4677: if(s[m][i]==-2){ /* Vital status is really unknown */
4678: nbwarn++;
4679: if((int)anint[m][i] == 9999){ /* Has the vital status really been verified? */
4680: 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);
4681: 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);
4682: }
4683: break;
4684: }
4685: break;
1.224 brouard 4686: #endif
1.227 brouard 4687: }/* End m >= lastpass */
1.126 brouard 4688: }/* end while */
1.224 brouard 4689:
1.227 brouard 4690: /* 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 4691: /* After last pass */
1.224 brouard 4692: /* Treating death states */
1.214 brouard 4693: if (s[m][i] > nlstate){ /* In a death state */
1.227 brouard 4694: /* if( mint[m][i]==mdc[m][i] && anint[m][i]==andc[m][i]){ /\* same date of death and date of interview *\/ */
4695: /* } */
1.126 brouard 4696: mi++; /* Death is another wave */
4697: /* if(mi==0) never been interviewed correctly before death */
1.227 brouard 4698: /* Only death is a correct wave */
1.126 brouard 4699: mw[mi][i]=m;
1.224 brouard 4700: }
4701: #ifndef DISPATCHINGKNOWNDEATHAFTERLASTWAVE
1.227 brouard 4702: else if ((int) andc[i] != 9999) { /* Status is negative. A death occured after lastpass, we can't take it into account because of potential bias */
1.216 brouard 4703: /* m++; */
4704: /* mi++; */
4705: /* s[m][i]=nlstate+1; /\* We are setting the status to the last of non live state *\/ */
4706: /* mw[mi][i]=m; */
1.218 brouard 4707: if ((int)anint[m][i]!= 9999) { /* date of last interview is known */
1.227 brouard 4708: 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 */
4709: nbwarn++;
4710: if(firstfiv==0){
4711: 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 );
4712: firstfiv=1;
4713: }else{
4714: 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 );
4715: }
4716: }else{ /* Death occured afer last wave potential bias */
4717: nberr++;
4718: if(firstwo==0){
4719: 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.\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 );
4720: firstwo=1;
4721: }
4722: 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.\n",num[i],i,(int) moisdc[i], (int) andc[i], lastpass,(int)mint[m][i],(int)anint[m][i], i,m );
4723: }
1.218 brouard 4724: }else{ /* end date of interview is known */
1.227 brouard 4725: /* death is known but not confirmed by death status at any wave */
4726: if(firstfour==0){
4727: 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 );
4728: firstfour=1;
4729: }
4730: 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 4731: }
1.224 brouard 4732: } /* end if date of death is known */
4733: #endif
4734: wav[i]=mi; /* mi should be the last effective wave (or mli) */
4735: /* wav[i]=mw[mi][i]; */
1.126 brouard 4736: if(mi==0){
4737: nbwarn++;
4738: if(first==0){
1.227 brouard 4739: printf("Warning! No valid information for individual %ld line=%d (skipped) and may be others, see log file\n",num[i],i);
4740: first=1;
1.126 brouard 4741: }
4742: if(first==1){
1.227 brouard 4743: fprintf(ficlog,"Warning! No valid information for individual %ld line=%d (skipped)\n",num[i],i);
1.126 brouard 4744: }
4745: } /* end mi==0 */
4746: } /* End individuals */
1.214 brouard 4747: /* wav and mw are no more changed */
1.223 brouard 4748:
1.214 brouard 4749:
1.126 brouard 4750: for(i=1; i<=imx; i++){
4751: for(mi=1; mi<wav[i];mi++){
4752: if (stepm <=0)
1.227 brouard 4753: dh[mi][i]=1;
1.126 brouard 4754: else{
1.227 brouard 4755: if (s[mw[mi+1][i]][i] > nlstate) { /* A death */
4756: if (agedc[i] < 2*AGESUP) {
4757: j= rint(agedc[i]*12-agev[mw[mi][i]][i]*12);
4758: if(j==0) j=1; /* Survives at least one month after exam */
4759: else if(j<0){
4760: nberr++;
4761: 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]);
4762: j=1; /* Temporary Dangerous patch */
4763: 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);
4764: 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]);
4765: 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);
4766: }
4767: k=k+1;
4768: if (j >= jmax){
4769: jmax=j;
4770: ijmax=i;
4771: }
4772: if (j <= jmin){
4773: jmin=j;
4774: ijmin=i;
4775: }
4776: sum=sum+j;
4777: /*if (j<0) printf("j=%d num=%d \n",j,i);*/
4778: /* printf("%d %d %d %d\n", s[mw[mi][i]][i] ,s[mw[mi+1][i]][i],j,i);*/
4779: }
4780: }
4781: else{
4782: j= rint( (agev[mw[mi+1][i]][i]*12 - agev[mw[mi][i]][i]*12));
1.126 brouard 4783: /* 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 4784:
1.227 brouard 4785: k=k+1;
4786: if (j >= jmax) {
4787: jmax=j;
4788: ijmax=i;
4789: }
4790: else if (j <= jmin){
4791: jmin=j;
4792: ijmin=i;
4793: }
4794: /* if (j<10) printf("j=%d jmin=%d num=%d ",j,jmin,i); */
4795: /*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]);*/
4796: if(j<0){
4797: nberr++;
4798: 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]);
4799: 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]);
4800: }
4801: sum=sum+j;
4802: }
4803: jk= j/stepm;
4804: jl= j -jk*stepm;
4805: ju= j -(jk+1)*stepm;
4806: if(mle <=1){ /* only if we use a the linear-interpoloation pseudo-likelihood */
4807: if(jl==0){
4808: dh[mi][i]=jk;
4809: bh[mi][i]=0;
4810: }else{ /* We want a negative bias in order to only have interpolation ie
4811: * to avoid the price of an extra matrix product in likelihood */
4812: dh[mi][i]=jk+1;
4813: bh[mi][i]=ju;
4814: }
4815: }else{
4816: if(jl <= -ju){
4817: dh[mi][i]=jk;
4818: bh[mi][i]=jl; /* bias is positive if real duration
4819: * is higher than the multiple of stepm and negative otherwise.
4820: */
4821: }
4822: else{
4823: dh[mi][i]=jk+1;
4824: bh[mi][i]=ju;
4825: }
4826: if(dh[mi][i]==0){
4827: dh[mi][i]=1; /* At least one step */
4828: bh[mi][i]=ju; /* At least one step */
4829: /* 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);*/
4830: }
4831: } /* end if mle */
1.126 brouard 4832: }
4833: } /* end wave */
4834: }
4835: jmean=sum/k;
4836: 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 4837: 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 4838: }
1.126 brouard 4839:
4840: /*********** Tricode ****************************/
1.220 brouard 4841: void tricode(int *cptcov, int *Tvar, int **nbcode, int imx, int *Ndum)
1.242 brouard 4842: {
4843: /**< Uses cptcovn+2*cptcovprod as the number of covariates */
4844: /* Tvar[i]=atoi(stre); find 'n' in Vn and stores in Tvar. If model=V2+V1 Tvar[1]=2 and Tvar[2]=1
4845: * Boring subroutine which should only output nbcode[Tvar[j]][k]
4846: * Tvar[5] in V2+V1+V3*age+V2*V4 is 4 (V4) even it is a time varying or quantitative variable
4847: * nbcode[Tvar[5]][1]= nbcode[4][1]=0, nbcode[4][2]=1 (usually);
4848: */
1.130 brouard 4849:
1.242 brouard 4850: int ij=1, k=0, j=0, i=0, maxncov=NCOVMAX;
4851: int modmaxcovj=0; /* Modality max of covariates j */
4852: int cptcode=0; /* Modality max of covariates j */
4853: int modmincovj=0; /* Modality min of covariates j */
1.145 brouard 4854:
4855:
1.242 brouard 4856: /* cptcoveff=0; */
4857: /* *cptcov=0; */
1.126 brouard 4858:
1.242 brouard 4859: for (k=1; k <= maxncov; k++) ncodemax[k]=0; /* Horrible constant again replaced by NCOVMAX */
1.126 brouard 4860:
1.242 brouard 4861: /* Loop on covariates without age and products and no quantitative variable */
4862: /* for (j=1; j<=(cptcovs); j++) { /\* From model V1 + V2*age+ V3 + V3*V4 keeps V1 + V3 = 2 only *\/ */
4863: for (k=1; k<=cptcovt; k++) { /* From model V1 + V2*age + V3 + V3*V4 keeps V1 + V3 = 2 only */
4864: for (j=-1; (j < maxncov); j++) Ndum[j]=0;
4865: if(Dummy[k]==0 && Typevar[k] !=1){ /* Dummy covariate and not age product */
4866: switch(Fixed[k]) {
4867: case 0: /* Testing on fixed dummy covariate, simple or product of fixed */
4868: 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*/
4869: ij=(int)(covar[Tvar[k]][i]);
4870: /* ij=0 or 1 or -1. Value of the covariate Tvar[j] for individual i
4871: * If product of Vn*Vm, still boolean *:
4872: * If it was coded 1, 2, 3, 4 should be splitted into 3 boolean variables
4873: * 1 => 0 0 0, 2 => 0 0 1, 3 => 0 1 1, 4=1 0 0 */
4874: /* Finds for covariate j, n=Tvar[j] of Vn . ij is the
4875: modality of the nth covariate of individual i. */
4876: if (ij > modmaxcovj)
4877: modmaxcovj=ij;
4878: else if (ij < modmincovj)
4879: modmincovj=ij;
4880: if ((ij < -1) && (ij > NCOVMAX)){
4881: printf( "Error: minimal is less than -1 or maximal is bigger than %d. Exiting. \n", NCOVMAX );
4882: exit(1);
4883: }else
4884: Ndum[ij]++; /*counts and stores the occurence of this modality 0, 1, -1*/
4885: /* If coded 1, 2, 3 , counts the number of 1 Ndum[1], number of 2, Ndum[2], etc */
4886: /*printf("i=%d ij=%d Ndum[ij]=%d imx=%d",i,ij,Ndum[ij],imx);*/
4887: /* getting the maximum value of the modality of the covariate
4888: (should be 0 or 1 now) Tvar[j]. If V=sex and male is coded 0 and
4889: female ies 1, then modmaxcovj=1.
4890: */
4891: } /* end for loop on individuals i */
4892: printf(" Minimal and maximal values of %d th (fixed) covariate V%d: min=%d max=%d \n", k, Tvar[k], modmincovj, modmaxcovj);
4893: fprintf(ficlog," Minimal and maximal values of %d th (fixed) covariate V%d: min=%d max=%d \n", k, Tvar[k], modmincovj, modmaxcovj);
4894: cptcode=modmaxcovj;
4895: /* Ndum[0] = frequency of 0 for model-covariate j, Ndum[1] frequency of 1 etc. */
4896: /*for (i=0; i<=cptcode; i++) {*/
4897: for (j=modmincovj; j<=modmaxcovj; j++) { /* j=-1 ? 0 and 1*//* For each value j of the modality of model-cov k */
4898: printf("Frequencies of (fixed) covariate %d ie V%d with value %d: %d\n", k, Tvar[k], j, Ndum[j]);
4899: fprintf(ficlog, "Frequencies of (fixed) covariate %d ie V%d with value %d: %d\n", k, Tvar[k], j, Ndum[j]);
4900: if( Ndum[j] != 0 ){ /* Counts if nobody answered modality j ie empty modality, we skip it and reorder */
4901: if( j != -1){
4902: ncodemax[k]++; /* ncodemax[k]= Number of modalities of the k th
4903: covariate for which somebody answered excluding
4904: undefined. Usually 2: 0 and 1. */
4905: }
4906: ncodemaxwundef[k]++; /* ncodemax[j]= Number of modalities of the k th
4907: covariate for which somebody answered including
4908: undefined. Usually 3: -1, 0 and 1. */
4909: } /* In fact ncodemax[k]=2 (dichotom. variables only) but it could be more for
4910: * historical reasons: 3 if coded 1, 2, 3 and 4 and Ndum[2]=0 */
4911: } /* Ndum[-1] number of undefined modalities */
1.231 brouard 4912:
1.242 brouard 4913: /* j is a covariate, n=Tvar[j] of Vn; Fills nbcode */
4914: /* For covariate j, modalities could be 1, 2, 3, 4, 5, 6, 7. */
4915: /* If Ndum[1]=0, Ndum[2]=0, Ndum[3]= 635, Ndum[4]=0, Ndum[5]=0, Ndum[6]=27, Ndum[7]=125; */
4916: /* modmincovj=3; modmaxcovj = 7; */
4917: /* There are only 3 modalities non empty 3, 6, 7 (or 2 if 27 is too few) : ncodemax[j]=3; */
4918: /* which will be coded 0, 1, 2 which in binary on 2=3-1 digits are 0=00 1=01, 2=10; */
4919: /* defining two dummy variables: variables V1_1 and V1_2.*/
4920: /* nbcode[Tvar[j]][ij]=k; */
4921: /* nbcode[Tvar[j]][1]=0; */
4922: /* nbcode[Tvar[j]][2]=1; */
4923: /* nbcode[Tvar[j]][3]=2; */
4924: /* To be continued (not working yet). */
4925: ij=0; /* ij is similar to i but can jump over null modalities */
4926: 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*/
4927: if (Ndum[i] == 0) { /* If nobody responded to this modality k */
4928: break;
4929: }
4930: ij++;
4931: 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*/
4932: cptcode = ij; /* New max modality for covar j */
4933: } /* end of loop on modality i=-1 to 1 or more */
4934: break;
4935: case 1: /* Testing on varying covariate, could be simple and
4936: * should look at waves or product of fixed *
4937: * varying. No time to test -1, assuming 0 and 1 only */
4938: ij=0;
4939: for(i=0; i<=1;i++){
4940: nbcode[Tvar[k]][++ij]=i;
4941: }
4942: break;
4943: default:
4944: break;
4945: } /* end switch */
4946: } /* end dummy test */
4947:
4948: /* for (k=0; k<= cptcode; k++) { /\* k=-1 ? k=0 to 1 *\//\* Could be 1 to 4 *\//\* cptcode=modmaxcovj *\/ */
4949: /* /\*recode from 0 *\/ */
4950: /* k is a modality. If we have model=V1+V1*sex */
4951: /* then: nbcode[1][1]=0 ; nbcode[1][2]=1; nbcode[2][1]=0 ; nbcode[2][2]=1; */
4952: /* But if some modality were not used, it is recoded from 0 to a newer modmaxcovj=cptcode *\/ */
4953: /* } */
4954: /* /\* cptcode = ij; *\/ /\* New max modality for covar j *\/ */
4955: /* if (ij > ncodemax[j]) { */
4956: /* printf( " Error ij=%d > ncodemax[%d]=%d\n", ij, j, ncodemax[j]); */
4957: /* fprintf(ficlog, " Error ij=%d > ncodemax[%d]=%d\n", ij, j, ncodemax[j]); */
4958: /* break; */
4959: /* } */
4960: /* } /\* end of loop on modality k *\/ */
4961: } /* end of loop on model-covariate j. nbcode[Tvarj][1]=0 and nbcode[Tvarj][2]=1 sets the value of covariate j*/
4962:
4963: for (k=-1; k< maxncov; k++) Ndum[k]=0;
4964: /* Look at fixed dummy (single or product) covariates to check empty modalities */
4965: for (i=1; i<=ncovmodel-2-nagesqr; i++) { /* -2, cste and age and eventually age*age */
4966: /* Listing of all covariables in statement model to see if some covariates appear twice. For example, V1 appears twice in V1+V1*V2.*/
4967: 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 */
4968: 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 */
4969: /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, {2, 1, 1, 1, 2, 1, 1, 0, 0} */
4970: } /* V4+V3+V5, Ndum[1]@5={0, 0, 1, 1, 1} */
4971:
4972: ij=0;
4973: /* for (i=0; i<= maxncov-1; i++) { /\* modmaxcovj is unknown here. Only Ndum[2(V2),3(age*V3), 5(V3*V2) 6(V1*V4) *\/ */
4974: for (k=1; k<= cptcovt; k++) { /* modmaxcovj is unknown here. Only Ndum[2(V2),3(age*V3), 5(V3*V2) 6(V1*V4) */
4975: /*printf("Ndum[%d]=%d\n",i, Ndum[i]);*/
4976: /* if((Ndum[i]!=0) && (i<=ncovcol)){ /\* Tvar[i] <= ncovmodel ? *\/ */
4977: if(Ndum[Tvar[k]]!=0 && Dummy[k] == 0 && Typevar[k]==0){ /* Only Dummy and non empty in the model */
4978: /* If product not in single variable we don't print results */
4979: /*printf("diff Ndum[%d]=%d\n",i, Ndum[i]);*/
4980: ++ij;/* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, */
4981: 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*/
4982: Tmodelind[ij]=k; /* Tmodelind: index in model of dummies Tmodelind[1]=2 V4: pos=2; V3: pos=3, V1=9 {2, 3, 9, ?, ?,} */
4983: 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 */
4984: if(Fixed[k]!=0)
4985: anyvaryingduminmodel=1;
4986: /* }else if((Ndum[i]!=0) && (i<=ncovcol+nqv)){ */
4987: /* Tvaraff[++ij]=-10; /\* Dont'n know how to treat quantitative variables yet *\/ */
4988: /* }else if((Ndum[i]!=0) && (i<=ncovcol+nqv+ntv)){ */
4989: /* Tvaraff[++ij]=i; /\*For printing (unclear) *\/ */
4990: /* }else if((Ndum[i]!=0) && (i<=ncovcol+nqv+ntv+nqtv)){ */
4991: /* Tvaraff[++ij]=-20; /\* Dont'n know how to treat quantitative variables yet *\/ */
4992: }
4993: } /* Tvaraff[1]@5 {3, 4, -20, 0, 0} Very strange */
4994: /* ij--; */
4995: /* cptcoveff=ij; /\*Number of total covariates*\/ */
4996: *cptcov=ij; /*Number of total real effective covariates: effective
4997: * because they can be excluded from the model and real
4998: * if in the model but excluded because missing values, but how to get k from ij?*/
4999: for(j=ij+1; j<= cptcovt; j++){
5000: Tvaraff[j]=0;
5001: Tmodelind[j]=0;
5002: }
5003: for(j=ntveff+1; j<= cptcovt; j++){
5004: TmodelInvind[j]=0;
5005: }
5006: /* To be sorted */
5007: ;
5008: }
1.126 brouard 5009:
1.145 brouard 5010:
1.126 brouard 5011: /*********** Health Expectancies ****************/
5012:
1.235 brouard 5013: 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 5014:
5015: {
5016: /* Health expectancies, no variances */
1.164 brouard 5017: int i, j, nhstepm, hstepm, h, nstepm;
1.126 brouard 5018: int nhstepma, nstepma; /* Decreasing with age */
5019: double age, agelim, hf;
5020: double ***p3mat;
5021: double eip;
5022:
1.238 brouard 5023: /* pstamp(ficreseij); */
1.126 brouard 5024: fprintf(ficreseij,"# (a) Life expectancies by health status at initial age and (b) health expectancies by health status at initial age\n");
5025: fprintf(ficreseij,"# Age");
5026: for(i=1; i<=nlstate;i++){
5027: for(j=1; j<=nlstate;j++){
5028: fprintf(ficreseij," e%1d%1d ",i,j);
5029: }
5030: fprintf(ficreseij," e%1d. ",i);
5031: }
5032: fprintf(ficreseij,"\n");
5033:
5034:
5035: if(estepm < stepm){
5036: printf ("Problem %d lower than %d\n",estepm, stepm);
5037: }
5038: else hstepm=estepm;
5039: /* We compute the life expectancy from trapezoids spaced every estepm months
5040: * This is mainly to measure the difference between two models: for example
5041: * if stepm=24 months pijx are given only every 2 years and by summing them
5042: * we are calculating an estimate of the Life Expectancy assuming a linear
5043: * progression in between and thus overestimating or underestimating according
5044: * to the curvature of the survival function. If, for the same date, we
5045: * estimate the model with stepm=1 month, we can keep estepm to 24 months
5046: * to compare the new estimate of Life expectancy with the same linear
5047: * hypothesis. A more precise result, taking into account a more precise
5048: * curvature will be obtained if estepm is as small as stepm. */
5049:
5050: /* For example we decided to compute the life expectancy with the smallest unit */
5051: /* hstepm beeing the number of stepms, if hstepm=1 the length of hstepm is stepm.
5052: nhstepm is the number of hstepm from age to agelim
5053: nstepm is the number of stepm from age to agelin.
5054: Look at hpijx to understand the reason of that which relies in memory size
5055: and note for a fixed period like estepm months */
5056: /* We decided (b) to get a life expectancy respecting the most precise curvature of the
5057: survival function given by stepm (the optimization length). Unfortunately it
5058: means that if the survival funtion is printed only each two years of age and if
5059: you sum them up and add 1 year (area under the trapezoids) you won't get the same
5060: results. So we changed our mind and took the option of the best precision.
5061: */
5062: hstepm=hstepm/stepm; /* Typically in stepm units, if stepm=6 & estepm=24 , = 24/6 months = 4 */
5063:
5064: agelim=AGESUP;
5065: /* If stepm=6 months */
5066: /* Computed by stepm unit matrices, product of hstepm matrices, stored
5067: in an array of nhstepm length: nhstepm=10, hstepm=4, stepm=6 months */
5068:
5069: /* nhstepm age range expressed in number of stepm */
5070: nstepm=(int) rint((agelim-bage)*YEARM/stepm); /* Biggest nstepm */
5071: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
5072: /* if (stepm >= YEARM) hstepm=1;*/
5073: nhstepm = nstepm/hstepm;/* Expressed in hstepm, typically nhstepm=40/4=10 */
5074: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
5075:
5076: for (age=bage; age<=fage; age ++){
5077: nstepma=(int) rint((agelim-bage)*YEARM/stepm); /* Biggest nstepm */
5078: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
5079: /* if (stepm >= YEARM) hstepm=1;*/
5080: nhstepma = nstepma/hstepm;/* Expressed in hstepm, typically nhstepma=40/4=10 */
5081:
5082: /* If stepm=6 months */
5083: /* Computed by stepm unit matrices, product of hstepma matrices, stored
5084: in an array of nhstepma length: nhstepma=10, hstepm=4, stepm=6 months */
5085:
1.235 brouard 5086: hpxij(p3mat,nhstepma,age,hstepm,x,nlstate,stepm,oldm, savm, cij, nres);
1.126 brouard 5087:
5088: hf=hstepm*stepm/YEARM; /* Duration of hstepm expressed in year unit. */
5089:
5090: printf("%d|",(int)age);fflush(stdout);
5091: fprintf(ficlog,"%d|",(int)age);fflush(ficlog);
5092:
5093: /* Computing expectancies */
5094: for(i=1; i<=nlstate;i++)
5095: for(j=1; j<=nlstate;j++)
5096: for (h=0, eij[i][j][(int)age]=0; h<=nhstepm-1; h++){
5097: eij[i][j][(int)age] += (p3mat[i][j][h]+p3mat[i][j][h+1])/2.0*hf;
5098:
5099: /* 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]);*/
5100:
5101: }
5102:
5103: fprintf(ficreseij,"%3.0f",age );
5104: for(i=1; i<=nlstate;i++){
5105: eip=0;
5106: for(j=1; j<=nlstate;j++){
5107: eip +=eij[i][j][(int)age];
5108: fprintf(ficreseij,"%9.4f", eij[i][j][(int)age] );
5109: }
5110: fprintf(ficreseij,"%9.4f", eip );
5111: }
5112: fprintf(ficreseij,"\n");
5113:
5114: }
5115: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
5116: printf("\n");
5117: fprintf(ficlog,"\n");
5118:
5119: }
5120:
1.235 brouard 5121: 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 5122:
5123: {
5124: /* Covariances of health expectancies eij and of total life expectancies according
1.222 brouard 5125: to initial status i, ei. .
1.126 brouard 5126: */
5127: int i, j, nhstepm, hstepm, h, nstepm, k, cptj, cptj2, i2, j2, ij, ji;
5128: int nhstepma, nstepma; /* Decreasing with age */
5129: double age, agelim, hf;
5130: double ***p3matp, ***p3matm, ***varhe;
5131: double **dnewm,**doldm;
5132: double *xp, *xm;
5133: double **gp, **gm;
5134: double ***gradg, ***trgradg;
5135: int theta;
5136:
5137: double eip, vip;
5138:
5139: varhe=ma3x(1,nlstate*nlstate,1,nlstate*nlstate,(int) bage, (int) fage);
5140: xp=vector(1,npar);
5141: xm=vector(1,npar);
5142: dnewm=matrix(1,nlstate*nlstate,1,npar);
5143: doldm=matrix(1,nlstate*nlstate,1,nlstate*nlstate);
5144:
5145: pstamp(ficresstdeij);
5146: fprintf(ficresstdeij,"# Health expectancies with standard errors\n");
5147: fprintf(ficresstdeij,"# Age");
5148: for(i=1; i<=nlstate;i++){
5149: for(j=1; j<=nlstate;j++)
5150: fprintf(ficresstdeij," e%1d%1d (SE)",i,j);
5151: fprintf(ficresstdeij," e%1d. ",i);
5152: }
5153: fprintf(ficresstdeij,"\n");
5154:
5155: pstamp(ficrescveij);
5156: fprintf(ficrescveij,"# Subdiagonal matrix of covariances of health expectancies by age: cov(eij,ekl)\n");
5157: fprintf(ficrescveij,"# Age");
5158: for(i=1; i<=nlstate;i++)
5159: for(j=1; j<=nlstate;j++){
5160: cptj= (j-1)*nlstate+i;
5161: for(i2=1; i2<=nlstate;i2++)
5162: for(j2=1; j2<=nlstate;j2++){
5163: cptj2= (j2-1)*nlstate+i2;
5164: if(cptj2 <= cptj)
5165: fprintf(ficrescveij," %1d%1d,%1d%1d",i,j,i2,j2);
5166: }
5167: }
5168: fprintf(ficrescveij,"\n");
5169:
5170: if(estepm < stepm){
5171: printf ("Problem %d lower than %d\n",estepm, stepm);
5172: }
5173: else hstepm=estepm;
5174: /* We compute the life expectancy from trapezoids spaced every estepm months
5175: * This is mainly to measure the difference between two models: for example
5176: * if stepm=24 months pijx are given only every 2 years and by summing them
5177: * we are calculating an estimate of the Life Expectancy assuming a linear
5178: * progression in between and thus overestimating or underestimating according
5179: * to the curvature of the survival function. If, for the same date, we
5180: * estimate the model with stepm=1 month, we can keep estepm to 24 months
5181: * to compare the new estimate of Life expectancy with the same linear
5182: * hypothesis. A more precise result, taking into account a more precise
5183: * curvature will be obtained if estepm is as small as stepm. */
5184:
5185: /* For example we decided to compute the life expectancy with the smallest unit */
5186: /* hstepm beeing the number of stepms, if hstepm=1 the length of hstepm is stepm.
5187: nhstepm is the number of hstepm from age to agelim
5188: nstepm is the number of stepm from age to agelin.
5189: Look at hpijx to understand the reason of that which relies in memory size
5190: and note for a fixed period like estepm months */
5191: /* We decided (b) to get a life expectancy respecting the most precise curvature of the
5192: survival function given by stepm (the optimization length). Unfortunately it
5193: means that if the survival funtion is printed only each two years of age and if
5194: you sum them up and add 1 year (area under the trapezoids) you won't get the same
5195: results. So we changed our mind and took the option of the best precision.
5196: */
5197: hstepm=hstepm/stepm; /* Typically in stepm units, if stepm=6 & estepm=24 , = 24/6 months = 4 */
5198:
5199: /* If stepm=6 months */
5200: /* nhstepm age range expressed in number of stepm */
5201: agelim=AGESUP;
5202: nstepm=(int) rint((agelim-bage)*YEARM/stepm);
5203: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
5204: /* if (stepm >= YEARM) hstepm=1;*/
5205: nhstepm = nstepm/hstepm;/* Expressed in hstepm, typically nhstepm=40/4=10 */
5206:
5207: p3matp=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
5208: p3matm=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
5209: gradg=ma3x(0,nhstepm,1,npar,1,nlstate*nlstate);
5210: trgradg =ma3x(0,nhstepm,1,nlstate*nlstate,1,npar);
5211: gp=matrix(0,nhstepm,1,nlstate*nlstate);
5212: gm=matrix(0,nhstepm,1,nlstate*nlstate);
5213:
5214: for (age=bage; age<=fage; age ++){
5215: nstepma=(int) rint((agelim-bage)*YEARM/stepm); /* Biggest nstepm */
5216: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
5217: /* if (stepm >= YEARM) hstepm=1;*/
5218: nhstepma = nstepma/hstepm;/* Expressed in hstepm, typically nhstepma=40/4=10 */
1.218 brouard 5219:
1.126 brouard 5220: /* If stepm=6 months */
5221: /* Computed by stepm unit matrices, product of hstepma matrices, stored
5222: in an array of nhstepma length: nhstepma=10, hstepm=4, stepm=6 months */
5223:
5224: hf=hstepm*stepm/YEARM; /* Duration of hstepm expressed in year unit. */
1.218 brouard 5225:
1.126 brouard 5226: /* Computing Variances of health expectancies */
5227: /* Gradient is computed with plus gp and minus gm. Code is duplicated in order to
5228: decrease memory allocation */
5229: for(theta=1; theta <=npar; theta++){
5230: for(i=1; i<=npar; i++){
1.222 brouard 5231: xp[i] = x[i] + (i==theta ?delti[theta]:0);
5232: xm[i] = x[i] - (i==theta ?delti[theta]:0);
1.126 brouard 5233: }
1.235 brouard 5234: hpxij(p3matp,nhstepm,age,hstepm,xp,nlstate,stepm,oldm,savm, cij, nres);
5235: hpxij(p3matm,nhstepm,age,hstepm,xm,nlstate,stepm,oldm,savm, cij, nres);
1.218 brouard 5236:
1.126 brouard 5237: for(j=1; j<= nlstate; j++){
1.222 brouard 5238: for(i=1; i<=nlstate; i++){
5239: for(h=0; h<=nhstepm-1; h++){
5240: gp[h][(j-1)*nlstate + i] = (p3matp[i][j][h]+p3matp[i][j][h+1])/2.;
5241: gm[h][(j-1)*nlstate + i] = (p3matm[i][j][h]+p3matm[i][j][h+1])/2.;
5242: }
5243: }
1.126 brouard 5244: }
1.218 brouard 5245:
1.126 brouard 5246: for(ij=1; ij<= nlstate*nlstate; ij++)
1.222 brouard 5247: for(h=0; h<=nhstepm-1; h++){
5248: gradg[h][theta][ij]= (gp[h][ij]-gm[h][ij])/2./delti[theta];
5249: }
1.126 brouard 5250: }/* End theta */
5251:
5252:
5253: for(h=0; h<=nhstepm-1; h++)
5254: for(j=1; j<=nlstate*nlstate;j++)
1.222 brouard 5255: for(theta=1; theta <=npar; theta++)
5256: trgradg[h][j][theta]=gradg[h][theta][j];
1.126 brouard 5257:
1.218 brouard 5258:
1.222 brouard 5259: for(ij=1;ij<=nlstate*nlstate;ij++)
1.126 brouard 5260: for(ji=1;ji<=nlstate*nlstate;ji++)
1.222 brouard 5261: varhe[ij][ji][(int)age] =0.;
1.218 brouard 5262:
1.222 brouard 5263: printf("%d|",(int)age);fflush(stdout);
5264: fprintf(ficlog,"%d|",(int)age);fflush(ficlog);
5265: for(h=0;h<=nhstepm-1;h++){
1.126 brouard 5266: for(k=0;k<=nhstepm-1;k++){
1.222 brouard 5267: matprod2(dnewm,trgradg[h],1,nlstate*nlstate,1,npar,1,npar,matcov);
5268: matprod2(doldm,dnewm,1,nlstate*nlstate,1,npar,1,nlstate*nlstate,gradg[k]);
5269: for(ij=1;ij<=nlstate*nlstate;ij++)
5270: for(ji=1;ji<=nlstate*nlstate;ji++)
5271: varhe[ij][ji][(int)age] += doldm[ij][ji]*hf*hf;
1.126 brouard 5272: }
5273: }
1.218 brouard 5274:
1.126 brouard 5275: /* Computing expectancies */
1.235 brouard 5276: hpxij(p3matm,nhstepm,age,hstepm,x,nlstate,stepm,oldm, savm, cij,nres);
1.126 brouard 5277: for(i=1; i<=nlstate;i++)
5278: for(j=1; j<=nlstate;j++)
1.222 brouard 5279: for (h=0, eij[i][j][(int)age]=0; h<=nhstepm-1; h++){
5280: eij[i][j][(int)age] += (p3matm[i][j][h]+p3matm[i][j][h+1])/2.0*hf;
1.218 brouard 5281:
1.222 brouard 5282: /* 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 5283:
1.222 brouard 5284: }
1.218 brouard 5285:
1.126 brouard 5286: fprintf(ficresstdeij,"%3.0f",age );
5287: for(i=1; i<=nlstate;i++){
5288: eip=0.;
5289: vip=0.;
5290: for(j=1; j<=nlstate;j++){
1.222 brouard 5291: eip += eij[i][j][(int)age];
5292: for(k=1; k<=nlstate;k++) /* Sum on j and k of cov(eij,eik) */
5293: vip += varhe[(j-1)*nlstate+i][(k-1)*nlstate+i][(int)age];
5294: 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 5295: }
5296: fprintf(ficresstdeij," %9.4f (%.4f)", eip, sqrt(vip));
5297: }
5298: fprintf(ficresstdeij,"\n");
1.218 brouard 5299:
1.126 brouard 5300: fprintf(ficrescveij,"%3.0f",age );
5301: for(i=1; i<=nlstate;i++)
5302: for(j=1; j<=nlstate;j++){
1.222 brouard 5303: cptj= (j-1)*nlstate+i;
5304: for(i2=1; i2<=nlstate;i2++)
5305: for(j2=1; j2<=nlstate;j2++){
5306: cptj2= (j2-1)*nlstate+i2;
5307: if(cptj2 <= cptj)
5308: fprintf(ficrescveij," %.4f", varhe[cptj][cptj2][(int)age]);
5309: }
1.126 brouard 5310: }
5311: fprintf(ficrescveij,"\n");
1.218 brouard 5312:
1.126 brouard 5313: }
5314: free_matrix(gm,0,nhstepm,1,nlstate*nlstate);
5315: free_matrix(gp,0,nhstepm,1,nlstate*nlstate);
5316: free_ma3x(gradg,0,nhstepm,1,npar,1,nlstate*nlstate);
5317: free_ma3x(trgradg,0,nhstepm,1,nlstate*nlstate,1,npar);
5318: free_ma3x(p3matm,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
5319: free_ma3x(p3matp,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
5320: printf("\n");
5321: fprintf(ficlog,"\n");
1.218 brouard 5322:
1.126 brouard 5323: free_vector(xm,1,npar);
5324: free_vector(xp,1,npar);
5325: free_matrix(dnewm,1,nlstate*nlstate,1,npar);
5326: free_matrix(doldm,1,nlstate*nlstate,1,nlstate*nlstate);
5327: free_ma3x(varhe,1,nlstate*nlstate,1,nlstate*nlstate,(int) bage, (int)fage);
5328: }
1.218 brouard 5329:
1.126 brouard 5330: /************ Variance ******************/
1.235 brouard 5331: 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 5332: {
5333: /* Variance of health expectancies */
5334: /* double **prevalim(double **prlim, int nlstate, double *xp, double age, double **oldm, double ** savm,double ftolpl);*/
5335: /* double **newm;*/
5336: /* int movingaverage(double ***probs, double bage,double fage, double ***mobaverage, int mobilav)*/
5337:
5338: /* int movingaverage(); */
5339: double **dnewm,**doldm;
5340: double **dnewmp,**doldmp;
5341: int i, j, nhstepm, hstepm, h, nstepm ;
5342: int k;
5343: double *xp;
5344: double **gp, **gm; /* for var eij */
5345: double ***gradg, ***trgradg; /*for var eij */
5346: double **gradgp, **trgradgp; /* for var p point j */
5347: double *gpp, *gmp; /* for var p point j */
5348: double **varppt; /* for var p point j nlstate to nlstate+ndeath */
5349: double ***p3mat;
5350: double age,agelim, hf;
5351: /* double ***mobaverage; */
5352: int theta;
5353: char digit[4];
5354: char digitp[25];
5355:
5356: char fileresprobmorprev[FILENAMELENGTH];
5357:
5358: if(popbased==1){
5359: if(mobilav!=0)
5360: strcpy(digitp,"-POPULBASED-MOBILAV_");
5361: else strcpy(digitp,"-POPULBASED-NOMOBIL_");
5362: }
5363: else
5364: strcpy(digitp,"-STABLBASED_");
1.126 brouard 5365:
1.218 brouard 5366: /* if (mobilav!=0) { */
5367: /* mobaverage= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
5368: /* if (movingaverage(probs, bage, fage, mobaverage,mobilav)!=0){ */
5369: /* fprintf(ficlog," Error in movingaverage mobilav=%d\n",mobilav); */
5370: /* printf(" Error in movingaverage mobilav=%d\n",mobilav); */
5371: /* } */
5372: /* } */
5373:
5374: strcpy(fileresprobmorprev,"PRMORPREV-");
5375: sprintf(digit,"%-d",ij);
5376: /*printf("DIGIT=%s, ij=%d ijr=%-d|\n",digit, ij,ij);*/
5377: strcat(fileresprobmorprev,digit); /* Tvar to be done */
5378: strcat(fileresprobmorprev,digitp); /* Popbased or not, mobilav or not */
5379: strcat(fileresprobmorprev,fileresu);
5380: if((ficresprobmorprev=fopen(fileresprobmorprev,"w"))==NULL) {
5381: printf("Problem with resultfile: %s\n", fileresprobmorprev);
5382: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprobmorprev);
5383: }
5384: printf("Computing total mortality p.j=w1*p1j+w2*p2j+..: result on file '%s' \n",fileresprobmorprev);
5385: fprintf(ficlog,"Computing total mortality p.j=w1*p1j+w2*p2j+..: result on file '%s' \n",fileresprobmorprev);
5386: pstamp(ficresprobmorprev);
5387: 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 5388: fprintf(ficresprobmorprev,"# Selected quantitative variables and dummies");
5389: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
5390: fprintf(ficresprobmorprev," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
5391: }
5392: for(j=1;j<=cptcoveff;j++)
5393: fprintf(ficresprobmorprev,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(ij,j)]);
5394: fprintf(ficresprobmorprev,"\n");
5395:
1.218 brouard 5396: fprintf(ficresprobmorprev,"# Age cov=%-d",ij);
5397: for(j=nlstate+1; j<=(nlstate+ndeath);j++){
5398: fprintf(ficresprobmorprev," p.%-d SE",j);
5399: for(i=1; i<=nlstate;i++)
5400: fprintf(ficresprobmorprev," w%1d p%-d%-d",i,i,j);
5401: }
5402: fprintf(ficresprobmorprev,"\n");
5403:
5404: fprintf(ficgp,"\n# Routine varevsij");
5405: fprintf(ficgp,"\nunset title \n");
5406: /* fprintf(fichtm, "#Local time at start: %s", strstart);*/
5407: 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");
5408: fprintf(fichtm,"\n<br>%s <br>\n",digitp);
5409: /* } */
5410: varppt = matrix(nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
5411: pstamp(ficresvij);
5412: fprintf(ficresvij,"# Variance and covariance of health expectancies e.j \n# (weighted average of eij where weights are ");
5413: if(popbased==1)
5414: 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);
5415: else
5416: fprintf(ficresvij,"the age specific period (stable) prevalences in each health state \n");
5417: fprintf(ficresvij,"# Age");
5418: for(i=1; i<=nlstate;i++)
5419: for(j=1; j<=nlstate;j++)
5420: fprintf(ficresvij," Cov(e.%1d, e.%1d)",i,j);
5421: fprintf(ficresvij,"\n");
5422:
5423: xp=vector(1,npar);
5424: dnewm=matrix(1,nlstate,1,npar);
5425: doldm=matrix(1,nlstate,1,nlstate);
5426: dnewmp= matrix(nlstate+1,nlstate+ndeath,1,npar);
5427: doldmp= matrix(nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
5428:
5429: gradgp=matrix(1,npar,nlstate+1,nlstate+ndeath);
5430: gpp=vector(nlstate+1,nlstate+ndeath);
5431: gmp=vector(nlstate+1,nlstate+ndeath);
5432: trgradgp =matrix(nlstate+1,nlstate+ndeath,1,npar); /* mu or p point j*/
1.126 brouard 5433:
1.218 brouard 5434: if(estepm < stepm){
5435: printf ("Problem %d lower than %d\n",estepm, stepm);
5436: }
5437: else hstepm=estepm;
5438: /* For example we decided to compute the life expectancy with the smallest unit */
5439: /* hstepm beeing the number of stepms, if hstepm=1 the length of hstepm is stepm.
5440: nhstepm is the number of hstepm from age to agelim
5441: nstepm is the number of stepm from age to agelim.
5442: Look at function hpijx to understand why because of memory size limitations,
5443: we decided (b) to get a life expectancy respecting the most precise curvature of the
5444: survival function given by stepm (the optimization length). Unfortunately it
5445: means that if the survival funtion is printed every two years of age and if
5446: you sum them up and add 1 year (area under the trapezoids) you won't get the same
5447: results. So we changed our mind and took the option of the best precision.
5448: */
5449: hstepm=hstepm/stepm; /* Typically in stepm units, if stepm=6 & estepm=24 , = 24/6 months = 4 */
5450: agelim = AGESUP;
5451: for (age=bage; age<=fage; age ++){ /* If stepm=6 months */
5452: nstepm=(int) rint((agelim-age)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
5453: nhstepm = nstepm/hstepm;/* Expressed in hstepm, typically nhstepm=40/4=10 */
5454: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
5455: gradg=ma3x(0,nhstepm,1,npar,1,nlstate);
5456: gp=matrix(0,nhstepm,1,nlstate);
5457: gm=matrix(0,nhstepm,1,nlstate);
5458:
5459:
5460: for(theta=1; theta <=npar; theta++){
5461: for(i=1; i<=npar; i++){ /* Computes gradient x + delta*/
5462: xp[i] = x[i] + (i==theta ?delti[theta]:0);
5463: }
5464:
1.242 brouard 5465: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij, nres);
1.218 brouard 5466:
5467: if (popbased==1) {
5468: if(mobilav ==0){
5469: for(i=1; i<=nlstate;i++)
5470: prlim[i][i]=probs[(int)age][i][ij];
5471: }else{ /* mobilav */
5472: for(i=1; i<=nlstate;i++)
5473: prlim[i][i]=mobaverage[(int)age][i][ij];
5474: }
5475: }
5476:
1.235 brouard 5477: 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 5478: for(j=1; j<= nlstate; j++){
5479: for(h=0; h<=nhstepm; h++){
5480: for(i=1, gp[h][j]=0.;i<=nlstate;i++)
5481: gp[h][j] += prlim[i][i]*p3mat[i][j][h];
5482: }
5483: }
5484: /* Next for computing probability of death (h=1 means
5485: computed over hstepm matrices product = hstepm*stepm months)
5486: as a weighted average of prlim.
5487: */
5488: for(j=nlstate+1;j<=nlstate+ndeath;j++){
5489: for(i=1,gpp[j]=0.; i<= nlstate; i++)
5490: gpp[j] += prlim[i][i]*p3mat[i][j][1];
5491: }
5492: /* end probability of death */
5493:
5494: for(i=1; i<=npar; i++) /* Computes gradient x - delta */
5495: xp[i] = x[i] - (i==theta ?delti[theta]:0);
5496:
1.242 brouard 5497: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp, ij, nres);
1.218 brouard 5498:
5499: if (popbased==1) {
5500: if(mobilav ==0){
5501: for(i=1; i<=nlstate;i++)
5502: prlim[i][i]=probs[(int)age][i][ij];
5503: }else{ /* mobilav */
5504: for(i=1; i<=nlstate;i++)
5505: prlim[i][i]=mobaverage[(int)age][i][ij];
5506: }
5507: }
5508:
1.235 brouard 5509: hpxij(p3mat,nhstepm,age,hstepm,xp,nlstate,stepm,oldm,savm, ij,nres);
1.218 brouard 5510:
5511: for(j=1; j<= nlstate; j++){ /* Sum of wi * eij = e.j */
5512: for(h=0; h<=nhstepm; h++){
5513: for(i=1, gm[h][j]=0.;i<=nlstate;i++)
5514: gm[h][j] += prlim[i][i]*p3mat[i][j][h];
5515: }
5516: }
5517: /* This for computing probability of death (h=1 means
5518: computed over hstepm matrices product = hstepm*stepm months)
5519: as a weighted average of prlim.
5520: */
5521: for(j=nlstate+1;j<=nlstate+ndeath;j++){
5522: for(i=1,gmp[j]=0.; i<= nlstate; i++)
5523: gmp[j] += prlim[i][i]*p3mat[i][j][1];
5524: }
5525: /* end probability of death */
5526:
5527: for(j=1; j<= nlstate; j++) /* vareij */
5528: for(h=0; h<=nhstepm; h++){
5529: gradg[h][theta][j]= (gp[h][j]-gm[h][j])/2./delti[theta];
5530: }
5531:
5532: for(j=nlstate+1; j<= nlstate+ndeath; j++){ /* var mu */
5533: gradgp[theta][j]= (gpp[j]-gmp[j])/2./delti[theta];
5534: }
5535:
5536: } /* End theta */
5537:
5538: trgradg =ma3x(0,nhstepm,1,nlstate,1,npar); /* veij */
5539:
5540: for(h=0; h<=nhstepm; h++) /* veij */
5541: for(j=1; j<=nlstate;j++)
5542: for(theta=1; theta <=npar; theta++)
5543: trgradg[h][j][theta]=gradg[h][theta][j];
5544:
5545: for(j=nlstate+1; j<=nlstate+ndeath;j++) /* mu */
5546: for(theta=1; theta <=npar; theta++)
5547: trgradgp[j][theta]=gradgp[theta][j];
5548:
5549:
5550: hf=hstepm*stepm/YEARM; /* Duration of hstepm expressed in year unit. */
5551: for(i=1;i<=nlstate;i++)
5552: for(j=1;j<=nlstate;j++)
5553: vareij[i][j][(int)age] =0.;
5554:
5555: for(h=0;h<=nhstepm;h++){
5556: for(k=0;k<=nhstepm;k++){
5557: matprod2(dnewm,trgradg[h],1,nlstate,1,npar,1,npar,matcov);
5558: matprod2(doldm,dnewm,1,nlstate,1,npar,1,nlstate,gradg[k]);
5559: for(i=1;i<=nlstate;i++)
5560: for(j=1;j<=nlstate;j++)
5561: vareij[i][j][(int)age] += doldm[i][j]*hf*hf;
5562: }
5563: }
5564:
5565: /* pptj */
5566: matprod2(dnewmp,trgradgp,nlstate+1,nlstate+ndeath,1,npar,1,npar,matcov);
5567: matprod2(doldmp,dnewmp,nlstate+1,nlstate+ndeath,1,npar,nlstate+1,nlstate+ndeath,gradgp);
5568: for(j=nlstate+1;j<=nlstate+ndeath;j++)
5569: for(i=nlstate+1;i<=nlstate+ndeath;i++)
5570: varppt[j][i]=doldmp[j][i];
5571: /* end ppptj */
5572: /* x centered again */
5573:
1.242 brouard 5574: prevalim(prlim,nlstate,x,age,oldm,savm,ftolpl,ncvyearp,ij, nres);
1.218 brouard 5575:
5576: if (popbased==1) {
5577: if(mobilav ==0){
5578: for(i=1; i<=nlstate;i++)
5579: prlim[i][i]=probs[(int)age][i][ij];
5580: }else{ /* mobilav */
5581: for(i=1; i<=nlstate;i++)
5582: prlim[i][i]=mobaverage[(int)age][i][ij];
5583: }
5584: }
5585:
5586: /* This for computing probability of death (h=1 means
5587: computed over hstepm (estepm) matrices product = hstepm*stepm months)
5588: as a weighted average of prlim.
5589: */
1.235 brouard 5590: hpxij(p3mat,nhstepm,age,hstepm,x,nlstate,stepm,oldm,savm, ij, nres);
1.218 brouard 5591: for(j=nlstate+1;j<=nlstate+ndeath;j++){
5592: for(i=1,gmp[j]=0.;i<= nlstate; i++)
5593: gmp[j] += prlim[i][i]*p3mat[i][j][1];
5594: }
5595: /* end probability of death */
5596:
5597: fprintf(ficresprobmorprev,"%3d %d ",(int) age, ij);
5598: for(j=nlstate+1; j<=(nlstate+ndeath);j++){
5599: fprintf(ficresprobmorprev," %11.3e %11.3e",gmp[j], sqrt(varppt[j][j]));
5600: for(i=1; i<=nlstate;i++){
5601: fprintf(ficresprobmorprev," %11.3e %11.3e ",prlim[i][i],p3mat[i][j][1]);
5602: }
5603: }
5604: fprintf(ficresprobmorprev,"\n");
5605:
5606: fprintf(ficresvij,"%.0f ",age );
5607: for(i=1; i<=nlstate;i++)
5608: for(j=1; j<=nlstate;j++){
5609: fprintf(ficresvij," %.4f", vareij[i][j][(int)age]);
5610: }
5611: fprintf(ficresvij,"\n");
5612: free_matrix(gp,0,nhstepm,1,nlstate);
5613: free_matrix(gm,0,nhstepm,1,nlstate);
5614: free_ma3x(gradg,0,nhstepm,1,npar,1,nlstate);
5615: free_ma3x(trgradg,0,nhstepm,1,nlstate,1,npar);
5616: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
5617: } /* End age */
5618: free_vector(gpp,nlstate+1,nlstate+ndeath);
5619: free_vector(gmp,nlstate+1,nlstate+ndeath);
5620: free_matrix(gradgp,1,npar,nlstate+1,nlstate+ndeath);
5621: free_matrix(trgradgp,nlstate+1,nlstate+ndeath,1,npar); /* mu or p point j*/
5622: /* fprintf(ficgp,"\nunset parametric;unset label; set ter png small size 320, 240"); */
5623: fprintf(ficgp,"\nunset parametric;unset label; set ter svg size 640, 480");
5624: /* for(j=nlstate+1; j<= nlstate+ndeath; j++){ *//* Only the first actually */
5625: fprintf(ficgp,"\n set log y; unset log x;set xlabel \"Age\"; set ylabel \"Force of mortality (year-1)\";");
5626: fprintf(ficgp,"\nset out \"%s%s.svg\";",subdirf3(optionfilefiname,"VARMUPTJGR-",digitp),digit);
5627: /* fprintf(ficgp,"\n plot \"%s\" u 1:($3*%6.3f) not w l 1 ",fileresprobmorprev,YEARM/estepm); */
5628: /* fprintf(ficgp,"\n replot \"%s\" u 1:(($3+1.96*$4)*%6.3f) t \"95\%% interval\" w l 2 ",fileresprobmorprev,YEARM/estepm); */
5629: /* fprintf(ficgp,"\n replot \"%s\" u 1:(($3-1.96*$4)*%6.3f) not w l 2 ",fileresprobmorprev,YEARM/estepm); */
5630: fprintf(ficgp,"\n plot \"%s\" u 1:($3) not w l lt 1 ",subdirf(fileresprobmorprev));
5631: fprintf(ficgp,"\n replot \"%s\" u 1:(($3+1.96*$4)) t \"95%% interval\" w l lt 2 ",subdirf(fileresprobmorprev));
5632: fprintf(ficgp,"\n replot \"%s\" u 1:(($3-1.96*$4)) not w l lt 2 ",subdirf(fileresprobmorprev));
5633: fprintf(fichtm,"\n<br> File (multiple files are possible if covariates are present): <A href=\"%s\">%s</a>\n",subdirf(fileresprobmorprev),subdirf(fileresprobmorprev));
5634: 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);
5635: /* 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 5636: */
1.218 brouard 5637: /* fprintf(ficgp,"\nset out \"varmuptjgr%s%s%s.svg\";replot;",digitp,optionfilefiname,digit); */
5638: fprintf(ficgp,"\nset out;\nset out \"%s%s.svg\";replot;set out;\n",subdirf3(optionfilefiname,"VARMUPTJGR-",digitp),digit);
1.126 brouard 5639:
1.218 brouard 5640: free_vector(xp,1,npar);
5641: free_matrix(doldm,1,nlstate,1,nlstate);
5642: free_matrix(dnewm,1,nlstate,1,npar);
5643: free_matrix(doldmp,nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
5644: free_matrix(dnewmp,nlstate+1,nlstate+ndeath,1,npar);
5645: free_matrix(varppt,nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
5646: /* if (mobilav!=0) free_ma3x(mobaverage,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
5647: fclose(ficresprobmorprev);
5648: fflush(ficgp);
5649: fflush(fichtm);
5650: } /* end varevsij */
1.126 brouard 5651:
5652: /************ Variance of prevlim ******************/
1.235 brouard 5653: void varprevlim(char fileres[], double **varpl, double **matcov, double x[], double delti[], int nlstate, int stepm, double bage, double fage, double **oldm, double **savm, double **prlim, double ftolpl, int *ncvyearp, int ij, char strstart[], int nres)
1.126 brouard 5654: {
1.205 brouard 5655: /* Variance of prevalence limit for each state ij using current parameters x[] and estimates of neighbourhood give by delti*/
1.126 brouard 5656: /* double **prevalim(double **prlim, int nlstate, double *xp, double age, double **oldm, double **savm,double ftolpl);*/
1.164 brouard 5657:
1.126 brouard 5658: double **dnewm,**doldm;
5659: int i, j, nhstepm, hstepm;
5660: double *xp;
5661: double *gp, *gm;
5662: double **gradg, **trgradg;
1.208 brouard 5663: double **mgm, **mgp;
1.126 brouard 5664: double age,agelim;
5665: int theta;
5666:
5667: pstamp(ficresvpl);
5668: fprintf(ficresvpl,"# Standard deviation of period (stable) prevalences \n");
1.241 brouard 5669: fprintf(ficresvpl,"# Age ");
5670: if(nresult >=1)
5671: fprintf(ficresvpl," Result# ");
1.126 brouard 5672: for(i=1; i<=nlstate;i++)
5673: fprintf(ficresvpl," %1d-%1d",i,i);
5674: fprintf(ficresvpl,"\n");
5675:
5676: xp=vector(1,npar);
5677: dnewm=matrix(1,nlstate,1,npar);
5678: doldm=matrix(1,nlstate,1,nlstate);
5679:
5680: hstepm=1*YEARM; /* Every year of age */
5681: hstepm=hstepm/stepm; /* Typically in stepm units, if j= 2 years, = 2/6 months = 4 */
5682: agelim = AGESUP;
5683: for (age=bage; age<=fage; age ++){ /* If stepm=6 months */
5684: nhstepm=(int) rint((agelim-age)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
5685: if (stepm >= YEARM) hstepm=1;
5686: nhstepm = nhstepm/hstepm; /* Typically 40/4=10 */
5687: gradg=matrix(1,npar,1,nlstate);
1.208 brouard 5688: mgp=matrix(1,npar,1,nlstate);
5689: mgm=matrix(1,npar,1,nlstate);
1.126 brouard 5690: gp=vector(1,nlstate);
5691: gm=vector(1,nlstate);
5692:
5693: for(theta=1; theta <=npar; theta++){
5694: for(i=1; i<=npar; i++){ /* Computes gradient */
5695: xp[i] = x[i] + (i==theta ?delti[theta]:0);
5696: }
1.209 brouard 5697: if((int)age==79 ||(int)age== 80 ||(int)age== 81 )
1.235 brouard 5698: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres);
1.209 brouard 5699: else
1.235 brouard 5700: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres);
1.208 brouard 5701: for(i=1;i<=nlstate;i++){
1.126 brouard 5702: gp[i] = prlim[i][i];
1.208 brouard 5703: mgp[theta][i] = prlim[i][i];
5704: }
1.126 brouard 5705: for(i=1; i<=npar; i++) /* Computes gradient */
5706: xp[i] = x[i] - (i==theta ?delti[theta]:0);
1.209 brouard 5707: if((int)age==79 ||(int)age== 80 ||(int)age== 81 )
1.235 brouard 5708: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres);
1.209 brouard 5709: else
1.235 brouard 5710: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres);
1.208 brouard 5711: for(i=1;i<=nlstate;i++){
1.126 brouard 5712: gm[i] = prlim[i][i];
1.208 brouard 5713: mgm[theta][i] = prlim[i][i];
5714: }
1.126 brouard 5715: for(i=1;i<=nlstate;i++)
5716: gradg[theta][i]= (gp[i]-gm[i])/2./delti[theta];
1.209 brouard 5717: /* gradg[theta][2]= -gradg[theta][1]; */ /* For testing if nlstate=2 */
1.126 brouard 5718: } /* End theta */
5719:
5720: trgradg =matrix(1,nlstate,1,npar);
5721:
5722: for(j=1; j<=nlstate;j++)
5723: for(theta=1; theta <=npar; theta++)
5724: trgradg[j][theta]=gradg[theta][j];
1.209 brouard 5725: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
5726: /* printf("\nmgm mgp %d ",(int)age); */
5727: /* for(j=1; j<=nlstate;j++){ */
5728: /* printf(" %d ",j); */
5729: /* for(theta=1; theta <=npar; theta++) */
5730: /* printf(" %d %lf %lf",theta,mgm[theta][j],mgp[theta][j]); */
5731: /* printf("\n "); */
5732: /* } */
5733: /* } */
5734: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
5735: /* printf("\n gradg %d ",(int)age); */
5736: /* for(j=1; j<=nlstate;j++){ */
5737: /* printf("%d ",j); */
5738: /* for(theta=1; theta <=npar; theta++) */
5739: /* printf("%d %lf ",theta,gradg[theta][j]); */
5740: /* printf("\n "); */
5741: /* } */
5742: /* } */
1.126 brouard 5743:
5744: for(i=1;i<=nlstate;i++)
5745: varpl[i][(int)age] =0.;
1.209 brouard 5746: if((int)age==79 ||(int)age== 80 ||(int)age== 81){
1.205 brouard 5747: matprod2(dnewm,trgradg,1,nlstate,1,npar,1,npar,matcov);
5748: matprod2(doldm,dnewm,1,nlstate,1,npar,1,nlstate,gradg);
5749: }else{
1.126 brouard 5750: matprod2(dnewm,trgradg,1,nlstate,1,npar,1,npar,matcov);
5751: matprod2(doldm,dnewm,1,nlstate,1,npar,1,nlstate,gradg);
1.205 brouard 5752: }
1.126 brouard 5753: for(i=1;i<=nlstate;i++)
5754: varpl[i][(int)age] = doldm[i][i]; /* Covariances are useless */
5755:
5756: fprintf(ficresvpl,"%.0f ",age );
1.241 brouard 5757: if(nresult >=1)
5758: fprintf(ficresvpl,"%d ",nres );
1.126 brouard 5759: for(i=1; i<=nlstate;i++)
5760: fprintf(ficresvpl," %.5f (%.5f)",prlim[i][i],sqrt(varpl[i][(int)age]));
5761: fprintf(ficresvpl,"\n");
5762: free_vector(gp,1,nlstate);
5763: free_vector(gm,1,nlstate);
1.208 brouard 5764: free_matrix(mgm,1,npar,1,nlstate);
5765: free_matrix(mgp,1,npar,1,nlstate);
1.126 brouard 5766: free_matrix(gradg,1,npar,1,nlstate);
5767: free_matrix(trgradg,1,nlstate,1,npar);
5768: } /* End age */
5769:
5770: free_vector(xp,1,npar);
5771: free_matrix(doldm,1,nlstate,1,npar);
5772: free_matrix(dnewm,1,nlstate,1,nlstate);
5773:
5774: }
5775:
5776: /************ Variance of one-step probabilities ******************/
5777: 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 5778: {
5779: int i, j=0, k1, l1, tj;
5780: int k2, l2, j1, z1;
5781: int k=0, l;
5782: int first=1, first1, first2;
5783: double cv12, mu1, mu2, lc1, lc2, v12, v21, v11, v22,v1,v2, c12, tnalp;
5784: double **dnewm,**doldm;
5785: double *xp;
5786: double *gp, *gm;
5787: double **gradg, **trgradg;
5788: double **mu;
5789: double age, cov[NCOVMAX+1];
5790: double std=2.0; /* Number of standard deviation wide of confidence ellipsoids */
5791: int theta;
5792: char fileresprob[FILENAMELENGTH];
5793: char fileresprobcov[FILENAMELENGTH];
5794: char fileresprobcor[FILENAMELENGTH];
5795: double ***varpij;
5796:
5797: strcpy(fileresprob,"PROB_");
5798: strcat(fileresprob,fileres);
5799: if((ficresprob=fopen(fileresprob,"w"))==NULL) {
5800: printf("Problem with resultfile: %s\n", fileresprob);
5801: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprob);
5802: }
5803: strcpy(fileresprobcov,"PROBCOV_");
5804: strcat(fileresprobcov,fileresu);
5805: if((ficresprobcov=fopen(fileresprobcov,"w"))==NULL) {
5806: printf("Problem with resultfile: %s\n", fileresprobcov);
5807: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprobcov);
5808: }
5809: strcpy(fileresprobcor,"PROBCOR_");
5810: strcat(fileresprobcor,fileresu);
5811: if((ficresprobcor=fopen(fileresprobcor,"w"))==NULL) {
5812: printf("Problem with resultfile: %s\n", fileresprobcor);
5813: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprobcor);
5814: }
5815: printf("Computing standard deviation of one-step probabilities: result on file '%s' \n",fileresprob);
5816: fprintf(ficlog,"Computing standard deviation of one-step probabilities: result on file '%s' \n",fileresprob);
5817: printf("Computing matrix of variance covariance of one-step probabilities: result on file '%s' \n",fileresprobcov);
5818: fprintf(ficlog,"Computing matrix of variance covariance of one-step probabilities: result on file '%s' \n",fileresprobcov);
5819: printf("and correlation matrix of one-step probabilities: result on file '%s' \n",fileresprobcor);
5820: fprintf(ficlog,"and correlation matrix of one-step probabilities: result on file '%s' \n",fileresprobcor);
5821: pstamp(ficresprob);
5822: fprintf(ficresprob,"#One-step probabilities and stand. devi in ()\n");
5823: fprintf(ficresprob,"# Age");
5824: pstamp(ficresprobcov);
5825: fprintf(ficresprobcov,"#One-step probabilities and covariance matrix\n");
5826: fprintf(ficresprobcov,"# Age");
5827: pstamp(ficresprobcor);
5828: fprintf(ficresprobcor,"#One-step probabilities and correlation matrix\n");
5829: fprintf(ficresprobcor,"# Age");
1.126 brouard 5830:
5831:
1.222 brouard 5832: for(i=1; i<=nlstate;i++)
5833: for(j=1; j<=(nlstate+ndeath);j++){
5834: fprintf(ficresprob," p%1d-%1d (SE)",i,j);
5835: fprintf(ficresprobcov," p%1d-%1d ",i,j);
5836: fprintf(ficresprobcor," p%1d-%1d ",i,j);
5837: }
5838: /* fprintf(ficresprob,"\n");
5839: fprintf(ficresprobcov,"\n");
5840: fprintf(ficresprobcor,"\n");
5841: */
5842: xp=vector(1,npar);
5843: dnewm=matrix(1,(nlstate)*(nlstate+ndeath),1,npar);
5844: doldm=matrix(1,(nlstate)*(nlstate+ndeath),1,(nlstate)*(nlstate+ndeath));
5845: mu=matrix(1,(nlstate)*(nlstate+ndeath), (int) bage, (int)fage);
5846: varpij=ma3x(1,nlstate*(nlstate+ndeath),1,nlstate*(nlstate+ndeath),(int) bage, (int) fage);
5847: first=1;
5848: fprintf(ficgp,"\n# Routine varprob");
5849: fprintf(fichtm,"\n<li><h4> Computing and drawing one step probabilities with their confidence intervals</h4></li>\n");
5850: fprintf(fichtm,"\n");
5851:
5852: fprintf(fichtm,"\n<li><h4> <a href=\"%s\">Matrix of variance-covariance of one-step probabilities (drawings)</a></h4> this page is important in order to visualize confidence intervals and especially correlation between disability and recovery, or more generally, way in and way back.</li>\n",optionfilehtmcov);
5853: 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);
5854: fprintf(fichtmcov,"\nEllipsoids of confidence centered on point (p<inf>ij</inf>, p<inf>kl</inf>) are estimated \
1.126 brouard 5855: and drawn. It helps understanding how is the covariance between two incidences.\
5856: They are expressed in year<sup>-1</sup> in order to be less dependent of stepm.<br>\n");
1.222 brouard 5857: 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 5858: It can be understood this way: if pij and pkl where uncorrelated the (2x2) matrix of covariance \
5859: would have been (1/(var pij), 0 , 0, 1/(var pkl)), and the confidence interval would be 2 \
5860: standard deviations wide on each axis. <br>\
5861: Now, if both incidences are correlated (usual case) we diagonalised the inverse of the covariance matrix\
5862: and made the appropriate rotation to look at the uncorrelated principal directions.<br>\
5863: To be simple, these graphs help to understand the significativity of each parameter in relation to a second other one.<br> \n");
5864:
1.222 brouard 5865: cov[1]=1;
5866: /* tj=cptcoveff; */
1.225 brouard 5867: tj = (int) pow(2,cptcoveff);
1.222 brouard 5868: if (cptcovn<1) {tj=1;ncodemax[1]=1;}
5869: j1=0;
1.224 brouard 5870: for(j1=1; j1<=tj;j1++){ /* For each valid combination of covariates or only once*/
1.222 brouard 5871: if (cptcovn>0) {
5872: fprintf(ficresprob, "\n#********** Variable ");
1.225 brouard 5873: for (z1=1; z1<=cptcoveff; z1++) fprintf(ficresprob, "V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
1.222 brouard 5874: fprintf(ficresprob, "**********\n#\n");
5875: fprintf(ficresprobcov, "\n#********** Variable ");
1.225 brouard 5876: for (z1=1; z1<=cptcoveff; z1++) fprintf(ficresprobcov, "V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
1.222 brouard 5877: fprintf(ficresprobcov, "**********\n#\n");
1.220 brouard 5878:
1.222 brouard 5879: fprintf(ficgp, "\n#********** Variable ");
1.225 brouard 5880: for (z1=1; z1<=cptcoveff; z1++) fprintf(ficgp, " V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
1.222 brouard 5881: fprintf(ficgp, "**********\n#\n");
1.220 brouard 5882:
5883:
1.222 brouard 5884: fprintf(fichtmcov, "\n<hr size=\"2\" color=\"#EC5E5E\">********** Variable ");
1.225 brouard 5885: for (z1=1; z1<=cptcoveff; z1++) fprintf(fichtm, "V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
1.222 brouard 5886: fprintf(fichtmcov, "**********\n<hr size=\"2\" color=\"#EC5E5E\">");
1.220 brouard 5887:
1.222 brouard 5888: fprintf(ficresprobcor, "\n#********** Variable ");
1.225 brouard 5889: for (z1=1; z1<=cptcoveff; z1++) fprintf(ficresprobcor, "V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
1.222 brouard 5890: fprintf(ficresprobcor, "**********\n#");
5891: if(invalidvarcomb[j1]){
5892: fprintf(ficgp,"\n#Combination (%d) ignored because no cases \n",j1);
5893: fprintf(fichtmcov,"\n<h3>Combination (%d) ignored because no cases </h3>\n",j1);
5894: continue;
5895: }
5896: }
5897: gradg=matrix(1,npar,1,(nlstate)*(nlstate+ndeath));
5898: trgradg=matrix(1,(nlstate)*(nlstate+ndeath),1,npar);
5899: gp=vector(1,(nlstate)*(nlstate+ndeath));
5900: gm=vector(1,(nlstate)*(nlstate+ndeath));
5901: for (age=bage; age<=fage; age ++){
5902: cov[2]=age;
5903: if(nagesqr==1)
5904: cov[3]= age*age;
5905: for (k=1; k<=cptcovn;k++) {
5906: cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(j1,k)];
5907: /*cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(j1,Tvar[k])];*//* j1 1 2 3 4
5908: * 1 1 1 1 1
5909: * 2 2 1 1 1
5910: * 3 1 2 1 1
5911: */
5912: /* nbcode[1][1]=0 nbcode[1][2]=1;*/
5913: }
5914: /* for (k=1; k<=cptcovage;k++) cov[2+Tage[k]]=cov[2+Tage[k]]*cov[2]; */
5915: for (k=1; k<=cptcovage;k++) cov[2+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2];
5916: for (k=1; k<=cptcovprod;k++)
5917: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)]*nbcode[Tvard[k][2]][codtabm(ij,k)];
1.220 brouard 5918:
5919:
1.222 brouard 5920: for(theta=1; theta <=npar; theta++){
5921: for(i=1; i<=npar; i++)
5922: xp[i] = x[i] + (i==theta ?delti[theta]:(double)0);
1.220 brouard 5923:
1.222 brouard 5924: pmij(pmmij,cov,ncovmodel,xp,nlstate);
1.220 brouard 5925:
1.222 brouard 5926: k=0;
5927: for(i=1; i<= (nlstate); i++){
5928: for(j=1; j<=(nlstate+ndeath);j++){
5929: k=k+1;
5930: gp[k]=pmmij[i][j];
5931: }
5932: }
1.220 brouard 5933:
1.222 brouard 5934: for(i=1; i<=npar; i++)
5935: xp[i] = x[i] - (i==theta ?delti[theta]:(double)0);
1.220 brouard 5936:
1.222 brouard 5937: pmij(pmmij,cov,ncovmodel,xp,nlstate);
5938: k=0;
5939: for(i=1; i<=(nlstate); i++){
5940: for(j=1; j<=(nlstate+ndeath);j++){
5941: k=k+1;
5942: gm[k]=pmmij[i][j];
5943: }
5944: }
1.220 brouard 5945:
1.222 brouard 5946: for(i=1; i<= (nlstate)*(nlstate+ndeath); i++)
5947: gradg[theta][i]=(gp[i]-gm[i])/(double)2./delti[theta];
5948: }
1.126 brouard 5949:
1.222 brouard 5950: for(j=1; j<=(nlstate)*(nlstate+ndeath);j++)
5951: for(theta=1; theta <=npar; theta++)
5952: trgradg[j][theta]=gradg[theta][j];
1.220 brouard 5953:
1.222 brouard 5954: matprod2(dnewm,trgradg,1,(nlstate)*(nlstate+ndeath),1,npar,1,npar,matcov);
5955: matprod2(doldm,dnewm,1,(nlstate)*(nlstate+ndeath),1,npar,1,(nlstate)*(nlstate+ndeath),gradg);
1.220 brouard 5956:
1.222 brouard 5957: pmij(pmmij,cov,ncovmodel,x,nlstate);
1.220 brouard 5958:
1.222 brouard 5959: k=0;
5960: for(i=1; i<=(nlstate); i++){
5961: for(j=1; j<=(nlstate+ndeath);j++){
5962: k=k+1;
5963: mu[k][(int) age]=pmmij[i][j];
5964: }
5965: }
5966: for(i=1;i<=(nlstate)*(nlstate+ndeath);i++)
5967: for(j=1;j<=(nlstate)*(nlstate+ndeath);j++)
5968: varpij[i][j][(int)age] = doldm[i][j];
1.220 brouard 5969:
1.222 brouard 5970: /*printf("\n%d ",(int)age);
5971: for (i=1; i<=(nlstate)*(nlstate+ndeath);i++){
5972: printf("%e [%e ;%e] ",gm[i],gm[i]-2*sqrt(doldm[i][i]),gm[i]+2*sqrt(doldm[i][i]));
5973: fprintf(ficlog,"%e [%e ;%e] ",gm[i],gm[i]-2*sqrt(doldm[i][i]),gm[i]+2*sqrt(doldm[i][i]));
5974: }*/
1.220 brouard 5975:
1.222 brouard 5976: fprintf(ficresprob,"\n%d ",(int)age);
5977: fprintf(ficresprobcov,"\n%d ",(int)age);
5978: fprintf(ficresprobcor,"\n%d ",(int)age);
1.220 brouard 5979:
1.222 brouard 5980: for (i=1; i<=(nlstate)*(nlstate+ndeath);i++)
5981: fprintf(ficresprob,"%11.3e (%11.3e) ",mu[i][(int) age],sqrt(varpij[i][i][(int)age]));
5982: for (i=1; i<=(nlstate)*(nlstate+ndeath);i++){
5983: fprintf(ficresprobcov,"%11.3e ",mu[i][(int) age]);
5984: fprintf(ficresprobcor,"%11.3e ",mu[i][(int) age]);
5985: }
5986: i=0;
5987: for (k=1; k<=(nlstate);k++){
5988: for (l=1; l<=(nlstate+ndeath);l++){
5989: i++;
5990: fprintf(ficresprobcov,"\n%d %d-%d",(int)age,k,l);
5991: fprintf(ficresprobcor,"\n%d %d-%d",(int)age,k,l);
5992: for (j=1; j<=i;j++){
5993: /* printf(" k=%d l=%d i=%d j=%d\n",k,l,i,j);fflush(stdout); */
5994: fprintf(ficresprobcov," %11.3e",varpij[i][j][(int)age]);
5995: fprintf(ficresprobcor," %11.3e",varpij[i][j][(int) age]/sqrt(varpij[i][i][(int) age])/sqrt(varpij[j][j][(int)age]));
5996: }
5997: }
5998: }/* end of loop for state */
5999: } /* end of loop for age */
6000: free_vector(gp,1,(nlstate+ndeath)*(nlstate+ndeath));
6001: free_vector(gm,1,(nlstate+ndeath)*(nlstate+ndeath));
6002: free_matrix(trgradg,1,(nlstate+ndeath)*(nlstate+ndeath),1,npar);
6003: free_matrix(gradg,1,(nlstate+ndeath)*(nlstate+ndeath),1,npar);
6004:
6005: /* Confidence intervalle of pij */
6006: /*
6007: fprintf(ficgp,"\nunset parametric;unset label");
6008: fprintf(ficgp,"\nset log y;unset log x; set xlabel \"Age\";set ylabel \"probability (year-1)\"");
6009: fprintf(ficgp,"\nset ter png small\nset size 0.65,0.65");
6010: 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);
6011: fprintf(fichtm,"\n<br><img src=\"pijgr%s.png\"> ",optionfilefiname);
6012: fprintf(ficgp,"\nset out \"pijgr%s.png\"",optionfilefiname);
6013: fprintf(ficgp,"\nplot \"%s\" every :::%d::%d u 1:2 \"\%%lf",k1,k2,xfilevarprob);
6014: */
6015:
6016: /* Drawing ellipsoids of confidence of two variables p(k1-l1,k2-l2)*/
6017: first1=1;first2=2;
6018: for (k2=1; k2<=(nlstate);k2++){
6019: for (l2=1; l2<=(nlstate+ndeath);l2++){
6020: if(l2==k2) continue;
6021: j=(k2-1)*(nlstate+ndeath)+l2;
6022: for (k1=1; k1<=(nlstate);k1++){
6023: for (l1=1; l1<=(nlstate+ndeath);l1++){
6024: if(l1==k1) continue;
6025: i=(k1-1)*(nlstate+ndeath)+l1;
6026: if(i<=j) continue;
6027: for (age=bage; age<=fage; age ++){
6028: if ((int)age %5==0){
6029: v1=varpij[i][i][(int)age]/stepm*YEARM/stepm*YEARM;
6030: v2=varpij[j][j][(int)age]/stepm*YEARM/stepm*YEARM;
6031: cv12=varpij[i][j][(int)age]/stepm*YEARM/stepm*YEARM;
6032: mu1=mu[i][(int) age]/stepm*YEARM ;
6033: mu2=mu[j][(int) age]/stepm*YEARM;
6034: c12=cv12/sqrt(v1*v2);
6035: /* Computing eigen value of matrix of covariance */
6036: lc1=((v1+v2)+sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
6037: lc2=((v1+v2)-sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
6038: if ((lc2 <0) || (lc1 <0) ){
6039: if(first2==1){
6040: first1=0;
6041: 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);
6042: }
6043: 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);
6044: /* lc1=fabs(lc1); */ /* If we want to have them positive */
6045: /* lc2=fabs(lc2); */
6046: }
1.220 brouard 6047:
1.222 brouard 6048: /* Eigen vectors */
6049: v11=(1./sqrt(1+(v1-lc1)*(v1-lc1)/cv12/cv12));
6050: /*v21=sqrt(1.-v11*v11); *//* error */
6051: v21=(lc1-v1)/cv12*v11;
6052: v12=-v21;
6053: v22=v11;
6054: tnalp=v21/v11;
6055: if(first1==1){
6056: first1=0;
6057: 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);
6058: }
6059: 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);
6060: /*printf(fignu*/
6061: /* mu1+ v11*lc1*cost + v12*lc2*sin(t) */
6062: /* mu2+ v21*lc1*cost + v22*lc2*sin(t) */
6063: if(first==1){
6064: first=0;
6065: fprintf(ficgp,"\n# Ellipsoids of confidence\n#\n");
6066: fprintf(ficgp,"\nset parametric;unset label");
6067: 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);
6068: fprintf(ficgp,"\nset ter svg size 640, 480");
6069: fprintf(fichtmcov,"\n<br>Ellipsoids of confidence cov(p%1d%1d,p%1d%1d) expressed in year<sup>-1</sup>\
1.220 brouard 6070: :<a href=\"%s_%d%1d%1d-%1d%1d.svg\"> \
1.201 brouard 6071: %s_%d%1d%1d-%1d%1d.svg</A>, ",k1,l1,k2,l2,\
1.222 brouard 6072: subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2, \
6073: subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
6074: fprintf(fichtmcov,"\n<br><img src=\"%s_%d%1d%1d-%1d%1d.svg\"> ",subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
6075: fprintf(fichtmcov,"\n<br> Correlation at age %d (%.3f),",(int) age, c12);
6076: fprintf(ficgp,"\nset out \"%s_%d%1d%1d-%1d%1d.svg\"",subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
6077: fprintf(ficgp,"\nset label \"%d\" at %11.3e,%11.3e center",(int) age, mu1,mu2);
6078: fprintf(ficgp,"\n# Age %d, p%1d%1d - p%1d%1d",(int) age, k1,l1,k2,l2);
6079: 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", \
6080: mu1,std,v11,sqrt(lc1),v12,sqrt(lc2), \
6081: mu2,std,v21,sqrt(lc1),v22,sqrt(lc2));
6082: }else{
6083: first=0;
6084: fprintf(fichtmcov," %d (%.3f),",(int) age, c12);
6085: fprintf(ficgp,"\n# Age %d, p%1d%1d - p%1d%1d",(int) age, k1,l1,k2,l2);
6086: fprintf(ficgp,"\nset label \"%d\" at %11.3e,%11.3e center",(int) age, mu1,mu2);
6087: 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", \
6088: mu1,std,v11,sqrt(lc1),v12,sqrt(lc2), \
6089: mu2,std,v21,sqrt(lc1),v22,sqrt(lc2));
6090: }/* if first */
6091: } /* age mod 5 */
6092: } /* end loop age */
6093: fprintf(ficgp,"\nset out;\nset out \"%s_%d%1d%1d-%1d%1d.svg\";replot;set out;",subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
6094: first=1;
6095: } /*l12 */
6096: } /* k12 */
6097: } /*l1 */
6098: }/* k1 */
6099: } /* loop on combination of covariates j1 */
6100: free_ma3x(varpij,1,nlstate,1,nlstate+ndeath,(int) bage, (int)fage);
6101: free_matrix(mu,1,(nlstate+ndeath)*(nlstate+ndeath),(int) bage, (int)fage);
6102: free_matrix(doldm,1,(nlstate)*(nlstate+ndeath),1,(nlstate)*(nlstate+ndeath));
6103: free_matrix(dnewm,1,(nlstate)*(nlstate+ndeath),1,npar);
6104: free_vector(xp,1,npar);
6105: fclose(ficresprob);
6106: fclose(ficresprobcov);
6107: fclose(ficresprobcor);
6108: fflush(ficgp);
6109: fflush(fichtmcov);
6110: }
1.126 brouard 6111:
6112:
6113: /******************* Printing html file ***********/
1.201 brouard 6114: void printinghtml(char fileresu[], char title[], char datafile[], int firstpass, \
1.126 brouard 6115: int lastpass, int stepm, int weightopt, char model[],\
6116: int imx,int jmin, int jmax, double jmeanint,char rfileres[],\
1.217 brouard 6117: int popforecast, int prevfcast, int backcast, int estepm , \
1.213 brouard 6118: double jprev1, double mprev1,double anprev1, double dateprev1, \
6119: double jprev2, double mprev2,double anprev2, double dateprev2){
1.237 brouard 6120: int jj1, k1, i1, cpt, k4, nres;
1.126 brouard 6121:
6122: fprintf(fichtm,"<ul><li><a href='#firstorder'>Result files (first order: no variance)</a>\n \
6123: <li><a href='#secondorder'>Result files (second order (variance)</a>\n \
6124: </ul>");
1.237 brouard 6125: fprintf(fichtm,"<ul><li> model=1+age+%s\n \
6126: </ul>", model);
1.214 brouard 6127: fprintf(fichtm,"<ul><li><h4><a name='firstorder'>Result files (first order: no variance)</a></h4>\n");
6128: 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",
6129: jprev1, mprev1,anprev1,jprev2, mprev2,anprev2,subdirfext3(optionfilefiname,"PHTMFR_",".htm"),subdirfext3(optionfilefiname,"PHTMFR_",".htm"));
6130: 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 6131: jprev1, mprev1,anprev1,jprev2, mprev2,anprev2,subdirfext3(optionfilefiname,"PHTM_",".htm"),subdirfext3(optionfilefiname,"PHTM_",".htm"));
6132: fprintf(fichtm,", <a href=\"%s\">%s</a> (text file) <br>\n",subdirf2(fileresu,"P_"),subdirf2(fileresu,"P_"));
1.126 brouard 6133: fprintf(fichtm,"\
6134: - Estimated transition probabilities over %d (stepm) months: <a href=\"%s\">%s</a><br>\n ",
1.201 brouard 6135: stepm,subdirf2(fileresu,"PIJ_"),subdirf2(fileresu,"PIJ_"));
1.126 brouard 6136: fprintf(fichtm,"\
1.217 brouard 6137: - Estimated back transition probabilities over %d (stepm) months: <a href=\"%s\">%s</a><br>\n ",
6138: stepm,subdirf2(fileresu,"PIJB_"),subdirf2(fileresu,"PIJB_"));
6139: fprintf(fichtm,"\
1.126 brouard 6140: - Period (stable) prevalence in each health state: <a href=\"%s\">%s</a> <br>\n",
1.201 brouard 6141: subdirf2(fileresu,"PL_"),subdirf2(fileresu,"PL_"));
1.126 brouard 6142: fprintf(fichtm,"\
1.217 brouard 6143: - Period (stable) back prevalence in each health state: <a href=\"%s\">%s</a> <br>\n",
6144: subdirf2(fileresu,"PLB_"),subdirf2(fileresu,"PLB_"));
6145: fprintf(fichtm,"\
1.211 brouard 6146: - (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 6147: <a href=\"%s\">%s</a> <br>\n",
1.201 brouard 6148: estepm,subdirf2(fileresu,"E_"),subdirf2(fileresu,"E_"));
1.211 brouard 6149: if(prevfcast==1){
6150: fprintf(fichtm,"\
6151: - Prevalence projections by age and states: \
1.201 brouard 6152: <a href=\"%s\">%s</a> <br>\n</li>", subdirf2(fileresu,"F_"),subdirf2(fileresu,"F_"));
1.211 brouard 6153: }
1.126 brouard 6154:
1.222 brouard 6155: fprintf(fichtm," \n<ul><li><b>Graphs</b></li><p>");
1.126 brouard 6156:
1.225 brouard 6157: m=pow(2,cptcoveff);
1.222 brouard 6158: if (cptcovn < 1) {m=1;ncodemax[1]=1;}
1.126 brouard 6159:
1.222 brouard 6160: jj1=0;
1.237 brouard 6161:
6162: for(nres=1; nres <= nresult; nres++) /* For each resultline */
1.241 brouard 6163: for(k1=1; k1<=m;k1++){ /* For each combination of covariate */
1.237 brouard 6164: if(TKresult[nres]!= k1)
6165: continue;
1.220 brouard 6166:
1.222 brouard 6167: /* for(i1=1; i1<=ncodemax[k1];i1++){ */
6168: jj1++;
6169: if (cptcovn > 0) {
6170: fprintf(fichtm,"<hr size=\"2\" color=\"#EC5E5E\">************ Results for covariates");
1.225 brouard 6171: for (cpt=1; cpt<=cptcoveff;cpt++){
1.237 brouard 6172: fprintf(fichtm," V%d=%d ",Tvresult[nres][cpt],(int)Tresult[nres][cpt]);
6173: printf(" V%d=%d ",Tvresult[nres][cpt],Tresult[nres][cpt]);fflush(stdout);
6174: /* fprintf(fichtm," V%d=%d ",Tvaraff[cpt],nbcode[Tvaraff[cpt]][codtabm(jj1,cpt)]); */
6175: /* printf(" V%d=%d ",Tvaraff[cpt],nbcode[Tvaraff[cpt]][codtabm(jj1,cpt)]);fflush(stdout); */
1.222 brouard 6176: }
1.237 brouard 6177: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
6178: fprintf(fichtm," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
6179: printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);fflush(stdout);
6180: }
6181:
1.230 brouard 6182: /* if(nqfveff+nqtveff 0) */ /* Test to be done */
1.222 brouard 6183: fprintf(fichtm," ************\n<hr size=\"2\" color=\"#EC5E5E\">");
6184: if(invalidvarcomb[k1]){
6185: fprintf(fichtm,"\n<h3>Combination (%d) ignored because no cases </h3>\n",k1);
6186: printf("\nCombination (%d) ignored because no cases \n",k1);
6187: continue;
6188: }
6189: }
6190: /* aij, bij */
1.241 brouard 6191: fprintf(fichtm,"<br>- Logit model (yours is: 1+age+%s), for example: logit(pij)=log(pij/pii)= aij+ bij age + V1 age + etc. as a function of age: <a href=\"%s_%d-1-%d.svg\">%s_%d-1-%d.svg</a><br> \
6192: <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 6193: /* Pij */
1.241 brouard 6194: 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> \
6195: <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 6196: /* Quasi-incidences */
6197: 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 6198: before but expressed in per year i.e. quasi incidences if stepm is small and probabilities too, \
1.211 brouard 6199: 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 6200: 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> \
6201: <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 6202: /* Survival functions (period) in state j */
6203: for(cpt=1; cpt<=nlstate;cpt++){
1.241 brouard 6204: 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> \
6205: <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 6206: }
6207: /* State specific survival functions (period) */
6208: for(cpt=1; cpt<=nlstate;cpt++){
6209: fprintf(fichtm,"<br>\n- Survival functions from state %d in each live state and total.\
1.220 brouard 6210: Or probability to survive in various states (1 to %d) being in state %d at different ages. \
1.241 brouard 6211: <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 6212: }
6213: /* Period (stable) prevalence in each health state */
6214: for(cpt=1; cpt<=nlstate;cpt++){
1.241 brouard 6215: fprintf(fichtm,"<br>\n- Convergence to period (stable) prevalence in state %d. Or probability to be in state %d being in state (1 to %d) at different ages. <a href=\"%s_%d-%d-%d.svg\">%s_%d-%d-%d.svg</a><br> \
6216: <img src=\"%s_%d-%d-%d.svg\">", cpt, cpt, nlstate, subdirf2(optionfilefiname,"P_"),cpt,k1,nres,subdirf2(optionfilefiname,"P_"),cpt,k1,nres,subdirf2(optionfilefiname,"P_"),cpt,k1,nres);
1.222 brouard 6217: }
6218: if(backcast==1){
6219: /* Period (stable) back prevalence in each health state */
6220: for(cpt=1; cpt<=nlstate;cpt++){
1.241 brouard 6221: fprintf(fichtm,"<br>\n- Convergence to period (stable) back prevalence in state %d. Or probability to be in state %d being in state (1 to %d) at different ages. <a href=\"%s_%d-%d-%d.svg\">%s_%d-%d-%d.svg</a><br> \
6222: <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 6223: }
1.217 brouard 6224: }
1.222 brouard 6225: if(prevfcast==1){
6226: /* Projection of prevalence up to period (stable) prevalence in each health state */
6227: for(cpt=1; cpt<=nlstate;cpt++){
1.241 brouard 6228: fprintf(fichtm,"<br>\n- Projection of cross-sectional prevalence (estimated with cases observed from %.1f to %.1f) up to period (stable) prevalence in state %d. Or probability to be in state %d being in state (1 to %d) at different ages. <a href=\"%s_%d-%d-%d.svg\">%s_%d-%d-%d.svg</a><br> \
6229: <img src=\"%s_%d-%d-%d.svg\">", dateprev1, dateprev2, cpt, cpt, nlstate, subdirf2(optionfilefiname,"PROJ_"),cpt,k1,nres,subdirf2(optionfilefiname,"PROJ_"),cpt,k1,nres,subdirf2(optionfilefiname,"PROJ_"),cpt,k1,nres);
1.222 brouard 6230: }
6231: }
1.220 brouard 6232:
1.222 brouard 6233: for(cpt=1; cpt<=nlstate;cpt++) {
1.241 brouard 6234: 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> \
6235: <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 6236: }
6237: /* } /\* end i1 *\/ */
6238: }/* End k1 */
6239: fprintf(fichtm,"</ul>");
1.126 brouard 6240:
1.222 brouard 6241: fprintf(fichtm,"\
1.126 brouard 6242: \n<br><li><h4> <a name='secondorder'>Result files (second order: variances)</a></h4>\n\
1.193 brouard 6243: - Parameter file with estimated parameters and covariance matrix: <a href=\"%s\">%s</a> <br> \
1.203 brouard 6244: - 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 6245: But because parameters are usually highly correlated (a higher incidence of disability \
6246: and a higher incidence of recovery can give very close observed transition) it might \
6247: be very useful to look not only at linear confidence intervals estimated from the \
6248: variances but at the covariance matrix. And instead of looking at the estimated coefficients \
6249: (parameters) of the logistic regression, it might be more meaningful to visualize the \
6250: covariance matrix of the one-step probabilities. \
6251: See page 'Matrix of variance-covariance of one-step probabilities' below. \n", rfileres,rfileres);
1.126 brouard 6252:
1.222 brouard 6253: fprintf(fichtm," - Standard deviation of one-step probabilities: <a href=\"%s\">%s</a> <br>\n",
6254: subdirf2(fileresu,"PROB_"),subdirf2(fileresu,"PROB_"));
6255: fprintf(fichtm,"\
1.126 brouard 6256: - Variance-covariance of one-step probabilities: <a href=\"%s\">%s</a> <br>\n",
1.222 brouard 6257: subdirf2(fileresu,"PROBCOV_"),subdirf2(fileresu,"PROBCOV_"));
1.126 brouard 6258:
1.222 brouard 6259: fprintf(fichtm,"\
1.126 brouard 6260: - Correlation matrix of one-step probabilities: <a href=\"%s\">%s</a> <br>\n",
1.222 brouard 6261: subdirf2(fileresu,"PROBCOR_"),subdirf2(fileresu,"PROBCOR_"));
6262: fprintf(fichtm,"\
1.126 brouard 6263: - 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): \
6264: <a href=\"%s\">%s</a> <br>\n</li>",
1.201 brouard 6265: estepm,subdirf2(fileresu,"CVE_"),subdirf2(fileresu,"CVE_"));
1.222 brouard 6266: fprintf(fichtm,"\
1.126 brouard 6267: - (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): \
6268: <a href=\"%s\">%s</a> <br>\n</li>",
1.201 brouard 6269: estepm,subdirf2(fileresu,"STDE_"),subdirf2(fileresu,"STDE_"));
1.222 brouard 6270: fprintf(fichtm,"\
1.128 brouard 6271: - 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 6272: estepm, subdirf2(fileresu,"V_"),subdirf2(fileresu,"V_"));
6273: fprintf(fichtm,"\
1.128 brouard 6274: - 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 6275: estepm, subdirf2(fileresu,"T_"),subdirf2(fileresu,"T_"));
6276: fprintf(fichtm,"\
1.126 brouard 6277: - Standard deviation of period (stable) prevalences: <a href=\"%s\">%s</a> <br>\n",\
1.222 brouard 6278: subdirf2(fileresu,"VPL_"),subdirf2(fileresu,"VPL_"));
1.126 brouard 6279:
6280: /* if(popforecast==1) fprintf(fichtm,"\n */
6281: /* - Prevalences forecasting: <a href=\"f%s\">f%s</a> <br>\n */
6282: /* - Population forecasting (if popforecast=1): <a href=\"pop%s\">pop%s</a> <br>\n */
6283: /* <br>",fileres,fileres,fileres,fileres); */
6284: /* else */
6285: /* 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 6286: fflush(fichtm);
6287: fprintf(fichtm," <ul><li><b>Graphs</b></li><p>");
1.126 brouard 6288:
1.225 brouard 6289: m=pow(2,cptcoveff);
1.222 brouard 6290: if (cptcovn < 1) {m=1;ncodemax[1]=1;}
1.126 brouard 6291:
1.222 brouard 6292: jj1=0;
1.237 brouard 6293:
1.241 brouard 6294: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.222 brouard 6295: for(k1=1; k1<=m;k1++){
1.237 brouard 6296: if(TKresult[nres]!= k1)
6297: continue;
1.222 brouard 6298: /* for(i1=1; i1<=ncodemax[k1];i1++){ */
6299: jj1++;
1.126 brouard 6300: if (cptcovn > 0) {
6301: fprintf(fichtm,"<hr size=\"2\" color=\"#EC5E5E\">************ Results for covariates");
1.225 brouard 6302: for (cpt=1; cpt<=cptcoveff;cpt++) /**< cptcoveff number of variables */
1.237 brouard 6303: fprintf(fichtm," V%d=%d ",Tvresult[nres][cpt],Tresult[nres][cpt]);
6304: /* fprintf(fichtm," V%d=%d ",Tvaraff[cpt],nbcode[Tvaraff[cpt]][codtabm(jj1,cpt)]); */
6305: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
6306: fprintf(fichtm," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
6307: }
6308:
1.126 brouard 6309: fprintf(fichtm," ************\n<hr size=\"2\" color=\"#EC5E5E\">");
1.220 brouard 6310:
1.222 brouard 6311: if(invalidvarcomb[k1]){
6312: fprintf(fichtm,"\n<h4>Combination (%d) ignored because no cases </h4>\n",k1);
6313: continue;
6314: }
1.126 brouard 6315: }
6316: for(cpt=1; cpt<=nlstate;cpt++) {
1.218 brouard 6317: fprintf(fichtm,"\n<br>- Observed (cross-sectional) and period (incidence based) \
1.241 brouard 6318: prevalence (with 95%% confidence interval) in state (%d): <a href=\"%s_%d-%d-%d.svg\"> %s_%d-%d-%d.svg</a>\n <br>\
6319: <img src=\"%s_%d-%d-%d.svg\">",cpt,subdirf2(optionfilefiname,"V_"),cpt,k1,nres,subdirf2(optionfilefiname,"V_"),cpt,k1,nres,subdirf2(optionfilefiname,"V_"),cpt,k1,nres);
1.126 brouard 6320: }
6321: fprintf(fichtm,"\n<br>- Total life expectancy by age and \
1.128 brouard 6322: health expectancies in states (1) and (2). If popbased=1 the smooth (due to the model) \
6323: true period expectancies (those weighted with period prevalences are also\
6324: drawn in addition to the population based expectancies computed using\
1.241 brouard 6325: observed and cahotic prevalences: <a href=\"%s_%d-%d.svg\">%s_%d-%d.svg</a>\n<br>\
6326: <img src=\"%s_%d-%d.svg\">",subdirf2(optionfilefiname,"E_"),k1,nres,subdirf2(optionfilefiname,"E_"),k1,nres,subdirf2(optionfilefiname,"E_"),k1,nres);
1.222 brouard 6327: /* } /\* end i1 *\/ */
6328: }/* End k1 */
1.241 brouard 6329: }/* End nres */
1.222 brouard 6330: fprintf(fichtm,"</ul>");
6331: fflush(fichtm);
1.126 brouard 6332: }
6333:
6334: /******************* Gnuplot file **************/
1.223 brouard 6335: void printinggnuplot(char fileresu[], char optionfilefiname[], double ageminpar, double agemaxpar, double fage , int prevfcast, int backcast, char pathc[], double p[]){
1.126 brouard 6336:
6337: char dirfileres[132],optfileres[132];
1.223 brouard 6338: char gplotcondition[132];
1.237 brouard 6339: 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 6340: int lv=0, vlv=0, kl=0;
1.130 brouard 6341: int ng=0;
1.201 brouard 6342: int vpopbased;
1.223 brouard 6343: int ioffset; /* variable offset for columns */
1.235 brouard 6344: int nres=0; /* Index of resultline */
1.219 brouard 6345:
1.126 brouard 6346: /* if((ficgp=fopen(optionfilegnuplot,"a"))==NULL) { */
6347: /* printf("Problem with file %s",optionfilegnuplot); */
6348: /* fprintf(ficlog,"Problem with file %s",optionfilegnuplot); */
6349: /* } */
6350:
6351: /*#ifdef windows */
6352: fprintf(ficgp,"cd \"%s\" \n",pathc);
1.223 brouard 6353: /*#endif */
1.225 brouard 6354: m=pow(2,cptcoveff);
1.126 brouard 6355:
1.202 brouard 6356: /* Contribution to likelihood */
6357: /* Plot the probability implied in the likelihood */
1.223 brouard 6358: fprintf(ficgp,"\n# Contributions to the Likelihood, mle >=1. For mle=4 no interpolation, pure matrix products.\n#\n");
6359: fprintf(ficgp,"\n set log y; unset log x;set xlabel \"Age\"; set ylabel \"Likelihood (-2Log(L))\";");
6360: /* fprintf(ficgp,"\nset ter svg size 640, 480"); */ /* Too big for svg */
6361: fprintf(ficgp,"\nset ter pngcairo size 640, 480");
1.204 brouard 6362: /* nice for mle=4 plot by number of matrix products.
1.202 brouard 6363: replot "rrtest1/toto.txt" u 2:($4 == 1 && $5==2 ? $9 : 1/0):5 t "p12" with point lc 1 */
6364: /* replot exp(p1+p2*x)/(1+exp(p1+p2*x)+exp(p3+p4*x)+exp(p5+p6*x)) t "p12(x)" */
1.223 brouard 6365: /* fprintf(ficgp,"\nset out \"%s.svg\";",subdirf2(optionfilefiname,"ILK_")); */
6366: fprintf(ficgp,"\nset out \"%s-dest.png\";",subdirf2(optionfilefiname,"ILK_"));
6367: 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));
6368: fprintf(ficgp,"\nset out \"%s-ori.png\";",subdirf2(optionfilefiname,"ILK_"));
6369: 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));
6370: for (i=1; i<= nlstate ; i ++) {
6371: fprintf(ficgp,"\nset out \"%s-p%dj.png\";set ylabel \"Probability for each individual/wave\";",subdirf2(optionfilefiname,"ILK_"),i);
6372: fprintf(ficgp,"unset log;\n# plot weighted, mean weight should have point size of 0.5\n plot \"%s\"",subdirf(fileresilk));
6373: 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);
6374: for (j=2; j<= nlstate+ndeath ; j ++) {
6375: 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);
6376: }
6377: fprintf(ficgp,";\nset out; unset ylabel;\n");
6378: }
6379: /* 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 */
6380: /* fprintf(ficgp,"\nset log y;plot \"%s\" u 2:(-$11):3 t \"All sample, all transitions\" with dots lc variable",subdirf(fileresilk)); */
6381: /* fprintf(ficgp,"\nreplot \"%s\" u 2:($3 <= 3 ? -$11 : 1/0):3 t \"First 3 individuals\" with line lc variable", subdirf(fileresilk)); */
6382: fprintf(ficgp,"\nset out;unset log\n");
6383: /* fprintf(ficgp,"\nset out \"%s.svg\"; replot; set out; # bug gnuplot",subdirf2(optionfilefiname,"ILK_")); */
1.202 brouard 6384:
1.126 brouard 6385: strcpy(dirfileres,optionfilefiname);
6386: strcpy(optfileres,"vpl");
1.223 brouard 6387: /* 1eme*/
1.238 brouard 6388: for (cpt=1; cpt<= nlstate ; cpt ++){ /* For each live state */
6389: for (k1=1; k1<= m ; k1 ++){ /* For each valid combination of covariate */
1.236 brouard 6390: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.238 brouard 6391: /* plot [100000000000000000000:-100000000000000000000] "mysbiaspar/vplrmysbiaspar.txt to check */
6392: if(TKresult[nres]!= k1)
6393: continue;
6394: /* We are interested in selected combination by the resultline */
6395: printf("\n# 1st: Period (stable) prevalence with CI: 'VPL_' files and live state =%d ", cpt);
6396: fprintf(ficgp,"\n# 1st: Period (stable) prevalence with CI: 'VPL_' files and live state =%d ", cpt);
6397: for (k=1; k<=cptcoveff; k++){ /* For each covariate k get corresponding value lv for combination k1 */
6398: lv= decodtabm(k1,k,cptcoveff); /* Should be the value of the covariate corresponding to k1 combination */
6399: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
6400: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
6401: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
6402: vlv= nbcode[Tvaraff[k]][lv]; /* vlv is the value of the covariate lv, 0 or 1 */
6403: /* For each combination of covariate k1 (V1=1, V3=0), we printed the current covariate k and its value vlv */
6404: printf(" V%d=%d ",Tvaraff[k],vlv);
6405: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
6406: }
6407: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
6408: printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
6409: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
6410: }
6411: printf("\n#\n");
6412: fprintf(ficgp,"\n#\n");
6413: if(invalidvarcomb[k1]){
6414: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
6415: continue;
6416: }
1.235 brouard 6417:
1.241 brouard 6418: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"V_"),cpt,k1,nres);
6419: fprintf(ficgp,"\n#set out \"V_%s_%d-%d-%d.svg\" \n",optionfilefiname,cpt,k1,nres);
6420: 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);
1.235 brouard 6421:
1.238 brouard 6422: for (i=1; i<= nlstate ; i ++) {
6423: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
6424: else fprintf(ficgp," %%*lf (%%*lf)");
6425: }
1.242 brouard 6426: 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_"),k1-1,k1-1,nres);
1.238 brouard 6427: for (i=1; i<= nlstate ; i ++) {
6428: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
6429: else fprintf(ficgp," %%*lf (%%*lf)");
6430: }
1.242 brouard 6431: fprintf(ficgp,"\" t\"95%% CI\" w l lt 1,\"%s\" every :::%d::%d u 1:($2==%d ? $3-1.96*$4 : 1/0) \"%%lf %%lf",subdirf2(fileresu,"VPL_"),k1-1,k1-1,nres);
1.238 brouard 6432: for (i=1; i<= nlstate ; i ++) {
6433: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
6434: else fprintf(ficgp," %%*lf (%%*lf)");
6435: }
6436: fprintf(ficgp,"\" t\"\" w l lt 1,\"%s\" every :::%d::%d u 1:($%d) t\"Observed prevalence\" w l lt 2",subdirf2(fileresu,"P_"),k1-1,k1-1,2+4*(cpt-1));
6437: if(backcast==1){ /* We need to get the corresponding values of the covariates involved in this combination k1 */
6438: /* fprintf(ficgp,",\"%s\" every :::%d::%d u 1:($%d) t\"Backward stable prevalence\" w l lt 3",subdirf2(fileresu,"PLB_"),k1-1,k1-1,1+cpt); */
1.242 brouard 6439: fprintf(ficgp,",\"%s\" u 1:((",subdirf2(fileresu,"PLB_")); /* Age is in 1, nres in 2 to be fixed */
1.238 brouard 6440: if(cptcoveff ==0){
6441: fprintf(ficgp,"$%d)) t 'Backward prevalence in state %d' with line ", 2+(cpt-1), cpt );
6442: }else{
6443: kl=0;
6444: for (k=1; k<=cptcoveff; k++){ /* For each combination of covariate */
6445: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate value corresponding to k1 combination and kth covariate */
6446: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
6447: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
6448: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
6449: vlv= nbcode[Tvaraff[k]][lv];
1.223 brouard 6450: kl++;
1.238 brouard 6451: /* 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 *\/ */
6452: /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */
6453: /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */
6454: /* '' u 6:(($1==1 && $2==0 && $3==2 && $4==0)? $9/(1.-$15) : 1/0):($5==2000? 3:2) t 'p.1' with line lc variable*/
6455: if(k==cptcoveff){
6456: fprintf(ficgp,"$%d==%d && $%d==%d)? $%d : 1/0) t 'Backward prevalence in state %d' ",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][lv], \
1.242 brouard 6457: 2+cptcoveff*2+(cpt-1), cpt ); /* 4 or 6 ?*/
1.238 brouard 6458: }else{
6459: fprintf(ficgp,"$%d==%d && $%d==%d && ",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][lv]);
6460: kl++;
6461: }
6462: } /* end covariate */
6463: } /* end if no covariate */
6464: } /* end if backcast */
6465: fprintf(ficgp,"\nset out \n");
6466: } /* nres */
1.201 brouard 6467: } /* k1 */
6468: } /* cpt */
1.235 brouard 6469:
6470:
1.126 brouard 6471: /*2 eme*/
1.238 brouard 6472: for (k1=1; k1<= m ; k1 ++){
6473: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
6474: if(TKresult[nres]!= k1)
6475: continue;
6476: fprintf(ficgp,"\n# 2nd: Total life expectancy with CI: 't' files ");
6477: for (k=1; k<=cptcoveff; k++){ /* For each covariate and each value */
1.225 brouard 6478: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate number corresponding to k1 combination */
1.223 brouard 6479: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
6480: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
6481: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
6482: vlv= nbcode[Tvaraff[k]][lv];
6483: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.211 brouard 6484: }
1.237 brouard 6485: /* for(k=1; k <= ncovds; k++){ */
1.236 brouard 6486: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
1.238 brouard 6487: printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.236 brouard 6488: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.238 brouard 6489: }
1.211 brouard 6490: fprintf(ficgp,"\n#\n");
1.223 brouard 6491: if(invalidvarcomb[k1]){
6492: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
6493: continue;
6494: }
1.219 brouard 6495:
1.241 brouard 6496: fprintf(ficgp,"\nset out \"%s_%d-%d.svg\" \n",subdirf2(optionfilefiname,"E_"),k1,nres);
1.238 brouard 6497: for(vpopbased=0; vpopbased <= popbased; vpopbased++){ /* Done for vpopbased=0 and vpopbased=1 if popbased==1*/
6498: if(vpopbased==0)
6499: fprintf(ficgp,"set ylabel \"Years\" \nset ter svg size 640, 480\nplot [%.f:%.f] ",ageminpar,fage);
6500: else
6501: fprintf(ficgp,"\nreplot ");
6502: for (i=1; i<= nlstate+1 ; i ++) {
6503: k=2*i;
6504: fprintf(ficgp,"\"%s\" every :::%d::%d u 1:($2==%d && $4!=0 ?$4 : 1/0) \"%%lf %%lf %%lf",subdirf2(fileresu,"T_"),k1-1,k1-1, vpopbased);
6505: for (j=1; j<= nlstate+1 ; j ++) {
6506: if (j==i) fprintf(ficgp," %%lf (%%lf)");
6507: else fprintf(ficgp," %%*lf (%%*lf)");
6508: }
6509: if (i== 1) fprintf(ficgp,"\" t\"TLE\" w l lt %d, \\\n",i);
6510: else fprintf(ficgp,"\" t\"LE in state (%d)\" w l lt %d, \\\n",i-1,i+1);
6511: fprintf(ficgp,"\"%s\" every :::%d::%d u 1:($2==%d && $4!=0 ? $4-$5*2 : 1/0) \"%%lf %%lf %%lf",subdirf2(fileresu,"T_"),k1-1,k1-1,vpopbased);
6512: for (j=1; j<= nlstate+1 ; j ++) {
6513: if (j==i) fprintf(ficgp," %%lf (%%lf)");
6514: else fprintf(ficgp," %%*lf (%%*lf)");
6515: }
6516: fprintf(ficgp,"\" t\"\" w l lt 0,");
6517: fprintf(ficgp,"\"%s\" every :::%d::%d u 1:($2==%d && $4!=0 ? $4+$5*2 : 1/0) \"%%lf %%lf %%lf",subdirf2(fileresu,"T_"),k1-1,k1-1,vpopbased);
6518: for (j=1; j<= nlstate+1 ; j ++) {
6519: if (j==i) fprintf(ficgp," %%lf (%%lf)");
6520: else fprintf(ficgp," %%*lf (%%*lf)");
6521: }
6522: if (i== (nlstate+1)) fprintf(ficgp,"\" t\"\" w l lt 0");
6523: else fprintf(ficgp,"\" t\"\" w l lt 0,\\\n");
6524: } /* state */
6525: } /* vpopbased */
6526: fprintf(ficgp,"\nset out;set out \"%s_%d.svg\"; replot; set out; \n",subdirf2(optionfilefiname,"E_"),k1); /* Buggy gnuplot */
6527: } /* end nres */
6528: } /* k1 end 2 eme*/
6529:
6530:
6531: /*3eme*/
6532: for (k1=1; k1<= m ; k1 ++){
6533: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.240 brouard 6534: if(TKresult[nres]!= k1)
1.238 brouard 6535: continue;
6536:
6537: for (cpt=1; cpt<= nlstate ; cpt ++) {
6538: fprintf(ficgp,"\n# 3d: Life expectancy with EXP_ files: combination=%d state=%d",k1, cpt);
6539: for (k=1; k<=cptcoveff; k++){ /* For each covariate and each value */
6540: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate number corresponding to k1 combination */
6541: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
6542: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
6543: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
6544: vlv= nbcode[Tvaraff[k]][lv];
6545: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
6546: }
6547: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
6548: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
6549: }
6550: fprintf(ficgp,"\n#\n");
6551: if(invalidvarcomb[k1]){
6552: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
6553: continue;
6554: }
6555:
6556: /* k=2+nlstate*(2*cpt-2); */
6557: k=2+(nlstate+1)*(cpt-1);
1.241 brouard 6558: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"EXP_"),cpt,k1,nres);
1.238 brouard 6559: fprintf(ficgp,"set ter svg size 640, 480\n\
1.201 brouard 6560: plot [%.f:%.f] \"%s\" every :::%d::%d u 1:%d t \"e%d1\" w l",ageminpar,fage,subdirf2(fileresu,"E_"),k1-1,k1-1,k,cpt);
1.238 brouard 6561: /*fprintf(ficgp,",\"e%s\" every :::%d::%d u 1:($%d-2*$%d) \"\%%lf ",fileres,k1-1,k1-1,k,k+1);
6562: for (i=1; i<= nlstate*2 ; i ++) fprintf(ficgp,"\%%lf (\%%lf) ");
6563: fprintf(ficgp,"\" t \"e%d1\" w l",cpt);
6564: fprintf(ficgp,",\"e%s\" every :::%d::%d u 1:($%d+2*$%d) \"\%%lf ",fileres,k1-1,k1-1,k,k+1);
6565: for (i=1; i<= nlstate*2 ; i ++) fprintf(ficgp,"\%%lf (\%%lf) ");
6566: fprintf(ficgp,"\" t \"e%d1\" w l",cpt);
1.219 brouard 6567:
1.238 brouard 6568: */
6569: for (i=1; i< nlstate ; i ++) {
6570: fprintf(ficgp," ,\"%s\" every :::%d::%d u 1:%d t \"e%d%d\" w l",subdirf2(fileresu,"E_"),k1-1,k1-1,k+i,cpt,i+1);
6571: /* 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 6572:
1.238 brouard 6573: }
6574: fprintf(ficgp," ,\"%s\" every :::%d::%d u 1:%d t \"e%d.\" w l",subdirf2(fileresu,"E_"),k1-1,k1-1,k+nlstate,cpt);
6575: }
6576: } /* end nres */
6577: } /* end kl 3eme */
1.126 brouard 6578:
1.223 brouard 6579: /* 4eme */
1.201 brouard 6580: /* Survival functions (period) from state i in state j by initial state i */
1.238 brouard 6581: for (k1=1; k1<=m; k1++){ /* For each covariate and each value */
6582: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
6583: if(TKresult[nres]!= k1)
1.223 brouard 6584: continue;
1.238 brouard 6585: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state cpt*/
6586: fprintf(ficgp,"\n#\n#\n# Survival functions in state j : 'LIJ_' files, cov=%d state=%d",k1, cpt);
6587: for (k=1; k<=cptcoveff; k++){ /* For each covariate and each value */
6588: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate number corresponding to k1 combination */
6589: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
6590: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
6591: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
6592: vlv= nbcode[Tvaraff[k]][lv];
6593: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
6594: }
6595: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
6596: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
6597: }
6598: fprintf(ficgp,"\n#\n");
6599: if(invalidvarcomb[k1]){
6600: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
6601: continue;
1.223 brouard 6602: }
1.238 brouard 6603:
1.241 brouard 6604: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"LIJ_"),cpt,k1,nres);
1.238 brouard 6605: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability to be alive\" \n\
6606: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
6607: k=3;
6608: for (i=1; i<= nlstate ; i ++){
6609: if(i==1){
6610: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJ_"));
6611: }else{
6612: fprintf(ficgp,", '' ");
6613: }
6614: l=(nlstate+ndeath)*(i-1)+1;
6615: fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d/($%d",k1,k+l+(cpt-1),k+l);
6616: for (j=2; j<= nlstate+ndeath ; j ++)
6617: fprintf(ficgp,"+$%d",k+l+j-1);
6618: fprintf(ficgp,")) t \"l(%d,%d)\" w l",i,cpt);
6619: } /* nlstate */
6620: fprintf(ficgp,"\nset out\n");
6621: } /* end cpt state*/
6622: } /* end nres */
6623: } /* end covariate k1 */
6624:
1.220 brouard 6625: /* 5eme */
1.201 brouard 6626: /* Survival functions (period) from state i in state j by final state j */
1.238 brouard 6627: for (k1=1; k1<= m ; k1++){ /* For each covariate combination if any */
6628: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
6629: if(TKresult[nres]!= k1)
1.227 brouard 6630: continue;
1.238 brouard 6631: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each inital state */
6632: 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);
6633: for (k=1; k<=cptcoveff; k++){ /* For each covariate and each value */
6634: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate number corresponding to k1 combination */
6635: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
6636: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
6637: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
6638: vlv= nbcode[Tvaraff[k]][lv];
6639: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
6640: }
6641: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
6642: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
6643: }
6644: fprintf(ficgp,"\n#\n");
6645: if(invalidvarcomb[k1]){
6646: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
6647: continue;
6648: }
1.227 brouard 6649:
1.241 brouard 6650: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"LIJT_"),cpt,k1,nres);
1.238 brouard 6651: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability to be alive\" \n\
6652: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
6653: k=3;
6654: for (j=1; j<= nlstate ; j ++){ /* Lived in state j */
6655: if(j==1)
6656: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJ_"));
6657: else
6658: fprintf(ficgp,", '' ");
6659: l=(nlstate+ndeath)*(cpt-1) +j;
6660: fprintf(ficgp," u (($1==%d && (floor($2)%%5 == 0)) ? ($3):1/0):($%d",k1,k+l);
6661: /* for (i=2; i<= nlstate+ndeath ; i ++) */
6662: /* fprintf(ficgp,"+$%d",k+l+i-1); */
6663: fprintf(ficgp,") t \"l(%d,%d)\" w l",cpt,j);
6664: } /* nlstate */
6665: fprintf(ficgp,", '' ");
6666: fprintf(ficgp," u (($1==%d && (floor($2)%%5 == 0)) ? ($3):1/0):(",k1);
6667: for (j=1; j<= nlstate ; j ++){ /* Lived in state j */
6668: l=(nlstate+ndeath)*(cpt-1) +j;
6669: if(j < nlstate)
6670: fprintf(ficgp,"$%d +",k+l);
6671: else
6672: fprintf(ficgp,"$%d) t\"l(%d,.)\" w l",k+l,cpt);
6673: }
6674: fprintf(ficgp,"\nset out\n");
6675: } /* end cpt state*/
6676: } /* end covariate */
6677: } /* end nres */
1.227 brouard 6678:
1.220 brouard 6679: /* 6eme */
1.202 brouard 6680: /* CV preval stable (period) for each covariate */
1.237 brouard 6681: for (k1=1; k1<= m ; k1 ++) /* For each covariate combination if any */
6682: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
6683: if(TKresult[nres]!= k1)
6684: continue;
1.153 brouard 6685: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state */
1.227 brouard 6686:
1.211 brouard 6687: fprintf(ficgp,"\n#\n#\n#CV preval stable (period): 'pij' files, covariatecombination#=%d state=%d",k1, cpt);
1.225 brouard 6688: for (k=1; k<=cptcoveff; k++){ /* For each covariate and each value */
1.227 brouard 6689: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate number corresponding to k1 combination */
6690: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
6691: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
6692: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
6693: vlv= nbcode[Tvaraff[k]][lv];
6694: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.211 brouard 6695: }
1.237 brouard 6696: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
6697: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
6698: }
1.211 brouard 6699: fprintf(ficgp,"\n#\n");
1.223 brouard 6700: if(invalidvarcomb[k1]){
1.227 brouard 6701: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
6702: continue;
1.223 brouard 6703: }
1.227 brouard 6704:
1.241 brouard 6705: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"P_"),cpt,k1,nres);
1.126 brouard 6706: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability\" \n\
1.238 brouard 6707: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
1.211 brouard 6708: k=3; /* Offset */
1.153 brouard 6709: for (i=1; i<= nlstate ; i ++){
1.227 brouard 6710: if(i==1)
6711: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJ_"));
6712: else
6713: fprintf(ficgp,", '' ");
6714: l=(nlstate+ndeath)*(i-1)+1;
6715: fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d/($%d",k1,k+l+(cpt-1),k+l);
6716: for (j=2; j<= nlstate ; j ++)
6717: fprintf(ficgp,"+$%d",k+l+j-1);
6718: fprintf(ficgp,")) t \"prev(%d,%d)\" w l",i,cpt);
1.153 brouard 6719: } /* nlstate */
1.201 brouard 6720: fprintf(ficgp,"\nset out\n");
1.153 brouard 6721: } /* end cpt state*/
6722: } /* end covariate */
1.227 brouard 6723:
6724:
1.220 brouard 6725: /* 7eme */
1.218 brouard 6726: if(backcast == 1){
1.217 brouard 6727: /* CV back preval stable (period) for each covariate */
1.237 brouard 6728: for (k1=1; k1<= m ; k1 ++) /* For each covariate combination if any */
6729: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
6730: if(TKresult[nres]!= k1)
6731: continue;
1.218 brouard 6732: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state */
1.227 brouard 6733: fprintf(ficgp,"\n#\n#\n#CV Back preval stable (period): 'pij' files, covariatecombination#=%d state=%d",k1, cpt);
6734: for (k=1; k<=cptcoveff; k++){ /* For each covariate and each value */
6735: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate number corresponding to k1 combination */
6736: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
6737: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
1.223 brouard 6738: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
1.227 brouard 6739: vlv= nbcode[Tvaraff[k]][lv];
6740: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
6741: }
1.237 brouard 6742: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
6743: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
6744: }
1.227 brouard 6745: fprintf(ficgp,"\n#\n");
6746: if(invalidvarcomb[k1]){
6747: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
6748: continue;
6749: }
6750:
1.241 brouard 6751: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"PB_"),cpt,k1,nres);
1.227 brouard 6752: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability\" \n\
1.238 brouard 6753: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
1.227 brouard 6754: k=3; /* Offset */
6755: for (i=1; i<= nlstate ; i ++){
6756: if(i==1)
6757: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJB_"));
6758: else
6759: fprintf(ficgp,", '' ");
6760: /* l=(nlstate+ndeath)*(i-1)+1; */
6761: l=(nlstate+ndeath)*(cpt-1)+1;
6762: /* fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d/($%d",k1,k+l+(cpt-1),k+l); /\* a vérifier *\/ */
6763: /* fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d/($%d",k1,k+l+(cpt-1),k+l+(cpt-1)+i-1); /\* a vérifier *\/ */
6764: fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d",k1,k+l+(cpt-1)+i-1); /* a vérifier */
6765: /* for (j=2; j<= nlstate ; j ++) */
6766: /* fprintf(ficgp,"+$%d",k+l+j-1); */
6767: /* /\* fprintf(ficgp,"+$%d",k+l+j-1); *\/ */
6768: fprintf(ficgp,") t \"bprev(%d,%d)\" w l",i,cpt);
6769: } /* nlstate */
6770: fprintf(ficgp,"\nset out\n");
1.218 brouard 6771: } /* end cpt state*/
6772: } /* end covariate */
6773: } /* End if backcast */
6774:
1.223 brouard 6775: /* 8eme */
1.218 brouard 6776: if(prevfcast==1){
6777: /* Projection from cross-sectional to stable (period) for each covariate */
6778:
1.237 brouard 6779: for (k1=1; k1<= m ; k1 ++) /* For each covariate combination if any */
6780: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
6781: if(TKresult[nres]!= k1)
6782: continue;
1.211 brouard 6783: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state */
1.227 brouard 6784: fprintf(ficgp,"\n#\n#\n#Projection of prevalence to stable (period): 'PROJ_' files, covariatecombination#=%d state=%d",k1, cpt);
6785: for (k=1; k<=cptcoveff; k++){ /* For each correspondig covariate value */
6786: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate value corresponding to k1 combination and kth covariate */
6787: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
6788: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
6789: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
6790: vlv= nbcode[Tvaraff[k]][lv];
6791: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
6792: }
1.237 brouard 6793: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
6794: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
6795: }
1.227 brouard 6796: fprintf(ficgp,"\n#\n");
6797: if(invalidvarcomb[k1]){
6798: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
6799: continue;
6800: }
6801:
6802: fprintf(ficgp,"# hpijx=probability over h years, hp.jx is weighted by observed prev\n ");
1.241 brouard 6803: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"PROJ_"),cpt,k1,nres);
1.227 brouard 6804: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Prevalence\" \n\
1.238 brouard 6805: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
1.227 brouard 6806: for (i=1; i<= nlstate+1 ; i ++){ /* nlstate +1 p11 p21 p.1 */
6807: /*# V1 = 1 V2 = 0 yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
6808: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
6809: /*# yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
6810: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
6811: if(i==1){
6812: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"F_"));
6813: }else{
6814: fprintf(ficgp,",\\\n '' ");
6815: }
6816: if(cptcoveff ==0){ /* No covariate */
6817: ioffset=2; /* Age is in 2 */
6818: /*# yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/
6819: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */
6820: /*# V1 = 1 yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/
6821: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */
6822: fprintf(ficgp," u %d:(", ioffset);
6823: if(i==nlstate+1)
6824: fprintf(ficgp," $%d/(1.-$%d)) t 'pw.%d' with line ", \
6825: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,cpt );
6826: else
6827: fprintf(ficgp," $%d/(1.-$%d)) t 'p%d%d' with line ", \
6828: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,i,cpt );
6829: }else{ /* more than 2 covariates */
6830: if(cptcoveff ==1){
6831: ioffset=4; /* Age is in 4 */
6832: }else{
6833: ioffset=6; /* Age is in 6 */
6834: /*# V1 = 1 V2 = 0 yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
6835: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
6836: }
6837: fprintf(ficgp," u %d:(",ioffset);
6838: kl=0;
6839: strcpy(gplotcondition,"(");
6840: for (k=1; k<=cptcoveff; k++){ /* For each covariate writing the chain of conditions */
6841: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate value corresponding to combination k1 and covariate k */
6842: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
6843: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
6844: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
6845: vlv= nbcode[Tvaraff[k]][lv]; /* Value of the modality of Tvaraff[k] */
6846: kl++;
6847: sprintf(gplotcondition+strlen(gplotcondition),"$%d==%d && $%d==%d " ,kl,Tvaraff[k], kl+1, nbcode[Tvaraff[k]][lv]);
6848: kl++;
6849: if(k <cptcoveff && cptcoveff>1)
6850: sprintf(gplotcondition+strlen(gplotcondition)," && ");
6851: }
6852: strcpy(gplotcondition+strlen(gplotcondition),")");
6853: /* 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 *\/ */
6854: /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */
6855: /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */
6856: /* '' 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*/
6857: if(i==nlstate+1){
6858: fprintf(ficgp,"%s ? $%d/(1.-$%d) : 1/0) t 'p.%d' with line ", gplotcondition, \
6859: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,cpt );
6860: }else{
6861: fprintf(ficgp,"%s ? $%d/(1.-$%d) : 1/0) t 'p%d%d' with line ", gplotcondition, \
6862: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset +1+(i-1)+(nlstate+1)*nlstate,i,cpt );
6863: }
6864: } /* end if covariate */
6865: } /* nlstate */
6866: fprintf(ficgp,"\nset out\n");
1.223 brouard 6867: } /* end cpt state*/
6868: } /* end covariate */
6869: } /* End if prevfcast */
1.227 brouard 6870:
6871:
1.238 brouard 6872: /* 9eme writing MLE parameters */
6873: fprintf(ficgp,"\n##############\n#9eme MLE estimated parameters\n#############\n");
1.126 brouard 6874: for(i=1,jk=1; i <=nlstate; i++){
1.187 brouard 6875: fprintf(ficgp,"# initial state %d\n",i);
1.126 brouard 6876: for(k=1; k <=(nlstate+ndeath); k++){
6877: if (k != i) {
1.227 brouard 6878: fprintf(ficgp,"# current state %d\n",k);
6879: for(j=1; j <=ncovmodel; j++){
6880: fprintf(ficgp,"p%d=%f; ",jk,p[jk]);
6881: jk++;
6882: }
6883: fprintf(ficgp,"\n");
1.126 brouard 6884: }
6885: }
1.223 brouard 6886: }
1.187 brouard 6887: fprintf(ficgp,"##############\n#\n");
1.227 brouard 6888:
1.145 brouard 6889: /*goto avoid;*/
1.238 brouard 6890: /* 10eme Graphics of probabilities or incidences using written MLE parameters */
6891: fprintf(ficgp,"\n##############\n#10eme Graphics of probabilities or incidences\n#############\n");
1.187 brouard 6892: fprintf(ficgp,"# logi(p12/p11)=a12+b12*age+c12age*age+d12*V1+e12*V1*age\n");
6893: fprintf(ficgp,"# logi(p12/p11)=p1 +p2*age +p3*age*age+ p4*V1+ p5*V1*age\n");
6894: fprintf(ficgp,"# logi(p13/p11)=a13+b13*age+c13age*age+d13*V1+e13*V1*age\n");
6895: fprintf(ficgp,"# logi(p13/p11)=p6 +p7*age +p8*age*age+ p9*V1+ p10*V1*age\n");
6896: fprintf(ficgp,"# p12+p13+p14+p11=1=p11(1+exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)\n");
6897: fprintf(ficgp,"# +exp(a13+b13*age+c13age*age+d13*V1+e13*V1*age)+...)\n");
6898: fprintf(ficgp,"# p11=1/(1+exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)\n");
6899: fprintf(ficgp,"# +exp(a13+b13*age+c13age*age+d13*V1+e13*V1*age)+...)\n");
6900: fprintf(ficgp,"# p12=exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)/\n");
6901: fprintf(ficgp,"# (1+exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)\n");
6902: fprintf(ficgp,"# +exp(a13+b13*age+c13age*age+d13*V1+e13*V1*age))\n");
6903: fprintf(ficgp,"# +exp(a14+b14*age+c14age*age+d14*V1+e14*V1*age)+...)\n");
6904: fprintf(ficgp,"#\n");
1.223 brouard 6905: for(ng=1; ng<=3;ng++){ /* Number of graphics: first is logit, 2nd is probabilities, third is incidences per year*/
1.238 brouard 6906: fprintf(ficgp,"#Number of graphics: first is logit, 2nd is probabilities, third is incidences per year\n");
1.237 brouard 6907: fprintf(ficgp,"#model=%s \n",model);
1.238 brouard 6908: fprintf(ficgp,"# Type of graphic ng=%d\n",ng);
1.237 brouard 6909: fprintf(ficgp,"# jk=1 to 2^%d=%d\n",cptcoveff,m);/* to be checked */
6910: for(jk=1; jk <=m; jk++) /* For each combination of covariate */
6911: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
6912: if(TKresult[nres]!= jk)
6913: continue;
6914: fprintf(ficgp,"# Combination of dummy jk=%d and ",jk);
6915: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
6916: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
6917: }
6918: fprintf(ficgp,"\n#\n");
1.241 brouard 6919: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" ",subdirf2(optionfilefiname,"PE_"),jk,ng,nres);
1.223 brouard 6920: fprintf(ficgp,"\nset ter svg size 640, 480 ");
6921: if (ng==1){
6922: fprintf(ficgp,"\nset ylabel \"Value of the logit of the model\"\n"); /* exp(a12+b12*x) could be nice */
6923: fprintf(ficgp,"\nunset log y");
6924: }else if (ng==2){
6925: fprintf(ficgp,"\nset ylabel \"Probability\"\n");
6926: fprintf(ficgp,"\nset log y");
6927: }else if (ng==3){
6928: fprintf(ficgp,"\nset ylabel \"Quasi-incidence per year\"\n");
6929: fprintf(ficgp,"\nset log y");
6930: }else
6931: fprintf(ficgp,"\nunset title ");
6932: fprintf(ficgp,"\nplot [%.f:%.f] ",ageminpar,agemaxpar);
6933: i=1;
6934: for(k2=1; k2<=nlstate; k2++) {
6935: k3=i;
6936: for(k=1; k<=(nlstate+ndeath); k++) {
6937: if (k != k2){
6938: switch( ng) {
6939: case 1:
6940: if(nagesqr==0)
6941: fprintf(ficgp," p%d+p%d*x",i,i+1);
6942: else /* nagesqr =1 */
6943: fprintf(ficgp," p%d+p%d*x+p%d*x*x",i,i+1,i+1+nagesqr);
6944: break;
6945: case 2: /* ng=2 */
6946: if(nagesqr==0)
6947: fprintf(ficgp," exp(p%d+p%d*x",i,i+1);
6948: else /* nagesqr =1 */
6949: fprintf(ficgp," exp(p%d+p%d*x+p%d*x*x",i,i+1,i+1+nagesqr);
6950: break;
6951: case 3:
6952: if(nagesqr==0)
6953: fprintf(ficgp," %f*exp(p%d+p%d*x",YEARM/stepm,i,i+1);
6954: else /* nagesqr =1 */
6955: fprintf(ficgp," %f*exp(p%d+p%d*x+p%d*x*x",YEARM/stepm,i,i+1,i+1+nagesqr);
6956: break;
6957: }
6958: ij=1;/* To be checked else nbcode[0][0] wrong */
1.237 brouard 6959: ijp=1; /* product no age */
6960: /* for(j=3; j <=ncovmodel-nagesqr; j++) { */
6961: for(j=1; j <=cptcovt; j++) { /* For each covariate of the simplified model */
1.223 brouard 6962: /* printf("Tage[%d]=%d, j=%d\n", ij, Tage[ij], j); */
1.237 brouard 6963: if(j==Tage[ij]) { /* Product by age */
6964: if(ij <=cptcovage) { /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, 2 V5 and V1 */
1.238 brouard 6965: if(DummyV[j]==0){
1.237 brouard 6966: fprintf(ficgp,"+p%d*%d*x",i+j+2+nagesqr-1,Tinvresult[nres][Tvar[j]]);;
6967: }else{ /* quantitative */
6968: fprintf(ficgp,"+p%d*%f*x",i+j+2+nagesqr-1,Tqinvresult[nres][Tvar[j]]); /* Tqinvresult in decoderesult */
6969: /* fprintf(ficgp,"+p%d*%d*x",i+j+nagesqr-1,nbcode[Tvar[j-2]][codtabm(jk,Tvar[j-2])]); */
6970: }
6971: ij++;
6972: }
6973: }else if(j==Tprod[ijp]) { /* */
6974: /* printf("Tprod[%d]=%d, j=%d\n", ij, Tprod[ijp], j); */
6975: if(ijp <=cptcovprod) { /* Product */
1.238 brouard 6976: if(DummyV[Tvard[ijp][1]]==0){/* Vn is dummy */
6977: if(DummyV[Tvard[ijp][2]]==0){/* Vn and Vm are dummy */
1.237 brouard 6978: /* fprintf(ficgp,"+p%d*%d*%d",i+j+2+nagesqr-1,nbcode[Tvard[ijp][1]][codtabm(jk,j)],nbcode[Tvard[ijp][2]][codtabm(jk,j)]); */
6979: fprintf(ficgp,"+p%d*%d*%d",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tinvresult[nres][Tvard[ijp][2]]);
6980: }else{ /* Vn is dummy and Vm is quanti */
6981: /* fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,nbcode[Tvard[ijp][1]][codtabm(jk,j)],Tqinvresult[nres][Tvard[ijp][2]]); */
6982: fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]);
6983: }
6984: }else{ /* Vn*Vm Vn is quanti */
1.238 brouard 6985: if(DummyV[Tvard[ijp][2]]==0){
1.237 brouard 6986: fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][2]],Tqinvresult[nres][Tvard[ijp][1]]);
6987: }else{ /* Both quanti */
6988: fprintf(ficgp,"+p%d*%f*%f",i+j+2+nagesqr-1,Tqinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]);
6989: }
6990: }
1.238 brouard 6991: ijp++;
1.237 brouard 6992: }
6993: } else{ /* simple covariate */
6994: /* fprintf(ficgp,"+p%d*%d",i+j+2+nagesqr-1,nbcode[Tvar[j]][codtabm(jk,j)]); /\* Valgrind bug nbcode *\/ */
6995: if(Dummy[j]==0){
6996: fprintf(ficgp,"+p%d*%d",i+j+2+nagesqr-1,Tinvresult[nres][Tvar[j]]); /* */
6997: }else{ /* quantitative */
6998: fprintf(ficgp,"+p%d*%f",i+j+2+nagesqr-1,Tqinvresult[nres][Tvar[j]]); /* */
1.223 brouard 6999: /* fprintf(ficgp,"+p%d*%d*x",i+j+nagesqr-1,nbcode[Tvar[j-2]][codtabm(jk,Tvar[j-2])]); */
7000: }
1.237 brouard 7001: } /* end simple */
7002: } /* end j */
1.223 brouard 7003: }else{
7004: i=i-ncovmodel;
7005: if(ng !=1 ) /* For logit formula of log p11 is more difficult to get */
7006: fprintf(ficgp," (1.");
7007: }
1.227 brouard 7008:
1.223 brouard 7009: if(ng != 1){
7010: fprintf(ficgp,")/(1");
1.227 brouard 7011:
1.223 brouard 7012: for(k1=1; k1 <=nlstate; k1++){
7013: if(nagesqr==0)
7014: fprintf(ficgp,"+exp(p%d+p%d*x",k3+(k1-1)*ncovmodel,k3+(k1-1)*ncovmodel+1);
7015: else /* nagesqr =1 */
7016: fprintf(ficgp,"+exp(p%d+p%d*x+p%d*x*x",k3+(k1-1)*ncovmodel,k3+(k1-1)*ncovmodel+1,k3+(k1-1)*ncovmodel+1+nagesqr);
1.217 brouard 7017:
1.223 brouard 7018: ij=1;
7019: for(j=3; j <=ncovmodel-nagesqr; j++){
1.237 brouard 7020: if((j-2)==Tage[ij]) { /* Bug valgrind */
7021: if(ij <=cptcovage) { /* Bug valgrind */
1.223 brouard 7022: fprintf(ficgp,"+p%d*%d*x",k3+(k1-1)*ncovmodel+1+j-2+nagesqr,nbcode[Tvar[j-2]][codtabm(jk,j-2)]);
7023: /* fprintf(ficgp,"+p%d*%d*x",k3+(k1-1)*ncovmodel+1+j-2+nagesqr,nbcode[Tvar[j-2]][codtabm(jk,Tvar[j-2])]); */
7024: ij++;
7025: }
7026: }
7027: else
1.225 brouard 7028: fprintf(ficgp,"+p%d*%d",k3+(k1-1)*ncovmodel+1+j-2+nagesqr,nbcode[Tvar[j-2]][codtabm(jk,j-2)]);/* Valgrind bug nbcode */
1.223 brouard 7029: }
7030: fprintf(ficgp,")");
7031: }
7032: fprintf(ficgp,")");
7033: if(ng ==2)
7034: fprintf(ficgp," t \"p%d%d\" ", k2,k);
7035: else /* ng= 3 */
7036: fprintf(ficgp," t \"i%d%d\" ", k2,k);
7037: }else{ /* end ng <> 1 */
7038: if( k !=k2) /* logit p11 is hard to draw */
7039: fprintf(ficgp," t \"logit(p%d%d)\" ", k2,k);
7040: }
7041: if ((k+k2)!= (nlstate*2+ndeath) && ng != 1)
7042: fprintf(ficgp,",");
7043: if (ng == 1 && k!=k2 && (k+k2)!= (nlstate*2+ndeath))
7044: fprintf(ficgp,",");
7045: i=i+ncovmodel;
7046: } /* end k */
7047: } /* end k2 */
7048: fprintf(ficgp,"\n set out\n");
7049: } /* end jk */
7050: } /* end ng */
7051: /* avoid: */
7052: fflush(ficgp);
1.126 brouard 7053: } /* end gnuplot */
7054:
7055:
7056: /*************** Moving average **************/
1.219 brouard 7057: /* int movingaverage(double ***probs, double bage, double fage, double ***mobaverage, int mobilav, double bageout, double fageout){ */
1.222 brouard 7058: int movingaverage(double ***probs, double bage, double fage, double ***mobaverage, int mobilav){
1.218 brouard 7059:
1.222 brouard 7060: int i, cpt, cptcod;
7061: int modcovmax =1;
7062: int mobilavrange, mob;
7063: int iage=0;
7064:
7065: double sum=0.;
7066: double age;
7067: double *sumnewp, *sumnewm;
7068: double *agemingood, *agemaxgood; /* Currently identical for all covariates */
7069:
7070:
1.225 brouard 7071: /* modcovmax=2*cptcoveff;/\* Max number of modalities. We suppose */
1.222 brouard 7072: /* a covariate has 2 modalities, should be equal to ncovcombmax *\/ */
7073:
7074: sumnewp = vector(1,ncovcombmax);
7075: sumnewm = vector(1,ncovcombmax);
7076: agemingood = vector(1,ncovcombmax);
7077: agemaxgood = vector(1,ncovcombmax);
7078:
7079: for (cptcod=1;cptcod<=ncovcombmax;cptcod++){
7080: sumnewm[cptcod]=0.;
7081: sumnewp[cptcod]=0.;
7082: agemingood[cptcod]=0;
7083: agemaxgood[cptcod]=0;
7084: }
7085: if (cptcovn<1) ncovcombmax=1; /* At least 1 pass */
7086:
7087: if(mobilav==1||mobilav ==3 ||mobilav==5 ||mobilav== 7){
7088: if(mobilav==1) mobilavrange=5; /* default */
7089: else mobilavrange=mobilav;
7090: for (age=bage; age<=fage; age++)
7091: for (i=1; i<=nlstate;i++)
7092: for (cptcod=1;cptcod<=ncovcombmax;cptcod++)
7093: mobaverage[(int)age][i][cptcod]=probs[(int)age][i][cptcod];
7094: /* We keep the original values on the extreme ages bage, fage and for
7095: fage+1 and bage-1 we use a 3 terms moving average; for fage+2 bage+2
7096: we use a 5 terms etc. until the borders are no more concerned.
7097: */
7098: for (mob=3;mob <=mobilavrange;mob=mob+2){
7099: for (age=bage+(mob-1)/2; age<=fage-(mob-1)/2; age++){
7100: for (i=1; i<=nlstate;i++){
7101: for (cptcod=1;cptcod<=ncovcombmax;cptcod++){
7102: mobaverage[(int)age][i][cptcod] =probs[(int)age][i][cptcod];
7103: for (cpt=1;cpt<=(mob-1)/2;cpt++){
7104: mobaverage[(int)age][i][cptcod] +=probs[(int)age-cpt][i][cptcod];
7105: mobaverage[(int)age][i][cptcod] +=probs[(int)age+cpt][i][cptcod];
7106: }
7107: mobaverage[(int)age][i][cptcod]=mobaverage[(int)age][i][cptcod]/mob;
7108: }
7109: }
7110: }/* end age */
7111: }/* end mob */
7112: }else
7113: return -1;
7114: for (cptcod=1;cptcod<=ncovcombmax;cptcod++){
7115: /* for (age=bage+(mob-1)/2; age<=fage-(mob-1)/2; age++){ */
7116: if(invalidvarcomb[cptcod]){
7117: printf("\nCombination (%d) ignored because no cases \n",cptcod);
7118: continue;
7119: }
1.219 brouard 7120:
1.222 brouard 7121: agemingood[cptcod]=fage-(mob-1)/2;
7122: for (age=fage-(mob-1)/2; age>=bage; age--){/* From oldest to youngest, finding the youngest wrong */
7123: sumnewm[cptcod]=0.;
7124: for (i=1; i<=nlstate;i++){
7125: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
7126: }
7127: if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
7128: agemingood[cptcod]=age;
7129: }else{ /* bad */
7130: for (i=1; i<=nlstate;i++){
7131: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemingood[cptcod]][i][cptcod];
7132: } /* i */
7133: } /* end bad */
7134: }/* age */
7135: sum=0.;
7136: for (i=1; i<=nlstate;i++){
7137: sum+=mobaverage[(int)agemingood[cptcod]][i][cptcod];
7138: }
7139: if(fabs(sum - 1.) > 1.e-3) { /* bad */
7140: printf("For this combination of covariate cptcod=%d, we can't get a smoothed prevalence which sums to one at any descending age!\n",cptcod);
7141: /* for (i=1; i<=nlstate;i++){ */
7142: /* mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemingood[cptcod]][i][cptcod]; */
7143: /* } /\* i *\/ */
7144: } /* end bad */
7145: /* else{ /\* We found some ages summing to one, we will smooth the oldest *\/ */
7146: /* From youngest, finding the oldest wrong */
7147: agemaxgood[cptcod]=bage+(mob-1)/2;
7148: for (age=bage+(mob-1)/2; age<=fage; age++){
7149: sumnewm[cptcod]=0.;
7150: for (i=1; i<=nlstate;i++){
7151: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
7152: }
7153: if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
7154: agemaxgood[cptcod]=age;
7155: }else{ /* bad */
7156: for (i=1; i<=nlstate;i++){
7157: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemaxgood[cptcod]][i][cptcod];
7158: } /* i */
7159: } /* end bad */
7160: }/* age */
7161: sum=0.;
7162: for (i=1; i<=nlstate;i++){
7163: sum+=mobaverage[(int)agemaxgood[cptcod]][i][cptcod];
7164: }
7165: if(fabs(sum - 1.) > 1.e-3) { /* bad */
7166: printf("For this combination of covariate cptcod=%d, we can't get a smoothed prevalence which sums to one at any ascending age!\n",cptcod);
7167: /* for (i=1; i<=nlstate;i++){ */
7168: /* mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemingood[cptcod]][i][cptcod]; */
7169: /* } /\* i *\/ */
7170: } /* end bad */
7171:
7172: for (age=bage; age<=fage; age++){
1.235 brouard 7173: /* printf("%d %d ", cptcod, (int)age); */
1.222 brouard 7174: sumnewp[cptcod]=0.;
7175: sumnewm[cptcod]=0.;
7176: for (i=1; i<=nlstate;i++){
7177: sumnewp[cptcod]+=probs[(int)age][i][cptcod];
7178: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
7179: /* printf("%.4f %.4f ",probs[(int)age][i][cptcod], mobaverage[(int)age][i][cptcod]); */
7180: }
7181: /* printf("%.4f %.4f \n",sumnewp[cptcod], sumnewm[cptcod]); */
7182: }
7183: /* printf("\n"); */
7184: /* } */
7185: /* brutal averaging */
7186: for (i=1; i<=nlstate;i++){
7187: for (age=1; age<=bage; age++){
7188: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemingood[cptcod]][i][cptcod];
7189: /* printf("age=%d i=%d cptcod=%d mobaverage=%.4f \n",(int)age,i, cptcod, mobaverage[(int)age][i][cptcod]); */
7190: }
7191: for (age=fage; age<=AGESUP; age++){
7192: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemaxgood[cptcod]][i][cptcod];
7193: /* printf("age=%d i=%d cptcod=%d mobaverage=%.4f \n",(int)age,i, cptcod, mobaverage[(int)age][i][cptcod]); */
7194: }
7195: } /* end i status */
7196: for (i=nlstate+1; i<=nlstate+ndeath;i++){
7197: for (age=1; age<=AGESUP; age++){
7198: /*printf("i=%d, age=%d, cptcod=%d\n",i, (int)age, cptcod);*/
7199: mobaverage[(int)age][i][cptcod]=0.;
7200: }
7201: }
7202: }/* end cptcod */
7203: free_vector(sumnewm,1, ncovcombmax);
7204: free_vector(sumnewp,1, ncovcombmax);
7205: free_vector(agemaxgood,1, ncovcombmax);
7206: free_vector(agemingood,1, ncovcombmax);
7207: return 0;
7208: }/* End movingaverage */
1.218 brouard 7209:
1.126 brouard 7210:
7211: /************** Forecasting ******************/
1.235 brouard 7212: void prevforecast(char fileres[], double anproj1, double mproj1, double jproj1, double ageminpar, double agemax, double dateprev1, double dateprev2, int mobilav, double bage, double fage, int firstpass, int lastpass, double anproj2, double p[], int cptcoveff){
1.126 brouard 7213: /* proj1, year, month, day of starting projection
7214: agemin, agemax range of age
7215: dateprev1 dateprev2 range of dates during which prevalence is computed
7216: anproj2 year of en of projection (same day and month as proj1).
7217: */
1.235 brouard 7218: int yearp, stepsize, hstepm, nhstepm, j, k, cptcod, i, h, i1, k4, nres=0;
1.126 brouard 7219: double agec; /* generic age */
7220: double agelim, ppij, yp,yp1,yp2,jprojmean,mprojmean,anprojmean;
7221: double *popeffectif,*popcount;
7222: double ***p3mat;
1.218 brouard 7223: /* double ***mobaverage; */
1.126 brouard 7224: char fileresf[FILENAMELENGTH];
7225:
7226: agelim=AGESUP;
1.211 brouard 7227: /* Compute observed prevalence between dateprev1 and dateprev2 by counting the number of people
7228: in each health status at the date of interview (if between dateprev1 and dateprev2).
7229: We still use firstpass and lastpass as another selection.
7230: */
1.214 brouard 7231: /* freqsummary(fileres, agemin, agemax, s, agev, nlstate, imx,Tvaraff,nbcode, ncodemax,mint,anint,strstart,\ */
7232: /* firstpass, lastpass, stepm, weightopt, model); */
1.126 brouard 7233:
1.201 brouard 7234: strcpy(fileresf,"F_");
7235: strcat(fileresf,fileresu);
1.126 brouard 7236: if((ficresf=fopen(fileresf,"w"))==NULL) {
7237: printf("Problem with forecast resultfile: %s\n", fileresf);
7238: fprintf(ficlog,"Problem with forecast resultfile: %s\n", fileresf);
7239: }
1.235 brouard 7240: printf("\nComputing forecasting: result on file '%s', please wait... \n", fileresf);
7241: fprintf(ficlog,"\nComputing forecasting: result on file '%s', please wait... \n", fileresf);
1.126 brouard 7242:
1.225 brouard 7243: if (cptcoveff==0) ncodemax[cptcoveff]=1;
1.126 brouard 7244:
7245:
7246: stepsize=(int) (stepm+YEARM-1)/YEARM;
7247: if (stepm<=12) stepsize=1;
7248: if(estepm < stepm){
7249: printf ("Problem %d lower than %d\n",estepm, stepm);
7250: }
7251: else hstepm=estepm;
7252:
7253: hstepm=hstepm/stepm;
7254: yp1=modf(dateintmean,&yp);/* extracts integral of datemean in yp and
7255: fractional in yp1 */
7256: anprojmean=yp;
7257: yp2=modf((yp1*12),&yp);
7258: mprojmean=yp;
7259: yp1=modf((yp2*30.5),&yp);
7260: jprojmean=yp;
7261: if(jprojmean==0) jprojmean=1;
7262: if(mprojmean==0) jprojmean=1;
7263:
1.227 brouard 7264: i1=pow(2,cptcoveff);
1.126 brouard 7265: if (cptcovn < 1){i1=1;}
7266:
7267: fprintf(ficresf,"# Mean day of interviews %.lf/%.lf/%.lf (%.2f) between %.2f and %.2f \n",jprojmean,mprojmean,anprojmean,dateintmean,dateprev1,dateprev2);
7268:
7269: fprintf(ficresf,"#****** Routine prevforecast **\n");
1.227 brouard 7270:
1.126 brouard 7271: /* if (h==(int)(YEARM*yearp)){ */
1.235 brouard 7272: for(nres=1; nres <= nresult; nres++) /* For each resultline */
7273: for(k=1; k<=i1;k++){
7274: if(TKresult[nres]!= k)
7275: continue;
1.227 brouard 7276: if(invalidvarcomb[k]){
7277: printf("\nCombination (%d) projection ignored because no cases \n",k);
7278: continue;
7279: }
7280: fprintf(ficresf,"\n#****** hpijx=probability over h years, hp.jx is weighted by observed prev \n#");
7281: for(j=1;j<=cptcoveff;j++) {
7282: fprintf(ficresf," V%d (=) %d",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
7283: }
1.235 brouard 7284: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
1.238 brouard 7285: fprintf(ficresf," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.235 brouard 7286: }
1.227 brouard 7287: fprintf(ficresf," yearproj age");
7288: for(j=1; j<=nlstate+ndeath;j++){
7289: for(i=1; i<=nlstate;i++)
7290: fprintf(ficresf," p%d%d",i,j);
7291: fprintf(ficresf," wp.%d",j);
7292: }
7293: for (yearp=0; yearp<=(anproj2-anproj1);yearp +=stepsize) {
7294: fprintf(ficresf,"\n");
7295: fprintf(ficresf,"\n# Forecasting at date %.lf/%.lf/%.lf ",jproj1,mproj1,anproj1+yearp);
7296: for (agec=fage; agec>=(ageminpar-1); agec--){
7297: nhstepm=(int) rint((agelim-agec)*YEARM/stepm);
7298: nhstepm = nhstepm/hstepm;
7299: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
7300: oldm=oldms;savm=savms;
1.235 brouard 7301: hpxij(p3mat,nhstepm,agec,hstepm,p,nlstate,stepm,oldm,savm, k,nres);
1.227 brouard 7302:
7303: for (h=0; h<=nhstepm; h++){
7304: if (h*hstepm/YEARM*stepm ==yearp) {
7305: fprintf(ficresf,"\n");
7306: for(j=1;j<=cptcoveff;j++)
7307: fprintf(ficresf,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
7308: fprintf(ficresf,"%.f %.f ",anproj1+yearp,agec+h*hstepm/YEARM*stepm);
7309: }
7310: for(j=1; j<=nlstate+ndeath;j++) {
7311: ppij=0.;
7312: for(i=1; i<=nlstate;i++) {
7313: if (mobilav==1)
7314: ppij=ppij+p3mat[i][j][h]*mobaverage[(int)agec][i][k];
7315: else {
7316: ppij=ppij+p3mat[i][j][h]*probs[(int)(agec)][i][k];
7317: }
7318: if (h*hstepm/YEARM*stepm== yearp) {
7319: fprintf(ficresf," %.3f", p3mat[i][j][h]);
7320: }
7321: } /* end i */
7322: if (h*hstepm/YEARM*stepm==yearp) {
7323: fprintf(ficresf," %.3f", ppij);
7324: }
7325: }/* end j */
7326: } /* end h */
7327: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
7328: } /* end agec */
7329: } /* end yearp */
7330: } /* end k */
1.219 brouard 7331:
1.126 brouard 7332: fclose(ficresf);
1.215 brouard 7333: printf("End of Computing forecasting \n");
7334: fprintf(ficlog,"End of Computing forecasting\n");
7335:
1.126 brouard 7336: }
7337:
1.218 brouard 7338: /* /\************** Back Forecasting ******************\/ */
1.225 brouard 7339: /* void prevbackforecast(char fileres[], double anback1, double mback1, double jback1, double ageminpar, double agemax, double dateprev1, double dateprev2, int mobilav, double bage, double fage, int firstpass, int lastpass, double anback2, double p[], int cptcoveff){ */
1.218 brouard 7340: /* /\* back1, year, month, day of starting backection */
7341: /* agemin, agemax range of age */
7342: /* dateprev1 dateprev2 range of dates during which prevalence is computed */
7343: /* anback2 year of en of backection (same day and month as back1). */
7344: /* *\/ */
7345: /* int yearp, stepsize, hstepm, nhstepm, j, k, cptcod, i, h, i1; */
7346: /* double agec; /\* generic age *\/ */
7347: /* double agelim, ppij, yp,yp1,yp2,jprojmean,mprojmean,anprojmean; */
7348: /* double *popeffectif,*popcount; */
7349: /* double ***p3mat; */
7350: /* /\* double ***mobaverage; *\/ */
7351: /* char fileresfb[FILENAMELENGTH]; */
7352:
7353: /* agelim=AGESUP; */
7354: /* /\* Compute observed prevalence between dateprev1 and dateprev2 by counting the number of people */
7355: /* in each health status at the date of interview (if between dateprev1 and dateprev2). */
7356: /* We still use firstpass and lastpass as another selection. */
7357: /* *\/ */
7358: /* /\* freqsummary(fileres, agemin, agemax, s, agev, nlstate, imx,Tvaraff,nbcode, ncodemax,mint,anint,strstart,\ *\/ */
7359: /* /\* firstpass, lastpass, stepm, weightopt, model); *\/ */
7360: /* prevalence(probs, ageminpar, agemax, s, agev, nlstate, imx, Tvar, nbcode, ncodemax, mint, anint, dateprev1, dateprev2, firstpass, lastpass); */
7361:
7362: /* strcpy(fileresfb,"FB_"); */
7363: /* strcat(fileresfb,fileresu); */
7364: /* if((ficresfb=fopen(fileresfb,"w"))==NULL) { */
7365: /* printf("Problem with back forecast resultfile: %s\n", fileresfb); */
7366: /* fprintf(ficlog,"Problem with back forecast resultfile: %s\n", fileresfb); */
7367: /* } */
7368: /* printf("Computing back forecasting: result on file '%s', please wait... \n", fileresfb); */
7369: /* fprintf(ficlog,"Computing back forecasting: result on file '%s', please wait... \n", fileresfb); */
7370:
1.225 brouard 7371: /* if (cptcoveff==0) ncodemax[cptcoveff]=1; */
1.218 brouard 7372:
7373: /* /\* if (mobilav!=0) { *\/ */
7374: /* /\* mobaverage= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); *\/ */
7375: /* /\* if (movingaverage(probs, ageminpar, fage, mobaverage,mobilav)!=0){ *\/ */
7376: /* /\* fprintf(ficlog," Error in movingaverage mobilav=%d\n",mobilav); *\/ */
7377: /* /\* printf(" Error in movingaverage mobilav=%d\n",mobilav); *\/ */
7378: /* /\* } *\/ */
7379: /* /\* } *\/ */
7380:
7381: /* stepsize=(int) (stepm+YEARM-1)/YEARM; */
7382: /* if (stepm<=12) stepsize=1; */
7383: /* if(estepm < stepm){ */
7384: /* printf ("Problem %d lower than %d\n",estepm, stepm); */
7385: /* } */
7386: /* else hstepm=estepm; */
7387:
7388: /* hstepm=hstepm/stepm; */
7389: /* yp1=modf(dateintmean,&yp);/\* extracts integral of datemean in yp and */
7390: /* fractional in yp1 *\/ */
7391: /* anprojmean=yp; */
7392: /* yp2=modf((yp1*12),&yp); */
7393: /* mprojmean=yp; */
7394: /* yp1=modf((yp2*30.5),&yp); */
7395: /* jprojmean=yp; */
7396: /* if(jprojmean==0) jprojmean=1; */
7397: /* if(mprojmean==0) jprojmean=1; */
7398:
1.225 brouard 7399: /* i1=cptcoveff; */
1.218 brouard 7400: /* if (cptcovn < 1){i1=1;} */
1.217 brouard 7401:
1.218 brouard 7402: /* fprintf(ficresfb,"# Mean day of interviews %.lf/%.lf/%.lf (%.2f) between %.2f and %.2f \n",jprojmean,mprojmean,anprojmean,dateintmean,dateprev1,dateprev2); */
1.217 brouard 7403:
1.218 brouard 7404: /* fprintf(ficresfb,"#****** Routine prevbackforecast **\n"); */
7405:
7406: /* /\* if (h==(int)(YEARM*yearp)){ *\/ */
7407: /* for(cptcov=1, k=0;cptcov<=i1;cptcov++){ */
1.225 brouard 7408: /* for(cptcod=1;cptcod<=ncodemax[cptcoveff];cptcod++){ */
1.218 brouard 7409: /* k=k+1; */
7410: /* fprintf(ficresfb,"\n#****** hbijx=probability over h years, hp.jx is weighted by observed prev \n#"); */
1.225 brouard 7411: /* for(j=1;j<=cptcoveff;j++) { */
1.218 brouard 7412: /* fprintf(ficresfb," V%d (=) %d",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]); */
7413: /* } */
7414: /* fprintf(ficresfb," yearbproj age"); */
7415: /* for(j=1; j<=nlstate+ndeath;j++){ */
7416: /* for(i=1; i<=nlstate;i++) */
7417: /* fprintf(ficresfb," p%d%d",i,j); */
7418: /* fprintf(ficresfb," p.%d",j); */
7419: /* } */
7420: /* for (yearp=0; yearp>=(anback2-anback1);yearp -=stepsize) { */
7421: /* /\* for (yearp=0; yearp<=(anproj2-anproj1);yearp +=stepsize) { *\/ */
7422: /* fprintf(ficresfb,"\n"); */
7423: /* fprintf(ficresfb,"\n# Back Forecasting at date %.lf/%.lf/%.lf ",jback1,mback1,anback1+yearp); */
7424: /* for (agec=fage; agec>=(ageminpar-1); agec--){ */
7425: /* nhstepm=(int) rint((agelim-agec)*YEARM/stepm); */
7426: /* nhstepm = nhstepm/hstepm; */
7427: /* p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
7428: /* oldm=oldms;savm=savms; */
7429: /* hbxij(p3mat,nhstepm,agec,hstepm,p,prevacurrent,nlstate,stepm,oldm,savm,oldm,savm, dnewm, doldm, dsavm, k); */
7430: /* for (h=0; h<=nhstepm; h++){ */
7431: /* if (h*hstepm/YEARM*stepm ==yearp) { */
7432: /* fprintf(ficresfb,"\n"); */
1.225 brouard 7433: /* for(j=1;j<=cptcoveff;j++) */
1.218 brouard 7434: /* fprintf(ficresfb,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]); */
7435: /* fprintf(ficresfb,"%.f %.f ",anback1+yearp,agec+h*hstepm/YEARM*stepm); */
7436: /* } */
7437: /* for(j=1; j<=nlstate+ndeath;j++) { */
7438: /* ppij=0.; */
7439: /* for(i=1; i<=nlstate;i++) { */
7440: /* if (mobilav==1) */
7441: /* ppij=ppij+p3mat[i][j][h]*mobaverage[(int)agec][i][cptcod]; */
7442: /* else { */
7443: /* ppij=ppij+p3mat[i][j][h]*probs[(int)(agec)][i][cptcod]; */
7444: /* } */
7445: /* if (h*hstepm/YEARM*stepm== yearp) { */
7446: /* fprintf(ficresfb," %.3f", p3mat[i][j][h]); */
7447: /* } */
7448: /* } /\* end i *\/ */
7449: /* if (h*hstepm/YEARM*stepm==yearp) { */
7450: /* fprintf(ficresfb," %.3f", ppij); */
7451: /* } */
7452: /* }/\* end j *\/ */
7453: /* } /\* end h *\/ */
7454: /* free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
7455: /* } /\* end agec *\/ */
7456: /* } /\* end yearp *\/ */
7457: /* } /\* end cptcod *\/ */
7458: /* } /\* end cptcov *\/ */
7459:
7460: /* /\* if (mobilav!=0) free_ma3x(mobaverage,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); *\/ */
7461:
7462: /* fclose(ficresfb); */
7463: /* printf("End of Computing Back forecasting \n"); */
7464: /* fprintf(ficlog,"End of Computing Back forecasting\n"); */
1.217 brouard 7465:
1.218 brouard 7466: /* } */
1.217 brouard 7467:
1.126 brouard 7468: /************** Forecasting *****not tested NB*************/
1.227 brouard 7469: /* 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 7470:
1.227 brouard 7471: /* int cpt, stepsize, hstepm, nhstepm, j,k,c, cptcod, i,h; */
7472: /* int *popage; */
7473: /* double calagedatem, agelim, kk1, kk2; */
7474: /* double *popeffectif,*popcount; */
7475: /* double ***p3mat,***tabpop,***tabpopprev; */
7476: /* /\* double ***mobaverage; *\/ */
7477: /* char filerespop[FILENAMELENGTH]; */
1.126 brouard 7478:
1.227 brouard 7479: /* tabpop= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
7480: /* tabpopprev= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
7481: /* agelim=AGESUP; */
7482: /* calagedatem=(anpyram+mpyram/12.+jpyram/365.-dateintmean)*YEARM; */
1.126 brouard 7483:
1.227 brouard 7484: /* prevalence(probs, ageminpar, agemax, s, agev, nlstate, imx, Tvar, nbcode, ncodemax, mint, anint, dateprev1, dateprev2, firstpass, lastpass); */
1.126 brouard 7485:
7486:
1.227 brouard 7487: /* strcpy(filerespop,"POP_"); */
7488: /* strcat(filerespop,fileresu); */
7489: /* if((ficrespop=fopen(filerespop,"w"))==NULL) { */
7490: /* printf("Problem with forecast resultfile: %s\n", filerespop); */
7491: /* fprintf(ficlog,"Problem with forecast resultfile: %s\n", filerespop); */
7492: /* } */
7493: /* printf("Computing forecasting: result on file '%s' \n", filerespop); */
7494: /* fprintf(ficlog,"Computing forecasting: result on file '%s' \n", filerespop); */
1.126 brouard 7495:
1.227 brouard 7496: /* if (cptcoveff==0) ncodemax[cptcoveff]=1; */
1.126 brouard 7497:
1.227 brouard 7498: /* /\* if (mobilav!=0) { *\/ */
7499: /* /\* mobaverage= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); *\/ */
7500: /* /\* if (movingaverage(probs, ageminpar, fage, mobaverage,mobilav)!=0){ *\/ */
7501: /* /\* fprintf(ficlog," Error in movingaverage mobilav=%d\n",mobilav); *\/ */
7502: /* /\* printf(" Error in movingaverage mobilav=%d\n",mobilav); *\/ */
7503: /* /\* } *\/ */
7504: /* /\* } *\/ */
1.126 brouard 7505:
1.227 brouard 7506: /* stepsize=(int) (stepm+YEARM-1)/YEARM; */
7507: /* if (stepm<=12) stepsize=1; */
1.126 brouard 7508:
1.227 brouard 7509: /* agelim=AGESUP; */
1.126 brouard 7510:
1.227 brouard 7511: /* hstepm=1; */
7512: /* hstepm=hstepm/stepm; */
1.218 brouard 7513:
1.227 brouard 7514: /* if (popforecast==1) { */
7515: /* if((ficpop=fopen(popfile,"r"))==NULL) { */
7516: /* printf("Problem with population file : %s\n",popfile);exit(0); */
7517: /* fprintf(ficlog,"Problem with population file : %s\n",popfile);exit(0); */
7518: /* } */
7519: /* popage=ivector(0,AGESUP); */
7520: /* popeffectif=vector(0,AGESUP); */
7521: /* popcount=vector(0,AGESUP); */
1.126 brouard 7522:
1.227 brouard 7523: /* i=1; */
7524: /* while ((c=fscanf(ficpop,"%d %lf\n",&popage[i],&popcount[i])) != EOF) i=i+1; */
1.218 brouard 7525:
1.227 brouard 7526: /* imx=i; */
7527: /* for (i=1; i<imx;i++) popeffectif[popage[i]]=popcount[i]; */
7528: /* } */
1.218 brouard 7529:
1.227 brouard 7530: /* for(cptcov=1,k=0;cptcov<=i2;cptcov++){ */
7531: /* for(cptcod=1;cptcod<=ncodemax[cptcoveff];cptcod++){ */
7532: /* k=k+1; */
7533: /* fprintf(ficrespop,"\n#******"); */
7534: /* for(j=1;j<=cptcoveff;j++) { */
7535: /* fprintf(ficrespop," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]); */
7536: /* } */
7537: /* fprintf(ficrespop,"******\n"); */
7538: /* fprintf(ficrespop,"# Age"); */
7539: /* for(j=1; j<=nlstate+ndeath;j++) fprintf(ficrespop," P.%d",j); */
7540: /* if (popforecast==1) fprintf(ficrespop," [Population]"); */
1.126 brouard 7541:
1.227 brouard 7542: /* for (cpt=0; cpt<=0;cpt++) { */
7543: /* fprintf(ficrespop,"\n\n# Forecasting at date %.lf/%.lf/%.lf ",jpyram,mpyram,anpyram+cpt); */
1.126 brouard 7544:
1.227 brouard 7545: /* for (agedeb=(fage-((int)calagedatem %12/12.)); agedeb>=(ageminpar-((int)calagedatem %12)/12.); agedeb--){ */
7546: /* nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); */
7547: /* nhstepm = nhstepm/hstepm; */
1.126 brouard 7548:
1.227 brouard 7549: /* p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
7550: /* oldm=oldms;savm=savms; */
7551: /* hpxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k); */
1.218 brouard 7552:
1.227 brouard 7553: /* for (h=0; h<=nhstepm; h++){ */
7554: /* if (h==(int) (calagedatem+YEARM*cpt)) { */
7555: /* fprintf(ficrespop,"\n %3.f ",agedeb+h*hstepm/YEARM*stepm); */
7556: /* } */
7557: /* for(j=1; j<=nlstate+ndeath;j++) { */
7558: /* kk1=0.;kk2=0; */
7559: /* for(i=1; i<=nlstate;i++) { */
7560: /* if (mobilav==1) */
7561: /* kk1=kk1+p3mat[i][j][h]*mobaverage[(int)agedeb+1][i][cptcod]; */
7562: /* else { */
7563: /* kk1=kk1+p3mat[i][j][h]*probs[(int)(agedeb+1)][i][cptcod]; */
7564: /* } */
7565: /* } */
7566: /* if (h==(int)(calagedatem+12*cpt)){ */
7567: /* tabpop[(int)(agedeb)][j][cptcod]=kk1; */
7568: /* /\*fprintf(ficrespop," %.3f", kk1); */
7569: /* if (popforecast==1) fprintf(ficrespop," [%.f]", kk1*popeffectif[(int)agedeb+1]);*\/ */
7570: /* } */
7571: /* } */
7572: /* for(i=1; i<=nlstate;i++){ */
7573: /* kk1=0.; */
7574: /* for(j=1; j<=nlstate;j++){ */
7575: /* kk1= kk1+tabpop[(int)(agedeb)][j][cptcod]; */
7576: /* } */
7577: /* tabpopprev[(int)(agedeb)][i][cptcod]=tabpop[(int)(agedeb)][i][cptcod]/kk1*popeffectif[(int)(agedeb+(calagedatem+12*cpt)*hstepm/YEARM*stepm-1)]; */
7578: /* } */
1.218 brouard 7579:
1.227 brouard 7580: /* if (h==(int)(calagedatem+12*cpt)) */
7581: /* for(j=1; j<=nlstate;j++) */
7582: /* fprintf(ficrespop," %15.2f",tabpopprev[(int)(agedeb+1)][j][cptcod]); */
7583: /* } */
7584: /* free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
7585: /* } */
7586: /* } */
1.218 brouard 7587:
1.227 brouard 7588: /* /\******\/ */
1.218 brouard 7589:
1.227 brouard 7590: /* for (cpt=1; cpt<=(anpyram1-anpyram);cpt++) { */
7591: /* fprintf(ficrespop,"\n\n# Forecasting at date %.lf/%.lf/%.lf ",jpyram,mpyram,anpyram+cpt); */
7592: /* for (agedeb=(fage-((int)calagedatem %12/12.)); agedeb>=(ageminpar-((int)calagedatem %12)/12.); agedeb--){ */
7593: /* nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); */
7594: /* nhstepm = nhstepm/hstepm; */
1.126 brouard 7595:
1.227 brouard 7596: /* p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
7597: /* oldm=oldms;savm=savms; */
7598: /* hpxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k); */
7599: /* for (h=0; h<=nhstepm; h++){ */
7600: /* if (h==(int) (calagedatem+YEARM*cpt)) { */
7601: /* fprintf(ficresf,"\n %3.f ",agedeb+h*hstepm/YEARM*stepm); */
7602: /* } */
7603: /* for(j=1; j<=nlstate+ndeath;j++) { */
7604: /* kk1=0.;kk2=0; */
7605: /* for(i=1; i<=nlstate;i++) { */
7606: /* kk1=kk1+p3mat[i][j][h]*tabpopprev[(int)agedeb+1][i][cptcod]; */
7607: /* } */
7608: /* if (h==(int)(calagedatem+12*cpt)) fprintf(ficresf," %15.2f", kk1); */
7609: /* } */
7610: /* } */
7611: /* free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
7612: /* } */
7613: /* } */
7614: /* } */
7615: /* } */
1.218 brouard 7616:
1.227 brouard 7617: /* /\* if (mobilav!=0) free_ma3x(mobaverage,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); *\/ */
1.218 brouard 7618:
1.227 brouard 7619: /* if (popforecast==1) { */
7620: /* free_ivector(popage,0,AGESUP); */
7621: /* free_vector(popeffectif,0,AGESUP); */
7622: /* free_vector(popcount,0,AGESUP); */
7623: /* } */
7624: /* free_ma3x(tabpop,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
7625: /* free_ma3x(tabpopprev,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
7626: /* fclose(ficrespop); */
7627: /* } /\* End of popforecast *\/ */
1.218 brouard 7628:
1.126 brouard 7629: int fileappend(FILE *fichier, char *optionfich)
7630: {
7631: if((fichier=fopen(optionfich,"a"))==NULL) {
7632: printf("Problem with file: %s\n", optionfich);
7633: fprintf(ficlog,"Problem with file: %s\n", optionfich);
7634: return (0);
7635: }
7636: fflush(fichier);
7637: return (1);
7638: }
7639:
7640:
7641: /**************** function prwizard **********************/
7642: void prwizard(int ncovmodel, int nlstate, int ndeath, char model[], FILE *ficparo)
7643: {
7644:
7645: /* Wizard to print covariance matrix template */
7646:
1.164 brouard 7647: char ca[32], cb[32];
7648: int i,j, k, li, lj, lk, ll, jj, npar, itimes;
1.126 brouard 7649: int numlinepar;
7650:
7651: printf("# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
7652: fprintf(ficparo,"# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
7653: for(i=1; i <=nlstate; i++){
7654: jj=0;
7655: for(j=1; j <=nlstate+ndeath; j++){
7656: if(j==i) continue;
7657: jj++;
7658: /*ca[0]= k+'a'-1;ca[1]='\0';*/
7659: printf("%1d%1d",i,j);
7660: fprintf(ficparo,"%1d%1d",i,j);
7661: for(k=1; k<=ncovmodel;k++){
7662: /* printf(" %lf",param[i][j][k]); */
7663: /* fprintf(ficparo," %lf",param[i][j][k]); */
7664: printf(" 0.");
7665: fprintf(ficparo," 0.");
7666: }
7667: printf("\n");
7668: fprintf(ficparo,"\n");
7669: }
7670: }
7671: printf("# Scales (for hessian or gradient estimation)\n");
7672: fprintf(ficparo,"# Scales (for hessian or gradient estimation)\n");
7673: npar= (nlstate+ndeath-1)*nlstate*ncovmodel; /* Number of parameters*/
7674: for(i=1; i <=nlstate; i++){
7675: jj=0;
7676: for(j=1; j <=nlstate+ndeath; j++){
7677: if(j==i) continue;
7678: jj++;
7679: fprintf(ficparo,"%1d%1d",i,j);
7680: printf("%1d%1d",i,j);
7681: fflush(stdout);
7682: for(k=1; k<=ncovmodel;k++){
7683: /* printf(" %le",delti3[i][j][k]); */
7684: /* fprintf(ficparo," %le",delti3[i][j][k]); */
7685: printf(" 0.");
7686: fprintf(ficparo," 0.");
7687: }
7688: numlinepar++;
7689: printf("\n");
7690: fprintf(ficparo,"\n");
7691: }
7692: }
7693: printf("# Covariance matrix\n");
7694: /* # 121 Var(a12)\n\ */
7695: /* # 122 Cov(b12,a12) Var(b12)\n\ */
7696: /* # 131 Cov(a13,a12) Cov(a13,b12, Var(a13)\n\ */
7697: /* # 132 Cov(b13,a12) Cov(b13,b12, Cov(b13,a13) Var(b13)\n\ */
7698: /* # 212 Cov(a21,a12) Cov(a21,b12, Cov(a21,a13) Cov(a21,b13) Var(a21)\n\ */
7699: /* # 212 Cov(b21,a12) Cov(b21,b12, Cov(b21,a13) Cov(b21,b13) Cov(b21,a21) Var(b21)\n\ */
7700: /* # 232 Cov(a23,a12) Cov(a23,b12, Cov(a23,a13) Cov(a23,b13) Cov(a23,a21) Cov(a23,b21) Var(a23)\n\ */
7701: /* # 232 Cov(b23,a12) Cov(b23,b12) ... Var (b23)\n" */
7702: fflush(stdout);
7703: fprintf(ficparo,"# Covariance matrix\n");
7704: /* # 121 Var(a12)\n\ */
7705: /* # 122 Cov(b12,a12) Var(b12)\n\ */
7706: /* # ...\n\ */
7707: /* # 232 Cov(b23,a12) Cov(b23,b12) ... Var (b23)\n" */
7708:
7709: for(itimes=1;itimes<=2;itimes++){
7710: jj=0;
7711: for(i=1; i <=nlstate; i++){
7712: for(j=1; j <=nlstate+ndeath; j++){
7713: if(j==i) continue;
7714: for(k=1; k<=ncovmodel;k++){
7715: jj++;
7716: ca[0]= k+'a'-1;ca[1]='\0';
7717: if(itimes==1){
7718: printf("#%1d%1d%d",i,j,k);
7719: fprintf(ficparo,"#%1d%1d%d",i,j,k);
7720: }else{
7721: printf("%1d%1d%d",i,j,k);
7722: fprintf(ficparo,"%1d%1d%d",i,j,k);
7723: /* printf(" %.5le",matcov[i][j]); */
7724: }
7725: ll=0;
7726: for(li=1;li <=nlstate; li++){
7727: for(lj=1;lj <=nlstate+ndeath; lj++){
7728: if(lj==li) continue;
7729: for(lk=1;lk<=ncovmodel;lk++){
7730: ll++;
7731: if(ll<=jj){
7732: cb[0]= lk +'a'-1;cb[1]='\0';
7733: if(ll<jj){
7734: if(itimes==1){
7735: printf(" Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
7736: fprintf(ficparo," Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
7737: }else{
7738: printf(" 0.");
7739: fprintf(ficparo," 0.");
7740: }
7741: }else{
7742: if(itimes==1){
7743: printf(" Var(%s%1d%1d)",ca,i,j);
7744: fprintf(ficparo," Var(%s%1d%1d)",ca,i,j);
7745: }else{
7746: printf(" 0.");
7747: fprintf(ficparo," 0.");
7748: }
7749: }
7750: }
7751: } /* end lk */
7752: } /* end lj */
7753: } /* end li */
7754: printf("\n");
7755: fprintf(ficparo,"\n");
7756: numlinepar++;
7757: } /* end k*/
7758: } /*end j */
7759: } /* end i */
7760: } /* end itimes */
7761:
7762: } /* end of prwizard */
7763: /******************* Gompertz Likelihood ******************************/
7764: double gompertz(double x[])
7765: {
7766: double A,B,L=0.0,sump=0.,num=0.;
7767: int i,n=0; /* n is the size of the sample */
7768:
1.220 brouard 7769: for (i=1;i<=imx ; i++) {
1.126 brouard 7770: sump=sump+weight[i];
7771: /* sump=sump+1;*/
7772: num=num+1;
7773: }
7774:
7775:
7776: /* for (i=0; i<=imx; i++)
7777: 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]);*/
7778:
7779: for (i=1;i<=imx ; i++)
7780: {
7781: if (cens[i] == 1 && wav[i]>1)
7782: A=-x[1]/(x[2])*(exp(x[2]*(agecens[i]-agegomp))-exp(x[2]*(ageexmed[i]-agegomp)));
7783:
7784: if (cens[i] == 0 && wav[i]>1)
7785: A=-x[1]/(x[2])*(exp(x[2]*(agedc[i]-agegomp))-exp(x[2]*(ageexmed[i]-agegomp)))
7786: +log(x[1]/YEARM)+x[2]*(agedc[i]-agegomp)+log(YEARM);
7787:
7788: /*if (wav[i] > 1 && agecens[i] > 15) {*/ /* ??? */
7789: if (wav[i] > 1 ) { /* ??? */
7790: L=L+A*weight[i];
7791: /* 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]);*/
7792: }
7793: }
7794:
7795: /*printf("x1=%2.9f x2=%2.9f x3=%2.9f L=%f\n",x[1],x[2],x[3],L);*/
7796:
7797: return -2*L*num/sump;
7798: }
7799:
1.136 brouard 7800: #ifdef GSL
7801: /******************* Gompertz_f Likelihood ******************************/
7802: double gompertz_f(const gsl_vector *v, void *params)
7803: {
7804: double A,B,LL=0.0,sump=0.,num=0.;
7805: double *x= (double *) v->data;
7806: int i,n=0; /* n is the size of the sample */
7807:
7808: for (i=0;i<=imx-1 ; i++) {
7809: sump=sump+weight[i];
7810: /* sump=sump+1;*/
7811: num=num+1;
7812: }
7813:
7814:
7815: /* for (i=0; i<=imx; i++)
7816: 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]);*/
7817: printf("x[0]=%lf x[1]=%lf\n",x[0],x[1]);
7818: for (i=1;i<=imx ; i++)
7819: {
7820: if (cens[i] == 1 && wav[i]>1)
7821: A=-x[0]/(x[1])*(exp(x[1]*(agecens[i]-agegomp))-exp(x[1]*(ageexmed[i]-agegomp)));
7822:
7823: if (cens[i] == 0 && wav[i]>1)
7824: A=-x[0]/(x[1])*(exp(x[1]*(agedc[i]-agegomp))-exp(x[1]*(ageexmed[i]-agegomp)))
7825: +log(x[0]/YEARM)+x[1]*(agedc[i]-agegomp)+log(YEARM);
7826:
7827: /*if (wav[i] > 1 && agecens[i] > 15) {*/ /* ??? */
7828: if (wav[i] > 1 ) { /* ??? */
7829: LL=LL+A*weight[i];
7830: /* 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]);*/
7831: }
7832: }
7833:
7834: /*printf("x1=%2.9f x2=%2.9f x3=%2.9f L=%f\n",x[1],x[2],x[3],L);*/
7835: printf("x[0]=%lf x[1]=%lf -2*LL*num/sump=%lf\n",x[0],x[1],-2*LL*num/sump);
7836:
7837: return -2*LL*num/sump;
7838: }
7839: #endif
7840:
1.126 brouard 7841: /******************* Printing html file ***********/
1.201 brouard 7842: void printinghtmlmort(char fileresu[], char title[], char datafile[], int firstpass, \
1.126 brouard 7843: int lastpass, int stepm, int weightopt, char model[],\
7844: int imx, double p[],double **matcov,double agemortsup){
7845: int i,k;
7846:
7847: fprintf(fichtm,"<ul><li><h4>Result files </h4>\n Force of mortality. Parameters of the Gompertz fit (with confidence interval in brackets):<br>");
7848: fprintf(fichtm," mu(age) =%lf*exp(%lf*(age-%d)) per year<br><br>",p[1],p[2],agegomp);
7849: for (i=1;i<=2;i++)
7850: 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 7851: fprintf(fichtm,"<br><br><img src=\"graphmort.svg\">");
1.126 brouard 7852: fprintf(fichtm,"</ul>");
7853:
7854: fprintf(fichtm,"<ul><li><h4>Life table</h4>\n <br>");
7855:
7856: 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>");
7857:
7858: for (k=agegomp;k<(agemortsup-2);k++)
7859: 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]);
7860:
7861:
7862: fflush(fichtm);
7863: }
7864:
7865: /******************* Gnuplot file **************/
1.201 brouard 7866: void printinggnuplotmort(char fileresu[], char optionfilefiname[], double ageminpar, double agemaxpar, double fage , char pathc[], double p[]){
1.126 brouard 7867:
7868: char dirfileres[132],optfileres[132];
1.164 brouard 7869:
1.126 brouard 7870: int ng;
7871:
7872:
7873: /*#ifdef windows */
7874: fprintf(ficgp,"cd \"%s\" \n",pathc);
7875: /*#endif */
7876:
7877:
7878: strcpy(dirfileres,optionfilefiname);
7879: strcpy(optfileres,"vpl");
1.199 brouard 7880: fprintf(ficgp,"set out \"graphmort.svg\"\n ");
1.126 brouard 7881: fprintf(ficgp,"set xlabel \"Age\"\n set ylabel \"Force of mortality (per year)\" \n ");
1.199 brouard 7882: fprintf(ficgp, "set ter svg size 640, 480\n set log y\n");
1.145 brouard 7883: /* fprintf(ficgp, "set size 0.65,0.65\n"); */
1.126 brouard 7884: fprintf(ficgp,"plot [%d:100] %lf*exp(%lf*(x-%d))",agegomp,p[1],p[2],agegomp);
7885:
7886: }
7887:
1.136 brouard 7888: int readdata(char datafile[], int firstobs, int lastobs, int *imax)
7889: {
1.126 brouard 7890:
1.136 brouard 7891: /*-------- data file ----------*/
7892: FILE *fic;
7893: char dummy[]=" ";
1.240 brouard 7894: int i=0, j=0, n=0, iv=0, v;
1.223 brouard 7895: int lstra;
1.136 brouard 7896: int linei, month, year,iout;
7897: char line[MAXLINE], linetmp[MAXLINE];
1.164 brouard 7898: char stra[MAXLINE], strb[MAXLINE];
1.136 brouard 7899: char *stratrunc;
1.223 brouard 7900:
1.240 brouard 7901: DummyV=ivector(1,NCOVMAX); /* 1 to 3 */
7902: FixedV=ivector(1,NCOVMAX); /* 1 to 3 */
1.126 brouard 7903:
1.240 brouard 7904: for(v=1; v <=ncovcol;v++){
7905: DummyV[v]=0;
7906: FixedV[v]=0;
7907: }
7908: for(v=ncovcol+1; v <=ncovcol+nqv;v++){
7909: DummyV[v]=1;
7910: FixedV[v]=0;
7911: }
7912: for(v=ncovcol+nqv+1; v <=ncovcol+nqv+ntv;v++){
7913: DummyV[v]=0;
7914: FixedV[v]=1;
7915: }
7916: for(v=ncovcol+nqv+ntv+1; v <=ncovcol+nqv+ntv+nqtv;v++){
7917: DummyV[v]=1;
7918: FixedV[v]=1;
7919: }
7920: for(v=1; v <=ncovcol+nqv+ntv+nqtv;v++){
7921: printf("Covariate type in the data: V%d, DummyV(V%d)=%d, FixedV(V%d)=%d\n",v,v,DummyV[v],v,FixedV[v]);
7922: 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]);
7923: }
1.126 brouard 7924:
1.136 brouard 7925: if((fic=fopen(datafile,"r"))==NULL) {
1.218 brouard 7926: printf("Problem while opening datafile: %s with errno='%s'\n", datafile,strerror(errno));fflush(stdout);
7927: fprintf(ficlog,"Problem while opening datafile: %s with errno='%s'\n", datafile,strerror(errno));fflush(ficlog);return 1;
1.136 brouard 7928: }
1.126 brouard 7929:
1.136 brouard 7930: i=1;
7931: linei=0;
7932: while ((fgets(line, MAXLINE, fic) != NULL) &&((i >= firstobs) && (i <=lastobs))) {
7933: linei=linei+1;
7934: for(j=strlen(line); j>=0;j--){ /* Untabifies line */
7935: if(line[j] == '\t')
7936: line[j] = ' ';
7937: }
7938: for(j=strlen(line)-1; (line[j]==' ')||(line[j]==10)||(line[j]==13);j--){
7939: ;
7940: };
7941: line[j+1]=0; /* Trims blanks at end of line */
7942: if(line[0]=='#'){
7943: fprintf(ficlog,"Comment line\n%s\n",line);
7944: printf("Comment line\n%s\n",line);
7945: continue;
7946: }
7947: trimbb(linetmp,line); /* Trims multiple blanks in line */
1.164 brouard 7948: strcpy(line, linetmp);
1.223 brouard 7949:
7950: /* Loops on waves */
7951: for (j=maxwav;j>=1;j--){
7952: for (iv=nqtv;iv>=1;iv--){ /* Loop on time varying quantitative variables */
1.238 brouard 7953: cutv(stra, strb, line, ' ');
7954: if(strb[0]=='.') { /* Missing value */
7955: lval=-1;
7956: cotqvar[j][iv][i]=-1; /* 0.0/0.0 */
7957: cotvar[j][ntv+iv][i]=-1; /* For performance reasons */
7958: if(isalpha(strb[1])) { /* .m or .d Really Missing value */
7959: 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);
7960: 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);
7961: return 1;
7962: }
7963: }else{
7964: errno=0;
7965: /* what_kind_of_number(strb); */
7966: dval=strtod(strb,&endptr);
7967: /* if( strb[0]=='\0' || (*endptr != '\0')){ */
7968: /* if(strb != endptr && *endptr == '\0') */
7969: /* dval=dlval; */
7970: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN)) */
7971: if( strb[0]=='\0' || (*endptr != '\0')){
7972: 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);
7973: 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);
7974: return 1;
7975: }
7976: cotqvar[j][iv][i]=dval;
7977: cotvar[j][ntv+iv][i]=dval;
7978: }
7979: strcpy(line,stra);
1.223 brouard 7980: }/* end loop ntqv */
1.225 brouard 7981:
1.223 brouard 7982: for (iv=ntv;iv>=1;iv--){ /* Loop on time varying dummies */
1.238 brouard 7983: cutv(stra, strb, line, ' ');
7984: if(strb[0]=='.') { /* Missing value */
7985: lval=-1;
7986: }else{
7987: errno=0;
7988: lval=strtol(strb,&endptr,10);
7989: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN))*/
7990: if( strb[0]=='\0' || (*endptr != '\0')){
7991: 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);
7992: 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);
7993: return 1;
7994: }
7995: }
7996: if(lval <-1 || lval >1){
7997: printf("Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.223 brouard 7998: Should be a value of %d(nth) covariate (0 should be the value for the reference and 1\n \
7999: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.238 brouard 8000: For example, for multinomial values like 1, 2 and 3,\n \
8001: build V1=0 V2=0 for the reference value (1),\n \
8002: V1=1 V2=0 for (2) \n \
1.223 brouard 8003: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.238 brouard 8004: output of IMaCh is often meaningless.\n \
1.223 brouard 8005: Exiting.\n",lval,linei, i,line,j);
1.238 brouard 8006: fprintf(ficlog,"Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.223 brouard 8007: Should be a value of %d(nth) covariate (0 should be the value for the reference and 1\n \
8008: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.238 brouard 8009: For example, for multinomial values like 1, 2 and 3,\n \
8010: build V1=0 V2=0 for the reference value (1),\n \
8011: V1=1 V2=0 for (2) \n \
1.223 brouard 8012: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.238 brouard 8013: output of IMaCh is often meaningless.\n \
1.223 brouard 8014: Exiting.\n",lval,linei, i,line,j);fflush(ficlog);
1.238 brouard 8015: return 1;
8016: }
8017: cotvar[j][iv][i]=(double)(lval);
8018: strcpy(line,stra);
1.223 brouard 8019: }/* end loop ntv */
1.225 brouard 8020:
1.223 brouard 8021: /* Statuses at wave */
1.137 brouard 8022: cutv(stra, strb, line, ' ');
1.223 brouard 8023: if(strb[0]=='.') { /* Missing value */
1.238 brouard 8024: lval=-1;
1.136 brouard 8025: }else{
1.238 brouard 8026: errno=0;
8027: lval=strtol(strb,&endptr,10);
8028: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN))*/
8029: if( strb[0]=='\0' || (*endptr != '\0')){
8030: 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);
8031: 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);
8032: return 1;
8033: }
1.136 brouard 8034: }
1.225 brouard 8035:
1.136 brouard 8036: s[j][i]=lval;
1.225 brouard 8037:
1.223 brouard 8038: /* Date of Interview */
1.136 brouard 8039: strcpy(line,stra);
8040: cutv(stra, strb,line,' ');
1.169 brouard 8041: if( (iout=sscanf(strb,"%d/%d",&month, &year)) != 0){
1.136 brouard 8042: }
1.169 brouard 8043: else if( (iout=sscanf(strb,"%s.",dummy)) != 0){
1.225 brouard 8044: month=99;
8045: year=9999;
1.136 brouard 8046: }else{
1.225 brouard 8047: 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);
8048: 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);
8049: return 1;
1.136 brouard 8050: }
8051: anint[j][i]= (double) year;
8052: mint[j][i]= (double)month;
8053: strcpy(line,stra);
1.223 brouard 8054: } /* End loop on waves */
1.225 brouard 8055:
1.223 brouard 8056: /* Date of death */
1.136 brouard 8057: cutv(stra, strb,line,' ');
1.169 brouard 8058: if( (iout=sscanf(strb,"%d/%d",&month, &year)) != 0){
1.136 brouard 8059: }
1.169 brouard 8060: else if( (iout=sscanf(strb,"%s.",dummy)) != 0){
1.136 brouard 8061: month=99;
8062: year=9999;
8063: }else{
1.141 brouard 8064: 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 8065: 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);
8066: return 1;
1.136 brouard 8067: }
8068: andc[i]=(double) year;
8069: moisdc[i]=(double) month;
8070: strcpy(line,stra);
8071:
1.223 brouard 8072: /* Date of birth */
1.136 brouard 8073: cutv(stra, strb,line,' ');
1.169 brouard 8074: if( (iout=sscanf(strb,"%d/%d",&month, &year)) != 0){
1.136 brouard 8075: }
1.169 brouard 8076: else if( (iout=sscanf(strb,"%s.", dummy)) != 0){
1.136 brouard 8077: month=99;
8078: year=9999;
8079: }else{
1.141 brouard 8080: 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);
8081: 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 8082: return 1;
1.136 brouard 8083: }
8084: if (year==9999) {
1.141 brouard 8085: 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);
8086: 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 8087: return 1;
8088:
1.136 brouard 8089: }
8090: annais[i]=(double)(year);
8091: moisnais[i]=(double)(month);
8092: strcpy(line,stra);
1.225 brouard 8093:
1.223 brouard 8094: /* Sample weight */
1.136 brouard 8095: cutv(stra, strb,line,' ');
8096: errno=0;
8097: dval=strtod(strb,&endptr);
8098: if( strb[0]=='\0' || (*endptr != '\0')){
1.141 brouard 8099: printf("Error reading data around '%f' at line number %d, \"%s\" for individual %d\nShould be a weight. Exiting.\n",dval, i,line,linei);
8100: 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 8101: fflush(ficlog);
8102: return 1;
8103: }
8104: weight[i]=dval;
8105: strcpy(line,stra);
1.225 brouard 8106:
1.223 brouard 8107: for (iv=nqv;iv>=1;iv--){ /* Loop on fixed quantitative variables */
8108: cutv(stra, strb, line, ' ');
8109: if(strb[0]=='.') { /* Missing value */
1.225 brouard 8110: lval=-1;
1.223 brouard 8111: }else{
1.225 brouard 8112: errno=0;
8113: /* what_kind_of_number(strb); */
8114: dval=strtod(strb,&endptr);
8115: /* if(strb != endptr && *endptr == '\0') */
8116: /* dval=dlval; */
8117: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN)) */
8118: if( strb[0]=='\0' || (*endptr != '\0')){
8119: 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);
8120: 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);
8121: return 1;
8122: }
8123: coqvar[iv][i]=dval;
1.226 brouard 8124: covar[ncovcol+iv][i]=dval; /* including qvar in standard covar for performance reasons */
1.223 brouard 8125: }
8126: strcpy(line,stra);
8127: }/* end loop nqv */
1.136 brouard 8128:
1.223 brouard 8129: /* Covariate values */
1.136 brouard 8130: for (j=ncovcol;j>=1;j--){
8131: cutv(stra, strb,line,' ');
1.223 brouard 8132: if(strb[0]=='.') { /* Missing covariate value */
1.225 brouard 8133: lval=-1;
1.136 brouard 8134: }else{
1.225 brouard 8135: errno=0;
8136: lval=strtol(strb,&endptr,10);
8137: if( strb[0]=='\0' || (*endptr != '\0')){
8138: 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);
8139: 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);
8140: return 1;
8141: }
1.136 brouard 8142: }
8143: if(lval <-1 || lval >1){
1.225 brouard 8144: printf("Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.136 brouard 8145: Should be a value of %d(nth) covariate (0 should be the value for the reference and 1\n \
8146: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.225 brouard 8147: For example, for multinomial values like 1, 2 and 3,\n \
8148: build V1=0 V2=0 for the reference value (1),\n \
8149: V1=1 V2=0 for (2) \n \
1.136 brouard 8150: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.225 brouard 8151: output of IMaCh is often meaningless.\n \
1.136 brouard 8152: Exiting.\n",lval,linei, i,line,j);
1.225 brouard 8153: fprintf(ficlog,"Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.136 brouard 8154: Should be a value of %d(nth) covariate (0 should be the value for the reference and 1\n \
8155: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.225 brouard 8156: For example, for multinomial values like 1, 2 and 3,\n \
8157: build V1=0 V2=0 for the reference value (1),\n \
8158: V1=1 V2=0 for (2) \n \
1.136 brouard 8159: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.225 brouard 8160: output of IMaCh is often meaningless.\n \
1.136 brouard 8161: Exiting.\n",lval,linei, i,line,j);fflush(ficlog);
1.225 brouard 8162: return 1;
1.136 brouard 8163: }
8164: covar[j][i]=(double)(lval);
8165: strcpy(line,stra);
8166: }
8167: lstra=strlen(stra);
1.225 brouard 8168:
1.136 brouard 8169: if(lstra > 9){ /* More than 2**32 or max of what printf can write with %ld */
8170: stratrunc = &(stra[lstra-9]);
8171: num[i]=atol(stratrunc);
8172: }
8173: else
8174: num[i]=atol(stra);
8175: /*if((s[2][i]==2) && (s[3][i]==-1)&&(s[4][i]==9)){
8176: 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;}*/
8177:
8178: i=i+1;
8179: } /* End loop reading data */
1.225 brouard 8180:
1.136 brouard 8181: *imax=i-1; /* Number of individuals */
8182: fclose(fic);
1.225 brouard 8183:
1.136 brouard 8184: return (0);
1.164 brouard 8185: /* endread: */
1.225 brouard 8186: printf("Exiting readdata: ");
8187: fclose(fic);
8188: return (1);
1.223 brouard 8189: }
1.126 brouard 8190:
1.234 brouard 8191: void removefirstspace(char **stri){/*, char stro[]) {*/
1.230 brouard 8192: char *p1 = *stri, *p2 = *stri;
1.235 brouard 8193: while (*p2 == ' ')
1.234 brouard 8194: p2++;
8195: /* while ((*p1++ = *p2++) !=0) */
8196: /* ; */
8197: /* do */
8198: /* while (*p2 == ' ') */
8199: /* p2++; */
8200: /* while (*p1++ == *p2++); */
8201: *stri=p2;
1.145 brouard 8202: }
8203:
1.235 brouard 8204: int decoderesult ( char resultline[], int nres)
1.230 brouard 8205: /**< This routine decode one result line and returns the combination # of dummy covariates only **/
8206: {
1.235 brouard 8207: int j=0, k=0, k1=0, k2=0, k3=0, k4=0, match=0, k2q=0, k3q=0, k4q=0;
1.230 brouard 8208: char resultsav[MAXLINE];
1.234 brouard 8209: int resultmodel[MAXLINE];
8210: int modelresult[MAXLINE];
1.230 brouard 8211: char stra[80], strb[80], strc[80], strd[80],stre[80];
8212:
1.234 brouard 8213: removefirstspace(&resultline);
1.233 brouard 8214: printf("decoderesult:%s\n",resultline);
1.230 brouard 8215:
8216: if (strstr(resultline,"v") !=0){
8217: printf("Error. 'v' must be in upper case 'V' result: %s ",resultline);
8218: fprintf(ficlog,"Error. 'v' must be in upper case result: %s ",resultline);fflush(ficlog);
8219: return 1;
8220: }
8221: trimbb(resultsav, resultline);
8222: if (strlen(resultsav) >1){
8223: j=nbocc(resultsav,'='); /**< j=Number of covariate values'=' */
8224: }
1.234 brouard 8225: if( j != cptcovs ){ /* Be careful if a variable is in a product but not single */
8226: 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);
8227: 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);
8228: }
8229: for(k=1; k<=j;k++){ /* Loop on any covariate of the result line */
8230: if(nbocc(resultsav,'=') >1){
8231: cutl(stra,strb,resultsav,' '); /* keeps in strb after the first ' '
8232: resultsav= V4=1 V5=25.1 V3=0 strb=V3=0 stra= V4=1 V5=25.1 */
8233: cutl(strc,strd,strb,'='); /* strb:V4=1 strc=1 strd=V4 */
8234: }else
8235: cutl(strc,strd,resultsav,'=');
1.230 brouard 8236: Tvalsel[k]=atof(strc); /* 1 */
1.234 brouard 8237:
1.230 brouard 8238: cutl(strc,stre,strd,'V'); /* strd='V4' strc=4 stre='V' */;
8239: Tvarsel[k]=atoi(strc);
8240: /* Typevarsel[k]=1; /\* 1 for age product *\/ */
8241: /* cptcovsel++; */
8242: if (nbocc(stra,'=') >0)
8243: strcpy(resultsav,stra); /* and analyzes it */
8244: }
1.235 brouard 8245: /* Checking for missing or useless values in comparison of current model needs */
1.236 brouard 8246: for(k1=1; k1<= cptcovt ;k1++){ /* model line V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
8247: if(Typevar[k1]==0){ /* Single covariate in model */
1.234 brouard 8248: match=0;
1.236 brouard 8249: for(k2=1; k2 <=j;k2++){/* result line V4=1 V5=24.1 V3=1 V2=8 V1=0 */
1.237 brouard 8250: if(Tvar[k1]==Tvarsel[k2]) {/* Tvar[1]=5 == Tvarsel[2]=5 */
1.236 brouard 8251: modelresult[k2]=k1;/* modelresult[2]=1 modelresult[1]=2 modelresult[3]=3 modelresult[6]=4 modelresult[9]=5 */
1.234 brouard 8252: match=1;
8253: break;
8254: }
8255: }
8256: if(match == 0){
8257: printf("Error in result line: %d value missing; result: %s, model=%s\n",k1, resultline, model);
8258: }
8259: }
8260: }
1.235 brouard 8261: /* Checking for missing or useless values in comparison of current model needs */
8262: for(k2=1; k2 <=j;k2++){ /* result line V4=1 V5=24.1 V3=1 V2=8 V1=0 */
1.234 brouard 8263: match=0;
1.235 brouard 8264: for(k1=1; k1<= cptcovt ;k1++){ /* model line V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
8265: if(Typevar[k1]==0){ /* Single */
1.237 brouard 8266: if(Tvar[k1]==Tvarsel[k2]) { /* Tvar[2]=4 == Tvarsel[1]=4 */
1.235 brouard 8267: resultmodel[k1]=k2; /* resultmodel[2]=1 resultmodel[1]=2 resultmodel[3]=3 resultmodel[6]=4 resultmodel[9]=5 */
1.234 brouard 8268: ++match;
8269: }
8270: }
8271: }
8272: if(match == 0){
8273: printf("Error in result line: %d value missing; result: %s, model=%s\n",k1, resultline, model);
8274: }else if(match > 1){
8275: printf("Error in result line: %d doubled; result: %s, model=%s\n",k2, resultline, model);
8276: }
8277: }
1.235 brouard 8278:
1.234 brouard 8279: /* We need to deduce which combination number is chosen and save quantitative values */
1.235 brouard 8280: /* model line V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
8281: /* result line V4=1 V5=25.1 V3=0 V2=8 V1=1 */
8282: /* should give a combination of dummy V4=1, V3=0, V1=1 => V4*2**(0) + V3*2**(1) + V1*2**(2) = 5 + (1offset) = 6*/
8283: /* result line V4=1 V5=24.1 V3=1 V2=8 V1=0 */
8284: /* should give a combination of dummy V4=1, V3=1, V1=0 => V4*2**(0) + V3*2**(1) + V1*2**(2) = 3 + (1offset) = 4*/
8285: /* 1 0 0 0 */
8286: /* 2 1 0 0 */
8287: /* 3 0 1 0 */
8288: /* 4 1 1 0 */ /* V4=1, V3=1, V1=0 */
8289: /* 5 0 0 1 */
8290: /* 6 1 0 1 */ /* V4=1, V3=0, V1=1 */
8291: /* 7 0 1 1 */
8292: /* 8 1 1 1 */
1.237 brouard 8293: /* V(Tvresult)=Tresult V4=1 V3=0 V1=1 Tresult[nres=1][2]=0 */
8294: /* V(Tvqresult)=Tqresult V5=25.1 V2=8 Tqresult[nres=1][1]=25.1 */
8295: /* V5*age V5 known which value for nres? */
8296: /* Tqinvresult[2]=8 Tqinvresult[1]=25.1 */
1.235 brouard 8297: for(k1=1, k=0, k4=0, k4q=0; k1 <=cptcovt;k1++){ /* model line */
8298: if( Dummy[k1]==0 && Typevar[k1]==0 ){ /* Single dummy */
1.237 brouard 8299: k3= resultmodel[k1]; /* resultmodel[2(V4)] = 1=k3 */
1.235 brouard 8300: k2=(int)Tvarsel[k3]; /* Tvarsel[resultmodel[2]]= Tvarsel[1] = 4=k2 */
8301: k+=Tvalsel[k3]*pow(2,k4); /* Tvalsel[1]=1 */
1.237 brouard 8302: Tresult[nres][k4+1]=Tvalsel[k3];/* Tresult[nres][1]=1(V4=1) Tresult[nres][2]=0(V3=0) */
8303: Tvresult[nres][k4+1]=(int)Tvarsel[k3];/* Tvresult[nres][1]=4 Tvresult[nres][3]=1 */
8304: Tinvresult[nres][(int)Tvarsel[k3]]=Tvalsel[k3]; /* Tinvresult[nres][4]=1 */
1.235 brouard 8305: printf("Decoderesult Dummy k=%d, V(k2=V%d)= Tvalsel[%d]=%d, 2**(%d)\n",k, k2, k3, (int)Tvalsel[k3], k4);
8306: k4++;;
8307: } else if( Dummy[k1]==1 && Typevar[k1]==0 ){ /* Single quantitative */
8308: k3q= resultmodel[k1]; /* resultmodel[2] = 1=k3 */
8309: k2q=(int)Tvarsel[k3q]; /* Tvarsel[resultmodel[2]]= Tvarsel[1] = 4=k2 */
1.237 brouard 8310: Tqresult[nres][k4q+1]=Tvalsel[k3q]; /* Tqresult[nres][1]=25.1 */
8311: Tvqresult[nres][k4q+1]=(int)Tvarsel[k3q]; /* Tvqresult[nres][1]=5 */
8312: Tqinvresult[nres][(int)Tvarsel[k3q]]=Tvalsel[k3q]; /* Tqinvresult[nres][5]=25.1 */
1.235 brouard 8313: printf("Decoderesult Quantitative nres=%d, V(k2q=V%d)= Tvalsel[%d]=%d, Tvarsel[%d]=%f\n",nres, k2q, k3q, Tvarsel[k3q], k3q, Tvalsel[k3q]);
8314: k4q++;;
8315: }
8316: }
1.234 brouard 8317:
1.235 brouard 8318: TKresult[nres]=++k; /* Combination for the nresult and the model */
1.230 brouard 8319: return (0);
8320: }
1.235 brouard 8321:
1.230 brouard 8322: int decodemodel( char model[], int lastobs)
8323: /**< This routine decodes the model and returns:
1.224 brouard 8324: * Model V1+V2+V3+V8+V7*V8+V5*V6+V8*age+V3*age+age*age
8325: * - nagesqr = 1 if age*age in the model, otherwise 0.
8326: * - cptcovt total number of covariates of the model nbocc(+)+1 = 8 excepting constant and age and age*age
8327: * - cptcovn or number of covariates k of the models excluding age*products =6 and age*age
8328: * - cptcovage number of covariates with age*products =2
8329: * - cptcovs number of simple covariates
8330: * - 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
8331: * which is a new column after the 9 (ncovcol) variables.
8332: * - if k is a product Vn*Vm covar[k][i] is filled with correct values for each individual
8333: * - Tprod[l] gives the kth covariates of the product Vn*Vm l=1 to cptcovprod-cptcovage
8334: * Tprod[1]@2 {5, 6}: position of first product V7*V8 is 5, and second V5*V6 is 6.
8335: * - Tvard[k] p Tvard[1][1]@4 {7, 8, 5, 6} for V7*V8 and V5*V6 .
8336: */
1.136 brouard 8337: {
1.238 brouard 8338: int i, j, k, ks, v;
1.227 brouard 8339: int j1, k1, k2, k3, k4;
1.136 brouard 8340: char modelsav[80];
1.145 brouard 8341: char stra[80], strb[80], strc[80], strd[80],stre[80];
1.187 brouard 8342: char *strpt;
1.136 brouard 8343:
1.145 brouard 8344: /*removespace(model);*/
1.136 brouard 8345: if (strlen(model) >1){ /* If there is at least 1 covariate */
1.145 brouard 8346: j=0, j1=0, k1=0, k2=-1, ks=0, cptcovn=0;
1.137 brouard 8347: if (strstr(model,"AGE") !=0){
1.192 brouard 8348: printf("Error. AGE must be in lower case 'age' model=1+age+%s. ",model);
8349: fprintf(ficlog,"Error. AGE must be in lower case model=1+age+%s. ",model);fflush(ficlog);
1.136 brouard 8350: return 1;
8351: }
1.141 brouard 8352: if (strstr(model,"v") !=0){
8353: printf("Error. 'v' must be in upper case 'V' model=%s ",model);
8354: fprintf(ficlog,"Error. 'v' must be in upper case model=%s ",model);fflush(ficlog);
8355: return 1;
8356: }
1.187 brouard 8357: strcpy(modelsav,model);
8358: if ((strpt=strstr(model,"age*age")) !=0){
8359: printf(" strpt=%s, model=%s\n",strpt, model);
8360: if(strpt != model){
1.234 brouard 8361: printf("Error in model: 'model=%s'; 'age*age' should in first place before other covariates\n \
1.192 brouard 8362: 'model=1+age+age*age+V1.' or 'model=1+age+age*age+V1+V1*age.', please swap as well as \n \
1.187 brouard 8363: corresponding column of parameters.\n",model);
1.234 brouard 8364: fprintf(ficlog,"Error in model: 'model=%s'; 'age*age' should in first place before other covariates\n \
1.192 brouard 8365: 'model=1+age+age*age+V1.' or 'model=1+age+age*age+V1+V1*age.', please swap as well as \n \
1.187 brouard 8366: corresponding column of parameters.\n",model); fflush(ficlog);
1.234 brouard 8367: return 1;
1.225 brouard 8368: }
1.187 brouard 8369: nagesqr=1;
8370: if (strstr(model,"+age*age") !=0)
1.234 brouard 8371: substrchaine(modelsav, model, "+age*age");
1.187 brouard 8372: else if (strstr(model,"age*age+") !=0)
1.234 brouard 8373: substrchaine(modelsav, model, "age*age+");
1.187 brouard 8374: else
1.234 brouard 8375: substrchaine(modelsav, model, "age*age");
1.187 brouard 8376: }else
8377: nagesqr=0;
8378: if (strlen(modelsav) >1){
8379: j=nbocc(modelsav,'+'); /**< j=Number of '+' */
8380: j1=nbocc(modelsav,'*'); /**< j1=Number of '*' */
1.224 brouard 8381: cptcovs=j+1-j1; /**< Number of simple covariates V1+V1*age+V3 +V3*V4+age*age=> V1 + V3 =5-3=2 */
1.187 brouard 8382: cptcovt= j+1; /* Number of total covariates in the model, not including
1.225 brouard 8383: * cst, age and age*age
8384: * V1+V1*age+ V3 + V3*V4+age*age=> 3+1=4*/
8385: /* including age products which are counted in cptcovage.
8386: * but the covariates which are products must be treated
8387: * separately: ncovn=4- 2=2 (V1+V3). */
1.187 brouard 8388: cptcovprod=j1; /**< Number of products V1*V2 +v3*age = 2 */
8389: cptcovprodnoage=0; /**< Number of covariate products without age: V3*V4 =1 */
1.225 brouard 8390:
8391:
1.187 brouard 8392: /* Design
8393: * V1 V2 V3 V4 V5 V6 V7 V8 V9 Weight
8394: * < ncovcol=8 >
8395: * Model V2 + V1 + V3*age + V3 + V5*V6 + V7*V8 + V8*age + V8
8396: * k= 1 2 3 4 5 6 7 8
8397: * cptcovn number of covariates (not including constant and age ) = # of + plus 1 = 7+1=8
8398: * covar[k,i], value of kth covariate if not including age for individual i:
1.224 brouard 8399: * covar[1][i]= (V1), covar[4][i]=(V4), covar[8][i]=(V8)
8400: * Tvar[k] # of the kth covariate: Tvar[1]=2 Tvar[2]=1 Tvar[4]=3 Tvar[8]=8
1.187 brouard 8401: * if multiplied by age: V3*age Tvar[3=V3*age]=3 (V3) Tvar[7]=8 and
8402: * Tage[++cptcovage]=k
8403: * if products, new covar are created after ncovcol with k1
8404: * Tvar[k]=ncovcol+k1; # of the kth covariate product: Tvar[5]=ncovcol+1=10 Tvar[6]=ncovcol+1=11
8405: * Tprod[k1]=k; Tprod[1]=5 Tprod[2]= 6; gives the position of the k1th product
8406: * 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
8407: * Tvar[cptcovn+k2]=Tvard[k1][1];Tvar[cptcovn+k2+1]=Tvard[k1][2];
8408: * Tvar[8+1]=5;Tvar[8+2]=6;Tvar[8+3]=7;Tvar[8+4]=8 inverted
8409: * V1 V2 V3 V4 V5 V6 V7 V8 V9 V10 V11
8410: * < ncovcol=8 >
8411: * Model V2 + V1 + V3*age + V3 + V5*V6 + V7*V8 + V8*age + V8 d1 d1 d2 d2
8412: * k= 1 2 3 4 5 6 7 8 9 10 11 12
8413: * Tvar[k]= 2 1 3 3 10 11 8 8 5 6 7 8
8414: * p Tvar[1]@12={2, 1, 3, 3, 11, 10, 8, 8, 7, 8, 5, 6}
8415: * p Tprod[1]@2={ 6, 5}
8416: *p Tvard[1][1]@4= {7, 8, 5, 6}
8417: * covar[k][i]= V2 V1 ? V3 V5*V6? V7*V8? ? V8
8418: * cov[Tage[kk]+2]=covar[Tvar[Tage[kk]]][i]*cov[2];
8419: *How to reorganize?
8420: * Model V1 + V2 + V3 + V8 + V5*V6 + V7*V8 + V3*age + V8*age
8421: * Tvars {2, 1, 3, 3, 11, 10, 8, 8, 7, 8, 5, 6}
8422: * {2, 1, 4, 8, 5, 6, 3, 7}
8423: * Struct []
8424: */
1.225 brouard 8425:
1.187 brouard 8426: /* This loop fills the array Tvar from the string 'model'.*/
8427: /* j is the number of + signs in the model V1+V2+V3 j=2 i=3 to 1 */
8428: /* modelsav=V2+V1+V4+age*V3 strb=age*V3 stra=V2+V1+V4 */
8429: /* k=4 (age*V3) Tvar[k=4]= 3 (from V3) Tage[cptcovage=1]=4 */
8430: /* k=3 V4 Tvar[k=3]= 4 (from V4) */
8431: /* k=2 V1 Tvar[k=2]= 1 (from V1) */
8432: /* k=1 Tvar[1]=2 (from V2) */
8433: /* k=5 Tvar[5] */
8434: /* for (k=1; k<=cptcovn;k++) { */
1.198 brouard 8435: /* cov[2+k]=nbcode[Tvar[k]][codtabm(ij,Tvar[k])]; */
1.187 brouard 8436: /* } */
1.198 brouard 8437: /* for (k=1; k<=cptcovage;k++) cov[2+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,Tvar[Tage[k])]]*cov[2]; */
1.187 brouard 8438: /*
8439: * Treating invertedly V2+V1+V3*age+V2*V4 is as if written V2*V4 +V3*age + V1 + V2 */
1.227 brouard 8440: for(k=cptcovt; k>=1;k--){ /**< Number of covariates not including constant and age, neither age*age*/
8441: Tvar[k]=0; Tprod[k]=0; Tposprod[k]=0;
8442: }
1.187 brouard 8443: cptcovage=0;
8444: for(k=1; k<=cptcovt;k++){ /* Loop on total covariates of the model */
1.234 brouard 8445: cutl(stra,strb,modelsav,'+'); /* keeps in strb after the first '+'
1.225 brouard 8446: modelsav==V2+V1+V4+V3*age strb=V3*age stra=V2+V1+V4 */
1.234 brouard 8447: if (nbocc(modelsav,'+')==0) strcpy(strb,modelsav); /* and analyzes it */
8448: /* printf("i=%d a=%s b=%s sav=%s\n",i, stra,strb,modelsav);*/
8449: /*scanf("%d",i);*/
8450: if (strchr(strb,'*')) { /**< Model includes a product V2+V1+V4+V3*age strb=V3*age */
8451: cutl(strc,strd,strb,'*'); /**< strd*strc Vm*Vn: strb=V3*age(input) strc=age strd=V3 ; V3*V2 strc=V2, strd=V3 */
8452: if (strcmp(strc,"age")==0) { /**< Model includes age: Vn*age */
8453: /* covar is not filled and then is empty */
8454: cptcovprod--;
8455: cutl(stre,strb,strd,'V'); /* strd=V3(input): stre="3" */
8456: Tvar[k]=atoi(stre); /* V2+V1+V4+V3*age Tvar[4]=3 ; V1+V2*age Tvar[2]=2; V1+V1*age Tvar[2]=1 */
8457: Typevar[k]=1; /* 1 for age product */
8458: cptcovage++; /* Sums the number of covariates which include age as a product */
8459: Tage[cptcovage]=k; /* Tvar[4]=3, Tage[1] = 4 or V1+V1*age Tvar[2]=1, Tage[1]=2 */
8460: /*printf("stre=%s ", stre);*/
8461: } else if (strcmp(strd,"age")==0) { /* or age*Vn */
8462: cptcovprod--;
8463: cutl(stre,strb,strc,'V');
8464: Tvar[k]=atoi(stre);
8465: Typevar[k]=1; /* 1 for age product */
8466: cptcovage++;
8467: Tage[cptcovage]=k;
8468: } else { /* Age is not in the model product V2+V1+V1*V4+V3*age+V3*V2 strb=V3*V2*/
8469: /* loops on k1=1 (V3*V2) and k1=2 V4*V3 */
8470: cptcovn++;
8471: cptcovprodnoage++;k1++;
8472: cutl(stre,strb,strc,'V'); /* strc= Vn, stre is n; strb=V3*V2 stre=3 strc=*/
8473: Tvar[k]=ncovcol+nqv+ntv+nqtv+k1; /* For model-covariate k tells which data-covariate to use but
8474: because this model-covariate is a construction we invent a new column
8475: which is after existing variables ncovcol+nqv+ntv+nqtv + k1
8476: If already ncovcol=4 and model=V2+V1+V1*V4+age*V3+V3*V2
8477: Tvar[3=V1*V4]=4+1 Tvar[5=V3*V2]=4 + 2= 6, etc */
8478: Typevar[k]=2; /* 2 for double fixed dummy covariates */
8479: cutl(strc,strb,strd,'V'); /* strd was Vm, strc is m */
8480: Tprod[k1]=k; /* Tprod[1]=3(=V1*V4) for V2+V1+V1*V4+age*V3+V3*V2 */
8481: Tposprod[k]=k1; /* Tpsprod[3]=1, Tposprod[2]=5 */
8482: Tvard[k1][1] =atoi(strc); /* m 1 for V1*/
8483: Tvard[k1][2] =atoi(stre); /* n 4 for V4*/
8484: k2=k2+2; /* k2 is initialize to -1, We want to store the n and m in Vn*Vm at the end of Tvar */
8485: /* Tvar[cptcovt+k2]=Tvard[k1][1]; /\* Tvar[(cptcovt=4+k2=1)=5]= 1 (V1) *\/ */
8486: /* Tvar[cptcovt+k2+1]=Tvard[k1][2]; /\* Tvar[(cptcovt=4+(k2=1)+1)=6]= 4 (V4) *\/ */
1.225 brouard 8487: /*ncovcol=4 and model=V2+V1+V1*V4+age*V3+V3*V2, Tvar[3]=5, Tvar[4]=6, cptcovt=5 */
1.234 brouard 8488: /* 1 2 3 4 5 | Tvar[5+1)=1, Tvar[7]=2 */
8489: for (i=1; i<=lastobs;i++){
8490: /* Computes the new covariate which is a product of
8491: covar[n][i]* covar[m][i] and stores it at ncovol+k1 May not be defined */
8492: covar[ncovcol+k1][i]=covar[atoi(stre)][i]*covar[atoi(strc)][i];
8493: }
8494: } /* End age is not in the model */
8495: } /* End if model includes a product */
8496: else { /* no more sum */
8497: /*printf("d=%s c=%s b=%s\n", strd,strc,strb);*/
8498: /* scanf("%d",i);*/
8499: cutl(strd,strc,strb,'V');
8500: ks++; /**< Number of simple covariates dummy or quantitative, fixe or varying */
8501: cptcovn++; /** V4+V3+V5: V4 and V3 timevarying dummy covariates, V5 timevarying quantitative */
8502: Tvar[k]=atoi(strd);
8503: Typevar[k]=0; /* 0 for simple covariates */
8504: }
8505: strcpy(modelsav,stra); /* modelsav=V2+V1+V4 stra=V2+V1+V4 */
1.223 brouard 8506: /*printf("a=%s b=%s sav=%s\n", stra,strb,modelsav);
1.225 brouard 8507: scanf("%d",i);*/
1.187 brouard 8508: } /* end of loop + on total covariates */
8509: } /* end if strlen(modelsave == 0) age*age might exist */
8510: } /* end if strlen(model == 0) */
1.136 brouard 8511:
8512: /*The number n of Vn is stored in Tvar. cptcovage =number of age covariate. Tage gives the position of age. cptcovprod= number of products.
8513: If model=V1+V1*age then Tvar[1]=1 Tvar[2]=1 cptcovage=1 Tage[1]=2 cptcovprod=0*/
1.225 brouard 8514:
1.136 brouard 8515: /* printf("tvar1=%d tvar2=%d tvar3=%d cptcovage=%d Tage=%d",Tvar[1],Tvar[2],Tvar[3],cptcovage,Tage[1]);
1.225 brouard 8516: printf("cptcovprod=%d ", cptcovprod);
8517: fprintf(ficlog,"cptcovprod=%d ", cptcovprod);
8518: scanf("%d ",i);*/
8519:
8520:
1.230 brouard 8521: /* Until here, decodemodel knows only the grammar (simple, product, age*) of the model but not what kind
8522: of variable (dummy vs quantitative, fixed vs time varying) is behind. But we know the # of each. */
1.226 brouard 8523: /* ncovcol= 1, nqv=1 | ntv=2, nqtv= 1 = 5 possible variables data: 2 fixed 3, varying
8524: model= V5 + V4 +V3 + V4*V3 + V5*age + V2 + V1*V2 + V1*age + V5*age, V1 is not used saving its place
8525: k = 1 2 3 4 5 6 7 8 9
8526: Tvar[k]= 5 4 3 1+1+2+1+1=6 5 2 7 1 5
8527: Typevar[k]= 0 0 0 2 1 0 2 1 1
1.227 brouard 8528: Fixed[k] 1 1 1 1 3 0 0 or 2 2 3
8529: Dummy[k] 1 0 0 0 3 1 1 2 3
8530: Tmodelind[combination of covar]=k;
1.225 brouard 8531: */
8532: /* Dispatching between quantitative and time varying covariates */
1.226 brouard 8533: /* If Tvar[k] >ncovcol it is a product */
1.225 brouard 8534: /* 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 8535: /* Computing effective variables, ie used by the model, that is from the cptcovt variables */
1.227 brouard 8536: printf("Model=%s\n\
8537: Typevar: 0 for simple covariate (dummy, quantitative, fixed or varying), 1 for age product, 2 for product \n\
8538: Fixed[k] 0=fixed (product or simple), 1 varying, 2 fixed with age product, 3 varying with age product \n\
8539: 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);
8540: fprintf(ficlog,"Model=%s\n\
8541: Typevar: 0 for simple covariate (dummy, quantitative, fixed or varying), 1 for age product, 2 for product \n\
8542: Fixed[k] 0=fixed (product or simple), 1 varying, 2 fixed with age product, 3 varying with age product \n\
8543: 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 8544: for(k=1;k<=cptcovt; k++){ Fixed[k]=0; Dummy[k]=0;}
1.234 brouard 8545: 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 */
8546: if (Tvar[k] <=ncovcol && Typevar[k]==0 ){ /* Simple fixed dummy (<=ncovcol) covariates */
1.227 brouard 8547: Fixed[k]= 0;
8548: Dummy[k]= 0;
1.225 brouard 8549: ncoveff++;
1.232 brouard 8550: ncovf++;
1.234 brouard 8551: nsd++;
8552: modell[k].maintype= FTYPE;
8553: TvarsD[nsd]=Tvar[k];
8554: TvarsDind[nsd]=k;
8555: TvarF[ncovf]=Tvar[k];
8556: TvarFind[ncovf]=k;
8557: TvarFD[ncoveff]=Tvar[k]; /* TvarFD[1]=V1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
8558: TvarFDind[ncoveff]=k; /* TvarFDind[1]=9 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
8559: }else if( Tvar[k] <=ncovcol && Typevar[k]==2){ /* Product of fixed dummy (<=ncovcol) covariates */
8560: Fixed[k]= 0;
8561: Dummy[k]= 0;
8562: ncoveff++;
8563: ncovf++;
8564: modell[k].maintype= FTYPE;
8565: TvarF[ncovf]=Tvar[k];
8566: TvarFind[ncovf]=k;
1.230 brouard 8567: TvarFD[ncoveff]=Tvar[k]; /* TvarFD[1]=V1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1.231 brouard 8568: TvarFDind[ncoveff]=k; /* TvarFDind[1]=9 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1.240 brouard 8569: }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 8570: Fixed[k]= 0;
8571: Dummy[k]= 1;
1.230 brouard 8572: nqfveff++;
1.234 brouard 8573: modell[k].maintype= FTYPE;
8574: modell[k].subtype= FQ;
8575: nsq++;
8576: TvarsQ[nsq]=Tvar[k];
8577: TvarsQind[nsq]=k;
1.232 brouard 8578: ncovf++;
1.234 brouard 8579: TvarF[ncovf]=Tvar[k];
8580: TvarFind[ncovf]=k;
1.231 brouard 8581: 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 8582: 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 8583: }else if( Tvar[k] <=ncovcol+nqv+ntv && Typevar[k]==0){/* Only simple time varying dummy variables */
1.227 brouard 8584: Fixed[k]= 1;
8585: Dummy[k]= 0;
1.225 brouard 8586: ntveff++; /* Only simple time varying dummy variable */
1.234 brouard 8587: modell[k].maintype= VTYPE;
8588: modell[k].subtype= VD;
8589: nsd++;
8590: TvarsD[nsd]=Tvar[k];
8591: TvarsDind[nsd]=k;
8592: ncovv++; /* Only simple time varying variables */
8593: TvarV[ncovv]=Tvar[k];
1.242 brouard 8594: 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 8595: 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 */
8596: 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 8597: 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);
8598: printf("Quasi TmodelInvind[%d]=%d\n",k,Tvar[k]- ncovcol-nqv);
1.231 brouard 8599: }else if( Tvar[k] <=ncovcol+nqv+ntv+nqtv && Typevar[k]==0){ /* Only simple time varying quantitative variable V5*/
1.234 brouard 8600: Fixed[k]= 1;
8601: Dummy[k]= 1;
8602: nqtveff++;
8603: modell[k].maintype= VTYPE;
8604: modell[k].subtype= VQ;
8605: ncovv++; /* Only simple time varying variables */
8606: nsq++;
8607: TvarsQ[nsq]=Tvar[k];
8608: TvarsQind[nsq]=k;
8609: TvarV[ncovv]=Tvar[k];
1.242 brouard 8610: 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 8611: 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 */
8612: 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 8613: TmodelInvQind[nqtveff]=Tvar[k]- ncovcol-nqv-ntv;/* Only simple time varying quantitative variable */
8614: /* Tmodeliqind[k]=nqtveff;/\* Only simple time varying quantitative variable *\/ */
8615: 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 8616: printf("Quasi TmodelInvQind[%d]=%d\n",k,Tvar[k]- ncovcol-nqv-ntv);
1.227 brouard 8617: }else if (Typevar[k] == 1) { /* product with age */
1.234 brouard 8618: ncova++;
8619: TvarA[ncova]=Tvar[k];
8620: TvarAind[ncova]=k;
1.231 brouard 8621: if (Tvar[k] <=ncovcol ){ /* Product age with fixed dummy covariatee */
1.240 brouard 8622: Fixed[k]= 2;
8623: Dummy[k]= 2;
8624: modell[k].maintype= ATYPE;
8625: modell[k].subtype= APFD;
8626: /* ncoveff++; */
1.227 brouard 8627: }else if( Tvar[k] <=ncovcol+nqv) { /* Remind that product Vn*Vm are added in k*/
1.240 brouard 8628: Fixed[k]= 2;
8629: Dummy[k]= 3;
8630: modell[k].maintype= ATYPE;
8631: modell[k].subtype= APFQ; /* Product age * fixed quantitative */
8632: /* nqfveff++; /\* Only simple fixed quantitative variable *\/ */
1.227 brouard 8633: }else if( Tvar[k] <=ncovcol+nqv+ntv ){
1.240 brouard 8634: Fixed[k]= 3;
8635: Dummy[k]= 2;
8636: modell[k].maintype= ATYPE;
8637: modell[k].subtype= APVD; /* Product age * varying dummy */
8638: /* ntveff++; /\* Only simple time varying dummy variable *\/ */
1.227 brouard 8639: }else if( Tvar[k] <=ncovcol+nqv+ntv+nqtv){
1.240 brouard 8640: Fixed[k]= 3;
8641: Dummy[k]= 3;
8642: modell[k].maintype= ATYPE;
8643: modell[k].subtype= APVQ; /* Product age * varying quantitative */
8644: /* nqtveff++;/\* Only simple time varying quantitative variable *\/ */
1.227 brouard 8645: }
8646: }else if (Typevar[k] == 2) { /* product without age */
8647: k1=Tposprod[k];
8648: if(Tvard[k1][1] <=ncovcol){
1.240 brouard 8649: if(Tvard[k1][2] <=ncovcol){
8650: Fixed[k]= 1;
8651: Dummy[k]= 0;
8652: modell[k].maintype= FTYPE;
8653: modell[k].subtype= FPDD; /* Product fixed dummy * fixed dummy */
8654: ncovf++; /* Fixed variables without age */
8655: TvarF[ncovf]=Tvar[k];
8656: TvarFind[ncovf]=k;
8657: }else if(Tvard[k1][2] <=ncovcol+nqv){
8658: Fixed[k]= 0; /* or 2 ?*/
8659: Dummy[k]= 1;
8660: modell[k].maintype= FTYPE;
8661: modell[k].subtype= FPDQ; /* Product fixed dummy * fixed quantitative */
8662: ncovf++; /* Varying variables without age */
8663: TvarF[ncovf]=Tvar[k];
8664: TvarFind[ncovf]=k;
8665: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){
8666: Fixed[k]= 1;
8667: Dummy[k]= 0;
8668: modell[k].maintype= VTYPE;
8669: modell[k].subtype= VPDD; /* Product fixed dummy * varying dummy */
8670: ncovv++; /* Varying variables without age */
8671: TvarV[ncovv]=Tvar[k];
8672: TvarVind[ncovv]=k;
8673: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){
8674: Fixed[k]= 1;
8675: Dummy[k]= 1;
8676: modell[k].maintype= VTYPE;
8677: modell[k].subtype= VPDQ; /* Product fixed dummy * varying quantitative */
8678: ncovv++; /* Varying variables without age */
8679: TvarV[ncovv]=Tvar[k];
8680: TvarVind[ncovv]=k;
8681: }
1.227 brouard 8682: }else if(Tvard[k1][1] <=ncovcol+nqv){
1.240 brouard 8683: if(Tvard[k1][2] <=ncovcol){
8684: Fixed[k]= 0; /* or 2 ?*/
8685: Dummy[k]= 1;
8686: modell[k].maintype= FTYPE;
8687: modell[k].subtype= FPDQ; /* Product fixed quantitative * fixed dummy */
8688: ncovf++; /* Fixed variables without age */
8689: TvarF[ncovf]=Tvar[k];
8690: TvarFind[ncovf]=k;
8691: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){
8692: Fixed[k]= 1;
8693: Dummy[k]= 1;
8694: modell[k].maintype= VTYPE;
8695: modell[k].subtype= VPDQ; /* Product fixed quantitative * varying dummy */
8696: ncovv++; /* Varying variables without age */
8697: TvarV[ncovv]=Tvar[k];
8698: TvarVind[ncovv]=k;
8699: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){
8700: Fixed[k]= 1;
8701: Dummy[k]= 1;
8702: modell[k].maintype= VTYPE;
8703: modell[k].subtype= VPQQ; /* Product fixed quantitative * varying quantitative */
8704: ncovv++; /* Varying variables without age */
8705: TvarV[ncovv]=Tvar[k];
8706: TvarVind[ncovv]=k;
8707: ncovv++; /* Varying variables without age */
8708: TvarV[ncovv]=Tvar[k];
8709: TvarVind[ncovv]=k;
8710: }
1.227 brouard 8711: }else if(Tvard[k1][1] <=ncovcol+nqv+ntv){
1.240 brouard 8712: if(Tvard[k1][2] <=ncovcol){
8713: Fixed[k]= 1;
8714: Dummy[k]= 1;
8715: modell[k].maintype= VTYPE;
8716: modell[k].subtype= VPDD; /* Product time varying dummy * fixed dummy */
8717: ncovv++; /* Varying variables without age */
8718: TvarV[ncovv]=Tvar[k];
8719: TvarVind[ncovv]=k;
8720: }else if(Tvard[k1][2] <=ncovcol+nqv){
8721: Fixed[k]= 1;
8722: Dummy[k]= 1;
8723: modell[k].maintype= VTYPE;
8724: modell[k].subtype= VPDQ; /* Product time varying dummy * fixed quantitative */
8725: ncovv++; /* Varying variables without age */
8726: TvarV[ncovv]=Tvar[k];
8727: TvarVind[ncovv]=k;
8728: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){
8729: Fixed[k]= 1;
8730: Dummy[k]= 0;
8731: modell[k].maintype= VTYPE;
8732: modell[k].subtype= VPDD; /* Product time varying dummy * time varying dummy */
8733: ncovv++; /* Varying variables without age */
8734: TvarV[ncovv]=Tvar[k];
8735: TvarVind[ncovv]=k;
8736: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){
8737: Fixed[k]= 1;
8738: Dummy[k]= 1;
8739: modell[k].maintype= VTYPE;
8740: modell[k].subtype= VPDQ; /* Product time varying dummy * time varying quantitative */
8741: ncovv++; /* Varying variables without age */
8742: TvarV[ncovv]=Tvar[k];
8743: TvarVind[ncovv]=k;
8744: }
1.227 brouard 8745: }else if(Tvard[k1][1] <=ncovcol+nqv+ntv+nqtv){
1.240 brouard 8746: if(Tvard[k1][2] <=ncovcol){
8747: Fixed[k]= 1;
8748: Dummy[k]= 1;
8749: modell[k].maintype= VTYPE;
8750: modell[k].subtype= VPDQ; /* Product time varying quantitative * fixed dummy */
8751: ncovv++; /* Varying variables without age */
8752: TvarV[ncovv]=Tvar[k];
8753: TvarVind[ncovv]=k;
8754: }else if(Tvard[k1][2] <=ncovcol+nqv){
8755: Fixed[k]= 1;
8756: Dummy[k]= 1;
8757: modell[k].maintype= VTYPE;
8758: modell[k].subtype= VPQQ; /* Product time varying quantitative * fixed quantitative */
8759: ncovv++; /* Varying variables without age */
8760: TvarV[ncovv]=Tvar[k];
8761: TvarVind[ncovv]=k;
8762: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){
8763: Fixed[k]= 1;
8764: Dummy[k]= 1;
8765: modell[k].maintype= VTYPE;
8766: modell[k].subtype= VPDQ; /* Product time varying quantitative * time varying dummy */
8767: ncovv++; /* Varying variables without age */
8768: TvarV[ncovv]=Tvar[k];
8769: TvarVind[ncovv]=k;
8770: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){
8771: Fixed[k]= 1;
8772: Dummy[k]= 1;
8773: modell[k].maintype= VTYPE;
8774: modell[k].subtype= VPQQ; /* Product time varying quantitative * time varying quantitative */
8775: ncovv++; /* Varying variables without age */
8776: TvarV[ncovv]=Tvar[k];
8777: TvarVind[ncovv]=k;
8778: }
1.227 brouard 8779: }else{
1.240 brouard 8780: printf("Error unknown type of covariate: Tvard[%d][1]=%d,Tvard[%d][2]=%d\n",k1,Tvard[k1][1],k1,Tvard[k1][2]);
8781: fprintf(ficlog,"Error unknown type of covariate: Tvard[%d][1]=%d,Tvard[%d][2]=%d\n",k1,Tvard[k1][1],k1,Tvard[k1][2]);
8782: } /*end k1*/
1.225 brouard 8783: }else{
1.226 brouard 8784: printf("Error, current version can't treat for performance reasons, Tvar[%d]=%d, Typevar[%d]=%d\n", k, Tvar[k], k, Typevar[k]);
8785: 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 8786: }
1.227 brouard 8787: 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 8788: printf(" modell[%d].maintype=%d, modell[%d].subtype=%d\n",k,modell[k].maintype,k,modell[k].subtype);
1.227 brouard 8789: 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]);
8790: }
8791: /* Searching for doublons in the model */
8792: for(k1=1; k1<= cptcovt;k1++){
8793: for(k2=1; k2 <k1;k2++){
8794: if((Typevar[k1]==Typevar[k2]) && (Fixed[Tvar[k1]]==Fixed[Tvar[k2]]) && (Dummy[Tvar[k1]]==Dummy[Tvar[k2]] )){
1.234 brouard 8795: if((Typevar[k1] == 0 || Typevar[k1] == 1)){ /* Simple or age product */
8796: if(Tvar[k1]==Tvar[k2]){
8797: 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]]);
8798: 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);
8799: return(1);
8800: }
8801: }else if (Typevar[k1] ==2){
8802: k3=Tposprod[k1];
8803: k4=Tposprod[k2];
8804: 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])) ){
8805: 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]]);
8806: 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);
8807: return(1);
8808: }
8809: }
1.227 brouard 8810: }
8811: }
1.225 brouard 8812: }
8813: printf("ncoveff=%d, nqfveff=%d, ntveff=%d, nqtveff=%d, cptcovn=%d\n",ncoveff,nqfveff,ntveff,nqtveff,cptcovn);
8814: fprintf(ficlog,"ncoveff=%d, nqfveff=%d, ntveff=%d, nqtveff=%d, cptcovn=%d\n",ncoveff,nqfveff,ntveff,nqtveff,cptcovn);
1.234 brouard 8815: printf("ncovf=%d, ncovv=%d, ncova=%d, nsd=%d, nsq=%d\n",ncovf,ncovv,ncova,nsd,nsq);
8816: fprintf(ficlog,"ncovf=%d, ncovv=%d, ncova=%d, nsd=%d, nsq=%d\n",ncovf,ncovv,ncova,nsd, nsq);
1.137 brouard 8817: return (0); /* with covar[new additional covariate if product] and Tage if age */
1.164 brouard 8818: /*endread:*/
1.225 brouard 8819: printf("Exiting decodemodel: ");
8820: return (1);
1.136 brouard 8821: }
8822:
1.169 brouard 8823: int calandcheckages(int imx, int maxwav, double *agemin, double *agemax, int *nberr, int *nbwarn )
1.136 brouard 8824: {
8825: int i, m;
1.218 brouard 8826: int firstone=0;
8827:
1.136 brouard 8828: for (i=1; i<=imx; i++) {
8829: for(m=2; (m<= maxwav); m++) {
8830: if (((int)mint[m][i]== 99) && (s[m][i] <= nlstate)){
8831: anint[m][i]=9999;
1.216 brouard 8832: if (s[m][i] != -2) /* Keeping initial status of unknown vital status */
8833: s[m][i]=-1;
1.136 brouard 8834: }
8835: if((int)moisdc[i]==99 && (int)andc[i]==9999 && s[m][i]>nlstate){
1.169 brouard 8836: *nberr = *nberr + 1;
1.218 brouard 8837: if(firstone == 0){
8838: firstone=1;
8839: printf("Error! Date of death (month %2d and year %4d) of individual %ld on line %d was unknown, you must set an arbitrary year of death or he/she is skipped and results can be biased (%d) because status is a death state %d at wave %d. Wave dropped.\nOther similar cases in log file\n",(int)moisdc[i],(int)andc[i],num[i],i, *nberr,s[m][i],m);
8840: }
8841: fprintf(ficlog,"Error! Date of death (month %2d and year %4d) of individual %ld on line %d was unknown, you must set an arbitrary year of death or he/she is skipped and results can be biased (%d) because status is a death state %d at wave %d. Wave dropped.\n",(int)moisdc[i],(int)andc[i],num[i],i, *nberr,s[m][i],m);
1.136 brouard 8842: s[m][i]=-1;
8843: }
8844: if((int)moisdc[i]==99 && (int)andc[i]!=9999 && s[m][i]>nlstate){
1.169 brouard 8845: (*nberr)++;
1.136 brouard 8846: printf("Error! Month of death of individual %ld on line %d was unknown %2d, you should set it otherwise the information on the death is skipped and results are biased.\n",num[i],i,(int)moisdc[i]);
8847: fprintf(ficlog,"Error! Month of death of individual %ld on line %d was unknown %f, you should set it otherwise the information on the death is skipped and results are biased.\n",num[i],i,moisdc[i]);
8848: s[m][i]=-1; /* We prefer to skip it (and to skip it in version 0.8a1 too */
8849: }
8850: }
8851: }
8852:
8853: for (i=1; i<=imx; i++) {
8854: agedc[i]=(moisdc[i]/12.+andc[i])-(moisnais[i]/12.+annais[i]);
8855: for(m=firstpass; (m<= lastpass); m++){
1.214 brouard 8856: 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 8857: if (s[m][i] >= nlstate+1) {
1.169 brouard 8858: if(agedc[i]>0){
8859: if((int)moisdc[i]!=99 && (int)andc[i]!=9999){
1.136 brouard 8860: agev[m][i]=agedc[i];
1.214 brouard 8861: /*if(moisdc[i]==99 && andc[i]==9999) s[m][i]=-1;*/
1.169 brouard 8862: }else {
1.136 brouard 8863: if ((int)andc[i]!=9999){
8864: nbwarn++;
8865: printf("Warning negative age at death: %ld line:%d\n",num[i],i);
8866: fprintf(ficlog,"Warning negative age at death: %ld line:%d\n",num[i],i);
8867: agev[m][i]=-1;
8868: }
8869: }
1.169 brouard 8870: } /* agedc > 0 */
1.214 brouard 8871: } /* end if */
1.136 brouard 8872: else if(s[m][i] !=9){ /* Standard case, age in fractional
8873: years but with the precision of a month */
8874: agev[m][i]=(mint[m][i]/12.+1./24.+anint[m][i])-(moisnais[i]/12.+1./24.+annais[i]);
8875: if((int)mint[m][i]==99 || (int)anint[m][i]==9999)
8876: agev[m][i]=1;
8877: else if(agev[m][i] < *agemin){
8878: *agemin=agev[m][i];
8879: printf(" Min anint[%d][%d]=%.2f annais[%d]=%.2f, agemin=%.2f\n",m,i,anint[m][i], i,annais[i], *agemin);
8880: }
8881: else if(agev[m][i] >*agemax){
8882: *agemax=agev[m][i];
1.156 brouard 8883: /* printf(" Max anint[%d][%d]=%.0f annais[%d]=%.0f, agemax=%.2f\n",m,i,anint[m][i], i,annais[i], *agemax);*/
1.136 brouard 8884: }
8885: /*agev[m][i]=anint[m][i]-annais[i];*/
8886: /* agev[m][i] = age[i]+2*m;*/
1.214 brouard 8887: } /* en if 9*/
1.136 brouard 8888: else { /* =9 */
1.214 brouard 8889: /* printf("Debug num[%d]=%ld s[%d][%d]=%d\n",i,num[i], m,i, s[m][i]); */
1.136 brouard 8890: agev[m][i]=1;
8891: s[m][i]=-1;
8892: }
8893: }
1.214 brouard 8894: else if(s[m][i]==0) /*= 0 Unknown */
1.136 brouard 8895: agev[m][i]=1;
1.214 brouard 8896: else{
8897: printf("Warning, num[%d]=%ld, s[%d][%d]=%d\n", i, num[i], m, i,s[m][i]);
8898: fprintf(ficlog, "Warning, num[%d]=%ld, s[%d][%d]=%d\n", i, num[i], m, i,s[m][i]);
8899: agev[m][i]=0;
8900: }
8901: } /* End for lastpass */
8902: }
1.136 brouard 8903:
8904: for (i=1; i<=imx; i++) {
8905: for(m=firstpass; (m<=lastpass); m++){
8906: if (s[m][i] > (nlstate+ndeath)) {
1.169 brouard 8907: (*nberr)++;
1.136 brouard 8908: 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);
8909: 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);
8910: return 1;
8911: }
8912: }
8913: }
8914:
8915: /*for (i=1; i<=imx; i++){
8916: for (m=firstpass; (m<lastpass); m++){
8917: printf("%ld %d %.lf %d %d\n", num[i],(covar[1][i]),agev[m][i],s[m][i],s[m+1][i]);
8918: }
8919:
8920: }*/
8921:
8922:
1.139 brouard 8923: printf("Total number of individuals= %d, Agemin = %.2f, Agemax= %.2f\n\n", imx, *agemin, *agemax);
8924: fprintf(ficlog,"Total number of individuals= %d, Agemin = %.2f, Agemax= %.2f\n\n", imx, *agemin, *agemax);
1.136 brouard 8925:
8926: return (0);
1.164 brouard 8927: /* endread:*/
1.136 brouard 8928: printf("Exiting calandcheckages: ");
8929: return (1);
8930: }
8931:
1.172 brouard 8932: #if defined(_MSC_VER)
8933: /*printf("Visual C++ compiler: %s \n;", _MSC_FULL_VER);*/
8934: /*fprintf(ficlog, "Visual C++ compiler: %s \n;", _MSC_FULL_VER);*/
8935: //#include "stdafx.h"
8936: //#include <stdio.h>
8937: //#include <tchar.h>
8938: //#include <windows.h>
8939: //#include <iostream>
8940: typedef BOOL(WINAPI *LPFN_ISWOW64PROCESS) (HANDLE, PBOOL);
8941:
8942: LPFN_ISWOW64PROCESS fnIsWow64Process;
8943:
8944: BOOL IsWow64()
8945: {
8946: BOOL bIsWow64 = FALSE;
8947:
8948: //typedef BOOL (APIENTRY *LPFN_ISWOW64PROCESS)
8949: // (HANDLE, PBOOL);
8950:
8951: //LPFN_ISWOW64PROCESS fnIsWow64Process;
8952:
8953: HMODULE module = GetModuleHandle(_T("kernel32"));
8954: const char funcName[] = "IsWow64Process";
8955: fnIsWow64Process = (LPFN_ISWOW64PROCESS)
8956: GetProcAddress(module, funcName);
8957:
8958: if (NULL != fnIsWow64Process)
8959: {
8960: if (!fnIsWow64Process(GetCurrentProcess(),
8961: &bIsWow64))
8962: //throw std::exception("Unknown error");
8963: printf("Unknown error\n");
8964: }
8965: return bIsWow64 != FALSE;
8966: }
8967: #endif
1.177 brouard 8968:
1.191 brouard 8969: void syscompilerinfo(int logged)
1.167 brouard 8970: {
8971: /* #include "syscompilerinfo.h"*/
1.185 brouard 8972: /* command line Intel compiler 32bit windows, XP compatible:*/
8973: /* /GS /W3 /Gy
8974: /Zc:wchar_t /Zi /O2 /Fd"Release\vc120.pdb" /D "WIN32" /D "NDEBUG" /D
8975: "_CONSOLE" /D "_LIB" /D "_USING_V110_SDK71_" /D "_UNICODE" /D
8976: "UNICODE" /Qipo /Zc:forScope /Gd /Oi /MT /Fa"Release\" /EHsc /nologo
1.186 brouard 8977: /Fo"Release\" /Qprof-dir "Release\" /Fp"Release\IMaCh.pch"
8978: */
8979: /* 64 bits */
1.185 brouard 8980: /*
8981: /GS /W3 /Gy
8982: /Zc:wchar_t /Zi /O2 /Fd"x64\Release\vc120.pdb" /D "WIN32" /D "NDEBUG"
8983: /D "_CONSOLE" /D "_LIB" /D "_UNICODE" /D "UNICODE" /Qipo /Zc:forScope
8984: /Oi /MD /Fa"x64\Release\" /EHsc /nologo /Fo"x64\Release\" /Qprof-dir
8985: "x64\Release\" /Fp"x64\Release\IMaCh.pch" */
8986: /* Optimization are useless and O3 is slower than O2 */
8987: /*
8988: /GS /W3 /Gy /Zc:wchar_t /Zi /O3 /Fd"x64\Release\vc120.pdb" /D "WIN32"
8989: /D "NDEBUG" /D "_CONSOLE" /D "_LIB" /D "_UNICODE" /D "UNICODE" /Qipo
8990: /Zc:forScope /Oi /MD /Fa"x64\Release\" /EHsc /nologo /Qparallel
8991: /Fo"x64\Release\" /Qprof-dir "x64\Release\" /Fp"x64\Release\IMaCh.pch"
8992: */
1.186 brouard 8993: /* Link is */ /* /OUT:"visual studio
1.185 brouard 8994: 2013\Projects\IMaCh\Release\IMaCh.exe" /MANIFEST /NXCOMPAT
8995: /PDB:"visual studio
8996: 2013\Projects\IMaCh\Release\IMaCh.pdb" /DYNAMICBASE
8997: "kernel32.lib" "user32.lib" "gdi32.lib" "winspool.lib"
8998: "comdlg32.lib" "advapi32.lib" "shell32.lib" "ole32.lib"
8999: "oleaut32.lib" "uuid.lib" "odbc32.lib" "odbccp32.lib"
9000: /MACHINE:X86 /OPT:REF /SAFESEH /INCREMENTAL:NO
9001: /SUBSYSTEM:CONSOLE",5.01" /MANIFESTUAC:"level='asInvoker'
9002: uiAccess='false'"
9003: /ManifestFile:"Release\IMaCh.exe.intermediate.manifest" /OPT:ICF
9004: /NOLOGO /TLBID:1
9005: */
1.177 brouard 9006: #if defined __INTEL_COMPILER
1.178 brouard 9007: #if defined(__GNUC__)
9008: struct utsname sysInfo; /* For Intel on Linux and OS/X */
9009: #endif
1.177 brouard 9010: #elif defined(__GNUC__)
1.179 brouard 9011: #ifndef __APPLE__
1.174 brouard 9012: #include <gnu/libc-version.h> /* Only on gnu */
1.179 brouard 9013: #endif
1.177 brouard 9014: struct utsname sysInfo;
1.178 brouard 9015: int cross = CROSS;
9016: if (cross){
9017: printf("Cross-");
1.191 brouard 9018: if(logged) fprintf(ficlog, "Cross-");
1.178 brouard 9019: }
1.174 brouard 9020: #endif
9021:
1.171 brouard 9022: #include <stdint.h>
1.178 brouard 9023:
1.191 brouard 9024: printf("Compiled with:");if(logged)fprintf(ficlog,"Compiled with:");
1.169 brouard 9025: #if defined(__clang__)
1.191 brouard 9026: printf(" Clang/LLVM");if(logged)fprintf(ficlog," Clang/LLVM"); /* Clang/LLVM. ---------------------------------------------- */
1.169 brouard 9027: #endif
9028: #if defined(__ICC) || defined(__INTEL_COMPILER)
1.191 brouard 9029: printf(" Intel ICC/ICPC");if(logged)fprintf(ficlog," Intel ICC/ICPC");/* Intel ICC/ICPC. ------------------------------------------ */
1.169 brouard 9030: #endif
9031: #if defined(__GNUC__) || defined(__GNUG__)
1.191 brouard 9032: printf(" GNU GCC/G++");if(logged)fprintf(ficlog," GNU GCC/G++");/* GNU GCC/G++. --------------------------------------------- */
1.169 brouard 9033: #endif
9034: #if defined(__HP_cc) || defined(__HP_aCC)
1.191 brouard 9035: printf(" Hewlett-Packard C/aC++");if(logged)fprintf(fcilog," Hewlett-Packard C/aC++"); /* Hewlett-Packard C/aC++. ---------------------------------- */
1.169 brouard 9036: #endif
9037: #if defined(__IBMC__) || defined(__IBMCPP__)
1.191 brouard 9038: printf(" IBM XL C/C++"); if(logged) fprintf(ficlog," IBM XL C/C++");/* IBM XL C/C++. -------------------------------------------- */
1.169 brouard 9039: #endif
9040: #if defined(_MSC_VER)
1.191 brouard 9041: printf(" Microsoft Visual Studio");if(logged)fprintf(ficlog," Microsoft Visual Studio");/* Microsoft Visual Studio. --------------------------------- */
1.169 brouard 9042: #endif
9043: #if defined(__PGI)
1.191 brouard 9044: printf(" Portland Group PGCC/PGCPP");if(logged) fprintf(ficlog," Portland Group PGCC/PGCPP");/* Portland Group PGCC/PGCPP. ------------------------------- */
1.169 brouard 9045: #endif
9046: #if defined(__SUNPRO_C) || defined(__SUNPRO_CC)
1.191 brouard 9047: printf(" Oracle Solaris Studio");if(logged)fprintf(ficlog," Oracle Solaris Studio\n");/* Oracle Solaris Studio. ----------------------------------- */
1.167 brouard 9048: #endif
1.191 brouard 9049: printf(" for "); if (logged) fprintf(ficlog, " for ");
1.169 brouard 9050:
1.167 brouard 9051: // http://stackoverflow.com/questions/4605842/how-to-identify-platform-compiler-from-preprocessor-macros
9052: #ifdef _WIN32 // note the underscore: without it, it's not msdn official!
9053: // Windows (x64 and x86)
1.191 brouard 9054: printf("Windows (x64 and x86) ");if(logged) fprintf(ficlog,"Windows (x64 and x86) ");
1.167 brouard 9055: #elif __unix__ // all unices, not all compilers
9056: // Unix
1.191 brouard 9057: printf("Unix ");if(logged) fprintf(ficlog,"Unix ");
1.167 brouard 9058: #elif __linux__
9059: // linux
1.191 brouard 9060: printf("linux ");if(logged) fprintf(ficlog,"linux ");
1.167 brouard 9061: #elif __APPLE__
1.174 brouard 9062: // Mac OS, not sure if this is covered by __posix__ and/or __unix__ though..
1.191 brouard 9063: printf("Mac OS ");if(logged) fprintf(ficlog,"Mac OS ");
1.167 brouard 9064: #endif
9065:
9066: /* __MINGW32__ */
9067: /* __CYGWIN__ */
9068: /* __MINGW64__ */
9069: // http://msdn.microsoft.com/en-us/library/b0084kay.aspx
9070: /* _MSC_VER //the Visual C++ compiler is 17.00.51106.1, the _MSC_VER macro evaluates to 1700. Type cl /? */
9071: /* _MSC_FULL_VER //the Visual C++ compiler is 15.00.20706.01, the _MSC_FULL_VER macro evaluates to 150020706 */
9072: /* _WIN64 // Defined for applications for Win64. */
9073: /* _M_X64 // Defined for compilations that target x64 processors. */
9074: /* _DEBUG // Defined when you compile with /LDd, /MDd, and /MTd. */
1.171 brouard 9075:
1.167 brouard 9076: #if UINTPTR_MAX == 0xffffffff
1.191 brouard 9077: printf(" 32-bit"); if(logged) fprintf(ficlog," 32-bit");/* 32-bit */
1.167 brouard 9078: #elif UINTPTR_MAX == 0xffffffffffffffff
1.191 brouard 9079: printf(" 64-bit"); if(logged) fprintf(ficlog," 64-bit");/* 64-bit */
1.167 brouard 9080: #else
1.191 brouard 9081: printf(" wtf-bit"); if(logged) fprintf(ficlog," wtf-bit");/* wtf */
1.167 brouard 9082: #endif
9083:
1.169 brouard 9084: #if defined(__GNUC__)
9085: # if defined(__GNUC_PATCHLEVEL__)
9086: # define __GNUC_VERSION__ (__GNUC__ * 10000 \
9087: + __GNUC_MINOR__ * 100 \
9088: + __GNUC_PATCHLEVEL__)
9089: # else
9090: # define __GNUC_VERSION__ (__GNUC__ * 10000 \
9091: + __GNUC_MINOR__ * 100)
9092: # endif
1.174 brouard 9093: printf(" using GNU C version %d.\n", __GNUC_VERSION__);
1.191 brouard 9094: if(logged) fprintf(ficlog, " using GNU C version %d.\n", __GNUC_VERSION__);
1.176 brouard 9095:
9096: if (uname(&sysInfo) != -1) {
9097: printf("Running on: %s %s %s %s %s\n",sysInfo.sysname, sysInfo.nodename, sysInfo.release, sysInfo.version, sysInfo.machine);
1.191 brouard 9098: 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 9099: }
9100: else
9101: perror("uname() error");
1.179 brouard 9102: //#ifndef __INTEL_COMPILER
9103: #if !defined (__INTEL_COMPILER) && !defined(__APPLE__)
1.174 brouard 9104: printf("GNU libc version: %s\n", gnu_get_libc_version());
1.191 brouard 9105: if(logged) fprintf(ficlog,"GNU libc version: %s\n", gnu_get_libc_version());
1.177 brouard 9106: #endif
1.169 brouard 9107: #endif
1.172 brouard 9108:
9109: // void main()
9110: // {
1.169 brouard 9111: #if defined(_MSC_VER)
1.174 brouard 9112: if (IsWow64()){
1.191 brouard 9113: printf("\nThe program (probably compiled for 32bit) is running under WOW64 (64bit) emulation.\n");
9114: if (logged) fprintf(ficlog, "\nThe program (probably compiled for 32bit) is running under WOW64 (64bit) emulation.\n");
1.174 brouard 9115: }
9116: else{
1.191 brouard 9117: printf("\nThe program is not running under WOW64 (i.e probably on a 64bit Windows).\n");
9118: if (logged) fprintf(ficlog, "\nThe programm is not running under WOW64 (i.e probably on a 64bit Windows).\n");
1.174 brouard 9119: }
1.172 brouard 9120: // printf("\nPress Enter to continue...");
9121: // getchar();
9122: // }
9123:
1.169 brouard 9124: #endif
9125:
1.167 brouard 9126:
1.219 brouard 9127: }
1.136 brouard 9128:
1.219 brouard 9129: int prevalence_limit(double *p, double **prlim, double ageminpar, double agemaxpar, double ftolpl, int *ncvyearp){
1.180 brouard 9130: /*--------------- Prevalence limit (period or stable prevalence) --------------*/
1.235 brouard 9131: int i, j, k, i1, k4=0, nres=0 ;
1.202 brouard 9132: /* double ftolpl = 1.e-10; */
1.180 brouard 9133: double age, agebase, agelim;
1.203 brouard 9134: double tot;
1.180 brouard 9135:
1.202 brouard 9136: strcpy(filerespl,"PL_");
9137: strcat(filerespl,fileresu);
9138: if((ficrespl=fopen(filerespl,"w"))==NULL) {
9139: printf("Problem with period (stable) prevalence resultfile: %s\n", filerespl);return 1;
9140: fprintf(ficlog,"Problem with period (stable) prevalence resultfile: %s\n", filerespl);return 1;
9141: }
1.227 brouard 9142: printf("\nComputing period (stable) prevalence: result on file '%s' \n", filerespl);
9143: fprintf(ficlog,"\nComputing period (stable) prevalence: result on file '%s' \n", filerespl);
1.202 brouard 9144: pstamp(ficrespl);
1.203 brouard 9145: fprintf(ficrespl,"# Period (stable) prevalence. Precision given by ftolpl=%g \n", ftolpl);
1.202 brouard 9146: fprintf(ficrespl,"#Age ");
9147: for(i=1; i<=nlstate;i++) fprintf(ficrespl,"%d-%d ",i,i);
9148: fprintf(ficrespl,"\n");
1.180 brouard 9149:
1.219 brouard 9150: /* prlim=matrix(1,nlstate,1,nlstate);*/ /* back in main */
1.180 brouard 9151:
1.219 brouard 9152: agebase=ageminpar;
9153: agelim=agemaxpar;
1.180 brouard 9154:
1.227 brouard 9155: /* i1=pow(2,ncoveff); */
1.234 brouard 9156: i1=pow(2,cptcoveff); /* Number of combination of dummy covariates */
1.219 brouard 9157: if (cptcovn < 1){i1=1;}
1.180 brouard 9158:
1.238 brouard 9159: for(k=1; k<=i1;k++){ /* For each combination k of dummy covariates in the model */
9160: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
9161: if(TKresult[nres]!= k)
9162: continue;
1.235 brouard 9163:
1.238 brouard 9164: /* for(cptcov=1,k=0;cptcov<=i1;cptcov++){ */
9165: /* for(cptcov=1,k=0;cptcov<=1;cptcov++){ */
9166: //for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){
9167: /* k=k+1; */
9168: /* to clean */
9169: //printf("cptcov=%d cptcod=%d codtab=%d\n",cptcov, cptcod,codtabm(cptcod,cptcov));
9170: fprintf(ficrespl,"#******");
9171: printf("#******");
9172: fprintf(ficlog,"#******");
9173: for(j=1;j<=cptcoveff ;j++) {/* all covariates */
9174: fprintf(ficrespl," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]); /* Here problem for varying dummy*/
9175: printf(" V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
9176: fprintf(ficlog," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
9177: }
9178: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
9179: printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
9180: fprintf(ficrespl," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
9181: fprintf(ficlog," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
9182: }
9183: fprintf(ficrespl,"******\n");
9184: printf("******\n");
9185: fprintf(ficlog,"******\n");
9186: if(invalidvarcomb[k]){
9187: printf("\nCombination (%d) ignored because no case \n",k);
9188: fprintf(ficrespl,"#Combination (%d) ignored because no case \n",k);
9189: fprintf(ficlog,"\nCombination (%d) ignored because no case \n",k);
9190: continue;
9191: }
1.219 brouard 9192:
1.238 brouard 9193: fprintf(ficrespl,"#Age ");
9194: for(j=1;j<=cptcoveff;j++) {
9195: fprintf(ficrespl,"V%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
9196: }
9197: for(i=1; i<=nlstate;i++) fprintf(ficrespl," %d-%d ",i,i);
9198: fprintf(ficrespl,"Total Years_to_converge\n");
1.227 brouard 9199:
1.238 brouard 9200: for (age=agebase; age<=agelim; age++){
9201: /* for (age=agebase; age<=agebase; age++){ */
9202: prevalim(prlim, nlstate, p, age, oldm, savm, ftolpl, ncvyearp, k, nres);
9203: fprintf(ficrespl,"%.0f ",age );
9204: for(j=1;j<=cptcoveff;j++)
9205: fprintf(ficrespl,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
9206: tot=0.;
9207: for(i=1; i<=nlstate;i++){
9208: tot += prlim[i][i];
9209: fprintf(ficrespl," %.5f", prlim[i][i]);
9210: }
9211: fprintf(ficrespl," %.3f %d\n", tot, *ncvyearp);
9212: } /* Age */
9213: /* was end of cptcod */
9214: } /* cptcov */
9215: } /* nres */
1.219 brouard 9216: return 0;
1.180 brouard 9217: }
9218:
1.218 brouard 9219: 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){
9220: /*--------------- Back Prevalence limit (period or stable prevalence) --------------*/
9221:
9222: /* Computes the back prevalence limit for any combination of covariate values
9223: * at any age between ageminpar and agemaxpar
9224: */
1.235 brouard 9225: int i, j, k, i1, nres=0 ;
1.217 brouard 9226: /* double ftolpl = 1.e-10; */
9227: double age, agebase, agelim;
9228: double tot;
1.218 brouard 9229: /* double ***mobaverage; */
9230: /* double **dnewm, **doldm, **dsavm; /\* for use *\/ */
1.217 brouard 9231:
9232: strcpy(fileresplb,"PLB_");
9233: strcat(fileresplb,fileresu);
9234: if((ficresplb=fopen(fileresplb,"w"))==NULL) {
9235: printf("Problem with period (stable) back prevalence resultfile: %s\n", fileresplb);return 1;
9236: fprintf(ficlog,"Problem with period (stable) back prevalence resultfile: %s\n", fileresplb);return 1;
9237: }
9238: printf("Computing period (stable) back prevalence: result on file '%s' \n", fileresplb);
9239: fprintf(ficlog,"Computing period (stable) back prevalence: result on file '%s' \n", fileresplb);
9240: pstamp(ficresplb);
9241: fprintf(ficresplb,"# Period (stable) back prevalence. Precision given by ftolpl=%g \n", ftolpl);
9242: fprintf(ficresplb,"#Age ");
9243: for(i=1; i<=nlstate;i++) fprintf(ficresplb,"%d-%d ",i,i);
9244: fprintf(ficresplb,"\n");
9245:
1.218 brouard 9246:
9247: /* prlim=matrix(1,nlstate,1,nlstate);*/ /* back in main */
9248:
9249: agebase=ageminpar;
9250: agelim=agemaxpar;
9251:
9252:
1.227 brouard 9253: i1=pow(2,cptcoveff);
1.218 brouard 9254: if (cptcovn < 1){i1=1;}
1.227 brouard 9255:
1.238 brouard 9256: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
9257: for(k=1; k<=i1;k++){ /* For any combination of dummy covariates, fixed and varying */
9258: if(TKresult[nres]!= k)
9259: continue;
9260: //printf("cptcov=%d cptcod=%d codtab=%d\n",cptcov, cptcod,codtabm(cptcod,cptcov));
9261: fprintf(ficresplb,"#******");
9262: printf("#******");
9263: fprintf(ficlog,"#******");
9264: for(j=1;j<=cptcoveff ;j++) {/* all covariates */
9265: fprintf(ficresplb," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
9266: printf(" V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
9267: fprintf(ficlog," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
9268: }
9269: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
9270: printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
9271: fprintf(ficresplb," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
9272: fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
9273: }
9274: fprintf(ficresplb,"******\n");
9275: printf("******\n");
9276: fprintf(ficlog,"******\n");
9277: if(invalidvarcomb[k]){
9278: printf("\nCombination (%d) ignored because no cases \n",k);
9279: fprintf(ficresplb,"#Combination (%d) ignored because no cases \n",k);
9280: fprintf(ficlog,"\nCombination (%d) ignored because no cases \n",k);
9281: continue;
9282: }
1.218 brouard 9283:
1.238 brouard 9284: fprintf(ficresplb,"#Age ");
9285: for(j=1;j<=cptcoveff;j++) {
9286: fprintf(ficresplb,"V%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
9287: }
9288: for(i=1; i<=nlstate;i++) fprintf(ficresplb," %d-%d ",i,i);
9289: fprintf(ficresplb,"Total Years_to_converge\n");
1.218 brouard 9290:
9291:
1.238 brouard 9292: for (age=agebase; age<=agelim; age++){
9293: /* for (age=agebase; age<=agebase; age++){ */
9294: if(mobilavproj > 0){
9295: /* bprevalim(bprlim, mobaverage, nlstate, p, age, ageminpar, agemaxpar, oldm, savm, doldm, dsavm, ftolpl, ncvyearp, k); */
9296: /* bprevalim(bprlim, mobaverage, nlstate, p, age, oldm, savm, dnewm, doldm, dsavm, ftolpl, ncvyearp, k); */
1.242 brouard 9297: bprevalim(bprlim, mobaverage, nlstate, p, age, ftolpl, ncvyearp, k, nres);
1.238 brouard 9298: }else if (mobilavproj == 0){
9299: 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);
9300: 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);
9301: exit(1);
9302: }else{
9303: /* bprevalim(bprlim, probs, nlstate, p, age, oldm, savm, dnewm, doldm, dsavm, ftolpl, ncvyearp, k); */
1.242 brouard 9304: bprevalim(bprlim, probs, nlstate, p, age, ftolpl, ncvyearp, k,nres);
1.238 brouard 9305: }
9306: fprintf(ficresplb,"%.0f ",age );
9307: for(j=1;j<=cptcoveff;j++)
9308: fprintf(ficresplb,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
9309: tot=0.;
9310: for(i=1; i<=nlstate;i++){
9311: tot += bprlim[i][i];
9312: fprintf(ficresplb," %.5f", bprlim[i][i]);
9313: }
9314: fprintf(ficresplb," %.3f %d\n", tot, *ncvyearp);
9315: } /* Age */
9316: /* was end of cptcod */
9317: } /* end of any combination */
9318: } /* end of nres */
1.218 brouard 9319: /* hBijx(p, bage, fage); */
9320: /* fclose(ficrespijb); */
9321:
9322: return 0;
1.217 brouard 9323: }
1.218 brouard 9324:
1.180 brouard 9325: int hPijx(double *p, int bage, int fage){
9326: /*------------- h Pij x at various ages ------------*/
9327:
9328: int stepsize;
9329: int agelim;
9330: int hstepm;
9331: int nhstepm;
1.235 brouard 9332: int h, i, i1, j, k, k4, nres=0;
1.180 brouard 9333:
9334: double agedeb;
9335: double ***p3mat;
9336:
1.201 brouard 9337: strcpy(filerespij,"PIJ_"); strcat(filerespij,fileresu);
1.180 brouard 9338: if((ficrespij=fopen(filerespij,"w"))==NULL) {
9339: printf("Problem with Pij resultfile: %s\n", filerespij); return 1;
9340: fprintf(ficlog,"Problem with Pij resultfile: %s\n", filerespij); return 1;
9341: }
9342: printf("Computing pij: result on file '%s' \n", filerespij);
9343: fprintf(ficlog,"Computing pij: result on file '%s' \n", filerespij);
9344:
9345: stepsize=(int) (stepm+YEARM-1)/YEARM;
9346: /*if (stepm<=24) stepsize=2;*/
9347:
9348: agelim=AGESUP;
9349: hstepm=stepsize*YEARM; /* Every year of age */
9350: hstepm=hstepm/stepm; /* Typically 2 years, = 2/6 months = 4 */
1.218 brouard 9351:
1.180 brouard 9352: /* hstepm=1; aff par mois*/
9353: pstamp(ficrespij);
9354: fprintf(ficrespij,"#****** h Pij x Probability to be in state j at age x+h being in i at x ");
1.227 brouard 9355: i1= pow(2,cptcoveff);
1.218 brouard 9356: /* for(cptcov=1,k=0;cptcov<=i1;cptcov++){ */
9357: /* /\*for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){*\/ */
9358: /* k=k+1; */
1.235 brouard 9359: for(nres=1; nres <= nresult; nres++) /* For each resultline */
9360: for(k=1; k<=i1;k++){
9361: if(TKresult[nres]!= k)
9362: continue;
1.183 brouard 9363: fprintf(ficrespij,"\n#****** ");
1.227 brouard 9364: for(j=1;j<=cptcoveff;j++)
1.198 brouard 9365: fprintf(ficrespij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
1.235 brouard 9366: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
9367: printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
9368: fprintf(ficrespij," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
9369: }
1.183 brouard 9370: fprintf(ficrespij,"******\n");
9371:
9372: for (agedeb=fage; agedeb>=bage; agedeb--){ /* If stepm=6 months */
9373: nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
9374: nhstepm = nhstepm/hstepm; /* Typically 40/4=10 */
9375:
9376: /* nhstepm=nhstepm*YEARM; aff par mois*/
1.180 brouard 9377:
1.183 brouard 9378: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
9379: oldm=oldms;savm=savms;
1.235 brouard 9380: hpxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k, nres);
1.183 brouard 9381: fprintf(ficrespij,"# Cov Agex agex+h hpijx with i,j=");
9382: for(i=1; i<=nlstate;i++)
9383: for(j=1; j<=nlstate+ndeath;j++)
9384: fprintf(ficrespij," %1d-%1d",i,j);
9385: fprintf(ficrespij,"\n");
9386: for (h=0; h<=nhstepm; h++){
9387: /*agedebphstep = agedeb + h*hstepm/YEARM*stepm;*/
9388: fprintf(ficrespij,"%d %3.f %3.f",k, agedeb, agedeb + h*hstepm/YEARM*stepm );
1.180 brouard 9389: for(i=1; i<=nlstate;i++)
9390: for(j=1; j<=nlstate+ndeath;j++)
1.183 brouard 9391: fprintf(ficrespij," %.5f", p3mat[i][j][h]);
1.180 brouard 9392: fprintf(ficrespij,"\n");
9393: }
1.183 brouard 9394: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
9395: fprintf(ficrespij,"\n");
9396: }
1.180 brouard 9397: /*}*/
9398: }
1.218 brouard 9399: return 0;
1.180 brouard 9400: }
1.218 brouard 9401:
9402: int hBijx(double *p, int bage, int fage, double ***prevacurrent){
1.217 brouard 9403: /*------------- h Bij x at various ages ------------*/
9404:
9405: int stepsize;
1.218 brouard 9406: /* int agelim; */
9407: int ageminl;
1.217 brouard 9408: int hstepm;
9409: int nhstepm;
1.238 brouard 9410: int h, i, i1, j, k, nres;
1.218 brouard 9411:
1.217 brouard 9412: double agedeb;
9413: double ***p3mat;
1.218 brouard 9414:
9415: strcpy(filerespijb,"PIJB_"); strcat(filerespijb,fileresu);
9416: if((ficrespijb=fopen(filerespijb,"w"))==NULL) {
9417: printf("Problem with Pij back resultfile: %s\n", filerespijb); return 1;
9418: fprintf(ficlog,"Problem with Pij back resultfile: %s\n", filerespijb); return 1;
9419: }
9420: printf("Computing pij back: result on file '%s' \n", filerespijb);
9421: fprintf(ficlog,"Computing pij back: result on file '%s' \n", filerespijb);
9422:
9423: stepsize=(int) (stepm+YEARM-1)/YEARM;
9424: /*if (stepm<=24) stepsize=2;*/
1.217 brouard 9425:
1.218 brouard 9426: /* agelim=AGESUP; */
9427: ageminl=30;
9428: hstepm=stepsize*YEARM; /* Every year of age */
9429: hstepm=hstepm/stepm; /* Typically 2 years, = 2/6 months = 4 */
9430:
9431: /* hstepm=1; aff par mois*/
9432: pstamp(ficrespijb);
9433: fprintf(ficrespijb,"#****** h Pij x Back Probability to be in state i at age x-h being in j at x ");
1.227 brouard 9434: i1= pow(2,cptcoveff);
1.218 brouard 9435: /* for(cptcov=1,k=0;cptcov<=i1;cptcov++){ */
9436: /* /\*for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){*\/ */
9437: /* k=k+1; */
1.238 brouard 9438: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
9439: for(k=1; k<=i1;k++){ /* For any combination of dummy covariates, fixed and varying */
9440: if(TKresult[nres]!= k)
9441: continue;
9442: fprintf(ficrespijb,"\n#****** ");
9443: for(j=1;j<=cptcoveff;j++)
9444: fprintf(ficrespijb,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
9445: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
9446: fprintf(ficrespijb," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
9447: }
9448: fprintf(ficrespijb,"******\n");
9449: if(invalidvarcomb[k]){
9450: fprintf(ficrespijb,"\n#Combination (%d) ignored because no cases \n",k);
9451: continue;
9452: }
9453:
9454: /* for (agedeb=fage; agedeb>=bage; agedeb--){ /\* If stepm=6 months *\/ */
9455: for (agedeb=bage; agedeb<=fage; agedeb++){ /* If stepm=6 months and estepm=24 (2 years) */
9456: /* nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); /\* Typically 20 years = 20*12/6=40 *\/ */
9457: nhstepm=(int) rint((agedeb-ageminl)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
9458: nhstepm = nhstepm/hstepm; /* Typically 40/4=10, because estepm=24 stepm=6 => hstepm=24/6=4 */
9459:
9460: /* nhstepm=nhstepm*YEARM; aff par mois*/
9461:
9462: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
9463: /* oldm=oldms;savm=savms; */
9464: /* hbxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k); */
9465: hbxij(p3mat,nhstepm,agedeb,hstepm,p,prevacurrent,nlstate,stepm, k);
9466: /* hbxij(p3mat,nhstepm,agedeb,hstepm,p,prevacurrent,nlstate,stepm,oldm,savm, dnewm, doldm, dsavm, k); */
9467: fprintf(ficrespijb,"# Cov Agex agex-h hpijx with i,j=");
1.217 brouard 9468: for(i=1; i<=nlstate;i++)
9469: for(j=1; j<=nlstate+ndeath;j++)
1.238 brouard 9470: fprintf(ficrespijb," %1d-%1d",i,j);
1.217 brouard 9471: fprintf(ficrespijb,"\n");
1.238 brouard 9472: for (h=0; h<=nhstepm; h++){
9473: /*agedebphstep = agedeb + h*hstepm/YEARM*stepm;*/
9474: fprintf(ficrespijb,"%d %3.f %3.f",k, agedeb, agedeb - h*hstepm/YEARM*stepm );
9475: /* fprintf(ficrespijb,"%d %3.f %3.f",k, agedeb, agedeb + h*hstepm/YEARM*stepm ); */
9476: for(i=1; i<=nlstate;i++)
9477: for(j=1; j<=nlstate+ndeath;j++)
9478: fprintf(ficrespijb," %.5f", p3mat[i][j][h]);
9479: fprintf(ficrespijb,"\n");
9480: }
9481: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
9482: fprintf(ficrespijb,"\n");
9483: } /* end age deb */
9484: } /* end combination */
9485: } /* end nres */
1.218 brouard 9486: return 0;
9487: } /* hBijx */
1.217 brouard 9488:
1.180 brouard 9489:
1.136 brouard 9490: /***********************************************/
9491: /**************** Main Program *****************/
9492: /***********************************************/
9493:
9494: int main(int argc, char *argv[])
9495: {
9496: #ifdef GSL
9497: const gsl_multimin_fminimizer_type *T;
9498: size_t iteri = 0, it;
9499: int rval = GSL_CONTINUE;
9500: int status = GSL_SUCCESS;
9501: double ssval;
9502: #endif
9503: int movingaverage(double ***probs, double bage,double fage, double ***mobaverage, int mobilav);
1.164 brouard 9504: int i,j, k, n=MAXN,iter=0,m,size=100, cptcod;
1.209 brouard 9505: int ncvyear=0; /* Number of years needed for the period prevalence to converge */
1.164 brouard 9506: int jj, ll, li, lj, lk;
1.136 brouard 9507: int numlinepar=0; /* Current linenumber of parameter file */
1.197 brouard 9508: int num_filled;
1.136 brouard 9509: int itimes;
9510: int NDIM=2;
9511: int vpopbased=0;
1.235 brouard 9512: int nres=0;
1.136 brouard 9513:
1.164 brouard 9514: char ca[32], cb[32];
1.136 brouard 9515: /* FILE *fichtm; *//* Html File */
9516: /* FILE *ficgp;*/ /*Gnuplot File */
9517: struct stat info;
1.191 brouard 9518: double agedeb=0.;
1.194 brouard 9519:
9520: double ageminpar=AGEOVERFLOW,agemin=AGEOVERFLOW, agemaxpar=-AGEOVERFLOW, agemax=-AGEOVERFLOW;
1.219 brouard 9521: double ageminout=-AGEOVERFLOW,agemaxout=AGEOVERFLOW; /* Smaller Age range redefined after movingaverage */
1.136 brouard 9522:
1.165 brouard 9523: double fret;
1.191 brouard 9524: double dum=0.; /* Dummy variable */
1.136 brouard 9525: double ***p3mat;
1.218 brouard 9526: /* double ***mobaverage; */
1.164 brouard 9527:
9528: char line[MAXLINE];
1.197 brouard 9529: char path[MAXLINE],pathc[MAXLINE],pathcd[MAXLINE],pathtot[MAXLINE];
9530:
1.234 brouard 9531: char modeltemp[MAXLINE];
1.230 brouard 9532: char resultline[MAXLINE];
9533:
1.136 brouard 9534: char pathr[MAXLINE], pathimach[MAXLINE];
1.164 brouard 9535: char *tok, *val; /* pathtot */
1.136 brouard 9536: int firstobs=1, lastobs=10;
1.195 brouard 9537: int c, h , cpt, c2;
1.191 brouard 9538: int jl=0;
9539: int i1, j1, jk, stepsize=0;
1.194 brouard 9540: int count=0;
9541:
1.164 brouard 9542: int *tab;
1.136 brouard 9543: int mobilavproj=0 , prevfcast=0 ; /* moving average of prev, If prevfcast=1 prevalence projection */
1.217 brouard 9544: int backcast=0;
1.136 brouard 9545: int mobilav=0,popforecast=0;
1.191 brouard 9546: int hstepm=0, nhstepm=0;
1.136 brouard 9547: int agemortsup;
9548: float sumlpop=0.;
9549: double jprev1=1, mprev1=1,anprev1=2000,jprev2=1, mprev2=1,anprev2=2000;
9550: double jpyram=1, mpyram=1,anpyram=2000,jpyram1=1, mpyram1=1,anpyram1=2000;
9551:
1.191 brouard 9552: double bage=0, fage=110., age, agelim=0., agebase=0.;
1.136 brouard 9553: double ftolpl=FTOL;
9554: double **prlim;
1.217 brouard 9555: double **bprlim;
1.136 brouard 9556: double ***param; /* Matrix of parameters */
9557: double *p;
9558: double **matcov; /* Matrix of covariance */
1.203 brouard 9559: double **hess; /* Hessian matrix */
1.136 brouard 9560: double ***delti3; /* Scale */
9561: double *delti; /* Scale */
9562: double ***eij, ***vareij;
9563: double **varpl; /* Variances of prevalence limits by age */
9564: double *epj, vepp;
1.164 brouard 9565:
1.136 brouard 9566: double dateprev1, dateprev2,jproj1=1,mproj1=1,anproj1=2000,jproj2=1,mproj2=1,anproj2=2000;
1.217 brouard 9567: double jback1=1,mback1=1,anback1=2000,jback2=1,mback2=1,anback2=2000;
9568:
1.136 brouard 9569: double **ximort;
1.145 brouard 9570: char *alph[]={"a","a","b","c","d","e"}, str[4]="1234";
1.136 brouard 9571: int *dcwave;
9572:
1.164 brouard 9573: char z[1]="c";
1.136 brouard 9574:
9575: /*char *strt;*/
9576: char strtend[80];
1.126 brouard 9577:
1.164 brouard 9578:
1.126 brouard 9579: /* setlocale (LC_ALL, ""); */
9580: /* bindtextdomain (PACKAGE, LOCALEDIR); */
9581: /* textdomain (PACKAGE); */
9582: /* setlocale (LC_CTYPE, ""); */
9583: /* setlocale (LC_MESSAGES, ""); */
9584:
9585: /* gettimeofday(&start_time, (struct timezone*)0); */ /* at first time */
1.157 brouard 9586: rstart_time = time(NULL);
9587: /* (void) gettimeofday(&start_time,&tzp);*/
9588: start_time = *localtime(&rstart_time);
1.126 brouard 9589: curr_time=start_time;
1.157 brouard 9590: /*tml = *localtime(&start_time.tm_sec);*/
9591: /* strcpy(strstart,asctime(&tml)); */
9592: strcpy(strstart,asctime(&start_time));
1.126 brouard 9593:
9594: /* printf("Localtime (at start)=%s",strstart); */
1.157 brouard 9595: /* tp.tm_sec = tp.tm_sec +86400; */
9596: /* tm = *localtime(&start_time.tm_sec); */
1.126 brouard 9597: /* tmg.tm_year=tmg.tm_year +dsign*dyear; */
9598: /* tmg.tm_mon=tmg.tm_mon +dsign*dmonth; */
9599: /* tmg.tm_hour=tmg.tm_hour + 1; */
1.157 brouard 9600: /* tp.tm_sec = mktime(&tmg); */
1.126 brouard 9601: /* strt=asctime(&tmg); */
9602: /* printf("Time(after) =%s",strstart); */
9603: /* (void) time (&time_value);
9604: * printf("time=%d,t-=%d\n",time_value,time_value-86400);
9605: * tm = *localtime(&time_value);
9606: * strstart=asctime(&tm);
9607: * printf("tim_value=%d,asctime=%s\n",time_value,strstart);
9608: */
9609:
9610: nberr=0; /* Number of errors and warnings */
9611: nbwarn=0;
1.184 brouard 9612: #ifdef WIN32
9613: _getcwd(pathcd, size);
9614: #else
1.126 brouard 9615: getcwd(pathcd, size);
1.184 brouard 9616: #endif
1.191 brouard 9617: syscompilerinfo(0);
1.196 brouard 9618: printf("\nIMaCh version %s, %s\n%s",version, copyright, fullversion);
1.126 brouard 9619: if(argc <=1){
9620: printf("\nEnter the parameter file name: ");
1.205 brouard 9621: if(!fgets(pathr,FILENAMELENGTH,stdin)){
9622: printf("ERROR Empty parameter file name\n");
9623: goto end;
9624: }
1.126 brouard 9625: i=strlen(pathr);
9626: if(pathr[i-1]=='\n')
9627: pathr[i-1]='\0';
1.156 brouard 9628: i=strlen(pathr);
1.205 brouard 9629: if(i >= 1 && pathr[i-1]==' ') {/* This may happen when dragging on oS/X! */
1.156 brouard 9630: pathr[i-1]='\0';
1.205 brouard 9631: }
9632: i=strlen(pathr);
9633: if( i==0 ){
9634: printf("ERROR Empty parameter file name\n");
9635: goto end;
9636: }
9637: for (tok = pathr; tok != NULL; ){
1.126 brouard 9638: printf("Pathr |%s|\n",pathr);
9639: while ((val = strsep(&tok, "\"" )) != NULL && *val == '\0');
9640: printf("val= |%s| pathr=%s\n",val,pathr);
9641: strcpy (pathtot, val);
9642: if(pathr[0] == '\0') break; /* Dirty */
9643: }
9644: }
9645: else{
9646: strcpy(pathtot,argv[1]);
9647: }
9648: /*if(getcwd(pathcd, MAXLINE)!= NULL)printf ("Error pathcd\n");*/
9649: /*cygwin_split_path(pathtot,path,optionfile);
9650: printf("pathtot=%s, path=%s, optionfile=%s\n",pathtot,path,optionfile);*/
9651: /* cutv(path,optionfile,pathtot,'\\');*/
9652:
9653: /* Split argv[0], imach program to get pathimach */
9654: printf("\nargv[0]=%s argv[1]=%s, \n",argv[0],argv[1]);
9655: split(argv[0],pathimach,optionfile,optionfilext,optionfilefiname);
9656: printf("\nargv[0]=%s pathimach=%s, \noptionfile=%s \noptionfilext=%s \noptionfilefiname=%s\n",argv[0],pathimach,optionfile,optionfilext,optionfilefiname);
9657: /* strcpy(pathimach,argv[0]); */
9658: /* Split argv[1]=pathtot, parameter file name to get path, optionfile, extension and name */
9659: split(pathtot,path,optionfile,optionfilext,optionfilefiname);
9660: printf("\npathtot=%s,\npath=%s,\noptionfile=%s \noptionfilext=%s \noptionfilefiname=%s\n",pathtot,path,optionfile,optionfilext,optionfilefiname);
1.184 brouard 9661: #ifdef WIN32
9662: _chdir(path); /* Can be a relative path */
9663: if(_getcwd(pathcd,MAXLINE) > 0) /* So pathcd is the full path */
9664: #else
1.126 brouard 9665: chdir(path); /* Can be a relative path */
1.184 brouard 9666: if (getcwd(pathcd, MAXLINE) > 0) /* So pathcd is the full path */
9667: #endif
9668: printf("Current directory %s!\n",pathcd);
1.126 brouard 9669: strcpy(command,"mkdir ");
9670: strcat(command,optionfilefiname);
9671: if((outcmd=system(command)) != 0){
1.169 brouard 9672: printf("Directory already exists (or can't create it) %s%s, err=%d\n",path,optionfilefiname,outcmd);
1.126 brouard 9673: /* fprintf(ficlog,"Problem creating directory %s%s\n",path,optionfilefiname); */
9674: /* fclose(ficlog); */
9675: /* exit(1); */
9676: }
9677: /* if((imk=mkdir(optionfilefiname))<0){ */
9678: /* perror("mkdir"); */
9679: /* } */
9680:
9681: /*-------- arguments in the command line --------*/
9682:
1.186 brouard 9683: /* Main Log file */
1.126 brouard 9684: strcat(filelog, optionfilefiname);
9685: strcat(filelog,".log"); /* */
9686: if((ficlog=fopen(filelog,"w"))==NULL) {
9687: printf("Problem with logfile %s\n",filelog);
9688: goto end;
9689: }
9690: fprintf(ficlog,"Log filename:%s\n",filelog);
1.197 brouard 9691: fprintf(ficlog,"Version %s %s",version,fullversion);
1.126 brouard 9692: fprintf(ficlog,"\nEnter the parameter file name: \n");
9693: fprintf(ficlog,"pathimach=%s\npathtot=%s\n\
9694: path=%s \n\
9695: optionfile=%s\n\
9696: optionfilext=%s\n\
1.156 brouard 9697: optionfilefiname='%s'\n",pathimach,pathtot,path,optionfile,optionfilext,optionfilefiname);
1.126 brouard 9698:
1.197 brouard 9699: syscompilerinfo(1);
1.167 brouard 9700:
1.126 brouard 9701: printf("Local time (at start):%s",strstart);
9702: fprintf(ficlog,"Local time (at start): %s",strstart);
9703: fflush(ficlog);
9704: /* (void) gettimeofday(&curr_time,&tzp); */
1.157 brouard 9705: /* printf("Elapsed time %d\n", asc_diff_time(curr_time.tm_sec-start_time.tm_sec,tmpout)); */
1.126 brouard 9706:
9707: /* */
9708: strcpy(fileres,"r");
9709: strcat(fileres, optionfilefiname);
1.201 brouard 9710: strcat(fileresu, optionfilefiname); /* Without r in front */
1.126 brouard 9711: strcat(fileres,".txt"); /* Other files have txt extension */
1.201 brouard 9712: strcat(fileresu,".txt"); /* Other files have txt extension */
1.126 brouard 9713:
1.186 brouard 9714: /* Main ---------arguments file --------*/
1.126 brouard 9715:
9716: if((ficpar=fopen(optionfile,"r"))==NULL) {
1.155 brouard 9717: printf("Problem with optionfile '%s' with errno='%s'\n",optionfile,strerror(errno));
9718: fprintf(ficlog,"Problem with optionfile '%s' with errno='%s'\n",optionfile,strerror(errno));
1.126 brouard 9719: fflush(ficlog);
1.149 brouard 9720: /* goto end; */
9721: exit(70);
1.126 brouard 9722: }
9723:
9724:
9725:
9726: strcpy(filereso,"o");
1.201 brouard 9727: strcat(filereso,fileresu);
1.126 brouard 9728: if((ficparo=fopen(filereso,"w"))==NULL) { /* opened on subdirectory */
9729: printf("Problem with Output resultfile: %s\n", filereso);
9730: fprintf(ficlog,"Problem with Output resultfile: %s\n", filereso);
9731: fflush(ficlog);
9732: goto end;
9733: }
9734:
9735: /* Reads comments: lines beginning with '#' */
9736: numlinepar=0;
1.197 brouard 9737:
9738: /* First parameter line */
9739: while(fgets(line, MAXLINE, ficpar)) {
9740: /* If line starts with a # it is a comment */
9741: if (line[0] == '#') {
9742: numlinepar++;
9743: fputs(line,stdout);
9744: fputs(line,ficparo);
9745: fputs(line,ficlog);
9746: continue;
9747: }else
9748: break;
9749: }
9750: if((num_filled=sscanf(line,"title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", \
9751: title, datafile, &lastobs, &firstpass,&lastpass)) !=EOF){
9752: if (num_filled != 5) {
9753: printf("Should be 5 parameters\n");
9754: }
1.126 brouard 9755: numlinepar++;
1.197 brouard 9756: printf("title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", title, datafile, lastobs, firstpass,lastpass);
9757: }
9758: /* Second parameter line */
9759: while(fgets(line, MAXLINE, ficpar)) {
9760: /* If line starts with a # it is a comment */
9761: if (line[0] == '#') {
9762: numlinepar++;
9763: fputs(line,stdout);
9764: fputs(line,ficparo);
9765: fputs(line,ficlog);
9766: continue;
9767: }else
9768: break;
9769: }
1.223 brouard 9770: 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", \
9771: &ftol, &stepm, &ncovcol, &nqv, &ntv, &nqtv, &nlstate, &ndeath, &maxwav, &mle, &weightopt)) !=EOF){
9772: if (num_filled != 11) {
9773: 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 9774: printf("but line=%s\n",line);
1.197 brouard 9775: }
1.223 brouard 9776: 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 9777: }
1.203 brouard 9778: /* ftolpl=6*ftol*1.e5; /\* 6.e-3 make convergences in less than 80 loops for the prevalence limit *\/ */
1.209 brouard 9779: /*ftolpl=6.e-4; *//* 6.e-3 make convergences in less than 80 loops for the prevalence limit */
1.197 brouard 9780: /* Third parameter line */
9781: while(fgets(line, MAXLINE, ficpar)) {
9782: /* If line starts with a # it is a comment */
9783: if (line[0] == '#') {
9784: numlinepar++;
9785: fputs(line,stdout);
9786: fputs(line,ficparo);
9787: fputs(line,ficlog);
9788: continue;
9789: }else
9790: break;
9791: }
1.201 brouard 9792: if((num_filled=sscanf(line,"model=1+age%[^.\n]", model)) !=EOF){
9793: if (num_filled == 0)
9794: model[0]='\0';
9795: else if (num_filled != 1){
1.197 brouard 9796: printf("ERROR %d: Model should be at minimum 'model=1+age.' %s\n",num_filled, line);
9797: fprintf(ficlog,"ERROR %d: Model should be at minimum 'model=1+age.' %s\n",num_filled, line);
9798: model[0]='\0';
9799: goto end;
9800: }
9801: else{
9802: if (model[0]=='+'){
9803: for(i=1; i<=strlen(model);i++)
9804: modeltemp[i-1]=model[i];
1.201 brouard 9805: strcpy(model,modeltemp);
1.197 brouard 9806: }
9807: }
1.199 brouard 9808: /* printf(" model=1+age%s modeltemp= %s, model=%s\n",model, modeltemp, model);fflush(stdout); */
1.203 brouard 9809: printf("model=1+age+%s\n",model);fflush(stdout);
1.197 brouard 9810: }
9811: /* 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); */
9812: /* numlinepar=numlinepar+3; /\* In general *\/ */
9813: /* 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 9814: 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);
9815: 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 9816: fflush(ficlog);
1.190 brouard 9817: /* if(model[0]=='#'|| model[0]== '\0'){ */
9818: if(model[0]=='#'){
1.187 brouard 9819: printf("Error in 'model' line: model should start with 'model=1+age+' and end with '.' \n \
9820: 'model=1+age+.' or 'model=1+age+V1.' or 'model=1+age+age*age+V1+V1*age.' or \n \
9821: 'model=1+age+V1+V2.' or 'model=1+age+V1+V2+V1*V2.' etc. \n"); \
9822: if(mle != -1){
9823: printf("Fix the model line and run imach with mle=-1 to get a correct template of the parameter file.\n");
9824: exit(1);
9825: }
9826: }
1.126 brouard 9827: while((c=getc(ficpar))=='#' && c!= EOF){
9828: ungetc(c,ficpar);
9829: fgets(line, MAXLINE, ficpar);
9830: numlinepar++;
1.195 brouard 9831: if(line[1]=='q'){ /* This #q will quit imach (the answer is q) */
9832: z[0]=line[1];
9833: }
9834: /* printf("****line [1] = %c \n",line[1]); */
1.141 brouard 9835: fputs(line, stdout);
9836: //puts(line);
1.126 brouard 9837: fputs(line,ficparo);
9838: fputs(line,ficlog);
9839: }
9840: ungetc(c,ficpar);
9841:
9842:
1.145 brouard 9843: covar=matrix(0,NCOVMAX,1,n); /**< used in readdata */
1.225 brouard 9844: coqvar=matrix(1,nqv,1,n); /**< Fixed quantitative covariate */
1.233 brouard 9845: cotvar=ma3x(1,maxwav,1,ntv+nqtv,1,n); /**< Time varying covariate (dummy and quantitative)*/
1.225 brouard 9846: cotqvar=ma3x(1,maxwav,1,nqtv,1,n); /**< Time varying quantitative covariate */
1.136 brouard 9847: cptcovn=0; /*Number of covariates, i.e. number of '+' in model statement plus one, indepently of n in Vn*/
9848: /* v1+v2+v3+v2*v4+v5*age makes cptcovn = 5
9849: v1+v2*age+v2*v3 makes cptcovn = 3
9850: */
9851: if (strlen(model)>1)
1.187 brouard 9852: 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 9853: else
1.187 brouard 9854: ncovmodel=2; /* Constant and age */
1.133 brouard 9855: nforce= (nlstate+ndeath-1)*nlstate; /* Number of forces ij from state i to j */
9856: npar= nforce*ncovmodel; /* Number of parameters like aij*/
1.131 brouard 9857: if(npar >MAXPARM || nlstate >NLSTATEMAX || ndeath >NDEATHMAX || ncovmodel>NCOVMAX){
9858: 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);
9859: 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);
9860: fflush(stdout);
9861: fclose (ficlog);
9862: goto end;
9863: }
1.126 brouard 9864: delti3= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
9865: delti=delti3[1][1];
9866: /*delti=vector(1,npar); *//* Scale of each paramater (output from hesscov)*/
9867: if(mle==-1){ /* Print a wizard for help writing covariance matrix */
9868: prwizard(ncovmodel, nlstate, ndeath, model, ficparo);
1.191 brouard 9869: printf(" You chose mle=-1, look at file %s for a template of covariance matrix \n",filereso);
9870: fprintf(ficlog," You chose mle=-1, look at file %s for a template of covariance matrix \n",filereso);
1.126 brouard 9871: free_ma3x(delti3,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
9872: fclose (ficparo);
9873: fclose (ficlog);
9874: goto end;
9875: exit(0);
1.220 brouard 9876: } else if(mle==-5) { /* Main Wizard */
1.126 brouard 9877: prwizard(ncovmodel, nlstate, ndeath, model, ficparo);
1.192 brouard 9878: printf(" You chose mle=-3, look at file %s for a template of covariance matrix \n",filereso);
9879: fprintf(ficlog," You chose mle=-3, look at file %s for a template of covariance matrix \n",filereso);
1.126 brouard 9880: param= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
9881: matcov=matrix(1,npar,1,npar);
1.203 brouard 9882: hess=matrix(1,npar,1,npar);
1.220 brouard 9883: } else{ /* Begin of mle != -1 or -5 */
1.145 brouard 9884: /* Read guessed parameters */
1.126 brouard 9885: /* Reads comments: lines beginning with '#' */
9886: while((c=getc(ficpar))=='#' && c!= EOF){
9887: ungetc(c,ficpar);
9888: fgets(line, MAXLINE, ficpar);
9889: numlinepar++;
1.141 brouard 9890: fputs(line,stdout);
1.126 brouard 9891: fputs(line,ficparo);
9892: fputs(line,ficlog);
9893: }
9894: ungetc(c,ficpar);
9895:
9896: param= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
9897: for(i=1; i <=nlstate; i++){
1.234 brouard 9898: j=0;
1.126 brouard 9899: for(jj=1; jj <=nlstate+ndeath; jj++){
1.234 brouard 9900: if(jj==i) continue;
9901: j++;
9902: fscanf(ficpar,"%1d%1d",&i1,&j1);
9903: if ((i1 != i) || (j1 != jj)){
9904: printf("Error in line parameters number %d, %1d%1d instead of %1d%1d \n \
1.126 brouard 9905: It might be a problem of design; if ncovcol and the model are correct\n \
9906: run imach with mle=-1 to get a correct template of the parameter file.\n",numlinepar, i,j, i1, j1);
1.234 brouard 9907: exit(1);
9908: }
9909: fprintf(ficparo,"%1d%1d",i1,j1);
9910: if(mle==1)
9911: printf("%1d%1d",i,jj);
9912: fprintf(ficlog,"%1d%1d",i,jj);
9913: for(k=1; k<=ncovmodel;k++){
9914: fscanf(ficpar," %lf",¶m[i][j][k]);
9915: if(mle==1){
9916: printf(" %lf",param[i][j][k]);
9917: fprintf(ficlog," %lf",param[i][j][k]);
9918: }
9919: else
9920: fprintf(ficlog," %lf",param[i][j][k]);
9921: fprintf(ficparo," %lf",param[i][j][k]);
9922: }
9923: fscanf(ficpar,"\n");
9924: numlinepar++;
9925: if(mle==1)
9926: printf("\n");
9927: fprintf(ficlog,"\n");
9928: fprintf(ficparo,"\n");
1.126 brouard 9929: }
9930: }
9931: fflush(ficlog);
1.234 brouard 9932:
1.145 brouard 9933: /* Reads scales values */
1.126 brouard 9934: p=param[1][1];
9935:
9936: /* Reads comments: lines beginning with '#' */
9937: while((c=getc(ficpar))=='#' && c!= EOF){
9938: ungetc(c,ficpar);
9939: fgets(line, MAXLINE, ficpar);
9940: numlinepar++;
1.141 brouard 9941: fputs(line,stdout);
1.126 brouard 9942: fputs(line,ficparo);
9943: fputs(line,ficlog);
9944: }
9945: ungetc(c,ficpar);
9946:
9947: for(i=1; i <=nlstate; i++){
9948: for(j=1; j <=nlstate+ndeath-1; j++){
1.234 brouard 9949: fscanf(ficpar,"%1d%1d",&i1,&j1);
9950: if ( (i1-i) * (j1-j) != 0){
9951: printf("Error in line parameters number %d, %1d%1d instead of %1d%1d \n",numlinepar, i,j, i1, j1);
9952: exit(1);
9953: }
9954: printf("%1d%1d",i,j);
9955: fprintf(ficparo,"%1d%1d",i1,j1);
9956: fprintf(ficlog,"%1d%1d",i1,j1);
9957: for(k=1; k<=ncovmodel;k++){
9958: fscanf(ficpar,"%le",&delti3[i][j][k]);
9959: printf(" %le",delti3[i][j][k]);
9960: fprintf(ficparo," %le",delti3[i][j][k]);
9961: fprintf(ficlog," %le",delti3[i][j][k]);
9962: }
9963: fscanf(ficpar,"\n");
9964: numlinepar++;
9965: printf("\n");
9966: fprintf(ficparo,"\n");
9967: fprintf(ficlog,"\n");
1.126 brouard 9968: }
9969: }
9970: fflush(ficlog);
1.234 brouard 9971:
1.145 brouard 9972: /* Reads covariance matrix */
1.126 brouard 9973: delti=delti3[1][1];
1.220 brouard 9974:
9975:
1.126 brouard 9976: /* 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 9977:
1.126 brouard 9978: /* Reads comments: lines beginning with '#' */
9979: while((c=getc(ficpar))=='#' && c!= EOF){
9980: ungetc(c,ficpar);
9981: fgets(line, MAXLINE, ficpar);
9982: numlinepar++;
1.141 brouard 9983: fputs(line,stdout);
1.126 brouard 9984: fputs(line,ficparo);
9985: fputs(line,ficlog);
9986: }
9987: ungetc(c,ficpar);
1.220 brouard 9988:
1.126 brouard 9989: matcov=matrix(1,npar,1,npar);
1.203 brouard 9990: hess=matrix(1,npar,1,npar);
1.131 brouard 9991: for(i=1; i <=npar; i++)
9992: for(j=1; j <=npar; j++) matcov[i][j]=0.;
1.220 brouard 9993:
1.194 brouard 9994: /* Scans npar lines */
1.126 brouard 9995: for(i=1; i <=npar; i++){
1.226 brouard 9996: count=fscanf(ficpar,"%1d%1d%d",&i1,&j1,&jk);
1.194 brouard 9997: if(count != 3){
1.226 brouard 9998: printf("Error! Error in parameter file %s at line %d after line starting with %1d%1d%1d\n\
1.194 brouard 9999: This is probably because your covariance matrix doesn't \n contain exactly %d lines corresponding to your model line '1+age+%s'.\n\
10000: Please run with mle=-1 to get a correct covariance matrix.\n",optionfile,numlinepar, i1,j1,jk, npar, model);
1.226 brouard 10001: fprintf(ficlog,"Error! Error in parameter file %s at line %d after line starting with %1d%1d%1d\n\
1.194 brouard 10002: This is probably because your covariance matrix doesn't \n contain exactly %d lines corresponding to your model line '1+age+%s'.\n\
10003: Please run with mle=-1 to get a correct covariance matrix.\n",optionfile,numlinepar, i1,j1,jk, npar, model);
1.226 brouard 10004: exit(1);
1.220 brouard 10005: }else{
1.226 brouard 10006: if(mle==1)
10007: printf("%1d%1d%d",i1,j1,jk);
10008: }
10009: fprintf(ficlog,"%1d%1d%d",i1,j1,jk);
10010: fprintf(ficparo,"%1d%1d%d",i1,j1,jk);
1.126 brouard 10011: for(j=1; j <=i; j++){
1.226 brouard 10012: fscanf(ficpar," %le",&matcov[i][j]);
10013: if(mle==1){
10014: printf(" %.5le",matcov[i][j]);
10015: }
10016: fprintf(ficlog," %.5le",matcov[i][j]);
10017: fprintf(ficparo," %.5le",matcov[i][j]);
1.126 brouard 10018: }
10019: fscanf(ficpar,"\n");
10020: numlinepar++;
10021: if(mle==1)
1.220 brouard 10022: printf("\n");
1.126 brouard 10023: fprintf(ficlog,"\n");
10024: fprintf(ficparo,"\n");
10025: }
1.194 brouard 10026: /* End of read covariance matrix npar lines */
1.126 brouard 10027: for(i=1; i <=npar; i++)
10028: for(j=i+1;j<=npar;j++)
1.226 brouard 10029: matcov[i][j]=matcov[j][i];
1.126 brouard 10030:
10031: if(mle==1)
10032: printf("\n");
10033: fprintf(ficlog,"\n");
10034:
10035: fflush(ficlog);
10036:
10037: /*-------- Rewriting parameter file ----------*/
10038: strcpy(rfileres,"r"); /* "Rparameterfile */
10039: strcat(rfileres,optionfilefiname); /* Parameter file first name*/
10040: strcat(rfileres,"."); /* */
10041: strcat(rfileres,optionfilext); /* Other files have txt extension */
10042: if((ficres =fopen(rfileres,"w"))==NULL) {
1.201 brouard 10043: printf("Problem writing new parameter file: %s\n", rfileres);goto end;
10044: fprintf(ficlog,"Problem writing new parameter file: %s\n", rfileres);goto end;
1.126 brouard 10045: }
10046: fprintf(ficres,"#%s\n",version);
10047: } /* End of mle != -3 */
1.218 brouard 10048:
1.186 brouard 10049: /* Main data
10050: */
1.126 brouard 10051: n= lastobs;
10052: num=lvector(1,n);
10053: moisnais=vector(1,n);
10054: annais=vector(1,n);
10055: moisdc=vector(1,n);
10056: andc=vector(1,n);
1.220 brouard 10057: weight=vector(1,n);
1.126 brouard 10058: agedc=vector(1,n);
10059: cod=ivector(1,n);
1.220 brouard 10060: for(i=1;i<=n;i++){
1.234 brouard 10061: num[i]=0;
10062: moisnais[i]=0;
10063: annais[i]=0;
10064: moisdc[i]=0;
10065: andc[i]=0;
10066: agedc[i]=0;
10067: cod[i]=0;
10068: weight[i]=1.0; /* Equal weights, 1 by default */
10069: }
1.126 brouard 10070: mint=matrix(1,maxwav,1,n);
10071: anint=matrix(1,maxwav,1,n);
1.131 brouard 10072: s=imatrix(1,maxwav+1,1,n); /* s[i][j] health state for wave i and individual j */
1.126 brouard 10073: tab=ivector(1,NCOVMAX);
1.144 brouard 10074: ncodemax=ivector(1,NCOVMAX); /* Number of code per covariate; if O and 1 only, 2**ncov; V1+V2+V3+V4=>16 */
1.192 brouard 10075: 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 10076:
1.136 brouard 10077: /* Reads data from file datafile */
10078: if (readdata(datafile, firstobs, lastobs, &imx)==1)
10079: goto end;
10080:
10081: /* Calculation of the number of parameters from char model */
1.234 brouard 10082: /* modelsav=V2+V1+V4+age*V3 strb=age*V3 stra=V2+V1+V4
1.137 brouard 10083: k=4 (age*V3) Tvar[k=4]= 3 (from V3) Tag[cptcovage=1]=4
10084: k=3 V4 Tvar[k=3]= 4 (from V4)
10085: k=2 V1 Tvar[k=2]= 1 (from V1)
10086: k=1 Tvar[1]=2 (from V2)
1.234 brouard 10087: */
10088:
10089: Tvar=ivector(1,NCOVMAX); /* Was 15 changed to NCOVMAX. */
10090: TvarsDind=ivector(1,NCOVMAX); /* */
10091: TvarsD=ivector(1,NCOVMAX); /* */
10092: TvarsQind=ivector(1,NCOVMAX); /* */
10093: TvarsQ=ivector(1,NCOVMAX); /* */
1.232 brouard 10094: TvarF=ivector(1,NCOVMAX); /* */
10095: TvarFind=ivector(1,NCOVMAX); /* */
10096: TvarV=ivector(1,NCOVMAX); /* */
10097: TvarVind=ivector(1,NCOVMAX); /* */
10098: TvarA=ivector(1,NCOVMAX); /* */
10099: TvarAind=ivector(1,NCOVMAX); /* */
1.231 brouard 10100: TvarFD=ivector(1,NCOVMAX); /* */
10101: TvarFDind=ivector(1,NCOVMAX); /* */
10102: TvarFQ=ivector(1,NCOVMAX); /* */
10103: TvarFQind=ivector(1,NCOVMAX); /* */
10104: TvarVD=ivector(1,NCOVMAX); /* */
10105: TvarVDind=ivector(1,NCOVMAX); /* */
10106: TvarVQ=ivector(1,NCOVMAX); /* */
10107: TvarVQind=ivector(1,NCOVMAX); /* */
10108:
1.230 brouard 10109: Tvalsel=vector(1,NCOVMAX); /* */
1.233 brouard 10110: Tvarsel=ivector(1,NCOVMAX); /* */
1.226 brouard 10111: Typevar=ivector(-1,NCOVMAX); /* -1 to 2 */
10112: Fixed=ivector(-1,NCOVMAX); /* -1 to 3 */
10113: Dummy=ivector(-1,NCOVMAX); /* -1 to 3 */
1.137 brouard 10114: /* V2+V1+V4+age*V3 is a model with 4 covariates (3 plus signs).
10115: For each model-covariate stores the data-covariate id. Tvar[1]=2, Tvar[2]=1, Tvar[3]=4,
10116: Tvar[4=age*V3] is 3 and 'age' is recorded in Tage.
10117: */
10118: /* For model-covariate k tells which data-covariate to use but
10119: because this model-covariate is a construction we invent a new column
10120: ncovcol + k1
10121: If already ncovcol=4 and model=V2+V1+V1*V4+age*V3
10122: Tvar[3=V1*V4]=4+1 etc */
1.227 brouard 10123: Tprod=ivector(1,NCOVMAX); /* Gives the k position of the k1 product */
10124: Tposprod=ivector(1,NCOVMAX); /* Gives the k1 product from the k position */
1.137 brouard 10125: /* Tprod[k1=1]=3(=V1*V4) for V2+V1+V1*V4+age*V3
10126: if V2+V1+V1*V4+age*V3+V3*V2 TProd[k1=2]=5 (V3*V2)
1.227 brouard 10127: Tposprod[k]=k1 , Tposprod[3]=1, Tposprod[5]=2
1.137 brouard 10128: */
1.145 brouard 10129: Tvaraff=ivector(1,NCOVMAX); /* Unclear */
10130: 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 10131: * For V3*V2 (in V2+V1+V1*V4+age*V3+V3*V2), V3*V2 position is 2nd.
10132: * Tvard[k1=2][1]=3 (V3) Tvard[k1=2][2]=2(V2) */
1.145 brouard 10133: Tage=ivector(1,NCOVMAX); /* Gives the covariate id of covariates associated with age: V2 + V1 + age*V4 + V3*age
1.137 brouard 10134: 4 covariates (3 plus signs)
10135: Tage[1=V3*age]= 4; Tage[2=age*V4] = 3
10136: */
1.230 brouard 10137: Tmodelind=ivector(1,NCOVMAX);/** gives the k model position of an
1.227 brouard 10138: * individual dummy, fixed or varying:
10139: * Tmodelind[Tvaraff[3]]=9,Tvaraff[1]@9={4,
10140: * 3, 1, 0, 0, 0, 0, 0, 0},
1.230 brouard 10141: * model=V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 ,
10142: * V1 df, V2 qf, V3 & V4 dv, V5 qv
10143: * Tmodelind[1]@9={9,0,3,2,}*/
10144: TmodelInvind=ivector(1,NCOVMAX); /* TmodelInvind=Tvar[k]- ncovcol-nqv={5-2-1=2,*/
10145: TmodelInvQind=ivector(1,NCOVMAX);/** gives the k model position of an
1.228 brouard 10146: * individual quantitative, fixed or varying:
10147: * Tmodelqind[1]=1,Tvaraff[1]@9={4,
10148: * 3, 1, 0, 0, 0, 0, 0, 0},
10149: * model=V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1*/
1.186 brouard 10150: /* Main decodemodel */
10151:
1.187 brouard 10152:
1.223 brouard 10153: if(decodemodel(model, lastobs) == 1) /* In order to get Tvar[k] V4+V3+V5 p Tvar[1]@3 = {4, 3, 5}*/
1.136 brouard 10154: goto end;
10155:
1.137 brouard 10156: if((double)(lastobs-imx)/(double)imx > 1.10){
10157: nbwarn++;
10158: 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);
10159: 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);
10160: }
1.136 brouard 10161: /* if(mle==1){*/
1.137 brouard 10162: if (weightopt != 1) { /* Maximisation without weights. We can have weights different from 1 but want no weight*/
10163: for(i=1;i<=imx;i++) weight[i]=1.0; /* changed to imx */
1.136 brouard 10164: }
10165:
10166: /*-calculation of age at interview from date of interview and age at death -*/
10167: agev=matrix(1,maxwav,1,imx);
10168:
10169: if(calandcheckages(imx, maxwav, &agemin, &agemax, &nberr, &nbwarn) == 1)
10170: goto end;
10171:
1.126 brouard 10172:
1.136 brouard 10173: agegomp=(int)agemin;
10174: free_vector(moisnais,1,n);
10175: free_vector(annais,1,n);
1.126 brouard 10176: /* free_matrix(mint,1,maxwav,1,n);
10177: free_matrix(anint,1,maxwav,1,n);*/
1.215 brouard 10178: /* free_vector(moisdc,1,n); */
10179: /* free_vector(andc,1,n); */
1.145 brouard 10180: /* */
10181:
1.126 brouard 10182: wav=ivector(1,imx);
1.214 brouard 10183: /* dh=imatrix(1,lastpass-firstpass+1,1,imx); */
10184: /* bh=imatrix(1,lastpass-firstpass+1,1,imx); */
10185: /* mw=imatrix(1,lastpass-firstpass+1,1,imx); */
10186: 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.*/
10187: bh=imatrix(1,lastpass-firstpass+2,1,imx);
10188: mw=imatrix(1,lastpass-firstpass+2,1,imx);
1.126 brouard 10189:
10190: /* Concatenates waves */
1.214 brouard 10191: /* Concatenates waves: wav[i] is the number of effective (useful waves) of individual i.
10192: Death is a valid wave (if date is known).
10193: mw[mi][i] is the number of (mi=1 to wav[i]) effective wave out of mi of individual i
10194: dh[m][i] or dh[mw[mi][i]][i] is the delay between two effective waves m=mw[mi][i]
10195: and mw[mi+1][i]. dh depends on stepm.
10196: */
10197:
1.126 brouard 10198: concatwav(wav, dh, bh, mw, s, agedc, agev, firstpass, lastpass, imx, nlstate, stepm);
1.145 brouard 10199: /* */
10200:
1.215 brouard 10201: free_vector(moisdc,1,n);
10202: free_vector(andc,1,n);
10203:
1.126 brouard 10204: /* Routine tricode is to calculate cptcoveff (real number of unique covariates) and to associate covariable number and modality */
10205: nbcode=imatrix(0,NCOVMAX,0,NCOVMAX);
10206: ncodemax[1]=1;
1.145 brouard 10207: Ndum =ivector(-1,NCOVMAX);
1.225 brouard 10208: cptcoveff=0;
1.220 brouard 10209: if (ncovmodel-nagesqr > 2 ){ /* That is if covariate other than cst, age and age*age */
10210: tricode(&cptcoveff,Tvar,nbcode,imx, Ndum); /**< Fills nbcode[Tvar[j]][l]; */
1.227 brouard 10211: }
10212:
10213: ncovcombmax=pow(2,cptcoveff);
10214: invalidvarcomb=ivector(1, ncovcombmax);
10215: for(i=1;i<ncovcombmax;i++)
10216: invalidvarcomb[i]=0;
10217:
1.211 brouard 10218: /* Nbcode gives the value of the lth modality (currently 1 to 2) of jth covariate, in
1.186 brouard 10219: V2+V1*age, there are 3 covariates Tvar[2]=1 (V1).*/
1.211 brouard 10220: /* 1 to ncodemax[j] which is the maximum value of this jth covariate */
1.227 brouard 10221:
1.200 brouard 10222: /* codtab=imatrix(1,100,1,10);*/ /* codtab[h,k]=( (h-1) - mod(k-1,2**(k-1) )/2**(k-1) */
1.198 brouard 10223: /*printf(" codtab[1,1],codtab[100,10]=%d,%d\n", codtab[1][1],codtabm(100,10));*/
1.186 brouard 10224: /* codtab gives the value 1 or 2 of the hth combination of k covariates (1 or 2).*/
1.211 brouard 10225: /* nbcode[Tvaraff[j]][codtabm(h,j)]) : if there are only 2 modalities for a covariate j,
10226: * codtabm(h,j) gives its value classified at position h and nbcode gives how it is coded
10227: * (currently 0 or 1) in the data.
10228: * In a loop on h=1 to 2**k, and a loop on j (=1 to k), we get the value of
10229: * corresponding modality (h,j).
10230: */
10231:
1.145 brouard 10232: h=0;
10233: /*if (cptcovn > 0) */
1.126 brouard 10234: m=pow(2,cptcoveff);
10235:
1.144 brouard 10236: /**< codtab(h,k) k = codtab[h,k]=( (h-1) - mod(k-1,2**(k-1) )/2**(k-1) + 1
1.211 brouard 10237: * For k=4 covariates, h goes from 1 to m=2**k
10238: * codtabm(h,k)= (1 & (h-1) >> (k-1)) + 1;
10239: * #define codtabm(h,k) (1 & (h-1) >> (k-1))+1
1.186 brouard 10240: * h\k 1 2 3 4
1.143 brouard 10241: *______________________________
10242: * 1 i=1 1 i=1 1 i=1 1 i=1 1
10243: * 2 2 1 1 1
10244: * 3 i=2 1 2 1 1
10245: * 4 2 2 1 1
10246: * 5 i=3 1 i=2 1 2 1
10247: * 6 2 1 2 1
10248: * 7 i=4 1 2 2 1
10249: * 8 2 2 2 1
1.197 brouard 10250: * 9 i=5 1 i=3 1 i=2 1 2
10251: * 10 2 1 1 2
10252: * 11 i=6 1 2 1 2
10253: * 12 2 2 1 2
10254: * 13 i=7 1 i=4 1 2 2
10255: * 14 2 1 2 2
10256: * 15 i=8 1 2 2 2
10257: * 16 2 2 2 2
1.143 brouard 10258: */
1.212 brouard 10259: /* How to do the opposite? From combination h (=1 to 2**k) how to get the value on the covariates? */
1.211 brouard 10260: /* from h=5 and m, we get then number of covariates k=log(m)/log(2)=4
10261: * and the value of each covariate?
10262: * V1=1, V2=1, V3=2, V4=1 ?
10263: * h-1=4 and 4 is 0100 or reverse 0010, and +1 is 1121 ok.
10264: * h=6, 6-1=5, 5 is 0101, 1010, 2121, V1=2nd, V2=1st, V3=2nd, V4=1st.
10265: * In order to get the real value in the data, we use nbcode
10266: * nbcode[Tvar[3][2nd]]=1 and nbcode[Tvar[4][1]]=0
10267: * We are keeping this crazy system in order to be able (in the future?)
10268: * to have more than 2 values (0 or 1) for a covariate.
10269: * #define codtabm(h,k) (1 & (h-1) >> (k-1))+1
10270: * h=6, k=2? h-1=5=0101, reverse 1010, +1=2121, k=2nd position: value is 1: codtabm(6,2)=1
10271: * bbbbbbbb
10272: * 76543210
10273: * h-1 00000101 (6-1=5)
1.219 brouard 10274: *(h-1)>>(k-1)= 00000010 >> (2-1) = 1 right shift
1.211 brouard 10275: * &
10276: * 1 00000001 (1)
1.219 brouard 10277: * 00000000 = 1 & ((h-1) >> (k-1))
10278: * +1= 00000001 =1
1.211 brouard 10279: *
10280: * h=14, k=3 => h'=h-1=13, k'=k-1=2
10281: * h' 1101 =2^3+2^2+0x2^1+2^0
10282: * >>k' 11
10283: * & 00000001
10284: * = 00000001
10285: * +1 = 00000010=2 = codtabm(14,3)
10286: * Reverse h=6 and m=16?
10287: * cptcoveff=log(16)/log(2)=4 covariate: 6-1=5=0101 reversed=1010 +1=2121 =>V1=2, V2=1, V3=2, V4=1.
10288: * for (j=1 to cptcoveff) Vj=decodtabm(j,h,cptcoveff)
10289: * decodtabm(h,j,cptcoveff)= (((h-1) >> (j-1)) & 1) +1
10290: * decodtabm(h,j,cptcoveff)= (h <= (1<<cptcoveff)?(((h-1) >> (j-1)) & 1) +1 : -1)
10291: * V3=decodtabm(14,3,2**4)=2
10292: * h'=13 1101 =2^3+2^2+0x2^1+2^0
10293: *(h-1) >> (j-1) 0011 =13 >> 2
10294: * &1 000000001
10295: * = 000000001
10296: * +1= 000000010 =2
10297: * 2211
10298: * V1=1+1, V2=0+1, V3=1+1, V4=1+1
10299: * V3=2
1.220 brouard 10300: * codtabm and decodtabm are identical
1.211 brouard 10301: */
10302:
1.145 brouard 10303:
10304: free_ivector(Ndum,-1,NCOVMAX);
10305:
10306:
1.126 brouard 10307:
1.186 brouard 10308: /* Initialisation of ----------- gnuplot -------------*/
1.126 brouard 10309: strcpy(optionfilegnuplot,optionfilefiname);
10310: if(mle==-3)
1.201 brouard 10311: strcat(optionfilegnuplot,"-MORT_");
1.126 brouard 10312: strcat(optionfilegnuplot,".gp");
10313:
10314: if((ficgp=fopen(optionfilegnuplot,"w"))==NULL) {
10315: printf("Problem with file %s",optionfilegnuplot);
10316: }
10317: else{
1.204 brouard 10318: fprintf(ficgp,"\n# IMaCh-%s\n", version);
1.126 brouard 10319: fprintf(ficgp,"# %s\n", optionfilegnuplot);
1.141 brouard 10320: //fprintf(ficgp,"set missing 'NaNq'\n");
10321: fprintf(ficgp,"set datafile missing 'NaNq'\n");
1.126 brouard 10322: }
10323: /* fclose(ficgp);*/
1.186 brouard 10324:
10325:
10326: /* Initialisation of --------- index.htm --------*/
1.126 brouard 10327:
10328: strcpy(optionfilehtm,optionfilefiname); /* Main html file */
10329: if(mle==-3)
1.201 brouard 10330: strcat(optionfilehtm,"-MORT_");
1.126 brouard 10331: strcat(optionfilehtm,".htm");
10332: if((fichtm=fopen(optionfilehtm,"w"))==NULL) {
1.131 brouard 10333: printf("Problem with %s \n",optionfilehtm);
10334: exit(0);
1.126 brouard 10335: }
10336:
10337: strcpy(optionfilehtmcov,optionfilefiname); /* Only for matrix of covariance */
10338: strcat(optionfilehtmcov,"-cov.htm");
10339: if((fichtmcov=fopen(optionfilehtmcov,"w"))==NULL) {
10340: printf("Problem with %s \n",optionfilehtmcov), exit(0);
10341: }
10342: else{
10343: fprintf(fichtmcov,"<html><head>\n<title>IMaCh Cov %s</title></head>\n <body><font size=\"2\">%s <br> %s</font> \
10344: <hr size=\"2\" color=\"#EC5E5E\"> \n\
1.204 brouard 10345: Title=%s <br>Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s<br>\n",\
1.126 brouard 10346: optionfilehtmcov,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model);
10347: }
10348:
1.213 brouard 10349: 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 10350: <hr size=\"2\" color=\"#EC5E5E\"> \n\
10351: <font size=\"2\">IMaCh-%s <br> %s</font> \
1.126 brouard 10352: <hr size=\"2\" color=\"#EC5E5E\"> \n\
1.204 brouard 10353: Title=%s <br>Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s<br>\n\
1.126 brouard 10354: \n\
10355: <hr size=\"2\" color=\"#EC5E5E\">\
10356: <ul><li><h4>Parameter files</h4>\n\
10357: - Parameter file: <a href=\"%s.%s\">%s.%s</a><br>\n\
10358: - Copy of the parameter file: <a href=\"o%s\">o%s</a><br>\n\
10359: - Log file of the run: <a href=\"%s\">%s</a><br>\n\
10360: - Gnuplot file name: <a href=\"%s\">%s</a><br>\n\
10361: - Date and time at start: %s</ul>\n",\
10362: optionfilehtm,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model,\
10363: optionfilefiname,optionfilext,optionfilefiname,optionfilext,\
10364: fileres,fileres,\
10365: filelog,filelog,optionfilegnuplot,optionfilegnuplot,strstart);
10366: fflush(fichtm);
10367:
10368: strcpy(pathr,path);
10369: strcat(pathr,optionfilefiname);
1.184 brouard 10370: #ifdef WIN32
10371: _chdir(optionfilefiname); /* Move to directory named optionfile */
10372: #else
1.126 brouard 10373: chdir(optionfilefiname); /* Move to directory named optionfile */
1.184 brouard 10374: #endif
10375:
1.126 brouard 10376:
1.220 brouard 10377: /* Calculates basic frequencies. Computes observed prevalence at single age
10378: and for any valid combination of covariates
1.126 brouard 10379: and prints on file fileres'p'. */
1.227 brouard 10380: freqsummary(fileres, agemin, agemax, s, agev, nlstate, imx, Tvaraff, invalidvarcomb, nbcode, ncodemax,mint,anint,strstart, \
10381: firstpass, lastpass, stepm, weightopt, model);
1.126 brouard 10382:
10383: fprintf(fichtm,"\n");
10384: fprintf(fichtm,"<br>Total number of observations=%d <br>\n\
10385: Youngest age at first (selected) pass %.2f, oldest age %.2f<br>\n\
10386: Interval (in months) between two waves: Min=%d Max=%d Mean=%.2lf<br>\n",\
10387: imx,agemin,agemax,jmin,jmax,jmean);
10388: pmmij= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
1.220 brouard 10389: oldms= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
10390: newms= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
10391: savms= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
10392: oldm=oldms; newm=newms; savm=savms; /* Keeps fixed addresses to free */
1.218 brouard 10393:
1.126 brouard 10394: /* For Powell, parameters are in a vector p[] starting at p[1]
10395: so we point p on param[1][1] so that p[1] maps on param[1][1][1] */
10396: p=param[1][1]; /* *(*(*(param +1)+1)+0) */
10397:
10398: globpr=0; /* To get the number ipmx of contributions and the sum of weights*/
1.186 brouard 10399: /* For mortality only */
1.126 brouard 10400: if (mle==-3){
1.136 brouard 10401: ximort=matrix(1,NDIM,1,NDIM);
1.220 brouard 10402: for(i=1;i<=NDIM;i++)
10403: for(j=1;j<=NDIM;j++)
10404: ximort[i][j]=0.;
1.186 brouard 10405: /* ximort=gsl_matrix_alloc(1,NDIM,1,NDIM); */
1.126 brouard 10406: cens=ivector(1,n);
10407: ageexmed=vector(1,n);
10408: agecens=vector(1,n);
10409: dcwave=ivector(1,n);
1.223 brouard 10410:
1.126 brouard 10411: for (i=1; i<=imx; i++){
10412: dcwave[i]=-1;
10413: for (m=firstpass; m<=lastpass; m++)
1.226 brouard 10414: if (s[m][i]>nlstate) {
10415: dcwave[i]=m;
10416: /* printf("i=%d j=%d s=%d dcwave=%d\n",i,j, s[j][i],dcwave[i]);*/
10417: break;
10418: }
1.126 brouard 10419: }
1.226 brouard 10420:
1.126 brouard 10421: for (i=1; i<=imx; i++) {
10422: if (wav[i]>0){
1.226 brouard 10423: ageexmed[i]=agev[mw[1][i]][i];
10424: j=wav[i];
10425: agecens[i]=1.;
10426:
10427: if (ageexmed[i]> 1 && wav[i] > 0){
10428: agecens[i]=agev[mw[j][i]][i];
10429: cens[i]= 1;
10430: }else if (ageexmed[i]< 1)
10431: cens[i]= -1;
10432: if (agedc[i]< AGESUP && agedc[i]>1 && dcwave[i]>firstpass && dcwave[i]<=lastpass)
10433: cens[i]=0 ;
1.126 brouard 10434: }
10435: else cens[i]=-1;
10436: }
10437:
10438: for (i=1;i<=NDIM;i++) {
10439: for (j=1;j<=NDIM;j++)
1.226 brouard 10440: ximort[i][j]=(i == j ? 1.0 : 0.0);
1.126 brouard 10441: }
10442:
1.145 brouard 10443: /*p[1]=0.0268; p[NDIM]=0.083;*/
1.126 brouard 10444: /*printf("%lf %lf", p[1], p[2]);*/
10445:
10446:
1.136 brouard 10447: #ifdef GSL
10448: printf("GSL optimization\n"); fprintf(ficlog,"Powell\n");
1.162 brouard 10449: #else
1.126 brouard 10450: printf("Powell\n"); fprintf(ficlog,"Powell\n");
1.136 brouard 10451: #endif
1.201 brouard 10452: strcpy(filerespow,"POW-MORT_");
10453: strcat(filerespow,fileresu);
1.126 brouard 10454: if((ficrespow=fopen(filerespow,"w"))==NULL) {
10455: printf("Problem with resultfile: %s\n", filerespow);
10456: fprintf(ficlog,"Problem with resultfile: %s\n", filerespow);
10457: }
1.136 brouard 10458: #ifdef GSL
10459: fprintf(ficrespow,"# GSL optimization\n# iter -2*LL");
1.162 brouard 10460: #else
1.126 brouard 10461: fprintf(ficrespow,"# Powell\n# iter -2*LL");
1.136 brouard 10462: #endif
1.126 brouard 10463: /* for (i=1;i<=nlstate;i++)
10464: for(j=1;j<=nlstate+ndeath;j++)
10465: if(j!=i)fprintf(ficrespow," p%1d%1d",i,j);
10466: */
10467: fprintf(ficrespow,"\n");
1.136 brouard 10468: #ifdef GSL
10469: /* gsl starts here */
10470: T = gsl_multimin_fminimizer_nmsimplex;
10471: gsl_multimin_fminimizer *sfm = NULL;
10472: gsl_vector *ss, *x;
10473: gsl_multimin_function minex_func;
10474:
10475: /* Initial vertex size vector */
10476: ss = gsl_vector_alloc (NDIM);
10477:
10478: if (ss == NULL){
10479: GSL_ERROR_VAL ("failed to allocate space for ss", GSL_ENOMEM, 0);
10480: }
10481: /* Set all step sizes to 1 */
10482: gsl_vector_set_all (ss, 0.001);
10483:
10484: /* Starting point */
1.126 brouard 10485:
1.136 brouard 10486: x = gsl_vector_alloc (NDIM);
10487:
10488: if (x == NULL){
10489: gsl_vector_free(ss);
10490: GSL_ERROR_VAL ("failed to allocate space for x", GSL_ENOMEM, 0);
10491: }
10492:
10493: /* Initialize method and iterate */
10494: /* p[1]=0.0268; p[NDIM]=0.083; */
1.186 brouard 10495: /* gsl_vector_set(x, 0, 0.0268); */
10496: /* gsl_vector_set(x, 1, 0.083); */
1.136 brouard 10497: gsl_vector_set(x, 0, p[1]);
10498: gsl_vector_set(x, 1, p[2]);
10499:
10500: minex_func.f = &gompertz_f;
10501: minex_func.n = NDIM;
10502: minex_func.params = (void *)&p; /* ??? */
10503:
10504: sfm = gsl_multimin_fminimizer_alloc (T, NDIM);
10505: gsl_multimin_fminimizer_set (sfm, &minex_func, x, ss);
10506:
10507: printf("Iterations beginning .....\n\n");
10508: printf("Iter. # Intercept Slope -Log Likelihood Simplex size\n");
10509:
10510: iteri=0;
10511: while (rval == GSL_CONTINUE){
10512: iteri++;
10513: status = gsl_multimin_fminimizer_iterate(sfm);
10514:
10515: if (status) printf("error: %s\n", gsl_strerror (status));
10516: fflush(0);
10517:
10518: if (status)
10519: break;
10520:
10521: rval = gsl_multimin_test_size (gsl_multimin_fminimizer_size (sfm), 1e-6);
10522: ssval = gsl_multimin_fminimizer_size (sfm);
10523:
10524: if (rval == GSL_SUCCESS)
10525: printf ("converged to a local maximum at\n");
10526:
10527: printf("%5d ", iteri);
10528: for (it = 0; it < NDIM; it++){
10529: printf ("%10.5f ", gsl_vector_get (sfm->x, it));
10530: }
10531: printf("f() = %-10.5f ssize = %.7f\n", sfm->fval, ssval);
10532: }
10533:
10534: printf("\n\n Please note: Program should be run many times with varying starting points to detemine global maximum\n\n");
10535:
10536: gsl_vector_free(x); /* initial values */
10537: gsl_vector_free(ss); /* inital step size */
10538: for (it=0; it<NDIM; it++){
10539: p[it+1]=gsl_vector_get(sfm->x,it);
10540: fprintf(ficrespow," %.12lf", p[it]);
10541: }
10542: gsl_multimin_fminimizer_free (sfm); /* p *(sfm.x.data) et p *(sfm.x.data+1) */
10543: #endif
10544: #ifdef POWELL
10545: powell(p,ximort,NDIM,ftol,&iter,&fret,gompertz);
10546: #endif
1.126 brouard 10547: fclose(ficrespow);
10548:
1.203 brouard 10549: hesscov(matcov, hess, p, NDIM, delti, 1e-4, gompertz);
1.126 brouard 10550:
10551: for(i=1; i <=NDIM; i++)
10552: for(j=i+1;j<=NDIM;j++)
1.220 brouard 10553: matcov[i][j]=matcov[j][i];
1.126 brouard 10554:
10555: printf("\nCovariance matrix\n ");
1.203 brouard 10556: fprintf(ficlog,"\nCovariance matrix\n ");
1.126 brouard 10557: for(i=1; i <=NDIM; i++) {
10558: for(j=1;j<=NDIM;j++){
1.220 brouard 10559: printf("%f ",matcov[i][j]);
10560: fprintf(ficlog,"%f ",matcov[i][j]);
1.126 brouard 10561: }
1.203 brouard 10562: printf("\n "); fprintf(ficlog,"\n ");
1.126 brouard 10563: }
10564:
10565: printf("iter=%d MLE=%f Eq=%lf*exp(%lf*(age-%d))\n",iter,-gompertz(p),p[1],p[2],agegomp);
1.193 brouard 10566: for (i=1;i<=NDIM;i++) {
1.126 brouard 10567: printf("%f [%f ; %f]\n",p[i],p[i]-2*sqrt(matcov[i][i]),p[i]+2*sqrt(matcov[i][i]));
1.193 brouard 10568: fprintf(ficlog,"%f [%f ; %f]\n",p[i],p[i]-2*sqrt(matcov[i][i]),p[i]+2*sqrt(matcov[i][i]));
10569: }
1.126 brouard 10570: lsurv=vector(1,AGESUP);
10571: lpop=vector(1,AGESUP);
10572: tpop=vector(1,AGESUP);
10573: lsurv[agegomp]=100000;
10574:
10575: for (k=agegomp;k<=AGESUP;k++) {
10576: agemortsup=k;
10577: if (p[1]*exp(p[2]*(k-agegomp))>1) break;
10578: }
10579:
10580: for (k=agegomp;k<agemortsup;k++)
10581: lsurv[k+1]=lsurv[k]-lsurv[k]*(p[1]*exp(p[2]*(k-agegomp)));
10582:
10583: for (k=agegomp;k<agemortsup;k++){
10584: lpop[k]=(lsurv[k]+lsurv[k+1])/2.;
10585: sumlpop=sumlpop+lpop[k];
10586: }
10587:
10588: tpop[agegomp]=sumlpop;
10589: for (k=agegomp;k<(agemortsup-3);k++){
10590: /* tpop[k+1]=2;*/
10591: tpop[k+1]=tpop[k]-lpop[k];
10592: }
10593:
10594:
10595: printf("\nAge lx qx dx Lx Tx e(x)\n");
10596: for (k=agegomp;k<(agemortsup-2);k++)
10597: 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]);
10598:
10599:
10600: replace_back_to_slash(pathc,pathcd); /* Even gnuplot wants a / */
1.220 brouard 10601: ageminpar=50;
10602: agemaxpar=100;
1.194 brouard 10603: if(ageminpar == AGEOVERFLOW ||agemaxpar == AGEOVERFLOW){
10604: printf("Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
10605: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
10606: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
10607: fprintf(ficlog,"Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
10608: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
10609: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
1.220 brouard 10610: }else{
10611: printf("Warning! ageminpar %f and agemaxpar %f have been fixed because for simplification until it is fixed...\n\n",ageminpar,agemaxpar);
10612: 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 10613: printinggnuplotmort(fileresu, optionfilefiname,ageminpar,agemaxpar,fage, pathc,p);
1.220 brouard 10614: }
1.201 brouard 10615: printinghtmlmort(fileresu,title,datafile, firstpass, lastpass, \
1.126 brouard 10616: stepm, weightopt,\
10617: model,imx,p,matcov,agemortsup);
10618:
10619: free_vector(lsurv,1,AGESUP);
10620: free_vector(lpop,1,AGESUP);
10621: free_vector(tpop,1,AGESUP);
1.220 brouard 10622: free_matrix(ximort,1,NDIM,1,NDIM);
1.136 brouard 10623: free_ivector(cens,1,n);
10624: free_vector(agecens,1,n);
10625: free_ivector(dcwave,1,n);
1.220 brouard 10626: #ifdef GSL
1.136 brouard 10627: #endif
1.186 brouard 10628: } /* Endof if mle==-3 mortality only */
1.205 brouard 10629: /* Standard */
10630: else{ /* For mle !=- 3, could be 0 or 1 or 4 etc. */
10631: globpr=0;/* Computes sum of likelihood for globpr=1 and funcone */
10632: /* Computes likelihood for initial parameters, uses funcone to compute gpimx and gsw */
1.132 brouard 10633: likelione(ficres, p, npar, nlstate, &globpr, &ipmx, &sw, &fretone, funcone); /* Prints the contributions to the likelihood */
1.126 brouard 10634: printf("First Likeli=%12.6f ipmx=%ld sw=%12.6f",fretone,ipmx,sw);
10635: for (k=1; k<=npar;k++)
10636: printf(" %d %8.5f",k,p[k]);
10637: printf("\n");
1.205 brouard 10638: if(mle>=1){ /* Could be 1 or 2, Real Maximization */
10639: /* mlikeli uses func not funcone */
10640: mlikeli(ficres,p, npar, ncovmodel, nlstate, ftol, func);
10641: }
10642: if(mle==0) {/* No optimization, will print the likelihoods for the datafile */
10643: globpr=0;/* Computes sum of likelihood for globpr=1 and funcone */
10644: /* Computes likelihood for initial parameters, uses funcone to compute gpimx and gsw */
10645: likelione(ficres, p, npar, nlstate, &globpr, &ipmx, &sw, &fretone, funcone); /* Prints the contributions to the likelihood */
10646: }
10647: globpr=1; /* again, to print the individual contributions using computed gpimx and gsw */
1.126 brouard 10648: likelione(ficres, p, npar, nlstate, &globpr, &ipmx, &sw, &fretone, funcone); /* Prints the contributions to the likelihood */
10649: printf("Second Likeli=%12.6f ipmx=%ld sw=%12.6f",fretone,ipmx,sw);
10650: for (k=1; k<=npar;k++)
10651: printf(" %d %8.5f",k,p[k]);
10652: printf("\n");
10653:
10654: /*--------- results files --------------*/
1.224 brouard 10655: 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 10656:
10657:
10658: fprintf(ficres,"# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
10659: printf("# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
10660: fprintf(ficlog,"# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
10661: for(i=1,jk=1; i <=nlstate; i++){
10662: for(k=1; k <=(nlstate+ndeath); k++){
1.225 brouard 10663: if (k != i) {
10664: printf("%d%d ",i,k);
10665: fprintf(ficlog,"%d%d ",i,k);
10666: fprintf(ficres,"%1d%1d ",i,k);
10667: for(j=1; j <=ncovmodel; j++){
10668: printf("%12.7f ",p[jk]);
10669: fprintf(ficlog,"%12.7f ",p[jk]);
10670: fprintf(ficres,"%12.7f ",p[jk]);
10671: jk++;
10672: }
10673: printf("\n");
10674: fprintf(ficlog,"\n");
10675: fprintf(ficres,"\n");
10676: }
1.126 brouard 10677: }
10678: }
1.203 brouard 10679: if(mle != 0){
10680: /* Computing hessian and covariance matrix only at a peak of the Likelihood, that is after optimization */
1.126 brouard 10681: ftolhess=ftol; /* Usually correct */
1.203 brouard 10682: hesscov(matcov, hess, p, npar, delti, ftolhess, func);
10683: 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");
10684: 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");
10685: for(i=1,jk=1; i <=nlstate; i++){
1.225 brouard 10686: for(k=1; k <=(nlstate+ndeath); k++){
10687: if (k != i) {
10688: printf("%d%d ",i,k);
10689: fprintf(ficlog,"%d%d ",i,k);
10690: for(j=1; j <=ncovmodel; j++){
10691: 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]));
10692: 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]));
10693: jk++;
10694: }
10695: printf("\n");
10696: fprintf(ficlog,"\n");
10697: }
10698: }
1.193 brouard 10699: }
1.203 brouard 10700: } /* end of hesscov and Wald tests */
1.225 brouard 10701:
1.203 brouard 10702: /* */
1.126 brouard 10703: fprintf(ficres,"# Scales (for hessian or gradient estimation)\n");
10704: printf("# Scales (for hessian or gradient estimation)\n");
10705: fprintf(ficlog,"# Scales (for hessian or gradient estimation)\n");
10706: for(i=1,jk=1; i <=nlstate; i++){
10707: for(j=1; j <=nlstate+ndeath; j++){
1.225 brouard 10708: if (j!=i) {
10709: fprintf(ficres,"%1d%1d",i,j);
10710: printf("%1d%1d",i,j);
10711: fprintf(ficlog,"%1d%1d",i,j);
10712: for(k=1; k<=ncovmodel;k++){
10713: printf(" %.5e",delti[jk]);
10714: fprintf(ficlog," %.5e",delti[jk]);
10715: fprintf(ficres," %.5e",delti[jk]);
10716: jk++;
10717: }
10718: printf("\n");
10719: fprintf(ficlog,"\n");
10720: fprintf(ficres,"\n");
10721: }
1.126 brouard 10722: }
10723: }
10724:
10725: 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 10726: if(mle >= 1) /* To big for the screen */
1.126 brouard 10727: 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");
10728: 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");
10729: /* # 121 Var(a12)\n\ */
10730: /* # 122 Cov(b12,a12) Var(b12)\n\ */
10731: /* # 131 Cov(a13,a12) Cov(a13,b12, Var(a13)\n\ */
10732: /* # 132 Cov(b13,a12) Cov(b13,b12, Cov(b13,a13) Var(b13)\n\ */
10733: /* # 212 Cov(a21,a12) Cov(a21,b12, Cov(a21,a13) Cov(a21,b13) Var(a21)\n\ */
10734: /* # 212 Cov(b21,a12) Cov(b21,b12, Cov(b21,a13) Cov(b21,b13) Cov(b21,a21) Var(b21)\n\ */
10735: /* # 232 Cov(a23,a12) Cov(a23,b12, Cov(a23,a13) Cov(a23,b13) Cov(a23,a21) Cov(a23,b21) Var(a23)\n\ */
10736: /* # 232 Cov(b23,a12) Cov(b23,b12) ... Var (b23)\n" */
10737:
10738:
10739: /* Just to have a covariance matrix which will be more understandable
10740: even is we still don't want to manage dictionary of variables
10741: */
10742: for(itimes=1;itimes<=2;itimes++){
10743: jj=0;
10744: for(i=1; i <=nlstate; i++){
1.225 brouard 10745: for(j=1; j <=nlstate+ndeath; j++){
10746: if(j==i) continue;
10747: for(k=1; k<=ncovmodel;k++){
10748: jj++;
10749: ca[0]= k+'a'-1;ca[1]='\0';
10750: if(itimes==1){
10751: if(mle>=1)
10752: printf("#%1d%1d%d",i,j,k);
10753: fprintf(ficlog,"#%1d%1d%d",i,j,k);
10754: fprintf(ficres,"#%1d%1d%d",i,j,k);
10755: }else{
10756: if(mle>=1)
10757: printf("%1d%1d%d",i,j,k);
10758: fprintf(ficlog,"%1d%1d%d",i,j,k);
10759: fprintf(ficres,"%1d%1d%d",i,j,k);
10760: }
10761: ll=0;
10762: for(li=1;li <=nlstate; li++){
10763: for(lj=1;lj <=nlstate+ndeath; lj++){
10764: if(lj==li) continue;
10765: for(lk=1;lk<=ncovmodel;lk++){
10766: ll++;
10767: if(ll<=jj){
10768: cb[0]= lk +'a'-1;cb[1]='\0';
10769: if(ll<jj){
10770: if(itimes==1){
10771: if(mle>=1)
10772: printf(" Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
10773: fprintf(ficlog," Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
10774: fprintf(ficres," Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
10775: }else{
10776: if(mle>=1)
10777: printf(" %.5e",matcov[jj][ll]);
10778: fprintf(ficlog," %.5e",matcov[jj][ll]);
10779: fprintf(ficres," %.5e",matcov[jj][ll]);
10780: }
10781: }else{
10782: if(itimes==1){
10783: if(mle>=1)
10784: printf(" Var(%s%1d%1d)",ca,i,j);
10785: fprintf(ficlog," Var(%s%1d%1d)",ca,i,j);
10786: fprintf(ficres," Var(%s%1d%1d)",ca,i,j);
10787: }else{
10788: if(mle>=1)
10789: printf(" %.7e",matcov[jj][ll]);
10790: fprintf(ficlog," %.7e",matcov[jj][ll]);
10791: fprintf(ficres," %.7e",matcov[jj][ll]);
10792: }
10793: }
10794: }
10795: } /* end lk */
10796: } /* end lj */
10797: } /* end li */
10798: if(mle>=1)
10799: printf("\n");
10800: fprintf(ficlog,"\n");
10801: fprintf(ficres,"\n");
10802: numlinepar++;
10803: } /* end k*/
10804: } /*end j */
1.126 brouard 10805: } /* end i */
10806: } /* end itimes */
10807:
10808: fflush(ficlog);
10809: fflush(ficres);
1.225 brouard 10810: while(fgets(line, MAXLINE, ficpar)) {
10811: /* If line starts with a # it is a comment */
10812: if (line[0] == '#') {
10813: numlinepar++;
10814: fputs(line,stdout);
10815: fputs(line,ficparo);
10816: fputs(line,ficlog);
10817: continue;
10818: }else
10819: break;
10820: }
10821:
1.209 brouard 10822: /* while((c=getc(ficpar))=='#' && c!= EOF){ */
10823: /* ungetc(c,ficpar); */
10824: /* fgets(line, MAXLINE, ficpar); */
10825: /* fputs(line,stdout); */
10826: /* fputs(line,ficparo); */
10827: /* } */
10828: /* ungetc(c,ficpar); */
1.126 brouard 10829:
10830: estepm=0;
1.209 brouard 10831: 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 10832:
10833: if (num_filled != 6) {
10834: 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);
10835: 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);
10836: goto end;
10837: }
10838: printf("agemin=%lf agemax=%lf bage=%lf fage=%lf estepm=%d ftolpl=%lf\n",ageminpar,agemaxpar, bage, fage, estepm, ftolpl);
10839: }
10840: /* ftolpl=6*ftol*1.e5; /\* 6.e-3 make convergences in less than 80 loops for the prevalence limit *\/ */
10841: /*ftolpl=6.e-4;*/ /* 6.e-3 make convergences in less than 80 loops for the prevalence limit */
10842:
1.209 brouard 10843: /* fscanf(ficpar,"agemin=%lf agemax=%lf bage=%lf fage=%lf estepm=%d ftolpl=%\n",&ageminpar,&agemaxpar, &bage, &fage, &estepm); */
1.126 brouard 10844: if (estepm==0 || estepm < stepm) estepm=stepm;
10845: if (fage <= 2) {
10846: bage = ageminpar;
10847: fage = agemaxpar;
10848: }
10849:
10850: fprintf(ficres,"# agemin agemax for life expectancy, bage fage (if mle==0 ie no data nor Max likelihood).\n");
1.211 brouard 10851: fprintf(ficres,"agemin=%.0f agemax=%.0f bage=%.0f fage=%.0f estepm=%d ftolpl=%e\n",ageminpar,agemaxpar,bage,fage, estepm, ftolpl);
10852: fprintf(ficparo,"agemin=%.0f agemax=%.0f bage=%.0f fage=%.0f estepm=%d, ftolpl=%e\n",ageminpar,agemaxpar,bage,fage, estepm, ftolpl);
1.220 brouard 10853:
1.186 brouard 10854: /* Other stuffs, more or less useful */
1.126 brouard 10855: while((c=getc(ficpar))=='#' && c!= EOF){
10856: ungetc(c,ficpar);
10857: fgets(line, MAXLINE, ficpar);
1.141 brouard 10858: fputs(line,stdout);
1.126 brouard 10859: fputs(line,ficparo);
10860: }
10861: ungetc(c,ficpar);
10862:
10863: fscanf(ficpar,"begin-prev-date=%lf/%lf/%lf end-prev-date=%lf/%lf/%lf mov_average=%d\n",&jprev1, &mprev1,&anprev1,&jprev2, &mprev2,&anprev2,&mobilav);
10864: 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);
10865: 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);
10866: printf("begin-prev-date=%.lf/%.lf/%.lf end-prev-date=%.lf/%.lf/%.lf mov_average=%d\n",jprev1, mprev1,anprev1,jprev2, mprev2,anprev2,mobilav);
10867: 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);
10868:
10869: while((c=getc(ficpar))=='#' && c!= EOF){
10870: ungetc(c,ficpar);
10871: fgets(line, MAXLINE, ficpar);
1.141 brouard 10872: fputs(line,stdout);
1.126 brouard 10873: fputs(line,ficparo);
10874: }
10875: ungetc(c,ficpar);
10876:
10877:
10878: dateprev1=anprev1+(mprev1-1)/12.+(jprev1-1)/365.;
10879: dateprev2=anprev2+(mprev2-1)/12.+(jprev2-1)/365.;
10880:
10881: fscanf(ficpar,"pop_based=%d\n",&popbased);
1.193 brouard 10882: fprintf(ficlog,"pop_based=%d\n",popbased);
1.126 brouard 10883: fprintf(ficparo,"pop_based=%d\n",popbased);
10884: fprintf(ficres,"pop_based=%d\n",popbased);
10885:
10886: while((c=getc(ficpar))=='#' && c!= EOF){
10887: ungetc(c,ficpar);
10888: fgets(line, MAXLINE, ficpar);
1.141 brouard 10889: fputs(line,stdout);
1.238 brouard 10890: fputs(line,ficres);
1.126 brouard 10891: fputs(line,ficparo);
10892: }
10893: ungetc(c,ficpar);
10894:
10895: fscanf(ficpar,"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);
10896: 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);
10897: 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);
10898: 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);
10899: 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);
10900: /* day and month of proj2 are not used but only year anproj2.*/
10901:
1.217 brouard 10902: while((c=getc(ficpar))=='#' && c!= EOF){
10903: ungetc(c,ficpar);
10904: fgets(line, MAXLINE, ficpar);
10905: fputs(line,stdout);
10906: fputs(line,ficparo);
1.238 brouard 10907: fputs(line,ficres);
1.217 brouard 10908: }
10909: ungetc(c,ficpar);
10910:
10911: 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);
1.223 brouard 10912: 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);
10913: 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);
10914: 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);
1.217 brouard 10915: /* day and month of proj2 are not used but only year anproj2.*/
1.126 brouard 10916:
1.230 brouard 10917: /* Results */
1.235 brouard 10918: nresult=0;
1.230 brouard 10919: while(fgets(line, MAXLINE, ficpar)) {
10920: /* If line starts with a # it is a comment */
10921: if (line[0] == '#') {
10922: numlinepar++;
10923: fputs(line,stdout);
10924: fputs(line,ficparo);
10925: fputs(line,ficlog);
1.238 brouard 10926: fputs(line,ficres);
1.230 brouard 10927: continue;
10928: }else
10929: break;
10930: }
1.240 brouard 10931: if (!feof(ficpar))
1.230 brouard 10932: while((num_filled=sscanf(line,"result:%[^\n]\n",resultline)) !=EOF){
1.240 brouard 10933: if (num_filled == 0){
1.230 brouard 10934: resultline[0]='\0';
1.240 brouard 10935: break;
10936: } else if (num_filled != 1){
1.230 brouard 10937: printf("ERROR %d: result line should be at minimum 'result=' %s\n",num_filled, line);
10938: }
1.235 brouard 10939: nresult++; /* Sum of resultlines */
10940: printf("Result %d: result=%s\n",nresult, resultline);
10941: if(nresult > MAXRESULTLINES){
10942: printf("ERROR: Current version of IMaCh limits the number of resultlines to %d, you used %d\n",MAXRESULTLINES,nresult);
10943: fprintf(ficlog,"ERROR: Current version of IMaCh limits the number of resultlines to %d, you used %d\n",MAXRESULTLINES,nresult);
10944: goto end;
10945: }
10946: decoderesult(resultline, nresult); /* Fills TKresult[nresult] combination and Tresult[nresult][k4+1] combination values */
1.238 brouard 10947: fprintf(ficparo,"result: %s\n",resultline);
10948: fprintf(ficres,"result: %s\n",resultline);
10949: fprintf(ficlog,"result: %s\n",resultline);
1.230 brouard 10950: while(fgets(line, MAXLINE, ficpar)) {
10951: /* If line starts with a # it is a comment */
10952: if (line[0] == '#') {
10953: numlinepar++;
10954: fputs(line,stdout);
10955: fputs(line,ficparo);
1.238 brouard 10956: fputs(line,ficres);
1.230 brouard 10957: fputs(line,ficlog);
10958: continue;
10959: }else
10960: break;
10961: }
10962: if (feof(ficpar))
10963: break;
10964: else{ /* Processess output results for this combination of covariate values */
10965: }
1.240 brouard 10966: } /* end while */
1.230 brouard 10967:
10968:
1.126 brouard 10969:
1.230 brouard 10970: /* freqsummary(fileres, agemin, agemax, s, agev, nlstate, imx,Tvaraff,nbcode, ncodemax,mint,anint); */
1.145 brouard 10971: /* ,dateprev1,dateprev2,jprev1, mprev1,anprev1,jprev2, mprev2,anprev2); */
1.126 brouard 10972:
10973: replace_back_to_slash(pathc,pathcd); /* Even gnuplot wants a / */
1.194 brouard 10974: if(ageminpar == AGEOVERFLOW ||agemaxpar == -AGEOVERFLOW){
1.230 brouard 10975: printf("Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
1.194 brouard 10976: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
10977: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
1.230 brouard 10978: fprintf(ficlog,"Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
1.194 brouard 10979: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
10980: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
1.220 brouard 10981: }else{
1.218 brouard 10982: printinggnuplot(fileresu, optionfilefiname,ageminpar,agemaxpar,fage, prevfcast, backcast, pathc,p);
1.220 brouard 10983: }
10984: printinghtml(fileresu,title,datafile, firstpass, lastpass, stepm, weightopt, \
1.225 brouard 10985: model,imx,jmin,jmax,jmean,rfileres,popforecast,prevfcast,backcast, estepm, \
10986: jprev1,mprev1,anprev1,dateprev1,jprev2,mprev2,anprev2,dateprev2);
1.220 brouard 10987:
1.225 brouard 10988: /*------------ free_vector -------------*/
10989: /* chdir(path); */
1.220 brouard 10990:
1.215 brouard 10991: /* free_ivector(wav,1,imx); */ /* Moved after last prevalence call */
10992: /* free_imatrix(dh,1,lastpass-firstpass+2,1,imx); */
10993: /* free_imatrix(bh,1,lastpass-firstpass+2,1,imx); */
10994: /* free_imatrix(mw,1,lastpass-firstpass+2,1,imx); */
1.126 brouard 10995: free_lvector(num,1,n);
10996: free_vector(agedc,1,n);
10997: /*free_matrix(covar,0,NCOVMAX,1,n);*/
10998: /*free_matrix(covar,1,NCOVMAX,1,n);*/
10999: fclose(ficparo);
11000: fclose(ficres);
1.220 brouard 11001:
11002:
1.186 brouard 11003: /* Other results (useful)*/
1.220 brouard 11004:
11005:
1.126 brouard 11006: /*--------------- Prevalence limit (period or stable prevalence) --------------*/
1.180 brouard 11007: /*#include "prevlim.h"*/ /* Use ficrespl, ficlog */
11008: prlim=matrix(1,nlstate,1,nlstate);
1.209 brouard 11009: prevalence_limit(p, prlim, ageminpar, agemaxpar, ftolpl, &ncvyear);
1.126 brouard 11010: fclose(ficrespl);
11011:
11012: /*------------- h Pij x at various ages ------------*/
1.180 brouard 11013: /*#include "hpijx.h"*/
11014: hPijx(p, bage, fage);
1.145 brouard 11015: fclose(ficrespij);
1.227 brouard 11016:
1.220 brouard 11017: /* ncovcombmax= pow(2,cptcoveff); */
1.219 brouard 11018: /*-------------- Variance of one-step probabilities---*/
1.145 brouard 11019: k=1;
1.126 brouard 11020: varprob(optionfilefiname, matcov, p, delti, nlstate, bage, fage,k,Tvar,nbcode, ncodemax,strstart);
1.227 brouard 11021:
1.219 brouard 11022: /* Prevalence for each covariates in probs[age][status][cov] */
1.218 brouard 11023: probs= ma3x(1,AGESUP,1,nlstate+ndeath, 1,ncovcombmax);
1.126 brouard 11024: for(i=1;i<=AGESUP;i++)
1.219 brouard 11025: for(j=1;j<=nlstate+ndeath;j++) /* ndeath is useless but a necessity to be compared with mobaverages */
1.225 brouard 11026: for(k=1;k<=ncovcombmax;k++)
11027: probs[i][j][k]=0.;
1.219 brouard 11028: prevalence(probs, ageminpar, agemaxpar, s, agev, nlstate, imx, Tvar, nbcode, ncodemax, mint, anint, dateprev1, dateprev2, firstpass, lastpass);
11029: if (mobilav!=0 ||mobilavproj !=0 ) {
11030: mobaverages= ma3x(1, AGESUP,1,nlstate+ndeath, 1,ncovcombmax);
1.227 brouard 11031: for(i=1;i<=AGESUP;i++)
11032: for(j=1;j<=nlstate;j++)
11033: for(k=1;k<=ncovcombmax;k++)
11034: mobaverages[i][j][k]=0.;
1.219 brouard 11035: mobaverage=mobaverages;
11036: if (mobilav!=0) {
1.235 brouard 11037: printf("Movingaveraging observed prevalence\n");
1.227 brouard 11038: if (movingaverage(probs, ageminpar, agemaxpar, mobaverage, mobilav)!=0){
11039: fprintf(ficlog," Error in movingaverage mobilav=%d\n",mobilav);
11040: printf(" Error in movingaverage mobilav=%d\n",mobilav);
11041: }
1.219 brouard 11042: }
11043: /* /\* Prevalence for each covariates in probs[age][status][cov] *\/ */
11044: /* prevalence(probs, ageminpar, agemaxpar, s, agev, nlstate, imx, Tvar, nbcode, ncodemax, mint, anint, dateprev1, dateprev2, firstpass, lastpass); */
11045: else if (mobilavproj !=0) {
1.235 brouard 11046: printf("Movingaveraging projected observed prevalence\n");
1.227 brouard 11047: if (movingaverage(probs, ageminpar, agemaxpar, mobaverage, mobilavproj)!=0){
11048: fprintf(ficlog," Error in movingaverage mobilavproj=%d\n",mobilavproj);
11049: printf(" Error in movingaverage mobilavproj=%d\n",mobilavproj);
11050: }
1.219 brouard 11051: }
11052: }/* end if moving average */
1.227 brouard 11053:
1.126 brouard 11054: /*---------- Forecasting ------------------*/
11055: /*if((stepm == 1) && (strcmp(model,".")==0)){*/
11056: if(prevfcast==1){
11057: /* if(stepm ==1){*/
1.225 brouard 11058: prevforecast(fileresu, anproj1, mproj1, jproj1, agemin, agemax, dateprev1, dateprev2, mobilavproj, bage, fage, firstpass, lastpass, anproj2, p, cptcoveff);
1.126 brouard 11059: }
1.217 brouard 11060: if(backcast==1){
1.219 brouard 11061: ddnewms=matrix(1,nlstate+ndeath,1,nlstate+ndeath);
11062: ddoldms=matrix(1,nlstate+ndeath,1,nlstate+ndeath);
11063: ddsavms=matrix(1,nlstate+ndeath,1,nlstate+ndeath);
11064:
11065: /*--------------- Back Prevalence limit (period or stable prevalence) --------------*/
11066:
11067: bprlim=matrix(1,nlstate,1,nlstate);
11068: back_prevalence_limit(p, bprlim, ageminpar, agemaxpar, ftolpl, &ncvyear, dateprev1, dateprev2, firstpass, lastpass, mobilavproj);
11069: fclose(ficresplb);
11070:
1.222 brouard 11071: hBijx(p, bage, fage, mobaverage);
11072: fclose(ficrespijb);
1.219 brouard 11073: free_matrix(bprlim,1,nlstate,1,nlstate); /*here or after loop ? */
11074:
11075: /* prevbackforecast(fileresu, anback1, mback1, jback1, agemin, agemax, dateprev1, dateprev2, mobilavproj,
1.225 brouard 11076: bage, fage, firstpass, lastpass, anback2, p, cptcoveff); */
1.219 brouard 11077: free_matrix(ddnewms, 1, nlstate+ndeath, 1, nlstate+ndeath);
11078: free_matrix(ddsavms, 1, nlstate+ndeath, 1, nlstate+ndeath);
11079: free_matrix(ddoldms, 1, nlstate+ndeath, 1, nlstate+ndeath);
11080: }
1.217 brouard 11081:
1.186 brouard 11082:
11083: /* ------ Other prevalence ratios------------ */
1.126 brouard 11084:
1.215 brouard 11085: free_ivector(wav,1,imx);
11086: free_imatrix(dh,1,lastpass-firstpass+2,1,imx);
11087: free_imatrix(bh,1,lastpass-firstpass+2,1,imx);
11088: free_imatrix(mw,1,lastpass-firstpass+2,1,imx);
1.218 brouard 11089:
11090:
1.127 brouard 11091: /*---------- Health expectancies, no variances ------------*/
1.218 brouard 11092:
1.201 brouard 11093: strcpy(filerese,"E_");
11094: strcat(filerese,fileresu);
1.126 brouard 11095: if((ficreseij=fopen(filerese,"w"))==NULL) {
11096: printf("Problem with Health Exp. resultfile: %s\n", filerese); exit(0);
11097: fprintf(ficlog,"Problem with Health Exp. resultfile: %s\n", filerese); exit(0);
11098: }
1.208 brouard 11099: printf("Computing Health Expectancies: result on file '%s' ...", filerese);fflush(stdout);
11100: fprintf(ficlog,"Computing Health Expectancies: result on file '%s' ...", filerese);fflush(ficlog);
1.238 brouard 11101:
11102: pstamp(ficreseij);
1.219 brouard 11103:
1.235 brouard 11104: i1=pow(2,cptcoveff); /* Number of combination of dummy covariates */
11105: if (cptcovn < 1){i1=1;}
11106:
11107: for(nres=1; nres <= nresult; nres++) /* For each resultline */
11108: for(k=1; k<=i1;k++){ /* For any combination of dummy covariates, fixed and varying */
11109: if(TKresult[nres]!= k)
11110: continue;
1.219 brouard 11111: fprintf(ficreseij,"\n#****** ");
1.235 brouard 11112: printf("\n#****** ");
1.225 brouard 11113: for(j=1;j<=cptcoveff;j++) {
1.227 brouard 11114: fprintf(ficreseij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
1.235 brouard 11115: printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
11116: }
11117: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
11118: printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
11119: fprintf(ficreseij," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
1.219 brouard 11120: }
11121: fprintf(ficreseij,"******\n");
1.235 brouard 11122: printf("******\n");
1.219 brouard 11123:
11124: eij=ma3x(1,nlstate,1,nlstate,(int) bage, (int) fage);
11125: oldm=oldms;savm=savms;
1.235 brouard 11126: evsij(eij, p, nlstate, stepm, (int) bage, (int)fage, oldm, savm, k, estepm, strstart, nres);
1.127 brouard 11127:
1.219 brouard 11128: free_ma3x(eij,1,nlstate,1,nlstate,(int) bage, (int)fage);
1.127 brouard 11129: }
11130: fclose(ficreseij);
1.208 brouard 11131: printf("done evsij\n");fflush(stdout);
11132: fprintf(ficlog,"done evsij\n");fflush(ficlog);
1.218 brouard 11133:
1.227 brouard 11134: /*---------- State-specific expectancies and variances ------------*/
1.218 brouard 11135:
11136:
1.201 brouard 11137: strcpy(filerest,"T_");
11138: strcat(filerest,fileresu);
1.127 brouard 11139: if((ficrest=fopen(filerest,"w"))==NULL) {
11140: printf("Problem with total LE resultfile: %s\n", filerest);goto end;
11141: fprintf(ficlog,"Problem with total LE resultfile: %s\n", filerest);goto end;
11142: }
1.208 brouard 11143: printf("Computing Total Life expectancies with their standard errors: file '%s' ...\n", filerest); fflush(stdout);
11144: fprintf(ficlog,"Computing Total Life expectancies with their standard errors: file '%s' ...\n", filerest); fflush(ficlog);
1.218 brouard 11145:
1.126 brouard 11146:
1.201 brouard 11147: strcpy(fileresstde,"STDE_");
11148: strcat(fileresstde,fileresu);
1.126 brouard 11149: if((ficresstdeij=fopen(fileresstde,"w"))==NULL) {
1.227 brouard 11150: printf("Problem with State specific Exp. and std errors resultfile: %s\n", fileresstde); exit(0);
11151: fprintf(ficlog,"Problem with State specific Exp. and std errors resultfile: %s\n", fileresstde); exit(0);
1.126 brouard 11152: }
1.227 brouard 11153: printf(" Computing State-specific Expectancies and standard errors: result on file '%s' \n", fileresstde);
11154: fprintf(ficlog," Computing State-specific Expectancies and standard errors: result on file '%s' \n", fileresstde);
1.126 brouard 11155:
1.201 brouard 11156: strcpy(filerescve,"CVE_");
11157: strcat(filerescve,fileresu);
1.126 brouard 11158: if((ficrescveij=fopen(filerescve,"w"))==NULL) {
1.227 brouard 11159: printf("Problem with Covar. State-specific Exp. resultfile: %s\n", filerescve); exit(0);
11160: fprintf(ficlog,"Problem with Covar. State-specific Exp. resultfile: %s\n", filerescve); exit(0);
1.126 brouard 11161: }
1.227 brouard 11162: printf(" Computing Covar. of State-specific Expectancies: result on file '%s' \n", filerescve);
11163: fprintf(ficlog," Computing Covar. of State-specific Expectancies: result on file '%s' \n", filerescve);
1.126 brouard 11164:
1.201 brouard 11165: strcpy(fileresv,"V_");
11166: strcat(fileresv,fileresu);
1.126 brouard 11167: if((ficresvij=fopen(fileresv,"w"))==NULL) {
11168: printf("Problem with variance resultfile: %s\n", fileresv);exit(0);
11169: fprintf(ficlog,"Problem with variance resultfile: %s\n", fileresv);exit(0);
11170: }
1.227 brouard 11171: printf(" Computing Variance-covariance of State-specific Expectancies: file '%s' ... ", fileresv);fflush(stdout);
11172: fprintf(ficlog," Computing Variance-covariance of State-specific Expectancies: file '%s' ... ", fileresv);fflush(ficlog);
1.126 brouard 11173:
1.145 brouard 11174: /*for(cptcov=1,k=0;cptcov<=i1;cptcov++){
11175: for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){*/
11176:
1.235 brouard 11177: i1=pow(2,cptcoveff); /* Number of combination of dummy covariates */
11178: if (cptcovn < 1){i1=1;}
11179:
11180: for(nres=1; nres <= nresult; nres++) /* For each resultline */
11181: for(k=1; k<=i1;k++){ /* For any combination of dummy covariates, fixed and varying */
11182: if(TKresult[nres]!= k)
11183: continue;
1.242 brouard 11184: printf("\n#****** Result for:");
11185: fprintf(ficrest,"\n#****** Result for:");
11186: fprintf(ficlog,"\n#****** Result for:");
1.227 brouard 11187: for(j=1;j<=cptcoveff;j++){
11188: printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
11189: fprintf(ficrest,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
11190: fprintf(ficlog,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
11191: }
1.235 brouard 11192: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
11193: printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
11194: fprintf(ficrest," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
11195: fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
11196: }
1.208 brouard 11197: fprintf(ficrest,"******\n");
1.227 brouard 11198: fprintf(ficlog,"******\n");
11199: printf("******\n");
1.208 brouard 11200:
11201: fprintf(ficresstdeij,"\n#****** ");
11202: fprintf(ficrescveij,"\n#****** ");
1.225 brouard 11203: for(j=1;j<=cptcoveff;j++) {
1.227 brouard 11204: fprintf(ficresstdeij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
11205: fprintf(ficrescveij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
1.208 brouard 11206: }
1.235 brouard 11207: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
11208: fprintf(ficresstdeij," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
11209: fprintf(ficrescveij," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
11210: }
1.208 brouard 11211: fprintf(ficresstdeij,"******\n");
11212: fprintf(ficrescveij,"******\n");
11213:
11214: fprintf(ficresvij,"\n#****** ");
1.238 brouard 11215: /* pstamp(ficresvij); */
1.225 brouard 11216: for(j=1;j<=cptcoveff;j++)
1.227 brouard 11217: fprintf(ficresvij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
1.235 brouard 11218: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
11219: fprintf(ficresvij," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
11220: }
1.208 brouard 11221: fprintf(ficresvij,"******\n");
11222:
11223: eij=ma3x(1,nlstate,1,nlstate,(int) bage, (int) fage);
11224: oldm=oldms;savm=savms;
1.235 brouard 11225: printf(" cvevsij ");
11226: fprintf(ficlog, " cvevsij ");
11227: cvevsij(eij, p, nlstate, stepm, (int) bage, (int)fage, oldm, savm, k, estepm, delti, matcov, strstart, nres);
1.208 brouard 11228: printf(" end cvevsij \n ");
11229: fprintf(ficlog, " end cvevsij \n ");
11230:
11231: /*
11232: */
11233: /* goto endfree; */
11234:
11235: vareij=ma3x(1,nlstate,1,nlstate,(int) bage, (int) fage);
11236: pstamp(ficrest);
11237:
11238:
11239: for(vpopbased=0; vpopbased <= popbased; vpopbased++){ /* Done for vpopbased=0 and vpopbased=1 if popbased==1*/
1.227 brouard 11240: oldm=oldms;savm=savms; /* ZZ Segmentation fault */
11241: cptcod= 0; /* To be deleted */
11242: printf("varevsij vpopbased=%d \n",vpopbased);
11243: fprintf(ficlog, "varevsij vpopbased=%d \n",vpopbased);
1.235 brouard 11244: 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 11245: 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 ");
11246: if(vpopbased==1)
11247: 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);
11248: else
11249: fprintf(ficrest,"the age specific period (stable) prevalences in each health state \n");
11250: fprintf(ficrest,"# Age popbased mobilav e.. (std) ");
11251: for (i=1;i<=nlstate;i++) fprintf(ficrest,"e.%d (std) ",i);
11252: fprintf(ficrest,"\n");
11253: /* printf("Which p?\n"); for(i=1;i<=npar;i++)printf("p[i=%d]=%lf,",i,p[i]);printf("\n"); */
11254: epj=vector(1,nlstate+1);
11255: printf("Computing age specific period (stable) prevalences in each health state \n");
11256: fprintf(ficlog,"Computing age specific period (stable) prevalences in each health state \n");
11257: for(age=bage; age <=fage ;age++){
1.235 brouard 11258: prevalim(prlim, nlstate, p, age, oldm, savm, ftolpl, &ncvyear, k, nres); /*ZZ Is it the correct prevalim */
1.227 brouard 11259: if (vpopbased==1) {
11260: if(mobilav ==0){
11261: for(i=1; i<=nlstate;i++)
11262: prlim[i][i]=probs[(int)age][i][k];
11263: }else{ /* mobilav */
11264: for(i=1; i<=nlstate;i++)
11265: prlim[i][i]=mobaverage[(int)age][i][k];
11266: }
11267: }
1.219 brouard 11268:
1.227 brouard 11269: fprintf(ficrest," %4.0f %d %d",age, vpopbased, mobilav);
11270: /* fprintf(ficrest," %4.0f %d %d %d %d",age, vpopbased, mobilav,Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]); */ /* to be done */
11271: /* printf(" age %4.0f ",age); */
11272: for(j=1, epj[nlstate+1]=0.;j <=nlstate;j++){
11273: for(i=1, epj[j]=0.;i <=nlstate;i++) {
11274: epj[j] += prlim[i][i]*eij[i][j][(int)age];
11275: /*ZZZ printf("%lf %lf ", prlim[i][i] ,eij[i][j][(int)age]);*/
11276: /* printf("%lf %lf ", prlim[i][i] ,eij[i][j][(int)age]); */
11277: }
11278: epj[nlstate+1] +=epj[j];
11279: }
11280: /* printf(" age %4.0f \n",age); */
1.219 brouard 11281:
1.227 brouard 11282: for(i=1, vepp=0.;i <=nlstate;i++)
11283: for(j=1;j <=nlstate;j++)
11284: vepp += vareij[i][j][(int)age];
11285: fprintf(ficrest," %7.3f (%7.3f)", epj[nlstate+1],sqrt(vepp));
11286: for(j=1;j <=nlstate;j++){
11287: fprintf(ficrest," %7.3f (%7.3f)", epj[j],sqrt(vareij[j][j][(int)age]));
11288: }
11289: fprintf(ficrest,"\n");
11290: }
1.208 brouard 11291: } /* End vpopbased */
11292: free_ma3x(eij,1,nlstate,1,nlstate,(int) bage, (int)fage);
11293: free_ma3x(vareij,1,nlstate,1,nlstate,(int) bage, (int)fage);
11294: free_vector(epj,1,nlstate+1);
1.235 brouard 11295: printf("done selection\n");fflush(stdout);
11296: fprintf(ficlog,"done selection\n");fflush(ficlog);
1.208 brouard 11297:
1.145 brouard 11298: /*}*/
1.235 brouard 11299: } /* End k selection */
1.227 brouard 11300:
11301: printf("done State-specific expectancies\n");fflush(stdout);
11302: fprintf(ficlog,"done State-specific expectancies\n");fflush(ficlog);
11303:
1.126 brouard 11304: /*------- Variance of period (stable) prevalence------*/
1.227 brouard 11305:
1.201 brouard 11306: strcpy(fileresvpl,"VPL_");
11307: strcat(fileresvpl,fileresu);
1.126 brouard 11308: if((ficresvpl=fopen(fileresvpl,"w"))==NULL) {
11309: printf("Problem with variance of period (stable) prevalence resultfile: %s\n", fileresvpl);
11310: exit(0);
11311: }
1.208 brouard 11312: printf("Computing Variance-covariance of period (stable) prevalence: file '%s' ...", fileresvpl);fflush(stdout);
11313: fprintf(ficlog, "Computing Variance-covariance of period (stable) prevalence: file '%s' ...", fileresvpl);fflush(ficlog);
1.227 brouard 11314:
1.145 brouard 11315: /*for(cptcov=1,k=0;cptcov<=i1;cptcov++){
11316: for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){*/
1.227 brouard 11317:
1.235 brouard 11318: i1=pow(2,cptcoveff);
11319: if (cptcovn < 1){i1=1;}
11320:
11321: for(nres=1; nres <= nresult; nres++) /* For each resultline */
11322: for(k=1; k<=i1;k++){
11323: if(TKresult[nres]!= k)
11324: continue;
1.227 brouard 11325: fprintf(ficresvpl,"\n#****** ");
11326: printf("\n#****** ");
11327: fprintf(ficlog,"\n#****** ");
11328: for(j=1;j<=cptcoveff;j++) {
11329: fprintf(ficresvpl,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
11330: fprintf(ficlog,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
11331: printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
11332: }
1.235 brouard 11333: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
11334: printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
11335: fprintf(ficresvpl," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
11336: fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
11337: }
1.227 brouard 11338: fprintf(ficresvpl,"******\n");
11339: printf("******\n");
11340: fprintf(ficlog,"******\n");
11341:
11342: varpl=matrix(1,nlstate,(int) bage, (int) fage);
11343: oldm=oldms;savm=savms;
1.235 brouard 11344: varprevlim(fileres, varpl, matcov, p, delti, nlstate, stepm, (int) bage, (int) fage, oldm, savm, prlim, ftolpl, &ncvyear, k, strstart, nres);
1.227 brouard 11345: free_matrix(varpl,1,nlstate,(int) bage, (int)fage);
1.145 brouard 11346: /*}*/
1.126 brouard 11347: }
1.227 brouard 11348:
1.126 brouard 11349: fclose(ficresvpl);
1.208 brouard 11350: printf("done variance-covariance of period prevalence\n");fflush(stdout);
11351: fprintf(ficlog,"done variance-covariance of period prevalence\n");fflush(ficlog);
1.227 brouard 11352:
11353: free_vector(weight,1,n);
11354: free_imatrix(Tvard,1,NCOVMAX,1,2);
11355: free_imatrix(s,1,maxwav+1,1,n);
11356: free_matrix(anint,1,maxwav,1,n);
11357: free_matrix(mint,1,maxwav,1,n);
11358: free_ivector(cod,1,n);
11359: free_ivector(tab,1,NCOVMAX);
11360: fclose(ficresstdeij);
11361: fclose(ficrescveij);
11362: fclose(ficresvij);
11363: fclose(ficrest);
11364: fclose(ficpar);
11365:
11366:
1.126 brouard 11367: /*---------- End : free ----------------*/
1.219 brouard 11368: if (mobilav!=0 ||mobilavproj !=0)
11369: free_ma3x(mobaverages,1, AGESUP,1,nlstate+ndeath, 1,ncovcombmax); /* We need to have a squared matrix with prevalence of the dead! */
1.218 brouard 11370: free_ma3x(probs,1,AGESUP,1,nlstate+ndeath, 1,ncovcombmax);
1.220 brouard 11371: free_matrix(prlim,1,nlstate,1,nlstate); /*here or after loop ? */
11372: free_matrix(pmmij,1,nlstate+ndeath,1,nlstate+ndeath);
1.126 brouard 11373: } /* mle==-3 arrives here for freeing */
1.227 brouard 11374: /* endfree:*/
11375: free_matrix(oldms, 1,nlstate+ndeath,1,nlstate+ndeath);
11376: free_matrix(newms, 1,nlstate+ndeath,1,nlstate+ndeath);
11377: free_matrix(savms, 1,nlstate+ndeath,1,nlstate+ndeath);
11378: free_ma3x(cotqvar,1,maxwav,1,nqtv,1,n);
1.233 brouard 11379: free_ma3x(cotvar,1,maxwav,1,ntv+nqtv,1,n);
1.227 brouard 11380: free_matrix(coqvar,1,maxwav,1,n);
11381: free_matrix(covar,0,NCOVMAX,1,n);
11382: free_matrix(matcov,1,npar,1,npar);
11383: free_matrix(hess,1,npar,1,npar);
11384: /*free_vector(delti,1,npar);*/
11385: free_ma3x(delti3,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
11386: free_matrix(agev,1,maxwav,1,imx);
11387: free_ma3x(param,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
11388:
11389: free_ivector(ncodemax,1,NCOVMAX);
11390: free_ivector(ncodemaxwundef,1,NCOVMAX);
11391: free_ivector(Dummy,-1,NCOVMAX);
11392: free_ivector(Fixed,-1,NCOVMAX);
1.238 brouard 11393: free_ivector(DummyV,1,NCOVMAX);
11394: free_ivector(FixedV,1,NCOVMAX);
1.227 brouard 11395: free_ivector(Typevar,-1,NCOVMAX);
11396: free_ivector(Tvar,1,NCOVMAX);
1.234 brouard 11397: free_ivector(TvarsQ,1,NCOVMAX);
11398: free_ivector(TvarsQind,1,NCOVMAX);
11399: free_ivector(TvarsD,1,NCOVMAX);
11400: free_ivector(TvarsDind,1,NCOVMAX);
1.231 brouard 11401: free_ivector(TvarFD,1,NCOVMAX);
11402: free_ivector(TvarFDind,1,NCOVMAX);
1.232 brouard 11403: free_ivector(TvarF,1,NCOVMAX);
11404: free_ivector(TvarFind,1,NCOVMAX);
11405: free_ivector(TvarV,1,NCOVMAX);
11406: free_ivector(TvarVind,1,NCOVMAX);
11407: free_ivector(TvarA,1,NCOVMAX);
11408: free_ivector(TvarAind,1,NCOVMAX);
1.231 brouard 11409: free_ivector(TvarFQ,1,NCOVMAX);
11410: free_ivector(TvarFQind,1,NCOVMAX);
11411: free_ivector(TvarVD,1,NCOVMAX);
11412: free_ivector(TvarVDind,1,NCOVMAX);
11413: free_ivector(TvarVQ,1,NCOVMAX);
11414: free_ivector(TvarVQind,1,NCOVMAX);
1.230 brouard 11415: free_ivector(Tvarsel,1,NCOVMAX);
11416: free_vector(Tvalsel,1,NCOVMAX);
1.227 brouard 11417: free_ivector(Tposprod,1,NCOVMAX);
11418: free_ivector(Tprod,1,NCOVMAX);
11419: free_ivector(Tvaraff,1,NCOVMAX);
11420: free_ivector(invalidvarcomb,1,ncovcombmax);
11421: free_ivector(Tage,1,NCOVMAX);
11422: free_ivector(Tmodelind,1,NCOVMAX);
1.228 brouard 11423: free_ivector(TmodelInvind,1,NCOVMAX);
11424: free_ivector(TmodelInvQind,1,NCOVMAX);
1.227 brouard 11425:
11426: free_imatrix(nbcode,0,NCOVMAX,0,NCOVMAX);
11427: /* free_imatrix(codtab,1,100,1,10); */
1.126 brouard 11428: fflush(fichtm);
11429: fflush(ficgp);
11430:
1.227 brouard 11431:
1.126 brouard 11432: if((nberr >0) || (nbwarn>0)){
1.216 brouard 11433: printf("End of Imach with %d errors and/or %d warnings. Please look at the log file for details.\n",nberr,nbwarn);
11434: 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 11435: }else{
11436: printf("End of Imach\n");
11437: fprintf(ficlog,"End of Imach\n");
11438: }
11439: printf("See log file on %s\n",filelog);
11440: /* gettimeofday(&end_time, (struct timezone*)0);*/ /* after time */
1.157 brouard 11441: /*(void) gettimeofday(&end_time,&tzp);*/
11442: rend_time = time(NULL);
11443: end_time = *localtime(&rend_time);
11444: /* tml = *localtime(&end_time.tm_sec); */
11445: strcpy(strtend,asctime(&end_time));
1.126 brouard 11446: printf("Local time at start %s\nLocal time at end %s",strstart, strtend);
11447: fprintf(ficlog,"Local time at start %s\nLocal time at end %s\n",strstart, strtend);
1.157 brouard 11448: printf("Total time used %s\n", asc_diff_time(rend_time -rstart_time,tmpout));
1.227 brouard 11449:
1.157 brouard 11450: printf("Total time was %.0lf Sec.\n", difftime(rend_time,rstart_time));
11451: fprintf(ficlog,"Total time used %s\n", asc_diff_time(rend_time -rstart_time,tmpout));
11452: fprintf(ficlog,"Total time was %.0lf Sec.\n", difftime(rend_time,rstart_time));
1.126 brouard 11453: /* printf("Total time was %d uSec.\n", total_usecs);*/
11454: /* if(fileappend(fichtm,optionfilehtm)){ */
11455: fprintf(fichtm,"<br>Local time at start %s<br>Local time at end %s<br>\n</body></html>",strstart, strtend);
11456: fclose(fichtm);
11457: fprintf(fichtmcov,"<br>Local time at start %s<br>Local time at end %s<br>\n</body></html>",strstart, strtend);
11458: fclose(fichtmcov);
11459: fclose(ficgp);
11460: fclose(ficlog);
11461: /*------ End -----------*/
1.227 brouard 11462:
11463:
11464: printf("Before Current directory %s!\n",pathcd);
1.184 brouard 11465: #ifdef WIN32
1.227 brouard 11466: if (_chdir(pathcd) != 0)
11467: printf("Can't move to directory %s!\n",path);
11468: if(_getcwd(pathcd,MAXLINE) > 0)
1.184 brouard 11469: #else
1.227 brouard 11470: if(chdir(pathcd) != 0)
11471: printf("Can't move to directory %s!\n", path);
11472: if (getcwd(pathcd, MAXLINE) > 0)
1.184 brouard 11473: #endif
1.126 brouard 11474: printf("Current directory %s!\n",pathcd);
11475: /*strcat(plotcmd,CHARSEPARATOR);*/
11476: sprintf(plotcmd,"gnuplot");
1.157 brouard 11477: #ifdef _WIN32
1.126 brouard 11478: sprintf(plotcmd,"\"%sgnuplot.exe\"",pathimach);
11479: #endif
11480: if(!stat(plotcmd,&info)){
1.158 brouard 11481: printf("Error or gnuplot program not found: '%s'\n",plotcmd);fflush(stdout);
1.126 brouard 11482: if(!stat(getenv("GNUPLOTBIN"),&info)){
1.158 brouard 11483: printf("Error or gnuplot program not found: '%s' Environment GNUPLOTBIN not set.\n",plotcmd);fflush(stdout);
1.126 brouard 11484: }else
11485: strcpy(pplotcmd,plotcmd);
1.157 brouard 11486: #ifdef __unix
1.126 brouard 11487: strcpy(plotcmd,GNUPLOTPROGRAM);
11488: if(!stat(plotcmd,&info)){
1.158 brouard 11489: printf("Error gnuplot program not found: '%s'\n",plotcmd);fflush(stdout);
1.126 brouard 11490: }else
11491: strcpy(pplotcmd,plotcmd);
11492: #endif
11493: }else
11494: strcpy(pplotcmd,plotcmd);
11495:
11496: sprintf(plotcmd,"%s %s",pplotcmd, optionfilegnuplot);
1.158 brouard 11497: printf("Starting graphs with: '%s'\n",plotcmd);fflush(stdout);
1.227 brouard 11498:
1.126 brouard 11499: if((outcmd=system(plotcmd)) != 0){
1.158 brouard 11500: printf("gnuplot command might not be in your path: '%s', err=%d\n", plotcmd, outcmd);
1.154 brouard 11501: printf("\n Trying if gnuplot resides on the same directory that IMaCh\n");
1.152 brouard 11502: sprintf(plotcmd,"%sgnuplot %s", pathimach, optionfilegnuplot);
1.150 brouard 11503: if((outcmd=system(plotcmd)) != 0)
1.153 brouard 11504: printf("\n Still a problem with gnuplot command %s, err=%d\n", plotcmd, outcmd);
1.126 brouard 11505: }
1.158 brouard 11506: printf(" Successful, please wait...");
1.126 brouard 11507: while (z[0] != 'q') {
11508: /* chdir(path); */
1.154 brouard 11509: printf("\nType e to edit results with your browser, g to graph again and q for exit: ");
1.126 brouard 11510: scanf("%s",z);
11511: /* if (z[0] == 'c') system("./imach"); */
11512: if (z[0] == 'e') {
1.158 brouard 11513: #ifdef __APPLE__
1.152 brouard 11514: sprintf(pplotcmd, "open %s", optionfilehtm);
1.157 brouard 11515: #elif __linux
11516: sprintf(pplotcmd, "xdg-open %s", optionfilehtm);
1.153 brouard 11517: #else
1.152 brouard 11518: sprintf(pplotcmd, "%s", optionfilehtm);
1.153 brouard 11519: #endif
11520: printf("Starting browser with: %s",pplotcmd);fflush(stdout);
11521: system(pplotcmd);
1.126 brouard 11522: }
11523: else if (z[0] == 'g') system(plotcmd);
11524: else if (z[0] == 'q') exit(0);
11525: }
1.227 brouard 11526: end:
1.126 brouard 11527: while (z[0] != 'q') {
1.195 brouard 11528: printf("\nType q for exiting: "); fflush(stdout);
1.126 brouard 11529: scanf("%s",z);
11530: }
11531: }
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