Annotation of imach/src/imach.c, revision 1.268
1.268 ! brouard 1: /* $Id: imach.c,v 1.267 2017/05/13 10:25:05 brouard Exp $
1.126 brouard 2: $State: Exp $
1.163 brouard 3: $Log: imach.c,v $
1.268 ! brouard 4: Revision 1.267 2017/05/13 10:25:05 brouard
! 5: Summary: temporary save for backprojection
! 6:
1.267 brouard 7: Revision 1.266 2017/05/13 07:26:12 brouard
8: Summary: Version 0.99r13 (improvements and bugs fixed)
9:
1.266 brouard 10: Revision 1.265 2017/04/26 16:22:11 brouard
11: Summary: imach 0.99r13 Some bugs fixed
12:
1.265 brouard 13: Revision 1.264 2017/04/26 06:01:29 brouard
14: Summary: Labels in graphs
15:
1.264 brouard 16: Revision 1.263 2017/04/24 15:23:15 brouard
17: Summary: to save
18:
1.263 brouard 19: Revision 1.262 2017/04/18 16:48:12 brouard
20: *** empty log message ***
21:
1.262 brouard 22: Revision 1.261 2017/04/05 10:14:09 brouard
23: Summary: Bug in E_ as well as in T_ fixed nres-1 vs k1-1
24:
1.261 brouard 25: Revision 1.260 2017/04/04 17:46:59 brouard
26: Summary: Gnuplot indexations fixed (humm)
27:
1.260 brouard 28: Revision 1.259 2017/04/04 13:01:16 brouard
29: Summary: Some errors to warnings only if date of death is unknown but status is death we could set to pi3
30:
1.259 brouard 31: Revision 1.258 2017/04/03 10:17:47 brouard
32: Summary: Version 0.99r12
33:
34: Some cleanings, conformed with updated documentation.
35:
1.258 brouard 36: Revision 1.257 2017/03/29 16:53:30 brouard
37: Summary: Temp
38:
1.257 brouard 39: Revision 1.256 2017/03/27 05:50:23 brouard
40: Summary: Temporary
41:
1.256 brouard 42: Revision 1.255 2017/03/08 16:02:28 brouard
43: Summary: IMaCh version 0.99r10 bugs in gnuplot fixed
44:
1.255 brouard 45: Revision 1.254 2017/03/08 07:13:00 brouard
46: Summary: Fixing data parameter line
47:
1.254 brouard 48: Revision 1.253 2016/12/15 11:59:41 brouard
49: Summary: 0.99 in progress
50:
1.253 brouard 51: Revision 1.252 2016/09/15 21:15:37 brouard
52: *** empty log message ***
53:
1.252 brouard 54: Revision 1.251 2016/09/15 15:01:13 brouard
55: Summary: not working
56:
1.251 brouard 57: Revision 1.250 2016/09/08 16:07:27 brouard
58: Summary: continue
59:
1.250 brouard 60: Revision 1.249 2016/09/07 17:14:18 brouard
61: Summary: Starting values from frequencies
62:
1.249 brouard 63: Revision 1.248 2016/09/07 14:10:18 brouard
64: *** empty log message ***
65:
1.248 brouard 66: Revision 1.247 2016/09/02 11:11:21 brouard
67: *** empty log message ***
68:
1.247 brouard 69: Revision 1.246 2016/09/02 08:49:22 brouard
70: *** empty log message ***
71:
1.246 brouard 72: Revision 1.245 2016/09/02 07:25:01 brouard
73: *** empty log message ***
74:
1.245 brouard 75: Revision 1.244 2016/09/02 07:17:34 brouard
76: *** empty log message ***
77:
1.244 brouard 78: Revision 1.243 2016/09/02 06:45:35 brouard
79: *** empty log message ***
80:
1.243 brouard 81: Revision 1.242 2016/08/30 15:01:20 brouard
82: Summary: Fixing a lots
83:
1.242 brouard 84: Revision 1.241 2016/08/29 17:17:25 brouard
85: Summary: gnuplot problem in Back projection to fix
86:
1.241 brouard 87: Revision 1.240 2016/08/29 07:53:18 brouard
88: Summary: Better
89:
1.240 brouard 90: Revision 1.239 2016/08/26 15:51:03 brouard
91: Summary: Improvement in Powell output in order to copy and paste
92:
93: Author:
94:
1.239 brouard 95: Revision 1.238 2016/08/26 14:23:35 brouard
96: Summary: Starting tests of 0.99
97:
1.238 brouard 98: Revision 1.237 2016/08/26 09:20:19 brouard
99: Summary: to valgrind
100:
1.237 brouard 101: Revision 1.236 2016/08/25 10:50:18 brouard
102: *** empty log message ***
103:
1.236 brouard 104: Revision 1.235 2016/08/25 06:59:23 brouard
105: *** empty log message ***
106:
1.235 brouard 107: Revision 1.234 2016/08/23 16:51:20 brouard
108: *** empty log message ***
109:
1.234 brouard 110: Revision 1.233 2016/08/23 07:40:50 brouard
111: Summary: not working
112:
1.233 brouard 113: Revision 1.232 2016/08/22 14:20:21 brouard
114: Summary: not working
115:
1.232 brouard 116: Revision 1.231 2016/08/22 07:17:15 brouard
117: Summary: not working
118:
1.231 brouard 119: Revision 1.230 2016/08/22 06:55:53 brouard
120: Summary: Not working
121:
1.230 brouard 122: Revision 1.229 2016/07/23 09:45:53 brouard
123: Summary: Completing for func too
124:
1.229 brouard 125: Revision 1.228 2016/07/22 17:45:30 brouard
126: Summary: Fixing some arrays, still debugging
127:
1.227 brouard 128: Revision 1.226 2016/07/12 18:42:34 brouard
129: Summary: temp
130:
1.226 brouard 131: Revision 1.225 2016/07/12 08:40:03 brouard
132: Summary: saving but not running
133:
1.225 brouard 134: Revision 1.224 2016/07/01 13:16:01 brouard
135: Summary: Fixes
136:
1.224 brouard 137: Revision 1.223 2016/02/19 09:23:35 brouard
138: Summary: temporary
139:
1.223 brouard 140: Revision 1.222 2016/02/17 08:14:50 brouard
141: Summary: Probably last 0.98 stable version 0.98r6
142:
1.222 brouard 143: Revision 1.221 2016/02/15 23:35:36 brouard
144: Summary: minor bug
145:
1.220 brouard 146: Revision 1.219 2016/02/15 00:48:12 brouard
147: *** empty log message ***
148:
1.219 brouard 149: Revision 1.218 2016/02/12 11:29:23 brouard
150: Summary: 0.99 Back projections
151:
1.218 brouard 152: Revision 1.217 2015/12/23 17:18:31 brouard
153: Summary: Experimental backcast
154:
1.217 brouard 155: Revision 1.216 2015/12/18 17:32:11 brouard
156: Summary: 0.98r4 Warning and status=-2
157:
158: Version 0.98r4 is now:
159: - displaying an error when status is -1, date of interview unknown and date of death known;
160: - permitting a status -2 when the vital status is unknown at a known date of right truncation.
161: Older changes concerning s=-2, dating from 2005 have been supersed.
162:
1.216 brouard 163: Revision 1.215 2015/12/16 08:52:24 brouard
164: Summary: 0.98r4 working
165:
1.215 brouard 166: Revision 1.214 2015/12/16 06:57:54 brouard
167: Summary: temporary not working
168:
1.214 brouard 169: Revision 1.213 2015/12/11 18:22:17 brouard
170: Summary: 0.98r4
171:
1.213 brouard 172: Revision 1.212 2015/11/21 12:47:24 brouard
173: Summary: minor typo
174:
1.212 brouard 175: Revision 1.211 2015/11/21 12:41:11 brouard
176: Summary: 0.98r3 with some graph of projected cross-sectional
177:
178: Author: Nicolas Brouard
179:
1.211 brouard 180: Revision 1.210 2015/11/18 17:41:20 brouard
1.252 brouard 181: Summary: Start working on projected prevalences Revision 1.209 2015/11/17 22:12:03 brouard
1.210 brouard 182: Summary: Adding ftolpl parameter
183: Author: N Brouard
184:
185: We had difficulties to get smoothed confidence intervals. It was due
186: to the period prevalence which wasn't computed accurately. The inner
187: parameter ftolpl is now an outer parameter of the .imach parameter
188: file after estepm. If ftolpl is small 1.e-4 and estepm too,
189: computation are long.
190:
1.209 brouard 191: Revision 1.208 2015/11/17 14:31:57 brouard
192: Summary: temporary
193:
1.208 brouard 194: Revision 1.207 2015/10/27 17:36:57 brouard
195: *** empty log message ***
196:
1.207 brouard 197: Revision 1.206 2015/10/24 07:14:11 brouard
198: *** empty log message ***
199:
1.206 brouard 200: Revision 1.205 2015/10/23 15:50:53 brouard
201: Summary: 0.98r3 some clarification for graphs on likelihood contributions
202:
1.205 brouard 203: Revision 1.204 2015/10/01 16:20:26 brouard
204: Summary: Some new graphs of contribution to likelihood
205:
1.204 brouard 206: Revision 1.203 2015/09/30 17:45:14 brouard
207: Summary: looking at better estimation of the hessian
208:
209: Also a better criteria for convergence to the period prevalence And
210: therefore adding the number of years needed to converge. (The
211: prevalence in any alive state shold sum to one
212:
1.203 brouard 213: Revision 1.202 2015/09/22 19:45:16 brouard
214: Summary: Adding some overall graph on contribution to likelihood. Might change
215:
1.202 brouard 216: Revision 1.201 2015/09/15 17:34:58 brouard
217: Summary: 0.98r0
218:
219: - Some new graphs like suvival functions
220: - Some bugs fixed like model=1+age+V2.
221:
1.201 brouard 222: Revision 1.200 2015/09/09 16:53:55 brouard
223: Summary: Big bug thanks to Flavia
224:
225: Even model=1+age+V2. did not work anymore
226:
1.200 brouard 227: Revision 1.199 2015/09/07 14:09:23 brouard
228: Summary: 0.98q6 changing default small png format for graph to vectorized svg.
229:
1.199 brouard 230: Revision 1.198 2015/09/03 07:14:39 brouard
231: Summary: 0.98q5 Flavia
232:
1.198 brouard 233: Revision 1.197 2015/09/01 18:24:39 brouard
234: *** empty log message ***
235:
1.197 brouard 236: Revision 1.196 2015/08/18 23:17:52 brouard
237: Summary: 0.98q5
238:
1.196 brouard 239: Revision 1.195 2015/08/18 16:28:39 brouard
240: Summary: Adding a hack for testing purpose
241:
242: After reading the title, ftol and model lines, if the comment line has
243: a q, starting with #q, the answer at the end of the run is quit. It
244: permits to run test files in batch with ctest. The former workaround was
245: $ echo q | imach foo.imach
246:
1.195 brouard 247: Revision 1.194 2015/08/18 13:32:00 brouard
248: Summary: Adding error when the covariance matrix doesn't contain the exact number of lines required by the model line.
249:
1.194 brouard 250: Revision 1.193 2015/08/04 07:17:42 brouard
251: Summary: 0.98q4
252:
1.193 brouard 253: Revision 1.192 2015/07/16 16:49:02 brouard
254: Summary: Fixing some outputs
255:
1.192 brouard 256: Revision 1.191 2015/07/14 10:00:33 brouard
257: Summary: Some fixes
258:
1.191 brouard 259: Revision 1.190 2015/05/05 08:51:13 brouard
260: Summary: Adding digits in output parameters (7 digits instead of 6)
261:
262: Fix 1+age+.
263:
1.190 brouard 264: Revision 1.189 2015/04/30 14:45:16 brouard
265: Summary: 0.98q2
266:
1.189 brouard 267: Revision 1.188 2015/04/30 08:27:53 brouard
268: *** empty log message ***
269:
1.188 brouard 270: Revision 1.187 2015/04/29 09:11:15 brouard
271: *** empty log message ***
272:
1.187 brouard 273: Revision 1.186 2015/04/23 12:01:52 brouard
274: Summary: V1*age is working now, version 0.98q1
275:
276: Some codes had been disabled in order to simplify and Vn*age was
277: working in the optimization phase, ie, giving correct MLE parameters,
278: but, as usual, outputs were not correct and program core dumped.
279:
1.186 brouard 280: Revision 1.185 2015/03/11 13:26:42 brouard
281: Summary: Inclusion of compile and links command line for Intel Compiler
282:
1.185 brouard 283: Revision 1.184 2015/03/11 11:52:39 brouard
284: Summary: Back from Windows 8. Intel Compiler
285:
1.184 brouard 286: Revision 1.183 2015/03/10 20:34:32 brouard
287: Summary: 0.98q0, trying with directest, mnbrak fixed
288:
289: We use directest instead of original Powell test; probably no
290: incidence on the results, but better justifications;
291: We fixed Numerical Recipes mnbrak routine which was wrong and gave
292: wrong results.
293:
1.183 brouard 294: Revision 1.182 2015/02/12 08:19:57 brouard
295: Summary: Trying to keep directest which seems simpler and more general
296: Author: Nicolas Brouard
297:
1.182 brouard 298: Revision 1.181 2015/02/11 23:22:24 brouard
299: Summary: Comments on Powell added
300:
301: Author:
302:
1.181 brouard 303: Revision 1.180 2015/02/11 17:33:45 brouard
304: Summary: Finishing move from main to function (hpijx and prevalence_limit)
305:
1.180 brouard 306: Revision 1.179 2015/01/04 09:57:06 brouard
307: Summary: back to OS/X
308:
1.179 brouard 309: Revision 1.178 2015/01/04 09:35:48 brouard
310: *** empty log message ***
311:
1.178 brouard 312: Revision 1.177 2015/01/03 18:40:56 brouard
313: Summary: Still testing ilc32 on OSX
314:
1.177 brouard 315: Revision 1.176 2015/01/03 16:45:04 brouard
316: *** empty log message ***
317:
1.176 brouard 318: Revision 1.175 2015/01/03 16:33:42 brouard
319: *** empty log message ***
320:
1.175 brouard 321: Revision 1.174 2015/01/03 16:15:49 brouard
322: Summary: Still in cross-compilation
323:
1.174 brouard 324: Revision 1.173 2015/01/03 12:06:26 brouard
325: Summary: trying to detect cross-compilation
326:
1.173 brouard 327: Revision 1.172 2014/12/27 12:07:47 brouard
328: Summary: Back from Visual Studio and Intel, options for compiling for Windows XP
329:
1.172 brouard 330: Revision 1.171 2014/12/23 13:26:59 brouard
331: Summary: Back from Visual C
332:
333: Still problem with utsname.h on Windows
334:
1.171 brouard 335: Revision 1.170 2014/12/23 11:17:12 brouard
336: Summary: Cleaning some \%% back to %%
337:
338: The escape was mandatory for a specific compiler (which one?), but too many warnings.
339:
1.170 brouard 340: Revision 1.169 2014/12/22 23:08:31 brouard
341: Summary: 0.98p
342:
343: Outputs some informations on compiler used, OS etc. Testing on different platforms.
344:
1.169 brouard 345: Revision 1.168 2014/12/22 15:17:42 brouard
1.170 brouard 346: Summary: update
1.169 brouard 347:
1.168 brouard 348: Revision 1.167 2014/12/22 13:50:56 brouard
349: Summary: Testing uname and compiler version and if compiled 32 or 64
350:
351: Testing on Linux 64
352:
1.167 brouard 353: Revision 1.166 2014/12/22 11:40:47 brouard
354: *** empty log message ***
355:
1.166 brouard 356: Revision 1.165 2014/12/16 11:20:36 brouard
357: Summary: After compiling on Visual C
358:
359: * imach.c (Module): Merging 1.61 to 1.162
360:
1.165 brouard 361: Revision 1.164 2014/12/16 10:52:11 brouard
362: Summary: Merging with Visual C after suppressing some warnings for unused variables. Also fixing Saito's bug 0.98Xn
363:
364: * imach.c (Module): Merging 1.61 to 1.162
365:
1.164 brouard 366: Revision 1.163 2014/12/16 10:30:11 brouard
367: * imach.c (Module): Merging 1.61 to 1.162
368:
1.163 brouard 369: Revision 1.162 2014/09/25 11:43:39 brouard
370: Summary: temporary backup 0.99!
371:
1.162 brouard 372: Revision 1.1 2014/09/16 11:06:58 brouard
373: Summary: With some code (wrong) for nlopt
374:
375: Author:
376:
377: Revision 1.161 2014/09/15 20:41:41 brouard
378: Summary: Problem with macro SQR on Intel compiler
379:
1.161 brouard 380: Revision 1.160 2014/09/02 09:24:05 brouard
381: *** empty log message ***
382:
1.160 brouard 383: Revision 1.159 2014/09/01 10:34:10 brouard
384: Summary: WIN32
385: Author: Brouard
386:
1.159 brouard 387: Revision 1.158 2014/08/27 17:11:51 brouard
388: *** empty log message ***
389:
1.158 brouard 390: Revision 1.157 2014/08/27 16:26:55 brouard
391: Summary: Preparing windows Visual studio version
392: Author: Brouard
393:
394: In order to compile on Visual studio, time.h is now correct and time_t
395: and tm struct should be used. difftime should be used but sometimes I
396: just make the differences in raw time format (time(&now).
397: Trying to suppress #ifdef LINUX
398: Add xdg-open for __linux in order to open default browser.
399:
1.157 brouard 400: Revision 1.156 2014/08/25 20:10:10 brouard
401: *** empty log message ***
402:
1.156 brouard 403: Revision 1.155 2014/08/25 18:32:34 brouard
404: Summary: New compile, minor changes
405: Author: Brouard
406:
1.155 brouard 407: Revision 1.154 2014/06/20 17:32:08 brouard
408: Summary: Outputs now all graphs of convergence to period prevalence
409:
1.154 brouard 410: Revision 1.153 2014/06/20 16:45:46 brouard
411: Summary: If 3 live state, convergence to period prevalence on same graph
412: Author: Brouard
413:
1.153 brouard 414: Revision 1.152 2014/06/18 17:54:09 brouard
415: Summary: open browser, use gnuplot on same dir than imach if not found in the path
416:
1.152 brouard 417: Revision 1.151 2014/06/18 16:43:30 brouard
418: *** empty log message ***
419:
1.151 brouard 420: Revision 1.150 2014/06/18 16:42:35 brouard
421: Summary: If gnuplot is not in the path try on same directory than imach binary (OSX)
422: Author: brouard
423:
1.150 brouard 424: Revision 1.149 2014/06/18 15:51:14 brouard
425: Summary: Some fixes in parameter files errors
426: Author: Nicolas Brouard
427:
1.149 brouard 428: Revision 1.148 2014/06/17 17:38:48 brouard
429: Summary: Nothing new
430: Author: Brouard
431:
432: Just a new packaging for OS/X version 0.98nS
433:
1.148 brouard 434: Revision 1.147 2014/06/16 10:33:11 brouard
435: *** empty log message ***
436:
1.147 brouard 437: Revision 1.146 2014/06/16 10:20:28 brouard
438: Summary: Merge
439: Author: Brouard
440:
441: Merge, before building revised version.
442:
1.146 brouard 443: Revision 1.145 2014/06/10 21:23:15 brouard
444: Summary: Debugging with valgrind
445: Author: Nicolas Brouard
446:
447: Lot of changes in order to output the results with some covariates
448: After the Edimburgh REVES conference 2014, it seems mandatory to
449: improve the code.
450: No more memory valgrind error but a lot has to be done in order to
451: continue the work of splitting the code into subroutines.
452: Also, decodemodel has been improved. Tricode is still not
453: optimal. nbcode should be improved. Documentation has been added in
454: the source code.
455:
1.144 brouard 456: Revision 1.143 2014/01/26 09:45:38 brouard
457: Summary: Version 0.98nR (to be improved, but gives same optimization results as 0.98k. Nice, promising
458:
459: * imach.c (Module): Trying to merge old staffs together while being at Tokyo. Not tested...
460: (Module): Version 0.98nR Running ok, but output format still only works for three covariates.
461:
1.143 brouard 462: Revision 1.142 2014/01/26 03:57:36 brouard
463: Summary: gnuplot changed plot w l 1 has to be changed to plot w l lt 2
464:
465: * imach.c (Module): Trying to merge old staffs together while being at Tokyo. Not tested...
466:
1.142 brouard 467: Revision 1.141 2014/01/26 02:42:01 brouard
468: * imach.c (Module): Trying to merge old staffs together while being at Tokyo. Not tested...
469:
1.141 brouard 470: Revision 1.140 2011/09/02 10:37:54 brouard
471: Summary: times.h is ok with mingw32 now.
472:
1.140 brouard 473: Revision 1.139 2010/06/14 07:50:17 brouard
474: After the theft of my laptop, I probably lost some lines of codes which were not uploaded to the CVS tree.
475: I remember having already fixed agemin agemax which are pointers now but not cvs saved.
476:
1.139 brouard 477: Revision 1.138 2010/04/30 18:19:40 brouard
478: *** empty log message ***
479:
1.138 brouard 480: Revision 1.137 2010/04/29 18:11:38 brouard
481: (Module): Checking covariates for more complex models
482: than V1+V2. A lot of change to be done. Unstable.
483:
1.137 brouard 484: Revision 1.136 2010/04/26 20:30:53 brouard
485: (Module): merging some libgsl code. Fixing computation
486: of likelione (using inter/intrapolation if mle = 0) in order to
487: get same likelihood as if mle=1.
488: Some cleaning of code and comments added.
489:
1.136 brouard 490: Revision 1.135 2009/10/29 15:33:14 brouard
491: (Module): Now imach stops if date of birth, at least year of birth, is not given. Some cleaning of the code.
492:
1.135 brouard 493: Revision 1.134 2009/10/29 13:18:53 brouard
494: (Module): Now imach stops if date of birth, at least year of birth, is not given. Some cleaning of the code.
495:
1.134 brouard 496: Revision 1.133 2009/07/06 10:21:25 brouard
497: just nforces
498:
1.133 brouard 499: Revision 1.132 2009/07/06 08:22:05 brouard
500: Many tings
501:
1.132 brouard 502: Revision 1.131 2009/06/20 16:22:47 brouard
503: Some dimensions resccaled
504:
1.131 brouard 505: Revision 1.130 2009/05/26 06:44:34 brouard
506: (Module): Max Covariate is now set to 20 instead of 8. A
507: lot of cleaning with variables initialized to 0. Trying to make
508: V2+V3*age+V1+V4 strb=V3*age+V1+V4 working better.
509:
1.130 brouard 510: Revision 1.129 2007/08/31 13:49:27 lievre
511: Modification of the way of exiting when the covariate is not binary in order to see on the window the error message before exiting
512:
1.129 lievre 513: Revision 1.128 2006/06/30 13:02:05 brouard
514: (Module): Clarifications on computing e.j
515:
1.128 brouard 516: Revision 1.127 2006/04/28 18:11:50 brouard
517: (Module): Yes the sum of survivors was wrong since
518: imach-114 because nhstepm was no more computed in the age
519: loop. Now we define nhstepma in the age loop.
520: (Module): In order to speed up (in case of numerous covariates) we
521: compute health expectancies (without variances) in a first step
522: and then all the health expectancies with variances or standard
523: deviation (needs data from the Hessian matrices) which slows the
524: computation.
525: In the future we should be able to stop the program is only health
526: expectancies and graph are needed without standard deviations.
527:
1.127 brouard 528: Revision 1.126 2006/04/28 17:23:28 brouard
529: (Module): Yes the sum of survivors was wrong since
530: imach-114 because nhstepm was no more computed in the age
531: loop. Now we define nhstepma in the age loop.
532: Version 0.98h
533:
1.126 brouard 534: Revision 1.125 2006/04/04 15:20:31 lievre
535: Errors in calculation of health expectancies. Age was not initialized.
536: Forecasting file added.
537:
538: Revision 1.124 2006/03/22 17:13:53 lievre
539: Parameters are printed with %lf instead of %f (more numbers after the comma).
540: The log-likelihood is printed in the log file
541:
542: Revision 1.123 2006/03/20 10:52:43 brouard
543: * imach.c (Module): <title> changed, corresponds to .htm file
544: name. <head> headers where missing.
545:
546: * imach.c (Module): Weights can have a decimal point as for
547: English (a comma might work with a correct LC_NUMERIC environment,
548: otherwise the weight is truncated).
549: Modification of warning when the covariates values are not 0 or
550: 1.
551: Version 0.98g
552:
553: Revision 1.122 2006/03/20 09:45:41 brouard
554: (Module): Weights can have a decimal point as for
555: English (a comma might work with a correct LC_NUMERIC environment,
556: otherwise the weight is truncated).
557: Modification of warning when the covariates values are not 0 or
558: 1.
559: Version 0.98g
560:
561: Revision 1.121 2006/03/16 17:45:01 lievre
562: * imach.c (Module): Comments concerning covariates added
563:
564: * imach.c (Module): refinements in the computation of lli if
565: status=-2 in order to have more reliable computation if stepm is
566: not 1 month. Version 0.98f
567:
568: Revision 1.120 2006/03/16 15:10:38 lievre
569: (Module): refinements in the computation of lli if
570: status=-2 in order to have more reliable computation if stepm is
571: not 1 month. Version 0.98f
572:
573: Revision 1.119 2006/03/15 17:42:26 brouard
574: (Module): Bug if status = -2, the loglikelihood was
575: computed as likelihood omitting the logarithm. Version O.98e
576:
577: Revision 1.118 2006/03/14 18:20:07 brouard
578: (Module): varevsij Comments added explaining the second
579: table of variances if popbased=1 .
580: (Module): Covariances of eij, ekl added, graphs fixed, new html link.
581: (Module): Function pstamp added
582: (Module): Version 0.98d
583:
584: Revision 1.117 2006/03/14 17:16:22 brouard
585: (Module): varevsij Comments added explaining the second
586: table of variances if popbased=1 .
587: (Module): Covariances of eij, ekl added, graphs fixed, new html link.
588: (Module): Function pstamp added
589: (Module): Version 0.98d
590:
591: Revision 1.116 2006/03/06 10:29:27 brouard
592: (Module): Variance-covariance wrong links and
593: varian-covariance of ej. is needed (Saito).
594:
595: Revision 1.115 2006/02/27 12:17:45 brouard
596: (Module): One freematrix added in mlikeli! 0.98c
597:
598: Revision 1.114 2006/02/26 12:57:58 brouard
599: (Module): Some improvements in processing parameter
600: filename with strsep.
601:
602: Revision 1.113 2006/02/24 14:20:24 brouard
603: (Module): Memory leaks checks with valgrind and:
604: datafile was not closed, some imatrix were not freed and on matrix
605: allocation too.
606:
607: Revision 1.112 2006/01/30 09:55:26 brouard
608: (Module): Back to gnuplot.exe instead of wgnuplot.exe
609:
610: Revision 1.111 2006/01/25 20:38:18 brouard
611: (Module): Lots of cleaning and bugs added (Gompertz)
612: (Module): Comments can be added in data file. Missing date values
613: can be a simple dot '.'.
614:
615: Revision 1.110 2006/01/25 00:51:50 brouard
616: (Module): Lots of cleaning and bugs added (Gompertz)
617:
618: Revision 1.109 2006/01/24 19:37:15 brouard
619: (Module): Comments (lines starting with a #) are allowed in data.
620:
621: Revision 1.108 2006/01/19 18:05:42 lievre
622: Gnuplot problem appeared...
623: To be fixed
624:
625: Revision 1.107 2006/01/19 16:20:37 brouard
626: Test existence of gnuplot in imach path
627:
628: Revision 1.106 2006/01/19 13:24:36 brouard
629: Some cleaning and links added in html output
630:
631: Revision 1.105 2006/01/05 20:23:19 lievre
632: *** empty log message ***
633:
634: Revision 1.104 2005/09/30 16:11:43 lievre
635: (Module): sump fixed, loop imx fixed, and simplifications.
636: (Module): If the status is missing at the last wave but we know
637: that the person is alive, then we can code his/her status as -2
638: (instead of missing=-1 in earlier versions) and his/her
639: contributions to the likelihood is 1 - Prob of dying from last
640: health status (= 1-p13= p11+p12 in the easiest case of somebody in
641: the healthy state at last known wave). Version is 0.98
642:
643: Revision 1.103 2005/09/30 15:54:49 lievre
644: (Module): sump fixed, loop imx fixed, and simplifications.
645:
646: Revision 1.102 2004/09/15 17:31:30 brouard
647: Add the possibility to read data file including tab characters.
648:
649: Revision 1.101 2004/09/15 10:38:38 brouard
650: Fix on curr_time
651:
652: Revision 1.100 2004/07/12 18:29:06 brouard
653: Add version for Mac OS X. Just define UNIX in Makefile
654:
655: Revision 1.99 2004/06/05 08:57:40 brouard
656: *** empty log message ***
657:
658: Revision 1.98 2004/05/16 15:05:56 brouard
659: New version 0.97 . First attempt to estimate force of mortality
660: directly from the data i.e. without the need of knowing the health
661: state at each age, but using a Gompertz model: log u =a + b*age .
662: This is the basic analysis of mortality and should be done before any
663: other analysis, in order to test if the mortality estimated from the
664: cross-longitudinal survey is different from the mortality estimated
665: from other sources like vital statistic data.
666:
667: The same imach parameter file can be used but the option for mle should be -3.
668:
1.133 brouard 669: Agnès, who wrote this part of the code, tried to keep most of the
1.126 brouard 670: former routines in order to include the new code within the former code.
671:
672: The output is very simple: only an estimate of the intercept and of
673: the slope with 95% confident intervals.
674:
675: Current limitations:
676: A) Even if you enter covariates, i.e. with the
677: model= V1+V2 equation for example, the programm does only estimate a unique global model without covariates.
678: B) There is no computation of Life Expectancy nor Life Table.
679:
680: Revision 1.97 2004/02/20 13:25:42 lievre
681: Version 0.96d. Population forecasting command line is (temporarily)
682: suppressed.
683:
684: Revision 1.96 2003/07/15 15:38:55 brouard
685: * imach.c (Repository): Errors in subdirf, 2, 3 while printing tmpout is
686: rewritten within the same printf. Workaround: many printfs.
687:
688: Revision 1.95 2003/07/08 07:54:34 brouard
689: * imach.c (Repository):
690: (Repository): Using imachwizard code to output a more meaningful covariance
691: matrix (cov(a12,c31) instead of numbers.
692:
693: Revision 1.94 2003/06/27 13:00:02 brouard
694: Just cleaning
695:
696: Revision 1.93 2003/06/25 16:33:55 brouard
697: (Module): On windows (cygwin) function asctime_r doesn't
698: exist so I changed back to asctime which exists.
699: (Module): Version 0.96b
700:
701: Revision 1.92 2003/06/25 16:30:45 brouard
702: (Module): On windows (cygwin) function asctime_r doesn't
703: exist so I changed back to asctime which exists.
704:
705: Revision 1.91 2003/06/25 15:30:29 brouard
706: * imach.c (Repository): Duplicated warning errors corrected.
707: (Repository): Elapsed time after each iteration is now output. It
708: helps to forecast when convergence will be reached. Elapsed time
709: is stamped in powell. We created a new html file for the graphs
710: concerning matrix of covariance. It has extension -cov.htm.
711:
712: Revision 1.90 2003/06/24 12:34:15 brouard
713: (Module): Some bugs corrected for windows. Also, when
714: mle=-1 a template is output in file "or"mypar.txt with the design
715: of the covariance matrix to be input.
716:
717: Revision 1.89 2003/06/24 12:30:52 brouard
718: (Module): Some bugs corrected for windows. Also, when
719: mle=-1 a template is output in file "or"mypar.txt with the design
720: of the covariance matrix to be input.
721:
722: Revision 1.88 2003/06/23 17:54:56 brouard
723: * 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.
724:
725: Revision 1.87 2003/06/18 12:26:01 brouard
726: Version 0.96
727:
728: Revision 1.86 2003/06/17 20:04:08 brouard
729: (Module): Change position of html and gnuplot routines and added
730: routine fileappend.
731:
732: Revision 1.85 2003/06/17 13:12:43 brouard
733: * imach.c (Repository): Check when date of death was earlier that
734: current date of interview. It may happen when the death was just
735: prior to the death. In this case, dh was negative and likelihood
736: was wrong (infinity). We still send an "Error" but patch by
737: assuming that the date of death was just one stepm after the
738: interview.
739: (Repository): Because some people have very long ID (first column)
740: we changed int to long in num[] and we added a new lvector for
741: memory allocation. But we also truncated to 8 characters (left
742: truncation)
743: (Repository): No more line truncation errors.
744:
745: Revision 1.84 2003/06/13 21:44:43 brouard
746: * imach.c (Repository): Replace "freqsummary" at a correct
747: place. It differs from routine "prevalence" which may be called
748: many times. Probs is memory consuming and must be used with
749: parcimony.
750: Version 0.95a3 (should output exactly the same maximization than 0.8a2)
751:
752: Revision 1.83 2003/06/10 13:39:11 lievre
753: *** empty log message ***
754:
755: Revision 1.82 2003/06/05 15:57:20 brouard
756: Add log in imach.c and fullversion number is now printed.
757:
758: */
759: /*
760: Interpolated Markov Chain
761:
762: Short summary of the programme:
763:
1.227 brouard 764: This program computes Healthy Life Expectancies or State-specific
765: (if states aren't health statuses) Expectancies from
766: cross-longitudinal data. Cross-longitudinal data consist in:
767:
768: -1- a first survey ("cross") where individuals from different ages
769: are interviewed on their health status or degree of disability (in
770: the case of a health survey which is our main interest)
771:
772: -2- at least a second wave of interviews ("longitudinal") which
773: measure each change (if any) in individual health status. Health
774: expectancies are computed from the time spent in each health state
775: according to a model. More health states you consider, more time is
776: necessary to reach the Maximum Likelihood of the parameters involved
777: in the model. The simplest model is the multinomial logistic model
778: where pij is the probability to be observed in state j at the second
779: wave conditional to be observed in state i at the first
780: wave. Therefore the model is: log(pij/pii)= aij + bij*age+ cij*sex +
781: etc , where 'age' is age and 'sex' is a covariate. If you want to
782: have a more complex model than "constant and age", you should modify
783: the program where the markup *Covariates have to be included here
784: again* invites you to do it. More covariates you add, slower the
1.126 brouard 785: convergence.
786:
787: The advantage of this computer programme, compared to a simple
788: multinomial logistic model, is clear when the delay between waves is not
789: identical for each individual. Also, if a individual missed an
790: intermediate interview, the information is lost, but taken into
791: account using an interpolation or extrapolation.
792:
793: hPijx is the probability to be observed in state i at age x+h
794: conditional to the observed state i at age x. The delay 'h' can be
795: split into an exact number (nh*stepm) of unobserved intermediate
796: states. This elementary transition (by month, quarter,
797: semester or year) is modelled as a multinomial logistic. The hPx
798: matrix is simply the matrix product of nh*stepm elementary matrices
799: and the contribution of each individual to the likelihood is simply
800: hPijx.
801:
802: Also this programme outputs the covariance matrix of the parameters but also
1.218 brouard 803: of the life expectancies. It also computes the period (stable) prevalence.
804:
805: Back prevalence and projections:
1.227 brouard 806:
807: - back_prevalence_limit(double *p, double **bprlim, double ageminpar,
808: double agemaxpar, double ftolpl, int *ncvyearp, double
809: dateprev1,double dateprev2, int firstpass, int lastpass, int
810: mobilavproj)
811:
812: Computes the back prevalence limit for any combination of
813: covariate values k at any age between ageminpar and agemaxpar and
814: returns it in **bprlim. In the loops,
815:
816: - **bprevalim(**bprlim, ***mobaverage, nlstate, *p, age, **oldm,
817: **savm, **dnewm, **doldm, **dsavm, ftolpl, ncvyearp, k);
818:
819: - hBijx Back Probability to be in state i at age x-h being in j at x
1.218 brouard 820: Computes for any combination of covariates k and any age between bage and fage
821: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
822: oldm=oldms;savm=savms;
1.227 brouard 823:
1.267 brouard 824: - hbxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k, nres);
1.218 brouard 825: Computes the transition matrix starting at age 'age' over
826: 'nhstepm*hstepm*stepm' months (i.e. until
827: age (in years) age+nhstepm*hstepm*stepm/12) by multiplying
1.227 brouard 828: nhstepm*hstepm matrices.
829:
830: Returns p3mat[i][j][h] after calling
831: p3mat[i][j][h]=matprod2(newm,
832: bmij(pmmij,cov,ncovmodel,x,nlstate,prevacurrent, dnewm, doldm,
833: dsavm,ij),\ 1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath,
834: oldm);
1.226 brouard 835:
836: Important routines
837:
838: - func (or funcone), computes logit (pij) distinguishing
839: o fixed variables (single or product dummies or quantitative);
840: o varying variables by:
841: (1) wave (single, product dummies, quantitative),
842: (2) by age (can be month) age (done), age*age (done), age*Vn where Vn can be:
843: % fixed dummy (treated) or quantitative (not done because time-consuming);
844: % varying dummy (not done) or quantitative (not done);
845: - Tricode which tests the modality of dummy variables (in order to warn with wrong or empty modalities)
846: and returns the number of efficient covariates cptcoveff and modalities nbcode[Tvar[k]][1]= 0 and nbcode[Tvar[k]][2]= 1 usually.
847: - printinghtml which outputs results like life expectancy in and from a state for a combination of modalities of dummy variables
848: o There are 2*cptcoveff combinations of (0,1) for cptcoveff variables. Outputting only combinations with people, éliminating 1 1 if
849: race White (0 0), Black vs White (1 0), Hispanic (0 1) and 1 1 being meaningless.
1.218 brouard 850:
1.226 brouard 851:
852:
1.133 brouard 853: Authors: Nicolas Brouard (brouard@ined.fr) and Agnès Lièvre (lievre@ined.fr).
854: Institut national d'études démographiques, Paris.
1.126 brouard 855: This software have been partly granted by Euro-REVES, a concerted action
856: from the European Union.
857: It is copyrighted identically to a GNU software product, ie programme and
858: software can be distributed freely for non commercial use. Latest version
859: can be accessed at http://euroreves.ined.fr/imach .
860:
861: Help to debug: LD_PRELOAD=/usr/local/lib/libnjamd.so ./imach foo.imach
862: or better on gdb : set env LD_PRELOAD=/usr/local/lib/libnjamd.so
863:
864: **********************************************************************/
865: /*
866: main
867: read parameterfile
868: read datafile
869: concatwav
870: freqsummary
871: if (mle >= 1)
872: mlikeli
873: print results files
874: if mle==1
875: computes hessian
876: read end of parameter file: agemin, agemax, bage, fage, estepm
877: begin-prev-date,...
878: open gnuplot file
879: open html file
1.145 brouard 880: period (stable) prevalence | pl_nom 1-1 2-2 etc by covariate
881: for age prevalim() | #****** V1=0 V2=1 V3=1 V4=0 ******
882: | 65 1 0 2 1 3 1 4 0 0.96326 0.03674
883: freexexit2 possible for memory heap.
884:
885: h Pij x | pij_nom ficrestpij
886: # Cov Agex agex+h hpijx with i,j= 1-1 1-2 1-3 2-1 2-2 2-3
887: 1 85 85 1.00000 0.00000 0.00000 0.00000 1.00000 0.00000
888: 1 85 86 0.68299 0.22291 0.09410 0.71093 0.00000 0.28907
889:
890: 1 65 99 0.00364 0.00322 0.99314 0.00350 0.00310 0.99340
891: 1 65 100 0.00214 0.00204 0.99581 0.00206 0.00196 0.99597
892: variance of p one-step probabilities varprob | prob_nom ficresprob #One-step probabilities and stand. devi in ()
893: Standard deviation of one-step probabilities | probcor_nom ficresprobcor #One-step probabilities and correlation matrix
894: Matrix of variance covariance of one-step probabilities | probcov_nom ficresprobcov #One-step probabilities and covariance matrix
895:
1.126 brouard 896: forecasting if prevfcast==1 prevforecast call prevalence()
897: health expectancies
898: Variance-covariance of DFLE
899: prevalence()
900: movingaverage()
901: varevsij()
902: if popbased==1 varevsij(,popbased)
903: total life expectancies
904: Variance of period (stable) prevalence
905: end
906: */
907:
1.187 brouard 908: /* #define DEBUG */
909: /* #define DEBUGBRENT */
1.203 brouard 910: /* #define DEBUGLINMIN */
911: /* #define DEBUGHESS */
912: #define DEBUGHESSIJ
1.224 brouard 913: /* #define LINMINORIGINAL /\* Don't use loop on scale in linmin (accepting nan) *\/ */
1.165 brouard 914: #define POWELL /* Instead of NLOPT */
1.224 brouard 915: #define POWELLNOF3INFF1TEST /* Skip test */
1.186 brouard 916: /* #define POWELLORIGINAL /\* Don't use Directest to decide new direction but original Powell test *\/ */
917: /* #define MNBRAKORIGINAL /\* Don't use mnbrak fix *\/ */
1.126 brouard 918:
919: #include <math.h>
920: #include <stdio.h>
921: #include <stdlib.h>
922: #include <string.h>
1.226 brouard 923: #include <ctype.h>
1.159 brouard 924:
925: #ifdef _WIN32
926: #include <io.h>
1.172 brouard 927: #include <windows.h>
928: #include <tchar.h>
1.159 brouard 929: #else
1.126 brouard 930: #include <unistd.h>
1.159 brouard 931: #endif
1.126 brouard 932:
933: #include <limits.h>
934: #include <sys/types.h>
1.171 brouard 935:
936: #if defined(__GNUC__)
937: #include <sys/utsname.h> /* Doesn't work on Windows */
938: #endif
939:
1.126 brouard 940: #include <sys/stat.h>
941: #include <errno.h>
1.159 brouard 942: /* extern int errno; */
1.126 brouard 943:
1.157 brouard 944: /* #ifdef LINUX */
945: /* #include <time.h> */
946: /* #include "timeval.h" */
947: /* #else */
948: /* #include <sys/time.h> */
949: /* #endif */
950:
1.126 brouard 951: #include <time.h>
952:
1.136 brouard 953: #ifdef GSL
954: #include <gsl/gsl_errno.h>
955: #include <gsl/gsl_multimin.h>
956: #endif
957:
1.167 brouard 958:
1.162 brouard 959: #ifdef NLOPT
960: #include <nlopt.h>
961: typedef struct {
962: double (* function)(double [] );
963: } myfunc_data ;
964: #endif
965:
1.126 brouard 966: /* #include <libintl.h> */
967: /* #define _(String) gettext (String) */
968:
1.251 brouard 969: #define MAXLINE 2048 /* Was 256 and 1024. Overflow with 312 with 2 states and 4 covariates. Should be ok */
1.126 brouard 970:
971: #define GNUPLOTPROGRAM "gnuplot"
972: /*#define GNUPLOTPROGRAM "..\\gp37mgw\\wgnuplot"*/
973: #define FILENAMELENGTH 132
974:
975: #define GLOCK_ERROR_NOPATH -1 /* empty path */
976: #define GLOCK_ERROR_GETCWD -2 /* cannot get cwd */
977:
1.144 brouard 978: #define MAXPARM 128 /**< Maximum number of parameters for the optimization */
979: #define NPARMAX 64 /**< (nlstate+ndeath-1)*nlstate*ncovmodel */
1.126 brouard 980:
981: #define NINTERVMAX 8
1.144 brouard 982: #define NLSTATEMAX 8 /**< Maximum number of live states (for func) */
983: #define NDEATHMAX 8 /**< Maximum number of dead states (for func) */
984: #define NCOVMAX 20 /**< Maximum number of covariates, including generated covariates V1*V2 */
1.197 brouard 985: #define codtabm(h,k) (1 & (h-1) >> (k-1))+1
1.211 brouard 986: /*#define decodtabm(h,k,cptcoveff)= (h <= (1<<cptcoveff)?(((h-1) >> (k-1)) & 1) +1 : -1)*/
987: #define decodtabm(h,k,cptcoveff) (((h-1) >> (k-1)) & 1) +1
1.126 brouard 988: #define MAXN 20000
1.144 brouard 989: #define YEARM 12. /**< Number of months per year */
1.218 brouard 990: /* #define AGESUP 130 */
991: #define AGESUP 150
1.268 ! brouard 992: #define AGEINF 0
1.218 brouard 993: #define AGEMARGE 25 /* Marge for agemin and agemax for(iage=agemin-AGEMARGE; iage <= agemax+3+AGEMARGE; iage++) */
1.126 brouard 994: #define AGEBASE 40
1.194 brouard 995: #define AGEOVERFLOW 1.e20
1.164 brouard 996: #define AGEGOMP 10 /**< Minimal age for Gompertz adjustment */
1.157 brouard 997: #ifdef _WIN32
998: #define DIRSEPARATOR '\\'
999: #define CHARSEPARATOR "\\"
1000: #define ODIRSEPARATOR '/'
1001: #else
1.126 brouard 1002: #define DIRSEPARATOR '/'
1003: #define CHARSEPARATOR "/"
1004: #define ODIRSEPARATOR '\\'
1005: #endif
1006:
1.268 ! brouard 1007: /* $Id: imach.c,v 1.267 2017/05/13 10:25:05 brouard Exp $ */
1.126 brouard 1008: /* $State: Exp $ */
1.196 brouard 1009: #include "version.h"
1010: char version[]=__IMACH_VERSION__;
1.224 brouard 1011: 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";
1.268 ! brouard 1012: char fullversion[]="$Revision: 1.267 $ $Date: 2017/05/13 10:25:05 $";
1.126 brouard 1013: char strstart[80];
1014: char optionfilext[10], optionfilefiname[FILENAMELENGTH];
1.130 brouard 1015: int erreur=0, nberr=0, nbwarn=0; /* Error number, number of errors number of warnings */
1.187 brouard 1016: int nagesqr=0, nforce=0; /* nagesqr=1 if model is including age*age, number of forces */
1.145 brouard 1017: /* Number of covariates model=V2+V1+ V3*age+V2*V4 */
1018: int cptcovn=0; /**< cptcovn number of covariates added in the model (excepting constant and age and age*product) */
1019: int cptcovt=0; /**< cptcovt number of covariates added in the model (excepting constant and age) */
1.225 brouard 1020: int cptcovs=0; /**< cptcovs number of simple covariates in the model V2+V1 =2 */
1021: int cptcovsnq=0; /**< cptcovsnq number of simple covariates in the model but non quantitative V2+V1 =2 */
1.145 brouard 1022: int cptcovage=0; /**< Number of covariates with age: V3*age only =1 */
1023: int cptcovprodnoage=0; /**< Number of covariate products without age */
1024: int cptcoveff=0; /* Total number of covariates to vary for printing results */
1.233 brouard 1025: int ncovf=0; /* Total number of effective fixed covariates (dummy or quantitative) in the model */
1026: int ncovv=0; /* Total number of effective (wave) varying covariates (dummy or quantitative) in the model */
1.232 brouard 1027: int ncova=0; /* Total number of effective (wave and stepm) varying with age covariates (dummy of quantitative) in the model */
1.234 brouard 1028: int nsd=0; /**< Total number of single dummy variables (output) */
1029: int nsq=0; /**< Total number of single quantitative variables (output) */
1.232 brouard 1030: int ncoveff=0; /* Total number of effective fixed dummy covariates in the model */
1.225 brouard 1031: int nqfveff=0; /**< nqfveff Number of Quantitative Fixed Variables Effective */
1.224 brouard 1032: int ntveff=0; /**< ntveff number of effective time varying variables */
1033: int nqtveff=0; /**< ntqveff number of effective time varying quantitative variables */
1.145 brouard 1034: int cptcov=0; /* Working variable */
1.218 brouard 1035: int ncovcombmax=NCOVMAX; /* Maximum calculated number of covariate combination = pow(2, cptcoveff) */
1.126 brouard 1036: int npar=NPARMAX;
1037: int nlstate=2; /* Number of live states */
1038: int ndeath=1; /* Number of dead states */
1.130 brouard 1039: int ncovmodel=0, ncovcol=0; /* Total number of covariables including constant a12*1 +b12*x ncovmodel=2 */
1.223 brouard 1040: int nqv=0, ntv=0, nqtv=0; /* Total number of quantitative variables, time variable (dummy), quantitative and time variable */
1.126 brouard 1041: int popbased=0;
1042:
1043: int *wav; /* Number of waves for this individuual 0 is possible */
1.130 brouard 1044: int maxwav=0; /* Maxim number of waves */
1045: int jmin=0, jmax=0; /* min, max spacing between 2 waves */
1046: int ijmin=0, ijmax=0; /* Individuals having jmin and jmax */
1047: int gipmx=0, gsw=0; /* Global variables on the number of contributions
1.126 brouard 1048: to the likelihood and the sum of weights (done by funcone)*/
1.130 brouard 1049: int mle=1, weightopt=0;
1.126 brouard 1050: int **mw; /* mw[mi][i] is number of the mi wave for this individual */
1051: int **dh; /* dh[mi][i] is number of steps between mi,mi+1 for this individual */
1052: int **bh; /* bh[mi][i] is the bias (+ or -) for this individual if the delay between
1053: * wave mi and wave mi+1 is not an exact multiple of stepm. */
1.162 brouard 1054: int countcallfunc=0; /* Count the number of calls to func */
1.230 brouard 1055: int selected(int kvar); /* Is covariate kvar selected for printing results */
1056:
1.130 brouard 1057: double jmean=1; /* Mean space between 2 waves */
1.145 brouard 1058: double **matprod2(); /* test */
1.126 brouard 1059: double **oldm, **newm, **savm; /* Working pointers to matrices */
1060: double **oldms, **newms, **savms; /* Fixed working pointers to matrices */
1.218 brouard 1061: double **ddnewms, **ddoldms, **ddsavms; /* for freeing later */
1062:
1.136 brouard 1063: /*FILE *fic ; */ /* Used in readdata only */
1.217 brouard 1064: FILE *ficpar, *ficparo,*ficres, *ficresp, *ficresphtm, *ficresphtmfr, *ficrespl, *ficresplb,*ficrespij, *ficrespijb, *ficrest,*ficresf, *ficresfb,*ficrespop;
1.126 brouard 1065: FILE *ficlog, *ficrespow;
1.130 brouard 1066: int globpr=0; /* Global variable for printing or not */
1.126 brouard 1067: double fretone; /* Only one call to likelihood */
1.130 brouard 1068: long ipmx=0; /* Number of contributions */
1.126 brouard 1069: double sw; /* Sum of weights */
1070: char filerespow[FILENAMELENGTH];
1071: char fileresilk[FILENAMELENGTH]; /* File of individual contributions to the likelihood */
1072: FILE *ficresilk;
1073: FILE *ficgp,*ficresprob,*ficpop, *ficresprobcov, *ficresprobcor;
1074: FILE *ficresprobmorprev;
1075: FILE *fichtm, *fichtmcov; /* Html File */
1076: FILE *ficreseij;
1077: char filerese[FILENAMELENGTH];
1078: FILE *ficresstdeij;
1079: char fileresstde[FILENAMELENGTH];
1080: FILE *ficrescveij;
1081: char filerescve[FILENAMELENGTH];
1082: FILE *ficresvij;
1083: char fileresv[FILENAMELENGTH];
1084: FILE *ficresvpl;
1085: char fileresvpl[FILENAMELENGTH];
1.268 ! brouard 1086: FILE *ficresvbl;
! 1087: char fileresvbl[FILENAMELENGTH];
1.126 brouard 1088: char title[MAXLINE];
1.234 brouard 1089: char model[MAXLINE]; /**< The model line */
1.217 brouard 1090: char optionfile[FILENAMELENGTH], datafile[FILENAMELENGTH], filerespl[FILENAMELENGTH], fileresplb[FILENAMELENGTH];
1.126 brouard 1091: char plotcmd[FILENAMELENGTH], pplotcmd[FILENAMELENGTH];
1092: char tmpout[FILENAMELENGTH], tmpout2[FILENAMELENGTH];
1093: char command[FILENAMELENGTH];
1094: int outcmd=0;
1095:
1.217 brouard 1096: char fileres[FILENAMELENGTH], filerespij[FILENAMELENGTH], filerespijb[FILENAMELENGTH], filereso[FILENAMELENGTH], rfileres[FILENAMELENGTH];
1.202 brouard 1097: char fileresu[FILENAMELENGTH]; /* fileres without r in front */
1.126 brouard 1098: char filelog[FILENAMELENGTH]; /* Log file */
1099: char filerest[FILENAMELENGTH];
1100: char fileregp[FILENAMELENGTH];
1101: char popfile[FILENAMELENGTH];
1102:
1103: char optionfilegnuplot[FILENAMELENGTH], optionfilehtm[FILENAMELENGTH], optionfilehtmcov[FILENAMELENGTH] ;
1104:
1.157 brouard 1105: /* struct timeval start_time, end_time, curr_time, last_time, forecast_time; */
1106: /* struct timezone tzp; */
1107: /* extern int gettimeofday(); */
1108: struct tm tml, *gmtime(), *localtime();
1109:
1110: extern time_t time();
1111:
1112: struct tm start_time, end_time, curr_time, last_time, forecast_time;
1113: time_t rstart_time, rend_time, rcurr_time, rlast_time, rforecast_time; /* raw time */
1114: struct tm tm;
1115:
1.126 brouard 1116: char strcurr[80], strfor[80];
1117:
1118: char *endptr;
1119: long lval;
1120: double dval;
1121:
1122: #define NR_END 1
1123: #define FREE_ARG char*
1124: #define FTOL 1.0e-10
1125:
1126: #define NRANSI
1.240 brouard 1127: #define ITMAX 200
1128: #define ITPOWMAX 20 /* This is now multiplied by the number of parameters */
1.126 brouard 1129:
1130: #define TOL 2.0e-4
1131:
1132: #define CGOLD 0.3819660
1133: #define ZEPS 1.0e-10
1134: #define SHFT(a,b,c,d) (a)=(b);(b)=(c);(c)=(d);
1135:
1136: #define GOLD 1.618034
1137: #define GLIMIT 100.0
1138: #define TINY 1.0e-20
1139:
1140: static double maxarg1,maxarg2;
1141: #define FMAX(a,b) (maxarg1=(a),maxarg2=(b),(maxarg1)>(maxarg2)? (maxarg1):(maxarg2))
1142: #define FMIN(a,b) (maxarg1=(a),maxarg2=(b),(maxarg1)<(maxarg2)? (maxarg1):(maxarg2))
1143:
1144: #define SIGN(a,b) ((b)>0.0 ? fabs(a) : -fabs(a))
1145: #define rint(a) floor(a+0.5)
1.166 brouard 1146: /* http://www.thphys.uni-heidelberg.de/~robbers/cmbeasy/doc/html/myutils_8h-source.html */
1.183 brouard 1147: #define mytinydouble 1.0e-16
1.166 brouard 1148: /* #define DEQUAL(a,b) (fabs((a)-(b))<mytinydouble) */
1149: /* http://www.thphys.uni-heidelberg.de/~robbers/cmbeasy/doc/html/mynrutils_8h-source.html */
1150: /* static double dsqrarg; */
1151: /* #define DSQR(a) (DEQUAL((dsqrarg=(a)),0.0) ? 0.0 : dsqrarg*dsqrarg) */
1.126 brouard 1152: static double sqrarg;
1153: #define SQR(a) ((sqrarg=(a)) == 0.0 ? 0.0 :sqrarg*sqrarg)
1154: #define SWAP(a,b) {temp=(a);(a)=(b);(b)=temp;}
1155: int agegomp= AGEGOMP;
1156:
1157: int imx;
1158: int stepm=1;
1159: /* Stepm, step in month: minimum step interpolation*/
1160:
1161: int estepm;
1162: /* Estepm, step in month to interpolate survival function in order to approximate Life Expectancy*/
1163:
1164: int m,nb;
1165: long *num;
1.197 brouard 1166: int firstpass=0, lastpass=4,*cod, *cens;
1.192 brouard 1167: int *ncodemax; /* ncodemax[j]= Number of modalities of the j th
1168: covariate for which somebody answered excluding
1169: undefined. Usually 2: 0 and 1. */
1170: int *ncodemaxwundef; /* ncodemax[j]= Number of modalities of the j th
1171: covariate for which somebody answered including
1172: undefined. Usually 3: -1, 0 and 1. */
1.126 brouard 1173: double **agev,*moisnais, *annais, *moisdc, *andc,**mint, **anint;
1.218 brouard 1174: double **pmmij, ***probs; /* Global pointer */
1.219 brouard 1175: double ***mobaverage, ***mobaverages; /* New global variable */
1.126 brouard 1176: double *ageexmed,*agecens;
1177: double dateintmean=0;
1178:
1179: double *weight;
1180: int **s; /* Status */
1.141 brouard 1181: double *agedc;
1.145 brouard 1182: double **covar; /**< covar[j,i], value of jth covariate for individual i,
1.141 brouard 1183: * covar=matrix(0,NCOVMAX,1,n);
1.187 brouard 1184: * cov[Tage[kk]+2]=covar[Tvar[Tage[kk]]][i]*age; */
1.268 ! brouard 1185: double **coqvar; /* Fixed quantitative covariate nqv */
! 1186: double ***cotvar; /* Time varying covariate ntv */
1.225 brouard 1187: double ***cotqvar; /* Time varying quantitative covariate itqv */
1.141 brouard 1188: double idx;
1189: int **nbcode, *Tvar; /**< model=V2 => Tvar[1]= 2 */
1.234 brouard 1190: /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1191: /*k 1 2 3 4 5 6 7 8 9 */
1192: /*Tvar[k]= 5 4 3 6 5 2 7 1 1 */
1193: /* Tndvar[k] 1 2 3 4 5 */
1194: /*TDvar 4 3 6 7 1 */ /* For outputs only; combination of dummies fixed or varying */
1195: /* Tns[k] 1 2 2 4 5 */ /* Number of single cova */
1196: /* TvarsD[k] 1 2 3 */ /* Number of single dummy cova */
1197: /* TvarsDind 2 3 9 */ /* position K of single dummy cova */
1198: /* TvarsQ[k] 1 2 */ /* Number of single quantitative cova */
1199: /* TvarsQind 1 6 */ /* position K of single quantitative cova */
1200: /* Tprod[i]=k 4 7 */
1201: /* Tage[i]=k 5 8 */
1202: /* */
1203: /* Type */
1204: /* V 1 2 3 4 5 */
1205: /* F F V V V */
1206: /* D Q D D Q */
1207: /* */
1208: int *TvarsD;
1209: int *TvarsDind;
1210: int *TvarsQ;
1211: int *TvarsQind;
1212:
1.235 brouard 1213: #define MAXRESULTLINES 10
1214: int nresult=0;
1.258 brouard 1215: int parameterline=0; /* # of the parameter (type) line */
1.235 brouard 1216: int TKresult[MAXRESULTLINES];
1.237 brouard 1217: int Tresult[MAXRESULTLINES][NCOVMAX];/* For dummy variable , value (output) */
1218: int Tinvresult[MAXRESULTLINES][NCOVMAX];/* For dummy variable , value (output) */
1.235 brouard 1219: int Tvresult[MAXRESULTLINES][NCOVMAX]; /* For dummy variable , variable # (output) */
1220: double Tqresult[MAXRESULTLINES][NCOVMAX]; /* For quantitative variable , value (output) */
1.237 brouard 1221: double Tqinvresult[MAXRESULTLINES][NCOVMAX]; /* For quantitative variable , value (output) */
1.235 brouard 1222: int Tvqresult[MAXRESULTLINES][NCOVMAX]; /* For quantitative variable , variable # (output) */
1223:
1.234 brouard 1224: /* int *TDvar; /\**< TDvar[1]=4, TDvarF[2]=3, TDvar[3]=6 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 *\/ */
1.232 brouard 1225: int *TvarF; /**< TvarF[1]=Tvar[6]=2, TvarF[2]=Tvar[7]=7, TvarF[3]=Tvar[9]=1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1226: int *TvarFind; /**< TvarFind[1]=6, TvarFind[2]=7, Tvarind[3]=9 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1227: int *TvarV; /**< TvarV[1]=Tvar[1]=5, TvarV[2]=Tvar[2]=4 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1228: int *TvarVind; /**< TvarVind[1]=1, TvarVind[2]=2 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1229: int *TvarA; /**< TvarA[1]=Tvar[5]=5, TvarA[2]=Tvar[8]=1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1230: int *TvarAind; /**< TvarindA[1]=5, TvarAind[2]=8 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1.231 brouard 1231: int *TvarFD; /**< TvarFD[1]=V1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1232: int *TvarFDind; /* TvarFDind[1]=9 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1233: int *TvarFQ; /* TvarFQ[1]=V2 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1234: int *TvarFQind; /* TvarFQind[1]=6 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1235: int *TvarVD; /* TvarVD[1]=V5 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1236: int *TvarVDind; /* TvarVDind[1]=1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1237: int *TvarVQ; /* TvarVQ[1]=V5 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple time varying quantitative variable */
1238: int *TvarVQind; /* TvarVQind[1]=1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple time varying quantitative variable */
1239:
1.230 brouard 1240: int *Tvarsel; /**< Selected covariates for output */
1241: double *Tvalsel; /**< Selected modality value of covariate for output */
1.226 brouard 1242: int *Typevar; /**< 0 for simple covariate (dummy, quantitative, fixed or varying), 1 for age product, 2 for product */
1.227 brouard 1243: int *Fixed; /** Fixed[k] 0=fixed, 1 varying, 2 fixed with age product, 3 varying with age product */
1244: int *Dummy; /** Dummy[k] 0=dummy (0 1), 1 quantitative (single or product without age), 2 dummy with age product, 3 quant with age product */
1.238 brouard 1245: int *DummyV; /** Dummy[v] 0=dummy (0 1), 1 quantitative */
1246: int *FixedV; /** FixedV[v] 0 fixed, 1 varying */
1.197 brouard 1247: int *Tage;
1.227 brouard 1248: int anyvaryingduminmodel=0; /**< Any varying dummy in Model=1 yes, 0 no, to avoid a loop on waves in freq */
1.228 brouard 1249: int *Tmodelind; /** Tmodelind[Tvaraff[3]]=9 for V1 position,Tvaraff[1]@9={4, 3, 1, 0, 0, 0, 0, 0, 0}, model=V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1*/
1.230 brouard 1250: int *TmodelInvind; /** Tmodelind[Tvaraff[3]]=9 for V1 position,Tvaraff[1]@9={4, 3, 1, 0, 0, 0, 0, 0, 0}, model=V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1*/
1251: int *TmodelInvQind; /** Tmodelqind[1]=1 for V5(quantitative varying) position,Tvaraff[1]@9={4, 3, 1, 0, 0, 0, 0, 0, 0}, model=V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1.145 brouard 1252: int *Ndum; /** Freq of modality (tricode */
1.200 brouard 1253: /* int **codtab;*/ /**< codtab=imatrix(1,100,1,10); */
1.227 brouard 1254: int **Tvard;
1255: int *Tprod;/**< Gives the k position of the k1 product */
1.238 brouard 1256: /* Tprod[k1=1]=3(=V1*V4) for V2+V1+V1*V4+age*V3 */
1.227 brouard 1257: int *Tposprod; /**< Gives the k1 product from the k position */
1.238 brouard 1258: /* if V2+V1+V1*V4+age*V3+V3*V2 TProd[k1=2]=5 (V3*V2) */
1259: /* Tposprod[k]=k1 , Tposprod[3]=1, Tposprod[5(V3*V2)]=2 (2nd product without age) */
1.227 brouard 1260: int cptcovprod, *Tvaraff, *invalidvarcomb;
1.126 brouard 1261: double *lsurv, *lpop, *tpop;
1262:
1.231 brouard 1263: #define FD 1; /* Fixed dummy covariate */
1264: #define FQ 2; /* Fixed quantitative covariate */
1265: #define FP 3; /* Fixed product covariate */
1266: #define FPDD 7; /* Fixed product dummy*dummy covariate */
1267: #define FPDQ 8; /* Fixed product dummy*quantitative covariate */
1268: #define FPQQ 9; /* Fixed product quantitative*quantitative covariate */
1269: #define VD 10; /* Varying dummy covariate */
1270: #define VQ 11; /* Varying quantitative covariate */
1271: #define VP 12; /* Varying product covariate */
1272: #define VPDD 13; /* Varying product dummy*dummy covariate */
1273: #define VPDQ 14; /* Varying product dummy*quantitative covariate */
1274: #define VPQQ 15; /* Varying product quantitative*quantitative covariate */
1275: #define APFD 16; /* Age product * fixed dummy covariate */
1276: #define APFQ 17; /* Age product * fixed quantitative covariate */
1277: #define APVD 18; /* Age product * varying dummy covariate */
1278: #define APVQ 19; /* Age product * varying quantitative covariate */
1279:
1280: #define FTYPE 1; /* Fixed covariate */
1281: #define VTYPE 2; /* Varying covariate (loop in wave) */
1282: #define ATYPE 2; /* Age product covariate (loop in dh within wave)*/
1283:
1284: struct kmodel{
1285: int maintype; /* main type */
1286: int subtype; /* subtype */
1287: };
1288: struct kmodel modell[NCOVMAX];
1289:
1.143 brouard 1290: double ftol=FTOL; /**< Tolerance for computing Max Likelihood */
1291: double ftolhess; /**< Tolerance for computing hessian */
1.126 brouard 1292:
1293: /**************** split *************************/
1294: static int split( char *path, char *dirc, char *name, char *ext, char *finame )
1295: {
1296: /* From a file name with (full) path (either Unix or Windows) we extract the directory (dirc)
1297: the name of the file (name), its extension only (ext) and its first part of the name (finame)
1298: */
1299: char *ss; /* pointer */
1.186 brouard 1300: int l1=0, l2=0; /* length counters */
1.126 brouard 1301:
1302: l1 = strlen(path ); /* length of path */
1303: if ( l1 == 0 ) return( GLOCK_ERROR_NOPATH );
1304: ss= strrchr( path, DIRSEPARATOR ); /* find last / */
1305: if ( ss == NULL ) { /* no directory, so determine current directory */
1306: strcpy( name, path ); /* we got the fullname name because no directory */
1307: /*if(strrchr(path, ODIRSEPARATOR )==NULL)
1308: printf("Warning you should use %s as a separator\n",DIRSEPARATOR);*/
1309: /* get current working directory */
1310: /* extern char* getcwd ( char *buf , int len);*/
1.184 brouard 1311: #ifdef WIN32
1312: if (_getcwd( dirc, FILENAME_MAX ) == NULL ) {
1313: #else
1314: if (getcwd(dirc, FILENAME_MAX) == NULL) {
1315: #endif
1.126 brouard 1316: return( GLOCK_ERROR_GETCWD );
1317: }
1318: /* got dirc from getcwd*/
1319: printf(" DIRC = %s \n",dirc);
1.205 brouard 1320: } else { /* strip directory from path */
1.126 brouard 1321: ss++; /* after this, the filename */
1322: l2 = strlen( ss ); /* length of filename */
1323: if ( l2 == 0 ) return( GLOCK_ERROR_NOPATH );
1324: strcpy( name, ss ); /* save file name */
1325: strncpy( dirc, path, l1 - l2 ); /* now the directory */
1.186 brouard 1326: dirc[l1-l2] = '\0'; /* add zero */
1.126 brouard 1327: printf(" DIRC2 = %s \n",dirc);
1328: }
1329: /* We add a separator at the end of dirc if not exists */
1330: l1 = strlen( dirc ); /* length of directory */
1331: if( dirc[l1-1] != DIRSEPARATOR ){
1332: dirc[l1] = DIRSEPARATOR;
1333: dirc[l1+1] = 0;
1334: printf(" DIRC3 = %s \n",dirc);
1335: }
1336: ss = strrchr( name, '.' ); /* find last / */
1337: if (ss >0){
1338: ss++;
1339: strcpy(ext,ss); /* save extension */
1340: l1= strlen( name);
1341: l2= strlen(ss)+1;
1342: strncpy( finame, name, l1-l2);
1343: finame[l1-l2]= 0;
1344: }
1345:
1346: return( 0 ); /* we're done */
1347: }
1348:
1349:
1350: /******************************************/
1351:
1352: void replace_back_to_slash(char *s, char*t)
1353: {
1354: int i;
1355: int lg=0;
1356: i=0;
1357: lg=strlen(t);
1358: for(i=0; i<= lg; i++) {
1359: (s[i] = t[i]);
1360: if (t[i]== '\\') s[i]='/';
1361: }
1362: }
1363:
1.132 brouard 1364: char *trimbb(char *out, char *in)
1.137 brouard 1365: { /* Trim multiple blanks in line but keeps first blanks if line starts with blanks */
1.132 brouard 1366: char *s;
1367: s=out;
1368: while (*in != '\0'){
1.137 brouard 1369: while( *in == ' ' && *(in+1) == ' '){ /* && *(in+1) != '\0'){*/
1.132 brouard 1370: in++;
1371: }
1372: *out++ = *in++;
1373: }
1374: *out='\0';
1375: return s;
1376: }
1377:
1.187 brouard 1378: /* char *substrchaine(char *out, char *in, char *chain) */
1379: /* { */
1380: /* /\* Substract chain 'chain' from 'in', return and output 'out' *\/ */
1381: /* char *s, *t; */
1382: /* t=in;s=out; */
1383: /* while ((*in != *chain) && (*in != '\0')){ */
1384: /* *out++ = *in++; */
1385: /* } */
1386:
1387: /* /\* *in matches *chain *\/ */
1388: /* while ((*in++ == *chain++) && (*in != '\0')){ */
1389: /* printf("*in = %c, *out= %c *chain= %c \n", *in, *out, *chain); */
1390: /* } */
1391: /* in--; chain--; */
1392: /* while ( (*in != '\0')){ */
1393: /* printf("Bef *in = %c, *out= %c *chain= %c \n", *in, *out, *chain); */
1394: /* *out++ = *in++; */
1395: /* printf("Aft *in = %c, *out= %c *chain= %c \n", *in, *out, *chain); */
1396: /* } */
1397: /* *out='\0'; */
1398: /* out=s; */
1399: /* return out; */
1400: /* } */
1401: char *substrchaine(char *out, char *in, char *chain)
1402: {
1403: /* Substract chain 'chain' from 'in', return and output 'out' */
1404: /* in="V1+V1*age+age*age+V2", chain="age*age" */
1405:
1406: char *strloc;
1407:
1408: strcpy (out, in);
1409: strloc = strstr(out, chain); /* strloc points to out at age*age+V2 */
1410: printf("Bef strloc=%s chain=%s out=%s \n", strloc, chain, out);
1411: if(strloc != NULL){
1412: /* will affect out */ /* strloc+strlenc(chain)=+V2 */ /* Will also work in Unicode */
1413: memmove(strloc,strloc+strlen(chain), strlen(strloc+strlen(chain))+1);
1414: /* strcpy (strloc, strloc +strlen(chain));*/
1415: }
1416: printf("Aft strloc=%s chain=%s in=%s out=%s \n", strloc, chain, in, out);
1417: return out;
1418: }
1419:
1420:
1.145 brouard 1421: char *cutl(char *blocc, char *alocc, char *in, char occ)
1422: {
1.187 brouard 1423: /* cuts string in into blocc and alocc where blocc ends before FIRST occurence of char 'occ'
1.145 brouard 1424: and alocc starts after first occurence of char 'occ' : ex cutv(blocc,alocc,"abcdef2ghi2j",'2')
1.187 brouard 1425: gives blocc="abcdef" and alocc="ghi2j".
1.145 brouard 1426: If occ is not found blocc is null and alocc is equal to in. Returns blocc
1427: */
1.160 brouard 1428: char *s, *t;
1.145 brouard 1429: t=in;s=in;
1430: while ((*in != occ) && (*in != '\0')){
1431: *alocc++ = *in++;
1432: }
1433: if( *in == occ){
1434: *(alocc)='\0';
1435: s=++in;
1436: }
1437:
1438: if (s == t) {/* occ not found */
1439: *(alocc-(in-s))='\0';
1440: in=s;
1441: }
1442: while ( *in != '\0'){
1443: *blocc++ = *in++;
1444: }
1445:
1446: *blocc='\0';
1447: return t;
1448: }
1.137 brouard 1449: char *cutv(char *blocc, char *alocc, char *in, char occ)
1450: {
1.187 brouard 1451: /* cuts string in into blocc and alocc where blocc ends before LAST occurence of char 'occ'
1.137 brouard 1452: and alocc starts after last occurence of char 'occ' : ex cutv(blocc,alocc,"abcdef2ghi2j",'2')
1453: gives blocc="abcdef2ghi" and alocc="j".
1454: If occ is not found blocc is null and alocc is equal to in. Returns alocc
1455: */
1456: char *s, *t;
1457: t=in;s=in;
1458: while (*in != '\0'){
1459: while( *in == occ){
1460: *blocc++ = *in++;
1461: s=in;
1462: }
1463: *blocc++ = *in++;
1464: }
1465: if (s == t) /* occ not found */
1466: *(blocc-(in-s))='\0';
1467: else
1468: *(blocc-(in-s)-1)='\0';
1469: in=s;
1470: while ( *in != '\0'){
1471: *alocc++ = *in++;
1472: }
1473:
1474: *alocc='\0';
1475: return s;
1476: }
1477:
1.126 brouard 1478: int nbocc(char *s, char occ)
1479: {
1480: int i,j=0;
1481: int lg=20;
1482: i=0;
1483: lg=strlen(s);
1484: for(i=0; i<= lg; i++) {
1.234 brouard 1485: if (s[i] == occ ) j++;
1.126 brouard 1486: }
1487: return j;
1488: }
1489:
1.137 brouard 1490: /* void cutv(char *u,char *v, char*t, char occ) */
1491: /* { */
1492: /* /\* cuts string t into u and v where u ends before last occurence of char 'occ' */
1493: /* and v starts after last occurence of char 'occ' : ex cutv(u,v,"abcdef2ghi2j",'2') */
1494: /* gives u="abcdef2ghi" and v="j" *\/ */
1495: /* int i,lg,j,p=0; */
1496: /* i=0; */
1497: /* lg=strlen(t); */
1498: /* for(j=0; j<=lg-1; j++) { */
1499: /* if((t[j]!= occ) && (t[j+1]== occ)) p=j+1; */
1500: /* } */
1.126 brouard 1501:
1.137 brouard 1502: /* for(j=0; j<p; j++) { */
1503: /* (u[j] = t[j]); */
1504: /* } */
1505: /* u[p]='\0'; */
1.126 brouard 1506:
1.137 brouard 1507: /* for(j=0; j<= lg; j++) { */
1508: /* if (j>=(p+1))(v[j-p-1] = t[j]); */
1509: /* } */
1510: /* } */
1.126 brouard 1511:
1.160 brouard 1512: #ifdef _WIN32
1513: char * strsep(char **pp, const char *delim)
1514: {
1515: char *p, *q;
1516:
1517: if ((p = *pp) == NULL)
1518: return 0;
1519: if ((q = strpbrk (p, delim)) != NULL)
1520: {
1521: *pp = q + 1;
1522: *q = '\0';
1523: }
1524: else
1525: *pp = 0;
1526: return p;
1527: }
1528: #endif
1529:
1.126 brouard 1530: /********************** nrerror ********************/
1531:
1532: void nrerror(char error_text[])
1533: {
1534: fprintf(stderr,"ERREUR ...\n");
1535: fprintf(stderr,"%s\n",error_text);
1536: exit(EXIT_FAILURE);
1537: }
1538: /*********************** vector *******************/
1539: double *vector(int nl, int nh)
1540: {
1541: double *v;
1542: v=(double *) malloc((size_t)((nh-nl+1+NR_END)*sizeof(double)));
1543: if (!v) nrerror("allocation failure in vector");
1544: return v-nl+NR_END;
1545: }
1546:
1547: /************************ free vector ******************/
1548: void free_vector(double*v, int nl, int nh)
1549: {
1550: free((FREE_ARG)(v+nl-NR_END));
1551: }
1552:
1553: /************************ivector *******************************/
1554: int *ivector(long nl,long nh)
1555: {
1556: int *v;
1557: v=(int *) malloc((size_t)((nh-nl+1+NR_END)*sizeof(int)));
1558: if (!v) nrerror("allocation failure in ivector");
1559: return v-nl+NR_END;
1560: }
1561:
1562: /******************free ivector **************************/
1563: void free_ivector(int *v, long nl, long nh)
1564: {
1565: free((FREE_ARG)(v+nl-NR_END));
1566: }
1567:
1568: /************************lvector *******************************/
1569: long *lvector(long nl,long nh)
1570: {
1571: long *v;
1572: v=(long *) malloc((size_t)((nh-nl+1+NR_END)*sizeof(long)));
1573: if (!v) nrerror("allocation failure in ivector");
1574: return v-nl+NR_END;
1575: }
1576:
1577: /******************free lvector **************************/
1578: void free_lvector(long *v, long nl, long nh)
1579: {
1580: free((FREE_ARG)(v+nl-NR_END));
1581: }
1582:
1583: /******************* imatrix *******************************/
1584: int **imatrix(long nrl, long nrh, long ncl, long nch)
1585: /* allocate a int matrix with subscript range m[nrl..nrh][ncl..nch] */
1586: {
1587: long i, nrow=nrh-nrl+1,ncol=nch-ncl+1;
1588: int **m;
1589:
1590: /* allocate pointers to rows */
1591: m=(int **) malloc((size_t)((nrow+NR_END)*sizeof(int*)));
1592: if (!m) nrerror("allocation failure 1 in matrix()");
1593: m += NR_END;
1594: m -= nrl;
1595:
1596:
1597: /* allocate rows and set pointers to them */
1598: m[nrl]=(int *) malloc((size_t)((nrow*ncol+NR_END)*sizeof(int)));
1599: if (!m[nrl]) nrerror("allocation failure 2 in matrix()");
1600: m[nrl] += NR_END;
1601: m[nrl] -= ncl;
1602:
1603: for(i=nrl+1;i<=nrh;i++) m[i]=m[i-1]+ncol;
1604:
1605: /* return pointer to array of pointers to rows */
1606: return m;
1607: }
1608:
1609: /****************** free_imatrix *************************/
1610: void free_imatrix(m,nrl,nrh,ncl,nch)
1611: int **m;
1612: long nch,ncl,nrh,nrl;
1613: /* free an int matrix allocated by imatrix() */
1614: {
1615: free((FREE_ARG) (m[nrl]+ncl-NR_END));
1616: free((FREE_ARG) (m+nrl-NR_END));
1617: }
1618:
1619: /******************* matrix *******************************/
1620: double **matrix(long nrl, long nrh, long ncl, long nch)
1621: {
1622: long i, nrow=nrh-nrl+1, ncol=nch-ncl+1;
1623: double **m;
1624:
1625: m=(double **) malloc((size_t)((nrow+NR_END)*sizeof(double*)));
1626: if (!m) nrerror("allocation failure 1 in matrix()");
1627: m += NR_END;
1628: m -= nrl;
1629:
1630: m[nrl]=(double *) malloc((size_t)((nrow*ncol+NR_END)*sizeof(double)));
1631: if (!m[nrl]) nrerror("allocation failure 2 in matrix()");
1632: m[nrl] += NR_END;
1633: m[nrl] -= ncl;
1634:
1635: for (i=nrl+1; i<=nrh; i++) m[i]=m[i-1]+ncol;
1636: return m;
1.145 brouard 1637: /* print *(*(m+1)+70) or print m[1][70]; print m+1 or print &(m[1]) or &(m[1][0])
1638: m[i] = address of ith row of the table. &(m[i]) is its value which is another adress
1639: that of m[i][0]. In order to get the value p m[i][0] but it is unitialized.
1.126 brouard 1640: */
1641: }
1642:
1643: /*************************free matrix ************************/
1644: void free_matrix(double **m, long nrl, long nrh, long ncl, long nch)
1645: {
1646: free((FREE_ARG)(m[nrl]+ncl-NR_END));
1647: free((FREE_ARG)(m+nrl-NR_END));
1648: }
1649:
1650: /******************* ma3x *******************************/
1651: double ***ma3x(long nrl, long nrh, long ncl, long nch, long nll, long nlh)
1652: {
1653: long i, j, nrow=nrh-nrl+1, ncol=nch-ncl+1, nlay=nlh-nll+1;
1654: double ***m;
1655:
1656: m=(double ***) malloc((size_t)((nrow+NR_END)*sizeof(double*)));
1657: if (!m) nrerror("allocation failure 1 in matrix()");
1658: m += NR_END;
1659: m -= nrl;
1660:
1661: m[nrl]=(double **) malloc((size_t)((nrow*ncol+NR_END)*sizeof(double)));
1662: if (!m[nrl]) nrerror("allocation failure 2 in matrix()");
1663: m[nrl] += NR_END;
1664: m[nrl] -= ncl;
1665:
1666: for (i=nrl+1; i<=nrh; i++) m[i]=m[i-1]+ncol;
1667:
1668: m[nrl][ncl]=(double *) malloc((size_t)((nrow*ncol*nlay+NR_END)*sizeof(double)));
1669: if (!m[nrl][ncl]) nrerror("allocation failure 3 in matrix()");
1670: m[nrl][ncl] += NR_END;
1671: m[nrl][ncl] -= nll;
1672: for (j=ncl+1; j<=nch; j++)
1673: m[nrl][j]=m[nrl][j-1]+nlay;
1674:
1675: for (i=nrl+1; i<=nrh; i++) {
1676: m[i][ncl]=m[i-1l][ncl]+ncol*nlay;
1677: for (j=ncl+1; j<=nch; j++)
1678: m[i][j]=m[i][j-1]+nlay;
1679: }
1680: return m;
1681: /* gdb: p *(m+1) <=> p m[1] and p (m+1) <=> p (m+1) <=> p &(m[1])
1682: &(m[i][j][k]) <=> *((*(m+i) + j)+k)
1683: */
1684: }
1685:
1686: /*************************free ma3x ************************/
1687: void free_ma3x(double ***m, long nrl, long nrh, long ncl, long nch,long nll, long nlh)
1688: {
1689: free((FREE_ARG)(m[nrl][ncl]+ nll-NR_END));
1690: free((FREE_ARG)(m[nrl]+ncl-NR_END));
1691: free((FREE_ARG)(m+nrl-NR_END));
1692: }
1693:
1694: /*************** function subdirf ***********/
1695: char *subdirf(char fileres[])
1696: {
1697: /* Caution optionfilefiname is hidden */
1698: strcpy(tmpout,optionfilefiname);
1699: strcat(tmpout,"/"); /* Add to the right */
1700: strcat(tmpout,fileres);
1701: return tmpout;
1702: }
1703:
1704: /*************** function subdirf2 ***********/
1705: char *subdirf2(char fileres[], char *preop)
1706: {
1707:
1708: /* Caution optionfilefiname is hidden */
1709: strcpy(tmpout,optionfilefiname);
1710: strcat(tmpout,"/");
1711: strcat(tmpout,preop);
1712: strcat(tmpout,fileres);
1713: return tmpout;
1714: }
1715:
1716: /*************** function subdirf3 ***********/
1717: char *subdirf3(char fileres[], char *preop, char *preop2)
1718: {
1719:
1720: /* Caution optionfilefiname is hidden */
1721: strcpy(tmpout,optionfilefiname);
1722: strcat(tmpout,"/");
1723: strcat(tmpout,preop);
1724: strcat(tmpout,preop2);
1725: strcat(tmpout,fileres);
1726: return tmpout;
1727: }
1.213 brouard 1728:
1729: /*************** function subdirfext ***********/
1730: char *subdirfext(char fileres[], char *preop, char *postop)
1731: {
1732:
1733: strcpy(tmpout,preop);
1734: strcat(tmpout,fileres);
1735: strcat(tmpout,postop);
1736: return tmpout;
1737: }
1.126 brouard 1738:
1.213 brouard 1739: /*************** function subdirfext3 ***********/
1740: char *subdirfext3(char fileres[], char *preop, char *postop)
1741: {
1742:
1743: /* Caution optionfilefiname is hidden */
1744: strcpy(tmpout,optionfilefiname);
1745: strcat(tmpout,"/");
1746: strcat(tmpout,preop);
1747: strcat(tmpout,fileres);
1748: strcat(tmpout,postop);
1749: return tmpout;
1750: }
1751:
1.162 brouard 1752: char *asc_diff_time(long time_sec, char ascdiff[])
1753: {
1754: long sec_left, days, hours, minutes;
1755: days = (time_sec) / (60*60*24);
1756: sec_left = (time_sec) % (60*60*24);
1757: hours = (sec_left) / (60*60) ;
1758: sec_left = (sec_left) %(60*60);
1759: minutes = (sec_left) /60;
1760: sec_left = (sec_left) % (60);
1761: sprintf(ascdiff,"%ld day(s) %ld hour(s) %ld minute(s) %ld second(s)",days, hours, minutes, sec_left);
1762: return ascdiff;
1763: }
1764:
1.126 brouard 1765: /***************** f1dim *************************/
1766: extern int ncom;
1767: extern double *pcom,*xicom;
1768: extern double (*nrfunc)(double []);
1769:
1770: double f1dim(double x)
1771: {
1772: int j;
1773: double f;
1774: double *xt;
1775:
1776: xt=vector(1,ncom);
1777: for (j=1;j<=ncom;j++) xt[j]=pcom[j]+x*xicom[j];
1778: f=(*nrfunc)(xt);
1779: free_vector(xt,1,ncom);
1780: return f;
1781: }
1782:
1783: /*****************brent *************************/
1784: double brent(double ax, double bx, double cx, double (*f)(double), double tol, double *xmin)
1.187 brouard 1785: {
1786: /* Given a function f, and given a bracketing triplet of abscissas ax, bx, cx (such that bx is
1787: * between ax and cx, and f(bx) is less than both f(ax) and f(cx) ), this routine isolates
1788: * the minimum to a fractional precision of about tol using Brent’s method. The abscissa of
1789: * the minimum is returned as xmin, and the minimum function value is returned as brent , the
1790: * returned function value.
1791: */
1.126 brouard 1792: int iter;
1793: double a,b,d,etemp;
1.159 brouard 1794: double fu=0,fv,fw,fx;
1.164 brouard 1795: double ftemp=0.;
1.126 brouard 1796: double p,q,r,tol1,tol2,u,v,w,x,xm;
1797: double e=0.0;
1798:
1799: a=(ax < cx ? ax : cx);
1800: b=(ax > cx ? ax : cx);
1801: x=w=v=bx;
1802: fw=fv=fx=(*f)(x);
1803: for (iter=1;iter<=ITMAX;iter++) {
1804: xm=0.5*(a+b);
1805: tol2=2.0*(tol1=tol*fabs(x)+ZEPS);
1806: /* if (2.0*fabs(fp-(*fret)) <= ftol*(fabs(fp)+fabs(*fret)))*/
1807: printf(".");fflush(stdout);
1808: fprintf(ficlog,".");fflush(ficlog);
1.162 brouard 1809: #ifdef DEBUGBRENT
1.126 brouard 1810: printf("br %d,x=%.10e xm=%.10e b=%.10e a=%.10e tol=%.10e tol1=%.10e tol2=%.10e x-xm=%.10e fx=%.12e fu=%.12e,fw=%.12e,ftemp=%.12e,ftol=%.12e\n",iter,x,xm,b,a,tol,tol1,tol2,(x-xm),fx,fu,fw,ftemp,ftol);
1811: fprintf(ficlog,"br %d,x=%.10e xm=%.10e b=%.10e a=%.10e tol=%.10e tol1=%.10e tol2=%.10e x-xm=%.10e fx=%.12e fu=%.12e,fw=%.12e,ftemp=%.12e,ftol=%.12e\n",iter,x,xm,b,a,tol,tol1,tol2,(x-xm),fx,fu,fw,ftemp,ftol);
1812: /* if ((fabs(x-xm) <= (tol2-0.5*(b-a)))||(2.0*fabs(fu-ftemp) <= ftol*1.e-2*(fabs(fu)+fabs(ftemp)))) { */
1813: #endif
1814: if (fabs(x-xm) <= (tol2-0.5*(b-a))){
1815: *xmin=x;
1816: return fx;
1817: }
1818: ftemp=fu;
1819: if (fabs(e) > tol1) {
1820: r=(x-w)*(fx-fv);
1821: q=(x-v)*(fx-fw);
1822: p=(x-v)*q-(x-w)*r;
1823: q=2.0*(q-r);
1824: if (q > 0.0) p = -p;
1825: q=fabs(q);
1826: etemp=e;
1827: e=d;
1828: if (fabs(p) >= fabs(0.5*q*etemp) || p <= q*(a-x) || p >= q*(b-x))
1.224 brouard 1829: d=CGOLD*(e=(x >= xm ? a-x : b-x));
1.126 brouard 1830: else {
1.224 brouard 1831: d=p/q;
1832: u=x+d;
1833: if (u-a < tol2 || b-u < tol2)
1834: d=SIGN(tol1,xm-x);
1.126 brouard 1835: }
1836: } else {
1837: d=CGOLD*(e=(x >= xm ? a-x : b-x));
1838: }
1839: u=(fabs(d) >= tol1 ? x+d : x+SIGN(tol1,d));
1840: fu=(*f)(u);
1841: if (fu <= fx) {
1842: if (u >= x) a=x; else b=x;
1843: SHFT(v,w,x,u)
1.183 brouard 1844: SHFT(fv,fw,fx,fu)
1845: } else {
1846: if (u < x) a=u; else b=u;
1847: if (fu <= fw || w == x) {
1.224 brouard 1848: v=w;
1849: w=u;
1850: fv=fw;
1851: fw=fu;
1.183 brouard 1852: } else if (fu <= fv || v == x || v == w) {
1.224 brouard 1853: v=u;
1854: fv=fu;
1.183 brouard 1855: }
1856: }
1.126 brouard 1857: }
1858: nrerror("Too many iterations in brent");
1859: *xmin=x;
1860: return fx;
1861: }
1862:
1863: /****************** mnbrak ***********************/
1864:
1865: void mnbrak(double *ax, double *bx, double *cx, double *fa, double *fb, double *fc,
1866: double (*func)(double))
1.183 brouard 1867: { /* Given a function func , and given distinct initial points ax and bx , this routine searches in
1868: the downhill direction (defined by the function as evaluated at the initial points) and returns
1869: new points ax , bx , cx that bracket a minimum of the function. Also returned are the function
1870: values at the three points, fa, fb , and fc such that fa > fb and fb < fc.
1871: */
1.126 brouard 1872: double ulim,u,r,q, dum;
1873: double fu;
1.187 brouard 1874:
1875: double scale=10.;
1876: int iterscale=0;
1877:
1878: *fa=(*func)(*ax); /* xta[j]=pcom[j]+(*ax)*xicom[j]; fa=f(xta[j])*/
1879: *fb=(*func)(*bx); /* xtb[j]=pcom[j]+(*bx)*xicom[j]; fb=f(xtb[j]) */
1880:
1881:
1882: /* while(*fb != *fb){ /\* *ax should be ok, reducing distance to *ax *\/ */
1883: /* printf("Warning mnbrak *fb = %lf, *bx=%lf *ax=%lf *fa==%lf iter=%d\n",*fb, *bx, *ax, *fa, iterscale++); */
1884: /* *bx = *ax - (*ax - *bx)/scale; */
1885: /* *fb=(*func)(*bx); /\* xtb[j]=pcom[j]+(*bx)*xicom[j]; fb=f(xtb[j]) *\/ */
1886: /* } */
1887:
1.126 brouard 1888: if (*fb > *fa) {
1889: SHFT(dum,*ax,*bx,dum)
1.183 brouard 1890: SHFT(dum,*fb,*fa,dum)
1891: }
1.126 brouard 1892: *cx=(*bx)+GOLD*(*bx-*ax);
1893: *fc=(*func)(*cx);
1.183 brouard 1894: #ifdef DEBUG
1.224 brouard 1895: printf("mnbrak0 a=%lf *fa=%lf, b=%lf *fb=%lf, c=%lf *fc=%lf\n",*ax,*fa,*bx,*fb,*cx, *fc);
1896: fprintf(ficlog,"mnbrak0 a=%lf *fa=%lf, b=%lf *fb=%lf, c=%lf *fc=%lf\n",*ax,*fa,*bx,*fb,*cx, *fc);
1.183 brouard 1897: #endif
1.224 brouard 1898: while (*fb > *fc) { /* Declining a,b,c with fa> fb > fc. If fc=inf it exits and if flat fb=fc it exits too.*/
1.126 brouard 1899: r=(*bx-*ax)*(*fb-*fc);
1.224 brouard 1900: q=(*bx-*cx)*(*fb-*fa); /* What if fa=inf */
1.126 brouard 1901: u=(*bx)-((*bx-*cx)*q-(*bx-*ax)*r)/
1.183 brouard 1902: (2.0*SIGN(FMAX(fabs(q-r),TINY),q-r)); /* Minimum abscissa of a parabolic estimated from (a,fa), (b,fb) and (c,fc). */
1903: ulim=(*bx)+GLIMIT*(*cx-*bx); /* Maximum abscissa where function should be evaluated */
1904: if ((*bx-u)*(u-*cx) > 0.0) { /* if u_p is between b and c */
1.126 brouard 1905: fu=(*func)(u);
1.163 brouard 1906: #ifdef DEBUG
1907: /* f(x)=A(x-u)**2+f(u) */
1908: double A, fparabu;
1909: A= (*fb - *fa)/(*bx-*ax)/(*bx+*ax-2*u);
1910: fparabu= *fa - A*(*ax-u)*(*ax-u);
1.224 brouard 1911: printf("\nmnbrak (*ax=%.12f, *fa=%.12lf), (*bx=%.12f, *fb=%.12lf), (*cx=%.12f, *fc=%.12lf), (*u=%.12f, fu=%.12lf, fparabu=%.12f, q=%lf < %lf=r)\n",*ax,*fa,*bx,*fb,*cx,*fc,u,fu, fparabu,q,r);
1912: fprintf(ficlog,"\nmnbrak (*ax=%.12f, *fa=%.12lf), (*bx=%.12f, *fb=%.12lf), (*cx=%.12f, *fc=%.12lf), (*u=%.12f, fu=%.12lf, fparabu=%.12f, q=%lf < %lf=r)\n",*ax,*fa,*bx,*fb,*cx,*fc,u,fu, fparabu,q,r);
1.183 brouard 1913: /* And thus,it can be that fu > *fc even if fparabu < *fc */
1914: /* mnbrak (*ax=7.666299858533, *fa=299039.693133272231), (*bx=8.595447774979, *fb=298976.598289369489),
1915: (*cx=10.098840694817, *fc=298946.631474258087), (*u=9.852501168332, fu=298948.773013752128, fparabu=298945.434711494134) */
1916: /* In that case, there is no bracket in the output! Routine is wrong with many consequences.*/
1.163 brouard 1917: #endif
1.184 brouard 1918: #ifdef MNBRAKORIGINAL
1.183 brouard 1919: #else
1.191 brouard 1920: /* if (fu > *fc) { */
1921: /* #ifdef DEBUG */
1922: /* printf("mnbrak4 fu > fc \n"); */
1923: /* fprintf(ficlog, "mnbrak4 fu > fc\n"); */
1924: /* #endif */
1925: /* /\* SHFT(u,*cx,*cx,u) /\\* ie a=c, c=u and u=c; in that case, next SHFT(a,b,c,u) will give a=b=b, b=c=u, c=u=c and *\\/ *\/ */
1926: /* /\* SHFT(*fa,*fc,fu,*fc) /\\* (b, u, c) is a bracket while test fb > fc will be fu > fc will exit *\\/ *\/ */
1927: /* dum=u; /\* Shifting c and u *\/ */
1928: /* u = *cx; */
1929: /* *cx = dum; */
1930: /* dum = fu; */
1931: /* fu = *fc; */
1932: /* *fc =dum; */
1933: /* } else { /\* end *\/ */
1934: /* #ifdef DEBUG */
1935: /* printf("mnbrak3 fu < fc \n"); */
1936: /* fprintf(ficlog, "mnbrak3 fu < fc\n"); */
1937: /* #endif */
1938: /* dum=u; /\* Shifting c and u *\/ */
1939: /* u = *cx; */
1940: /* *cx = dum; */
1941: /* dum = fu; */
1942: /* fu = *fc; */
1943: /* *fc =dum; */
1944: /* } */
1.224 brouard 1945: #ifdef DEBUGMNBRAK
1946: double A, fparabu;
1947: A= (*fb - *fa)/(*bx-*ax)/(*bx+*ax-2*u);
1948: fparabu= *fa - A*(*ax-u)*(*ax-u);
1949: printf("\nmnbrak35 ax=%lf fa=%lf bx=%lf fb=%lf, u=%lf fp=%lf fu=%lf < or >= fc=%lf cx=%lf, q=%lf < %lf=r \n",*ax, *fa, *bx,*fb,u,fparabu,fu,*fc,*cx,q,r);
1950: fprintf(ficlog,"\nmnbrak35 ax=%lf fa=%lf bx=%lf fb=%lf, u=%lf fp=%lf fu=%lf < or >= fc=%lf cx=%lf, q=%lf < %lf=r \n",*ax, *fa, *bx,*fb,u,fparabu,fu,*fc,*cx,q,r);
1.183 brouard 1951: #endif
1.191 brouard 1952: dum=u; /* Shifting c and u */
1953: u = *cx;
1954: *cx = dum;
1955: dum = fu;
1956: fu = *fc;
1957: *fc =dum;
1.183 brouard 1958: #endif
1.162 brouard 1959: } else if ((*cx-u)*(u-ulim) > 0.0) { /* u is after c but before ulim */
1.183 brouard 1960: #ifdef DEBUG
1.224 brouard 1961: printf("\nmnbrak2 u=%lf after c=%lf but before ulim\n",u,*cx);
1962: fprintf(ficlog,"\nmnbrak2 u=%lf after c=%lf but before ulim\n",u,*cx);
1.183 brouard 1963: #endif
1.126 brouard 1964: fu=(*func)(u);
1965: if (fu < *fc) {
1.183 brouard 1966: #ifdef DEBUG
1.224 brouard 1967: printf("\nmnbrak2 u=%lf after c=%lf but before ulim=%lf AND fu=%lf < %lf=fc\n",u,*cx,ulim,fu, *fc);
1968: fprintf(ficlog,"\nmnbrak2 u=%lf after c=%lf but before ulim=%lf AND fu=%lf < %lf=fc\n",u,*cx,ulim,fu, *fc);
1969: #endif
1970: SHFT(*bx,*cx,u,*cx+GOLD*(*cx-*bx))
1971: SHFT(*fb,*fc,fu,(*func)(u))
1972: #ifdef DEBUG
1973: printf("\nmnbrak2 shift GOLD c=%lf",*cx+GOLD*(*cx-*bx));
1.183 brouard 1974: #endif
1975: }
1.162 brouard 1976: } else if ((u-ulim)*(ulim-*cx) >= 0.0) { /* u outside ulim (verifying that ulim is beyond c) */
1.183 brouard 1977: #ifdef DEBUG
1.224 brouard 1978: printf("\nmnbrak2 u=%lf outside ulim=%lf (verifying that ulim is beyond c=%lf)\n",u,ulim,*cx);
1979: fprintf(ficlog,"\nmnbrak2 u=%lf outside ulim=%lf (verifying that ulim is beyond c=%lf)\n",u,ulim,*cx);
1.183 brouard 1980: #endif
1.126 brouard 1981: u=ulim;
1982: fu=(*func)(u);
1.183 brouard 1983: } else { /* u could be left to b (if r > q parabola has a maximum) */
1984: #ifdef DEBUG
1.224 brouard 1985: printf("\nmnbrak2 u=%lf could be left to b=%lf (if r=%lf > q=%lf parabola has a maximum)\n",u,*bx,r,q);
1986: fprintf(ficlog,"\nmnbrak2 u=%lf could be left to b=%lf (if r=%lf > q=%lf parabola has a maximum)\n",u,*bx,r,q);
1.183 brouard 1987: #endif
1.126 brouard 1988: u=(*cx)+GOLD*(*cx-*bx);
1989: fu=(*func)(u);
1.224 brouard 1990: #ifdef DEBUG
1991: printf("\nmnbrak2 new u=%lf fu=%lf shifted gold left from c=%lf and b=%lf \n",u,fu,*cx,*bx);
1992: fprintf(ficlog,"\nmnbrak2 new u=%lf fu=%lf shifted gold left from c=%lf and b=%lf \n",u,fu,*cx,*bx);
1993: #endif
1.183 brouard 1994: } /* end tests */
1.126 brouard 1995: SHFT(*ax,*bx,*cx,u)
1.183 brouard 1996: SHFT(*fa,*fb,*fc,fu)
1997: #ifdef DEBUG
1.224 brouard 1998: printf("\nmnbrak2 shift (*ax=%.12f, *fa=%.12lf), (*bx=%.12f, *fb=%.12lf), (*cx=%.12f, *fc=%.12lf)\n",*ax,*fa,*bx,*fb,*cx,*fc);
1999: fprintf(ficlog, "\nmnbrak2 shift (*ax=%.12f, *fa=%.12lf), (*bx=%.12f, *fb=%.12lf), (*cx=%.12f, *fc=%.12lf)\n",*ax,*fa,*bx,*fb,*cx,*fc);
1.183 brouard 2000: #endif
2001: } /* end while; ie return (a, b, c, fa, fb, fc) such that a < b < c with f(a) > f(b) and fb < f(c) */
1.126 brouard 2002: }
2003:
2004: /*************** linmin ************************/
1.162 brouard 2005: /* Given an n -dimensional point p[1..n] and an n -dimensional direction xi[1..n] , moves and
2006: resets p to where the function func(p) takes on a minimum along the direction xi from p ,
2007: and replaces xi by the actual vector displacement that p was moved. Also returns as fret
2008: the value of func at the returned location p . This is actually all accomplished by calling the
2009: routines mnbrak and brent .*/
1.126 brouard 2010: int ncom;
2011: double *pcom,*xicom;
2012: double (*nrfunc)(double []);
2013:
1.224 brouard 2014: #ifdef LINMINORIGINAL
1.126 brouard 2015: void linmin(double p[], double xi[], int n, double *fret,double (*func)(double []))
1.224 brouard 2016: #else
2017: void linmin(double p[], double xi[], int n, double *fret,double (*func)(double []), int *flat)
2018: #endif
1.126 brouard 2019: {
2020: double brent(double ax, double bx, double cx,
2021: double (*f)(double), double tol, double *xmin);
2022: double f1dim(double x);
2023: void mnbrak(double *ax, double *bx, double *cx, double *fa, double *fb,
2024: double *fc, double (*func)(double));
2025: int j;
2026: double xx,xmin,bx,ax;
2027: double fx,fb,fa;
1.187 brouard 2028:
1.203 brouard 2029: #ifdef LINMINORIGINAL
2030: #else
2031: double scale=10., axs, xxs; /* Scale added for infinity */
2032: #endif
2033:
1.126 brouard 2034: ncom=n;
2035: pcom=vector(1,n);
2036: xicom=vector(1,n);
2037: nrfunc=func;
2038: for (j=1;j<=n;j++) {
2039: pcom[j]=p[j];
1.202 brouard 2040: xicom[j]=xi[j]; /* Former scale xi[j] of currrent direction i */
1.126 brouard 2041: }
1.187 brouard 2042:
1.203 brouard 2043: #ifdef LINMINORIGINAL
2044: xx=1.;
2045: #else
2046: axs=0.0;
2047: xxs=1.;
2048: do{
2049: xx= xxs;
2050: #endif
1.187 brouard 2051: ax=0.;
2052: mnbrak(&ax,&xx,&bx,&fa,&fx,&fb,f1dim); /* Outputs: xtx[j]=pcom[j]+(*xx)*xicom[j]; fx=f(xtx[j]) */
2053: /* brackets with inputs ax=0 and xx=1, but points, pcom=p, and directions values, xicom=xi, are sent via f1dim(x) */
2054: /* xt[x,j]=pcom[j]+x*xicom[j] f(ax) = f(xt(a,j=1,n)) = f(p(j) + 0 * xi(j)) and f(xx) = f(xt(x, j=1,n)) = f(p(j) + 1 * xi(j)) */
2055: /* Outputs: fa=f(p(j)) and fx=f(p(j) + xxs * xi(j) ) and f(bx)= f(p(j)+ bx* xi(j)) */
2056: /* Given input ax=axs and xx=xxs, xx might be too far from ax to get a finite f(xx) */
2057: /* Searches on line, outputs (ax, xx, bx) such that fx < min(fa and fb) */
2058: /* Find a bracket a,x,b in direction n=xi ie xicom, order may change. Scale is [0:xxs*xi[j]] et non plus [0:xi[j]]*/
1.203 brouard 2059: #ifdef LINMINORIGINAL
2060: #else
2061: if (fx != fx){
1.224 brouard 2062: xxs=xxs/scale; /* Trying a smaller xx, closer to initial ax=0 */
2063: printf("|");
2064: fprintf(ficlog,"|");
1.203 brouard 2065: #ifdef DEBUGLINMIN
1.224 brouard 2066: printf("\nLinmin NAN : input [axs=%lf:xxs=%lf], mnbrak outputs fx=%lf <(fb=%lf and fa=%lf) with xx=%lf in [ax=%lf:bx=%lf] \n", axs, xxs, fx,fb, fa, xx, ax, bx);
1.203 brouard 2067: #endif
2068: }
1.224 brouard 2069: }while(fx != fx && xxs > 1.e-5);
1.203 brouard 2070: #endif
2071:
1.191 brouard 2072: #ifdef DEBUGLINMIN
2073: printf("\nLinmin after mnbrak: ax=%12.7f xx=%12.7f bx=%12.7f fa=%12.2f fx=%12.2f fb=%12.2f\n", ax,xx,bx,fa,fx,fb);
1.202 brouard 2074: fprintf(ficlog,"\nLinmin after mnbrak: ax=%12.7f xx=%12.7f bx=%12.7f fa=%12.2f fx=%12.2f fb=%12.2f\n", ax,xx,bx,fa,fx,fb);
1.191 brouard 2075: #endif
1.224 brouard 2076: #ifdef LINMINORIGINAL
2077: #else
2078: if(fb == fx){ /* Flat function in the direction */
2079: xmin=xx;
2080: *flat=1;
2081: }else{
2082: *flat=0;
2083: #endif
2084: /*Flat mnbrak2 shift (*ax=0.000000000000, *fa=51626.272983130431), (*bx=-1.618034000000, *fb=51590.149499362531), (*cx=-4.236068025156, *fc=51590.149499362531) */
1.187 brouard 2085: *fret=brent(ax,xx,bx,f1dim,TOL,&xmin); /* Giving a bracketting triplet (ax, xx, bx), find a minimum, xmin, according to f1dim, *fret(xmin),*/
2086: /* fa = f(p[j] + ax * xi[j]), fx = f(p[j] + xx * xi[j]), fb = f(p[j] + bx * xi[j]) */
2087: /* fmin = f(p[j] + xmin * xi[j]) */
2088: /* P+lambda n in that direction (lambdamin), with TOL between abscisses */
2089: /* f1dim(xmin): for (j=1;j<=ncom;j++) xt[j]=pcom[j]+xmin*xicom[j]; */
1.126 brouard 2090: #ifdef DEBUG
1.224 brouard 2091: printf("retour brent from bracket (a=%lf fa=%lf, xx=%lf fx=%lf, b=%lf fb=%lf): fret=%lf xmin=%lf\n",ax,fa,xx,fx,bx,fb,*fret,xmin);
2092: fprintf(ficlog,"retour brent from bracket (a=%lf fa=%lf, xx=%lf fx=%lf, b=%lf fb=%lf): fret=%lf xmin=%lf\n",ax,fa,xx,fx,bx,fb,*fret,xmin);
2093: #endif
2094: #ifdef LINMINORIGINAL
2095: #else
2096: }
1.126 brouard 2097: #endif
1.191 brouard 2098: #ifdef DEBUGLINMIN
2099: printf("linmin end ");
1.202 brouard 2100: fprintf(ficlog,"linmin end ");
1.191 brouard 2101: #endif
1.126 brouard 2102: for (j=1;j<=n;j++) {
1.203 brouard 2103: #ifdef LINMINORIGINAL
2104: xi[j] *= xmin;
2105: #else
2106: #ifdef DEBUGLINMIN
2107: if(xxs <1.0)
2108: printf(" before xi[%d]=%12.8f", j,xi[j]);
2109: #endif
2110: xi[j] *= xmin*xxs; /* xi rescaled by xmin and number of loops: if xmin=-1.237 and xi=(1,0,...,0) xi=(-1.237,0,...,0) */
2111: #ifdef DEBUGLINMIN
2112: if(xxs <1.0)
2113: printf(" after xi[%d]=%12.8f, xmin=%12.8f, ax=%12.8f, xx=%12.8f, bx=%12.8f, xxs=%12.8f", j,xi[j], xmin, ax, xx, bx,xxs );
2114: #endif
2115: #endif
1.187 brouard 2116: p[j] += xi[j]; /* Parameters values are updated accordingly */
1.126 brouard 2117: }
1.191 brouard 2118: #ifdef DEBUGLINMIN
1.203 brouard 2119: printf("\n");
1.191 brouard 2120: printf("Comparing last *frec(xmin=%12.8f)=%12.8f from Brent and frec(0.)=%12.8f \n", xmin, *fret, (*func)(p));
1.202 brouard 2121: fprintf(ficlog,"Comparing last *frec(xmin=%12.8f)=%12.8f from Brent and frec(0.)=%12.8f \n", xmin, *fret, (*func)(p));
1.191 brouard 2122: for (j=1;j<=n;j++) {
1.202 brouard 2123: printf(" xi[%d]= %14.10f p[%d]= %12.7f",j,xi[j],j,p[j]);
2124: fprintf(ficlog," xi[%d]= %14.10f p[%d]= %12.7f",j,xi[j],j,p[j]);
2125: if(j % ncovmodel == 0){
1.191 brouard 2126: printf("\n");
1.202 brouard 2127: fprintf(ficlog,"\n");
2128: }
1.191 brouard 2129: }
1.203 brouard 2130: #else
1.191 brouard 2131: #endif
1.126 brouard 2132: free_vector(xicom,1,n);
2133: free_vector(pcom,1,n);
2134: }
2135:
2136:
2137: /*************** powell ************************/
1.162 brouard 2138: /*
2139: Minimization of a function func of n variables. Input consists of an initial starting point
2140: p[1..n] ; an initial matrix xi[1..n][1..n] , whose columns contain the initial set of di-
2141: rections (usually the n unit vectors); and ftol , the fractional tolerance in the function value
2142: such that failure to decrease by more than this amount on one iteration signals doneness. On
2143: output, p is set to the best point found, xi is the then-current direction set, fret is the returned
2144: function value at p , and iter is the number of iterations taken. The routine linmin is used.
2145: */
1.224 brouard 2146: #ifdef LINMINORIGINAL
2147: #else
2148: int *flatdir; /* Function is vanishing in that direction */
1.225 brouard 2149: int flat=0, flatd=0; /* Function is vanishing in that direction */
1.224 brouard 2150: #endif
1.126 brouard 2151: void powell(double p[], double **xi, int n, double ftol, int *iter, double *fret,
2152: double (*func)(double []))
2153: {
1.224 brouard 2154: #ifdef LINMINORIGINAL
2155: void linmin(double p[], double xi[], int n, double *fret,
1.126 brouard 2156: double (*func)(double []));
1.224 brouard 2157: #else
1.241 brouard 2158: void linmin(double p[], double xi[], int n, double *fret,
2159: double (*func)(double []),int *flat);
1.224 brouard 2160: #endif
1.239 brouard 2161: int i,ibig,j,jk,k;
1.126 brouard 2162: double del,t,*pt,*ptt,*xit;
1.181 brouard 2163: double directest;
1.126 brouard 2164: double fp,fptt;
2165: double *xits;
2166: int niterf, itmp;
1.224 brouard 2167: #ifdef LINMINORIGINAL
2168: #else
2169:
2170: flatdir=ivector(1,n);
2171: for (j=1;j<=n;j++) flatdir[j]=0;
2172: #endif
1.126 brouard 2173:
2174: pt=vector(1,n);
2175: ptt=vector(1,n);
2176: xit=vector(1,n);
2177: xits=vector(1,n);
2178: *fret=(*func)(p);
2179: for (j=1;j<=n;j++) pt[j]=p[j];
1.202 brouard 2180: rcurr_time = time(NULL);
1.126 brouard 2181: for (*iter=1;;++(*iter)) {
1.187 brouard 2182: fp=(*fret); /* From former iteration or initial value */
1.126 brouard 2183: ibig=0;
2184: del=0.0;
1.157 brouard 2185: rlast_time=rcurr_time;
2186: /* (void) gettimeofday(&curr_time,&tzp); */
2187: rcurr_time = time(NULL);
2188: curr_time = *localtime(&rcurr_time);
2189: printf("\nPowell iter=%d -2*LL=%.12f %ld sec. %ld sec.",*iter,*fret, rcurr_time-rlast_time, rcurr_time-rstart_time);fflush(stdout);
2190: fprintf(ficlog,"\nPowell iter=%d -2*LL=%.12f %ld sec. %ld sec.",*iter,*fret,rcurr_time-rlast_time, rcurr_time-rstart_time); fflush(ficlog);
2191: /* fprintf(ficrespow,"%d %.12f %ld",*iter,*fret,curr_time.tm_sec-start_time.tm_sec); */
1.192 brouard 2192: for (i=1;i<=n;i++) {
1.126 brouard 2193: fprintf(ficrespow," %.12lf", p[i]);
2194: }
1.239 brouard 2195: fprintf(ficrespow,"\n");fflush(ficrespow);
2196: printf("\n#model= 1 + age ");
2197: fprintf(ficlog,"\n#model= 1 + age ");
2198: if(nagesqr==1){
1.241 brouard 2199: printf(" + age*age ");
2200: fprintf(ficlog," + age*age ");
1.239 brouard 2201: }
2202: for(j=1;j <=ncovmodel-2;j++){
2203: if(Typevar[j]==0) {
2204: printf(" + V%d ",Tvar[j]);
2205: fprintf(ficlog," + V%d ",Tvar[j]);
2206: }else if(Typevar[j]==1) {
2207: printf(" + V%d*age ",Tvar[j]);
2208: fprintf(ficlog," + V%d*age ",Tvar[j]);
2209: }else if(Typevar[j]==2) {
2210: printf(" + V%d*V%d ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
2211: fprintf(ficlog," + V%d*V%d ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
2212: }
2213: }
1.126 brouard 2214: printf("\n");
1.239 brouard 2215: /* printf("12 47.0114589 0.0154322 33.2424412 0.3279905 2.3731903 */
2216: /* 13 -21.5392400 0.1118147 1.2680506 1.2973408 -1.0663662 */
1.126 brouard 2217: fprintf(ficlog,"\n");
1.239 brouard 2218: for(i=1,jk=1; i <=nlstate; i++){
2219: for(k=1; k <=(nlstate+ndeath); k++){
2220: if (k != i) {
2221: printf("%d%d ",i,k);
2222: fprintf(ficlog,"%d%d ",i,k);
2223: for(j=1; j <=ncovmodel; j++){
2224: printf("%12.7f ",p[jk]);
2225: fprintf(ficlog,"%12.7f ",p[jk]);
2226: jk++;
2227: }
2228: printf("\n");
2229: fprintf(ficlog,"\n");
2230: }
2231: }
2232: }
1.241 brouard 2233: if(*iter <=3 && *iter >1){
1.157 brouard 2234: tml = *localtime(&rcurr_time);
2235: strcpy(strcurr,asctime(&tml));
2236: rforecast_time=rcurr_time;
1.126 brouard 2237: itmp = strlen(strcurr);
2238: if(strcurr[itmp-1]=='\n') /* Windows outputs with a new line */
1.241 brouard 2239: strcurr[itmp-1]='\0';
1.162 brouard 2240: printf("\nConsidering the time needed for the last iteration #%d: %ld seconds,\n",*iter,rcurr_time-rlast_time);
1.157 brouard 2241: fprintf(ficlog,"\nConsidering the time needed for this last iteration #%d: %ld seconds,\n",*iter,rcurr_time-rlast_time);
1.126 brouard 2242: for(niterf=10;niterf<=30;niterf+=10){
1.241 brouard 2243: rforecast_time=rcurr_time+(niterf-*iter)*(rcurr_time-rlast_time);
2244: forecast_time = *localtime(&rforecast_time);
2245: strcpy(strfor,asctime(&forecast_time));
2246: itmp = strlen(strfor);
2247: if(strfor[itmp-1]=='\n')
2248: strfor[itmp-1]='\0';
2249: printf(" - if your program needs %d iterations to converge, convergence will be \n reached in %s i.e.\n on %s (current time is %s);\n",niterf, asc_diff_time(rforecast_time-rcurr_time,tmpout),strfor,strcurr);
2250: fprintf(ficlog," - if your program needs %d iterations to converge, convergence will be \n reached in %s i.e.\n on %s (current time is %s);\n",niterf, asc_diff_time(rforecast_time-rcurr_time,tmpout),strfor,strcurr);
1.126 brouard 2251: }
2252: }
1.187 brouard 2253: for (i=1;i<=n;i++) { /* For each direction i */
2254: for (j=1;j<=n;j++) xit[j]=xi[j][i]; /* Directions stored from previous iteration with previous scales */
1.126 brouard 2255: fptt=(*fret);
2256: #ifdef DEBUG
1.203 brouard 2257: printf("fret=%lf, %lf, %lf \n", *fret, *fret, *fret);
2258: fprintf(ficlog, "fret=%lf, %lf, %lf \n", *fret, *fret, *fret);
1.126 brouard 2259: #endif
1.203 brouard 2260: printf("%d",i);fflush(stdout); /* print direction (parameter) i */
1.126 brouard 2261: fprintf(ficlog,"%d",i);fflush(ficlog);
1.224 brouard 2262: #ifdef LINMINORIGINAL
1.188 brouard 2263: linmin(p,xit,n,fret,func); /* Point p[n]. xit[n] has been loaded for direction i as input.*/
1.224 brouard 2264: #else
2265: linmin(p,xit,n,fret,func,&flat); /* Point p[n]. xit[n] has been loaded for direction i as input.*/
2266: flatdir[i]=flat; /* Function is vanishing in that direction i */
2267: #endif
2268: /* Outputs are fret(new point p) p is updated and xit rescaled */
1.188 brouard 2269: if (fabs(fptt-(*fret)) > del) { /* We are keeping the max gain on each of the n directions */
1.224 brouard 2270: /* because that direction will be replaced unless the gain del is small */
2271: /* in comparison with the 'probable' gain, mu^2, with the last average direction. */
2272: /* Unless the n directions are conjugate some gain in the determinant may be obtained */
2273: /* with the new direction. */
2274: del=fabs(fptt-(*fret));
2275: ibig=i;
1.126 brouard 2276: }
2277: #ifdef DEBUG
2278: printf("%d %.12e",i,(*fret));
2279: fprintf(ficlog,"%d %.12e",i,(*fret));
2280: for (j=1;j<=n;j++) {
1.224 brouard 2281: xits[j]=FMAX(fabs(p[j]-pt[j]),1.e-5);
2282: printf(" x(%d)=%.12e",j,xit[j]);
2283: fprintf(ficlog," x(%d)=%.12e",j,xit[j]);
1.126 brouard 2284: }
2285: for(j=1;j<=n;j++) {
1.225 brouard 2286: printf(" p(%d)=%.12e",j,p[j]);
2287: fprintf(ficlog," p(%d)=%.12e",j,p[j]);
1.126 brouard 2288: }
2289: printf("\n");
2290: fprintf(ficlog,"\n");
2291: #endif
1.187 brouard 2292: } /* end loop on each direction i */
2293: /* Convergence test will use last linmin estimation (fret) and compare former iteration (fp) */
1.188 brouard 2294: /* But p and xit have been updated at the end of linmin, *fret corresponds to new p, xit */
1.187 brouard 2295: /* New value of last point Pn is not computed, P(n-1) */
1.224 brouard 2296: for(j=1;j<=n;j++) {
1.225 brouard 2297: if(flatdir[j] >0){
2298: printf(" p(%d)=%lf flat=%d ",j,p[j],flatdir[j]);
2299: fprintf(ficlog," p(%d)=%lf flat=%d ",j,p[j],flatdir[j]);
2300: }
2301: /* printf("\n"); */
2302: /* fprintf(ficlog,"\n"); */
2303: }
1.243 brouard 2304: /* if (2.0*fabs(fp-(*fret)) <= ftol*(fabs(fp)+fabs(*fret))) { /\* Did we reach enough precision? *\/ */
2305: if (2.0*fabs(fp-(*fret)) <= ftol) { /* Did we reach enough precision? */
1.188 brouard 2306: /* We could compare with a chi^2. chisquare(0.95,ddl=1)=3.84 */
2307: /* By adding age*age in a model, the new -2LL should be lower and the difference follows a */
2308: /* a chisquare statistics with 1 degree. To be significant at the 95% level, it should have */
2309: /* decreased of more than 3.84 */
2310: /* By adding age*age and V1*age the gain (-2LL) should be more than 5.99 (ddl=2) */
2311: /* By using V1+V2+V3, the gain should be 7.82, compared with basic 1+age. */
2312: /* By adding 10 parameters more the gain should be 18.31 */
1.224 brouard 2313:
1.188 brouard 2314: /* Starting the program with initial values given by a former maximization will simply change */
2315: /* the scales of the directions and the directions, because the are reset to canonical directions */
2316: /* Thus the first calls to linmin will give new points and better maximizations until fp-(*fret) is */
2317: /* under the tolerance value. If the tolerance is very small 1.e-9, it could last long. */
1.126 brouard 2318: #ifdef DEBUG
2319: int k[2],l;
2320: k[0]=1;
2321: k[1]=-1;
2322: printf("Max: %.12e",(*func)(p));
2323: fprintf(ficlog,"Max: %.12e",(*func)(p));
2324: for (j=1;j<=n;j++) {
2325: printf(" %.12e",p[j]);
2326: fprintf(ficlog," %.12e",p[j]);
2327: }
2328: printf("\n");
2329: fprintf(ficlog,"\n");
2330: for(l=0;l<=1;l++) {
2331: for (j=1;j<=n;j++) {
2332: ptt[j]=p[j]+(p[j]-pt[j])*k[l];
2333: printf("l=%d j=%d ptt=%.12e, xits=%.12e, p=%.12e, xit=%.12e", l,j,ptt[j],xits[j],p[j],xit[j]);
2334: fprintf(ficlog,"l=%d j=%d ptt=%.12e, xits=%.12e, p=%.12e, xit=%.12e", l,j,ptt[j],xits[j],p[j],xit[j]);
2335: }
2336: printf("func(ptt)=%.12e, deriv=%.12e\n",(*func)(ptt),(ptt[j]-p[j])/((*func)(ptt)-(*func)(p)));
2337: fprintf(ficlog,"func(ptt)=%.12e, deriv=%.12e\n",(*func)(ptt),(ptt[j]-p[j])/((*func)(ptt)-(*func)(p)));
2338: }
2339: #endif
2340:
1.224 brouard 2341: #ifdef LINMINORIGINAL
2342: #else
2343: free_ivector(flatdir,1,n);
2344: #endif
1.126 brouard 2345: free_vector(xit,1,n);
2346: free_vector(xits,1,n);
2347: free_vector(ptt,1,n);
2348: free_vector(pt,1,n);
2349: return;
1.192 brouard 2350: } /* enough precision */
1.240 brouard 2351: if (*iter == ITMAX*n) nrerror("powell exceeding maximum iterations.");
1.181 brouard 2352: for (j=1;j<=n;j++) { /* Computes the extrapolated point P_0 + 2 (P_n-P_0) */
1.126 brouard 2353: ptt[j]=2.0*p[j]-pt[j];
2354: xit[j]=p[j]-pt[j];
2355: pt[j]=p[j];
2356: }
1.181 brouard 2357: fptt=(*func)(ptt); /* f_3 */
1.224 brouard 2358: #ifdef NODIRECTIONCHANGEDUNTILNITER /* No change in drections until some iterations are done */
2359: if (*iter <=4) {
1.225 brouard 2360: #else
2361: #endif
1.224 brouard 2362: #ifdef POWELLNOF3INFF1TEST /* skips test F3 <F1 */
1.192 brouard 2363: #else
1.161 brouard 2364: if (fptt < fp) { /* If extrapolated point is better, decide if we keep that new direction or not */
1.192 brouard 2365: #endif
1.162 brouard 2366: /* (x1 f1=fp), (x2 f2=*fret), (x3 f3=fptt), (xm fm) */
1.161 brouard 2367: /* From x1 (P0) distance of x2 is at h and x3 is 2h */
1.162 brouard 2368: /* Let f"(x2) be the 2nd derivative equal everywhere. */
2369: /* Then the parabolic through (x1,f1), (x2,f2) and (x3,f3) */
2370: /* will reach at f3 = fm + h^2/2 f"m ; f" = (f1 -2f2 +f3 ) / h**2 */
1.224 brouard 2371: /* Conditional for using this new direction is that mu^2 = (f1-2f2+f3)^2 /2 < del or directest <0 */
2372: /* also lamda^2=(f1-f2)^2/mu² is a parasite solution of powell */
2373: /* For powell, inclusion of this average direction is only if t(del)<0 or del inbetween mu^2 and lambda^2 */
1.161 brouard 2374: /* t=2.0*(fp-2.0*(*fret)+fptt)*SQR(fp-(*fret)-del)-del*SQR(fp-fptt); */
1.224 brouard 2375: /* Even if f3 <f1, directest can be negative and t >0 */
2376: /* mu² and del² are equal when f3=f1 */
2377: /* f3 < f1 : mu² < del <= lambda^2 both test are equivalent */
2378: /* f3 < f1 : mu² < lambda^2 < del then directtest is negative and powell t is positive */
2379: /* f3 > f1 : lambda² < mu^2 < del then t is negative and directest >0 */
2380: /* f3 > f1 : lambda² < del < mu^2 then t is positive and directest >0 */
1.183 brouard 2381: #ifdef NRCORIGINAL
2382: t=2.0*(fp-2.0*(*fret)+fptt)*SQR(fp-(*fret)-del)- del*SQR(fp-fptt); /* Original Numerical Recipes in C*/
2383: #else
2384: t=2.0*(fp-2.0*(*fret)+fptt)*SQR(fp-(*fret)-del); /* Intel compiler doesn't work on one line; bug reported */
1.161 brouard 2385: t= t- del*SQR(fp-fptt);
1.183 brouard 2386: #endif
1.202 brouard 2387: directest = fp-2.0*(*fret)+fptt - 2.0 * del; /* If delta was big enough we change it for a new direction */
1.161 brouard 2388: #ifdef DEBUG
1.181 brouard 2389: printf("t1= %.12lf, t2= %.12lf, t=%.12lf directest=%.12lf\n", 2.0*(fp-2.0*(*fret)+fptt)*SQR(fp-(*fret)-del),del*SQR(fp-fptt),t,directest);
2390: fprintf(ficlog,"t1= %.12lf, t2= %.12lf, t=%.12lf directest=%.12lf\n", 2.0*(fp-2.0*(*fret)+fptt)*SQR(fp-(*fret)-del),del*SQR(fp-fptt),t,directest);
1.161 brouard 2391: printf("t3= %.12lf, t4= %.12lf, t3*= %.12lf, t4*= %.12lf\n",SQR(fp-(*fret)-del),SQR(fp-fptt),
2392: (fp-(*fret)-del)*(fp-(*fret)-del),(fp-fptt)*(fp-fptt));
2393: fprintf(ficlog,"t3= %.12lf, t4= %.12lf, t3*= %.12lf, t4*= %.12lf\n",SQR(fp-(*fret)-del),SQR(fp-fptt),
2394: (fp-(*fret)-del)*(fp-(*fret)-del),(fp-fptt)*(fp-fptt));
2395: printf("tt= %.12lf, t=%.12lf\n",2.0*(fp-2.0*(*fret)+fptt)*(fp-(*fret)-del)*(fp-(*fret)-del)-del*(fp-fptt)*(fp-fptt),t);
2396: fprintf(ficlog, "tt= %.12lf, t=%.12lf\n",2.0*(fp-2.0*(*fret)+fptt)*(fp-(*fret)-del)*(fp-(*fret)-del)-del*(fp-fptt)*(fp-fptt),t);
2397: #endif
1.183 brouard 2398: #ifdef POWELLORIGINAL
2399: if (t < 0.0) { /* Then we use it for new direction */
2400: #else
1.182 brouard 2401: if (directest*t < 0.0) { /* Contradiction between both tests */
1.224 brouard 2402: printf("directest= %.12lf (if <0 we include P0 Pn as new direction), t= %.12lf, f1= %.12lf,f2= %.12lf,f3= %.12lf, del= %.12lf\n",directest, t, fp,(*fret),fptt,del);
1.192 brouard 2403: printf("f1-2f2+f3= %.12lf, f1-f2-del= %.12lf, f1-f3= %.12lf\n",fp-2.0*(*fret)+fptt, fp -(*fret) -del, fp-fptt);
1.224 brouard 2404: fprintf(ficlog,"directest= %.12lf (if directest<0 or t<0 we include P0 Pn as new direction), t= %.12lf, f1= %.12lf,f2= %.12lf,f3= %.12lf, del= %.12lf\n",directest, t, fp,(*fret),fptt, del);
1.192 brouard 2405: fprintf(ficlog,"f1-2f2+f3= %.12lf, f1-f2-del= %.12lf, f1-f3= %.12lf\n",fp-2.0*(*fret)+fptt, fp -(*fret) -del, fp-fptt);
2406: }
1.181 brouard 2407: if (directest < 0.0) { /* Then we use it for new direction */
2408: #endif
1.191 brouard 2409: #ifdef DEBUGLINMIN
1.234 brouard 2410: printf("Before linmin in direction P%d-P0\n",n);
2411: for (j=1;j<=n;j++) {
2412: printf(" Before xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
2413: fprintf(ficlog," Before xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
2414: if(j % ncovmodel == 0){
2415: printf("\n");
2416: fprintf(ficlog,"\n");
2417: }
2418: }
1.224 brouard 2419: #endif
2420: #ifdef LINMINORIGINAL
1.234 brouard 2421: linmin(p,xit,n,fret,func); /* computes minimum on the extrapolated direction: changes p and rescales xit.*/
1.224 brouard 2422: #else
1.234 brouard 2423: linmin(p,xit,n,fret,func,&flat); /* computes minimum on the extrapolated direction: changes p and rescales xit.*/
2424: flatdir[i]=flat; /* Function is vanishing in that direction i */
1.191 brouard 2425: #endif
1.234 brouard 2426:
1.191 brouard 2427: #ifdef DEBUGLINMIN
1.234 brouard 2428: for (j=1;j<=n;j++) {
2429: printf("After xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
2430: fprintf(ficlog,"After xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
2431: if(j % ncovmodel == 0){
2432: printf("\n");
2433: fprintf(ficlog,"\n");
2434: }
2435: }
1.224 brouard 2436: #endif
1.234 brouard 2437: for (j=1;j<=n;j++) {
2438: xi[j][ibig]=xi[j][n]; /* Replace direction with biggest decrease by last direction n */
2439: xi[j][n]=xit[j]; /* and this nth direction by the by the average p_0 p_n */
2440: }
1.224 brouard 2441: #ifdef LINMINORIGINAL
2442: #else
1.234 brouard 2443: for (j=1, flatd=0;j<=n;j++) {
2444: if(flatdir[j]>0)
2445: flatd++;
2446: }
2447: if(flatd >0){
1.255 brouard 2448: printf("%d flat directions: ",flatd);
2449: fprintf(ficlog,"%d flat directions :",flatd);
1.234 brouard 2450: for (j=1;j<=n;j++) {
2451: if(flatdir[j]>0){
2452: printf("%d ",j);
2453: fprintf(ficlog,"%d ",j);
2454: }
2455: }
2456: printf("\n");
2457: fprintf(ficlog,"\n");
2458: }
1.191 brouard 2459: #endif
1.234 brouard 2460: printf("Gaining to use new average direction of P0 P%d instead of biggest increase direction %d :\n",n,ibig);
2461: fprintf(ficlog,"Gaining to use new average direction of P0 P%d instead of biggest increase direction %d :\n",n,ibig);
2462:
1.126 brouard 2463: #ifdef DEBUG
1.234 brouard 2464: printf("Direction changed last moved %d in place of ibig=%d, new last is the average:\n",n,ibig);
2465: fprintf(ficlog,"Direction changed last moved %d in place of ibig=%d, new last is the average:\n",n,ibig);
2466: for(j=1;j<=n;j++){
2467: printf(" %lf",xit[j]);
2468: fprintf(ficlog," %lf",xit[j]);
2469: }
2470: printf("\n");
2471: fprintf(ficlog,"\n");
1.126 brouard 2472: #endif
1.192 brouard 2473: } /* end of t or directest negative */
1.224 brouard 2474: #ifdef POWELLNOF3INFF1TEST
1.192 brouard 2475: #else
1.234 brouard 2476: } /* end if (fptt < fp) */
1.192 brouard 2477: #endif
1.225 brouard 2478: #ifdef NODIRECTIONCHANGEDUNTILNITER /* No change in drections until some iterations are done */
1.234 brouard 2479: } /*NODIRECTIONCHANGEDUNTILNITER No change in drections until some iterations are done */
1.225 brouard 2480: #else
1.224 brouard 2481: #endif
1.234 brouard 2482: } /* loop iteration */
1.126 brouard 2483: }
1.234 brouard 2484:
1.126 brouard 2485: /**** Prevalence limit (stable or period prevalence) ****************/
1.234 brouard 2486:
1.235 brouard 2487: double **prevalim(double **prlim, int nlstate, double x[], double age, double **oldm, double **savm, double ftolpl, int *ncvyear, int ij, int nres)
1.234 brouard 2488: {
1.235 brouard 2489: /* Computes the prevalence limit in each live state at age x and for covariate combination ij
2490: (and selected quantitative values in nres)
2491: by left multiplying the unit
1.234 brouard 2492: matrix by transitions matrix until convergence is reached with precision ftolpl */
1.206 brouard 2493: /* Wx= Wx-1 Px-1= Wx-2 Px-2 Px-1 = Wx-n Px-n ... Px-2 Px-1 I */
2494: /* Wx is row vector: population in state 1, population in state 2, population dead */
2495: /* or prevalence in state 1, prevalence in state 2, 0 */
2496: /* newm is the matrix after multiplications, its rows are identical at a factor */
2497: /* Initial matrix pimij */
2498: /* {0.85204250825084937, 0.13044499163996345, 0.017512500109187184, */
2499: /* 0.090851990222114765, 0.88271245433047185, 0.026435555447413338, */
2500: /* 0, 0 , 1} */
2501: /*
2502: * and after some iteration: */
2503: /* {0.45504275246439968, 0.42731458730878791, 0.11764266022681241, */
2504: /* 0.45201005341706885, 0.42865420071559901, 0.11933574586733192, */
2505: /* 0, 0 , 1} */
2506: /* And prevalence by suppressing the deaths are close to identical rows in prlim: */
2507: /* {0.51571254859325999, 0.4842874514067399, */
2508: /* 0.51326036147820708, 0.48673963852179264} */
2509: /* If we start from prlim again, prlim tends to a constant matrix */
1.234 brouard 2510:
1.126 brouard 2511: int i, ii,j,k;
1.209 brouard 2512: double *min, *max, *meandiff, maxmax,sumnew=0.;
1.145 brouard 2513: /* double **matprod2(); */ /* test */
1.218 brouard 2514: double **out, cov[NCOVMAX+1], **pmij(); /* **pmmij is a global variable feeded with oldms etc */
1.126 brouard 2515: double **newm;
1.209 brouard 2516: double agefin, delaymax=200. ; /* 100 Max number of years to converge */
1.203 brouard 2517: int ncvloop=0;
1.169 brouard 2518:
1.209 brouard 2519: min=vector(1,nlstate);
2520: max=vector(1,nlstate);
2521: meandiff=vector(1,nlstate);
2522:
1.218 brouard 2523: /* Starting with matrix unity */
1.126 brouard 2524: for (ii=1;ii<=nlstate+ndeath;ii++)
2525: for (j=1;j<=nlstate+ndeath;j++){
2526: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
2527: }
1.169 brouard 2528:
2529: cov[1]=1.;
2530:
2531: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
1.202 brouard 2532: /* Start at agefin= age, computes the matrix of passage and loops decreasing agefin until convergence is reached */
1.126 brouard 2533: for(agefin=age-stepm/YEARM; agefin>=age-delaymax; agefin=agefin-stepm/YEARM){
1.202 brouard 2534: ncvloop++;
1.126 brouard 2535: newm=savm;
2536: /* Covariates have to be included here again */
1.138 brouard 2537: cov[2]=agefin;
1.187 brouard 2538: if(nagesqr==1)
2539: cov[3]= agefin*agefin;;
1.234 brouard 2540: for (k=1; k<=nsd;k++) { /* For single dummy covariates only */
2541: /* Here comes the value of the covariate 'ij' after renumbering k with single dummy covariates */
2542: cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,k)];
1.235 brouard 2543: /* printf("prevalim Dummy combi=%d k=%d TvarsD[%d]=V%d TvarsDind[%d]=%d nbcode=%d cov=%lf codtabm(%d,Tvar[%d])=%d \n",ij,k, k, TvarsD[k],k,TvarsDind[k],nbcode[TvarsD[k]][codtabm(ij,k)],cov[2+nagesqr+TvarsDind[k]], ij, k, codtabm(ij,k)); */
1.234 brouard 2544: }
2545: for (k=1; k<=nsq;k++) { /* For single varying covariates only */
2546: /* Here comes the value of quantitative after renumbering k with single quantitative covariates */
1.235 brouard 2547: cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k];
2548: /* printf("prevalim Quantitative k=%d TvarsQind[%d]=%d, TvarsQ[%d]=V%d,Tqresult[%d][%d]=%f\n",k,k,TvarsQind[k],k,TvarsQ[k],nres,k,Tqresult[nres][k]); */
1.138 brouard 2549: }
1.237 brouard 2550: for (k=1; k<=cptcovage;k++){ /* For product with age */
1.234 brouard 2551: if(Dummy[Tvar[Tage[k]]]){
2552: cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2];
2553: } else{
1.235 brouard 2554: cov[2+nagesqr+Tage[k]]=Tqresult[nres][k];
1.234 brouard 2555: }
1.235 brouard 2556: /* printf("prevalim Age combi=%d k=%d Tage[%d]=V%d Tqresult[%d][%d]=%f\n",ij,k,k,Tage[k],nres,k,Tqresult[nres][k]); */
1.234 brouard 2557: }
1.237 brouard 2558: for (k=1; k<=cptcovprod;k++){ /* For product without age */
1.235 brouard 2559: /* printf("prevalim Prod ij=%d k=%d Tprod[%d]=%d Tvard[%d][1]=V%d, Tvard[%d][2]=V%d\n",ij,k,k,Tprod[k], k,Tvard[k][1], k,Tvard[k][2]); */
1.237 brouard 2560: if(Dummy[Tvard[k][1]==0]){
2561: if(Dummy[Tvard[k][2]==0]){
2562: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)];
2563: }else{
2564: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * Tqresult[nres][k];
2565: }
2566: }else{
2567: if(Dummy[Tvard[k][2]==0]){
2568: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][2]][codtabm(ij,k)] * Tqinvresult[nres][Tvard[k][1]];
2569: }else{
2570: cov[2+nagesqr+Tprod[k]]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]];
2571: }
2572: }
1.234 brouard 2573: }
1.138 brouard 2574: /*printf("ij=%d cptcovprod=%d tvar=%d ", ij, cptcovprod, Tvar[1]);*/
2575: /*printf("ij=%d cov[3]=%lf cov[4]=%lf \n",ij, cov[3],cov[4]);*/
2576: /*printf("ij=%d cov[3]=%lf \n",ij, cov[3]);*/
1.145 brouard 2577: /* savm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
2578: /* out=matprod2(newm, pmij(pmmij,cov,ncovmodel,x,nlstate),1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); /\* Bug Valgrind *\/ */
1.218 brouard 2579: /* age and covariate values of ij are in 'cov' */
1.142 brouard 2580: out=matprod2(newm, pmij(pmmij,cov,ncovmodel,x,nlstate),1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); /* Bug Valgrind */
1.138 brouard 2581:
1.126 brouard 2582: savm=oldm;
2583: oldm=newm;
1.209 brouard 2584:
2585: for(j=1; j<=nlstate; j++){
2586: max[j]=0.;
2587: min[j]=1.;
2588: }
2589: for(i=1;i<=nlstate;i++){
2590: sumnew=0;
2591: for(k=1; k<=ndeath; k++) sumnew+=newm[i][nlstate+k];
2592: for(j=1; j<=nlstate; j++){
2593: prlim[i][j]= newm[i][j]/(1-sumnew);
2594: max[j]=FMAX(max[j],prlim[i][j]);
2595: min[j]=FMIN(min[j],prlim[i][j]);
2596: }
2597: }
2598:
1.126 brouard 2599: maxmax=0.;
1.209 brouard 2600: for(j=1; j<=nlstate; j++){
2601: meandiff[j]=(max[j]-min[j])/(max[j]+min[j])*2.; /* mean difference for each column */
2602: maxmax=FMAX(maxmax,meandiff[j]);
2603: /* printf(" age= %d meandiff[%d]=%f, agefin=%d max[%d]=%f min[%d]=%f maxmax=%f\n", (int)age, j, meandiff[j],(int)agefin, j, max[j], j, min[j],maxmax); */
1.169 brouard 2604: } /* j loop */
1.203 brouard 2605: *ncvyear= (int)age- (int)agefin;
1.208 brouard 2606: /* printf("maxmax=%lf maxmin=%lf ncvloop=%d, age=%d, agefin=%d ncvyear=%d \n", maxmax, maxmin, ncvloop, (int)age, (int)agefin, *ncvyear); */
1.126 brouard 2607: if(maxmax < ftolpl){
1.209 brouard 2608: /* printf("maxmax=%lf ncvloop=%ld, age=%d, agefin=%d ncvyear=%d \n", maxmax, ncvloop, (int)age, (int)agefin, *ncvyear); */
2609: free_vector(min,1,nlstate);
2610: free_vector(max,1,nlstate);
2611: free_vector(meandiff,1,nlstate);
1.126 brouard 2612: return prlim;
2613: }
1.169 brouard 2614: } /* age loop */
1.208 brouard 2615: /* After some age loop it doesn't converge */
1.209 brouard 2616: printf("Warning: the stable prevalence at age %d did not converge with the required precision (%g > ftolpl=%g) within %.0f years. Try to lower 'ftolpl'. \n\
1.208 brouard 2617: Earliest age to start was %d-%d=%d, ncvloop=%d, ncvyear=%d\n", (int)age, maxmax, ftolpl, delaymax, (int)age, (int)delaymax, (int)agefin, ncvloop, *ncvyear);
1.209 brouard 2618: /* Try to lower 'ftol', for example from 1.e-8 to 6.e-9.\n", ftolpl, (int)age, (int)delaymax, (int)agefin, ncvloop, (int)age-(int)agefin); */
2619: free_vector(min,1,nlstate);
2620: free_vector(max,1,nlstate);
2621: free_vector(meandiff,1,nlstate);
1.208 brouard 2622:
1.169 brouard 2623: return prlim; /* should not reach here */
1.126 brouard 2624: }
2625:
1.217 brouard 2626:
2627: /**** Back Prevalence limit (stable or period prevalence) ****************/
2628:
1.218 brouard 2629: /* double **bprevalim(double **bprlim, double ***prevacurrent, int nlstate, double x[], double age, double ageminpar, double agemaxpar, double **oldm, double **savm, double **dnewm, double **doldm, double **dsavm, double ftolpl, int *ncvyear, int ij) */
2630: /* double **bprevalim(double **bprlim, double ***prevacurrent, int nlstate, double x[], double age, double **oldm, double **savm, double **dnewm, double **doldm, double **dsavm, double ftolpl, int *ncvyear, int ij) */
1.242 brouard 2631: double **bprevalim(double **bprlim, double ***prevacurrent, int nlstate, double x[], double age, double ftolpl, int *ncvyear, int ij, int nres)
1.217 brouard 2632: {
1.264 brouard 2633: /* Computes the prevalence limit in each live state at age x and for covariate combination ij (<=2**cptcoveff) by left multiplying the unit
1.217 brouard 2634: matrix by transitions matrix until convergence is reached with precision ftolpl */
2635: /* Wx= Wx-1 Px-1= Wx-2 Px-2 Px-1 = Wx-n Px-n ... Px-2 Px-1 I */
2636: /* Wx is row vector: population in state 1, population in state 2, population dead */
2637: /* or prevalence in state 1, prevalence in state 2, 0 */
2638: /* newm is the matrix after multiplications, its rows are identical at a factor */
2639: /* Initial matrix pimij */
2640: /* {0.85204250825084937, 0.13044499163996345, 0.017512500109187184, */
2641: /* 0.090851990222114765, 0.88271245433047185, 0.026435555447413338, */
2642: /* 0, 0 , 1} */
2643: /*
2644: * and after some iteration: */
2645: /* {0.45504275246439968, 0.42731458730878791, 0.11764266022681241, */
2646: /* 0.45201005341706885, 0.42865420071559901, 0.11933574586733192, */
2647: /* 0, 0 , 1} */
2648: /* And prevalence by suppressing the deaths are close to identical rows in prlim: */
2649: /* {0.51571254859325999, 0.4842874514067399, */
2650: /* 0.51326036147820708, 0.48673963852179264} */
2651: /* If we start from prlim again, prlim tends to a constant matrix */
2652:
2653: int i, ii,j,k;
1.247 brouard 2654: int first=0;
1.217 brouard 2655: double *min, *max, *meandiff, maxmax,sumnew=0.;
2656: /* double **matprod2(); */ /* test */
2657: double **out, cov[NCOVMAX+1], **bmij();
2658: double **newm;
1.218 brouard 2659: double **dnewm, **doldm, **dsavm; /* for use */
2660: double **oldm, **savm; /* for use */
2661:
1.217 brouard 2662: double agefin, delaymax=200. ; /* 100 Max number of years to converge */
2663: int ncvloop=0;
2664:
2665: min=vector(1,nlstate);
2666: max=vector(1,nlstate);
2667: meandiff=vector(1,nlstate);
2668:
1.266 brouard 2669: dnewm=ddnewms; doldm=ddoldms; dsavm=ddsavms;
2670: oldm=oldms; savm=savms;
2671:
2672: /* Starting with matrix unity */
2673: for (ii=1;ii<=nlstate+ndeath;ii++)
2674: for (j=1;j<=nlstate+ndeath;j++){
1.217 brouard 2675: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
2676: }
2677:
2678: cov[1]=1.;
2679:
2680: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
2681: /* Start at agefin= age, computes the matrix of passage and loops decreasing agefin until convergence is reached */
1.218 brouard 2682: /* for(agefin=age+stepm/YEARM; agefin<=age+delaymax; agefin=agefin+stepm/YEARM){ /\* A changer en age *\/ */
2683: for(agefin=age; agefin<AGESUP; agefin=agefin+stepm/YEARM){ /* A changer en age */
1.217 brouard 2684: ncvloop++;
1.218 brouard 2685: newm=savm; /* oldm should be kept from previous iteration or unity at start */
2686: /* newm points to the allocated table savm passed by the function it can be written, savm could be reallocated */
1.217 brouard 2687: /* Covariates have to be included here again */
2688: cov[2]=agefin;
2689: if(nagesqr==1)
2690: cov[3]= agefin*agefin;;
1.242 brouard 2691: for (k=1; k<=nsd;k++) { /* For single dummy covariates only */
2692: /* Here comes the value of the covariate 'ij' after renumbering k with single dummy covariates */
2693: cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,k)];
1.264 brouard 2694: /* printf("bprevalim Dummy agefin=%.0f combi=%d k=%d TvarsD[%d]=V%d TvarsDind[%d]=%d nbcode=%d cov[%d]=%lf codtabm(%d,Tvar[%d])=%d \n",agefin,ij,k, k, TvarsD[k],k,TvarsDind[k],nbcode[TvarsD[k]][codtabm(ij,k)],2+nagesqr+TvarsDind[k],cov[2+nagesqr+TvarsDind[k]], ij, k, codtabm(ij,k)); */
1.242 brouard 2695: }
2696: /* for (k=1; k<=cptcovn;k++) { */
2697: /* /\* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,Tvar[k])]; *\/ */
2698: /* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,k)]; */
2699: /* /\* printf("prevalim ij=%d k=%d Tvar[%d]=%d nbcode=%d cov=%lf codtabm(%d,Tvar[%d])=%d \n",ij,k, k, Tvar[k],nbcode[Tvar[k]][codtabm(ij,Tvar[k])],cov[2+k], ij, k, codtabm(ij,Tvar[k])]); *\/ */
2700: /* } */
2701: for (k=1; k<=nsq;k++) { /* For single varying covariates only */
2702: /* Here comes the value of quantitative after renumbering k with single quantitative covariates */
2703: cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k];
2704: /* printf("prevalim Quantitative k=%d TvarsQind[%d]=%d, TvarsQ[%d]=V%d,Tqresult[%d][%d]=%f\n",k,k,TvarsQind[k],k,TvarsQ[k],nres,k,Tqresult[nres][k]); */
2705: }
2706: /* for (k=1; k<=cptcovage;k++) cov[2+nagesqr+Tage[k]]=nbcode[Tvar[k]][codtabm(ij,k)]*cov[2]; */
2707: /* for (k=1; k<=cptcovprod;k++) /\* Useless *\/ */
2708: /* /\* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])]; *\/ */
2709: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)]; */
2710: for (k=1; k<=cptcovage;k++){ /* For product with age */
2711: if(Dummy[Tvar[Tage[k]]]){
2712: cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2];
2713: } else{
2714: cov[2+nagesqr+Tage[k]]=Tqresult[nres][k];
2715: }
2716: /* printf("prevalim Age combi=%d k=%d Tage[%d]=V%d Tqresult[%d][%d]=%f\n",ij,k,k,Tage[k],nres,k,Tqresult[nres][k]); */
2717: }
2718: for (k=1; k<=cptcovprod;k++){ /* For product without age */
2719: /* printf("prevalim Prod ij=%d k=%d Tprod[%d]=%d Tvard[%d][1]=V%d, Tvard[%d][2]=V%d\n",ij,k,k,Tprod[k], k,Tvard[k][1], k,Tvard[k][2]); */
2720: if(Dummy[Tvard[k][1]==0]){
2721: if(Dummy[Tvard[k][2]==0]){
2722: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)];
2723: }else{
2724: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * Tqresult[nres][k];
2725: }
2726: }else{
2727: if(Dummy[Tvard[k][2]==0]){
2728: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][2]][codtabm(ij,k)] * Tqinvresult[nres][Tvard[k][1]];
2729: }else{
2730: cov[2+nagesqr+Tprod[k]]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]];
2731: }
2732: }
1.217 brouard 2733: }
2734:
2735: /*printf("ij=%d cptcovprod=%d tvar=%d ", ij, cptcovprod, Tvar[1]);*/
2736: /*printf("ij=%d cov[3]=%lf cov[4]=%lf \n",ij, cov[3],cov[4]);*/
2737: /*printf("ij=%d cov[3]=%lf \n",ij, cov[3]);*/
2738: /* savm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
2739: /* out=matprod2(newm, pmij(pmmij,cov,ncovmodel,x,nlstate),1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); /\* Bug Valgrind *\/ */
1.218 brouard 2740: /* ij should be linked to the correct index of cov */
2741: /* age and covariate values ij are in 'cov', but we need to pass
2742: * ij for the observed prevalence at age and status and covariate
2743: * number: prevacurrent[(int)agefin][ii][ij]
2744: */
2745: /* out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, bmij(pmmij,cov,ncovmodel,x,nlstate,prevacurrent, ageminpar, agemaxpar, dnewm, doldm, dsavm,ij)); /\* Bug Valgrind *\/ */
2746: /* out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, bmij(pmmij,cov,ncovmodel,x,nlstate,prevacurrent, dnewm, doldm, dsavm,ij)); /\* Bug Valgrind *\/ */
2747: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, bmij(pmmij,cov,ncovmodel,x,nlstate,prevacurrent,ij)); /* Bug Valgrind */
1.268 ! brouard 2748: /* if((int)age == 86 || (int)age == 87){ */
1.266 brouard 2749: /* printf(" Backward prevalim age=%d agefin=%d \n", (int) age, (int) agefin); */
2750: /* for(i=1; i<=nlstate+ndeath; i++) { */
2751: /* printf("%d newm= ",i); */
2752: /* for(j=1;j<=nlstate+ndeath;j++) { */
2753: /* printf("%f ",newm[i][j]); */
2754: /* } */
2755: /* printf("oldm * "); */
2756: /* for(j=1;j<=nlstate+ndeath;j++) { */
2757: /* printf("%f ",oldm[i][j]); */
2758: /* } */
1.268 ! brouard 2759: /* printf(" bmmij "); */
1.266 brouard 2760: /* for(j=1;j<=nlstate+ndeath;j++) { */
2761: /* printf("%f ",pmmij[i][j]); */
2762: /* } */
2763: /* printf("\n"); */
2764: /* } */
2765: /* } */
1.217 brouard 2766: savm=oldm;
2767: oldm=newm;
1.266 brouard 2768:
1.217 brouard 2769: for(j=1; j<=nlstate; j++){
2770: max[j]=0.;
2771: min[j]=1.;
2772: }
2773: for(j=1; j<=nlstate; j++){
2774: for(i=1;i<=nlstate;i++){
1.234 brouard 2775: /* bprlim[i][j]= newm[i][j]/(1-sumnew); */
2776: bprlim[i][j]= newm[i][j];
2777: max[i]=FMAX(max[i],bprlim[i][j]); /* Max in line */
2778: min[i]=FMIN(min[i],bprlim[i][j]);
1.217 brouard 2779: }
2780: }
1.218 brouard 2781:
1.217 brouard 2782: maxmax=0.;
2783: for(i=1; i<=nlstate; i++){
2784: meandiff[i]=(max[i]-min[i])/(max[i]+min[i])*2.; /* mean difference for each column */
2785: maxmax=FMAX(maxmax,meandiff[i]);
2786: /* printf("Back age= %d meandiff[%d]=%f, agefin=%d max[%d]=%f min[%d]=%f maxmax=%f\n", (int)age, i, meandiff[i],(int)agefin, i, max[i], i, min[i],maxmax); */
1.268 ! brouard 2787: } /* i loop */
1.217 brouard 2788: *ncvyear= -( (int)age- (int)agefin);
1.268 ! brouard 2789: /* printf("Back maxmax=%lf ncvloop=%d, age=%d, agefin=%d ncvyear=%d \n", maxmax, ncvloop, (int)age, (int)agefin, *ncvyear); */
1.217 brouard 2790: if(maxmax < ftolpl){
1.220 brouard 2791: /* printf("OK Back maxmax=%lf ncvloop=%d, age=%d, agefin=%d ncvyear=%d \n", maxmax, ncvloop, (int)age, (int)agefin, *ncvyear); */
1.217 brouard 2792: free_vector(min,1,nlstate);
2793: free_vector(max,1,nlstate);
2794: free_vector(meandiff,1,nlstate);
2795: return bprlim;
2796: }
2797: } /* age loop */
2798: /* After some age loop it doesn't converge */
1.247 brouard 2799: if(first){
2800: first=1;
2801: printf("Warning: the back stable prevalence at age %d did not converge with the required precision (%g > ftolpl=%g) within %.0f years. Try to lower 'ftolpl'. Others in log file only...\n\
2802: Oldest age to start was %d-%d=%d, ncvloop=%d, ncvyear=%d\n", (int)age, maxmax, ftolpl, delaymax, (int)age, (int)delaymax, (int)agefin, ncvloop, *ncvyear);
2803: }
2804: fprintf(ficlog,"Warning: the back stable prevalence at age %d did not converge with the required precision (%g > ftolpl=%g) within %.0f years. Try to lower 'ftolpl'. \n\
1.217 brouard 2805: Oldest age to start was %d-%d=%d, ncvloop=%d, ncvyear=%d\n", (int)age, maxmax, ftolpl, delaymax, (int)age, (int)delaymax, (int)agefin, ncvloop, *ncvyear);
2806: /* Try to lower 'ftol', for example from 1.e-8 to 6.e-9.\n", ftolpl, (int)age, (int)delaymax, (int)agefin, ncvloop, (int)age-(int)agefin); */
2807: free_vector(min,1,nlstate);
2808: free_vector(max,1,nlstate);
2809: free_vector(meandiff,1,nlstate);
2810:
2811: return bprlim; /* should not reach here */
2812: }
2813:
1.126 brouard 2814: /*************** transition probabilities ***************/
2815:
2816: double **pmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate )
2817: {
1.138 brouard 2818: /* According to parameters values stored in x and the covariate's values stored in cov,
1.266 brouard 2819: computes the probability to be observed in state j (after stepm years) being in state i by appying the
1.138 brouard 2820: model to the ncovmodel covariates (including constant and age).
2821: lnpijopii=ln(pij/pii)= aij+bij*age+cij*v1+dij*v2+... = sum_nc=1^ncovmodel xij(nc)*cov[nc]
2822: and, according on how parameters are entered, the position of the coefficient xij(nc) of the
2823: ncth covariate in the global vector x is given by the formula:
2824: j<i nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel
2825: j>=i nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel
2826: Computes ln(pij/pii) (lnpijopii), deduces pij/pii by exponentiation,
2827: sums on j different of i to get 1-pii/pii, deduces pii, and then all pij.
1.266 brouard 2828: Outputs ps[i][j] or probability to be observed in j being in i according to
1.138 brouard 2829: the values of the covariates cov[nc] and corresponding parameter values x[nc+shiftij]
1.266 brouard 2830: Sum on j ps[i][j] should equal to 1.
1.138 brouard 2831: */
2832: double s1, lnpijopii;
1.126 brouard 2833: /*double t34;*/
1.164 brouard 2834: int i,j, nc, ii, jj;
1.126 brouard 2835:
1.223 brouard 2836: for(i=1; i<= nlstate; i++){
2837: for(j=1; j<i;j++){
2838: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
2839: /*lnpijopii += param[i][j][nc]*cov[nc];*/
2840: lnpijopii += x[nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel]*cov[nc];
2841: /* printf("Int j<i s1=%.17e, lnpijopii=%.17e\n",s1,lnpijopii); */
2842: }
2843: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
2844: /* printf("s1=%.17e, lnpijopii=%.17e\n",s1,lnpijopii); */
2845: }
2846: for(j=i+1; j<=nlstate+ndeath;j++){
2847: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
2848: /*lnpijopii += x[(i-1)*nlstate*ncovmodel+(j-2)*ncovmodel+nc+(i-1)*(ndeath-1)*ncovmodel]*cov[nc];*/
2849: lnpijopii += x[nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel]*cov[nc];
2850: /* printf("Int j>i s1=%.17e, lnpijopii=%.17e %lx %lx\n",s1,lnpijopii,s1,lnpijopii); */
2851: }
2852: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
2853: }
2854: }
1.218 brouard 2855:
1.223 brouard 2856: for(i=1; i<= nlstate; i++){
2857: s1=0;
2858: for(j=1; j<i; j++){
2859: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
2860: /*printf("debug1 %d %d ps=%lf exp(ps)=%lf s1+=%lf\n",i,j,ps[i][j],exp(ps[i][j]),s1); */
2861: }
2862: for(j=i+1; j<=nlstate+ndeath; j++){
2863: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
2864: /*printf("debug2 %d %d ps=%lf exp(ps)=%lf s1+=%lf\n",i,j,ps[i][j],exp(ps[i][j]),s1); */
2865: }
2866: /* s1= sum_{j<>i} pij/pii=(1-pii)/pii and thus pii is known from s1 */
2867: ps[i][i]=1./(s1+1.);
2868: /* Computing other pijs */
2869: for(j=1; j<i; j++)
2870: ps[i][j]= exp(ps[i][j])*ps[i][i];
2871: for(j=i+1; j<=nlstate+ndeath; j++)
2872: ps[i][j]= exp(ps[i][j])*ps[i][i];
2873: /* ps[i][nlstate+1]=1.-s1- ps[i][i];*/ /* Sum should be 1 */
2874: } /* end i */
1.218 brouard 2875:
1.223 brouard 2876: for(ii=nlstate+1; ii<= nlstate+ndeath; ii++){
2877: for(jj=1; jj<= nlstate+ndeath; jj++){
2878: ps[ii][jj]=0;
2879: ps[ii][ii]=1;
2880: }
2881: }
1.218 brouard 2882:
2883:
1.223 brouard 2884: /* for(ii=1; ii<= nlstate+ndeath; ii++){ */
2885: /* for(jj=1; jj<= nlstate+ndeath; jj++){ */
2886: /* printf(" pmij ps[%d][%d]=%lf ",ii,jj,ps[ii][jj]); */
2887: /* } */
2888: /* printf("\n "); */
2889: /* } */
2890: /* printf("\n ");printf("%lf ",cov[2]);*/
2891: /*
2892: for(i=1; i<= npar; i++) printf("%f ",x[i]);
1.218 brouard 2893: goto end;*/
1.266 brouard 2894: return ps; /* Pointer is unchanged since its call */
1.126 brouard 2895: }
2896:
1.218 brouard 2897: /*************** backward transition probabilities ***************/
2898:
2899: /* double **bmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate, double ***prevacurrent, double ageminpar, double agemaxpar, double ***dnewm, double **doldm, double **dsavm, int ij ) */
2900: /* double **bmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate, double ***prevacurrent, double ***dnewm, double **doldm, double **dsavm, int ij ) */
2901: double **bmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate, double ***prevacurrent, int ij )
2902: {
1.266 brouard 2903: /* Computes the backward probability at age agefin and covariate combination ij. In fact cov is already filled and x too.
2904: * Call to pmij(cov and x), call to cross prevalence, sums and inverses, left multiply, and returns in **ps as well as **bmij.
1.222 brouard 2905: */
1.218 brouard 2906: int i, ii, j,k;
1.222 brouard 2907:
2908: double **out, **pmij();
2909: double sumnew=0.;
1.218 brouard 2910: double agefin;
1.268 ! brouard 2911: double k3=0.; /* constant of the w_x diagonal matrixe (in order for B to sum to 1 even for death state) */
1.222 brouard 2912: double **dnewm, **dsavm, **doldm;
2913: double **bbmij;
2914:
1.218 brouard 2915: doldm=ddoldms; /* global pointers */
1.222 brouard 2916: dnewm=ddnewms;
2917: dsavm=ddsavms;
2918:
2919: agefin=cov[2];
1.268 ! brouard 2920: /* Bx = Diag(w_x) P_x Diag(Sum_i w^i_x p^ij_x */
1.222 brouard 2921: /* bmij *//* age is cov[2], ij is included in cov, but we need for
1.266 brouard 2922: the observed prevalence (with this covariate ij) at beginning of transition */
2923: /* dsavm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
1.268 ! brouard 2924:
! 2925: /* P_x */
1.266 brouard 2926: pmmij=pmij(pmmij,cov,ncovmodel,x,nlstate); /*This is forward probability from agefin to agefin + stepm */
1.268 ! brouard 2927: /* outputs pmmij which is a stochastic matrix in row */
! 2928:
! 2929: /* Diag(w_x) */
! 2930: /* Problem with prevacurrent which can be zero */
! 2931: sumnew=0.;
! 2932: /* for (ii=1;ii<=nlstate+ndeath;ii++){ */
! 2933: for (ii=1;ii<=nlstate;ii++){ /* Only on live states */
! 2934: sumnew+=prevacurrent[(int)agefin][ii][ij];
! 2935: }
! 2936: if(sumnew >0.01){ /* At least some value in the prevalence */
! 2937: for (ii=1;ii<=nlstate+ndeath;ii++){
! 2938: for (j=1;j<=nlstate+ndeath;j++)
! 2939: doldm[ii][j]=(ii==j ? prevacurrent[(int)agefin][ii][ij]/sumnew : 0.0);
! 2940: }
! 2941: }else{
! 2942: for (ii=1;ii<=nlstate+ndeath;ii++){
! 2943: for (j=1;j<=nlstate+ndeath;j++)
! 2944: doldm[ii][j]=(ii==j ? 1./nlstate : 0.0);
! 2945: }
! 2946: /* if(sumnew <0.9){ */
! 2947: /* printf("Problem internal bmij B: sum on i wi <0.9: j=%d, sum_i wi=%lf,agefin=%d\n",j,sumnew, (int)agefin); */
! 2948: /* } */
! 2949: }
! 2950: k3=0.0; /* We put the last diagonal to 0 */
! 2951: for (ii=nlstate+1;ii<=nlstate+ndeath;ii++){
! 2952: doldm[ii][ii]= k3;
! 2953: }
! 2954: /* End doldm, At the end doldm is diag[(w_i)] */
! 2955:
! 2956: /* left Product of this diag matrix by pmmij=Px (dnewm=dsavm*doldm) */
! 2957: bbmij=matprod2(dnewm, doldm,1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, pmmij); /* Bug Valgrind */
! 2958:
! 2959: /* Diag(Sum_i w^i_x p^ij_x */
! 2960: /* w1 p11 + w2 p21 only on live states N1./N..*N11/N1. + N2./N..*N21/N2.=(N11+N21)/N..=N.1/N.. */
1.222 brouard 2961: for (j=1;j<=nlstate+ndeath;j++){
1.268 ! brouard 2962: sumnew=0.;
1.222 brouard 2963: for (ii=1;ii<=nlstate;ii++){
1.266 brouard 2964: /* sumnew+=dsavm[ii][j]*prevacurrent[(int)agefin][ii][ij]; */
1.268 ! brouard 2965: sumnew+=pmmij[ii][j]*doldm[ii][ii]; /* Yes prevalence at beginning of transition */
1.222 brouard 2966: } /* sumnew is (N11+N21)/N..= N.1/N.. = sum on i of w_i pij */
1.268 ! brouard 2967: for (ii=1;ii<=nlstate+ndeath;ii++){
1.222 brouard 2968: /* if(agefin >= agemaxpar && agefin <= agemaxpar+stepm/YEARM){ */
1.268 ! brouard 2969: /* dsavm[ii][j]=(ii==j ? 1./sumnew : 0.0); */
1.222 brouard 2970: /* }else if(agefin >= agemaxpar+stepm/YEARM){ */
1.268 ! brouard 2971: /* dsavm[ii][j]=(ii==j ? 1./sumnew : 0.0); */
1.222 brouard 2972: /* }else */
1.268 ! brouard 2973: dsavm[ii][j]=(ii==j ? 1./sumnew : 0.0);
! 2974: } /*End ii */
! 2975: } /* End j, At the end dsavm is diag[1/(w_1p1i+w_2 p2i)] for ALL states even if the sum is only for live states */
! 2976:
! 2977: ps=matprod2(ps, dnewm,1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, dsavm); /* Bug Valgrind */
! 2978: /* ps is now diag[w_i] * Px * diag [1/(w_1p1i+w_2 p2i)] */
1.222 brouard 2979: /* end bmij */
1.266 brouard 2980: return ps; /*pointer is unchanged */
1.218 brouard 2981: }
1.217 brouard 2982: /*************** transition probabilities ***************/
2983:
1.218 brouard 2984: double **bpmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate )
1.217 brouard 2985: {
2986: /* According to parameters values stored in x and the covariate's values stored in cov,
2987: computes the probability to be observed in state j being in state i by appying the
2988: model to the ncovmodel covariates (including constant and age).
2989: lnpijopii=ln(pij/pii)= aij+bij*age+cij*v1+dij*v2+... = sum_nc=1^ncovmodel xij(nc)*cov[nc]
2990: and, according on how parameters are entered, the position of the coefficient xij(nc) of the
2991: ncth covariate in the global vector x is given by the formula:
2992: j<i nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel
2993: j>=i nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel
2994: Computes ln(pij/pii) (lnpijopii), deduces pij/pii by exponentiation,
2995: sums on j different of i to get 1-pii/pii, deduces pii, and then all pij.
2996: Outputs ps[i][j] the probability to be observed in j being in j according to
2997: the values of the covariates cov[nc] and corresponding parameter values x[nc+shiftij]
2998: */
2999: double s1, lnpijopii;
3000: /*double t34;*/
3001: int i,j, nc, ii, jj;
3002:
1.234 brouard 3003: for(i=1; i<= nlstate; i++){
3004: for(j=1; j<i;j++){
3005: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
3006: /*lnpijopii += param[i][j][nc]*cov[nc];*/
3007: lnpijopii += x[nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel]*cov[nc];
3008: /* printf("Int j<i s1=%.17e, lnpijopii=%.17e\n",s1,lnpijopii); */
3009: }
3010: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
3011: /* printf("s1=%.17e, lnpijopii=%.17e\n",s1,lnpijopii); */
3012: }
3013: for(j=i+1; j<=nlstate+ndeath;j++){
3014: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
3015: /*lnpijopii += x[(i-1)*nlstate*ncovmodel+(j-2)*ncovmodel+nc+(i-1)*(ndeath-1)*ncovmodel]*cov[nc];*/
3016: lnpijopii += x[nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel]*cov[nc];
3017: /* printf("Int j>i s1=%.17e, lnpijopii=%.17e %lx %lx\n",s1,lnpijopii,s1,lnpijopii); */
3018: }
3019: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
3020: }
3021: }
3022:
3023: for(i=1; i<= nlstate; i++){
3024: s1=0;
3025: for(j=1; j<i; j++){
3026: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
3027: /*printf("debug1 %d %d ps=%lf exp(ps)=%lf s1+=%lf\n",i,j,ps[i][j],exp(ps[i][j]),s1); */
3028: }
3029: for(j=i+1; j<=nlstate+ndeath; j++){
3030: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
3031: /*printf("debug2 %d %d ps=%lf exp(ps)=%lf s1+=%lf\n",i,j,ps[i][j],exp(ps[i][j]),s1); */
3032: }
3033: /* s1= sum_{j<>i} pij/pii=(1-pii)/pii and thus pii is known from s1 */
3034: ps[i][i]=1./(s1+1.);
3035: /* Computing other pijs */
3036: for(j=1; j<i; j++)
3037: ps[i][j]= exp(ps[i][j])*ps[i][i];
3038: for(j=i+1; j<=nlstate+ndeath; j++)
3039: ps[i][j]= exp(ps[i][j])*ps[i][i];
3040: /* ps[i][nlstate+1]=1.-s1- ps[i][i];*/ /* Sum should be 1 */
3041: } /* end i */
3042:
3043: for(ii=nlstate+1; ii<= nlstate+ndeath; ii++){
3044: for(jj=1; jj<= nlstate+ndeath; jj++){
3045: ps[ii][jj]=0;
3046: ps[ii][ii]=1;
3047: }
3048: }
3049: /* Added for backcast */ /* Transposed matrix too */
3050: for(jj=1; jj<= nlstate+ndeath; jj++){
3051: s1=0.;
3052: for(ii=1; ii<= nlstate+ndeath; ii++){
3053: s1+=ps[ii][jj];
3054: }
3055: for(ii=1; ii<= nlstate; ii++){
3056: ps[ii][jj]=ps[ii][jj]/s1;
3057: }
3058: }
3059: /* Transposition */
3060: for(jj=1; jj<= nlstate+ndeath; jj++){
3061: for(ii=jj; ii<= nlstate+ndeath; ii++){
3062: s1=ps[ii][jj];
3063: ps[ii][jj]=ps[jj][ii];
3064: ps[jj][ii]=s1;
3065: }
3066: }
3067: /* for(ii=1; ii<= nlstate+ndeath; ii++){ */
3068: /* for(jj=1; jj<= nlstate+ndeath; jj++){ */
3069: /* printf(" pmij ps[%d][%d]=%lf ",ii,jj,ps[ii][jj]); */
3070: /* } */
3071: /* printf("\n "); */
3072: /* } */
3073: /* printf("\n ");printf("%lf ",cov[2]);*/
3074: /*
3075: for(i=1; i<= npar; i++) printf("%f ",x[i]);
3076: goto end;*/
3077: return ps;
1.217 brouard 3078: }
3079:
3080:
1.126 brouard 3081: /**************** Product of 2 matrices ******************/
3082:
1.145 brouard 3083: double **matprod2(double **out, double **in,int nrl, int nrh, int ncl, int nch, int ncolol, int ncoloh, double **b)
1.126 brouard 3084: {
3085: /* Computes the matrix product of in(1,nrh-nrl+1)(1,nch-ncl+1) times
3086: b(1,nch-ncl+1)(1,ncoloh-ncolol+1) into out(...) */
3087: /* in, b, out are matrice of pointers which should have been initialized
3088: before: only the contents of out is modified. The function returns
3089: a pointer to pointers identical to out */
1.145 brouard 3090: int i, j, k;
1.126 brouard 3091: for(i=nrl; i<= nrh; i++)
1.145 brouard 3092: for(k=ncolol; k<=ncoloh; k++){
3093: out[i][k]=0.;
3094: for(j=ncl; j<=nch; j++)
3095: out[i][k] +=in[i][j]*b[j][k];
3096: }
1.126 brouard 3097: return out;
3098: }
3099:
3100:
3101: /************* Higher Matrix Product ***************/
3102:
1.235 brouard 3103: 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 3104: {
1.218 brouard 3105: /* Computes the transition matrix starting at age 'age' and combination of covariate values corresponding to ij over
1.126 brouard 3106: 'nhstepm*hstepm*stepm' months (i.e. until
3107: age (in years) age+nhstepm*hstepm*stepm/12) by multiplying
3108: nhstepm*hstepm matrices.
3109: Output is stored in matrix po[i][j][h] for h every 'hstepm' step
3110: (typically every 2 years instead of every month which is too big
3111: for the memory).
3112: Model is determined by parameters x and covariates have to be
3113: included manually here.
3114:
3115: */
3116:
3117: int i, j, d, h, k;
1.131 brouard 3118: double **out, cov[NCOVMAX+1];
1.126 brouard 3119: double **newm;
1.187 brouard 3120: double agexact;
1.214 brouard 3121: double agebegin, ageend;
1.126 brouard 3122:
3123: /* Hstepm could be zero and should return the unit matrix */
3124: for (i=1;i<=nlstate+ndeath;i++)
3125: for (j=1;j<=nlstate+ndeath;j++){
3126: oldm[i][j]=(i==j ? 1.0 : 0.0);
3127: po[i][j][0]=(i==j ? 1.0 : 0.0);
3128: }
3129: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
3130: for(h=1; h <=nhstepm; h++){
3131: for(d=1; d <=hstepm; d++){
3132: newm=savm;
3133: /* Covariates have to be included here again */
3134: cov[1]=1.;
1.214 brouard 3135: agexact=age+((h-1)*hstepm + (d-1))*stepm/YEARM; /* age just before transition */
1.187 brouard 3136: cov[2]=agexact;
3137: if(nagesqr==1)
1.227 brouard 3138: cov[3]= agexact*agexact;
1.235 brouard 3139: for (k=1; k<=nsd;k++) { /* For single dummy covariates only */
3140: /* Here comes the value of the covariate 'ij' after renumbering k with single dummy covariates */
3141: cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,k)];
3142: /* 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)); */
3143: }
3144: for (k=1; k<=nsq;k++) { /* For single varying covariates only */
3145: /* Here comes the value of quantitative after renumbering k with single quantitative covariates */
3146: cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k];
3147: /* 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]); */
3148: }
3149: for (k=1; k<=cptcovage;k++){
3150: if(Dummy[Tvar[Tage[k]]]){
3151: cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2];
3152: } else{
3153: cov[2+nagesqr+Tage[k]]=Tqresult[nres][k];
3154: }
3155: /* 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]); */
3156: }
3157: for (k=1; k<=cptcovprod;k++){ /* */
3158: /* 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]); */
3159: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)];
3160: }
3161: /* for (k=1; k<=cptcovn;k++) */
3162: /* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,k)]; */
3163: /* for (k=1; k<=cptcovage;k++) /\* Should start at cptcovn+1 *\/ */
3164: /* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2]; */
3165: /* for (k=1; k<=cptcovprod;k++) /\* Useless because included in cptcovn *\/ */
3166: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)]*nbcode[Tvard[k][2]][codtabm(ij,k)]; */
1.227 brouard 3167:
3168:
1.126 brouard 3169: /*printf("hxi cptcov=%d cptcode=%d\n",cptcov,cptcode);*/
3170: /*printf("h=%d d=%d age=%f cov=%f\n",h,d,age,cov[2]);*/
1.218 brouard 3171: /* right multiplication of oldm by the current matrix */
1.126 brouard 3172: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath,
3173: pmij(pmmij,cov,ncovmodel,x,nlstate));
1.217 brouard 3174: /* if((int)age == 70){ */
3175: /* printf(" Forward hpxij age=%d agexact=%f d=%d nhstepm=%d hstepm=%d\n", (int) age, agexact, d, nhstepm, hstepm); */
3176: /* for(i=1; i<=nlstate+ndeath; i++) { */
3177: /* printf("%d pmmij ",i); */
3178: /* for(j=1;j<=nlstate+ndeath;j++) { */
3179: /* printf("%f ",pmmij[i][j]); */
3180: /* } */
3181: /* printf(" oldm "); */
3182: /* for(j=1;j<=nlstate+ndeath;j++) { */
3183: /* printf("%f ",oldm[i][j]); */
3184: /* } */
3185: /* printf("\n"); */
3186: /* } */
3187: /* } */
1.126 brouard 3188: savm=oldm;
3189: oldm=newm;
3190: }
3191: for(i=1; i<=nlstate+ndeath; i++)
3192: for(j=1;j<=nlstate+ndeath;j++) {
1.267 brouard 3193: po[i][j][h]=newm[i][j];
3194: /*if(h==nhstepm) printf("po[%d][%d][%d]=%f ",i,j,h,po[i][j][h]);*/
1.126 brouard 3195: }
1.128 brouard 3196: /*printf("h=%d ",h);*/
1.126 brouard 3197: } /* end h */
1.267 brouard 3198: /* printf("\n H=%d \n",h); */
1.126 brouard 3199: return po;
3200: }
3201:
1.217 brouard 3202: /************* Higher Back Matrix Product ***************/
1.218 brouard 3203: /* double ***hbxij(double ***po, int nhstepm, double age, int hstepm, double *x, double ***prevacurrent, int nlstate, int stepm, double **oldm, double **savm, double **dnewm, double **doldm, double **dsavm, int ij ) */
1.267 brouard 3204: double ***hbxij(double ***po, int nhstepm, double age, int hstepm, double *x, double ***prevacurrent, int nlstate, int stepm, int ij, int nres )
1.217 brouard 3205: {
1.266 brouard 3206: /* For a combination of dummy covariate ij, computes the transition matrix starting at age 'age' over
1.217 brouard 3207: 'nhstepm*hstepm*stepm' months (i.e. until
1.218 brouard 3208: age (in years) age+nhstepm*hstepm*stepm/12) by multiplying
3209: nhstepm*hstepm matrices.
3210: Output is stored in matrix po[i][j][h] for h every 'hstepm' step
3211: (typically every 2 years instead of every month which is too big
1.217 brouard 3212: for the memory).
1.218 brouard 3213: Model is determined by parameters x and covariates have to be
1.266 brouard 3214: included manually here. Then we use a call to bmij(x and cov)
3215: The addresss of po (p3mat allocated to the dimension of nhstepm) should be stored for output
1.222 brouard 3216: */
1.217 brouard 3217:
3218: int i, j, d, h, k;
1.266 brouard 3219: double **out, cov[NCOVMAX+1], **bmij();
3220: double **newm, ***newmm;
1.217 brouard 3221: double agexact;
3222: double agebegin, ageend;
1.222 brouard 3223: double **oldm, **savm;
1.217 brouard 3224:
1.266 brouard 3225: newmm=po; /* To be saved */
3226: oldm=oldms;savm=savms; /* Global pointers */
1.217 brouard 3227: /* Hstepm could be zero and should return the unit matrix */
3228: for (i=1;i<=nlstate+ndeath;i++)
3229: for (j=1;j<=nlstate+ndeath;j++){
3230: oldm[i][j]=(i==j ? 1.0 : 0.0);
3231: po[i][j][0]=(i==j ? 1.0 : 0.0);
3232: }
3233: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
3234: for(h=1; h <=nhstepm; h++){
3235: for(d=1; d <=hstepm; d++){
3236: newm=savm;
3237: /* Covariates have to be included here again */
3238: cov[1]=1.;
1.266 brouard 3239: agexact=age-((h-1)*hstepm + (d))*stepm/YEARM; /* age just before transition, d or d-1? */
1.217 brouard 3240: /* agexact=age+((h-1)*hstepm + (d-1))*stepm/YEARM; /\* age just before transition *\/ */
3241: cov[2]=agexact;
3242: if(nagesqr==1)
1.222 brouard 3243: cov[3]= agexact*agexact;
1.266 brouard 3244: for (k=1; k<=cptcovn;k++){
3245: /* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,k)]; */
3246: /* /\* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,Tvar[k])]; *\/ */
3247: cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,k)];
3248: /* printf("hbxij Dummy agexact=%.0f combi=%d k=%d TvarsD[%d]=V%d TvarsDind[%d]=%d nbcode=%d cov[%d]=%lf codtabm(%d,Tvar[%d])=%d \n",agexact,ij,k, k, TvarsD[k],k,TvarsDind[k],nbcode[TvarsD[k]][codtabm(ij,k)],2+nagesqr+TvarsDind[k],cov[2+nagesqr+TvarsDind[k]], ij, k, codtabm(ij,k)); */
3249: }
1.267 brouard 3250: for (k=1; k<=nsq;k++) { /* For single varying covariates only */
3251: /* Here comes the value of quantitative after renumbering k with single quantitative covariates */
3252: cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k];
3253: /* 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]); */
3254: }
3255: for (k=1; k<=cptcovage;k++){ /* Should start at cptcovn+1 */
3256: if(Dummy[Tvar[Tage[k]]]){
3257: cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2];
3258: } else{
3259: cov[2+nagesqr+Tage[k]]=Tqresult[nres][k];
3260: }
3261: /* printf("hBxij Age combi=%d k=%d Tage[%d]=V%d Tqresult[%d][%d]=%f\n",ij,k,k,Tage[k],nres,k,Tqresult[nres][k]); */
3262: }
3263: for (k=1; k<=cptcovprod;k++){ /* Useless because included in cptcovn */
1.222 brouard 3264: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)]*nbcode[Tvard[k][2]][codtabm(ij,k)];
1.267 brouard 3265: }
1.217 brouard 3266: /*printf("hxi cptcov=%d cptcode=%d\n",cptcov,cptcode);*/
3267: /*printf("h=%d d=%d age=%f cov=%f\n",h,d,age,cov[2]);*/
1.267 brouard 3268:
1.218 brouard 3269: /* Careful transposed matrix */
1.266 brouard 3270: /* age is in cov[2], prevacurrent at beginning of transition. */
1.218 brouard 3271: /* out=matprod2(newm, bmij(pmmij,cov,ncovmodel,x,nlstate,prevacurrent, dnewm, doldm, dsavm,ij),\ */
1.222 brouard 3272: /* 1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); */
1.218 brouard 3273: out=matprod2(newm, bmij(pmmij,cov,ncovmodel,x,nlstate,prevacurrent,ij),\
1.222 brouard 3274: 1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm);
1.217 brouard 3275: /* if((int)age == 70){ */
3276: /* printf(" Backward hbxij age=%d agexact=%f d=%d nhstepm=%d hstepm=%d\n", (int) age, agexact, d, nhstepm, hstepm); */
3277: /* for(i=1; i<=nlstate+ndeath; i++) { */
3278: /* printf("%d pmmij ",i); */
3279: /* for(j=1;j<=nlstate+ndeath;j++) { */
3280: /* printf("%f ",pmmij[i][j]); */
3281: /* } */
3282: /* printf(" oldm "); */
3283: /* for(j=1;j<=nlstate+ndeath;j++) { */
3284: /* printf("%f ",oldm[i][j]); */
3285: /* } */
3286: /* printf("\n"); */
3287: /* } */
3288: /* } */
3289: savm=oldm;
3290: oldm=newm;
3291: }
3292: for(i=1; i<=nlstate+ndeath; i++)
3293: for(j=1;j<=nlstate+ndeath;j++) {
1.222 brouard 3294: po[i][j][h]=newm[i][j];
1.268 ! brouard 3295: /* if(h==nhstepm) */
! 3296: /* printf("po[%d][%d][%d]=%f ",i,j,h,po[i][j][h]); */
1.217 brouard 3297: }
1.268 ! brouard 3298: /* printf("h=%d %.1f ",h, agexact); */
1.217 brouard 3299: } /* end h */
1.268 ! brouard 3300: /* printf("\n H=%d nhs=%d \n",h, nhstepm); */
1.217 brouard 3301: return po;
3302: }
3303:
3304:
1.162 brouard 3305: #ifdef NLOPT
3306: double myfunc(unsigned n, const double *p1, double *grad, void *pd){
3307: double fret;
3308: double *xt;
3309: int j;
3310: myfunc_data *d2 = (myfunc_data *) pd;
3311: /* xt = (p1-1); */
3312: xt=vector(1,n);
3313: for (j=1;j<=n;j++) xt[j]=p1[j-1]; /* xt[1]=p1[0] */
3314:
3315: fret=(d2->function)(xt); /* p xt[1]@8 is fine */
3316: /* fret=(*func)(xt); /\* p xt[1]@8 is fine *\/ */
3317: printf("Function = %.12lf ",fret);
3318: for (j=1;j<=n;j++) printf(" %d %.8lf", j, xt[j]);
3319: printf("\n");
3320: free_vector(xt,1,n);
3321: return fret;
3322: }
3323: #endif
1.126 brouard 3324:
3325: /*************** log-likelihood *************/
3326: double func( double *x)
3327: {
1.226 brouard 3328: int i, ii, j, k, mi, d, kk;
3329: int ioffset=0;
3330: double l, ll[NLSTATEMAX+1], cov[NCOVMAX+1];
3331: double **out;
3332: double lli; /* Individual log likelihood */
3333: int s1, s2;
1.228 brouard 3334: 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 3335: double bbh, survp;
3336: long ipmx;
3337: double agexact;
3338: /*extern weight */
3339: /* We are differentiating ll according to initial status */
3340: /* for (i=1;i<=npar;i++) printf("%f ", x[i]);*/
3341: /*for(i=1;i<imx;i++)
3342: printf(" %d\n",s[4][i]);
3343: */
1.162 brouard 3344:
1.226 brouard 3345: ++countcallfunc;
1.162 brouard 3346:
1.226 brouard 3347: cov[1]=1.;
1.126 brouard 3348:
1.226 brouard 3349: for(k=1; k<=nlstate; k++) ll[k]=0.;
1.224 brouard 3350: ioffset=0;
1.226 brouard 3351: if(mle==1){
3352: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
3353: /* Computes the values of the ncovmodel covariates of the model
3354: depending if the covariates are fixed or varying (age dependent) and stores them in cov[]
3355: Then computes with function pmij which return a matrix p[i][j] giving the elementary probability
3356: to be observed in j being in i according to the model.
3357: */
1.243 brouard 3358: ioffset=2+nagesqr ;
1.233 brouard 3359: /* Fixed */
1.234 brouard 3360: for (k=1; k<=ncovf;k++){ /* Simple and product fixed covariates without age* products */
3361: 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)*/
3362: }
1.226 brouard 3363: /* In model V2+V1*V4+age*V3+V3*V2 Tvar[1] is V2, Tvar[2=V1*V4]
3364: is 6, Tvar[3=age*V3] should not be computed because of age Tvar[4=V3*V2]
3365: has been calculated etc */
3366: /* For an individual i, wav[i] gives the number of effective waves */
3367: /* We compute the contribution to Likelihood of each effective transition
3368: mw[mi][i] is real wave of the mi th effectve wave */
3369: /* Then statuses are computed at each begin and end of an effective wave s1=s[ mw[mi][i] ][i];
3370: s2=s[mw[mi+1][i]][i];
3371: And the iv th varying covariate is the cotvar[mw[mi+1][i]][iv][i]
3372: But if the variable is not in the model TTvar[iv] is the real variable effective in the model:
3373: meaning that decodemodel should be used cotvar[mw[mi+1][i]][TTvar[iv]][i]
3374: */
3375: for(mi=1; mi<= wav[i]-1; mi++){
1.234 brouard 3376: for(k=1; k <= ncovv ; k++){ /* Varying covariates (single and product but no age )*/
1.242 brouard 3377: /* cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]][i]; */
3378: cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]-ncovcol-nqv][i];
1.234 brouard 3379: }
3380: for (ii=1;ii<=nlstate+ndeath;ii++)
3381: for (j=1;j<=nlstate+ndeath;j++){
3382: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
3383: savm[ii][j]=(ii==j ? 1.0 : 0.0);
3384: }
3385: for(d=0; d<dh[mi][i]; d++){
3386: newm=savm;
3387: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
3388: cov[2]=agexact;
3389: if(nagesqr==1)
3390: cov[3]= agexact*agexact; /* Should be changed here */
3391: for (kk=1; kk<=cptcovage;kk++) {
1.242 brouard 3392: if(!FixedV[Tvar[Tage[kk]]])
1.234 brouard 3393: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact; /* Tage[kk] gives the data-covariate associated with age */
1.242 brouard 3394: else
3395: cov[Tage[kk]+2+nagesqr]=cotvar[mw[mi][i]][Tvar[Tage[kk]]-ncovcol-nqv][i]*agexact;
1.234 brouard 3396: }
3397: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
3398: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
3399: savm=oldm;
3400: oldm=newm;
3401: } /* end mult */
3402:
3403: /*lli=log(out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]);*/ /* Original formula */
3404: /* But now since version 0.9 we anticipate for bias at large stepm.
3405: * If stepm is larger than one month (smallest stepm) and if the exact delay
3406: * (in months) between two waves is not a multiple of stepm, we rounded to
3407: * the nearest (and in case of equal distance, to the lowest) interval but now
3408: * we keep into memory the bias bh[mi][i] and also the previous matrix product
3409: * (i.e to dh[mi][i]-1) saved in 'savm'. Then we inter(extra)polate the
3410: * probability in order to take into account the bias as a fraction of the way
1.231 brouard 3411: * from savm to out if bh is negative or even beyond if bh is positive. bh varies
3412: * -stepm/2 to stepm/2 .
3413: * For stepm=1 the results are the same as for previous versions of Imach.
3414: * For stepm > 1 the results are less biased than in previous versions.
3415: */
1.234 brouard 3416: s1=s[mw[mi][i]][i];
3417: s2=s[mw[mi+1][i]][i];
3418: bbh=(double)bh[mi][i]/(double)stepm;
3419: /* bias bh is positive if real duration
3420: * is higher than the multiple of stepm and negative otherwise.
3421: */
3422: /* lli= (savm[s1][s2]>1.e-8 ?(1.+bbh)*log(out[s1][s2])- bbh*log(savm[s1][s2]):log((1.+bbh)*out[s1][s2]));*/
3423: if( s2 > nlstate){
3424: /* i.e. if s2 is a death state and if the date of death is known
3425: then the contribution to the likelihood is the probability to
3426: die between last step unit time and current step unit time,
3427: which is also equal to probability to die before dh
3428: minus probability to die before dh-stepm .
3429: In version up to 0.92 likelihood was computed
3430: as if date of death was unknown. Death was treated as any other
3431: health state: the date of the interview describes the actual state
3432: and not the date of a change in health state. The former idea was
3433: to consider that at each interview the state was recorded
3434: (healthy, disable or death) and IMaCh was corrected; but when we
3435: introduced the exact date of death then we should have modified
3436: the contribution of an exact death to the likelihood. This new
3437: contribution is smaller and very dependent of the step unit
3438: stepm. It is no more the probability to die between last interview
3439: and month of death but the probability to survive from last
3440: interview up to one month before death multiplied by the
3441: probability to die within a month. Thanks to Chris
3442: Jackson for correcting this bug. Former versions increased
3443: mortality artificially. The bad side is that we add another loop
3444: which slows down the processing. The difference can be up to 10%
3445: lower mortality.
3446: */
3447: /* If, at the beginning of the maximization mostly, the
3448: cumulative probability or probability to be dead is
3449: constant (ie = 1) over time d, the difference is equal to
3450: 0. out[s1][3] = savm[s1][3]: probability, being at state
3451: s1 at precedent wave, to be dead a month before current
3452: wave is equal to probability, being at state s1 at
3453: precedent wave, to be dead at mont of the current
3454: wave. Then the observed probability (that this person died)
3455: is null according to current estimated parameter. In fact,
3456: it should be very low but not zero otherwise the log go to
3457: infinity.
3458: */
1.183 brouard 3459: /* #ifdef INFINITYORIGINAL */
3460: /* lli=log(out[s1][s2] - savm[s1][s2]); */
3461: /* #else */
3462: /* if ((out[s1][s2] - savm[s1][s2]) < mytinydouble) */
3463: /* lli=log(mytinydouble); */
3464: /* else */
3465: /* lli=log(out[s1][s2] - savm[s1][s2]); */
3466: /* #endif */
1.226 brouard 3467: lli=log(out[s1][s2] - savm[s1][s2]);
1.216 brouard 3468:
1.226 brouard 3469: } else if ( s2==-1 ) { /* alive */
3470: for (j=1,survp=0. ; j<=nlstate; j++)
3471: survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j];
3472: /*survp += out[s1][j]; */
3473: lli= log(survp);
3474: }
3475: else if (s2==-4) {
3476: for (j=3,survp=0. ; j<=nlstate; j++)
3477: survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j];
3478: lli= log(survp);
3479: }
3480: else if (s2==-5) {
3481: for (j=1,survp=0. ; j<=2; j++)
3482: survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j];
3483: lli= log(survp);
3484: }
3485: else{
3486: lli= log((1.+bbh)*out[s1][s2]- bbh*savm[s1][s2]); /* linear interpolation */
3487: /* 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 */
3488: }
3489: /*lli=(1.+bbh)*log(out[s1][s2])- bbh*log(savm[s1][s2]);*/
3490: /*if(lli ==000.0)*/
3491: /*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); */
3492: ipmx +=1;
3493: sw += weight[i];
3494: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
3495: /* if (lli < log(mytinydouble)){ */
3496: /* 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); */
3497: /* 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]); */
3498: /* } */
3499: } /* end of wave */
3500: } /* end of individual */
3501: } else if(mle==2){
3502: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
3503: for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i];
3504: for(mi=1; mi<= wav[i]-1; mi++){
3505: for (ii=1;ii<=nlstate+ndeath;ii++)
3506: for (j=1;j<=nlstate+ndeath;j++){
3507: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
3508: savm[ii][j]=(ii==j ? 1.0 : 0.0);
3509: }
3510: for(d=0; d<=dh[mi][i]; d++){
3511: newm=savm;
3512: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
3513: cov[2]=agexact;
3514: if(nagesqr==1)
3515: cov[3]= agexact*agexact;
3516: for (kk=1; kk<=cptcovage;kk++) {
3517: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
3518: }
3519: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
3520: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
3521: savm=oldm;
3522: oldm=newm;
3523: } /* end mult */
3524:
3525: s1=s[mw[mi][i]][i];
3526: s2=s[mw[mi+1][i]][i];
3527: bbh=(double)bh[mi][i]/(double)stepm;
3528: 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 */
3529: ipmx +=1;
3530: sw += weight[i];
3531: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
3532: } /* end of wave */
3533: } /* end of individual */
3534: } else if(mle==3){ /* exponential inter-extrapolation */
3535: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
3536: for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i];
3537: for(mi=1; mi<= wav[i]-1; mi++){
3538: for (ii=1;ii<=nlstate+ndeath;ii++)
3539: for (j=1;j<=nlstate+ndeath;j++){
3540: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
3541: savm[ii][j]=(ii==j ? 1.0 : 0.0);
3542: }
3543: for(d=0; d<dh[mi][i]; d++){
3544: newm=savm;
3545: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
3546: cov[2]=agexact;
3547: if(nagesqr==1)
3548: cov[3]= agexact*agexact;
3549: for (kk=1; kk<=cptcovage;kk++) {
3550: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
3551: }
3552: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
3553: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
3554: savm=oldm;
3555: oldm=newm;
3556: } /* end mult */
3557:
3558: s1=s[mw[mi][i]][i];
3559: s2=s[mw[mi+1][i]][i];
3560: bbh=(double)bh[mi][i]/(double)stepm;
3561: 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 */
3562: ipmx +=1;
3563: sw += weight[i];
3564: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
3565: } /* end of wave */
3566: } /* end of individual */
3567: }else if (mle==4){ /* ml=4 no inter-extrapolation */
3568: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
3569: for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i];
3570: for(mi=1; mi<= wav[i]-1; mi++){
3571: for (ii=1;ii<=nlstate+ndeath;ii++)
3572: for (j=1;j<=nlstate+ndeath;j++){
3573: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
3574: savm[ii][j]=(ii==j ? 1.0 : 0.0);
3575: }
3576: for(d=0; d<dh[mi][i]; d++){
3577: newm=savm;
3578: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
3579: cov[2]=agexact;
3580: if(nagesqr==1)
3581: cov[3]= agexact*agexact;
3582: for (kk=1; kk<=cptcovage;kk++) {
3583: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
3584: }
1.126 brouard 3585:
1.226 brouard 3586: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
3587: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
3588: savm=oldm;
3589: oldm=newm;
3590: } /* end mult */
3591:
3592: s1=s[mw[mi][i]][i];
3593: s2=s[mw[mi+1][i]][i];
3594: if( s2 > nlstate){
3595: lli=log(out[s1][s2] - savm[s1][s2]);
3596: } else if ( s2==-1 ) { /* alive */
3597: for (j=1,survp=0. ; j<=nlstate; j++)
3598: survp += out[s1][j];
3599: lli= log(survp);
3600: }else{
3601: lli=log(out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]); /* Original formula */
3602: }
3603: ipmx +=1;
3604: sw += weight[i];
3605: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
1.126 brouard 3606: /* 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 3607: } /* end of wave */
3608: } /* end of individual */
3609: }else{ /* ml=5 no inter-extrapolation no jackson =0.8a */
3610: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
3611: for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i];
3612: for(mi=1; mi<= wav[i]-1; mi++){
3613: for (ii=1;ii<=nlstate+ndeath;ii++)
3614: for (j=1;j<=nlstate+ndeath;j++){
3615: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
3616: savm[ii][j]=(ii==j ? 1.0 : 0.0);
3617: }
3618: for(d=0; d<dh[mi][i]; d++){
3619: newm=savm;
3620: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
3621: cov[2]=agexact;
3622: if(nagesqr==1)
3623: cov[3]= agexact*agexact;
3624: for (kk=1; kk<=cptcovage;kk++) {
3625: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
3626: }
1.126 brouard 3627:
1.226 brouard 3628: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
3629: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
3630: savm=oldm;
3631: oldm=newm;
3632: } /* end mult */
3633:
3634: s1=s[mw[mi][i]][i];
3635: s2=s[mw[mi+1][i]][i];
3636: lli=log(out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]); /* Original formula */
3637: ipmx +=1;
3638: sw += weight[i];
3639: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
3640: /*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]);*/
3641: } /* end of wave */
3642: } /* end of individual */
3643: } /* End of if */
3644: for(k=1,l=0.; k<=nlstate; k++) l += ll[k];
3645: /* printf("l1=%f l2=%f ",ll[1],ll[2]); */
3646: l= l*ipmx/sw; /* To get the same order of magnitude as if weight=1 for every body */
3647: return -l;
1.126 brouard 3648: }
3649:
3650: /*************** log-likelihood *************/
3651: double funcone( double *x)
3652: {
1.228 brouard 3653: /* Same as func but slower because of a lot of printf and if */
1.126 brouard 3654: int i, ii, j, k, mi, d, kk;
1.228 brouard 3655: int ioffset=0;
1.131 brouard 3656: double l, ll[NLSTATEMAX+1], cov[NCOVMAX+1];
1.126 brouard 3657: double **out;
3658: double lli; /* Individual log likelihood */
3659: double llt;
3660: int s1, s2;
1.228 brouard 3661: int iv=0, iqv=0, itv=0, iqtv=0 ; /* Index of varying covariate, fixed quantitative cov, time varying covariate, quantitative time varying covariate */
3662:
1.126 brouard 3663: double bbh, survp;
1.187 brouard 3664: double agexact;
1.214 brouard 3665: double agebegin, ageend;
1.126 brouard 3666: /*extern weight */
3667: /* We are differentiating ll according to initial status */
3668: /* for (i=1;i<=npar;i++) printf("%f ", x[i]);*/
3669: /*for(i=1;i<imx;i++)
3670: printf(" %d\n",s[4][i]);
3671: */
3672: cov[1]=1.;
3673:
3674: for(k=1; k<=nlstate; k++) ll[k]=0.;
1.224 brouard 3675: ioffset=0;
3676: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
1.243 brouard 3677: /* ioffset=2+nagesqr+cptcovage; */
3678: ioffset=2+nagesqr;
1.232 brouard 3679: /* Fixed */
1.224 brouard 3680: /* for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i]; */
1.232 brouard 3681: /* for (k=1; k<=ncoveff;k++){ /\* Simple and product fixed Dummy covariates without age* products *\/ */
3682: for (k=1; k<=ncovf;k++){ /* Simple and product fixed covariates without age* products */
3683: 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)*/
3684: /* cov[ioffset+TvarFind[1]]=covar[Tvar[TvarFind[1]]][i]; */
3685: /* cov[2+6]=covar[Tvar[6]][i]; */
3686: /* cov[2+6]=covar[2][i]; V2 */
3687: /* cov[TvarFind[2]]=covar[Tvar[TvarFind[2]]][i]; */
3688: /* cov[2+7]=covar[Tvar[7]][i]; */
3689: /* cov[2+7]=covar[7][i]; V7=V1*V2 */
3690: /* cov[TvarFind[3]]=covar[Tvar[TvarFind[3]]][i]; */
3691: /* cov[2+9]=covar[Tvar[9]][i]; */
3692: /* cov[2+9]=covar[1][i]; V1 */
1.225 brouard 3693: }
1.232 brouard 3694: /* for (k=1; k<=nqfveff;k++){ /\* Simple and product fixed Quantitative covariates without age* products *\/ */
3695: /* 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?)*\/ */
3696: /* } */
1.231 brouard 3697: /* for(iqv=1; iqv <= nqfveff; iqv++){ /\* Quantitative fixed covariates *\/ */
3698: /* cov[++ioffset]=coqvar[Tvar[iqv]][i]; /\* Only V2 k=6 and V1*V2 7 *\/ */
3699: /* } */
1.225 brouard 3700:
1.233 brouard 3701:
3702: for(mi=1; mi<= wav[i]-1; mi++){ /* Varying with waves */
1.232 brouard 3703: /* Wave varying (but not age varying) */
3704: for(k=1; k <= ncovv ; k++){ /* Varying covariates (single and product but no age )*/
1.242 brouard 3705: /* cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]][i]; */
3706: cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]-ncovcol-nqv][i];
3707: }
1.232 brouard 3708: /* for(itv=1; itv <= ntveff; itv++){ /\* Varying dummy covariates (single??)*\/ */
1.242 brouard 3709: /* iv= Tvar[Tmodelind[ioffset-2-nagesqr-cptcovage+itv]]-ncovcol-nqv; /\* Counting the # varying covariate from 1 to ntveff *\/ */
3710: /* cov[ioffset+iv]=cotvar[mw[mi][i]][iv][i]; */
3711: /* k=ioffset-2-nagesqr-cptcovage+itv; /\* position in simple model *\/ */
3712: /* cov[ioffset+itv]=cotvar[mw[mi][i]][TmodelInvind[itv]][i]; */
3713: /* 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 3714: /* for(iqtv=1; iqtv <= nqtveff; iqtv++){ /\* Varying quantitatives covariates *\/ */
1.242 brouard 3715: /* iv=TmodelInvQind[iqtv]; /\* Counting the # varying covariate from 1 to ntveff *\/ */
3716: /* /\* 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]); *\/ */
3717: /* cov[ioffset+ntveff+iqtv]=cotqvar[mw[mi][i]][TmodelInvQind[iqtv]][i]; */
1.232 brouard 3718: /* } */
1.126 brouard 3719: for (ii=1;ii<=nlstate+ndeath;ii++)
1.242 brouard 3720: for (j=1;j<=nlstate+ndeath;j++){
3721: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
3722: savm[ii][j]=(ii==j ? 1.0 : 0.0);
3723: }
1.214 brouard 3724:
3725: agebegin=agev[mw[mi][i]][i]; /* Age at beginning of effective wave */
3726: ageend=agev[mw[mi][i]][i] + (dh[mi][i])*stepm/YEARM; /* Age at end of effective wave and at the end of transition */
3727: for(d=0; d<dh[mi][i]; d++){ /* Delay between two effective waves */
1.247 brouard 3728: /* for(d=0; d<=0; d++){ /\* Delay between two effective waves Only one matrix to speed up*\/ */
1.242 brouard 3729: /*dh[m][i] or dh[mw[mi][i]][i] is the delay between two effective waves m=mw[mi][i]
3730: and mw[mi+1][i]. dh depends on stepm.*/
3731: newm=savm;
1.247 brouard 3732: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM; /* Here d is needed */
1.242 brouard 3733: cov[2]=agexact;
3734: if(nagesqr==1)
3735: cov[3]= agexact*agexact;
3736: for (kk=1; kk<=cptcovage;kk++) {
3737: if(!FixedV[Tvar[Tage[kk]]])
3738: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
3739: else
3740: cov[Tage[kk]+2+nagesqr]=cotvar[mw[mi][i]][Tvar[Tage[kk]]-ncovcol-nqv][i]*agexact;
3741: }
3742: /* printf("i=%d,mi=%d,d=%d,mw[mi][i]=%d\n",i, mi,d,mw[mi][i]); */
3743: /* savm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
3744: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
3745: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
3746: /* out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath, */
3747: /* 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate)); */
3748: savm=oldm;
3749: oldm=newm;
1.126 brouard 3750: } /* end mult */
3751:
3752: s1=s[mw[mi][i]][i];
3753: s2=s[mw[mi+1][i]][i];
1.217 brouard 3754: /* if(s2==-1){ */
1.268 ! brouard 3755: /* printf(" ERROR s1=%d, s2=%d i=%d \n", s1, s2, i); */
1.217 brouard 3756: /* /\* exit(1); *\/ */
3757: /* } */
1.126 brouard 3758: bbh=(double)bh[mi][i]/(double)stepm;
3759: /* bias is positive if real duration
3760: * is higher than the multiple of stepm and negative otherwise.
3761: */
3762: if( s2 > nlstate && (mle <5) ){ /* Jackson */
1.242 brouard 3763: lli=log(out[s1][s2] - savm[s1][s2]);
1.216 brouard 3764: } else if ( s2==-1 ) { /* alive */
1.242 brouard 3765: for (j=1,survp=0. ; j<=nlstate; j++)
3766: survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j];
3767: lli= log(survp);
1.126 brouard 3768: }else if (mle==1){
1.242 brouard 3769: lli= log((1.+bbh)*out[s1][s2]- bbh*savm[s1][s2]); /* linear interpolation */
1.126 brouard 3770: } else if(mle==2){
1.242 brouard 3771: 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 3772: } else if(mle==3){ /* exponential inter-extrapolation */
1.242 brouard 3773: 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 3774: } else if (mle==4){ /* mle=4 no inter-extrapolation */
1.242 brouard 3775: lli=log(out[s1][s2]); /* Original formula */
1.136 brouard 3776: } else{ /* mle=0 back to 1 */
1.242 brouard 3777: lli= log((1.+bbh)*out[s1][s2]- bbh*savm[s1][s2]); /* linear interpolation */
3778: /*lli=log(out[s1][s2]); */ /* Original formula */
1.126 brouard 3779: } /* End of if */
3780: ipmx +=1;
3781: sw += weight[i];
3782: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
1.132 brouard 3783: /*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 3784: if(globpr){
1.246 brouard 3785: fprintf(ficresilk,"%09ld %6.1f %6.1f %6d %2d %2d %2d %2d %3d %15.6f %8.4f %8.3f\
1.126 brouard 3786: %11.6f %11.6f %11.6f ", \
1.242 brouard 3787: num[i], agebegin, ageend, i,s1,s2,mi,mw[mi][i],dh[mi][i],exp(lli),weight[i],weight[i]*gipmx/gsw,
1.268 ! brouard 3788: 2*weight[i]*lli,(s2==-1? -1: out[s1][s2]),(s2==-1? -1: savm[s1][s2]));
1.242 brouard 3789: for(k=1,llt=0.,l=0.; k<=nlstate; k++){
3790: llt +=ll[k]*gipmx/gsw;
3791: fprintf(ficresilk," %10.6f",-ll[k]*gipmx/gsw);
3792: }
3793: fprintf(ficresilk," %10.6f\n", -llt);
1.126 brouard 3794: }
1.232 brouard 3795: } /* end of wave */
3796: } /* end of individual */
3797: for(k=1,l=0.; k<=nlstate; k++) l += ll[k];
3798: /* printf("l1=%f l2=%f ",ll[1],ll[2]); */
3799: l= l*ipmx/sw; /* To get the same order of magnitude as if weight=1 for every body */
3800: if(globpr==0){ /* First time we count the contributions and weights */
3801: gipmx=ipmx;
3802: gsw=sw;
3803: }
3804: return -l;
1.126 brouard 3805: }
3806:
3807:
3808: /*************** function likelione ***********/
3809: void likelione(FILE *ficres,double p[], int npar, int nlstate, int *globpri, long *ipmx, double *sw, double *fretone, double (*funcone)(double []))
3810: {
3811: /* This routine should help understanding what is done with
3812: the selection of individuals/waves and
3813: to check the exact contribution to the likelihood.
3814: Plotting could be done.
3815: */
3816: int k;
3817:
3818: if(*globpri !=0){ /* Just counts and sums, no printings */
1.201 brouard 3819: strcpy(fileresilk,"ILK_");
1.202 brouard 3820: strcat(fileresilk,fileresu);
1.126 brouard 3821: if((ficresilk=fopen(fileresilk,"w"))==NULL) {
3822: printf("Problem with resultfile: %s\n", fileresilk);
3823: fprintf(ficlog,"Problem with resultfile: %s\n", fileresilk);
3824: }
1.214 brouard 3825: 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");
3826: fprintf(ficresilk, "#num_i ageb agend i s1 s2 mi mw dh likeli weight %%weight 2wlli out sav ");
1.126 brouard 3827: /* i,s1,s2,mi,mw[mi][i],dh[mi][i],exp(lli),weight[i],2*weight[i]*lli,out[s1][s2],savm[s1][s2]); */
3828: for(k=1; k<=nlstate; k++)
3829: fprintf(ficresilk," -2*gipw/gsw*weight*ll[%d]++",k);
3830: fprintf(ficresilk," -2*gipw/gsw*weight*ll(total)\n");
3831: }
3832:
3833: *fretone=(*funcone)(p);
3834: if(*globpri !=0){
3835: fclose(ficresilk);
1.205 brouard 3836: if (mle ==0)
3837: fprintf(fichtm,"\n<br>File of contributions to the likelihood computed with initial parameters and mle = %d.",mle);
3838: else if(mle >=1)
3839: fprintf(fichtm,"\n<br>File of contributions to the likelihood computed with optimized parameters mle = %d.",mle);
3840: 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 3841:
1.208 brouard 3842:
3843: for (k=1; k<= nlstate ; k++) {
1.211 brouard 3844: 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 3845: <img src=\"%s-p%dj.png\">",k,k,subdirf2(optionfilefiname,"ILK_"),k,subdirf2(optionfilefiname,"ILK_"),k,subdirf2(optionfilefiname,"ILK_"),k);
3846: }
1.207 brouard 3847: 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 3848: <img src=\"%s-ori.png\">",subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"));
1.207 brouard 3849: fprintf(fichtm,"<br>- and by state of destination <a href=\"%s-dest.png\">%s-dest.png</a><br> \
1.204 brouard 3850: <img src=\"%s-dest.png\">",subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"));
1.207 brouard 3851: fflush(fichtm);
1.205 brouard 3852: }
1.126 brouard 3853: return;
3854: }
3855:
3856:
3857: /*********** Maximum Likelihood Estimation ***************/
3858:
3859: void mlikeli(FILE *ficres,double p[], int npar, int ncovmodel, int nlstate, double ftol, double (*func)(double []))
3860: {
1.165 brouard 3861: int i,j, iter=0;
1.126 brouard 3862: double **xi;
3863: double fret;
3864: double fretone; /* Only one call to likelihood */
3865: /* char filerespow[FILENAMELENGTH];*/
1.162 brouard 3866:
3867: #ifdef NLOPT
3868: int creturn;
3869: nlopt_opt opt;
3870: /* double lb[9] = { -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL }; /\* lower bounds *\/ */
3871: double *lb;
3872: double minf; /* the minimum objective value, upon return */
3873: double * p1; /* Shifted parameters from 0 instead of 1 */
3874: myfunc_data dinst, *d = &dinst;
3875: #endif
3876:
3877:
1.126 brouard 3878: xi=matrix(1,npar,1,npar);
3879: for (i=1;i<=npar;i++)
3880: for (j=1;j<=npar;j++)
3881: xi[i][j]=(i==j ? 1.0 : 0.0);
3882: printf("Powell\n"); fprintf(ficlog,"Powell\n");
1.201 brouard 3883: strcpy(filerespow,"POW_");
1.126 brouard 3884: strcat(filerespow,fileres);
3885: if((ficrespow=fopen(filerespow,"w"))==NULL) {
3886: printf("Problem with resultfile: %s\n", filerespow);
3887: fprintf(ficlog,"Problem with resultfile: %s\n", filerespow);
3888: }
3889: fprintf(ficrespow,"# Powell\n# iter -2*LL");
3890: for (i=1;i<=nlstate;i++)
3891: for(j=1;j<=nlstate+ndeath;j++)
3892: if(j!=i)fprintf(ficrespow," p%1d%1d",i,j);
3893: fprintf(ficrespow,"\n");
1.162 brouard 3894: #ifdef POWELL
1.126 brouard 3895: powell(p,xi,npar,ftol,&iter,&fret,func);
1.162 brouard 3896: #endif
1.126 brouard 3897:
1.162 brouard 3898: #ifdef NLOPT
3899: #ifdef NEWUOA
3900: opt = nlopt_create(NLOPT_LN_NEWUOA,npar);
3901: #else
3902: opt = nlopt_create(NLOPT_LN_BOBYQA,npar);
3903: #endif
3904: lb=vector(0,npar-1);
3905: for (i=0;i<npar;i++) lb[i]= -HUGE_VAL;
3906: nlopt_set_lower_bounds(opt, lb);
3907: nlopt_set_initial_step1(opt, 0.1);
3908:
3909: p1= (p+1); /* p *(p+1)@8 and p *(p1)@8 are equal p1[0]=p[1] */
3910: d->function = func;
3911: printf(" Func %.12lf \n",myfunc(npar,p1,NULL,d));
3912: nlopt_set_min_objective(opt, myfunc, d);
3913: nlopt_set_xtol_rel(opt, ftol);
3914: if ((creturn=nlopt_optimize(opt, p1, &minf)) < 0) {
3915: printf("nlopt failed! %d\n",creturn);
3916: }
3917: else {
3918: printf("found minimum after %d evaluations (NLOPT=%d)\n", countcallfunc ,NLOPT);
3919: printf("found minimum at f(%g,%g) = %0.10g\n", p[0], p[1], minf);
3920: iter=1; /* not equal */
3921: }
3922: nlopt_destroy(opt);
3923: #endif
1.126 brouard 3924: free_matrix(xi,1,npar,1,npar);
3925: fclose(ficrespow);
1.203 brouard 3926: printf("\n#Number of iterations & function calls = %d & %d, -2 Log likelihood = %.12f\n",iter, countcallfunc,func(p));
3927: fprintf(ficlog,"\n#Number of iterations & function calls = %d & %d, -2 Log likelihood = %.12f\n",iter, countcallfunc,func(p));
1.180 brouard 3928: fprintf(ficres,"#Number of iterations & function calls = %d & %d, -2 Log likelihood = %.12f\n",iter, countcallfunc,func(p));
1.126 brouard 3929:
3930: }
3931:
3932: /**** Computes Hessian and covariance matrix ***/
1.203 brouard 3933: void hesscov(double **matcov, double **hess, double p[], int npar, double delti[], double ftolhess, double (*func)(double []))
1.126 brouard 3934: {
3935: double **a,**y,*x,pd;
1.203 brouard 3936: /* double **hess; */
1.164 brouard 3937: int i, j;
1.126 brouard 3938: int *indx;
3939:
3940: double hessii(double p[], double delta, int theta, double delti[],double (*func)(double []),int npar);
1.203 brouard 3941: double hessij(double p[], double **hess, double delti[], int i, int j,double (*func)(double []),int npar);
1.126 brouard 3942: void lubksb(double **a, int npar, int *indx, double b[]) ;
3943: void ludcmp(double **a, int npar, int *indx, double *d) ;
3944: double gompertz(double p[]);
1.203 brouard 3945: /* hess=matrix(1,npar,1,npar); */
1.126 brouard 3946:
3947: printf("\nCalculation of the hessian matrix. Wait...\n");
3948: fprintf(ficlog,"\nCalculation of the hessian matrix. Wait...\n");
3949: for (i=1;i<=npar;i++){
1.203 brouard 3950: printf("%d-",i);fflush(stdout);
3951: fprintf(ficlog,"%d-",i);fflush(ficlog);
1.126 brouard 3952:
3953: hess[i][i]=hessii(p,ftolhess,i,delti,func,npar);
3954:
3955: /* printf(" %f ",p[i]);
3956: printf(" %lf %lf %lf",hess[i][i],ftolhess,delti[i]);*/
3957: }
3958:
3959: for (i=1;i<=npar;i++) {
3960: for (j=1;j<=npar;j++) {
3961: if (j>i) {
1.203 brouard 3962: printf(".%d-%d",i,j);fflush(stdout);
3963: fprintf(ficlog,".%d-%d",i,j);fflush(ficlog);
3964: hess[i][j]=hessij(p,hess, delti,i,j,func,npar);
1.126 brouard 3965:
3966: hess[j][i]=hess[i][j];
3967: /*printf(" %lf ",hess[i][j]);*/
3968: }
3969: }
3970: }
3971: printf("\n");
3972: fprintf(ficlog,"\n");
3973:
3974: printf("\nInverting the hessian to get the covariance matrix. Wait...\n");
3975: fprintf(ficlog,"\nInverting the hessian to get the covariance matrix. Wait...\n");
3976:
3977: a=matrix(1,npar,1,npar);
3978: y=matrix(1,npar,1,npar);
3979: x=vector(1,npar);
3980: indx=ivector(1,npar);
3981: for (i=1;i<=npar;i++)
3982: for (j=1;j<=npar;j++) a[i][j]=hess[i][j];
3983: ludcmp(a,npar,indx,&pd);
3984:
3985: for (j=1;j<=npar;j++) {
3986: for (i=1;i<=npar;i++) x[i]=0;
3987: x[j]=1;
3988: lubksb(a,npar,indx,x);
3989: for (i=1;i<=npar;i++){
3990: matcov[i][j]=x[i];
3991: }
3992: }
3993:
3994: printf("\n#Hessian matrix#\n");
3995: fprintf(ficlog,"\n#Hessian matrix#\n");
3996: for (i=1;i<=npar;i++) {
3997: for (j=1;j<=npar;j++) {
1.203 brouard 3998: printf("%.6e ",hess[i][j]);
3999: fprintf(ficlog,"%.6e ",hess[i][j]);
1.126 brouard 4000: }
4001: printf("\n");
4002: fprintf(ficlog,"\n");
4003: }
4004:
1.203 brouard 4005: /* printf("\n#Covariance matrix#\n"); */
4006: /* fprintf(ficlog,"\n#Covariance matrix#\n"); */
4007: /* for (i=1;i<=npar;i++) { */
4008: /* for (j=1;j<=npar;j++) { */
4009: /* printf("%.6e ",matcov[i][j]); */
4010: /* fprintf(ficlog,"%.6e ",matcov[i][j]); */
4011: /* } */
4012: /* printf("\n"); */
4013: /* fprintf(ficlog,"\n"); */
4014: /* } */
4015:
1.126 brouard 4016: /* Recompute Inverse */
1.203 brouard 4017: /* for (i=1;i<=npar;i++) */
4018: /* for (j=1;j<=npar;j++) a[i][j]=matcov[i][j]; */
4019: /* ludcmp(a,npar,indx,&pd); */
4020:
4021: /* printf("\n#Hessian matrix recomputed#\n"); */
4022:
4023: /* for (j=1;j<=npar;j++) { */
4024: /* for (i=1;i<=npar;i++) x[i]=0; */
4025: /* x[j]=1; */
4026: /* lubksb(a,npar,indx,x); */
4027: /* for (i=1;i<=npar;i++){ */
4028: /* y[i][j]=x[i]; */
4029: /* printf("%.3e ",y[i][j]); */
4030: /* fprintf(ficlog,"%.3e ",y[i][j]); */
4031: /* } */
4032: /* printf("\n"); */
4033: /* fprintf(ficlog,"\n"); */
4034: /* } */
4035:
4036: /* Verifying the inverse matrix */
4037: #ifdef DEBUGHESS
4038: y=matprod2(y,hess,1,npar,1,npar,1,npar,matcov);
1.126 brouard 4039:
1.203 brouard 4040: printf("\n#Verification: multiplying the matrix of covariance by the Hessian matrix, should be unity:#\n");
4041: fprintf(ficlog,"\n#Verification: multiplying the matrix of covariance by the Hessian matrix. Should be unity:#\n");
1.126 brouard 4042:
4043: for (j=1;j<=npar;j++) {
4044: for (i=1;i<=npar;i++){
1.203 brouard 4045: printf("%.2f ",y[i][j]);
4046: fprintf(ficlog,"%.2f ",y[i][j]);
1.126 brouard 4047: }
4048: printf("\n");
4049: fprintf(ficlog,"\n");
4050: }
1.203 brouard 4051: #endif
1.126 brouard 4052:
4053: free_matrix(a,1,npar,1,npar);
4054: free_matrix(y,1,npar,1,npar);
4055: free_vector(x,1,npar);
4056: free_ivector(indx,1,npar);
1.203 brouard 4057: /* free_matrix(hess,1,npar,1,npar); */
1.126 brouard 4058:
4059:
4060: }
4061:
4062: /*************** hessian matrix ****************/
4063: double hessii(double x[], double delta, int theta, double delti[], double (*func)(double []), int npar)
1.203 brouard 4064: { /* Around values of x, computes the function func and returns the scales delti and hessian */
1.126 brouard 4065: int i;
4066: int l=1, lmax=20;
1.203 brouard 4067: double k1,k2, res, fx;
1.132 brouard 4068: double p2[MAXPARM+1]; /* identical to x */
1.126 brouard 4069: double delt=0.0001, delts, nkhi=10.,nkhif=1., khi=1.e-4;
4070: int k=0,kmax=10;
4071: double l1;
4072:
4073: fx=func(x);
4074: for (i=1;i<=npar;i++) p2[i]=x[i];
1.145 brouard 4075: for(l=0 ; l <=lmax; l++){ /* Enlarging the zone around the Maximum */
1.126 brouard 4076: l1=pow(10,l);
4077: delts=delt;
4078: for(k=1 ; k <kmax; k=k+1){
4079: delt = delta*(l1*k);
4080: p2[theta]=x[theta] +delt;
1.145 brouard 4081: k1=func(p2)-fx; /* Might be negative if too close to the theoretical maximum */
1.126 brouard 4082: p2[theta]=x[theta]-delt;
4083: k2=func(p2)-fx;
4084: /*res= (k1-2.0*fx+k2)/delt/delt; */
1.203 brouard 4085: res= (k1+k2)/delt/delt/2.; /* Divided by 2 because L and not 2*L */
1.126 brouard 4086:
1.203 brouard 4087: #ifdef DEBUGHESSII
1.126 brouard 4088: 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);
4089: 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);
4090: #endif
4091: /*if(fabs(k1-2.0*fx+k2) <1.e-13){ */
4092: if((k1 <khi/nkhi/2.) || (k2 <khi/nkhi/2.)){
4093: k=kmax;
4094: }
4095: else if((k1 >khi/nkhif) || (k2 >khi/nkhif)){ /* Keeps lastvalue before 3.84/2 KHI2 5% 1d.f. */
1.164 brouard 4096: k=kmax; l=lmax*10;
1.126 brouard 4097: }
4098: else if((k1 >khi/nkhi) || (k2 >khi/nkhi)){
4099: delts=delt;
4100: }
1.203 brouard 4101: } /* End loop k */
1.126 brouard 4102: }
4103: delti[theta]=delts;
4104: return res;
4105:
4106: }
4107:
1.203 brouard 4108: double hessij( double x[], double **hess, double delti[], int thetai,int thetaj,double (*func)(double []),int npar)
1.126 brouard 4109: {
4110: int i;
1.164 brouard 4111: int l=1, lmax=20;
1.126 brouard 4112: double k1,k2,k3,k4,res,fx;
1.132 brouard 4113: double p2[MAXPARM+1];
1.203 brouard 4114: int k, kmax=1;
4115: double v1, v2, cv12, lc1, lc2;
1.208 brouard 4116:
4117: int firstime=0;
1.203 brouard 4118:
1.126 brouard 4119: fx=func(x);
1.203 brouard 4120: for (k=1; k<=kmax; k=k+10) {
1.126 brouard 4121: for (i=1;i<=npar;i++) p2[i]=x[i];
1.203 brouard 4122: p2[thetai]=x[thetai]+delti[thetai]*k;
4123: p2[thetaj]=x[thetaj]+delti[thetaj]*k;
1.126 brouard 4124: k1=func(p2)-fx;
4125:
1.203 brouard 4126: p2[thetai]=x[thetai]+delti[thetai]*k;
4127: p2[thetaj]=x[thetaj]-delti[thetaj]*k;
1.126 brouard 4128: k2=func(p2)-fx;
4129:
1.203 brouard 4130: p2[thetai]=x[thetai]-delti[thetai]*k;
4131: p2[thetaj]=x[thetaj]+delti[thetaj]*k;
1.126 brouard 4132: k3=func(p2)-fx;
4133:
1.203 brouard 4134: p2[thetai]=x[thetai]-delti[thetai]*k;
4135: p2[thetaj]=x[thetaj]-delti[thetaj]*k;
1.126 brouard 4136: k4=func(p2)-fx;
1.203 brouard 4137: res=(k1-k2-k3+k4)/4.0/delti[thetai]/k/delti[thetaj]/k/2.; /* Because of L not 2*L */
4138: if(k1*k2*k3*k4 <0.){
1.208 brouard 4139: firstime=1;
1.203 brouard 4140: kmax=kmax+10;
1.208 brouard 4141: }
4142: if(kmax >=10 || firstime ==1){
1.246 brouard 4143: printf("Warning: directions %d-%d, you are not estimating the Hessian at the exact maximum likelihood; you could increase ftol=%.2e\n",thetai,thetaj, ftol);
4144: fprintf(ficlog,"Warning: directions %d-%d, you are not estimating the Hessian at the exact maximum likelihood; you could increase ftol=%.2e\n",thetai,thetaj, ftol);
1.203 brouard 4145: 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);
4146: 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);
4147: }
4148: #ifdef DEBUGHESSIJ
4149: v1=hess[thetai][thetai];
4150: v2=hess[thetaj][thetaj];
4151: cv12=res;
4152: /* Computing eigen value of Hessian matrix */
4153: lc1=((v1+v2)+sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
4154: lc2=((v1+v2)-sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
4155: if ((lc2 <0) || (lc1 <0) ){
4156: printf("Warning: sub Hessian matrix '%d%d' does not have positive eigen values \n",thetai,thetaj);
4157: fprintf(ficlog, "Warning: sub Hessian matrix '%d%d' does not have positive eigen values \n",thetai,thetaj);
4158: 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);
4159: 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);
4160: }
1.126 brouard 4161: #endif
4162: }
4163: return res;
4164: }
4165:
1.203 brouard 4166: /* Not done yet: Was supposed to fix if not exactly at the maximum */
4167: /* double hessij( double x[], double delti[], int thetai,int thetaj,double (*func)(double []),int npar) */
4168: /* { */
4169: /* int i; */
4170: /* int l=1, lmax=20; */
4171: /* double k1,k2,k3,k4,res,fx; */
4172: /* double p2[MAXPARM+1]; */
4173: /* double delt=0.0001, delts, nkhi=10.,nkhif=1., khi=1.e-4; */
4174: /* int k=0,kmax=10; */
4175: /* double l1; */
4176:
4177: /* fx=func(x); */
4178: /* for(l=0 ; l <=lmax; l++){ /\* Enlarging the zone around the Maximum *\/ */
4179: /* l1=pow(10,l); */
4180: /* delts=delt; */
4181: /* for(k=1 ; k <kmax; k=k+1){ */
4182: /* delt = delti*(l1*k); */
4183: /* for (i=1;i<=npar;i++) p2[i]=x[i]; */
4184: /* p2[thetai]=x[thetai]+delti[thetai]/k; */
4185: /* p2[thetaj]=x[thetaj]+delti[thetaj]/k; */
4186: /* k1=func(p2)-fx; */
4187:
4188: /* p2[thetai]=x[thetai]+delti[thetai]/k; */
4189: /* p2[thetaj]=x[thetaj]-delti[thetaj]/k; */
4190: /* k2=func(p2)-fx; */
4191:
4192: /* p2[thetai]=x[thetai]-delti[thetai]/k; */
4193: /* p2[thetaj]=x[thetaj]+delti[thetaj]/k; */
4194: /* k3=func(p2)-fx; */
4195:
4196: /* p2[thetai]=x[thetai]-delti[thetai]/k; */
4197: /* p2[thetaj]=x[thetaj]-delti[thetaj]/k; */
4198: /* k4=func(p2)-fx; */
4199: /* res=(k1-k2-k3+k4)/4.0/delti[thetai]*k/delti[thetaj]*k/2.; /\* Because of L not 2*L *\/ */
4200: /* #ifdef DEBUGHESSIJ */
4201: /* 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); */
4202: /* 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); */
4203: /* #endif */
4204: /* if((k1 <khi/nkhi/2.) || (k2 <khi/nkhi/2.)|| (k4 <khi/nkhi/2.)|| (k4 <khi/nkhi/2.)){ */
4205: /* k=kmax; */
4206: /* } */
4207: /* else if((k1 >khi/nkhif) || (k2 >khi/nkhif) || (k4 >khi/nkhif) || (k4 >khi/nkhif)){ /\* Keeps lastvalue before 3.84/2 KHI2 5% 1d.f. *\/ */
4208: /* k=kmax; l=lmax*10; */
4209: /* } */
4210: /* else if((k1 >khi/nkhi) || (k2 >khi/nkhi)){ */
4211: /* delts=delt; */
4212: /* } */
4213: /* } /\* End loop k *\/ */
4214: /* } */
4215: /* delti[theta]=delts; */
4216: /* return res; */
4217: /* } */
4218:
4219:
1.126 brouard 4220: /************** Inverse of matrix **************/
4221: void ludcmp(double **a, int n, int *indx, double *d)
4222: {
4223: int i,imax,j,k;
4224: double big,dum,sum,temp;
4225: double *vv;
4226:
4227: vv=vector(1,n);
4228: *d=1.0;
4229: for (i=1;i<=n;i++) {
4230: big=0.0;
4231: for (j=1;j<=n;j++)
4232: if ((temp=fabs(a[i][j])) > big) big=temp;
1.256 brouard 4233: if (big == 0.0){
4234: printf(" Singular Hessian matrix at row %d:\n",i);
4235: for (j=1;j<=n;j++) {
4236: printf(" a[%d][%d]=%f,",i,j,a[i][j]);
4237: fprintf(ficlog," a[%d][%d]=%f,",i,j,a[i][j]);
4238: }
4239: fflush(ficlog);
4240: fclose(ficlog);
4241: nrerror("Singular matrix in routine ludcmp");
4242: }
1.126 brouard 4243: vv[i]=1.0/big;
4244: }
4245: for (j=1;j<=n;j++) {
4246: for (i=1;i<j;i++) {
4247: sum=a[i][j];
4248: for (k=1;k<i;k++) sum -= a[i][k]*a[k][j];
4249: a[i][j]=sum;
4250: }
4251: big=0.0;
4252: for (i=j;i<=n;i++) {
4253: sum=a[i][j];
4254: for (k=1;k<j;k++)
4255: sum -= a[i][k]*a[k][j];
4256: a[i][j]=sum;
4257: if ( (dum=vv[i]*fabs(sum)) >= big) {
4258: big=dum;
4259: imax=i;
4260: }
4261: }
4262: if (j != imax) {
4263: for (k=1;k<=n;k++) {
4264: dum=a[imax][k];
4265: a[imax][k]=a[j][k];
4266: a[j][k]=dum;
4267: }
4268: *d = -(*d);
4269: vv[imax]=vv[j];
4270: }
4271: indx[j]=imax;
4272: if (a[j][j] == 0.0) a[j][j]=TINY;
4273: if (j != n) {
4274: dum=1.0/(a[j][j]);
4275: for (i=j+1;i<=n;i++) a[i][j] *= dum;
4276: }
4277: }
4278: free_vector(vv,1,n); /* Doesn't work */
4279: ;
4280: }
4281:
4282: void lubksb(double **a, int n, int *indx, double b[])
4283: {
4284: int i,ii=0,ip,j;
4285: double sum;
4286:
4287: for (i=1;i<=n;i++) {
4288: ip=indx[i];
4289: sum=b[ip];
4290: b[ip]=b[i];
4291: if (ii)
4292: for (j=ii;j<=i-1;j++) sum -= a[i][j]*b[j];
4293: else if (sum) ii=i;
4294: b[i]=sum;
4295: }
4296: for (i=n;i>=1;i--) {
4297: sum=b[i];
4298: for (j=i+1;j<=n;j++) sum -= a[i][j]*b[j];
4299: b[i]=sum/a[i][i];
4300: }
4301: }
4302:
4303: void pstamp(FILE *fichier)
4304: {
1.196 brouard 4305: fprintf(fichier,"# %s.%s\n#IMaCh version %s, %s\n#%s\n# %s", optionfilefiname,optionfilext,version,copyright, fullversion, strstart);
1.126 brouard 4306: }
4307:
1.253 brouard 4308:
4309:
1.126 brouard 4310: /************ Frequencies ********************/
1.251 brouard 4311: void freqsummary(char fileres[], double p[], double pstart[], int iagemin, int iagemax, int **s, double **agev, int nlstate, int imx, \
1.226 brouard 4312: int *Tvaraff, int *invalidvarcomb, int **nbcode, int *ncodemax,double **mint,double **anint, char strstart[], \
4313: int firstpass, int lastpass, int stepm, int weightopt, char model[])
1.250 brouard 4314: { /* Some frequencies as well as proposing some starting values */
1.226 brouard 4315:
1.265 brouard 4316: int i, m, jk, j1, bool, z1,j, nj, nl, k, iv, jj=0, s1=1, s2=1;
1.226 brouard 4317: int iind=0, iage=0;
4318: int mi; /* Effective wave */
4319: int first;
4320: double ***freq; /* Frequencies */
1.268 ! brouard 4321: double *x, *y, a=0.,b=0.,r=1., sa=0., sb=0.; /* for regression, y=b+m*x and r is the correlation coefficient */
! 4322: int no=0, linreg(int ifi, int ila, int *no, const double x[], const double y[], double* a, double* b, double* r, double* sa, double * sb);
1.226 brouard 4323: double *meanq;
4324: double **meanqt;
4325: double *pp, **prop, *posprop, *pospropt;
4326: double pos=0., posproptt=0., pospropta=0., k2, dateintsum=0,k2cpt=0;
4327: char fileresp[FILENAMELENGTH], fileresphtm[FILENAMELENGTH], fileresphtmfr[FILENAMELENGTH];
4328: double agebegin, ageend;
4329:
4330: pp=vector(1,nlstate);
1.251 brouard 4331: prop=matrix(1,nlstate,iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.226 brouard 4332: posprop=vector(1,nlstate); /* Counting the number of transition starting from a live state per age */
4333: pospropt=vector(1,nlstate); /* Counting the number of transition starting from a live state */
4334: /* prop=matrix(1,nlstate,iagemin,iagemax+3); */
4335: meanq=vector(1,nqfveff); /* Number of Quantitative Fixed Variables Effective */
4336: meanqt=matrix(1,lastpass,1,nqtveff);
4337: strcpy(fileresp,"P_");
4338: strcat(fileresp,fileresu);
4339: /*strcat(fileresphtm,fileresu);*/
4340: if((ficresp=fopen(fileresp,"w"))==NULL) {
4341: printf("Problem with prevalence resultfile: %s\n", fileresp);
4342: fprintf(ficlog,"Problem with prevalence resultfile: %s\n", fileresp);
4343: exit(0);
4344: }
1.240 brouard 4345:
1.226 brouard 4346: strcpy(fileresphtm,subdirfext(optionfilefiname,"PHTM_",".htm"));
4347: if((ficresphtm=fopen(fileresphtm,"w"))==NULL) {
4348: printf("Problem with prevalence HTM resultfile '%s' with errno='%s'\n",fileresphtm,strerror(errno));
4349: fprintf(ficlog,"Problem with prevalence HTM resultfile '%s' with errno='%s'\n",fileresphtm,strerror(errno));
4350: fflush(ficlog);
4351: exit(70);
4352: }
4353: else{
4354: fprintf(ficresphtm,"<html><head>\n<title>IMaCh PHTM_ %s</title></head>\n <body><font size=\"2\">%s <br> %s</font> \
1.240 brouard 4355: <hr size=\"2\" color=\"#EC5E5E\"> \n \
1.214 brouard 4356: Title=%s <br>Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s<br>\n",\
1.226 brouard 4357: fileresphtm,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model);
4358: }
1.237 brouard 4359: 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 4360:
1.226 brouard 4361: strcpy(fileresphtmfr,subdirfext(optionfilefiname,"PHTMFR_",".htm"));
4362: if((ficresphtmfr=fopen(fileresphtmfr,"w"))==NULL) {
4363: printf("Problem with frequency table HTM resultfile '%s' with errno='%s'\n",fileresphtmfr,strerror(errno));
4364: fprintf(ficlog,"Problem with frequency table HTM resultfile '%s' with errno='%s'\n",fileresphtmfr,strerror(errno));
4365: fflush(ficlog);
4366: exit(70);
1.240 brouard 4367: } else{
1.226 brouard 4368: 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 4369: <hr size=\"2\" color=\"#EC5E5E\"> \n \
1.214 brouard 4370: Title=%s <br>Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s<br>\n",\
1.226 brouard 4371: fileresphtmfr,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model);
4372: }
1.240 brouard 4373: 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);
4374:
1.253 brouard 4375: y= vector(iagemin-AGEMARGE,iagemax+4+AGEMARGE);
4376: x= vector(iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.251 brouard 4377: freq= ma3x(-5,nlstate+ndeath,-5,nlstate+ndeath,iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.226 brouard 4378: j1=0;
1.126 brouard 4379:
1.227 brouard 4380: /* j=ncoveff; /\* Only fixed dummy covariates *\/ */
4381: j=cptcoveff; /* Only dummy covariates of the model */
1.226 brouard 4382: if (cptcovn<1) {j=1;ncodemax[1]=1;}
1.240 brouard 4383:
4384:
1.226 brouard 4385: /* Detects if a combination j1 is empty: for a multinomial variable like 3 education levels:
4386: reference=low_education V1=0,V2=0
4387: med_educ V1=1 V2=0,
4388: high_educ V1=0 V2=1
4389: Then V1=1 and V2=1 is a noisy combination that we want to exclude for the list 2**cptcoveff
4390: */
1.249 brouard 4391: dateintsum=0;
4392: k2cpt=0;
4393:
1.253 brouard 4394: if(cptcoveff == 0 )
1.265 brouard 4395: nl=1; /* Constant and age model only */
1.253 brouard 4396: else
4397: nl=2;
1.265 brouard 4398:
4399: /* if a constant only model, one pass to compute frequency tables and to write it on ficresp */
4400: /* Loop on nj=1 or 2 if dummy covariates j!=0
4401: * Loop on j1(1 to 2**cptcoveff) covariate combination
4402: * freq[s1][s2][iage] =0.
4403: * Loop on iind
4404: * ++freq[s1][s2][iage] weighted
4405: * end iind
4406: * if covariate and j!0
4407: * headers Variable on one line
4408: * endif cov j!=0
4409: * header of frequency table by age
4410: * Loop on age
4411: * pp[s1]+=freq[s1][s2][iage] weighted
4412: * pos+=freq[s1][s2][iage] weighted
4413: * Loop on s1 initial state
4414: * fprintf(ficresp
4415: * end s1
4416: * end age
4417: * if j!=0 computes starting values
4418: * end compute starting values
4419: * end j1
4420: * end nl
4421: */
1.253 brouard 4422: for (nj = 1; nj <= nl; nj++){ /* nj= 1 constant model, nl number of loops. */
4423: if(nj==1)
4424: j=0; /* First pass for the constant */
1.265 brouard 4425: else{
1.253 brouard 4426: j=cptcoveff; /* Other passes for the covariate values */
1.265 brouard 4427: }
1.251 brouard 4428: first=1;
1.265 brouard 4429: for (j1 = 1; j1 <= (int) pow(2,j); j1++){ /* Loop on all covariates combination of the model, excluding quantitatives, V4=0, V3=0 for example, fixed or varying covariates */
1.251 brouard 4430: posproptt=0.;
4431: /*printf("cptcoveff=%d Tvaraff=%d", cptcoveff,Tvaraff[1]);
4432: scanf("%d", i);*/
4433: for (i=-5; i<=nlstate+ndeath; i++)
1.265 brouard 4434: for (s2=-5; s2<=nlstate+ndeath; s2++)
1.251 brouard 4435: for(m=iagemin; m <= iagemax+3; m++)
1.265 brouard 4436: freq[i][s2][m]=0;
1.251 brouard 4437:
4438: for (i=1; i<=nlstate; i++) {
1.240 brouard 4439: for(m=iagemin; m <= iagemax+3; m++)
1.251 brouard 4440: prop[i][m]=0;
4441: posprop[i]=0;
4442: pospropt[i]=0;
4443: }
4444: /* for (z1=1; z1<= nqfveff; z1++) { */
4445: /* meanq[z1]+=0.; */
4446: /* for(m=1;m<=lastpass;m++){ */
4447: /* meanqt[m][z1]=0.; */
4448: /* } */
4449: /* } */
4450:
4451: /* dateintsum=0; */
4452: /* k2cpt=0; */
4453:
1.265 brouard 4454: /* For that combination of covariates j1 (V4=1 V3=0 for example), we count and print the frequencies in one pass */
1.251 brouard 4455: for (iind=1; iind<=imx; iind++) { /* For each individual iind */
4456: bool=1;
4457: if(j !=0){
4458: if(anyvaryingduminmodel==0){ /* If All fixed covariates */
4459: if (cptcoveff >0) { /* Filter is here: Must be looked at for model=V1+V2+V3+V4 */
4460: /* for (z1=1; z1<= nqfveff; z1++) { */
4461: /* meanq[z1]+=coqvar[Tvar[z1]][iind]; /\* Computes mean of quantitative with selected filter *\/ */
4462: /* } */
4463: for (z1=1; z1<=cptcoveff; z1++) { /* loops on covariates in the model */
4464: /* if(Tvaraff[z1] ==-20){ */
4465: /* /\* sumnew+=cotvar[mw[mi][iind]][z1][iind]; *\/ */
4466: /* }else if(Tvaraff[z1] ==-10){ */
4467: /* /\* sumnew+=coqvar[z1][iind]; *\/ */
4468: /* }else */
4469: if (covar[Tvaraff[z1]][iind]!= nbcode[Tvaraff[z1]][codtabm(j1,z1)]){ /* for combination j1 of covariates */
1.265 brouard 4470: /* Tests if the value of the covariate z1 for this individual iind responded to combination j1 (V4=1 V3=0) */
1.251 brouard 4471: bool=0; /* bool should be equal to 1 to be selected, one covariate value failed */
4472: /* 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",
4473: bool,i,z1, z1, Tvaraff[z1],i,covar[Tvaraff[z1]][i],j1,z1,codtabm(j1,z1),
4474: j1,z1,nbcode[Tvaraff[z1]][codtabm(j1,z1)],j1);*/
4475: /* For j1=7 in V1+V2+V3+V4 = 0 1 1 0 and codtabm(7,3)=1 and nbcde[3][?]=1*/
4476: } /* Onlyf fixed */
4477: } /* end z1 */
4478: } /* cptcovn > 0 */
4479: } /* end any */
4480: }/* end j==0 */
1.265 brouard 4481: if (bool==1){ /* We selected an individual iind satisfying combination j1 (V4=1 V3=0) or all fixed covariates */
1.251 brouard 4482: /* for(m=firstpass; m<=lastpass; m++){ */
4483: for(mi=1; mi<wav[iind];mi++){ /* For that wave */
4484: m=mw[mi][iind];
4485: if(j!=0){
4486: if(anyvaryingduminmodel==1){ /* Some are varying covariates */
4487: for (z1=1; z1<=cptcoveff; z1++) {
4488: if( Fixed[Tmodelind[z1]]==1){
4489: iv= Tvar[Tmodelind[z1]]-ncovcol-nqv;
4490: if (cotvar[m][iv][iind]!= nbcode[Tvaraff[z1]][codtabm(j1,z1)]) /* iv=1 to ntv, right modality. If covariate's
4491: value is -1, we don't select. It differs from the
4492: constant and age model which counts them. */
4493: bool=0; /* not selected */
4494: }else if( Fixed[Tmodelind[z1]]== 0) { /* fixed */
4495: if (covar[Tvaraff[z1]][iind]!= nbcode[Tvaraff[z1]][codtabm(j1,z1)]) {
4496: bool=0;
4497: }
4498: }
4499: }
4500: }/* Some are varying covariates, we tried to speed up if all fixed covariates in the model, avoiding waves loop */
4501: } /* end j==0 */
4502: /* bool =0 we keep that guy which corresponds to the combination of dummy values */
4503: if(bool==1){
4504: /* dh[m][iind] or dh[mw[mi][iind]][iind] is the delay between two effective (mi) waves m=mw[mi][iind]
4505: and mw[mi+1][iind]. dh depends on stepm. */
4506: agebegin=agev[m][iind]; /* Age at beginning of wave before transition*/
4507: ageend=agev[m][iind]+(dh[m][iind])*stepm/YEARM; /* Age at end of wave and transition */
4508: if(m >=firstpass && m <=lastpass){
4509: k2=anint[m][iind]+(mint[m][iind]/12.);
4510: /*if ((k2>=dateprev1) && (k2<=dateprev2)) {*/
4511: if(agev[m][iind]==0) agev[m][iind]=iagemax+1; /* All ages equal to 0 are in iagemax+1 */
4512: if(agev[m][iind]==1) agev[m][iind]=iagemax+2; /* All ages equal to 1 are in iagemax+2 */
4513: if (s[m][iind]>0 && s[m][iind]<=nlstate) /* If status at wave m is known and a live state */
4514: prop[s[m][iind]][(int)agev[m][iind]] += weight[iind]; /* At age of beginning of transition, where status is known */
4515: if (m<lastpass) {
4516: /* if(s[m][iind]==4 && s[m+1][iind]==4) */
4517: /* 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]); */
4518: if(s[m][iind]==-1)
4519: 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.));
4520: freq[s[m][iind]][s[m+1][iind]][(int)agev[m][iind]] += weight[iind]; /* At age of beginning of transition, where status is known */
4521: /* if((int)agev[m][iind] == 55) */
4522: /* printf("j=%d, j1=%d Age %d, iind=%d, num=%09ld m=%d\n",j,j1,(int)agev[m][iind],iind, num[iind],m); */
4523: /* freq[s[m][iind]][s[m+1][iind]][(int)((agebegin+ageend)/2.)] += weight[iind]; */
4524: freq[s[m][iind]][s[m+1][iind]][iagemax+3] += weight[iind]; /* Total is in iagemax+3 *//* At age of beginning of transition, where status is known */
1.234 brouard 4525: }
1.251 brouard 4526: } /* end if between passes */
4527: if ((agev[m][iind]>1) && (agev[m][iind]< (iagemax+3)) && (anint[m][iind]!=9999) && (mint[m][iind]!=99) && (j==0)) {
4528: dateintsum=dateintsum+k2; /* on all covariates ?*/
4529: k2cpt++;
4530: /* printf("iind=%ld dateintmean = %lf dateintsum=%lf k2cpt=%lf k2=%lf\n",iind, dateintsum/k2cpt, dateintsum,k2cpt, k2); */
1.234 brouard 4531: }
1.251 brouard 4532: }else{
4533: bool=1;
4534: }/* end bool 2 */
4535: } /* end m */
4536: } /* end bool */
4537: } /* end iind = 1 to imx */
4538: /* prop[s][age] is feeded for any initial and valid live state as well as
4539: freq[s1][s2][age] at single age of beginning the transition, for a combination j1 */
4540:
4541:
4542: /* fprintf(ficresp, "#Count between %.lf/%.lf/%.lf and %.lf/%.lf/%.lf\n",jprev1, mprev1,anprev1,jprev2, mprev2,anprev2);*/
1.265 brouard 4543: if(cptcoveff==0 && nj==1) /* no covariate and first pass */
4544: pstamp(ficresp);
1.251 brouard 4545: if (cptcoveff>0 && j!=0){
1.265 brouard 4546: pstamp(ficresp);
1.251 brouard 4547: printf( "\n#********** Variable ");
4548: fprintf(ficresp, "\n#********** Variable ");
4549: fprintf(ficresphtm, "\n<br/><br/><h3>********** Variable ");
4550: fprintf(ficresphtmfr, "\n<br/><br/><h3>********** Variable ");
4551: fprintf(ficlog, "\n#********** Variable ");
4552: for (z1=1; z1<=cptcoveff; z1++){
4553: if(!FixedV[Tvaraff[z1]]){
4554: printf( "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4555: fprintf(ficresp, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4556: fprintf(ficresphtm, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4557: fprintf(ficresphtmfr, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4558: fprintf(ficlog, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
1.250 brouard 4559: }else{
1.251 brouard 4560: printf( "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4561: fprintf(ficresp, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4562: fprintf(ficresphtm, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4563: fprintf(ficresphtmfr, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4564: fprintf(ficlog, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4565: }
4566: }
4567: printf( "**********\n#");
4568: fprintf(ficresp, "**********\n#");
4569: fprintf(ficresphtm, "**********</h3>\n");
4570: fprintf(ficresphtmfr, "**********</h3>\n");
4571: fprintf(ficlog, "**********\n");
4572: }
4573: fprintf(ficresphtm,"<table style=\"text-align:center; border: 1px solid\">");
1.265 brouard 4574: if((cptcoveff==0 && nj==1)|| nj==2 ) /* no covariate and first pass */
4575: fprintf(ficresp, " Age");
4576: if(nj==2) for (z1=1; z1<=cptcoveff; z1++) fprintf(ficresp, " V%d=%d",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
1.251 brouard 4577: for(i=1; i<=nlstate;i++) {
1.265 brouard 4578: if((cptcoveff==0 && nj==1)|| nj==2 ) fprintf(ficresp," Prev(%d) N(%d) N ",i,i);
1.251 brouard 4579: fprintf(ficresphtm, "<th>Age</th><th>Prev(%d)</th><th>N(%d)</th><th>N</th>",i,i);
4580: }
1.265 brouard 4581: if((cptcoveff==0 && nj==1)|| nj==2 ) fprintf(ficresp, "\n");
1.251 brouard 4582: fprintf(ficresphtm, "\n");
4583:
4584: /* Header of frequency table by age */
4585: fprintf(ficresphtmfr,"<table style=\"text-align:center; border: 1px solid\">");
4586: fprintf(ficresphtmfr,"<th>Age</th> ");
1.265 brouard 4587: for(s2=-1; s2 <=nlstate+ndeath; s2++){
1.251 brouard 4588: for(m=-1; m <=nlstate+ndeath; m++){
1.265 brouard 4589: if(s2!=0 && m!=0)
4590: fprintf(ficresphtmfr,"<th>%d%d</th> ",s2,m);
1.240 brouard 4591: }
1.226 brouard 4592: }
1.251 brouard 4593: fprintf(ficresphtmfr, "\n");
4594:
4595: /* For each age */
4596: for(iage=iagemin; iage <= iagemax+3; iage++){
4597: fprintf(ficresphtm,"<tr>");
4598: if(iage==iagemax+1){
4599: fprintf(ficlog,"1");
4600: fprintf(ficresphtmfr,"<tr><th>0</th> ");
4601: }else if(iage==iagemax+2){
4602: fprintf(ficlog,"0");
4603: fprintf(ficresphtmfr,"<tr><th>Unknown</th> ");
4604: }else if(iage==iagemax+3){
4605: fprintf(ficlog,"Total");
4606: fprintf(ficresphtmfr,"<tr><th>Total</th> ");
4607: }else{
1.240 brouard 4608: if(first==1){
1.251 brouard 4609: first=0;
4610: printf("See log file for details...\n");
4611: }
4612: fprintf(ficresphtmfr,"<tr><th>%d</th> ",iage);
4613: fprintf(ficlog,"Age %d", iage);
4614: }
1.265 brouard 4615: for(s1=1; s1 <=nlstate ; s1++){
4616: for(m=-1, pp[s1]=0; m <=nlstate+ndeath ; m++)
4617: pp[s1] += freq[s1][m][iage];
1.251 brouard 4618: }
1.265 brouard 4619: for(s1=1; s1 <=nlstate ; s1++){
1.251 brouard 4620: for(m=-1, pos=0; m <=0 ; m++)
1.265 brouard 4621: pos += freq[s1][m][iage];
4622: if(pp[s1]>=1.e-10){
1.251 brouard 4623: if(first==1){
1.265 brouard 4624: printf(" %d.=%.0f loss[%d]=%.1f%%",s1,pp[s1],s1,100*pos/pp[s1]);
1.251 brouard 4625: }
1.265 brouard 4626: fprintf(ficlog," %d.=%.0f loss[%d]=%.1f%%",s1,pp[s1],s1,100*pos/pp[s1]);
1.251 brouard 4627: }else{
4628: if(first==1)
1.265 brouard 4629: printf(" %d.=%.0f loss[%d]=NaNQ%%",s1,pp[s1],s1);
4630: fprintf(ficlog," %d.=%.0f loss[%d]=NaNQ%%",s1,pp[s1],s1);
1.240 brouard 4631: }
4632: }
4633:
1.265 brouard 4634: for(s1=1; s1 <=nlstate ; s1++){
4635: /* posprop[s1]=0; */
4636: for(m=0, pp[s1]=0; m <=nlstate+ndeath; m++)/* Summing on all ages */
4637: pp[s1] += freq[s1][m][iage];
4638: } /* pp[s1] is the total number of transitions starting from state s1 and any ending status until this age */
4639:
4640: for(s1=1,pos=0, pospropta=0.; s1 <=nlstate ; s1++){
4641: pos += pp[s1]; /* pos is the total number of transitions until this age */
4642: posprop[s1] += prop[s1][iage]; /* prop is the number of transitions from a live state
4643: from s1 at age iage prop[s[m][iind]][(int)agev[m][iind]] += weight[iind] */
4644: pospropta += prop[s1][iage]; /* prop is the number of transitions from a live state
4645: from s1 at age iage prop[s[m][iind]][(int)agev[m][iind]] += weight[iind] */
4646: }
4647:
4648: /* Writing ficresp */
4649: if(cptcoveff==0 && nj==1){ /* no covariate and first pass */
4650: if( iage <= iagemax){
4651: fprintf(ficresp," %d",iage);
4652: }
4653: }else if( nj==2){
4654: if( iage <= iagemax){
4655: fprintf(ficresp," %d",iage);
4656: for (z1=1; z1<=cptcoveff; z1++) fprintf(ficresp, " %d %d",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
4657: }
1.240 brouard 4658: }
1.265 brouard 4659: for(s1=1; s1 <=nlstate ; s1++){
1.240 brouard 4660: if(pos>=1.e-5){
1.251 brouard 4661: if(first==1)
1.265 brouard 4662: printf(" %d.=%.0f prev[%d]=%.1f%%",s1,pp[s1],s1,100*pp[s1]/pos);
4663: fprintf(ficlog," %d.=%.0f prev[%d]=%.1f%%",s1,pp[s1],s1,100*pp[s1]/pos);
1.251 brouard 4664: }else{
4665: if(first==1)
1.265 brouard 4666: printf(" %d.=%.0f prev[%d]=NaNQ%%",s1,pp[s1],s1);
4667: fprintf(ficlog," %d.=%.0f prev[%d]=NaNQ%%",s1,pp[s1],s1);
1.251 brouard 4668: }
4669: if( iage <= iagemax){
4670: if(pos>=1.e-5){
1.265 brouard 4671: if(cptcoveff==0 && nj==1){ /* no covariate and first pass */
4672: fprintf(ficresp," %.5f %.0f %.0f",prop[s1][iage]/pospropta, prop[s1][iage],pospropta);
4673: }else if( nj==2){
4674: fprintf(ficresp," %.5f %.0f %.0f",prop[s1][iage]/pospropta, prop[s1][iage],pospropta);
4675: }
4676: fprintf(ficresphtm,"<th>%d</th><td>%.5f</td><td>%.0f</td><td>%.0f</td>",iage,prop[s1][iage]/pospropta, prop[s1][iage],pospropta);
4677: /*probs[iage][s1][j1]= pp[s1]/pos;*/
4678: /*printf("\niage=%d s1=%d j1=%d %.5f %.0f %.0f %f",iage,s1,j1,pp[s1]/pos, pp[s1],pos,probs[iage][s1][j1]);*/
4679: } else{
4680: if((cptcoveff==0 && nj==1)|| nj==2 ) fprintf(ficresp," NaNq %.0f %.0f",prop[s1][iage],pospropta);
4681: fprintf(ficresphtm,"<th>%d</th><td>NaNq</td><td>%.0f</td><td>%.0f</td>",iage, prop[s1][iage],pospropta);
1.251 brouard 4682: }
1.240 brouard 4683: }
1.265 brouard 4684: pospropt[s1] +=posprop[s1];
4685: } /* end loop s1 */
1.251 brouard 4686: /* pospropt=0.; */
1.265 brouard 4687: for(s1=-1; s1 <=nlstate+ndeath; s1++){
1.251 brouard 4688: for(m=-1; m <=nlstate+ndeath; m++){
1.265 brouard 4689: if(freq[s1][m][iage] !=0 ) { /* minimizing output */
1.251 brouard 4690: if(first==1){
1.265 brouard 4691: printf(" %d%d=%.0f",s1,m,freq[s1][m][iage]);
1.251 brouard 4692: }
1.265 brouard 4693: /* printf(" %d%d=%.0f",s1,m,freq[s1][m][iage]); */
4694: fprintf(ficlog," %d%d=%.0f",s1,m,freq[s1][m][iage]);
1.251 brouard 4695: }
1.265 brouard 4696: if(s1!=0 && m!=0)
4697: fprintf(ficresphtmfr,"<td>%.0f</td> ",freq[s1][m][iage]);
1.240 brouard 4698: }
1.265 brouard 4699: } /* end loop s1 */
1.251 brouard 4700: posproptt=0.;
1.265 brouard 4701: for(s1=1; s1 <=nlstate; s1++){
4702: posproptt += pospropt[s1];
1.251 brouard 4703: }
4704: fprintf(ficresphtmfr,"</tr>\n ");
1.265 brouard 4705: fprintf(ficresphtm,"</tr>\n");
4706: if((cptcoveff==0 && nj==1)|| nj==2 ) {
4707: if(iage <= iagemax)
4708: fprintf(ficresp,"\n");
1.240 brouard 4709: }
1.251 brouard 4710: if(first==1)
4711: printf("Others in log...\n");
4712: fprintf(ficlog,"\n");
4713: } /* end loop age iage */
1.265 brouard 4714:
1.251 brouard 4715: fprintf(ficresphtm,"<tr><th>Tot</th>");
1.265 brouard 4716: for(s1=1; s1 <=nlstate ; s1++){
1.251 brouard 4717: if(posproptt < 1.e-5){
1.265 brouard 4718: fprintf(ficresphtm,"<td>Nanq</td><td>%.0f</td><td>%.0f</td>",pospropt[s1],posproptt);
1.251 brouard 4719: }else{
1.265 brouard 4720: fprintf(ficresphtm,"<td>%.5f</td><td>%.0f</td><td>%.0f</td>",pospropt[s1]/posproptt,pospropt[s1],posproptt);
1.240 brouard 4721: }
1.226 brouard 4722: }
1.251 brouard 4723: fprintf(ficresphtm,"</tr>\n");
4724: fprintf(ficresphtm,"</table>\n");
4725: fprintf(ficresphtmfr,"</table>\n");
1.226 brouard 4726: if(posproptt < 1.e-5){
1.251 brouard 4727: fprintf(ficresphtm,"\n <p><b> This combination (%d) is not valid and no result will be produced</b></p>",j1);
4728: fprintf(ficresphtmfr,"\n <p><b> This combination (%d) is not valid and no result will be produced</b></p>",j1);
1.260 brouard 4729: fprintf(ficlog,"# This combination (%d) is not valid and no result will be produced\n",j1);
4730: printf("# This combination (%d) is not valid and no result will be produced\n",j1);
1.251 brouard 4731: invalidvarcomb[j1]=1;
1.226 brouard 4732: }else{
1.251 brouard 4733: fprintf(ficresphtm,"\n <p> This combination (%d) is valid and result will be produced.</p>",j1);
4734: invalidvarcomb[j1]=0;
1.226 brouard 4735: }
1.251 brouard 4736: fprintf(ficresphtmfr,"</table>\n");
4737: fprintf(ficlog,"\n");
4738: if(j!=0){
4739: printf("#Freqsummary: Starting values for combination j1=%d:\n", j1);
1.265 brouard 4740: for(i=1,s1=1; i <=nlstate; i++){
1.251 brouard 4741: for(k=1; k <=(nlstate+ndeath); k++){
4742: if (k != i) {
1.265 brouard 4743: for(jj=1; jj <=ncovmodel; jj++){ /* For counting s1 */
1.253 brouard 4744: if(jj==1){ /* Constant case (in fact cste + age) */
1.251 brouard 4745: if(j1==1){ /* All dummy covariates to zero */
4746: freq[i][k][iagemax+4]=freq[i][k][iagemax+3]; /* Stores case 0 0 0 */
4747: freq[i][i][iagemax+4]=freq[i][i][iagemax+3]; /* Stores case 0 0 0 */
1.252 brouard 4748: printf("%d%d ",i,k);
4749: fprintf(ficlog,"%d%d ",i,k);
1.265 brouard 4750: printf("%12.7f ln(%.0f/%.0f)= %f, OR=%f sd=%f \n",p[s1],freq[i][k][iagemax+3],freq[i][i][iagemax+3], log(freq[i][k][iagemax+3]/freq[i][i][iagemax+3]),freq[i][k][iagemax+3]/freq[i][i][iagemax+3], sqrt(1/freq[i][k][iagemax+3]+1/freq[i][i][iagemax+3]));
4751: fprintf(ficlog,"%12.7f ln(%.0f/%.0f)= %12.7f \n",p[s1],freq[i][k][iagemax+3],freq[i][i][iagemax+3], log(freq[i][k][iagemax+3]/freq[i][i][iagemax+3]));
4752: pstart[s1]= log(freq[i][k][iagemax+3]/freq[i][i][iagemax+3]);
1.251 brouard 4753: }
1.253 brouard 4754: }else if((j1==1) && (jj==2 || nagesqr==1)){ /* age or age*age parameter without covariate V4*age (to be done later) */
4755: for(iage=iagemin; iage <= iagemax+3; iage++){
4756: x[iage]= (double)iage;
4757: y[iage]= log(freq[i][k][iage]/freq[i][i][iage]);
1.265 brouard 4758: /* printf("i=%d, k=%d, s1=%d, j1=%d, jj=%d, y[%d]=%f\n",i,k,s1,j1,jj, iage, y[iage]); */
1.253 brouard 4759: }
1.268 ! brouard 4760: /* Some are not finite, but linreg will ignore these ages */
! 4761: no=0;
1.253 brouard 4762: linreg(iagemin,iagemax,&no,x,y,&a,&b,&r, &sa, &sb ); /* y= a+b*x with standard errors */
1.265 brouard 4763: pstart[s1]=b;
4764: pstart[s1-1]=a;
1.252 brouard 4765: }else if( j1!=1 && (j1==2 || (log(j1-1.)/log(2.)-(int)(log(j1-1.)/log(2.))) <0.010) && ( TvarsDind[(int)(log(j1-1.)/log(2.))+1]+2+nagesqr == jj) && Dummy[jj-2-nagesqr]==0){ /* We want only if the position, jj, in model corresponds to unique covariate equal to 1 in j1 combination */
4766: printf("j1=%d, jj=%d, (int)(log(j1-1.)/log(2.))+1=%d, TvarsDind[(int)(log(j1-1.)/log(2.))+1]=%d\n",j1, jj,(int)(log(j1-1.)/log(2.))+1,TvarsDind[(int)(log(j1-1.)/log(2.))+1]);
4767: printf("j1=%d, jj=%d, (log(j1-1.)/log(2.))+1=%f, TvarsDind[(int)(log(j1-1.)/log(2.))+1]=%d\n",j1, jj,(log(j1-1.)/log(2.))+1,TvarsDind[(int)(log(j1-1.)/log(2.))+1]);
1.265 brouard 4768: pstart[s1]= log((freq[i][k][iagemax+3]/freq[i][i][iagemax+3])/(freq[i][k][iagemax+4]/freq[i][i][iagemax+4]));
1.252 brouard 4769: printf("%d%d ",i,k);
4770: fprintf(ficlog,"%d%d ",i,k);
1.265 brouard 4771: printf("s1=%d,i=%d,k=%d,p[%d]=%12.7f ln((%.0f/%.0f)/(%.0f/%.0f))= %f, OR=%f sd=%f \n",s1,i,k,s1,p[s1],freq[i][k][iagemax+3],freq[i][i][iagemax+3],freq[i][k][iagemax+4],freq[i][i][iagemax+4], log((freq[i][k][iagemax+3]/freq[i][i][iagemax+3])/(freq[i][k][iagemax+4]/freq[i][i][iagemax+4])),(freq[i][k][iagemax+3]/freq[i][i][iagemax+3])/(freq[i][k][iagemax+4]/freq[i][i][iagemax+4]), sqrt(1/freq[i][k][iagemax+3]+1/freq[i][i][iagemax+3]+1/freq[i][k][iagemax+4]+1/freq[i][i][iagemax+4]));
1.251 brouard 4772: }else{ /* Other cases, like quantitative fixed or varying covariates */
4773: ;
4774: }
4775: /* printf("%12.7f )", param[i][jj][k]); */
4776: /* fprintf(ficlog,"%12.7f )", param[i][jj][k]); */
1.265 brouard 4777: s1++;
1.251 brouard 4778: } /* end jj */
4779: } /* end k!= i */
4780: } /* end k */
1.265 brouard 4781: } /* end i, s1 */
1.251 brouard 4782: } /* end j !=0 */
4783: } /* end selected combination of covariate j1 */
4784: if(j==0){ /* We can estimate starting values from the occurences in each case */
4785: printf("#Freqsummary: Starting values for the constants:\n");
4786: fprintf(ficlog,"\n");
1.265 brouard 4787: for(i=1,s1=1; i <=nlstate; i++){
1.251 brouard 4788: for(k=1; k <=(nlstate+ndeath); k++){
4789: if (k != i) {
4790: printf("%d%d ",i,k);
4791: fprintf(ficlog,"%d%d ",i,k);
4792: for(jj=1; jj <=ncovmodel; jj++){
1.265 brouard 4793: pstart[s1]=p[s1]; /* Setting pstart to p values by default */
1.253 brouard 4794: if(jj==1){ /* Age has to be done */
1.265 brouard 4795: pstart[s1]= log(freq[i][k][iagemax+3]/freq[i][i][iagemax+3]);
4796: printf("%12.7f ln(%.0f/%.0f)= %12.7f ",p[s1],freq[i][k][iagemax+3],freq[i][i][iagemax+3], log(freq[i][k][iagemax+3]/freq[i][i][iagemax+3]));
4797: fprintf(ficlog,"%12.7f ln(%.0f/%.0f)= %12.7f ",p[s1],freq[i][k][iagemax+3],freq[i][i][iagemax+3], log(freq[i][k][iagemax+3]/freq[i][i][iagemax+3]));
1.251 brouard 4798: }
4799: /* printf("%12.7f )", param[i][jj][k]); */
4800: /* fprintf(ficlog,"%12.7f )", param[i][jj][k]); */
1.265 brouard 4801: s1++;
1.250 brouard 4802: }
1.251 brouard 4803: printf("\n");
4804: fprintf(ficlog,"\n");
1.250 brouard 4805: }
4806: }
4807: }
1.251 brouard 4808: printf("#Freqsummary\n");
4809: fprintf(ficlog,"\n");
1.265 brouard 4810: for(s1=-1; s1 <=nlstate+ndeath; s1++){
4811: for(s2=-1; s2 <=nlstate+ndeath; s2++){
4812: /* param[i]|j][k]= freq[s1][s2][iagemax+3] */
4813: printf(" %d%d=%.0f",s1,s2,freq[s1][s2][iagemax+3]);
4814: fprintf(ficlog," %d%d=%.0f",s1,s2,freq[s1][s2][iagemax+3]);
4815: /* if(freq[s1][s2][iage] !=0 ) { /\* minimizing output *\/ */
4816: /* printf(" %d%d=%.0f",s1,s2,freq[s1][s2][iagemax+3]); */
4817: /* fprintf(ficlog," %d%d=%.0f",s1,s2,freq[s1][s2][iagemax+3]); */
1.251 brouard 4818: /* } */
4819: }
1.265 brouard 4820: } /* end loop s1 */
1.251 brouard 4821:
4822: printf("\n");
4823: fprintf(ficlog,"\n");
4824: } /* end j=0 */
1.249 brouard 4825: } /* end j */
1.252 brouard 4826:
1.253 brouard 4827: if(mle == -2){ /* We want to use these values as starting values */
1.252 brouard 4828: for(i=1, jk=1; i <=nlstate; i++){
4829: for(j=1; j <=nlstate+ndeath; j++){
4830: if(j!=i){
4831: /*ca[0]= k+'a'-1;ca[1]='\0';*/
4832: printf("%1d%1d",i,j);
4833: fprintf(ficparo,"%1d%1d",i,j);
4834: for(k=1; k<=ncovmodel;k++){
4835: /* printf(" %lf",param[i][j][k]); */
4836: /* fprintf(ficparo," %lf",param[i][j][k]); */
4837: p[jk]=pstart[jk];
4838: printf(" %f ",pstart[jk]);
4839: fprintf(ficparo," %f ",pstart[jk]);
4840: jk++;
4841: }
4842: printf("\n");
4843: fprintf(ficparo,"\n");
4844: }
4845: }
4846: }
4847: } /* end mle=-2 */
1.226 brouard 4848: dateintmean=dateintsum/k2cpt;
1.240 brouard 4849:
1.226 brouard 4850: fclose(ficresp);
4851: fclose(ficresphtm);
4852: fclose(ficresphtmfr);
4853: free_vector(meanq,1,nqfveff);
4854: free_matrix(meanqt,1,lastpass,1,nqtveff);
1.253 brouard 4855: free_vector(x, iagemin-AGEMARGE, iagemax+4+AGEMARGE);
4856: free_vector(y, iagemin-AGEMARGE, iagemax+4+AGEMARGE);
1.251 brouard 4857: free_ma3x(freq,-5,nlstate+ndeath,-5,nlstate+ndeath, iagemin-AGEMARGE, iagemax+4+AGEMARGE);
1.226 brouard 4858: free_vector(pospropt,1,nlstate);
4859: free_vector(posprop,1,nlstate);
1.251 brouard 4860: free_matrix(prop,1,nlstate,iagemin-AGEMARGE, iagemax+4+AGEMARGE);
1.226 brouard 4861: free_vector(pp,1,nlstate);
4862: /* End of freqsummary */
4863: }
1.126 brouard 4864:
1.268 ! brouard 4865: /* Simple linear regression */
! 4866: int linreg(int ifi, int ila, int *no, const double x[], const double y[], double* a, double* b, double* r, double* sa, double * sb) {
! 4867:
! 4868: /* y=a+bx regression */
! 4869: double sumx = 0.0; /* sum of x */
! 4870: double sumx2 = 0.0; /* sum of x**2 */
! 4871: double sumxy = 0.0; /* sum of x * y */
! 4872: double sumy = 0.0; /* sum of y */
! 4873: double sumy2 = 0.0; /* sum of y**2 */
! 4874: double sume2 = 0.0; /* sum of square or residuals */
! 4875: double yhat;
! 4876:
! 4877: double denom=0;
! 4878: int i;
! 4879: int ne=*no;
! 4880:
! 4881: for ( i=ifi, ne=0;i<=ila;i++) {
! 4882: if(!isfinite(x[i]) || !isfinite(y[i])){
! 4883: /* printf(" x[%d]=%f, y[%d]=%f\n",i,x[i],i,y[i]); */
! 4884: continue;
! 4885: }
! 4886: ne=ne+1;
! 4887: sumx += x[i];
! 4888: sumx2 += x[i]*x[i];
! 4889: sumxy += x[i] * y[i];
! 4890: sumy += y[i];
! 4891: sumy2 += y[i]*y[i];
! 4892: denom = (ne * sumx2 - sumx*sumx);
! 4893: /* printf("ne=%d, i=%d,x[%d]=%f, y[%d]=%f sumx=%f, sumx2=%f, sumxy=%f, sumy=%f, sumy2=%f, denom=%f\n",ne,i,i,x[i],i,y[i], sumx, sumx2,sumxy, sumy, sumy2,denom); */
! 4894: }
! 4895:
! 4896: denom = (ne * sumx2 - sumx*sumx);
! 4897: if (denom == 0) {
! 4898: // vertical, slope m is infinity
! 4899: *b = INFINITY;
! 4900: *a = 0;
! 4901: if (r) *r = 0;
! 4902: return 1;
! 4903: }
! 4904:
! 4905: *b = (ne * sumxy - sumx * sumy) / denom;
! 4906: *a = (sumy * sumx2 - sumx * sumxy) / denom;
! 4907: if (r!=NULL) {
! 4908: *r = (sumxy - sumx * sumy / ne) / /* compute correlation coeff */
! 4909: sqrt((sumx2 - sumx*sumx/ne) *
! 4910: (sumy2 - sumy*sumy/ne));
! 4911: }
! 4912: *no=ne;
! 4913: for ( i=ifi, ne=0;i<=ila;i++) {
! 4914: if(!isfinite(x[i]) || !isfinite(y[i])){
! 4915: /* printf(" x[%d]=%f, y[%d]=%f\n",i,x[i],i,y[i]); */
! 4916: continue;
! 4917: }
! 4918: ne=ne+1;
! 4919: yhat = y[i] - *a -*b* x[i];
! 4920: sume2 += yhat * yhat ;
! 4921:
! 4922: denom = (ne * sumx2 - sumx*sumx);
! 4923: /* printf("ne=%d, i=%d,x[%d]=%f, y[%d]=%f sumx=%f, sumx2=%f, sumxy=%f, sumy=%f, sumy2=%f, denom=%f\n",ne,i,i,x[i],i,y[i], sumx, sumx2,sumxy, sumy, sumy2,denom); */
! 4924: }
! 4925: *sb = sqrt(sume2/(double)(ne-2)/(sumx2 - sumx * sumx /(double)ne));
! 4926: *sa= *sb * sqrt(sumx2/ne);
! 4927:
! 4928: return 0;
! 4929: }
! 4930:
1.126 brouard 4931: /************ Prevalence ********************/
1.227 brouard 4932: 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)
4933: {
4934: /* Compute observed prevalence between dateprev1 and dateprev2 by counting the number of people
4935: in each health status at the date of interview (if between dateprev1 and dateprev2).
4936: We still use firstpass and lastpass as another selection.
4937: */
1.126 brouard 4938:
1.227 brouard 4939: int i, m, jk, j1, bool, z1,j, iv;
4940: int mi; /* Effective wave */
4941: int iage;
4942: double agebegin, ageend;
4943:
4944: double **prop;
4945: double posprop;
4946: double y2; /* in fractional years */
4947: int iagemin, iagemax;
4948: int first; /** to stop verbosity which is redirected to log file */
4949:
4950: iagemin= (int) agemin;
4951: iagemax= (int) agemax;
4952: /*pp=vector(1,nlstate);*/
1.251 brouard 4953: prop=matrix(1,nlstate,iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.227 brouard 4954: /* freq=ma3x(-1,nlstate+ndeath,-1,nlstate+ndeath,iagemin,iagemax+3);*/
4955: j1=0;
1.222 brouard 4956:
1.227 brouard 4957: /*j=cptcoveff;*/
4958: if (cptcovn<1) {j=1;ncodemax[1]=1;}
1.222 brouard 4959:
1.227 brouard 4960: first=1;
4961: for(j1=1; j1<= (int) pow(2,cptcoveff);j1++){ /* For each combination of covariate */
4962: for (i=1; i<=nlstate; i++)
1.251 brouard 4963: for(iage=iagemin-AGEMARGE; iage <= iagemax+4+AGEMARGE; iage++)
1.227 brouard 4964: prop[i][iage]=0.0;
4965: printf("Prevalence combination of varying and fixed dummies %d\n",j1);
4966: /* fprintf(ficlog," V%d=%d ",Tvaraff[j1],nbcode[Tvaraff[j1]][codtabm(k,j1)]); */
4967: fprintf(ficlog,"Prevalence combination of varying and fixed dummies %d\n",j1);
4968:
4969: for (i=1; i<=imx; i++) { /* Each individual */
4970: bool=1;
4971: /* for(m=firstpass; m<=lastpass; m++){/\* Other selection (we can limit to certain interviews*\/ */
4972: for(mi=1; mi<wav[i];mi++){ /* For this wave too look where individual can be counted V4=0 V3=0 */
4973: m=mw[mi][i];
4974: /* Tmodelind[z1]=k is the position of the varying covariate in the model, but which # within 1 to ntv? */
4975: /* Tvar[Tmodelind[z1]] is the n of Vn; n-ncovcol-nqv is the first time varying covariate or iv */
4976: for (z1=1; z1<=cptcoveff; z1++){
4977: if( Fixed[Tmodelind[z1]]==1){
4978: iv= Tvar[Tmodelind[z1]]-ncovcol-nqv;
4979: if (cotvar[m][iv][i]!= nbcode[Tvaraff[z1]][codtabm(j1,z1)]) /* iv=1 to ntv, right modality */
4980: bool=0;
4981: }else if( Fixed[Tmodelind[z1]]== 0) /* fixed */
4982: if (covar[Tvaraff[z1]][i]!= nbcode[Tvaraff[z1]][codtabm(j1,z1)]) {
4983: bool=0;
4984: }
4985: }
4986: if(bool==1){ /* Otherwise we skip that wave/person */
4987: agebegin=agev[m][i]; /* Age at beginning of wave before transition*/
4988: /* ageend=agev[m][i]+(dh[m][i])*stepm/YEARM; /\* Age at end of wave and transition *\/ */
4989: if(m >=firstpass && m <=lastpass){
4990: y2=anint[m][i]+(mint[m][i]/12.); /* Fractional date in year */
4991: if ((y2>=dateprev1) && (y2<=dateprev2)) { /* Here is the main selection (fractional years) */
4992: if(agev[m][i]==0) agev[m][i]=iagemax+1;
4993: if(agev[m][i]==1) agev[m][i]=iagemax+2;
1.251 brouard 4994: if((int)agev[m][i] <iagemin-AGEMARGE || (int)agev[m][i] >iagemax+4+AGEMARGE){
1.227 brouard 4995: 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);
4996: exit(1);
4997: }
4998: if (s[m][i]>0 && s[m][i]<=nlstate) {
4999: /*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]]);*/
5000: prop[s[m][i]][(int)agev[m][i]] += weight[i];/* At age of beginning of transition, where status is known */
5001: prop[s[m][i]][iagemax+3] += weight[i];
5002: } /* end valid statuses */
5003: } /* end selection of dates */
5004: } /* end selection of waves */
5005: } /* end bool */
5006: } /* end wave */
5007: } /* end individual */
5008: for(i=iagemin; i <= iagemax+3; i++){
5009: for(jk=1,posprop=0; jk <=nlstate ; jk++) {
5010: posprop += prop[jk][i];
5011: }
5012:
5013: for(jk=1; jk <=nlstate ; jk++){
5014: if( i <= iagemax){
5015: if(posprop>=1.e-5){
5016: probs[i][jk][j1]= prop[jk][i]/posprop;
5017: } else{
5018: if(first==1){
5019: first=0;
1.266 brouard 5020: printf("Warning Observed prevalence doesn't sum to 1 for state %d: probs[%d][%d][%d]=%lf because of lack of cases\nSee others in log file...\n",jk,i,jk, j1,probs[i][jk][j1]);
5021: fprintf(ficlog,"Warning Observed prevalence doesn't sum to 1 for state %d: probs[%d][%d][%d]=%lf because of lack of cases\nSee others in log file...\n",jk,i,jk, j1,probs[i][jk][j1]);
5022: }else{
5023: fprintf(ficlog,"Warning Observed prevalence doesn't sum to 1 for state %d: probs[%d][%d][%d]=%lf because of lack of cases\nSee others in log file...\n",jk,i,jk, j1,probs[i][jk][j1]);
1.227 brouard 5024: }
5025: }
5026: }
5027: }/* end jk */
5028: }/* end i */
1.222 brouard 5029: /*} *//* end i1 */
1.227 brouard 5030: } /* end j1 */
1.222 brouard 5031:
1.227 brouard 5032: /* free_ma3x(freq,-1,nlstate+ndeath,-1,nlstate+ndeath, iagemin, iagemax+3);*/
5033: /*free_vector(pp,1,nlstate);*/
1.251 brouard 5034: free_matrix(prop,1,nlstate, iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.227 brouard 5035: } /* End of prevalence */
1.126 brouard 5036:
5037: /************* Waves Concatenation ***************/
5038:
5039: 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)
5040: {
5041: /* Concatenates waves: wav[i] is the number of effective (useful waves) of individual i.
5042: Death is a valid wave (if date is known).
5043: mw[mi][i] is the mi (mi=1 to wav[i]) effective wave of individual i
5044: dh[m][i] or dh[mw[mi][i]][i] is the delay between two effective waves m=mw[mi][i]
5045: and mw[mi+1][i]. dh depends on stepm.
1.227 brouard 5046: */
1.126 brouard 5047:
1.224 brouard 5048: int i=0, mi=0, m=0, mli=0;
1.126 brouard 5049: /* int j, k=0,jk, ju, jl,jmin=1e+5, jmax=-1;
5050: double sum=0., jmean=0.;*/
1.224 brouard 5051: int first=0, firstwo=0, firsthree=0, firstfour=0, firstfiv=0;
1.126 brouard 5052: int j, k=0,jk, ju, jl;
5053: double sum=0.;
5054: first=0;
1.214 brouard 5055: firstwo=0;
1.217 brouard 5056: firsthree=0;
1.218 brouard 5057: firstfour=0;
1.164 brouard 5058: jmin=100000;
1.126 brouard 5059: jmax=-1;
5060: jmean=0.;
1.224 brouard 5061:
5062: /* Treating live states */
1.214 brouard 5063: for(i=1; i<=imx; i++){ /* For simple cases and if state is death */
1.224 brouard 5064: mi=0; /* First valid wave */
1.227 brouard 5065: mli=0; /* Last valid wave */
1.126 brouard 5066: m=firstpass;
1.214 brouard 5067: while(s[m][i] <= nlstate){ /* a live state */
1.227 brouard 5068: 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 */
5069: mli=m-1;/* mw[++mi][i]=m-1; */
5070: }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 */
5071: mw[++mi][i]=m;
5072: mli=m;
1.224 brouard 5073: } /* else might be a useless wave -1 and mi is not incremented and mw[mi] not updated */
5074: if(m < lastpass){ /* m < lastpass, standard case */
1.227 brouard 5075: m++; /* mi gives the "effective" current wave, m the current wave, go to next wave by incrementing m */
1.216 brouard 5076: }
1.227 brouard 5077: else{ /* m >= lastpass, eventual special issue with warning */
1.224 brouard 5078: #ifdef UNKNOWNSTATUSNOTCONTRIBUTING
1.227 brouard 5079: break;
1.224 brouard 5080: #else
1.227 brouard 5081: if(s[m][i]==-1 && (int) andc[i] == 9999 && (int)anint[m][i] != 9999){
5082: if(firsthree == 0){
1.262 brouard 5083: printf("Information! Unknown status for individual %ld line=%d occurred at last wave %d at known date %d/%d. Please, check if your unknown date of death %d/%d means a live state %d at wave %d. This case(%d)/wave(%d) contributes to the likelihood as 1-p%d%d .\nOthers in log file only\n",num[i],i,lastpass,(int)mint[m][i],(int)anint[m][i], (int) moisdc[i], (int) andc[i], s[m][i], m, i, m, s[m][i], nlstate+ndeath);
1.227 brouard 5084: firsthree=1;
5085: }
1.262 brouard 5086: fprintf(ficlog,"Information! Unknown status for individual %ld line=%d occurred at last wave %d at known date %d/%d. Please, check if your unknown date of death %d/%d means a live state %d at wave %d. This case(%d)/wave(%d) contributes to the likelihood as 1-p%d%d .\n",num[i],i,lastpass,(int)mint[m][i],(int)anint[m][i], (int) moisdc[i], (int) andc[i], s[m][i], m, i, m, s[m][i], nlstate+ndeath);
1.227 brouard 5087: mw[++mi][i]=m;
5088: mli=m;
5089: }
5090: if(s[m][i]==-2){ /* Vital status is really unknown */
5091: nbwarn++;
5092: if((int)anint[m][i] == 9999){ /* Has the vital status really been verified? */
5093: 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);
5094: 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);
5095: }
5096: break;
5097: }
5098: break;
1.224 brouard 5099: #endif
1.227 brouard 5100: }/* End m >= lastpass */
1.126 brouard 5101: }/* end while */
1.224 brouard 5102:
1.227 brouard 5103: /* 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 5104: /* After last pass */
1.224 brouard 5105: /* Treating death states */
1.214 brouard 5106: if (s[m][i] > nlstate){ /* In a death state */
1.227 brouard 5107: /* if( mint[m][i]==mdc[m][i] && anint[m][i]==andc[m][i]){ /\* same date of death and date of interview *\/ */
5108: /* } */
1.126 brouard 5109: mi++; /* Death is another wave */
5110: /* if(mi==0) never been interviewed correctly before death */
1.227 brouard 5111: /* Only death is a correct wave */
1.126 brouard 5112: mw[mi][i]=m;
1.257 brouard 5113: } /* else not in a death state */
1.224 brouard 5114: #ifndef DISPATCHINGKNOWNDEATHAFTERLASTWAVE
1.257 brouard 5115: else if ((int) andc[i] != 9999) { /* Date of death is known */
1.218 brouard 5116: if ((int)anint[m][i]!= 9999) { /* date of last interview is known */
1.227 brouard 5117: 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 */
5118: nbwarn++;
5119: if(firstfiv==0){
5120: 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 );
5121: firstfiv=1;
5122: }else{
5123: 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 );
5124: }
5125: }else{ /* Death occured afer last wave potential bias */
5126: nberr++;
5127: if(firstwo==0){
1.257 brouard 5128: printf("Error! Death for individual %ld line=%d occurred at %d/%d after last wave %d interviewed at %d/%d. Potential bias if other individuals are still alive at this date but ignored. This case (%d)/wave (%d) is skipped, no contribution to likelihood. Please add a new fictive wave at the date of last vital status scan, with a dead status or alive but unknown state status (-1). See documentation\nOthers in log file only\n",num[i],i,(int) moisdc[i], (int) andc[i], lastpass,(int)mint[m][i],(int)anint[m][i], i,m );
1.227 brouard 5129: firstwo=1;
5130: }
1.257 brouard 5131: fprintf(ficlog,"Error! Death for individual %ld line=%d occurred at %d/%d after last wave %d interviewed at %d/%d. Potential bias if other individuals are still alive at this date but ignored. This case (%d)/wave (%d) is skipped, no contribution to likelihood. Please add a new fictive wave at the date of last vital status scan, with a dead status or alive but unknown state status (-1). See documentation\n\n",num[i],i,(int) moisdc[i], (int) andc[i], lastpass,(int)mint[m][i],(int)anint[m][i], i,m );
1.227 brouard 5132: }
1.257 brouard 5133: }else{ /* if date of interview is unknown */
1.227 brouard 5134: /* death is known but not confirmed by death status at any wave */
5135: if(firstfour==0){
5136: 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 );
5137: firstfour=1;
5138: }
5139: 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 5140: }
1.224 brouard 5141: } /* end if date of death is known */
5142: #endif
5143: wav[i]=mi; /* mi should be the last effective wave (or mli) */
5144: /* wav[i]=mw[mi][i]; */
1.126 brouard 5145: if(mi==0){
5146: nbwarn++;
5147: if(first==0){
1.227 brouard 5148: printf("Warning! No valid information for individual %ld line=%d (skipped) and may be others, see log file\n",num[i],i);
5149: first=1;
1.126 brouard 5150: }
5151: if(first==1){
1.227 brouard 5152: fprintf(ficlog,"Warning! No valid information for individual %ld line=%d (skipped)\n",num[i],i);
1.126 brouard 5153: }
5154: } /* end mi==0 */
5155: } /* End individuals */
1.214 brouard 5156: /* wav and mw are no more changed */
1.223 brouard 5157:
1.214 brouard 5158:
1.126 brouard 5159: for(i=1; i<=imx; i++){
5160: for(mi=1; mi<wav[i];mi++){
5161: if (stepm <=0)
1.227 brouard 5162: dh[mi][i]=1;
1.126 brouard 5163: else{
1.260 brouard 5164: if (s[mw[mi+1][i]][i] > nlstate) { /* A death, but what if date is unknown? */
1.227 brouard 5165: if (agedc[i] < 2*AGESUP) {
5166: j= rint(agedc[i]*12-agev[mw[mi][i]][i]*12);
5167: if(j==0) j=1; /* Survives at least one month after exam */
5168: else if(j<0){
5169: nberr++;
5170: 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]);
5171: j=1; /* Temporary Dangerous patch */
5172: 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);
5173: 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]);
5174: 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);
5175: }
5176: k=k+1;
5177: if (j >= jmax){
5178: jmax=j;
5179: ijmax=i;
5180: }
5181: if (j <= jmin){
5182: jmin=j;
5183: ijmin=i;
5184: }
5185: sum=sum+j;
5186: /*if (j<0) printf("j=%d num=%d \n",j,i);*/
5187: /* printf("%d %d %d %d\n", s[mw[mi][i]][i] ,s[mw[mi+1][i]][i],j,i);*/
5188: }
5189: }
5190: else{
5191: j= rint( (agev[mw[mi+1][i]][i]*12 - agev[mw[mi][i]][i]*12));
1.126 brouard 5192: /* 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 5193:
1.227 brouard 5194: k=k+1;
5195: if (j >= jmax) {
5196: jmax=j;
5197: ijmax=i;
5198: }
5199: else if (j <= jmin){
5200: jmin=j;
5201: ijmin=i;
5202: }
5203: /* if (j<10) printf("j=%d jmin=%d num=%d ",j,jmin,i); */
5204: /*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]);*/
5205: if(j<0){
5206: nberr++;
5207: 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]);
5208: 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]);
5209: }
5210: sum=sum+j;
5211: }
5212: jk= j/stepm;
5213: jl= j -jk*stepm;
5214: ju= j -(jk+1)*stepm;
5215: if(mle <=1){ /* only if we use a the linear-interpoloation pseudo-likelihood */
5216: if(jl==0){
5217: dh[mi][i]=jk;
5218: bh[mi][i]=0;
5219: }else{ /* We want a negative bias in order to only have interpolation ie
5220: * to avoid the price of an extra matrix product in likelihood */
5221: dh[mi][i]=jk+1;
5222: bh[mi][i]=ju;
5223: }
5224: }else{
5225: if(jl <= -ju){
5226: dh[mi][i]=jk;
5227: bh[mi][i]=jl; /* bias is positive if real duration
5228: * is higher than the multiple of stepm and negative otherwise.
5229: */
5230: }
5231: else{
5232: dh[mi][i]=jk+1;
5233: bh[mi][i]=ju;
5234: }
5235: if(dh[mi][i]==0){
5236: dh[mi][i]=1; /* At least one step */
5237: bh[mi][i]=ju; /* At least one step */
5238: /* 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);*/
5239: }
5240: } /* end if mle */
1.126 brouard 5241: }
5242: } /* end wave */
5243: }
5244: jmean=sum/k;
5245: 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 5246: 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 5247: }
1.126 brouard 5248:
5249: /*********** Tricode ****************************/
1.220 brouard 5250: void tricode(int *cptcov, int *Tvar, int **nbcode, int imx, int *Ndum)
1.242 brouard 5251: {
5252: /**< Uses cptcovn+2*cptcovprod as the number of covariates */
5253: /* Tvar[i]=atoi(stre); find 'n' in Vn and stores in Tvar. If model=V2+V1 Tvar[1]=2 and Tvar[2]=1
5254: * Boring subroutine which should only output nbcode[Tvar[j]][k]
5255: * Tvar[5] in V2+V1+V3*age+V2*V4 is 4 (V4) even it is a time varying or quantitative variable
5256: * nbcode[Tvar[5]][1]= nbcode[4][1]=0, nbcode[4][2]=1 (usually);
5257: */
1.130 brouard 5258:
1.242 brouard 5259: int ij=1, k=0, j=0, i=0, maxncov=NCOVMAX;
5260: int modmaxcovj=0; /* Modality max of covariates j */
5261: int cptcode=0; /* Modality max of covariates j */
5262: int modmincovj=0; /* Modality min of covariates j */
1.145 brouard 5263:
5264:
1.242 brouard 5265: /* cptcoveff=0; */
5266: /* *cptcov=0; */
1.126 brouard 5267:
1.242 brouard 5268: for (k=1; k <= maxncov; k++) ncodemax[k]=0; /* Horrible constant again replaced by NCOVMAX */
1.126 brouard 5269:
1.242 brouard 5270: /* Loop on covariates without age and products and no quantitative variable */
5271: /* for (j=1; j<=(cptcovs); j++) { /\* From model V1 + V2*age+ V3 + V3*V4 keeps V1 + V3 = 2 only *\/ */
5272: for (k=1; k<=cptcovt; k++) { /* From model V1 + V2*age + V3 + V3*V4 keeps V1 + V3 = 2 only */
5273: for (j=-1; (j < maxncov); j++) Ndum[j]=0;
5274: if(Dummy[k]==0 && Typevar[k] !=1){ /* Dummy covariate and not age product */
5275: switch(Fixed[k]) {
5276: case 0: /* Testing on fixed dummy covariate, simple or product of fixed */
5277: 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*/
5278: ij=(int)(covar[Tvar[k]][i]);
5279: /* ij=0 or 1 or -1. Value of the covariate Tvar[j] for individual i
5280: * If product of Vn*Vm, still boolean *:
5281: * If it was coded 1, 2, 3, 4 should be splitted into 3 boolean variables
5282: * 1 => 0 0 0, 2 => 0 0 1, 3 => 0 1 1, 4=1 0 0 */
5283: /* Finds for covariate j, n=Tvar[j] of Vn . ij is the
5284: modality of the nth covariate of individual i. */
5285: if (ij > modmaxcovj)
5286: modmaxcovj=ij;
5287: else if (ij < modmincovj)
5288: modmincovj=ij;
5289: if ((ij < -1) && (ij > NCOVMAX)){
5290: printf( "Error: minimal is less than -1 or maximal is bigger than %d. Exiting. \n", NCOVMAX );
5291: exit(1);
5292: }else
5293: Ndum[ij]++; /*counts and stores the occurence of this modality 0, 1, -1*/
5294: /* If coded 1, 2, 3 , counts the number of 1 Ndum[1], number of 2, Ndum[2], etc */
5295: /*printf("i=%d ij=%d Ndum[ij]=%d imx=%d",i,ij,Ndum[ij],imx);*/
5296: /* getting the maximum value of the modality of the covariate
5297: (should be 0 or 1 now) Tvar[j]. If V=sex and male is coded 0 and
5298: female ies 1, then modmaxcovj=1.
5299: */
5300: } /* end for loop on individuals i */
5301: printf(" Minimal and maximal values of %d th (fixed) covariate V%d: min=%d max=%d \n", k, Tvar[k], modmincovj, modmaxcovj);
5302: fprintf(ficlog," Minimal and maximal values of %d th (fixed) covariate V%d: min=%d max=%d \n", k, Tvar[k], modmincovj, modmaxcovj);
5303: cptcode=modmaxcovj;
5304: /* Ndum[0] = frequency of 0 for model-covariate j, Ndum[1] frequency of 1 etc. */
5305: /*for (i=0; i<=cptcode; i++) {*/
5306: for (j=modmincovj; j<=modmaxcovj; j++) { /* j=-1 ? 0 and 1*//* For each value j of the modality of model-cov k */
5307: printf("Frequencies of (fixed) covariate %d ie V%d with value %d: %d\n", k, Tvar[k], j, Ndum[j]);
5308: fprintf(ficlog, "Frequencies of (fixed) covariate %d ie V%d with value %d: %d\n", k, Tvar[k], j, Ndum[j]);
5309: if( Ndum[j] != 0 ){ /* Counts if nobody answered modality j ie empty modality, we skip it and reorder */
5310: if( j != -1){
5311: ncodemax[k]++; /* ncodemax[k]= Number of modalities of the k th
5312: covariate for which somebody answered excluding
5313: undefined. Usually 2: 0 and 1. */
5314: }
5315: ncodemaxwundef[k]++; /* ncodemax[j]= Number of modalities of the k th
5316: covariate for which somebody answered including
5317: undefined. Usually 3: -1, 0 and 1. */
5318: } /* In fact ncodemax[k]=2 (dichotom. variables only) but it could be more for
5319: * historical reasons: 3 if coded 1, 2, 3 and 4 and Ndum[2]=0 */
5320: } /* Ndum[-1] number of undefined modalities */
1.231 brouard 5321:
1.242 brouard 5322: /* j is a covariate, n=Tvar[j] of Vn; Fills nbcode */
5323: /* For covariate j, modalities could be 1, 2, 3, 4, 5, 6, 7. */
5324: /* If Ndum[1]=0, Ndum[2]=0, Ndum[3]= 635, Ndum[4]=0, Ndum[5]=0, Ndum[6]=27, Ndum[7]=125; */
5325: /* modmincovj=3; modmaxcovj = 7; */
5326: /* There are only 3 modalities non empty 3, 6, 7 (or 2 if 27 is too few) : ncodemax[j]=3; */
5327: /* which will be coded 0, 1, 2 which in binary on 2=3-1 digits are 0=00 1=01, 2=10; */
5328: /* defining two dummy variables: variables V1_1 and V1_2.*/
5329: /* nbcode[Tvar[j]][ij]=k; */
5330: /* nbcode[Tvar[j]][1]=0; */
5331: /* nbcode[Tvar[j]][2]=1; */
5332: /* nbcode[Tvar[j]][3]=2; */
5333: /* To be continued (not working yet). */
5334: ij=0; /* ij is similar to i but can jump over null modalities */
5335: 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*/
5336: if (Ndum[i] == 0) { /* If nobody responded to this modality k */
5337: break;
5338: }
5339: ij++;
5340: 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*/
5341: cptcode = ij; /* New max modality for covar j */
5342: } /* end of loop on modality i=-1 to 1 or more */
5343: break;
5344: case 1: /* Testing on varying covariate, could be simple and
5345: * should look at waves or product of fixed *
5346: * varying. No time to test -1, assuming 0 and 1 only */
5347: ij=0;
5348: for(i=0; i<=1;i++){
5349: nbcode[Tvar[k]][++ij]=i;
5350: }
5351: break;
5352: default:
5353: break;
5354: } /* end switch */
5355: } /* end dummy test */
5356:
5357: /* for (k=0; k<= cptcode; k++) { /\* k=-1 ? k=0 to 1 *\//\* Could be 1 to 4 *\//\* cptcode=modmaxcovj *\/ */
5358: /* /\*recode from 0 *\/ */
5359: /* k is a modality. If we have model=V1+V1*sex */
5360: /* then: nbcode[1][1]=0 ; nbcode[1][2]=1; nbcode[2][1]=0 ; nbcode[2][2]=1; */
5361: /* But if some modality were not used, it is recoded from 0 to a newer modmaxcovj=cptcode *\/ */
5362: /* } */
5363: /* /\* cptcode = ij; *\/ /\* New max modality for covar j *\/ */
5364: /* if (ij > ncodemax[j]) { */
5365: /* printf( " Error ij=%d > ncodemax[%d]=%d\n", ij, j, ncodemax[j]); */
5366: /* fprintf(ficlog, " Error ij=%d > ncodemax[%d]=%d\n", ij, j, ncodemax[j]); */
5367: /* break; */
5368: /* } */
5369: /* } /\* end of loop on modality k *\/ */
5370: } /* end of loop on model-covariate j. nbcode[Tvarj][1]=0 and nbcode[Tvarj][2]=1 sets the value of covariate j*/
5371:
5372: for (k=-1; k< maxncov; k++) Ndum[k]=0;
5373: /* Look at fixed dummy (single or product) covariates to check empty modalities */
5374: for (i=1; i<=ncovmodel-2-nagesqr; i++) { /* -2, cste and age and eventually age*age */
5375: /* Listing of all covariables in statement model to see if some covariates appear twice. For example, V1 appears twice in V1+V1*V2.*/
5376: 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 */
5377: 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 */
5378: /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, {2, 1, 1, 1, 2, 1, 1, 0, 0} */
5379: } /* V4+V3+V5, Ndum[1]@5={0, 0, 1, 1, 1} */
5380:
5381: ij=0;
5382: /* for (i=0; i<= maxncov-1; i++) { /\* modmaxcovj is unknown here. Only Ndum[2(V2),3(age*V3), 5(V3*V2) 6(V1*V4) *\/ */
5383: for (k=1; k<= cptcovt; k++) { /* modmaxcovj is unknown here. Only Ndum[2(V2),3(age*V3), 5(V3*V2) 6(V1*V4) */
5384: /*printf("Ndum[%d]=%d\n",i, Ndum[i]);*/
5385: /* if((Ndum[i]!=0) && (i<=ncovcol)){ /\* Tvar[i] <= ncovmodel ? *\/ */
5386: if(Ndum[Tvar[k]]!=0 && Dummy[k] == 0 && Typevar[k]==0){ /* Only Dummy and non empty in the model */
5387: /* If product not in single variable we don't print results */
5388: /*printf("diff Ndum[%d]=%d\n",i, Ndum[i]);*/
5389: ++ij;/* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, */
5390: 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*/
5391: Tmodelind[ij]=k; /* Tmodelind: index in model of dummies Tmodelind[1]=2 V4: pos=2; V3: pos=3, V1=9 {2, 3, 9, ?, ?,} */
5392: 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 */
5393: if(Fixed[k]!=0)
5394: anyvaryingduminmodel=1;
5395: /* }else if((Ndum[i]!=0) && (i<=ncovcol+nqv)){ */
5396: /* Tvaraff[++ij]=-10; /\* Dont'n know how to treat quantitative variables yet *\/ */
5397: /* }else if((Ndum[i]!=0) && (i<=ncovcol+nqv+ntv)){ */
5398: /* Tvaraff[++ij]=i; /\*For printing (unclear) *\/ */
5399: /* }else if((Ndum[i]!=0) && (i<=ncovcol+nqv+ntv+nqtv)){ */
5400: /* Tvaraff[++ij]=-20; /\* Dont'n know how to treat quantitative variables yet *\/ */
5401: }
5402: } /* Tvaraff[1]@5 {3, 4, -20, 0, 0} Very strange */
5403: /* ij--; */
5404: /* cptcoveff=ij; /\*Number of total covariates*\/ */
5405: *cptcov=ij; /*Number of total real effective covariates: effective
5406: * because they can be excluded from the model and real
5407: * if in the model but excluded because missing values, but how to get k from ij?*/
5408: for(j=ij+1; j<= cptcovt; j++){
5409: Tvaraff[j]=0;
5410: Tmodelind[j]=0;
5411: }
5412: for(j=ntveff+1; j<= cptcovt; j++){
5413: TmodelInvind[j]=0;
5414: }
5415: /* To be sorted */
5416: ;
5417: }
1.126 brouard 5418:
1.145 brouard 5419:
1.126 brouard 5420: /*********** Health Expectancies ****************/
5421:
1.235 brouard 5422: 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 5423:
5424: {
5425: /* Health expectancies, no variances */
1.164 brouard 5426: int i, j, nhstepm, hstepm, h, nstepm;
1.126 brouard 5427: int nhstepma, nstepma; /* Decreasing with age */
5428: double age, agelim, hf;
5429: double ***p3mat;
5430: double eip;
5431:
1.238 brouard 5432: /* pstamp(ficreseij); */
1.126 brouard 5433: fprintf(ficreseij,"# (a) Life expectancies by health status at initial age and (b) health expectancies by health status at initial age\n");
5434: fprintf(ficreseij,"# Age");
5435: for(i=1; i<=nlstate;i++){
5436: for(j=1; j<=nlstate;j++){
5437: fprintf(ficreseij," e%1d%1d ",i,j);
5438: }
5439: fprintf(ficreseij," e%1d. ",i);
5440: }
5441: fprintf(ficreseij,"\n");
5442:
5443:
5444: if(estepm < stepm){
5445: printf ("Problem %d lower than %d\n",estepm, stepm);
5446: }
5447: else hstepm=estepm;
5448: /* We compute the life expectancy from trapezoids spaced every estepm months
5449: * This is mainly to measure the difference between two models: for example
5450: * if stepm=24 months pijx are given only every 2 years and by summing them
5451: * we are calculating an estimate of the Life Expectancy assuming a linear
5452: * progression in between and thus overestimating or underestimating according
5453: * to the curvature of the survival function. If, for the same date, we
5454: * estimate the model with stepm=1 month, we can keep estepm to 24 months
5455: * to compare the new estimate of Life expectancy with the same linear
5456: * hypothesis. A more precise result, taking into account a more precise
5457: * curvature will be obtained if estepm is as small as stepm. */
5458:
5459: /* For example we decided to compute the life expectancy with the smallest unit */
5460: /* hstepm beeing the number of stepms, if hstepm=1 the length of hstepm is stepm.
5461: nhstepm is the number of hstepm from age to agelim
5462: nstepm is the number of stepm from age to agelin.
5463: Look at hpijx to understand the reason of that which relies in memory size
5464: and note for a fixed period like estepm months */
5465: /* We decided (b) to get a life expectancy respecting the most precise curvature of the
5466: survival function given by stepm (the optimization length). Unfortunately it
5467: means that if the survival funtion is printed only each two years of age and if
5468: you sum them up and add 1 year (area under the trapezoids) you won't get the same
5469: results. So we changed our mind and took the option of the best precision.
5470: */
5471: hstepm=hstepm/stepm; /* Typically in stepm units, if stepm=6 & estepm=24 , = 24/6 months = 4 */
5472:
5473: agelim=AGESUP;
5474: /* If stepm=6 months */
5475: /* Computed by stepm unit matrices, product of hstepm matrices, stored
5476: in an array of nhstepm length: nhstepm=10, hstepm=4, stepm=6 months */
5477:
5478: /* nhstepm age range expressed in number of stepm */
5479: nstepm=(int) rint((agelim-bage)*YEARM/stepm); /* Biggest nstepm */
5480: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
5481: /* if (stepm >= YEARM) hstepm=1;*/
5482: nhstepm = nstepm/hstepm;/* Expressed in hstepm, typically nhstepm=40/4=10 */
5483: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
5484:
5485: for (age=bage; age<=fage; age ++){
5486: nstepma=(int) rint((agelim-bage)*YEARM/stepm); /* Biggest nstepm */
5487: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
5488: /* if (stepm >= YEARM) hstepm=1;*/
5489: nhstepma = nstepma/hstepm;/* Expressed in hstepm, typically nhstepma=40/4=10 */
5490:
5491: /* If stepm=6 months */
5492: /* Computed by stepm unit matrices, product of hstepma matrices, stored
5493: in an array of nhstepma length: nhstepma=10, hstepm=4, stepm=6 months */
5494:
1.235 brouard 5495: hpxij(p3mat,nhstepma,age,hstepm,x,nlstate,stepm,oldm, savm, cij, nres);
1.126 brouard 5496:
5497: hf=hstepm*stepm/YEARM; /* Duration of hstepm expressed in year unit. */
5498:
5499: printf("%d|",(int)age);fflush(stdout);
5500: fprintf(ficlog,"%d|",(int)age);fflush(ficlog);
5501:
5502: /* Computing expectancies */
5503: for(i=1; i<=nlstate;i++)
5504: for(j=1; j<=nlstate;j++)
5505: for (h=0, eij[i][j][(int)age]=0; h<=nhstepm-1; h++){
5506: eij[i][j][(int)age] += (p3mat[i][j][h]+p3mat[i][j][h+1])/2.0*hf;
5507:
5508: /* 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]);*/
5509:
5510: }
5511:
5512: fprintf(ficreseij,"%3.0f",age );
5513: for(i=1; i<=nlstate;i++){
5514: eip=0;
5515: for(j=1; j<=nlstate;j++){
5516: eip +=eij[i][j][(int)age];
5517: fprintf(ficreseij,"%9.4f", eij[i][j][(int)age] );
5518: }
5519: fprintf(ficreseij,"%9.4f", eip );
5520: }
5521: fprintf(ficreseij,"\n");
5522:
5523: }
5524: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
5525: printf("\n");
5526: fprintf(ficlog,"\n");
5527:
5528: }
5529:
1.235 brouard 5530: 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 5531:
5532: {
5533: /* Covariances of health expectancies eij and of total life expectancies according
1.222 brouard 5534: to initial status i, ei. .
1.126 brouard 5535: */
5536: int i, j, nhstepm, hstepm, h, nstepm, k, cptj, cptj2, i2, j2, ij, ji;
5537: int nhstepma, nstepma; /* Decreasing with age */
5538: double age, agelim, hf;
5539: double ***p3matp, ***p3matm, ***varhe;
5540: double **dnewm,**doldm;
5541: double *xp, *xm;
5542: double **gp, **gm;
5543: double ***gradg, ***trgradg;
5544: int theta;
5545:
5546: double eip, vip;
5547:
5548: varhe=ma3x(1,nlstate*nlstate,1,nlstate*nlstate,(int) bage, (int) fage);
5549: xp=vector(1,npar);
5550: xm=vector(1,npar);
5551: dnewm=matrix(1,nlstate*nlstate,1,npar);
5552: doldm=matrix(1,nlstate*nlstate,1,nlstate*nlstate);
5553:
5554: pstamp(ficresstdeij);
5555: fprintf(ficresstdeij,"# Health expectancies with standard errors\n");
5556: fprintf(ficresstdeij,"# Age");
5557: for(i=1; i<=nlstate;i++){
5558: for(j=1; j<=nlstate;j++)
5559: fprintf(ficresstdeij," e%1d%1d (SE)",i,j);
5560: fprintf(ficresstdeij," e%1d. ",i);
5561: }
5562: fprintf(ficresstdeij,"\n");
5563:
5564: pstamp(ficrescveij);
5565: fprintf(ficrescveij,"# Subdiagonal matrix of covariances of health expectancies by age: cov(eij,ekl)\n");
5566: fprintf(ficrescveij,"# Age");
5567: for(i=1; i<=nlstate;i++)
5568: for(j=1; j<=nlstate;j++){
5569: cptj= (j-1)*nlstate+i;
5570: for(i2=1; i2<=nlstate;i2++)
5571: for(j2=1; j2<=nlstate;j2++){
5572: cptj2= (j2-1)*nlstate+i2;
5573: if(cptj2 <= cptj)
5574: fprintf(ficrescveij," %1d%1d,%1d%1d",i,j,i2,j2);
5575: }
5576: }
5577: fprintf(ficrescveij,"\n");
5578:
5579: if(estepm < stepm){
5580: printf ("Problem %d lower than %d\n",estepm, stepm);
5581: }
5582: else hstepm=estepm;
5583: /* We compute the life expectancy from trapezoids spaced every estepm months
5584: * This is mainly to measure the difference between two models: for example
5585: * if stepm=24 months pijx are given only every 2 years and by summing them
5586: * we are calculating an estimate of the Life Expectancy assuming a linear
5587: * progression in between and thus overestimating or underestimating according
5588: * to the curvature of the survival function. If, for the same date, we
5589: * estimate the model with stepm=1 month, we can keep estepm to 24 months
5590: * to compare the new estimate of Life expectancy with the same linear
5591: * hypothesis. A more precise result, taking into account a more precise
5592: * curvature will be obtained if estepm is as small as stepm. */
5593:
5594: /* For example we decided to compute the life expectancy with the smallest unit */
5595: /* hstepm beeing the number of stepms, if hstepm=1 the length of hstepm is stepm.
5596: nhstepm is the number of hstepm from age to agelim
5597: nstepm is the number of stepm from age to agelin.
5598: Look at hpijx to understand the reason of that which relies in memory size
5599: and note for a fixed period like estepm months */
5600: /* We decided (b) to get a life expectancy respecting the most precise curvature of the
5601: survival function given by stepm (the optimization length). Unfortunately it
5602: means that if the survival funtion is printed only each two years of age and if
5603: you sum them up and add 1 year (area under the trapezoids) you won't get the same
5604: results. So we changed our mind and took the option of the best precision.
5605: */
5606: hstepm=hstepm/stepm; /* Typically in stepm units, if stepm=6 & estepm=24 , = 24/6 months = 4 */
5607:
5608: /* If stepm=6 months */
5609: /* nhstepm age range expressed in number of stepm */
5610: agelim=AGESUP;
5611: nstepm=(int) rint((agelim-bage)*YEARM/stepm);
5612: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
5613: /* if (stepm >= YEARM) hstepm=1;*/
5614: nhstepm = nstepm/hstepm;/* Expressed in hstepm, typically nhstepm=40/4=10 */
5615:
5616: p3matp=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
5617: p3matm=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
5618: gradg=ma3x(0,nhstepm,1,npar,1,nlstate*nlstate);
5619: trgradg =ma3x(0,nhstepm,1,nlstate*nlstate,1,npar);
5620: gp=matrix(0,nhstepm,1,nlstate*nlstate);
5621: gm=matrix(0,nhstepm,1,nlstate*nlstate);
5622:
5623: for (age=bage; age<=fage; age ++){
5624: nstepma=(int) rint((agelim-bage)*YEARM/stepm); /* Biggest nstepm */
5625: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
5626: /* if (stepm >= YEARM) hstepm=1;*/
5627: nhstepma = nstepma/hstepm;/* Expressed in hstepm, typically nhstepma=40/4=10 */
1.218 brouard 5628:
1.126 brouard 5629: /* If stepm=6 months */
5630: /* Computed by stepm unit matrices, product of hstepma matrices, stored
5631: in an array of nhstepma length: nhstepma=10, hstepm=4, stepm=6 months */
5632:
5633: hf=hstepm*stepm/YEARM; /* Duration of hstepm expressed in year unit. */
1.218 brouard 5634:
1.126 brouard 5635: /* Computing Variances of health expectancies */
5636: /* Gradient is computed with plus gp and minus gm. Code is duplicated in order to
5637: decrease memory allocation */
5638: for(theta=1; theta <=npar; theta++){
5639: for(i=1; i<=npar; i++){
1.222 brouard 5640: xp[i] = x[i] + (i==theta ?delti[theta]:0);
5641: xm[i] = x[i] - (i==theta ?delti[theta]:0);
1.126 brouard 5642: }
1.235 brouard 5643: hpxij(p3matp,nhstepm,age,hstepm,xp,nlstate,stepm,oldm,savm, cij, nres);
5644: hpxij(p3matm,nhstepm,age,hstepm,xm,nlstate,stepm,oldm,savm, cij, nres);
1.218 brouard 5645:
1.126 brouard 5646: for(j=1; j<= nlstate; j++){
1.222 brouard 5647: for(i=1; i<=nlstate; i++){
5648: for(h=0; h<=nhstepm-1; h++){
5649: gp[h][(j-1)*nlstate + i] = (p3matp[i][j][h]+p3matp[i][j][h+1])/2.;
5650: gm[h][(j-1)*nlstate + i] = (p3matm[i][j][h]+p3matm[i][j][h+1])/2.;
5651: }
5652: }
1.126 brouard 5653: }
1.218 brouard 5654:
1.126 brouard 5655: for(ij=1; ij<= nlstate*nlstate; ij++)
1.222 brouard 5656: for(h=0; h<=nhstepm-1; h++){
5657: gradg[h][theta][ij]= (gp[h][ij]-gm[h][ij])/2./delti[theta];
5658: }
1.126 brouard 5659: }/* End theta */
5660:
5661:
5662: for(h=0; h<=nhstepm-1; h++)
5663: for(j=1; j<=nlstate*nlstate;j++)
1.222 brouard 5664: for(theta=1; theta <=npar; theta++)
5665: trgradg[h][j][theta]=gradg[h][theta][j];
1.126 brouard 5666:
1.218 brouard 5667:
1.222 brouard 5668: for(ij=1;ij<=nlstate*nlstate;ij++)
1.126 brouard 5669: for(ji=1;ji<=nlstate*nlstate;ji++)
1.222 brouard 5670: varhe[ij][ji][(int)age] =0.;
1.218 brouard 5671:
1.222 brouard 5672: printf("%d|",(int)age);fflush(stdout);
5673: fprintf(ficlog,"%d|",(int)age);fflush(ficlog);
5674: for(h=0;h<=nhstepm-1;h++){
1.126 brouard 5675: for(k=0;k<=nhstepm-1;k++){
1.222 brouard 5676: matprod2(dnewm,trgradg[h],1,nlstate*nlstate,1,npar,1,npar,matcov);
5677: matprod2(doldm,dnewm,1,nlstate*nlstate,1,npar,1,nlstate*nlstate,gradg[k]);
5678: for(ij=1;ij<=nlstate*nlstate;ij++)
5679: for(ji=1;ji<=nlstate*nlstate;ji++)
5680: varhe[ij][ji][(int)age] += doldm[ij][ji]*hf*hf;
1.126 brouard 5681: }
5682: }
1.218 brouard 5683:
1.126 brouard 5684: /* Computing expectancies */
1.235 brouard 5685: hpxij(p3matm,nhstepm,age,hstepm,x,nlstate,stepm,oldm, savm, cij,nres);
1.126 brouard 5686: for(i=1; i<=nlstate;i++)
5687: for(j=1; j<=nlstate;j++)
1.222 brouard 5688: for (h=0, eij[i][j][(int)age]=0; h<=nhstepm-1; h++){
5689: eij[i][j][(int)age] += (p3matm[i][j][h]+p3matm[i][j][h+1])/2.0*hf;
1.218 brouard 5690:
1.222 brouard 5691: /* 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 5692:
1.222 brouard 5693: }
1.218 brouard 5694:
1.126 brouard 5695: fprintf(ficresstdeij,"%3.0f",age );
5696: for(i=1; i<=nlstate;i++){
5697: eip=0.;
5698: vip=0.;
5699: for(j=1; j<=nlstate;j++){
1.222 brouard 5700: eip += eij[i][j][(int)age];
5701: for(k=1; k<=nlstate;k++) /* Sum on j and k of cov(eij,eik) */
5702: vip += varhe[(j-1)*nlstate+i][(k-1)*nlstate+i][(int)age];
5703: 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 5704: }
5705: fprintf(ficresstdeij," %9.4f (%.4f)", eip, sqrt(vip));
5706: }
5707: fprintf(ficresstdeij,"\n");
1.218 brouard 5708:
1.126 brouard 5709: fprintf(ficrescveij,"%3.0f",age );
5710: for(i=1; i<=nlstate;i++)
5711: for(j=1; j<=nlstate;j++){
1.222 brouard 5712: cptj= (j-1)*nlstate+i;
5713: for(i2=1; i2<=nlstate;i2++)
5714: for(j2=1; j2<=nlstate;j2++){
5715: cptj2= (j2-1)*nlstate+i2;
5716: if(cptj2 <= cptj)
5717: fprintf(ficrescveij," %.4f", varhe[cptj][cptj2][(int)age]);
5718: }
1.126 brouard 5719: }
5720: fprintf(ficrescveij,"\n");
1.218 brouard 5721:
1.126 brouard 5722: }
5723: free_matrix(gm,0,nhstepm,1,nlstate*nlstate);
5724: free_matrix(gp,0,nhstepm,1,nlstate*nlstate);
5725: free_ma3x(gradg,0,nhstepm,1,npar,1,nlstate*nlstate);
5726: free_ma3x(trgradg,0,nhstepm,1,nlstate*nlstate,1,npar);
5727: free_ma3x(p3matm,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
5728: free_ma3x(p3matp,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
5729: printf("\n");
5730: fprintf(ficlog,"\n");
1.218 brouard 5731:
1.126 brouard 5732: free_vector(xm,1,npar);
5733: free_vector(xp,1,npar);
5734: free_matrix(dnewm,1,nlstate*nlstate,1,npar);
5735: free_matrix(doldm,1,nlstate*nlstate,1,nlstate*nlstate);
5736: free_ma3x(varhe,1,nlstate*nlstate,1,nlstate*nlstate,(int) bage, (int)fage);
5737: }
1.218 brouard 5738:
1.126 brouard 5739: /************ Variance ******************/
1.235 brouard 5740: 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 5741: {
5742: /* Variance of health expectancies */
5743: /* double **prevalim(double **prlim, int nlstate, double *xp, double age, double **oldm, double ** savm,double ftolpl);*/
5744: /* double **newm;*/
5745: /* int movingaverage(double ***probs, double bage,double fage, double ***mobaverage, int mobilav)*/
5746:
5747: /* int movingaverage(); */
5748: double **dnewm,**doldm;
5749: double **dnewmp,**doldmp;
5750: int i, j, nhstepm, hstepm, h, nstepm ;
5751: int k;
5752: double *xp;
5753: double **gp, **gm; /* for var eij */
5754: double ***gradg, ***trgradg; /*for var eij */
5755: double **gradgp, **trgradgp; /* for var p point j */
5756: double *gpp, *gmp; /* for var p point j */
5757: double **varppt; /* for var p point j nlstate to nlstate+ndeath */
5758: double ***p3mat;
5759: double age,agelim, hf;
5760: /* double ***mobaverage; */
5761: int theta;
5762: char digit[4];
5763: char digitp[25];
5764:
5765: char fileresprobmorprev[FILENAMELENGTH];
5766:
5767: if(popbased==1){
5768: if(mobilav!=0)
5769: strcpy(digitp,"-POPULBASED-MOBILAV_");
5770: else strcpy(digitp,"-POPULBASED-NOMOBIL_");
5771: }
5772: else
5773: strcpy(digitp,"-STABLBASED_");
1.126 brouard 5774:
1.218 brouard 5775: /* if (mobilav!=0) { */
5776: /* mobaverage= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
5777: /* if (movingaverage(probs, bage, fage, mobaverage,mobilav)!=0){ */
5778: /* fprintf(ficlog," Error in movingaverage mobilav=%d\n",mobilav); */
5779: /* printf(" Error in movingaverage mobilav=%d\n",mobilav); */
5780: /* } */
5781: /* } */
5782:
5783: strcpy(fileresprobmorprev,"PRMORPREV-");
5784: sprintf(digit,"%-d",ij);
5785: /*printf("DIGIT=%s, ij=%d ijr=%-d|\n",digit, ij,ij);*/
5786: strcat(fileresprobmorprev,digit); /* Tvar to be done */
5787: strcat(fileresprobmorprev,digitp); /* Popbased or not, mobilav or not */
5788: strcat(fileresprobmorprev,fileresu);
5789: if((ficresprobmorprev=fopen(fileresprobmorprev,"w"))==NULL) {
5790: printf("Problem with resultfile: %s\n", fileresprobmorprev);
5791: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprobmorprev);
5792: }
5793: printf("Computing total mortality p.j=w1*p1j+w2*p2j+..: result on file '%s' \n",fileresprobmorprev);
5794: fprintf(ficlog,"Computing total mortality p.j=w1*p1j+w2*p2j+..: result on file '%s' \n",fileresprobmorprev);
5795: pstamp(ficresprobmorprev);
5796: 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 5797: fprintf(ficresprobmorprev,"# Selected quantitative variables and dummies");
5798: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
5799: fprintf(ficresprobmorprev," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
5800: }
5801: for(j=1;j<=cptcoveff;j++)
5802: fprintf(ficresprobmorprev,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(ij,j)]);
5803: fprintf(ficresprobmorprev,"\n");
5804:
1.218 brouard 5805: fprintf(ficresprobmorprev,"# Age cov=%-d",ij);
5806: for(j=nlstate+1; j<=(nlstate+ndeath);j++){
5807: fprintf(ficresprobmorprev," p.%-d SE",j);
5808: for(i=1; i<=nlstate;i++)
5809: fprintf(ficresprobmorprev," w%1d p%-d%-d",i,i,j);
5810: }
5811: fprintf(ficresprobmorprev,"\n");
5812:
5813: fprintf(ficgp,"\n# Routine varevsij");
5814: fprintf(ficgp,"\nunset title \n");
5815: /* fprintf(fichtm, "#Local time at start: %s", strstart);*/
5816: 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");
5817: fprintf(fichtm,"\n<br>%s <br>\n",digitp);
5818: /* } */
5819: varppt = matrix(nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
5820: pstamp(ficresvij);
5821: fprintf(ficresvij,"# Variance and covariance of health expectancies e.j \n# (weighted average of eij where weights are ");
5822: if(popbased==1)
5823: 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);
5824: else
5825: fprintf(ficresvij,"the age specific period (stable) prevalences in each health state \n");
5826: fprintf(ficresvij,"# Age");
5827: for(i=1; i<=nlstate;i++)
5828: for(j=1; j<=nlstate;j++)
5829: fprintf(ficresvij," Cov(e.%1d, e.%1d)",i,j);
5830: fprintf(ficresvij,"\n");
5831:
5832: xp=vector(1,npar);
5833: dnewm=matrix(1,nlstate,1,npar);
5834: doldm=matrix(1,nlstate,1,nlstate);
5835: dnewmp= matrix(nlstate+1,nlstate+ndeath,1,npar);
5836: doldmp= matrix(nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
5837:
5838: gradgp=matrix(1,npar,nlstate+1,nlstate+ndeath);
5839: gpp=vector(nlstate+1,nlstate+ndeath);
5840: gmp=vector(nlstate+1,nlstate+ndeath);
5841: trgradgp =matrix(nlstate+1,nlstate+ndeath,1,npar); /* mu or p point j*/
1.126 brouard 5842:
1.218 brouard 5843: if(estepm < stepm){
5844: printf ("Problem %d lower than %d\n",estepm, stepm);
5845: }
5846: else hstepm=estepm;
5847: /* For example we decided to compute the life expectancy with the smallest unit */
5848: /* hstepm beeing the number of stepms, if hstepm=1 the length of hstepm is stepm.
5849: nhstepm is the number of hstepm from age to agelim
5850: nstepm is the number of stepm from age to agelim.
5851: Look at function hpijx to understand why because of memory size limitations,
5852: we decided (b) to get a life expectancy respecting the most precise curvature of the
5853: survival function given by stepm (the optimization length). Unfortunately it
5854: means that if the survival funtion is printed every two years of age and if
5855: you sum them up and add 1 year (area under the trapezoids) you won't get the same
5856: results. So we changed our mind and took the option of the best precision.
5857: */
5858: hstepm=hstepm/stepm; /* Typically in stepm units, if stepm=6 & estepm=24 , = 24/6 months = 4 */
5859: agelim = AGESUP;
5860: for (age=bage; age<=fage; age ++){ /* If stepm=6 months */
5861: nstepm=(int) rint((agelim-age)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
5862: nhstepm = nstepm/hstepm;/* Expressed in hstepm, typically nhstepm=40/4=10 */
5863: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
5864: gradg=ma3x(0,nhstepm,1,npar,1,nlstate);
5865: gp=matrix(0,nhstepm,1,nlstate);
5866: gm=matrix(0,nhstepm,1,nlstate);
5867:
5868:
5869: for(theta=1; theta <=npar; theta++){
5870: for(i=1; i<=npar; i++){ /* Computes gradient x + delta*/
5871: xp[i] = x[i] + (i==theta ?delti[theta]:0);
5872: }
5873:
1.242 brouard 5874: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij, nres);
1.218 brouard 5875:
5876: if (popbased==1) {
5877: if(mobilav ==0){
5878: for(i=1; i<=nlstate;i++)
5879: prlim[i][i]=probs[(int)age][i][ij];
5880: }else{ /* mobilav */
5881: for(i=1; i<=nlstate;i++)
5882: prlim[i][i]=mobaverage[(int)age][i][ij];
5883: }
5884: }
5885:
1.235 brouard 5886: 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 5887: for(j=1; j<= nlstate; j++){
5888: for(h=0; h<=nhstepm; h++){
5889: for(i=1, gp[h][j]=0.;i<=nlstate;i++)
5890: gp[h][j] += prlim[i][i]*p3mat[i][j][h];
5891: }
5892: }
5893: /* Next for computing probability of death (h=1 means
5894: computed over hstepm matrices product = hstepm*stepm months)
5895: as a weighted average of prlim.
5896: */
5897: for(j=nlstate+1;j<=nlstate+ndeath;j++){
5898: for(i=1,gpp[j]=0.; i<= nlstate; i++)
5899: gpp[j] += prlim[i][i]*p3mat[i][j][1];
5900: }
5901: /* end probability of death */
5902:
5903: for(i=1; i<=npar; i++) /* Computes gradient x - delta */
5904: xp[i] = x[i] - (i==theta ?delti[theta]:0);
5905:
1.242 brouard 5906: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp, ij, nres);
1.218 brouard 5907:
5908: if (popbased==1) {
5909: if(mobilav ==0){
5910: for(i=1; i<=nlstate;i++)
5911: prlim[i][i]=probs[(int)age][i][ij];
5912: }else{ /* mobilav */
5913: for(i=1; i<=nlstate;i++)
5914: prlim[i][i]=mobaverage[(int)age][i][ij];
5915: }
5916: }
5917:
1.235 brouard 5918: hpxij(p3mat,nhstepm,age,hstepm,xp,nlstate,stepm,oldm,savm, ij,nres);
1.218 brouard 5919:
5920: for(j=1; j<= nlstate; j++){ /* Sum of wi * eij = e.j */
5921: for(h=0; h<=nhstepm; h++){
5922: for(i=1, gm[h][j]=0.;i<=nlstate;i++)
5923: gm[h][j] += prlim[i][i]*p3mat[i][j][h];
5924: }
5925: }
5926: /* This for computing probability of death (h=1 means
5927: computed over hstepm matrices product = hstepm*stepm months)
5928: as a weighted average of prlim.
5929: */
5930: for(j=nlstate+1;j<=nlstate+ndeath;j++){
5931: for(i=1,gmp[j]=0.; i<= nlstate; i++)
5932: gmp[j] += prlim[i][i]*p3mat[i][j][1];
5933: }
5934: /* end probability of death */
5935:
5936: for(j=1; j<= nlstate; j++) /* vareij */
5937: for(h=0; h<=nhstepm; h++){
5938: gradg[h][theta][j]= (gp[h][j]-gm[h][j])/2./delti[theta];
5939: }
5940:
5941: for(j=nlstate+1; j<= nlstate+ndeath; j++){ /* var mu */
5942: gradgp[theta][j]= (gpp[j]-gmp[j])/2./delti[theta];
5943: }
5944:
5945: } /* End theta */
5946:
5947: trgradg =ma3x(0,nhstepm,1,nlstate,1,npar); /* veij */
5948:
5949: for(h=0; h<=nhstepm; h++) /* veij */
5950: for(j=1; j<=nlstate;j++)
5951: for(theta=1; theta <=npar; theta++)
5952: trgradg[h][j][theta]=gradg[h][theta][j];
5953:
5954: for(j=nlstate+1; j<=nlstate+ndeath;j++) /* mu */
5955: for(theta=1; theta <=npar; theta++)
5956: trgradgp[j][theta]=gradgp[theta][j];
5957:
5958:
5959: hf=hstepm*stepm/YEARM; /* Duration of hstepm expressed in year unit. */
5960: for(i=1;i<=nlstate;i++)
5961: for(j=1;j<=nlstate;j++)
5962: vareij[i][j][(int)age] =0.;
5963:
5964: for(h=0;h<=nhstepm;h++){
5965: for(k=0;k<=nhstepm;k++){
5966: matprod2(dnewm,trgradg[h],1,nlstate,1,npar,1,npar,matcov);
5967: matprod2(doldm,dnewm,1,nlstate,1,npar,1,nlstate,gradg[k]);
5968: for(i=1;i<=nlstate;i++)
5969: for(j=1;j<=nlstate;j++)
5970: vareij[i][j][(int)age] += doldm[i][j]*hf*hf;
5971: }
5972: }
5973:
5974: /* pptj */
5975: matprod2(dnewmp,trgradgp,nlstate+1,nlstate+ndeath,1,npar,1,npar,matcov);
5976: matprod2(doldmp,dnewmp,nlstate+1,nlstate+ndeath,1,npar,nlstate+1,nlstate+ndeath,gradgp);
5977: for(j=nlstate+1;j<=nlstate+ndeath;j++)
5978: for(i=nlstate+1;i<=nlstate+ndeath;i++)
5979: varppt[j][i]=doldmp[j][i];
5980: /* end ppptj */
5981: /* x centered again */
5982:
1.242 brouard 5983: prevalim(prlim,nlstate,x,age,oldm,savm,ftolpl,ncvyearp,ij, nres);
1.218 brouard 5984:
5985: if (popbased==1) {
5986: if(mobilav ==0){
5987: for(i=1; i<=nlstate;i++)
5988: prlim[i][i]=probs[(int)age][i][ij];
5989: }else{ /* mobilav */
5990: for(i=1; i<=nlstate;i++)
5991: prlim[i][i]=mobaverage[(int)age][i][ij];
5992: }
5993: }
5994:
5995: /* This for computing probability of death (h=1 means
5996: computed over hstepm (estepm) matrices product = hstepm*stepm months)
5997: as a weighted average of prlim.
5998: */
1.235 brouard 5999: hpxij(p3mat,nhstepm,age,hstepm,x,nlstate,stepm,oldm,savm, ij, nres);
1.218 brouard 6000: for(j=nlstate+1;j<=nlstate+ndeath;j++){
6001: for(i=1,gmp[j]=0.;i<= nlstate; i++)
6002: gmp[j] += prlim[i][i]*p3mat[i][j][1];
6003: }
6004: /* end probability of death */
6005:
6006: fprintf(ficresprobmorprev,"%3d %d ",(int) age, ij);
6007: for(j=nlstate+1; j<=(nlstate+ndeath);j++){
6008: fprintf(ficresprobmorprev," %11.3e %11.3e",gmp[j], sqrt(varppt[j][j]));
6009: for(i=1; i<=nlstate;i++){
6010: fprintf(ficresprobmorprev," %11.3e %11.3e ",prlim[i][i],p3mat[i][j][1]);
6011: }
6012: }
6013: fprintf(ficresprobmorprev,"\n");
6014:
6015: fprintf(ficresvij,"%.0f ",age );
6016: for(i=1; i<=nlstate;i++)
6017: for(j=1; j<=nlstate;j++){
6018: fprintf(ficresvij," %.4f", vareij[i][j][(int)age]);
6019: }
6020: fprintf(ficresvij,"\n");
6021: free_matrix(gp,0,nhstepm,1,nlstate);
6022: free_matrix(gm,0,nhstepm,1,nlstate);
6023: free_ma3x(gradg,0,nhstepm,1,npar,1,nlstate);
6024: free_ma3x(trgradg,0,nhstepm,1,nlstate,1,npar);
6025: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
6026: } /* End age */
6027: free_vector(gpp,nlstate+1,nlstate+ndeath);
6028: free_vector(gmp,nlstate+1,nlstate+ndeath);
6029: free_matrix(gradgp,1,npar,nlstate+1,nlstate+ndeath);
6030: free_matrix(trgradgp,nlstate+1,nlstate+ndeath,1,npar); /* mu or p point j*/
6031: /* fprintf(ficgp,"\nunset parametric;unset label; set ter png small size 320, 240"); */
6032: fprintf(ficgp,"\nunset parametric;unset label; set ter svg size 640, 480");
6033: /* for(j=nlstate+1; j<= nlstate+ndeath; j++){ *//* Only the first actually */
6034: fprintf(ficgp,"\n set log y; unset log x;set xlabel \"Age\"; set ylabel \"Force of mortality (year-1)\";");
6035: fprintf(ficgp,"\nset out \"%s%s.svg\";",subdirf3(optionfilefiname,"VARMUPTJGR-",digitp),digit);
6036: /* fprintf(ficgp,"\n plot \"%s\" u 1:($3*%6.3f) not w l 1 ",fileresprobmorprev,YEARM/estepm); */
6037: /* fprintf(ficgp,"\n replot \"%s\" u 1:(($3+1.96*$4)*%6.3f) t \"95\%% interval\" w l 2 ",fileresprobmorprev,YEARM/estepm); */
6038: /* fprintf(ficgp,"\n replot \"%s\" u 1:(($3-1.96*$4)*%6.3f) not w l 2 ",fileresprobmorprev,YEARM/estepm); */
6039: fprintf(ficgp,"\n plot \"%s\" u 1:($3) not w l lt 1 ",subdirf(fileresprobmorprev));
6040: fprintf(ficgp,"\n replot \"%s\" u 1:(($3+1.96*$4)) t \"95%% interval\" w l lt 2 ",subdirf(fileresprobmorprev));
6041: fprintf(ficgp,"\n replot \"%s\" u 1:(($3-1.96*$4)) not w l lt 2 ",subdirf(fileresprobmorprev));
6042: fprintf(fichtm,"\n<br> File (multiple files are possible if covariates are present): <A href=\"%s\">%s</a>\n",subdirf(fileresprobmorprev),subdirf(fileresprobmorprev));
6043: 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);
6044: /* 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 6045: */
1.218 brouard 6046: /* fprintf(ficgp,"\nset out \"varmuptjgr%s%s%s.svg\";replot;",digitp,optionfilefiname,digit); */
6047: fprintf(ficgp,"\nset out;\nset out \"%s%s.svg\";replot;set out;\n",subdirf3(optionfilefiname,"VARMUPTJGR-",digitp),digit);
1.126 brouard 6048:
1.218 brouard 6049: free_vector(xp,1,npar);
6050: free_matrix(doldm,1,nlstate,1,nlstate);
6051: free_matrix(dnewm,1,nlstate,1,npar);
6052: free_matrix(doldmp,nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
6053: free_matrix(dnewmp,nlstate+1,nlstate+ndeath,1,npar);
6054: free_matrix(varppt,nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
6055: /* if (mobilav!=0) free_ma3x(mobaverage,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
6056: fclose(ficresprobmorprev);
6057: fflush(ficgp);
6058: fflush(fichtm);
6059: } /* end varevsij */
1.126 brouard 6060:
6061: /************ Variance of prevlim ******************/
1.235 brouard 6062: 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 6063: {
1.205 brouard 6064: /* Variance of prevalence limit for each state ij using current parameters x[] and estimates of neighbourhood give by delti*/
1.126 brouard 6065: /* double **prevalim(double **prlim, int nlstate, double *xp, double age, double **oldm, double **savm,double ftolpl);*/
1.164 brouard 6066:
1.268 ! brouard 6067: double **dnewmpar,**doldm;
1.126 brouard 6068: int i, j, nhstepm, hstepm;
6069: double *xp;
6070: double *gp, *gm;
6071: double **gradg, **trgradg;
1.208 brouard 6072: double **mgm, **mgp;
1.126 brouard 6073: double age,agelim;
6074: int theta;
6075:
6076: pstamp(ficresvpl);
6077: fprintf(ficresvpl,"# Standard deviation of period (stable) prevalences \n");
1.241 brouard 6078: fprintf(ficresvpl,"# Age ");
6079: if(nresult >=1)
6080: fprintf(ficresvpl," Result# ");
1.126 brouard 6081: for(i=1; i<=nlstate;i++)
6082: fprintf(ficresvpl," %1d-%1d",i,i);
6083: fprintf(ficresvpl,"\n");
6084:
6085: xp=vector(1,npar);
1.268 ! brouard 6086: dnewmpar=matrix(1,nlstate,1,npar);
1.126 brouard 6087: doldm=matrix(1,nlstate,1,nlstate);
6088:
6089: hstepm=1*YEARM; /* Every year of age */
6090: hstepm=hstepm/stepm; /* Typically in stepm units, if j= 2 years, = 2/6 months = 4 */
6091: agelim = AGESUP;
6092: for (age=bage; age<=fage; age ++){ /* If stepm=6 months */
6093: nhstepm=(int) rint((agelim-age)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
6094: if (stepm >= YEARM) hstepm=1;
6095: nhstepm = nhstepm/hstepm; /* Typically 40/4=10 */
6096: gradg=matrix(1,npar,1,nlstate);
1.208 brouard 6097: mgp=matrix(1,npar,1,nlstate);
6098: mgm=matrix(1,npar,1,nlstate);
1.126 brouard 6099: gp=vector(1,nlstate);
6100: gm=vector(1,nlstate);
6101:
6102: for(theta=1; theta <=npar; theta++){
6103: for(i=1; i<=npar; i++){ /* Computes gradient */
6104: xp[i] = x[i] + (i==theta ?delti[theta]:0);
6105: }
1.209 brouard 6106: if((int)age==79 ||(int)age== 80 ||(int)age== 81 )
1.235 brouard 6107: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres);
1.209 brouard 6108: else
1.235 brouard 6109: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres);
1.208 brouard 6110: for(i=1;i<=nlstate;i++){
1.126 brouard 6111: gp[i] = prlim[i][i];
1.208 brouard 6112: mgp[theta][i] = prlim[i][i];
6113: }
1.126 brouard 6114: for(i=1; i<=npar; i++) /* Computes gradient */
6115: xp[i] = x[i] - (i==theta ?delti[theta]:0);
1.209 brouard 6116: if((int)age==79 ||(int)age== 80 ||(int)age== 81 )
1.235 brouard 6117: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres);
1.209 brouard 6118: else
1.235 brouard 6119: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres);
1.208 brouard 6120: for(i=1;i<=nlstate;i++){
1.126 brouard 6121: gm[i] = prlim[i][i];
1.208 brouard 6122: mgm[theta][i] = prlim[i][i];
6123: }
1.126 brouard 6124: for(i=1;i<=nlstate;i++)
6125: gradg[theta][i]= (gp[i]-gm[i])/2./delti[theta];
1.209 brouard 6126: /* gradg[theta][2]= -gradg[theta][1]; */ /* For testing if nlstate=2 */
1.126 brouard 6127: } /* End theta */
6128:
6129: trgradg =matrix(1,nlstate,1,npar);
6130:
6131: for(j=1; j<=nlstate;j++)
6132: for(theta=1; theta <=npar; theta++)
6133: trgradg[j][theta]=gradg[theta][j];
1.209 brouard 6134: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
6135: /* printf("\nmgm mgp %d ",(int)age); */
6136: /* for(j=1; j<=nlstate;j++){ */
6137: /* printf(" %d ",j); */
6138: /* for(theta=1; theta <=npar; theta++) */
6139: /* printf(" %d %lf %lf",theta,mgm[theta][j],mgp[theta][j]); */
6140: /* printf("\n "); */
6141: /* } */
6142: /* } */
6143: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
6144: /* printf("\n gradg %d ",(int)age); */
6145: /* for(j=1; j<=nlstate;j++){ */
6146: /* printf("%d ",j); */
6147: /* for(theta=1; theta <=npar; theta++) */
6148: /* printf("%d %lf ",theta,gradg[theta][j]); */
6149: /* printf("\n "); */
6150: /* } */
6151: /* } */
1.126 brouard 6152:
6153: for(i=1;i<=nlstate;i++)
6154: varpl[i][(int)age] =0.;
1.209 brouard 6155: if((int)age==79 ||(int)age== 80 ||(int)age== 81){
1.268 ! brouard 6156: matprod2(dnewmpar,trgradg,1,nlstate,1,npar,1,npar,matcov);
! 6157: matprod2(doldm,dnewmpar,1,nlstate,1,npar,1,nlstate,gradg);
1.205 brouard 6158: }else{
1.268 ! brouard 6159: matprod2(dnewmpar,trgradg,1,nlstate,1,npar,1,npar,matcov);
! 6160: matprod2(doldm,dnewmpar,1,nlstate,1,npar,1,nlstate,gradg);
1.205 brouard 6161: }
1.126 brouard 6162: for(i=1;i<=nlstate;i++)
6163: varpl[i][(int)age] = doldm[i][i]; /* Covariances are useless */
6164:
6165: fprintf(ficresvpl,"%.0f ",age );
1.241 brouard 6166: if(nresult >=1)
6167: fprintf(ficresvpl,"%d ",nres );
1.126 brouard 6168: for(i=1; i<=nlstate;i++)
6169: fprintf(ficresvpl," %.5f (%.5f)",prlim[i][i],sqrt(varpl[i][(int)age]));
6170: fprintf(ficresvpl,"\n");
6171: free_vector(gp,1,nlstate);
6172: free_vector(gm,1,nlstate);
1.208 brouard 6173: free_matrix(mgm,1,npar,1,nlstate);
6174: free_matrix(mgp,1,npar,1,nlstate);
1.126 brouard 6175: free_matrix(gradg,1,npar,1,nlstate);
6176: free_matrix(trgradg,1,nlstate,1,npar);
6177: } /* End age */
6178:
6179: free_vector(xp,1,npar);
6180: free_matrix(doldm,1,nlstate,1,npar);
1.268 ! brouard 6181: free_matrix(dnewmpar,1,nlstate,1,nlstate);
! 6182:
! 6183: }
! 6184:
! 6185:
! 6186: /************ Variance of backprevalence limit ******************/
! 6187: void varbrevlim(char fileres[], double **varbpl, double **matcov, double x[], double delti[], int nlstate, int stepm, double bage, double fage, double **oldm, double **savm, double **bprlim, double ftolpl, int mobilavproj, int *ncvyearp, int ij, char strstart[], int nres)
! 6188: {
! 6189: /* Variance of backward prevalence limit for each state ij using current parameters x[] and estimates of neighbourhood give by delti*/
! 6190: /* double **prevalim(double **prlim, int nlstate, double *xp, double age, double **oldm, double **savm,double ftolpl);*/
! 6191:
! 6192: double **dnewmpar,**doldm;
! 6193: int i, j, nhstepm, hstepm;
! 6194: double *xp;
! 6195: double *gp, *gm;
! 6196: double **gradg, **trgradg;
! 6197: double **mgm, **mgp;
! 6198: double age,agelim;
! 6199: int theta;
! 6200:
! 6201: pstamp(ficresvbl);
! 6202: fprintf(ficresvbl,"# Standard deviation of back (stable) prevalences \n");
! 6203: fprintf(ficresvbl,"# Age ");
! 6204: if(nresult >=1)
! 6205: fprintf(ficresvbl," Result# ");
! 6206: for(i=1; i<=nlstate;i++)
! 6207: fprintf(ficresvbl," %1d-%1d",i,i);
! 6208: fprintf(ficresvbl,"\n");
! 6209:
! 6210: xp=vector(1,npar);
! 6211: dnewmpar=matrix(1,nlstate,1,npar);
! 6212: doldm=matrix(1,nlstate,1,nlstate);
! 6213:
! 6214: hstepm=1*YEARM; /* Every year of age */
! 6215: hstepm=hstepm/stepm; /* Typically in stepm units, if j= 2 years, = 2/6 months = 4 */
! 6216: agelim = AGEINF;
! 6217: for (age=fage; age>=bage; age --){ /* If stepm=6 months */
! 6218: nhstepm=(int) rint((age-agelim)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
! 6219: if (stepm >= YEARM) hstepm=1;
! 6220: nhstepm = nhstepm/hstepm; /* Typically 40/4=10 */
! 6221: gradg=matrix(1,npar,1,nlstate);
! 6222: mgp=matrix(1,npar,1,nlstate);
! 6223: mgm=matrix(1,npar,1,nlstate);
! 6224: gp=vector(1,nlstate);
! 6225: gm=vector(1,nlstate);
! 6226:
! 6227: for(theta=1; theta <=npar; theta++){
! 6228: for(i=1; i<=npar; i++){ /* Computes gradient */
! 6229: xp[i] = x[i] + (i==theta ?delti[theta]:0);
! 6230: }
! 6231: if(mobilavproj > 0 )
! 6232: bprevalim(bprlim, mobaverage,nlstate,xp,age,ftolpl,ncvyearp,ij,nres);
! 6233: else
! 6234: bprevalim(bprlim, mobaverage,nlstate,xp,age,ftolpl,ncvyearp,ij,nres);
! 6235: for(i=1;i<=nlstate;i++){
! 6236: gp[i] = bprlim[i][i];
! 6237: mgp[theta][i] = bprlim[i][i];
! 6238: }
! 6239: for(i=1; i<=npar; i++) /* Computes gradient */
! 6240: xp[i] = x[i] - (i==theta ?delti[theta]:0);
! 6241: if(mobilavproj > 0 )
! 6242: bprevalim(bprlim, mobaverage,nlstate,xp,age,ftolpl,ncvyearp,ij,nres);
! 6243: else
! 6244: bprevalim(bprlim, mobaverage,nlstate,xp,age,ftolpl,ncvyearp,ij,nres);
! 6245: for(i=1;i<=nlstate;i++){
! 6246: gm[i] = bprlim[i][i];
! 6247: mgm[theta][i] = bprlim[i][i];
! 6248: }
! 6249: for(i=1;i<=nlstate;i++)
! 6250: gradg[theta][i]= (gp[i]-gm[i])/2./delti[theta];
! 6251: /* gradg[theta][2]= -gradg[theta][1]; */ /* For testing if nlstate=2 */
! 6252: } /* End theta */
! 6253:
! 6254: trgradg =matrix(1,nlstate,1,npar);
! 6255:
! 6256: for(j=1; j<=nlstate;j++)
! 6257: for(theta=1; theta <=npar; theta++)
! 6258: trgradg[j][theta]=gradg[theta][j];
! 6259: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
! 6260: /* printf("\nmgm mgp %d ",(int)age); */
! 6261: /* for(j=1; j<=nlstate;j++){ */
! 6262: /* printf(" %d ",j); */
! 6263: /* for(theta=1; theta <=npar; theta++) */
! 6264: /* printf(" %d %lf %lf",theta,mgm[theta][j],mgp[theta][j]); */
! 6265: /* printf("\n "); */
! 6266: /* } */
! 6267: /* } */
! 6268: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
! 6269: /* printf("\n gradg %d ",(int)age); */
! 6270: /* for(j=1; j<=nlstate;j++){ */
! 6271: /* printf("%d ",j); */
! 6272: /* for(theta=1; theta <=npar; theta++) */
! 6273: /* printf("%d %lf ",theta,gradg[theta][j]); */
! 6274: /* printf("\n "); */
! 6275: /* } */
! 6276: /* } */
! 6277:
! 6278: for(i=1;i<=nlstate;i++)
! 6279: varbpl[i][(int)age] =0.;
! 6280: if((int)age==79 ||(int)age== 80 ||(int)age== 81){
! 6281: matprod2(dnewmpar,trgradg,1,nlstate,1,npar,1,npar,matcov);
! 6282: matprod2(doldm,dnewmpar,1,nlstate,1,npar,1,nlstate,gradg);
! 6283: }else{
! 6284: matprod2(dnewmpar,trgradg,1,nlstate,1,npar,1,npar,matcov);
! 6285: matprod2(doldm,dnewmpar,1,nlstate,1,npar,1,nlstate,gradg);
! 6286: }
! 6287: for(i=1;i<=nlstate;i++)
! 6288: varbpl[i][(int)age] = doldm[i][i]; /* Covariances are useless */
! 6289:
! 6290: fprintf(ficresvbl,"%.0f ",age );
! 6291: if(nresult >=1)
! 6292: fprintf(ficresvbl,"%d ",nres );
! 6293: for(i=1; i<=nlstate;i++)
! 6294: fprintf(ficresvbl," %.5f (%.5f)",bprlim[i][i],sqrt(varbpl[i][(int)age]));
! 6295: fprintf(ficresvbl,"\n");
! 6296: free_vector(gp,1,nlstate);
! 6297: free_vector(gm,1,nlstate);
! 6298: free_matrix(mgm,1,npar,1,nlstate);
! 6299: free_matrix(mgp,1,npar,1,nlstate);
! 6300: free_matrix(gradg,1,npar,1,nlstate);
! 6301: free_matrix(trgradg,1,nlstate,1,npar);
! 6302: } /* End age */
! 6303:
! 6304: free_vector(xp,1,npar);
! 6305: free_matrix(doldm,1,nlstate,1,npar);
! 6306: free_matrix(dnewmpar,1,nlstate,1,nlstate);
1.126 brouard 6307:
6308: }
6309:
6310: /************ Variance of one-step probabilities ******************/
6311: 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 6312: {
6313: int i, j=0, k1, l1, tj;
6314: int k2, l2, j1, z1;
6315: int k=0, l;
6316: int first=1, first1, first2;
6317: double cv12, mu1, mu2, lc1, lc2, v12, v21, v11, v22,v1,v2, c12, tnalp;
6318: double **dnewm,**doldm;
6319: double *xp;
6320: double *gp, *gm;
6321: double **gradg, **trgradg;
6322: double **mu;
6323: double age, cov[NCOVMAX+1];
6324: double std=2.0; /* Number of standard deviation wide of confidence ellipsoids */
6325: int theta;
6326: char fileresprob[FILENAMELENGTH];
6327: char fileresprobcov[FILENAMELENGTH];
6328: char fileresprobcor[FILENAMELENGTH];
6329: double ***varpij;
6330:
6331: strcpy(fileresprob,"PROB_");
6332: strcat(fileresprob,fileres);
6333: if((ficresprob=fopen(fileresprob,"w"))==NULL) {
6334: printf("Problem with resultfile: %s\n", fileresprob);
6335: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprob);
6336: }
6337: strcpy(fileresprobcov,"PROBCOV_");
6338: strcat(fileresprobcov,fileresu);
6339: if((ficresprobcov=fopen(fileresprobcov,"w"))==NULL) {
6340: printf("Problem with resultfile: %s\n", fileresprobcov);
6341: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprobcov);
6342: }
6343: strcpy(fileresprobcor,"PROBCOR_");
6344: strcat(fileresprobcor,fileresu);
6345: if((ficresprobcor=fopen(fileresprobcor,"w"))==NULL) {
6346: printf("Problem with resultfile: %s\n", fileresprobcor);
6347: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprobcor);
6348: }
6349: printf("Computing standard deviation of one-step probabilities: result on file '%s' \n",fileresprob);
6350: fprintf(ficlog,"Computing standard deviation of one-step probabilities: result on file '%s' \n",fileresprob);
6351: printf("Computing matrix of variance covariance of one-step probabilities: result on file '%s' \n",fileresprobcov);
6352: fprintf(ficlog,"Computing matrix of variance covariance of one-step probabilities: result on file '%s' \n",fileresprobcov);
6353: printf("and correlation matrix of one-step probabilities: result on file '%s' \n",fileresprobcor);
6354: fprintf(ficlog,"and correlation matrix of one-step probabilities: result on file '%s' \n",fileresprobcor);
6355: pstamp(ficresprob);
6356: fprintf(ficresprob,"#One-step probabilities and stand. devi in ()\n");
6357: fprintf(ficresprob,"# Age");
6358: pstamp(ficresprobcov);
6359: fprintf(ficresprobcov,"#One-step probabilities and covariance matrix\n");
6360: fprintf(ficresprobcov,"# Age");
6361: pstamp(ficresprobcor);
6362: fprintf(ficresprobcor,"#One-step probabilities and correlation matrix\n");
6363: fprintf(ficresprobcor,"# Age");
1.126 brouard 6364:
6365:
1.222 brouard 6366: for(i=1; i<=nlstate;i++)
6367: for(j=1; j<=(nlstate+ndeath);j++){
6368: fprintf(ficresprob," p%1d-%1d (SE)",i,j);
6369: fprintf(ficresprobcov," p%1d-%1d ",i,j);
6370: fprintf(ficresprobcor," p%1d-%1d ",i,j);
6371: }
6372: /* fprintf(ficresprob,"\n");
6373: fprintf(ficresprobcov,"\n");
6374: fprintf(ficresprobcor,"\n");
6375: */
6376: xp=vector(1,npar);
6377: dnewm=matrix(1,(nlstate)*(nlstate+ndeath),1,npar);
6378: doldm=matrix(1,(nlstate)*(nlstate+ndeath),1,(nlstate)*(nlstate+ndeath));
6379: mu=matrix(1,(nlstate)*(nlstate+ndeath), (int) bage, (int)fage);
6380: varpij=ma3x(1,nlstate*(nlstate+ndeath),1,nlstate*(nlstate+ndeath),(int) bage, (int) fage);
6381: first=1;
6382: fprintf(ficgp,"\n# Routine varprob");
6383: fprintf(fichtm,"\n<li><h4> Computing and drawing one step probabilities with their confidence intervals</h4></li>\n");
6384: fprintf(fichtm,"\n");
6385:
1.266 brouard 6386: fprintf(fichtm,"\n<li><h4> <a href=\"%s\">Matrix of variance-covariance of one-step probabilities (drawings)</a></h4> this page is important in order to visualize confidence intervals and especially correlation between disability and recovery, or more generally, way in and way back. %s</li>\n",optionfilehtmcov,optionfilehtmcov);
1.222 brouard 6387: 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);
6388: fprintf(fichtmcov,"\nEllipsoids of confidence centered on point (p<inf>ij</inf>, p<inf>kl</inf>) are estimated \
1.126 brouard 6389: and drawn. It helps understanding how is the covariance between two incidences.\
6390: They are expressed in year<sup>-1</sup> in order to be less dependent of stepm.<br>\n");
1.222 brouard 6391: 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 6392: It can be understood this way: if pij and pkl where uncorrelated the (2x2) matrix of covariance \
6393: would have been (1/(var pij), 0 , 0, 1/(var pkl)), and the confidence interval would be 2 \
6394: standard deviations wide on each axis. <br>\
6395: Now, if both incidences are correlated (usual case) we diagonalised the inverse of the covariance matrix\
6396: and made the appropriate rotation to look at the uncorrelated principal directions.<br>\
6397: To be simple, these graphs help to understand the significativity of each parameter in relation to a second other one.<br> \n");
6398:
1.222 brouard 6399: cov[1]=1;
6400: /* tj=cptcoveff; */
1.225 brouard 6401: tj = (int) pow(2,cptcoveff);
1.222 brouard 6402: if (cptcovn<1) {tj=1;ncodemax[1]=1;}
6403: j1=0;
1.224 brouard 6404: for(j1=1; j1<=tj;j1++){ /* For each valid combination of covariates or only once*/
1.222 brouard 6405: if (cptcovn>0) {
6406: fprintf(ficresprob, "\n#********** Variable ");
1.225 brouard 6407: for (z1=1; z1<=cptcoveff; z1++) fprintf(ficresprob, "V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
1.222 brouard 6408: fprintf(ficresprob, "**********\n#\n");
6409: fprintf(ficresprobcov, "\n#********** Variable ");
1.225 brouard 6410: for (z1=1; z1<=cptcoveff; z1++) fprintf(ficresprobcov, "V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
1.222 brouard 6411: fprintf(ficresprobcov, "**********\n#\n");
1.220 brouard 6412:
1.222 brouard 6413: fprintf(ficgp, "\n#********** Variable ");
1.225 brouard 6414: for (z1=1; z1<=cptcoveff; z1++) fprintf(ficgp, " V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
1.222 brouard 6415: fprintf(ficgp, "**********\n#\n");
1.220 brouard 6416:
6417:
1.222 brouard 6418: fprintf(fichtmcov, "\n<hr size=\"2\" color=\"#EC5E5E\">********** Variable ");
1.225 brouard 6419: for (z1=1; z1<=cptcoveff; z1++) fprintf(fichtm, "V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
1.222 brouard 6420: fprintf(fichtmcov, "**********\n<hr size=\"2\" color=\"#EC5E5E\">");
1.220 brouard 6421:
1.222 brouard 6422: fprintf(ficresprobcor, "\n#********** Variable ");
1.225 brouard 6423: for (z1=1; z1<=cptcoveff; z1++) fprintf(ficresprobcor, "V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
1.222 brouard 6424: fprintf(ficresprobcor, "**********\n#");
6425: if(invalidvarcomb[j1]){
6426: fprintf(ficgp,"\n#Combination (%d) ignored because no cases \n",j1);
6427: fprintf(fichtmcov,"\n<h3>Combination (%d) ignored because no cases </h3>\n",j1);
6428: continue;
6429: }
6430: }
6431: gradg=matrix(1,npar,1,(nlstate)*(nlstate+ndeath));
6432: trgradg=matrix(1,(nlstate)*(nlstate+ndeath),1,npar);
6433: gp=vector(1,(nlstate)*(nlstate+ndeath));
6434: gm=vector(1,(nlstate)*(nlstate+ndeath));
6435: for (age=bage; age<=fage; age ++){
6436: cov[2]=age;
6437: if(nagesqr==1)
6438: cov[3]= age*age;
6439: for (k=1; k<=cptcovn;k++) {
6440: cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(j1,k)];
6441: /*cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(j1,Tvar[k])];*//* j1 1 2 3 4
6442: * 1 1 1 1 1
6443: * 2 2 1 1 1
6444: * 3 1 2 1 1
6445: */
6446: /* nbcode[1][1]=0 nbcode[1][2]=1;*/
6447: }
6448: /* for (k=1; k<=cptcovage;k++) cov[2+Tage[k]]=cov[2+Tage[k]]*cov[2]; */
6449: for (k=1; k<=cptcovage;k++) cov[2+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2];
6450: for (k=1; k<=cptcovprod;k++)
6451: cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)]*nbcode[Tvard[k][2]][codtabm(ij,k)];
1.220 brouard 6452:
6453:
1.222 brouard 6454: for(theta=1; theta <=npar; theta++){
6455: for(i=1; i<=npar; i++)
6456: xp[i] = x[i] + (i==theta ?delti[theta]:(double)0);
1.220 brouard 6457:
1.222 brouard 6458: pmij(pmmij,cov,ncovmodel,xp,nlstate);
1.220 brouard 6459:
1.222 brouard 6460: k=0;
6461: for(i=1; i<= (nlstate); i++){
6462: for(j=1; j<=(nlstate+ndeath);j++){
6463: k=k+1;
6464: gp[k]=pmmij[i][j];
6465: }
6466: }
1.220 brouard 6467:
1.222 brouard 6468: for(i=1; i<=npar; i++)
6469: xp[i] = x[i] - (i==theta ?delti[theta]:(double)0);
1.220 brouard 6470:
1.222 brouard 6471: pmij(pmmij,cov,ncovmodel,xp,nlstate);
6472: k=0;
6473: for(i=1; i<=(nlstate); i++){
6474: for(j=1; j<=(nlstate+ndeath);j++){
6475: k=k+1;
6476: gm[k]=pmmij[i][j];
6477: }
6478: }
1.220 brouard 6479:
1.222 brouard 6480: for(i=1; i<= (nlstate)*(nlstate+ndeath); i++)
6481: gradg[theta][i]=(gp[i]-gm[i])/(double)2./delti[theta];
6482: }
1.126 brouard 6483:
1.222 brouard 6484: for(j=1; j<=(nlstate)*(nlstate+ndeath);j++)
6485: for(theta=1; theta <=npar; theta++)
6486: trgradg[j][theta]=gradg[theta][j];
1.220 brouard 6487:
1.222 brouard 6488: matprod2(dnewm,trgradg,1,(nlstate)*(nlstate+ndeath),1,npar,1,npar,matcov);
6489: matprod2(doldm,dnewm,1,(nlstate)*(nlstate+ndeath),1,npar,1,(nlstate)*(nlstate+ndeath),gradg);
1.220 brouard 6490:
1.222 brouard 6491: pmij(pmmij,cov,ncovmodel,x,nlstate);
1.220 brouard 6492:
1.222 brouard 6493: k=0;
6494: for(i=1; i<=(nlstate); i++){
6495: for(j=1; j<=(nlstate+ndeath);j++){
6496: k=k+1;
6497: mu[k][(int) age]=pmmij[i][j];
6498: }
6499: }
6500: for(i=1;i<=(nlstate)*(nlstate+ndeath);i++)
6501: for(j=1;j<=(nlstate)*(nlstate+ndeath);j++)
6502: varpij[i][j][(int)age] = doldm[i][j];
1.220 brouard 6503:
1.222 brouard 6504: /*printf("\n%d ",(int)age);
6505: for (i=1; i<=(nlstate)*(nlstate+ndeath);i++){
6506: printf("%e [%e ;%e] ",gm[i],gm[i]-2*sqrt(doldm[i][i]),gm[i]+2*sqrt(doldm[i][i]));
6507: fprintf(ficlog,"%e [%e ;%e] ",gm[i],gm[i]-2*sqrt(doldm[i][i]),gm[i]+2*sqrt(doldm[i][i]));
6508: }*/
1.220 brouard 6509:
1.222 brouard 6510: fprintf(ficresprob,"\n%d ",(int)age);
6511: fprintf(ficresprobcov,"\n%d ",(int)age);
6512: fprintf(ficresprobcor,"\n%d ",(int)age);
1.220 brouard 6513:
1.222 brouard 6514: for (i=1; i<=(nlstate)*(nlstate+ndeath);i++)
6515: fprintf(ficresprob,"%11.3e (%11.3e) ",mu[i][(int) age],sqrt(varpij[i][i][(int)age]));
6516: for (i=1; i<=(nlstate)*(nlstate+ndeath);i++){
6517: fprintf(ficresprobcov,"%11.3e ",mu[i][(int) age]);
6518: fprintf(ficresprobcor,"%11.3e ",mu[i][(int) age]);
6519: }
6520: i=0;
6521: for (k=1; k<=(nlstate);k++){
6522: for (l=1; l<=(nlstate+ndeath);l++){
6523: i++;
6524: fprintf(ficresprobcov,"\n%d %d-%d",(int)age,k,l);
6525: fprintf(ficresprobcor,"\n%d %d-%d",(int)age,k,l);
6526: for (j=1; j<=i;j++){
6527: /* printf(" k=%d l=%d i=%d j=%d\n",k,l,i,j);fflush(stdout); */
6528: fprintf(ficresprobcov," %11.3e",varpij[i][j][(int)age]);
6529: fprintf(ficresprobcor," %11.3e",varpij[i][j][(int) age]/sqrt(varpij[i][i][(int) age])/sqrt(varpij[j][j][(int)age]));
6530: }
6531: }
6532: }/* end of loop for state */
6533: } /* end of loop for age */
6534: free_vector(gp,1,(nlstate+ndeath)*(nlstate+ndeath));
6535: free_vector(gm,1,(nlstate+ndeath)*(nlstate+ndeath));
6536: free_matrix(trgradg,1,(nlstate+ndeath)*(nlstate+ndeath),1,npar);
6537: free_matrix(gradg,1,(nlstate+ndeath)*(nlstate+ndeath),1,npar);
6538:
6539: /* Confidence intervalle of pij */
6540: /*
6541: fprintf(ficgp,"\nunset parametric;unset label");
6542: fprintf(ficgp,"\nset log y;unset log x; set xlabel \"Age\";set ylabel \"probability (year-1)\"");
6543: fprintf(ficgp,"\nset ter png small\nset size 0.65,0.65");
6544: 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);
6545: fprintf(fichtm,"\n<br><img src=\"pijgr%s.png\"> ",optionfilefiname);
6546: fprintf(ficgp,"\nset out \"pijgr%s.png\"",optionfilefiname);
6547: fprintf(ficgp,"\nplot \"%s\" every :::%d::%d u 1:2 \"\%%lf",k1,k2,xfilevarprob);
6548: */
6549:
6550: /* Drawing ellipsoids of confidence of two variables p(k1-l1,k2-l2)*/
6551: first1=1;first2=2;
6552: for (k2=1; k2<=(nlstate);k2++){
6553: for (l2=1; l2<=(nlstate+ndeath);l2++){
6554: if(l2==k2) continue;
6555: j=(k2-1)*(nlstate+ndeath)+l2;
6556: for (k1=1; k1<=(nlstate);k1++){
6557: for (l1=1; l1<=(nlstate+ndeath);l1++){
6558: if(l1==k1) continue;
6559: i=(k1-1)*(nlstate+ndeath)+l1;
6560: if(i<=j) continue;
6561: for (age=bage; age<=fage; age ++){
6562: if ((int)age %5==0){
6563: v1=varpij[i][i][(int)age]/stepm*YEARM/stepm*YEARM;
6564: v2=varpij[j][j][(int)age]/stepm*YEARM/stepm*YEARM;
6565: cv12=varpij[i][j][(int)age]/stepm*YEARM/stepm*YEARM;
6566: mu1=mu[i][(int) age]/stepm*YEARM ;
6567: mu2=mu[j][(int) age]/stepm*YEARM;
6568: c12=cv12/sqrt(v1*v2);
6569: /* Computing eigen value of matrix of covariance */
6570: lc1=((v1+v2)+sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
6571: lc2=((v1+v2)-sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
6572: if ((lc2 <0) || (lc1 <0) ){
6573: if(first2==1){
6574: first1=0;
6575: 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);
6576: }
6577: 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);
6578: /* lc1=fabs(lc1); */ /* If we want to have them positive */
6579: /* lc2=fabs(lc2); */
6580: }
1.220 brouard 6581:
1.222 brouard 6582: /* Eigen vectors */
6583: v11=(1./sqrt(1+(v1-lc1)*(v1-lc1)/cv12/cv12));
6584: /*v21=sqrt(1.-v11*v11); *//* error */
6585: v21=(lc1-v1)/cv12*v11;
6586: v12=-v21;
6587: v22=v11;
6588: tnalp=v21/v11;
6589: if(first1==1){
6590: first1=0;
6591: 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);
6592: }
6593: 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);
6594: /*printf(fignu*/
6595: /* mu1+ v11*lc1*cost + v12*lc2*sin(t) */
6596: /* mu2+ v21*lc1*cost + v22*lc2*sin(t) */
6597: if(first==1){
6598: first=0;
6599: fprintf(ficgp,"\n# Ellipsoids of confidence\n#\n");
6600: fprintf(ficgp,"\nset parametric;unset label");
6601: 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);
6602: fprintf(ficgp,"\nset ter svg size 640, 480");
1.266 brouard 6603: fprintf(fichtmcov,"\n<p><br>Ellipsoids of confidence cov(p%1d%1d,p%1d%1d) expressed in year<sup>-1</sup>\
1.220 brouard 6604: :<a href=\"%s_%d%1d%1d-%1d%1d.svg\"> \
1.201 brouard 6605: %s_%d%1d%1d-%1d%1d.svg</A>, ",k1,l1,k2,l2,\
1.222 brouard 6606: subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2, \
6607: subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
6608: fprintf(fichtmcov,"\n<br><img src=\"%s_%d%1d%1d-%1d%1d.svg\"> ",subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
6609: fprintf(fichtmcov,"\n<br> Correlation at age %d (%.3f),",(int) age, c12);
6610: fprintf(ficgp,"\nset out \"%s_%d%1d%1d-%1d%1d.svg\"",subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
6611: fprintf(ficgp,"\nset label \"%d\" at %11.3e,%11.3e center",(int) age, mu1,mu2);
6612: fprintf(ficgp,"\n# Age %d, p%1d%1d - p%1d%1d",(int) age, k1,l1,k2,l2);
6613: fprintf(ficgp,"\nplot [-pi:pi] %11.3e+ %.3f*(%11.3e*%11.3e*cos(t)+%11.3e*%11.3e*sin(t)), %11.3e +%.3f*(%11.3e*%11.3e*cos(t)+%11.3e*%11.3e*sin(t)) not", \
1.266 brouard 6614: mu1,std,v11,sqrt(lc1),v12,sqrt(fabs(lc2)), \
6615: mu2,std,v21,sqrt(lc1),v22,sqrt(fabs(lc2))); /* For gnuplot only */
1.222 brouard 6616: }else{
6617: first=0;
6618: fprintf(fichtmcov," %d (%.3f),",(int) age, c12);
6619: fprintf(ficgp,"\n# Age %d, p%1d%1d - p%1d%1d",(int) age, k1,l1,k2,l2);
6620: fprintf(ficgp,"\nset label \"%d\" at %11.3e,%11.3e center",(int) age, mu1,mu2);
6621: fprintf(ficgp,"\nreplot %11.3e+ %.3f*(%11.3e*%11.3e*cos(t)+%11.3e*%11.3e*sin(t)), %11.3e +%.3f*(%11.3e*%11.3e*cos(t)+%11.3e*%11.3e*sin(t)) not", \
1.266 brouard 6622: mu1,std,v11,sqrt(lc1),v12,sqrt(fabs(lc2)), \
6623: mu2,std,v21,sqrt(lc1),v22,sqrt(fabs(lc2)));
1.222 brouard 6624: }/* if first */
6625: } /* age mod 5 */
6626: } /* end loop age */
6627: fprintf(ficgp,"\nset out;\nset out \"%s_%d%1d%1d-%1d%1d.svg\";replot;set out;",subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
6628: first=1;
6629: } /*l12 */
6630: } /* k12 */
6631: } /*l1 */
6632: }/* k1 */
6633: } /* loop on combination of covariates j1 */
6634: free_ma3x(varpij,1,nlstate,1,nlstate+ndeath,(int) bage, (int)fage);
6635: free_matrix(mu,1,(nlstate+ndeath)*(nlstate+ndeath),(int) bage, (int)fage);
6636: free_matrix(doldm,1,(nlstate)*(nlstate+ndeath),1,(nlstate)*(nlstate+ndeath));
6637: free_matrix(dnewm,1,(nlstate)*(nlstate+ndeath),1,npar);
6638: free_vector(xp,1,npar);
6639: fclose(ficresprob);
6640: fclose(ficresprobcov);
6641: fclose(ficresprobcor);
6642: fflush(ficgp);
6643: fflush(fichtmcov);
6644: }
1.126 brouard 6645:
6646:
6647: /******************* Printing html file ***********/
1.201 brouard 6648: void printinghtml(char fileresu[], char title[], char datafile[], int firstpass, \
1.126 brouard 6649: int lastpass, int stepm, int weightopt, char model[],\
6650: int imx,int jmin, int jmax, double jmeanint,char rfileres[],\
1.258 brouard 6651: int popforecast, int mobilav, int prevfcast, int mobilavproj, int backcast, int estepm , \
1.213 brouard 6652: double jprev1, double mprev1,double anprev1, double dateprev1, \
6653: double jprev2, double mprev2,double anprev2, double dateprev2){
1.237 brouard 6654: int jj1, k1, i1, cpt, k4, nres;
1.126 brouard 6655:
6656: fprintf(fichtm,"<ul><li><a href='#firstorder'>Result files (first order: no variance)</a>\n \
6657: <li><a href='#secondorder'>Result files (second order (variance)</a>\n \
6658: </ul>");
1.237 brouard 6659: fprintf(fichtm,"<ul><li> model=1+age+%s\n \
6660: </ul>", model);
1.214 brouard 6661: fprintf(fichtm,"<ul><li><h4><a name='firstorder'>Result files (first order: no variance)</a></h4>\n");
6662: 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",
6663: jprev1, mprev1,anprev1,jprev2, mprev2,anprev2,subdirfext3(optionfilefiname,"PHTMFR_",".htm"),subdirfext3(optionfilefiname,"PHTMFR_",".htm"));
6664: 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 6665: jprev1, mprev1,anprev1,jprev2, mprev2,anprev2,subdirfext3(optionfilefiname,"PHTM_",".htm"),subdirfext3(optionfilefiname,"PHTM_",".htm"));
6666: fprintf(fichtm,", <a href=\"%s\">%s</a> (text file) <br>\n",subdirf2(fileresu,"P_"),subdirf2(fileresu,"P_"));
1.126 brouard 6667: fprintf(fichtm,"\
6668: - Estimated transition probabilities over %d (stepm) months: <a href=\"%s\">%s</a><br>\n ",
1.201 brouard 6669: stepm,subdirf2(fileresu,"PIJ_"),subdirf2(fileresu,"PIJ_"));
1.126 brouard 6670: fprintf(fichtm,"\
1.217 brouard 6671: - Estimated back transition probabilities over %d (stepm) months: <a href=\"%s\">%s</a><br>\n ",
6672: stepm,subdirf2(fileresu,"PIJB_"),subdirf2(fileresu,"PIJB_"));
6673: fprintf(fichtm,"\
1.126 brouard 6674: - Period (stable) prevalence in each health state: <a href=\"%s\">%s</a> <br>\n",
1.201 brouard 6675: subdirf2(fileresu,"PL_"),subdirf2(fileresu,"PL_"));
1.126 brouard 6676: fprintf(fichtm,"\
1.217 brouard 6677: - Period (stable) back prevalence in each health state: <a href=\"%s\">%s</a> <br>\n",
6678: subdirf2(fileresu,"PLB_"),subdirf2(fileresu,"PLB_"));
6679: fprintf(fichtm,"\
1.211 brouard 6680: - (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 6681: <a href=\"%s\">%s</a> <br>\n",
1.201 brouard 6682: estepm,subdirf2(fileresu,"E_"),subdirf2(fileresu,"E_"));
1.211 brouard 6683: if(prevfcast==1){
6684: fprintf(fichtm,"\
6685: - Prevalence projections by age and states: \
1.201 brouard 6686: <a href=\"%s\">%s</a> <br>\n</li>", subdirf2(fileresu,"F_"),subdirf2(fileresu,"F_"));
1.211 brouard 6687: }
1.126 brouard 6688:
6689:
1.225 brouard 6690: m=pow(2,cptcoveff);
1.222 brouard 6691: if (cptcovn < 1) {m=1;ncodemax[1]=1;}
1.126 brouard 6692:
1.264 brouard 6693: fprintf(fichtm," \n<ul><li><b>Graphs</b></li><p>");
6694:
6695: jj1=0;
6696:
6697: fprintf(fichtm," \n<ul>");
6698: for(nres=1; nres <= nresult; nres++) /* For each resultline */
6699: for(k1=1; k1<=m;k1++){ /* For each combination of covariate */
6700: if(m != 1 && TKresult[nres]!= k1)
6701: continue;
6702: jj1++;
6703: if (cptcovn > 0) {
6704: fprintf(fichtm,"\n<li><a size=\"1\" color=\"#EC5E5E\" href=\"#rescov");
6705: for (cpt=1; cpt<=cptcoveff;cpt++){
6706: fprintf(fichtm,"_V%d=%d_",Tvresult[nres][cpt],(int)Tresult[nres][cpt]);
6707: }
6708: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
6709: fprintf(fichtm,"_V%d=%f_",Tvqresult[nres][k4],Tqresult[nres][k4]);
6710: }
6711: fprintf(fichtm,"\">");
6712:
6713: /* if(nqfveff+nqtveff 0) */ /* Test to be done */
6714: fprintf(fichtm,"************ Results for covariates");
6715: for (cpt=1; cpt<=cptcoveff;cpt++){
6716: fprintf(fichtm," V%d=%d ",Tvresult[nres][cpt],(int)Tresult[nres][cpt]);
6717: }
6718: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
6719: fprintf(fichtm," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
6720: }
6721: if(invalidvarcomb[k1]){
6722: fprintf(fichtm," Warning Combination (%d) ignored because no cases ",k1);
6723: continue;
6724: }
6725: fprintf(fichtm,"</a></li>");
6726: } /* cptcovn >0 */
6727: }
6728: fprintf(fichtm," \n</ul>");
6729:
1.222 brouard 6730: jj1=0;
1.237 brouard 6731:
6732: for(nres=1; nres <= nresult; nres++) /* For each resultline */
1.241 brouard 6733: for(k1=1; k1<=m;k1++){ /* For each combination of covariate */
1.253 brouard 6734: if(m != 1 && TKresult[nres]!= k1)
1.237 brouard 6735: continue;
1.220 brouard 6736:
1.222 brouard 6737: /* for(i1=1; i1<=ncodemax[k1];i1++){ */
6738: jj1++;
6739: if (cptcovn > 0) {
1.264 brouard 6740: fprintf(fichtm,"\n<p><a name=\"rescov");
6741: for (cpt=1; cpt<=cptcoveff;cpt++){
6742: fprintf(fichtm,"_V%d=%d_",Tvresult[nres][cpt],(int)Tresult[nres][cpt]);
6743: }
6744: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
6745: fprintf(fichtm,"_V%d=%f_",Tvqresult[nres][k4],Tqresult[nres][k4]);
6746: }
6747: fprintf(fichtm,"\"</a>");
6748:
1.222 brouard 6749: fprintf(fichtm,"<hr size=\"2\" color=\"#EC5E5E\">************ Results for covariates");
1.225 brouard 6750: for (cpt=1; cpt<=cptcoveff;cpt++){
1.237 brouard 6751: fprintf(fichtm," V%d=%d ",Tvresult[nres][cpt],(int)Tresult[nres][cpt]);
6752: printf(" V%d=%d ",Tvresult[nres][cpt],Tresult[nres][cpt]);fflush(stdout);
6753: /* fprintf(fichtm," V%d=%d ",Tvaraff[cpt],nbcode[Tvaraff[cpt]][codtabm(jj1,cpt)]); */
6754: /* printf(" V%d=%d ",Tvaraff[cpt],nbcode[Tvaraff[cpt]][codtabm(jj1,cpt)]);fflush(stdout); */
1.222 brouard 6755: }
1.237 brouard 6756: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
6757: fprintf(fichtm," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
6758: printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);fflush(stdout);
6759: }
6760:
1.230 brouard 6761: /* if(nqfveff+nqtveff 0) */ /* Test to be done */
1.222 brouard 6762: fprintf(fichtm," ************\n<hr size=\"2\" color=\"#EC5E5E\">");
6763: if(invalidvarcomb[k1]){
6764: fprintf(fichtm,"\n<h3>Combination (%d) ignored because no cases </h3>\n",k1);
6765: printf("\nCombination (%d) ignored because no cases \n",k1);
6766: continue;
6767: }
6768: }
6769: /* aij, bij */
1.259 brouard 6770: fprintf(fichtm,"<br>- Logit model (yours is: logit(pij)=log(pij/pii)= aij+ bij age+%s) as a function of age: <a href=\"%s_%d-1-%d.svg\">%s_%d-1-%d.svg</a><br> \
1.241 brouard 6771: <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 6772: /* Pij */
1.241 brouard 6773: 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> \
6774: <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 6775: /* Quasi-incidences */
6776: 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 6777: before but expressed in per year i.e. quasi incidences if stepm is small and probabilities too, \
1.211 brouard 6778: 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 6779: 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> \
6780: <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 6781: /* Survival functions (period) in state j */
6782: for(cpt=1; cpt<=nlstate;cpt++){
1.241 brouard 6783: 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> \
6784: <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 6785: }
6786: /* State specific survival functions (period) */
6787: for(cpt=1; cpt<=nlstate;cpt++){
6788: fprintf(fichtm,"<br>\n- Survival functions from state %d in each live state and total.\
1.220 brouard 6789: Or probability to survive in various states (1 to %d) being in state %d at different ages. \
1.241 brouard 6790: <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 6791: }
6792: /* Period (stable) prevalence in each health state */
6793: for(cpt=1; cpt<=nlstate;cpt++){
1.264 brouard 6794: fprintf(fichtm,"<br>\n- Convergence to period (stable) prevalence in state %d. Or probability for a person being in state (1 to %d) at different ages, to be in state %d some years after. <a href=\"%s_%d-%d-%d.svg\">%s_%d-%d-%d.svg</a><br> \
6795: <img src=\"%s_%d-%d-%d.svg\">", cpt, nlstate, cpt, subdirf2(optionfilefiname,"P_"),cpt,k1,nres,subdirf2(optionfilefiname,"P_"),cpt,k1,nres,subdirf2(optionfilefiname,"P_"),cpt,k1,nres);
1.222 brouard 6796: }
6797: if(backcast==1){
6798: /* Period (stable) back prevalence in each health state */
6799: for(cpt=1; cpt<=nlstate;cpt++){
1.264 brouard 6800: fprintf(fichtm,"<br>\n- Convergence to mixed (stable) back prevalence in state %d. Or probability for a person to be in state %d at a younger age, knowing that she/he was in state (1 to %d) at different older ages. <a href=\"%s_%d-%d-%d.svg\">%s_%d-%d-%d.svg</a><br> \
1.241 brouard 6801: <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 6802: }
1.217 brouard 6803: }
1.222 brouard 6804: if(prevfcast==1){
6805: /* Projection of prevalence up to period (stable) prevalence in each health state */
6806: for(cpt=1; cpt<=nlstate;cpt++){
1.268 ! brouard 6807: fprintf(fichtm,"<br>\n- Projection of cross-sectional prevalence (estimated with cases observed from %.1f to %.1f and mobil_average=%d) up to period (stable) prevalence in state %d. Or probability to be in state %d being in an observed weighted state (from 1 to %d). <a href=\"%s_%d-%d-%d.svg\">%s_%d-%d-%d.svg</a><br> \
1.258 brouard 6808: <img src=\"%s_%d-%d-%d.svg\">", dateprev1, dateprev2, mobilavproj, cpt, cpt, nlstate, subdirf2(optionfilefiname,"PROJ_"),cpt,k1,nres,subdirf2(optionfilefiname,"PROJ_"),cpt,k1,nres,subdirf2(optionfilefiname,"PROJ_"),cpt,k1,nres);
1.222 brouard 6809: }
6810: }
1.268 ! brouard 6811: if(backcast==1){
! 6812: /* Back projection of prevalence up to stable (mixed) back-prevalence in each health state */
! 6813: for(cpt=1; cpt<=nlstate;cpt++){
! 6814: fprintf(fichtm,"<br>\n- Back projection of cross-sectional prevalence (estimated with cases observed from %.1f to %.1f and mobil_average=%d) up to stable (mixed) back prevalence in state %d. Or probability to have been in an state %d, knowing that the person was in either state (1 or %d) with weights corresponding to observed prevalence at different ages. <a href=\"%s_%d-%d-%d.svg\">%s_%d-%d-%d.svg</a><br> \
! 6815: <img src=\"%s_%d-%d-%d.svg\">", dateprev1, dateprev2, mobilavproj, cpt, cpt, nlstate, subdirf2(optionfilefiname,"PROJB_"),cpt,k1,nres,subdirf2(optionfilefiname,"PROJB_"),cpt,k1,nres,subdirf2(optionfilefiname,"PROJB_"),cpt,k1,nres);
! 6816: }
! 6817: }
1.220 brouard 6818:
1.222 brouard 6819: for(cpt=1; cpt<=nlstate;cpt++) {
1.241 brouard 6820: 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> \
6821: <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 6822: }
6823: /* } /\* end i1 *\/ */
6824: }/* End k1 */
6825: fprintf(fichtm,"</ul>");
1.126 brouard 6826:
1.222 brouard 6827: fprintf(fichtm,"\
1.126 brouard 6828: \n<br><li><h4> <a name='secondorder'>Result files (second order: variances)</a></h4>\n\
1.193 brouard 6829: - Parameter file with estimated parameters and covariance matrix: <a href=\"%s\">%s</a> <br> \
1.203 brouard 6830: - 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 6831: But because parameters are usually highly correlated (a higher incidence of disability \
6832: and a higher incidence of recovery can give very close observed transition) it might \
6833: be very useful to look not only at linear confidence intervals estimated from the \
6834: variances but at the covariance matrix. And instead of looking at the estimated coefficients \
6835: (parameters) of the logistic regression, it might be more meaningful to visualize the \
6836: covariance matrix of the one-step probabilities. \
6837: See page 'Matrix of variance-covariance of one-step probabilities' below. \n", rfileres,rfileres);
1.126 brouard 6838:
1.222 brouard 6839: fprintf(fichtm," - Standard deviation of one-step probabilities: <a href=\"%s\">%s</a> <br>\n",
6840: subdirf2(fileresu,"PROB_"),subdirf2(fileresu,"PROB_"));
6841: fprintf(fichtm,"\
1.126 brouard 6842: - Variance-covariance of one-step probabilities: <a href=\"%s\">%s</a> <br>\n",
1.222 brouard 6843: subdirf2(fileresu,"PROBCOV_"),subdirf2(fileresu,"PROBCOV_"));
1.126 brouard 6844:
1.222 brouard 6845: fprintf(fichtm,"\
1.126 brouard 6846: - Correlation matrix of one-step probabilities: <a href=\"%s\">%s</a> <br>\n",
1.222 brouard 6847: subdirf2(fileresu,"PROBCOR_"),subdirf2(fileresu,"PROBCOR_"));
6848: fprintf(fichtm,"\
1.126 brouard 6849: - 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): \
6850: <a href=\"%s\">%s</a> <br>\n</li>",
1.201 brouard 6851: estepm,subdirf2(fileresu,"CVE_"),subdirf2(fileresu,"CVE_"));
1.222 brouard 6852: fprintf(fichtm,"\
1.126 brouard 6853: - (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): \
6854: <a href=\"%s\">%s</a> <br>\n</li>",
1.201 brouard 6855: estepm,subdirf2(fileresu,"STDE_"),subdirf2(fileresu,"STDE_"));
1.222 brouard 6856: fprintf(fichtm,"\
1.128 brouard 6857: - 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 6858: estepm, subdirf2(fileresu,"V_"),subdirf2(fileresu,"V_"));
6859: fprintf(fichtm,"\
1.128 brouard 6860: - 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 6861: estepm, subdirf2(fileresu,"T_"),subdirf2(fileresu,"T_"));
6862: fprintf(fichtm,"\
1.126 brouard 6863: - Standard deviation of period (stable) prevalences: <a href=\"%s\">%s</a> <br>\n",\
1.222 brouard 6864: subdirf2(fileresu,"VPL_"),subdirf2(fileresu,"VPL_"));
1.126 brouard 6865:
6866: /* if(popforecast==1) fprintf(fichtm,"\n */
6867: /* - Prevalences forecasting: <a href=\"f%s\">f%s</a> <br>\n */
6868: /* - Population forecasting (if popforecast=1): <a href=\"pop%s\">pop%s</a> <br>\n */
6869: /* <br>",fileres,fileres,fileres,fileres); */
6870: /* else */
6871: /* 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 6872: fflush(fichtm);
6873: fprintf(fichtm," <ul><li><b>Graphs</b></li><p>");
1.126 brouard 6874:
1.225 brouard 6875: m=pow(2,cptcoveff);
1.222 brouard 6876: if (cptcovn < 1) {m=1;ncodemax[1]=1;}
1.126 brouard 6877:
1.222 brouard 6878: jj1=0;
1.237 brouard 6879:
1.241 brouard 6880: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.222 brouard 6881: for(k1=1; k1<=m;k1++){
1.253 brouard 6882: if(m != 1 && TKresult[nres]!= k1)
1.237 brouard 6883: continue;
1.222 brouard 6884: /* for(i1=1; i1<=ncodemax[k1];i1++){ */
6885: jj1++;
1.126 brouard 6886: if (cptcovn > 0) {
6887: fprintf(fichtm,"<hr size=\"2\" color=\"#EC5E5E\">************ Results for covariates");
1.225 brouard 6888: for (cpt=1; cpt<=cptcoveff;cpt++) /**< cptcoveff number of variables */
1.237 brouard 6889: fprintf(fichtm," V%d=%d ",Tvresult[nres][cpt],Tresult[nres][cpt]);
6890: /* fprintf(fichtm," V%d=%d ",Tvaraff[cpt],nbcode[Tvaraff[cpt]][codtabm(jj1,cpt)]); */
6891: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
6892: fprintf(fichtm," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
6893: }
6894:
1.126 brouard 6895: fprintf(fichtm," ************\n<hr size=\"2\" color=\"#EC5E5E\">");
1.220 brouard 6896:
1.222 brouard 6897: if(invalidvarcomb[k1]){
6898: fprintf(fichtm,"\n<h4>Combination (%d) ignored because no cases </h4>\n",k1);
6899: continue;
6900: }
1.126 brouard 6901: }
6902: for(cpt=1; cpt<=nlstate;cpt++) {
1.258 brouard 6903: fprintf(fichtm,"\n<br>- Observed (cross-sectional with mov_average=%d) and period (incidence based) \
1.241 brouard 6904: prevalence (with 95%% confidence interval) in state (%d): <a href=\"%s_%d-%d-%d.svg\"> %s_%d-%d-%d.svg</a>\n <br>\
1.258 brouard 6905: <img src=\"%s_%d-%d-%d.svg\">",mobilav,cpt,subdirf2(optionfilefiname,"V_"),cpt,k1,nres,subdirf2(optionfilefiname,"V_"),cpt,k1,nres,subdirf2(optionfilefiname,"V_"),cpt,k1,nres);
1.126 brouard 6906: }
6907: fprintf(fichtm,"\n<br>- Total life expectancy by age and \
1.128 brouard 6908: health expectancies in states (1) and (2). If popbased=1 the smooth (due to the model) \
6909: true period expectancies (those weighted with period prevalences are also\
6910: drawn in addition to the population based expectancies computed using\
1.241 brouard 6911: observed and cahotic prevalences: <a href=\"%s_%d-%d.svg\">%s_%d-%d.svg</a>\n<br>\
6912: <img src=\"%s_%d-%d.svg\">",subdirf2(optionfilefiname,"E_"),k1,nres,subdirf2(optionfilefiname,"E_"),k1,nres,subdirf2(optionfilefiname,"E_"),k1,nres);
1.222 brouard 6913: /* } /\* end i1 *\/ */
6914: }/* End k1 */
1.241 brouard 6915: }/* End nres */
1.222 brouard 6916: fprintf(fichtm,"</ul>");
6917: fflush(fichtm);
1.126 brouard 6918: }
6919:
6920: /******************* Gnuplot file **************/
1.268 ! brouard 6921: void printinggnuplot(char fileresu[], char optionfilefiname[], double ageminpar, double agemaxpar, double fage , int prevfcast, int backcast, char pathc[], double p[], int offyear, int offbyear){
1.126 brouard 6922:
6923: char dirfileres[132],optfileres[132];
1.264 brouard 6924: char gplotcondition[132], gplotlabel[132];
1.237 brouard 6925: 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 6926: int lv=0, vlv=0, kl=0;
1.130 brouard 6927: int ng=0;
1.201 brouard 6928: int vpopbased;
1.223 brouard 6929: int ioffset; /* variable offset for columns */
1.235 brouard 6930: int nres=0; /* Index of resultline */
1.266 brouard 6931: int istart=1; /* For starting graphs in projections */
1.219 brouard 6932:
1.126 brouard 6933: /* if((ficgp=fopen(optionfilegnuplot,"a"))==NULL) { */
6934: /* printf("Problem with file %s",optionfilegnuplot); */
6935: /* fprintf(ficlog,"Problem with file %s",optionfilegnuplot); */
6936: /* } */
6937:
6938: /*#ifdef windows */
6939: fprintf(ficgp,"cd \"%s\" \n",pathc);
1.223 brouard 6940: /*#endif */
1.225 brouard 6941: m=pow(2,cptcoveff);
1.126 brouard 6942:
1.202 brouard 6943: /* Contribution to likelihood */
6944: /* Plot the probability implied in the likelihood */
1.223 brouard 6945: fprintf(ficgp,"\n# Contributions to the Likelihood, mle >=1. For mle=4 no interpolation, pure matrix products.\n#\n");
6946: fprintf(ficgp,"\n set log y; unset log x;set xlabel \"Age\"; set ylabel \"Likelihood (-2Log(L))\";");
6947: /* fprintf(ficgp,"\nset ter svg size 640, 480"); */ /* Too big for svg */
6948: fprintf(ficgp,"\nset ter pngcairo size 640, 480");
1.204 brouard 6949: /* nice for mle=4 plot by number of matrix products.
1.202 brouard 6950: replot "rrtest1/toto.txt" u 2:($4 == 1 && $5==2 ? $9 : 1/0):5 t "p12" with point lc 1 */
6951: /* replot exp(p1+p2*x)/(1+exp(p1+p2*x)+exp(p3+p4*x)+exp(p5+p6*x)) t "p12(x)" */
1.223 brouard 6952: /* fprintf(ficgp,"\nset out \"%s.svg\";",subdirf2(optionfilefiname,"ILK_")); */
6953: fprintf(ficgp,"\nset out \"%s-dest.png\";",subdirf2(optionfilefiname,"ILK_"));
6954: 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));
6955: fprintf(ficgp,"\nset out \"%s-ori.png\";",subdirf2(optionfilefiname,"ILK_"));
6956: 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));
6957: for (i=1; i<= nlstate ; i ++) {
6958: fprintf(ficgp,"\nset out \"%s-p%dj.png\";set ylabel \"Probability for each individual/wave\";",subdirf2(optionfilefiname,"ILK_"),i);
6959: fprintf(ficgp,"unset log;\n# plot weighted, mean weight should have point size of 0.5\n plot \"%s\"",subdirf(fileresilk));
6960: 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);
6961: for (j=2; j<= nlstate+ndeath ; j ++) {
6962: 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);
6963: }
6964: fprintf(ficgp,";\nset out; unset ylabel;\n");
6965: }
6966: /* 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 */
6967: /* fprintf(ficgp,"\nset log y;plot \"%s\" u 2:(-$11):3 t \"All sample, all transitions\" with dots lc variable",subdirf(fileresilk)); */
6968: /* fprintf(ficgp,"\nreplot \"%s\" u 2:($3 <= 3 ? -$11 : 1/0):3 t \"First 3 individuals\" with line lc variable", subdirf(fileresilk)); */
6969: fprintf(ficgp,"\nset out;unset log\n");
6970: /* fprintf(ficgp,"\nset out \"%s.svg\"; replot; set out; # bug gnuplot",subdirf2(optionfilefiname,"ILK_")); */
1.202 brouard 6971:
1.126 brouard 6972: strcpy(dirfileres,optionfilefiname);
6973: strcpy(optfileres,"vpl");
1.223 brouard 6974: /* 1eme*/
1.238 brouard 6975: for (cpt=1; cpt<= nlstate ; cpt ++){ /* For each live state */
6976: for (k1=1; k1<= m ; k1 ++){ /* For each valid combination of covariate */
1.236 brouard 6977: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.238 brouard 6978: /* plot [100000000000000000000:-100000000000000000000] "mysbiaspar/vplrmysbiaspar.txt to check */
1.253 brouard 6979: if(m != 1 && TKresult[nres]!= k1)
1.238 brouard 6980: continue;
6981: /* We are interested in selected combination by the resultline */
1.246 brouard 6982: /* printf("\n# 1st: Period (stable) prevalence with CI: 'VPL_' files and live state =%d ", cpt); */
1.238 brouard 6983: fprintf(ficgp,"\n# 1st: Period (stable) prevalence with CI: 'VPL_' files and live state =%d ", cpt);
1.264 brouard 6984: strcpy(gplotlabel,"(");
1.238 brouard 6985: for (k=1; k<=cptcoveff; k++){ /* For each covariate k get corresponding value lv for combination k1 */
6986: lv= decodtabm(k1,k,cptcoveff); /* Should be the value of the covariate corresponding to k1 combination */
6987: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
6988: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
6989: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
6990: vlv= nbcode[Tvaraff[k]][lv]; /* vlv is the value of the covariate lv, 0 or 1 */
6991: /* For each combination of covariate k1 (V1=1, V3=0), we printed the current covariate k and its value vlv */
1.246 brouard 6992: /* printf(" V%d=%d ",Tvaraff[k],vlv); */
1.238 brouard 6993: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 6994: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.238 brouard 6995: }
6996: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
1.246 brouard 6997: /* printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
1.238 brouard 6998: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 6999: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
7000: }
7001: strcpy(gplotlabel+strlen(gplotlabel),")");
1.246 brouard 7002: /* printf("\n#\n"); */
1.238 brouard 7003: fprintf(ficgp,"\n#\n");
7004: if(invalidvarcomb[k1]){
1.260 brouard 7005: /*k1=k1-1;*/ /* To be checked */
1.238 brouard 7006: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7007: continue;
7008: }
1.235 brouard 7009:
1.241 brouard 7010: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"V_"),cpt,k1,nres);
7011: fprintf(ficgp,"\n#set out \"V_%s_%d-%d-%d.svg\" \n",optionfilefiname,cpt,k1,nres);
1.264 brouard 7012: fprintf(ficgp,"set label \"Alive state %d %s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",cpt,gplotlabel);
1.260 brouard 7013: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability\" \nset ter svg size 640, 480\nplot [%.f:%.f] \"%s\" every :::%d::%d u 1:($2==%d ? $3:1/0) \"%%lf %%lf",ageminpar,fage,subdirf2(fileresu,"VPL_"),nres-1,nres-1,nres);
7014: /* 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); */
7015: /* k1-1 error should be nres-1*/
1.238 brouard 7016: for (i=1; i<= nlstate ; i ++) {
7017: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
7018: else fprintf(ficgp," %%*lf (%%*lf)");
7019: }
1.260 brouard 7020: fprintf(ficgp,"\" t\"Period (stable) prevalence\" w l lt 0,\"%s\" every :::%d::%d u 1:($2==%d ? $3+1.96*$4 : 1/0) \"%%lf %%lf",subdirf2(fileresu,"VPL_"),nres-1,nres-1,nres);
1.238 brouard 7021: for (i=1; i<= nlstate ; i ++) {
7022: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
7023: else fprintf(ficgp," %%*lf (%%*lf)");
7024: }
1.260 brouard 7025: fprintf(ficgp,"\" t\"95%% CI\" w l lt 1,\"%s\" every :::%d::%d u 1:($2==%d ? $3-1.96*$4 : 1/0) \"%%lf %%lf",subdirf2(fileresu,"VPL_"),nres-1,nres-1,nres);
1.238 brouard 7026: for (i=1; i<= nlstate ; i ++) {
7027: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
7028: else fprintf(ficgp," %%*lf (%%*lf)");
7029: }
1.265 brouard 7030: /* fprintf(ficgp,"\" t\"\" w l lt 1,\"%s\" every :::%d::%d u 1:($%d) t\"Observed prevalence\" w l lt 2",subdirf2(fileresu,"P_"),k1-1,k1-1,2+4*(cpt-1)); */
7031:
7032: fprintf(ficgp,"\" t\"\" w l lt 1,\"%s\" u 1:((",subdirf2(fileresu,"P_"));
7033: if(cptcoveff ==0){
7034: fprintf(ficgp,"$%d)) t 'Observed prevalence in state %d' with line lt 3", 2+(cpt-1), cpt );
7035: }else{
7036: kl=0;
7037: for (k=1; k<=cptcoveff; k++){ /* For each combination of covariate */
7038: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate value corresponding to k1 combination and kth covariate */
7039: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7040: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7041: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7042: vlv= nbcode[Tvaraff[k]][lv];
7043: kl++;
7044: /* 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 *\/ */
7045: /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */
7046: /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */
7047: /* '' u 6:(($1==1 && $2==0 && $3==2 && $4==0)? $9/(1.-$15) : 1/0):($5==2000? 3:2) t 'p.1' with line lc variable*/
7048: if(k==cptcoveff){
7049: fprintf(ficgp,"$%d==%d && $%d==%d)? $%d : 1/0) t 'Observed prevalence in state %d' w l lt 2",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][lv], \
7050: 2+cptcoveff*2+3*(cpt-1), cpt ); /* 4 or 6 ?*/
7051: }else{
7052: fprintf(ficgp,"$%d==%d && $%d==%d && ",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][lv]);
7053: kl++;
7054: }
7055: } /* end covariate */
7056: } /* end if no covariate */
7057:
1.238 brouard 7058: if(backcast==1){ /* We need to get the corresponding values of the covariates involved in this combination k1 */
7059: /* fprintf(ficgp,",\"%s\" every :::%d::%d u 1:($%d) t\"Backward stable prevalence\" w l lt 3",subdirf2(fileresu,"PLB_"),k1-1,k1-1,1+cpt); */
1.242 brouard 7060: fprintf(ficgp,",\"%s\" u 1:((",subdirf2(fileresu,"PLB_")); /* Age is in 1, nres in 2 to be fixed */
1.238 brouard 7061: if(cptcoveff ==0){
1.245 brouard 7062: fprintf(ficgp,"$%d)) t 'Backward prevalence in state %d' with line lt 3", 2+(cpt-1), cpt );
1.238 brouard 7063: }else{
7064: kl=0;
7065: for (k=1; k<=cptcoveff; k++){ /* For each combination of covariate */
7066: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate value corresponding to k1 combination and kth covariate */
7067: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7068: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7069: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7070: vlv= nbcode[Tvaraff[k]][lv];
1.223 brouard 7071: kl++;
1.238 brouard 7072: /* 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 *\/ */
7073: /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */
7074: /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */
7075: /* '' u 6:(($1==1 && $2==0 && $3==2 && $4==0)? $9/(1.-$15) : 1/0):($5==2000? 3:2) t 'p.1' with line lc variable*/
7076: if(k==cptcoveff){
1.245 brouard 7077: fprintf(ficgp,"$%d==%d && $%d==%d)? $%d : 1/0) t 'Backward prevalence in state %d' w l lt 3",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][lv], \
1.242 brouard 7078: 2+cptcoveff*2+(cpt-1), cpt ); /* 4 or 6 ?*/
1.238 brouard 7079: }else{
7080: fprintf(ficgp,"$%d==%d && $%d==%d && ",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][lv]);
7081: kl++;
7082: }
7083: } /* end covariate */
7084: } /* end if no covariate */
1.268 ! brouard 7085: if(backcast == 1){
! 7086: fprintf(ficgp,", \"%s\" every :::%d::%d u 1:($2==%d ? $3:1/0) \"%%lf %%lf",subdirf2(fileresu,"VBL_"),nres-1,nres-1,nres);
! 7087: /* k1-1 error should be nres-1*/
! 7088: for (i=1; i<= nlstate ; i ++) {
! 7089: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
! 7090: else fprintf(ficgp," %%*lf (%%*lf)");
! 7091: }
! 7092: fprintf(ficgp,"\" t\"Backward (stable) prevalence\" w l lt 0,\"%s\" every :::%d::%d u 1:($2==%d ? $3+1.96*$4 : 1/0) \"%%lf %%lf",subdirf2(fileresu,"VBL_"),nres-1,nres-1,nres);
! 7093: for (i=1; i<= nlstate ; i ++) {
! 7094: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
! 7095: else fprintf(ficgp," %%*lf (%%*lf)");
! 7096: }
! 7097: fprintf(ficgp,"\" t\"95%% CI\" w l lt 1,\"%s\" every :::%d::%d u 1:($2==%d ? $3-1.96*$4 : 1/0) \"%%lf %%lf",subdirf2(fileresu,"VBL_"),nres-1,nres-1,nres);
! 7098: for (i=1; i<= nlstate ; i ++) {
! 7099: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
! 7100: else fprintf(ficgp," %%*lf (%%*lf)");
! 7101: }
! 7102: fprintf(ficgp,"\" t\"\" w l lt 1");
! 7103: } /* end if backprojcast */
1.238 brouard 7104: } /* end if backcast */
1.264 brouard 7105: fprintf(ficgp,"\nset out ;unset label;\n");
1.238 brouard 7106: } /* nres */
1.201 brouard 7107: } /* k1 */
7108: } /* cpt */
1.235 brouard 7109:
7110:
1.126 brouard 7111: /*2 eme*/
1.238 brouard 7112: for (k1=1; k1<= m ; k1 ++){
7113: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 7114: if(m != 1 && TKresult[nres]!= k1)
1.238 brouard 7115: continue;
7116: fprintf(ficgp,"\n# 2nd: Total life expectancy with CI: 't' files ");
1.264 brouard 7117: strcpy(gplotlabel,"(");
1.238 brouard 7118: for (k=1; k<=cptcoveff; k++){ /* For each covariate and each value */
1.225 brouard 7119: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate number corresponding to k1 combination */
1.223 brouard 7120: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7121: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7122: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7123: vlv= nbcode[Tvaraff[k]][lv];
7124: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 7125: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.211 brouard 7126: }
1.237 brouard 7127: /* for(k=1; k <= ncovds; k++){ */
1.236 brouard 7128: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
1.238 brouard 7129: printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.236 brouard 7130: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7131: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.238 brouard 7132: }
1.264 brouard 7133: strcpy(gplotlabel+strlen(gplotlabel),")");
1.211 brouard 7134: fprintf(ficgp,"\n#\n");
1.223 brouard 7135: if(invalidvarcomb[k1]){
7136: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7137: continue;
7138: }
1.219 brouard 7139:
1.241 brouard 7140: fprintf(ficgp,"\nset out \"%s_%d-%d.svg\" \n",subdirf2(optionfilefiname,"E_"),k1,nres);
1.238 brouard 7141: for(vpopbased=0; vpopbased <= popbased; vpopbased++){ /* Done for vpopbased=0 and vpopbased=1 if popbased==1*/
1.264 brouard 7142: fprintf(ficgp,"\nset label \"popbased %d %s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",vpopbased,gplotlabel);
7143: if(vpopbased==0){
1.238 brouard 7144: fprintf(ficgp,"set ylabel \"Years\" \nset ter svg size 640, 480\nplot [%.f:%.f] ",ageminpar,fage);
1.264 brouard 7145: }else
1.238 brouard 7146: fprintf(ficgp,"\nreplot ");
7147: for (i=1; i<= nlstate+1 ; i ++) {
7148: k=2*i;
1.261 brouard 7149: fprintf(ficgp,"\"%s\" every :::%d::%d u 1:($2==%d && $4!=0 ?$4 : 1/0) \"%%lf %%lf %%lf",subdirf2(fileresu,"T_"),nres-1,nres-1, vpopbased);
1.238 brouard 7150: for (j=1; j<= nlstate+1 ; j ++) {
7151: if (j==i) fprintf(ficgp," %%lf (%%lf)");
7152: else fprintf(ficgp," %%*lf (%%*lf)");
7153: }
7154: if (i== 1) fprintf(ficgp,"\" t\"TLE\" w l lt %d, \\\n",i);
7155: else fprintf(ficgp,"\" t\"LE in state (%d)\" w l lt %d, \\\n",i-1,i+1);
1.261 brouard 7156: fprintf(ficgp,"\"%s\" every :::%d::%d u 1:($2==%d && $4!=0 ? $4-$5*2 : 1/0) \"%%lf %%lf %%lf",subdirf2(fileresu,"T_"),nres-1,nres-1,vpopbased);
1.238 brouard 7157: for (j=1; j<= nlstate+1 ; j ++) {
7158: if (j==i) fprintf(ficgp," %%lf (%%lf)");
7159: else fprintf(ficgp," %%*lf (%%*lf)");
7160: }
7161: fprintf(ficgp,"\" t\"\" w l lt 0,");
1.261 brouard 7162: fprintf(ficgp,"\"%s\" every :::%d::%d u 1:($2==%d && $4!=0 ? $4+$5*2 : 1/0) \"%%lf %%lf %%lf",subdirf2(fileresu,"T_"),nres-1,nres-1,vpopbased);
1.238 brouard 7163: for (j=1; j<= nlstate+1 ; j ++) {
7164: if (j==i) fprintf(ficgp," %%lf (%%lf)");
7165: else fprintf(ficgp," %%*lf (%%*lf)");
7166: }
7167: if (i== (nlstate+1)) fprintf(ficgp,"\" t\"\" w l lt 0");
7168: else fprintf(ficgp,"\" t\"\" w l lt 0,\\\n");
7169: } /* state */
7170: } /* vpopbased */
1.264 brouard 7171: fprintf(ficgp,"\nset out;set out \"%s_%d-%d.svg\"; replot; set out; unset label;\n",subdirf2(optionfilefiname,"E_"),k1,nres); /* Buggy gnuplot */
1.238 brouard 7172: } /* end nres */
7173: } /* k1 end 2 eme*/
7174:
7175:
7176: /*3eme*/
7177: for (k1=1; k1<= m ; k1 ++){
7178: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 7179: if(m != 1 && TKresult[nres]!= k1)
1.238 brouard 7180: continue;
7181:
7182: for (cpt=1; cpt<= nlstate ; cpt ++) {
1.261 brouard 7183: fprintf(ficgp,"\n\n# 3d: Life expectancy with EXP_ files: combination=%d state=%d",k1, cpt);
1.264 brouard 7184: strcpy(gplotlabel,"(");
1.238 brouard 7185: for (k=1; k<=cptcoveff; k++){ /* For each covariate and each value */
7186: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate number corresponding to k1 combination */
7187: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7188: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7189: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7190: vlv= nbcode[Tvaraff[k]][lv];
7191: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 7192: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.238 brouard 7193: }
7194: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7195: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7196: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.238 brouard 7197: }
1.264 brouard 7198: strcpy(gplotlabel+strlen(gplotlabel),")");
1.238 brouard 7199: fprintf(ficgp,"\n#\n");
7200: if(invalidvarcomb[k1]){
7201: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7202: continue;
7203: }
7204:
7205: /* k=2+nlstate*(2*cpt-2); */
7206: k=2+(nlstate+1)*(cpt-1);
1.241 brouard 7207: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"EXP_"),cpt,k1,nres);
1.264 brouard 7208: fprintf(ficgp,"set label \"%s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",gplotlabel);
1.238 brouard 7209: fprintf(ficgp,"set ter svg size 640, 480\n\
1.261 brouard 7210: plot [%.f:%.f] \"%s\" every :::%d::%d u 1:%d t \"e%d1\" w l",ageminpar,fage,subdirf2(fileresu,"E_"),nres-1,nres-1,k,cpt);
1.238 brouard 7211: /*fprintf(ficgp,",\"e%s\" every :::%d::%d u 1:($%d-2*$%d) \"\%%lf ",fileres,k1-1,k1-1,k,k+1);
7212: for (i=1; i<= nlstate*2 ; i ++) fprintf(ficgp,"\%%lf (\%%lf) ");
7213: fprintf(ficgp,"\" t \"e%d1\" w l",cpt);
7214: fprintf(ficgp,",\"e%s\" every :::%d::%d u 1:($%d+2*$%d) \"\%%lf ",fileres,k1-1,k1-1,k,k+1);
7215: for (i=1; i<= nlstate*2 ; i ++) fprintf(ficgp,"\%%lf (\%%lf) ");
7216: fprintf(ficgp,"\" t \"e%d1\" w l",cpt);
1.219 brouard 7217:
1.238 brouard 7218: */
7219: for (i=1; i< nlstate ; i ++) {
1.261 brouard 7220: fprintf(ficgp," ,\"%s\" every :::%d::%d u 1:%d t \"e%d%d\" w l",subdirf2(fileresu,"E_"),nres-1,nres-1,k+i,cpt,i+1);
1.238 brouard 7221: /* 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 7222:
1.238 brouard 7223: }
1.261 brouard 7224: fprintf(ficgp," ,\"%s\" every :::%d::%d u 1:%d t \"e%d.\" w l",subdirf2(fileresu,"E_"),nres-1,nres-1,k+nlstate,cpt);
1.238 brouard 7225: }
1.264 brouard 7226: fprintf(ficgp,"\nunset label;\n");
1.238 brouard 7227: } /* end nres */
7228: } /* end kl 3eme */
1.126 brouard 7229:
1.223 brouard 7230: /* 4eme */
1.201 brouard 7231: /* Survival functions (period) from state i in state j by initial state i */
1.238 brouard 7232: for (k1=1; k1<=m; k1++){ /* For each covariate and each value */
7233: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 7234: if(m != 1 && TKresult[nres]!= k1)
1.223 brouard 7235: continue;
1.238 brouard 7236: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state cpt*/
1.264 brouard 7237: strcpy(gplotlabel,"(");
1.238 brouard 7238: fprintf(ficgp,"\n#\n#\n# Survival functions in state j : 'LIJ_' files, cov=%d state=%d",k1, cpt);
7239: for (k=1; k<=cptcoveff; k++){ /* For each covariate and each value */
7240: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate number corresponding to k1 combination */
7241: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7242: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7243: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7244: vlv= nbcode[Tvaraff[k]][lv];
7245: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 7246: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.238 brouard 7247: }
7248: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7249: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7250: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.238 brouard 7251: }
1.264 brouard 7252: strcpy(gplotlabel+strlen(gplotlabel),")");
1.238 brouard 7253: fprintf(ficgp,"\n#\n");
7254: if(invalidvarcomb[k1]){
7255: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7256: continue;
1.223 brouard 7257: }
1.238 brouard 7258:
1.241 brouard 7259: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"LIJ_"),cpt,k1,nres);
1.264 brouard 7260: fprintf(ficgp,"set label \"Alive state %d %s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",cpt,gplotlabel);
1.238 brouard 7261: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability to be alive\" \n\
7262: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
7263: k=3;
7264: for (i=1; i<= nlstate ; i ++){
7265: if(i==1){
7266: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJ_"));
7267: }else{
7268: fprintf(ficgp,", '' ");
7269: }
7270: l=(nlstate+ndeath)*(i-1)+1;
7271: fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d/($%d",k1,k+l+(cpt-1),k+l);
7272: for (j=2; j<= nlstate+ndeath ; j ++)
7273: fprintf(ficgp,"+$%d",k+l+j-1);
7274: fprintf(ficgp,")) t \"l(%d,%d)\" w l",i,cpt);
7275: } /* nlstate */
1.264 brouard 7276: fprintf(ficgp,"\nset out; unset label;\n");
1.238 brouard 7277: } /* end cpt state*/
7278: } /* end nres */
7279: } /* end covariate k1 */
7280:
1.220 brouard 7281: /* 5eme */
1.201 brouard 7282: /* Survival functions (period) from state i in state j by final state j */
1.238 brouard 7283: for (k1=1; k1<= m ; k1++){ /* For each covariate combination if any */
7284: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 7285: if(m != 1 && TKresult[nres]!= k1)
1.227 brouard 7286: continue;
1.238 brouard 7287: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each inital state */
1.264 brouard 7288: strcpy(gplotlabel,"(");
1.238 brouard 7289: 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);
7290: for (k=1; k<=cptcoveff; k++){ /* For each covariate and each value */
7291: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate number corresponding to k1 combination */
7292: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7293: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7294: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7295: vlv= nbcode[Tvaraff[k]][lv];
7296: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 7297: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.238 brouard 7298: }
7299: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7300: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7301: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.238 brouard 7302: }
1.264 brouard 7303: strcpy(gplotlabel+strlen(gplotlabel),")");
1.238 brouard 7304: fprintf(ficgp,"\n#\n");
7305: if(invalidvarcomb[k1]){
7306: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7307: continue;
7308: }
1.227 brouard 7309:
1.241 brouard 7310: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"LIJT_"),cpt,k1,nres);
1.264 brouard 7311: fprintf(ficgp,"set label \"Alive state %d %s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",cpt,gplotlabel);
1.238 brouard 7312: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability to be alive\" \n\
7313: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
7314: k=3;
7315: for (j=1; j<= nlstate ; j ++){ /* Lived in state j */
7316: if(j==1)
7317: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJ_"));
7318: else
7319: fprintf(ficgp,", '' ");
7320: l=(nlstate+ndeath)*(cpt-1) +j;
7321: fprintf(ficgp," u (($1==%d && (floor($2)%%5 == 0)) ? ($3):1/0):($%d",k1,k+l);
7322: /* for (i=2; i<= nlstate+ndeath ; i ++) */
7323: /* fprintf(ficgp,"+$%d",k+l+i-1); */
7324: fprintf(ficgp,") t \"l(%d,%d)\" w l",cpt,j);
7325: } /* nlstate */
7326: fprintf(ficgp,", '' ");
7327: fprintf(ficgp," u (($1==%d && (floor($2)%%5 == 0)) ? ($3):1/0):(",k1);
7328: for (j=1; j<= nlstate ; j ++){ /* Lived in state j */
7329: l=(nlstate+ndeath)*(cpt-1) +j;
7330: if(j < nlstate)
7331: fprintf(ficgp,"$%d +",k+l);
7332: else
7333: fprintf(ficgp,"$%d) t\"l(%d,.)\" w l",k+l,cpt);
7334: }
1.264 brouard 7335: fprintf(ficgp,"\nset out; unset label;\n");
1.238 brouard 7336: } /* end cpt state*/
7337: } /* end covariate */
7338: } /* end nres */
1.227 brouard 7339:
1.220 brouard 7340: /* 6eme */
1.202 brouard 7341: /* CV preval stable (period) for each covariate */
1.237 brouard 7342: for (k1=1; k1<= m ; k1 ++) /* For each covariate combination if any */
7343: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 7344: if(m != 1 && TKresult[nres]!= k1)
1.237 brouard 7345: continue;
1.255 brouard 7346: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state of arrival */
1.264 brouard 7347: strcpy(gplotlabel,"(");
1.211 brouard 7348: fprintf(ficgp,"\n#\n#\n#CV preval stable (period): 'pij' files, covariatecombination#=%d state=%d",k1, cpt);
1.225 brouard 7349: for (k=1; k<=cptcoveff; k++){ /* For each covariate and each value */
1.227 brouard 7350: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate number corresponding to k1 combination */
7351: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7352: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7353: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7354: vlv= nbcode[Tvaraff[k]][lv];
7355: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 7356: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.211 brouard 7357: }
1.237 brouard 7358: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7359: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7360: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.237 brouard 7361: }
1.264 brouard 7362: strcpy(gplotlabel+strlen(gplotlabel),")");
1.211 brouard 7363: fprintf(ficgp,"\n#\n");
1.223 brouard 7364: if(invalidvarcomb[k1]){
1.227 brouard 7365: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7366: continue;
1.223 brouard 7367: }
1.227 brouard 7368:
1.241 brouard 7369: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"P_"),cpt,k1,nres);
1.264 brouard 7370: fprintf(ficgp,"set label \"Alive state %d %s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",cpt,gplotlabel);
1.126 brouard 7371: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability\" \n\
1.238 brouard 7372: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
1.211 brouard 7373: k=3; /* Offset */
1.255 brouard 7374: for (i=1; i<= nlstate ; i ++){ /* State of origin */
1.227 brouard 7375: if(i==1)
7376: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJ_"));
7377: else
7378: fprintf(ficgp,", '' ");
1.255 brouard 7379: l=(nlstate+ndeath)*(i-1)+1; /* 1, 1+ nlstate+ndeath, 1+2*(nlstate+ndeath) */
1.227 brouard 7380: fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d/($%d",k1,k+l+(cpt-1),k+l);
7381: for (j=2; j<= nlstate ; j ++)
7382: fprintf(ficgp,"+$%d",k+l+j-1);
7383: fprintf(ficgp,")) t \"prev(%d,%d)\" w l",i,cpt);
1.153 brouard 7384: } /* nlstate */
1.264 brouard 7385: fprintf(ficgp,"\nset out; unset label;\n");
1.153 brouard 7386: } /* end cpt state*/
7387: } /* end covariate */
1.227 brouard 7388:
7389:
1.220 brouard 7390: /* 7eme */
1.218 brouard 7391: if(backcast == 1){
1.217 brouard 7392: /* CV back preval stable (period) for each covariate */
1.237 brouard 7393: for (k1=1; k1<= m ; k1 ++) /* For each covariate combination if any */
7394: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 7395: if(m != 1 && TKresult[nres]!= k1)
1.237 brouard 7396: continue;
1.268 ! brouard 7397: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life origin state */
1.264 brouard 7398: strcpy(gplotlabel,"(");
7399: fprintf(ficgp,"\n#\n#\n#CV Back preval stable (period): 'pijb' files, covariatecombination#=%d state=%d",k1, cpt);
1.227 brouard 7400: for (k=1; k<=cptcoveff; k++){ /* For each covariate and each value */
7401: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate number corresponding to k1 combination */
7402: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7403: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
1.223 brouard 7404: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
1.227 brouard 7405: vlv= nbcode[Tvaraff[k]][lv];
7406: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 7407: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.227 brouard 7408: }
1.237 brouard 7409: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7410: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7411: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.237 brouard 7412: }
1.264 brouard 7413: strcpy(gplotlabel+strlen(gplotlabel),")");
1.227 brouard 7414: fprintf(ficgp,"\n#\n");
7415: if(invalidvarcomb[k1]){
7416: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7417: continue;
7418: }
7419:
1.241 brouard 7420: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"PB_"),cpt,k1,nres);
1.268 ! brouard 7421: fprintf(ficgp,"set label \"Origin alive state %d %s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",cpt,gplotlabel);
1.227 brouard 7422: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability\" \n\
1.238 brouard 7423: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
1.227 brouard 7424: k=3; /* Offset */
1.268 ! brouard 7425: for (i=1; i<= nlstate ; i ++){ /* State of arrival */
1.227 brouard 7426: if(i==1)
7427: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJB_"));
7428: else
7429: fprintf(ficgp,", '' ");
7430: /* l=(nlstate+ndeath)*(i-1)+1; */
1.255 brouard 7431: l=(nlstate+ndeath)*(cpt-1)+1; /* fixed for i; cpt=1 1, cpt=2 1+ nlstate+ndeath, 1+2*(nlstate+ndeath) */
1.227 brouard 7432: /* fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d/($%d",k1,k+l+(cpt-1),k+l); /\* a vérifier *\/ */
7433: /* fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d/($%d",k1,k+l+(cpt-1),k+l+(cpt-1)+i-1); /\* a vérifier *\/ */
1.255 brouard 7434: fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d",k1,k+l+i-1); /* To be verified */
1.227 brouard 7435: /* for (j=2; j<= nlstate ; j ++) */
7436: /* fprintf(ficgp,"+$%d",k+l+j-1); */
7437: /* /\* fprintf(ficgp,"+$%d",k+l+j-1); *\/ */
1.268 ! brouard 7438: fprintf(ficgp,") t \"bprev(%d,%d)\" w l",cpt,i);
1.227 brouard 7439: } /* nlstate */
1.264 brouard 7440: fprintf(ficgp,"\nset out; unset label;\n");
1.218 brouard 7441: } /* end cpt state*/
7442: } /* end covariate */
7443: } /* End if backcast */
7444:
1.223 brouard 7445: /* 8eme */
1.218 brouard 7446: if(prevfcast==1){
7447: /* Projection from cross-sectional to stable (period) for each covariate */
7448:
1.237 brouard 7449: for (k1=1; k1<= m ; k1 ++) /* For each covariate combination if any */
7450: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 7451: if(m != 1 && TKresult[nres]!= k1)
1.237 brouard 7452: continue;
1.211 brouard 7453: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state */
1.264 brouard 7454: strcpy(gplotlabel,"(");
1.227 brouard 7455: fprintf(ficgp,"\n#\n#\n#Projection of prevalence to stable (period): 'PROJ_' files, covariatecombination#=%d state=%d",k1, cpt);
7456: for (k=1; k<=cptcoveff; k++){ /* For each correspondig covariate value */
7457: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate value corresponding to k1 combination and kth covariate */
7458: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7459: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7460: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7461: vlv= nbcode[Tvaraff[k]][lv];
7462: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
1.264 brouard 7463: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
1.227 brouard 7464: }
1.237 brouard 7465: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7466: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7467: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.237 brouard 7468: }
1.264 brouard 7469: strcpy(gplotlabel+strlen(gplotlabel),")");
1.227 brouard 7470: fprintf(ficgp,"\n#\n");
7471: if(invalidvarcomb[k1]){
7472: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
7473: continue;
7474: }
7475:
7476: fprintf(ficgp,"# hpijx=probability over h years, hp.jx is weighted by observed prev\n ");
1.241 brouard 7477: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"PROJ_"),cpt,k1,nres);
1.264 brouard 7478: fprintf(ficgp,"set label \"Alive state %d %s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",cpt,gplotlabel);
1.227 brouard 7479: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Prevalence\" \n\
1.238 brouard 7480: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
1.266 brouard 7481:
7482: /* for (i=1; i<= nlstate+1 ; i ++){ /\* nlstate +1 p11 p21 p.1 *\/ */
7483: istart=nlstate+1; /* Could be one if by state, but nlstate+1 is w.i projection only */
7484: /*istart=1;*/ /* Could be one if by state, but nlstate+1 is w.i projection only */
7485: for (i=istart; i<= nlstate+1 ; i ++){ /* nlstate +1 p11 p21 p.1 */
1.227 brouard 7486: /*# V1 = 1 V2 = 0 yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
7487: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
7488: /*# yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
7489: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
1.266 brouard 7490: if(i==istart){
1.227 brouard 7491: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"F_"));
7492: }else{
7493: fprintf(ficgp,",\\\n '' ");
7494: }
7495: if(cptcoveff ==0){ /* No covariate */
7496: ioffset=2; /* Age is in 2 */
7497: /*# yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/
7498: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */
7499: /*# V1 = 1 yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/
7500: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */
7501: fprintf(ficgp," u %d:(", ioffset);
1.266 brouard 7502: if(i==nlstate+1){
7503: fprintf(ficgp," $%d/(1.-$%d)):5 t 'pw.%d' with line lc variable ", \
7504: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,cpt );
7505: fprintf(ficgp,",\\\n '' ");
7506: fprintf(ficgp," u %d:(",ioffset);
7507: fprintf(ficgp," (($5-$6) == %d ) ? $%d/(1.-$%d) : 1/0):5 with labels center not ", \
7508: offyear, \
1.268 ! brouard 7509: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate );
1.266 brouard 7510: }else
1.227 brouard 7511: fprintf(ficgp," $%d/(1.-$%d)) t 'p%d%d' with line ", \
7512: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,i,cpt );
7513: }else{ /* more than 2 covariates */
7514: if(cptcoveff ==1){
7515: ioffset=4; /* Age is in 4 */
7516: }else{
7517: ioffset=6; /* Age is in 6 */
7518: /*# V1 = 1 V2 = 0 yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
7519: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
7520: }
7521: fprintf(ficgp," u %d:(",ioffset);
7522: kl=0;
7523: strcpy(gplotcondition,"(");
7524: for (k=1; k<=cptcoveff; k++){ /* For each covariate writing the chain of conditions */
7525: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate value corresponding to combination k1 and covariate k */
7526: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7527: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7528: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7529: vlv= nbcode[Tvaraff[k]][lv]; /* Value of the modality of Tvaraff[k] */
7530: kl++;
7531: sprintf(gplotcondition+strlen(gplotcondition),"$%d==%d && $%d==%d " ,kl,Tvaraff[k], kl+1, nbcode[Tvaraff[k]][lv]);
7532: kl++;
7533: if(k <cptcoveff && cptcoveff>1)
7534: sprintf(gplotcondition+strlen(gplotcondition)," && ");
7535: }
7536: strcpy(gplotcondition+strlen(gplotcondition),")");
7537: /* 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 *\/ */
7538: /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */
7539: /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */
7540: /* '' 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*/
7541: if(i==nlstate+1){
1.266 brouard 7542: fprintf(ficgp,"%s ? $%d/(1.-$%d) : 1/0):5 t 'p.%d' with line lc variable", gplotcondition, \
7543: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,cpt );
7544: fprintf(ficgp,",\\\n '' ");
7545: fprintf(ficgp," u %d:(",ioffset);
7546: fprintf(ficgp,"%s && (($5-$6) == %d ) ? $%d/(1.-$%d) : 1/0):5 with labels center not ", gplotcondition, \
7547: offyear, \
1.268 ! brouard 7548: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate );
1.266 brouard 7549: /* '' u 6:(($1==1 && $2==0 && $3==2 && $4==0) && (($5-$6) == 1947) ? $10/(1.-$22) : 1/0):5 with labels center boxed not*/
1.227 brouard 7550: }else{
7551: fprintf(ficgp,"%s ? $%d/(1.-$%d) : 1/0) t 'p%d%d' with line ", gplotcondition, \
7552: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset +1+(i-1)+(nlstate+1)*nlstate,i,cpt );
7553: }
7554: } /* end if covariate */
7555: } /* nlstate */
1.264 brouard 7556: fprintf(ficgp,"\nset out; unset label;\n");
1.223 brouard 7557: } /* end cpt state*/
7558: } /* end covariate */
7559: } /* End if prevfcast */
1.227 brouard 7560:
1.268 ! brouard 7561: if(backcast==1){
! 7562: /* Back projection from cross-sectional to stable (mixed) for each covariate */
! 7563:
! 7564: for (k1=1; k1<= m ; k1 ++) /* For each covariate combination if any */
! 7565: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
! 7566: if(m != 1 && TKresult[nres]!= k1)
! 7567: continue;
! 7568: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state */
! 7569: strcpy(gplotlabel,"(");
! 7570: fprintf(ficgp,"\n#\n#\n#Back projection of prevalence to stable (mixed) back prevalence: 'BPROJ_' files, covariatecombination#=%d originstate=%d",k1, cpt);
! 7571: for (k=1; k<=cptcoveff; k++){ /* For each correspondig covariate value */
! 7572: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate value corresponding to k1 combination and kth covariate */
! 7573: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
! 7574: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
! 7575: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
! 7576: vlv= nbcode[Tvaraff[k]][lv];
! 7577: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
! 7578: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
! 7579: }
! 7580: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
! 7581: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
! 7582: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
! 7583: }
! 7584: strcpy(gplotlabel+strlen(gplotlabel),")");
! 7585: fprintf(ficgp,"\n#\n");
! 7586: if(invalidvarcomb[k1]){
! 7587: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
! 7588: continue;
! 7589: }
! 7590:
! 7591: fprintf(ficgp,"# hbijx=backprobability over h years, hb.jx is weighted by observed prev at destination state\n ");
! 7592: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"PROJB_"),cpt,k1,nres);
! 7593: fprintf(ficgp,"set label \"Origin alive state %d %s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",cpt,gplotlabel);
! 7594: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Prevalence\" \n\
! 7595: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
! 7596:
! 7597: /* for (i=1; i<= nlstate+1 ; i ++){ /\* nlstate +1 p11 p21 p.1 *\/ */
! 7598: istart=nlstate+1; /* Could be one if by state, but nlstate+1 is w.i projection only */
! 7599: /*istart=1;*/ /* Could be one if by state, but nlstate+1 is w.i projection only */
! 7600: for (i=istart; i<= nlstate+1 ; i ++){ /* nlstate +1 p11 p21 p.1 */
! 7601: /*# V1 = 1 V2 = 0 yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
! 7602: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
! 7603: /*# yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
! 7604: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
! 7605: if(i==istart){
! 7606: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"FB_"));
! 7607: }else{
! 7608: fprintf(ficgp,",\\\n '' ");
! 7609: }
! 7610: if(cptcoveff ==0){ /* No covariate */
! 7611: ioffset=2; /* Age is in 2 */
! 7612: /*# yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/
! 7613: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */
! 7614: /*# V1 = 1 yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/
! 7615: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */
! 7616: fprintf(ficgp," u %d:(", ioffset);
! 7617: if(i==nlstate+1){
! 7618: fprintf(ficgp," $%d/(1.-$%d)):5 t 'bw%d' with line lc variable ", \
! 7619: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,cpt );
! 7620: fprintf(ficgp,",\\\n '' ");
! 7621: fprintf(ficgp," u %d:(",ioffset);
! 7622: fprintf(ficgp," (($5-$6) == %d ) ? $%d : 1/0):5 with labels center not ", \
! 7623: offbyear, \
! 7624: ioffset+(cpt-1)*(nlstate+1)+1+(i-1) );
! 7625: }else
! 7626: fprintf(ficgp," $%d/(1.-$%d)) t 'b%d%d' with line ", \
! 7627: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,cpt,i );
! 7628: }else{ /* more than 2 covariates */
! 7629: if(cptcoveff ==1){
! 7630: ioffset=4; /* Age is in 4 */
! 7631: }else{
! 7632: ioffset=6; /* Age is in 6 */
! 7633: /*# V1 = 1 V2 = 0 yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
! 7634: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
! 7635: }
! 7636: fprintf(ficgp," u %d:(",ioffset);
! 7637: kl=0;
! 7638: strcpy(gplotcondition,"(");
! 7639: for (k=1; k<=cptcoveff; k++){ /* For each covariate writing the chain of conditions */
! 7640: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate value corresponding to combination k1 and covariate k */
! 7641: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
! 7642: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
! 7643: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
! 7644: vlv= nbcode[Tvaraff[k]][lv]; /* Value of the modality of Tvaraff[k] */
! 7645: kl++;
! 7646: sprintf(gplotcondition+strlen(gplotcondition),"$%d==%d && $%d==%d " ,kl,Tvaraff[k], kl+1, nbcode[Tvaraff[k]][lv]);
! 7647: kl++;
! 7648: if(k <cptcoveff && cptcoveff>1)
! 7649: sprintf(gplotcondition+strlen(gplotcondition)," && ");
! 7650: }
! 7651: strcpy(gplotcondition+strlen(gplotcondition),")");
! 7652: /* 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 *\/ */
! 7653: /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */
! 7654: /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */
! 7655: /* '' 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*/
! 7656: if(i==nlstate+1){
! 7657: fprintf(ficgp,"%s ? $%d : 1/0):5 t 'bw%d' with line lc variable", gplotcondition, \
! 7658: ioffset+(cpt-1)*(nlstate+1)+1+(i-1),cpt );
! 7659: fprintf(ficgp,",\\\n '' ");
! 7660: fprintf(ficgp," u %d:(",ioffset);
! 7661: /* fprintf(ficgp,"%s && (($5-$6) == %d ) ? $%d/(1.-$%d) : 1/0):5 with labels center not ", gplotcondition, \ */
! 7662: fprintf(ficgp,"%s && (($5-$6) == %d ) ? $%d : 1/0):5 with labels center not ", gplotcondition, \
! 7663: offbyear, \
! 7664: ioffset+(cpt-1)*(nlstate+1)+1+(i-1) );
! 7665: /* '' u 6:(($1==1 && $2==0 && $3==2 && $4==0) && (($5-$6) == 1947) ? $10/(1.-$22) : 1/0):5 with labels center boxed not*/
! 7666: }else{
! 7667: /* fprintf(ficgp,"%s ? $%d/(1.-$%d) : 1/0) t 'p%d%d' with line ", gplotcondition, \ */
! 7668: fprintf(ficgp,"%s ? $%d : 1/0) t 'b%d%d' with line ", gplotcondition, \
! 7669: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), cpt,i );
! 7670: }
! 7671: } /* end if covariate */
! 7672: } /* nlstate */
! 7673: fprintf(ficgp,"\nset out; unset label;\n");
! 7674: } /* end cpt state*/
! 7675: } /* end covariate */
! 7676: } /* End if backcast */
! 7677:
1.227 brouard 7678:
1.238 brouard 7679: /* 9eme writing MLE parameters */
7680: fprintf(ficgp,"\n##############\n#9eme MLE estimated parameters\n#############\n");
1.126 brouard 7681: for(i=1,jk=1; i <=nlstate; i++){
1.187 brouard 7682: fprintf(ficgp,"# initial state %d\n",i);
1.126 brouard 7683: for(k=1; k <=(nlstate+ndeath); k++){
7684: if (k != i) {
1.227 brouard 7685: fprintf(ficgp,"# current state %d\n",k);
7686: for(j=1; j <=ncovmodel; j++){
7687: fprintf(ficgp,"p%d=%f; ",jk,p[jk]);
7688: jk++;
7689: }
7690: fprintf(ficgp,"\n");
1.126 brouard 7691: }
7692: }
1.223 brouard 7693: }
1.187 brouard 7694: fprintf(ficgp,"##############\n#\n");
1.227 brouard 7695:
1.145 brouard 7696: /*goto avoid;*/
1.238 brouard 7697: /* 10eme Graphics of probabilities or incidences using written MLE parameters */
7698: fprintf(ficgp,"\n##############\n#10eme Graphics of probabilities or incidences\n#############\n");
1.187 brouard 7699: fprintf(ficgp,"# logi(p12/p11)=a12+b12*age+c12age*age+d12*V1+e12*V1*age\n");
7700: fprintf(ficgp,"# logi(p12/p11)=p1 +p2*age +p3*age*age+ p4*V1+ p5*V1*age\n");
7701: fprintf(ficgp,"# logi(p13/p11)=a13+b13*age+c13age*age+d13*V1+e13*V1*age\n");
7702: fprintf(ficgp,"# logi(p13/p11)=p6 +p7*age +p8*age*age+ p9*V1+ p10*V1*age\n");
7703: fprintf(ficgp,"# p12+p13+p14+p11=1=p11(1+exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)\n");
7704: fprintf(ficgp,"# +exp(a13+b13*age+c13age*age+d13*V1+e13*V1*age)+...)\n");
7705: fprintf(ficgp,"# p11=1/(1+exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)\n");
7706: fprintf(ficgp,"# +exp(a13+b13*age+c13age*age+d13*V1+e13*V1*age)+...)\n");
7707: fprintf(ficgp,"# p12=exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)/\n");
7708: fprintf(ficgp,"# (1+exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)\n");
7709: fprintf(ficgp,"# +exp(a13+b13*age+c13age*age+d13*V1+e13*V1*age))\n");
7710: fprintf(ficgp,"# +exp(a14+b14*age+c14age*age+d14*V1+e14*V1*age)+...)\n");
7711: fprintf(ficgp,"#\n");
1.223 brouard 7712: for(ng=1; ng<=3;ng++){ /* Number of graphics: first is logit, 2nd is probabilities, third is incidences per year*/
1.238 brouard 7713: fprintf(ficgp,"#Number of graphics: first is logit, 2nd is probabilities, third is incidences per year\n");
1.237 brouard 7714: fprintf(ficgp,"#model=%s \n",model);
1.238 brouard 7715: fprintf(ficgp,"# Type of graphic ng=%d\n",ng);
1.264 brouard 7716: fprintf(ficgp,"# k1=1 to 2^%d=%d\n",cptcoveff,m);/* to be checked */
7717: for(k1=1; k1 <=m; k1++) /* For each combination of covariate */
1.237 brouard 7718: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.264 brouard 7719: if(m != 1 && TKresult[nres]!= k1)
1.237 brouard 7720: continue;
1.264 brouard 7721: fprintf(ficgp,"\n\n# Combination of dummy k1=%d which is ",k1);
7722: strcpy(gplotlabel,"(");
7723: sprintf(gplotlabel+strlen(gplotlabel)," Dummy combination %d ",k1);
7724: for (k=1; k<=cptcoveff; k++){ /* For each correspondig covariate value */
7725: lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate value corresponding to k1 combination and kth covariate */
7726: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
7727: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
7728: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
7729: vlv= nbcode[Tvaraff[k]][lv];
7730: fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv);
7731: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv);
7732: }
1.237 brouard 7733: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
7734: fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.264 brouard 7735: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.237 brouard 7736: }
1.264 brouard 7737: strcpy(gplotlabel+strlen(gplotlabel),")");
1.237 brouard 7738: fprintf(ficgp,"\n#\n");
1.264 brouard 7739: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" ",subdirf2(optionfilefiname,"PE_"),k1,ng,nres);
7740: fprintf(ficgp,"\nset label \"%s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",gplotlabel);
1.223 brouard 7741: fprintf(ficgp,"\nset ter svg size 640, 480 ");
7742: if (ng==1){
7743: fprintf(ficgp,"\nset ylabel \"Value of the logit of the model\"\n"); /* exp(a12+b12*x) could be nice */
7744: fprintf(ficgp,"\nunset log y");
7745: }else if (ng==2){
7746: fprintf(ficgp,"\nset ylabel \"Probability\"\n");
7747: fprintf(ficgp,"\nset log y");
7748: }else if (ng==3){
7749: fprintf(ficgp,"\nset ylabel \"Quasi-incidence per year\"\n");
7750: fprintf(ficgp,"\nset log y");
7751: }else
7752: fprintf(ficgp,"\nunset title ");
7753: fprintf(ficgp,"\nplot [%.f:%.f] ",ageminpar,agemaxpar);
7754: i=1;
7755: for(k2=1; k2<=nlstate; k2++) {
7756: k3=i;
7757: for(k=1; k<=(nlstate+ndeath); k++) {
7758: if (k != k2){
7759: switch( ng) {
7760: case 1:
7761: if(nagesqr==0)
7762: fprintf(ficgp," p%d+p%d*x",i,i+1);
7763: else /* nagesqr =1 */
7764: fprintf(ficgp," p%d+p%d*x+p%d*x*x",i,i+1,i+1+nagesqr);
7765: break;
7766: case 2: /* ng=2 */
7767: if(nagesqr==0)
7768: fprintf(ficgp," exp(p%d+p%d*x",i,i+1);
7769: else /* nagesqr =1 */
7770: fprintf(ficgp," exp(p%d+p%d*x+p%d*x*x",i,i+1,i+1+nagesqr);
7771: break;
7772: case 3:
7773: if(nagesqr==0)
7774: fprintf(ficgp," %f*exp(p%d+p%d*x",YEARM/stepm,i,i+1);
7775: else /* nagesqr =1 */
7776: fprintf(ficgp," %f*exp(p%d+p%d*x+p%d*x*x",YEARM/stepm,i,i+1,i+1+nagesqr);
7777: break;
7778: }
7779: ij=1;/* To be checked else nbcode[0][0] wrong */
1.237 brouard 7780: ijp=1; /* product no age */
7781: /* for(j=3; j <=ncovmodel-nagesqr; j++) { */
7782: for(j=1; j <=cptcovt; j++) { /* For each covariate of the simplified model */
1.223 brouard 7783: /* printf("Tage[%d]=%d, j=%d\n", ij, Tage[ij], j); */
1.268 ! brouard 7784: if(cptcovage >0){ /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, 2 V5 and V1 */
! 7785: if(j==Tage[ij]) { /* Product by age To be looked at!!*/
! 7786: if(ij <=cptcovage) { /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, 2 V5 and V1 */
! 7787: if(DummyV[j]==0){
! 7788: fprintf(ficgp,"+p%d*%d*x",i+j+2+nagesqr-1,Tinvresult[nres][Tvar[j]]);;
! 7789: }else{ /* quantitative */
! 7790: fprintf(ficgp,"+p%d*%f*x",i+j+2+nagesqr-1,Tqinvresult[nres][Tvar[j]]); /* Tqinvresult in decoderesult */
! 7791: /* fprintf(ficgp,"+p%d*%d*x",i+j+nagesqr-1,nbcode[Tvar[j-2]][codtabm(k1,Tvar[j-2])]); */
! 7792: }
! 7793: ij++;
1.237 brouard 7794: }
1.268 ! brouard 7795: }
! 7796: }else if(cptcovprod >0){
! 7797: if(j==Tprod[ijp]) { /* */
! 7798: /* printf("Tprod[%d]=%d, j=%d\n", ij, Tprod[ijp], j); */
! 7799: if(ijp <=cptcovprod) { /* Product */
! 7800: if(DummyV[Tvard[ijp][1]]==0){/* Vn is dummy */
! 7801: if(DummyV[Tvard[ijp][2]]==0){/* Vn and Vm are dummy */
! 7802: /* fprintf(ficgp,"+p%d*%d*%d",i+j+2+nagesqr-1,nbcode[Tvard[ijp][1]][codtabm(k1,j)],nbcode[Tvard[ijp][2]][codtabm(k1,j)]); */
! 7803: fprintf(ficgp,"+p%d*%d*%d",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tinvresult[nres][Tvard[ijp][2]]);
! 7804: }else{ /* Vn is dummy and Vm is quanti */
! 7805: /* fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,nbcode[Tvard[ijp][1]][codtabm(k1,j)],Tqinvresult[nres][Tvard[ijp][2]]); */
! 7806: fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]);
! 7807: }
! 7808: }else{ /* Vn*Vm Vn is quanti */
! 7809: if(DummyV[Tvard[ijp][2]]==0){
! 7810: fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][2]],Tqinvresult[nres][Tvard[ijp][1]]);
! 7811: }else{ /* Both quanti */
! 7812: fprintf(ficgp,"+p%d*%f*%f",i+j+2+nagesqr-1,Tqinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]);
! 7813: }
1.237 brouard 7814: }
1.268 ! brouard 7815: ijp++;
1.237 brouard 7816: }
1.268 ! brouard 7817: } /* end Tprod */
1.237 brouard 7818: } else{ /* simple covariate */
1.264 brouard 7819: /* fprintf(ficgp,"+p%d*%d",i+j+2+nagesqr-1,nbcode[Tvar[j]][codtabm(k1,j)]); /\* Valgrind bug nbcode *\/ */
1.237 brouard 7820: if(Dummy[j]==0){
7821: fprintf(ficgp,"+p%d*%d",i+j+2+nagesqr-1,Tinvresult[nres][Tvar[j]]); /* */
7822: }else{ /* quantitative */
7823: fprintf(ficgp,"+p%d*%f",i+j+2+nagesqr-1,Tqinvresult[nres][Tvar[j]]); /* */
1.264 brouard 7824: /* fprintf(ficgp,"+p%d*%d*x",i+j+nagesqr-1,nbcode[Tvar[j-2]][codtabm(k1,Tvar[j-2])]); */
1.223 brouard 7825: }
1.237 brouard 7826: } /* end simple */
7827: } /* end j */
1.223 brouard 7828: }else{
7829: i=i-ncovmodel;
7830: if(ng !=1 ) /* For logit formula of log p11 is more difficult to get */
7831: fprintf(ficgp," (1.");
7832: }
1.227 brouard 7833:
1.223 brouard 7834: if(ng != 1){
7835: fprintf(ficgp,")/(1");
1.227 brouard 7836:
1.264 brouard 7837: for(cpt=1; cpt <=nlstate; cpt++){
1.223 brouard 7838: if(nagesqr==0)
1.264 brouard 7839: fprintf(ficgp,"+exp(p%d+p%d*x",k3+(cpt-1)*ncovmodel,k3+(cpt-1)*ncovmodel+1);
1.223 brouard 7840: else /* nagesqr =1 */
1.264 brouard 7841: fprintf(ficgp,"+exp(p%d+p%d*x+p%d*x*x",k3+(cpt-1)*ncovmodel,k3+(cpt-1)*ncovmodel+1,k3+(cpt-1)*ncovmodel+1+nagesqr);
1.217 brouard 7842:
1.223 brouard 7843: ij=1;
7844: for(j=3; j <=ncovmodel-nagesqr; j++){
1.268 ! brouard 7845: if(cptcovage >0){
! 7846: if((j-2)==Tage[ij]) { /* Bug valgrind */
! 7847: if(ij <=cptcovage) { /* Bug valgrind */
! 7848: fprintf(ficgp,"+p%d*%d*x",k3+(cpt-1)*ncovmodel+1+j-2+nagesqr,nbcode[Tvar[j-2]][codtabm(k1,j-2)]);
! 7849: /* fprintf(ficgp,"+p%d*%d*x",k3+(cpt-1)*ncovmodel+1+j-2+nagesqr,nbcode[Tvar[j-2]][codtabm(k1,Tvar[j-2])]); */
! 7850: ij++;
! 7851: }
! 7852: }
! 7853: }else
! 7854: fprintf(ficgp,"+p%d*%d",k3+(cpt-1)*ncovmodel+1+j-2+nagesqr,nbcode[Tvar[j-2]][codtabm(k1,j-2)]);/* Valgrind bug nbcode */
1.223 brouard 7855: }
7856: fprintf(ficgp,")");
7857: }
7858: fprintf(ficgp,")");
7859: if(ng ==2)
7860: fprintf(ficgp," t \"p%d%d\" ", k2,k);
7861: else /* ng= 3 */
7862: fprintf(ficgp," t \"i%d%d\" ", k2,k);
7863: }else{ /* end ng <> 1 */
7864: if( k !=k2) /* logit p11 is hard to draw */
7865: fprintf(ficgp," t \"logit(p%d%d)\" ", k2,k);
7866: }
7867: if ((k+k2)!= (nlstate*2+ndeath) && ng != 1)
7868: fprintf(ficgp,",");
7869: if (ng == 1 && k!=k2 && (k+k2)!= (nlstate*2+ndeath))
7870: fprintf(ficgp,",");
7871: i=i+ncovmodel;
7872: } /* end k */
7873: } /* end k2 */
1.264 brouard 7874: fprintf(ficgp,"\n set out; unset label;\n");
7875: } /* end k1 */
1.223 brouard 7876: } /* end ng */
7877: /* avoid: */
7878: fflush(ficgp);
1.126 brouard 7879: } /* end gnuplot */
7880:
7881:
7882: /*************** Moving average **************/
1.219 brouard 7883: /* int movingaverage(double ***probs, double bage, double fage, double ***mobaverage, int mobilav, double bageout, double fageout){ */
1.222 brouard 7884: int movingaverage(double ***probs, double bage, double fage, double ***mobaverage, int mobilav){
1.218 brouard 7885:
1.222 brouard 7886: int i, cpt, cptcod;
7887: int modcovmax =1;
7888: int mobilavrange, mob;
7889: int iage=0;
7890:
1.266 brouard 7891: double sum=0., sumr=0.;
1.222 brouard 7892: double age;
1.266 brouard 7893: double *sumnewp, *sumnewm, *sumnewmr;
7894: double *agemingood, *agemaxgood;
7895: double *agemingoodr, *agemaxgoodr;
1.222 brouard 7896:
7897:
1.225 brouard 7898: /* modcovmax=2*cptcoveff;/\* Max number of modalities. We suppose */
1.222 brouard 7899: /* a covariate has 2 modalities, should be equal to ncovcombmax *\/ */
7900:
7901: sumnewp = vector(1,ncovcombmax);
7902: sumnewm = vector(1,ncovcombmax);
1.266 brouard 7903: sumnewmr = vector(1,ncovcombmax);
1.222 brouard 7904: agemingood = vector(1,ncovcombmax);
1.266 brouard 7905: agemingoodr = vector(1,ncovcombmax);
1.222 brouard 7906: agemaxgood = vector(1,ncovcombmax);
1.266 brouard 7907: agemaxgoodr = vector(1,ncovcombmax);
1.222 brouard 7908:
7909: for (cptcod=1;cptcod<=ncovcombmax;cptcod++){
1.266 brouard 7910: sumnewm[cptcod]=0.; sumnewmr[cptcod]=0.;
1.222 brouard 7911: sumnewp[cptcod]=0.;
1.266 brouard 7912: agemingood[cptcod]=0, agemingoodr[cptcod]=0;
7913: agemaxgood[cptcod]=0, agemaxgoodr[cptcod]=0;
1.222 brouard 7914: }
7915: if (cptcovn<1) ncovcombmax=1; /* At least 1 pass */
7916:
1.266 brouard 7917: if(mobilav==-1 || mobilav==1||mobilav ==3 ||mobilav==5 ||mobilav== 7){
7918: if(mobilav==1 || mobilav==-1) mobilavrange=5; /* default */
1.222 brouard 7919: else mobilavrange=mobilav;
7920: for (age=bage; age<=fage; age++)
7921: for (i=1; i<=nlstate;i++)
7922: for (cptcod=1;cptcod<=ncovcombmax;cptcod++)
7923: mobaverage[(int)age][i][cptcod]=probs[(int)age][i][cptcod];
7924: /* We keep the original values on the extreme ages bage, fage and for
7925: fage+1 and bage-1 we use a 3 terms moving average; for fage+2 bage+2
7926: we use a 5 terms etc. until the borders are no more concerned.
7927: */
7928: for (mob=3;mob <=mobilavrange;mob=mob+2){
7929: for (age=bage+(mob-1)/2; age<=fage-(mob-1)/2; age++){
1.266 brouard 7930: for (cptcod=1;cptcod<=ncovcombmax;cptcod++){
7931: sumnewm[cptcod]=0.;
7932: for (i=1; i<=nlstate;i++){
1.222 brouard 7933: mobaverage[(int)age][i][cptcod] =probs[(int)age][i][cptcod];
7934: for (cpt=1;cpt<=(mob-1)/2;cpt++){
7935: mobaverage[(int)age][i][cptcod] +=probs[(int)age-cpt][i][cptcod];
7936: mobaverage[(int)age][i][cptcod] +=probs[(int)age+cpt][i][cptcod];
7937: }
7938: mobaverage[(int)age][i][cptcod]=mobaverage[(int)age][i][cptcod]/mob;
1.266 brouard 7939: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
7940: } /* end i */
7941: if(sumnewm[cptcod] >1.e-3) mobaverage[(int)age][i][cptcod]=mobaverage[(int)age][i][cptcod]/sumnewm[cptcod]; /* Rescaling to sum one */
7942: } /* end cptcod */
1.222 brouard 7943: }/* end age */
7944: }/* end mob */
1.266 brouard 7945: }else{
7946: printf("Error internal in movingaverage, mobilav=%d.\n",mobilav);
1.222 brouard 7947: return -1;
1.266 brouard 7948: }
7949:
7950: for (cptcod=1;cptcod<=ncovcombmax;cptcod++){ /* for each combination */
1.222 brouard 7951: /* for (age=bage+(mob-1)/2; age<=fage-(mob-1)/2; age++){ */
7952: if(invalidvarcomb[cptcod]){
7953: printf("\nCombination (%d) ignored because no cases \n",cptcod);
7954: continue;
7955: }
1.219 brouard 7956:
1.266 brouard 7957: for (age=fage-(mob-1)/2; age>=bage+(mob-1)/2; age--){ /*looking for the youngest and oldest good age */
7958: sumnewm[cptcod]=0.;
7959: sumnewmr[cptcod]=0.;
7960: for (i=1; i<=nlstate;i++){
7961: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
7962: sumnewmr[cptcod]+=probs[(int)age][i][cptcod];
7963: }
7964: if(fabs(sumnewmr[cptcod] - 1.) <= 1.e-3) { /* good without smoothing */
7965: agemingoodr[cptcod]=age;
7966: }
7967: if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
7968: agemingood[cptcod]=age;
7969: }
7970: } /* age */
7971: for (age=bage+(mob-1)/2; age<=fage-(mob-1)/2; age++){ /*looking for the youngest and oldest good age */
1.222 brouard 7972: sumnewm[cptcod]=0.;
1.266 brouard 7973: sumnewmr[cptcod]=0.;
1.222 brouard 7974: for (i=1; i<=nlstate;i++){
7975: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
1.266 brouard 7976: sumnewmr[cptcod]+=probs[(int)age][i][cptcod];
7977: }
7978: if(fabs(sumnewmr[cptcod] - 1.) <= 1.e-3) { /* good without smoothing */
7979: agemaxgoodr[cptcod]=age;
1.222 brouard 7980: }
7981: if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
1.266 brouard 7982: agemaxgood[cptcod]=age;
7983: }
7984: } /* age */
7985: /* Thus we have agemingood and agemaxgood as well as goodr for raw (preobs) */
7986: /* but they will change */
7987: for (age=fage-(mob-1)/2; age>=bage; age--){/* From oldest to youngest, filling up to the youngest */
7988: sumnewm[cptcod]=0.;
7989: sumnewmr[cptcod]=0.;
7990: for (i=1; i<=nlstate;i++){
7991: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
7992: sumnewmr[cptcod]+=probs[(int)age][i][cptcod];
7993: }
7994: if(mobilav==-1){ /* Forcing raw ages if good else agemingood */
7995: if(fabs(sumnewmr[cptcod] - 1.) <= 1.e-3) { /* good without smoothing */
7996: agemaxgoodr[cptcod]=age; /* age min */
7997: for (i=1; i<=nlstate;i++)
7998: mobaverage[(int)age][i][cptcod]=probs[(int)age][i][cptcod];
7999: }else{ /* bad we change the value with the values of good ages */
8000: for (i=1; i<=nlstate;i++){
8001: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemaxgoodr[cptcod]][i][cptcod];
8002: } /* i */
8003: } /* end bad */
8004: }else{
8005: if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
8006: agemaxgood[cptcod]=age;
8007: }else{ /* bad we change the value with the values of good ages */
8008: for (i=1; i<=nlstate;i++){
8009: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemaxgood[cptcod]][i][cptcod];
8010: } /* i */
8011: } /* end bad */
8012: }/* end else */
8013: sum=0.;sumr=0.;
8014: for (i=1; i<=nlstate;i++){
8015: sum+=mobaverage[(int)age][i][cptcod];
8016: sumr+=probs[(int)age][i][cptcod];
8017: }
8018: if(fabs(sum - 1.) > 1.e-3) { /* bad */
1.268 ! brouard 8019: printf("Moving average A1: For this combination of covariate cptcod=%d, we can't get a smoothed prevalence which sums to one (%f) at any descending age! age=%d, could you increase bage=%d\n",cptcod,sumr, (int)age, (int)bage);
1.266 brouard 8020: } /* end bad */
8021: /* else{ /\* We found some ages summing to one, we will smooth the oldest *\/ */
8022: if(fabs(sumr - 1.) > 1.e-3) { /* bad */
1.268 ! brouard 8023: printf("Moving average A2: For this combination of covariate cptcod=%d, the raw prevalence doesn't sums to one (%f) even with smoothed values at young ages! age=%d, could you increase bage=%d\n",cptcod,sumr, (int)age, (int)bage);
1.222 brouard 8024: } /* end bad */
8025: }/* age */
1.266 brouard 8026:
8027: for (age=bage+(mob-1)/2; age<=fage; age++){/* From youngest, finding the oldest wrong */
1.222 brouard 8028: sumnewm[cptcod]=0.;
1.266 brouard 8029: sumnewmr[cptcod]=0.;
1.222 brouard 8030: for (i=1; i<=nlstate;i++){
8031: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
1.266 brouard 8032: sumnewmr[cptcod]+=probs[(int)age][i][cptcod];
8033: }
8034: if(mobilav==-1){ /* Forcing raw ages if good else agemingood */
8035: if(fabs(sumnewmr[cptcod] - 1.) <= 1.e-3) { /* good */
8036: agemingoodr[cptcod]=age;
8037: for (i=1; i<=nlstate;i++)
8038: mobaverage[(int)age][i][cptcod]=probs[(int)age][i][cptcod];
8039: }else{ /* bad we change the value with the values of good ages */
8040: for (i=1; i<=nlstate;i++){
8041: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemingoodr[cptcod]][i][cptcod];
8042: } /* i */
8043: } /* end bad */
8044: }else{
8045: if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
8046: agemingood[cptcod]=age;
8047: }else{ /* bad */
8048: for (i=1; i<=nlstate;i++){
8049: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemingood[cptcod]][i][cptcod];
8050: } /* i */
8051: } /* end bad */
8052: }/* end else */
8053: sum=0.;sumr=0.;
8054: for (i=1; i<=nlstate;i++){
8055: sum+=mobaverage[(int)age][i][cptcod];
8056: sumr+=mobaverage[(int)age][i][cptcod];
1.222 brouard 8057: }
1.266 brouard 8058: if(fabs(sum - 1.) > 1.e-3) { /* bad */
1.268 ! brouard 8059: printf("Moving average B1: For this combination of covariate cptcod=%d, we can't get a smoothed prevalence which sums to one (%f) at any descending age! age=%d, could you decrease fage=%d?\n",cptcod, sum, (int) age, (int)fage);
1.266 brouard 8060: } /* end bad */
8061: /* else{ /\* We found some ages summing to one, we will smooth the oldest *\/ */
8062: if(fabs(sumr - 1.) > 1.e-3) { /* bad */
1.268 ! brouard 8063: printf("Moving average B2: For this combination of covariate cptcod=%d, the raw prevalence doesn't sums to one (%f) even with smoothed values at young ages! age=%d, could you increase fage=%d\n",cptcod,sumr, (int)age, (int)fage);
1.222 brouard 8064: } /* end bad */
8065: }/* age */
1.266 brouard 8066:
1.222 brouard 8067:
8068: for (age=bage; age<=fage; age++){
1.235 brouard 8069: /* printf("%d %d ", cptcod, (int)age); */
1.222 brouard 8070: sumnewp[cptcod]=0.;
8071: sumnewm[cptcod]=0.;
8072: for (i=1; i<=nlstate;i++){
8073: sumnewp[cptcod]+=probs[(int)age][i][cptcod];
8074: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
8075: /* printf("%.4f %.4f ",probs[(int)age][i][cptcod], mobaverage[(int)age][i][cptcod]); */
8076: }
8077: /* printf("%.4f %.4f \n",sumnewp[cptcod], sumnewm[cptcod]); */
8078: }
8079: /* printf("\n"); */
8080: /* } */
1.266 brouard 8081:
1.222 brouard 8082: /* brutal averaging */
1.266 brouard 8083: /* for (i=1; i<=nlstate;i++){ */
8084: /* for (age=1; age<=bage; age++){ */
8085: /* mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemingood[cptcod]][i][cptcod]; */
8086: /* /\* printf("age=%d i=%d cptcod=%d mobaverage=%.4f \n",(int)age,i, cptcod, mobaverage[(int)age][i][cptcod]); *\/ */
8087: /* } */
8088: /* for (age=fage; age<=AGESUP; age++){ */
8089: /* mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemaxgood[cptcod]][i][cptcod]; */
8090: /* /\* printf("age=%d i=%d cptcod=%d mobaverage=%.4f \n",(int)age,i, cptcod, mobaverage[(int)age][i][cptcod]); *\/ */
8091: /* } */
8092: /* } /\* end i status *\/ */
8093: /* for (i=nlstate+1; i<=nlstate+ndeath;i++){ */
8094: /* for (age=1; age<=AGESUP; age++){ */
8095: /* /\*printf("i=%d, age=%d, cptcod=%d\n",i, (int)age, cptcod);*\/ */
8096: /* mobaverage[(int)age][i][cptcod]=0.; */
8097: /* } */
8098: /* } */
1.222 brouard 8099: }/* end cptcod */
1.266 brouard 8100: free_vector(agemaxgoodr,1, ncovcombmax);
8101: free_vector(agemaxgood,1, ncovcombmax);
8102: free_vector(agemingood,1, ncovcombmax);
8103: free_vector(agemingoodr,1, ncovcombmax);
8104: free_vector(sumnewmr,1, ncovcombmax);
1.222 brouard 8105: free_vector(sumnewm,1, ncovcombmax);
8106: free_vector(sumnewp,1, ncovcombmax);
8107: return 0;
8108: }/* End movingaverage */
1.218 brouard 8109:
1.126 brouard 8110:
8111: /************** Forecasting ******************/
1.267 brouard 8112: 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 8113: /* proj1, year, month, day of starting projection
8114: agemin, agemax range of age
8115: dateprev1 dateprev2 range of dates during which prevalence is computed
8116: anproj2 year of en of projection (same day and month as proj1).
8117: */
1.267 brouard 8118: int yearp, stepsize, hstepm, nhstepm, j, k, cptcod, i, h, i1, k4, nres=0;
1.126 brouard 8119: double agec; /* generic age */
8120: double agelim, ppij, yp,yp1,yp2,jprojmean,mprojmean,anprojmean;
8121: double *popeffectif,*popcount;
8122: double ***p3mat;
1.218 brouard 8123: /* double ***mobaverage; */
1.126 brouard 8124: char fileresf[FILENAMELENGTH];
8125:
8126: agelim=AGESUP;
1.211 brouard 8127: /* Compute observed prevalence between dateprev1 and dateprev2 by counting the number of people
8128: in each health status at the date of interview (if between dateprev1 and dateprev2).
8129: We still use firstpass and lastpass as another selection.
8130: */
1.214 brouard 8131: /* freqsummary(fileres, agemin, agemax, s, agev, nlstate, imx,Tvaraff,nbcode, ncodemax,mint,anint,strstart,\ */
8132: /* firstpass, lastpass, stepm, weightopt, model); */
1.126 brouard 8133:
1.201 brouard 8134: strcpy(fileresf,"F_");
8135: strcat(fileresf,fileresu);
1.126 brouard 8136: if((ficresf=fopen(fileresf,"w"))==NULL) {
8137: printf("Problem with forecast resultfile: %s\n", fileresf);
8138: fprintf(ficlog,"Problem with forecast resultfile: %s\n", fileresf);
8139: }
1.235 brouard 8140: printf("\nComputing forecasting: result on file '%s', please wait... \n", fileresf);
8141: fprintf(ficlog,"\nComputing forecasting: result on file '%s', please wait... \n", fileresf);
1.126 brouard 8142:
1.225 brouard 8143: if (cptcoveff==0) ncodemax[cptcoveff]=1;
1.126 brouard 8144:
8145:
8146: stepsize=(int) (stepm+YEARM-1)/YEARM;
8147: if (stepm<=12) stepsize=1;
8148: if(estepm < stepm){
8149: printf ("Problem %d lower than %d\n",estepm, stepm);
8150: }
8151: else hstepm=estepm;
8152:
8153: hstepm=hstepm/stepm;
8154: yp1=modf(dateintmean,&yp);/* extracts integral of datemean in yp and
8155: fractional in yp1 */
8156: anprojmean=yp;
8157: yp2=modf((yp1*12),&yp);
8158: mprojmean=yp;
8159: yp1=modf((yp2*30.5),&yp);
8160: jprojmean=yp;
8161: if(jprojmean==0) jprojmean=1;
8162: if(mprojmean==0) jprojmean=1;
8163:
1.227 brouard 8164: i1=pow(2,cptcoveff);
1.126 brouard 8165: if (cptcovn < 1){i1=1;}
8166:
8167: fprintf(ficresf,"# Mean day of interviews %.lf/%.lf/%.lf (%.2f) between %.2f and %.2f \n",jprojmean,mprojmean,anprojmean,dateintmean,dateprev1,dateprev2);
8168:
8169: fprintf(ficresf,"#****** Routine prevforecast **\n");
1.227 brouard 8170:
1.126 brouard 8171: /* if (h==(int)(YEARM*yearp)){ */
1.235 brouard 8172: for(nres=1; nres <= nresult; nres++) /* For each resultline */
8173: for(k=1; k<=i1;k++){
1.253 brouard 8174: if(i1 != 1 && TKresult[nres]!= k)
1.235 brouard 8175: continue;
1.227 brouard 8176: if(invalidvarcomb[k]){
8177: printf("\nCombination (%d) projection ignored because no cases \n",k);
8178: continue;
8179: }
8180: fprintf(ficresf,"\n#****** hpijx=probability over h years, hp.jx is weighted by observed prev \n#");
8181: for(j=1;j<=cptcoveff;j++) {
8182: fprintf(ficresf," V%d (=) %d",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
8183: }
1.235 brouard 8184: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
1.238 brouard 8185: fprintf(ficresf," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
1.235 brouard 8186: }
1.227 brouard 8187: fprintf(ficresf," yearproj age");
8188: for(j=1; j<=nlstate+ndeath;j++){
8189: for(i=1; i<=nlstate;i++)
8190: fprintf(ficresf," p%d%d",i,j);
8191: fprintf(ficresf," wp.%d",j);
8192: }
8193: for (yearp=0; yearp<=(anproj2-anproj1);yearp +=stepsize) {
8194: fprintf(ficresf,"\n");
8195: fprintf(ficresf,"\n# Forecasting at date %.lf/%.lf/%.lf ",jproj1,mproj1,anproj1+yearp);
8196: for (agec=fage; agec>=(ageminpar-1); agec--){
8197: nhstepm=(int) rint((agelim-agec)*YEARM/stepm);
8198: nhstepm = nhstepm/hstepm;
8199: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
8200: oldm=oldms;savm=savms;
1.268 ! brouard 8201: /* We compute pii at age agec over nhstepm);*/
1.235 brouard 8202: hpxij(p3mat,nhstepm,agec,hstepm,p,nlstate,stepm,oldm,savm, k,nres);
1.268 ! brouard 8203: /* Then we print p3mat for h corresponding to the right agec+h*stepms=yearp */
1.227 brouard 8204: for (h=0; h<=nhstepm; h++){
8205: if (h*hstepm/YEARM*stepm ==yearp) {
1.268 ! brouard 8206: break;
! 8207: }
! 8208: }
! 8209: fprintf(ficresf,"\n");
! 8210: for(j=1;j<=cptcoveff;j++)
! 8211: fprintf(ficresf,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
! 8212: fprintf(ficresf,"%.f %.f ",anproj1+yearp,agec+h*hstepm/YEARM*stepm);
! 8213:
! 8214: for(j=1; j<=nlstate+ndeath;j++) {
! 8215: ppij=0.;
! 8216: for(i=1; i<=nlstate;i++) {
! 8217: /* if (mobilav>=1) */
! 8218: ppij=ppij+p3mat[i][j][h]*mobaverage[(int)agec][i][k];
! 8219: /* else { */ /* even if mobilav==-1 we use mobaverage */
! 8220: /* ppij=ppij+p3mat[i][j][h]*probs[(int)(agec)][i][k]; */
! 8221: /* } */
! 8222: fprintf(ficresf," %.3f", p3mat[i][j][h]);
! 8223: } /* end i */
! 8224: fprintf(ficresf," %.3f", ppij);
! 8225: }/* end j */
1.227 brouard 8226: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
8227: } /* end agec */
1.266 brouard 8228: /* diffyear=(int) anproj1+yearp-ageminpar-1; */
8229: /*printf("Prevforecast %d+%d-%d=diffyear=%d\n",(int) anproj1, (int)yearp,(int)ageminpar,(int) anproj1-(int)ageminpar);*/
1.227 brouard 8230: } /* end yearp */
8231: } /* end k */
1.219 brouard 8232:
1.126 brouard 8233: fclose(ficresf);
1.215 brouard 8234: printf("End of Computing forecasting \n");
8235: fprintf(ficlog,"End of Computing forecasting\n");
8236:
1.126 brouard 8237: }
8238:
1.218 brouard 8239: /* /\************** Back Forecasting ******************\/ */
1.267 brouard 8240: void prevbackforecast(char fileres[], double ***prevacurrent, double anback1, double mback1, double jback1, double ageminpar, double agemax, double dateprev1, double dateprev2, int mobilav, double bage, double fage, int firstpass, int lastpass, double anback2, double p[], int cptcoveff){
8241: /* back1, year, month, day of starting backection
8242: agemin, agemax range of age
8243: dateprev1 dateprev2 range of dates during which prevalence is computed
8244: anback2 year of en of backection (same day and month as back1).
8245: */
8246: int yearp, stepsize, hstepm, nhstepm, j, k, cptcod, i, h, i1, k4, nres=0;
8247: double agec; /* generic age */
1.268 ! brouard 8248: double agelim, ppij, ppi, yp,yp1,yp2,jprojmean,mprojmean,anprojmean;
1.267 brouard 8249: double *popeffectif,*popcount;
8250: double ***p3mat;
8251: /* double ***mobaverage; */
8252: char fileresfb[FILENAMELENGTH];
8253:
1.268 ! brouard 8254: agelim=AGEINF;
1.267 brouard 8255: /* Compute observed prevalence between dateprev1 and dateprev2 by counting the number of people
8256: in each health status at the date of interview (if between dateprev1 and dateprev2).
8257: We still use firstpass and lastpass as another selection.
8258: */
8259: /* freqsummary(fileres, agemin, agemax, s, agev, nlstate, imx,Tvaraff,nbcode, ncodemax,mint,anint,strstart,\ */
8260: /* firstpass, lastpass, stepm, weightopt, model); */
8261:
8262: /*Do we need to compute prevalence again?*/
8263:
8264: /* prevalence(probs, ageminpar, agemax, s, agev, nlstate, imx, Tvar, nbcode, ncodemax, mint, anint, dateprev1, dateprev2, firstpass, lastpass); */
8265:
8266: strcpy(fileresfb,"FB_");
8267: strcat(fileresfb,fileresu);
8268: if((ficresfb=fopen(fileresfb,"w"))==NULL) {
8269: printf("Problem with back forecast resultfile: %s\n", fileresfb);
8270: fprintf(ficlog,"Problem with back forecast resultfile: %s\n", fileresfb);
8271: }
8272: printf("\nComputing back forecasting: result on file '%s', please wait... \n", fileresfb);
8273: fprintf(ficlog,"\nComputing back forecasting: result on file '%s', please wait... \n", fileresfb);
8274:
8275: if (cptcoveff==0) ncodemax[cptcoveff]=1;
8276:
8277:
8278: stepsize=(int) (stepm+YEARM-1)/YEARM;
8279: if (stepm<=12) stepsize=1;
8280: if(estepm < stepm){
8281: printf ("Problem %d lower than %d\n",estepm, stepm);
8282: }
8283: else hstepm=estepm;
8284:
8285: hstepm=hstepm/stepm;
8286: yp1=modf(dateintmean,&yp);/* extracts integral of datemean in yp and
8287: fractional in yp1 */
8288: anprojmean=yp;
8289: yp2=modf((yp1*12),&yp);
8290: mprojmean=yp;
8291: yp1=modf((yp2*30.5),&yp);
8292: jprojmean=yp;
8293: if(jprojmean==0) jprojmean=1;
8294: if(mprojmean==0) jprojmean=1;
8295:
8296: i1=pow(2,cptcoveff);
8297: if (cptcovn < 1){i1=1;}
8298:
8299: fprintf(ficresfb,"# Mean day of interviews %.lf/%.lf/%.lf (%.2f) between %.2f and %.2f \n",jprojmean,mprojmean,anprojmean,dateintmean,dateprev1,dateprev2);
1.268 ! brouard 8300: printf("# Mean day of interviews %.lf/%.lf/%.lf (%.2f) between %.2f and %.2f \n",jprojmean,mprojmean,anprojmean,dateintmean,dateprev1,dateprev2);
1.267 brouard 8301:
8302: fprintf(ficresfb,"#****** Routine prevbackforecast **\n");
8303:
8304: /* if (h==(int)(YEARM*yearp)){ */
8305: /* for(cptcov=1, k=0;cptcov<=i1;cptcov++){ */
8306: /* for(cptcod=1;cptcod<=ncodemax[cptcoveff];cptcod++){ */
8307: /* k=k+1; */
8308: for(nres=1; nres <= nresult; nres++) /* For each resultline */
8309: for(k=1; k<=i1;k++){
8310: if(i1 != 1 && TKresult[nres]!= k)
8311: continue;
8312: if(invalidvarcomb[k]){
8313: printf("\nCombination (%d) projection ignored because no cases \n",k);
8314: continue;
8315: }
1.268 ! brouard 8316: fprintf(ficresfb,"\n#****** hbijx=probability over h years, hb.jx is weighted by observed prev \n#");
1.267 brouard 8317: for(j=1;j<=cptcoveff;j++) {
8318: fprintf(ficresfb," V%d (=) %d",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
8319: }
8320: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
8321: fprintf(ficresf," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
8322: }
8323: fprintf(ficresfb," yearbproj age");
8324: for(j=1; j<=nlstate+ndeath;j++){
8325: for(i=1; i<=nlstate;i++)
1.268 ! brouard 8326: fprintf(ficresfb," b%d%d",i,j);
! 8327: fprintf(ficresfb," b.%d",j);
1.267 brouard 8328: }
8329: for (yearp=0; yearp>=(anback2-anback1);yearp -=stepsize) {
8330: /* for (yearp=0; yearp<=(anproj2-anproj1);yearp +=stepsize) { */
8331: fprintf(ficresfb,"\n");
8332: fprintf(ficresfb,"\n# Back Forecasting at date %.lf/%.lf/%.lf ",jback1,mback1,anback1+yearp);
1.268 ! brouard 8333: printf("\n# Back Forecasting at date %.lf/%.lf/%.lf ",jback1,mback1,anback1+yearp);
1.267 brouard 8334: /* for (agec=fage; agec>=(ageminpar-1); agec--){ */
8335: /* nhstepm=(int) rint((agelim-agec)*YEARM/stepm); */
1.268 ! brouard 8336: for (agec=bage; agec<=agemax-1; agec++){ /* testing */
! 8337: /* We compute bij at age agec over nhstepm, nhstepm decreases when agec increases because of agemax;*/
! 8338: nhstepm=(int) rint((agec-agelim)*YEARM/stepm);
1.267 brouard 8339: nhstepm = nhstepm/hstepm;
8340: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
8341: oldm=oldms;savm=savms;
1.268 ! brouard 8342: /* computes hbxij at age agec over 1 to nhstepm */
1.267 brouard 8343: hbxij(p3mat,nhstepm,agec,hstepm,p,prevacurrent,nlstate,stepm, k, nres);
1.268 ! brouard 8344: /* hpxij(p3mat,nhstepm,agec,hstepm,p, nlstate,stepm,oldm,savm, k,nres); */
! 8345: /* Then we print p3mat for h corresponding to the right agec+h*stepms=yearp */
! 8346: /* printf(" agec=%.2f\n",agec);fflush(stdout); */
1.267 brouard 8347: for (h=0; h<=nhstepm; h++){
1.268 ! brouard 8348: if (h*hstepm/YEARM*stepm ==-yearp) {
! 8349: break;
! 8350: }
! 8351: }
! 8352: fprintf(ficresfb,"\n");
! 8353: for(j=1;j<=cptcoveff;j++)
! 8354: fprintf(ficresfb,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
! 8355: fprintf(ficresfb,"%.f %.f ",anback1+yearp,agec-h*hstepm/YEARM*stepm);
! 8356: for(i=1; i<=nlstate+ndeath;i++) {
! 8357: ppij=0.;ppi=0.;
! 8358: for(j=1; j<=nlstate;j++) {
! 8359: /* if (mobilav==1) */
! 8360: ppij=ppij+p3mat[i][j][h]*mobaverage[(int)agec][j][k];
! 8361: ppi=ppi+mobaverage[(int)agec][j][k];
1.267 brouard 8362: /* else { */
8363: /* ppij=ppij+p3mat[i][j][h]*probs[(int)(agec)][i][k]; */
8364: /* } */
1.268 ! brouard 8365: fprintf(ficresfb," %.3f", p3mat[i][j][h]);
! 8366: } /* end j */
! 8367: if(ppi <0.99){
! 8368: printf("Error in prevbackforecast, prevalence doesn't sum to 1 for state %d: %3f\n",i, ppi);
! 8369: fprintf(ficlog,"Error in prevbackforecast, prevalence doesn't sum to 1 for state %d: %3f\n",i, ppi);
! 8370: }
! 8371: fprintf(ficresfb," %.3f", ppij);
! 8372: }/* end j */
1.267 brouard 8373: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
8374: } /* end agec */
8375: } /* end yearp */
8376: } /* end k */
1.217 brouard 8377:
1.267 brouard 8378: /* if (mobilav!=0) free_ma3x(mobaverage,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
1.217 brouard 8379:
1.267 brouard 8380: fclose(ficresfb);
8381: printf("End of Computing Back forecasting \n");
8382: fprintf(ficlog,"End of Computing Back forecasting\n");
1.218 brouard 8383:
1.267 brouard 8384: }
1.217 brouard 8385:
1.126 brouard 8386: /************** Forecasting *****not tested NB*************/
1.227 brouard 8387: /* 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 8388:
1.227 brouard 8389: /* int cpt, stepsize, hstepm, nhstepm, j,k,c, cptcod, i,h; */
8390: /* int *popage; */
8391: /* double calagedatem, agelim, kk1, kk2; */
8392: /* double *popeffectif,*popcount; */
8393: /* double ***p3mat,***tabpop,***tabpopprev; */
8394: /* /\* double ***mobaverage; *\/ */
8395: /* char filerespop[FILENAMELENGTH]; */
1.126 brouard 8396:
1.227 brouard 8397: /* tabpop= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
8398: /* tabpopprev= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
8399: /* agelim=AGESUP; */
8400: /* calagedatem=(anpyram+mpyram/12.+jpyram/365.-dateintmean)*YEARM; */
1.126 brouard 8401:
1.227 brouard 8402: /* prevalence(probs, ageminpar, agemax, s, agev, nlstate, imx, Tvar, nbcode, ncodemax, mint, anint, dateprev1, dateprev2, firstpass, lastpass); */
1.126 brouard 8403:
8404:
1.227 brouard 8405: /* strcpy(filerespop,"POP_"); */
8406: /* strcat(filerespop,fileresu); */
8407: /* if((ficrespop=fopen(filerespop,"w"))==NULL) { */
8408: /* printf("Problem with forecast resultfile: %s\n", filerespop); */
8409: /* fprintf(ficlog,"Problem with forecast resultfile: %s\n", filerespop); */
8410: /* } */
8411: /* printf("Computing forecasting: result on file '%s' \n", filerespop); */
8412: /* fprintf(ficlog,"Computing forecasting: result on file '%s' \n", filerespop); */
1.126 brouard 8413:
1.227 brouard 8414: /* if (cptcoveff==0) ncodemax[cptcoveff]=1; */
1.126 brouard 8415:
1.227 brouard 8416: /* /\* if (mobilav!=0) { *\/ */
8417: /* /\* mobaverage= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); *\/ */
8418: /* /\* if (movingaverage(probs, ageminpar, fage, mobaverage,mobilav)!=0){ *\/ */
8419: /* /\* fprintf(ficlog," Error in movingaverage mobilav=%d\n",mobilav); *\/ */
8420: /* /\* printf(" Error in movingaverage mobilav=%d\n",mobilav); *\/ */
8421: /* /\* } *\/ */
8422: /* /\* } *\/ */
1.126 brouard 8423:
1.227 brouard 8424: /* stepsize=(int) (stepm+YEARM-1)/YEARM; */
8425: /* if (stepm<=12) stepsize=1; */
1.126 brouard 8426:
1.227 brouard 8427: /* agelim=AGESUP; */
1.126 brouard 8428:
1.227 brouard 8429: /* hstepm=1; */
8430: /* hstepm=hstepm/stepm; */
1.218 brouard 8431:
1.227 brouard 8432: /* if (popforecast==1) { */
8433: /* if((ficpop=fopen(popfile,"r"))==NULL) { */
8434: /* printf("Problem with population file : %s\n",popfile);exit(0); */
8435: /* fprintf(ficlog,"Problem with population file : %s\n",popfile);exit(0); */
8436: /* } */
8437: /* popage=ivector(0,AGESUP); */
8438: /* popeffectif=vector(0,AGESUP); */
8439: /* popcount=vector(0,AGESUP); */
1.126 brouard 8440:
1.227 brouard 8441: /* i=1; */
8442: /* while ((c=fscanf(ficpop,"%d %lf\n",&popage[i],&popcount[i])) != EOF) i=i+1; */
1.218 brouard 8443:
1.227 brouard 8444: /* imx=i; */
8445: /* for (i=1; i<imx;i++) popeffectif[popage[i]]=popcount[i]; */
8446: /* } */
1.218 brouard 8447:
1.227 brouard 8448: /* for(cptcov=1,k=0;cptcov<=i2;cptcov++){ */
8449: /* for(cptcod=1;cptcod<=ncodemax[cptcoveff];cptcod++){ */
8450: /* k=k+1; */
8451: /* fprintf(ficrespop,"\n#******"); */
8452: /* for(j=1;j<=cptcoveff;j++) { */
8453: /* fprintf(ficrespop," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]); */
8454: /* } */
8455: /* fprintf(ficrespop,"******\n"); */
8456: /* fprintf(ficrespop,"# Age"); */
8457: /* for(j=1; j<=nlstate+ndeath;j++) fprintf(ficrespop," P.%d",j); */
8458: /* if (popforecast==1) fprintf(ficrespop," [Population]"); */
1.126 brouard 8459:
1.227 brouard 8460: /* for (cpt=0; cpt<=0;cpt++) { */
8461: /* fprintf(ficrespop,"\n\n# Forecasting at date %.lf/%.lf/%.lf ",jpyram,mpyram,anpyram+cpt); */
1.126 brouard 8462:
1.227 brouard 8463: /* for (agedeb=(fage-((int)calagedatem %12/12.)); agedeb>=(ageminpar-((int)calagedatem %12)/12.); agedeb--){ */
8464: /* nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); */
8465: /* nhstepm = nhstepm/hstepm; */
1.126 brouard 8466:
1.227 brouard 8467: /* p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
8468: /* oldm=oldms;savm=savms; */
8469: /* hpxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k); */
1.218 brouard 8470:
1.227 brouard 8471: /* for (h=0; h<=nhstepm; h++){ */
8472: /* if (h==(int) (calagedatem+YEARM*cpt)) { */
8473: /* fprintf(ficrespop,"\n %3.f ",agedeb+h*hstepm/YEARM*stepm); */
8474: /* } */
8475: /* for(j=1; j<=nlstate+ndeath;j++) { */
8476: /* kk1=0.;kk2=0; */
8477: /* for(i=1; i<=nlstate;i++) { */
8478: /* if (mobilav==1) */
8479: /* kk1=kk1+p3mat[i][j][h]*mobaverage[(int)agedeb+1][i][cptcod]; */
8480: /* else { */
8481: /* kk1=kk1+p3mat[i][j][h]*probs[(int)(agedeb+1)][i][cptcod]; */
8482: /* } */
8483: /* } */
8484: /* if (h==(int)(calagedatem+12*cpt)){ */
8485: /* tabpop[(int)(agedeb)][j][cptcod]=kk1; */
8486: /* /\*fprintf(ficrespop," %.3f", kk1); */
8487: /* if (popforecast==1) fprintf(ficrespop," [%.f]", kk1*popeffectif[(int)agedeb+1]);*\/ */
8488: /* } */
8489: /* } */
8490: /* for(i=1; i<=nlstate;i++){ */
8491: /* kk1=0.; */
8492: /* for(j=1; j<=nlstate;j++){ */
8493: /* kk1= kk1+tabpop[(int)(agedeb)][j][cptcod]; */
8494: /* } */
8495: /* tabpopprev[(int)(agedeb)][i][cptcod]=tabpop[(int)(agedeb)][i][cptcod]/kk1*popeffectif[(int)(agedeb+(calagedatem+12*cpt)*hstepm/YEARM*stepm-1)]; */
8496: /* } */
1.218 brouard 8497:
1.227 brouard 8498: /* if (h==(int)(calagedatem+12*cpt)) */
8499: /* for(j=1; j<=nlstate;j++) */
8500: /* fprintf(ficrespop," %15.2f",tabpopprev[(int)(agedeb+1)][j][cptcod]); */
8501: /* } */
8502: /* free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
8503: /* } */
8504: /* } */
1.218 brouard 8505:
1.227 brouard 8506: /* /\******\/ */
1.218 brouard 8507:
1.227 brouard 8508: /* for (cpt=1; cpt<=(anpyram1-anpyram);cpt++) { */
8509: /* fprintf(ficrespop,"\n\n# Forecasting at date %.lf/%.lf/%.lf ",jpyram,mpyram,anpyram+cpt); */
8510: /* for (agedeb=(fage-((int)calagedatem %12/12.)); agedeb>=(ageminpar-((int)calagedatem %12)/12.); agedeb--){ */
8511: /* nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); */
8512: /* nhstepm = nhstepm/hstepm; */
1.126 brouard 8513:
1.227 brouard 8514: /* p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
8515: /* oldm=oldms;savm=savms; */
8516: /* hpxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k); */
8517: /* for (h=0; h<=nhstepm; h++){ */
8518: /* if (h==(int) (calagedatem+YEARM*cpt)) { */
8519: /* fprintf(ficresf,"\n %3.f ",agedeb+h*hstepm/YEARM*stepm); */
8520: /* } */
8521: /* for(j=1; j<=nlstate+ndeath;j++) { */
8522: /* kk1=0.;kk2=0; */
8523: /* for(i=1; i<=nlstate;i++) { */
8524: /* kk1=kk1+p3mat[i][j][h]*tabpopprev[(int)agedeb+1][i][cptcod]; */
8525: /* } */
8526: /* if (h==(int)(calagedatem+12*cpt)) fprintf(ficresf," %15.2f", kk1); */
8527: /* } */
8528: /* } */
8529: /* free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
8530: /* } */
8531: /* } */
8532: /* } */
8533: /* } */
1.218 brouard 8534:
1.227 brouard 8535: /* /\* if (mobilav!=0) free_ma3x(mobaverage,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); *\/ */
1.218 brouard 8536:
1.227 brouard 8537: /* if (popforecast==1) { */
8538: /* free_ivector(popage,0,AGESUP); */
8539: /* free_vector(popeffectif,0,AGESUP); */
8540: /* free_vector(popcount,0,AGESUP); */
8541: /* } */
8542: /* free_ma3x(tabpop,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
8543: /* free_ma3x(tabpopprev,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
8544: /* fclose(ficrespop); */
8545: /* } /\* End of popforecast *\/ */
1.218 brouard 8546:
1.126 brouard 8547: int fileappend(FILE *fichier, char *optionfich)
8548: {
8549: if((fichier=fopen(optionfich,"a"))==NULL) {
8550: printf("Problem with file: %s\n", optionfich);
8551: fprintf(ficlog,"Problem with file: %s\n", optionfich);
8552: return (0);
8553: }
8554: fflush(fichier);
8555: return (1);
8556: }
8557:
8558:
8559: /**************** function prwizard **********************/
8560: void prwizard(int ncovmodel, int nlstate, int ndeath, char model[], FILE *ficparo)
8561: {
8562:
8563: /* Wizard to print covariance matrix template */
8564:
1.164 brouard 8565: char ca[32], cb[32];
8566: int i,j, k, li, lj, lk, ll, jj, npar, itimes;
1.126 brouard 8567: int numlinepar;
8568:
8569: printf("# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
8570: fprintf(ficparo,"# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
8571: for(i=1; i <=nlstate; i++){
8572: jj=0;
8573: for(j=1; j <=nlstate+ndeath; j++){
8574: if(j==i) continue;
8575: jj++;
8576: /*ca[0]= k+'a'-1;ca[1]='\0';*/
8577: printf("%1d%1d",i,j);
8578: fprintf(ficparo,"%1d%1d",i,j);
8579: for(k=1; k<=ncovmodel;k++){
8580: /* printf(" %lf",param[i][j][k]); */
8581: /* fprintf(ficparo," %lf",param[i][j][k]); */
8582: printf(" 0.");
8583: fprintf(ficparo," 0.");
8584: }
8585: printf("\n");
8586: fprintf(ficparo,"\n");
8587: }
8588: }
8589: printf("# Scales (for hessian or gradient estimation)\n");
8590: fprintf(ficparo,"# Scales (for hessian or gradient estimation)\n");
8591: npar= (nlstate+ndeath-1)*nlstate*ncovmodel; /* Number of parameters*/
8592: for(i=1; i <=nlstate; i++){
8593: jj=0;
8594: for(j=1; j <=nlstate+ndeath; j++){
8595: if(j==i) continue;
8596: jj++;
8597: fprintf(ficparo,"%1d%1d",i,j);
8598: printf("%1d%1d",i,j);
8599: fflush(stdout);
8600: for(k=1; k<=ncovmodel;k++){
8601: /* printf(" %le",delti3[i][j][k]); */
8602: /* fprintf(ficparo," %le",delti3[i][j][k]); */
8603: printf(" 0.");
8604: fprintf(ficparo," 0.");
8605: }
8606: numlinepar++;
8607: printf("\n");
8608: fprintf(ficparo,"\n");
8609: }
8610: }
8611: printf("# Covariance matrix\n");
8612: /* # 121 Var(a12)\n\ */
8613: /* # 122 Cov(b12,a12) Var(b12)\n\ */
8614: /* # 131 Cov(a13,a12) Cov(a13,b12, Var(a13)\n\ */
8615: /* # 132 Cov(b13,a12) Cov(b13,b12, Cov(b13,a13) Var(b13)\n\ */
8616: /* # 212 Cov(a21,a12) Cov(a21,b12, Cov(a21,a13) Cov(a21,b13) Var(a21)\n\ */
8617: /* # 212 Cov(b21,a12) Cov(b21,b12, Cov(b21,a13) Cov(b21,b13) Cov(b21,a21) Var(b21)\n\ */
8618: /* # 232 Cov(a23,a12) Cov(a23,b12, Cov(a23,a13) Cov(a23,b13) Cov(a23,a21) Cov(a23,b21) Var(a23)\n\ */
8619: /* # 232 Cov(b23,a12) Cov(b23,b12) ... Var (b23)\n" */
8620: fflush(stdout);
8621: fprintf(ficparo,"# Covariance matrix\n");
8622: /* # 121 Var(a12)\n\ */
8623: /* # 122 Cov(b12,a12) Var(b12)\n\ */
8624: /* # ...\n\ */
8625: /* # 232 Cov(b23,a12) Cov(b23,b12) ... Var (b23)\n" */
8626:
8627: for(itimes=1;itimes<=2;itimes++){
8628: jj=0;
8629: for(i=1; i <=nlstate; i++){
8630: for(j=1; j <=nlstate+ndeath; j++){
8631: if(j==i) continue;
8632: for(k=1; k<=ncovmodel;k++){
8633: jj++;
8634: ca[0]= k+'a'-1;ca[1]='\0';
8635: if(itimes==1){
8636: printf("#%1d%1d%d",i,j,k);
8637: fprintf(ficparo,"#%1d%1d%d",i,j,k);
8638: }else{
8639: printf("%1d%1d%d",i,j,k);
8640: fprintf(ficparo,"%1d%1d%d",i,j,k);
8641: /* printf(" %.5le",matcov[i][j]); */
8642: }
8643: ll=0;
8644: for(li=1;li <=nlstate; li++){
8645: for(lj=1;lj <=nlstate+ndeath; lj++){
8646: if(lj==li) continue;
8647: for(lk=1;lk<=ncovmodel;lk++){
8648: ll++;
8649: if(ll<=jj){
8650: cb[0]= lk +'a'-1;cb[1]='\0';
8651: if(ll<jj){
8652: if(itimes==1){
8653: printf(" Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
8654: fprintf(ficparo," Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
8655: }else{
8656: printf(" 0.");
8657: fprintf(ficparo," 0.");
8658: }
8659: }else{
8660: if(itimes==1){
8661: printf(" Var(%s%1d%1d)",ca,i,j);
8662: fprintf(ficparo," Var(%s%1d%1d)",ca,i,j);
8663: }else{
8664: printf(" 0.");
8665: fprintf(ficparo," 0.");
8666: }
8667: }
8668: }
8669: } /* end lk */
8670: } /* end lj */
8671: } /* end li */
8672: printf("\n");
8673: fprintf(ficparo,"\n");
8674: numlinepar++;
8675: } /* end k*/
8676: } /*end j */
8677: } /* end i */
8678: } /* end itimes */
8679:
8680: } /* end of prwizard */
8681: /******************* Gompertz Likelihood ******************************/
8682: double gompertz(double x[])
8683: {
8684: double A,B,L=0.0,sump=0.,num=0.;
8685: int i,n=0; /* n is the size of the sample */
8686:
1.220 brouard 8687: for (i=1;i<=imx ; i++) {
1.126 brouard 8688: sump=sump+weight[i];
8689: /* sump=sump+1;*/
8690: num=num+1;
8691: }
8692:
8693:
8694: /* for (i=0; i<=imx; i++)
8695: 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]);*/
8696:
8697: for (i=1;i<=imx ; i++)
8698: {
8699: if (cens[i] == 1 && wav[i]>1)
8700: A=-x[1]/(x[2])*(exp(x[2]*(agecens[i]-agegomp))-exp(x[2]*(ageexmed[i]-agegomp)));
8701:
8702: if (cens[i] == 0 && wav[i]>1)
8703: A=-x[1]/(x[2])*(exp(x[2]*(agedc[i]-agegomp))-exp(x[2]*(ageexmed[i]-agegomp)))
8704: +log(x[1]/YEARM)+x[2]*(agedc[i]-agegomp)+log(YEARM);
8705:
8706: /*if (wav[i] > 1 && agecens[i] > 15) {*/ /* ??? */
8707: if (wav[i] > 1 ) { /* ??? */
8708: L=L+A*weight[i];
8709: /* 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]);*/
8710: }
8711: }
8712:
8713: /*printf("x1=%2.9f x2=%2.9f x3=%2.9f L=%f\n",x[1],x[2],x[3],L);*/
8714:
8715: return -2*L*num/sump;
8716: }
8717:
1.136 brouard 8718: #ifdef GSL
8719: /******************* Gompertz_f Likelihood ******************************/
8720: double gompertz_f(const gsl_vector *v, void *params)
8721: {
8722: double A,B,LL=0.0,sump=0.,num=0.;
8723: double *x= (double *) v->data;
8724: int i,n=0; /* n is the size of the sample */
8725:
8726: for (i=0;i<=imx-1 ; i++) {
8727: sump=sump+weight[i];
8728: /* sump=sump+1;*/
8729: num=num+1;
8730: }
8731:
8732:
8733: /* for (i=0; i<=imx; i++)
8734: 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]);*/
8735: printf("x[0]=%lf x[1]=%lf\n",x[0],x[1]);
8736: for (i=1;i<=imx ; i++)
8737: {
8738: if (cens[i] == 1 && wav[i]>1)
8739: A=-x[0]/(x[1])*(exp(x[1]*(agecens[i]-agegomp))-exp(x[1]*(ageexmed[i]-agegomp)));
8740:
8741: if (cens[i] == 0 && wav[i]>1)
8742: A=-x[0]/(x[1])*(exp(x[1]*(agedc[i]-agegomp))-exp(x[1]*(ageexmed[i]-agegomp)))
8743: +log(x[0]/YEARM)+x[1]*(agedc[i]-agegomp)+log(YEARM);
8744:
8745: /*if (wav[i] > 1 && agecens[i] > 15) {*/ /* ??? */
8746: if (wav[i] > 1 ) { /* ??? */
8747: LL=LL+A*weight[i];
8748: /* 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]);*/
8749: }
8750: }
8751:
8752: /*printf("x1=%2.9f x2=%2.9f x3=%2.9f L=%f\n",x[1],x[2],x[3],L);*/
8753: printf("x[0]=%lf x[1]=%lf -2*LL*num/sump=%lf\n",x[0],x[1],-2*LL*num/sump);
8754:
8755: return -2*LL*num/sump;
8756: }
8757: #endif
8758:
1.126 brouard 8759: /******************* Printing html file ***********/
1.201 brouard 8760: void printinghtmlmort(char fileresu[], char title[], char datafile[], int firstpass, \
1.126 brouard 8761: int lastpass, int stepm, int weightopt, char model[],\
8762: int imx, double p[],double **matcov,double agemortsup){
8763: int i,k;
8764:
8765: fprintf(fichtm,"<ul><li><h4>Result files </h4>\n Force of mortality. Parameters of the Gompertz fit (with confidence interval in brackets):<br>");
8766: fprintf(fichtm," mu(age) =%lf*exp(%lf*(age-%d)) per year<br><br>",p[1],p[2],agegomp);
8767: for (i=1;i<=2;i++)
8768: 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 8769: fprintf(fichtm,"<br><br><img src=\"graphmort.svg\">");
1.126 brouard 8770: fprintf(fichtm,"</ul>");
8771:
8772: fprintf(fichtm,"<ul><li><h4>Life table</h4>\n <br>");
8773:
8774: 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>");
8775:
8776: for (k=agegomp;k<(agemortsup-2);k++)
8777: 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]);
8778:
8779:
8780: fflush(fichtm);
8781: }
8782:
8783: /******************* Gnuplot file **************/
1.201 brouard 8784: void printinggnuplotmort(char fileresu[], char optionfilefiname[], double ageminpar, double agemaxpar, double fage , char pathc[], double p[]){
1.126 brouard 8785:
8786: char dirfileres[132],optfileres[132];
1.164 brouard 8787:
1.126 brouard 8788: int ng;
8789:
8790:
8791: /*#ifdef windows */
8792: fprintf(ficgp,"cd \"%s\" \n",pathc);
8793: /*#endif */
8794:
8795:
8796: strcpy(dirfileres,optionfilefiname);
8797: strcpy(optfileres,"vpl");
1.199 brouard 8798: fprintf(ficgp,"set out \"graphmort.svg\"\n ");
1.126 brouard 8799: fprintf(ficgp,"set xlabel \"Age\"\n set ylabel \"Force of mortality (per year)\" \n ");
1.199 brouard 8800: fprintf(ficgp, "set ter svg size 640, 480\n set log y\n");
1.145 brouard 8801: /* fprintf(ficgp, "set size 0.65,0.65\n"); */
1.126 brouard 8802: fprintf(ficgp,"plot [%d:100] %lf*exp(%lf*(x-%d))",agegomp,p[1],p[2],agegomp);
8803:
8804: }
8805:
1.136 brouard 8806: int readdata(char datafile[], int firstobs, int lastobs, int *imax)
8807: {
1.126 brouard 8808:
1.136 brouard 8809: /*-------- data file ----------*/
8810: FILE *fic;
8811: char dummy[]=" ";
1.240 brouard 8812: int i=0, j=0, n=0, iv=0, v;
1.223 brouard 8813: int lstra;
1.136 brouard 8814: int linei, month, year,iout;
8815: char line[MAXLINE], linetmp[MAXLINE];
1.164 brouard 8816: char stra[MAXLINE], strb[MAXLINE];
1.136 brouard 8817: char *stratrunc;
1.223 brouard 8818:
1.240 brouard 8819: DummyV=ivector(1,NCOVMAX); /* 1 to 3 */
8820: FixedV=ivector(1,NCOVMAX); /* 1 to 3 */
1.126 brouard 8821:
1.240 brouard 8822: for(v=1; v <=ncovcol;v++){
8823: DummyV[v]=0;
8824: FixedV[v]=0;
8825: }
8826: for(v=ncovcol+1; v <=ncovcol+nqv;v++){
8827: DummyV[v]=1;
8828: FixedV[v]=0;
8829: }
8830: for(v=ncovcol+nqv+1; v <=ncovcol+nqv+ntv;v++){
8831: DummyV[v]=0;
8832: FixedV[v]=1;
8833: }
8834: for(v=ncovcol+nqv+ntv+1; v <=ncovcol+nqv+ntv+nqtv;v++){
8835: DummyV[v]=1;
8836: FixedV[v]=1;
8837: }
8838: for(v=1; v <=ncovcol+nqv+ntv+nqtv;v++){
8839: printf("Covariate type in the data: V%d, DummyV(V%d)=%d, FixedV(V%d)=%d\n",v,v,DummyV[v],v,FixedV[v]);
8840: 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]);
8841: }
1.126 brouard 8842:
1.136 brouard 8843: if((fic=fopen(datafile,"r"))==NULL) {
1.218 brouard 8844: printf("Problem while opening datafile: %s with errno='%s'\n", datafile,strerror(errno));fflush(stdout);
8845: fprintf(ficlog,"Problem while opening datafile: %s with errno='%s'\n", datafile,strerror(errno));fflush(ficlog);return 1;
1.136 brouard 8846: }
1.126 brouard 8847:
1.136 brouard 8848: i=1;
8849: linei=0;
8850: while ((fgets(line, MAXLINE, fic) != NULL) &&((i >= firstobs) && (i <=lastobs))) {
8851: linei=linei+1;
8852: for(j=strlen(line); j>=0;j--){ /* Untabifies line */
8853: if(line[j] == '\t')
8854: line[j] = ' ';
8855: }
8856: for(j=strlen(line)-1; (line[j]==' ')||(line[j]==10)||(line[j]==13);j--){
8857: ;
8858: };
8859: line[j+1]=0; /* Trims blanks at end of line */
8860: if(line[0]=='#'){
8861: fprintf(ficlog,"Comment line\n%s\n",line);
8862: printf("Comment line\n%s\n",line);
8863: continue;
8864: }
8865: trimbb(linetmp,line); /* Trims multiple blanks in line */
1.164 brouard 8866: strcpy(line, linetmp);
1.223 brouard 8867:
8868: /* Loops on waves */
8869: for (j=maxwav;j>=1;j--){
8870: for (iv=nqtv;iv>=1;iv--){ /* Loop on time varying quantitative variables */
1.238 brouard 8871: cutv(stra, strb, line, ' ');
8872: if(strb[0]=='.') { /* Missing value */
8873: lval=-1;
8874: cotqvar[j][iv][i]=-1; /* 0.0/0.0 */
8875: cotvar[j][ntv+iv][i]=-1; /* For performance reasons */
8876: if(isalpha(strb[1])) { /* .m or .d Really Missing value */
8877: 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);
8878: 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);
8879: return 1;
8880: }
8881: }else{
8882: errno=0;
8883: /* what_kind_of_number(strb); */
8884: dval=strtod(strb,&endptr);
8885: /* if( strb[0]=='\0' || (*endptr != '\0')){ */
8886: /* if(strb != endptr && *endptr == '\0') */
8887: /* dval=dlval; */
8888: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN)) */
8889: if( strb[0]=='\0' || (*endptr != '\0')){
8890: 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);
8891: 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);
8892: return 1;
8893: }
8894: cotqvar[j][iv][i]=dval;
8895: cotvar[j][ntv+iv][i]=dval;
8896: }
8897: strcpy(line,stra);
1.223 brouard 8898: }/* end loop ntqv */
1.225 brouard 8899:
1.223 brouard 8900: for (iv=ntv;iv>=1;iv--){ /* Loop on time varying dummies */
1.238 brouard 8901: cutv(stra, strb, line, ' ');
8902: if(strb[0]=='.') { /* Missing value */
8903: lval=-1;
8904: }else{
8905: errno=0;
8906: lval=strtol(strb,&endptr,10);
8907: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN))*/
8908: if( strb[0]=='\0' || (*endptr != '\0')){
8909: 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);
8910: 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);
8911: return 1;
8912: }
8913: }
8914: if(lval <-1 || lval >1){
8915: printf("Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.223 brouard 8916: Should be a value of %d(nth) covariate (0 should be the value for the reference and 1\n \
8917: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.238 brouard 8918: For example, for multinomial values like 1, 2 and 3,\n \
8919: build V1=0 V2=0 for the reference value (1),\n \
8920: V1=1 V2=0 for (2) \n \
1.223 brouard 8921: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.238 brouard 8922: output of IMaCh is often meaningless.\n \
1.223 brouard 8923: Exiting.\n",lval,linei, i,line,j);
1.238 brouard 8924: fprintf(ficlog,"Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.223 brouard 8925: Should be a value of %d(nth) covariate (0 should be the value for the reference and 1\n \
8926: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.238 brouard 8927: For example, for multinomial values like 1, 2 and 3,\n \
8928: build V1=0 V2=0 for the reference value (1),\n \
8929: V1=1 V2=0 for (2) \n \
1.223 brouard 8930: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.238 brouard 8931: output of IMaCh is often meaningless.\n \
1.223 brouard 8932: Exiting.\n",lval,linei, i,line,j);fflush(ficlog);
1.238 brouard 8933: return 1;
8934: }
8935: cotvar[j][iv][i]=(double)(lval);
8936: strcpy(line,stra);
1.223 brouard 8937: }/* end loop ntv */
1.225 brouard 8938:
1.223 brouard 8939: /* Statuses at wave */
1.137 brouard 8940: cutv(stra, strb, line, ' ');
1.223 brouard 8941: if(strb[0]=='.') { /* Missing value */
1.238 brouard 8942: lval=-1;
1.136 brouard 8943: }else{
1.238 brouard 8944: errno=0;
8945: lval=strtol(strb,&endptr,10);
8946: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN))*/
8947: if( strb[0]=='\0' || (*endptr != '\0')){
8948: 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);
8949: 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);
8950: return 1;
8951: }
1.136 brouard 8952: }
1.225 brouard 8953:
1.136 brouard 8954: s[j][i]=lval;
1.225 brouard 8955:
1.223 brouard 8956: /* Date of Interview */
1.136 brouard 8957: strcpy(line,stra);
8958: cutv(stra, strb,line,' ');
1.169 brouard 8959: if( (iout=sscanf(strb,"%d/%d",&month, &year)) != 0){
1.136 brouard 8960: }
1.169 brouard 8961: else if( (iout=sscanf(strb,"%s.",dummy)) != 0){
1.225 brouard 8962: month=99;
8963: year=9999;
1.136 brouard 8964: }else{
1.225 brouard 8965: 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);
8966: 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);
8967: return 1;
1.136 brouard 8968: }
8969: anint[j][i]= (double) year;
8970: mint[j][i]= (double)month;
8971: strcpy(line,stra);
1.223 brouard 8972: } /* End loop on waves */
1.225 brouard 8973:
1.223 brouard 8974: /* Date of death */
1.136 brouard 8975: cutv(stra, strb,line,' ');
1.169 brouard 8976: if( (iout=sscanf(strb,"%d/%d",&month, &year)) != 0){
1.136 brouard 8977: }
1.169 brouard 8978: else if( (iout=sscanf(strb,"%s.",dummy)) != 0){
1.136 brouard 8979: month=99;
8980: year=9999;
8981: }else{
1.141 brouard 8982: 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 8983: 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);
8984: return 1;
1.136 brouard 8985: }
8986: andc[i]=(double) year;
8987: moisdc[i]=(double) month;
8988: strcpy(line,stra);
8989:
1.223 brouard 8990: /* Date of birth */
1.136 brouard 8991: cutv(stra, strb,line,' ');
1.169 brouard 8992: if( (iout=sscanf(strb,"%d/%d",&month, &year)) != 0){
1.136 brouard 8993: }
1.169 brouard 8994: else if( (iout=sscanf(strb,"%s.", dummy)) != 0){
1.136 brouard 8995: month=99;
8996: year=9999;
8997: }else{
1.141 brouard 8998: 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);
8999: 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 9000: return 1;
1.136 brouard 9001: }
9002: if (year==9999) {
1.141 brouard 9003: 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);
9004: 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 9005: return 1;
9006:
1.136 brouard 9007: }
9008: annais[i]=(double)(year);
9009: moisnais[i]=(double)(month);
9010: strcpy(line,stra);
1.225 brouard 9011:
1.223 brouard 9012: /* Sample weight */
1.136 brouard 9013: cutv(stra, strb,line,' ');
9014: errno=0;
9015: dval=strtod(strb,&endptr);
9016: if( strb[0]=='\0' || (*endptr != '\0')){
1.141 brouard 9017: printf("Error reading data around '%f' at line number %d, \"%s\" for individual %d\nShould be a weight. Exiting.\n",dval, i,line,linei);
9018: 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 9019: fflush(ficlog);
9020: return 1;
9021: }
9022: weight[i]=dval;
9023: strcpy(line,stra);
1.225 brouard 9024:
1.223 brouard 9025: for (iv=nqv;iv>=1;iv--){ /* Loop on fixed quantitative variables */
9026: cutv(stra, strb, line, ' ');
9027: if(strb[0]=='.') { /* Missing value */
1.225 brouard 9028: lval=-1;
1.223 brouard 9029: }else{
1.225 brouard 9030: errno=0;
9031: /* what_kind_of_number(strb); */
9032: dval=strtod(strb,&endptr);
9033: /* if(strb != endptr && *endptr == '\0') */
9034: /* dval=dlval; */
9035: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN)) */
9036: if( strb[0]=='\0' || (*endptr != '\0')){
9037: 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);
9038: 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);
9039: return 1;
9040: }
9041: coqvar[iv][i]=dval;
1.226 brouard 9042: covar[ncovcol+iv][i]=dval; /* including qvar in standard covar for performance reasons */
1.223 brouard 9043: }
9044: strcpy(line,stra);
9045: }/* end loop nqv */
1.136 brouard 9046:
1.223 brouard 9047: /* Covariate values */
1.136 brouard 9048: for (j=ncovcol;j>=1;j--){
9049: cutv(stra, strb,line,' ');
1.223 brouard 9050: if(strb[0]=='.') { /* Missing covariate value */
1.225 brouard 9051: lval=-1;
1.136 brouard 9052: }else{
1.225 brouard 9053: errno=0;
9054: lval=strtol(strb,&endptr,10);
9055: if( strb[0]=='\0' || (*endptr != '\0')){
9056: 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);
9057: 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);
9058: return 1;
9059: }
1.136 brouard 9060: }
9061: if(lval <-1 || lval >1){
1.225 brouard 9062: printf("Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.136 brouard 9063: Should be a value of %d(nth) covariate (0 should be the value for the reference and 1\n \
9064: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.225 brouard 9065: For example, for multinomial values like 1, 2 and 3,\n \
9066: build V1=0 V2=0 for the reference value (1),\n \
9067: V1=1 V2=0 for (2) \n \
1.136 brouard 9068: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.225 brouard 9069: output of IMaCh is often meaningless.\n \
1.136 brouard 9070: Exiting.\n",lval,linei, i,line,j);
1.225 brouard 9071: fprintf(ficlog,"Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.136 brouard 9072: Should be a value of %d(nth) covariate (0 should be the value for the reference and 1\n \
9073: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.225 brouard 9074: For example, for multinomial values like 1, 2 and 3,\n \
9075: build V1=0 V2=0 for the reference value (1),\n \
9076: V1=1 V2=0 for (2) \n \
1.136 brouard 9077: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.225 brouard 9078: output of IMaCh is often meaningless.\n \
1.136 brouard 9079: Exiting.\n",lval,linei, i,line,j);fflush(ficlog);
1.225 brouard 9080: return 1;
1.136 brouard 9081: }
9082: covar[j][i]=(double)(lval);
9083: strcpy(line,stra);
9084: }
9085: lstra=strlen(stra);
1.225 brouard 9086:
1.136 brouard 9087: if(lstra > 9){ /* More than 2**32 or max of what printf can write with %ld */
9088: stratrunc = &(stra[lstra-9]);
9089: num[i]=atol(stratrunc);
9090: }
9091: else
9092: num[i]=atol(stra);
9093: /*if((s[2][i]==2) && (s[3][i]==-1)&&(s[4][i]==9)){
9094: 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;}*/
9095:
9096: i=i+1;
9097: } /* End loop reading data */
1.225 brouard 9098:
1.136 brouard 9099: *imax=i-1; /* Number of individuals */
9100: fclose(fic);
1.225 brouard 9101:
1.136 brouard 9102: return (0);
1.164 brouard 9103: /* endread: */
1.225 brouard 9104: printf("Exiting readdata: ");
9105: fclose(fic);
9106: return (1);
1.223 brouard 9107: }
1.126 brouard 9108:
1.234 brouard 9109: void removefirstspace(char **stri){/*, char stro[]) {*/
1.230 brouard 9110: char *p1 = *stri, *p2 = *stri;
1.235 brouard 9111: while (*p2 == ' ')
1.234 brouard 9112: p2++;
9113: /* while ((*p1++ = *p2++) !=0) */
9114: /* ; */
9115: /* do */
9116: /* while (*p2 == ' ') */
9117: /* p2++; */
9118: /* while (*p1++ == *p2++); */
9119: *stri=p2;
1.145 brouard 9120: }
9121:
1.235 brouard 9122: int decoderesult ( char resultline[], int nres)
1.230 brouard 9123: /**< This routine decode one result line and returns the combination # of dummy covariates only **/
9124: {
1.235 brouard 9125: int j=0, k=0, k1=0, k2=0, k3=0, k4=0, match=0, k2q=0, k3q=0, k4q=0;
1.230 brouard 9126: char resultsav[MAXLINE];
1.234 brouard 9127: int resultmodel[MAXLINE];
9128: int modelresult[MAXLINE];
1.230 brouard 9129: char stra[80], strb[80], strc[80], strd[80],stre[80];
9130:
1.234 brouard 9131: removefirstspace(&resultline);
1.233 brouard 9132: printf("decoderesult:%s\n",resultline);
1.230 brouard 9133:
9134: if (strstr(resultline,"v") !=0){
9135: printf("Error. 'v' must be in upper case 'V' result: %s ",resultline);
9136: fprintf(ficlog,"Error. 'v' must be in upper case result: %s ",resultline);fflush(ficlog);
9137: return 1;
9138: }
9139: trimbb(resultsav, resultline);
9140: if (strlen(resultsav) >1){
9141: j=nbocc(resultsav,'='); /**< j=Number of covariate values'=' */
9142: }
1.253 brouard 9143: if(j == 0){ /* Resultline but no = */
9144: TKresult[nres]=0; /* Combination for the nresult and the model */
9145: return (0);
9146: }
9147:
1.234 brouard 9148: if( j != cptcovs ){ /* Be careful if a variable is in a product but not single */
9149: 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);
9150: 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);
9151: }
9152: for(k=1; k<=j;k++){ /* Loop on any covariate of the result line */
9153: if(nbocc(resultsav,'=') >1){
9154: cutl(stra,strb,resultsav,' '); /* keeps in strb after the first ' '
9155: resultsav= V4=1 V5=25.1 V3=0 strb=V3=0 stra= V4=1 V5=25.1 */
9156: cutl(strc,strd,strb,'='); /* strb:V4=1 strc=1 strd=V4 */
9157: }else
9158: cutl(strc,strd,resultsav,'=');
1.230 brouard 9159: Tvalsel[k]=atof(strc); /* 1 */
1.234 brouard 9160:
1.230 brouard 9161: cutl(strc,stre,strd,'V'); /* strd='V4' strc=4 stre='V' */;
9162: Tvarsel[k]=atoi(strc);
9163: /* Typevarsel[k]=1; /\* 1 for age product *\/ */
9164: /* cptcovsel++; */
9165: if (nbocc(stra,'=') >0)
9166: strcpy(resultsav,stra); /* and analyzes it */
9167: }
1.235 brouard 9168: /* Checking for missing or useless values in comparison of current model needs */
1.236 brouard 9169: for(k1=1; k1<= cptcovt ;k1++){ /* model line V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
9170: if(Typevar[k1]==0){ /* Single covariate in model */
1.234 brouard 9171: match=0;
1.236 brouard 9172: for(k2=1; k2 <=j;k2++){/* result line V4=1 V5=24.1 V3=1 V2=8 V1=0 */
1.237 brouard 9173: if(Tvar[k1]==Tvarsel[k2]) {/* Tvar[1]=5 == Tvarsel[2]=5 */
1.236 brouard 9174: modelresult[k2]=k1;/* modelresult[2]=1 modelresult[1]=2 modelresult[3]=3 modelresult[6]=4 modelresult[9]=5 */
1.234 brouard 9175: match=1;
9176: break;
9177: }
9178: }
9179: if(match == 0){
9180: printf("Error in result line: %d value missing; result: %s, model=%s\n",k1, resultline, model);
9181: }
9182: }
9183: }
1.235 brouard 9184: /* Checking for missing or useless values in comparison of current model needs */
9185: for(k2=1; k2 <=j;k2++){ /* result line V4=1 V5=24.1 V3=1 V2=8 V1=0 */
1.234 brouard 9186: match=0;
1.235 brouard 9187: for(k1=1; k1<= cptcovt ;k1++){ /* model line V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
9188: if(Typevar[k1]==0){ /* Single */
1.237 brouard 9189: if(Tvar[k1]==Tvarsel[k2]) { /* Tvar[2]=4 == Tvarsel[1]=4 */
1.235 brouard 9190: resultmodel[k1]=k2; /* resultmodel[2]=1 resultmodel[1]=2 resultmodel[3]=3 resultmodel[6]=4 resultmodel[9]=5 */
1.234 brouard 9191: ++match;
9192: }
9193: }
9194: }
9195: if(match == 0){
9196: printf("Error in result line: %d value missing; result: %s, model=%s\n",k1, resultline, model);
9197: }else if(match > 1){
9198: printf("Error in result line: %d doubled; result: %s, model=%s\n",k2, resultline, model);
9199: }
9200: }
1.235 brouard 9201:
1.234 brouard 9202: /* We need to deduce which combination number is chosen and save quantitative values */
1.235 brouard 9203: /* model line V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
9204: /* result line V4=1 V5=25.1 V3=0 V2=8 V1=1 */
9205: /* should give a combination of dummy V4=1, V3=0, V1=1 => V4*2**(0) + V3*2**(1) + V1*2**(2) = 5 + (1offset) = 6*/
9206: /* result line V4=1 V5=24.1 V3=1 V2=8 V1=0 */
9207: /* should give a combination of dummy V4=1, V3=1, V1=0 => V4*2**(0) + V3*2**(1) + V1*2**(2) = 3 + (1offset) = 4*/
9208: /* 1 0 0 0 */
9209: /* 2 1 0 0 */
9210: /* 3 0 1 0 */
9211: /* 4 1 1 0 */ /* V4=1, V3=1, V1=0 */
9212: /* 5 0 0 1 */
9213: /* 6 1 0 1 */ /* V4=1, V3=0, V1=1 */
9214: /* 7 0 1 1 */
9215: /* 8 1 1 1 */
1.237 brouard 9216: /* V(Tvresult)=Tresult V4=1 V3=0 V1=1 Tresult[nres=1][2]=0 */
9217: /* V(Tvqresult)=Tqresult V5=25.1 V2=8 Tqresult[nres=1][1]=25.1 */
9218: /* V5*age V5 known which value for nres? */
9219: /* Tqinvresult[2]=8 Tqinvresult[1]=25.1 */
1.235 brouard 9220: for(k1=1, k=0, k4=0, k4q=0; k1 <=cptcovt;k1++){ /* model line */
9221: if( Dummy[k1]==0 && Typevar[k1]==0 ){ /* Single dummy */
1.237 brouard 9222: k3= resultmodel[k1]; /* resultmodel[2(V4)] = 1=k3 */
1.235 brouard 9223: k2=(int)Tvarsel[k3]; /* Tvarsel[resultmodel[2]]= Tvarsel[1] = 4=k2 */
9224: k+=Tvalsel[k3]*pow(2,k4); /* Tvalsel[1]=1 */
1.237 brouard 9225: Tresult[nres][k4+1]=Tvalsel[k3];/* Tresult[nres][1]=1(V4=1) Tresult[nres][2]=0(V3=0) */
9226: Tvresult[nres][k4+1]=(int)Tvarsel[k3];/* Tvresult[nres][1]=4 Tvresult[nres][3]=1 */
9227: Tinvresult[nres][(int)Tvarsel[k3]]=Tvalsel[k3]; /* Tinvresult[nres][4]=1 */
1.235 brouard 9228: printf("Decoderesult Dummy k=%d, V(k2=V%d)= Tvalsel[%d]=%d, 2**(%d)\n",k, k2, k3, (int)Tvalsel[k3], k4);
9229: k4++;;
9230: } else if( Dummy[k1]==1 && Typevar[k1]==0 ){ /* Single quantitative */
9231: k3q= resultmodel[k1]; /* resultmodel[2] = 1=k3 */
9232: k2q=(int)Tvarsel[k3q]; /* Tvarsel[resultmodel[2]]= Tvarsel[1] = 4=k2 */
1.237 brouard 9233: Tqresult[nres][k4q+1]=Tvalsel[k3q]; /* Tqresult[nres][1]=25.1 */
9234: Tvqresult[nres][k4q+1]=(int)Tvarsel[k3q]; /* Tvqresult[nres][1]=5 */
9235: Tqinvresult[nres][(int)Tvarsel[k3q]]=Tvalsel[k3q]; /* Tqinvresult[nres][5]=25.1 */
1.235 brouard 9236: printf("Decoderesult Quantitative nres=%d, V(k2q=V%d)= Tvalsel[%d]=%d, Tvarsel[%d]=%f\n",nres, k2q, k3q, Tvarsel[k3q], k3q, Tvalsel[k3q]);
9237: k4q++;;
9238: }
9239: }
1.234 brouard 9240:
1.235 brouard 9241: TKresult[nres]=++k; /* Combination for the nresult and the model */
1.230 brouard 9242: return (0);
9243: }
1.235 brouard 9244:
1.230 brouard 9245: int decodemodel( char model[], int lastobs)
9246: /**< This routine decodes the model and returns:
1.224 brouard 9247: * Model V1+V2+V3+V8+V7*V8+V5*V6+V8*age+V3*age+age*age
9248: * - nagesqr = 1 if age*age in the model, otherwise 0.
9249: * - cptcovt total number of covariates of the model nbocc(+)+1 = 8 excepting constant and age and age*age
9250: * - cptcovn or number of covariates k of the models excluding age*products =6 and age*age
9251: * - cptcovage number of covariates with age*products =2
9252: * - cptcovs number of simple covariates
9253: * - 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
9254: * which is a new column after the 9 (ncovcol) variables.
9255: * - if k is a product Vn*Vm covar[k][i] is filled with correct values for each individual
9256: * - Tprod[l] gives the kth covariates of the product Vn*Vm l=1 to cptcovprod-cptcovage
9257: * Tprod[1]@2 {5, 6}: position of first product V7*V8 is 5, and second V5*V6 is 6.
9258: * - Tvard[k] p Tvard[1][1]@4 {7, 8, 5, 6} for V7*V8 and V5*V6 .
9259: */
1.136 brouard 9260: {
1.238 brouard 9261: int i, j, k, ks, v;
1.227 brouard 9262: int j1, k1, k2, k3, k4;
1.136 brouard 9263: char modelsav[80];
1.145 brouard 9264: char stra[80], strb[80], strc[80], strd[80],stre[80];
1.187 brouard 9265: char *strpt;
1.136 brouard 9266:
1.145 brouard 9267: /*removespace(model);*/
1.136 brouard 9268: if (strlen(model) >1){ /* If there is at least 1 covariate */
1.145 brouard 9269: j=0, j1=0, k1=0, k2=-1, ks=0, cptcovn=0;
1.137 brouard 9270: if (strstr(model,"AGE") !=0){
1.192 brouard 9271: printf("Error. AGE must be in lower case 'age' model=1+age+%s. ",model);
9272: fprintf(ficlog,"Error. AGE must be in lower case model=1+age+%s. ",model);fflush(ficlog);
1.136 brouard 9273: return 1;
9274: }
1.141 brouard 9275: if (strstr(model,"v") !=0){
9276: printf("Error. 'v' must be in upper case 'V' model=%s ",model);
9277: fprintf(ficlog,"Error. 'v' must be in upper case model=%s ",model);fflush(ficlog);
9278: return 1;
9279: }
1.187 brouard 9280: strcpy(modelsav,model);
9281: if ((strpt=strstr(model,"age*age")) !=0){
9282: printf(" strpt=%s, model=%s\n",strpt, model);
9283: if(strpt != model){
1.234 brouard 9284: printf("Error in model: 'model=%s'; 'age*age' should in first place before other covariates\n \
1.192 brouard 9285: 'model=1+age+age*age+V1.' or 'model=1+age+age*age+V1+V1*age.', please swap as well as \n \
1.187 brouard 9286: corresponding column of parameters.\n",model);
1.234 brouard 9287: fprintf(ficlog,"Error in model: 'model=%s'; 'age*age' should in first place before other covariates\n \
1.192 brouard 9288: 'model=1+age+age*age+V1.' or 'model=1+age+age*age+V1+V1*age.', please swap as well as \n \
1.187 brouard 9289: corresponding column of parameters.\n",model); fflush(ficlog);
1.234 brouard 9290: return 1;
1.225 brouard 9291: }
1.187 brouard 9292: nagesqr=1;
9293: if (strstr(model,"+age*age") !=0)
1.234 brouard 9294: substrchaine(modelsav, model, "+age*age");
1.187 brouard 9295: else if (strstr(model,"age*age+") !=0)
1.234 brouard 9296: substrchaine(modelsav, model, "age*age+");
1.187 brouard 9297: else
1.234 brouard 9298: substrchaine(modelsav, model, "age*age");
1.187 brouard 9299: }else
9300: nagesqr=0;
9301: if (strlen(modelsav) >1){
9302: j=nbocc(modelsav,'+'); /**< j=Number of '+' */
9303: j1=nbocc(modelsav,'*'); /**< j1=Number of '*' */
1.224 brouard 9304: cptcovs=j+1-j1; /**< Number of simple covariates V1+V1*age+V3 +V3*V4+age*age=> V1 + V3 =5-3=2 */
1.187 brouard 9305: cptcovt= j+1; /* Number of total covariates in the model, not including
1.225 brouard 9306: * cst, age and age*age
9307: * V1+V1*age+ V3 + V3*V4+age*age=> 3+1=4*/
9308: /* including age products which are counted in cptcovage.
9309: * but the covariates which are products must be treated
9310: * separately: ncovn=4- 2=2 (V1+V3). */
1.187 brouard 9311: cptcovprod=j1; /**< Number of products V1*V2 +v3*age = 2 */
9312: cptcovprodnoage=0; /**< Number of covariate products without age: V3*V4 =1 */
1.225 brouard 9313:
9314:
1.187 brouard 9315: /* Design
9316: * V1 V2 V3 V4 V5 V6 V7 V8 V9 Weight
9317: * < ncovcol=8 >
9318: * Model V2 + V1 + V3*age + V3 + V5*V6 + V7*V8 + V8*age + V8
9319: * k= 1 2 3 4 5 6 7 8
9320: * cptcovn number of covariates (not including constant and age ) = # of + plus 1 = 7+1=8
9321: * covar[k,i], value of kth covariate if not including age for individual i:
1.224 brouard 9322: * covar[1][i]= (V1), covar[4][i]=(V4), covar[8][i]=(V8)
9323: * Tvar[k] # of the kth covariate: Tvar[1]=2 Tvar[2]=1 Tvar[4]=3 Tvar[8]=8
1.187 brouard 9324: * if multiplied by age: V3*age Tvar[3=V3*age]=3 (V3) Tvar[7]=8 and
9325: * Tage[++cptcovage]=k
9326: * if products, new covar are created after ncovcol with k1
9327: * Tvar[k]=ncovcol+k1; # of the kth covariate product: Tvar[5]=ncovcol+1=10 Tvar[6]=ncovcol+1=11
9328: * Tprod[k1]=k; Tprod[1]=5 Tprod[2]= 6; gives the position of the k1th product
9329: * 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
9330: * Tvar[cptcovn+k2]=Tvard[k1][1];Tvar[cptcovn+k2+1]=Tvard[k1][2];
9331: * Tvar[8+1]=5;Tvar[8+2]=6;Tvar[8+3]=7;Tvar[8+4]=8 inverted
9332: * V1 V2 V3 V4 V5 V6 V7 V8 V9 V10 V11
9333: * < ncovcol=8 >
9334: * Model V2 + V1 + V3*age + V3 + V5*V6 + V7*V8 + V8*age + V8 d1 d1 d2 d2
9335: * k= 1 2 3 4 5 6 7 8 9 10 11 12
9336: * Tvar[k]= 2 1 3 3 10 11 8 8 5 6 7 8
9337: * p Tvar[1]@12={2, 1, 3, 3, 11, 10, 8, 8, 7, 8, 5, 6}
9338: * p Tprod[1]@2={ 6, 5}
9339: *p Tvard[1][1]@4= {7, 8, 5, 6}
9340: * covar[k][i]= V2 V1 ? V3 V5*V6? V7*V8? ? V8
9341: * cov[Tage[kk]+2]=covar[Tvar[Tage[kk]]][i]*cov[2];
9342: *How to reorganize?
9343: * Model V1 + V2 + V3 + V8 + V5*V6 + V7*V8 + V3*age + V8*age
9344: * Tvars {2, 1, 3, 3, 11, 10, 8, 8, 7, 8, 5, 6}
9345: * {2, 1, 4, 8, 5, 6, 3, 7}
9346: * Struct []
9347: */
1.225 brouard 9348:
1.187 brouard 9349: /* This loop fills the array Tvar from the string 'model'.*/
9350: /* j is the number of + signs in the model V1+V2+V3 j=2 i=3 to 1 */
9351: /* modelsav=V2+V1+V4+age*V3 strb=age*V3 stra=V2+V1+V4 */
9352: /* k=4 (age*V3) Tvar[k=4]= 3 (from V3) Tage[cptcovage=1]=4 */
9353: /* k=3 V4 Tvar[k=3]= 4 (from V4) */
9354: /* k=2 V1 Tvar[k=2]= 1 (from V1) */
9355: /* k=1 Tvar[1]=2 (from V2) */
9356: /* k=5 Tvar[5] */
9357: /* for (k=1; k<=cptcovn;k++) { */
1.198 brouard 9358: /* cov[2+k]=nbcode[Tvar[k]][codtabm(ij,Tvar[k])]; */
1.187 brouard 9359: /* } */
1.198 brouard 9360: /* for (k=1; k<=cptcovage;k++) cov[2+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,Tvar[Tage[k])]]*cov[2]; */
1.187 brouard 9361: /*
9362: * Treating invertedly V2+V1+V3*age+V2*V4 is as if written V2*V4 +V3*age + V1 + V2 */
1.227 brouard 9363: for(k=cptcovt; k>=1;k--){ /**< Number of covariates not including constant and age, neither age*age*/
9364: Tvar[k]=0; Tprod[k]=0; Tposprod[k]=0;
9365: }
1.187 brouard 9366: cptcovage=0;
9367: for(k=1; k<=cptcovt;k++){ /* Loop on total covariates of the model */
1.234 brouard 9368: cutl(stra,strb,modelsav,'+'); /* keeps in strb after the first '+'
1.225 brouard 9369: modelsav==V2+V1+V4+V3*age strb=V3*age stra=V2+V1+V4 */
1.234 brouard 9370: if (nbocc(modelsav,'+')==0) strcpy(strb,modelsav); /* and analyzes it */
9371: /* printf("i=%d a=%s b=%s sav=%s\n",i, stra,strb,modelsav);*/
9372: /*scanf("%d",i);*/
9373: if (strchr(strb,'*')) { /**< Model includes a product V2+V1+V4+V3*age strb=V3*age */
9374: cutl(strc,strd,strb,'*'); /**< strd*strc Vm*Vn: strb=V3*age(input) strc=age strd=V3 ; V3*V2 strc=V2, strd=V3 */
9375: if (strcmp(strc,"age")==0) { /**< Model includes age: Vn*age */
9376: /* covar is not filled and then is empty */
9377: cptcovprod--;
9378: cutl(stre,strb,strd,'V'); /* strd=V3(input): stre="3" */
9379: Tvar[k]=atoi(stre); /* V2+V1+V4+V3*age Tvar[4]=3 ; V1+V2*age Tvar[2]=2; V1+V1*age Tvar[2]=1 */
9380: Typevar[k]=1; /* 1 for age product */
9381: cptcovage++; /* Sums the number of covariates which include age as a product */
9382: Tage[cptcovage]=k; /* Tvar[4]=3, Tage[1] = 4 or V1+V1*age Tvar[2]=1, Tage[1]=2 */
9383: /*printf("stre=%s ", stre);*/
9384: } else if (strcmp(strd,"age")==0) { /* or age*Vn */
9385: cptcovprod--;
9386: cutl(stre,strb,strc,'V');
9387: Tvar[k]=atoi(stre);
9388: Typevar[k]=1; /* 1 for age product */
9389: cptcovage++;
9390: Tage[cptcovage]=k;
9391: } else { /* Age is not in the model product V2+V1+V1*V4+V3*age+V3*V2 strb=V3*V2*/
9392: /* loops on k1=1 (V3*V2) and k1=2 V4*V3 */
9393: cptcovn++;
9394: cptcovprodnoage++;k1++;
9395: cutl(stre,strb,strc,'V'); /* strc= Vn, stre is n; strb=V3*V2 stre=3 strc=*/
9396: Tvar[k]=ncovcol+nqv+ntv+nqtv+k1; /* For model-covariate k tells which data-covariate to use but
9397: because this model-covariate is a construction we invent a new column
9398: which is after existing variables ncovcol+nqv+ntv+nqtv + k1
9399: If already ncovcol=4 and model=V2+V1+V1*V4+age*V3+V3*V2
9400: Tvar[3=V1*V4]=4+1 Tvar[5=V3*V2]=4 + 2= 6, etc */
9401: Typevar[k]=2; /* 2 for double fixed dummy covariates */
9402: cutl(strc,strb,strd,'V'); /* strd was Vm, strc is m */
9403: Tprod[k1]=k; /* Tprod[1]=3(=V1*V4) for V2+V1+V1*V4+age*V3+V3*V2 */
9404: Tposprod[k]=k1; /* Tpsprod[3]=1, Tposprod[2]=5 */
9405: Tvard[k1][1] =atoi(strc); /* m 1 for V1*/
9406: Tvard[k1][2] =atoi(stre); /* n 4 for V4*/
9407: k2=k2+2; /* k2 is initialize to -1, We want to store the n and m in Vn*Vm at the end of Tvar */
9408: /* Tvar[cptcovt+k2]=Tvard[k1][1]; /\* Tvar[(cptcovt=4+k2=1)=5]= 1 (V1) *\/ */
9409: /* Tvar[cptcovt+k2+1]=Tvard[k1][2]; /\* Tvar[(cptcovt=4+(k2=1)+1)=6]= 4 (V4) *\/ */
1.225 brouard 9410: /*ncovcol=4 and model=V2+V1+V1*V4+age*V3+V3*V2, Tvar[3]=5, Tvar[4]=6, cptcovt=5 */
1.234 brouard 9411: /* 1 2 3 4 5 | Tvar[5+1)=1, Tvar[7]=2 */
9412: for (i=1; i<=lastobs;i++){
9413: /* Computes the new covariate which is a product of
9414: covar[n][i]* covar[m][i] and stores it at ncovol+k1 May not be defined */
9415: covar[ncovcol+k1][i]=covar[atoi(stre)][i]*covar[atoi(strc)][i];
9416: }
9417: } /* End age is not in the model */
9418: } /* End if model includes a product */
9419: else { /* no more sum */
9420: /*printf("d=%s c=%s b=%s\n", strd,strc,strb);*/
9421: /* scanf("%d",i);*/
9422: cutl(strd,strc,strb,'V');
9423: ks++; /**< Number of simple covariates dummy or quantitative, fixe or varying */
9424: cptcovn++; /** V4+V3+V5: V4 and V3 timevarying dummy covariates, V5 timevarying quantitative */
9425: Tvar[k]=atoi(strd);
9426: Typevar[k]=0; /* 0 for simple covariates */
9427: }
9428: strcpy(modelsav,stra); /* modelsav=V2+V1+V4 stra=V2+V1+V4 */
1.223 brouard 9429: /*printf("a=%s b=%s sav=%s\n", stra,strb,modelsav);
1.225 brouard 9430: scanf("%d",i);*/
1.187 brouard 9431: } /* end of loop + on total covariates */
9432: } /* end if strlen(modelsave == 0) age*age might exist */
9433: } /* end if strlen(model == 0) */
1.136 brouard 9434:
9435: /*The number n of Vn is stored in Tvar. cptcovage =number of age covariate. Tage gives the position of age. cptcovprod= number of products.
9436: If model=V1+V1*age then Tvar[1]=1 Tvar[2]=1 cptcovage=1 Tage[1]=2 cptcovprod=0*/
1.225 brouard 9437:
1.136 brouard 9438: /* printf("tvar1=%d tvar2=%d tvar3=%d cptcovage=%d Tage=%d",Tvar[1],Tvar[2],Tvar[3],cptcovage,Tage[1]);
1.225 brouard 9439: printf("cptcovprod=%d ", cptcovprod);
9440: fprintf(ficlog,"cptcovprod=%d ", cptcovprod);
9441: scanf("%d ",i);*/
9442:
9443:
1.230 brouard 9444: /* Until here, decodemodel knows only the grammar (simple, product, age*) of the model but not what kind
9445: of variable (dummy vs quantitative, fixed vs time varying) is behind. But we know the # of each. */
1.226 brouard 9446: /* ncovcol= 1, nqv=1 | ntv=2, nqtv= 1 = 5 possible variables data: 2 fixed 3, varying
9447: model= V5 + V4 +V3 + V4*V3 + V5*age + V2 + V1*V2 + V1*age + V5*age, V1 is not used saving its place
9448: k = 1 2 3 4 5 6 7 8 9
9449: Tvar[k]= 5 4 3 1+1+2+1+1=6 5 2 7 1 5
9450: Typevar[k]= 0 0 0 2 1 0 2 1 1
1.227 brouard 9451: Fixed[k] 1 1 1 1 3 0 0 or 2 2 3
9452: Dummy[k] 1 0 0 0 3 1 1 2 3
9453: Tmodelind[combination of covar]=k;
1.225 brouard 9454: */
9455: /* Dispatching between quantitative and time varying covariates */
1.226 brouard 9456: /* If Tvar[k] >ncovcol it is a product */
1.225 brouard 9457: /* 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 9458: /* Computing effective variables, ie used by the model, that is from the cptcovt variables */
1.227 brouard 9459: printf("Model=%s\n\
9460: Typevar: 0 for simple covariate (dummy, quantitative, fixed or varying), 1 for age product, 2 for product \n\
9461: Fixed[k] 0=fixed (product or simple), 1 varying, 2 fixed with age product, 3 varying with age product \n\
9462: 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);
9463: fprintf(ficlog,"Model=%s\n\
9464: Typevar: 0 for simple covariate (dummy, quantitative, fixed or varying), 1 for age product, 2 for product \n\
9465: Fixed[k] 0=fixed (product or simple), 1 varying, 2 fixed with age product, 3 varying with age product \n\
9466: 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 9467: for(k=1;k<=cptcovt; k++){ Fixed[k]=0; Dummy[k]=0;}
1.234 brouard 9468: 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 */
9469: if (Tvar[k] <=ncovcol && Typevar[k]==0 ){ /* Simple fixed dummy (<=ncovcol) covariates */
1.227 brouard 9470: Fixed[k]= 0;
9471: Dummy[k]= 0;
1.225 brouard 9472: ncoveff++;
1.232 brouard 9473: ncovf++;
1.234 brouard 9474: nsd++;
9475: modell[k].maintype= FTYPE;
9476: TvarsD[nsd]=Tvar[k];
9477: TvarsDind[nsd]=k;
9478: TvarF[ncovf]=Tvar[k];
9479: TvarFind[ncovf]=k;
9480: TvarFD[ncoveff]=Tvar[k]; /* TvarFD[1]=V1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
9481: TvarFDind[ncoveff]=k; /* TvarFDind[1]=9 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
9482: }else if( Tvar[k] <=ncovcol && Typevar[k]==2){ /* Product of fixed dummy (<=ncovcol) covariates */
9483: Fixed[k]= 0;
9484: Dummy[k]= 0;
9485: ncoveff++;
9486: ncovf++;
9487: modell[k].maintype= FTYPE;
9488: TvarF[ncovf]=Tvar[k];
9489: TvarFind[ncovf]=k;
1.230 brouard 9490: TvarFD[ncoveff]=Tvar[k]; /* TvarFD[1]=V1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1.231 brouard 9491: TvarFDind[ncoveff]=k; /* TvarFDind[1]=9 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1.240 brouard 9492: }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 9493: Fixed[k]= 0;
9494: Dummy[k]= 1;
1.230 brouard 9495: nqfveff++;
1.234 brouard 9496: modell[k].maintype= FTYPE;
9497: modell[k].subtype= FQ;
9498: nsq++;
9499: TvarsQ[nsq]=Tvar[k];
9500: TvarsQind[nsq]=k;
1.232 brouard 9501: ncovf++;
1.234 brouard 9502: TvarF[ncovf]=Tvar[k];
9503: TvarFind[ncovf]=k;
1.231 brouard 9504: 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 9505: 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 9506: }else if( Tvar[k] <=ncovcol+nqv+ntv && Typevar[k]==0){/* Only simple time varying dummy variables */
1.227 brouard 9507: Fixed[k]= 1;
9508: Dummy[k]= 0;
1.225 brouard 9509: ntveff++; /* Only simple time varying dummy variable */
1.234 brouard 9510: modell[k].maintype= VTYPE;
9511: modell[k].subtype= VD;
9512: nsd++;
9513: TvarsD[nsd]=Tvar[k];
9514: TvarsDind[nsd]=k;
9515: ncovv++; /* Only simple time varying variables */
9516: TvarV[ncovv]=Tvar[k];
1.242 brouard 9517: 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 9518: 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 */
9519: 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 9520: 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);
9521: printf("Quasi TmodelInvind[%d]=%d\n",k,Tvar[k]- ncovcol-nqv);
1.231 brouard 9522: }else if( Tvar[k] <=ncovcol+nqv+ntv+nqtv && Typevar[k]==0){ /* Only simple time varying quantitative variable V5*/
1.234 brouard 9523: Fixed[k]= 1;
9524: Dummy[k]= 1;
9525: nqtveff++;
9526: modell[k].maintype= VTYPE;
9527: modell[k].subtype= VQ;
9528: ncovv++; /* Only simple time varying variables */
9529: nsq++;
9530: TvarsQ[nsq]=Tvar[k];
9531: TvarsQind[nsq]=k;
9532: TvarV[ncovv]=Tvar[k];
1.242 brouard 9533: 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 9534: 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 */
9535: 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 9536: TmodelInvQind[nqtveff]=Tvar[k]- ncovcol-nqv-ntv;/* Only simple time varying quantitative variable */
9537: /* Tmodeliqind[k]=nqtveff;/\* Only simple time varying quantitative variable *\/ */
9538: 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 9539: printf("Quasi TmodelInvQind[%d]=%d\n",k,Tvar[k]- ncovcol-nqv-ntv);
1.227 brouard 9540: }else if (Typevar[k] == 1) { /* product with age */
1.234 brouard 9541: ncova++;
9542: TvarA[ncova]=Tvar[k];
9543: TvarAind[ncova]=k;
1.231 brouard 9544: if (Tvar[k] <=ncovcol ){ /* Product age with fixed dummy covariatee */
1.240 brouard 9545: Fixed[k]= 2;
9546: Dummy[k]= 2;
9547: modell[k].maintype= ATYPE;
9548: modell[k].subtype= APFD;
9549: /* ncoveff++; */
1.227 brouard 9550: }else if( Tvar[k] <=ncovcol+nqv) { /* Remind that product Vn*Vm are added in k*/
1.240 brouard 9551: Fixed[k]= 2;
9552: Dummy[k]= 3;
9553: modell[k].maintype= ATYPE;
9554: modell[k].subtype= APFQ; /* Product age * fixed quantitative */
9555: /* nqfveff++; /\* Only simple fixed quantitative variable *\/ */
1.227 brouard 9556: }else if( Tvar[k] <=ncovcol+nqv+ntv ){
1.240 brouard 9557: Fixed[k]= 3;
9558: Dummy[k]= 2;
9559: modell[k].maintype= ATYPE;
9560: modell[k].subtype= APVD; /* Product age * varying dummy */
9561: /* ntveff++; /\* Only simple time varying dummy variable *\/ */
1.227 brouard 9562: }else if( Tvar[k] <=ncovcol+nqv+ntv+nqtv){
1.240 brouard 9563: Fixed[k]= 3;
9564: Dummy[k]= 3;
9565: modell[k].maintype= ATYPE;
9566: modell[k].subtype= APVQ; /* Product age * varying quantitative */
9567: /* nqtveff++;/\* Only simple time varying quantitative variable *\/ */
1.227 brouard 9568: }
9569: }else if (Typevar[k] == 2) { /* product without age */
9570: k1=Tposprod[k];
9571: if(Tvard[k1][1] <=ncovcol){
1.240 brouard 9572: if(Tvard[k1][2] <=ncovcol){
9573: Fixed[k]= 1;
9574: Dummy[k]= 0;
9575: modell[k].maintype= FTYPE;
9576: modell[k].subtype= FPDD; /* Product fixed dummy * fixed dummy */
9577: ncovf++; /* Fixed variables without age */
9578: TvarF[ncovf]=Tvar[k];
9579: TvarFind[ncovf]=k;
9580: }else if(Tvard[k1][2] <=ncovcol+nqv){
9581: Fixed[k]= 0; /* or 2 ?*/
9582: Dummy[k]= 1;
9583: modell[k].maintype= FTYPE;
9584: modell[k].subtype= FPDQ; /* Product fixed dummy * fixed quantitative */
9585: ncovf++; /* Varying variables without age */
9586: TvarF[ncovf]=Tvar[k];
9587: TvarFind[ncovf]=k;
9588: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){
9589: Fixed[k]= 1;
9590: Dummy[k]= 0;
9591: modell[k].maintype= VTYPE;
9592: modell[k].subtype= VPDD; /* Product fixed dummy * varying dummy */
9593: ncovv++; /* Varying variables without age */
9594: TvarV[ncovv]=Tvar[k];
9595: TvarVind[ncovv]=k;
9596: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){
9597: Fixed[k]= 1;
9598: Dummy[k]= 1;
9599: modell[k].maintype= VTYPE;
9600: modell[k].subtype= VPDQ; /* Product fixed dummy * varying quantitative */
9601: ncovv++; /* Varying variables without age */
9602: TvarV[ncovv]=Tvar[k];
9603: TvarVind[ncovv]=k;
9604: }
1.227 brouard 9605: }else if(Tvard[k1][1] <=ncovcol+nqv){
1.240 brouard 9606: if(Tvard[k1][2] <=ncovcol){
9607: Fixed[k]= 0; /* or 2 ?*/
9608: Dummy[k]= 1;
9609: modell[k].maintype= FTYPE;
9610: modell[k].subtype= FPDQ; /* Product fixed quantitative * fixed dummy */
9611: ncovf++; /* Fixed variables without age */
9612: TvarF[ncovf]=Tvar[k];
9613: TvarFind[ncovf]=k;
9614: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){
9615: Fixed[k]= 1;
9616: Dummy[k]= 1;
9617: modell[k].maintype= VTYPE;
9618: modell[k].subtype= VPDQ; /* Product fixed quantitative * varying dummy */
9619: ncovv++; /* Varying variables without age */
9620: TvarV[ncovv]=Tvar[k];
9621: TvarVind[ncovv]=k;
9622: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){
9623: Fixed[k]= 1;
9624: Dummy[k]= 1;
9625: modell[k].maintype= VTYPE;
9626: modell[k].subtype= VPQQ; /* Product fixed quantitative * varying quantitative */
9627: ncovv++; /* Varying variables without age */
9628: TvarV[ncovv]=Tvar[k];
9629: TvarVind[ncovv]=k;
9630: ncovv++; /* Varying variables without age */
9631: TvarV[ncovv]=Tvar[k];
9632: TvarVind[ncovv]=k;
9633: }
1.227 brouard 9634: }else if(Tvard[k1][1] <=ncovcol+nqv+ntv){
1.240 brouard 9635: if(Tvard[k1][2] <=ncovcol){
9636: Fixed[k]= 1;
9637: Dummy[k]= 1;
9638: modell[k].maintype= VTYPE;
9639: modell[k].subtype= VPDD; /* Product time varying dummy * fixed dummy */
9640: ncovv++; /* Varying variables without age */
9641: TvarV[ncovv]=Tvar[k];
9642: TvarVind[ncovv]=k;
9643: }else if(Tvard[k1][2] <=ncovcol+nqv){
9644: Fixed[k]= 1;
9645: Dummy[k]= 1;
9646: modell[k].maintype= VTYPE;
9647: modell[k].subtype= VPDQ; /* Product time varying dummy * fixed quantitative */
9648: ncovv++; /* Varying variables without age */
9649: TvarV[ncovv]=Tvar[k];
9650: TvarVind[ncovv]=k;
9651: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){
9652: Fixed[k]= 1;
9653: Dummy[k]= 0;
9654: modell[k].maintype= VTYPE;
9655: modell[k].subtype= VPDD; /* Product time varying dummy * time varying dummy */
9656: ncovv++; /* Varying variables without age */
9657: TvarV[ncovv]=Tvar[k];
9658: TvarVind[ncovv]=k;
9659: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){
9660: Fixed[k]= 1;
9661: Dummy[k]= 1;
9662: modell[k].maintype= VTYPE;
9663: modell[k].subtype= VPDQ; /* Product time varying dummy * time varying quantitative */
9664: ncovv++; /* Varying variables without age */
9665: TvarV[ncovv]=Tvar[k];
9666: TvarVind[ncovv]=k;
9667: }
1.227 brouard 9668: }else if(Tvard[k1][1] <=ncovcol+nqv+ntv+nqtv){
1.240 brouard 9669: if(Tvard[k1][2] <=ncovcol){
9670: Fixed[k]= 1;
9671: Dummy[k]= 1;
9672: modell[k].maintype= VTYPE;
9673: modell[k].subtype= VPDQ; /* Product time varying quantitative * fixed dummy */
9674: ncovv++; /* Varying variables without age */
9675: TvarV[ncovv]=Tvar[k];
9676: TvarVind[ncovv]=k;
9677: }else if(Tvard[k1][2] <=ncovcol+nqv){
9678: Fixed[k]= 1;
9679: Dummy[k]= 1;
9680: modell[k].maintype= VTYPE;
9681: modell[k].subtype= VPQQ; /* Product time varying quantitative * fixed quantitative */
9682: ncovv++; /* Varying variables without age */
9683: TvarV[ncovv]=Tvar[k];
9684: TvarVind[ncovv]=k;
9685: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){
9686: Fixed[k]= 1;
9687: Dummy[k]= 1;
9688: modell[k].maintype= VTYPE;
9689: modell[k].subtype= VPDQ; /* Product time varying quantitative * time varying dummy */
9690: ncovv++; /* Varying variables without age */
9691: TvarV[ncovv]=Tvar[k];
9692: TvarVind[ncovv]=k;
9693: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){
9694: Fixed[k]= 1;
9695: Dummy[k]= 1;
9696: modell[k].maintype= VTYPE;
9697: modell[k].subtype= VPQQ; /* Product time varying quantitative * time varying quantitative */
9698: ncovv++; /* Varying variables without age */
9699: TvarV[ncovv]=Tvar[k];
9700: TvarVind[ncovv]=k;
9701: }
1.227 brouard 9702: }else{
1.240 brouard 9703: printf("Error unknown type of covariate: Tvard[%d][1]=%d,Tvard[%d][2]=%d\n",k1,Tvard[k1][1],k1,Tvard[k1][2]);
9704: fprintf(ficlog,"Error unknown type of covariate: Tvard[%d][1]=%d,Tvard[%d][2]=%d\n",k1,Tvard[k1][1],k1,Tvard[k1][2]);
9705: } /*end k1*/
1.225 brouard 9706: }else{
1.226 brouard 9707: printf("Error, current version can't treat for performance reasons, Tvar[%d]=%d, Typevar[%d]=%d\n", k, Tvar[k], k, Typevar[k]);
9708: 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 9709: }
1.227 brouard 9710: 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 9711: printf(" modell[%d].maintype=%d, modell[%d].subtype=%d\n",k,modell[k].maintype,k,modell[k].subtype);
1.227 brouard 9712: 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]);
9713: }
9714: /* Searching for doublons in the model */
9715: for(k1=1; k1<= cptcovt;k1++){
9716: for(k2=1; k2 <k1;k2++){
9717: if((Typevar[k1]==Typevar[k2]) && (Fixed[Tvar[k1]]==Fixed[Tvar[k2]]) && (Dummy[Tvar[k1]]==Dummy[Tvar[k2]] )){
1.234 brouard 9718: if((Typevar[k1] == 0 || Typevar[k1] == 1)){ /* Simple or age product */
9719: if(Tvar[k1]==Tvar[k2]){
9720: 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]]);
9721: 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);
9722: return(1);
9723: }
9724: }else if (Typevar[k1] ==2){
9725: k3=Tposprod[k1];
9726: k4=Tposprod[k2];
9727: 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])) ){
9728: 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]]);
9729: 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);
9730: return(1);
9731: }
9732: }
1.227 brouard 9733: }
9734: }
1.225 brouard 9735: }
9736: printf("ncoveff=%d, nqfveff=%d, ntveff=%d, nqtveff=%d, cptcovn=%d\n",ncoveff,nqfveff,ntveff,nqtveff,cptcovn);
9737: fprintf(ficlog,"ncoveff=%d, nqfveff=%d, ntveff=%d, nqtveff=%d, cptcovn=%d\n",ncoveff,nqfveff,ntveff,nqtveff,cptcovn);
1.234 brouard 9738: printf("ncovf=%d, ncovv=%d, ncova=%d, nsd=%d, nsq=%d\n",ncovf,ncovv,ncova,nsd,nsq);
9739: fprintf(ficlog,"ncovf=%d, ncovv=%d, ncova=%d, nsd=%d, nsq=%d\n",ncovf,ncovv,ncova,nsd, nsq);
1.137 brouard 9740: return (0); /* with covar[new additional covariate if product] and Tage if age */
1.164 brouard 9741: /*endread:*/
1.225 brouard 9742: printf("Exiting decodemodel: ");
9743: return (1);
1.136 brouard 9744: }
9745:
1.169 brouard 9746: int calandcheckages(int imx, int maxwav, double *agemin, double *agemax, int *nberr, int *nbwarn )
1.248 brouard 9747: {/* Check ages at death */
1.136 brouard 9748: int i, m;
1.218 brouard 9749: int firstone=0;
9750:
1.136 brouard 9751: for (i=1; i<=imx; i++) {
9752: for(m=2; (m<= maxwav); m++) {
9753: if (((int)mint[m][i]== 99) && (s[m][i] <= nlstate)){
9754: anint[m][i]=9999;
1.216 brouard 9755: if (s[m][i] != -2) /* Keeping initial status of unknown vital status */
9756: s[m][i]=-1;
1.136 brouard 9757: }
9758: if((int)moisdc[i]==99 && (int)andc[i]==9999 && s[m][i]>nlstate){
1.260 brouard 9759: *nberr = *nberr + 1;
1.218 brouard 9760: if(firstone == 0){
9761: firstone=1;
1.260 brouard 9762: printf("Warning (#%d)! Date of death (month %2d and year %4d) of individual %ld on line %d was unknown but status is a death state %d at wave %d. If you don't know the vital status, please enter -2. If he/she is still alive but don't know the state, please code with '-1 or '.'. Here, we do not believe in a death, skipped.\nOther similar cases in log file\n", *nberr,(int)moisdc[i],(int)andc[i],num[i],i,s[m][i],m);
1.218 brouard 9763: }
1.262 brouard 9764: fprintf(ficlog,"Warning (#%d)! Date of death (month %2d and year %4d) of individual %ld on line %d was unknown but status is a death state %d at wave %d. If you don't know the vital status, please enter -2. If he/she is still alive but don't know the state, please code with '-1 or '.'. Here, we do not believe in a death, skipped.\n", *nberr,(int)moisdc[i],(int)andc[i],num[i],i,s[m][i],m);
1.260 brouard 9765: s[m][i]=-1; /* Droping the death status */
1.136 brouard 9766: }
9767: if((int)moisdc[i]==99 && (int)andc[i]!=9999 && s[m][i]>nlstate){
1.169 brouard 9768: (*nberr)++;
1.259 brouard 9769: printf("Error (#%d)! Month of death of individual %ld on line %d was unknown (%2d) (year of death is %4d) and status is a death state %d at wave %d. Please impute an arbitrary (or not) month and rerun. Currently this transition to death will be skipped (status is set to -2).\nOther similar cases in log file\n", *nberr, num[i],i,(int)moisdc[i],(int)andc[i],s[m][i],m);
1.262 brouard 9770: fprintf(ficlog,"Error (#%d)! Month of death of individual %ld on line %d was unknown (%2d) (year of death is %4d) and status is a death state %d at wave %d. Please impute an arbitrary (or not) month and rerun. Currently this transition to death will be skipped (status is set to -2).\n", *nberr, num[i],i,(int)moisdc[i],(int)andc[i],s[m][i],m);
1.259 brouard 9771: s[m][i]=-2; /* We prefer to skip it (and to skip it in version 0.8a1 too */
1.136 brouard 9772: }
9773: }
9774: }
9775:
9776: for (i=1; i<=imx; i++) {
9777: agedc[i]=(moisdc[i]/12.+andc[i])-(moisnais[i]/12.+annais[i]);
9778: for(m=firstpass; (m<= lastpass); m++){
1.214 brouard 9779: 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 9780: if (s[m][i] >= nlstate+1) {
1.169 brouard 9781: if(agedc[i]>0){
9782: if((int)moisdc[i]!=99 && (int)andc[i]!=9999){
1.136 brouard 9783: agev[m][i]=agedc[i];
1.214 brouard 9784: /*if(moisdc[i]==99 && andc[i]==9999) s[m][i]=-1;*/
1.169 brouard 9785: }else {
1.136 brouard 9786: if ((int)andc[i]!=9999){
9787: nbwarn++;
9788: printf("Warning negative age at death: %ld line:%d\n",num[i],i);
9789: fprintf(ficlog,"Warning negative age at death: %ld line:%d\n",num[i],i);
9790: agev[m][i]=-1;
9791: }
9792: }
1.169 brouard 9793: } /* agedc > 0 */
1.214 brouard 9794: } /* end if */
1.136 brouard 9795: else if(s[m][i] !=9){ /* Standard case, age in fractional
9796: years but with the precision of a month */
9797: agev[m][i]=(mint[m][i]/12.+1./24.+anint[m][i])-(moisnais[i]/12.+1./24.+annais[i]);
9798: if((int)mint[m][i]==99 || (int)anint[m][i]==9999)
9799: agev[m][i]=1;
9800: else if(agev[m][i] < *agemin){
9801: *agemin=agev[m][i];
9802: printf(" Min anint[%d][%d]=%.2f annais[%d]=%.2f, agemin=%.2f\n",m,i,anint[m][i], i,annais[i], *agemin);
9803: }
9804: else if(agev[m][i] >*agemax){
9805: *agemax=agev[m][i];
1.156 brouard 9806: /* printf(" Max anint[%d][%d]=%.0f annais[%d]=%.0f, agemax=%.2f\n",m,i,anint[m][i], i,annais[i], *agemax);*/
1.136 brouard 9807: }
9808: /*agev[m][i]=anint[m][i]-annais[i];*/
9809: /* agev[m][i] = age[i]+2*m;*/
1.214 brouard 9810: } /* en if 9*/
1.136 brouard 9811: else { /* =9 */
1.214 brouard 9812: /* printf("Debug num[%d]=%ld s[%d][%d]=%d\n",i,num[i], m,i, s[m][i]); */
1.136 brouard 9813: agev[m][i]=1;
9814: s[m][i]=-1;
9815: }
9816: }
1.214 brouard 9817: else if(s[m][i]==0) /*= 0 Unknown */
1.136 brouard 9818: agev[m][i]=1;
1.214 brouard 9819: else{
9820: printf("Warning, num[%d]=%ld, s[%d][%d]=%d\n", i, num[i], m, i,s[m][i]);
9821: fprintf(ficlog, "Warning, num[%d]=%ld, s[%d][%d]=%d\n", i, num[i], m, i,s[m][i]);
9822: agev[m][i]=0;
9823: }
9824: } /* End for lastpass */
9825: }
1.136 brouard 9826:
9827: for (i=1; i<=imx; i++) {
9828: for(m=firstpass; (m<=lastpass); m++){
9829: if (s[m][i] > (nlstate+ndeath)) {
1.169 brouard 9830: (*nberr)++;
1.136 brouard 9831: 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);
9832: 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);
9833: return 1;
9834: }
9835: }
9836: }
9837:
9838: /*for (i=1; i<=imx; i++){
9839: for (m=firstpass; (m<lastpass); m++){
9840: printf("%ld %d %.lf %d %d\n", num[i],(covar[1][i]),agev[m][i],s[m][i],s[m+1][i]);
9841: }
9842:
9843: }*/
9844:
9845:
1.139 brouard 9846: printf("Total number of individuals= %d, Agemin = %.2f, Agemax= %.2f\n\n", imx, *agemin, *agemax);
9847: fprintf(ficlog,"Total number of individuals= %d, Agemin = %.2f, Agemax= %.2f\n\n", imx, *agemin, *agemax);
1.136 brouard 9848:
9849: return (0);
1.164 brouard 9850: /* endread:*/
1.136 brouard 9851: printf("Exiting calandcheckages: ");
9852: return (1);
9853: }
9854:
1.172 brouard 9855: #if defined(_MSC_VER)
9856: /*printf("Visual C++ compiler: %s \n;", _MSC_FULL_VER);*/
9857: /*fprintf(ficlog, "Visual C++ compiler: %s \n;", _MSC_FULL_VER);*/
9858: //#include "stdafx.h"
9859: //#include <stdio.h>
9860: //#include <tchar.h>
9861: //#include <windows.h>
9862: //#include <iostream>
9863: typedef BOOL(WINAPI *LPFN_ISWOW64PROCESS) (HANDLE, PBOOL);
9864:
9865: LPFN_ISWOW64PROCESS fnIsWow64Process;
9866:
9867: BOOL IsWow64()
9868: {
9869: BOOL bIsWow64 = FALSE;
9870:
9871: //typedef BOOL (APIENTRY *LPFN_ISWOW64PROCESS)
9872: // (HANDLE, PBOOL);
9873:
9874: //LPFN_ISWOW64PROCESS fnIsWow64Process;
9875:
9876: HMODULE module = GetModuleHandle(_T("kernel32"));
9877: const char funcName[] = "IsWow64Process";
9878: fnIsWow64Process = (LPFN_ISWOW64PROCESS)
9879: GetProcAddress(module, funcName);
9880:
9881: if (NULL != fnIsWow64Process)
9882: {
9883: if (!fnIsWow64Process(GetCurrentProcess(),
9884: &bIsWow64))
9885: //throw std::exception("Unknown error");
9886: printf("Unknown error\n");
9887: }
9888: return bIsWow64 != FALSE;
9889: }
9890: #endif
1.177 brouard 9891:
1.191 brouard 9892: void syscompilerinfo(int logged)
1.167 brouard 9893: {
9894: /* #include "syscompilerinfo.h"*/
1.185 brouard 9895: /* command line Intel compiler 32bit windows, XP compatible:*/
9896: /* /GS /W3 /Gy
9897: /Zc:wchar_t /Zi /O2 /Fd"Release\vc120.pdb" /D "WIN32" /D "NDEBUG" /D
9898: "_CONSOLE" /D "_LIB" /D "_USING_V110_SDK71_" /D "_UNICODE" /D
9899: "UNICODE" /Qipo /Zc:forScope /Gd /Oi /MT /Fa"Release\" /EHsc /nologo
1.186 brouard 9900: /Fo"Release\" /Qprof-dir "Release\" /Fp"Release\IMaCh.pch"
9901: */
9902: /* 64 bits */
1.185 brouard 9903: /*
9904: /GS /W3 /Gy
9905: /Zc:wchar_t /Zi /O2 /Fd"x64\Release\vc120.pdb" /D "WIN32" /D "NDEBUG"
9906: /D "_CONSOLE" /D "_LIB" /D "_UNICODE" /D "UNICODE" /Qipo /Zc:forScope
9907: /Oi /MD /Fa"x64\Release\" /EHsc /nologo /Fo"x64\Release\" /Qprof-dir
9908: "x64\Release\" /Fp"x64\Release\IMaCh.pch" */
9909: /* Optimization are useless and O3 is slower than O2 */
9910: /*
9911: /GS /W3 /Gy /Zc:wchar_t /Zi /O3 /Fd"x64\Release\vc120.pdb" /D "WIN32"
9912: /D "NDEBUG" /D "_CONSOLE" /D "_LIB" /D "_UNICODE" /D "UNICODE" /Qipo
9913: /Zc:forScope /Oi /MD /Fa"x64\Release\" /EHsc /nologo /Qparallel
9914: /Fo"x64\Release\" /Qprof-dir "x64\Release\" /Fp"x64\Release\IMaCh.pch"
9915: */
1.186 brouard 9916: /* Link is */ /* /OUT:"visual studio
1.185 brouard 9917: 2013\Projects\IMaCh\Release\IMaCh.exe" /MANIFEST /NXCOMPAT
9918: /PDB:"visual studio
9919: 2013\Projects\IMaCh\Release\IMaCh.pdb" /DYNAMICBASE
9920: "kernel32.lib" "user32.lib" "gdi32.lib" "winspool.lib"
9921: "comdlg32.lib" "advapi32.lib" "shell32.lib" "ole32.lib"
9922: "oleaut32.lib" "uuid.lib" "odbc32.lib" "odbccp32.lib"
9923: /MACHINE:X86 /OPT:REF /SAFESEH /INCREMENTAL:NO
9924: /SUBSYSTEM:CONSOLE",5.01" /MANIFESTUAC:"level='asInvoker'
9925: uiAccess='false'"
9926: /ManifestFile:"Release\IMaCh.exe.intermediate.manifest" /OPT:ICF
9927: /NOLOGO /TLBID:1
9928: */
1.177 brouard 9929: #if defined __INTEL_COMPILER
1.178 brouard 9930: #if defined(__GNUC__)
9931: struct utsname sysInfo; /* For Intel on Linux and OS/X */
9932: #endif
1.177 brouard 9933: #elif defined(__GNUC__)
1.179 brouard 9934: #ifndef __APPLE__
1.174 brouard 9935: #include <gnu/libc-version.h> /* Only on gnu */
1.179 brouard 9936: #endif
1.177 brouard 9937: struct utsname sysInfo;
1.178 brouard 9938: int cross = CROSS;
9939: if (cross){
9940: printf("Cross-");
1.191 brouard 9941: if(logged) fprintf(ficlog, "Cross-");
1.178 brouard 9942: }
1.174 brouard 9943: #endif
9944:
1.171 brouard 9945: #include <stdint.h>
1.178 brouard 9946:
1.191 brouard 9947: printf("Compiled with:");if(logged)fprintf(ficlog,"Compiled with:");
1.169 brouard 9948: #if defined(__clang__)
1.191 brouard 9949: printf(" Clang/LLVM");if(logged)fprintf(ficlog," Clang/LLVM"); /* Clang/LLVM. ---------------------------------------------- */
1.169 brouard 9950: #endif
9951: #if defined(__ICC) || defined(__INTEL_COMPILER)
1.191 brouard 9952: printf(" Intel ICC/ICPC");if(logged)fprintf(ficlog," Intel ICC/ICPC");/* Intel ICC/ICPC. ------------------------------------------ */
1.169 brouard 9953: #endif
9954: #if defined(__GNUC__) || defined(__GNUG__)
1.191 brouard 9955: printf(" GNU GCC/G++");if(logged)fprintf(ficlog," GNU GCC/G++");/* GNU GCC/G++. --------------------------------------------- */
1.169 brouard 9956: #endif
9957: #if defined(__HP_cc) || defined(__HP_aCC)
1.191 brouard 9958: printf(" Hewlett-Packard C/aC++");if(logged)fprintf(fcilog," Hewlett-Packard C/aC++"); /* Hewlett-Packard C/aC++. ---------------------------------- */
1.169 brouard 9959: #endif
9960: #if defined(__IBMC__) || defined(__IBMCPP__)
1.191 brouard 9961: printf(" IBM XL C/C++"); if(logged) fprintf(ficlog," IBM XL C/C++");/* IBM XL C/C++. -------------------------------------------- */
1.169 brouard 9962: #endif
9963: #if defined(_MSC_VER)
1.191 brouard 9964: printf(" Microsoft Visual Studio");if(logged)fprintf(ficlog," Microsoft Visual Studio");/* Microsoft Visual Studio. --------------------------------- */
1.169 brouard 9965: #endif
9966: #if defined(__PGI)
1.191 brouard 9967: printf(" Portland Group PGCC/PGCPP");if(logged) fprintf(ficlog," Portland Group PGCC/PGCPP");/* Portland Group PGCC/PGCPP. ------------------------------- */
1.169 brouard 9968: #endif
9969: #if defined(__SUNPRO_C) || defined(__SUNPRO_CC)
1.191 brouard 9970: printf(" Oracle Solaris Studio");if(logged)fprintf(ficlog," Oracle Solaris Studio\n");/* Oracle Solaris Studio. ----------------------------------- */
1.167 brouard 9971: #endif
1.191 brouard 9972: printf(" for "); if (logged) fprintf(ficlog, " for ");
1.169 brouard 9973:
1.167 brouard 9974: // http://stackoverflow.com/questions/4605842/how-to-identify-platform-compiler-from-preprocessor-macros
9975: #ifdef _WIN32 // note the underscore: without it, it's not msdn official!
9976: // Windows (x64 and x86)
1.191 brouard 9977: printf("Windows (x64 and x86) ");if(logged) fprintf(ficlog,"Windows (x64 and x86) ");
1.167 brouard 9978: #elif __unix__ // all unices, not all compilers
9979: // Unix
1.191 brouard 9980: printf("Unix ");if(logged) fprintf(ficlog,"Unix ");
1.167 brouard 9981: #elif __linux__
9982: // linux
1.191 brouard 9983: printf("linux ");if(logged) fprintf(ficlog,"linux ");
1.167 brouard 9984: #elif __APPLE__
1.174 brouard 9985: // Mac OS, not sure if this is covered by __posix__ and/or __unix__ though..
1.191 brouard 9986: printf("Mac OS ");if(logged) fprintf(ficlog,"Mac OS ");
1.167 brouard 9987: #endif
9988:
9989: /* __MINGW32__ */
9990: /* __CYGWIN__ */
9991: /* __MINGW64__ */
9992: // http://msdn.microsoft.com/en-us/library/b0084kay.aspx
9993: /* _MSC_VER //the Visual C++ compiler is 17.00.51106.1, the _MSC_VER macro evaluates to 1700. Type cl /? */
9994: /* _MSC_FULL_VER //the Visual C++ compiler is 15.00.20706.01, the _MSC_FULL_VER macro evaluates to 150020706 */
9995: /* _WIN64 // Defined for applications for Win64. */
9996: /* _M_X64 // Defined for compilations that target x64 processors. */
9997: /* _DEBUG // Defined when you compile with /LDd, /MDd, and /MTd. */
1.171 brouard 9998:
1.167 brouard 9999: #if UINTPTR_MAX == 0xffffffff
1.191 brouard 10000: printf(" 32-bit"); if(logged) fprintf(ficlog," 32-bit");/* 32-bit */
1.167 brouard 10001: #elif UINTPTR_MAX == 0xffffffffffffffff
1.191 brouard 10002: printf(" 64-bit"); if(logged) fprintf(ficlog," 64-bit");/* 64-bit */
1.167 brouard 10003: #else
1.191 brouard 10004: printf(" wtf-bit"); if(logged) fprintf(ficlog," wtf-bit");/* wtf */
1.167 brouard 10005: #endif
10006:
1.169 brouard 10007: #if defined(__GNUC__)
10008: # if defined(__GNUC_PATCHLEVEL__)
10009: # define __GNUC_VERSION__ (__GNUC__ * 10000 \
10010: + __GNUC_MINOR__ * 100 \
10011: + __GNUC_PATCHLEVEL__)
10012: # else
10013: # define __GNUC_VERSION__ (__GNUC__ * 10000 \
10014: + __GNUC_MINOR__ * 100)
10015: # endif
1.174 brouard 10016: printf(" using GNU C version %d.\n", __GNUC_VERSION__);
1.191 brouard 10017: if(logged) fprintf(ficlog, " using GNU C version %d.\n", __GNUC_VERSION__);
1.176 brouard 10018:
10019: if (uname(&sysInfo) != -1) {
10020: printf("Running on: %s %s %s %s %s\n",sysInfo.sysname, sysInfo.nodename, sysInfo.release, sysInfo.version, sysInfo.machine);
1.191 brouard 10021: 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 10022: }
10023: else
10024: perror("uname() error");
1.179 brouard 10025: //#ifndef __INTEL_COMPILER
10026: #if !defined (__INTEL_COMPILER) && !defined(__APPLE__)
1.174 brouard 10027: printf("GNU libc version: %s\n", gnu_get_libc_version());
1.191 brouard 10028: if(logged) fprintf(ficlog,"GNU libc version: %s\n", gnu_get_libc_version());
1.177 brouard 10029: #endif
1.169 brouard 10030: #endif
1.172 brouard 10031:
10032: // void main()
10033: // {
1.169 brouard 10034: #if defined(_MSC_VER)
1.174 brouard 10035: if (IsWow64()){
1.191 brouard 10036: printf("\nThe program (probably compiled for 32bit) is running under WOW64 (64bit) emulation.\n");
10037: if (logged) fprintf(ficlog, "\nThe program (probably compiled for 32bit) is running under WOW64 (64bit) emulation.\n");
1.174 brouard 10038: }
10039: else{
1.191 brouard 10040: printf("\nThe program is not running under WOW64 (i.e probably on a 64bit Windows).\n");
10041: if (logged) fprintf(ficlog, "\nThe programm is not running under WOW64 (i.e probably on a 64bit Windows).\n");
1.174 brouard 10042: }
1.172 brouard 10043: // printf("\nPress Enter to continue...");
10044: // getchar();
10045: // }
10046:
1.169 brouard 10047: #endif
10048:
1.167 brouard 10049:
1.219 brouard 10050: }
1.136 brouard 10051:
1.219 brouard 10052: int prevalence_limit(double *p, double **prlim, double ageminpar, double agemaxpar, double ftolpl, int *ncvyearp){
1.180 brouard 10053: /*--------------- Prevalence limit (period or stable prevalence) --------------*/
1.235 brouard 10054: int i, j, k, i1, k4=0, nres=0 ;
1.202 brouard 10055: /* double ftolpl = 1.e-10; */
1.180 brouard 10056: double age, agebase, agelim;
1.203 brouard 10057: double tot;
1.180 brouard 10058:
1.202 brouard 10059: strcpy(filerespl,"PL_");
10060: strcat(filerespl,fileresu);
10061: if((ficrespl=fopen(filerespl,"w"))==NULL) {
10062: printf("Problem with period (stable) prevalence resultfile: %s\n", filerespl);return 1;
10063: fprintf(ficlog,"Problem with period (stable) prevalence resultfile: %s\n", filerespl);return 1;
10064: }
1.227 brouard 10065: printf("\nComputing period (stable) prevalence: result on file '%s' \n", filerespl);
10066: fprintf(ficlog,"\nComputing period (stable) prevalence: result on file '%s' \n", filerespl);
1.202 brouard 10067: pstamp(ficrespl);
1.203 brouard 10068: fprintf(ficrespl,"# Period (stable) prevalence. Precision given by ftolpl=%g \n", ftolpl);
1.202 brouard 10069: fprintf(ficrespl,"#Age ");
10070: for(i=1; i<=nlstate;i++) fprintf(ficrespl,"%d-%d ",i,i);
10071: fprintf(ficrespl,"\n");
1.180 brouard 10072:
1.219 brouard 10073: /* prlim=matrix(1,nlstate,1,nlstate);*/ /* back in main */
1.180 brouard 10074:
1.219 brouard 10075: agebase=ageminpar;
10076: agelim=agemaxpar;
1.180 brouard 10077:
1.227 brouard 10078: /* i1=pow(2,ncoveff); */
1.234 brouard 10079: i1=pow(2,cptcoveff); /* Number of combination of dummy covariates */
1.219 brouard 10080: if (cptcovn < 1){i1=1;}
1.180 brouard 10081:
1.238 brouard 10082: for(k=1; k<=i1;k++){ /* For each combination k of dummy covariates in the model */
10083: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.253 brouard 10084: if(i1 != 1 && TKresult[nres]!= k)
1.238 brouard 10085: continue;
1.235 brouard 10086:
1.238 brouard 10087: /* for(cptcov=1,k=0;cptcov<=i1;cptcov++){ */
10088: /* for(cptcov=1,k=0;cptcov<=1;cptcov++){ */
10089: //for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){
10090: /* k=k+1; */
10091: /* to clean */
10092: //printf("cptcov=%d cptcod=%d codtab=%d\n",cptcov, cptcod,codtabm(cptcod,cptcov));
10093: fprintf(ficrespl,"#******");
10094: printf("#******");
10095: fprintf(ficlog,"#******");
10096: for(j=1;j<=cptcoveff ;j++) {/* all covariates */
10097: fprintf(ficrespl," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]); /* Here problem for varying dummy*/
10098: printf(" V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10099: fprintf(ficlog," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10100: }
10101: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
10102: printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
10103: fprintf(ficrespl," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
10104: fprintf(ficlog," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
10105: }
10106: fprintf(ficrespl,"******\n");
10107: printf("******\n");
10108: fprintf(ficlog,"******\n");
10109: if(invalidvarcomb[k]){
10110: printf("\nCombination (%d) ignored because no case \n",k);
10111: fprintf(ficrespl,"#Combination (%d) ignored because no case \n",k);
10112: fprintf(ficlog,"\nCombination (%d) ignored because no case \n",k);
10113: continue;
10114: }
1.219 brouard 10115:
1.238 brouard 10116: fprintf(ficrespl,"#Age ");
10117: for(j=1;j<=cptcoveff;j++) {
10118: fprintf(ficrespl,"V%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10119: }
10120: for(i=1; i<=nlstate;i++) fprintf(ficrespl," %d-%d ",i,i);
10121: fprintf(ficrespl,"Total Years_to_converge\n");
1.227 brouard 10122:
1.238 brouard 10123: for (age=agebase; age<=agelim; age++){
10124: /* for (age=agebase; age<=agebase; age++){ */
10125: prevalim(prlim, nlstate, p, age, oldm, savm, ftolpl, ncvyearp, k, nres);
10126: fprintf(ficrespl,"%.0f ",age );
10127: for(j=1;j<=cptcoveff;j++)
10128: fprintf(ficrespl,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10129: tot=0.;
10130: for(i=1; i<=nlstate;i++){
10131: tot += prlim[i][i];
10132: fprintf(ficrespl," %.5f", prlim[i][i]);
10133: }
10134: fprintf(ficrespl," %.3f %d\n", tot, *ncvyearp);
10135: } /* Age */
10136: /* was end of cptcod */
10137: } /* cptcov */
10138: } /* nres */
1.219 brouard 10139: return 0;
1.180 brouard 10140: }
10141:
1.218 brouard 10142: 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){
10143: /*--------------- Back Prevalence limit (period or stable prevalence) --------------*/
10144:
10145: /* Computes the back prevalence limit for any combination of covariate values
10146: * at any age between ageminpar and agemaxpar
10147: */
1.235 brouard 10148: int i, j, k, i1, nres=0 ;
1.217 brouard 10149: /* double ftolpl = 1.e-10; */
10150: double age, agebase, agelim;
10151: double tot;
1.218 brouard 10152: /* double ***mobaverage; */
10153: /* double **dnewm, **doldm, **dsavm; /\* for use *\/ */
1.217 brouard 10154:
10155: strcpy(fileresplb,"PLB_");
10156: strcat(fileresplb,fileresu);
10157: if((ficresplb=fopen(fileresplb,"w"))==NULL) {
10158: printf("Problem with period (stable) back prevalence resultfile: %s\n", fileresplb);return 1;
10159: fprintf(ficlog,"Problem with period (stable) back prevalence resultfile: %s\n", fileresplb);return 1;
10160: }
10161: printf("Computing period (stable) back prevalence: result on file '%s' \n", fileresplb);
10162: fprintf(ficlog,"Computing period (stable) back prevalence: result on file '%s' \n", fileresplb);
10163: pstamp(ficresplb);
10164: fprintf(ficresplb,"# Period (stable) back prevalence. Precision given by ftolpl=%g \n", ftolpl);
10165: fprintf(ficresplb,"#Age ");
10166: for(i=1; i<=nlstate;i++) fprintf(ficresplb,"%d-%d ",i,i);
10167: fprintf(ficresplb,"\n");
10168:
1.218 brouard 10169:
10170: /* prlim=matrix(1,nlstate,1,nlstate);*/ /* back in main */
10171:
10172: agebase=ageminpar;
10173: agelim=agemaxpar;
10174:
10175:
1.227 brouard 10176: i1=pow(2,cptcoveff);
1.218 brouard 10177: if (cptcovn < 1){i1=1;}
1.227 brouard 10178:
1.238 brouard 10179: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
10180: for(k=1; k<=i1;k++){ /* For any combination of dummy covariates, fixed and varying */
1.253 brouard 10181: if(i1 != 1 && TKresult[nres]!= k)
1.238 brouard 10182: continue;
10183: //printf("cptcov=%d cptcod=%d codtab=%d\n",cptcov, cptcod,codtabm(cptcod,cptcov));
10184: fprintf(ficresplb,"#******");
10185: printf("#******");
10186: fprintf(ficlog,"#******");
10187: for(j=1;j<=cptcoveff ;j++) {/* all covariates */
10188: fprintf(ficresplb," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10189: printf(" V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10190: fprintf(ficlog," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10191: }
10192: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
10193: printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
10194: fprintf(ficresplb," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
10195: fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
10196: }
10197: fprintf(ficresplb,"******\n");
10198: printf("******\n");
10199: fprintf(ficlog,"******\n");
10200: if(invalidvarcomb[k]){
10201: printf("\nCombination (%d) ignored because no cases \n",k);
10202: fprintf(ficresplb,"#Combination (%d) ignored because no cases \n",k);
10203: fprintf(ficlog,"\nCombination (%d) ignored because no cases \n",k);
10204: continue;
10205: }
1.218 brouard 10206:
1.238 brouard 10207: fprintf(ficresplb,"#Age ");
10208: for(j=1;j<=cptcoveff;j++) {
10209: fprintf(ficresplb,"V%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10210: }
10211: for(i=1; i<=nlstate;i++) fprintf(ficresplb," %d-%d ",i,i);
10212: fprintf(ficresplb,"Total Years_to_converge\n");
1.218 brouard 10213:
10214:
1.238 brouard 10215: for (age=agebase; age<=agelim; age++){
10216: /* for (age=agebase; age<=agebase; age++){ */
10217: if(mobilavproj > 0){
10218: /* bprevalim(bprlim, mobaverage, nlstate, p, age, ageminpar, agemaxpar, oldm, savm, doldm, dsavm, ftolpl, ncvyearp, k); */
10219: /* bprevalim(bprlim, mobaverage, nlstate, p, age, oldm, savm, dnewm, doldm, dsavm, ftolpl, ncvyearp, k); */
1.242 brouard 10220: bprevalim(bprlim, mobaverage, nlstate, p, age, ftolpl, ncvyearp, k, nres);
1.238 brouard 10221: }else if (mobilavproj == 0){
10222: 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);
10223: 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);
10224: exit(1);
10225: }else{
10226: /* bprevalim(bprlim, probs, nlstate, p, age, oldm, savm, dnewm, doldm, dsavm, ftolpl, ncvyearp, k); */
1.242 brouard 10227: bprevalim(bprlim, probs, nlstate, p, age, ftolpl, ncvyearp, k,nres);
1.266 brouard 10228: /* printf("TOTOT\n"); */
10229: /* exit(1); */
1.238 brouard 10230: }
10231: fprintf(ficresplb,"%.0f ",age );
10232: for(j=1;j<=cptcoveff;j++)
10233: fprintf(ficresplb,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10234: tot=0.;
10235: for(i=1; i<=nlstate;i++){
10236: tot += bprlim[i][i];
10237: fprintf(ficresplb," %.5f", bprlim[i][i]);
10238: }
10239: fprintf(ficresplb," %.3f %d\n", tot, *ncvyearp);
10240: } /* Age */
10241: /* was end of cptcod */
1.255 brouard 10242: /*fprintf(ficresplb,"\n");*/ /* Seems to be necessary for gnuplot only if two result lines and no covariate. */
1.238 brouard 10243: } /* end of any combination */
10244: } /* end of nres */
1.218 brouard 10245: /* hBijx(p, bage, fage); */
10246: /* fclose(ficrespijb); */
10247:
10248: return 0;
1.217 brouard 10249: }
1.218 brouard 10250:
1.180 brouard 10251: int hPijx(double *p, int bage, int fage){
10252: /*------------- h Pij x at various ages ------------*/
10253:
10254: int stepsize;
10255: int agelim;
10256: int hstepm;
10257: int nhstepm;
1.235 brouard 10258: int h, i, i1, j, k, k4, nres=0;
1.180 brouard 10259:
10260: double agedeb;
10261: double ***p3mat;
10262:
1.201 brouard 10263: strcpy(filerespij,"PIJ_"); strcat(filerespij,fileresu);
1.180 brouard 10264: if((ficrespij=fopen(filerespij,"w"))==NULL) {
10265: printf("Problem with Pij resultfile: %s\n", filerespij); return 1;
10266: fprintf(ficlog,"Problem with Pij resultfile: %s\n", filerespij); return 1;
10267: }
10268: printf("Computing pij: result on file '%s' \n", filerespij);
10269: fprintf(ficlog,"Computing pij: result on file '%s' \n", filerespij);
10270:
10271: stepsize=(int) (stepm+YEARM-1)/YEARM;
10272: /*if (stepm<=24) stepsize=2;*/
10273:
10274: agelim=AGESUP;
10275: hstepm=stepsize*YEARM; /* Every year of age */
10276: hstepm=hstepm/stepm; /* Typically 2 years, = 2/6 months = 4 */
1.218 brouard 10277:
1.180 brouard 10278: /* hstepm=1; aff par mois*/
10279: pstamp(ficrespij);
10280: fprintf(ficrespij,"#****** h Pij x Probability to be in state j at age x+h being in i at x ");
1.227 brouard 10281: i1= pow(2,cptcoveff);
1.218 brouard 10282: /* for(cptcov=1,k=0;cptcov<=i1;cptcov++){ */
10283: /* /\*for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){*\/ */
10284: /* k=k+1; */
1.235 brouard 10285: for(nres=1; nres <= nresult; nres++) /* For each resultline */
10286: for(k=1; k<=i1;k++){
1.253 brouard 10287: if(i1 != 1 && TKresult[nres]!= k)
1.235 brouard 10288: continue;
1.183 brouard 10289: fprintf(ficrespij,"\n#****** ");
1.227 brouard 10290: for(j=1;j<=cptcoveff;j++)
1.198 brouard 10291: fprintf(ficrespij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
1.235 brouard 10292: for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */
10293: printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
10294: fprintf(ficrespij," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
10295: }
1.183 brouard 10296: fprintf(ficrespij,"******\n");
10297:
10298: for (agedeb=fage; agedeb>=bage; agedeb--){ /* If stepm=6 months */
10299: nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
10300: nhstepm = nhstepm/hstepm; /* Typically 40/4=10 */
10301:
10302: /* nhstepm=nhstepm*YEARM; aff par mois*/
1.180 brouard 10303:
1.183 brouard 10304: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
10305: oldm=oldms;savm=savms;
1.235 brouard 10306: hpxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k, nres);
1.183 brouard 10307: fprintf(ficrespij,"# Cov Agex agex+h hpijx with i,j=");
10308: for(i=1; i<=nlstate;i++)
10309: for(j=1; j<=nlstate+ndeath;j++)
10310: fprintf(ficrespij," %1d-%1d",i,j);
10311: fprintf(ficrespij,"\n");
10312: for (h=0; h<=nhstepm; h++){
10313: /*agedebphstep = agedeb + h*hstepm/YEARM*stepm;*/
10314: fprintf(ficrespij,"%d %3.f %3.f",k, agedeb, agedeb + h*hstepm/YEARM*stepm );
1.180 brouard 10315: for(i=1; i<=nlstate;i++)
10316: for(j=1; j<=nlstate+ndeath;j++)
1.183 brouard 10317: fprintf(ficrespij," %.5f", p3mat[i][j][h]);
1.180 brouard 10318: fprintf(ficrespij,"\n");
10319: }
1.183 brouard 10320: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
10321: fprintf(ficrespij,"\n");
10322: }
1.180 brouard 10323: /*}*/
10324: }
1.218 brouard 10325: return 0;
1.180 brouard 10326: }
1.218 brouard 10327:
10328: int hBijx(double *p, int bage, int fage, double ***prevacurrent){
1.217 brouard 10329: /*------------- h Bij x at various ages ------------*/
10330:
10331: int stepsize;
1.218 brouard 10332: /* int agelim; */
10333: int ageminl;
1.217 brouard 10334: int hstepm;
10335: int nhstepm;
1.238 brouard 10336: int h, i, i1, j, k, nres;
1.218 brouard 10337:
1.217 brouard 10338: double agedeb;
10339: double ***p3mat;
1.218 brouard 10340:
10341: strcpy(filerespijb,"PIJB_"); strcat(filerespijb,fileresu);
10342: if((ficrespijb=fopen(filerespijb,"w"))==NULL) {
10343: printf("Problem with Pij back resultfile: %s\n", filerespijb); return 1;
10344: fprintf(ficlog,"Problem with Pij back resultfile: %s\n", filerespijb); return 1;
10345: }
10346: printf("Computing pij back: result on file '%s' \n", filerespijb);
10347: fprintf(ficlog,"Computing pij back: result on file '%s' \n", filerespijb);
10348:
10349: stepsize=(int) (stepm+YEARM-1)/YEARM;
10350: /*if (stepm<=24) stepsize=2;*/
1.217 brouard 10351:
1.218 brouard 10352: /* agelim=AGESUP; */
10353: ageminl=30;
10354: hstepm=stepsize*YEARM; /* Every year of age */
10355: hstepm=hstepm/stepm; /* Typically 2 years, = 2/6 months = 4 */
10356:
10357: /* hstepm=1; aff par mois*/
10358: pstamp(ficrespijb);
1.255 brouard 10359: fprintf(ficrespijb,"#****** h Bij x Back probability to be in state i at age x-h being in j at x: B1j+B2j+...=1 ");
1.227 brouard 10360: i1= pow(2,cptcoveff);
1.218 brouard 10361: /* for(cptcov=1,k=0;cptcov<=i1;cptcov++){ */
10362: /* /\*for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){*\/ */
10363: /* k=k+1; */
1.238 brouard 10364: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
10365: for(k=1; k<=i1;k++){ /* For any combination of dummy covariates, fixed and varying */
1.253 brouard 10366: if(i1 != 1 && TKresult[nres]!= k)
1.238 brouard 10367: continue;
10368: fprintf(ficrespijb,"\n#****** ");
10369: for(j=1;j<=cptcoveff;j++)
10370: fprintf(ficrespijb,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
10371: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
10372: fprintf(ficrespijb," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
10373: }
10374: fprintf(ficrespijb,"******\n");
1.264 brouard 10375: if(invalidvarcomb[k]){ /* Is it necessary here? */
1.238 brouard 10376: fprintf(ficrespijb,"\n#Combination (%d) ignored because no cases \n",k);
10377: continue;
10378: }
10379:
10380: /* for (agedeb=fage; agedeb>=bage; agedeb--){ /\* If stepm=6 months *\/ */
10381: for (agedeb=bage; agedeb<=fage; agedeb++){ /* If stepm=6 months and estepm=24 (2 years) */
10382: /* nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); /\* Typically 20 years = 20*12/6=40 *\/ */
10383: nhstepm=(int) rint((agedeb-ageminl)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
10384: nhstepm = nhstepm/hstepm; /* Typically 40/4=10, because estepm=24 stepm=6 => hstepm=24/6=4 */
10385:
10386: /* nhstepm=nhstepm*YEARM; aff par mois*/
10387:
1.266 brouard 10388: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); /* We can't have it at an upper level because of nhstepm */
10389: /* and memory limitations if stepm is small */
10390:
1.238 brouard 10391: /* oldm=oldms;savm=savms; */
10392: /* hbxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k); */
1.267 brouard 10393: hbxij(p3mat,nhstepm,agedeb,hstepm,p,prevacurrent,nlstate,stepm, k, nres);
1.238 brouard 10394: /* hbxij(p3mat,nhstepm,agedeb,hstepm,p,prevacurrent,nlstate,stepm,oldm,savm, dnewm, doldm, dsavm, k); */
1.255 brouard 10395: fprintf(ficrespijb,"# Cov Agex agex-h hbijx with i,j=");
1.217 brouard 10396: for(i=1; i<=nlstate;i++)
10397: for(j=1; j<=nlstate+ndeath;j++)
1.238 brouard 10398: fprintf(ficrespijb," %1d-%1d",i,j);
1.217 brouard 10399: fprintf(ficrespijb,"\n");
1.238 brouard 10400: for (h=0; h<=nhstepm; h++){
10401: /*agedebphstep = agedeb + h*hstepm/YEARM*stepm;*/
10402: fprintf(ficrespijb,"%d %3.f %3.f",k, agedeb, agedeb - h*hstepm/YEARM*stepm );
10403: /* fprintf(ficrespijb,"%d %3.f %3.f",k, agedeb, agedeb + h*hstepm/YEARM*stepm ); */
10404: for(i=1; i<=nlstate;i++)
10405: for(j=1; j<=nlstate+ndeath;j++)
10406: fprintf(ficrespijb," %.5f", p3mat[i][j][h]);
10407: fprintf(ficrespijb,"\n");
10408: }
10409: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
10410: fprintf(ficrespijb,"\n");
10411: } /* end age deb */
10412: } /* end combination */
10413: } /* end nres */
1.218 brouard 10414: return 0;
10415: } /* hBijx */
1.217 brouard 10416:
1.180 brouard 10417:
1.136 brouard 10418: /***********************************************/
10419: /**************** Main Program *****************/
10420: /***********************************************/
10421:
10422: int main(int argc, char *argv[])
10423: {
10424: #ifdef GSL
10425: const gsl_multimin_fminimizer_type *T;
10426: size_t iteri = 0, it;
10427: int rval = GSL_CONTINUE;
10428: int status = GSL_SUCCESS;
10429: double ssval;
10430: #endif
10431: int movingaverage(double ***probs, double bage,double fage, double ***mobaverage, int mobilav);
1.164 brouard 10432: int i,j, k, n=MAXN,iter=0,m,size=100, cptcod;
1.209 brouard 10433: int ncvyear=0; /* Number of years needed for the period prevalence to converge */
1.164 brouard 10434: int jj, ll, li, lj, lk;
1.136 brouard 10435: int numlinepar=0; /* Current linenumber of parameter file */
1.197 brouard 10436: int num_filled;
1.136 brouard 10437: int itimes;
10438: int NDIM=2;
10439: int vpopbased=0;
1.235 brouard 10440: int nres=0;
1.258 brouard 10441: int endishere=0;
1.136 brouard 10442:
1.164 brouard 10443: char ca[32], cb[32];
1.136 brouard 10444: /* FILE *fichtm; *//* Html File */
10445: /* FILE *ficgp;*/ /*Gnuplot File */
10446: struct stat info;
1.191 brouard 10447: double agedeb=0.;
1.194 brouard 10448:
10449: double ageminpar=AGEOVERFLOW,agemin=AGEOVERFLOW, agemaxpar=-AGEOVERFLOW, agemax=-AGEOVERFLOW;
1.219 brouard 10450: double ageminout=-AGEOVERFLOW,agemaxout=AGEOVERFLOW; /* Smaller Age range redefined after movingaverage */
1.136 brouard 10451:
1.165 brouard 10452: double fret;
1.191 brouard 10453: double dum=0.; /* Dummy variable */
1.136 brouard 10454: double ***p3mat;
1.218 brouard 10455: /* double ***mobaverage; */
1.164 brouard 10456:
10457: char line[MAXLINE];
1.197 brouard 10458: char path[MAXLINE],pathc[MAXLINE],pathcd[MAXLINE],pathtot[MAXLINE];
10459:
1.234 brouard 10460: char modeltemp[MAXLINE];
1.230 brouard 10461: char resultline[MAXLINE];
10462:
1.136 brouard 10463: char pathr[MAXLINE], pathimach[MAXLINE];
1.164 brouard 10464: char *tok, *val; /* pathtot */
1.136 brouard 10465: int firstobs=1, lastobs=10;
1.195 brouard 10466: int c, h , cpt, c2;
1.191 brouard 10467: int jl=0;
10468: int i1, j1, jk, stepsize=0;
1.194 brouard 10469: int count=0;
10470:
1.164 brouard 10471: int *tab;
1.136 brouard 10472: int mobilavproj=0 , prevfcast=0 ; /* moving average of prev, If prevfcast=1 prevalence projection */
1.217 brouard 10473: int backcast=0;
1.136 brouard 10474: int mobilav=0,popforecast=0;
1.191 brouard 10475: int hstepm=0, nhstepm=0;
1.136 brouard 10476: int agemortsup;
10477: float sumlpop=0.;
10478: double jprev1=1, mprev1=1,anprev1=2000,jprev2=1, mprev2=1,anprev2=2000;
10479: double jpyram=1, mpyram=1,anpyram=2000,jpyram1=1, mpyram1=1,anpyram1=2000;
10480:
1.191 brouard 10481: double bage=0, fage=110., age, agelim=0., agebase=0.;
1.136 brouard 10482: double ftolpl=FTOL;
10483: double **prlim;
1.217 brouard 10484: double **bprlim;
1.136 brouard 10485: double ***param; /* Matrix of parameters */
1.251 brouard 10486: double ***paramstart; /* Matrix of starting parameter values */
10487: double *p, *pstart; /* p=param[1][1] pstart is for starting values guessed by freqsummary */
1.136 brouard 10488: double **matcov; /* Matrix of covariance */
1.203 brouard 10489: double **hess; /* Hessian matrix */
1.136 brouard 10490: double ***delti3; /* Scale */
10491: double *delti; /* Scale */
10492: double ***eij, ***vareij;
10493: double **varpl; /* Variances of prevalence limits by age */
1.268 ! brouard 10494: double **varbpl; /* Variances of back prevalence limits by age */
1.136 brouard 10495: double *epj, vepp;
1.164 brouard 10496:
1.136 brouard 10497: double dateprev1, dateprev2,jproj1=1,mproj1=1,anproj1=2000,jproj2=1,mproj2=1,anproj2=2000;
1.217 brouard 10498: double jback1=1,mback1=1,anback1=2000,jback2=1,mback2=1,anback2=2000;
10499:
1.136 brouard 10500: double **ximort;
1.145 brouard 10501: char *alph[]={"a","a","b","c","d","e"}, str[4]="1234";
1.136 brouard 10502: int *dcwave;
10503:
1.164 brouard 10504: char z[1]="c";
1.136 brouard 10505:
10506: /*char *strt;*/
10507: char strtend[80];
1.126 brouard 10508:
1.164 brouard 10509:
1.126 brouard 10510: /* setlocale (LC_ALL, ""); */
10511: /* bindtextdomain (PACKAGE, LOCALEDIR); */
10512: /* textdomain (PACKAGE); */
10513: /* setlocale (LC_CTYPE, ""); */
10514: /* setlocale (LC_MESSAGES, ""); */
10515:
10516: /* gettimeofday(&start_time, (struct timezone*)0); */ /* at first time */
1.157 brouard 10517: rstart_time = time(NULL);
10518: /* (void) gettimeofday(&start_time,&tzp);*/
10519: start_time = *localtime(&rstart_time);
1.126 brouard 10520: curr_time=start_time;
1.157 brouard 10521: /*tml = *localtime(&start_time.tm_sec);*/
10522: /* strcpy(strstart,asctime(&tml)); */
10523: strcpy(strstart,asctime(&start_time));
1.126 brouard 10524:
10525: /* printf("Localtime (at start)=%s",strstart); */
1.157 brouard 10526: /* tp.tm_sec = tp.tm_sec +86400; */
10527: /* tm = *localtime(&start_time.tm_sec); */
1.126 brouard 10528: /* tmg.tm_year=tmg.tm_year +dsign*dyear; */
10529: /* tmg.tm_mon=tmg.tm_mon +dsign*dmonth; */
10530: /* tmg.tm_hour=tmg.tm_hour + 1; */
1.157 brouard 10531: /* tp.tm_sec = mktime(&tmg); */
1.126 brouard 10532: /* strt=asctime(&tmg); */
10533: /* printf("Time(after) =%s",strstart); */
10534: /* (void) time (&time_value);
10535: * printf("time=%d,t-=%d\n",time_value,time_value-86400);
10536: * tm = *localtime(&time_value);
10537: * strstart=asctime(&tm);
10538: * printf("tim_value=%d,asctime=%s\n",time_value,strstart);
10539: */
10540:
10541: nberr=0; /* Number of errors and warnings */
10542: nbwarn=0;
1.184 brouard 10543: #ifdef WIN32
10544: _getcwd(pathcd, size);
10545: #else
1.126 brouard 10546: getcwd(pathcd, size);
1.184 brouard 10547: #endif
1.191 brouard 10548: syscompilerinfo(0);
1.196 brouard 10549: printf("\nIMaCh version %s, %s\n%s",version, copyright, fullversion);
1.126 brouard 10550: if(argc <=1){
10551: printf("\nEnter the parameter file name: ");
1.205 brouard 10552: if(!fgets(pathr,FILENAMELENGTH,stdin)){
10553: printf("ERROR Empty parameter file name\n");
10554: goto end;
10555: }
1.126 brouard 10556: i=strlen(pathr);
10557: if(pathr[i-1]=='\n')
10558: pathr[i-1]='\0';
1.156 brouard 10559: i=strlen(pathr);
1.205 brouard 10560: if(i >= 1 && pathr[i-1]==' ') {/* This may happen when dragging on oS/X! */
1.156 brouard 10561: pathr[i-1]='\0';
1.205 brouard 10562: }
10563: i=strlen(pathr);
10564: if( i==0 ){
10565: printf("ERROR Empty parameter file name\n");
10566: goto end;
10567: }
10568: for (tok = pathr; tok != NULL; ){
1.126 brouard 10569: printf("Pathr |%s|\n",pathr);
10570: while ((val = strsep(&tok, "\"" )) != NULL && *val == '\0');
10571: printf("val= |%s| pathr=%s\n",val,pathr);
10572: strcpy (pathtot, val);
10573: if(pathr[0] == '\0') break; /* Dirty */
10574: }
10575: }
10576: else{
10577: strcpy(pathtot,argv[1]);
10578: }
10579: /*if(getcwd(pathcd, MAXLINE)!= NULL)printf ("Error pathcd\n");*/
10580: /*cygwin_split_path(pathtot,path,optionfile);
10581: printf("pathtot=%s, path=%s, optionfile=%s\n",pathtot,path,optionfile);*/
10582: /* cutv(path,optionfile,pathtot,'\\');*/
10583:
10584: /* Split argv[0], imach program to get pathimach */
10585: printf("\nargv[0]=%s argv[1]=%s, \n",argv[0],argv[1]);
10586: split(argv[0],pathimach,optionfile,optionfilext,optionfilefiname);
10587: printf("\nargv[0]=%s pathimach=%s, \noptionfile=%s \noptionfilext=%s \noptionfilefiname=%s\n",argv[0],pathimach,optionfile,optionfilext,optionfilefiname);
10588: /* strcpy(pathimach,argv[0]); */
10589: /* Split argv[1]=pathtot, parameter file name to get path, optionfile, extension and name */
10590: split(pathtot,path,optionfile,optionfilext,optionfilefiname);
10591: printf("\npathtot=%s,\npath=%s,\noptionfile=%s \noptionfilext=%s \noptionfilefiname=%s\n",pathtot,path,optionfile,optionfilext,optionfilefiname);
1.184 brouard 10592: #ifdef WIN32
10593: _chdir(path); /* Can be a relative path */
10594: if(_getcwd(pathcd,MAXLINE) > 0) /* So pathcd is the full path */
10595: #else
1.126 brouard 10596: chdir(path); /* Can be a relative path */
1.184 brouard 10597: if (getcwd(pathcd, MAXLINE) > 0) /* So pathcd is the full path */
10598: #endif
10599: printf("Current directory %s!\n",pathcd);
1.126 brouard 10600: strcpy(command,"mkdir ");
10601: strcat(command,optionfilefiname);
10602: if((outcmd=system(command)) != 0){
1.169 brouard 10603: printf("Directory already exists (or can't create it) %s%s, err=%d\n",path,optionfilefiname,outcmd);
1.126 brouard 10604: /* fprintf(ficlog,"Problem creating directory %s%s\n",path,optionfilefiname); */
10605: /* fclose(ficlog); */
10606: /* exit(1); */
10607: }
10608: /* if((imk=mkdir(optionfilefiname))<0){ */
10609: /* perror("mkdir"); */
10610: /* } */
10611:
10612: /*-------- arguments in the command line --------*/
10613:
1.186 brouard 10614: /* Main Log file */
1.126 brouard 10615: strcat(filelog, optionfilefiname);
10616: strcat(filelog,".log"); /* */
10617: if((ficlog=fopen(filelog,"w"))==NULL) {
10618: printf("Problem with logfile %s\n",filelog);
10619: goto end;
10620: }
10621: fprintf(ficlog,"Log filename:%s\n",filelog);
1.197 brouard 10622: fprintf(ficlog,"Version %s %s",version,fullversion);
1.126 brouard 10623: fprintf(ficlog,"\nEnter the parameter file name: \n");
10624: fprintf(ficlog,"pathimach=%s\npathtot=%s\n\
10625: path=%s \n\
10626: optionfile=%s\n\
10627: optionfilext=%s\n\
1.156 brouard 10628: optionfilefiname='%s'\n",pathimach,pathtot,path,optionfile,optionfilext,optionfilefiname);
1.126 brouard 10629:
1.197 brouard 10630: syscompilerinfo(1);
1.167 brouard 10631:
1.126 brouard 10632: printf("Local time (at start):%s",strstart);
10633: fprintf(ficlog,"Local time (at start): %s",strstart);
10634: fflush(ficlog);
10635: /* (void) gettimeofday(&curr_time,&tzp); */
1.157 brouard 10636: /* printf("Elapsed time %d\n", asc_diff_time(curr_time.tm_sec-start_time.tm_sec,tmpout)); */
1.126 brouard 10637:
10638: /* */
10639: strcpy(fileres,"r");
10640: strcat(fileres, optionfilefiname);
1.201 brouard 10641: strcat(fileresu, optionfilefiname); /* Without r in front */
1.126 brouard 10642: strcat(fileres,".txt"); /* Other files have txt extension */
1.201 brouard 10643: strcat(fileresu,".txt"); /* Other files have txt extension */
1.126 brouard 10644:
1.186 brouard 10645: /* Main ---------arguments file --------*/
1.126 brouard 10646:
10647: if((ficpar=fopen(optionfile,"r"))==NULL) {
1.155 brouard 10648: printf("Problem with optionfile '%s' with errno='%s'\n",optionfile,strerror(errno));
10649: fprintf(ficlog,"Problem with optionfile '%s' with errno='%s'\n",optionfile,strerror(errno));
1.126 brouard 10650: fflush(ficlog);
1.149 brouard 10651: /* goto end; */
10652: exit(70);
1.126 brouard 10653: }
10654:
10655:
10656:
10657: strcpy(filereso,"o");
1.201 brouard 10658: strcat(filereso,fileresu);
1.126 brouard 10659: if((ficparo=fopen(filereso,"w"))==NULL) { /* opened on subdirectory */
10660: printf("Problem with Output resultfile: %s\n", filereso);
10661: fprintf(ficlog,"Problem with Output resultfile: %s\n", filereso);
10662: fflush(ficlog);
10663: goto end;
10664: }
10665:
10666: /* Reads comments: lines beginning with '#' */
10667: numlinepar=0;
1.197 brouard 10668:
10669: /* First parameter line */
10670: while(fgets(line, MAXLINE, ficpar)) {
10671: /* If line starts with a # it is a comment */
10672: if (line[0] == '#') {
10673: numlinepar++;
10674: fputs(line,stdout);
10675: fputs(line,ficparo);
10676: fputs(line,ficlog);
10677: continue;
10678: }else
10679: break;
10680: }
10681: if((num_filled=sscanf(line,"title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", \
10682: title, datafile, &lastobs, &firstpass,&lastpass)) !=EOF){
10683: if (num_filled != 5) {
10684: printf("Should be 5 parameters\n");
10685: }
1.126 brouard 10686: numlinepar++;
1.197 brouard 10687: printf("title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", title, datafile, lastobs, firstpass,lastpass);
10688: }
10689: /* Second parameter line */
10690: while(fgets(line, MAXLINE, ficpar)) {
10691: /* If line starts with a # it is a comment */
10692: if (line[0] == '#') {
10693: numlinepar++;
10694: fputs(line,stdout);
10695: fputs(line,ficparo);
10696: fputs(line,ficlog);
10697: continue;
10698: }else
10699: break;
10700: }
1.223 brouard 10701: 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", \
10702: &ftol, &stepm, &ncovcol, &nqv, &ntv, &nqtv, &nlstate, &ndeath, &maxwav, &mle, &weightopt)) !=EOF){
10703: if (num_filled != 11) {
10704: 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 10705: printf("but line=%s\n",line);
1.197 brouard 10706: }
1.223 brouard 10707: 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 10708: }
1.203 brouard 10709: /* ftolpl=6*ftol*1.e5; /\* 6.e-3 make convergences in less than 80 loops for the prevalence limit *\/ */
1.209 brouard 10710: /*ftolpl=6.e-4; *//* 6.e-3 make convergences in less than 80 loops for the prevalence limit */
1.197 brouard 10711: /* Third parameter line */
10712: while(fgets(line, MAXLINE, ficpar)) {
10713: /* If line starts with a # it is a comment */
10714: if (line[0] == '#') {
10715: numlinepar++;
10716: fputs(line,stdout);
10717: fputs(line,ficparo);
10718: fputs(line,ficlog);
10719: continue;
10720: }else
10721: break;
10722: }
1.201 brouard 10723: if((num_filled=sscanf(line,"model=1+age%[^.\n]", model)) !=EOF){
1.263 brouard 10724: if (num_filled == 0){
10725: printf("ERROR %d: Model should be at minimum 'model=1+age.' WITHOUT space:'%s'\n",num_filled, line);
10726: fprintf(ficlog,"ERROR %d: Model should be at minimum 'model=1+age.' WITHOUT space:'%s'\n",num_filled, line);
10727: model[0]='\0';
10728: goto end;
10729: } else if (num_filled != 1){
1.197 brouard 10730: printf("ERROR %d: Model should be at minimum 'model=1+age.' %s\n",num_filled, line);
10731: fprintf(ficlog,"ERROR %d: Model should be at minimum 'model=1+age.' %s\n",num_filled, line);
10732: model[0]='\0';
10733: goto end;
10734: }
10735: else{
10736: if (model[0]=='+'){
10737: for(i=1; i<=strlen(model);i++)
10738: modeltemp[i-1]=model[i];
1.201 brouard 10739: strcpy(model,modeltemp);
1.197 brouard 10740: }
10741: }
1.199 brouard 10742: /* printf(" model=1+age%s modeltemp= %s, model=%s\n",model, modeltemp, model);fflush(stdout); */
1.203 brouard 10743: printf("model=1+age+%s\n",model);fflush(stdout);
1.197 brouard 10744: }
10745: /* 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); */
10746: /* numlinepar=numlinepar+3; /\* In general *\/ */
10747: /* 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 10748: 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);
10749: 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 10750: fflush(ficlog);
1.190 brouard 10751: /* if(model[0]=='#'|| model[0]== '\0'){ */
10752: if(model[0]=='#'){
1.187 brouard 10753: printf("Error in 'model' line: model should start with 'model=1+age+' and end with '.' \n \
10754: 'model=1+age+.' or 'model=1+age+V1.' or 'model=1+age+age*age+V1+V1*age.' or \n \
10755: 'model=1+age+V1+V2.' or 'model=1+age+V1+V2+V1*V2.' etc. \n"); \
10756: if(mle != -1){
10757: printf("Fix the model line and run imach with mle=-1 to get a correct template of the parameter file.\n");
10758: exit(1);
10759: }
10760: }
1.126 brouard 10761: while((c=getc(ficpar))=='#' && c!= EOF){
10762: ungetc(c,ficpar);
10763: fgets(line, MAXLINE, ficpar);
10764: numlinepar++;
1.195 brouard 10765: if(line[1]=='q'){ /* This #q will quit imach (the answer is q) */
10766: z[0]=line[1];
10767: }
10768: /* printf("****line [1] = %c \n",line[1]); */
1.141 brouard 10769: fputs(line, stdout);
10770: //puts(line);
1.126 brouard 10771: fputs(line,ficparo);
10772: fputs(line,ficlog);
10773: }
10774: ungetc(c,ficpar);
10775:
10776:
1.145 brouard 10777: covar=matrix(0,NCOVMAX,1,n); /**< used in readdata */
1.268 ! brouard 10778: if(nqv>=1)coqvar=matrix(1,nqv,1,n); /**< Fixed quantitative covariate */
! 10779: if(nqtv>=1)cotqvar=ma3x(1,maxwav,1,nqtv,1,n); /**< Time varying quantitative covariate */
! 10780: if(ntv+nqtv>=1)cotvar=ma3x(1,maxwav,1,ntv+nqtv,1,n); /**< Time varying covariate (dummy and quantitative)*/
1.136 brouard 10781: cptcovn=0; /*Number of covariates, i.e. number of '+' in model statement plus one, indepently of n in Vn*/
10782: /* v1+v2+v3+v2*v4+v5*age makes cptcovn = 5
10783: v1+v2*age+v2*v3 makes cptcovn = 3
10784: */
10785: if (strlen(model)>1)
1.187 brouard 10786: 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 10787: else
1.187 brouard 10788: ncovmodel=2; /* Constant and age */
1.133 brouard 10789: nforce= (nlstate+ndeath-1)*nlstate; /* Number of forces ij from state i to j */
10790: npar= nforce*ncovmodel; /* Number of parameters like aij*/
1.131 brouard 10791: if(npar >MAXPARM || nlstate >NLSTATEMAX || ndeath >NDEATHMAX || ncovmodel>NCOVMAX){
10792: 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);
10793: 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);
10794: fflush(stdout);
10795: fclose (ficlog);
10796: goto end;
10797: }
1.126 brouard 10798: delti3= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
10799: delti=delti3[1][1];
10800: /*delti=vector(1,npar); *//* Scale of each paramater (output from hesscov)*/
10801: if(mle==-1){ /* Print a wizard for help writing covariance matrix */
1.247 brouard 10802: /* We could also provide initial parameters values giving by simple logistic regression
10803: * only one way, that is without matrix product. We will have nlstate maximizations */
10804: /* for(i=1;i<nlstate;i++){ */
10805: /* /\*reducing xi for 1 to npar to 1 to ncovmodel; *\/ */
10806: /* mlikeli(ficres,p, ncovmodel, ncovmodel, nlstate, ftol, funcnoprod); */
10807: /* } */
1.126 brouard 10808: prwizard(ncovmodel, nlstate, ndeath, model, ficparo);
1.191 brouard 10809: printf(" You chose mle=-1, look at file %s for a template of covariance matrix \n",filereso);
10810: fprintf(ficlog," You chose mle=-1, look at file %s for a template of covariance matrix \n",filereso);
1.126 brouard 10811: free_ma3x(delti3,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
10812: fclose (ficparo);
10813: fclose (ficlog);
10814: goto end;
10815: exit(0);
1.220 brouard 10816: } else if(mle==-5) { /* Main Wizard */
1.126 brouard 10817: prwizard(ncovmodel, nlstate, ndeath, model, ficparo);
1.192 brouard 10818: printf(" You chose mle=-3, look at file %s for a template of covariance matrix \n",filereso);
10819: fprintf(ficlog," You chose mle=-3, look at file %s for a template of covariance matrix \n",filereso);
1.126 brouard 10820: param= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
10821: matcov=matrix(1,npar,1,npar);
1.203 brouard 10822: hess=matrix(1,npar,1,npar);
1.220 brouard 10823: } else{ /* Begin of mle != -1 or -5 */
1.145 brouard 10824: /* Read guessed parameters */
1.126 brouard 10825: /* Reads comments: lines beginning with '#' */
10826: while((c=getc(ficpar))=='#' && c!= EOF){
10827: ungetc(c,ficpar);
10828: fgets(line, MAXLINE, ficpar);
10829: numlinepar++;
1.141 brouard 10830: fputs(line,stdout);
1.126 brouard 10831: fputs(line,ficparo);
10832: fputs(line,ficlog);
10833: }
10834: ungetc(c,ficpar);
10835:
10836: param= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
1.251 brouard 10837: paramstart= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
1.126 brouard 10838: for(i=1; i <=nlstate; i++){
1.234 brouard 10839: j=0;
1.126 brouard 10840: for(jj=1; jj <=nlstate+ndeath; jj++){
1.234 brouard 10841: if(jj==i) continue;
10842: j++;
10843: fscanf(ficpar,"%1d%1d",&i1,&j1);
10844: if ((i1 != i) || (j1 != jj)){
10845: printf("Error in line parameters number %d, %1d%1d instead of %1d%1d \n \
1.126 brouard 10846: It might be a problem of design; if ncovcol and the model are correct\n \
10847: run imach with mle=-1 to get a correct template of the parameter file.\n",numlinepar, i,j, i1, j1);
1.234 brouard 10848: exit(1);
10849: }
10850: fprintf(ficparo,"%1d%1d",i1,j1);
10851: if(mle==1)
10852: printf("%1d%1d",i,jj);
10853: fprintf(ficlog,"%1d%1d",i,jj);
10854: for(k=1; k<=ncovmodel;k++){
10855: fscanf(ficpar," %lf",¶m[i][j][k]);
10856: if(mle==1){
10857: printf(" %lf",param[i][j][k]);
10858: fprintf(ficlog," %lf",param[i][j][k]);
10859: }
10860: else
10861: fprintf(ficlog," %lf",param[i][j][k]);
10862: fprintf(ficparo," %lf",param[i][j][k]);
10863: }
10864: fscanf(ficpar,"\n");
10865: numlinepar++;
10866: if(mle==1)
10867: printf("\n");
10868: fprintf(ficlog,"\n");
10869: fprintf(ficparo,"\n");
1.126 brouard 10870: }
10871: }
10872: fflush(ficlog);
1.234 brouard 10873:
1.251 brouard 10874: /* Reads parameters values */
1.126 brouard 10875: p=param[1][1];
1.251 brouard 10876: pstart=paramstart[1][1];
1.126 brouard 10877:
10878: /* Reads comments: lines beginning with '#' */
10879: while((c=getc(ficpar))=='#' && c!= EOF){
10880: ungetc(c,ficpar);
10881: fgets(line, MAXLINE, ficpar);
10882: numlinepar++;
1.141 brouard 10883: fputs(line,stdout);
1.126 brouard 10884: fputs(line,ficparo);
10885: fputs(line,ficlog);
10886: }
10887: ungetc(c,ficpar);
10888:
10889: for(i=1; i <=nlstate; i++){
10890: for(j=1; j <=nlstate+ndeath-1; j++){
1.234 brouard 10891: fscanf(ficpar,"%1d%1d",&i1,&j1);
10892: if ( (i1-i) * (j1-j) != 0){
10893: printf("Error in line parameters number %d, %1d%1d instead of %1d%1d \n",numlinepar, i,j, i1, j1);
10894: exit(1);
10895: }
10896: printf("%1d%1d",i,j);
10897: fprintf(ficparo,"%1d%1d",i1,j1);
10898: fprintf(ficlog,"%1d%1d",i1,j1);
10899: for(k=1; k<=ncovmodel;k++){
10900: fscanf(ficpar,"%le",&delti3[i][j][k]);
10901: printf(" %le",delti3[i][j][k]);
10902: fprintf(ficparo," %le",delti3[i][j][k]);
10903: fprintf(ficlog," %le",delti3[i][j][k]);
10904: }
10905: fscanf(ficpar,"\n");
10906: numlinepar++;
10907: printf("\n");
10908: fprintf(ficparo,"\n");
10909: fprintf(ficlog,"\n");
1.126 brouard 10910: }
10911: }
10912: fflush(ficlog);
1.234 brouard 10913:
1.145 brouard 10914: /* Reads covariance matrix */
1.126 brouard 10915: delti=delti3[1][1];
1.220 brouard 10916:
10917:
1.126 brouard 10918: /* 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 10919:
1.126 brouard 10920: /* Reads comments: lines beginning with '#' */
10921: while((c=getc(ficpar))=='#' && c!= EOF){
10922: ungetc(c,ficpar);
10923: fgets(line, MAXLINE, ficpar);
10924: numlinepar++;
1.141 brouard 10925: fputs(line,stdout);
1.126 brouard 10926: fputs(line,ficparo);
10927: fputs(line,ficlog);
10928: }
10929: ungetc(c,ficpar);
1.220 brouard 10930:
1.126 brouard 10931: matcov=matrix(1,npar,1,npar);
1.203 brouard 10932: hess=matrix(1,npar,1,npar);
1.131 brouard 10933: for(i=1; i <=npar; i++)
10934: for(j=1; j <=npar; j++) matcov[i][j]=0.;
1.220 brouard 10935:
1.194 brouard 10936: /* Scans npar lines */
1.126 brouard 10937: for(i=1; i <=npar; i++){
1.226 brouard 10938: count=fscanf(ficpar,"%1d%1d%d",&i1,&j1,&jk);
1.194 brouard 10939: if(count != 3){
1.226 brouard 10940: printf("Error! Error in parameter file %s at line %d after line starting with %1d%1d%1d\n\
1.194 brouard 10941: This is probably because your covariance matrix doesn't \n contain exactly %d lines corresponding to your model line '1+age+%s'.\n\
10942: Please run with mle=-1 to get a correct covariance matrix.\n",optionfile,numlinepar, i1,j1,jk, npar, model);
1.226 brouard 10943: fprintf(ficlog,"Error! Error in parameter file %s at line %d after line starting with %1d%1d%1d\n\
1.194 brouard 10944: This is probably because your covariance matrix doesn't \n contain exactly %d lines corresponding to your model line '1+age+%s'.\n\
10945: Please run with mle=-1 to get a correct covariance matrix.\n",optionfile,numlinepar, i1,j1,jk, npar, model);
1.226 brouard 10946: exit(1);
1.220 brouard 10947: }else{
1.226 brouard 10948: if(mle==1)
10949: printf("%1d%1d%d",i1,j1,jk);
10950: }
10951: fprintf(ficlog,"%1d%1d%d",i1,j1,jk);
10952: fprintf(ficparo,"%1d%1d%d",i1,j1,jk);
1.126 brouard 10953: for(j=1; j <=i; j++){
1.226 brouard 10954: fscanf(ficpar," %le",&matcov[i][j]);
10955: if(mle==1){
10956: printf(" %.5le",matcov[i][j]);
10957: }
10958: fprintf(ficlog," %.5le",matcov[i][j]);
10959: fprintf(ficparo," %.5le",matcov[i][j]);
1.126 brouard 10960: }
10961: fscanf(ficpar,"\n");
10962: numlinepar++;
10963: if(mle==1)
1.220 brouard 10964: printf("\n");
1.126 brouard 10965: fprintf(ficlog,"\n");
10966: fprintf(ficparo,"\n");
10967: }
1.194 brouard 10968: /* End of read covariance matrix npar lines */
1.126 brouard 10969: for(i=1; i <=npar; i++)
10970: for(j=i+1;j<=npar;j++)
1.226 brouard 10971: matcov[i][j]=matcov[j][i];
1.126 brouard 10972:
10973: if(mle==1)
10974: printf("\n");
10975: fprintf(ficlog,"\n");
10976:
10977: fflush(ficlog);
10978:
10979: /*-------- Rewriting parameter file ----------*/
10980: strcpy(rfileres,"r"); /* "Rparameterfile */
10981: strcat(rfileres,optionfilefiname); /* Parameter file first name*/
10982: strcat(rfileres,"."); /* */
10983: strcat(rfileres,optionfilext); /* Other files have txt extension */
10984: if((ficres =fopen(rfileres,"w"))==NULL) {
1.201 brouard 10985: printf("Problem writing new parameter file: %s\n", rfileres);goto end;
10986: fprintf(ficlog,"Problem writing new parameter file: %s\n", rfileres);goto end;
1.126 brouard 10987: }
10988: fprintf(ficres,"#%s\n",version);
10989: } /* End of mle != -3 */
1.218 brouard 10990:
1.186 brouard 10991: /* Main data
10992: */
1.126 brouard 10993: n= lastobs;
10994: num=lvector(1,n);
10995: moisnais=vector(1,n);
10996: annais=vector(1,n);
10997: moisdc=vector(1,n);
10998: andc=vector(1,n);
1.220 brouard 10999: weight=vector(1,n);
1.126 brouard 11000: agedc=vector(1,n);
11001: cod=ivector(1,n);
1.220 brouard 11002: for(i=1;i<=n;i++){
1.234 brouard 11003: num[i]=0;
11004: moisnais[i]=0;
11005: annais[i]=0;
11006: moisdc[i]=0;
11007: andc[i]=0;
11008: agedc[i]=0;
11009: cod[i]=0;
11010: weight[i]=1.0; /* Equal weights, 1 by default */
11011: }
1.126 brouard 11012: mint=matrix(1,maxwav,1,n);
11013: anint=matrix(1,maxwav,1,n);
1.131 brouard 11014: s=imatrix(1,maxwav+1,1,n); /* s[i][j] health state for wave i and individual j */
1.126 brouard 11015: tab=ivector(1,NCOVMAX);
1.144 brouard 11016: ncodemax=ivector(1,NCOVMAX); /* Number of code per covariate; if O and 1 only, 2**ncov; V1+V2+V3+V4=>16 */
1.192 brouard 11017: 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 11018:
1.136 brouard 11019: /* Reads data from file datafile */
11020: if (readdata(datafile, firstobs, lastobs, &imx)==1)
11021: goto end;
11022:
11023: /* Calculation of the number of parameters from char model */
1.234 brouard 11024: /* modelsav=V2+V1+V4+age*V3 strb=age*V3 stra=V2+V1+V4
1.137 brouard 11025: k=4 (age*V3) Tvar[k=4]= 3 (from V3) Tag[cptcovage=1]=4
11026: k=3 V4 Tvar[k=3]= 4 (from V4)
11027: k=2 V1 Tvar[k=2]= 1 (from V1)
11028: k=1 Tvar[1]=2 (from V2)
1.234 brouard 11029: */
11030:
11031: Tvar=ivector(1,NCOVMAX); /* Was 15 changed to NCOVMAX. */
11032: TvarsDind=ivector(1,NCOVMAX); /* */
11033: TvarsD=ivector(1,NCOVMAX); /* */
11034: TvarsQind=ivector(1,NCOVMAX); /* */
11035: TvarsQ=ivector(1,NCOVMAX); /* */
1.232 brouard 11036: TvarF=ivector(1,NCOVMAX); /* */
11037: TvarFind=ivector(1,NCOVMAX); /* */
11038: TvarV=ivector(1,NCOVMAX); /* */
11039: TvarVind=ivector(1,NCOVMAX); /* */
11040: TvarA=ivector(1,NCOVMAX); /* */
11041: TvarAind=ivector(1,NCOVMAX); /* */
1.231 brouard 11042: TvarFD=ivector(1,NCOVMAX); /* */
11043: TvarFDind=ivector(1,NCOVMAX); /* */
11044: TvarFQ=ivector(1,NCOVMAX); /* */
11045: TvarFQind=ivector(1,NCOVMAX); /* */
11046: TvarVD=ivector(1,NCOVMAX); /* */
11047: TvarVDind=ivector(1,NCOVMAX); /* */
11048: TvarVQ=ivector(1,NCOVMAX); /* */
11049: TvarVQind=ivector(1,NCOVMAX); /* */
11050:
1.230 brouard 11051: Tvalsel=vector(1,NCOVMAX); /* */
1.233 brouard 11052: Tvarsel=ivector(1,NCOVMAX); /* */
1.226 brouard 11053: Typevar=ivector(-1,NCOVMAX); /* -1 to 2 */
11054: Fixed=ivector(-1,NCOVMAX); /* -1 to 3 */
11055: Dummy=ivector(-1,NCOVMAX); /* -1 to 3 */
1.137 brouard 11056: /* V2+V1+V4+age*V3 is a model with 4 covariates (3 plus signs).
11057: For each model-covariate stores the data-covariate id. Tvar[1]=2, Tvar[2]=1, Tvar[3]=4,
11058: Tvar[4=age*V3] is 3 and 'age' is recorded in Tage.
11059: */
11060: /* For model-covariate k tells which data-covariate to use but
11061: because this model-covariate is a construction we invent a new column
11062: ncovcol + k1
11063: If already ncovcol=4 and model=V2+V1+V1*V4+age*V3
11064: Tvar[3=V1*V4]=4+1 etc */
1.227 brouard 11065: Tprod=ivector(1,NCOVMAX); /* Gives the k position of the k1 product */
11066: Tposprod=ivector(1,NCOVMAX); /* Gives the k1 product from the k position */
1.137 brouard 11067: /* Tprod[k1=1]=3(=V1*V4) for V2+V1+V1*V4+age*V3
11068: if V2+V1+V1*V4+age*V3+V3*V2 TProd[k1=2]=5 (V3*V2)
1.227 brouard 11069: Tposprod[k]=k1 , Tposprod[3]=1, Tposprod[5]=2
1.137 brouard 11070: */
1.145 brouard 11071: Tvaraff=ivector(1,NCOVMAX); /* Unclear */
11072: 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 11073: * For V3*V2 (in V2+V1+V1*V4+age*V3+V3*V2), V3*V2 position is 2nd.
11074: * Tvard[k1=2][1]=3 (V3) Tvard[k1=2][2]=2(V2) */
1.145 brouard 11075: Tage=ivector(1,NCOVMAX); /* Gives the covariate id of covariates associated with age: V2 + V1 + age*V4 + V3*age
1.137 brouard 11076: 4 covariates (3 plus signs)
11077: Tage[1=V3*age]= 4; Tage[2=age*V4] = 3
11078: */
1.230 brouard 11079: Tmodelind=ivector(1,NCOVMAX);/** gives the k model position of an
1.227 brouard 11080: * individual dummy, fixed or varying:
11081: * Tmodelind[Tvaraff[3]]=9,Tvaraff[1]@9={4,
11082: * 3, 1, 0, 0, 0, 0, 0, 0},
1.230 brouard 11083: * model=V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 ,
11084: * V1 df, V2 qf, V3 & V4 dv, V5 qv
11085: * Tmodelind[1]@9={9,0,3,2,}*/
11086: TmodelInvind=ivector(1,NCOVMAX); /* TmodelInvind=Tvar[k]- ncovcol-nqv={5-2-1=2,*/
11087: TmodelInvQind=ivector(1,NCOVMAX);/** gives the k model position of an
1.228 brouard 11088: * individual quantitative, fixed or varying:
11089: * Tmodelqind[1]=1,Tvaraff[1]@9={4,
11090: * 3, 1, 0, 0, 0, 0, 0, 0},
11091: * model=V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1*/
1.186 brouard 11092: /* Main decodemodel */
11093:
1.187 brouard 11094:
1.223 brouard 11095: if(decodemodel(model, lastobs) == 1) /* In order to get Tvar[k] V4+V3+V5 p Tvar[1]@3 = {4, 3, 5}*/
1.136 brouard 11096: goto end;
11097:
1.137 brouard 11098: if((double)(lastobs-imx)/(double)imx > 1.10){
11099: nbwarn++;
11100: 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);
11101: 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);
11102: }
1.136 brouard 11103: /* if(mle==1){*/
1.137 brouard 11104: if (weightopt != 1) { /* Maximisation without weights. We can have weights different from 1 but want no weight*/
11105: for(i=1;i<=imx;i++) weight[i]=1.0; /* changed to imx */
1.136 brouard 11106: }
11107:
11108: /*-calculation of age at interview from date of interview and age at death -*/
11109: agev=matrix(1,maxwav,1,imx);
11110:
11111: if(calandcheckages(imx, maxwav, &agemin, &agemax, &nberr, &nbwarn) == 1)
11112: goto end;
11113:
1.126 brouard 11114:
1.136 brouard 11115: agegomp=(int)agemin;
11116: free_vector(moisnais,1,n);
11117: free_vector(annais,1,n);
1.126 brouard 11118: /* free_matrix(mint,1,maxwav,1,n);
11119: free_matrix(anint,1,maxwav,1,n);*/
1.215 brouard 11120: /* free_vector(moisdc,1,n); */
11121: /* free_vector(andc,1,n); */
1.145 brouard 11122: /* */
11123:
1.126 brouard 11124: wav=ivector(1,imx);
1.214 brouard 11125: /* dh=imatrix(1,lastpass-firstpass+1,1,imx); */
11126: /* bh=imatrix(1,lastpass-firstpass+1,1,imx); */
11127: /* mw=imatrix(1,lastpass-firstpass+1,1,imx); */
11128: 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.*/
11129: bh=imatrix(1,lastpass-firstpass+2,1,imx);
11130: mw=imatrix(1,lastpass-firstpass+2,1,imx);
1.126 brouard 11131:
11132: /* Concatenates waves */
1.214 brouard 11133: /* Concatenates waves: wav[i] is the number of effective (useful waves) of individual i.
11134: Death is a valid wave (if date is known).
11135: mw[mi][i] is the number of (mi=1 to wav[i]) effective wave out of mi of individual i
11136: dh[m][i] or dh[mw[mi][i]][i] is the delay between two effective waves m=mw[mi][i]
11137: and mw[mi+1][i]. dh depends on stepm.
11138: */
11139:
1.126 brouard 11140: concatwav(wav, dh, bh, mw, s, agedc, agev, firstpass, lastpass, imx, nlstate, stepm);
1.248 brouard 11141: /* Concatenates waves */
1.145 brouard 11142:
1.215 brouard 11143: free_vector(moisdc,1,n);
11144: free_vector(andc,1,n);
11145:
1.126 brouard 11146: /* Routine tricode is to calculate cptcoveff (real number of unique covariates) and to associate covariable number and modality */
11147: nbcode=imatrix(0,NCOVMAX,0,NCOVMAX);
11148: ncodemax[1]=1;
1.145 brouard 11149: Ndum =ivector(-1,NCOVMAX);
1.225 brouard 11150: cptcoveff=0;
1.220 brouard 11151: if (ncovmodel-nagesqr > 2 ){ /* That is if covariate other than cst, age and age*age */
11152: tricode(&cptcoveff,Tvar,nbcode,imx, Ndum); /**< Fills nbcode[Tvar[j]][l]; */
1.227 brouard 11153: }
11154:
11155: ncovcombmax=pow(2,cptcoveff);
11156: invalidvarcomb=ivector(1, ncovcombmax);
11157: for(i=1;i<ncovcombmax;i++)
11158: invalidvarcomb[i]=0;
11159:
1.211 brouard 11160: /* Nbcode gives the value of the lth modality (currently 1 to 2) of jth covariate, in
1.186 brouard 11161: V2+V1*age, there are 3 covariates Tvar[2]=1 (V1).*/
1.211 brouard 11162: /* 1 to ncodemax[j] which is the maximum value of this jth covariate */
1.227 brouard 11163:
1.200 brouard 11164: /* codtab=imatrix(1,100,1,10);*/ /* codtab[h,k]=( (h-1) - mod(k-1,2**(k-1) )/2**(k-1) */
1.198 brouard 11165: /*printf(" codtab[1,1],codtab[100,10]=%d,%d\n", codtab[1][1],codtabm(100,10));*/
1.186 brouard 11166: /* codtab gives the value 1 or 2 of the hth combination of k covariates (1 or 2).*/
1.211 brouard 11167: /* nbcode[Tvaraff[j]][codtabm(h,j)]) : if there are only 2 modalities for a covariate j,
11168: * codtabm(h,j) gives its value classified at position h and nbcode gives how it is coded
11169: * (currently 0 or 1) in the data.
11170: * In a loop on h=1 to 2**k, and a loop on j (=1 to k), we get the value of
11171: * corresponding modality (h,j).
11172: */
11173:
1.145 brouard 11174: h=0;
11175: /*if (cptcovn > 0) */
1.126 brouard 11176: m=pow(2,cptcoveff);
11177:
1.144 brouard 11178: /**< codtab(h,k) k = codtab[h,k]=( (h-1) - mod(k-1,2**(k-1) )/2**(k-1) + 1
1.211 brouard 11179: * For k=4 covariates, h goes from 1 to m=2**k
11180: * codtabm(h,k)= (1 & (h-1) >> (k-1)) + 1;
11181: * #define codtabm(h,k) (1 & (h-1) >> (k-1))+1
1.186 brouard 11182: * h\k 1 2 3 4
1.143 brouard 11183: *______________________________
11184: * 1 i=1 1 i=1 1 i=1 1 i=1 1
11185: * 2 2 1 1 1
11186: * 3 i=2 1 2 1 1
11187: * 4 2 2 1 1
11188: * 5 i=3 1 i=2 1 2 1
11189: * 6 2 1 2 1
11190: * 7 i=4 1 2 2 1
11191: * 8 2 2 2 1
1.197 brouard 11192: * 9 i=5 1 i=3 1 i=2 1 2
11193: * 10 2 1 1 2
11194: * 11 i=6 1 2 1 2
11195: * 12 2 2 1 2
11196: * 13 i=7 1 i=4 1 2 2
11197: * 14 2 1 2 2
11198: * 15 i=8 1 2 2 2
11199: * 16 2 2 2 2
1.143 brouard 11200: */
1.212 brouard 11201: /* How to do the opposite? From combination h (=1 to 2**k) how to get the value on the covariates? */
1.211 brouard 11202: /* from h=5 and m, we get then number of covariates k=log(m)/log(2)=4
11203: * and the value of each covariate?
11204: * V1=1, V2=1, V3=2, V4=1 ?
11205: * h-1=4 and 4 is 0100 or reverse 0010, and +1 is 1121 ok.
11206: * h=6, 6-1=5, 5 is 0101, 1010, 2121, V1=2nd, V2=1st, V3=2nd, V4=1st.
11207: * In order to get the real value in the data, we use nbcode
11208: * nbcode[Tvar[3][2nd]]=1 and nbcode[Tvar[4][1]]=0
11209: * We are keeping this crazy system in order to be able (in the future?)
11210: * to have more than 2 values (0 or 1) for a covariate.
11211: * #define codtabm(h,k) (1 & (h-1) >> (k-1))+1
11212: * h=6, k=2? h-1=5=0101, reverse 1010, +1=2121, k=2nd position: value is 1: codtabm(6,2)=1
11213: * bbbbbbbb
11214: * 76543210
11215: * h-1 00000101 (6-1=5)
1.219 brouard 11216: *(h-1)>>(k-1)= 00000010 >> (2-1) = 1 right shift
1.211 brouard 11217: * &
11218: * 1 00000001 (1)
1.219 brouard 11219: * 00000000 = 1 & ((h-1) >> (k-1))
11220: * +1= 00000001 =1
1.211 brouard 11221: *
11222: * h=14, k=3 => h'=h-1=13, k'=k-1=2
11223: * h' 1101 =2^3+2^2+0x2^1+2^0
11224: * >>k' 11
11225: * & 00000001
11226: * = 00000001
11227: * +1 = 00000010=2 = codtabm(14,3)
11228: * Reverse h=6 and m=16?
11229: * cptcoveff=log(16)/log(2)=4 covariate: 6-1=5=0101 reversed=1010 +1=2121 =>V1=2, V2=1, V3=2, V4=1.
11230: * for (j=1 to cptcoveff) Vj=decodtabm(j,h,cptcoveff)
11231: * decodtabm(h,j,cptcoveff)= (((h-1) >> (j-1)) & 1) +1
11232: * decodtabm(h,j,cptcoveff)= (h <= (1<<cptcoveff)?(((h-1) >> (j-1)) & 1) +1 : -1)
11233: * V3=decodtabm(14,3,2**4)=2
11234: * h'=13 1101 =2^3+2^2+0x2^1+2^0
11235: *(h-1) >> (j-1) 0011 =13 >> 2
11236: * &1 000000001
11237: * = 000000001
11238: * +1= 000000010 =2
11239: * 2211
11240: * V1=1+1, V2=0+1, V3=1+1, V4=1+1
11241: * V3=2
1.220 brouard 11242: * codtabm and decodtabm are identical
1.211 brouard 11243: */
11244:
1.145 brouard 11245:
11246: free_ivector(Ndum,-1,NCOVMAX);
11247:
11248:
1.126 brouard 11249:
1.186 brouard 11250: /* Initialisation of ----------- gnuplot -------------*/
1.126 brouard 11251: strcpy(optionfilegnuplot,optionfilefiname);
11252: if(mle==-3)
1.201 brouard 11253: strcat(optionfilegnuplot,"-MORT_");
1.126 brouard 11254: strcat(optionfilegnuplot,".gp");
11255:
11256: if((ficgp=fopen(optionfilegnuplot,"w"))==NULL) {
11257: printf("Problem with file %s",optionfilegnuplot);
11258: }
11259: else{
1.204 brouard 11260: fprintf(ficgp,"\n# IMaCh-%s\n", version);
1.126 brouard 11261: fprintf(ficgp,"# %s\n", optionfilegnuplot);
1.141 brouard 11262: //fprintf(ficgp,"set missing 'NaNq'\n");
11263: fprintf(ficgp,"set datafile missing 'NaNq'\n");
1.126 brouard 11264: }
11265: /* fclose(ficgp);*/
1.186 brouard 11266:
11267:
11268: /* Initialisation of --------- index.htm --------*/
1.126 brouard 11269:
11270: strcpy(optionfilehtm,optionfilefiname); /* Main html file */
11271: if(mle==-3)
1.201 brouard 11272: strcat(optionfilehtm,"-MORT_");
1.126 brouard 11273: strcat(optionfilehtm,".htm");
11274: if((fichtm=fopen(optionfilehtm,"w"))==NULL) {
1.131 brouard 11275: printf("Problem with %s \n",optionfilehtm);
11276: exit(0);
1.126 brouard 11277: }
11278:
11279: strcpy(optionfilehtmcov,optionfilefiname); /* Only for matrix of covariance */
11280: strcat(optionfilehtmcov,"-cov.htm");
11281: if((fichtmcov=fopen(optionfilehtmcov,"w"))==NULL) {
11282: printf("Problem with %s \n",optionfilehtmcov), exit(0);
11283: }
11284: else{
11285: fprintf(fichtmcov,"<html><head>\n<title>IMaCh Cov %s</title></head>\n <body><font size=\"2\">%s <br> %s</font> \
11286: <hr size=\"2\" color=\"#EC5E5E\"> \n\
1.204 brouard 11287: Title=%s <br>Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s<br>\n",\
1.126 brouard 11288: optionfilehtmcov,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model);
11289: }
11290:
1.213 brouard 11291: 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 11292: <hr size=\"2\" color=\"#EC5E5E\"> \n\
11293: <font size=\"2\">IMaCh-%s <br> %s</font> \
1.126 brouard 11294: <hr size=\"2\" color=\"#EC5E5E\"> \n\
1.204 brouard 11295: Title=%s <br>Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s<br>\n\
1.126 brouard 11296: \n\
11297: <hr size=\"2\" color=\"#EC5E5E\">\
11298: <ul><li><h4>Parameter files</h4>\n\
11299: - Parameter file: <a href=\"%s.%s\">%s.%s</a><br>\n\
11300: - Copy of the parameter file: <a href=\"o%s\">o%s</a><br>\n\
11301: - Log file of the run: <a href=\"%s\">%s</a><br>\n\
11302: - Gnuplot file name: <a href=\"%s\">%s</a><br>\n\
11303: - Date and time at start: %s</ul>\n",\
11304: optionfilehtm,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model,\
11305: optionfilefiname,optionfilext,optionfilefiname,optionfilext,\
11306: fileres,fileres,\
11307: filelog,filelog,optionfilegnuplot,optionfilegnuplot,strstart);
11308: fflush(fichtm);
11309:
11310: strcpy(pathr,path);
11311: strcat(pathr,optionfilefiname);
1.184 brouard 11312: #ifdef WIN32
11313: _chdir(optionfilefiname); /* Move to directory named optionfile */
11314: #else
1.126 brouard 11315: chdir(optionfilefiname); /* Move to directory named optionfile */
1.184 brouard 11316: #endif
11317:
1.126 brouard 11318:
1.220 brouard 11319: /* Calculates basic frequencies. Computes observed prevalence at single age
11320: and for any valid combination of covariates
1.126 brouard 11321: and prints on file fileres'p'. */
1.251 brouard 11322: freqsummary(fileres, p, pstart, agemin, agemax, s, agev, nlstate, imx, Tvaraff, invalidvarcomb, nbcode, ncodemax,mint,anint,strstart, \
1.227 brouard 11323: firstpass, lastpass, stepm, weightopt, model);
1.126 brouard 11324:
11325: fprintf(fichtm,"\n");
11326: fprintf(fichtm,"<br>Total number of observations=%d <br>\n\
11327: Youngest age at first (selected) pass %.2f, oldest age %.2f<br>\n\
11328: Interval (in months) between two waves: Min=%d Max=%d Mean=%.2lf<br>\n",\
11329: imx,agemin,agemax,jmin,jmax,jmean);
11330: pmmij= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
1.268 ! brouard 11331: oldms= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
! 11332: newms= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
! 11333: savms= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
! 11334: oldm=oldms; newm=newms; savm=savms; /* Keeps fixed addresses to free */
1.218 brouard 11335:
1.126 brouard 11336: /* For Powell, parameters are in a vector p[] starting at p[1]
11337: so we point p on param[1][1] so that p[1] maps on param[1][1][1] */
11338: p=param[1][1]; /* *(*(*(param +1)+1)+0) */
11339:
11340: globpr=0; /* To get the number ipmx of contributions and the sum of weights*/
1.186 brouard 11341: /* For mortality only */
1.126 brouard 11342: if (mle==-3){
1.136 brouard 11343: ximort=matrix(1,NDIM,1,NDIM);
1.248 brouard 11344: for(i=1;i<=NDIM;i++)
11345: for(j=1;j<=NDIM;j++)
11346: ximort[i][j]=0.;
1.186 brouard 11347: /* ximort=gsl_matrix_alloc(1,NDIM,1,NDIM); */
1.126 brouard 11348: cens=ivector(1,n);
11349: ageexmed=vector(1,n);
11350: agecens=vector(1,n);
11351: dcwave=ivector(1,n);
1.223 brouard 11352:
1.126 brouard 11353: for (i=1; i<=imx; i++){
11354: dcwave[i]=-1;
11355: for (m=firstpass; m<=lastpass; m++)
1.226 brouard 11356: if (s[m][i]>nlstate) {
11357: dcwave[i]=m;
11358: /* printf("i=%d j=%d s=%d dcwave=%d\n",i,j, s[j][i],dcwave[i]);*/
11359: break;
11360: }
1.126 brouard 11361: }
1.226 brouard 11362:
1.126 brouard 11363: for (i=1; i<=imx; i++) {
11364: if (wav[i]>0){
1.226 brouard 11365: ageexmed[i]=agev[mw[1][i]][i];
11366: j=wav[i];
11367: agecens[i]=1.;
11368:
11369: if (ageexmed[i]> 1 && wav[i] > 0){
11370: agecens[i]=agev[mw[j][i]][i];
11371: cens[i]= 1;
11372: }else if (ageexmed[i]< 1)
11373: cens[i]= -1;
11374: if (agedc[i]< AGESUP && agedc[i]>1 && dcwave[i]>firstpass && dcwave[i]<=lastpass)
11375: cens[i]=0 ;
1.126 brouard 11376: }
11377: else cens[i]=-1;
11378: }
11379:
11380: for (i=1;i<=NDIM;i++) {
11381: for (j=1;j<=NDIM;j++)
1.226 brouard 11382: ximort[i][j]=(i == j ? 1.0 : 0.0);
1.126 brouard 11383: }
11384:
1.145 brouard 11385: /*p[1]=0.0268; p[NDIM]=0.083;*/
1.126 brouard 11386: /*printf("%lf %lf", p[1], p[2]);*/
11387:
11388:
1.136 brouard 11389: #ifdef GSL
11390: printf("GSL optimization\n"); fprintf(ficlog,"Powell\n");
1.162 brouard 11391: #else
1.126 brouard 11392: printf("Powell\n"); fprintf(ficlog,"Powell\n");
1.136 brouard 11393: #endif
1.201 brouard 11394: strcpy(filerespow,"POW-MORT_");
11395: strcat(filerespow,fileresu);
1.126 brouard 11396: if((ficrespow=fopen(filerespow,"w"))==NULL) {
11397: printf("Problem with resultfile: %s\n", filerespow);
11398: fprintf(ficlog,"Problem with resultfile: %s\n", filerespow);
11399: }
1.136 brouard 11400: #ifdef GSL
11401: fprintf(ficrespow,"# GSL optimization\n# iter -2*LL");
1.162 brouard 11402: #else
1.126 brouard 11403: fprintf(ficrespow,"# Powell\n# iter -2*LL");
1.136 brouard 11404: #endif
1.126 brouard 11405: /* for (i=1;i<=nlstate;i++)
11406: for(j=1;j<=nlstate+ndeath;j++)
11407: if(j!=i)fprintf(ficrespow," p%1d%1d",i,j);
11408: */
11409: fprintf(ficrespow,"\n");
1.136 brouard 11410: #ifdef GSL
11411: /* gsl starts here */
11412: T = gsl_multimin_fminimizer_nmsimplex;
11413: gsl_multimin_fminimizer *sfm = NULL;
11414: gsl_vector *ss, *x;
11415: gsl_multimin_function minex_func;
11416:
11417: /* Initial vertex size vector */
11418: ss = gsl_vector_alloc (NDIM);
11419:
11420: if (ss == NULL){
11421: GSL_ERROR_VAL ("failed to allocate space for ss", GSL_ENOMEM, 0);
11422: }
11423: /* Set all step sizes to 1 */
11424: gsl_vector_set_all (ss, 0.001);
11425:
11426: /* Starting point */
1.126 brouard 11427:
1.136 brouard 11428: x = gsl_vector_alloc (NDIM);
11429:
11430: if (x == NULL){
11431: gsl_vector_free(ss);
11432: GSL_ERROR_VAL ("failed to allocate space for x", GSL_ENOMEM, 0);
11433: }
11434:
11435: /* Initialize method and iterate */
11436: /* p[1]=0.0268; p[NDIM]=0.083; */
1.186 brouard 11437: /* gsl_vector_set(x, 0, 0.0268); */
11438: /* gsl_vector_set(x, 1, 0.083); */
1.136 brouard 11439: gsl_vector_set(x, 0, p[1]);
11440: gsl_vector_set(x, 1, p[2]);
11441:
11442: minex_func.f = &gompertz_f;
11443: minex_func.n = NDIM;
11444: minex_func.params = (void *)&p; /* ??? */
11445:
11446: sfm = gsl_multimin_fminimizer_alloc (T, NDIM);
11447: gsl_multimin_fminimizer_set (sfm, &minex_func, x, ss);
11448:
11449: printf("Iterations beginning .....\n\n");
11450: printf("Iter. # Intercept Slope -Log Likelihood Simplex size\n");
11451:
11452: iteri=0;
11453: while (rval == GSL_CONTINUE){
11454: iteri++;
11455: status = gsl_multimin_fminimizer_iterate(sfm);
11456:
11457: if (status) printf("error: %s\n", gsl_strerror (status));
11458: fflush(0);
11459:
11460: if (status)
11461: break;
11462:
11463: rval = gsl_multimin_test_size (gsl_multimin_fminimizer_size (sfm), 1e-6);
11464: ssval = gsl_multimin_fminimizer_size (sfm);
11465:
11466: if (rval == GSL_SUCCESS)
11467: printf ("converged to a local maximum at\n");
11468:
11469: printf("%5d ", iteri);
11470: for (it = 0; it < NDIM; it++){
11471: printf ("%10.5f ", gsl_vector_get (sfm->x, it));
11472: }
11473: printf("f() = %-10.5f ssize = %.7f\n", sfm->fval, ssval);
11474: }
11475:
11476: printf("\n\n Please note: Program should be run many times with varying starting points to detemine global maximum\n\n");
11477:
11478: gsl_vector_free(x); /* initial values */
11479: gsl_vector_free(ss); /* inital step size */
11480: for (it=0; it<NDIM; it++){
11481: p[it+1]=gsl_vector_get(sfm->x,it);
11482: fprintf(ficrespow," %.12lf", p[it]);
11483: }
11484: gsl_multimin_fminimizer_free (sfm); /* p *(sfm.x.data) et p *(sfm.x.data+1) */
11485: #endif
11486: #ifdef POWELL
11487: powell(p,ximort,NDIM,ftol,&iter,&fret,gompertz);
11488: #endif
1.126 brouard 11489: fclose(ficrespow);
11490:
1.203 brouard 11491: hesscov(matcov, hess, p, NDIM, delti, 1e-4, gompertz);
1.126 brouard 11492:
11493: for(i=1; i <=NDIM; i++)
11494: for(j=i+1;j<=NDIM;j++)
1.220 brouard 11495: matcov[i][j]=matcov[j][i];
1.126 brouard 11496:
11497: printf("\nCovariance matrix\n ");
1.203 brouard 11498: fprintf(ficlog,"\nCovariance matrix\n ");
1.126 brouard 11499: for(i=1; i <=NDIM; i++) {
11500: for(j=1;j<=NDIM;j++){
1.220 brouard 11501: printf("%f ",matcov[i][j]);
11502: fprintf(ficlog,"%f ",matcov[i][j]);
1.126 brouard 11503: }
1.203 brouard 11504: printf("\n "); fprintf(ficlog,"\n ");
1.126 brouard 11505: }
11506:
11507: printf("iter=%d MLE=%f Eq=%lf*exp(%lf*(age-%d))\n",iter,-gompertz(p),p[1],p[2],agegomp);
1.193 brouard 11508: for (i=1;i<=NDIM;i++) {
1.126 brouard 11509: printf("%f [%f ; %f]\n",p[i],p[i]-2*sqrt(matcov[i][i]),p[i]+2*sqrt(matcov[i][i]));
1.193 brouard 11510: fprintf(ficlog,"%f [%f ; %f]\n",p[i],p[i]-2*sqrt(matcov[i][i]),p[i]+2*sqrt(matcov[i][i]));
11511: }
1.126 brouard 11512: lsurv=vector(1,AGESUP);
11513: lpop=vector(1,AGESUP);
11514: tpop=vector(1,AGESUP);
11515: lsurv[agegomp]=100000;
11516:
11517: for (k=agegomp;k<=AGESUP;k++) {
11518: agemortsup=k;
11519: if (p[1]*exp(p[2]*(k-agegomp))>1) break;
11520: }
11521:
11522: for (k=agegomp;k<agemortsup;k++)
11523: lsurv[k+1]=lsurv[k]-lsurv[k]*(p[1]*exp(p[2]*(k-agegomp)));
11524:
11525: for (k=agegomp;k<agemortsup;k++){
11526: lpop[k]=(lsurv[k]+lsurv[k+1])/2.;
11527: sumlpop=sumlpop+lpop[k];
11528: }
11529:
11530: tpop[agegomp]=sumlpop;
11531: for (k=agegomp;k<(agemortsup-3);k++){
11532: /* tpop[k+1]=2;*/
11533: tpop[k+1]=tpop[k]-lpop[k];
11534: }
11535:
11536:
11537: printf("\nAge lx qx dx Lx Tx e(x)\n");
11538: for (k=agegomp;k<(agemortsup-2);k++)
11539: 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]);
11540:
11541:
11542: replace_back_to_slash(pathc,pathcd); /* Even gnuplot wants a / */
1.220 brouard 11543: ageminpar=50;
11544: agemaxpar=100;
1.194 brouard 11545: if(ageminpar == AGEOVERFLOW ||agemaxpar == AGEOVERFLOW){
11546: printf("Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
11547: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
11548: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
11549: fprintf(ficlog,"Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
11550: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
11551: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
1.220 brouard 11552: }else{
11553: printf("Warning! ageminpar %f and agemaxpar %f have been fixed because for simplification until it is fixed...\n\n",ageminpar,agemaxpar);
11554: 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 11555: printinggnuplotmort(fileresu, optionfilefiname,ageminpar,agemaxpar,fage, pathc,p);
1.220 brouard 11556: }
1.201 brouard 11557: printinghtmlmort(fileresu,title,datafile, firstpass, lastpass, \
1.126 brouard 11558: stepm, weightopt,\
11559: model,imx,p,matcov,agemortsup);
11560:
11561: free_vector(lsurv,1,AGESUP);
11562: free_vector(lpop,1,AGESUP);
11563: free_vector(tpop,1,AGESUP);
1.220 brouard 11564: free_matrix(ximort,1,NDIM,1,NDIM);
1.136 brouard 11565: free_ivector(cens,1,n);
11566: free_vector(agecens,1,n);
11567: free_ivector(dcwave,1,n);
1.220 brouard 11568: #ifdef GSL
1.136 brouard 11569: #endif
1.186 brouard 11570: } /* Endof if mle==-3 mortality only */
1.205 brouard 11571: /* Standard */
11572: else{ /* For mle !=- 3, could be 0 or 1 or 4 etc. */
11573: globpr=0;/* Computes sum of likelihood for globpr=1 and funcone */
11574: /* Computes likelihood for initial parameters, uses funcone to compute gpimx and gsw */
1.132 brouard 11575: likelione(ficres, p, npar, nlstate, &globpr, &ipmx, &sw, &fretone, funcone); /* Prints the contributions to the likelihood */
1.126 brouard 11576: printf("First Likeli=%12.6f ipmx=%ld sw=%12.6f",fretone,ipmx,sw);
11577: for (k=1; k<=npar;k++)
11578: printf(" %d %8.5f",k,p[k]);
11579: printf("\n");
1.205 brouard 11580: if(mle>=1){ /* Could be 1 or 2, Real Maximization */
11581: /* mlikeli uses func not funcone */
1.247 brouard 11582: /* for(i=1;i<nlstate;i++){ */
11583: /* /\*reducing xi for 1 to npar to 1 to ncovmodel; *\/ */
11584: /* mlikeli(ficres,p, ncovmodel, ncovmodel, nlstate, ftol, funcnoprod); */
11585: /* } */
1.205 brouard 11586: mlikeli(ficres,p, npar, ncovmodel, nlstate, ftol, func);
11587: }
11588: if(mle==0) {/* No optimization, will print the likelihoods for the datafile */
11589: globpr=0;/* Computes sum of likelihood for globpr=1 and funcone */
11590: /* Computes likelihood for initial parameters, uses funcone to compute gpimx and gsw */
11591: likelione(ficres, p, npar, nlstate, &globpr, &ipmx, &sw, &fretone, funcone); /* Prints the contributions to the likelihood */
11592: }
11593: globpr=1; /* again, to print the individual contributions using computed gpimx and gsw */
1.126 brouard 11594: likelione(ficres, p, npar, nlstate, &globpr, &ipmx, &sw, &fretone, funcone); /* Prints the contributions to the likelihood */
11595: printf("Second Likeli=%12.6f ipmx=%ld sw=%12.6f",fretone,ipmx,sw);
11596: for (k=1; k<=npar;k++)
11597: printf(" %d %8.5f",k,p[k]);
11598: printf("\n");
11599:
11600: /*--------- results files --------------*/
1.224 brouard 11601: 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 11602:
11603:
11604: fprintf(ficres,"# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
11605: printf("# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
11606: fprintf(ficlog,"# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
11607: for(i=1,jk=1; i <=nlstate; i++){
11608: for(k=1; k <=(nlstate+ndeath); k++){
1.225 brouard 11609: if (k != i) {
11610: printf("%d%d ",i,k);
11611: fprintf(ficlog,"%d%d ",i,k);
11612: fprintf(ficres,"%1d%1d ",i,k);
11613: for(j=1; j <=ncovmodel; j++){
11614: printf("%12.7f ",p[jk]);
11615: fprintf(ficlog,"%12.7f ",p[jk]);
11616: fprintf(ficres,"%12.7f ",p[jk]);
11617: jk++;
11618: }
11619: printf("\n");
11620: fprintf(ficlog,"\n");
11621: fprintf(ficres,"\n");
11622: }
1.126 brouard 11623: }
11624: }
1.203 brouard 11625: if(mle != 0){
11626: /* Computing hessian and covariance matrix only at a peak of the Likelihood, that is after optimization */
1.126 brouard 11627: ftolhess=ftol; /* Usually correct */
1.203 brouard 11628: hesscov(matcov, hess, p, npar, delti, ftolhess, func);
11629: 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");
11630: 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");
11631: for(i=1,jk=1; i <=nlstate; i++){
1.225 brouard 11632: for(k=1; k <=(nlstate+ndeath); k++){
11633: if (k != i) {
11634: printf("%d%d ",i,k);
11635: fprintf(ficlog,"%d%d ",i,k);
11636: for(j=1; j <=ncovmodel; j++){
11637: 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]));
11638: 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]));
11639: jk++;
11640: }
11641: printf("\n");
11642: fprintf(ficlog,"\n");
11643: }
11644: }
1.193 brouard 11645: }
1.203 brouard 11646: } /* end of hesscov and Wald tests */
1.225 brouard 11647:
1.203 brouard 11648: /* */
1.126 brouard 11649: fprintf(ficres,"# Scales (for hessian or gradient estimation)\n");
11650: printf("# Scales (for hessian or gradient estimation)\n");
11651: fprintf(ficlog,"# Scales (for hessian or gradient estimation)\n");
11652: for(i=1,jk=1; i <=nlstate; i++){
11653: for(j=1; j <=nlstate+ndeath; j++){
1.225 brouard 11654: if (j!=i) {
11655: fprintf(ficres,"%1d%1d",i,j);
11656: printf("%1d%1d",i,j);
11657: fprintf(ficlog,"%1d%1d",i,j);
11658: for(k=1; k<=ncovmodel;k++){
11659: printf(" %.5e",delti[jk]);
11660: fprintf(ficlog," %.5e",delti[jk]);
11661: fprintf(ficres," %.5e",delti[jk]);
11662: jk++;
11663: }
11664: printf("\n");
11665: fprintf(ficlog,"\n");
11666: fprintf(ficres,"\n");
11667: }
1.126 brouard 11668: }
11669: }
11670:
11671: 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 11672: if(mle >= 1) /* To big for the screen */
1.126 brouard 11673: 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");
11674: 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");
11675: /* # 121 Var(a12)\n\ */
11676: /* # 122 Cov(b12,a12) Var(b12)\n\ */
11677: /* # 131 Cov(a13,a12) Cov(a13,b12, Var(a13)\n\ */
11678: /* # 132 Cov(b13,a12) Cov(b13,b12, Cov(b13,a13) Var(b13)\n\ */
11679: /* # 212 Cov(a21,a12) Cov(a21,b12, Cov(a21,a13) Cov(a21,b13) Var(a21)\n\ */
11680: /* # 212 Cov(b21,a12) Cov(b21,b12, Cov(b21,a13) Cov(b21,b13) Cov(b21,a21) Var(b21)\n\ */
11681: /* # 232 Cov(a23,a12) Cov(a23,b12, Cov(a23,a13) Cov(a23,b13) Cov(a23,a21) Cov(a23,b21) Var(a23)\n\ */
11682: /* # 232 Cov(b23,a12) Cov(b23,b12) ... Var (b23)\n" */
11683:
11684:
11685: /* Just to have a covariance matrix which will be more understandable
11686: even is we still don't want to manage dictionary of variables
11687: */
11688: for(itimes=1;itimes<=2;itimes++){
11689: jj=0;
11690: for(i=1; i <=nlstate; i++){
1.225 brouard 11691: for(j=1; j <=nlstate+ndeath; j++){
11692: if(j==i) continue;
11693: for(k=1; k<=ncovmodel;k++){
11694: jj++;
11695: ca[0]= k+'a'-1;ca[1]='\0';
11696: if(itimes==1){
11697: if(mle>=1)
11698: printf("#%1d%1d%d",i,j,k);
11699: fprintf(ficlog,"#%1d%1d%d",i,j,k);
11700: fprintf(ficres,"#%1d%1d%d",i,j,k);
11701: }else{
11702: if(mle>=1)
11703: printf("%1d%1d%d",i,j,k);
11704: fprintf(ficlog,"%1d%1d%d",i,j,k);
11705: fprintf(ficres,"%1d%1d%d",i,j,k);
11706: }
11707: ll=0;
11708: for(li=1;li <=nlstate; li++){
11709: for(lj=1;lj <=nlstate+ndeath; lj++){
11710: if(lj==li) continue;
11711: for(lk=1;lk<=ncovmodel;lk++){
11712: ll++;
11713: if(ll<=jj){
11714: cb[0]= lk +'a'-1;cb[1]='\0';
11715: if(ll<jj){
11716: if(itimes==1){
11717: if(mle>=1)
11718: printf(" Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
11719: fprintf(ficlog," Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
11720: fprintf(ficres," Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
11721: }else{
11722: if(mle>=1)
11723: printf(" %.5e",matcov[jj][ll]);
11724: fprintf(ficlog," %.5e",matcov[jj][ll]);
11725: fprintf(ficres," %.5e",matcov[jj][ll]);
11726: }
11727: }else{
11728: if(itimes==1){
11729: if(mle>=1)
11730: printf(" Var(%s%1d%1d)",ca,i,j);
11731: fprintf(ficlog," Var(%s%1d%1d)",ca,i,j);
11732: fprintf(ficres," Var(%s%1d%1d)",ca,i,j);
11733: }else{
11734: if(mle>=1)
11735: printf(" %.7e",matcov[jj][ll]);
11736: fprintf(ficlog," %.7e",matcov[jj][ll]);
11737: fprintf(ficres," %.7e",matcov[jj][ll]);
11738: }
11739: }
11740: }
11741: } /* end lk */
11742: } /* end lj */
11743: } /* end li */
11744: if(mle>=1)
11745: printf("\n");
11746: fprintf(ficlog,"\n");
11747: fprintf(ficres,"\n");
11748: numlinepar++;
11749: } /* end k*/
11750: } /*end j */
1.126 brouard 11751: } /* end i */
11752: } /* end itimes */
11753:
11754: fflush(ficlog);
11755: fflush(ficres);
1.225 brouard 11756: while(fgets(line, MAXLINE, ficpar)) {
11757: /* If line starts with a # it is a comment */
11758: if (line[0] == '#') {
11759: numlinepar++;
11760: fputs(line,stdout);
11761: fputs(line,ficparo);
11762: fputs(line,ficlog);
11763: continue;
11764: }else
11765: break;
11766: }
11767:
1.209 brouard 11768: /* while((c=getc(ficpar))=='#' && c!= EOF){ */
11769: /* ungetc(c,ficpar); */
11770: /* fgets(line, MAXLINE, ficpar); */
11771: /* fputs(line,stdout); */
11772: /* fputs(line,ficparo); */
11773: /* } */
11774: /* ungetc(c,ficpar); */
1.126 brouard 11775:
11776: estepm=0;
1.209 brouard 11777: 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 11778:
11779: if (num_filled != 6) {
11780: 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);
11781: 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);
11782: goto end;
11783: }
11784: printf("agemin=%lf agemax=%lf bage=%lf fage=%lf estepm=%d ftolpl=%lf\n",ageminpar,agemaxpar, bage, fage, estepm, ftolpl);
11785: }
11786: /* ftolpl=6*ftol*1.e5; /\* 6.e-3 make convergences in less than 80 loops for the prevalence limit *\/ */
11787: /*ftolpl=6.e-4;*/ /* 6.e-3 make convergences in less than 80 loops for the prevalence limit */
11788:
1.209 brouard 11789: /* fscanf(ficpar,"agemin=%lf agemax=%lf bage=%lf fage=%lf estepm=%d ftolpl=%\n",&ageminpar,&agemaxpar, &bage, &fage, &estepm); */
1.126 brouard 11790: if (estepm==0 || estepm < stepm) estepm=stepm;
11791: if (fage <= 2) {
11792: bage = ageminpar;
11793: fage = agemaxpar;
11794: }
11795:
11796: fprintf(ficres,"# agemin agemax for life expectancy, bage fage (if mle==0 ie no data nor Max likelihood).\n");
1.211 brouard 11797: fprintf(ficres,"agemin=%.0f agemax=%.0f bage=%.0f fage=%.0f estepm=%d ftolpl=%e\n",ageminpar,agemaxpar,bage,fage, estepm, ftolpl);
11798: fprintf(ficparo,"agemin=%.0f agemax=%.0f bage=%.0f fage=%.0f estepm=%d, ftolpl=%e\n",ageminpar,agemaxpar,bage,fage, estepm, ftolpl);
1.220 brouard 11799:
1.186 brouard 11800: /* Other stuffs, more or less useful */
1.254 brouard 11801: while(fgets(line, MAXLINE, ficpar)) {
11802: /* If line starts with a # it is a comment */
11803: if (line[0] == '#') {
11804: numlinepar++;
11805: fputs(line,stdout);
11806: fputs(line,ficparo);
11807: fputs(line,ficlog);
11808: continue;
11809: }else
11810: break;
11811: }
11812:
11813: if((num_filled=sscanf(line,"begin-prev-date=%lf/%lf/%lf end-prev-date=%lf/%lf/%lf mov_average=%d\n",&jprev1, &mprev1,&anprev1,&jprev2, &mprev2,&anprev2,&mobilav)) !=EOF){
11814:
11815: if (num_filled != 7) {
11816: printf("Error: Not 7 (data)parameters in line but %d, for example:begin-prev-date=1/1/1990 end-prev-date=1/6/2004 mov_average=0\n, your line=%s . Probably you are running an older format.\n",num_filled,line);
11817: fprintf(ficlog,"Error: Not 7 (data)parameters in line but %d, for example:begin-prev-date=1/1/1990 end-prev-date=1/6/2004 mov_average=0\n, your line=%s . Probably you are running an older format.\n",num_filled,line);
11818: goto end;
11819: }
11820: printf("begin-prev-date=%.lf/%.lf/%.lf end-prev-date=%.lf/%.lf/%.lf mov_average=%d\n",jprev1, mprev1,anprev1,jprev2, mprev2,anprev2,mobilav);
11821: 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);
11822: 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);
11823: fprintf(ficlog,"begin-prev-date=%.lf/%.lf/%.lf end-prev-date=%.lf/%.lf/%.lf mov_average=%d\n",jprev1, mprev1,anprev1,jprev2, mprev2,anprev2,mobilav);
1.126 brouard 11824: }
1.254 brouard 11825:
11826: while(fgets(line, MAXLINE, ficpar)) {
11827: /* If line starts with a # it is a comment */
11828: if (line[0] == '#') {
11829: numlinepar++;
11830: fputs(line,stdout);
11831: fputs(line,ficparo);
11832: fputs(line,ficlog);
11833: continue;
11834: }else
11835: break;
1.126 brouard 11836: }
11837:
11838:
11839: dateprev1=anprev1+(mprev1-1)/12.+(jprev1-1)/365.;
11840: dateprev2=anprev2+(mprev2-1)/12.+(jprev2-1)/365.;
11841:
1.254 brouard 11842: if((num_filled=sscanf(line,"pop_based=%d\n",&popbased)) !=EOF){
11843: if (num_filled != 1) {
11844: printf("Error: Not 1 (data)parameters in line but %d, for example:pop_based=0\n, your line=%s . Probably you are running an older format.\n",num_filled,line);
11845: fprintf(ficlog,"Error: Not 1 (data)parameters in line but %d, for example: pop_based=1\n, your line=%s . Probably you are running an older format.\n",num_filled,line);
11846: goto end;
11847: }
11848: printf("pop_based=%d\n",popbased);
11849: fprintf(ficlog,"pop_based=%d\n",popbased);
11850: fprintf(ficparo,"pop_based=%d\n",popbased);
11851: fprintf(ficres,"pop_based=%d\n",popbased);
11852: }
11853:
1.258 brouard 11854: /* Results */
11855: nresult=0;
11856: do{
11857: if(!fgets(line, MAXLINE, ficpar)){
11858: endishere=1;
11859: parameterline=14;
11860: }else if (line[0] == '#') {
11861: /* If line starts with a # it is a comment */
1.254 brouard 11862: numlinepar++;
11863: fputs(line,stdout);
11864: fputs(line,ficparo);
11865: fputs(line,ficlog);
11866: continue;
1.258 brouard 11867: }else if(sscanf(line,"prevforecast=%[^\n]\n",modeltemp))
11868: parameterline=11;
11869: else if(sscanf(line,"backcast=%[^\n]\n",modeltemp))
11870: parameterline=12;
11871: else if(sscanf(line,"result:%[^\n]\n",modeltemp))
11872: parameterline=13;
11873: else{
11874: parameterline=14;
1.254 brouard 11875: }
1.258 brouard 11876: switch (parameterline){
11877: case 11:
11878: if((num_filled=sscanf(line,"prevforecast=%d starting-proj-date=%lf/%lf/%lf final-proj-date=%lf/%lf/%lf mobil_average=%d\n",&prevfcast,&jproj1,&mproj1,&anproj1,&jproj2,&mproj2,&anproj2,&mobilavproj)) !=EOF){
11879: if (num_filled != 8) {
11880: printf("Error: Not 8 (data)parameters in line but %d, for example:prevforecast=1 starting-proj-date=1/1/1990 final-proj-date=1/1/2000 mobil_average=0\n, your line=%s . Probably you are running an older format.\n",num_filled,line);
11881: fprintf(ficlog,"Error: Not 8 (data)parameters in line but %d, for example:prevforecast=1 starting-proj-date=1/1/1990 final-proj-date=1/1/2000 mov_average=0\n, your line=%s . Probably you are running an older format.\n",num_filled,line);
11882: goto end;
11883: }
11884: 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);
11885: 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);
11886: 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);
11887: 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);
11888: /* day and month of proj2 are not used but only year anproj2.*/
11889: }
1.254 brouard 11890: break;
1.258 brouard 11891: case 12:
11892: /*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);*/
11893: if((num_filled=sscanf(line,"backcast=%d starting-back-date=%lf/%lf/%lf final-back-date=%lf/%lf/%lf mobil_average=%d\n",&backcast,&jback1,&mback1,&anback1,&jback2,&mback2,&anback2,&mobilavproj)) !=EOF){
11894: if (num_filled != 8) {
1.262 brouard 11895: printf("Error: Not 8 (data)parameters in line but %d, for example:backcast=1 starting-back-date=1/1/1990 final-back-date=1/1/1970 mobil_average=1\n, your line=%s . Probably you are running an older format.\n",num_filled,line);
11896: fprintf(ficlog,"Error: Not 8 (data)parameters in line but %d, for example:backcast=1 starting-back-date=1/1/1990 final-back-date=1/1/1970 mobil_average=1\n, your line=%s . Probably you are running an older format.\n",num_filled,line);
1.258 brouard 11897: goto end;
11898: }
11899: printf("backcast=%d starting-back-date=%.lf/%.lf/%.lf final-back-date=%.lf/%.lf/%.lf mobil_average=%d\n",backcast,jback1,mback1,anback1,jback2,mback2,anback2,mobilavproj);
11900: 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);
11901: 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);
11902: 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);
11903: /* day and month of proj2 are not used but only year anproj2.*/
11904: }
1.230 brouard 11905: break;
1.258 brouard 11906: case 13:
11907: if((num_filled=sscanf(line,"result:%[^\n]\n",resultline)) !=EOF){
11908: if (num_filled == 0){
11909: resultline[0]='\0';
11910: printf("Warning %d: no result line! It should be at minimum 'result: V2=0 V1=1 or result:.\n%s\n", num_filled, line);
11911: fprintf(ficlog,"Warning %d: no result line! It should be at minimum 'result: V2=0 V1=1 or result:.\n%s\n", num_filled, line);
11912: break;
11913: } else if (num_filled != 1){
11914: printf("ERROR %d: result line! It should be at minimum 'result: V2=0 V1=1 or result:.' %s\n",num_filled, line);
11915: fprintf(ficlog,"ERROR %d: result line! It should be at minimum 'result: V2=0 V1=1 or result:.' %s\n",num_filled, line);
11916: }
11917: nresult++; /* Sum of resultlines */
11918: printf("Result %d: result=%s\n",nresult, resultline);
11919: if(nresult > MAXRESULTLINES){
11920: printf("ERROR: Current version of IMaCh limits the number of resultlines to %d, you used %d\n",MAXRESULTLINES,nresult);
11921: fprintf(ficlog,"ERROR: Current version of IMaCh limits the number of resultlines to %d, you used %d\n",MAXRESULTLINES,nresult);
11922: goto end;
11923: }
11924: decoderesult(resultline, nresult); /* Fills TKresult[nresult] combination and Tresult[nresult][k4+1] combination values */
11925: fprintf(ficparo,"result: %s\n",resultline);
11926: fprintf(ficres,"result: %s\n",resultline);
11927: fprintf(ficlog,"result: %s\n",resultline);
1.230 brouard 11928: break;
1.258 brouard 11929: case 14:
1.259 brouard 11930: if(ncovmodel >2 && nresult==0 ){
11931: printf("ERROR: no result lines! It should be at minimum 'result: V2=0 V1=1 or result:.' %s\n",line);
1.258 brouard 11932: goto end;
11933: }
1.259 brouard 11934: break;
1.258 brouard 11935: default:
11936: nresult=1;
11937: decoderesult(".",nresult ); /* No covariate */
11938: }
11939: } /* End switch parameterline */
11940: }while(endishere==0); /* End do */
1.126 brouard 11941:
1.230 brouard 11942: /* freqsummary(fileres, agemin, agemax, s, agev, nlstate, imx,Tvaraff,nbcode, ncodemax,mint,anint); */
1.145 brouard 11943: /* ,dateprev1,dateprev2,jprev1, mprev1,anprev1,jprev2, mprev2,anprev2); */
1.126 brouard 11944:
11945: replace_back_to_slash(pathc,pathcd); /* Even gnuplot wants a / */
1.194 brouard 11946: if(ageminpar == AGEOVERFLOW ||agemaxpar == -AGEOVERFLOW){
1.230 brouard 11947: printf("Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
1.194 brouard 11948: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
11949: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
1.230 brouard 11950: fprintf(ficlog,"Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
1.194 brouard 11951: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
11952: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
1.220 brouard 11953: }else{
1.268 ! brouard 11954: printinggnuplot(fileresu, optionfilefiname,ageminpar,agemaxpar,fage, prevfcast, backcast, pathc,p, (int)anproj1-(int)agemin, (int)anback1-(int)agemax+1);
1.220 brouard 11955: }
11956: printinghtml(fileresu,title,datafile, firstpass, lastpass, stepm, weightopt, \
1.258 brouard 11957: model,imx,jmin,jmax,jmean,rfileres,popforecast,mobilav,prevfcast,mobilavproj,backcast, estepm, \
1.225 brouard 11958: jprev1,mprev1,anprev1,dateprev1,jprev2,mprev2,anprev2,dateprev2);
1.220 brouard 11959:
1.225 brouard 11960: /*------------ free_vector -------------*/
11961: /* chdir(path); */
1.220 brouard 11962:
1.215 brouard 11963: /* free_ivector(wav,1,imx); */ /* Moved after last prevalence call */
11964: /* free_imatrix(dh,1,lastpass-firstpass+2,1,imx); */
11965: /* free_imatrix(bh,1,lastpass-firstpass+2,1,imx); */
11966: /* free_imatrix(mw,1,lastpass-firstpass+2,1,imx); */
1.126 brouard 11967: free_lvector(num,1,n);
11968: free_vector(agedc,1,n);
11969: /*free_matrix(covar,0,NCOVMAX,1,n);*/
11970: /*free_matrix(covar,1,NCOVMAX,1,n);*/
11971: fclose(ficparo);
11972: fclose(ficres);
1.220 brouard 11973:
11974:
1.186 brouard 11975: /* Other results (useful)*/
1.220 brouard 11976:
11977:
1.126 brouard 11978: /*--------------- Prevalence limit (period or stable prevalence) --------------*/
1.180 brouard 11979: /*#include "prevlim.h"*/ /* Use ficrespl, ficlog */
11980: prlim=matrix(1,nlstate,1,nlstate);
1.209 brouard 11981: prevalence_limit(p, prlim, ageminpar, agemaxpar, ftolpl, &ncvyear);
1.126 brouard 11982: fclose(ficrespl);
11983:
11984: /*------------- h Pij x at various ages ------------*/
1.180 brouard 11985: /*#include "hpijx.h"*/
11986: hPijx(p, bage, fage);
1.145 brouard 11987: fclose(ficrespij);
1.227 brouard 11988:
1.220 brouard 11989: /* ncovcombmax= pow(2,cptcoveff); */
1.219 brouard 11990: /*-------------- Variance of one-step probabilities---*/
1.145 brouard 11991: k=1;
1.126 brouard 11992: varprob(optionfilefiname, matcov, p, delti, nlstate, bage, fage,k,Tvar,nbcode, ncodemax,strstart);
1.227 brouard 11993:
1.219 brouard 11994: /* Prevalence for each covariates in probs[age][status][cov] */
1.218 brouard 11995: probs= ma3x(1,AGESUP,1,nlstate+ndeath, 1,ncovcombmax);
1.126 brouard 11996: for(i=1;i<=AGESUP;i++)
1.219 brouard 11997: for(j=1;j<=nlstate+ndeath;j++) /* ndeath is useless but a necessity to be compared with mobaverages */
1.225 brouard 11998: for(k=1;k<=ncovcombmax;k++)
11999: probs[i][j][k]=0.;
1.219 brouard 12000: prevalence(probs, ageminpar, agemaxpar, s, agev, nlstate, imx, Tvar, nbcode, ncodemax, mint, anint, dateprev1, dateprev2, firstpass, lastpass);
12001: if (mobilav!=0 ||mobilavproj !=0 ) {
12002: mobaverages= ma3x(1, AGESUP,1,nlstate+ndeath, 1,ncovcombmax);
1.227 brouard 12003: for(i=1;i<=AGESUP;i++)
1.268 ! brouard 12004: for(j=1;j<=nlstate+ndeath;j++)
1.227 brouard 12005: for(k=1;k<=ncovcombmax;k++)
12006: mobaverages[i][j][k]=0.;
1.219 brouard 12007: mobaverage=mobaverages;
12008: if (mobilav!=0) {
1.235 brouard 12009: printf("Movingaveraging observed prevalence\n");
1.258 brouard 12010: fprintf(ficlog,"Movingaveraging observed prevalence\n");
1.227 brouard 12011: if (movingaverage(probs, ageminpar, agemaxpar, mobaverage, mobilav)!=0){
12012: fprintf(ficlog," Error in movingaverage mobilav=%d\n",mobilav);
12013: printf(" Error in movingaverage mobilav=%d\n",mobilav);
12014: }
1.219 brouard 12015: }
1.266 brouard 12016: /* else if(mobilavproj==-1){ /\* Forcing raw observed prevalences *\/ */
12017: /* for(i=1;i<=AGESUP;i++) */
12018: /* for(j=1;j<=nlstate;j++) */
12019: /* for(k=1;k<=ncovcombmax;k++) */
12020: /* mobaverages[i][j][k]=probs[i][j][k]; */
12021: /* /\* /\\* Prevalence for each covariates in probs[age][status][cov] *\\/ *\/ */
12022: /* /\* prevalence(probs, ageminpar, agemaxpar, s, agev, nlstate, imx, Tvar, nbcode, ncodemax, mint, anint, dateprev1, dateprev2, firstpass, lastpass); *\/ */
12023: /* } */
1.219 brouard 12024: else if (mobilavproj !=0) {
1.235 brouard 12025: printf("Movingaveraging projected observed prevalence\n");
1.258 brouard 12026: fprintf(ficlog,"Movingaveraging projected observed prevalence\n");
1.227 brouard 12027: if (movingaverage(probs, ageminpar, agemaxpar, mobaverage, mobilavproj)!=0){
12028: fprintf(ficlog," Error in movingaverage mobilavproj=%d\n",mobilavproj);
12029: printf(" Error in movingaverage mobilavproj=%d\n",mobilavproj);
12030: }
1.219 brouard 12031: }
12032: }/* end if moving average */
1.227 brouard 12033:
1.126 brouard 12034: /*---------- Forecasting ------------------*/
12035: /*if((stepm == 1) && (strcmp(model,".")==0)){*/
12036: if(prevfcast==1){
12037: /* if(stepm ==1){*/
1.225 brouard 12038: prevforecast(fileresu, anproj1, mproj1, jproj1, agemin, agemax, dateprev1, dateprev2, mobilavproj, bage, fage, firstpass, lastpass, anproj2, p, cptcoveff);
1.126 brouard 12039: }
1.217 brouard 12040: if(backcast==1){
1.219 brouard 12041: ddnewms=matrix(1,nlstate+ndeath,1,nlstate+ndeath);
12042: ddoldms=matrix(1,nlstate+ndeath,1,nlstate+ndeath);
12043: ddsavms=matrix(1,nlstate+ndeath,1,nlstate+ndeath);
12044:
12045: /*--------------- Back Prevalence limit (period or stable prevalence) --------------*/
12046:
12047: bprlim=matrix(1,nlstate,1,nlstate);
12048: back_prevalence_limit(p, bprlim, ageminpar, agemaxpar, ftolpl, &ncvyear, dateprev1, dateprev2, firstpass, lastpass, mobilavproj);
12049: fclose(ficresplb);
12050:
1.222 brouard 12051: hBijx(p, bage, fage, mobaverage);
12052: fclose(ficrespijb);
1.268 ! brouard 12053: /* free_matrix(bprlim,1,nlstate,1,nlstate); /\*here or after loop ? *\/ */
1.219 brouard 12054:
1.267 brouard 12055: prevbackforecast(fileresu, mobaverage, anback1, mback1, jback1, agemin, agemax, dateprev1, dateprev2, mobilavproj,
12056: bage, fage, firstpass, lastpass, anback2, p, cptcoveff);
1.268 ! brouard 12057:
! 12058: /*------- Variance of back (stable) prevalence------*/
! 12059:
! 12060: strcpy(fileresvbl,"VBL_");
! 12061: strcat(fileresvbl,fileresu);
! 12062: if((ficresvbl=fopen(fileresvbl,"w"))==NULL) {
! 12063: printf("Problem with variance of back (stable) prevalence resultfile: %s\n", fileresvbl);
! 12064: exit(0);
! 12065: }
! 12066: printf("Computing Variance-covariance of back (stable) prevalence: file '%s' ...", fileresvbl);fflush(stdout);
! 12067: fprintf(ficlog, "Computing Variance-covariance of back (stable) prevalence: file '%s' ...", fileresvbl);fflush(ficlog);
! 12068:
! 12069: /*for(cptcov=1,k=0;cptcov<=i1;cptcov++){
! 12070: for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){*/
! 12071:
! 12072: i1=pow(2,cptcoveff);
! 12073: if (cptcovn < 1){i1=1;}
! 12074:
! 12075: for(nres=1; nres <= nresult; nres++) /* For each resultline */
! 12076: for(k=1; k<=i1;k++){
! 12077: if(i1 != 1 && TKresult[nres]!= k)
! 12078: continue;
! 12079: fprintf(ficresvbl,"\n#****** ");
! 12080: printf("\n#****** ");
! 12081: fprintf(ficlog,"\n#****** ");
! 12082: for(j=1;j<=cptcoveff;j++) {
! 12083: fprintf(ficresvbl,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
! 12084: fprintf(ficlog,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
! 12085: printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
! 12086: }
! 12087: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
! 12088: printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
! 12089: fprintf(ficresvbl," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
! 12090: fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
! 12091: }
! 12092: fprintf(ficresvbl,"******\n");
! 12093: printf("******\n");
! 12094: fprintf(ficlog,"******\n");
! 12095:
! 12096: varbpl=matrix(1,nlstate,(int) bage, (int) fage);
! 12097: oldm=oldms;savm=savms;
! 12098:
! 12099: varbrevlim(fileres, varbpl, matcov, p, delti, nlstate, stepm, (int) bage, (int) fage, oldm, savm, bprlim, ftolpl, mobilavproj, &ncvyear, k, strstart, nres);
! 12100: free_matrix(varbpl,1,nlstate,(int) bage, (int)fage);
! 12101: /*}*/
! 12102: }
! 12103:
! 12104: fclose(ficresvbl);
! 12105: printf("done variance-covariance of back prevalence\n");fflush(stdout);
! 12106: fprintf(ficlog,"done variance-covariance of back prevalence\n");fflush(ficlog);
! 12107:
1.219 brouard 12108: free_matrix(ddnewms, 1, nlstate+ndeath, 1, nlstate+ndeath);
12109: free_matrix(ddsavms, 1, nlstate+ndeath, 1, nlstate+ndeath);
12110: free_matrix(ddoldms, 1, nlstate+ndeath, 1, nlstate+ndeath);
12111: }
1.268 ! brouard 12112: free_matrix(bprlim,1,nlstate,1,nlstate); /*here or after loop ? */
! 12113:
1.186 brouard 12114:
12115: /* ------ Other prevalence ratios------------ */
1.126 brouard 12116:
1.215 brouard 12117: free_ivector(wav,1,imx);
12118: free_imatrix(dh,1,lastpass-firstpass+2,1,imx);
12119: free_imatrix(bh,1,lastpass-firstpass+2,1,imx);
12120: free_imatrix(mw,1,lastpass-firstpass+2,1,imx);
1.218 brouard 12121:
12122:
1.127 brouard 12123: /*---------- Health expectancies, no variances ------------*/
1.218 brouard 12124:
1.201 brouard 12125: strcpy(filerese,"E_");
12126: strcat(filerese,fileresu);
1.126 brouard 12127: if((ficreseij=fopen(filerese,"w"))==NULL) {
12128: printf("Problem with Health Exp. resultfile: %s\n", filerese); exit(0);
12129: fprintf(ficlog,"Problem with Health Exp. resultfile: %s\n", filerese); exit(0);
12130: }
1.208 brouard 12131: printf("Computing Health Expectancies: result on file '%s' ...", filerese);fflush(stdout);
12132: fprintf(ficlog,"Computing Health Expectancies: result on file '%s' ...", filerese);fflush(ficlog);
1.238 brouard 12133:
12134: pstamp(ficreseij);
1.219 brouard 12135:
1.235 brouard 12136: i1=pow(2,cptcoveff); /* Number of combination of dummy covariates */
12137: if (cptcovn < 1){i1=1;}
12138:
12139: for(nres=1; nres <= nresult; nres++) /* For each resultline */
12140: for(k=1; k<=i1;k++){ /* For any combination of dummy covariates, fixed and varying */
1.253 brouard 12141: if(i1 != 1 && TKresult[nres]!= k)
1.235 brouard 12142: continue;
1.219 brouard 12143: fprintf(ficreseij,"\n#****** ");
1.235 brouard 12144: printf("\n#****** ");
1.225 brouard 12145: for(j=1;j<=cptcoveff;j++) {
1.227 brouard 12146: fprintf(ficreseij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
1.235 brouard 12147: printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
12148: }
12149: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
12150: printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
12151: fprintf(ficreseij," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
1.219 brouard 12152: }
12153: fprintf(ficreseij,"******\n");
1.235 brouard 12154: printf("******\n");
1.219 brouard 12155:
12156: eij=ma3x(1,nlstate,1,nlstate,(int) bage, (int) fage);
12157: oldm=oldms;savm=savms;
1.235 brouard 12158: evsij(eij, p, nlstate, stepm, (int) bage, (int)fage, oldm, savm, k, estepm, strstart, nres);
1.127 brouard 12159:
1.219 brouard 12160: free_ma3x(eij,1,nlstate,1,nlstate,(int) bage, (int)fage);
1.127 brouard 12161: }
12162: fclose(ficreseij);
1.208 brouard 12163: printf("done evsij\n");fflush(stdout);
12164: fprintf(ficlog,"done evsij\n");fflush(ficlog);
1.218 brouard 12165:
1.227 brouard 12166: /*---------- State-specific expectancies and variances ------------*/
1.218 brouard 12167:
12168:
1.201 brouard 12169: strcpy(filerest,"T_");
12170: strcat(filerest,fileresu);
1.127 brouard 12171: if((ficrest=fopen(filerest,"w"))==NULL) {
12172: printf("Problem with total LE resultfile: %s\n", filerest);goto end;
12173: fprintf(ficlog,"Problem with total LE resultfile: %s\n", filerest);goto end;
12174: }
1.208 brouard 12175: printf("Computing Total Life expectancies with their standard errors: file '%s' ...\n", filerest); fflush(stdout);
12176: fprintf(ficlog,"Computing Total Life expectancies with their standard errors: file '%s' ...\n", filerest); fflush(ficlog);
1.218 brouard 12177:
1.126 brouard 12178:
1.201 brouard 12179: strcpy(fileresstde,"STDE_");
12180: strcat(fileresstde,fileresu);
1.126 brouard 12181: if((ficresstdeij=fopen(fileresstde,"w"))==NULL) {
1.227 brouard 12182: printf("Problem with State specific Exp. and std errors resultfile: %s\n", fileresstde); exit(0);
12183: fprintf(ficlog,"Problem with State specific Exp. and std errors resultfile: %s\n", fileresstde); exit(0);
1.126 brouard 12184: }
1.227 brouard 12185: printf(" Computing State-specific Expectancies and standard errors: result on file '%s' \n", fileresstde);
12186: fprintf(ficlog," Computing State-specific Expectancies and standard errors: result on file '%s' \n", fileresstde);
1.126 brouard 12187:
1.201 brouard 12188: strcpy(filerescve,"CVE_");
12189: strcat(filerescve,fileresu);
1.126 brouard 12190: if((ficrescveij=fopen(filerescve,"w"))==NULL) {
1.227 brouard 12191: printf("Problem with Covar. State-specific Exp. resultfile: %s\n", filerescve); exit(0);
12192: fprintf(ficlog,"Problem with Covar. State-specific Exp. resultfile: %s\n", filerescve); exit(0);
1.126 brouard 12193: }
1.227 brouard 12194: printf(" Computing Covar. of State-specific Expectancies: result on file '%s' \n", filerescve);
12195: fprintf(ficlog," Computing Covar. of State-specific Expectancies: result on file '%s' \n", filerescve);
1.126 brouard 12196:
1.201 brouard 12197: strcpy(fileresv,"V_");
12198: strcat(fileresv,fileresu);
1.126 brouard 12199: if((ficresvij=fopen(fileresv,"w"))==NULL) {
12200: printf("Problem with variance resultfile: %s\n", fileresv);exit(0);
12201: fprintf(ficlog,"Problem with variance resultfile: %s\n", fileresv);exit(0);
12202: }
1.227 brouard 12203: printf(" Computing Variance-covariance of State-specific Expectancies: file '%s' ... ", fileresv);fflush(stdout);
12204: fprintf(ficlog," Computing Variance-covariance of State-specific Expectancies: file '%s' ... ", fileresv);fflush(ficlog);
1.126 brouard 12205:
1.145 brouard 12206: /*for(cptcov=1,k=0;cptcov<=i1;cptcov++){
12207: for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){*/
12208:
1.235 brouard 12209: i1=pow(2,cptcoveff); /* Number of combination of dummy covariates */
12210: if (cptcovn < 1){i1=1;}
12211:
12212: for(nres=1; nres <= nresult; nres++) /* For each resultline */
12213: for(k=1; k<=i1;k++){ /* For any combination of dummy covariates, fixed and varying */
1.253 brouard 12214: if(i1 != 1 && TKresult[nres]!= k)
1.235 brouard 12215: continue;
1.242 brouard 12216: printf("\n#****** Result for:");
12217: fprintf(ficrest,"\n#****** Result for:");
12218: fprintf(ficlog,"\n#****** Result for:");
1.227 brouard 12219: for(j=1;j<=cptcoveff;j++){
12220: printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
12221: fprintf(ficrest,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
12222: fprintf(ficlog,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
12223: }
1.235 brouard 12224: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
12225: printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
12226: fprintf(ficrest," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
12227: fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
12228: }
1.208 brouard 12229: fprintf(ficrest,"******\n");
1.227 brouard 12230: fprintf(ficlog,"******\n");
12231: printf("******\n");
1.208 brouard 12232:
12233: fprintf(ficresstdeij,"\n#****** ");
12234: fprintf(ficrescveij,"\n#****** ");
1.225 brouard 12235: for(j=1;j<=cptcoveff;j++) {
1.227 brouard 12236: fprintf(ficresstdeij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
12237: fprintf(ficrescveij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
1.208 brouard 12238: }
1.235 brouard 12239: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
12240: fprintf(ficresstdeij," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
12241: fprintf(ficrescveij," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
12242: }
1.208 brouard 12243: fprintf(ficresstdeij,"******\n");
12244: fprintf(ficrescveij,"******\n");
12245:
12246: fprintf(ficresvij,"\n#****** ");
1.238 brouard 12247: /* pstamp(ficresvij); */
1.225 brouard 12248: for(j=1;j<=cptcoveff;j++)
1.227 brouard 12249: fprintf(ficresvij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
1.235 brouard 12250: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
12251: fprintf(ficresvij," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
12252: }
1.208 brouard 12253: fprintf(ficresvij,"******\n");
12254:
12255: eij=ma3x(1,nlstate,1,nlstate,(int) bage, (int) fage);
12256: oldm=oldms;savm=savms;
1.235 brouard 12257: printf(" cvevsij ");
12258: fprintf(ficlog, " cvevsij ");
12259: cvevsij(eij, p, nlstate, stepm, (int) bage, (int)fage, oldm, savm, k, estepm, delti, matcov, strstart, nres);
1.208 brouard 12260: printf(" end cvevsij \n ");
12261: fprintf(ficlog, " end cvevsij \n ");
12262:
12263: /*
12264: */
12265: /* goto endfree; */
12266:
12267: vareij=ma3x(1,nlstate,1,nlstate,(int) bage, (int) fage);
12268: pstamp(ficrest);
12269:
12270:
12271: for(vpopbased=0; vpopbased <= popbased; vpopbased++){ /* Done for vpopbased=0 and vpopbased=1 if popbased==1*/
1.227 brouard 12272: oldm=oldms;savm=savms; /* ZZ Segmentation fault */
12273: cptcod= 0; /* To be deleted */
12274: printf("varevsij vpopbased=%d \n",vpopbased);
12275: fprintf(ficlog, "varevsij vpopbased=%d \n",vpopbased);
1.235 brouard 12276: 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 12277: 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 ");
12278: if(vpopbased==1)
12279: 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);
12280: else
12281: fprintf(ficrest,"the age specific period (stable) prevalences in each health state \n");
12282: fprintf(ficrest,"# Age popbased mobilav e.. (std) ");
12283: for (i=1;i<=nlstate;i++) fprintf(ficrest,"e.%d (std) ",i);
12284: fprintf(ficrest,"\n");
12285: /* printf("Which p?\n"); for(i=1;i<=npar;i++)printf("p[i=%d]=%lf,",i,p[i]);printf("\n"); */
12286: epj=vector(1,nlstate+1);
12287: printf("Computing age specific period (stable) prevalences in each health state \n");
12288: fprintf(ficlog,"Computing age specific period (stable) prevalences in each health state \n");
12289: for(age=bage; age <=fage ;age++){
1.235 brouard 12290: prevalim(prlim, nlstate, p, age, oldm, savm, ftolpl, &ncvyear, k, nres); /*ZZ Is it the correct prevalim */
1.227 brouard 12291: if (vpopbased==1) {
12292: if(mobilav ==0){
12293: for(i=1; i<=nlstate;i++)
12294: prlim[i][i]=probs[(int)age][i][k];
12295: }else{ /* mobilav */
12296: for(i=1; i<=nlstate;i++)
12297: prlim[i][i]=mobaverage[(int)age][i][k];
12298: }
12299: }
1.219 brouard 12300:
1.227 brouard 12301: fprintf(ficrest," %4.0f %d %d",age, vpopbased, mobilav);
12302: /* fprintf(ficrest," %4.0f %d %d %d %d",age, vpopbased, mobilav,Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]); */ /* to be done */
12303: /* printf(" age %4.0f ",age); */
12304: for(j=1, epj[nlstate+1]=0.;j <=nlstate;j++){
12305: for(i=1, epj[j]=0.;i <=nlstate;i++) {
12306: epj[j] += prlim[i][i]*eij[i][j][(int)age];
12307: /*ZZZ printf("%lf %lf ", prlim[i][i] ,eij[i][j][(int)age]);*/
12308: /* printf("%lf %lf ", prlim[i][i] ,eij[i][j][(int)age]); */
12309: }
12310: epj[nlstate+1] +=epj[j];
12311: }
12312: /* printf(" age %4.0f \n",age); */
1.219 brouard 12313:
1.227 brouard 12314: for(i=1, vepp=0.;i <=nlstate;i++)
12315: for(j=1;j <=nlstate;j++)
12316: vepp += vareij[i][j][(int)age];
12317: fprintf(ficrest," %7.3f (%7.3f)", epj[nlstate+1],sqrt(vepp));
12318: for(j=1;j <=nlstate;j++){
12319: fprintf(ficrest," %7.3f (%7.3f)", epj[j],sqrt(vareij[j][j][(int)age]));
12320: }
12321: fprintf(ficrest,"\n");
12322: }
1.208 brouard 12323: } /* End vpopbased */
12324: free_ma3x(eij,1,nlstate,1,nlstate,(int) bage, (int)fage);
12325: free_ma3x(vareij,1,nlstate,1,nlstate,(int) bage, (int)fage);
12326: free_vector(epj,1,nlstate+1);
1.235 brouard 12327: printf("done selection\n");fflush(stdout);
12328: fprintf(ficlog,"done selection\n");fflush(ficlog);
1.208 brouard 12329:
1.145 brouard 12330: /*}*/
1.235 brouard 12331: } /* End k selection */
1.227 brouard 12332:
12333: printf("done State-specific expectancies\n");fflush(stdout);
12334: fprintf(ficlog,"done State-specific expectancies\n");fflush(ficlog);
12335:
1.126 brouard 12336: /*------- Variance of period (stable) prevalence------*/
1.227 brouard 12337:
1.201 brouard 12338: strcpy(fileresvpl,"VPL_");
12339: strcat(fileresvpl,fileresu);
1.126 brouard 12340: if((ficresvpl=fopen(fileresvpl,"w"))==NULL) {
12341: printf("Problem with variance of period (stable) prevalence resultfile: %s\n", fileresvpl);
12342: exit(0);
12343: }
1.208 brouard 12344: printf("Computing Variance-covariance of period (stable) prevalence: file '%s' ...", fileresvpl);fflush(stdout);
12345: fprintf(ficlog, "Computing Variance-covariance of period (stable) prevalence: file '%s' ...", fileresvpl);fflush(ficlog);
1.227 brouard 12346:
1.145 brouard 12347: /*for(cptcov=1,k=0;cptcov<=i1;cptcov++){
12348: for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){*/
1.227 brouard 12349:
1.235 brouard 12350: i1=pow(2,cptcoveff);
12351: if (cptcovn < 1){i1=1;}
12352:
12353: for(nres=1; nres <= nresult; nres++) /* For each resultline */
12354: for(k=1; k<=i1;k++){
1.253 brouard 12355: if(i1 != 1 && TKresult[nres]!= k)
1.235 brouard 12356: continue;
1.227 brouard 12357: fprintf(ficresvpl,"\n#****** ");
12358: printf("\n#****** ");
12359: fprintf(ficlog,"\n#****** ");
12360: for(j=1;j<=cptcoveff;j++) {
12361: fprintf(ficresvpl,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
12362: fprintf(ficlog,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
12363: printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
12364: }
1.235 brouard 12365: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
12366: printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
12367: fprintf(ficresvpl," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
12368: fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
12369: }
1.227 brouard 12370: fprintf(ficresvpl,"******\n");
12371: printf("******\n");
12372: fprintf(ficlog,"******\n");
12373:
12374: varpl=matrix(1,nlstate,(int) bage, (int) fage);
12375: oldm=oldms;savm=savms;
1.235 brouard 12376: varprevlim(fileres, varpl, matcov, p, delti, nlstate, stepm, (int) bage, (int) fage, oldm, savm, prlim, ftolpl, &ncvyear, k, strstart, nres);
1.227 brouard 12377: free_matrix(varpl,1,nlstate,(int) bage, (int)fage);
1.145 brouard 12378: /*}*/
1.126 brouard 12379: }
1.227 brouard 12380:
1.126 brouard 12381: fclose(ficresvpl);
1.208 brouard 12382: printf("done variance-covariance of period prevalence\n");fflush(stdout);
12383: fprintf(ficlog,"done variance-covariance of period prevalence\n");fflush(ficlog);
1.268 ! brouard 12384:
1.227 brouard 12385:
12386: free_vector(weight,1,n);
12387: free_imatrix(Tvard,1,NCOVMAX,1,2);
12388: free_imatrix(s,1,maxwav+1,1,n);
12389: free_matrix(anint,1,maxwav,1,n);
12390: free_matrix(mint,1,maxwav,1,n);
12391: free_ivector(cod,1,n);
12392: free_ivector(tab,1,NCOVMAX);
12393: fclose(ficresstdeij);
12394: fclose(ficrescveij);
12395: fclose(ficresvij);
12396: fclose(ficrest);
12397: fclose(ficpar);
12398:
12399:
1.126 brouard 12400: /*---------- End : free ----------------*/
1.219 brouard 12401: if (mobilav!=0 ||mobilavproj !=0)
12402: 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 12403: free_ma3x(probs,1,AGESUP,1,nlstate+ndeath, 1,ncovcombmax);
1.220 brouard 12404: free_matrix(prlim,1,nlstate,1,nlstate); /*here or after loop ? */
12405: free_matrix(pmmij,1,nlstate+ndeath,1,nlstate+ndeath);
1.126 brouard 12406: } /* mle==-3 arrives here for freeing */
1.227 brouard 12407: /* endfree:*/
12408: free_matrix(oldms, 1,nlstate+ndeath,1,nlstate+ndeath);
12409: free_matrix(newms, 1,nlstate+ndeath,1,nlstate+ndeath);
12410: free_matrix(savms, 1,nlstate+ndeath,1,nlstate+ndeath);
1.268 ! brouard 12411: if(ntv+nqtv>=1)free_ma3x(cotvar,1,maxwav,1,ntv+nqtv,1,n);
! 12412: if(nqtv>=1)free_ma3x(cotqvar,1,maxwav,1,nqtv,1,n);
! 12413: if(nqv>=1)free_matrix(coqvar,1,nqv,1,n);
1.227 brouard 12414: free_matrix(covar,0,NCOVMAX,1,n);
12415: free_matrix(matcov,1,npar,1,npar);
12416: free_matrix(hess,1,npar,1,npar);
12417: /*free_vector(delti,1,npar);*/
12418: free_ma3x(delti3,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
12419: free_matrix(agev,1,maxwav,1,imx);
12420: free_ma3x(param,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
12421:
12422: free_ivector(ncodemax,1,NCOVMAX);
12423: free_ivector(ncodemaxwundef,1,NCOVMAX);
12424: free_ivector(Dummy,-1,NCOVMAX);
12425: free_ivector(Fixed,-1,NCOVMAX);
1.238 brouard 12426: free_ivector(DummyV,1,NCOVMAX);
12427: free_ivector(FixedV,1,NCOVMAX);
1.227 brouard 12428: free_ivector(Typevar,-1,NCOVMAX);
12429: free_ivector(Tvar,1,NCOVMAX);
1.234 brouard 12430: free_ivector(TvarsQ,1,NCOVMAX);
12431: free_ivector(TvarsQind,1,NCOVMAX);
12432: free_ivector(TvarsD,1,NCOVMAX);
12433: free_ivector(TvarsDind,1,NCOVMAX);
1.231 brouard 12434: free_ivector(TvarFD,1,NCOVMAX);
12435: free_ivector(TvarFDind,1,NCOVMAX);
1.232 brouard 12436: free_ivector(TvarF,1,NCOVMAX);
12437: free_ivector(TvarFind,1,NCOVMAX);
12438: free_ivector(TvarV,1,NCOVMAX);
12439: free_ivector(TvarVind,1,NCOVMAX);
12440: free_ivector(TvarA,1,NCOVMAX);
12441: free_ivector(TvarAind,1,NCOVMAX);
1.231 brouard 12442: free_ivector(TvarFQ,1,NCOVMAX);
12443: free_ivector(TvarFQind,1,NCOVMAX);
12444: free_ivector(TvarVD,1,NCOVMAX);
12445: free_ivector(TvarVDind,1,NCOVMAX);
12446: free_ivector(TvarVQ,1,NCOVMAX);
12447: free_ivector(TvarVQind,1,NCOVMAX);
1.230 brouard 12448: free_ivector(Tvarsel,1,NCOVMAX);
12449: free_vector(Tvalsel,1,NCOVMAX);
1.227 brouard 12450: free_ivector(Tposprod,1,NCOVMAX);
12451: free_ivector(Tprod,1,NCOVMAX);
12452: free_ivector(Tvaraff,1,NCOVMAX);
12453: free_ivector(invalidvarcomb,1,ncovcombmax);
12454: free_ivector(Tage,1,NCOVMAX);
12455: free_ivector(Tmodelind,1,NCOVMAX);
1.228 brouard 12456: free_ivector(TmodelInvind,1,NCOVMAX);
12457: free_ivector(TmodelInvQind,1,NCOVMAX);
1.227 brouard 12458:
12459: free_imatrix(nbcode,0,NCOVMAX,0,NCOVMAX);
12460: /* free_imatrix(codtab,1,100,1,10); */
1.126 brouard 12461: fflush(fichtm);
12462: fflush(ficgp);
12463:
1.227 brouard 12464:
1.126 brouard 12465: if((nberr >0) || (nbwarn>0)){
1.216 brouard 12466: printf("End of Imach with %d errors and/or %d warnings. Please look at the log file for details.\n",nberr,nbwarn);
12467: 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 12468: }else{
12469: printf("End of Imach\n");
12470: fprintf(ficlog,"End of Imach\n");
12471: }
12472: printf("See log file on %s\n",filelog);
12473: /* gettimeofday(&end_time, (struct timezone*)0);*/ /* after time */
1.157 brouard 12474: /*(void) gettimeofday(&end_time,&tzp);*/
12475: rend_time = time(NULL);
12476: end_time = *localtime(&rend_time);
12477: /* tml = *localtime(&end_time.tm_sec); */
12478: strcpy(strtend,asctime(&end_time));
1.126 brouard 12479: printf("Local time at start %s\nLocal time at end %s",strstart, strtend);
12480: fprintf(ficlog,"Local time at start %s\nLocal time at end %s\n",strstart, strtend);
1.157 brouard 12481: printf("Total time used %s\n", asc_diff_time(rend_time -rstart_time,tmpout));
1.227 brouard 12482:
1.157 brouard 12483: printf("Total time was %.0lf Sec.\n", difftime(rend_time,rstart_time));
12484: fprintf(ficlog,"Total time used %s\n", asc_diff_time(rend_time -rstart_time,tmpout));
12485: fprintf(ficlog,"Total time was %.0lf Sec.\n", difftime(rend_time,rstart_time));
1.126 brouard 12486: /* printf("Total time was %d uSec.\n", total_usecs);*/
12487: /* if(fileappend(fichtm,optionfilehtm)){ */
12488: fprintf(fichtm,"<br>Local time at start %s<br>Local time at end %s<br>\n</body></html>",strstart, strtend);
12489: fclose(fichtm);
12490: fprintf(fichtmcov,"<br>Local time at start %s<br>Local time at end %s<br>\n</body></html>",strstart, strtend);
12491: fclose(fichtmcov);
12492: fclose(ficgp);
12493: fclose(ficlog);
12494: /*------ End -----------*/
1.227 brouard 12495:
12496:
12497: printf("Before Current directory %s!\n",pathcd);
1.184 brouard 12498: #ifdef WIN32
1.227 brouard 12499: if (_chdir(pathcd) != 0)
12500: printf("Can't move to directory %s!\n",path);
12501: if(_getcwd(pathcd,MAXLINE) > 0)
1.184 brouard 12502: #else
1.227 brouard 12503: if(chdir(pathcd) != 0)
12504: printf("Can't move to directory %s!\n", path);
12505: if (getcwd(pathcd, MAXLINE) > 0)
1.184 brouard 12506: #endif
1.126 brouard 12507: printf("Current directory %s!\n",pathcd);
12508: /*strcat(plotcmd,CHARSEPARATOR);*/
12509: sprintf(plotcmd,"gnuplot");
1.157 brouard 12510: #ifdef _WIN32
1.126 brouard 12511: sprintf(plotcmd,"\"%sgnuplot.exe\"",pathimach);
12512: #endif
12513: if(!stat(plotcmd,&info)){
1.158 brouard 12514: printf("Error or gnuplot program not found: '%s'\n",plotcmd);fflush(stdout);
1.126 brouard 12515: if(!stat(getenv("GNUPLOTBIN"),&info)){
1.158 brouard 12516: printf("Error or gnuplot program not found: '%s' Environment GNUPLOTBIN not set.\n",plotcmd);fflush(stdout);
1.126 brouard 12517: }else
12518: strcpy(pplotcmd,plotcmd);
1.157 brouard 12519: #ifdef __unix
1.126 brouard 12520: strcpy(plotcmd,GNUPLOTPROGRAM);
12521: if(!stat(plotcmd,&info)){
1.158 brouard 12522: printf("Error gnuplot program not found: '%s'\n",plotcmd);fflush(stdout);
1.126 brouard 12523: }else
12524: strcpy(pplotcmd,plotcmd);
12525: #endif
12526: }else
12527: strcpy(pplotcmd,plotcmd);
12528:
12529: sprintf(plotcmd,"%s %s",pplotcmd, optionfilegnuplot);
1.158 brouard 12530: printf("Starting graphs with: '%s'\n",plotcmd);fflush(stdout);
1.227 brouard 12531:
1.126 brouard 12532: if((outcmd=system(plotcmd)) != 0){
1.158 brouard 12533: printf("gnuplot command might not be in your path: '%s', err=%d\n", plotcmd, outcmd);
1.154 brouard 12534: printf("\n Trying if gnuplot resides on the same directory that IMaCh\n");
1.152 brouard 12535: sprintf(plotcmd,"%sgnuplot %s", pathimach, optionfilegnuplot);
1.150 brouard 12536: if((outcmd=system(plotcmd)) != 0)
1.153 brouard 12537: printf("\n Still a problem with gnuplot command %s, err=%d\n", plotcmd, outcmd);
1.126 brouard 12538: }
1.158 brouard 12539: printf(" Successful, please wait...");
1.126 brouard 12540: while (z[0] != 'q') {
12541: /* chdir(path); */
1.154 brouard 12542: printf("\nType e to edit results with your browser, g to graph again and q for exit: ");
1.126 brouard 12543: scanf("%s",z);
12544: /* if (z[0] == 'c') system("./imach"); */
12545: if (z[0] == 'e') {
1.158 brouard 12546: #ifdef __APPLE__
1.152 brouard 12547: sprintf(pplotcmd, "open %s", optionfilehtm);
1.157 brouard 12548: #elif __linux
12549: sprintf(pplotcmd, "xdg-open %s", optionfilehtm);
1.153 brouard 12550: #else
1.152 brouard 12551: sprintf(pplotcmd, "%s", optionfilehtm);
1.153 brouard 12552: #endif
12553: printf("Starting browser with: %s",pplotcmd);fflush(stdout);
12554: system(pplotcmd);
1.126 brouard 12555: }
12556: else if (z[0] == 'g') system(plotcmd);
12557: else if (z[0] == 'q') exit(0);
12558: }
1.227 brouard 12559: end:
1.126 brouard 12560: while (z[0] != 'q') {
1.195 brouard 12561: printf("\nType q for exiting: "); fflush(stdout);
1.126 brouard 12562: scanf("%s",z);
12563: }
12564: }
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