--- imach/src/imach.c 2000/12/28 18:49:56 1.1.1.1 +++ imach/src/imach.c 2016/12/15 11:59:41 1.253 @@ -1,93 +1,1084 @@ - -/*********************** Imach ************************************** - This program computes Healthy Life Expectancies from cross-longitudinal - data. Cross-longitudinal consist in a first survey ("cross") where - individuals from different ages are interviewed on their health status - or degree of disability. At least a second wave of interviews - ("longitudinal") should measure each new individual health status. - Health expectancies are computed from the transistions observed between - waves and are computed for each degree of severity of disability (number - of life states). More degrees you consider, more time is necessary to - reach the Maximum Likekilhood of the parameters involved in the model. - The simplest model is the multinomial logistic model where pij is - the probabibility to be observed in state j at the second wave conditional - to be observed in state i at the first wave. Therefore the model is: - log(pij/pii)= aij + bij*age+ cij*sex + etc , where 'age' is age and 'sex' - is a covariate. If you want to have a more complex model than "constant and - age", you should modify the program where the markup - *Covariates have to be included here again* invites you to do it. - More covariates you add, less is the speed of the convergence. - - The advantage that this computer programme claims, comes from that if the - delay between waves is not identical for each individual, or if some - individual missed an interview, the information is not rounded or lost, but - taken into account using an interpolation or extrapolation. - hPijx is the probability to be - observed in state i at age x+h conditional to the observed state i at age - x. The delay 'h' can be split into an exact number (nh*stepm) of - unobserved intermediate states. This elementary transition (by month or - quarter trimester, semester or year) is model as a multinomial logistic. - The hPx matrix is simply the matrix product of nh*stepm elementary matrices - and the contribution of each individual to the likelihood is simply hPijx. +/* $Id: imach.c,v 1.253 2016/12/15 11:59:41 brouard Exp $ + $State: Exp $ + $Log: imach.c,v $ + Revision 1.253 2016/12/15 11:59:41 brouard + Summary: 0.99 in progress + + Revision 1.252 2016/09/15 21:15:37 brouard + *** empty log message *** + + Revision 1.251 2016/09/15 15:01:13 brouard + Summary: not working + + Revision 1.250 2016/09/08 16:07:27 brouard + Summary: continue + + Revision 1.249 2016/09/07 17:14:18 brouard + Summary: Starting values from frequencies + + Revision 1.248 2016/09/07 14:10:18 brouard + *** empty log message *** + + Revision 1.247 2016/09/02 11:11:21 brouard + *** empty log message *** + + Revision 1.246 2016/09/02 08:49:22 brouard + *** empty log message *** + + Revision 1.245 2016/09/02 07:25:01 brouard + *** empty log message *** + + Revision 1.244 2016/09/02 07:17:34 brouard + *** empty log message *** + + Revision 1.243 2016/09/02 06:45:35 brouard + *** empty log message *** + + Revision 1.242 2016/08/30 15:01:20 brouard + Summary: Fixing a lots + + Revision 1.241 2016/08/29 17:17:25 brouard + Summary: gnuplot problem in Back projection to fix + + Revision 1.240 2016/08/29 07:53:18 brouard + Summary: Better + + Revision 1.239 2016/08/26 15:51:03 brouard + Summary: Improvement in Powell output in order to copy and paste + + Author: + + Revision 1.238 2016/08/26 14:23:35 brouard + Summary: Starting tests of 0.99 + + Revision 1.237 2016/08/26 09:20:19 brouard + Summary: to valgrind + + Revision 1.236 2016/08/25 10:50:18 brouard + *** empty log message *** + + Revision 1.235 2016/08/25 06:59:23 brouard + *** empty log message *** + + Revision 1.234 2016/08/23 16:51:20 brouard + *** empty log message *** + + Revision 1.233 2016/08/23 07:40:50 brouard + Summary: not working + + Revision 1.232 2016/08/22 14:20:21 brouard + Summary: not working + + Revision 1.231 2016/08/22 07:17:15 brouard + Summary: not working + + Revision 1.230 2016/08/22 06:55:53 brouard + Summary: Not working + + Revision 1.229 2016/07/23 09:45:53 brouard + Summary: Completing for func too + + Revision 1.228 2016/07/22 17:45:30 brouard + Summary: Fixing some arrays, still debugging + + Revision 1.226 2016/07/12 18:42:34 brouard + Summary: temp + + Revision 1.225 2016/07/12 08:40:03 brouard + Summary: saving but not running + + Revision 1.224 2016/07/01 13:16:01 brouard + Summary: Fixes + + Revision 1.223 2016/02/19 09:23:35 brouard + Summary: temporary + + Revision 1.222 2016/02/17 08:14:50 brouard + Summary: Probably last 0.98 stable version 0.98r6 + + Revision 1.221 2016/02/15 23:35:36 brouard + Summary: minor bug + + Revision 1.219 2016/02/15 00:48:12 brouard + *** empty log message *** + + Revision 1.218 2016/02/12 11:29:23 brouard + Summary: 0.99 Back projections + + Revision 1.217 2015/12/23 17:18:31 brouard + Summary: Experimental backcast + + Revision 1.216 2015/12/18 17:32:11 brouard + Summary: 0.98r4 Warning and status=-2 + + Version 0.98r4 is now: + - displaying an error when status is -1, date of interview unknown and date of death known; + - permitting a status -2 when the vital status is unknown at a known date of right truncation. + Older changes concerning s=-2, dating from 2005 have been supersed. + + Revision 1.215 2015/12/16 08:52:24 brouard + Summary: 0.98r4 working + + Revision 1.214 2015/12/16 06:57:54 brouard + Summary: temporary not working + + Revision 1.213 2015/12/11 18:22:17 brouard + Summary: 0.98r4 + + Revision 1.212 2015/11/21 12:47:24 brouard + Summary: minor typo + + Revision 1.211 2015/11/21 12:41:11 brouard + Summary: 0.98r3 with some graph of projected cross-sectional + + Author: Nicolas Brouard + + Revision 1.210 2015/11/18 17:41:20 brouard + Summary: Start working on projected prevalences Revision 1.209 2015/11/17 22:12:03 brouard + Summary: Adding ftolpl parameter + Author: N Brouard + + We had difficulties to get smoothed confidence intervals. It was due + to the period prevalence which wasn't computed accurately. The inner + parameter ftolpl is now an outer parameter of the .imach parameter + file after estepm. If ftolpl is small 1.e-4 and estepm too, + computation are long. + + Revision 1.208 2015/11/17 14:31:57 brouard + Summary: temporary + + Revision 1.207 2015/10/27 17:36:57 brouard + *** empty log message *** + + Revision 1.206 2015/10/24 07:14:11 brouard + *** empty log message *** + + Revision 1.205 2015/10/23 15:50:53 brouard + Summary: 0.98r3 some clarification for graphs on likelihood contributions + + Revision 1.204 2015/10/01 16:20:26 brouard + Summary: Some new graphs of contribution to likelihood + + Revision 1.203 2015/09/30 17:45:14 brouard + Summary: looking at better estimation of the hessian + + Also a better criteria for convergence to the period prevalence And + therefore adding the number of years needed to converge. (The + prevalence in any alive state shold sum to one + + Revision 1.202 2015/09/22 19:45:16 brouard + Summary: Adding some overall graph on contribution to likelihood. Might change + + Revision 1.201 2015/09/15 17:34:58 brouard + Summary: 0.98r0 + + - Some new graphs like suvival functions + - Some bugs fixed like model=1+age+V2. + + Revision 1.200 2015/09/09 16:53:55 brouard + Summary: Big bug thanks to Flavia + + Even model=1+age+V2. did not work anymore + + Revision 1.199 2015/09/07 14:09:23 brouard + Summary: 0.98q6 changing default small png format for graph to vectorized svg. + + Revision 1.198 2015/09/03 07:14:39 brouard + Summary: 0.98q5 Flavia + + Revision 1.197 2015/09/01 18:24:39 brouard + *** empty log message *** + + Revision 1.196 2015/08/18 23:17:52 brouard + Summary: 0.98q5 + + Revision 1.195 2015/08/18 16:28:39 brouard + Summary: Adding a hack for testing purpose + + After reading the title, ftol and model lines, if the comment line has + a q, starting with #q, the answer at the end of the run is quit. It + permits to run test files in batch with ctest. The former workaround was + $ echo q | imach foo.imach + + Revision 1.194 2015/08/18 13:32:00 brouard + Summary: Adding error when the covariance matrix doesn't contain the exact number of lines required by the model line. + + Revision 1.193 2015/08/04 07:17:42 brouard + Summary: 0.98q4 + + Revision 1.192 2015/07/16 16:49:02 brouard + Summary: Fixing some outputs + + Revision 1.191 2015/07/14 10:00:33 brouard + Summary: Some fixes + + Revision 1.190 2015/05/05 08:51:13 brouard + Summary: Adding digits in output parameters (7 digits instead of 6) + + Fix 1+age+. + + Revision 1.189 2015/04/30 14:45:16 brouard + Summary: 0.98q2 + + Revision 1.188 2015/04/30 08:27:53 brouard + *** empty log message *** + + Revision 1.187 2015/04/29 09:11:15 brouard + *** empty log message *** + + Revision 1.186 2015/04/23 12:01:52 brouard + Summary: V1*age is working now, version 0.98q1 + + Some codes had been disabled in order to simplify and Vn*age was + working in the optimization phase, ie, giving correct MLE parameters, + but, as usual, outputs were not correct and program core dumped. + + Revision 1.185 2015/03/11 13:26:42 brouard + Summary: Inclusion of compile and links command line for Intel Compiler + + Revision 1.184 2015/03/11 11:52:39 brouard + Summary: Back from Windows 8. Intel Compiler + + Revision 1.183 2015/03/10 20:34:32 brouard + Summary: 0.98q0, trying with directest, mnbrak fixed + + We use directest instead of original Powell test; probably no + incidence on the results, but better justifications; + We fixed Numerical Recipes mnbrak routine which was wrong and gave + wrong results. + + Revision 1.182 2015/02/12 08:19:57 brouard + Summary: Trying to keep directest which seems simpler and more general + Author: Nicolas Brouard + + Revision 1.181 2015/02/11 23:22:24 brouard + Summary: Comments on Powell added + + Author: + + Revision 1.180 2015/02/11 17:33:45 brouard + Summary: Finishing move from main to function (hpijx and prevalence_limit) + + Revision 1.179 2015/01/04 09:57:06 brouard + Summary: back to OS/X + + Revision 1.178 2015/01/04 09:35:48 brouard + *** empty log message *** + + Revision 1.177 2015/01/03 18:40:56 brouard + Summary: Still testing ilc32 on OSX + + Revision 1.176 2015/01/03 16:45:04 brouard + *** empty log message *** + + Revision 1.175 2015/01/03 16:33:42 brouard + *** empty log message *** + + Revision 1.174 2015/01/03 16:15:49 brouard + Summary: Still in cross-compilation + + Revision 1.173 2015/01/03 12:06:26 brouard + Summary: trying to detect cross-compilation + + Revision 1.172 2014/12/27 12:07:47 brouard + Summary: Back from Visual Studio and Intel, options for compiling for Windows XP + + Revision 1.171 2014/12/23 13:26:59 brouard + Summary: Back from Visual C + + Still problem with utsname.h on Windows + + Revision 1.170 2014/12/23 11:17:12 brouard + Summary: Cleaning some \%% back to %% + + The escape was mandatory for a specific compiler (which one?), but too many warnings. + + Revision 1.169 2014/12/22 23:08:31 brouard + Summary: 0.98p + + Outputs some informations on compiler used, OS etc. Testing on different platforms. + + Revision 1.168 2014/12/22 15:17:42 brouard + Summary: update + + Revision 1.167 2014/12/22 13:50:56 brouard + Summary: Testing uname and compiler version and if compiled 32 or 64 + + Testing on Linux 64 + + Revision 1.166 2014/12/22 11:40:47 brouard + *** empty log message *** + + Revision 1.165 2014/12/16 11:20:36 brouard + Summary: After compiling on Visual C + + * imach.c (Module): Merging 1.61 to 1.162 + + Revision 1.164 2014/12/16 10:52:11 brouard + Summary: Merging with Visual C after suppressing some warnings for unused variables. Also fixing Saito's bug 0.98Xn + + * imach.c (Module): Merging 1.61 to 1.162 + + Revision 1.163 2014/12/16 10:30:11 brouard + * imach.c (Module): Merging 1.61 to 1.162 + + Revision 1.162 2014/09/25 11:43:39 brouard + Summary: temporary backup 0.99! + + Revision 1.1 2014/09/16 11:06:58 brouard + Summary: With some code (wrong) for nlopt + + Author: + + Revision 1.161 2014/09/15 20:41:41 brouard + Summary: Problem with macro SQR on Intel compiler + + Revision 1.160 2014/09/02 09:24:05 brouard + *** empty log message *** + + Revision 1.159 2014/09/01 10:34:10 brouard + Summary: WIN32 + Author: Brouard + + Revision 1.158 2014/08/27 17:11:51 brouard + *** empty log message *** + + Revision 1.157 2014/08/27 16:26:55 brouard + Summary: Preparing windows Visual studio version + Author: Brouard + + In order to compile on Visual studio, time.h is now correct and time_t + and tm struct should be used. difftime should be used but sometimes I + just make the differences in raw time format (time(&now). + Trying to suppress #ifdef LINUX + Add xdg-open for __linux in order to open default browser. + + Revision 1.156 2014/08/25 20:10:10 brouard + *** empty log message *** + + Revision 1.155 2014/08/25 18:32:34 brouard + Summary: New compile, minor changes + Author: Brouard + + Revision 1.154 2014/06/20 17:32:08 brouard + Summary: Outputs now all graphs of convergence to period prevalence + + Revision 1.153 2014/06/20 16:45:46 brouard + Summary: If 3 live state, convergence to period prevalence on same graph + Author: Brouard + + Revision 1.152 2014/06/18 17:54:09 brouard + Summary: open browser, use gnuplot on same dir than imach if not found in the path + + Revision 1.151 2014/06/18 16:43:30 brouard + *** empty log message *** + + Revision 1.150 2014/06/18 16:42:35 brouard + Summary: If gnuplot is not in the path try on same directory than imach binary (OSX) + Author: brouard + + Revision 1.149 2014/06/18 15:51:14 brouard + Summary: Some fixes in parameter files errors + Author: Nicolas Brouard + + Revision 1.148 2014/06/17 17:38:48 brouard + Summary: Nothing new + Author: Brouard + + Just a new packaging for OS/X version 0.98nS + + Revision 1.147 2014/06/16 10:33:11 brouard + *** empty log message *** + + Revision 1.146 2014/06/16 10:20:28 brouard + Summary: Merge + Author: Brouard + + Merge, before building revised version. + + Revision 1.145 2014/06/10 21:23:15 brouard + Summary: Debugging with valgrind + Author: Nicolas Brouard + + Lot of changes in order to output the results with some covariates + After the Edimburgh REVES conference 2014, it seems mandatory to + improve the code. + No more memory valgrind error but a lot has to be done in order to + continue the work of splitting the code into subroutines. + Also, decodemodel has been improved. Tricode is still not + optimal. nbcode should be improved. Documentation has been added in + the source code. + + Revision 1.143 2014/01/26 09:45:38 brouard + Summary: Version 0.98nR (to be improved, but gives same optimization results as 0.98k. Nice, promising + + * imach.c (Module): Trying to merge old staffs together while being at Tokyo. Not tested... + (Module): Version 0.98nR Running ok, but output format still only works for three covariates. + + Revision 1.142 2014/01/26 03:57:36 brouard + Summary: gnuplot changed plot w l 1 has to be changed to plot w l lt 2 + + * imach.c (Module): Trying to merge old staffs together while being at Tokyo. Not tested... + + Revision 1.141 2014/01/26 02:42:01 brouard + * imach.c (Module): Trying to merge old staffs together while being at Tokyo. Not tested... + + Revision 1.140 2011/09/02 10:37:54 brouard + Summary: times.h is ok with mingw32 now. + + Revision 1.139 2010/06/14 07:50:17 brouard + After the theft of my laptop, I probably lost some lines of codes which were not uploaded to the CVS tree. + I remember having already fixed agemin agemax which are pointers now but not cvs saved. + + Revision 1.138 2010/04/30 18:19:40 brouard + *** empty log message *** + + Revision 1.137 2010/04/29 18:11:38 brouard + (Module): Checking covariates for more complex models + than V1+V2. A lot of change to be done. Unstable. + + Revision 1.136 2010/04/26 20:30:53 brouard + (Module): merging some libgsl code. Fixing computation + of likelione (using inter/intrapolation if mle = 0) in order to + get same likelihood as if mle=1. + Some cleaning of code and comments added. + + Revision 1.135 2009/10/29 15:33:14 brouard + (Module): Now imach stops if date of birth, at least year of birth, is not given. Some cleaning of the code. + + Revision 1.134 2009/10/29 13:18:53 brouard + (Module): Now imach stops if date of birth, at least year of birth, is not given. Some cleaning of the code. + + Revision 1.133 2009/07/06 10:21:25 brouard + just nforces + + Revision 1.132 2009/07/06 08:22:05 brouard + Many tings + + Revision 1.131 2009/06/20 16:22:47 brouard + Some dimensions resccaled + + Revision 1.130 2009/05/26 06:44:34 brouard + (Module): Max Covariate is now set to 20 instead of 8. A + lot of cleaning with variables initialized to 0. Trying to make + V2+V3*age+V1+V4 strb=V3*age+V1+V4 working better. + + Revision 1.129 2007/08/31 13:49:27 lievre + Modification of the way of exiting when the covariate is not binary in order to see on the window the error message before exiting + + Revision 1.128 2006/06/30 13:02:05 brouard + (Module): Clarifications on computing e.j + + Revision 1.127 2006/04/28 18:11:50 brouard + (Module): Yes the sum of survivors was wrong since + imach-114 because nhstepm was no more computed in the age + loop. Now we define nhstepma in the age loop. + (Module): In order to speed up (in case of numerous covariates) we + compute health expectancies (without variances) in a first step + and then all the health expectancies with variances or standard + deviation (needs data from the Hessian matrices) which slows the + computation. + In the future we should be able to stop the program is only health + expectancies and graph are needed without standard deviations. + + Revision 1.126 2006/04/28 17:23:28 brouard + (Module): Yes the sum of survivors was wrong since + imach-114 because nhstepm was no more computed in the age + loop. Now we define nhstepma in the age loop. + Version 0.98h + + Revision 1.125 2006/04/04 15:20:31 lievre + Errors in calculation of health expectancies. Age was not initialized. + Forecasting file added. + + Revision 1.124 2006/03/22 17:13:53 lievre + Parameters are printed with %lf instead of %f (more numbers after the comma). + The log-likelihood is printed in the log file + + Revision 1.123 2006/03/20 10:52:43 brouard + * imach.c (Module): changed, corresponds to .htm file + name. <head> headers where missing. + + * imach.c (Module): Weights can have a decimal point as for + English (a comma might work with a correct LC_NUMERIC environment, + otherwise the weight is truncated). + Modification of warning when the covariates values are not 0 or + 1. + Version 0.98g + + Revision 1.122 2006/03/20 09:45:41 brouard + (Module): Weights can have a decimal point as for + English (a comma might work with a correct LC_NUMERIC environment, + otherwise the weight is truncated). + Modification of warning when the covariates values are not 0 or + 1. + Version 0.98g + + Revision 1.121 2006/03/16 17:45:01 lievre + * imach.c (Module): Comments concerning covariates added + + * imach.c (Module): refinements in the computation of lli if + status=-2 in order to have more reliable computation if stepm is + not 1 month. Version 0.98f + + Revision 1.120 2006/03/16 15:10:38 lievre + (Module): refinements in the computation of lli if + status=-2 in order to have more reliable computation if stepm is + not 1 month. Version 0.98f + + Revision 1.119 2006/03/15 17:42:26 brouard + (Module): Bug if status = -2, the loglikelihood was + computed as likelihood omitting the logarithm. Version O.98e + + Revision 1.118 2006/03/14 18:20:07 brouard + (Module): varevsij Comments added explaining the second + table of variances if popbased=1 . + (Module): Covariances of eij, ekl added, graphs fixed, new html link. + (Module): Function pstamp added + (Module): Version 0.98d + + Revision 1.117 2006/03/14 17:16:22 brouard + (Module): varevsij Comments added explaining the second + table of variances if popbased=1 . + (Module): Covariances of eij, ekl added, graphs fixed, new html link. + (Module): Function pstamp added + (Module): Version 0.98d + + Revision 1.116 2006/03/06 10:29:27 brouard + (Module): Variance-covariance wrong links and + varian-covariance of ej. is needed (Saito). + + Revision 1.115 2006/02/27 12:17:45 brouard + (Module): One freematrix added in mlikeli! 0.98c + + Revision 1.114 2006/02/26 12:57:58 brouard + (Module): Some improvements in processing parameter + filename with strsep. + + Revision 1.113 2006/02/24 14:20:24 brouard + (Module): Memory leaks checks with valgrind and: + datafile was not closed, some imatrix were not freed and on matrix + allocation too. + + Revision 1.112 2006/01/30 09:55:26 brouard + (Module): Back to gnuplot.exe instead of wgnuplot.exe + + Revision 1.111 2006/01/25 20:38:18 brouard + (Module): Lots of cleaning and bugs added (Gompertz) + (Module): Comments can be added in data file. Missing date values + can be a simple dot '.'. + + Revision 1.110 2006/01/25 00:51:50 brouard + (Module): Lots of cleaning and bugs added (Gompertz) + + Revision 1.109 2006/01/24 19:37:15 brouard + (Module): Comments (lines starting with a #) are allowed in data. + + Revision 1.108 2006/01/19 18:05:42 lievre + Gnuplot problem appeared... + To be fixed + + Revision 1.107 2006/01/19 16:20:37 brouard + Test existence of gnuplot in imach path + + Revision 1.106 2006/01/19 13:24:36 brouard + Some cleaning and links added in html output + + Revision 1.105 2006/01/05 20:23:19 lievre + *** empty log message *** + + Revision 1.104 2005/09/30 16:11:43 lievre + (Module): sump fixed, loop imx fixed, and simplifications. + (Module): If the status is missing at the last wave but we know + that the person is alive, then we can code his/her status as -2 + (instead of missing=-1 in earlier versions) and his/her + contributions to the likelihood is 1 - Prob of dying from last + health status (= 1-p13= p11+p12 in the easiest case of somebody in + the healthy state at last known wave). Version is 0.98 + + Revision 1.103 2005/09/30 15:54:49 lievre + (Module): sump fixed, loop imx fixed, and simplifications. + + Revision 1.102 2004/09/15 17:31:30 brouard + Add the possibility to read data file including tab characters. + + Revision 1.101 2004/09/15 10:38:38 brouard + Fix on curr_time + + Revision 1.100 2004/07/12 18:29:06 brouard + Add version for Mac OS X. Just define UNIX in Makefile + + Revision 1.99 2004/06/05 08:57:40 brouard + *** empty log message *** + + Revision 1.98 2004/05/16 15:05:56 brouard + New version 0.97 . First attempt to estimate force of mortality + directly from the data i.e. without the need of knowing the health + state at each age, but using a Gompertz model: log u =a + b*age . + This is the basic analysis of mortality and should be done before any + other analysis, in order to test if the mortality estimated from the + cross-longitudinal survey is different from the mortality estimated + from other sources like vital statistic data. + + The same imach parameter file can be used but the option for mle should be -3. + + Agnès, who wrote this part of the code, tried to keep most of the + former routines in order to include the new code within the former code. + + The output is very simple: only an estimate of the intercept and of + the slope with 95% confident intervals. + + Current limitations: + A) Even if you enter covariates, i.e. with the + model= V1+V2 equation for example, the programm does only estimate a unique global model without covariates. + B) There is no computation of Life Expectancy nor Life Table. + + Revision 1.97 2004/02/20 13:25:42 lievre + Version 0.96d. Population forecasting command line is (temporarily) + suppressed. + + Revision 1.96 2003/07/15 15:38:55 brouard + * imach.c (Repository): Errors in subdirf, 2, 3 while printing tmpout is + rewritten within the same printf. Workaround: many printfs. + + Revision 1.95 2003/07/08 07:54:34 brouard + * imach.c (Repository): + (Repository): Using imachwizard code to output a more meaningful covariance + matrix (cov(a12,c31) instead of numbers. + + Revision 1.94 2003/06/27 13:00:02 brouard + Just cleaning + + Revision 1.93 2003/06/25 16:33:55 brouard + (Module): On windows (cygwin) function asctime_r doesn't + exist so I changed back to asctime which exists. + (Module): Version 0.96b + + Revision 1.92 2003/06/25 16:30:45 brouard + (Module): On windows (cygwin) function asctime_r doesn't + exist so I changed back to asctime which exists. + + Revision 1.91 2003/06/25 15:30:29 brouard + * imach.c (Repository): Duplicated warning errors corrected. + (Repository): Elapsed time after each iteration is now output. It + helps to forecast when convergence will be reached. Elapsed time + is stamped in powell. We created a new html file for the graphs + concerning matrix of covariance. It has extension -cov.htm. + + Revision 1.90 2003/06/24 12:34:15 brouard + (Module): Some bugs corrected for windows. Also, when + mle=-1 a template is output in file "or"mypar.txt with the design + of the covariance matrix to be input. + + Revision 1.89 2003/06/24 12:30:52 brouard + (Module): Some bugs corrected for windows. Also, when + mle=-1 a template is output in file "or"mypar.txt with the design + of the covariance matrix to be input. + + Revision 1.88 2003/06/23 17:54:56 brouard + * 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. + + Revision 1.87 2003/06/18 12:26:01 brouard + Version 0.96 + + Revision 1.86 2003/06/17 20:04:08 brouard + (Module): Change position of html and gnuplot routines and added + routine fileappend. + + Revision 1.85 2003/06/17 13:12:43 brouard + * imach.c (Repository): Check when date of death was earlier that + current date of interview. It may happen when the death was just + prior to the death. In this case, dh was negative and likelihood + was wrong (infinity). We still send an "Error" but patch by + assuming that the date of death was just one stepm after the + interview. + (Repository): Because some people have very long ID (first column) + we changed int to long in num[] and we added a new lvector for + memory allocation. But we also truncated to 8 characters (left + truncation) + (Repository): No more line truncation errors. + + Revision 1.84 2003/06/13 21:44:43 brouard + * imach.c (Repository): Replace "freqsummary" at a correct + place. It differs from routine "prevalence" which may be called + many times. Probs is memory consuming and must be used with + parcimony. + Version 0.95a3 (should output exactly the same maximization than 0.8a2) + + Revision 1.83 2003/06/10 13:39:11 lievre + *** empty log message *** + + Revision 1.82 2003/06/05 15:57:20 brouard + Add log in imach.c and fullversion number is now printed. + +*/ +/* + Interpolated Markov Chain + + Short summary of the programme: + + This program computes Healthy Life Expectancies or State-specific + (if states aren't health statuses) Expectancies from + cross-longitudinal data. Cross-longitudinal data consist in: + + -1- a first survey ("cross") where individuals from different ages + are interviewed on their health status or degree of disability (in + the case of a health survey which is our main interest) + + -2- at least a second wave of interviews ("longitudinal") which + measure each change (if any) in individual health status. Health + expectancies are computed from the time spent in each health state + according to a model. More health states you consider, more time is + necessary to reach the Maximum Likelihood of the parameters involved + in the model. The simplest model is the multinomial logistic model + where pij is the probability to be observed in state j at the second + wave conditional to be observed in state i at the first + wave. Therefore the model is: log(pij/pii)= aij + bij*age+ cij*sex + + etc , where 'age' is age and 'sex' is a covariate. If you want to + have a more complex model than "constant and age", you should modify + the program where the markup *Covariates have to be included here + again* invites you to do it. More covariates you add, slower the + convergence. + + The advantage of this computer programme, compared to a simple + multinomial logistic model, is clear when the delay between waves is not + identical for each individual. Also, if a individual missed an + intermediate interview, the information is lost, but taken into + account using an interpolation or extrapolation. + + hPijx is the probability to be observed in state i at age x+h + conditional to the observed state i at age x. The delay 'h' can be + split into an exact number (nh*stepm) of unobserved intermediate + states. This elementary transition (by month, quarter, + semester or year) is modelled as a multinomial logistic. The hPx + matrix is simply the matrix product of nh*stepm elementary matrices + and the contribution of each individual to the likelihood is simply + hPijx. Also this programme outputs the covariance matrix of the parameters but also - of the life expectancies. It also computes the prevalence limits. + of the life expectancies. It also computes the period (stable) prevalence. + +Back prevalence and projections: + + - 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) + + Computes the back prevalence limit for any combination of + covariate values k at any age between ageminpar and agemaxpar and + returns it in **bprlim. In the loops, + + - **bprevalim(**bprlim, ***mobaverage, nlstate, *p, age, **oldm, + **savm, **dnewm, **doldm, **dsavm, ftolpl, ncvyearp, k); + + - hBijx Back Probability to be in state i at age x-h being in j at x + Computes for any combination of covariates k and any age between bage and fage + p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); + oldm=oldms;savm=savms; + + - hbxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k); + Computes the transition matrix starting at age 'age' over + 'nhstepm*hstepm*stepm' months (i.e. until + age (in years) age+nhstepm*hstepm*stepm/12) by multiplying + nhstepm*hstepm matrices. + + Returns p3mat[i][j][h] after calling + p3mat[i][j][h]=matprod2(newm, + bmij(pmmij,cov,ncovmodel,x,nlstate,prevacurrent, dnewm, doldm, + dsavm,ij),\ 1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, + oldm); + +Important routines + +- func (or funcone), computes logit (pij) distinguishing + o fixed variables (single or product dummies or quantitative); + o varying variables by: + (1) wave (single, product dummies, quantitative), + (2) by age (can be month) age (done), age*age (done), age*Vn where Vn can be: + % fixed dummy (treated) or quantitative (not done because time-consuming); + % varying dummy (not done) or quantitative (not done); +- Tricode which tests the modality of dummy variables (in order to warn with wrong or empty modalities) + and returns the number of efficient covariates cptcoveff and modalities nbcode[Tvar[k]][1]= 0 and nbcode[Tvar[k]][2]= 1 usually. +- printinghtml which outputs results like life expectancy in and from a state for a combination of modalities of dummy variables + o There are 2*cptcoveff combinations of (0,1) for cptcoveff variables. Outputting only combinations with people, éliminating 1 1 if + race White (0 0), Black vs White (1 0), Hispanic (0 1) and 1 1 being meaningless. + + - Authors: Nicolas Brouard (brouard@ined.fr) and Agnès Lièvre (lievre@ined.fr). - Institut national d'études démographiques, Paris. + Authors: Nicolas Brouard (brouard@ined.fr) and Agnès Lièvre (lievre@ined.fr). + Institut national d'études démographiques, Paris. This software have been partly granted by Euro-REVES, a concerted action from the European Union. It is copyrighted identically to a GNU software product, ie programme and software can be distributed freely for non commercial use. Latest version can be accessed at http://euroreves.ined.fr/imach . + + Help to debug: LD_PRELOAD=/usr/local/lib/libnjamd.so ./imach foo.imach + or better on gdb : set env LD_PRELOAD=/usr/local/lib/libnjamd.so + **********************************************************************/ - +/* + main + read parameterfile + read datafile + concatwav + freqsummary + if (mle >= 1) + mlikeli + print results files + if mle==1 + computes hessian + read end of parameter file: agemin, agemax, bage, fage, estepm + begin-prev-date,... + open gnuplot file + open html file + period (stable) prevalence | pl_nom 1-1 2-2 etc by covariate + for age prevalim() | #****** V1=0 V2=1 V3=1 V4=0 ****** + | 65 1 0 2 1 3 1 4 0 0.96326 0.03674 + freexexit2 possible for memory heap. + + h Pij x | pij_nom ficrestpij + # Cov Agex agex+h hpijx with i,j= 1-1 1-2 1-3 2-1 2-2 2-3 + 1 85 85 1.00000 0.00000 0.00000 0.00000 1.00000 0.00000 + 1 85 86 0.68299 0.22291 0.09410 0.71093 0.00000 0.28907 + + 1 65 99 0.00364 0.00322 0.99314 0.00350 0.00310 0.99340 + 1 65 100 0.00214 0.00204 0.99581 0.00206 0.00196 0.99597 + variance of p one-step probabilities varprob | prob_nom ficresprob #One-step probabilities and stand. devi in () + Standard deviation of one-step probabilities | probcor_nom ficresprobcor #One-step probabilities and correlation matrix + Matrix of variance covariance of one-step probabilities | probcov_nom ficresprobcov #One-step probabilities and covariance matrix + + forecasting if prevfcast==1 prevforecast call prevalence() + health expectancies + Variance-covariance of DFLE + prevalence() + movingaverage() + varevsij() + if popbased==1 varevsij(,popbased) + total life expectancies + Variance of period (stable) prevalence + end +*/ + +/* #define DEBUG */ +/* #define DEBUGBRENT */ +/* #define DEBUGLINMIN */ +/* #define DEBUGHESS */ +#define DEBUGHESSIJ +/* #define LINMINORIGINAL /\* Don't use loop on scale in linmin (accepting nan) *\/ */ +#define POWELL /* Instead of NLOPT */ +#define POWELLNOF3INFF1TEST /* Skip test */ +/* #define POWELLORIGINAL /\* Don't use Directest to decide new direction but original Powell test *\/ */ +/* #define MNBRAKORIGINAL /\* Don't use mnbrak fix *\/ */ + #include <math.h> #include <stdio.h> #include <stdlib.h> +#include <string.h> +#include <ctype.h> + +#ifdef _WIN32 +#include <io.h> +#include <windows.h> +#include <tchar.h> +#else #include <unistd.h> +#endif + +#include <limits.h> +#include <sys/types.h> + +#if defined(__GNUC__) +#include <sys/utsname.h> /* Doesn't work on Windows */ +#endif + +#include <sys/stat.h> +#include <errno.h> +/* extern int errno; */ + +/* #ifdef LINUX */ +/* #include <time.h> */ +/* #include "timeval.h" */ +/* #else */ +/* #include <sys/time.h> */ +/* #endif */ + +#include <time.h> + +#ifdef GSL +#include <gsl/gsl_errno.h> +#include <gsl/gsl_multimin.h> +#endif + -#define MAXLINE 256 -#define FILENAMELENGTH 80 -/*#define DEBUG*/ -/*#define win*/ +#ifdef NLOPT +#include <nlopt.h> +typedef struct { + double (* function)(double [] ); +} myfunc_data ; +#endif + +/* #include <libintl.h> */ +/* #define _(String) gettext (String) */ + +#define MAXLINE 2048 /* Was 256 and 1024. Overflow with 312 with 2 states and 4 covariates. Should be ok */ + +#define GNUPLOTPROGRAM "gnuplot" +/*#define GNUPLOTPROGRAM "..\\gp37mgw\\wgnuplot"*/ +#define FILENAMELENGTH 132 -#define MAXPARM 30 /* Maximum number of parameters for the optimization */ -#define NPARMAX 64 /* (nlstate+ndeath-1)*nlstate*ncov */ +#define GLOCK_ERROR_NOPATH -1 /* empty path */ +#define GLOCK_ERROR_GETCWD -2 /* cannot get cwd */ + +#define MAXPARM 128 /**< Maximum number of parameters for the optimization */ +#define NPARMAX 64 /**< (nlstate+ndeath-1)*nlstate*ncovmodel */ #define NINTERVMAX 8 -#define NLSTATEMAX 8 /* Maximum number of live states (for func) */ -#define NDEATHMAX 8 /* Maximum number of dead states (for func) */ -#define NCOVMAX 8 /* Maximum number of covariates */ +#define NLSTATEMAX 8 /**< Maximum number of live states (for func) */ +#define NDEATHMAX 8 /**< Maximum number of dead states (for func) */ +#define NCOVMAX 20 /**< Maximum number of covariates, including generated covariates V1*V2 */ +#define codtabm(h,k) (1 & (h-1) >> (k-1))+1 +/*#define decodtabm(h,k,cptcoveff)= (h <= (1<<cptcoveff)?(((h-1) >> (k-1)) & 1) +1 : -1)*/ +#define decodtabm(h,k,cptcoveff) (((h-1) >> (k-1)) & 1) +1 #define MAXN 20000 -#define YEARM 12. /* Number of months per year */ -#define AGESUP 130 +#define YEARM 12. /**< Number of months per year */ +/* #define AGESUP 130 */ +#define AGESUP 150 +#define AGEMARGE 25 /* Marge for agemin and agemax for(iage=agemin-AGEMARGE; iage <= agemax+3+AGEMARGE; iage++) */ #define AGEBASE 40 +#define AGEOVERFLOW 1.e20 +#define AGEGOMP 10 /**< Minimal age for Gompertz adjustment */ +#ifdef _WIN32 +#define DIRSEPARATOR '\\' +#define CHARSEPARATOR "\\" +#define ODIRSEPARATOR '/' +#else +#define DIRSEPARATOR '/' +#define CHARSEPARATOR "/" +#define ODIRSEPARATOR '\\' +#endif - -int nvar; - +/* $Id: imach.c,v 1.253 2016/12/15 11:59:41 brouard Exp $ */ +/* $State: Exp $ */ +#include "version.h" +char version[]=__IMACH_VERSION__; +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"; +char fullversion[]="$Revision: 1.253 $ $Date: 2016/12/15 11:59:41 $"; +char strstart[80]; +char optionfilext[10], optionfilefiname[FILENAMELENGTH]; +int erreur=0, nberr=0, nbwarn=0; /* Error number, number of errors number of warnings */ +int nagesqr=0, nforce=0; /* nagesqr=1 if model is including age*age, number of forces */ +/* Number of covariates model=V2+V1+ V3*age+V2*V4 */ +int cptcovn=0; /**< cptcovn number of covariates added in the model (excepting constant and age and age*product) */ +int cptcovt=0; /**< cptcovt number of covariates added in the model (excepting constant and age) */ +int cptcovs=0; /**< cptcovs number of simple covariates in the model V2+V1 =2 */ +int cptcovsnq=0; /**< cptcovsnq number of simple covariates in the model but non quantitative V2+V1 =2 */ +int cptcovage=0; /**< Number of covariates with age: V3*age only =1 */ +int cptcovprodnoage=0; /**< Number of covariate products without age */ +int cptcoveff=0; /* Total number of covariates to vary for printing results */ +int ncovf=0; /* Total number of effective fixed covariates (dummy or quantitative) in the model */ +int ncovv=0; /* Total number of effective (wave) varying covariates (dummy or quantitative) in the model */ +int ncova=0; /* Total number of effective (wave and stepm) varying with age covariates (dummy of quantitative) in the model */ +int nsd=0; /**< Total number of single dummy variables (output) */ +int nsq=0; /**< Total number of single quantitative variables (output) */ +int ncoveff=0; /* Total number of effective fixed dummy covariates in the model */ +int nqfveff=0; /**< nqfveff Number of Quantitative Fixed Variables Effective */ +int ntveff=0; /**< ntveff number of effective time varying variables */ +int nqtveff=0; /**< ntqveff number of effective time varying quantitative variables */ +int cptcov=0; /* Working variable */ +int ncovcombmax=NCOVMAX; /* Maximum calculated number of covariate combination = pow(2, cptcoveff) */ int npar=NPARMAX; int nlstate=2; /* Number of live states */ int ndeath=1; /* Number of dead states */ -int ncov; /* Total number of covariables including constant a12*1 +b12*x ncov=2 */ +int ncovmodel=0, ncovcol=0; /* Total number of covariables including constant a12*1 +b12*x ncovmodel=2 */ +int nqv=0, ntv=0, nqtv=0; /* Total number of quantitative variables, time variable (dummy), quantitative and time variable */ +int popbased=0; int *wav; /* Number of waves for this individuual 0 is possible */ -int maxwav; /* Maxim number of waves */ -int mle, weightopt; +int maxwav=0; /* Maxim number of waves */ +int jmin=0, jmax=0; /* min, max spacing between 2 waves */ +int ijmin=0, ijmax=0; /* Individuals having jmin and jmax */ +int gipmx=0, gsw=0; /* Global variables on the number of contributions + to the likelihood and the sum of weights (done by funcone)*/ +int mle=1, weightopt=0; int **mw; /* mw[mi][i] is number of the mi wave for this individual */ int **dh; /* dh[mi][i] is number of steps between mi,mi+1 for this individual */ +int **bh; /* bh[mi][i] is the bias (+ or -) for this individual if the delay between + * wave mi and wave mi+1 is not an exact multiple of stepm. */ +int countcallfunc=0; /* Count the number of calls to func */ +int selected(int kvar); /* Is covariate kvar selected for printing results */ + +double jmean=1; /* Mean space between 2 waves */ +double **matprod2(); /* test */ double **oldm, **newm, **savm; /* Working pointers to matrices */ double **oldms, **newms, **savms; /* Fixed working pointers to matrices */ -FILE *fic,*ficpar, *ficparo,*ficres, *ficrespl, *ficrespij, *ficrest; -FILE *ficgp, *fichtm; +double **ddnewms, **ddoldms, **ddsavms; /* for freeing later */ + +/*FILE *fic ; */ /* Used in readdata only */ +FILE *ficpar, *ficparo,*ficres, *ficresp, *ficresphtm, *ficresphtmfr, *ficrespl, *ficresplb,*ficrespij, *ficrespijb, *ficrest,*ficresf, *ficresfb,*ficrespop; +FILE *ficlog, *ficrespow; +int globpr=0; /* Global variable for printing or not */ +double fretone; /* Only one call to likelihood */ +long ipmx=0; /* Number of contributions */ +double sw; /* Sum of weights */ +char filerespow[FILENAMELENGTH]; +char fileresilk[FILENAMELENGTH]; /* File of individual contributions to the likelihood */ +FILE *ficresilk; +FILE *ficgp,*ficresprob,*ficpop, *ficresprobcov, *ficresprobcor; +FILE *ficresprobmorprev; +FILE *fichtm, *fichtmcov; /* Html File */ +FILE *ficreseij; +char filerese[FILENAMELENGTH]; +FILE *ficresstdeij; +char fileresstde[FILENAMELENGTH]; +FILE *ficrescveij; +char filerescve[FILENAMELENGTH]; +FILE *ficresvij; +char fileresv[FILENAMELENGTH]; +FILE *ficresvpl; +char fileresvpl[FILENAMELENGTH]; +char title[MAXLINE]; +char model[MAXLINE]; /**< The model line */ +char optionfile[FILENAMELENGTH], datafile[FILENAMELENGTH], filerespl[FILENAMELENGTH], fileresplb[FILENAMELENGTH]; +char plotcmd[FILENAMELENGTH], pplotcmd[FILENAMELENGTH]; +char tmpout[FILENAMELENGTH], tmpout2[FILENAMELENGTH]; +char command[FILENAMELENGTH]; +int outcmd=0; + +char fileres[FILENAMELENGTH], filerespij[FILENAMELENGTH], filerespijb[FILENAMELENGTH], filereso[FILENAMELENGTH], rfileres[FILENAMELENGTH]; +char fileresu[FILENAMELENGTH]; /* fileres without r in front */ +char filelog[FILENAMELENGTH]; /* Log file */ +char filerest[FILENAMELENGTH]; +char fileregp[FILENAMELENGTH]; +char popfile[FILENAMELENGTH]; + +char optionfilegnuplot[FILENAMELENGTH], optionfilehtm[FILENAMELENGTH], optionfilehtmcov[FILENAMELENGTH] ; + +/* struct timeval start_time, end_time, curr_time, last_time, forecast_time; */ +/* struct timezone tzp; */ +/* extern int gettimeofday(); */ +struct tm tml, *gmtime(), *localtime(); + +extern time_t time(); + +struct tm start_time, end_time, curr_time, last_time, forecast_time; +time_t rstart_time, rend_time, rcurr_time, rlast_time, rforecast_time; /* raw time */ +struct tm tm; + +char strcurr[80], strfor[80]; + +char *endptr; +long lval; +double dval; #define NR_END 1 #define FREE_ARG char* #define FTOL 1.0e-10 #define NRANSI -#define ITMAX 200 +#define ITMAX 200 +#define ITPOWMAX 20 /* This is now multiplied by the number of parameters */ #define TOL 2.0e-4 @@ -102,38 +1093,218 @@ FILE *ficgp, *fichtm; static double maxarg1,maxarg2; #define FMAX(a,b) (maxarg1=(a),maxarg2=(b),(maxarg1)>(maxarg2)? (maxarg1):(maxarg2)) #define FMIN(a,b) (maxarg1=(a),maxarg2=(b),(maxarg1)<(maxarg2)? (maxarg1):(maxarg2)) - + #define SIGN(a,b) ((b)>0.0 ? fabs(a) : -fabs(a)) #define rint(a) floor(a+0.5) - +/* http://www.thphys.uni-heidelberg.de/~robbers/cmbeasy/doc/html/myutils_8h-source.html */ +#define mytinydouble 1.0e-16 +/* #define DEQUAL(a,b) (fabs((a)-(b))<mytinydouble) */ +/* http://www.thphys.uni-heidelberg.de/~robbers/cmbeasy/doc/html/mynrutils_8h-source.html */ +/* static double dsqrarg; */ +/* #define DSQR(a) (DEQUAL((dsqrarg=(a)),0.0) ? 0.0 : dsqrarg*dsqrarg) */ static double sqrarg; #define SQR(a) ((sqrarg=(a)) == 0.0 ? 0.0 :sqrarg*sqrarg) #define SWAP(a,b) {temp=(a);(a)=(b);(b)=temp;} +int agegomp= AGEGOMP; int imx; -int stepm; +int stepm=1; /* Stepm, step in month: minimum step interpolation*/ +int estepm; +/* Estepm, step in month to interpolate survival function in order to approximate Life Expectancy*/ + int m,nb; -int *num, firstpass=0, lastpass=2,*cod; +long *num; +int firstpass=0, lastpass=4,*cod, *cens; +int *ncodemax; /* ncodemax[j]= Number of modalities of the j th + covariate for which somebody answered excluding + undefined. Usually 2: 0 and 1. */ +int *ncodemaxwundef; /* ncodemax[j]= Number of modalities of the j th + covariate for which somebody answered including + undefined. Usually 3: -1, 0 and 1. */ double **agev,*moisnais, *annais, *moisdc, *andc,**mint, **anint; -double **pmmij; +double **pmmij, ***probs; /* Global pointer */ +double ***mobaverage, ***mobaverages; /* New global variable */ +double *ageexmed,*agecens; +double dateintmean=0; double *weight; int **s; /* Status */ -double *agedc, **covar, idx; +double *agedc; +double **covar; /**< covar[j,i], value of jth covariate for individual i, + * covar=matrix(0,NCOVMAX,1,n); + * cov[Tage[kk]+2]=covar[Tvar[Tage[kk]]][i]*age; */ +double **coqvar; /* Fixed quantitative covariate iqv */ +double ***cotvar; /* Time varying covariate itv */ +double ***cotqvar; /* Time varying quantitative covariate itqv */ +double idx; +int **nbcode, *Tvar; /**< model=V2 => Tvar[1]= 2 */ +/* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ +/*k 1 2 3 4 5 6 7 8 9 */ +/*Tvar[k]= 5 4 3 6 5 2 7 1 1 */ +/* Tndvar[k] 1 2 3 4 5 */ +/*TDvar 4 3 6 7 1 */ /* For outputs only; combination of dummies fixed or varying */ +/* Tns[k] 1 2 2 4 5 */ /* Number of single cova */ +/* TvarsD[k] 1 2 3 */ /* Number of single dummy cova */ +/* TvarsDind 2 3 9 */ /* position K of single dummy cova */ +/* TvarsQ[k] 1 2 */ /* Number of single quantitative cova */ +/* TvarsQind 1 6 */ /* position K of single quantitative cova */ +/* Tprod[i]=k 4 7 */ +/* Tage[i]=k 5 8 */ +/* */ +/* Type */ +/* V 1 2 3 4 5 */ +/* F F V V V */ +/* D Q D D Q */ +/* */ +int *TvarsD; +int *TvarsDind; +int *TvarsQ; +int *TvarsQind; + +#define MAXRESULTLINES 10 +int nresult=0; +int TKresult[MAXRESULTLINES]; +int Tresult[MAXRESULTLINES][NCOVMAX];/* For dummy variable , value (output) */ +int Tinvresult[MAXRESULTLINES][NCOVMAX];/* For dummy variable , value (output) */ +int Tvresult[MAXRESULTLINES][NCOVMAX]; /* For dummy variable , variable # (output) */ +double Tqresult[MAXRESULTLINES][NCOVMAX]; /* For quantitative variable , value (output) */ +double Tqinvresult[MAXRESULTLINES][NCOVMAX]; /* For quantitative variable , value (output) */ +int Tvqresult[MAXRESULTLINES][NCOVMAX]; /* For quantitative variable , variable # (output) */ + +/* 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 *\/ */ +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 */ +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 */ +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 */ +int *TvarVind; /**< TvarVind[1]=1, TvarVind[2]=2 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ +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 */ +int *TvarAind; /**< TvarindA[1]=5, TvarAind[2]=8 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ +int *TvarFD; /**< TvarFD[1]=V1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ +int *TvarFDind; /* TvarFDind[1]=9 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ +int *TvarFQ; /* TvarFQ[1]=V2 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */ +int *TvarFQind; /* TvarFQind[1]=6 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */ +int *TvarVD; /* TvarVD[1]=V5 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */ +int *TvarVDind; /* TvarVDind[1]=1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */ +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 */ +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 */ + +int *Tvarsel; /**< Selected covariates for output */ +double *Tvalsel; /**< Selected modality value of covariate for output */ +int *Typevar; /**< 0 for simple covariate (dummy, quantitative, fixed or varying), 1 for age product, 2 for product */ +int *Fixed; /** Fixed[k] 0=fixed, 1 varying, 2 fixed with age product, 3 varying with age product */ +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 */ +int *DummyV; /** Dummy[v] 0=dummy (0 1), 1 quantitative */ +int *FixedV; /** FixedV[v] 0 fixed, 1 varying */ +int *Tage; +int anyvaryingduminmodel=0; /**< Any varying dummy in Model=1 yes, 0 no, to avoid a loop on waves in freq */ +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*/ +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*/ +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 */ +int *Ndum; /** Freq of modality (tricode */ +/* int **codtab;*/ /**< codtab=imatrix(1,100,1,10); */ +int **Tvard; +int *Tprod;/**< Gives the k position of the k1 product */ +/* Tprod[k1=1]=3(=V1*V4) for V2+V1+V1*V4+age*V3 */ +int *Tposprod; /**< Gives the k1 product from the k position */ + /* if V2+V1+V1*V4+age*V3+V3*V2 TProd[k1=2]=5 (V3*V2) */ + /* Tposprod[k]=k1 , Tposprod[3]=1, Tposprod[5(V3*V2)]=2 (2nd product without age) */ +int cptcovprod, *Tvaraff, *invalidvarcomb; +double *lsurv, *lpop, *tpop; + +#define FD 1; /* Fixed dummy covariate */ +#define FQ 2; /* Fixed quantitative covariate */ +#define FP 3; /* Fixed product covariate */ +#define FPDD 7; /* Fixed product dummy*dummy covariate */ +#define FPDQ 8; /* Fixed product dummy*quantitative covariate */ +#define FPQQ 9; /* Fixed product quantitative*quantitative covariate */ +#define VD 10; /* Varying dummy covariate */ +#define VQ 11; /* Varying quantitative covariate */ +#define VP 12; /* Varying product covariate */ +#define VPDD 13; /* Varying product dummy*dummy covariate */ +#define VPDQ 14; /* Varying product dummy*quantitative covariate */ +#define VPQQ 15; /* Varying product quantitative*quantitative covariate */ +#define APFD 16; /* Age product * fixed dummy covariate */ +#define APFQ 17; /* Age product * fixed quantitative covariate */ +#define APVD 18; /* Age product * varying dummy covariate */ +#define APVQ 19; /* Age product * varying quantitative covariate */ + +#define FTYPE 1; /* Fixed covariate */ +#define VTYPE 2; /* Varying covariate (loop in wave) */ +#define ATYPE 2; /* Age product covariate (loop in dh within wave)*/ + +struct kmodel{ + int maintype; /* main type */ + int subtype; /* subtype */ +}; +struct kmodel modell[NCOVMAX]; +double ftol=FTOL; /**< Tolerance for computing Max Likelihood */ +double ftolhess; /**< Tolerance for computing hessian */ + +/**************** split *************************/ +static int split( char *path, char *dirc, char *name, char *ext, char *finame ) +{ + /* From a file name with (full) path (either Unix or Windows) we extract the directory (dirc) + the name of the file (name), its extension only (ext) and its first part of the name (finame) + */ + char *ss; /* pointer */ + int l1=0, l2=0; /* length counters */ + + l1 = strlen(path ); /* length of path */ + if ( l1 == 0 ) return( GLOCK_ERROR_NOPATH ); + ss= strrchr( path, DIRSEPARATOR ); /* find last / */ + if ( ss == NULL ) { /* no directory, so determine current directory */ + strcpy( name, path ); /* we got the fullname name because no directory */ + /*if(strrchr(path, ODIRSEPARATOR )==NULL) + printf("Warning you should use %s as a separator\n",DIRSEPARATOR);*/ + /* get current working directory */ + /* extern char* getcwd ( char *buf , int len);*/ +#ifdef WIN32 + if (_getcwd( dirc, FILENAME_MAX ) == NULL ) { +#else + if (getcwd(dirc, FILENAME_MAX) == NULL) { +#endif + return( GLOCK_ERROR_GETCWD ); + } + /* got dirc from getcwd*/ + printf(" DIRC = %s \n",dirc); + } else { /* strip directory from path */ + ss++; /* after this, the filename */ + l2 = strlen( ss ); /* length of filename */ + if ( l2 == 0 ) return( GLOCK_ERROR_NOPATH ); + strcpy( name, ss ); /* save file name */ + strncpy( dirc, path, l1 - l2 ); /* now the directory */ + dirc[l1-l2] = '\0'; /* add zero */ + printf(" DIRC2 = %s \n",dirc); + } + /* We add a separator at the end of dirc if not exists */ + l1 = strlen( dirc ); /* length of directory */ + if( dirc[l1-1] != DIRSEPARATOR ){ + dirc[l1] = DIRSEPARATOR; + dirc[l1+1] = 0; + printf(" DIRC3 = %s \n",dirc); + } + ss = strrchr( name, '.' ); /* find last / */ + if (ss >0){ + ss++; + strcpy(ext,ss); /* save extension */ + l1= strlen( name); + l2= strlen(ss)+1; + strncpy( finame, name, l1-l2); + finame[l1-l2]= 0; + } -double ftol=FTOL; /* Tolerance for computing Max Likelihood */ -double ftolhess; /* Tolerance for computing hessian */ + return( 0 ); /* we're done */ +} /******************************************/ -void replace(char *s, char*t) +void replace_back_to_slash(char *s, char*t) { int i; - int lg=20; + int lg=0; i=0; lg=strlen(t); for(i=0; i<= lg; i++) { @@ -141,32 +1312,180 @@ void replace(char *s, char*t) if (t[i]== '\\') s[i]='/'; } } -void cut(char *u,char *v, char*t) -{ - int i,lg,j,p; - i=0; - for(j=0; j<=strlen(t); j++) { - if(t[j]=='\\') p=j; - } - lg=strlen(t); - for(j=0; j<p; j++) { - (u[j] = t[j]); - u[p]='\0'; +char *trimbb(char *out, char *in) +{ /* Trim multiple blanks in line but keeps first blanks if line starts with blanks */ + char *s; + s=out; + while (*in != '\0'){ + while( *in == ' ' && *(in+1) == ' '){ /* && *(in+1) != '\0'){*/ + in++; + } + *out++ = *in++; } + *out='\0'; + return s; +} + +/* char *substrchaine(char *out, char *in, char *chain) */ +/* { */ +/* /\* Substract chain 'chain' from 'in', return and output 'out' *\/ */ +/* char *s, *t; */ +/* t=in;s=out; */ +/* while ((*in != *chain) && (*in != '\0')){ */ +/* *out++ = *in++; */ +/* } */ + +/* /\* *in matches *chain *\/ */ +/* while ((*in++ == *chain++) && (*in != '\0')){ */ +/* printf("*in = %c, *out= %c *chain= %c \n", *in, *out, *chain); */ +/* } */ +/* in--; chain--; */ +/* while ( (*in != '\0')){ */ +/* printf("Bef *in = %c, *out= %c *chain= %c \n", *in, *out, *chain); */ +/* *out++ = *in++; */ +/* printf("Aft *in = %c, *out= %c *chain= %c \n", *in, *out, *chain); */ +/* } */ +/* *out='\0'; */ +/* out=s; */ +/* return out; */ +/* } */ +char *substrchaine(char *out, char *in, char *chain) +{ + /* Substract chain 'chain' from 'in', return and output 'out' */ + /* in="V1+V1*age+age*age+V2", chain="age*age" */ + + char *strloc; - for(j=0; j<= lg; j++) { - if (j>=(p+1))(v[j-p-1] = t[j]); + strcpy (out, in); + strloc = strstr(out, chain); /* strloc points to out at age*age+V2 */ + printf("Bef strloc=%s chain=%s out=%s \n", strloc, chain, out); + if(strloc != NULL){ + /* will affect out */ /* strloc+strlenc(chain)=+V2 */ /* Will also work in Unicode */ + memmove(strloc,strloc+strlen(chain), strlen(strloc+strlen(chain))+1); + /* strcpy (strloc, strloc +strlen(chain));*/ } + printf("Aft strloc=%s chain=%s in=%s out=%s \n", strloc, chain, in, out); + return out; } -/********************** nrerror ********************/ + +char *cutl(char *blocc, char *alocc, char *in, char occ) +{ + /* cuts string in into blocc and alocc where blocc ends before FIRST occurence of char 'occ' + and alocc starts after first occurence of char 'occ' : ex cutv(blocc,alocc,"abcdef2ghi2j",'2') + gives blocc="abcdef" and alocc="ghi2j". + If occ is not found blocc is null and alocc is equal to in. Returns blocc + */ + char *s, *t; + t=in;s=in; + while ((*in != occ) && (*in != '\0')){ + *alocc++ = *in++; + } + if( *in == occ){ + *(alocc)='\0'; + s=++in; + } + + if (s == t) {/* occ not found */ + *(alocc-(in-s))='\0'; + in=s; + } + while ( *in != '\0'){ + *blocc++ = *in++; + } + + *blocc='\0'; + return t; +} +char *cutv(char *blocc, char *alocc, char *in, char occ) +{ + /* cuts string in into blocc and alocc where blocc ends before LAST occurence of char 'occ' + and alocc starts after last occurence of char 'occ' : ex cutv(blocc,alocc,"abcdef2ghi2j",'2') + gives blocc="abcdef2ghi" and alocc="j". + If occ is not found blocc is null and alocc is equal to in. Returns alocc + */ + char *s, *t; + t=in;s=in; + while (*in != '\0'){ + while( *in == occ){ + *blocc++ = *in++; + s=in; + } + *blocc++ = *in++; + } + if (s == t) /* occ not found */ + *(blocc-(in-s))='\0'; + else + *(blocc-(in-s)-1)='\0'; + in=s; + while ( *in != '\0'){ + *alocc++ = *in++; + } + + *alocc='\0'; + return s; +} + +int nbocc(char *s, char occ) +{ + int i,j=0; + int lg=20; + i=0; + lg=strlen(s); + for(i=0; i<= lg; i++) { + if (s[i] == occ ) j++; + } + return j; +} + +/* void cutv(char *u,char *v, char*t, char occ) */ +/* { */ +/* /\* cuts string t into u and v where u ends before last occurence of char 'occ' */ +/* and v starts after last occurence of char 'occ' : ex cutv(u,v,"abcdef2ghi2j",'2') */ +/* gives u="abcdef2ghi" and v="j" *\/ */ +/* int i,lg,j,p=0; */ +/* i=0; */ +/* lg=strlen(t); */ +/* for(j=0; j<=lg-1; j++) { */ +/* if((t[j]!= occ) && (t[j+1]== occ)) p=j+1; */ +/* } */ + +/* for(j=0; j<p; j++) { */ +/* (u[j] = t[j]); */ +/* } */ +/* u[p]='\0'; */ + +/* for(j=0; j<= lg; j++) { */ +/* if (j>=(p+1))(v[j-p-1] = t[j]); */ +/* } */ +/* } */ + +#ifdef _WIN32 +char * strsep(char **pp, const char *delim) +{ + char *p, *q; + + if ((p = *pp) == NULL) + return 0; + if ((q = strpbrk (p, delim)) != NULL) + { + *pp = q + 1; + *q = '\0'; + } + else + *pp = 0; + return p; +} +#endif + +/********************** nrerror ********************/ void nrerror(char error_text[]) { fprintf(stderr,"ERREUR ...\n"); fprintf(stderr,"%s\n",error_text); - exit(1); + exit(EXIT_FAILURE); } /*********************** vector *******************/ double *vector(int nl, int nh) @@ -198,6 +1517,21 @@ void free_ivector(int *v, long nl, long free((FREE_ARG)(v+nl-NR_END)); } +/************************lvector *******************************/ +long *lvector(long nl,long nh) +{ + long *v; + v=(long *) malloc((size_t)((nh-nl+1+NR_END)*sizeof(long))); + if (!v) nrerror("allocation failure in ivector"); + return v-nl+NR_END; +} + +/******************free lvector **************************/ +void free_lvector(long *v, long nl, long nh) +{ + free((FREE_ARG)(v+nl-NR_END)); +} + /******************* imatrix *******************************/ int **imatrix(long nrl, long nrh, long ncl, long nch) /* allocate a int matrix with subscript range m[nrl..nrh][ncl..nch] */ @@ -252,6 +1586,10 @@ double **matrix(long nrl, long nrh, long for (i=nrl+1; i<=nrh; i++) m[i]=m[i-1]+ncol; return m; + /* print *(*(m+1)+70) or print m[1][70]; print m+1 or print &(m[1]) or &(m[1][0]) +m[i] = address of ith row of the table. &(m[i]) is its value which is another adress +that of m[i][0]. In order to get the value p m[i][0] but it is unitialized. + */ } /*************************free matrix ************************/ @@ -291,7 +1629,10 @@ double ***ma3x(long nrl, long nrh, long for (j=ncl+1; j<=nch; j++) m[i][j]=m[i][j-1]+nlay; } - return m; + return m; + /* gdb: p *(m+1) <=> p m[1] and p (m+1) <=> p (m+1) <=> p &(m[1]) + &(m[i][j][k]) <=> *((*(m+i) + j)+k) + */ } /*************************free ma3x ************************/ @@ -302,6 +1643,77 @@ void free_ma3x(double ***m, long nrl, lo free((FREE_ARG)(m+nrl-NR_END)); } +/*************** function subdirf ***********/ +char *subdirf(char fileres[]) +{ + /* Caution optionfilefiname is hidden */ + strcpy(tmpout,optionfilefiname); + strcat(tmpout,"/"); /* Add to the right */ + strcat(tmpout,fileres); + return tmpout; +} + +/*************** function subdirf2 ***********/ +char *subdirf2(char fileres[], char *preop) +{ + + /* Caution optionfilefiname is hidden */ + strcpy(tmpout,optionfilefiname); + strcat(tmpout,"/"); + strcat(tmpout,preop); + strcat(tmpout,fileres); + return tmpout; +} + +/*************** function subdirf3 ***********/ +char *subdirf3(char fileres[], char *preop, char *preop2) +{ + + /* Caution optionfilefiname is hidden */ + strcpy(tmpout,optionfilefiname); + strcat(tmpout,"/"); + strcat(tmpout,preop); + strcat(tmpout,preop2); + strcat(tmpout,fileres); + return tmpout; +} + +/*************** function subdirfext ***********/ +char *subdirfext(char fileres[], char *preop, char *postop) +{ + + strcpy(tmpout,preop); + strcat(tmpout,fileres); + strcat(tmpout,postop); + return tmpout; +} + +/*************** function subdirfext3 ***********/ +char *subdirfext3(char fileres[], char *preop, char *postop) +{ + + /* Caution optionfilefiname is hidden */ + strcpy(tmpout,optionfilefiname); + strcat(tmpout,"/"); + strcat(tmpout,preop); + strcat(tmpout,fileres); + strcat(tmpout,postop); + return tmpout; +} + +char *asc_diff_time(long time_sec, char ascdiff[]) +{ + long sec_left, days, hours, minutes; + days = (time_sec) / (60*60*24); + sec_left = (time_sec) % (60*60*24); + hours = (sec_left) / (60*60) ; + sec_left = (sec_left) %(60*60); + minutes = (sec_left) /60; + sec_left = (sec_left) % (60); + sprintf(ascdiff,"%ld day(s) %ld hour(s) %ld minute(s) %ld second(s)",days, hours, minutes, sec_left); + return ascdiff; +} + /***************** f1dim *************************/ extern int ncom; extern double *pcom,*xicom; @@ -322,11 +1734,17 @@ double f1dim(double x) /*****************brent *************************/ double brent(double ax, double bx, double cx, double (*f)(double), double tol, double *xmin) -{ +{ + /* Given a function f, and given a bracketing triplet of abscissas ax, bx, cx (such that bx is + * between ax and cx, and f(bx) is less than both f(ax) and f(cx) ), this routine isolates + * the minimum to a fractional precision of about tol using Brent’s method. The abscissa of + * the minimum is returned as xmin, and the minimum function value is returned as brent , the + * returned function value. + */ int iter; double a,b,d,etemp; - double fu,fv,fw,fx; - double ftemp; + double fu=0,fv,fw,fx; + double ftemp=0.; double p,q,r,tol1,tol2,u,v,w,x,xm; double e=0.0; @@ -339,8 +1757,10 @@ double brent(double ax, double bx, doubl tol2=2.0*(tol1=tol*fabs(x)+ZEPS); /* if (2.0*fabs(fp-(*fret)) <= ftol*(fabs(fp)+fabs(*fret)))*/ printf(".");fflush(stdout); -#ifdef DEBUG + fprintf(ficlog,".");fflush(ficlog); +#ifdef DEBUGBRENT 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); + 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); /* if ((fabs(x-xm) <= (tol2-0.5*(b-a)))||(2.0*fabs(fu-ftemp) <= ftol*1.e-2*(fabs(fu)+fabs(ftemp)))) { */ #endif if (fabs(x-xm) <= (tol2-0.5*(b-a))){ @@ -358,12 +1778,12 @@ double brent(double ax, double bx, doubl etemp=e; e=d; if (fabs(p) >= fabs(0.5*q*etemp) || p <= q*(a-x) || p >= q*(b-x)) - d=CGOLD*(e=(x >= xm ? a-x : b-x)); + d=CGOLD*(e=(x >= xm ? a-x : b-x)); else { - d=p/q; - u=x+d; - if (u-a < tol2 || b-u < tol2) - d=SIGN(tol1,xm-x); + d=p/q; + u=x+d; + if (u-a < tol2 || b-u < tol2) + d=SIGN(tol1,xm-x); } } else { d=CGOLD*(e=(x >= xm ? a-x : b-x)); @@ -373,19 +1793,19 @@ double brent(double ax, double bx, doubl if (fu <= fx) { if (u >= x) a=x; else b=x; SHFT(v,w,x,u) - SHFT(fv,fw,fx,fu) - } else { - if (u < x) a=u; else b=u; - if (fu <= fw || w == x) { - v=w; - w=u; - fv=fw; - fw=fu; - } else if (fu <= fv || v == x || v == w) { - v=u; - fv=fu; - } - } + SHFT(fv,fw,fx,fu) + } else { + if (u < x) a=u; else b=u; + if (fu <= fw || w == x) { + v=w; + w=u; + fv=fw; + fw=fu; + } else if (fu <= fv || v == x || v == w) { + v=u; + fv=fu; + } + } } nrerror("Too many iterations in brent"); *xmin=x; @@ -396,51 +1816,158 @@ double brent(double ax, double bx, doubl void mnbrak(double *ax, double *bx, double *cx, double *fa, double *fb, double *fc, double (*func)(double)) -{ +{ /* Given a function func , and given distinct initial points ax and bx , this routine searches in +the downhill direction (defined by the function as evaluated at the initial points) and returns +new points ax , bx , cx that bracket a minimum of the function. Also returned are the function +values at the three points, fa, fb , and fc such that fa > fb and fb < fc. + */ double ulim,u,r,q, dum; double fu; - - *fa=(*func)(*ax); - *fb=(*func)(*bx); + + double scale=10.; + int iterscale=0; + + *fa=(*func)(*ax); /* xta[j]=pcom[j]+(*ax)*xicom[j]; fa=f(xta[j])*/ + *fb=(*func)(*bx); /* xtb[j]=pcom[j]+(*bx)*xicom[j]; fb=f(xtb[j]) */ + + + /* while(*fb != *fb){ /\* *ax should be ok, reducing distance to *ax *\/ */ + /* printf("Warning mnbrak *fb = %lf, *bx=%lf *ax=%lf *fa==%lf iter=%d\n",*fb, *bx, *ax, *fa, iterscale++); */ + /* *bx = *ax - (*ax - *bx)/scale; */ + /* *fb=(*func)(*bx); /\* xtb[j]=pcom[j]+(*bx)*xicom[j]; fb=f(xtb[j]) *\/ */ + /* } */ + if (*fb > *fa) { SHFT(dum,*ax,*bx,dum) - SHFT(dum,*fb,*fa,dum) - } + SHFT(dum,*fb,*fa,dum) + } *cx=(*bx)+GOLD*(*bx-*ax); *fc=(*func)(*cx); - while (*fb > *fc) { +#ifdef DEBUG + printf("mnbrak0 a=%lf *fa=%lf, b=%lf *fb=%lf, c=%lf *fc=%lf\n",*ax,*fa,*bx,*fb,*cx, *fc); + fprintf(ficlog,"mnbrak0 a=%lf *fa=%lf, b=%lf *fb=%lf, c=%lf *fc=%lf\n",*ax,*fa,*bx,*fb,*cx, *fc); +#endif + while (*fb > *fc) { /* Declining a,b,c with fa> fb > fc. If fc=inf it exits and if flat fb=fc it exits too.*/ r=(*bx-*ax)*(*fb-*fc); - q=(*bx-*cx)*(*fb-*fa); + q=(*bx-*cx)*(*fb-*fa); /* What if fa=inf */ u=(*bx)-((*bx-*cx)*q-(*bx-*ax)*r)/ - (2.0*SIGN(FMAX(fabs(q-r),TINY),q-r)); - ulim=(*bx)+GLIMIT*(*cx-*bx); - if ((*bx-u)*(u-*cx) > 0.0) { + (2.0*SIGN(FMAX(fabs(q-r),TINY),q-r)); /* Minimum abscissa of a parabolic estimated from (a,fa), (b,fb) and (c,fc). */ + ulim=(*bx)+GLIMIT*(*cx-*bx); /* Maximum abscissa where function should be evaluated */ + if ((*bx-u)*(u-*cx) > 0.0) { /* if u_p is between b and c */ fu=(*func)(u); - } else if ((*cx-u)*(u-ulim) > 0.0) { +#ifdef DEBUG + /* f(x)=A(x-u)**2+f(u) */ + double A, fparabu; + A= (*fb - *fa)/(*bx-*ax)/(*bx+*ax-2*u); + fparabu= *fa - A*(*ax-u)*(*ax-u); + 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); + 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); + /* And thus,it can be that fu > *fc even if fparabu < *fc */ + /* mnbrak (*ax=7.666299858533, *fa=299039.693133272231), (*bx=8.595447774979, *fb=298976.598289369489), + (*cx=10.098840694817, *fc=298946.631474258087), (*u=9.852501168332, fu=298948.773013752128, fparabu=298945.434711494134) */ + /* In that case, there is no bracket in the output! Routine is wrong with many consequences.*/ +#endif +#ifdef MNBRAKORIGINAL +#else +/* if (fu > *fc) { */ +/* #ifdef DEBUG */ +/* printf("mnbrak4 fu > fc \n"); */ +/* fprintf(ficlog, "mnbrak4 fu > fc\n"); */ +/* #endif */ +/* /\* 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 *\\/ *\/ */ +/* /\* SHFT(*fa,*fc,fu,*fc) /\\* (b, u, c) is a bracket while test fb > fc will be fu > fc will exit *\\/ *\/ */ +/* dum=u; /\* Shifting c and u *\/ */ +/* u = *cx; */ +/* *cx = dum; */ +/* dum = fu; */ +/* fu = *fc; */ +/* *fc =dum; */ +/* } else { /\* end *\/ */ +/* #ifdef DEBUG */ +/* printf("mnbrak3 fu < fc \n"); */ +/* fprintf(ficlog, "mnbrak3 fu < fc\n"); */ +/* #endif */ +/* dum=u; /\* Shifting c and u *\/ */ +/* u = *cx; */ +/* *cx = dum; */ +/* dum = fu; */ +/* fu = *fc; */ +/* *fc =dum; */ +/* } */ +#ifdef DEBUGMNBRAK + double A, fparabu; + A= (*fb - *fa)/(*bx-*ax)/(*bx+*ax-2*u); + fparabu= *fa - A*(*ax-u)*(*ax-u); + 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); + 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); +#endif + dum=u; /* Shifting c and u */ + u = *cx; + *cx = dum; + dum = fu; + fu = *fc; + *fc =dum; +#endif + } else if ((*cx-u)*(u-ulim) > 0.0) { /* u is after c but before ulim */ +#ifdef DEBUG + printf("\nmnbrak2 u=%lf after c=%lf but before ulim\n",u,*cx); + fprintf(ficlog,"\nmnbrak2 u=%lf after c=%lf but before ulim\n",u,*cx); +#endif fu=(*func)(u); if (fu < *fc) { - SHFT(*bx,*cx,u,*cx+GOLD*(*cx-*bx)) - SHFT(*fb,*fc,fu,(*func)(u)) - } - } else if ((u-ulim)*(ulim-*cx) >= 0.0) { +#ifdef DEBUG + printf("\nmnbrak2 u=%lf after c=%lf but before ulim=%lf AND fu=%lf < %lf=fc\n",u,*cx,ulim,fu, *fc); + fprintf(ficlog,"\nmnbrak2 u=%lf after c=%lf but before ulim=%lf AND fu=%lf < %lf=fc\n",u,*cx,ulim,fu, *fc); +#endif + SHFT(*bx,*cx,u,*cx+GOLD*(*cx-*bx)) + SHFT(*fb,*fc,fu,(*func)(u)) +#ifdef DEBUG + printf("\nmnbrak2 shift GOLD c=%lf",*cx+GOLD*(*cx-*bx)); +#endif + } + } else if ((u-ulim)*(ulim-*cx) >= 0.0) { /* u outside ulim (verifying that ulim is beyond c) */ +#ifdef DEBUG + printf("\nmnbrak2 u=%lf outside ulim=%lf (verifying that ulim is beyond c=%lf)\n",u,ulim,*cx); + fprintf(ficlog,"\nmnbrak2 u=%lf outside ulim=%lf (verifying that ulim is beyond c=%lf)\n",u,ulim,*cx); +#endif u=ulim; fu=(*func)(u); - } else { + } else { /* u could be left to b (if r > q parabola has a maximum) */ +#ifdef DEBUG + printf("\nmnbrak2 u=%lf could be left to b=%lf (if r=%lf > q=%lf parabola has a maximum)\n",u,*bx,r,q); + 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); +#endif u=(*cx)+GOLD*(*cx-*bx); fu=(*func)(u); - } +#ifdef DEBUG + printf("\nmnbrak2 new u=%lf fu=%lf shifted gold left from c=%lf and b=%lf \n",u,fu,*cx,*bx); + fprintf(ficlog,"\nmnbrak2 new u=%lf fu=%lf shifted gold left from c=%lf and b=%lf \n",u,fu,*cx,*bx); +#endif + } /* end tests */ SHFT(*ax,*bx,*cx,u) - SHFT(*fa,*fb,*fc,fu) - } + SHFT(*fa,*fb,*fc,fu) +#ifdef DEBUG + printf("\nmnbrak2 shift (*ax=%.12f, *fa=%.12lf), (*bx=%.12f, *fb=%.12lf), (*cx=%.12f, *fc=%.12lf)\n",*ax,*fa,*bx,*fb,*cx,*fc); + fprintf(ficlog, "\nmnbrak2 shift (*ax=%.12f, *fa=%.12lf), (*bx=%.12f, *fb=%.12lf), (*cx=%.12f, *fc=%.12lf)\n",*ax,*fa,*bx,*fb,*cx,*fc); +#endif + } /* end while; ie return (a, b, c, fa, fb, fc) such that a < b < c with f(a) > f(b) and fb < f(c) */ } /*************** linmin ************************/ - +/* Given an n -dimensional point p[1..n] and an n -dimensional direction xi[1..n] , moves and +resets p to where the function func(p) takes on a minimum along the direction xi from p , +and replaces xi by the actual vector displacement that p was moved. Also returns as fret +the value of func at the returned location p . This is actually all accomplished by calling the +routines mnbrak and brent .*/ int ncom; double *pcom,*xicom; double (*nrfunc)(double []); +#ifdef LINMINORIGINAL void linmin(double p[], double xi[], int n, double *fret,double (*func)(double [])) +#else +void linmin(double p[], double xi[], int n, double *fret,double (*func)(double []), int *flat) +#endif { double brent(double ax, double bx, double cx, double (*f)(double), double tol, double *xmin); @@ -450,276 +1977,1057 @@ void linmin(double p[], double xi[], int int j; double xx,xmin,bx,ax; double fx,fb,fa; - + +#ifdef LINMINORIGINAL +#else + double scale=10., axs, xxs; /* Scale added for infinity */ +#endif + ncom=n; pcom=vector(1,n); xicom=vector(1,n); nrfunc=func; for (j=1;j<=n;j++) { pcom[j]=p[j]; - xicom[j]=xi[j]; + xicom[j]=xi[j]; /* Former scale xi[j] of currrent direction i */ } - ax=0.0; - xx=1.0; - mnbrak(&ax,&xx,&bx,&fa,&fx,&fb,f1dim); - *fret=brent(ax,xx,bx,f1dim,TOL,&xmin); + +#ifdef LINMINORIGINAL + xx=1.; +#else + axs=0.0; + xxs=1.; + do{ + xx= xxs; +#endif + ax=0.; + mnbrak(&ax,&xx,&bx,&fa,&fx,&fb,f1dim); /* Outputs: xtx[j]=pcom[j]+(*xx)*xicom[j]; fx=f(xtx[j]) */ + /* brackets with inputs ax=0 and xx=1, but points, pcom=p, and directions values, xicom=xi, are sent via f1dim(x) */ + /* 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)) */ + /* Outputs: fa=f(p(j)) and fx=f(p(j) + xxs * xi(j) ) and f(bx)= f(p(j)+ bx* xi(j)) */ + /* Given input ax=axs and xx=xxs, xx might be too far from ax to get a finite f(xx) */ + /* Searches on line, outputs (ax, xx, bx) such that fx < min(fa and fb) */ + /* 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]]*/ +#ifdef LINMINORIGINAL +#else + if (fx != fx){ + xxs=xxs/scale; /* Trying a smaller xx, closer to initial ax=0 */ + printf("|"); + fprintf(ficlog,"|"); +#ifdef DEBUGLINMIN + 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); +#endif + } + }while(fx != fx && xxs > 1.e-5); +#endif + +#ifdef DEBUGLINMIN + 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); + 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); +#endif +#ifdef LINMINORIGINAL +#else + if(fb == fx){ /* Flat function in the direction */ + xmin=xx; + *flat=1; + }else{ + *flat=0; +#endif + /*Flat mnbrak2 shift (*ax=0.000000000000, *fa=51626.272983130431), (*bx=-1.618034000000, *fb=51590.149499362531), (*cx=-4.236068025156, *fc=51590.149499362531) */ + *fret=brent(ax,xx,bx,f1dim,TOL,&xmin); /* Giving a bracketting triplet (ax, xx, bx), find a minimum, xmin, according to f1dim, *fret(xmin),*/ + /* fa = f(p[j] + ax * xi[j]), fx = f(p[j] + xx * xi[j]), fb = f(p[j] + bx * xi[j]) */ + /* fmin = f(p[j] + xmin * xi[j]) */ + /* P+lambda n in that direction (lambdamin), with TOL between abscisses */ + /* f1dim(xmin): for (j=1;j<=ncom;j++) xt[j]=pcom[j]+xmin*xicom[j]; */ #ifdef DEBUG - printf("retour brent fret=%.12e xmin=%.12e\n",*fret,xmin); + 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); + 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); +#endif +#ifdef LINMINORIGINAL +#else + } +#endif +#ifdef DEBUGLINMIN + printf("linmin end "); + fprintf(ficlog,"linmin end "); #endif for (j=1;j<=n;j++) { +#ifdef LINMINORIGINAL xi[j] *= xmin; - p[j] += xi[j]; +#else +#ifdef DEBUGLINMIN + if(xxs <1.0) + printf(" before xi[%d]=%12.8f", j,xi[j]); +#endif + 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) */ +#ifdef DEBUGLINMIN + if(xxs <1.0) + 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 ); +#endif +#endif + p[j] += xi[j]; /* Parameters values are updated accordingly */ } +#ifdef DEBUGLINMIN + printf("\n"); + printf("Comparing last *frec(xmin=%12.8f)=%12.8f from Brent and frec(0.)=%12.8f \n", xmin, *fret, (*func)(p)); + fprintf(ficlog,"Comparing last *frec(xmin=%12.8f)=%12.8f from Brent and frec(0.)=%12.8f \n", xmin, *fret, (*func)(p)); + for (j=1;j<=n;j++) { + printf(" xi[%d]= %14.10f p[%d]= %12.7f",j,xi[j],j,p[j]); + fprintf(ficlog," xi[%d]= %14.10f p[%d]= %12.7f",j,xi[j],j,p[j]); + if(j % ncovmodel == 0){ + printf("\n"); + fprintf(ficlog,"\n"); + } + } +#else +#endif free_vector(xicom,1,n); free_vector(pcom,1,n); } + /*************** powell ************************/ +/* +Minimization of a function func of n variables. Input consists of an initial starting point +p[1..n] ; an initial matrix xi[1..n][1..n] , whose columns contain the initial set of di- +rections (usually the n unit vectors); and ftol , the fractional tolerance in the function value +such that failure to decrease by more than this amount on one iteration signals doneness. On +output, p is set to the best point found, xi is the then-current direction set, fret is the returned +function value at p , and iter is the number of iterations taken. The routine linmin is used. + */ +#ifdef LINMINORIGINAL +#else + int *flatdir; /* Function is vanishing in that direction */ + int flat=0, flatd=0; /* Function is vanishing in that direction */ +#endif void powell(double p[], double **xi, int n, double ftol, int *iter, double *fret, double (*func)(double [])) - { - - - void linmin(double p[], double xi[], int n, double *fret, +#ifdef LINMINORIGINAL + void linmin(double p[], double xi[], int n, double *fret, double (*func)(double [])); - int i,ibig,j; +#else + void linmin(double p[], double xi[], int n, double *fret, + double (*func)(double []),int *flat); +#endif + int i,ibig,j,jk,k; double del,t,*pt,*ptt,*xit; + double directest; double fp,fptt; double *xits; + int niterf, itmp; +#ifdef LINMINORIGINAL +#else + + flatdir=ivector(1,n); + for (j=1;j<=n;j++) flatdir[j]=0; +#endif + pt=vector(1,n); ptt=vector(1,n); xit=vector(1,n); xits=vector(1,n); *fret=(*func)(p); for (j=1;j<=n;j++) pt[j]=p[j]; + rcurr_time = time(NULL); for (*iter=1;;++(*iter)) { - fp=(*fret); + fp=(*fret); /* From former iteration or initial value */ ibig=0; del=0.0; - printf("\nPowell iter=%d -2*LL=%.12f",*iter,*fret); - for (i=1;i<=n;i++) - printf(" %d %.12f",i, p[i]); + rlast_time=rcurr_time; + /* (void) gettimeofday(&curr_time,&tzp); */ + rcurr_time = time(NULL); + curr_time = *localtime(&rcurr_time); + printf("\nPowell iter=%d -2*LL=%.12f %ld sec. %ld sec.",*iter,*fret, rcurr_time-rlast_time, rcurr_time-rstart_time);fflush(stdout); + fprintf(ficlog,"\nPowell iter=%d -2*LL=%.12f %ld sec. %ld sec.",*iter,*fret,rcurr_time-rlast_time, rcurr_time-rstart_time); fflush(ficlog); +/* fprintf(ficrespow,"%d %.12f %ld",*iter,*fret,curr_time.tm_sec-start_time.tm_sec); */ + for (i=1;i<=n;i++) { + fprintf(ficrespow," %.12lf", p[i]); + } + fprintf(ficrespow,"\n");fflush(ficrespow); + printf("\n#model= 1 + age "); + fprintf(ficlog,"\n#model= 1 + age "); + if(nagesqr==1){ + printf(" + age*age "); + fprintf(ficlog," + age*age "); + } + for(j=1;j <=ncovmodel-2;j++){ + if(Typevar[j]==0) { + printf(" + V%d ",Tvar[j]); + fprintf(ficlog," + V%d ",Tvar[j]); + }else if(Typevar[j]==1) { + printf(" + V%d*age ",Tvar[j]); + fprintf(ficlog," + V%d*age ",Tvar[j]); + }else if(Typevar[j]==2) { + printf(" + V%d*V%d ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]); + fprintf(ficlog," + V%d*V%d ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]); + } + } printf("\n"); - for (i=1;i<=n;i++) { - for (j=1;j<=n;j++) xit[j]=xi[j][i]; +/* printf("12 47.0114589 0.0154322 33.2424412 0.3279905 2.3731903 */ +/* 13 -21.5392400 0.1118147 1.2680506 1.2973408 -1.0663662 */ + fprintf(ficlog,"\n"); + for(i=1,jk=1; i <=nlstate; i++){ + for(k=1; k <=(nlstate+ndeath); k++){ + if (k != i) { + printf("%d%d ",i,k); + fprintf(ficlog,"%d%d ",i,k); + for(j=1; j <=ncovmodel; j++){ + printf("%12.7f ",p[jk]); + fprintf(ficlog,"%12.7f ",p[jk]); + jk++; + } + printf("\n"); + fprintf(ficlog,"\n"); + } + } + } + if(*iter <=3 && *iter >1){ + tml = *localtime(&rcurr_time); + strcpy(strcurr,asctime(&tml)); + rforecast_time=rcurr_time; + itmp = strlen(strcurr); + if(strcurr[itmp-1]=='\n') /* Windows outputs with a new line */ + strcurr[itmp-1]='\0'; + printf("\nConsidering the time needed for the last iteration #%d: %ld seconds,\n",*iter,rcurr_time-rlast_time); + fprintf(ficlog,"\nConsidering the time needed for this last iteration #%d: %ld seconds,\n",*iter,rcurr_time-rlast_time); + for(niterf=10;niterf<=30;niterf+=10){ + rforecast_time=rcurr_time+(niterf-*iter)*(rcurr_time-rlast_time); + forecast_time = *localtime(&rforecast_time); + strcpy(strfor,asctime(&forecast_time)); + itmp = strlen(strfor); + if(strfor[itmp-1]=='\n') + strfor[itmp-1]='\0'; + 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); + 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); + } + } + for (i=1;i<=n;i++) { /* For each direction i */ + for (j=1;j<=n;j++) xit[j]=xi[j][i]; /* Directions stored from previous iteration with previous scales */ fptt=(*fret); #ifdef DEBUG - printf("fret=%lf \n",*fret); + printf("fret=%lf, %lf, %lf \n", *fret, *fret, *fret); + fprintf(ficlog, "fret=%lf, %lf, %lf \n", *fret, *fret, *fret); +#endif + printf("%d",i);fflush(stdout); /* print direction (parameter) i */ + fprintf(ficlog,"%d",i);fflush(ficlog); +#ifdef LINMINORIGINAL + linmin(p,xit,n,fret,func); /* Point p[n]. xit[n] has been loaded for direction i as input.*/ +#else + linmin(p,xit,n,fret,func,&flat); /* Point p[n]. xit[n] has been loaded for direction i as input.*/ + flatdir[i]=flat; /* Function is vanishing in that direction i */ #endif - printf("%d",i);fflush(stdout); - linmin(p,xit,n,fret,func); - if (fabs(fptt-(*fret)) > del) { - del=fabs(fptt-(*fret)); - ibig=i; + /* Outputs are fret(new point p) p is updated and xit rescaled */ + if (fabs(fptt-(*fret)) > del) { /* We are keeping the max gain on each of the n directions */ + /* because that direction will be replaced unless the gain del is small */ + /* in comparison with the 'probable' gain, mu^2, with the last average direction. */ + /* Unless the n directions are conjugate some gain in the determinant may be obtained */ + /* with the new direction. */ + del=fabs(fptt-(*fret)); + ibig=i; } #ifdef DEBUG printf("%d %.12e",i,(*fret)); + fprintf(ficlog,"%d %.12e",i,(*fret)); for (j=1;j<=n;j++) { - xits[j]=FMAX(fabs(p[j]-pt[j]),1.e-5); - printf(" x(%d)=%.12e",j,xit[j]); + xits[j]=FMAX(fabs(p[j]-pt[j]),1.e-5); + printf(" x(%d)=%.12e",j,xit[j]); + fprintf(ficlog," x(%d)=%.12e",j,xit[j]); + } + for(j=1;j<=n;j++) { + printf(" p(%d)=%.12e",j,p[j]); + fprintf(ficlog," p(%d)=%.12e",j,p[j]); } - for(j=1;j<=n;j++) - printf(" p=%.12e",p[j]); printf("\n"); + fprintf(ficlog,"\n"); #endif - } - if (2.0*fabs(fp-(*fret)) <= ftol*(fabs(fp)+fabs(*fret))) { + } /* end loop on each direction i */ + /* Convergence test will use last linmin estimation (fret) and compare former iteration (fp) */ + /* But p and xit have been updated at the end of linmin, *fret corresponds to new p, xit */ + /* New value of last point Pn is not computed, P(n-1) */ + for(j=1;j<=n;j++) { + if(flatdir[j] >0){ + printf(" p(%d)=%lf flat=%d ",j,p[j],flatdir[j]); + fprintf(ficlog," p(%d)=%lf flat=%d ",j,p[j],flatdir[j]); + } + /* printf("\n"); */ + /* fprintf(ficlog,"\n"); */ + } + /* if (2.0*fabs(fp-(*fret)) <= ftol*(fabs(fp)+fabs(*fret))) { /\* Did we reach enough precision? *\/ */ + if (2.0*fabs(fp-(*fret)) <= ftol) { /* Did we reach enough precision? */ + /* We could compare with a chi^2. chisquare(0.95,ddl=1)=3.84 */ + /* By adding age*age in a model, the new -2LL should be lower and the difference follows a */ + /* a chisquare statistics with 1 degree. To be significant at the 95% level, it should have */ + /* decreased of more than 3.84 */ + /* By adding age*age and V1*age the gain (-2LL) should be more than 5.99 (ddl=2) */ + /* By using V1+V2+V3, the gain should be 7.82, compared with basic 1+age. */ + /* By adding 10 parameters more the gain should be 18.31 */ + + /* Starting the program with initial values given by a former maximization will simply change */ + /* the scales of the directions and the directions, because the are reset to canonical directions */ + /* Thus the first calls to linmin will give new points and better maximizations until fp-(*fret) is */ + /* under the tolerance value. If the tolerance is very small 1.e-9, it could last long. */ #ifdef DEBUG int k[2],l; k[0]=1; k[1]=-1; printf("Max: %.12e",(*func)(p)); - for (j=1;j<=n;j++) + fprintf(ficlog,"Max: %.12e",(*func)(p)); + for (j=1;j<=n;j++) { printf(" %.12e",p[j]); + fprintf(ficlog," %.12e",p[j]); + } printf("\n"); + fprintf(ficlog,"\n"); for(l=0;l<=1;l++) { for (j=1;j<=n;j++) { ptt[j]=p[j]+(p[j]-pt[j])*k[l]; printf("l=%d j=%d ptt=%.12e, xits=%.12e, p=%.12e, xit=%.12e", l,j,ptt[j],xits[j],p[j],xit[j]); + fprintf(ficlog,"l=%d j=%d ptt=%.12e, xits=%.12e, p=%.12e, xit=%.12e", l,j,ptt[j],xits[j],p[j],xit[j]); } printf("func(ptt)=%.12e, deriv=%.12e\n",(*func)(ptt),(ptt[j]-p[j])/((*func)(ptt)-(*func)(p))); + fprintf(ficlog,"func(ptt)=%.12e, deriv=%.12e\n",(*func)(ptt),(ptt[j]-p[j])/((*func)(ptt)-(*func)(p))); } #endif - +#ifdef LINMINORIGINAL +#else + free_ivector(flatdir,1,n); +#endif free_vector(xit,1,n); free_vector(xits,1,n); free_vector(ptt,1,n); free_vector(pt,1,n); return; - } - if (*iter == ITMAX) nrerror("powell exceeding maximum iterations."); - for (j=1;j<=n;j++) { + } /* enough precision */ + if (*iter == ITMAX*n) nrerror("powell exceeding maximum iterations."); + for (j=1;j<=n;j++) { /* Computes the extrapolated point P_0 + 2 (P_n-P_0) */ ptt[j]=2.0*p[j]-pt[j]; xit[j]=p[j]-pt[j]; pt[j]=p[j]; } - fptt=(*func)(ptt); - if (fptt < fp) { - t=2.0*(fp-2.0*(*fret)+fptt)*SQR(fp-(*fret)-del)-del*SQR(fp-fptt); - if (t < 0.0) { - linmin(p,xit,n,fret,func); + fptt=(*func)(ptt); /* f_3 */ +#ifdef NODIRECTIONCHANGEDUNTILNITER /* No change in drections until some iterations are done */ + if (*iter <=4) { +#else +#endif +#ifdef POWELLNOF3INFF1TEST /* skips test F3 <F1 */ +#else + if (fptt < fp) { /* If extrapolated point is better, decide if we keep that new direction or not */ +#endif + /* (x1 f1=fp), (x2 f2=*fret), (x3 f3=fptt), (xm fm) */ + /* From x1 (P0) distance of x2 is at h and x3 is 2h */ + /* Let f"(x2) be the 2nd derivative equal everywhere. */ + /* Then the parabolic through (x1,f1), (x2,f2) and (x3,f3) */ + /* will reach at f3 = fm + h^2/2 f"m ; f" = (f1 -2f2 +f3 ) / h**2 */ + /* Conditional for using this new direction is that mu^2 = (f1-2f2+f3)^2 /2 < del or directest <0 */ + /* also lamda^2=(f1-f2)^2/mu² is a parasite solution of powell */ + /* For powell, inclusion of this average direction is only if t(del)<0 or del inbetween mu^2 and lambda^2 */ + /* t=2.0*(fp-2.0*(*fret)+fptt)*SQR(fp-(*fret)-del)-del*SQR(fp-fptt); */ + /* Even if f3 <f1, directest can be negative and t >0 */ + /* mu² and del² are equal when f3=f1 */ + /* f3 < f1 : mu² < del <= lambda^2 both test are equivalent */ + /* f3 < f1 : mu² < lambda^2 < del then directtest is negative and powell t is positive */ + /* f3 > f1 : lambda² < mu^2 < del then t is negative and directest >0 */ + /* f3 > f1 : lambda² < del < mu^2 then t is positive and directest >0 */ +#ifdef NRCORIGINAL + t=2.0*(fp-2.0*(*fret)+fptt)*SQR(fp-(*fret)-del)- del*SQR(fp-fptt); /* Original Numerical Recipes in C*/ +#else + t=2.0*(fp-2.0*(*fret)+fptt)*SQR(fp-(*fret)-del); /* Intel compiler doesn't work on one line; bug reported */ + t= t- del*SQR(fp-fptt); +#endif + directest = fp-2.0*(*fret)+fptt - 2.0 * del; /* If delta was big enough we change it for a new direction */ +#ifdef DEBUG + 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); + 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); + printf("t3= %.12lf, t4= %.12lf, t3*= %.12lf, t4*= %.12lf\n",SQR(fp-(*fret)-del),SQR(fp-fptt), + (fp-(*fret)-del)*(fp-(*fret)-del),(fp-fptt)*(fp-fptt)); + fprintf(ficlog,"t3= %.12lf, t4= %.12lf, t3*= %.12lf, t4*= %.12lf\n",SQR(fp-(*fret)-del),SQR(fp-fptt), + (fp-(*fret)-del)*(fp-(*fret)-del),(fp-fptt)*(fp-fptt)); + 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); + 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); +#endif +#ifdef POWELLORIGINAL + if (t < 0.0) { /* Then we use it for new direction */ +#else + if (directest*t < 0.0) { /* Contradiction between both tests */ + 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); + printf("f1-2f2+f3= %.12lf, f1-f2-del= %.12lf, f1-f3= %.12lf\n",fp-2.0*(*fret)+fptt, fp -(*fret) -del, fp-fptt); + 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); + fprintf(ficlog,"f1-2f2+f3= %.12lf, f1-f2-del= %.12lf, f1-f3= %.12lf\n",fp-2.0*(*fret)+fptt, fp -(*fret) -del, fp-fptt); + } + if (directest < 0.0) { /* Then we use it for new direction */ +#endif +#ifdef DEBUGLINMIN + printf("Before linmin in direction P%d-P0\n",n); + for (j=1;j<=n;j++) { + printf(" Before xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]); + fprintf(ficlog," Before xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]); + if(j % ncovmodel == 0){ + printf("\n"); + fprintf(ficlog,"\n"); + } + } +#endif +#ifdef LINMINORIGINAL + linmin(p,xit,n,fret,func); /* computes minimum on the extrapolated direction: changes p and rescales xit.*/ +#else + linmin(p,xit,n,fret,func,&flat); /* computes minimum on the extrapolated direction: changes p and rescales xit.*/ + flatdir[i]=flat; /* Function is vanishing in that direction i */ +#endif + +#ifdef DEBUGLINMIN + for (j=1;j<=n;j++) { + printf("After xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]); + fprintf(ficlog,"After xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]); + if(j % ncovmodel == 0){ + printf("\n"); + fprintf(ficlog,"\n"); + } + } +#endif for (j=1;j<=n;j++) { - xi[j][ibig]=xi[j][n]; - xi[j][n]=xit[j]; + xi[j][ibig]=xi[j][n]; /* Replace direction with biggest decrease by last direction n */ + xi[j][n]=xit[j]; /* and this nth direction by the by the average p_0 p_n */ + } +#ifdef LINMINORIGINAL +#else + for (j=1, flatd=0;j<=n;j++) { + if(flatdir[j]>0) + flatd++; + } + if(flatd >0){ + printf("%d flat directions\n",flatd); + fprintf(ficlog,"%d flat directions\n",flatd); + for (j=1;j<=n;j++) { + if(flatdir[j]>0){ + printf("%d ",j); + fprintf(ficlog,"%d ",j); + } + } + printf("\n"); + fprintf(ficlog,"\n"); } +#endif + printf("Gaining to use new average direction of P0 P%d instead of biggest increase direction %d :\n",n,ibig); + fprintf(ficlog,"Gaining to use new average direction of P0 P%d instead of biggest increase direction %d :\n",n,ibig); + #ifdef DEBUG printf("Direction changed last moved %d in place of ibig=%d, new last is the average:\n",n,ibig); - for(j=1;j<=n;j++) - printf(" %.12e",xit[j]); + fprintf(ficlog,"Direction changed last moved %d in place of ibig=%d, new last is the average:\n",n,ibig); + for(j=1;j<=n;j++){ + printf(" %lf",xit[j]); + fprintf(ficlog," %lf",xit[j]); + } printf("\n"); + fprintf(ficlog,"\n"); #endif - } - } - } + } /* end of t or directest negative */ +#ifdef POWELLNOF3INFF1TEST +#else + } /* end if (fptt < fp) */ +#endif +#ifdef NODIRECTIONCHANGEDUNTILNITER /* No change in drections until some iterations are done */ + } /*NODIRECTIONCHANGEDUNTILNITER No change in drections until some iterations are done */ +#else +#endif + } /* loop iteration */ } - -/**** Prevalence limit ****************/ - -double **prevalim(double **prlim, int nlstate, double x[], double age, double **oldm, double **savm, double ftolpl) -{ - /* Computes the prevalence limit in each live state at age x by left multiplying the unit - matrix by transitions matrix until convergence is reached */ - + +/**** Prevalence limit (stable or period prevalence) ****************/ + + double **prevalim(double **prlim, int nlstate, double x[], double age, double **oldm, double **savm, double ftolpl, int *ncvyear, int ij, int nres) + { + /* Computes the prevalence limit in each live state at age x and for covariate combination ij + (and selected quantitative values in nres) + by left multiplying the unit + matrix by transitions matrix until convergence is reached with precision ftolpl */ + /* Wx= Wx-1 Px-1= Wx-2 Px-2 Px-1 = Wx-n Px-n ... Px-2 Px-1 I */ + /* Wx is row vector: population in state 1, population in state 2, population dead */ + /* or prevalence in state 1, prevalence in state 2, 0 */ + /* newm is the matrix after multiplications, its rows are identical at a factor */ + /* Initial matrix pimij */ + /* {0.85204250825084937, 0.13044499163996345, 0.017512500109187184, */ + /* 0.090851990222114765, 0.88271245433047185, 0.026435555447413338, */ + /* 0, 0 , 1} */ + /* + * and after some iteration: */ + /* {0.45504275246439968, 0.42731458730878791, 0.11764266022681241, */ + /* 0.45201005341706885, 0.42865420071559901, 0.11933574586733192, */ + /* 0, 0 , 1} */ + /* And prevalence by suppressing the deaths are close to identical rows in prlim: */ + /* {0.51571254859325999, 0.4842874514067399, */ + /* 0.51326036147820708, 0.48673963852179264} */ + /* If we start from prlim again, prlim tends to a constant matrix */ + int i, ii,j,k; - double min, max, maxmin, maxmax,sumnew=0.; - double **matprod2(); - double **out, cov[NCOVMAX], **pmij(); + double *min, *max, *meandiff, maxmax,sumnew=0.; + /* double **matprod2(); */ /* test */ + double **out, cov[NCOVMAX+1], **pmij(); /* **pmmij is a global variable feeded with oldms etc */ double **newm; - double agefin, delaymax=50 ; /* Max number of years to converge */ + double agefin, delaymax=200. ; /* 100 Max number of years to converge */ + int ncvloop=0; + + min=vector(1,nlstate); + max=vector(1,nlstate); + meandiff=vector(1,nlstate); + /* Starting with matrix unity */ for (ii=1;ii<=nlstate+ndeath;ii++) for (j=1;j<=nlstate+ndeath;j++){ oldm[ii][j]=(ii==j ? 1.0 : 0.0); } + + cov[1]=1.; + /* Even if hstepm = 1, at least one multiplication by the unit matrix */ + /* Start at agefin= age, computes the matrix of passage and loops decreasing agefin until convergence is reached */ for(agefin=age-stepm/YEARM; agefin>=age-delaymax; agefin=agefin-stepm/YEARM){ + ncvloop++; newm=savm; /* Covariates have to be included here again */ - cov[1]=1.; cov[2]=agefin; - out=matprod2(newm, pmij(pmmij,cov,ncov,x,nlstate),1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); -/* printf("age=%f agefin=%f po=%f pn=%f\n",age,agefin,oldm[1][1],newm[1][1]);*/ + if(nagesqr==1) + cov[3]= agefin*agefin;; + for (k=1; k<=nsd;k++) { /* For single dummy covariates only */ + /* Here comes the value of the covariate 'ij' after renumbering k with single dummy covariates */ + cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,k)]; + /* 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)); */ + } + for (k=1; k<=nsq;k++) { /* For single varying covariates only */ + /* Here comes the value of quantitative after renumbering k with single quantitative covariates */ + cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k]; + /* 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]); */ + } + for (k=1; k<=cptcovage;k++){ /* For product with age */ + if(Dummy[Tvar[Tage[k]]]){ + cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2]; + } else{ + cov[2+nagesqr+Tage[k]]=Tqresult[nres][k]; + } + /* 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]); */ + } + for (k=1; k<=cptcovprod;k++){ /* For product without age */ + /* 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]); */ + if(Dummy[Tvard[k][1]==0]){ + if(Dummy[Tvard[k][2]==0]){ + cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)]; + }else{ + cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * Tqresult[nres][k]; + } + }else{ + if(Dummy[Tvard[k][2]==0]){ + cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][2]][codtabm(ij,k)] * Tqinvresult[nres][Tvard[k][1]]; + }else{ + cov[2+nagesqr+Tprod[k]]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]]; + } + } + } + /*printf("ij=%d cptcovprod=%d tvar=%d ", ij, cptcovprod, Tvar[1]);*/ + /*printf("ij=%d cov[3]=%lf cov[4]=%lf \n",ij, cov[3],cov[4]);*/ + /*printf("ij=%d cov[3]=%lf \n",ij, cov[3]);*/ + /* savm=pmij(pmmij,cov,ncovmodel,x,nlstate); */ + /* out=matprod2(newm, pmij(pmmij,cov,ncovmodel,x,nlstate),1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); /\* Bug Valgrind *\/ */ + /* age and covariate values of ij are in 'cov' */ + out=matprod2(newm, pmij(pmmij,cov,ncovmodel,x,nlstate),1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); /* Bug Valgrind */ savm=oldm; oldm=newm; - maxmax=0.; - for(j=1;j<=nlstate;j++){ - min=1.; - max=0.; - for(i=1; i<=nlstate; i++) { - sumnew=0; - for(k=1; k<=ndeath; k++) sumnew+=newm[i][nlstate+k]; + + for(j=1; j<=nlstate; j++){ + max[j]=0.; + min[j]=1.; + } + for(i=1;i<=nlstate;i++){ + sumnew=0; + for(k=1; k<=ndeath; k++) sumnew+=newm[i][nlstate+k]; + for(j=1; j<=nlstate; j++){ prlim[i][j]= newm[i][j]/(1-sumnew); - max=FMAX(max,prlim[i][j]); - min=FMIN(min,prlim[i][j]); + max[j]=FMAX(max[j],prlim[i][j]); + min[j]=FMIN(min[j],prlim[i][j]); } - maxmin=max-min; - maxmax=FMAX(maxmax,maxmin); } + + maxmax=0.; + for(j=1; j<=nlstate; j++){ + meandiff[j]=(max[j]-min[j])/(max[j]+min[j])*2.; /* mean difference for each column */ + maxmax=FMAX(maxmax,meandiff[j]); + /* 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); */ + } /* j loop */ + *ncvyear= (int)age- (int)agefin; + /* printf("maxmax=%lf maxmin=%lf ncvloop=%d, age=%d, agefin=%d ncvyear=%d \n", maxmax, maxmin, ncvloop, (int)age, (int)agefin, *ncvyear); */ if(maxmax < ftolpl){ + /* printf("maxmax=%lf ncvloop=%ld, age=%d, agefin=%d ncvyear=%d \n", maxmax, ncvloop, (int)age, (int)agefin, *ncvyear); */ + free_vector(min,1,nlstate); + free_vector(max,1,nlstate); + free_vector(meandiff,1,nlstate); return prlim; } - } + } /* age loop */ + /* After some age loop it doesn't converge */ + 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\ +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); + /* 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); */ + free_vector(min,1,nlstate); + free_vector(max,1,nlstate); + free_vector(meandiff,1,nlstate); + + return prlim; /* should not reach here */ +} + + + /**** Back Prevalence limit (stable or period prevalence) ****************/ + + /* 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) */ + /* 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) */ + double **bprevalim(double **bprlim, double ***prevacurrent, int nlstate, double x[], double age, double ftolpl, int *ncvyear, int ij, int nres) +{ + /* Computes the prevalence limit in each live state at age x and covariate ij by left multiplying the unit + matrix by transitions matrix until convergence is reached with precision ftolpl */ + /* Wx= Wx-1 Px-1= Wx-2 Px-2 Px-1 = Wx-n Px-n ... Px-2 Px-1 I */ + /* Wx is row vector: population in state 1, population in state 2, population dead */ + /* or prevalence in state 1, prevalence in state 2, 0 */ + /* newm is the matrix after multiplications, its rows are identical at a factor */ + /* Initial matrix pimij */ + /* {0.85204250825084937, 0.13044499163996345, 0.017512500109187184, */ + /* 0.090851990222114765, 0.88271245433047185, 0.026435555447413338, */ + /* 0, 0 , 1} */ + /* + * and after some iteration: */ + /* {0.45504275246439968, 0.42731458730878791, 0.11764266022681241, */ + /* 0.45201005341706885, 0.42865420071559901, 0.11933574586733192, */ + /* 0, 0 , 1} */ + /* And prevalence by suppressing the deaths are close to identical rows in prlim: */ + /* {0.51571254859325999, 0.4842874514067399, */ + /* 0.51326036147820708, 0.48673963852179264} */ + /* If we start from prlim again, prlim tends to a constant matrix */ + + int i, ii,j,k; + int first=0; + double *min, *max, *meandiff, maxmax,sumnew=0.; + /* double **matprod2(); */ /* test */ + double **out, cov[NCOVMAX+1], **bmij(); + double **newm; + double **dnewm, **doldm, **dsavm; /* for use */ + double **oldm, **savm; /* for use */ + + double agefin, delaymax=200. ; /* 100 Max number of years to converge */ + int ncvloop=0; + + min=vector(1,nlstate); + max=vector(1,nlstate); + meandiff=vector(1,nlstate); + + dnewm=ddnewms; doldm=ddoldms; dsavm=ddsavms; + oldm=oldms; savm=savms; + + /* Starting with matrix unity */ + for (ii=1;ii<=nlstate+ndeath;ii++) + for (j=1;j<=nlstate+ndeath;j++){ + oldm[ii][j]=(ii==j ? 1.0 : 0.0); + } + + cov[1]=1.; + + /* Even if hstepm = 1, at least one multiplication by the unit matrix */ + /* Start at agefin= age, computes the matrix of passage and loops decreasing agefin until convergence is reached */ + /* for(agefin=age+stepm/YEARM; agefin<=age+delaymax; agefin=agefin+stepm/YEARM){ /\* A changer en age *\/ */ + for(agefin=age; agefin<AGESUP; agefin=agefin+stepm/YEARM){ /* A changer en age */ + ncvloop++; + newm=savm; /* oldm should be kept from previous iteration or unity at start */ + /* newm points to the allocated table savm passed by the function it can be written, savm could be reallocated */ + /* Covariates have to be included here again */ + cov[2]=agefin; + if(nagesqr==1) + cov[3]= agefin*agefin;; + for (k=1; k<=nsd;k++) { /* For single dummy covariates only */ + /* Here comes the value of the covariate 'ij' after renumbering k with single dummy covariates */ + cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,k)]; + /* printf("bprevalim Dummy combi=%d k=%d TvarsD[%d]=V%d TvarsDind[%d]=%d nbcode=%d cov=%lf codtabm(%d,Tvar[%d])=%d \n",ij,k, k, TvarsD[k],k,TvarsDind[k],nbcode[TvarsD[k]][codtabm(ij,k)],cov[2+nagesqr+TvarsDind[k]], ij, k, codtabm(ij,k)); */ + } + /* for (k=1; k<=cptcovn;k++) { */ + /* /\* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,Tvar[k])]; *\/ */ + /* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,k)]; */ + /* /\* 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])]); *\/ */ + /* } */ + for (k=1; k<=nsq;k++) { /* For single varying covariates only */ + /* Here comes the value of quantitative after renumbering k with single quantitative covariates */ + cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k]; + /* 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]); */ + } + /* for (k=1; k<=cptcovage;k++) cov[2+nagesqr+Tage[k]]=nbcode[Tvar[k]][codtabm(ij,k)]*cov[2]; */ + /* for (k=1; k<=cptcovprod;k++) /\* Useless *\/ */ + /* /\* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])]; *\/ */ + /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)]; */ + for (k=1; k<=cptcovage;k++){ /* For product with age */ + if(Dummy[Tvar[Tage[k]]]){ + cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2]; + } else{ + cov[2+nagesqr+Tage[k]]=Tqresult[nres][k]; + } + /* 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]); */ + } + for (k=1; k<=cptcovprod;k++){ /* For product without age */ + /* 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]); */ + if(Dummy[Tvard[k][1]==0]){ + if(Dummy[Tvard[k][2]==0]){ + cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)]; + }else{ + cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * Tqresult[nres][k]; + } + }else{ + if(Dummy[Tvard[k][2]==0]){ + cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][2]][codtabm(ij,k)] * Tqinvresult[nres][Tvard[k][1]]; + }else{ + cov[2+nagesqr+Tprod[k]]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]]; + } + } + } + + /*printf("ij=%d cptcovprod=%d tvar=%d ", ij, cptcovprod, Tvar[1]);*/ + /*printf("ij=%d cov[3]=%lf cov[4]=%lf \n",ij, cov[3],cov[4]);*/ + /*printf("ij=%d cov[3]=%lf \n",ij, cov[3]);*/ + /* savm=pmij(pmmij,cov,ncovmodel,x,nlstate); */ + /* out=matprod2(newm, pmij(pmmij,cov,ncovmodel,x,nlstate),1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); /\* Bug Valgrind *\/ */ + /* ij should be linked to the correct index of cov */ + /* age and covariate values ij are in 'cov', but we need to pass + * ij for the observed prevalence at age and status and covariate + * number: prevacurrent[(int)agefin][ii][ij] + */ + /* 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 *\/ */ + /* 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 *\/ */ + out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, bmij(pmmij,cov,ncovmodel,x,nlstate,prevacurrent,ij)); /* Bug Valgrind */ + savm=oldm; + oldm=newm; + for(j=1; j<=nlstate; j++){ + max[j]=0.; + min[j]=1.; + } + for(j=1; j<=nlstate; j++){ + for(i=1;i<=nlstate;i++){ + /* bprlim[i][j]= newm[i][j]/(1-sumnew); */ + bprlim[i][j]= newm[i][j]; + max[i]=FMAX(max[i],bprlim[i][j]); /* Max in line */ + min[i]=FMIN(min[i],bprlim[i][j]); + } + } + + maxmax=0.; + for(i=1; i<=nlstate; i++){ + meandiff[i]=(max[i]-min[i])/(max[i]+min[i])*2.; /* mean difference for each column */ + maxmax=FMAX(maxmax,meandiff[i]); + /* 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); */ + } /* j loop */ + *ncvyear= -( (int)age- (int)agefin); + /* printf("Back maxmax=%lf ncvloop=%d, age=%d, agefin=%d ncvyear=%d \n", maxmax, ncvloop, (int)age, (int)agefin, *ncvyear);*/ + if(maxmax < ftolpl){ + /* printf("OK Back maxmax=%lf ncvloop=%d, age=%d, agefin=%d ncvyear=%d \n", maxmax, ncvloop, (int)age, (int)agefin, *ncvyear); */ + free_vector(min,1,nlstate); + free_vector(max,1,nlstate); + free_vector(meandiff,1,nlstate); + return bprlim; + } + } /* age loop */ + /* After some age loop it doesn't converge */ + if(first){ + first=1; + 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\ +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); + } + 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\ +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); + /* 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); */ + free_vector(min,1,nlstate); + free_vector(max,1,nlstate); + free_vector(meandiff,1,nlstate); + + return bprlim; /* should not reach here */ } -/*************** transition probabilities **********/ +/*************** transition probabilities ***************/ -double **pmij(double **ps, double *cov, int ncov, double *x, int nlstate ) +double **pmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate ) { - double s1, s2; + /* According to parameters values stored in x and the covariate's values stored in cov, + computes the probability to be observed in state j being in state i by appying the + model to the ncovmodel covariates (including constant and age). + lnpijopii=ln(pij/pii)= aij+bij*age+cij*v1+dij*v2+... = sum_nc=1^ncovmodel xij(nc)*cov[nc] + and, according on how parameters are entered, the position of the coefficient xij(nc) of the + ncth covariate in the global vector x is given by the formula: + j<i nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel + j>=i nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel + Computes ln(pij/pii) (lnpijopii), deduces pij/pii by exponentiation, + sums on j different of i to get 1-pii/pii, deduces pii, and then all pij. + Outputs ps[i][j] the probability to be observed in j being in j according to + the values of the covariates cov[nc] and corresponding parameter values x[nc+shiftij] + */ + double s1, lnpijopii; /*double t34;*/ - int i,j,j1, nc, ii, jj; + int i,j, nc, ii, jj; - for(i=1; i<= nlstate; i++){ + for(i=1; i<= nlstate; i++){ for(j=1; j<i;j++){ - for (nc=1, s2=0.;nc <=ncov; nc++){ - /*s2 += param[i][j][nc]*cov[nc];*/ - s2 += x[(i-1)*nlstate*ncov+(j-1)*ncov+nc+(i-1)*(ndeath-1)*ncov]*cov[nc]; - /*printf("Int j<i s1=%.17e, s2=%.17e\n",s1,s2);*/ + for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){ + /*lnpijopii += param[i][j][nc]*cov[nc];*/ + lnpijopii += x[nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel]*cov[nc]; + /* printf("Int j<i s1=%.17e, lnpijopii=%.17e\n",s1,lnpijopii); */ } - ps[i][j]=s2; - /*printf("s1=%.17e, s2=%.17e\n",s1,s2);*/ + ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */ + /* printf("s1=%.17e, lnpijopii=%.17e\n",s1,lnpijopii); */ } for(j=i+1; j<=nlstate+ndeath;j++){ - for (nc=1, s2=0.;nc <=ncov; nc++){ - s2 += x[(i-1)*nlstate*ncov+(j-2)*ncov+nc+(i-1)*(ndeath-1)*ncov]*cov[nc]; - /*printf("Int j>i s1=%.17e, s2=%.17e %lx %lx\n",s1,s2,s1,s2);*/ + for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){ + /*lnpijopii += x[(i-1)*nlstate*ncovmodel+(j-2)*ncovmodel+nc+(i-1)*(ndeath-1)*ncovmodel]*cov[nc];*/ + lnpijopii += x[nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel]*cov[nc]; + /* printf("Int j>i s1=%.17e, lnpijopii=%.17e %lx %lx\n",s1,lnpijopii,s1,lnpijopii); */ } - ps[i][j]=s2; + ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */ } } + for(i=1; i<= nlstate; i++){ - s1=0; - for(j=1; j<i; j++) - s1+=exp(ps[i][j]); - for(j=i+1; j<=nlstate+ndeath; j++) - s1+=exp(ps[i][j]); + s1=0; + for(j=1; j<i; j++){ + s1+=exp(ps[i][j]); /* In fact sums pij/pii */ + /*printf("debug1 %d %d ps=%lf exp(ps)=%lf s1+=%lf\n",i,j,ps[i][j],exp(ps[i][j]),s1); */ + } + for(j=i+1; j<=nlstate+ndeath; j++){ + s1+=exp(ps[i][j]); /* In fact sums pij/pii */ + /*printf("debug2 %d %d ps=%lf exp(ps)=%lf s1+=%lf\n",i,j,ps[i][j],exp(ps[i][j]),s1); */ + } + /* s1= sum_{j<>i} pij/pii=(1-pii)/pii and thus pii is known from s1 */ ps[i][i]=1./(s1+1.); + /* Computing other pijs */ for(j=1; j<i; j++) ps[i][j]= exp(ps[i][j])*ps[i][i]; for(j=i+1; j<=nlstate+ndeath; j++) ps[i][j]= exp(ps[i][j])*ps[i][i]; /* ps[i][nlstate+1]=1.-s1- ps[i][i];*/ /* Sum should be 1 */ } /* end i */ - + for(ii=nlstate+1; ii<= nlstate+ndeath; ii++){ for(jj=1; jj<= nlstate+ndeath; jj++){ ps[ii][jj]=0; ps[ii][ii]=1; } } + + + /* for(ii=1; ii<= nlstate+ndeath; ii++){ */ + /* for(jj=1; jj<= nlstate+ndeath; jj++){ */ + /* printf(" pmij ps[%d][%d]=%lf ",ii,jj,ps[ii][jj]); */ + /* } */ + /* printf("\n "); */ + /* } */ + /* printf("\n ");printf("%lf ",cov[2]);*/ + /* + for(i=1; i<= npar; i++) printf("%f ",x[i]); + goto end;*/ + return ps; +} + +/*************** backward transition probabilities ***************/ + + /* 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 ) */ +/* double **bmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate, double ***prevacurrent, double ***dnewm, double **doldm, double **dsavm, int ij ) */ + double **bmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate, double ***prevacurrent, int ij ) +{ + /* Computes the backward probability at age agefin and covariate ij + * and returns in **ps as well as **bmij. + */ + int i, ii, j,k; + + double **out, **pmij(); + double sumnew=0.; + double agefin; + + double **dnewm, **dsavm, **doldm; + double **bbmij; + + doldm=ddoldms; /* global pointers */ + dnewm=ddnewms; + dsavm=ddsavms; + + agefin=cov[2]; + /* bmij *//* age is cov[2], ij is included in cov, but we need for + the observed prevalence (with this covariate ij) */ + dsavm=pmij(pmmij,cov,ncovmodel,x,nlstate); + /* We do have the matrix Px in savm and we need pij */ + for (j=1;j<=nlstate+ndeath;j++){ + sumnew=0.; /* w1 p11 + w2 p21 only on live states */ + for (ii=1;ii<=nlstate;ii++){ + sumnew+=dsavm[ii][j]*prevacurrent[(int)agefin][ii][ij]; + } /* sumnew is (N11+N21)/N..= N.1/N.. = sum on i of w_i pij */ + for (ii=1;ii<=nlstate+ndeath;ii++){ + if(sumnew >= 1.e-10){ + /* if(agefin >= agemaxpar && agefin <= agemaxpar+stepm/YEARM){ */ + /* doldm[ii][j]=(ii==j ? 1./sumnew : 0.0); */ + /* }else if(agefin >= agemaxpar+stepm/YEARM){ */ + /* doldm[ii][j]=(ii==j ? 1./sumnew : 0.0); */ + /* }else */ + doldm[ii][j]=(ii==j ? 1./sumnew : 0.0); + }else{ + ; + /* printf("ii=%d, i=%d, doldm=%lf dsavm=%lf, probs=%lf, sumnew=%lf,agefin=%d\n",ii,j,doldm[ii][j],dsavm[ii][j],prevacurrent[(int)agefin][ii][ij],sumnew, (int)agefin); */ + } + } /*End ii */ + } /* End j, At the end doldm is diag[1/(w_1p1i+w_2 p2i)] */ + /* left Product of this diag matrix by dsavm=Px (newm=dsavm*doldm) */ + bbmij=matprod2(dnewm, dsavm,1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, doldm); /* Bug Valgrind */ + /* dsavm=doldm; /\* dsavm is now diag [1/(w_1p1i+w_2 p2i)] but can be overwritten*\/ */ + /* doldm=dnewm; /\* doldm is now Px * diag [1/(w_1p1i+w_2 p2i)] *\/ */ + /* dnewm=dsavm; /\* doldm is now Px * diag [1/(w_1p1i+w_2 p2i)] *\/ */ + /* left Product of this matrix by diag matrix of prevalences (savm) */ + for (j=1;j<=nlstate+ndeath;j++){ + for (ii=1;ii<=nlstate+ndeath;ii++){ + dsavm[ii][j]=(ii==j ? prevacurrent[(int)agefin][ii][ij] : 0.0); + } + } /* End j, At the end oldm is diag[1/(w_1p1i+w_2 p2i)] */ + ps=matprod2(doldm, dsavm,1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, dnewm); /* Bug Valgrind */ + /* newm or out is now diag[w_i] * Px * diag [1/(w_1p1i+w_2 p2i)] */ + /* end bmij */ + return ps; +} +/*************** transition probabilities ***************/ + +double **bpmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate ) +{ + /* According to parameters values stored in x and the covariate's values stored in cov, + computes the probability to be observed in state j being in state i by appying the + model to the ncovmodel covariates (including constant and age). + lnpijopii=ln(pij/pii)= aij+bij*age+cij*v1+dij*v2+... = sum_nc=1^ncovmodel xij(nc)*cov[nc] + and, according on how parameters are entered, the position of the coefficient xij(nc) of the + ncth covariate in the global vector x is given by the formula: + j<i nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel + j>=i nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel + Computes ln(pij/pii) (lnpijopii), deduces pij/pii by exponentiation, + sums on j different of i to get 1-pii/pii, deduces pii, and then all pij. + Outputs ps[i][j] the probability to be observed in j being in j according to + the values of the covariates cov[nc] and corresponding parameter values x[nc+shiftij] + */ + double s1, lnpijopii; + /*double t34;*/ + int i,j, nc, ii, jj; - /* for(ii=1; ii<= nlstate+ndeath; ii++){ + for(i=1; i<= nlstate; i++){ + for(j=1; j<i;j++){ + for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){ + /*lnpijopii += param[i][j][nc]*cov[nc];*/ + lnpijopii += x[nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel]*cov[nc]; + /* printf("Int j<i s1=%.17e, lnpijopii=%.17e\n",s1,lnpijopii); */ + } + ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */ + /* printf("s1=%.17e, lnpijopii=%.17e\n",s1,lnpijopii); */ + } + for(j=i+1; j<=nlstate+ndeath;j++){ + for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){ + /*lnpijopii += x[(i-1)*nlstate*ncovmodel+(j-2)*ncovmodel+nc+(i-1)*(ndeath-1)*ncovmodel]*cov[nc];*/ + lnpijopii += x[nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel]*cov[nc]; + /* printf("Int j>i s1=%.17e, lnpijopii=%.17e %lx %lx\n",s1,lnpijopii,s1,lnpijopii); */ + } + ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */ + } + } + + for(i=1; i<= nlstate; i++){ + s1=0; + for(j=1; j<i; j++){ + s1+=exp(ps[i][j]); /* In fact sums pij/pii */ + /*printf("debug1 %d %d ps=%lf exp(ps)=%lf s1+=%lf\n",i,j,ps[i][j],exp(ps[i][j]),s1); */ + } + for(j=i+1; j<=nlstate+ndeath; j++){ + s1+=exp(ps[i][j]); /* In fact sums pij/pii */ + /*printf("debug2 %d %d ps=%lf exp(ps)=%lf s1+=%lf\n",i,j,ps[i][j],exp(ps[i][j]),s1); */ + } + /* s1= sum_{j<>i} pij/pii=(1-pii)/pii and thus pii is known from s1 */ + ps[i][i]=1./(s1+1.); + /* Computing other pijs */ + for(j=1; j<i; j++) + ps[i][j]= exp(ps[i][j])*ps[i][i]; + for(j=i+1; j<=nlstate+ndeath; j++) + ps[i][j]= exp(ps[i][j])*ps[i][i]; + /* ps[i][nlstate+1]=1.-s1- ps[i][i];*/ /* Sum should be 1 */ + } /* end i */ + + for(ii=nlstate+1; ii<= nlstate+ndeath; ii++){ for(jj=1; jj<= nlstate+ndeath; jj++){ - printf("%lf ",ps[ii][jj]); - } - printf("\n "); + ps[ii][jj]=0; + ps[ii][ii]=1; } - printf("\n ");printf("%lf ",cov[2]);*/ -/* - for(i=1; i<= npar; i++) printf("%f ",x[i]); - goto end;*/ - return ps; + } + /* Added for backcast */ /* Transposed matrix too */ + for(jj=1; jj<= nlstate+ndeath; jj++){ + s1=0.; + for(ii=1; ii<= nlstate+ndeath; ii++){ + s1+=ps[ii][jj]; + } + for(ii=1; ii<= nlstate; ii++){ + ps[ii][jj]=ps[ii][jj]/s1; + } + } + /* Transposition */ + for(jj=1; jj<= nlstate+ndeath; jj++){ + for(ii=jj; ii<= nlstate+ndeath; ii++){ + s1=ps[ii][jj]; + ps[ii][jj]=ps[jj][ii]; + ps[jj][ii]=s1; + } + } + /* for(ii=1; ii<= nlstate+ndeath; ii++){ */ + /* for(jj=1; jj<= nlstate+ndeath; jj++){ */ + /* printf(" pmij ps[%d][%d]=%lf ",ii,jj,ps[ii][jj]); */ + /* } */ + /* printf("\n "); */ + /* } */ + /* printf("\n ");printf("%lf ",cov[2]);*/ + /* + for(i=1; i<= npar; i++) printf("%f ",x[i]); + goto end;*/ + return ps; } + /**************** Product of 2 matrices ******************/ -double **matprod2(double **out, double **in,long nrl, long nrh, long ncl, long nch, long ncolol, long ncoloh, double **b) +double **matprod2(double **out, double **in,int nrl, int nrh, int ncl, int nch, int ncolol, int ncoloh, double **b) { - /* Computes the matric product of in(1,nrh-nrl+1)(1,nch-ncl+1) times + /* Computes the matrix product of in(1,nrh-nrl+1)(1,nch-ncl+1) times b(1,nch-ncl+1)(1,ncoloh-ncolol+1) into out(...) */ /* in, b, out are matrice of pointers which should have been initialized before: only the contents of out is modified. The function returns a pointer to pointers identical to out */ - long i, j, k; + int i, j, k; for(i=nrl; i<= nrh; i++) - for(k=ncolol; k<=ncoloh; k++) - for(j=ncl,out[i][k]=0.; j<=nch; j++) - out[i][k] +=in[i][j]*b[j][k]; - + for(k=ncolol; k<=ncoloh; k++){ + out[i][k]=0.; + for(j=ncl; j<=nch; j++) + out[i][k] +=in[i][j]*b[j][k]; + } return out; } /************* Higher Matrix Product ***************/ -double ***hpxij(double ***po, int nhstepm, double age, int hstepm, double *x, int nlstate, int stepm, double **oldm, double **savm ) +double ***hpxij(double ***po, int nhstepm, double age, int hstepm, double *x, int nlstate, int stepm, double **oldm, double **savm, int ij, int nres ) { - /* Computes the transition matrix starting at age 'age' over 'nhstepm*hstepm*stepm' month - duration (i.e. until - age (in years) age+nhstepm*stepm/12) by multiplying nhstepm*hstepm matrices. + /* Computes the transition matrix starting at age 'age' and combination of covariate values corresponding to ij over + 'nhstepm*hstepm*stepm' months (i.e. until + age (in years) age+nhstepm*hstepm*stepm/12) by multiplying + nhstepm*hstepm matrices. Output is stored in matrix po[i][j][h] for h every 'hstepm' step - (typically every 2 years instead of every month which is too big). + (typically every 2 years instead of every month which is too big + for the memory). Model is determined by parameters x and covariates have to be included manually here. */ - int i, j, d, h; - double **out, cov[NCOVMAX]; + int i, j, d, h, k; + double **out, cov[NCOVMAX+1]; double **newm; + double agexact; + double agebegin, ageend; /* Hstepm could be zero and should return the unit matrix */ for (i=1;i<=nlstate+ndeath;i++) @@ -733,126 +3041,834 @@ double ***hpxij(double ***po, int nhstep newm=savm; /* Covariates have to be included here again */ cov[1]=1.; - cov[2]=age+((h-1)*hstepm + (d-1))*stepm/YEARM; + agexact=age+((h-1)*hstepm + (d-1))*stepm/YEARM; /* age just before transition */ + cov[2]=agexact; + if(nagesqr==1) + cov[3]= agexact*agexact; + for (k=1; k<=nsd;k++) { /* For single dummy covariates only */ + /* Here comes the value of the covariate 'ij' after renumbering k with single dummy covariates */ + cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,k)]; + /* 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)); */ + } + for (k=1; k<=nsq;k++) { /* For single varying covariates only */ + /* Here comes the value of quantitative after renumbering k with single quantitative covariates */ + cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k]; + /* 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]); */ + } + for (k=1; k<=cptcovage;k++){ + if(Dummy[Tvar[Tage[k]]]){ + cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2]; + } else{ + cov[2+nagesqr+Tage[k]]=Tqresult[nres][k]; + } + /* 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]); */ + } + for (k=1; k<=cptcovprod;k++){ /* */ + /* 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]); */ + cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)]; + } + /* for (k=1; k<=cptcovn;k++) */ + /* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,k)]; */ + /* for (k=1; k<=cptcovage;k++) /\* Should start at cptcovn+1 *\/ */ + /* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2]; */ + /* for (k=1; k<=cptcovprod;k++) /\* Useless because included in cptcovn *\/ */ + /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)]*nbcode[Tvard[k][2]][codtabm(ij,k)]; */ + + + /*printf("hxi cptcov=%d cptcode=%d\n",cptcov,cptcode);*/ /*printf("h=%d d=%d age=%f cov=%f\n",h,d,age,cov[2]);*/ + /* right multiplication of oldm by the current matrix */ out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, - pmij(pmmij,cov,ncov,x,nlstate)); + pmij(pmmij,cov,ncovmodel,x,nlstate)); + /* if((int)age == 70){ */ + /* printf(" Forward hpxij age=%d agexact=%f d=%d nhstepm=%d hstepm=%d\n", (int) age, agexact, d, nhstepm, hstepm); */ + /* for(i=1; i<=nlstate+ndeath; i++) { */ + /* printf("%d pmmij ",i); */ + /* for(j=1;j<=nlstate+ndeath;j++) { */ + /* printf("%f ",pmmij[i][j]); */ + /* } */ + /* printf(" oldm "); */ + /* for(j=1;j<=nlstate+ndeath;j++) { */ + /* printf("%f ",oldm[i][j]); */ + /* } */ + /* printf("\n"); */ + /* } */ + /* } */ + savm=oldm; + oldm=newm; + } + for(i=1; i<=nlstate+ndeath; i++) + for(j=1;j<=nlstate+ndeath;j++) { + po[i][j][h]=newm[i][j]; + /*if(h==nhstepm) printf("po[%d][%d][%d]=%f ",i,j,h,po[i][j][h]);*/ + } + /*printf("h=%d ",h);*/ + } /* end h */ + /* printf("\n H=%d \n",h); */ + return po; +} + +/************* Higher Back Matrix Product ***************/ +/* 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 ) */ +double ***hbxij(double ***po, int nhstepm, double age, int hstepm, double *x, double ***prevacurrent, int nlstate, int stepm, int ij ) +{ + /* Computes the transition matrix starting at age 'age' over + 'nhstepm*hstepm*stepm' months (i.e. until + age (in years) age+nhstepm*hstepm*stepm/12) by multiplying + nhstepm*hstepm matrices. + Output is stored in matrix po[i][j][h] for h every 'hstepm' step + (typically every 2 years instead of every month which is too big + for the memory). + Model is determined by parameters x and covariates have to be + included manually here. + + */ + + int i, j, d, h, k; + double **out, cov[NCOVMAX+1]; + double **newm; + double agexact; + double agebegin, ageend; + double **oldm, **savm; + + oldm=oldms;savm=savms; + /* Hstepm could be zero and should return the unit matrix */ + for (i=1;i<=nlstate+ndeath;i++) + for (j=1;j<=nlstate+ndeath;j++){ + oldm[i][j]=(i==j ? 1.0 : 0.0); + po[i][j][0]=(i==j ? 1.0 : 0.0); + } + /* Even if hstepm = 1, at least one multiplication by the unit matrix */ + for(h=1; h <=nhstepm; h++){ + for(d=1; d <=hstepm; d++){ + newm=savm; + /* Covariates have to be included here again */ + cov[1]=1.; + agexact=age-((h-1)*hstepm + (d-1))*stepm/YEARM; /* age just before transition */ + /* agexact=age+((h-1)*hstepm + (d-1))*stepm/YEARM; /\* age just before transition *\/ */ + cov[2]=agexact; + if(nagesqr==1) + cov[3]= agexact*agexact; + for (k=1; k<=cptcovn;k++) + cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,k)]; + /* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,Tvar[k])]; */ + for (k=1; k<=cptcovage;k++) /* Should start at cptcovn+1 */ + /* cov[2+Tage[k]]=cov[2+Tage[k]]*cov[2]; */ + cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2]; + /* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,Tvar[Tage[k]])]*cov[2]; */ + for (k=1; k<=cptcovprod;k++) /* Useless because included in cptcovn */ + cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)]*nbcode[Tvard[k][2]][codtabm(ij,k)]; + /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])]*nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])]; */ + + + /*printf("hxi cptcov=%d cptcode=%d\n",cptcov,cptcode);*/ + /*printf("h=%d d=%d age=%f cov=%f\n",h,d,age,cov[2]);*/ + /* Careful transposed matrix */ + /* age is in cov[2] */ + /* out=matprod2(newm, bmij(pmmij,cov,ncovmodel,x,nlstate,prevacurrent, dnewm, doldm, dsavm,ij),\ */ + /* 1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); */ + out=matprod2(newm, bmij(pmmij,cov,ncovmodel,x,nlstate,prevacurrent,ij),\ + 1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); + /* if((int)age == 70){ */ + /* printf(" Backward hbxij age=%d agexact=%f d=%d nhstepm=%d hstepm=%d\n", (int) age, agexact, d, nhstepm, hstepm); */ + /* for(i=1; i<=nlstate+ndeath; i++) { */ + /* printf("%d pmmij ",i); */ + /* for(j=1;j<=nlstate+ndeath;j++) { */ + /* printf("%f ",pmmij[i][j]); */ + /* } */ + /* printf(" oldm "); */ + /* for(j=1;j<=nlstate+ndeath;j++) { */ + /* printf("%f ",oldm[i][j]); */ + /* } */ + /* printf("\n"); */ + /* } */ + /* } */ savm=oldm; oldm=newm; } for(i=1; i<=nlstate+ndeath; i++) for(j=1;j<=nlstate+ndeath;j++) { po[i][j][h]=newm[i][j]; - /*printf("i=%d j=%d h=%d po[i][j][h]=%f ",i,j,h,po[i][j][h]); - */ + /*if(h==nhstepm) printf("po[%d][%d][%d]=%f ",i,j,h,po[i][j][h]);*/ } + /*printf("h=%d ",h);*/ } /* end h */ + /* printf("\n H=%d \n",h); */ return po; } +#ifdef NLOPT + double myfunc(unsigned n, const double *p1, double *grad, void *pd){ + double fret; + double *xt; + int j; + myfunc_data *d2 = (myfunc_data *) pd; +/* xt = (p1-1); */ + xt=vector(1,n); + for (j=1;j<=n;j++) xt[j]=p1[j-1]; /* xt[1]=p1[0] */ + + fret=(d2->function)(xt); /* p xt[1]@8 is fine */ + /* fret=(*func)(xt); /\* p xt[1]@8 is fine *\/ */ + printf("Function = %.12lf ",fret); + for (j=1;j<=n;j++) printf(" %d %.8lf", j, xt[j]); + printf("\n"); + free_vector(xt,1,n); + return fret; +} +#endif + /*************** log-likelihood *************/ double func( double *x) { - int i, ii, j, k, mi, d; - double l, ll[NLSTATEMAX], cov[NCOVMAX]; + int i, ii, j, k, mi, d, kk; + int ioffset=0; + double l, ll[NLSTATEMAX+1], cov[NCOVMAX+1]; double **out; - double sw; /* Sum of weights */ double lli; /* Individual log likelihood */ + int s1, s2; + int iv=0, iqv=0, itv=0, iqtv=0 ; /* Index of varying covariate, fixed quantitative cov, time varying covariate, quantitative time varying covariate */ + double bbh, survp; long ipmx; + double agexact; /*extern weight */ /* We are differentiating ll according to initial status */ /* for (i=1;i<=npar;i++) printf("%f ", x[i]);*/ /*for(i=1;i<imx;i++) -printf(" %d\n",s[4][i]); + printf(" %d\n",s[4][i]); */ + ++countcallfunc; + + cov[1]=1.; + for(k=1; k<=nlstate; k++) ll[k]=0.; - for (i=1,ipmx=0, sw=0.; i<=imx; i++){ - for(mi=1; mi<= wav[i]-1; mi++){ - for (ii=1;ii<=nlstate+ndeath;ii++) - for (j=1;j<=nlstate+ndeath;j++) oldm[ii][j]=(ii==j ? 1.0 : 0.0); - for(d=0; d<dh[mi][i]; d++){ - newm=savm; - cov[1]=1.; - cov[2]=agev[mw[mi][i]][i]+d*stepm/YEARM; - out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath, - 1,nlstate+ndeath,pmij(pmmij,cov,ncov,x,nlstate)); + ioffset=0; + if(mle==1){ + for (i=1,ipmx=0, sw=0.; i<=imx; i++){ + /* Computes the values of the ncovmodel covariates of the model + depending if the covariates are fixed or varying (age dependent) and stores them in cov[] + Then computes with function pmij which return a matrix p[i][j] giving the elementary probability + to be observed in j being in i according to the model. + */ + ioffset=2+nagesqr ; + /* Fixed */ + for (k=1; k<=ncovf;k++){ /* Simple and product fixed covariates without age* products */ + 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)*/ + } + /* In model V2+V1*V4+age*V3+V3*V2 Tvar[1] is V2, Tvar[2=V1*V4] + is 6, Tvar[3=age*V3] should not be computed because of age Tvar[4=V3*V2] + has been calculated etc */ + /* For an individual i, wav[i] gives the number of effective waves */ + /* We compute the contribution to Likelihood of each effective transition + mw[mi][i] is real wave of the mi th effectve wave */ + /* Then statuses are computed at each begin and end of an effective wave s1=s[ mw[mi][i] ][i]; + s2=s[mw[mi+1][i]][i]; + And the iv th varying covariate is the cotvar[mw[mi+1][i]][iv][i] + But if the variable is not in the model TTvar[iv] is the real variable effective in the model: + meaning that decodemodel should be used cotvar[mw[mi+1][i]][TTvar[iv]][i] + */ + for(mi=1; mi<= wav[i]-1; mi++){ + for(k=1; k <= ncovv ; k++){ /* Varying covariates (single and product but no age )*/ + /* cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]][i]; */ + cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]-ncovcol-nqv][i]; + } + for (ii=1;ii<=nlstate+ndeath;ii++) + for (j=1;j<=nlstate+ndeath;j++){ + oldm[ii][j]=(ii==j ? 1.0 : 0.0); + savm[ii][j]=(ii==j ? 1.0 : 0.0); + } + for(d=0; d<dh[mi][i]; d++){ + newm=savm; + agexact=agev[mw[mi][i]][i]+d*stepm/YEARM; + cov[2]=agexact; + if(nagesqr==1) + cov[3]= agexact*agexact; /* Should be changed here */ + for (kk=1; kk<=cptcovage;kk++) { + if(!FixedV[Tvar[Tage[kk]]]) + cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact; /* Tage[kk] gives the data-covariate associated with age */ + else + cov[Tage[kk]+2+nagesqr]=cotvar[mw[mi][i]][Tvar[Tage[kk]]-ncovcol-nqv][i]*agexact; + } + out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath, + 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate)); + savm=oldm; + oldm=newm; + } /* end mult */ + + /*lli=log(out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]);*/ /* Original formula */ + /* But now since version 0.9 we anticipate for bias at large stepm. + * If stepm is larger than one month (smallest stepm) and if the exact delay + * (in months) between two waves is not a multiple of stepm, we rounded to + * the nearest (and in case of equal distance, to the lowest) interval but now + * we keep into memory the bias bh[mi][i] and also the previous matrix product + * (i.e to dh[mi][i]-1) saved in 'savm'. Then we inter(extra)polate the + * probability in order to take into account the bias as a fraction of the way + * from savm to out if bh is negative or even beyond if bh is positive. bh varies + * -stepm/2 to stepm/2 . + * For stepm=1 the results are the same as for previous versions of Imach. + * For stepm > 1 the results are less biased than in previous versions. + */ + s1=s[mw[mi][i]][i]; + s2=s[mw[mi+1][i]][i]; + bbh=(double)bh[mi][i]/(double)stepm; + /* bias bh is positive if real duration + * is higher than the multiple of stepm and negative otherwise. + */ + /* lli= (savm[s1][s2]>1.e-8 ?(1.+bbh)*log(out[s1][s2])- bbh*log(savm[s1][s2]):log((1.+bbh)*out[s1][s2]));*/ + if( s2 > nlstate){ + /* i.e. if s2 is a death state and if the date of death is known + then the contribution to the likelihood is the probability to + die between last step unit time and current step unit time, + which is also equal to probability to die before dh + minus probability to die before dh-stepm . + In version up to 0.92 likelihood was computed + as if date of death was unknown. Death was treated as any other + health state: the date of the interview describes the actual state + and not the date of a change in health state. The former idea was + to consider that at each interview the state was recorded + (healthy, disable or death) and IMaCh was corrected; but when we + introduced the exact date of death then we should have modified + the contribution of an exact death to the likelihood. This new + contribution is smaller and very dependent of the step unit + stepm. It is no more the probability to die between last interview + and month of death but the probability to survive from last + interview up to one month before death multiplied by the + probability to die within a month. Thanks to Chris + Jackson for correcting this bug. Former versions increased + mortality artificially. The bad side is that we add another loop + which slows down the processing. The difference can be up to 10% + lower mortality. + */ + /* If, at the beginning of the maximization mostly, the + cumulative probability or probability to be dead is + constant (ie = 1) over time d, the difference is equal to + 0. out[s1][3] = savm[s1][3]: probability, being at state + s1 at precedent wave, to be dead a month before current + wave is equal to probability, being at state s1 at + precedent wave, to be dead at mont of the current + wave. Then the observed probability (that this person died) + is null according to current estimated parameter. In fact, + it should be very low but not zero otherwise the log go to + infinity. + */ +/* #ifdef INFINITYORIGINAL */ +/* lli=log(out[s1][s2] - savm[s1][s2]); */ +/* #else */ +/* if ((out[s1][s2] - savm[s1][s2]) < mytinydouble) */ +/* lli=log(mytinydouble); */ +/* else */ +/* lli=log(out[s1][s2] - savm[s1][s2]); */ +/* #endif */ + lli=log(out[s1][s2] - savm[s1][s2]); + + } else if ( s2==-1 ) { /* alive */ + for (j=1,survp=0. ; j<=nlstate; j++) + survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j]; + /*survp += out[s1][j]; */ + lli= log(survp); + } + else if (s2==-4) { + for (j=3,survp=0. ; j<=nlstate; j++) + survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j]; + lli= log(survp); + } + else if (s2==-5) { + for (j=1,survp=0. ; j<=2; j++) + survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j]; + lli= log(survp); + } + else{ + lli= log((1.+bbh)*out[s1][s2]- bbh*savm[s1][s2]); /* linear interpolation */ + /* 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 */ + } + /*lli=(1.+bbh)*log(out[s1][s2])- bbh*log(savm[s1][s2]);*/ + /*if(lli ==000.0)*/ + /*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); */ + ipmx +=1; + sw += weight[i]; + ll[s[mw[mi][i]][i]] += 2*weight[i]*lli; + /* if (lli < log(mytinydouble)){ */ + /* 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); */ + /* 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]); */ + /* } */ + } /* end of wave */ + } /* end of individual */ + } else if(mle==2){ + for (i=1,ipmx=0, sw=0.; i<=imx; i++){ + for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i]; + for(mi=1; mi<= wav[i]-1; mi++){ + for (ii=1;ii<=nlstate+ndeath;ii++) + for (j=1;j<=nlstate+ndeath;j++){ + oldm[ii][j]=(ii==j ? 1.0 : 0.0); + savm[ii][j]=(ii==j ? 1.0 : 0.0); + } + for(d=0; d<=dh[mi][i]; d++){ + newm=savm; + agexact=agev[mw[mi][i]][i]+d*stepm/YEARM; + cov[2]=agexact; + if(nagesqr==1) + cov[3]= agexact*agexact; + for (kk=1; kk<=cptcovage;kk++) { + cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact; + } + out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath, + 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate)); + savm=oldm; + oldm=newm; + } /* end mult */ + + s1=s[mw[mi][i]][i]; + s2=s[mw[mi+1][i]][i]; + bbh=(double)bh[mi][i]/(double)stepm; + 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 */ + ipmx +=1; + sw += weight[i]; + ll[s[mw[mi][i]][i]] += 2*weight[i]*lli; + } /* end of wave */ + } /* end of individual */ + } else if(mle==3){ /* exponential inter-extrapolation */ + for (i=1,ipmx=0, sw=0.; i<=imx; i++){ + for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i]; + for(mi=1; mi<= wav[i]-1; mi++){ + for (ii=1;ii<=nlstate+ndeath;ii++) + for (j=1;j<=nlstate+ndeath;j++){ + oldm[ii][j]=(ii==j ? 1.0 : 0.0); + savm[ii][j]=(ii==j ? 1.0 : 0.0); + } + for(d=0; d<dh[mi][i]; d++){ + newm=savm; + agexact=agev[mw[mi][i]][i]+d*stepm/YEARM; + cov[2]=agexact; + if(nagesqr==1) + cov[3]= agexact*agexact; + for (kk=1; kk<=cptcovage;kk++) { + cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact; + } + out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath, + 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate)); + savm=oldm; + oldm=newm; + } /* end mult */ + + s1=s[mw[mi][i]][i]; + s2=s[mw[mi+1][i]][i]; + bbh=(double)bh[mi][i]/(double)stepm; + 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 */ + ipmx +=1; + sw += weight[i]; + ll[s[mw[mi][i]][i]] += 2*weight[i]*lli; + } /* end of wave */ + } /* end of individual */ + }else if (mle==4){ /* ml=4 no inter-extrapolation */ + for (i=1,ipmx=0, sw=0.; i<=imx; i++){ + for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i]; + for(mi=1; mi<= wav[i]-1; mi++){ + for (ii=1;ii<=nlstate+ndeath;ii++) + for (j=1;j<=nlstate+ndeath;j++){ + oldm[ii][j]=(ii==j ? 1.0 : 0.0); + savm[ii][j]=(ii==j ? 1.0 : 0.0); + } + for(d=0; d<dh[mi][i]; d++){ + newm=savm; + agexact=agev[mw[mi][i]][i]+d*stepm/YEARM; + cov[2]=agexact; + if(nagesqr==1) + cov[3]= agexact*agexact; + for (kk=1; kk<=cptcovage;kk++) { + cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact; + } + + out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath, + 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate)); + savm=oldm; + oldm=newm; + } /* end mult */ + + s1=s[mw[mi][i]][i]; + s2=s[mw[mi+1][i]][i]; + if( s2 > nlstate){ + lli=log(out[s1][s2] - savm[s1][s2]); + } else if ( s2==-1 ) { /* alive */ + for (j=1,survp=0. ; j<=nlstate; j++) + survp += out[s1][j]; + lli= log(survp); + }else{ + lli=log(out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]); /* Original formula */ + } + ipmx +=1; + sw += weight[i]; + ll[s[mw[mi][i]][i]] += 2*weight[i]*lli; +/* 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]); */ + } /* end of wave */ + } /* end of individual */ + }else{ /* ml=5 no inter-extrapolation no jackson =0.8a */ + for (i=1,ipmx=0, sw=0.; i<=imx; i++){ + for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i]; + for(mi=1; mi<= wav[i]-1; mi++){ + for (ii=1;ii<=nlstate+ndeath;ii++) + for (j=1;j<=nlstate+ndeath;j++){ + oldm[ii][j]=(ii==j ? 1.0 : 0.0); + savm[ii][j]=(ii==j ? 1.0 : 0.0); + } + for(d=0; d<dh[mi][i]; d++){ + newm=savm; + agexact=agev[mw[mi][i]][i]+d*stepm/YEARM; + cov[2]=agexact; + if(nagesqr==1) + cov[3]= agexact*agexact; + for (kk=1; kk<=cptcovage;kk++) { + cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact; + } + + out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath, + 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate)); savm=oldm; oldm=newm; + } /* end mult */ + + s1=s[mw[mi][i]][i]; + s2=s[mw[mi+1][i]][i]; + lli=log(out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]); /* Original formula */ + ipmx +=1; + sw += weight[i]; + ll[s[mw[mi][i]][i]] += 2*weight[i]*lli; + /*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]);*/ + } /* end of wave */ + } /* end of individual */ + } /* End of if */ + for(k=1,l=0.; k<=nlstate; k++) l += ll[k]; + /* printf("l1=%f l2=%f ",ll[1],ll[2]); */ + l= l*ipmx/sw; /* To get the same order of magnitude as if weight=1 for every body */ + return -l; +} + +/*************** log-likelihood *************/ +double funcone( double *x) +{ + /* Same as func but slower because of a lot of printf and if */ + int i, ii, j, k, mi, d, kk; + int ioffset=0; + double l, ll[NLSTATEMAX+1], cov[NCOVMAX+1]; + double **out; + double lli; /* Individual log likelihood */ + double llt; + int s1, s2; + int iv=0, iqv=0, itv=0, iqtv=0 ; /* Index of varying covariate, fixed quantitative cov, time varying covariate, quantitative time varying covariate */ + + double bbh, survp; + double agexact; + double agebegin, ageend; + /*extern weight */ + /* We are differentiating ll according to initial status */ + /* for (i=1;i<=npar;i++) printf("%f ", x[i]);*/ + /*for(i=1;i<imx;i++) + printf(" %d\n",s[4][i]); + */ + cov[1]=1.; + for(k=1; k<=nlstate; k++) ll[k]=0.; + ioffset=0; + for (i=1,ipmx=0, sw=0.; i<=imx; i++){ + /* ioffset=2+nagesqr+cptcovage; */ + ioffset=2+nagesqr; + /* Fixed */ + /* for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i]; */ + /* for (k=1; k<=ncoveff;k++){ /\* Simple and product fixed Dummy covariates without age* products *\/ */ + for (k=1; k<=ncovf;k++){ /* Simple and product fixed covariates without age* products */ + 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)*/ +/* cov[ioffset+TvarFind[1]]=covar[Tvar[TvarFind[1]]][i]; */ +/* cov[2+6]=covar[Tvar[6]][i]; */ +/* cov[2+6]=covar[2][i]; V2 */ +/* cov[TvarFind[2]]=covar[Tvar[TvarFind[2]]][i]; */ +/* cov[2+7]=covar[Tvar[7]][i]; */ +/* cov[2+7]=covar[7][i]; V7=V1*V2 */ +/* cov[TvarFind[3]]=covar[Tvar[TvarFind[3]]][i]; */ +/* cov[2+9]=covar[Tvar[9]][i]; */ +/* cov[2+9]=covar[1][i]; V1 */ + } + /* for (k=1; k<=nqfveff;k++){ /\* Simple and product fixed Quantitative covariates without age* products *\/ */ + /* 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?)*\/ */ + /* } */ + /* for(iqv=1; iqv <= nqfveff; iqv++){ /\* Quantitative fixed covariates *\/ */ + /* cov[++ioffset]=coqvar[Tvar[iqv]][i]; /\* Only V2 k=6 and V1*V2 7 *\/ */ + /* } */ + + for(mi=1; mi<= wav[i]-1; mi++){ /* Varying with waves */ + /* Wave varying (but not age varying) */ + for(k=1; k <= ncovv ; k++){ /* Varying covariates (single and product but no age )*/ + /* cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]][i]; */ + cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]-ncovcol-nqv][i]; + } + /* for(itv=1; itv <= ntveff; itv++){ /\* Varying dummy covariates (single??)*\/ */ + /* iv= Tvar[Tmodelind[ioffset-2-nagesqr-cptcovage+itv]]-ncovcol-nqv; /\* Counting the # varying covariate from 1 to ntveff *\/ */ + /* cov[ioffset+iv]=cotvar[mw[mi][i]][iv][i]; */ + /* k=ioffset-2-nagesqr-cptcovage+itv; /\* position in simple model *\/ */ + /* cov[ioffset+itv]=cotvar[mw[mi][i]][TmodelInvind[itv]][i]; */ + /* 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]); */ + /* for(iqtv=1; iqtv <= nqtveff; iqtv++){ /\* Varying quantitatives covariates *\/ */ + /* iv=TmodelInvQind[iqtv]; /\* Counting the # varying covariate from 1 to ntveff *\/ */ + /* /\* 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]); *\/ */ + /* cov[ioffset+ntveff+iqtv]=cotqvar[mw[mi][i]][TmodelInvQind[iqtv]][i]; */ + /* } */ + for (ii=1;ii<=nlstate+ndeath;ii++) + for (j=1;j<=nlstate+ndeath;j++){ + oldm[ii][j]=(ii==j ? 1.0 : 0.0); + savm[ii][j]=(ii==j ? 1.0 : 0.0); + } + + agebegin=agev[mw[mi][i]][i]; /* Age at beginning of effective wave */ + ageend=agev[mw[mi][i]][i] + (dh[mi][i])*stepm/YEARM; /* Age at end of effective wave and at the end of transition */ + for(d=0; d<dh[mi][i]; d++){ /* Delay between two effective waves */ + /* for(d=0; d<=0; d++){ /\* Delay between two effective waves Only one matrix to speed up*\/ */ + /*dh[m][i] or dh[mw[mi][i]][i] is the delay between two effective waves m=mw[mi][i] + and mw[mi+1][i]. dh depends on stepm.*/ + newm=savm; + agexact=agev[mw[mi][i]][i]+d*stepm/YEARM; /* Here d is needed */ + cov[2]=agexact; + if(nagesqr==1) + cov[3]= agexact*agexact; + for (kk=1; kk<=cptcovage;kk++) { + if(!FixedV[Tvar[Tage[kk]]]) + cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact; + else + cov[Tage[kk]+2+nagesqr]=cotvar[mw[mi][i]][Tvar[Tage[kk]]-ncovcol-nqv][i]*agexact; + } + /* printf("i=%d,mi=%d,d=%d,mw[mi][i]=%d\n",i, mi,d,mw[mi][i]); */ + /* savm=pmij(pmmij,cov,ncovmodel,x,nlstate); */ + out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath, + 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate)); + /* out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath, */ + /* 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate)); */ + savm=oldm; + oldm=newm; } /* end mult */ - - lli=log(out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]); - /* printf(" %f ",out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]);*/ + + s1=s[mw[mi][i]][i]; + s2=s[mw[mi+1][i]][i]; + /* if(s2==-1){ */ + /* printf(" s1=%d, s2=%d i=%d \n", s1, s2, i); */ + /* /\* exit(1); *\/ */ + /* } */ + bbh=(double)bh[mi][i]/(double)stepm; + /* bias is positive if real duration + * is higher than the multiple of stepm and negative otherwise. + */ + if( s2 > nlstate && (mle <5) ){ /* Jackson */ + lli=log(out[s1][s2] - savm[s1][s2]); + } else if ( s2==-1 ) { /* alive */ + for (j=1,survp=0. ; j<=nlstate; j++) + survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j]; + lli= log(survp); + }else if (mle==1){ + lli= log((1.+bbh)*out[s1][s2]- bbh*savm[s1][s2]); /* linear interpolation */ + } else if(mle==2){ + 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 */ + } else if(mle==3){ /* exponential inter-extrapolation */ + 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 */ + } else if (mle==4){ /* mle=4 no inter-extrapolation */ + lli=log(out[s1][s2]); /* Original formula */ + } else{ /* mle=0 back to 1 */ + lli= log((1.+bbh)*out[s1][s2]- bbh*savm[s1][s2]); /* linear interpolation */ + /*lli=log(out[s1][s2]); */ /* Original formula */ + } /* End of if */ ipmx +=1; sw += weight[i]; ll[s[mw[mi][i]][i]] += 2*weight[i]*lli; - } /* end of wave */ - } /* end of individual */ + /*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]); */ + if(globpr){ + fprintf(ficresilk,"%09ld %6.1f %6.1f %6d %2d %2d %2d %2d %3d %15.6f %8.4f %8.3f\ + %11.6f %11.6f %11.6f ", \ + num[i], agebegin, ageend, i,s1,s2,mi,mw[mi][i],dh[mi][i],exp(lli),weight[i],weight[i]*gipmx/gsw, + 2*weight[i]*lli,out[s1][s2],savm[s1][s2]); + for(k=1,llt=0.,l=0.; k<=nlstate; k++){ + llt +=ll[k]*gipmx/gsw; + fprintf(ficresilk," %10.6f",-ll[k]*gipmx/gsw); + } + fprintf(ficresilk," %10.6f\n", -llt); + } + } /* end of wave */ +} /* end of individual */ +for(k=1,l=0.; k<=nlstate; k++) l += ll[k]; +/* printf("l1=%f l2=%f ",ll[1],ll[2]); */ +l= l*ipmx/sw; /* To get the same order of magnitude as if weight=1 for every body */ +if(globpr==0){ /* First time we count the contributions and weights */ + gipmx=ipmx; + gsw=sw; +} +return -l; +} - for(k=1,l=0.; k<=nlstate; k++) l += ll[k]; - /* printf("l1=%f l2=%f ",ll[1],ll[2]); */ - l= l*ipmx/sw; /* To get the same order of magnitude as if weight=1 for every body */ - return -l; + +/*************** function likelione ***********/ +void likelione(FILE *ficres,double p[], int npar, int nlstate, int *globpri, long *ipmx, double *sw, double *fretone, double (*funcone)(double [])) +{ + /* This routine should help understanding what is done with + the selection of individuals/waves and + to check the exact contribution to the likelihood. + Plotting could be done. + */ + int k; + + if(*globpri !=0){ /* Just counts and sums, no printings */ + strcpy(fileresilk,"ILK_"); + strcat(fileresilk,fileresu); + if((ficresilk=fopen(fileresilk,"w"))==NULL) { + printf("Problem with resultfile: %s\n", fileresilk); + fprintf(ficlog,"Problem with resultfile: %s\n", fileresilk); + } + 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"); + fprintf(ficresilk, "#num_i ageb agend i s1 s2 mi mw dh likeli weight %%weight 2wlli out sav "); + /* i,s1,s2,mi,mw[mi][i],dh[mi][i],exp(lli),weight[i],2*weight[i]*lli,out[s1][s2],savm[s1][s2]); */ + for(k=1; k<=nlstate; k++) + fprintf(ficresilk," -2*gipw/gsw*weight*ll[%d]++",k); + fprintf(ficresilk," -2*gipw/gsw*weight*ll(total)\n"); + } + + *fretone=(*funcone)(p); + if(*globpri !=0){ + fclose(ficresilk); + if (mle ==0) + fprintf(fichtm,"\n<br>File of contributions to the likelihood computed with initial parameters and mle = %d.",mle); + else if(mle >=1) + fprintf(fichtm,"\n<br>File of contributions to the likelihood computed with optimized parameters mle = %d.",mle); + 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)); + + + for (k=1; k<= nlstate ; k++) { + 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> \ +<img src=\"%s-p%dj.png\">",k,k,subdirf2(optionfilefiname,"ILK_"),k,subdirf2(optionfilefiname,"ILK_"),k,subdirf2(optionfilefiname,"ILK_"),k); + } + 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> \ +<img src=\"%s-ori.png\">",subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_")); + fprintf(fichtm,"<br>- and by state of destination <a href=\"%s-dest.png\">%s-dest.png</a><br> \ +<img src=\"%s-dest.png\">",subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_")); + fflush(fichtm); + } + return; } /*********** Maximum Likelihood Estimation ***************/ -void mlikeli(FILE *ficres,double p[], int npar, int ncov, int nlstate, double ftol, double (*func)(double [])) +void mlikeli(FILE *ficres,double p[], int npar, int ncovmodel, int nlstate, double ftol, double (*func)(double [])) { - int i,j, iter; - double **xi,*delti; + int i,j, iter=0; + double **xi; double fret; + double fretone; /* Only one call to likelihood */ + /* char filerespow[FILENAMELENGTH];*/ + +#ifdef NLOPT + int creturn; + nlopt_opt opt; + /* double lb[9] = { -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL }; /\* lower bounds *\/ */ + double *lb; + double minf; /* the minimum objective value, upon return */ + double * p1; /* Shifted parameters from 0 instead of 1 */ + myfunc_data dinst, *d = &dinst; +#endif + + xi=matrix(1,npar,1,npar); for (i=1;i<=npar;i++) for (j=1;j<=npar;j++) xi[i][j]=(i==j ? 1.0 : 0.0); - printf("Powell\n"); + printf("Powell\n"); fprintf(ficlog,"Powell\n"); + strcpy(filerespow,"POW_"); + strcat(filerespow,fileres); + if((ficrespow=fopen(filerespow,"w"))==NULL) { + printf("Problem with resultfile: %s\n", filerespow); + fprintf(ficlog,"Problem with resultfile: %s\n", filerespow); + } + fprintf(ficrespow,"# Powell\n# iter -2*LL"); + for (i=1;i<=nlstate;i++) + for(j=1;j<=nlstate+ndeath;j++) + if(j!=i)fprintf(ficrespow," p%1d%1d",i,j); + fprintf(ficrespow,"\n"); +#ifdef POWELL powell(p,xi,npar,ftol,&iter,&fret,func); +#endif - printf("\n#Number of iterations = %d, -2 Log likelihood = %.12f\n",iter,func(p)); - fprintf(ficres,"#Number of iterations = %d, -2 Log likelihood = %.12f ",iter,func(p)); +#ifdef NLOPT +#ifdef NEWUOA + opt = nlopt_create(NLOPT_LN_NEWUOA,npar); +#else + opt = nlopt_create(NLOPT_LN_BOBYQA,npar); +#endif + lb=vector(0,npar-1); + for (i=0;i<npar;i++) lb[i]= -HUGE_VAL; + nlopt_set_lower_bounds(opt, lb); + nlopt_set_initial_step1(opt, 0.1); + + p1= (p+1); /* p *(p+1)@8 and p *(p1)@8 are equal p1[0]=p[1] */ + d->function = func; + printf(" Func %.12lf \n",myfunc(npar,p1,NULL,d)); + nlopt_set_min_objective(opt, myfunc, d); + nlopt_set_xtol_rel(opt, ftol); + if ((creturn=nlopt_optimize(opt, p1, &minf)) < 0) { + printf("nlopt failed! %d\n",creturn); + } + else { + printf("found minimum after %d evaluations (NLOPT=%d)\n", countcallfunc ,NLOPT); + printf("found minimum at f(%g,%g) = %0.10g\n", p[0], p[1], minf); + iter=1; /* not equal */ + } + nlopt_destroy(opt); +#endif + free_matrix(xi,1,npar,1,npar); + fclose(ficrespow); + printf("\n#Number of iterations & function calls = %d & %d, -2 Log likelihood = %.12f\n",iter, countcallfunc,func(p)); + fprintf(ficlog,"\n#Number of iterations & function calls = %d & %d, -2 Log likelihood = %.12f\n",iter, countcallfunc,func(p)); + fprintf(ficres,"#Number of iterations & function calls = %d & %d, -2 Log likelihood = %.12f\n",iter, countcallfunc,func(p)); } /**** Computes Hessian and covariance matrix ***/ -void hesscov(double **matcov, double p[], int npar, double delti[], double ftolhess, double (*func)(double [])) +void hesscov(double **matcov, double **hess, double p[], int npar, double delti[], double ftolhess, double (*func)(double [])) { double **a,**y,*x,pd; - double **hess; - int i, j,jk; + /* double **hess; */ + int i, j; int *indx; - double hessii(double p[], double delta, int theta, double delti[]); - double hessij(double p[], double delti[], int i, int j); + double hessii(double p[], double delta, int theta, double delti[],double (*func)(double []),int npar); + double hessij(double p[], double **hess, double delti[], int i, int j,double (*func)(double []),int npar); void lubksb(double **a, int npar, int *indx, double b[]) ; void ludcmp(double **a, int npar, int *indx, double *d) ; - - - hess=matrix(1,npar,1,npar); + double gompertz(double p[]); + /* hess=matrix(1,npar,1,npar); */ printf("\nCalculation of the hessian matrix. Wait...\n"); + fprintf(ficlog,"\nCalculation of the hessian matrix. Wait...\n"); for (i=1;i<=npar;i++){ - printf("%d",i);fflush(stdout); - hess[i][i]=hessii(p,ftolhess,i,delti); - /*printf(" %f ",p[i]);*/ + printf("%d-",i);fflush(stdout); + fprintf(ficlog,"%d-",i);fflush(ficlog); + + hess[i][i]=hessii(p,ftolhess,i,delti,func,npar); + + /* printf(" %f ",p[i]); + printf(" %lf %lf %lf",hess[i][i],ftolhess,delti[i]);*/ } - + for (i=1;i<=npar;i++) { for (j=1;j<=npar;j++) { if (j>i) { - printf(".%d%d",i,j);fflush(stdout); - hess[i][j]=hessij(p,delti,i,j); - hess[j][i]=hess[i][j]; + printf(".%d-%d",i,j);fflush(stdout); + fprintf(ficlog,".%d-%d",i,j);fflush(ficlog); + hess[i][j]=hessij(p,hess, delti,i,j,func,npar); + + hess[j][i]=hess[i][j]; + /*printf(" %lf ",hess[i][j]);*/ } } } printf("\n"); + fprintf(ficlog,"\n"); printf("\nInverting the hessian to get the covariance matrix. Wait...\n"); + fprintf(ficlog,"\nInverting the hessian to get the covariance matrix. Wait...\n"); a=matrix(1,npar,1,npar); y=matrix(1,npar,1,npar); @@ -872,122 +3888,231 @@ void hesscov(double **matcov, double p[] } printf("\n#Hessian matrix#\n"); + fprintf(ficlog,"\n#Hessian matrix#\n"); for (i=1;i<=npar;i++) { for (j=1;j<=npar;j++) { - printf("%.3e ",hess[i][j]); + printf("%.6e ",hess[i][j]); + fprintf(ficlog,"%.6e ",hess[i][j]); } printf("\n"); + fprintf(ficlog,"\n"); } + /* printf("\n#Covariance matrix#\n"); */ + /* fprintf(ficlog,"\n#Covariance matrix#\n"); */ + /* for (i=1;i<=npar;i++) { */ + /* for (j=1;j<=npar;j++) { */ + /* printf("%.6e ",matcov[i][j]); */ + /* fprintf(ficlog,"%.6e ",matcov[i][j]); */ + /* } */ + /* printf("\n"); */ + /* fprintf(ficlog,"\n"); */ + /* } */ + /* Recompute Inverse */ - for (i=1;i<=npar;i++) - for (j=1;j<=npar;j++) a[i][j]=matcov[i][j]; - ludcmp(a,npar,indx,&pd); + /* for (i=1;i<=npar;i++) */ + /* for (j=1;j<=npar;j++) a[i][j]=matcov[i][j]; */ + /* ludcmp(a,npar,indx,&pd); */ + + /* printf("\n#Hessian matrix recomputed#\n"); */ + + /* for (j=1;j<=npar;j++) { */ + /* for (i=1;i<=npar;i++) x[i]=0; */ + /* x[j]=1; */ + /* lubksb(a,npar,indx,x); */ + /* for (i=1;i<=npar;i++){ */ + /* y[i][j]=x[i]; */ + /* printf("%.3e ",y[i][j]); */ + /* fprintf(ficlog,"%.3e ",y[i][j]); */ + /* } */ + /* printf("\n"); */ + /* fprintf(ficlog,"\n"); */ + /* } */ + + /* Verifying the inverse matrix */ +#ifdef DEBUGHESS + y=matprod2(y,hess,1,npar,1,npar,1,npar,matcov); - /* printf("\n#Hessian matrix recomputed#\n"); + printf("\n#Verification: multiplying the matrix of covariance by the Hessian matrix, should be unity:#\n"); + fprintf(ficlog,"\n#Verification: multiplying the matrix of covariance by the Hessian matrix. Should be unity:#\n"); for (j=1;j<=npar;j++) { - for (i=1;i<=npar;i++) x[i]=0; - x[j]=1; - lubksb(a,npar,indx,x); for (i=1;i<=npar;i++){ - y[i][j]=x[i]; - printf("%.3e ",y[i][j]); + printf("%.2f ",y[i][j]); + fprintf(ficlog,"%.2f ",y[i][j]); } printf("\n"); + fprintf(ficlog,"\n"); } - */ +#endif free_matrix(a,1,npar,1,npar); free_matrix(y,1,npar,1,npar); free_vector(x,1,npar); free_ivector(indx,1,npar); - free_matrix(hess,1,npar,1,npar); + /* free_matrix(hess,1,npar,1,npar); */ } /*************** hessian matrix ****************/ -double hessii( double x[], double delta, int theta, double delti[]) -{ +double hessii(double x[], double delta, int theta, double delti[], double (*func)(double []), int npar) +{ /* Around values of x, computes the function func and returns the scales delti and hessian */ int i; int l=1, lmax=20; - double k1,k2; - double p2[NPARMAX+1]; - double res; - double delt, delts, nkhi=10.,nkhif=1., khi=1.e-4; - double fx; + double k1,k2, res, fx; + double p2[MAXPARM+1]; /* identical to x */ + double delt=0.0001, delts, nkhi=10.,nkhif=1., khi=1.e-4; int k=0,kmax=10; double l1; fx=func(x); for (i=1;i<=npar;i++) p2[i]=x[i]; - for(l=0 ; l <=lmax; l++){ + for(l=0 ; l <=lmax; l++){ /* Enlarging the zone around the Maximum */ l1=pow(10,l); delts=delt; for(k=1 ; k <kmax; k=k+1){ delt = delta*(l1*k); p2[theta]=x[theta] +delt; - k1=func(p2)-fx; + k1=func(p2)-fx; /* Might be negative if too close to the theoretical maximum */ p2[theta]=x[theta]-delt; k2=func(p2)-fx; /*res= (k1-2.0*fx+k2)/delt/delt; */ - res= (k1+k2)/delt/delt/2.; /* Divided by because L and not 2*L */ + res= (k1+k2)/delt/delt/2.; /* Divided by 2 because L and not 2*L */ -#ifdef DEBUG +#ifdef DEBUGHESSII 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); + 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); #endif /*if(fabs(k1-2.0*fx+k2) <1.e-13){ */ if((k1 <khi/nkhi/2.) || (k2 <khi/nkhi/2.)){ k=kmax; } else if((k1 >khi/nkhif) || (k2 >khi/nkhif)){ /* Keeps lastvalue before 3.84/2 KHI2 5% 1d.f. */ - k=kmax; l=lmax*10.; + k=kmax; l=lmax*10; } else if((k1 >khi/nkhi) || (k2 >khi/nkhi)){ delts=delt; } - } + } /* End loop k */ } delti[theta]=delts; - return res; + return res; } -double hessij( double x[], double delti[], int thetai,int thetaj) +double hessij( double x[], double **hess, double delti[], int thetai,int thetaj,double (*func)(double []),int npar) { int i; - int l=1, l1, lmax=20; + int l=1, lmax=20; double k1,k2,k3,k4,res,fx; - double p2[NPARMAX+1]; - int k; + double p2[MAXPARM+1]; + int k, kmax=1; + double v1, v2, cv12, lc1, lc2; + int firstime=0; + fx=func(x); - for (k=1; k<=2; k++) { + for (k=1; k<=kmax; k=k+10) { for (i=1;i<=npar;i++) p2[i]=x[i]; - p2[thetai]=x[thetai]+delti[thetai]/k; - p2[thetaj]=x[thetaj]+delti[thetaj]/k; + p2[thetai]=x[thetai]+delti[thetai]*k; + p2[thetaj]=x[thetaj]+delti[thetaj]*k; k1=func(p2)-fx; - p2[thetai]=x[thetai]+delti[thetai]/k; - p2[thetaj]=x[thetaj]-delti[thetaj]/k; + p2[thetai]=x[thetai]+delti[thetai]*k; + p2[thetaj]=x[thetaj]-delti[thetaj]*k; k2=func(p2)-fx; - p2[thetai]=x[thetai]-delti[thetai]/k; - p2[thetaj]=x[thetaj]+delti[thetaj]/k; + p2[thetai]=x[thetai]-delti[thetai]*k; + p2[thetaj]=x[thetaj]+delti[thetaj]*k; k3=func(p2)-fx; - p2[thetai]=x[thetai]-delti[thetai]/k; - p2[thetaj]=x[thetaj]-delti[thetaj]/k; + p2[thetai]=x[thetai]-delti[thetai]*k; + p2[thetaj]=x[thetaj]-delti[thetaj]*k; k4=func(p2)-fx; - res=(k1-k2-k3+k4)/4.0/delti[thetai]*k/delti[thetaj]*k/2.; /* Because of L not 2*L */ -#ifdef DEBUG - 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); + res=(k1-k2-k3+k4)/4.0/delti[thetai]/k/delti[thetaj]/k/2.; /* Because of L not 2*L */ + if(k1*k2*k3*k4 <0.){ + firstime=1; + kmax=kmax+10; + } + if(kmax >=10 || firstime ==1){ + 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); + 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); + 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); + 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); + } +#ifdef DEBUGHESSIJ + v1=hess[thetai][thetai]; + v2=hess[thetaj][thetaj]; + cv12=res; + /* Computing eigen value of Hessian matrix */ + lc1=((v1+v2)+sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.; + lc2=((v1+v2)-sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.; + if ((lc2 <0) || (lc1 <0) ){ + printf("Warning: sub Hessian matrix '%d%d' does not have positive eigen values \n",thetai,thetaj); + fprintf(ficlog, "Warning: sub Hessian matrix '%d%d' does not have positive eigen values \n",thetai,thetaj); + 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); + 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); + } #endif } return res; } + /* Not done yet: Was supposed to fix if not exactly at the maximum */ +/* double hessij( double x[], double delti[], int thetai,int thetaj,double (*func)(double []),int npar) */ +/* { */ +/* int i; */ +/* int l=1, lmax=20; */ +/* double k1,k2,k3,k4,res,fx; */ +/* double p2[MAXPARM+1]; */ +/* double delt=0.0001, delts, nkhi=10.,nkhif=1., khi=1.e-4; */ +/* int k=0,kmax=10; */ +/* double l1; */ + +/* fx=func(x); */ +/* for(l=0 ; l <=lmax; l++){ /\* Enlarging the zone around the Maximum *\/ */ +/* l1=pow(10,l); */ +/* delts=delt; */ +/* for(k=1 ; k <kmax; k=k+1){ */ +/* delt = delti*(l1*k); */ +/* for (i=1;i<=npar;i++) p2[i]=x[i]; */ +/* p2[thetai]=x[thetai]+delti[thetai]/k; */ +/* p2[thetaj]=x[thetaj]+delti[thetaj]/k; */ +/* k1=func(p2)-fx; */ + +/* p2[thetai]=x[thetai]+delti[thetai]/k; */ +/* p2[thetaj]=x[thetaj]-delti[thetaj]/k; */ +/* k2=func(p2)-fx; */ + +/* p2[thetai]=x[thetai]-delti[thetai]/k; */ +/* p2[thetaj]=x[thetaj]+delti[thetaj]/k; */ +/* k3=func(p2)-fx; */ + +/* p2[thetai]=x[thetai]-delti[thetai]/k; */ +/* p2[thetaj]=x[thetaj]-delti[thetaj]/k; */ +/* k4=func(p2)-fx; */ +/* res=(k1-k2-k3+k4)/4.0/delti[thetai]*k/delti[thetaj]*k/2.; /\* Because of L not 2*L *\/ */ +/* #ifdef DEBUGHESSIJ */ +/* 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); */ +/* 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); */ +/* #endif */ +/* if((k1 <khi/nkhi/2.) || (k2 <khi/nkhi/2.)|| (k4 <khi/nkhi/2.)|| (k4 <khi/nkhi/2.)){ */ +/* k=kmax; */ +/* } */ +/* else if((k1 >khi/nkhif) || (k2 >khi/nkhif) || (k4 >khi/nkhif) || (k4 >khi/nkhif)){ /\* Keeps lastvalue before 3.84/2 KHI2 5% 1d.f. *\/ */ +/* k=kmax; l=lmax*10; */ +/* } */ +/* else if((k1 >khi/nkhi) || (k2 >khi/nkhi)){ */ +/* delts=delt; */ +/* } */ +/* } /\* End loop k *\/ */ +/* } */ +/* delti[theta]=delts; */ +/* return res; */ +/* } */ + + /************** Inverse of matrix **************/ void ludcmp(double **a, int n, int *indx, double *d) { @@ -1062,371 +4187,1732 @@ void lubksb(double **a, int n, int *indx } } +void pstamp(FILE *fichier) +{ + fprintf(fichier,"# %s.%s\n#IMaCh version %s, %s\n#%s\n# %s", optionfilefiname,optionfilext,version,copyright, fullversion, strstart); +} + +int linreg(int ifi, int ila, int *no, const double x[], const double y[], double* a, double* b, double* r, double* sa, double * sb) { + + /* y=a+bx regression */ + double sumx = 0.0; /* sum of x */ + double sumx2 = 0.0; /* sum of x**2 */ + double sumxy = 0.0; /* sum of x * y */ + double sumy = 0.0; /* sum of y */ + double sumy2 = 0.0; /* sum of y**2 */ + double sume2; /* sum of square or residuals */ + double yhat; + + double denom=0; + int i; + int ne=*no; + + for ( i=ifi, ne=0;i<=ila;i++) { + if(!isfinite(x[i]) || !isfinite(y[i])){ + /* printf(" x[%d]=%f, y[%d]=%f\n",i,x[i],i,y[i]); */ + continue; + } + ne=ne+1; + sumx += x[i]; + sumx2 += x[i]*x[i]; + sumxy += x[i] * y[i]; + sumy += y[i]; + sumy2 += y[i]*y[i]; + denom = (ne * sumx2 - sumx*sumx); + /* 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); */ + } + + denom = (ne * sumx2 - sumx*sumx); + if (denom == 0) { + // vertical, slope m is infinity + *b = INFINITY; + *a = 0; + if (r) *r = 0; + return 1; + } + + *b = (ne * sumxy - sumx * sumy) / denom; + *a = (sumy * sumx2 - sumx * sumxy) / denom; + if (r!=NULL) { + *r = (sumxy - sumx * sumy / ne) / /* compute correlation coeff */ + sqrt((sumx2 - sumx*sumx/ne) * + (sumy2 - sumy*sumy/ne)); + } + *no=ne; + for ( i=ifi, ne=0;i<=ila;i++) { + if(!isfinite(x[i]) || !isfinite(y[i])){ + /* printf(" x[%d]=%f, y[%d]=%f\n",i,x[i],i,y[i]); */ + continue; + } + ne=ne+1; + yhat = y[i] - *a -*b* x[i]; + sume2 += yhat * yhat ; + + denom = (ne * sumx2 - sumx*sumx); + /* 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); */ + } + *sb = sqrt(sume2/(ne-2)/(sumx2 - sumx * sumx /ne)); + *sa= *sb * sqrt(sumx2/ne); + + return 0; +} + /************ Frequencies ********************/ -void freqsummary(char fileres[], int agemin, int agemax, int **s, double **agev, int nlstate, int imx) -{ /* Some frequencies */ - - int i, m, jk; +void freqsummary(char fileres[], double p[], double pstart[], int iagemin, int iagemax, int **s, double **agev, int nlstate, int imx, \ + int *Tvaraff, int *invalidvarcomb, int **nbcode, int *ncodemax,double **mint,double **anint, char strstart[], \ + int firstpass, int lastpass, int stepm, int weightopt, char model[]) +{ /* Some frequencies as well as proposing some starting values */ + + int i, m, jk, j1, bool, z1,j, nj, nl, k, iv, jj=0; + int iind=0, iage=0; + int mi; /* Effective wave */ + int first; double ***freq; /* Frequencies */ - double *pp; - double pos; - FILE *ficresp; - char fileresp[FILENAMELENGTH]; - + double *x, *y, a,b,r, sa, sb; /* for regression, y=b+m*x and r is the correlation coefficient */ + int no; + double *meanq; + double **meanqt; + double *pp, **prop, *posprop, *pospropt; + double pos=0., posproptt=0., pospropta=0., k2, dateintsum=0,k2cpt=0; + char fileresp[FILENAMELENGTH], fileresphtm[FILENAMELENGTH], fileresphtmfr[FILENAMELENGTH]; + double agebegin, ageend; + pp=vector(1,nlstate); - - strcpy(fileresp,"p"); - strcat(fileresp,fileres); + prop=matrix(1,nlstate,iagemin-AGEMARGE,iagemax+4+AGEMARGE); + posprop=vector(1,nlstate); /* Counting the number of transition starting from a live state per age */ + pospropt=vector(1,nlstate); /* Counting the number of transition starting from a live state */ + /* prop=matrix(1,nlstate,iagemin,iagemax+3); */ + meanq=vector(1,nqfveff); /* Number of Quantitative Fixed Variables Effective */ + meanqt=matrix(1,lastpass,1,nqtveff); + strcpy(fileresp,"P_"); + strcat(fileresp,fileresu); + /*strcat(fileresphtm,fileresu);*/ if((ficresp=fopen(fileresp,"w"))==NULL) { printf("Problem with prevalence resultfile: %s\n", fileresp); + fprintf(ficlog,"Problem with prevalence resultfile: %s\n", fileresp); exit(0); } + + strcpy(fileresphtm,subdirfext(optionfilefiname,"PHTM_",".htm")); + if((ficresphtm=fopen(fileresphtm,"w"))==NULL) { + printf("Problem with prevalence HTM resultfile '%s' with errno='%s'\n",fileresphtm,strerror(errno)); + fprintf(ficlog,"Problem with prevalence HTM resultfile '%s' with errno='%s'\n",fileresphtm,strerror(errno)); + fflush(ficlog); + exit(70); + } + else{ + fprintf(ficresphtm,"<html><head>\n<title>IMaCh PHTM_ %s\n %s
%s
\ +
\n \ +Title=%s
Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s
\n",\ + fileresphtm,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model); + } + fprintf(ficresphtm,"Current page is file %s
\n\n

Frequencies and prevalence by age at begin of transition and dummy covariate value at beginning of transition

\n",fileresphtm, fileresphtm); + + strcpy(fileresphtmfr,subdirfext(optionfilefiname,"PHTMFR_",".htm")); + if((ficresphtmfr=fopen(fileresphtmfr,"w"))==NULL) { + printf("Problem with frequency table HTM resultfile '%s' with errno='%s'\n",fileresphtmfr,strerror(errno)); + fprintf(ficlog,"Problem with frequency table HTM resultfile '%s' with errno='%s'\n",fileresphtmfr,strerror(errno)); + fflush(ficlog); + exit(70); + } else{ + fprintf(ficresphtmfr,"\nIMaCh PHTM_Frequency table %s\n %s
%s
\ +
\n \ +Title=%s
Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s
\n",\ + fileresphtmfr,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model); + } + fprintf(ficresphtmfr,"Current page is file %s
\n\n

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)

Unknown status is -1
\n",fileresphtmfr, fileresphtmfr); + + y= vector(iagemin-AGEMARGE,iagemax+4+AGEMARGE); + x= vector(iagemin-AGEMARGE,iagemax+4+AGEMARGE); + freq= ma3x(-5,nlstate+ndeath,-5,nlstate+ndeath,iagemin-AGEMARGE,iagemax+4+AGEMARGE); + j1=0; + + /* j=ncoveff; /\* Only fixed dummy covariates *\/ */ + j=cptcoveff; /* Only dummy covariates of the model */ + if (cptcovn<1) {j=1;ncodemax[1]=1;} + + + /* Detects if a combination j1 is empty: for a multinomial variable like 3 education levels: + reference=low_education V1=0,V2=0 + med_educ V1=1 V2=0, + high_educ V1=0 V2=1 + Then V1=1 and V2=1 is a noisy combination that we want to exclude for the list 2**cptcoveff + */ + dateintsum=0; + k2cpt=0; - freq= ma3x(-1,nlstate+ndeath,-1,nlstate+ndeath,agemin,agemax+3); - for (i=-1; i<=nlstate+ndeath; i++) - for (jk=-1; jk<=nlstate+ndeath; jk++) - for(m=agemin; m <= agemax+3; m++) - freq[i][jk][m]=0; - - for (i=1; i<=imx; i++) { - for(m=firstpass; m<= lastpass-1; m++){ - if(agev[m][i]==0) agev[m][i]=agemax+1; - if(agev[m][i]==1) agev[m][i]=agemax+2; - freq[s[m][i]][s[m+1][i]][(int)agev[m][i]] += weight[i]; - freq[s[m][i]][s[m+1][i]][(int) agemax+3] += weight[i]; - } - } - - fprintf(ficresp, "#"); - for(i=1; i<=nlstate;i++) - fprintf(ficresp, " Age Prev(%d) N(%d) N",i,i); -fprintf(ficresp, "\n"); - - for(i=(int)agemin; i <= (int)agemax+3; i++){ - if(i==(int)agemax+3) - printf("Total"); + if(cptcoveff == 0 ) + nl=1; /* Constant model only */ + else + nl=2; + for (nj = 1; nj <= nl; nj++){ /* nj= 1 constant model, nl number of loops. */ + if(nj==1) + j=0; /* First pass for the constant */ else - printf("Age %d", i); - for(jk=1; jk <=nlstate ; jk++){ - for(m=-1, pp[jk]=0; m <=nlstate+ndeath ; m++) - pp[jk] += freq[jk][m][i]; - } - for(jk=1; jk <=nlstate ; jk++){ - for(m=-1, pos=0; m <=0 ; m++) - pos += freq[jk][m][i]; - if(pp[jk]>=1.e-10) - printf(" %d.=%.0f loss[%d]=%.1f%%",jk,pp[jk],jk,100*pos/pp[jk]); - else - printf(" %d.=%.0f loss[%d]=NaNQ%%",jk,pp[jk],jk); - } - for(jk=1; jk <=nlstate ; jk++){ - for(m=1, pp[jk]=0; m <=nlstate+ndeath; m++) - pp[jk] += freq[jk][m][i]; - } - for(jk=1,pos=0; jk <=nlstate ; jk++) - pos += pp[jk]; - for(jk=1; jk <=nlstate ; jk++){ - if(pos>=1.e-5) - printf(" %d.=%.0f prev[%d]=%.1f%%",jk,pp[jk],jk,100*pp[jk]/pos); - else - printf(" %d.=%.0f prev[%d]=NaNQ%%",jk,pp[jk],jk); - if( i <= (int) agemax){ - if(pos>=1.e-5) - fprintf(ficresp," %d %.5f %.0f %.0f",i,pp[jk]/pos, pp[jk],pos); - else - fprintf(ficresp," %d NaNq %.0f %.0f",i,pp[jk],pos); + j=cptcoveff; /* Other passes for the covariate values */ + first=1; + for (j1 = 1; j1 <= (int) pow(2,j); j1++){ /* Loop on covariates combination in order of model, excluding quantitatives, V4=0, V3=0 for example, fixed or varying covariates */ + posproptt=0.; + /*printf("cptcoveff=%d Tvaraff=%d", cptcoveff,Tvaraff[1]); + scanf("%d", i);*/ + for (i=-5; i<=nlstate+ndeath; i++) + for (jk=-5; jk<=nlstate+ndeath; jk++) + for(m=iagemin; m <= iagemax+3; m++) + freq[i][jk][m]=0; + + for (i=1; i<=nlstate; i++) { + for(m=iagemin; m <= iagemax+3; m++) + prop[i][m]=0; + posprop[i]=0; + pospropt[i]=0; } - } - for(jk=-1; jk <=nlstate+ndeath; jk++) - for(m=-1; m <=nlstate+ndeath; m++) - if(freq[jk][m][i] !=0 ) printf(" %d%d=%.0f",jk,m,freq[jk][m][i]); - if(i <= (int) agemax) - fprintf(ficresp,"\n"); - printf("\n"); - } - - fclose(ficresp); - free_ma3x(freq,-1,nlstate+ndeath,-1,nlstate+ndeath,(int) agemin,(int) agemax+3); - free_vector(pp,1,nlstate); - -} /* End of Freq */ - -/************* Waves Concatenation ***************/ - -void concatwav(int wav[], int **dh, int **mw, int **s, double *agedc, double **agev, int firstpass, int lastpass, int imx, int nlstate, int stepm) -{ - /* Concatenates waves: wav[i] is the number of effective (useful waves) of individual i. + /* for (z1=1; z1<= nqfveff; z1++) { */ + /* meanq[z1]+=0.; */ + /* for(m=1;m<=lastpass;m++){ */ + /* meanqt[m][z1]=0.; */ + /* } */ + /* } */ + + /* dateintsum=0; */ + /* k2cpt=0; */ + + /* For that combination of covariate j1, we count and print the frequencies in one pass */ + for (iind=1; iind<=imx; iind++) { /* For each individual iind */ + bool=1; + if(j !=0){ + if(anyvaryingduminmodel==0){ /* If All fixed covariates */ + if (cptcoveff >0) { /* Filter is here: Must be looked at for model=V1+V2+V3+V4 */ + /* for (z1=1; z1<= nqfveff; z1++) { */ + /* meanq[z1]+=coqvar[Tvar[z1]][iind]; /\* Computes mean of quantitative with selected filter *\/ */ + /* } */ + for (z1=1; z1<=cptcoveff; z1++) { /* loops on covariates in the model */ + /* if(Tvaraff[z1] ==-20){ */ + /* /\* sumnew+=cotvar[mw[mi][iind]][z1][iind]; *\/ */ + /* }else if(Tvaraff[z1] ==-10){ */ + /* /\* sumnew+=coqvar[z1][iind]; *\/ */ + /* }else */ + if (covar[Tvaraff[z1]][iind]!= nbcode[Tvaraff[z1]][codtabm(j1,z1)]){ /* for combination j1 of covariates */ + /* Tests if this individual iind responded to combination j1 (V4=1 V3=0) */ + bool=0; /* bool should be equal to 1 to be selected, one covariate value failed */ + /* 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", + bool,i,z1, z1, Tvaraff[z1],i,covar[Tvaraff[z1]][i],j1,z1,codtabm(j1,z1), + j1,z1,nbcode[Tvaraff[z1]][codtabm(j1,z1)],j1);*/ + /* For j1=7 in V1+V2+V3+V4 = 0 1 1 0 and codtabm(7,3)=1 and nbcde[3][?]=1*/ + } /* Onlyf fixed */ + } /* end z1 */ + } /* cptcovn > 0 */ + } /* end any */ + }/* end j==0 */ + if (bool==1){ /* We selected an individual iind satisfying combination j1 or all fixed */ + /* for(m=firstpass; m<=lastpass; m++){ */ + for(mi=1; mi=firstpass && m <=lastpass){ + k2=anint[m][iind]+(mint[m][iind]/12.); + /*if ((k2>=dateprev1) && (k2<=dateprev2)) {*/ + if(agev[m][iind]==0) agev[m][iind]=iagemax+1; /* All ages equal to 0 are in iagemax+1 */ + if(agev[m][iind]==1) agev[m][iind]=iagemax+2; /* All ages equal to 1 are in iagemax+2 */ + if (s[m][iind]>0 && s[m][iind]<=nlstate) /* If status at wave m is known and a live state */ + prop[s[m][iind]][(int)agev[m][iind]] += weight[iind]; /* At age of beginning of transition, where status is known */ + if (m1) && (agev[m][iind]< (iagemax+3)) && (anint[m][iind]!=9999) && (mint[m][iind]!=99) && (j==0)) { + dateintsum=dateintsum+k2; /* on all covariates ?*/ + k2cpt++; + /* printf("iind=%ld dateintmean = %lf dateintsum=%lf k2cpt=%lf k2=%lf\n",iind, dateintsum/k2cpt, dateintsum,k2cpt, k2); */ + } + }else{ + bool=1; + }/* end bool 2 */ + } /* end m */ + } /* end bool */ + } /* end iind = 1 to imx */ + /* prop[s][age] is feeded for any initial and valid live state as well as + freq[s1][s2][age] at single age of beginning the transition, for a combination j1 */ + + + /* fprintf(ficresp, "#Count between %.lf/%.lf/%.lf and %.lf/%.lf/%.lf\n",jprev1, mprev1,anprev1,jprev2, mprev2,anprev2);*/ + pstamp(ficresp); + if (cptcoveff>0 && j!=0){ + printf( "\n#********** Variable "); + fprintf(ficresp, "\n#********** Variable "); + fprintf(ficresphtm, "\n

********** Variable "); + fprintf(ficresphtmfr, "\n

********** Variable "); + fprintf(ficlog, "\n#********** Variable "); + for (z1=1; z1<=cptcoveff; z1++){ + if(!FixedV[Tvaraff[z1]]){ + printf( "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]); + fprintf(ficresp, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]); + fprintf(ficresphtm, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]); + fprintf(ficresphtmfr, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]); + fprintf(ficlog, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]); + }else{ + printf( "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]); + fprintf(ficresp, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]); + fprintf(ficresphtm, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]); + fprintf(ficresphtmfr, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]); + fprintf(ficlog, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]); + } + } + printf( "**********\n#"); + fprintf(ficresp, "**********\n#"); + fprintf(ficresphtm, "**********

\n"); + fprintf(ficresphtmfr, "**********\n"); + fprintf(ficlog, "**********\n"); + } + fprintf(ficresphtm,""); + for(i=1; i<=nlstate;i++) { + fprintf(ficresp, " Age Prev(%d) N(%d) N ",i,i); + fprintf(ficresphtm, "",i,i); + } + fprintf(ficresp, "\n"); + fprintf(ficresphtm, "\n"); + + /* Header of frequency table by age */ + fprintf(ficresphtmfr,"
AgePrev(%d)N(%d)N
"); + fprintf(ficresphtmfr," "); + for(jk=-1; jk <=nlstate+ndeath; jk++){ + for(m=-1; m <=nlstate+ndeath; m++){ + if(jk!=0 && m!=0) + fprintf(ficresphtmfr," ",jk,m); + } + } + fprintf(ficresphtmfr, "\n"); + + /* For each age */ + for(iage=iagemin; iage <= iagemax+3; iage++){ + fprintf(ficresphtm,""); + if(iage==iagemax+1){ + fprintf(ficlog,"1"); + fprintf(ficresphtmfr," "); + }else if(iage==iagemax+2){ + fprintf(ficlog,"0"); + fprintf(ficresphtmfr," "); + }else if(iage==iagemax+3){ + fprintf(ficlog,"Total"); + fprintf(ficresphtmfr," "); + }else{ + if(first==1){ + first=0; + printf("See log file for details...\n"); + } + fprintf(ficresphtmfr," ",iage); + fprintf(ficlog,"Age %d", iage); + } + for(jk=1; jk <=nlstate ; jk++){ + for(m=-1, pp[jk]=0; m <=nlstate+ndeath ; m++) + pp[jk] += freq[jk][m][iage]; + } + for(jk=1; jk <=nlstate ; jk++){ + for(m=-1, pos=0; m <=0 ; m++) + pos += freq[jk][m][iage]; + if(pp[jk]>=1.e-10){ + if(first==1){ + printf(" %d.=%.0f loss[%d]=%.1f%%",jk,pp[jk],jk,100*pos/pp[jk]); + } + fprintf(ficlog," %d.=%.0f loss[%d]=%.1f%%",jk,pp[jk],jk,100*pos/pp[jk]); + }else{ + if(first==1) + printf(" %d.=%.0f loss[%d]=NaNQ%%",jk,pp[jk],jk); + fprintf(ficlog," %d.=%.0f loss[%d]=NaNQ%%",jk,pp[jk],jk); + } + } + + for(jk=1; jk <=nlstate ; jk++){ + /* posprop[jk]=0; */ + for(m=0, pp[jk]=0; m <=nlstate+ndeath; m++)/* Summing on all ages */ + pp[jk] += freq[jk][m][iage]; + } /* pp[jk] is the total number of transitions starting from state jk and any ending status until this age */ + + for(jk=1,pos=0, pospropta=0.; jk <=nlstate ; jk++){ + pos += pp[jk]; /* pos is the total number of transitions until this age */ + posprop[jk] += prop[jk][iage]; /* prop is the number of transitions from a live state + from jk at age iage prop[s[m][iind]][(int)agev[m][iind]] += weight[iind] */ + pospropta += prop[jk][iage]; /* prop is the number of transitions from a live state + from jk at age iage prop[s[m][iind]][(int)agev[m][iind]] += weight[iind] */ + } + for(jk=1; jk <=nlstate ; jk++){ + if(pos>=1.e-5){ + if(first==1) + printf(" %d.=%.0f prev[%d]=%.1f%%",jk,pp[jk],jk,100*pp[jk]/pos); + fprintf(ficlog," %d.=%.0f prev[%d]=%.1f%%",jk,pp[jk],jk,100*pp[jk]/pos); + }else{ + if(first==1) + printf(" %d.=%.0f prev[%d]=NaNQ%%",jk,pp[jk],jk); + fprintf(ficlog," %d.=%.0f prev[%d]=NaNQ%%",jk,pp[jk],jk); + } + if( iage <= iagemax){ + if(pos>=1.e-5){ + fprintf(ficresp," %d %.5f %.0f %.0f",iage,prop[jk][iage]/pospropta, prop[jk][iage],pospropta); + fprintf(ficresphtm,"",iage,prop[jk][iage]/pospropta, prop[jk][iage],pospropta); + /*probs[iage][jk][j1]= pp[jk]/pos;*/ + /*printf("\niage=%d jk=%d j1=%d %.5f %.0f %.0f %f",iage,jk,j1,pp[jk]/pos, pp[jk],pos,probs[iage][jk][j1]);*/ + } + else{ + fprintf(ficresp," %d NaNq %.0f %.0f",iage,prop[jk][iage],pospropta); + fprintf(ficresphtm,"",iage, prop[jk][iage],pospropta); + } + } + pospropt[jk] +=posprop[jk]; + } /* end loop jk */ + /* pospropt=0.; */ + for(jk=-1; jk <=nlstate+ndeath; jk++){ + for(m=-1; m <=nlstate+ndeath; m++){ + if(freq[jk][m][iage] !=0 ) { /* minimizing output */ + if(first==1){ + printf(" %d%d=%.0f",jk,m,freq[jk][m][iage]); + } + /* printf(" %d%d=%.0f",jk,m,freq[jk][m][iage]); */ + fprintf(ficlog," %d%d=%.0f",jk,m,freq[jk][m][iage]); + } + if(jk!=0 && m!=0) + fprintf(ficresphtmfr," ",freq[jk][m][iage]); + } + } /* end loop jk */ + posproptt=0.; + for(jk=1; jk <=nlstate; jk++){ + posproptt += pospropt[jk]; + } + fprintf(ficresphtmfr,"\n "); + if(iage <= iagemax){ + fprintf(ficresp,"\n"); + fprintf(ficresphtm,"\n"); + } + if(first==1) + printf("Others in log...\n"); + fprintf(ficlog,"\n"); + } /* end loop age iage */ + fprintf(ficresphtm,""); + for(jk=1; jk <=nlstate ; jk++){ + if(posproptt < 1.e-5){ + fprintf(ficresphtm,"",pospropt[jk],posproptt); + }else{ + fprintf(ficresphtm,"",pospropt[jk]/posproptt,pospropt[jk],posproptt); + } + } + fprintf(ficresphtm,"\n"); + fprintf(ficresphtm,"
Age%d%d
0
Unknown
Total
%d%d%.5f%.0f%.0f%dNaNq%.0f%.0f%.0f
TotNanq%.0f%.0f%.5f%.0f%.0f
\n"); + fprintf(ficresphtmfr,"\n"); + if(posproptt < 1.e-5){ + fprintf(ficresphtm,"\n

This combination (%d) is not valid and no result will be produced

",j1); + fprintf(ficresphtmfr,"\n

This combination (%d) is not valid and no result will be produced

",j1); + fprintf(ficres,"\n This combination (%d) is not valid and no result will be produced\n\n",j1); + invalidvarcomb[j1]=1; + }else{ + fprintf(ficresphtm,"\n

This combination (%d) is valid and result will be produced.

",j1); + invalidvarcomb[j1]=0; + } + fprintf(ficresphtmfr,"\n"); + fprintf(ficlog,"\n"); + if(j!=0){ + printf("#Freqsummary: Starting values for combination j1=%d:\n", j1); + for(i=1,jk=1; i <=nlstate; i++){ + for(k=1; k <=(nlstate+ndeath); k++){ + if (k != i) { + for(jj=1; jj <=ncovmodel; jj++){ /* For counting jk */ + if(jj==1){ /* Constant case (in fact cste + age) */ + if(j1==1){ /* All dummy covariates to zero */ + freq[i][k][iagemax+4]=freq[i][k][iagemax+3]; /* Stores case 0 0 0 */ + freq[i][i][iagemax+4]=freq[i][i][iagemax+3]; /* Stores case 0 0 0 */ + printf("%d%d ",i,k); + fprintf(ficlog,"%d%d ",i,k); + printf("%12.7f ln(%.0f/%.0f)= %f, OR=%f sd=%f \n",p[jk],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])); + fprintf(ficlog,"%12.7f ln(%.0f/%.0f)= %12.7f \n",p[jk],freq[i][k][iagemax+3],freq[i][i][iagemax+3], log(freq[i][k][iagemax+3]/freq[i][i][iagemax+3])); + pstart[jk]= log(freq[i][k][iagemax+3]/freq[i][i][iagemax+3]); + } + }else if((j1==1) && (jj==2 || nagesqr==1)){ /* age or age*age parameter without covariate V4*age (to be done later) */ + for(iage=iagemin; iage <= iagemax+3; iage++){ + x[iage]= (double)iage; + y[iage]= log(freq[i][k][iage]/freq[i][i][iage]); + /* printf("i=%d, k=%d, jk=%d, j1=%d, jj=%d, y[%d]=%f\n",i,k,jk,j1,jj, iage, y[iage]); */ + } + linreg(iagemin,iagemax,&no,x,y,&a,&b,&r, &sa, &sb ); /* y= a+b*x with standard errors */ + pstart[jk]=b; + pstart[jk-1]=a; + }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 */ + 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]); + 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]); + pstart[jk]= log((freq[i][k][iagemax+3]/freq[i][i][iagemax+3])/(freq[i][k][iagemax+4]/freq[i][i][iagemax+4])); + printf("%d%d ",i,k); + fprintf(ficlog,"%d%d ",i,k); + printf("jk=%d,i=%d,k=%d,p[%d]=%12.7f ln((%.0f/%.0f)/(%.0f/%.0f))= %f, OR=%f sd=%f \n",jk,i,k,jk,p[jk],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])); + }else{ /* Other cases, like quantitative fixed or varying covariates */ + ; + } + /* printf("%12.7f )", param[i][jj][k]); */ + /* fprintf(ficlog,"%12.7f )", param[i][jj][k]); */ + jk++; + } /* end jj */ + } /* end k!= i */ + } /* end k */ + } /* end i, jk */ + } /* end j !=0 */ + } /* end selected combination of covariate j1 */ + if(j==0){ /* We can estimate starting values from the occurences in each case */ + printf("#Freqsummary: Starting values for the constants:\n"); + fprintf(ficlog,"\n"); + for(i=1,jk=1; i <=nlstate; i++){ + for(k=1; k <=(nlstate+ndeath); k++){ + if (k != i) { + printf("%d%d ",i,k); + fprintf(ficlog,"%d%d ",i,k); + for(jj=1; jj <=ncovmodel; jj++){ + pstart[jk]=p[jk]; /* Setting pstart to p values by default */ + if(jj==1){ /* Age has to be done */ + pstart[jk]= log(freq[i][k][iagemax+3]/freq[i][i][iagemax+3]); + printf("%12.7f ln(%.0f/%.0f)= %12.7f ",p[jk],freq[i][k][iagemax+3],freq[i][i][iagemax+3], log(freq[i][k][iagemax+3]/freq[i][i][iagemax+3])); + fprintf(ficlog,"%12.7f ln(%.0f/%.0f)= %12.7f ",p[jk],freq[i][k][iagemax+3],freq[i][i][iagemax+3], log(freq[i][k][iagemax+3]/freq[i][i][iagemax+3])); + } + /* printf("%12.7f )", param[i][jj][k]); */ + /* fprintf(ficlog,"%12.7f )", param[i][jj][k]); */ + jk++; + } + printf("\n"); + fprintf(ficlog,"\n"); + } + } + } + printf("#Freqsummary\n"); + fprintf(ficlog,"\n"); + for(jk=-1; jk <=nlstate+ndeath; jk++){ + for(m=-1; m <=nlstate+ndeath; m++){ + /* param[i]|j][k]= freq[jk][m][iagemax+3] */ + printf(" %d%d=%.0f",jk,m,freq[jk][m][iagemax+3]); + fprintf(ficlog," %d%d=%.0f",jk,m,freq[jk][m][iagemax+3]); + /* if(freq[jk][m][iage] !=0 ) { /\* minimizing output *\/ */ + /* printf(" %d%d=%.0f",jk,m,freq[jk][m][iagemax+3]); */ + /* fprintf(ficlog," %d%d=%.0f",jk,m,freq[jk][m][iagemax+3]); */ + /* } */ + } + } /* end loop jk */ + + printf("\n"); + fprintf(ficlog,"\n"); + } /* end j=0 */ + } /* end j */ + + if(mle == -2){ /* We want to use these values as starting values */ + for(i=1, jk=1; i <=nlstate; i++){ + for(j=1; j <=nlstate+ndeath; j++){ + if(j!=i){ + /*ca[0]= k+'a'-1;ca[1]='\0';*/ + printf("%1d%1d",i,j); + fprintf(ficparo,"%1d%1d",i,j); + for(k=1; k<=ncovmodel;k++){ + /* printf(" %lf",param[i][j][k]); */ + /* fprintf(ficparo," %lf",param[i][j][k]); */ + p[jk]=pstart[jk]; + printf(" %f ",pstart[jk]); + fprintf(ficparo," %f ",pstart[jk]); + jk++; + } + printf("\n"); + fprintf(ficparo,"\n"); + } + } + } + } /* end mle=-2 */ + dateintmean=dateintsum/k2cpt; + + fclose(ficresp); + fclose(ficresphtm); + fclose(ficresphtmfr); + free_vector(meanq,1,nqfveff); + free_matrix(meanqt,1,lastpass,1,nqtveff); + free_vector(x, iagemin-AGEMARGE, iagemax+4+AGEMARGE); + free_vector(y, iagemin-AGEMARGE, iagemax+4+AGEMARGE); + free_ma3x(freq,-5,nlstate+ndeath,-5,nlstate+ndeath, iagemin-AGEMARGE, iagemax+4+AGEMARGE); + free_vector(pospropt,1,nlstate); + free_vector(posprop,1,nlstate); + free_matrix(prop,1,nlstate,iagemin-AGEMARGE, iagemax+4+AGEMARGE); + free_vector(pp,1,nlstate); + /* End of freqsummary */ +} + +/************ Prevalence ********************/ +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) +{ + /* Compute observed prevalence between dateprev1 and dateprev2 by counting the number of people + in each health status at the date of interview (if between dateprev1 and dateprev2). + We still use firstpass and lastpass as another selection. + */ + + int i, m, jk, j1, bool, z1,j, iv; + int mi; /* Effective wave */ + int iage; + double agebegin, ageend; + + double **prop; + double posprop; + double y2; /* in fractional years */ + int iagemin, iagemax; + int first; /** to stop verbosity which is redirected to log file */ + + iagemin= (int) agemin; + iagemax= (int) agemax; + /*pp=vector(1,nlstate);*/ + prop=matrix(1,nlstate,iagemin-AGEMARGE,iagemax+4+AGEMARGE); + /* freq=ma3x(-1,nlstate+ndeath,-1,nlstate+ndeath,iagemin,iagemax+3);*/ + j1=0; + + /*j=cptcoveff;*/ + if (cptcovn<1) {j=1;ncodemax[1]=1;} + + first=1; + for(j1=1; j1<= (int) pow(2,cptcoveff);j1++){ /* For each combination of covariate */ + for (i=1; i<=nlstate; i++) + for(iage=iagemin-AGEMARGE; iage <= iagemax+4+AGEMARGE; iage++) + prop[i][iage]=0.0; + printf("Prevalence combination of varying and fixed dummies %d\n",j1); + /* fprintf(ficlog," V%d=%d ",Tvaraff[j1],nbcode[Tvaraff[j1]][codtabm(k,j1)]); */ + fprintf(ficlog,"Prevalence combination of varying and fixed dummies %d\n",j1); + + for (i=1; i<=imx; i++) { /* Each individual */ + bool=1; + /* for(m=firstpass; m<=lastpass; m++){/\* Other selection (we can limit to certain interviews*\/ */ + for(mi=1; mi=firstpass && m <=lastpass){ + y2=anint[m][i]+(mint[m][i]/12.); /* Fractional date in year */ + if ((y2>=dateprev1) && (y2<=dateprev2)) { /* Here is the main selection (fractional years) */ + if(agev[m][i]==0) agev[m][i]=iagemax+1; + if(agev[m][i]==1) agev[m][i]=iagemax+2; + if((int)agev[m][i] iagemax+4+AGEMARGE){ + 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); + exit(1); + } + if (s[m][i]>0 && s[m][i]<=nlstate) { + /*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]]);*/ + prop[s[m][i]][(int)agev[m][i]] += weight[i];/* At age of beginning of transition, where status is known */ + prop[s[m][i]][iagemax+3] += weight[i]; + } /* end valid statuses */ + } /* end selection of dates */ + } /* end selection of waves */ + } /* end bool */ + } /* end wave */ + } /* end individual */ + for(i=iagemin; i <= iagemax+3; i++){ + for(jk=1,posprop=0; jk <=nlstate ; jk++) { + posprop += prop[jk][i]; + } + + for(jk=1; jk <=nlstate ; jk++){ + if( i <= iagemax){ + if(posprop>=1.e-5){ + probs[i][jk][j1]= prop[jk][i]/posprop; + } else{ + if(first==1){ + first=0; + printf("Warning Observed prevalence probs[%d][%d][%d]=%lf because of lack of cases\nSee others in log file...\n",jk,i,j1,probs[i][jk][j1]); + } + } + } + }/* end jk */ + }/* end i */ + /*} *//* end i1 */ + } /* end j1 */ + + /* free_ma3x(freq,-1,nlstate+ndeath,-1,nlstate+ndeath, iagemin, iagemax+3);*/ + /*free_vector(pp,1,nlstate);*/ + free_matrix(prop,1,nlstate, iagemin-AGEMARGE,iagemax+4+AGEMARGE); +} /* End of prevalence */ + +/************* Waves Concatenation ***************/ + +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) +{ + /* Concatenates waves: wav[i] is the number of effective (useful waves) of individual i. Death is a valid wave (if date is known). mw[mi][i] is the mi (mi=1 to wav[i]) effective wave of individual i - dh[m][i] of dh[mw[mi][i][i] is the delay between two effective waves m=mw[mi][i] + dh[m][i] or dh[mw[mi][i]][i] is the delay between two effective waves m=mw[mi][i] and mw[mi+1][i]. dh depends on stepm. - */ - - int i, mi, m; - int j, k=0,jk, ju, jl,jmin=1e+5, jmax=-1; -float sum=0.; + */ - for(i=1; i<=imx; i++){ - mi=0; + int i=0, mi=0, m=0, mli=0; + /* int j, k=0,jk, ju, jl,jmin=1e+5, jmax=-1; + double sum=0., jmean=0.;*/ + int first=0, firstwo=0, firsthree=0, firstfour=0, firstfiv=0; + int j, k=0,jk, ju, jl; + double sum=0.; + first=0; + firstwo=0; + firsthree=0; + firstfour=0; + jmin=100000; + jmax=-1; + jmean=0.; + +/* Treating live states */ + for(i=1; i<=imx; i++){ /* For simple cases and if state is death */ + mi=0; /* First valid wave */ + mli=0; /* Last valid wave */ m=firstpass; - while(s[m][i] <= nlstate){ - if(s[m][i]>=1) + while(s[m][i] <= nlstate){ /* a live state */ + 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 */ + mli=m-1;/* mw[++mi][i]=m-1; */ + }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 */ mw[++mi][i]=m; - if(m >=lastpass) + mli=m; + } /* else might be a useless wave -1 and mi is not incremented and mw[mi] not updated */ + if(m < lastpass){ /* m < lastpass, standard case */ + m++; /* mi gives the "effective" current wave, m the current wave, go to next wave by incrementing m */ + } + else{ /* m >= lastpass, eventual special issue with warning */ +#ifdef UNKNOWNSTATUSNOTCONTRIBUTING break; - else - m++; +#else + if(s[m][i]==-1 && (int) andc[i] == 9999 && (int)anint[m][i] != 9999){ + if(firsthree == 0){ + printf("Information! Unknown status for individual %ld line=%d occurred at last wave %d at known date %d/%d. Please, check if your unknown date of death %d/%d means a live state %d at wave %d. This case(%d)/wave(%d) contributes to the likelihood as pi. .\nOthers in log file only\n",num[i],i,lastpass,(int)mint[m][i],(int)anint[m][i], (int) moisdc[i], (int) andc[i], s[m][i], m, i, m); + firsthree=1; + } + fprintf(ficlog,"Information! Unknown status for individual %ld line=%d occurred at last wave %d at known date %d/%d. Please, check if your unknown date of death %d/%d means a live state %d at wave %d. This case(%d)/wave(%d) contributes to the likelihood as pi. .\n",num[i],i,lastpass,(int)mint[m][i],(int)anint[m][i], (int) moisdc[i], (int) andc[i], s[m][i], m, i, m); + mw[++mi][i]=m; + mli=m; + } + if(s[m][i]==-2){ /* Vital status is really unknown */ + nbwarn++; + if((int)anint[m][i] == 9999){ /* Has the vital status really been verified? */ + 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); + 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); + } + break; + } + break; +#endif + }/* End m >= lastpass */ }/* end while */ - if (s[m][i] > nlstate){ + + /* mi is the last effective wave, m is lastpass, mw[j][i] gives the # of j-th effective wave for individual i */ + /* After last pass */ +/* Treating death states */ + if (s[m][i] > nlstate){ /* In a death state */ + /* if( mint[m][i]==mdc[m][i] && anint[m][i]==andc[m][i]){ /\* same date of death and date of interview *\/ */ + /* } */ mi++; /* Death is another wave */ /* if(mi==0) never been interviewed correctly before death */ - /* Only death is a correct wave */ + /* Only death is a correct wave */ mw[mi][i]=m; } - - wav[i]=mi; - if(mi==0) - printf("Warning, no any valid information for:%d line=%d\n",num[i],i); - } - +#ifndef DISPATCHINGKNOWNDEATHAFTERLASTWAVE + else if ((int) andc[i] != 9999) { /* Status is negative. A death occured after lastpass, we can't take it into account because of potential bias */ + /* m++; */ + /* mi++; */ + /* s[m][i]=nlstate+1; /\* We are setting the status to the last of non live state *\/ */ + /* mw[mi][i]=m; */ + if ((int)anint[m][i]!= 9999) { /* date of last interview is known */ + 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 */ + nbwarn++; + if(firstfiv==0){ + 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 ); + firstfiv=1; + }else{ + 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 ); + } + }else{ /* Death occured afer last wave potential bias */ + nberr++; + if(firstwo==0){ + printf("Error! Death for individual %ld line=%d occurred at %d/%d after last wave %d interviewed at %d/%d. Potential bias if other individuals are still alive at this date but ignored. This case (%d)/wave (%d) is skipped, no contribution to likelihood.\nOthers in log file only\n",num[i],i,(int) moisdc[i], (int) andc[i], lastpass,(int)mint[m][i],(int)anint[m][i], i,m ); + firstwo=1; + } + fprintf(ficlog,"Error! Death for individual %ld line=%d occurred at %d/%d after last wave %d interviewed at %d/%d. Potential bias if other individuals are still alive at this date but ignored. This case (%d)/wave (%d) is skipped, no contribution to likelihood.\n",num[i],i,(int) moisdc[i], (int) andc[i], lastpass,(int)mint[m][i],(int)anint[m][i], i,m ); + } + }else{ /* end date of interview is known */ + /* death is known but not confirmed by death status at any wave */ + if(firstfour==0){ + 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 ); + firstfour=1; + } + 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 ); + } + } /* end if date of death is known */ +#endif + wav[i]=mi; /* mi should be the last effective wave (or mli) */ + /* wav[i]=mw[mi][i]; */ + if(mi==0){ + nbwarn++; + if(first==0){ + printf("Warning! No valid information for individual %ld line=%d (skipped) and may be others, see log file\n",num[i],i); + first=1; + } + if(first==1){ + fprintf(ficlog,"Warning! No valid information for individual %ld line=%d (skipped)\n",num[i],i); + } + } /* end mi==0 */ + } /* End individuals */ + /* wav and mw are no more changed */ + + for(i=1; i<=imx; i++){ for(mi=1; mi nlstate) { - j= rint(agedc[i]*12-agev[mw[mi][i]][i]*12); - if(j=0) j=1; /* Survives at least one month after exam */ + if (s[mw[mi+1][i]][i] > nlstate) { /* A death */ + if (agedc[i] < 2*AGESUP) { + j= rint(agedc[i]*12-agev[mw[mi][i]][i]*12); + if(j==0) j=1; /* Survives at least one month after exam */ + else if(j<0){ + nberr++; + 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]); + j=1; /* Temporary Dangerous patch */ + 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); + 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]); + 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); + } + k=k+1; + if (j >= jmax){ + jmax=j; + ijmax=i; + } + if (j <= jmin){ + jmin=j; + ijmin=i; + } + sum=sum+j; + /*if (j<0) printf("j=%d num=%d \n",j,i);*/ + /* printf("%d %d %d %d\n", s[mw[mi][i]][i] ,s[mw[mi+1][i]][i],j,i);*/ + } } else{ j= rint( (agev[mw[mi+1][i]][i]*12 - agev[mw[mi][i]][i]*12)); +/* 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]); */ + k=k+1; - if (j >= jmax) jmax=j; - else if (j <= jmin)jmin=j; + if (j >= jmax) { + jmax=j; + ijmax=i; + } + else if (j <= jmin){ + jmin=j; + ijmin=i; + } + /* if (j<10) printf("j=%d jmin=%d num=%d ",j,jmin,i); */ + /*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]);*/ + if(j<0){ + nberr++; + 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]); + 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]); + } sum=sum+j; } jk= j/stepm; jl= j -jk*stepm; ju= j -(jk+1)*stepm; - if(jl <= -ju) - dh[mi][i]=jk; - else - dh[mi][i]=jk+1; - if(dh[mi][i]==0) - dh[mi][i]=1; /* At least one step */ + if(mle <=1){ /* only if we use a the linear-interpoloation pseudo-likelihood */ + if(jl==0){ + dh[mi][i]=jk; + bh[mi][i]=0; + }else{ /* We want a negative bias in order to only have interpolation ie + * to avoid the price of an extra matrix product in likelihood */ + dh[mi][i]=jk+1; + bh[mi][i]=ju; + } + }else{ + if(jl <= -ju){ + dh[mi][i]=jk; + bh[mi][i]=jl; /* bias is positive if real duration + * is higher than the multiple of stepm and negative otherwise. + */ + } + else{ + dh[mi][i]=jk+1; + bh[mi][i]=ju; + } + if(dh[mi][i]==0){ + dh[mi][i]=1; /* At least one step */ + bh[mi][i]=ju; /* At least one step */ + /* 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);*/ + } + } /* end if mle */ } - } + } /* end wave */ } - printf("Delay (in months) between two waves Min=%d Max=%d Mean=%f\n\n ",jmin, jmax,sum/k); + jmean=sum/k; + 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); + 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); } +/*********** Tricode ****************************/ + void tricode(int *cptcov, int *Tvar, int **nbcode, int imx, int *Ndum) + { + /**< Uses cptcovn+2*cptcovprod as the number of covariates */ + /* Tvar[i]=atoi(stre); find 'n' in Vn and stores in Tvar. If model=V2+V1 Tvar[1]=2 and Tvar[2]=1 + * Boring subroutine which should only output nbcode[Tvar[j]][k] + * Tvar[5] in V2+V1+V3*age+V2*V4 is 4 (V4) even it is a time varying or quantitative variable + * nbcode[Tvar[5]][1]= nbcode[4][1]=0, nbcode[4][2]=1 (usually); + */ + + int ij=1, k=0, j=0, i=0, maxncov=NCOVMAX; + int modmaxcovj=0; /* Modality max of covariates j */ + int cptcode=0; /* Modality max of covariates j */ + int modmincovj=0; /* Modality min of covariates j */ + + + /* cptcoveff=0; */ + /* *cptcov=0; */ + + for (k=1; k <= maxncov; k++) ncodemax[k]=0; /* Horrible constant again replaced by NCOVMAX */ + + /* Loop on covariates without age and products and no quantitative variable */ + /* for (j=1; j<=(cptcovs); j++) { /\* From model V1 + V2*age+ V3 + V3*V4 keeps V1 + V3 = 2 only *\/ */ + for (k=1; k<=cptcovt; k++) { /* From model V1 + V2*age + V3 + V3*V4 keeps V1 + V3 = 2 only */ + for (j=-1; (j < maxncov); j++) Ndum[j]=0; + if(Dummy[k]==0 && Typevar[k] !=1){ /* Dummy covariate and not age product */ + switch(Fixed[k]) { + case 0: /* Testing on fixed dummy covariate, simple or product of fixed */ + 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*/ + ij=(int)(covar[Tvar[k]][i]); + /* ij=0 or 1 or -1. Value of the covariate Tvar[j] for individual i + * If product of Vn*Vm, still boolean *: + * If it was coded 1, 2, 3, 4 should be splitted into 3 boolean variables + * 1 => 0 0 0, 2 => 0 0 1, 3 => 0 1 1, 4=1 0 0 */ + /* Finds for covariate j, n=Tvar[j] of Vn . ij is the + modality of the nth covariate of individual i. */ + if (ij > modmaxcovj) + modmaxcovj=ij; + else if (ij < modmincovj) + modmincovj=ij; + if ((ij < -1) && (ij > NCOVMAX)){ + printf( "Error: minimal is less than -1 or maximal is bigger than %d. Exiting. \n", NCOVMAX ); + exit(1); + }else + Ndum[ij]++; /*counts and stores the occurence of this modality 0, 1, -1*/ + /* If coded 1, 2, 3 , counts the number of 1 Ndum[1], number of 2, Ndum[2], etc */ + /*printf("i=%d ij=%d Ndum[ij]=%d imx=%d",i,ij,Ndum[ij],imx);*/ + /* getting the maximum value of the modality of the covariate + (should be 0 or 1 now) Tvar[j]. If V=sex and male is coded 0 and + female ies 1, then modmaxcovj=1. + */ + } /* end for loop on individuals i */ + printf(" Minimal and maximal values of %d th (fixed) covariate V%d: min=%d max=%d \n", k, Tvar[k], modmincovj, modmaxcovj); + fprintf(ficlog," Minimal and maximal values of %d th (fixed) covariate V%d: min=%d max=%d \n", k, Tvar[k], modmincovj, modmaxcovj); + cptcode=modmaxcovj; + /* Ndum[0] = frequency of 0 for model-covariate j, Ndum[1] frequency of 1 etc. */ + /*for (i=0; i<=cptcode; i++) {*/ + for (j=modmincovj; j<=modmaxcovj; j++) { /* j=-1 ? 0 and 1*//* For each value j of the modality of model-cov k */ + printf("Frequencies of (fixed) covariate %d ie V%d with value %d: %d\n", k, Tvar[k], j, Ndum[j]); + fprintf(ficlog, "Frequencies of (fixed) covariate %d ie V%d with value %d: %d\n", k, Tvar[k], j, Ndum[j]); + if( Ndum[j] != 0 ){ /* Counts if nobody answered modality j ie empty modality, we skip it and reorder */ + if( j != -1){ + ncodemax[k]++; /* ncodemax[k]= Number of modalities of the k th + covariate for which somebody answered excluding + undefined. Usually 2: 0 and 1. */ + } + ncodemaxwundef[k]++; /* ncodemax[j]= Number of modalities of the k th + covariate for which somebody answered including + undefined. Usually 3: -1, 0 and 1. */ + } /* In fact ncodemax[k]=2 (dichotom. variables only) but it could be more for + * historical reasons: 3 if coded 1, 2, 3 and 4 and Ndum[2]=0 */ + } /* Ndum[-1] number of undefined modalities */ + + /* j is a covariate, n=Tvar[j] of Vn; Fills nbcode */ + /* For covariate j, modalities could be 1, 2, 3, 4, 5, 6, 7. */ + /* If Ndum[1]=0, Ndum[2]=0, Ndum[3]= 635, Ndum[4]=0, Ndum[5]=0, Ndum[6]=27, Ndum[7]=125; */ + /* modmincovj=3; modmaxcovj = 7; */ + /* There are only 3 modalities non empty 3, 6, 7 (or 2 if 27 is too few) : ncodemax[j]=3; */ + /* which will be coded 0, 1, 2 which in binary on 2=3-1 digits are 0=00 1=01, 2=10; */ + /* defining two dummy variables: variables V1_1 and V1_2.*/ + /* nbcode[Tvar[j]][ij]=k; */ + /* nbcode[Tvar[j]][1]=0; */ + /* nbcode[Tvar[j]][2]=1; */ + /* nbcode[Tvar[j]][3]=2; */ + /* To be continued (not working yet). */ + ij=0; /* ij is similar to i but can jump over null modalities */ + 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*/ + if (Ndum[i] == 0) { /* If nobody responded to this modality k */ + break; + } + ij++; + 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*/ + cptcode = ij; /* New max modality for covar j */ + } /* end of loop on modality i=-1 to 1 or more */ + break; + case 1: /* Testing on varying covariate, could be simple and + * should look at waves or product of fixed * + * varying. No time to test -1, assuming 0 and 1 only */ + ij=0; + for(i=0; i<=1;i++){ + nbcode[Tvar[k]][++ij]=i; + } + break; + default: + break; + } /* end switch */ + } /* end dummy test */ + + /* for (k=0; k<= cptcode; k++) { /\* k=-1 ? k=0 to 1 *\//\* Could be 1 to 4 *\//\* cptcode=modmaxcovj *\/ */ + /* /\*recode from 0 *\/ */ + /* k is a modality. If we have model=V1+V1*sex */ + /* then: nbcode[1][1]=0 ; nbcode[1][2]=1; nbcode[2][1]=0 ; nbcode[2][2]=1; */ + /* But if some modality were not used, it is recoded from 0 to a newer modmaxcovj=cptcode *\/ */ + /* } */ + /* /\* cptcode = ij; *\/ /\* New max modality for covar j *\/ */ + /* if (ij > ncodemax[j]) { */ + /* printf( " Error ij=%d > ncodemax[%d]=%d\n", ij, j, ncodemax[j]); */ + /* fprintf(ficlog, " Error ij=%d > ncodemax[%d]=%d\n", ij, j, ncodemax[j]); */ + /* break; */ + /* } */ + /* } /\* end of loop on modality k *\/ */ + } /* end of loop on model-covariate j. nbcode[Tvarj][1]=0 and nbcode[Tvarj][2]=1 sets the value of covariate j*/ + + for (k=-1; k< maxncov; k++) Ndum[k]=0; + /* Look at fixed dummy (single or product) covariates to check empty modalities */ + for (i=1; i<=ncovmodel-2-nagesqr; i++) { /* -2, cste and age and eventually age*age */ + /* Listing of all covariables in statement model to see if some covariates appear twice. For example, V1 appears twice in V1+V1*V2.*/ + 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 */ + 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 */ + /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, {2, 1, 1, 1, 2, 1, 1, 0, 0} */ + } /* V4+V3+V5, Ndum[1]@5={0, 0, 1, 1, 1} */ + + ij=0; + /* for (i=0; i<= maxncov-1; i++) { /\* modmaxcovj is unknown here. Only Ndum[2(V2),3(age*V3), 5(V3*V2) 6(V1*V4) *\/ */ + for (k=1; k<= cptcovt; k++) { /* modmaxcovj is unknown here. Only Ndum[2(V2),3(age*V3), 5(V3*V2) 6(V1*V4) */ + /*printf("Ndum[%d]=%d\n",i, Ndum[i]);*/ + /* if((Ndum[i]!=0) && (i<=ncovcol)){ /\* Tvar[i] <= ncovmodel ? *\/ */ + if(Ndum[Tvar[k]]!=0 && Dummy[k] == 0 && Typevar[k]==0){ /* Only Dummy and non empty in the model */ + /* If product not in single variable we don't print results */ + /*printf("diff Ndum[%d]=%d\n",i, Ndum[i]);*/ + ++ij;/* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, */ + 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*/ + Tmodelind[ij]=k; /* Tmodelind: index in model of dummies Tmodelind[1]=2 V4: pos=2; V3: pos=3, V1=9 {2, 3, 9, ?, ?,} */ + 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 */ + if(Fixed[k]!=0) + anyvaryingduminmodel=1; + /* }else if((Ndum[i]!=0) && (i<=ncovcol+nqv)){ */ + /* Tvaraff[++ij]=-10; /\* Dont'n know how to treat quantitative variables yet *\/ */ + /* }else if((Ndum[i]!=0) && (i<=ncovcol+nqv+ntv)){ */ + /* Tvaraff[++ij]=i; /\*For printing (unclear) *\/ */ + /* }else if((Ndum[i]!=0) && (i<=ncovcol+nqv+ntv+nqtv)){ */ + /* Tvaraff[++ij]=-20; /\* Dont'n know how to treat quantitative variables yet *\/ */ + } + } /* Tvaraff[1]@5 {3, 4, -20, 0, 0} Very strange */ + /* ij--; */ + /* cptcoveff=ij; /\*Number of total covariates*\/ */ + *cptcov=ij; /*Number of total real effective covariates: effective + * because they can be excluded from the model and real + * if in the model but excluded because missing values, but how to get k from ij?*/ + for(j=ij+1; j<= cptcovt; j++){ + Tvaraff[j]=0; + Tmodelind[j]=0; + } + for(j=ntveff+1; j<= cptcovt; j++){ + TmodelInvind[j]=0; + } + /* To be sorted */ + ; + } + + /*********** Health Expectancies ****************/ -void evsij(char fileres[], double ***eij, double x[], int nlstate, int stepm, int bage, int fage, double **oldm, double **savm) + 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 ) + { - /* Health expectancies */ - int i, j, nhstepm, hstepm, h; - double age, agelim,hf; + /* Health expectancies, no variances */ + int i, j, nhstepm, hstepm, h, nstepm; + int nhstepma, nstepma; /* Decreasing with age */ + double age, agelim, hf; double ***p3mat; + double eip; - FILE *ficreseij; - char filerese[FILENAMELENGTH]; - - strcpy(filerese,"e"); - strcat(filerese,fileres); - if((ficreseij=fopen(filerese,"w"))==NULL) { - printf("Problem with Health Exp. resultfile: %s\n", filerese); exit(0); - } - printf("Computing Health Expectancies: result on file '%s' \n", filerese); - - fprintf(ficreseij,"# Health expectancies\n"); + /* pstamp(ficreseij); */ + fprintf(ficreseij,"# (a) Life expectancies by health status at initial age and (b) health expectancies by health status at initial age\n"); fprintf(ficreseij,"# Age"); - for(i=1; i<=nlstate;i++) - for(j=1; j<=nlstate;j++) - fprintf(ficreseij," %1d-%1d",i,j); + for(i=1; i<=nlstate;i++){ + for(j=1; j<=nlstate;j++){ + fprintf(ficreseij," e%1d%1d ",i,j); + } + fprintf(ficreseij," e%1d. ",i); + } fprintf(ficreseij,"\n"); - hstepm=1*YEARM; /* Every j years of age (in month) */ - hstepm=hstepm/stepm; /* Typically in stepm units, if j= 2 years, = 2/6 months = 4 */ + + if(estepm < stepm){ + printf ("Problem %d lower than %d\n",estepm, stepm); + } + else hstepm=estepm; + /* We compute the life expectancy from trapezoids spaced every estepm months + * This is mainly to measure the difference between two models: for example + * if stepm=24 months pijx are given only every 2 years and by summing them + * we are calculating an estimate of the Life Expectancy assuming a linear + * progression in between and thus overestimating or underestimating according + * to the curvature of the survival function. If, for the same date, we + * estimate the model with stepm=1 month, we can keep estepm to 24 months + * to compare the new estimate of Life expectancy with the same linear + * hypothesis. A more precise result, taking into account a more precise + * curvature will be obtained if estepm is as small as stepm. */ + + /* For example we decided to compute the life expectancy with the smallest unit */ + /* hstepm beeing the number of stepms, if hstepm=1 the length of hstepm is stepm. + nhstepm is the number of hstepm from age to agelim + nstepm is the number of stepm from age to agelin. + Look at hpijx to understand the reason of that which relies in memory size + and note for a fixed period like estepm months */ + /* We decided (b) to get a life expectancy respecting the most precise curvature of the + survival function given by stepm (the optimization length). Unfortunately it + means that if the survival funtion is printed only each two years of age and if + you sum them up and add 1 year (area under the trapezoids) you won't get the same + results. So we changed our mind and took the option of the best precision. + */ + hstepm=hstepm/stepm; /* Typically in stepm units, if stepm=6 & estepm=24 , = 24/6 months = 4 */ agelim=AGESUP; - for (age=bage; age<=fage; age ++){ /* If stepm=6 months */ - /* nhstepm age range expressed in number of stepm */ - nhstepm=(int) rint((agelim-age)*YEARM/stepm); - /* Typically if 20 years = 20*12/6=40 stepm */ - if (stepm >= YEARM) hstepm=1; - nhstepm = nhstepm/hstepm;/* Expressed in hstepm, typically 40/4=10 */ - p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); + /* If stepm=6 months */ /* Computed by stepm unit matrices, product of hstepm matrices, stored in an array of nhstepm length: nhstepm=10, hstepm=4, stepm=6 months */ - hpxij(p3mat,nhstepm,age,hstepm,x,nlstate,stepm,oldm, savm); - - + +/* nhstepm age range expressed in number of stepm */ + nstepm=(int) rint((agelim-bage)*YEARM/stepm); /* Biggest nstepm */ + /* Typically if 20 years nstepm = 20*12/6=40 stepm */ + /* if (stepm >= YEARM) hstepm=1;*/ + nhstepm = nstepm/hstepm;/* Expressed in hstepm, typically nhstepm=40/4=10 */ + p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); + + for (age=bage; age<=fage; age ++){ + nstepma=(int) rint((agelim-bage)*YEARM/stepm); /* Biggest nstepm */ + /* Typically if 20 years nstepm = 20*12/6=40 stepm */ + /* if (stepm >= YEARM) hstepm=1;*/ + nhstepma = nstepma/hstepm;/* Expressed in hstepm, typically nhstepma=40/4=10 */ + + /* If stepm=6 months */ + /* Computed by stepm unit matrices, product of hstepma matrices, stored + in an array of nhstepma length: nhstepma=10, hstepm=4, stepm=6 months */ + + hpxij(p3mat,nhstepma,age,hstepm,x,nlstate,stepm,oldm, savm, cij, nres); + + hf=hstepm*stepm/YEARM; /* Duration of hstepm expressed in year unit. */ + + printf("%d|",(int)age);fflush(stdout); + fprintf(ficlog,"%d|",(int)age);fflush(ficlog); + + /* Computing expectancies */ for(i=1; i<=nlstate;i++) for(j=1; j<=nlstate;j++) - for (h=0, eij[i][j][(int)age]=0; h<=nhstepm; h++){ - eij[i][j][(int)age] +=p3mat[i][j][h]; + for (h=0, eij[i][j][(int)age]=0; h<=nhstepm-1; h++){ + eij[i][j][(int)age] += (p3mat[i][j][h]+p3mat[i][j][h+1])/2.0*hf; + + /* 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]);*/ + } - - hf=1; - if (stepm >= YEARM) hf=stepm/YEARM; - fprintf(ficreseij,"%.0f",age ); - for(i=1; i<=nlstate;i++) + + fprintf(ficreseij,"%3.0f",age ); + for(i=1; i<=nlstate;i++){ + eip=0; for(j=1; j<=nlstate;j++){ - fprintf(ficreseij," %.4f", hf*eij[i][j][(int)age]); + eip +=eij[i][j][(int)age]; + fprintf(ficreseij,"%9.4f", eij[i][j][(int)age] ); } + fprintf(ficreseij,"%9.4f", eip ); + } fprintf(ficreseij,"\n"); - free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); + } - fclose(ficreseij); + free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); + printf("\n"); + fprintf(ficlog,"\n"); + } -/************ Variance ******************/ -void varevsij(char fileres[], double ***vareij, double **matcov, double x[], double delti[], int nlstate, int stepm, double bage, double fage, double **oldm, double **savm, double **prlim, double ftolpl) + 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 ) + { - /* Variance of health expectancies */ - /* double **prevalim(double **prlim, int nlstate, double *xp, double age, double **oldm, double ** savm,double ftolpl);*/ - double **newm; + /* Covariances of health expectancies eij and of total life expectancies according + to initial status i, ei. . + */ + int i, j, nhstepm, hstepm, h, nstepm, k, cptj, cptj2, i2, j2, ij, ji; + int nhstepma, nstepma; /* Decreasing with age */ + double age, agelim, hf; + double ***p3matp, ***p3matm, ***varhe; double **dnewm,**doldm; - int i, j, nhstepm, hstepm, h; - int k; - FILE *ficresvij; - char fileresv[FILENAMELENGTH]; - double *xp; + double *xp, *xm; double **gp, **gm; double ***gradg, ***trgradg; - double ***p3mat; - double age,agelim; int theta; - strcpy(fileresv,"v"); - strcat(fileresv,fileres); - if((ficresvij=fopen(fileresv,"w"))==NULL) { - printf("Problem with variance resultfile: %s\n", fileresv);exit(0); - } - printf("Computing Variance-covariance of DFLEs: file '%s' \n", fileresv); - + double eip, vip; - fprintf(ficresvij,"# Covariances of life expectancies\n"); - fprintf(ficresvij,"# Age"); - for(i=1; i<=nlstate;i++) + varhe=ma3x(1,nlstate*nlstate,1,nlstate*nlstate,(int) bage, (int) fage); + xp=vector(1,npar); + xm=vector(1,npar); + dnewm=matrix(1,nlstate*nlstate,1,npar); + doldm=matrix(1,nlstate*nlstate,1,nlstate*nlstate); + + pstamp(ficresstdeij); + fprintf(ficresstdeij,"# Health expectancies with standard errors\n"); + fprintf(ficresstdeij,"# Age"); + for(i=1; i<=nlstate;i++){ for(j=1; j<=nlstate;j++) - fprintf(ficresvij," Cov(e%1d, e%1d)",i,j); - fprintf(ficresvij,"\n"); + fprintf(ficresstdeij," e%1d%1d (SE)",i,j); + fprintf(ficresstdeij," e%1d. ",i); + } + fprintf(ficresstdeij,"\n"); - xp=vector(1,npar); - dnewm=matrix(1,nlstate,1,npar); - doldm=matrix(1,nlstate,1,nlstate); + pstamp(ficrescveij); + fprintf(ficrescveij,"# Subdiagonal matrix of covariances of health expectancies by age: cov(eij,ekl)\n"); + fprintf(ficrescveij,"# Age"); + for(i=1; i<=nlstate;i++) + for(j=1; j<=nlstate;j++){ + cptj= (j-1)*nlstate+i; + for(i2=1; i2<=nlstate;i2++) + for(j2=1; j2<=nlstate;j2++){ + cptj2= (j2-1)*nlstate+i2; + if(cptj2 <= cptj) + fprintf(ficrescveij," %1d%1d,%1d%1d",i,j,i2,j2); + } + } + fprintf(ficrescveij,"\n"); - hstepm=1*YEARM; /* Every year of age */ - hstepm=hstepm/stepm; /* Typically in stepm units, if j= 2 years, = 2/6 months = 4 */ - agelim = AGESUP; - for (age=bage; age<=fage; age ++){ /* If stepm=6 months */ - nhstepm=(int) rint((agelim-age)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */ - if (stepm >= YEARM) hstepm=1; - nhstepm = nhstepm/hstepm; /* Typically 40/4=10 */ - p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); - gradg=ma3x(0,nhstepm,1,npar,1,nlstate); - gp=matrix(0,nhstepm,1,nlstate); - gm=matrix(0,nhstepm,1,nlstate); + if(estepm < stepm){ + printf ("Problem %d lower than %d\n",estepm, stepm); + } + else hstepm=estepm; + /* We compute the life expectancy from trapezoids spaced every estepm months + * This is mainly to measure the difference between two models: for example + * if stepm=24 months pijx are given only every 2 years and by summing them + * we are calculating an estimate of the Life Expectancy assuming a linear + * progression in between and thus overestimating or underestimating according + * to the curvature of the survival function. If, for the same date, we + * estimate the model with stepm=1 month, we can keep estepm to 24 months + * to compare the new estimate of Life expectancy with the same linear + * hypothesis. A more precise result, taking into account a more precise + * curvature will be obtained if estepm is as small as stepm. */ + + /* For example we decided to compute the life expectancy with the smallest unit */ + /* hstepm beeing the number of stepms, if hstepm=1 the length of hstepm is stepm. + nhstepm is the number of hstepm from age to agelim + nstepm is the number of stepm from age to agelin. + Look at hpijx to understand the reason of that which relies in memory size + and note for a fixed period like estepm months */ + /* We decided (b) to get a life expectancy respecting the most precise curvature of the + survival function given by stepm (the optimization length). Unfortunately it + means that if the survival funtion is printed only each two years of age and if + you sum them up and add 1 year (area under the trapezoids) you won't get the same + results. So we changed our mind and took the option of the best precision. + */ + hstepm=hstepm/stepm; /* Typically in stepm units, if stepm=6 & estepm=24 , = 24/6 months = 4 */ + /* If stepm=6 months */ + /* nhstepm age range expressed in number of stepm */ + agelim=AGESUP; + nstepm=(int) rint((agelim-bage)*YEARM/stepm); + /* Typically if 20 years nstepm = 20*12/6=40 stepm */ + /* if (stepm >= YEARM) hstepm=1;*/ + nhstepm = nstepm/hstepm;/* Expressed in hstepm, typically nhstepm=40/4=10 */ + + p3matp=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); + p3matm=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); + gradg=ma3x(0,nhstepm,1,npar,1,nlstate*nlstate); + trgradg =ma3x(0,nhstepm,1,nlstate*nlstate,1,npar); + gp=matrix(0,nhstepm,1,nlstate*nlstate); + gm=matrix(0,nhstepm,1,nlstate*nlstate); + + for (age=bage; age<=fage; age ++){ + nstepma=(int) rint((agelim-bage)*YEARM/stepm); /* Biggest nstepm */ + /* Typically if 20 years nstepm = 20*12/6=40 stepm */ + /* if (stepm >= YEARM) hstepm=1;*/ + nhstepma = nstepma/hstepm;/* Expressed in hstepm, typically nhstepma=40/4=10 */ + + /* If stepm=6 months */ + /* Computed by stepm unit matrices, product of hstepma matrices, stored + in an array of nhstepma length: nhstepma=10, hstepm=4, stepm=6 months */ + + hf=hstepm*stepm/YEARM; /* Duration of hstepm expressed in year unit. */ + + /* Computing Variances of health expectancies */ + /* Gradient is computed with plus gp and minus gm. Code is duplicated in order to + decrease memory allocation */ for(theta=1; theta <=npar; theta++){ - for(i=1; i<=npar; i++){ /* Computes gradient */ + for(i=1; i<=npar; i++){ xp[i] = x[i] + (i==theta ?delti[theta]:0); + xm[i] = x[i] - (i==theta ?delti[theta]:0); } - hpxij(p3mat,nhstepm,age,hstepm,xp,nlstate,stepm,oldm,savm); - prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl); - for(j=1; j<= nlstate; j++){ - for(h=0; h<=nhstepm; h++){ - for(i=1, gp[h][j]=0.;i<=nlstate;i++) - gp[h][j] += prlim[i][i]*p3mat[i][j][h]; - } - } - - for(i=1; i<=npar; i++) /* Computes gradient */ - xp[i] = x[i] - (i==theta ?delti[theta]:0); - hpxij(p3mat,nhstepm,age,hstepm,xp,nlstate,stepm,oldm,savm); - prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl); + hpxij(p3matp,nhstepm,age,hstepm,xp,nlstate,stepm,oldm,savm, cij, nres); + hpxij(p3matm,nhstepm,age,hstepm,xm,nlstate,stepm,oldm,savm, cij, nres); + for(j=1; j<= nlstate; j++){ - for(h=0; h<=nhstepm; h++){ - for(i=1, gm[h][j]=0.;i<=nlstate;i++) - gm[h][j] += prlim[i][i]*p3mat[i][j][h]; + for(i=1; i<=nlstate; i++){ + for(h=0; h<=nhstepm-1; h++){ + gp[h][(j-1)*nlstate + i] = (p3matp[i][j][h]+p3matp[i][j][h+1])/2.; + gm[h][(j-1)*nlstate + i] = (p3matm[i][j][h]+p3matm[i][j][h+1])/2.; + } } } - for(j=1; j<= nlstate; j++) - for(h=0; h<=nhstepm; h++){ - gradg[h][theta][j]= (gp[h][j]-gm[h][j])/2./delti[theta]; + + for(ij=1; ij<= nlstate*nlstate; ij++) + for(h=0; h<=nhstepm-1; h++){ + gradg[h][theta][ij]= (gp[h][ij]-gm[h][ij])/2./delti[theta]; } - } /* End theta */ - - trgradg =ma3x(0,nhstepm,1,nlstate,1,npar); - - for(h=0; h<=nhstepm; h++) - for(j=1; j<=nlstate;j++) + }/* End theta */ + + + for(h=0; h<=nhstepm-1; h++) + for(j=1; j<=nlstate*nlstate;j++) for(theta=1; theta <=npar; theta++) trgradg[h][j][theta]=gradg[h][theta][j]; - - for(i=1;i<=nlstate;i++) - for(j=1;j<=nlstate;j++) - vareij[i][j][(int)age] =0.; - for(h=0;h<=nhstepm;h++){ - for(k=0;k<=nhstepm;k++){ - matprod2(dnewm,trgradg[h],1,nlstate,1,npar,1,npar,matcov); - matprod2(doldm,dnewm,1,nlstate,1,npar,1,nlstate,gradg[k]); - for(i=1;i<=nlstate;i++) - for(j=1;j<=nlstate;j++) - vareij[i][j][(int)age] += doldm[i][j]; + + + for(ij=1;ij<=nlstate*nlstate;ij++) + for(ji=1;ji<=nlstate*nlstate;ji++) + varhe[ij][ji][(int)age] =0.; + + printf("%d|",(int)age);fflush(stdout); + fprintf(ficlog,"%d|",(int)age);fflush(ficlog); + for(h=0;h<=nhstepm-1;h++){ + for(k=0;k<=nhstepm-1;k++){ + matprod2(dnewm,trgradg[h],1,nlstate*nlstate,1,npar,1,npar,matcov); + matprod2(doldm,dnewm,1,nlstate*nlstate,1,npar,1,nlstate*nlstate,gradg[k]); + for(ij=1;ij<=nlstate*nlstate;ij++) + for(ji=1;ji<=nlstate*nlstate;ji++) + varhe[ij][ji][(int)age] += doldm[ij][ji]*hf*hf; } } - h=1; - if (stepm >= YEARM) h=stepm/YEARM; - fprintf(ficresvij,"%.0f ",age ); + + /* Computing expectancies */ + hpxij(p3matm,nhstepm,age,hstepm,x,nlstate,stepm,oldm, savm, cij,nres); for(i=1; i<=nlstate;i++) + for(j=1; j<=nlstate;j++) + for (h=0, eij[i][j][(int)age]=0; h<=nhstepm-1; h++){ + eij[i][j][(int)age] += (p3matm[i][j][h]+p3matm[i][j][h+1])/2.0*hf; + + /* 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]);*/ + + } + + fprintf(ficresstdeij,"%3.0f",age ); + for(i=1; i<=nlstate;i++){ + eip=0.; + vip=0.; for(j=1; j<=nlstate;j++){ - fprintf(ficresvij," %.4f", h*vareij[i][j][(int)age]); + eip += eij[i][j][(int)age]; + for(k=1; k<=nlstate;k++) /* Sum on j and k of cov(eij,eik) */ + vip += varhe[(j-1)*nlstate+i][(k-1)*nlstate+i][(int)age]; + fprintf(ficresstdeij," %9.4f (%.4f)", eij[i][j][(int)age], sqrt(varhe[(j-1)*nlstate+i][(j-1)*nlstate+i][(int)age]) ); } - fprintf(ficresvij,"\n"); - free_matrix(gp,0,nhstepm,1,nlstate); - free_matrix(gm,0,nhstepm,1,nlstate); - free_ma3x(gradg,0,nhstepm,1,npar,1,nlstate); - free_ma3x(trgradg,0,nhstepm,1,nlstate,1,npar); - free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); - } /* End age */ - fclose(ficresvij); + fprintf(ficresstdeij," %9.4f (%.4f)", eip, sqrt(vip)); + } + fprintf(ficresstdeij,"\n"); + + fprintf(ficrescveij,"%3.0f",age ); + for(i=1; i<=nlstate;i++) + for(j=1; j<=nlstate;j++){ + cptj= (j-1)*nlstate+i; + for(i2=1; i2<=nlstate;i2++) + for(j2=1; j2<=nlstate;j2++){ + cptj2= (j2-1)*nlstate+i2; + if(cptj2 <= cptj) + fprintf(ficrescveij," %.4f", varhe[cptj][cptj2][(int)age]); + } + } + fprintf(ficrescveij,"\n"); + + } + free_matrix(gm,0,nhstepm,1,nlstate*nlstate); + free_matrix(gp,0,nhstepm,1,nlstate*nlstate); + free_ma3x(gradg,0,nhstepm,1,npar,1,nlstate*nlstate); + free_ma3x(trgradg,0,nhstepm,1,nlstate*nlstate,1,npar); + free_ma3x(p3matm,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); + free_ma3x(p3matp,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); + printf("\n"); + fprintf(ficlog,"\n"); + + free_vector(xm,1,npar); free_vector(xp,1,npar); - free_matrix(doldm,1,nlstate,1,npar); - free_matrix(dnewm,1,nlstate,1,nlstate); - + free_matrix(dnewm,1,nlstate*nlstate,1,npar); + free_matrix(doldm,1,nlstate*nlstate,1,nlstate*nlstate); + free_ma3x(varhe,1,nlstate*nlstate,1,nlstate*nlstate,(int) bage, (int)fage); } + +/************ Variance ******************/ + 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) + { + /* Variance of health expectancies */ + /* double **prevalim(double **prlim, int nlstate, double *xp, double age, double **oldm, double ** savm,double ftolpl);*/ + /* double **newm;*/ + /* int movingaverage(double ***probs, double bage,double fage, double ***mobaverage, int mobilav)*/ + + /* int movingaverage(); */ + double **dnewm,**doldm; + double **dnewmp,**doldmp; + int i, j, nhstepm, hstepm, h, nstepm ; + int k; + double *xp; + double **gp, **gm; /* for var eij */ + double ***gradg, ***trgradg; /*for var eij */ + double **gradgp, **trgradgp; /* for var p point j */ + double *gpp, *gmp; /* for var p point j */ + double **varppt; /* for var p point j nlstate to nlstate+ndeath */ + double ***p3mat; + double age,agelim, hf; + /* double ***mobaverage; */ + int theta; + char digit[4]; + char digitp[25]; + + char fileresprobmorprev[FILENAMELENGTH]; + + if(popbased==1){ + if(mobilav!=0) + strcpy(digitp,"-POPULBASED-MOBILAV_"); + else strcpy(digitp,"-POPULBASED-NOMOBIL_"); + } + else + strcpy(digitp,"-STABLBASED_"); + + /* if (mobilav!=0) { */ + /* mobaverage= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */ + /* if (movingaverage(probs, bage, fage, mobaverage,mobilav)!=0){ */ + /* fprintf(ficlog," Error in movingaverage mobilav=%d\n",mobilav); */ + /* printf(" Error in movingaverage mobilav=%d\n",mobilav); */ + /* } */ + /* } */ + + strcpy(fileresprobmorprev,"PRMORPREV-"); + sprintf(digit,"%-d",ij); + /*printf("DIGIT=%s, ij=%d ijr=%-d|\n",digit, ij,ij);*/ + strcat(fileresprobmorprev,digit); /* Tvar to be done */ + strcat(fileresprobmorprev,digitp); /* Popbased or not, mobilav or not */ + strcat(fileresprobmorprev,fileresu); + if((ficresprobmorprev=fopen(fileresprobmorprev,"w"))==NULL) { + printf("Problem with resultfile: %s\n", fileresprobmorprev); + fprintf(ficlog,"Problem with resultfile: %s\n", fileresprobmorprev); + } + printf("Computing total mortality p.j=w1*p1j+w2*p2j+..: result on file '%s' \n",fileresprobmorprev); + fprintf(ficlog,"Computing total mortality p.j=w1*p1j+w2*p2j+..: result on file '%s' \n",fileresprobmorprev); + pstamp(ficresprobmorprev); + 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); + fprintf(ficresprobmorprev,"# Selected quantitative variables and dummies"); + for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */ + fprintf(ficresprobmorprev," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]); + } + for(j=1;j<=cptcoveff;j++) + fprintf(ficresprobmorprev,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(ij,j)]); + fprintf(ficresprobmorprev,"\n"); + + fprintf(ficresprobmorprev,"# Age cov=%-d",ij); + for(j=nlstate+1; j<=(nlstate+ndeath);j++){ + fprintf(ficresprobmorprev," p.%-d SE",j); + for(i=1; i<=nlstate;i++) + fprintf(ficresprobmorprev," w%1d p%-d%-d",i,i,j); + } + fprintf(ficresprobmorprev,"\n"); + + fprintf(ficgp,"\n# Routine varevsij"); + fprintf(ficgp,"\nunset title \n"); + /* fprintf(fichtm, "#Local time at start: %s", strstart);*/ + fprintf(fichtm,"\n
  • Computing probabilities of dying over estepm months as a weighted average (i.e global mortality independent of initial healh state)

  • \n"); + fprintf(fichtm,"\n
    %s
    \n",digitp); + /* } */ + varppt = matrix(nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath); + pstamp(ficresvij); + fprintf(ficresvij,"# Variance and covariance of health expectancies e.j \n# (weighted average of eij where weights are "); + if(popbased==1) + 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); + else + fprintf(ficresvij,"the age specific period (stable) prevalences in each health state \n"); + fprintf(ficresvij,"# Age"); + for(i=1; i<=nlstate;i++) + for(j=1; j<=nlstate;j++) + fprintf(ficresvij," Cov(e.%1d, e.%1d)",i,j); + fprintf(ficresvij,"\n"); + + xp=vector(1,npar); + dnewm=matrix(1,nlstate,1,npar); + doldm=matrix(1,nlstate,1,nlstate); + dnewmp= matrix(nlstate+1,nlstate+ndeath,1,npar); + doldmp= matrix(nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath); + + gradgp=matrix(1,npar,nlstate+1,nlstate+ndeath); + gpp=vector(nlstate+1,nlstate+ndeath); + gmp=vector(nlstate+1,nlstate+ndeath); + trgradgp =matrix(nlstate+1,nlstate+ndeath,1,npar); /* mu or p point j*/ + + if(estepm < stepm){ + printf ("Problem %d lower than %d\n",estepm, stepm); + } + else hstepm=estepm; + /* For example we decided to compute the life expectancy with the smallest unit */ + /* hstepm beeing the number of stepms, if hstepm=1 the length of hstepm is stepm. + nhstepm is the number of hstepm from age to agelim + nstepm is the number of stepm from age to agelim. + Look at function hpijx to understand why because of memory size limitations, + we decided (b) to get a life expectancy respecting the most precise curvature of the + survival function given by stepm (the optimization length). Unfortunately it + means that if the survival funtion is printed every two years of age and if + you sum them up and add 1 year (area under the trapezoids) you won't get the same + results. So we changed our mind and took the option of the best precision. + */ + hstepm=hstepm/stepm; /* Typically in stepm units, if stepm=6 & estepm=24 , = 24/6 months = 4 */ + agelim = AGESUP; + for (age=bage; age<=fage; age ++){ /* If stepm=6 months */ + nstepm=(int) rint((agelim-age)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */ + nhstepm = nstepm/hstepm;/* Expressed in hstepm, typically nhstepm=40/4=10 */ + p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); + gradg=ma3x(0,nhstepm,1,npar,1,nlstate); + gp=matrix(0,nhstepm,1,nlstate); + gm=matrix(0,nhstepm,1,nlstate); + + + for(theta=1; theta <=npar; theta++){ + for(i=1; i<=npar; i++){ /* Computes gradient x + delta*/ + xp[i] = x[i] + (i==theta ?delti[theta]:0); + } + + prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij, nres); + + if (popbased==1) { + if(mobilav ==0){ + for(i=1; i<=nlstate;i++) + prlim[i][i]=probs[(int)age][i][ij]; + }else{ /* mobilav */ + for(i=1; i<=nlstate;i++) + prlim[i][i]=mobaverage[(int)age][i][ij]; + } + } + + hpxij(p3mat,nhstepm,age,hstepm,xp,nlstate,stepm,oldm,savm, ij,nres); /* Returns p3mat[i][j][h] for h=1 to nhstepm */ + for(j=1; j<= nlstate; j++){ + for(h=0; h<=nhstepm; h++){ + for(i=1, gp[h][j]=0.;i<=nlstate;i++) + gp[h][j] += prlim[i][i]*p3mat[i][j][h]; + } + } + /* Next for computing probability of death (h=1 means + computed over hstepm matrices product = hstepm*stepm months) + as a weighted average of prlim. + */ + for(j=nlstate+1;j<=nlstate+ndeath;j++){ + for(i=1,gpp[j]=0.; i<= nlstate; i++) + gpp[j] += prlim[i][i]*p3mat[i][j][1]; + } + /* end probability of death */ + + for(i=1; i<=npar; i++) /* Computes gradient x - delta */ + xp[i] = x[i] - (i==theta ?delti[theta]:0); + + prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp, ij, nres); + + if (popbased==1) { + if(mobilav ==0){ + for(i=1; i<=nlstate;i++) + prlim[i][i]=probs[(int)age][i][ij]; + }else{ /* mobilav */ + for(i=1; i<=nlstate;i++) + prlim[i][i]=mobaverage[(int)age][i][ij]; + } + } + + hpxij(p3mat,nhstepm,age,hstepm,xp,nlstate,stepm,oldm,savm, ij,nres); + + for(j=1; j<= nlstate; j++){ /* Sum of wi * eij = e.j */ + for(h=0; h<=nhstepm; h++){ + for(i=1, gm[h][j]=0.;i<=nlstate;i++) + gm[h][j] += prlim[i][i]*p3mat[i][j][h]; + } + } + /* This for computing probability of death (h=1 means + computed over hstepm matrices product = hstepm*stepm months) + as a weighted average of prlim. + */ + for(j=nlstate+1;j<=nlstate+ndeath;j++){ + for(i=1,gmp[j]=0.; i<= nlstate; i++) + gmp[j] += prlim[i][i]*p3mat[i][j][1]; + } + /* end probability of death */ + + for(j=1; j<= nlstate; j++) /* vareij */ + for(h=0; h<=nhstepm; h++){ + gradg[h][theta][j]= (gp[h][j]-gm[h][j])/2./delti[theta]; + } + + for(j=nlstate+1; j<= nlstate+ndeath; j++){ /* var mu */ + gradgp[theta][j]= (gpp[j]-gmp[j])/2./delti[theta]; + } + + } /* End theta */ + + trgradg =ma3x(0,nhstepm,1,nlstate,1,npar); /* veij */ + + for(h=0; h<=nhstepm; h++) /* veij */ + for(j=1; j<=nlstate;j++) + for(theta=1; theta <=npar; theta++) + trgradg[h][j][theta]=gradg[h][theta][j]; + + for(j=nlstate+1; j<=nlstate+ndeath;j++) /* mu */ + for(theta=1; theta <=npar; theta++) + trgradgp[j][theta]=gradgp[theta][j]; + + + hf=hstepm*stepm/YEARM; /* Duration of hstepm expressed in year unit. */ + for(i=1;i<=nlstate;i++) + for(j=1;j<=nlstate;j++) + vareij[i][j][(int)age] =0.; + + for(h=0;h<=nhstepm;h++){ + for(k=0;k<=nhstepm;k++){ + matprod2(dnewm,trgradg[h],1,nlstate,1,npar,1,npar,matcov); + matprod2(doldm,dnewm,1,nlstate,1,npar,1,nlstate,gradg[k]); + for(i=1;i<=nlstate;i++) + for(j=1;j<=nlstate;j++) + vareij[i][j][(int)age] += doldm[i][j]*hf*hf; + } + } + + /* pptj */ + matprod2(dnewmp,trgradgp,nlstate+1,nlstate+ndeath,1,npar,1,npar,matcov); + matprod2(doldmp,dnewmp,nlstate+1,nlstate+ndeath,1,npar,nlstate+1,nlstate+ndeath,gradgp); + for(j=nlstate+1;j<=nlstate+ndeath;j++) + for(i=nlstate+1;i<=nlstate+ndeath;i++) + varppt[j][i]=doldmp[j][i]; + /* end ppptj */ + /* x centered again */ + + prevalim(prlim,nlstate,x,age,oldm,savm,ftolpl,ncvyearp,ij, nres); + + if (popbased==1) { + if(mobilav ==0){ + for(i=1; i<=nlstate;i++) + prlim[i][i]=probs[(int)age][i][ij]; + }else{ /* mobilav */ + for(i=1; i<=nlstate;i++) + prlim[i][i]=mobaverage[(int)age][i][ij]; + } + } + + /* This for computing probability of death (h=1 means + computed over hstepm (estepm) matrices product = hstepm*stepm months) + as a weighted average of prlim. + */ + hpxij(p3mat,nhstepm,age,hstepm,x,nlstate,stepm,oldm,savm, ij, nres); + for(j=nlstate+1;j<=nlstate+ndeath;j++){ + for(i=1,gmp[j]=0.;i<= nlstate; i++) + gmp[j] += prlim[i][i]*p3mat[i][j][1]; + } + /* end probability of death */ + + fprintf(ficresprobmorprev,"%3d %d ",(int) age, ij); + for(j=nlstate+1; j<=(nlstate+ndeath);j++){ + fprintf(ficresprobmorprev," %11.3e %11.3e",gmp[j], sqrt(varppt[j][j])); + for(i=1; i<=nlstate;i++){ + fprintf(ficresprobmorprev," %11.3e %11.3e ",prlim[i][i],p3mat[i][j][1]); + } + } + fprintf(ficresprobmorprev,"\n"); + + fprintf(ficresvij,"%.0f ",age ); + for(i=1; i<=nlstate;i++) + for(j=1; j<=nlstate;j++){ + fprintf(ficresvij," %.4f", vareij[i][j][(int)age]); + } + fprintf(ficresvij,"\n"); + free_matrix(gp,0,nhstepm,1,nlstate); + free_matrix(gm,0,nhstepm,1,nlstate); + free_ma3x(gradg,0,nhstepm,1,npar,1,nlstate); + free_ma3x(trgradg,0,nhstepm,1,nlstate,1,npar); + free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); + } /* End age */ + free_vector(gpp,nlstate+1,nlstate+ndeath); + free_vector(gmp,nlstate+1,nlstate+ndeath); + free_matrix(gradgp,1,npar,nlstate+1,nlstate+ndeath); + free_matrix(trgradgp,nlstate+1,nlstate+ndeath,1,npar); /* mu or p point j*/ + /* fprintf(ficgp,"\nunset parametric;unset label; set ter png small size 320, 240"); */ + fprintf(ficgp,"\nunset parametric;unset label; set ter svg size 640, 480"); + /* for(j=nlstate+1; j<= nlstate+ndeath; j++){ *//* Only the first actually */ + fprintf(ficgp,"\n set log y; unset log x;set xlabel \"Age\"; set ylabel \"Force of mortality (year-1)\";"); + fprintf(ficgp,"\nset out \"%s%s.svg\";",subdirf3(optionfilefiname,"VARMUPTJGR-",digitp),digit); + /* fprintf(ficgp,"\n plot \"%s\" u 1:($3*%6.3f) not w l 1 ",fileresprobmorprev,YEARM/estepm); */ + /* fprintf(ficgp,"\n replot \"%s\" u 1:(($3+1.96*$4)*%6.3f) t \"95\%% interval\" w l 2 ",fileresprobmorprev,YEARM/estepm); */ + /* fprintf(ficgp,"\n replot \"%s\" u 1:(($3-1.96*$4)*%6.3f) not w l 2 ",fileresprobmorprev,YEARM/estepm); */ + fprintf(ficgp,"\n plot \"%s\" u 1:($3) not w l lt 1 ",subdirf(fileresprobmorprev)); + fprintf(ficgp,"\n replot \"%s\" u 1:(($3+1.96*$4)) t \"95%% interval\" w l lt 2 ",subdirf(fileresprobmorprev)); + fprintf(ficgp,"\n replot \"%s\" u 1:(($3-1.96*$4)) not w l lt 2 ",subdirf(fileresprobmorprev)); + fprintf(fichtm,"\n
    File (multiple files are possible if covariates are present): %s\n",subdirf(fileresprobmorprev),subdirf(fileresprobmorprev)); + fprintf(fichtm,"\n
    Probability is computed over estepm=%d months.

    \n", estepm,subdirf3(optionfilefiname,"VARMUPTJGR-",digitp),digit); + /* fprintf(fichtm,"\n
    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

    \n", stepm,YEARM,digitp,digit); + */ + /* fprintf(ficgp,"\nset out \"varmuptjgr%s%s%s.svg\";replot;",digitp,optionfilefiname,digit); */ + fprintf(ficgp,"\nset out;\nset out \"%s%s.svg\";replot;set out;\n",subdirf3(optionfilefiname,"VARMUPTJGR-",digitp),digit); + + free_vector(xp,1,npar); + free_matrix(doldm,1,nlstate,1,nlstate); + free_matrix(dnewm,1,nlstate,1,npar); + free_matrix(doldmp,nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath); + free_matrix(dnewmp,nlstate+1,nlstate+ndeath,1,npar); + free_matrix(varppt,nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath); + /* if (mobilav!=0) free_ma3x(mobaverage,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */ + fclose(ficresprobmorprev); + fflush(ficgp); + fflush(fichtm); + } /* end varevsij */ /************ Variance of prevlim ******************/ -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) + 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) { - /* Variance of health expectancies */ - /* double **prevalim(double **prlim, int nlstate, double *xp, double age, double **oldm, double ** savm,double ftolpl);*/ - double **newm; + /* Variance of prevalence limit for each state ij using current parameters x[] and estimates of neighbourhood give by delti*/ + /* double **prevalim(double **prlim, int nlstate, double *xp, double age, double **oldm, double **savm,double ftolpl);*/ + double **dnewm,**doldm; int i, j, nhstepm, hstepm; - int k; - FILE *ficresvpl; - char fileresvpl[FILENAMELENGTH]; double *xp; double *gp, *gm; double **gradg, **trgradg; + double **mgm, **mgp; double age,agelim; int theta; - - strcpy(fileresvpl,"vpl"); - strcat(fileresvpl,fileres); - if((ficresvpl=fopen(fileresvpl,"w"))==NULL) { - printf("Problem with variance prev lim resultfile: %s\n", fileresvpl); - exit(0); - } - printf("Computing Variance-covariance of Prevalence limit: file '%s' \n", fileresvpl); - - - fprintf(ficresvpl,"# Standard deviation of prevalences limit\n"); - fprintf(ficresvpl,"# Age"); + + pstamp(ficresvpl); + fprintf(ficresvpl,"# Standard deviation of period (stable) prevalences \n"); + fprintf(ficresvpl,"# Age "); + if(nresult >=1) + fprintf(ficresvpl," Result# "); for(i=1; i<=nlstate;i++) fprintf(ficresvpl," %1d-%1d",i,i); fprintf(ficresvpl,"\n"); @@ -1443,6 +5929,8 @@ void varprevlim(char fileres[], double * if (stepm >= YEARM) hstepm=1; nhstepm = nhstepm/hstepm; /* Typically 40/4=10 */ gradg=matrix(1,npar,1,nlstate); + mgp=matrix(1,npar,1,nlstate); + mgm=matrix(1,npar,1,nlstate); gp=vector(1,nlstate); gm=vector(1,nlstate); @@ -1450,18 +5938,27 @@ void varprevlim(char fileres[], double * for(i=1; i<=npar; i++){ /* Computes gradient */ xp[i] = x[i] + (i==theta ?delti[theta]:0); } - prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl); - for(i=1;i<=nlstate;i++) + if((int)age==79 ||(int)age== 80 ||(int)age== 81 ) + prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres); + else + prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres); + for(i=1;i<=nlstate;i++){ gp[i] = prlim[i][i]; - + mgp[theta][i] = prlim[i][i]; + } for(i=1; i<=npar; i++) /* Computes gradient */ xp[i] = x[i] - (i==theta ?delti[theta]:0); - prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl); - for(i=1;i<=nlstate;i++) + if((int)age==79 ||(int)age== 80 ||(int)age== 81 ) + prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres); + else + prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres); + for(i=1;i<=nlstate;i++){ gm[i] = prlim[i][i]; - + mgm[theta][i] = prlim[i][i]; + } for(i=1;i<=nlstate;i++) gradg[theta][i]= (gp[i]-gm[i])/2./delti[theta]; + /* gradg[theta][2]= -gradg[theta][1]; */ /* For testing if nlstate=2 */ } /* End theta */ trgradg =matrix(1,nlstate,1,npar); @@ -1469,747 +5966,5829 @@ void varprevlim(char fileres[], double * for(j=1; j<=nlstate;j++) for(theta=1; theta <=npar; theta++) trgradg[j][theta]=gradg[theta][j]; + /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */ + /* printf("\nmgm mgp %d ",(int)age); */ + /* for(j=1; j<=nlstate;j++){ */ + /* printf(" %d ",j); */ + /* for(theta=1; theta <=npar; theta++) */ + /* printf(" %d %lf %lf",theta,mgm[theta][j],mgp[theta][j]); */ + /* printf("\n "); */ + /* } */ + /* } */ + /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */ + /* printf("\n gradg %d ",(int)age); */ + /* for(j=1; j<=nlstate;j++){ */ + /* printf("%d ",j); */ + /* for(theta=1; theta <=npar; theta++) */ + /* printf("%d %lf ",theta,gradg[theta][j]); */ + /* printf("\n "); */ + /* } */ + /* } */ for(i=1;i<=nlstate;i++) varpl[i][(int)age] =0.; + if((int)age==79 ||(int)age== 80 ||(int)age== 81){ matprod2(dnewm,trgradg,1,nlstate,1,npar,1,npar,matcov); matprod2(doldm,dnewm,1,nlstate,1,npar,1,nlstate,gradg); + }else{ + matprod2(dnewm,trgradg,1,nlstate,1,npar,1,npar,matcov); + matprod2(doldm,dnewm,1,nlstate,1,npar,1,nlstate,gradg); + } for(i=1;i<=nlstate;i++) varpl[i][(int)age] = doldm[i][i]; /* Covariances are useless */ fprintf(ficresvpl,"%.0f ",age ); + if(nresult >=1) + fprintf(ficresvpl,"%d ",nres ); for(i=1; i<=nlstate;i++) fprintf(ficresvpl," %.5f (%.5f)",prlim[i][i],sqrt(varpl[i][(int)age])); fprintf(ficresvpl,"\n"); free_vector(gp,1,nlstate); free_vector(gm,1,nlstate); + free_matrix(mgm,1,npar,1,nlstate); + free_matrix(mgp,1,npar,1,nlstate); free_matrix(gradg,1,npar,1,nlstate); free_matrix(trgradg,1,nlstate,1,npar); } /* End age */ - fclose(ficresvpl); + free_vector(xp,1,npar); free_matrix(doldm,1,nlstate,1,npar); free_matrix(dnewm,1,nlstate,1,nlstate); } - - -/***********************************************/ -/**************** Main Program *****************/ -/***********************************************/ - -/*int main(int argc, char *argv[])*/ -int main() -{ - - int i,j, k, n=MAXN,iter,m,size; - double agedeb, agefin,hf; - double agemin=1.e20, agemax=-1.e20; - - double fret; - double **xi,tmp,delta; - - double dum; /* Dummy variable */ - double ***p3mat; - int *indx; - char line[MAXLINE], linepar[MAXLINE]; - char title[MAXLINE]; - char optionfile[FILENAMELENGTH], datafile[FILENAMELENGTH], filerespl[FILENAMELENGTH]; - char fileres[FILENAMELENGTH], filerespij[FILENAMELENGTH], filereso[FILENAMELENGTH]; - char filerest[FILENAMELENGTH]; - char fileregp[FILENAMELENGTH]; - char path[80],pathc[80],pathcd[80],pathtot[80]; - int firstobs=1, lastobs=10; - int sdeb, sfin; /* Status at beginning and end */ - int c, h , cpt,l; - int ju,jl, mi; - int i1,j1, k1,jk,aa,bb, stepsize; - int jnais,jdc,jint4,jint1,jint2,jint3,**outcome,**adl,*tab; +/************ Variance of one-step probabilities ******************/ +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[]) + { + int i, j=0, k1, l1, tj; + int k2, l2, j1, z1; + int k=0, l; + int first=1, first1, first2; + double cv12, mu1, mu2, lc1, lc2, v12, v21, v11, v22,v1,v2, c12, tnalp; + double **dnewm,**doldm; + double *xp; + double *gp, *gm; + double **gradg, **trgradg; + double **mu; + double age, cov[NCOVMAX+1]; + double std=2.0; /* Number of standard deviation wide of confidence ellipsoids */ + int theta; + char fileresprob[FILENAMELENGTH]; + char fileresprobcov[FILENAMELENGTH]; + char fileresprobcor[FILENAMELENGTH]; + double ***varpij; + + strcpy(fileresprob,"PROB_"); + strcat(fileresprob,fileres); + if((ficresprob=fopen(fileresprob,"w"))==NULL) { + printf("Problem with resultfile: %s\n", fileresprob); + fprintf(ficlog,"Problem with resultfile: %s\n", fileresprob); + } + strcpy(fileresprobcov,"PROBCOV_"); + strcat(fileresprobcov,fileresu); + if((ficresprobcov=fopen(fileresprobcov,"w"))==NULL) { + printf("Problem with resultfile: %s\n", fileresprobcov); + fprintf(ficlog,"Problem with resultfile: %s\n", fileresprobcov); + } + strcpy(fileresprobcor,"PROBCOR_"); + strcat(fileresprobcor,fileresu); + if((ficresprobcor=fopen(fileresprobcor,"w"))==NULL) { + printf("Problem with resultfile: %s\n", fileresprobcor); + fprintf(ficlog,"Problem with resultfile: %s\n", fileresprobcor); + } + printf("Computing standard deviation of one-step probabilities: result on file '%s' \n",fileresprob); + fprintf(ficlog,"Computing standard deviation of one-step probabilities: result on file '%s' \n",fileresprob); + printf("Computing matrix of variance covariance of one-step probabilities: result on file '%s' \n",fileresprobcov); + fprintf(ficlog,"Computing matrix of variance covariance of one-step probabilities: result on file '%s' \n",fileresprobcov); + printf("and correlation matrix of one-step probabilities: result on file '%s' \n",fileresprobcor); + fprintf(ficlog,"and correlation matrix of one-step probabilities: result on file '%s' \n",fileresprobcor); + pstamp(ficresprob); + fprintf(ficresprob,"#One-step probabilities and stand. devi in ()\n"); + fprintf(ficresprob,"# Age"); + pstamp(ficresprobcov); + fprintf(ficresprobcov,"#One-step probabilities and covariance matrix\n"); + fprintf(ficresprobcov,"# Age"); + pstamp(ficresprobcor); + fprintf(ficresprobcor,"#One-step probabilities and correlation matrix\n"); + fprintf(ficresprobcor,"# Age"); + + + for(i=1; i<=nlstate;i++) + for(j=1; j<=(nlstate+ndeath);j++){ + fprintf(ficresprob," p%1d-%1d (SE)",i,j); + fprintf(ficresprobcov," p%1d-%1d ",i,j); + fprintf(ficresprobcor," p%1d-%1d ",i,j); + } + /* fprintf(ficresprob,"\n"); + fprintf(ficresprobcov,"\n"); + fprintf(ficresprobcor,"\n"); + */ + xp=vector(1,npar); + dnewm=matrix(1,(nlstate)*(nlstate+ndeath),1,npar); + doldm=matrix(1,(nlstate)*(nlstate+ndeath),1,(nlstate)*(nlstate+ndeath)); + mu=matrix(1,(nlstate)*(nlstate+ndeath), (int) bage, (int)fage); + varpij=ma3x(1,nlstate*(nlstate+ndeath),1,nlstate*(nlstate+ndeath),(int) bage, (int) fage); + first=1; + fprintf(ficgp,"\n# Routine varprob"); + fprintf(fichtm,"\n
  • Computing and drawing one step probabilities with their confidence intervals

  • \n"); + fprintf(fichtm,"\n"); + + fprintf(fichtm,"\n
  • Matrix of variance-covariance of one-step probabilities (drawings)

    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.
  • \n",optionfilehtmcov); + fprintf(fichtmcov,"Current page is file %s
    \n\n

    Matrix of variance-covariance of pairs of step probabilities

    \n",optionfilehtmcov, optionfilehtmcov); + fprintf(fichtmcov,"\nEllipsoids of confidence centered on point (pij, pkl) are estimated \ +and drawn. It helps understanding how is the covariance between two incidences.\ + They are expressed in year-1 in order to be less dependent of stepm.
    \n"); + fprintf(fichtmcov,"\n
    Contour plot corresponding to x'cov-1x = 4 (where x is the column vector (pij,pkl)) are drawn. \ +It can be understood this way: if pij and pkl where uncorrelated the (2x2) matrix of covariance \ +would have been (1/(var pij), 0 , 0, 1/(var pkl)), and the confidence interval would be 2 \ +standard deviations wide on each axis.
    \ + Now, if both incidences are correlated (usual case) we diagonalised the inverse of the covariance matrix\ + and made the appropriate rotation to look at the uncorrelated principal directions.
    \ +To be simple, these graphs help to understand the significativity of each parameter in relation to a second other one.
    \n"); + + cov[1]=1; + /* tj=cptcoveff; */ + tj = (int) pow(2,cptcoveff); + if (cptcovn<1) {tj=1;ncodemax[1]=1;} + j1=0; + for(j1=1; j1<=tj;j1++){ /* For each valid combination of covariates or only once*/ + if (cptcovn>0) { + fprintf(ficresprob, "\n#********** Variable "); + for (z1=1; z1<=cptcoveff; z1++) fprintf(ficresprob, "V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]); + fprintf(ficresprob, "**********\n#\n"); + fprintf(ficresprobcov, "\n#********** Variable "); + for (z1=1; z1<=cptcoveff; z1++) fprintf(ficresprobcov, "V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]); + fprintf(ficresprobcov, "**********\n#\n"); + + fprintf(ficgp, "\n#********** Variable "); + for (z1=1; z1<=cptcoveff; z1++) fprintf(ficgp, " V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]); + fprintf(ficgp, "**********\n#\n"); + + + fprintf(fichtmcov, "\n
    ********** Variable "); + for (z1=1; z1<=cptcoveff; z1++) fprintf(fichtm, "V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]); + fprintf(fichtmcov, "**********\n
    "); + + fprintf(ficresprobcor, "\n#********** Variable "); + for (z1=1; z1<=cptcoveff; z1++) fprintf(ficresprobcor, "V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]); + fprintf(ficresprobcor, "**********\n#"); + if(invalidvarcomb[j1]){ + fprintf(ficgp,"\n#Combination (%d) ignored because no cases \n",j1); + fprintf(fichtmcov,"\n

    Combination (%d) ignored because no cases

    \n",j1); + continue; + } + } + gradg=matrix(1,npar,1,(nlstate)*(nlstate+ndeath)); + trgradg=matrix(1,(nlstate)*(nlstate+ndeath),1,npar); + gp=vector(1,(nlstate)*(nlstate+ndeath)); + gm=vector(1,(nlstate)*(nlstate+ndeath)); + for (age=bage; age<=fage; age ++){ + cov[2]=age; + if(nagesqr==1) + cov[3]= age*age; + for (k=1; k<=cptcovn;k++) { + cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(j1,k)]; + /*cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(j1,Tvar[k])];*//* j1 1 2 3 4 + * 1 1 1 1 1 + * 2 2 1 1 1 + * 3 1 2 1 1 + */ + /* nbcode[1][1]=0 nbcode[1][2]=1;*/ + } + /* for (k=1; k<=cptcovage;k++) cov[2+Tage[k]]=cov[2+Tage[k]]*cov[2]; */ + for (k=1; k<=cptcovage;k++) cov[2+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2]; + for (k=1; k<=cptcovprod;k++) + cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)]*nbcode[Tvard[k][2]][codtabm(ij,k)]; + + + for(theta=1; theta <=npar; theta++){ + for(i=1; i<=npar; i++) + xp[i] = x[i] + (i==theta ?delti[theta]:(double)0); + + pmij(pmmij,cov,ncovmodel,xp,nlstate); + + k=0; + for(i=1; i<= (nlstate); i++){ + for(j=1; j<=(nlstate+ndeath);j++){ + k=k+1; + gp[k]=pmmij[i][j]; + } + } + + for(i=1; i<=npar; i++) + xp[i] = x[i] - (i==theta ?delti[theta]:(double)0); + + pmij(pmmij,cov,ncovmodel,xp,nlstate); + k=0; + for(i=1; i<=(nlstate); i++){ + for(j=1; j<=(nlstate+ndeath);j++){ + k=k+1; + gm[k]=pmmij[i][j]; + } + } + + for(i=1; i<= (nlstate)*(nlstate+ndeath); i++) + gradg[theta][i]=(gp[i]-gm[i])/(double)2./delti[theta]; + } + + for(j=1; j<=(nlstate)*(nlstate+ndeath);j++) + for(theta=1; theta <=npar; theta++) + trgradg[j][theta]=gradg[theta][j]; + + matprod2(dnewm,trgradg,1,(nlstate)*(nlstate+ndeath),1,npar,1,npar,matcov); + matprod2(doldm,dnewm,1,(nlstate)*(nlstate+ndeath),1,npar,1,(nlstate)*(nlstate+ndeath),gradg); + + pmij(pmmij,cov,ncovmodel,x,nlstate); + + k=0; + for(i=1; i<=(nlstate); i++){ + for(j=1; j<=(nlstate+ndeath);j++){ + k=k+1; + mu[k][(int) age]=pmmij[i][j]; + } + } + for(i=1;i<=(nlstate)*(nlstate+ndeath);i++) + for(j=1;j<=(nlstate)*(nlstate+ndeath);j++) + varpij[i][j][(int)age] = doldm[i][j]; + + /*printf("\n%d ",(int)age); + for (i=1; i<=(nlstate)*(nlstate+ndeath);i++){ + printf("%e [%e ;%e] ",gm[i],gm[i]-2*sqrt(doldm[i][i]),gm[i]+2*sqrt(doldm[i][i])); + fprintf(ficlog,"%e [%e ;%e] ",gm[i],gm[i]-2*sqrt(doldm[i][i]),gm[i]+2*sqrt(doldm[i][i])); + }*/ + + fprintf(ficresprob,"\n%d ",(int)age); + fprintf(ficresprobcov,"\n%d ",(int)age); + fprintf(ficresprobcor,"\n%d ",(int)age); + + for (i=1; i<=(nlstate)*(nlstate+ndeath);i++) + fprintf(ficresprob,"%11.3e (%11.3e) ",mu[i][(int) age],sqrt(varpij[i][i][(int)age])); + for (i=1; i<=(nlstate)*(nlstate+ndeath);i++){ + fprintf(ficresprobcov,"%11.3e ",mu[i][(int) age]); + fprintf(ficresprobcor,"%11.3e ",mu[i][(int) age]); + } + i=0; + for (k=1; k<=(nlstate);k++){ + for (l=1; l<=(nlstate+ndeath);l++){ + i++; + fprintf(ficresprobcov,"\n%d %d-%d",(int)age,k,l); + fprintf(ficresprobcor,"\n%d %d-%d",(int)age,k,l); + for (j=1; j<=i;j++){ + /* printf(" k=%d l=%d i=%d j=%d\n",k,l,i,j);fflush(stdout); */ + fprintf(ficresprobcov," %11.3e",varpij[i][j][(int)age]); + fprintf(ficresprobcor," %11.3e",varpij[i][j][(int) age]/sqrt(varpij[i][i][(int) age])/sqrt(varpij[j][j][(int)age])); + } + } + }/* end of loop for state */ + } /* end of loop for age */ + free_vector(gp,1,(nlstate+ndeath)*(nlstate+ndeath)); + free_vector(gm,1,(nlstate+ndeath)*(nlstate+ndeath)); + free_matrix(trgradg,1,(nlstate+ndeath)*(nlstate+ndeath),1,npar); + free_matrix(gradg,1,(nlstate+ndeath)*(nlstate+ndeath),1,npar); + + /* Confidence intervalle of pij */ + /* + fprintf(ficgp,"\nunset parametric;unset label"); + fprintf(ficgp,"\nset log y;unset log x; set xlabel \"Age\";set ylabel \"probability (year-1)\""); + fprintf(ficgp,"\nset ter png small\nset size 0.65,0.65"); + fprintf(fichtm,"\n
    Probability with confidence intervals expressed in year-1 :pijgr%s.png, ",optionfilefiname,optionfilefiname); + fprintf(fichtm,"\n
    ",optionfilefiname); + fprintf(ficgp,"\nset out \"pijgr%s.png\"",optionfilefiname); + fprintf(ficgp,"\nplot \"%s\" every :::%d::%d u 1:2 \"\%%lf",k1,k2,xfilevarprob); + */ + + /* Drawing ellipsoids of confidence of two variables p(k1-l1,k2-l2)*/ + first1=1;first2=2; + for (k2=1; k2<=(nlstate);k2++){ + for (l2=1; l2<=(nlstate+ndeath);l2++){ + if(l2==k2) continue; + j=(k2-1)*(nlstate+ndeath)+l2; + for (k1=1; k1<=(nlstate);k1++){ + for (l1=1; l1<=(nlstate+ndeath);l1++){ + if(l1==k1) continue; + i=(k1-1)*(nlstate+ndeath)+l1; + if(i<=j) continue; + for (age=bage; age<=fage; age ++){ + if ((int)age %5==0){ + v1=varpij[i][i][(int)age]/stepm*YEARM/stepm*YEARM; + v2=varpij[j][j][(int)age]/stepm*YEARM/stepm*YEARM; + cv12=varpij[i][j][(int)age]/stepm*YEARM/stepm*YEARM; + mu1=mu[i][(int) age]/stepm*YEARM ; + mu2=mu[j][(int) age]/stepm*YEARM; + c12=cv12/sqrt(v1*v2); + /* Computing eigen value of matrix of covariance */ + lc1=((v1+v2)+sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.; + lc2=((v1+v2)-sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.; + if ((lc2 <0) || (lc1 <0) ){ + if(first2==1){ + first1=0; + 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); + } + 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); + /* lc1=fabs(lc1); */ /* If we want to have them positive */ + /* lc2=fabs(lc2); */ + } + + /* Eigen vectors */ + v11=(1./sqrt(1+(v1-lc1)*(v1-lc1)/cv12/cv12)); + /*v21=sqrt(1.-v11*v11); *//* error */ + v21=(lc1-v1)/cv12*v11; + v12=-v21; + v22=v11; + tnalp=v21/v11; + if(first1==1){ + first1=0; + 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); + } + 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); + /*printf(fignu*/ + /* mu1+ v11*lc1*cost + v12*lc2*sin(t) */ + /* mu2+ v21*lc1*cost + v22*lc2*sin(t) */ + if(first==1){ + first=0; + fprintf(ficgp,"\n# Ellipsoids of confidence\n#\n"); + fprintf(ficgp,"\nset parametric;unset label"); + 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); + fprintf(ficgp,"\nset ter svg size 640, 480"); + fprintf(fichtmcov,"\n
    Ellipsoids of confidence cov(p%1d%1d,p%1d%1d) expressed in year-1\ + : \ +%s_%d%1d%1d-%1d%1d.svg, ",k1,l1,k2,l2,\ + subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2, \ + subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2); + fprintf(fichtmcov,"\n
    ",subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2); + fprintf(fichtmcov,"\n
    Correlation at age %d (%.3f),",(int) age, c12); + fprintf(ficgp,"\nset out \"%s_%d%1d%1d-%1d%1d.svg\"",subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2); + fprintf(ficgp,"\nset label \"%d\" at %11.3e,%11.3e center",(int) age, mu1,mu2); + fprintf(ficgp,"\n# Age %d, p%1d%1d - p%1d%1d",(int) age, k1,l1,k2,l2); + 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", \ + mu1,std,v11,sqrt(lc1),v12,sqrt(lc2), \ + mu2,std,v21,sqrt(lc1),v22,sqrt(lc2)); + }else{ + first=0; + fprintf(fichtmcov," %d (%.3f),",(int) age, c12); + fprintf(ficgp,"\n# Age %d, p%1d%1d - p%1d%1d",(int) age, k1,l1,k2,l2); + fprintf(ficgp,"\nset label \"%d\" at %11.3e,%11.3e center",(int) age, mu1,mu2); + 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", \ + mu1,std,v11,sqrt(lc1),v12,sqrt(lc2), \ + mu2,std,v21,sqrt(lc1),v22,sqrt(lc2)); + }/* if first */ + } /* age mod 5 */ + } /* end loop age */ + fprintf(ficgp,"\nset out;\nset out \"%s_%d%1d%1d-%1d%1d.svg\";replot;set out;",subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2); + first=1; + } /*l12 */ + } /* k12 */ + } /*l1 */ + }/* k1 */ + } /* loop on combination of covariates j1 */ + free_ma3x(varpij,1,nlstate,1,nlstate+ndeath,(int) bage, (int)fage); + free_matrix(mu,1,(nlstate+ndeath)*(nlstate+ndeath),(int) bage, (int)fage); + free_matrix(doldm,1,(nlstate)*(nlstate+ndeath),1,(nlstate)*(nlstate+ndeath)); + free_matrix(dnewm,1,(nlstate)*(nlstate+ndeath),1,npar); + free_vector(xp,1,npar); + fclose(ficresprob); + fclose(ficresprobcov); + fclose(ficresprobcor); + fflush(ficgp); + fflush(fichtmcov); + } + + +/******************* Printing html file ***********/ +void printinghtml(char fileresu[], char title[], char datafile[], int firstpass, \ + int lastpass, int stepm, int weightopt, char model[],\ + int imx,int jmin, int jmax, double jmeanint,char rfileres[],\ + int popforecast, int prevfcast, int backcast, int estepm , \ + double jprev1, double mprev1,double anprev1, double dateprev1, \ + double jprev2, double mprev2,double anprev2, double dateprev2){ + int jj1, k1, i1, cpt, k4, nres; + + fprintf(fichtm,""); + fprintf(fichtm,"
    • model=1+age+%s\n \ +
    ", model); + fprintf(fichtm,"
    • Result files (first order: no variance)

      \n"); + fprintf(fichtm,"
    • - Observed frequency between two states (during the period defined between %.lf/%.lf/%.lf and %.lf/%.lf/%.lf): %s (html file)
      \n", + jprev1, mprev1,anprev1,jprev2, mprev2,anprev2,subdirfext3(optionfilefiname,"PHTMFR_",".htm"),subdirfext3(optionfilefiname,"PHTMFR_",".htm")); + fprintf(fichtm,"
    • - Observed prevalence in each state (during the period defined between %.lf/%.lf/%.lf and %.lf/%.lf/%.lf): %s (html file) ", + jprev1, mprev1,anprev1,jprev2, mprev2,anprev2,subdirfext3(optionfilefiname,"PHTM_",".htm"),subdirfext3(optionfilefiname,"PHTM_",".htm")); + fprintf(fichtm,", %s (text file)
      \n",subdirf2(fileresu,"P_"),subdirf2(fileresu,"P_")); + fprintf(fichtm,"\ + - Estimated transition probabilities over %d (stepm) months: %s
      \n ", + stepm,subdirf2(fileresu,"PIJ_"),subdirf2(fileresu,"PIJ_")); + fprintf(fichtm,"\ + - Estimated back transition probabilities over %d (stepm) months: %s
      \n ", + stepm,subdirf2(fileresu,"PIJB_"),subdirf2(fileresu,"PIJB_")); + fprintf(fichtm,"\ + - Period (stable) prevalence in each health state: %s
      \n", + subdirf2(fileresu,"PL_"),subdirf2(fileresu,"PL_")); + fprintf(fichtm,"\ + - Period (stable) back prevalence in each health state: %s
      \n", + subdirf2(fileresu,"PLB_"),subdirf2(fileresu,"PLB_")); + fprintf(fichtm,"\ + - (a) Life expectancies by health status at initial age, ei. (b) health expectancies by health status at initial age, eij . 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): \ + %s
      \n", + estepm,subdirf2(fileresu,"E_"),subdirf2(fileresu,"E_")); + if(prevfcast==1){ + fprintf(fichtm,"\ + - Prevalence projections by age and states: \ + %s
      \n
    • ", subdirf2(fileresu,"F_"),subdirf2(fileresu,"F_")); + } + + fprintf(fichtm," \n
      • Graphs
      • "); + + m=pow(2,cptcoveff); + if (cptcovn < 1) {m=1;ncodemax[1]=1;} + + jj1=0; + + for(nres=1; nres <= nresult; nres++) /* For each resultline */ + for(k1=1; k1<=m;k1++){ /* For each combination of covariate */ + if(m != 1 && TKresult[nres]!= k1) + continue; + + /* for(i1=1; i1<=ncodemax[k1];i1++){ */ + jj1++; + if (cptcovn > 0) { + fprintf(fichtm,"


        ************ Results for covariates"); + for (cpt=1; cpt<=cptcoveff;cpt++){ + fprintf(fichtm," V%d=%d ",Tvresult[nres][cpt],(int)Tresult[nres][cpt]); + printf(" V%d=%d ",Tvresult[nres][cpt],Tresult[nres][cpt]);fflush(stdout); + /* fprintf(fichtm," V%d=%d ",Tvaraff[cpt],nbcode[Tvaraff[cpt]][codtabm(jj1,cpt)]); */ + /* printf(" V%d=%d ",Tvaraff[cpt],nbcode[Tvaraff[cpt]][codtabm(jj1,cpt)]);fflush(stdout); */ + } + for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */ + fprintf(fichtm," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); + printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);fflush(stdout); + } + + /* if(nqfveff+nqtveff 0) */ /* Test to be done */ + fprintf(fichtm," ************\n
        "); + if(invalidvarcomb[k1]){ + fprintf(fichtm,"\n

        Combination (%d) ignored because no cases

        \n",k1); + printf("\nCombination (%d) ignored because no cases \n",k1); + continue; + } + } + /* aij, bij */ + fprintf(fichtm,"
        - Logit model (yours is: 1+age+%s), for example: logit(pij)=log(pij/pii)= aij+ bij age + V1 age + etc. as a function of age: %s_%d-1-%d.svg
        \ +",model,subdirf2(optionfilefiname,"PE_"),k1,nres,subdirf2(optionfilefiname,"PE_"),k1,nres,subdirf2(optionfilefiname,"PE_"),k1,nres); + /* Pij */ + fprintf(fichtm,"
        \n- Pij or conditional probabilities to be observed in state j being in state i, %d (stepm) months before: %s_%d-2-%d.svg
        \ +",stepm,subdirf2(optionfilefiname,"PE_"),k1,nres,subdirf2(optionfilefiname,"PE_"),k1,nres,subdirf2(optionfilefiname,"PE_"),k1,nres); + /* Quasi-incidences */ + fprintf(fichtm,"
        \n- Iij or Conditional probabilities to be observed in state j being in state i %d (stepm) months\ + before but expressed in per year i.e. quasi incidences if stepm is small and probabilities too, \ + incidence (rates) are the limit when h tends to zero of the ratio of the probability hPij \ +divided by h: hPij/h : %s_%d-3-%d.svg
        \ +",stepm,subdirf2(optionfilefiname,"PE_"),k1,nres,subdirf2(optionfilefiname,"PE_"),k1,nres,subdirf2(optionfilefiname,"PE_"),k1,nres); + /* Survival functions (period) in state j */ + for(cpt=1; cpt<=nlstate;cpt++){ + fprintf(fichtm,"
        \n- Survival functions in state %d. Or probability to survive in state %d being in state (1 to %d) at different ages. %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); + } + /* State specific survival functions (period) */ + for(cpt=1; cpt<=nlstate;cpt++){ + fprintf(fichtm,"
        \n- Survival functions from state %d in each live state and total.\ + Or probability to survive in various states (1 to %d) being in state %d at different ages. \ + %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); + } + /* Period (stable) prevalence in each health state */ + for(cpt=1; cpt<=nlstate;cpt++){ + fprintf(fichtm,"
        \n- Convergence to period (stable) prevalence in state %d. Or probability to be in state %d being in state (1 to %d) at different ages. %s_%d-%d-%d.svg
        \ +", cpt, cpt, nlstate, subdirf2(optionfilefiname,"P_"),cpt,k1,nres,subdirf2(optionfilefiname,"P_"),cpt,k1,nres,subdirf2(optionfilefiname,"P_"),cpt,k1,nres); + } + if(backcast==1){ + /* Period (stable) back prevalence in each health state */ + for(cpt=1; cpt<=nlstate;cpt++){ + fprintf(fichtm,"
        \n- Convergence to period (stable) back prevalence in state %d. Or probability to be in state %d being in state (1 to %d) at different ages. %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); + } + } + if(prevfcast==1){ + /* Projection of prevalence up to period (stable) prevalence in each health state */ + for(cpt=1; cpt<=nlstate;cpt++){ + fprintf(fichtm,"
        \n- Projection of cross-sectional prevalence (estimated with cases observed from %.1f to %.1f) up to period (stable) prevalence in state %d. Or probability to be in state %d being in state (1 to %d) at different ages. %s_%d-%d-%d.svg
        \ +", dateprev1, dateprev2, cpt, cpt, nlstate, subdirf2(optionfilefiname,"PROJ_"),cpt,k1,nres,subdirf2(optionfilefiname,"PROJ_"),cpt,k1,nres,subdirf2(optionfilefiname,"PROJ_"),cpt,k1,nres); + } + } + + for(cpt=1; cpt<=nlstate;cpt++) { + fprintf(fichtm,"\n
        - 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): %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); + } + /* } /\* end i1 *\/ */ + }/* End k1 */ + fprintf(fichtm,"
      "); + + fprintf(fichtm,"\ +\n
    • Result files (second order: variances)

      \n\ + - Parameter file with estimated parameters and covariance matrix: %s
      \ + - 95%% confidence intervals and Wald tests of the estimated parameters are in the log file if optimization has been done (mle != 0).
      \ +But because parameters are usually highly correlated (a higher incidence of disability \ +and a higher incidence of recovery can give very close observed transition) it might \ +be very useful to look not only at linear confidence intervals estimated from the \ +variances but at the covariance matrix. And instead of looking at the estimated coefficients \ +(parameters) of the logistic regression, it might be more meaningful to visualize the \ +covariance matrix of the one-step probabilities. \ +See page 'Matrix of variance-covariance of one-step probabilities' below. \n", rfileres,rfileres); + + fprintf(fichtm," - Standard deviation of one-step probabilities: %s
      \n", + subdirf2(fileresu,"PROB_"),subdirf2(fileresu,"PROB_")); + fprintf(fichtm,"\ + - Variance-covariance of one-step probabilities: %s
      \n", + subdirf2(fileresu,"PROBCOV_"),subdirf2(fileresu,"PROBCOV_")); + + fprintf(fichtm,"\ + - Correlation matrix of one-step probabilities: %s
      \n", + subdirf2(fileresu,"PROBCOR_"),subdirf2(fileresu,"PROBCOR_")); + fprintf(fichtm,"\ + - Variances and covariances of health expectancies by age and initial health status (cov(eij,ekl)(estepm=%2d months): \ + %s
      \n
    • ", + estepm,subdirf2(fileresu,"CVE_"),subdirf2(fileresu,"CVE_")); + fprintf(fichtm,"\ + - (a) Health expectancies by health status at initial age (eij) and standard errors (in parentheses) (b) life expectancies and standard errors (ei.=ei1+ei2+...)(estepm=%2d months): \ + %s
      \n", + estepm,subdirf2(fileresu,"STDE_"),subdirf2(fileresu,"STDE_")); + fprintf(fichtm,"\ + - Variances and covariances of health expectancies by age. Status (i) based health expectancies (in state j), eij 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): %s
      \n", + estepm, subdirf2(fileresu,"V_"),subdirf2(fileresu,"V_")); + fprintf(fichtm,"\ + - Total life expectancy and total health expectancies to be spent in each health state e.j with their standard errors (if popbased=1, an additional computation is done using the cross-sectional prevalences, i.e population based) (estepm=%d months): %s
      \n", + estepm, subdirf2(fileresu,"T_"),subdirf2(fileresu,"T_")); + fprintf(fichtm,"\ + - Standard deviation of period (stable) prevalences: %s
      \n",\ + subdirf2(fileresu,"VPL_"),subdirf2(fileresu,"VPL_")); + +/* if(popforecast==1) fprintf(fichtm,"\n */ +/* - Prevalences forecasting: f%s
      \n */ +/* - Population forecasting (if popforecast=1): pop%s
      \n */ +/*
      ",fileres,fileres,fileres,fileres); */ +/* else */ +/* fprintf(fichtm,"\n No population forecast: popforecast = %d (instead of 1) or stepm = %d (instead of 1) or model=%s (instead of .)

      \n",popforecast, stepm, model); */ + fflush(fichtm); + fprintf(fichtm,"
      • Graphs
      • "); + + m=pow(2,cptcoveff); + if (cptcovn < 1) {m=1;ncodemax[1]=1;} + + jj1=0; + + for(nres=1; nres <= nresult; nres++){ /* For each resultline */ + for(k1=1; k1<=m;k1++){ + if(m != 1 && TKresult[nres]!= k1) + continue; + /* for(i1=1; i1<=ncodemax[k1];i1++){ */ + jj1++; + if (cptcovn > 0) { + fprintf(fichtm,"


        ************ Results for covariates"); + for (cpt=1; cpt<=cptcoveff;cpt++) /**< cptcoveff number of variables */ + fprintf(fichtm," V%d=%d ",Tvresult[nres][cpt],Tresult[nres][cpt]); + /* fprintf(fichtm," V%d=%d ",Tvaraff[cpt],nbcode[Tvaraff[cpt]][codtabm(jj1,cpt)]); */ + for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */ + fprintf(fichtm," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); + } + + fprintf(fichtm," ************\n
        "); + + if(invalidvarcomb[k1]){ + fprintf(fichtm,"\n

        Combination (%d) ignored because no cases

        \n",k1); + continue; + } + } + for(cpt=1; cpt<=nlstate;cpt++) { + fprintf(fichtm,"\n
        - Observed (cross-sectional) and period (incidence based) \ +prevalence (with 95%% confidence interval) in state (%d): %s_%d-%d-%d.svg\n
        \ +",cpt,subdirf2(optionfilefiname,"V_"),cpt,k1,nres,subdirf2(optionfilefiname,"V_"),cpt,k1,nres,subdirf2(optionfilefiname,"V_"),cpt,k1,nres); + } + fprintf(fichtm,"\n
        - Total life expectancy by age and \ +health expectancies in states (1) and (2). If popbased=1 the smooth (due to the model) \ +true period expectancies (those weighted with period prevalences are also\ + drawn in addition to the population based expectancies computed using\ + observed and cahotic prevalences: %s_%d-%d.svg\n
        \ +",subdirf2(optionfilefiname,"E_"),k1,nres,subdirf2(optionfilefiname,"E_"),k1,nres,subdirf2(optionfilefiname,"E_"),k1,nres); + /* } /\* end i1 *\/ */ + }/* End k1 */ + }/* End nres */ + fprintf(fichtm,"
      "); + fflush(fichtm); +} + +/******************* Gnuplot file **************/ +void printinggnuplot(char fileresu[], char optionfilefiname[], double ageminpar, double agemaxpar, double fage , int prevfcast, int backcast, char pathc[], double p[]){ + + char dirfileres[132],optfileres[132]; + char gplotcondition[132]; + 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; + int lv=0, vlv=0, kl=0; + int ng=0; + int vpopbased; + int ioffset; /* variable offset for columns */ + int nres=0; /* Index of resultline */ + +/* if((ficgp=fopen(optionfilegnuplot,"a"))==NULL) { */ +/* printf("Problem with file %s",optionfilegnuplot); */ +/* fprintf(ficlog,"Problem with file %s",optionfilegnuplot); */ +/* } */ + + /*#ifdef windows */ + fprintf(ficgp,"cd \"%s\" \n",pathc); + /*#endif */ + m=pow(2,cptcoveff); + + /* Contribution to likelihood */ + /* Plot the probability implied in the likelihood */ + fprintf(ficgp,"\n# Contributions to the Likelihood, mle >=1. For mle=4 no interpolation, pure matrix products.\n#\n"); + fprintf(ficgp,"\n set log y; unset log x;set xlabel \"Age\"; set ylabel \"Likelihood (-2Log(L))\";"); + /* fprintf(ficgp,"\nset ter svg size 640, 480"); */ /* Too big for svg */ + fprintf(ficgp,"\nset ter pngcairo size 640, 480"); +/* nice for mle=4 plot by number of matrix products. + replot "rrtest1/toto.txt" u 2:($4 == 1 && $5==2 ? $9 : 1/0):5 t "p12" with point lc 1 */ +/* replot exp(p1+p2*x)/(1+exp(p1+p2*x)+exp(p3+p4*x)+exp(p5+p6*x)) t "p12(x)" */ + /* fprintf(ficgp,"\nset out \"%s.svg\";",subdirf2(optionfilefiname,"ILK_")); */ + fprintf(ficgp,"\nset out \"%s-dest.png\";",subdirf2(optionfilefiname,"ILK_")); + 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)); + fprintf(ficgp,"\nset out \"%s-ori.png\";",subdirf2(optionfilefiname,"ILK_")); + 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)); + for (i=1; i<= nlstate ; i ++) { + fprintf(ficgp,"\nset out \"%s-p%dj.png\";set ylabel \"Probability for each individual/wave\";",subdirf2(optionfilefiname,"ILK_"),i); + fprintf(ficgp,"unset log;\n# plot weighted, mean weight should have point size of 0.5\n plot \"%s\"",subdirf(fileresilk)); + 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); + for (j=2; j<= nlstate+ndeath ; j ++) { + 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); + } + fprintf(ficgp,";\nset out; unset ylabel;\n"); + } + /* 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 */ + /* fprintf(ficgp,"\nset log y;plot \"%s\" u 2:(-$11):3 t \"All sample, all transitions\" with dots lc variable",subdirf(fileresilk)); */ + /* fprintf(ficgp,"\nreplot \"%s\" u 2:($3 <= 3 ? -$11 : 1/0):3 t \"First 3 individuals\" with line lc variable", subdirf(fileresilk)); */ + fprintf(ficgp,"\nset out;unset log\n"); + /* fprintf(ficgp,"\nset out \"%s.svg\"; replot; set out; # bug gnuplot",subdirf2(optionfilefiname,"ILK_")); */ + + strcpy(dirfileres,optionfilefiname); + strcpy(optfileres,"vpl"); + /* 1eme*/ + for (cpt=1; cpt<= nlstate ; cpt ++){ /* For each live state */ + for (k1=1; k1<= m ; k1 ++){ /* For each valid combination of covariate */ + for(nres=1; nres <= nresult; nres++){ /* For each resultline */ + /* plot [100000000000000000000:-100000000000000000000] "mysbiaspar/vplrmysbiaspar.txt to check */ + if(m != 1 && TKresult[nres]!= k1) + continue; + /* We are interested in selected combination by the resultline */ + /* printf("\n# 1st: Period (stable) prevalence with CI: 'VPL_' files and live state =%d ", cpt); */ + fprintf(ficgp,"\n# 1st: Period (stable) prevalence with CI: 'VPL_' files and live state =%d ", cpt); + for (k=1; k<=cptcoveff; k++){ /* For each covariate k get corresponding value lv for combination k1 */ + lv= decodtabm(k1,k,cptcoveff); /* Should be the value of the covariate corresponding to k1 combination */ + /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */ + /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */ + /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */ + vlv= nbcode[Tvaraff[k]][lv]; /* vlv is the value of the covariate lv, 0 or 1 */ + /* For each combination of covariate k1 (V1=1, V3=0), we printed the current covariate k and its value vlv */ + /* printf(" V%d=%d ",Tvaraff[k],vlv); */ + fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); + } + for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */ + /* printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */ + fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); + } + /* printf("\n#\n"); */ + fprintf(ficgp,"\n#\n"); + if(invalidvarcomb[k1]){ + fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1); + continue; + } + + fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"V_"),cpt,k1,nres); + fprintf(ficgp,"\n#set out \"V_%s_%d-%d-%d.svg\" \n",optionfilefiname,cpt,k1,nres); + 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); + + for (i=1; i<= nlstate ; i ++) { + if (i==cpt) fprintf(ficgp," %%lf (%%lf)"); + else fprintf(ficgp," %%*lf (%%*lf)"); + } + fprintf(ficgp,"\" t\"Period (stable) prevalence\" w l lt 0,\"%s\" every :::%d::%d u 1:($2==%d ? $3+1.96*$4 : 1/0) \"%%lf %%lf",subdirf2(fileresu,"VPL_"),k1-1,k1-1,nres); + for (i=1; i<= nlstate ; i ++) { + if (i==cpt) fprintf(ficgp," %%lf (%%lf)"); + else fprintf(ficgp," %%*lf (%%*lf)"); + } + fprintf(ficgp,"\" t\"95%% CI\" w l lt 1,\"%s\" every :::%d::%d u 1:($2==%d ? $3-1.96*$4 : 1/0) \"%%lf %%lf",subdirf2(fileresu,"VPL_"),k1-1,k1-1,nres); + for (i=1; i<= nlstate ; i ++) { + if (i==cpt) fprintf(ficgp," %%lf (%%lf)"); + else fprintf(ficgp," %%*lf (%%*lf)"); + } + fprintf(ficgp,"\" t\"\" w l lt 1,\"%s\" every :::%d::%d u 1:($%d) t\"Observed prevalence\" w l lt 2",subdirf2(fileresu,"P_"),k1-1,k1-1,2+4*(cpt-1)); + if(backcast==1){ /* We need to get the corresponding values of the covariates involved in this combination k1 */ + /* fprintf(ficgp,",\"%s\" every :::%d::%d u 1:($%d) t\"Backward stable prevalence\" w l lt 3",subdirf2(fileresu,"PLB_"),k1-1,k1-1,1+cpt); */ + fprintf(ficgp,",\"%s\" u 1:((",subdirf2(fileresu,"PLB_")); /* Age is in 1, nres in 2 to be fixed */ + if(cptcoveff ==0){ + fprintf(ficgp,"$%d)) t 'Backward prevalence in state %d' with line lt 3", 2+(cpt-1), cpt ); + }else{ + kl=0; + for (k=1; k<=cptcoveff; k++){ /* For each combination of covariate */ + lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate value corresponding to k1 combination and kth covariate */ + /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */ + /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */ + /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */ + vlv= nbcode[Tvaraff[k]][lv]; + kl++; + /* 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 *\/ */ + /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */ + /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */ + /* '' u 6:(($1==1 && $2==0 && $3==2 && $4==0)? $9/(1.-$15) : 1/0):($5==2000? 3:2) t 'p.1' with line lc variable*/ + if(k==cptcoveff){ + fprintf(ficgp,"$%d==%d && $%d==%d)? $%d : 1/0) t 'Backward prevalence in state %d' w l lt 3",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][lv], \ + 2+cptcoveff*2+(cpt-1), cpt ); /* 4 or 6 ?*/ + }else{ + fprintf(ficgp,"$%d==%d && $%d==%d && ",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][lv]); + kl++; + } + } /* end covariate */ + } /* end if no covariate */ + } /* end if backcast */ + fprintf(ficgp,"\nset out \n"); + } /* nres */ + } /* k1 */ + } /* cpt */ + + + /*2 eme*/ + for (k1=1; k1<= m ; k1 ++){ + for(nres=1; nres <= nresult; nres++){ /* For each resultline */ + if(m != 1 && TKresult[nres]!= k1) + continue; + fprintf(ficgp,"\n# 2nd: Total life expectancy with CI: 't' files "); + for (k=1; k<=cptcoveff; k++){ /* For each covariate and each value */ + lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate number corresponding to k1 combination */ + /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */ + /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */ + /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */ + vlv= nbcode[Tvaraff[k]][lv]; + fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); + } + /* for(k=1; k <= ncovds; k++){ */ + for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */ + printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); + fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); + } + fprintf(ficgp,"\n#\n"); + if(invalidvarcomb[k1]){ + fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1); + continue; + } + + fprintf(ficgp,"\nset out \"%s_%d-%d.svg\" \n",subdirf2(optionfilefiname,"E_"),k1,nres); + for(vpopbased=0; vpopbased <= popbased; vpopbased++){ /* Done for vpopbased=0 and vpopbased=1 if popbased==1*/ + if(vpopbased==0) + fprintf(ficgp,"set ylabel \"Years\" \nset ter svg size 640, 480\nplot [%.f:%.f] ",ageminpar,fage); + else + fprintf(ficgp,"\nreplot "); + for (i=1; i<= nlstate+1 ; i ++) { + k=2*i; + fprintf(ficgp,"\"%s\" every :::%d::%d u 1:($2==%d && $4!=0 ?$4 : 1/0) \"%%lf %%lf %%lf",subdirf2(fileresu,"T_"),k1-1,k1-1, vpopbased); + for (j=1; j<= nlstate+1 ; j ++) { + if (j==i) fprintf(ficgp," %%lf (%%lf)"); + else fprintf(ficgp," %%*lf (%%*lf)"); + } + if (i== 1) fprintf(ficgp,"\" t\"TLE\" w l lt %d, \\\n",i); + else fprintf(ficgp,"\" t\"LE in state (%d)\" w l lt %d, \\\n",i-1,i+1); + fprintf(ficgp,"\"%s\" every :::%d::%d u 1:($2==%d && $4!=0 ? $4-$5*2 : 1/0) \"%%lf %%lf %%lf",subdirf2(fileresu,"T_"),k1-1,k1-1,vpopbased); + for (j=1; j<= nlstate+1 ; j ++) { + if (j==i) fprintf(ficgp," %%lf (%%lf)"); + else fprintf(ficgp," %%*lf (%%*lf)"); + } + fprintf(ficgp,"\" t\"\" w l lt 0,"); + fprintf(ficgp,"\"%s\" every :::%d::%d u 1:($2==%d && $4!=0 ? $4+$5*2 : 1/0) \"%%lf %%lf %%lf",subdirf2(fileresu,"T_"),k1-1,k1-1,vpopbased); + for (j=1; j<= nlstate+1 ; j ++) { + if (j==i) fprintf(ficgp," %%lf (%%lf)"); + else fprintf(ficgp," %%*lf (%%*lf)"); + } + if (i== (nlstate+1)) fprintf(ficgp,"\" t\"\" w l lt 0"); + else fprintf(ficgp,"\" t\"\" w l lt 0,\\\n"); + } /* state */ + } /* vpopbased */ + fprintf(ficgp,"\nset out;set out \"%s_%d-%d.svg\"; replot; set out; \n",subdirf2(optionfilefiname,"E_"),k1,nres); /* Buggy gnuplot */ + } /* end nres */ + } /* k1 end 2 eme*/ + + + /*3eme*/ + for (k1=1; k1<= m ; k1 ++){ + for(nres=1; nres <= nresult; nres++){ /* For each resultline */ + if(m != 1 && TKresult[nres]!= k1) + continue; + + for (cpt=1; cpt<= nlstate ; cpt ++) { + fprintf(ficgp,"\n# 3d: Life expectancy with EXP_ files: combination=%d state=%d",k1, cpt); + for (k=1; k<=cptcoveff; k++){ /* For each covariate and each value */ + lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate number corresponding to k1 combination */ + /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */ + /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */ + /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */ + vlv= nbcode[Tvaraff[k]][lv]; + fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); + } + for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */ + fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); + } + fprintf(ficgp,"\n#\n"); + if(invalidvarcomb[k1]){ + fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1); + continue; + } + + /* k=2+nlstate*(2*cpt-2); */ + k=2+(nlstate+1)*(cpt-1); + fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"EXP_"),cpt,k1,nres); + fprintf(ficgp,"set ter svg size 640, 480\n\ +plot [%.f:%.f] \"%s\" every :::%d::%d u 1:%d t \"e%d1\" w l",ageminpar,fage,subdirf2(fileresu,"E_"),k1-1,k1-1,k,cpt); + /*fprintf(ficgp,",\"e%s\" every :::%d::%d u 1:($%d-2*$%d) \"\%%lf ",fileres,k1-1,k1-1,k,k+1); + for (i=1; i<= nlstate*2 ; i ++) fprintf(ficgp,"\%%lf (\%%lf) "); + fprintf(ficgp,"\" t \"e%d1\" w l",cpt); + fprintf(ficgp,",\"e%s\" every :::%d::%d u 1:($%d+2*$%d) \"\%%lf ",fileres,k1-1,k1-1,k,k+1); + for (i=1; i<= nlstate*2 ; i ++) fprintf(ficgp,"\%%lf (\%%lf) "); + fprintf(ficgp,"\" t \"e%d1\" w l",cpt); + + */ + for (i=1; i< nlstate ; i ++) { + fprintf(ficgp," ,\"%s\" every :::%d::%d u 1:%d t \"e%d%d\" w l",subdirf2(fileresu,"E_"),k1-1,k1-1,k+i,cpt,i+1); + /* 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);*/ + + } + fprintf(ficgp," ,\"%s\" every :::%d::%d u 1:%d t \"e%d.\" w l",subdirf2(fileresu,"E_"),k1-1,k1-1,k+nlstate,cpt); + } + } /* end nres */ + } /* end kl 3eme */ + + /* 4eme */ + /* Survival functions (period) from state i in state j by initial state i */ + for (k1=1; k1<=m; k1++){ /* For each covariate and each value */ + for(nres=1; nres <= nresult; nres++){ /* For each resultline */ + if(m != 1 && TKresult[nres]!= k1) + continue; + for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state cpt*/ + fprintf(ficgp,"\n#\n#\n# Survival functions in state j : 'LIJ_' files, cov=%d state=%d",k1, cpt); + for (k=1; k<=cptcoveff; k++){ /* For each covariate and each value */ + lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate number corresponding to k1 combination */ + /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */ + /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */ + /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */ + vlv= nbcode[Tvaraff[k]][lv]; + fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); + } + for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */ + fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); + } + fprintf(ficgp,"\n#\n"); + if(invalidvarcomb[k1]){ + fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1); + continue; + } + + fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"LIJ_"),cpt,k1,nres); + fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability to be alive\" \n\ +set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar); + k=3; + for (i=1; i<= nlstate ; i ++){ + if(i==1){ + fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJ_")); + }else{ + fprintf(ficgp,", '' "); + } + l=(nlstate+ndeath)*(i-1)+1; + fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d/($%d",k1,k+l+(cpt-1),k+l); + for (j=2; j<= nlstate+ndeath ; j ++) + fprintf(ficgp,"+$%d",k+l+j-1); + fprintf(ficgp,")) t \"l(%d,%d)\" w l",i,cpt); + } /* nlstate */ + fprintf(ficgp,"\nset out\n"); + } /* end cpt state*/ + } /* end nres */ + } /* end covariate k1 */ + +/* 5eme */ + /* Survival functions (period) from state i in state j by final state j */ + for (k1=1; k1<= m ; k1++){ /* For each covariate combination if any */ + for(nres=1; nres <= nresult; nres++){ /* For each resultline */ + if(m != 1 && TKresult[nres]!= k1) + continue; + for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each inital state */ + 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); + for (k=1; k<=cptcoveff; k++){ /* For each covariate and each value */ + lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate number corresponding to k1 combination */ + /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */ + /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */ + /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */ + vlv= nbcode[Tvaraff[k]][lv]; + fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); + } + for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */ + fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); + } + fprintf(ficgp,"\n#\n"); + if(invalidvarcomb[k1]){ + fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1); + continue; + } + + fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"LIJT_"),cpt,k1,nres); + fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability to be alive\" \n\ +set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar); + k=3; + for (j=1; j<= nlstate ; j ++){ /* Lived in state j */ + if(j==1) + fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJ_")); + else + fprintf(ficgp,", '' "); + l=(nlstate+ndeath)*(cpt-1) +j; + fprintf(ficgp," u (($1==%d && (floor($2)%%5 == 0)) ? ($3):1/0):($%d",k1,k+l); + /* for (i=2; i<= nlstate+ndeath ; i ++) */ + /* fprintf(ficgp,"+$%d",k+l+i-1); */ + fprintf(ficgp,") t \"l(%d,%d)\" w l",cpt,j); + } /* nlstate */ + fprintf(ficgp,", '' "); + fprintf(ficgp," u (($1==%d && (floor($2)%%5 == 0)) ? ($3):1/0):(",k1); + for (j=1; j<= nlstate ; j ++){ /* Lived in state j */ + l=(nlstate+ndeath)*(cpt-1) +j; + if(j < nlstate) + fprintf(ficgp,"$%d +",k+l); + else + fprintf(ficgp,"$%d) t\"l(%d,.)\" w l",k+l,cpt); + } + fprintf(ficgp,"\nset out\n"); + } /* end cpt state*/ + } /* end covariate */ + } /* end nres */ + +/* 6eme */ + /* CV preval stable (period) for each covariate */ + for (k1=1; k1<= m ; k1 ++) /* For each covariate combination if any */ + for(nres=1; nres <= nresult; nres++){ /* For each resultline */ + if(m != 1 && TKresult[nres]!= k1) + continue; + for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state */ + + fprintf(ficgp,"\n#\n#\n#CV preval stable (period): 'pij' files, covariatecombination#=%d state=%d",k1, cpt); + for (k=1; k<=cptcoveff; k++){ /* For each covariate and each value */ + lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate number corresponding to k1 combination */ + /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */ + /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */ + /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */ + vlv= nbcode[Tvaraff[k]][lv]; + fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); + } + for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */ + fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); + } + fprintf(ficgp,"\n#\n"); + if(invalidvarcomb[k1]){ + fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1); + continue; + } + + fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"P_"),cpt,k1,nres); + fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability\" \n\ +set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar); + k=3; /* Offset */ + for (i=1; i<= nlstate ; i ++){ + if(i==1) + fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJ_")); + else + fprintf(ficgp,", '' "); + l=(nlstate+ndeath)*(i-1)+1; + fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d/($%d",k1,k+l+(cpt-1),k+l); + for (j=2; j<= nlstate ; j ++) + fprintf(ficgp,"+$%d",k+l+j-1); + fprintf(ficgp,")) t \"prev(%d,%d)\" w l",i,cpt); + } /* nlstate */ + fprintf(ficgp,"\nset out\n"); + } /* end cpt state*/ + } /* end covariate */ + + +/* 7eme */ + if(backcast == 1){ + /* CV back preval stable (period) for each covariate */ + for (k1=1; k1<= m ; k1 ++) /* For each covariate combination if any */ + for(nres=1; nres <= nresult; nres++){ /* For each resultline */ + if(m != 1 && TKresult[nres]!= k1) + continue; + for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state */ + fprintf(ficgp,"\n#\n#\n#CV Back preval stable (period): 'pij' files, covariatecombination#=%d state=%d",k1, cpt); + for (k=1; k<=cptcoveff; k++){ /* For each covariate and each value */ + lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate number corresponding to k1 combination */ + /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */ + /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */ + /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */ + vlv= nbcode[Tvaraff[k]][lv]; + fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); + } + for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */ + fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); + } + fprintf(ficgp,"\n#\n"); + if(invalidvarcomb[k1]){ + fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1); + continue; + } + + fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"PB_"),cpt,k1,nres); + fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability\" \n\ +set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar); + k=3; /* Offset */ + for (i=1; i<= nlstate ; i ++){ + if(i==1) + fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJB_")); + else + fprintf(ficgp,", '' "); + /* l=(nlstate+ndeath)*(i-1)+1; */ + l=(nlstate+ndeath)*(cpt-1)+1; + /* fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d/($%d",k1,k+l+(cpt-1),k+l); /\* a vérifier *\/ */ + /* fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d/($%d",k1,k+l+(cpt-1),k+l+(cpt-1)+i-1); /\* a vérifier *\/ */ + fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d",k1,k+l+(cpt-1)+i-1); /* a vérifier */ + /* for (j=2; j<= nlstate ; j ++) */ + /* fprintf(ficgp,"+$%d",k+l+j-1); */ + /* /\* fprintf(ficgp,"+$%d",k+l+j-1); *\/ */ + fprintf(ficgp,") t \"bprev(%d,%d)\" w l",i,cpt); + } /* nlstate */ + fprintf(ficgp,"\nset out\n"); + } /* end cpt state*/ + } /* end covariate */ + } /* End if backcast */ + + /* 8eme */ + if(prevfcast==1){ + /* Projection from cross-sectional to stable (period) for each covariate */ + + for (k1=1; k1<= m ; k1 ++) /* For each covariate combination if any */ + for(nres=1; nres <= nresult; nres++){ /* For each resultline */ + if(m != 1 && TKresult[nres]!= k1) + continue; + for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state */ + fprintf(ficgp,"\n#\n#\n#Projection of prevalence to stable (period): 'PROJ_' files, covariatecombination#=%d state=%d",k1, cpt); + for (k=1; k<=cptcoveff; k++){ /* For each correspondig covariate value */ + lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate value corresponding to k1 combination and kth covariate */ + /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */ + /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */ + /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */ + vlv= nbcode[Tvaraff[k]][lv]; + fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); + } + for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */ + fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); + } + fprintf(ficgp,"\n#\n"); + if(invalidvarcomb[k1]){ + fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1); + continue; + } + + fprintf(ficgp,"# hpijx=probability over h years, hp.jx is weighted by observed prev\n "); + fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"PROJ_"),cpt,k1,nres); + fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Prevalence\" \n\ +set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar); + for (i=1; i<= nlstate+1 ; i ++){ /* nlstate +1 p11 p21 p.1 */ + /*# V1 = 1 V2 = 0 yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/ + /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */ + /*# yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/ + /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */ + if(i==1){ + fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"F_")); + }else{ + fprintf(ficgp,",\\\n '' "); + } + if(cptcoveff ==0){ /* No covariate */ + ioffset=2; /* Age is in 2 */ + /*# yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/ + /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */ + /*# V1 = 1 yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/ + /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */ + fprintf(ficgp," u %d:(", ioffset); + if(i==nlstate+1) + fprintf(ficgp," $%d/(1.-$%d)) t 'pw.%d' with line ", \ + ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,cpt ); + else + fprintf(ficgp," $%d/(1.-$%d)) t 'p%d%d' with line ", \ + ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,i,cpt ); + }else{ /* more than 2 covariates */ + if(cptcoveff ==1){ + ioffset=4; /* Age is in 4 */ + }else{ + ioffset=6; /* Age is in 6 */ + /*# V1 = 1 V2 = 0 yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/ + /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */ + } + fprintf(ficgp," u %d:(",ioffset); + kl=0; + strcpy(gplotcondition,"("); + for (k=1; k<=cptcoveff; k++){ /* For each covariate writing the chain of conditions */ + lv= decodtabm(k1,k,cptcoveff); /* Should be the covariate value corresponding to combination k1 and covariate k */ + /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */ + /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */ + /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */ + vlv= nbcode[Tvaraff[k]][lv]; /* Value of the modality of Tvaraff[k] */ + kl++; + sprintf(gplotcondition+strlen(gplotcondition),"$%d==%d && $%d==%d " ,kl,Tvaraff[k], kl+1, nbcode[Tvaraff[k]][lv]); + kl++; + if(k 1) + sprintf(gplotcondition+strlen(gplotcondition)," && "); + } + strcpy(gplotcondition+strlen(gplotcondition),")"); + /* 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 *\/ */ + /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */ + /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */ + /* '' 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*/ + if(i==nlstate+1){ + fprintf(ficgp,"%s ? $%d/(1.-$%d) : 1/0) t 'p.%d' with line ", gplotcondition, \ + ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,cpt ); + }else{ + fprintf(ficgp,"%s ? $%d/(1.-$%d) : 1/0) t 'p%d%d' with line ", gplotcondition, \ + ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset +1+(i-1)+(nlstate+1)*nlstate,i,cpt ); + } + } /* end if covariate */ + } /* nlstate */ + fprintf(ficgp,"\nset out\n"); + } /* end cpt state*/ + } /* end covariate */ + } /* End if prevfcast */ + + + /* 9eme writing MLE parameters */ + fprintf(ficgp,"\n##############\n#9eme MLE estimated parameters\n#############\n"); + for(i=1,jk=1; i <=nlstate; i++){ + fprintf(ficgp,"# initial state %d\n",i); + for(k=1; k <=(nlstate+ndeath); k++){ + if (k != i) { + fprintf(ficgp,"# current state %d\n",k); + for(j=1; j <=ncovmodel; j++){ + fprintf(ficgp,"p%d=%f; ",jk,p[jk]); + jk++; + } + fprintf(ficgp,"\n"); + } + } + } + fprintf(ficgp,"##############\n#\n"); + + /*goto avoid;*/ + /* 10eme Graphics of probabilities or incidences using written MLE parameters */ + fprintf(ficgp,"\n##############\n#10eme Graphics of probabilities or incidences\n#############\n"); + fprintf(ficgp,"# logi(p12/p11)=a12+b12*age+c12age*age+d12*V1+e12*V1*age\n"); + fprintf(ficgp,"# logi(p12/p11)=p1 +p2*age +p3*age*age+ p4*V1+ p5*V1*age\n"); + fprintf(ficgp,"# logi(p13/p11)=a13+b13*age+c13age*age+d13*V1+e13*V1*age\n"); + fprintf(ficgp,"# logi(p13/p11)=p6 +p7*age +p8*age*age+ p9*V1+ p10*V1*age\n"); + fprintf(ficgp,"# p12+p13+p14+p11=1=p11(1+exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)\n"); + fprintf(ficgp,"# +exp(a13+b13*age+c13age*age+d13*V1+e13*V1*age)+...)\n"); + fprintf(ficgp,"# p11=1/(1+exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)\n"); + fprintf(ficgp,"# +exp(a13+b13*age+c13age*age+d13*V1+e13*V1*age)+...)\n"); + fprintf(ficgp,"# p12=exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)/\n"); + fprintf(ficgp,"# (1+exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)\n"); + fprintf(ficgp,"# +exp(a13+b13*age+c13age*age+d13*V1+e13*V1*age))\n"); + fprintf(ficgp,"# +exp(a14+b14*age+c14age*age+d14*V1+e14*V1*age)+...)\n"); + fprintf(ficgp,"#\n"); + for(ng=1; ng<=3;ng++){ /* Number of graphics: first is logit, 2nd is probabilities, third is incidences per year*/ + fprintf(ficgp,"#Number of graphics: first is logit, 2nd is probabilities, third is incidences per year\n"); + fprintf(ficgp,"#model=%s \n",model); + fprintf(ficgp,"# Type of graphic ng=%d\n",ng); + fprintf(ficgp,"# jk=1 to 2^%d=%d\n",cptcoveff,m);/* to be checked */ + for(jk=1; jk <=m; jk++) /* For each combination of covariate */ + for(nres=1; nres <= nresult; nres++){ /* For each resultline */ + if(m != 1 && TKresult[nres]!= jk) + continue; + fprintf(ficgp,"# Combination of dummy jk=%d and ",jk); + for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */ + fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); + } + fprintf(ficgp,"\n#\n"); + fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" ",subdirf2(optionfilefiname,"PE_"),jk,ng,nres); + fprintf(ficgp,"\nset ter svg size 640, 480 "); + if (ng==1){ + fprintf(ficgp,"\nset ylabel \"Value of the logit of the model\"\n"); /* exp(a12+b12*x) could be nice */ + fprintf(ficgp,"\nunset log y"); + }else if (ng==2){ + fprintf(ficgp,"\nset ylabel \"Probability\"\n"); + fprintf(ficgp,"\nset log y"); + }else if (ng==3){ + fprintf(ficgp,"\nset ylabel \"Quasi-incidence per year\"\n"); + fprintf(ficgp,"\nset log y"); + }else + fprintf(ficgp,"\nunset title "); + fprintf(ficgp,"\nplot [%.f:%.f] ",ageminpar,agemaxpar); + i=1; + for(k2=1; k2<=nlstate; k2++) { + k3=i; + for(k=1; k<=(nlstate+ndeath); k++) { + if (k != k2){ + switch( ng) { + case 1: + if(nagesqr==0) + fprintf(ficgp," p%d+p%d*x",i,i+1); + else /* nagesqr =1 */ + fprintf(ficgp," p%d+p%d*x+p%d*x*x",i,i+1,i+1+nagesqr); + break; + case 2: /* ng=2 */ + if(nagesqr==0) + fprintf(ficgp," exp(p%d+p%d*x",i,i+1); + else /* nagesqr =1 */ + fprintf(ficgp," exp(p%d+p%d*x+p%d*x*x",i,i+1,i+1+nagesqr); + break; + case 3: + if(nagesqr==0) + fprintf(ficgp," %f*exp(p%d+p%d*x",YEARM/stepm,i,i+1); + else /* nagesqr =1 */ + fprintf(ficgp," %f*exp(p%d+p%d*x+p%d*x*x",YEARM/stepm,i,i+1,i+1+nagesqr); + break; + } + ij=1;/* To be checked else nbcode[0][0] wrong */ + ijp=1; /* product no age */ + /* for(j=3; j <=ncovmodel-nagesqr; j++) { */ + for(j=1; j <=cptcovt; j++) { /* For each covariate of the simplified model */ + /* printf("Tage[%d]=%d, j=%d\n", ij, Tage[ij], j); */ + if(j==Tage[ij]) { /* Product by age */ + if(ij <=cptcovage) { /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, 2 V5 and V1 */ + if(DummyV[j]==0){ + fprintf(ficgp,"+p%d*%d*x",i+j+2+nagesqr-1,Tinvresult[nres][Tvar[j]]);; + }else{ /* quantitative */ + fprintf(ficgp,"+p%d*%f*x",i+j+2+nagesqr-1,Tqinvresult[nres][Tvar[j]]); /* Tqinvresult in decoderesult */ + /* fprintf(ficgp,"+p%d*%d*x",i+j+nagesqr-1,nbcode[Tvar[j-2]][codtabm(jk,Tvar[j-2])]); */ + } + ij++; + } + }else if(j==Tprod[ijp]) { /* */ + /* printf("Tprod[%d]=%d, j=%d\n", ij, Tprod[ijp], j); */ + if(ijp <=cptcovprod) { /* Product */ + if(DummyV[Tvard[ijp][1]]==0){/* Vn is dummy */ + if(DummyV[Tvard[ijp][2]]==0){/* Vn and Vm are dummy */ + /* fprintf(ficgp,"+p%d*%d*%d",i+j+2+nagesqr-1,nbcode[Tvard[ijp][1]][codtabm(jk,j)],nbcode[Tvard[ijp][2]][codtabm(jk,j)]); */ + fprintf(ficgp,"+p%d*%d*%d",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tinvresult[nres][Tvard[ijp][2]]); + }else{ /* Vn is dummy and Vm is quanti */ + /* fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,nbcode[Tvard[ijp][1]][codtabm(jk,j)],Tqinvresult[nres][Tvard[ijp][2]]); */ + fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]); + } + }else{ /* Vn*Vm Vn is quanti */ + if(DummyV[Tvard[ijp][2]]==0){ + fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][2]],Tqinvresult[nres][Tvard[ijp][1]]); + }else{ /* Both quanti */ + fprintf(ficgp,"+p%d*%f*%f",i+j+2+nagesqr-1,Tqinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]); + } + } + ijp++; + } + } else{ /* simple covariate */ + /* fprintf(ficgp,"+p%d*%d",i+j+2+nagesqr-1,nbcode[Tvar[j]][codtabm(jk,j)]); /\* Valgrind bug nbcode *\/ */ + if(Dummy[j]==0){ + fprintf(ficgp,"+p%d*%d",i+j+2+nagesqr-1,Tinvresult[nres][Tvar[j]]); /* */ + }else{ /* quantitative */ + fprintf(ficgp,"+p%d*%f",i+j+2+nagesqr-1,Tqinvresult[nres][Tvar[j]]); /* */ + /* fprintf(ficgp,"+p%d*%d*x",i+j+nagesqr-1,nbcode[Tvar[j-2]][codtabm(jk,Tvar[j-2])]); */ + } + } /* end simple */ + } /* end j */ + }else{ + i=i-ncovmodel; + if(ng !=1 ) /* For logit formula of log p11 is more difficult to get */ + fprintf(ficgp," (1."); + } + + if(ng != 1){ + fprintf(ficgp,")/(1"); + + for(k1=1; k1 <=nlstate; k1++){ + if(nagesqr==0) + fprintf(ficgp,"+exp(p%d+p%d*x",k3+(k1-1)*ncovmodel,k3+(k1-1)*ncovmodel+1); + else /* nagesqr =1 */ + fprintf(ficgp,"+exp(p%d+p%d*x+p%d*x*x",k3+(k1-1)*ncovmodel,k3+(k1-1)*ncovmodel+1,k3+(k1-1)*ncovmodel+1+nagesqr); + + ij=1; + for(j=3; j <=ncovmodel-nagesqr; j++){ + if((j-2)==Tage[ij]) { /* Bug valgrind */ + if(ij <=cptcovage) { /* Bug valgrind */ + fprintf(ficgp,"+p%d*%d*x",k3+(k1-1)*ncovmodel+1+j-2+nagesqr,nbcode[Tvar[j-2]][codtabm(jk,j-2)]); + /* fprintf(ficgp,"+p%d*%d*x",k3+(k1-1)*ncovmodel+1+j-2+nagesqr,nbcode[Tvar[j-2]][codtabm(jk,Tvar[j-2])]); */ + ij++; + } + } + else + fprintf(ficgp,"+p%d*%d",k3+(k1-1)*ncovmodel+1+j-2+nagesqr,nbcode[Tvar[j-2]][codtabm(jk,j-2)]);/* Valgrind bug nbcode */ + } + fprintf(ficgp,")"); + } + fprintf(ficgp,")"); + if(ng ==2) + fprintf(ficgp," t \"p%d%d\" ", k2,k); + else /* ng= 3 */ + fprintf(ficgp," t \"i%d%d\" ", k2,k); + }else{ /* end ng <> 1 */ + if( k !=k2) /* logit p11 is hard to draw */ + fprintf(ficgp," t \"logit(p%d%d)\" ", k2,k); + } + if ((k+k2)!= (nlstate*2+ndeath) && ng != 1) + fprintf(ficgp,","); + if (ng == 1 && k!=k2 && (k+k2)!= (nlstate*2+ndeath)) + fprintf(ficgp,","); + i=i+ncovmodel; + } /* end k */ + } /* end k2 */ + fprintf(ficgp,"\n set out\n"); + } /* end jk */ + } /* end ng */ + /* avoid: */ + fflush(ficgp); +} /* end gnuplot */ + + +/*************** Moving average **************/ +/* int movingaverage(double ***probs, double bage, double fage, double ***mobaverage, int mobilav, double bageout, double fageout){ */ + int movingaverage(double ***probs, double bage, double fage, double ***mobaverage, int mobilav){ + + int i, cpt, cptcod; + int modcovmax =1; + int mobilavrange, mob; + int iage=0; + + double sum=0.; + double age; + double *sumnewp, *sumnewm; + double *agemingood, *agemaxgood; /* Currently identical for all covariates */ + + + /* modcovmax=2*cptcoveff;/\* Max number of modalities. We suppose */ + /* a covariate has 2 modalities, should be equal to ncovcombmax *\/ */ + + sumnewp = vector(1,ncovcombmax); + sumnewm = vector(1,ncovcombmax); + agemingood = vector(1,ncovcombmax); + agemaxgood = vector(1,ncovcombmax); + + for (cptcod=1;cptcod<=ncovcombmax;cptcod++){ + sumnewm[cptcod]=0.; + sumnewp[cptcod]=0.; + agemingood[cptcod]=0; + agemaxgood[cptcod]=0; + } + if (cptcovn<1) ncovcombmax=1; /* At least 1 pass */ + + if(mobilav==1||mobilav ==3 ||mobilav==5 ||mobilav== 7){ + if(mobilav==1) mobilavrange=5; /* default */ + else mobilavrange=mobilav; + for (age=bage; age<=fage; age++) + for (i=1; i<=nlstate;i++) + for (cptcod=1;cptcod<=ncovcombmax;cptcod++) + mobaverage[(int)age][i][cptcod]=probs[(int)age][i][cptcod]; + /* We keep the original values on the extreme ages bage, fage and for + fage+1 and bage-1 we use a 3 terms moving average; for fage+2 bage+2 + we use a 5 terms etc. until the borders are no more concerned. + */ + for (mob=3;mob <=mobilavrange;mob=mob+2){ + for (age=bage+(mob-1)/2; age<=fage-(mob-1)/2; age++){ + for (i=1; i<=nlstate;i++){ + for (cptcod=1;cptcod<=ncovcombmax;cptcod++){ + mobaverage[(int)age][i][cptcod] =probs[(int)age][i][cptcod]; + for (cpt=1;cpt<=(mob-1)/2;cpt++){ + mobaverage[(int)age][i][cptcod] +=probs[(int)age-cpt][i][cptcod]; + mobaverage[(int)age][i][cptcod] +=probs[(int)age+cpt][i][cptcod]; + } + mobaverage[(int)age][i][cptcod]=mobaverage[(int)age][i][cptcod]/mob; + } + } + }/* end age */ + }/* end mob */ + }else + return -1; + for (cptcod=1;cptcod<=ncovcombmax;cptcod++){ + /* for (age=bage+(mob-1)/2; age<=fage-(mob-1)/2; age++){ */ + if(invalidvarcomb[cptcod]){ + printf("\nCombination (%d) ignored because no cases \n",cptcod); + continue; + } + + agemingood[cptcod]=fage-(mob-1)/2; + for (age=fage-(mob-1)/2; age>=bage; age--){/* From oldest to youngest, finding the youngest wrong */ + sumnewm[cptcod]=0.; + for (i=1; i<=nlstate;i++){ + sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod]; + } + if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */ + agemingood[cptcod]=age; + }else{ /* bad */ + for (i=1; i<=nlstate;i++){ + mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemingood[cptcod]][i][cptcod]; + } /* i */ + } /* end bad */ + }/* age */ + sum=0.; + for (i=1; i<=nlstate;i++){ + sum+=mobaverage[(int)agemingood[cptcod]][i][cptcod]; + } + if(fabs(sum - 1.) > 1.e-3) { /* bad */ + printf("For this combination of covariate cptcod=%d, we can't get a smoothed prevalence which sums to one at any descending age!\n",cptcod); + /* for (i=1; i<=nlstate;i++){ */ + /* mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemingood[cptcod]][i][cptcod]; */ + /* } /\* i *\/ */ + } /* end bad */ + /* else{ /\* We found some ages summing to one, we will smooth the oldest *\/ */ + /* From youngest, finding the oldest wrong */ + agemaxgood[cptcod]=bage+(mob-1)/2; + for (age=bage+(mob-1)/2; age<=fage; age++){ + sumnewm[cptcod]=0.; + for (i=1; i<=nlstate;i++){ + sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod]; + } + if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */ + agemaxgood[cptcod]=age; + }else{ /* bad */ + for (i=1; i<=nlstate;i++){ + mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemaxgood[cptcod]][i][cptcod]; + } /* i */ + } /* end bad */ + }/* age */ + sum=0.; + for (i=1; i<=nlstate;i++){ + sum+=mobaverage[(int)agemaxgood[cptcod]][i][cptcod]; + } + if(fabs(sum - 1.) > 1.e-3) { /* bad */ + printf("For this combination of covariate cptcod=%d, we can't get a smoothed prevalence which sums to one at any ascending age!\n",cptcod); + /* for (i=1; i<=nlstate;i++){ */ + /* mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemingood[cptcod]][i][cptcod]; */ + /* } /\* i *\/ */ + } /* end bad */ + + for (age=bage; age<=fage; age++){ + /* printf("%d %d ", cptcod, (int)age); */ + sumnewp[cptcod]=0.; + sumnewm[cptcod]=0.; + for (i=1; i<=nlstate;i++){ + sumnewp[cptcod]+=probs[(int)age][i][cptcod]; + sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod]; + /* printf("%.4f %.4f ",probs[(int)age][i][cptcod], mobaverage[(int)age][i][cptcod]); */ + } + /* printf("%.4f %.4f \n",sumnewp[cptcod], sumnewm[cptcod]); */ + } + /* printf("\n"); */ + /* } */ + /* brutal averaging */ + for (i=1; i<=nlstate;i++){ + for (age=1; age<=bage; age++){ + mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemingood[cptcod]][i][cptcod]; + /* printf("age=%d i=%d cptcod=%d mobaverage=%.4f \n",(int)age,i, cptcod, mobaverage[(int)age][i][cptcod]); */ + } + for (age=fage; age<=AGESUP; age++){ + mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemaxgood[cptcod]][i][cptcod]; + /* printf("age=%d i=%d cptcod=%d mobaverage=%.4f \n",(int)age,i, cptcod, mobaverage[(int)age][i][cptcod]); */ + } + } /* end i status */ + for (i=nlstate+1; i<=nlstate+ndeath;i++){ + for (age=1; age<=AGESUP; age++){ + /*printf("i=%d, age=%d, cptcod=%d\n",i, (int)age, cptcod);*/ + mobaverage[(int)age][i][cptcod]=0.; + } + } + }/* end cptcod */ + free_vector(sumnewm,1, ncovcombmax); + free_vector(sumnewp,1, ncovcombmax); + free_vector(agemaxgood,1, ncovcombmax); + free_vector(agemingood,1, ncovcombmax); + return 0; + }/* End movingaverage */ + + +/************** Forecasting ******************/ + 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){ + /* proj1, year, month, day of starting projection + agemin, agemax range of age + dateprev1 dateprev2 range of dates during which prevalence is computed + anproj2 year of en of projection (same day and month as proj1). + */ + int yearp, stepsize, hstepm, nhstepm, j, k, cptcod, i, h, i1, k4, nres=0; + double agec; /* generic age */ + double agelim, ppij, yp,yp1,yp2,jprojmean,mprojmean,anprojmean; + double *popeffectif,*popcount; + double ***p3mat; + /* double ***mobaverage; */ + char fileresf[FILENAMELENGTH]; + + agelim=AGESUP; + /* Compute observed prevalence between dateprev1 and dateprev2 by counting the number of people + in each health status at the date of interview (if between dateprev1 and dateprev2). + We still use firstpass and lastpass as another selection. + */ + /* freqsummary(fileres, agemin, agemax, s, agev, nlstate, imx,Tvaraff,nbcode, ncodemax,mint,anint,strstart,\ */ + /* firstpass, lastpass, stepm, weightopt, model); */ + + strcpy(fileresf,"F_"); + strcat(fileresf,fileresu); + if((ficresf=fopen(fileresf,"w"))==NULL) { + printf("Problem with forecast resultfile: %s\n", fileresf); + fprintf(ficlog,"Problem with forecast resultfile: %s\n", fileresf); + } + printf("\nComputing forecasting: result on file '%s', please wait... \n", fileresf); + fprintf(ficlog,"\nComputing forecasting: result on file '%s', please wait... \n", fileresf); + + if (cptcoveff==0) ncodemax[cptcoveff]=1; + + + stepsize=(int) (stepm+YEARM-1)/YEARM; + if (stepm<=12) stepsize=1; + if(estepm < stepm){ + printf ("Problem %d lower than %d\n",estepm, stepm); + } + else hstepm=estepm; + + hstepm=hstepm/stepm; + yp1=modf(dateintmean,&yp);/* extracts integral of datemean in yp and + fractional in yp1 */ + anprojmean=yp; + yp2=modf((yp1*12),&yp); + mprojmean=yp; + yp1=modf((yp2*30.5),&yp); + jprojmean=yp; + if(jprojmean==0) jprojmean=1; + if(mprojmean==0) jprojmean=1; + + i1=pow(2,cptcoveff); + if (cptcovn < 1){i1=1;} + + fprintf(ficresf,"# Mean day of interviews %.lf/%.lf/%.lf (%.2f) between %.2f and %.2f \n",jprojmean,mprojmean,anprojmean,dateintmean,dateprev1,dateprev2); + + fprintf(ficresf,"#****** Routine prevforecast **\n"); + +/* if (h==(int)(YEARM*yearp)){ */ + for(nres=1; nres <= nresult; nres++) /* For each resultline */ + for(k=1; k<=i1;k++){ + if(i1 != 1 && TKresult[nres]!= k) + continue; + if(invalidvarcomb[k]){ + printf("\nCombination (%d) projection ignored because no cases \n",k); + continue; + } + fprintf(ficresf,"\n#****** hpijx=probability over h years, hp.jx is weighted by observed prev \n#"); + for(j=1;j<=cptcoveff;j++) { + fprintf(ficresf," V%d (=) %d",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]); + } + for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */ + fprintf(ficresf," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); + } + fprintf(ficresf," yearproj age"); + for(j=1; j<=nlstate+ndeath;j++){ + for(i=1; i<=nlstate;i++) + fprintf(ficresf," p%d%d",i,j); + fprintf(ficresf," wp.%d",j); + } + for (yearp=0; yearp<=(anproj2-anproj1);yearp +=stepsize) { + fprintf(ficresf,"\n"); + fprintf(ficresf,"\n# Forecasting at date %.lf/%.lf/%.lf ",jproj1,mproj1,anproj1+yearp); + for (agec=fage; agec>=(ageminpar-1); agec--){ + nhstepm=(int) rint((agelim-agec)*YEARM/stepm); + nhstepm = nhstepm/hstepm; + p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); + oldm=oldms;savm=savms; + hpxij(p3mat,nhstepm,agec,hstepm,p,nlstate,stepm,oldm,savm, k,nres); + + for (h=0; h<=nhstepm; h++){ + if (h*hstepm/YEARM*stepm ==yearp) { + fprintf(ficresf,"\n"); + for(j=1;j<=cptcoveff;j++) + fprintf(ficresf,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]); + fprintf(ficresf,"%.f %.f ",anproj1+yearp,agec+h*hstepm/YEARM*stepm); + } + for(j=1; j<=nlstate+ndeath;j++) { + ppij=0.; + for(i=1; i<=nlstate;i++) { + if (mobilav==1) + ppij=ppij+p3mat[i][j][h]*mobaverage[(int)agec][i][k]; + else { + ppij=ppij+p3mat[i][j][h]*probs[(int)(agec)][i][k]; + } + if (h*hstepm/YEARM*stepm== yearp) { + fprintf(ficresf," %.3f", p3mat[i][j][h]); + } + } /* end i */ + if (h*hstepm/YEARM*stepm==yearp) { + fprintf(ficresf," %.3f", ppij); + } + }/* end j */ + } /* end h */ + free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); + } /* end agec */ + } /* end yearp */ + } /* end k */ + + fclose(ficresf); + printf("End of Computing forecasting \n"); + fprintf(ficlog,"End of Computing forecasting\n"); + +} + +/* /\************** Back Forecasting ******************\/ */ +/* void prevbackforecast(char fileres[], double anback1, double mback1, double jback1, double ageminpar, double agemax, double dateprev1, double dateprev2, int mobilav, double bage, double fage, int firstpass, int lastpass, double anback2, double p[], int cptcoveff){ */ +/* /\* back1, year, month, day of starting backection */ +/* agemin, agemax range of age */ +/* dateprev1 dateprev2 range of dates during which prevalence is computed */ +/* anback2 year of en of backection (same day and month as back1). */ +/* *\/ */ +/* int yearp, stepsize, hstepm, nhstepm, j, k, cptcod, i, h, i1; */ +/* double agec; /\* generic age *\/ */ +/* double agelim, ppij, yp,yp1,yp2,jprojmean,mprojmean,anprojmean; */ +/* double *popeffectif,*popcount; */ +/* double ***p3mat; */ +/* /\* double ***mobaverage; *\/ */ +/* char fileresfb[FILENAMELENGTH]; */ + +/* agelim=AGESUP; */ +/* /\* Compute observed prevalence between dateprev1 and dateprev2 by counting the number of people */ +/* in each health status at the date of interview (if between dateprev1 and dateprev2). */ +/* We still use firstpass and lastpass as another selection. */ +/* *\/ */ +/* /\* freqsummary(fileres, agemin, agemax, s, agev, nlstate, imx,Tvaraff,nbcode, ncodemax,mint,anint,strstart,\ *\/ */ +/* /\* firstpass, lastpass, stepm, weightopt, model); *\/ */ +/* prevalence(probs, ageminpar, agemax, s, agev, nlstate, imx, Tvar, nbcode, ncodemax, mint, anint, dateprev1, dateprev2, firstpass, lastpass); */ + +/* strcpy(fileresfb,"FB_"); */ +/* strcat(fileresfb,fileresu); */ +/* if((ficresfb=fopen(fileresfb,"w"))==NULL) { */ +/* printf("Problem with back forecast resultfile: %s\n", fileresfb); */ +/* fprintf(ficlog,"Problem with back forecast resultfile: %s\n", fileresfb); */ +/* } */ +/* printf("Computing back forecasting: result on file '%s', please wait... \n", fileresfb); */ +/* fprintf(ficlog,"Computing back forecasting: result on file '%s', please wait... \n", fileresfb); */ + +/* if (cptcoveff==0) ncodemax[cptcoveff]=1; */ + +/* /\* if (mobilav!=0) { *\/ */ +/* /\* mobaverage= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); *\/ */ +/* /\* if (movingaverage(probs, ageminpar, fage, mobaverage,mobilav)!=0){ *\/ */ +/* /\* fprintf(ficlog," Error in movingaverage mobilav=%d\n",mobilav); *\/ */ +/* /\* printf(" Error in movingaverage mobilav=%d\n",mobilav); *\/ */ +/* /\* } *\/ */ +/* /\* } *\/ */ + +/* stepsize=(int) (stepm+YEARM-1)/YEARM; */ +/* if (stepm<=12) stepsize=1; */ +/* if(estepm < stepm){ */ +/* printf ("Problem %d lower than %d\n",estepm, stepm); */ +/* } */ +/* else hstepm=estepm; */ + +/* hstepm=hstepm/stepm; */ +/* yp1=modf(dateintmean,&yp);/\* extracts integral of datemean in yp and */ +/* fractional in yp1 *\/ */ +/* anprojmean=yp; */ +/* yp2=modf((yp1*12),&yp); */ +/* mprojmean=yp; */ +/* yp1=modf((yp2*30.5),&yp); */ +/* jprojmean=yp; */ +/* if(jprojmean==0) jprojmean=1; */ +/* if(mprojmean==0) jprojmean=1; */ + +/* i1=cptcoveff; */ +/* if (cptcovn < 1){i1=1;} */ + +/* fprintf(ficresfb,"# Mean day of interviews %.lf/%.lf/%.lf (%.2f) between %.2f and %.2f \n",jprojmean,mprojmean,anprojmean,dateintmean,dateprev1,dateprev2); */ + +/* fprintf(ficresfb,"#****** Routine prevbackforecast **\n"); */ + +/* /\* if (h==(int)(YEARM*yearp)){ *\/ */ +/* for(cptcov=1, k=0;cptcov<=i1;cptcov++){ */ +/* for(cptcod=1;cptcod<=ncodemax[cptcoveff];cptcod++){ */ +/* k=k+1; */ +/* fprintf(ficresfb,"\n#****** hbijx=probability over h years, hp.jx is weighted by observed prev \n#"); */ +/* for(j=1;j<=cptcoveff;j++) { */ +/* fprintf(ficresfb," V%d (=) %d",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]); */ +/* } */ +/* fprintf(ficresfb," yearbproj age"); */ +/* for(j=1; j<=nlstate+ndeath;j++){ */ +/* for(i=1; i<=nlstate;i++) */ +/* fprintf(ficresfb," p%d%d",i,j); */ +/* fprintf(ficresfb," p.%d",j); */ +/* } */ +/* for (yearp=0; yearp>=(anback2-anback1);yearp -=stepsize) { */ +/* /\* for (yearp=0; yearp<=(anproj2-anproj1);yearp +=stepsize) { *\/ */ +/* fprintf(ficresfb,"\n"); */ +/* fprintf(ficresfb,"\n# Back Forecasting at date %.lf/%.lf/%.lf ",jback1,mback1,anback1+yearp); */ +/* for (agec=fage; agec>=(ageminpar-1); agec--){ */ +/* nhstepm=(int) rint((agelim-agec)*YEARM/stepm); */ +/* nhstepm = nhstepm/hstepm; */ +/* p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */ +/* oldm=oldms;savm=savms; */ +/* hbxij(p3mat,nhstepm,agec,hstepm,p,prevacurrent,nlstate,stepm,oldm,savm,oldm,savm, dnewm, doldm, dsavm, k); */ +/* for (h=0; h<=nhstepm; h++){ */ +/* if (h*hstepm/YEARM*stepm ==yearp) { */ +/* fprintf(ficresfb,"\n"); */ +/* for(j=1;j<=cptcoveff;j++) */ +/* fprintf(ficresfb,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]); */ +/* fprintf(ficresfb,"%.f %.f ",anback1+yearp,agec+h*hstepm/YEARM*stepm); */ +/* } */ +/* for(j=1; j<=nlstate+ndeath;j++) { */ +/* ppij=0.; */ +/* for(i=1; i<=nlstate;i++) { */ +/* if (mobilav==1) */ +/* ppij=ppij+p3mat[i][j][h]*mobaverage[(int)agec][i][cptcod]; */ +/* else { */ +/* ppij=ppij+p3mat[i][j][h]*probs[(int)(agec)][i][cptcod]; */ +/* } */ +/* if (h*hstepm/YEARM*stepm== yearp) { */ +/* fprintf(ficresfb," %.3f", p3mat[i][j][h]); */ +/* } */ +/* } /\* end i *\/ */ +/* if (h*hstepm/YEARM*stepm==yearp) { */ +/* fprintf(ficresfb," %.3f", ppij); */ +/* } */ +/* }/\* end j *\/ */ +/* } /\* end h *\/ */ +/* free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */ +/* } /\* end agec *\/ */ +/* } /\* end yearp *\/ */ +/* } /\* end cptcod *\/ */ +/* } /\* end cptcov *\/ */ + +/* /\* if (mobilav!=0) free_ma3x(mobaverage,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); *\/ */ + +/* fclose(ficresfb); */ +/* printf("End of Computing Back forecasting \n"); */ +/* fprintf(ficlog,"End of Computing Back forecasting\n"); */ + +/* } */ + +/************** Forecasting *****not tested NB*************/ +/* 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){ */ + +/* int cpt, stepsize, hstepm, nhstepm, j,k,c, cptcod, i,h; */ +/* int *popage; */ +/* double calagedatem, agelim, kk1, kk2; */ +/* double *popeffectif,*popcount; */ +/* double ***p3mat,***tabpop,***tabpopprev; */ +/* /\* double ***mobaverage; *\/ */ +/* char filerespop[FILENAMELENGTH]; */ + +/* tabpop= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */ +/* tabpopprev= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */ +/* agelim=AGESUP; */ +/* calagedatem=(anpyram+mpyram/12.+jpyram/365.-dateintmean)*YEARM; */ + +/* prevalence(probs, ageminpar, agemax, s, agev, nlstate, imx, Tvar, nbcode, ncodemax, mint, anint, dateprev1, dateprev2, firstpass, lastpass); */ + + +/* strcpy(filerespop,"POP_"); */ +/* strcat(filerespop,fileresu); */ +/* if((ficrespop=fopen(filerespop,"w"))==NULL) { */ +/* printf("Problem with forecast resultfile: %s\n", filerespop); */ +/* fprintf(ficlog,"Problem with forecast resultfile: %s\n", filerespop); */ +/* } */ +/* printf("Computing forecasting: result on file '%s' \n", filerespop); */ +/* fprintf(ficlog,"Computing forecasting: result on file '%s' \n", filerespop); */ + +/* if (cptcoveff==0) ncodemax[cptcoveff]=1; */ + +/* /\* if (mobilav!=0) { *\/ */ +/* /\* mobaverage= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); *\/ */ +/* /\* if (movingaverage(probs, ageminpar, fage, mobaverage,mobilav)!=0){ *\/ */ +/* /\* fprintf(ficlog," Error in movingaverage mobilav=%d\n",mobilav); *\/ */ +/* /\* printf(" Error in movingaverage mobilav=%d\n",mobilav); *\/ */ +/* /\* } *\/ */ +/* /\* } *\/ */ + +/* stepsize=(int) (stepm+YEARM-1)/YEARM; */ +/* if (stepm<=12) stepsize=1; */ + +/* agelim=AGESUP; */ + +/* hstepm=1; */ +/* hstepm=hstepm/stepm; */ + +/* if (popforecast==1) { */ +/* if((ficpop=fopen(popfile,"r"))==NULL) { */ +/* printf("Problem with population file : %s\n",popfile);exit(0); */ +/* fprintf(ficlog,"Problem with population file : %s\n",popfile);exit(0); */ +/* } */ +/* popage=ivector(0,AGESUP); */ +/* popeffectif=vector(0,AGESUP); */ +/* popcount=vector(0,AGESUP); */ + +/* i=1; */ +/* while ((c=fscanf(ficpop,"%d %lf\n",&popage[i],&popcount[i])) != EOF) i=i+1; */ + +/* imx=i; */ +/* for (i=1; i=(ageminpar-((int)calagedatem %12)/12.); agedeb--){ */ +/* nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); */ +/* nhstepm = nhstepm/hstepm; */ + +/* p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */ +/* oldm=oldms;savm=savms; */ +/* hpxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k); */ + +/* for (h=0; h<=nhstepm; h++){ */ +/* if (h==(int) (calagedatem+YEARM*cpt)) { */ +/* fprintf(ficrespop,"\n %3.f ",agedeb+h*hstepm/YEARM*stepm); */ +/* } */ +/* for(j=1; j<=nlstate+ndeath;j++) { */ +/* kk1=0.;kk2=0; */ +/* for(i=1; i<=nlstate;i++) { */ +/* if (mobilav==1) */ +/* kk1=kk1+p3mat[i][j][h]*mobaverage[(int)agedeb+1][i][cptcod]; */ +/* else { */ +/* kk1=kk1+p3mat[i][j][h]*probs[(int)(agedeb+1)][i][cptcod]; */ +/* } */ +/* } */ +/* if (h==(int)(calagedatem+12*cpt)){ */ +/* tabpop[(int)(agedeb)][j][cptcod]=kk1; */ +/* /\*fprintf(ficrespop," %.3f", kk1); */ +/* if (popforecast==1) fprintf(ficrespop," [%.f]", kk1*popeffectif[(int)agedeb+1]);*\/ */ +/* } */ +/* } */ +/* for(i=1; i<=nlstate;i++){ */ +/* kk1=0.; */ +/* for(j=1; j<=nlstate;j++){ */ +/* kk1= kk1+tabpop[(int)(agedeb)][j][cptcod]; */ +/* } */ +/* tabpopprev[(int)(agedeb)][i][cptcod]=tabpop[(int)(agedeb)][i][cptcod]/kk1*popeffectif[(int)(agedeb+(calagedatem+12*cpt)*hstepm/YEARM*stepm-1)]; */ +/* } */ + +/* if (h==(int)(calagedatem+12*cpt)) */ +/* for(j=1; j<=nlstate;j++) */ +/* fprintf(ficrespop," %15.2f",tabpopprev[(int)(agedeb+1)][j][cptcod]); */ +/* } */ +/* free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */ +/* } */ +/* } */ + +/* /\******\/ */ + +/* for (cpt=1; cpt<=(anpyram1-anpyram);cpt++) { */ +/* fprintf(ficrespop,"\n\n# Forecasting at date %.lf/%.lf/%.lf ",jpyram,mpyram,anpyram+cpt); */ +/* for (agedeb=(fage-((int)calagedatem %12/12.)); agedeb>=(ageminpar-((int)calagedatem %12)/12.); agedeb--){ */ +/* nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); */ +/* nhstepm = nhstepm/hstepm; */ + +/* p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */ +/* oldm=oldms;savm=savms; */ +/* hpxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k); */ +/* for (h=0; h<=nhstepm; h++){ */ +/* if (h==(int) (calagedatem+YEARM*cpt)) { */ +/* fprintf(ficresf,"\n %3.f ",agedeb+h*hstepm/YEARM*stepm); */ +/* } */ +/* for(j=1; j<=nlstate+ndeath;j++) { */ +/* kk1=0.;kk2=0; */ +/* for(i=1; i<=nlstate;i++) { */ +/* kk1=kk1+p3mat[i][j][h]*tabpopprev[(int)agedeb+1][i][cptcod]; */ +/* } */ +/* if (h==(int)(calagedatem+12*cpt)) fprintf(ficresf," %15.2f", kk1); */ +/* } */ +/* } */ +/* free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */ +/* } */ +/* } */ +/* } */ +/* } */ + +/* /\* if (mobilav!=0) free_ma3x(mobaverage,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); *\/ */ + +/* if (popforecast==1) { */ +/* free_ivector(popage,0,AGESUP); */ +/* free_vector(popeffectif,0,AGESUP); */ +/* free_vector(popcount,0,AGESUP); */ +/* } */ +/* free_ma3x(tabpop,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */ +/* free_ma3x(tabpopprev,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */ +/* fclose(ficrespop); */ +/* } /\* End of popforecast *\/ */ + +int fileappend(FILE *fichier, char *optionfich) +{ + if((fichier=fopen(optionfich,"a"))==NULL) { + printf("Problem with file: %s\n", optionfich); + fprintf(ficlog,"Problem with file: %s\n", optionfich); + return (0); + } + fflush(fichier); + return (1); +} + + +/**************** function prwizard **********************/ +void prwizard(int ncovmodel, int nlstate, int ndeath, char model[], FILE *ficparo) +{ + + /* Wizard to print covariance matrix template */ + + char ca[32], cb[32]; + int i,j, k, li, lj, lk, ll, jj, npar, itimes; + int numlinepar; + + printf("# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n"); + fprintf(ficparo,"# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n"); + for(i=1; i <=nlstate; i++){ + jj=0; + for(j=1; j <=nlstate+ndeath; j++){ + if(j==i) continue; + jj++; + /*ca[0]= k+'a'-1;ca[1]='\0';*/ + printf("%1d%1d",i,j); + fprintf(ficparo,"%1d%1d",i,j); + for(k=1; k<=ncovmodel;k++){ + /* printf(" %lf",param[i][j][k]); */ + /* fprintf(ficparo," %lf",param[i][j][k]); */ + printf(" 0."); + fprintf(ficparo," 0."); + } + printf("\n"); + fprintf(ficparo,"\n"); + } + } + printf("# Scales (for hessian or gradient estimation)\n"); + fprintf(ficparo,"# Scales (for hessian or gradient estimation)\n"); + npar= (nlstate+ndeath-1)*nlstate*ncovmodel; /* Number of parameters*/ + for(i=1; i <=nlstate; i++){ + jj=0; + for(j=1; j <=nlstate+ndeath; j++){ + if(j==i) continue; + jj++; + fprintf(ficparo,"%1d%1d",i,j); + printf("%1d%1d",i,j); + fflush(stdout); + for(k=1; k<=ncovmodel;k++){ + /* printf(" %le",delti3[i][j][k]); */ + /* fprintf(ficparo," %le",delti3[i][j][k]); */ + printf(" 0."); + fprintf(ficparo," 0."); + } + numlinepar++; + printf("\n"); + fprintf(ficparo,"\n"); + } + } + printf("# Covariance matrix\n"); +/* # 121 Var(a12)\n\ */ +/* # 122 Cov(b12,a12) Var(b12)\n\ */ +/* # 131 Cov(a13,a12) Cov(a13,b12, Var(a13)\n\ */ +/* # 132 Cov(b13,a12) Cov(b13,b12, Cov(b13,a13) Var(b13)\n\ */ +/* # 212 Cov(a21,a12) Cov(a21,b12, Cov(a21,a13) Cov(a21,b13) Var(a21)\n\ */ +/* # 212 Cov(b21,a12) Cov(b21,b12, Cov(b21,a13) Cov(b21,b13) Cov(b21,a21) Var(b21)\n\ */ +/* # 232 Cov(a23,a12) Cov(a23,b12, Cov(a23,a13) Cov(a23,b13) Cov(a23,a21) Cov(a23,b21) Var(a23)\n\ */ +/* # 232 Cov(b23,a12) Cov(b23,b12) ... Var (b23)\n" */ + fflush(stdout); + fprintf(ficparo,"# 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" */ + + for(itimes=1;itimes<=2;itimes++){ + jj=0; + for(i=1; i <=nlstate; i++){ + for(j=1; j <=nlstate+ndeath; j++){ + if(j==i) continue; + for(k=1; k<=ncovmodel;k++){ + jj++; + ca[0]= k+'a'-1;ca[1]='\0'; + if(itimes==1){ + printf("#%1d%1d%d",i,j,k); + fprintf(ficparo,"#%1d%1d%d",i,j,k); + }else{ + printf("%1d%1d%d",i,j,k); + fprintf(ficparo,"%1d%1d%d",i,j,k); + /* printf(" %.5le",matcov[i][j]); */ + } + ll=0; + for(li=1;li <=nlstate; li++){ + for(lj=1;lj <=nlstate+ndeath; lj++){ + if(lj==li) continue; + for(lk=1;lk<=ncovmodel;lk++){ + ll++; + if(ll<=jj){ + cb[0]= lk +'a'-1;cb[1]='\0'; + if(ll0) printf("i=%d ageex=%lf agecens=%lf agedc=%lf cens=%d %d\n" ,i,ageexmed[i],agecens[i],agedc[i],cens[i],wav[i]);*/ + + for (i=1;i<=imx ; i++) + { + if (cens[i] == 1 && wav[i]>1) + A=-x[1]/(x[2])*(exp(x[2]*(agecens[i]-agegomp))-exp(x[2]*(ageexmed[i]-agegomp))); + + if (cens[i] == 0 && wav[i]>1) + A=-x[1]/(x[2])*(exp(x[2]*(agedc[i]-agegomp))-exp(x[2]*(ageexmed[i]-agegomp))) + +log(x[1]/YEARM)+x[2]*(agedc[i]-agegomp)+log(YEARM); + + /*if (wav[i] > 1 && agecens[i] > 15) {*/ /* ??? */ + if (wav[i] > 1 ) { /* ??? */ + L=L+A*weight[i]; + /* 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]);*/ + } + } + + /*printf("x1=%2.9f x2=%2.9f x3=%2.9f L=%f\n",x[1],x[2],x[3],L);*/ + + return -2*L*num/sump; +} + +#ifdef GSL +/******************* Gompertz_f Likelihood ******************************/ +double gompertz_f(const gsl_vector *v, void *params) +{ + double A,B,LL=0.0,sump=0.,num=0.; + double *x= (double *) v->data; + int i,n=0; /* n is the size of the sample */ + + for (i=0;i<=imx-1 ; i++) { + sump=sump+weight[i]; + /* sump=sump+1;*/ + num=num+1; + } + + + /* for (i=0; i<=imx; i++) + 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]);*/ + printf("x[0]=%lf x[1]=%lf\n",x[0],x[1]); + for (i=1;i<=imx ; i++) + { + if (cens[i] == 1 && wav[i]>1) + A=-x[0]/(x[1])*(exp(x[1]*(agecens[i]-agegomp))-exp(x[1]*(ageexmed[i]-agegomp))); + + if (cens[i] == 0 && wav[i]>1) + A=-x[0]/(x[1])*(exp(x[1]*(agedc[i]-agegomp))-exp(x[1]*(ageexmed[i]-agegomp))) + +log(x[0]/YEARM)+x[1]*(agedc[i]-agegomp)+log(YEARM); + + /*if (wav[i] > 1 && agecens[i] > 15) {*/ /* ??? */ + if (wav[i] > 1 ) { /* ??? */ + LL=LL+A*weight[i]; + /* 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]);*/ + } + } + + /*printf("x1=%2.9f x2=%2.9f x3=%2.9f L=%f\n",x[1],x[2],x[3],L);*/ + printf("x[0]=%lf x[1]=%lf -2*LL*num/sump=%lf\n",x[0],x[1],-2*LL*num/sump); + + return -2*LL*num/sump; +} +#endif + +/******************* Printing html file ***********/ +void printinghtmlmort(char fileresu[], char title[], char datafile[], int firstpass, \ + int lastpass, int stepm, int weightopt, char model[],\ + int imx, double p[],double **matcov,double agemortsup){ + int i,k; + + fprintf(fichtm,"
      • Result files

        \n Force of mortality. Parameters of the Gompertz fit (with confidence interval in brackets):
        "); + fprintf(fichtm," mu(age) =%lf*exp(%lf*(age-%d)) per year

        ",p[1],p[2],agegomp); + for (i=1;i<=2;i++) + fprintf(fichtm," p[%d] = %lf [%f ; %f]
        \n",i,p[i],p[i]-2*sqrt(matcov[i][i]),p[i]+2*sqrt(matcov[i][i])); + fprintf(fichtm,"

        "); + fprintf(fichtm,"
      "); + +fprintf(fichtm,"
      • Life table

        \n
        "); + + fprintf(fichtm,"\nAge lx qx d(x,x+1) Lx Tx e
        "); + + for (k=agegomp;k<(agemortsup-2);k++) + fprintf(fichtm,"%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]); + + + fflush(fichtm); +} + +/******************* Gnuplot file **************/ +void printinggnuplotmort(char fileresu[], char optionfilefiname[], double ageminpar, double agemaxpar, double fage , char pathc[], double p[]){ + + char dirfileres[132],optfileres[132]; + + int ng; + + + /*#ifdef windows */ + fprintf(ficgp,"cd \"%s\" \n",pathc); + /*#endif */ + + + strcpy(dirfileres,optionfilefiname); + strcpy(optfileres,"vpl"); + fprintf(ficgp,"set out \"graphmort.svg\"\n "); + fprintf(ficgp,"set xlabel \"Age\"\n set ylabel \"Force of mortality (per year)\" \n "); + fprintf(ficgp, "set ter svg size 640, 480\n set log y\n"); + /* fprintf(ficgp, "set size 0.65,0.65\n"); */ + fprintf(ficgp,"plot [%d:100] %lf*exp(%lf*(x-%d))",agegomp,p[1],p[2],agegomp); + +} + +int readdata(char datafile[], int firstobs, int lastobs, int *imax) +{ + + /*-------- data file ----------*/ + FILE *fic; + char dummy[]=" "; + int i=0, j=0, n=0, iv=0, v; + int lstra; + int linei, month, year,iout; + char line[MAXLINE], linetmp[MAXLINE]; + char stra[MAXLINE], strb[MAXLINE]; + char *stratrunc; + + DummyV=ivector(1,NCOVMAX); /* 1 to 3 */ + FixedV=ivector(1,NCOVMAX); /* 1 to 3 */ + + for(v=1; v <=ncovcol;v++){ + DummyV[v]=0; + FixedV[v]=0; + } + for(v=ncovcol+1; v <=ncovcol+nqv;v++){ + DummyV[v]=1; + FixedV[v]=0; + } + for(v=ncovcol+nqv+1; v <=ncovcol+nqv+ntv;v++){ + DummyV[v]=0; + FixedV[v]=1; + } + for(v=ncovcol+nqv+ntv+1; v <=ncovcol+nqv+ntv+nqtv;v++){ + DummyV[v]=1; + FixedV[v]=1; + } + for(v=1; v <=ncovcol+nqv+ntv+nqtv;v++){ + printf("Covariate type in the data: V%d, DummyV(V%d)=%d, FixedV(V%d)=%d\n",v,v,DummyV[v],v,FixedV[v]); + 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]); + } + + if((fic=fopen(datafile,"r"))==NULL) { + printf("Problem while opening datafile: %s with errno='%s'\n", datafile,strerror(errno));fflush(stdout); + fprintf(ficlog,"Problem while opening datafile: %s with errno='%s'\n", datafile,strerror(errno));fflush(ficlog);return 1; + } + + i=1; + linei=0; + while ((fgets(line, MAXLINE, fic) != NULL) &&((i >= firstobs) && (i <=lastobs))) { + linei=linei+1; + for(j=strlen(line); j>=0;j--){ /* Untabifies line */ + if(line[j] == '\t') + line[j] = ' '; + } + for(j=strlen(line)-1; (line[j]==' ')||(line[j]==10)||(line[j]==13);j--){ + ; + }; + line[j+1]=0; /* Trims blanks at end of line */ + if(line[0]=='#'){ + fprintf(ficlog,"Comment line\n%s\n",line); + printf("Comment line\n%s\n",line); + continue; + } + trimbb(linetmp,line); /* Trims multiple blanks in line */ + strcpy(line, linetmp); + + /* Loops on waves */ + for (j=maxwav;j>=1;j--){ + for (iv=nqtv;iv>=1;iv--){ /* Loop on time varying quantitative variables */ + cutv(stra, strb, line, ' '); + if(strb[0]=='.') { /* Missing value */ + lval=-1; + cotqvar[j][iv][i]=-1; /* 0.0/0.0 */ + cotvar[j][ntv+iv][i]=-1; /* For performance reasons */ + if(isalpha(strb[1])) { /* .m or .d Really Missing value */ + 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); + 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); + return 1; + } + }else{ + errno=0; + /* what_kind_of_number(strb); */ + dval=strtod(strb,&endptr); + /* if( strb[0]=='\0' || (*endptr != '\0')){ */ + /* if(strb != endptr && *endptr == '\0') */ + /* dval=dlval; */ + /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN)) */ + if( strb[0]=='\0' || (*endptr != '\0')){ + 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); + 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); + return 1; + } + cotqvar[j][iv][i]=dval; + cotvar[j][ntv+iv][i]=dval; + } + strcpy(line,stra); + }/* end loop ntqv */ + + for (iv=ntv;iv>=1;iv--){ /* Loop on time varying dummies */ + cutv(stra, strb, line, ' '); + if(strb[0]=='.') { /* Missing value */ + lval=-1; + }else{ + errno=0; + lval=strtol(strb,&endptr,10); + /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN))*/ + if( strb[0]=='\0' || (*endptr != '\0')){ + 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); + 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); + return 1; + } + } + if(lval <-1 || lval >1){ + printf("Error reading data around '%ld' at line number %d for individual %d, '%s'\n \ + Should be a value of %d(nth) covariate (0 should be the value for the reference and 1\n \ + for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \ + For example, for multinomial values like 1, 2 and 3,\n \ + build V1=0 V2=0 for the reference value (1),\n \ + V1=1 V2=0 for (2) \n \ + and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \ + output of IMaCh is often meaningless.\n \ + Exiting.\n",lval,linei, i,line,j); + fprintf(ficlog,"Error reading data around '%ld' at line number %d for individual %d, '%s'\n \ + Should be a value of %d(nth) covariate (0 should be the value for the reference and 1\n \ + for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \ + For example, for multinomial values like 1, 2 and 3,\n \ + build V1=0 V2=0 for the reference value (1),\n \ + V1=1 V2=0 for (2) \n \ + and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \ + output of IMaCh is often meaningless.\n \ + Exiting.\n",lval,linei, i,line,j);fflush(ficlog); + return 1; + } + cotvar[j][iv][i]=(double)(lval); + strcpy(line,stra); + }/* end loop ntv */ + + /* Statuses at wave */ + cutv(stra, strb, line, ' '); + if(strb[0]=='.') { /* Missing value */ + lval=-1; + }else{ + errno=0; + lval=strtol(strb,&endptr,10); + /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN))*/ + if( strb[0]=='\0' || (*endptr != '\0')){ + 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); + 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); + return 1; + } + } + + s[j][i]=lval; + + /* Date of Interview */ + strcpy(line,stra); + cutv(stra, strb,line,' '); + if( (iout=sscanf(strb,"%d/%d",&month, &year)) != 0){ + } + else if( (iout=sscanf(strb,"%s.",dummy)) != 0){ + month=99; + year=9999; + }else{ + 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); + 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); + return 1; + } + anint[j][i]= (double) year; + mint[j][i]= (double)month; + strcpy(line,stra); + } /* End loop on waves */ + + /* Date of death */ + cutv(stra, strb,line,' '); + if( (iout=sscanf(strb,"%d/%d",&month, &year)) != 0){ + } + else if( (iout=sscanf(strb,"%s.",dummy)) != 0){ + month=99; + year=9999; + }else{ + 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); + 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); + return 1; + } + andc[i]=(double) year; + moisdc[i]=(double) month; + strcpy(line,stra); + + /* Date of birth */ + cutv(stra, strb,line,' '); + if( (iout=sscanf(strb,"%d/%d",&month, &year)) != 0){ + } + else if( (iout=sscanf(strb,"%s.", dummy)) != 0){ + month=99; + year=9999; + }else{ + 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); + 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); + return 1; + } + if (year==9999) { + 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); + 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); + return 1; + + } + annais[i]=(double)(year); + moisnais[i]=(double)(month); + strcpy(line,stra); + + /* Sample weight */ + cutv(stra, strb,line,' '); + errno=0; + dval=strtod(strb,&endptr); + if( strb[0]=='\0' || (*endptr != '\0')){ + printf("Error reading data around '%f' at line number %d, \"%s\" for individual %d\nShould be a weight. Exiting.\n",dval, i,line,linei); + 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); + fflush(ficlog); + return 1; + } + weight[i]=dval; + strcpy(line,stra); + + for (iv=nqv;iv>=1;iv--){ /* Loop on fixed quantitative variables */ + cutv(stra, strb, line, ' '); + if(strb[0]=='.') { /* Missing value */ + lval=-1; + }else{ + errno=0; + /* what_kind_of_number(strb); */ + dval=strtod(strb,&endptr); + /* if(strb != endptr && *endptr == '\0') */ + /* dval=dlval; */ + /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN)) */ + if( strb[0]=='\0' || (*endptr != '\0')){ + 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); + 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); + return 1; + } + coqvar[iv][i]=dval; + covar[ncovcol+iv][i]=dval; /* including qvar in standard covar for performance reasons */ + } + strcpy(line,stra); + }/* end loop nqv */ + + /* Covariate values */ + for (j=ncovcol;j>=1;j--){ + cutv(stra, strb,line,' '); + if(strb[0]=='.') { /* Missing covariate value */ + lval=-1; + }else{ + errno=0; + lval=strtol(strb,&endptr,10); + if( strb[0]=='\0' || (*endptr != '\0')){ + 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); + 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); + return 1; + } + } + if(lval <-1 || lval >1){ + printf("Error reading data around '%ld' at line number %d for individual %d, '%s'\n \ + Should be a value of %d(nth) covariate (0 should be the value for the reference and 1\n \ + for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \ + For example, for multinomial values like 1, 2 and 3,\n \ + build V1=0 V2=0 for the reference value (1),\n \ + V1=1 V2=0 for (2) \n \ + and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \ + output of IMaCh is often meaningless.\n \ + Exiting.\n",lval,linei, i,line,j); + fprintf(ficlog,"Error reading data around '%ld' at line number %d for individual %d, '%s'\n \ + Should be a value of %d(nth) covariate (0 should be the value for the reference and 1\n \ + for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \ + For example, for multinomial values like 1, 2 and 3,\n \ + build V1=0 V2=0 for the reference value (1),\n \ + V1=1 V2=0 for (2) \n \ + and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \ + output of IMaCh is often meaningless.\n \ + Exiting.\n",lval,linei, i,line,j);fflush(ficlog); + return 1; + } + covar[j][i]=(double)(lval); + strcpy(line,stra); + } + lstra=strlen(stra); + + if(lstra > 9){ /* More than 2**32 or max of what printf can write with %ld */ + stratrunc = &(stra[lstra-9]); + num[i]=atol(stratrunc); + } + else + num[i]=atol(stra); + /*if((s[2][i]==2) && (s[3][i]==-1)&&(s[4][i]==9)){ + 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;}*/ + + i=i+1; + } /* End loop reading data */ + + *imax=i-1; /* Number of individuals */ + fclose(fic); + + return (0); + /* endread: */ + printf("Exiting readdata: "); + fclose(fic); + return (1); +} + +void removefirstspace(char **stri){/*, char stro[]) {*/ + char *p1 = *stri, *p2 = *stri; + while (*p2 == ' ') + p2++; + /* while ((*p1++ = *p2++) !=0) */ + /* ; */ + /* do */ + /* while (*p2 == ' ') */ + /* p2++; */ + /* while (*p1++ == *p2++); */ + *stri=p2; +} + +int decoderesult ( char resultline[], int nres) +/**< This routine decode one result line and returns the combination # of dummy covariates only **/ +{ + int j=0, k=0, k1=0, k2=0, k3=0, k4=0, match=0, k2q=0, k3q=0, k4q=0; + char resultsav[MAXLINE]; + int resultmodel[MAXLINE]; + int modelresult[MAXLINE]; + char stra[80], strb[80], strc[80], strd[80],stre[80]; + + removefirstspace(&resultline); + printf("decoderesult:%s\n",resultline); + + if (strstr(resultline,"v") !=0){ + printf("Error. 'v' must be in upper case 'V' result: %s ",resultline); + fprintf(ficlog,"Error. 'v' must be in upper case result: %s ",resultline);fflush(ficlog); + return 1; + } + trimbb(resultsav, resultline); + if (strlen(resultsav) >1){ + j=nbocc(resultsav,'='); /**< j=Number of covariate values'=' */ + } + if(j == 0){ /* Resultline but no = */ + TKresult[nres]=0; /* Combination for the nresult and the model */ + return (0); + } + + if( j != cptcovs ){ /* Be careful if a variable is in a product but not single */ + 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); + 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); + } + for(k=1; k<=j;k++){ /* Loop on any covariate of the result line */ + if(nbocc(resultsav,'=') >1){ + cutl(stra,strb,resultsav,' '); /* keeps in strb after the first ' ' + resultsav= V4=1 V5=25.1 V3=0 strb=V3=0 stra= V4=1 V5=25.1 */ + cutl(strc,strd,strb,'='); /* strb:V4=1 strc=1 strd=V4 */ + }else + cutl(strc,strd,resultsav,'='); + Tvalsel[k]=atof(strc); /* 1 */ + + cutl(strc,stre,strd,'V'); /* strd='V4' strc=4 stre='V' */; + Tvarsel[k]=atoi(strc); + /* Typevarsel[k]=1; /\* 1 for age product *\/ */ + /* cptcovsel++; */ + if (nbocc(stra,'=') >0) + strcpy(resultsav,stra); /* and analyzes it */ + } + /* Checking for missing or useless values in comparison of current model needs */ + for(k1=1; k1<= cptcovt ;k1++){ /* model line V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ + if(Typevar[k1]==0){ /* Single covariate in model */ + match=0; + for(k2=1; k2 <=j;k2++){/* result line V4=1 V5=24.1 V3=1 V2=8 V1=0 */ + if(Tvar[k1]==Tvarsel[k2]) {/* Tvar[1]=5 == Tvarsel[2]=5 */ + modelresult[k2]=k1;/* modelresult[2]=1 modelresult[1]=2 modelresult[3]=3 modelresult[6]=4 modelresult[9]=5 */ + match=1; + break; + } + } + if(match == 0){ + printf("Error in result line: %d value missing; result: %s, model=%s\n",k1, resultline, model); + } + } + } + /* Checking for missing or useless values in comparison of current model needs */ + for(k2=1; k2 <=j;k2++){ /* result line V4=1 V5=24.1 V3=1 V2=8 V1=0 */ + match=0; + for(k1=1; k1<= cptcovt ;k1++){ /* model line V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ + if(Typevar[k1]==0){ /* Single */ + if(Tvar[k1]==Tvarsel[k2]) { /* Tvar[2]=4 == Tvarsel[1]=4 */ + resultmodel[k1]=k2; /* resultmodel[2]=1 resultmodel[1]=2 resultmodel[3]=3 resultmodel[6]=4 resultmodel[9]=5 */ + ++match; + } + } + } + if(match == 0){ + printf("Error in result line: %d value missing; result: %s, model=%s\n",k1, resultline, model); + }else if(match > 1){ + printf("Error in result line: %d doubled; result: %s, model=%s\n",k2, resultline, model); + } + } + + /* We need to deduce which combination number is chosen and save quantitative values */ + /* model line V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ + /* result line V4=1 V5=25.1 V3=0 V2=8 V1=1 */ + /* should give a combination of dummy V4=1, V3=0, V1=1 => V4*2**(0) + V3*2**(1) + V1*2**(2) = 5 + (1offset) = 6*/ + /* result line V4=1 V5=24.1 V3=1 V2=8 V1=0 */ + /* should give a combination of dummy V4=1, V3=1, V1=0 => V4*2**(0) + V3*2**(1) + V1*2**(2) = 3 + (1offset) = 4*/ + /* 1 0 0 0 */ + /* 2 1 0 0 */ + /* 3 0 1 0 */ + /* 4 1 1 0 */ /* V4=1, V3=1, V1=0 */ + /* 5 0 0 1 */ + /* 6 1 0 1 */ /* V4=1, V3=0, V1=1 */ + /* 7 0 1 1 */ + /* 8 1 1 1 */ + /* V(Tvresult)=Tresult V4=1 V3=0 V1=1 Tresult[nres=1][2]=0 */ + /* V(Tvqresult)=Tqresult V5=25.1 V2=8 Tqresult[nres=1][1]=25.1 */ + /* V5*age V5 known which value for nres? */ + /* Tqinvresult[2]=8 Tqinvresult[1]=25.1 */ + for(k1=1, k=0, k4=0, k4q=0; k1 <=cptcovt;k1++){ /* model line */ + if( Dummy[k1]==0 && Typevar[k1]==0 ){ /* Single dummy */ + k3= resultmodel[k1]; /* resultmodel[2(V4)] = 1=k3 */ + k2=(int)Tvarsel[k3]; /* Tvarsel[resultmodel[2]]= Tvarsel[1] = 4=k2 */ + k+=Tvalsel[k3]*pow(2,k4); /* Tvalsel[1]=1 */ + Tresult[nres][k4+1]=Tvalsel[k3];/* Tresult[nres][1]=1(V4=1) Tresult[nres][2]=0(V3=0) */ + Tvresult[nres][k4+1]=(int)Tvarsel[k3];/* Tvresult[nres][1]=4 Tvresult[nres][3]=1 */ + Tinvresult[nres][(int)Tvarsel[k3]]=Tvalsel[k3]; /* Tinvresult[nres][4]=1 */ + printf("Decoderesult Dummy k=%d, V(k2=V%d)= Tvalsel[%d]=%d, 2**(%d)\n",k, k2, k3, (int)Tvalsel[k3], k4); + k4++;; + } else if( Dummy[k1]==1 && Typevar[k1]==0 ){ /* Single quantitative */ + k3q= resultmodel[k1]; /* resultmodel[2] = 1=k3 */ + k2q=(int)Tvarsel[k3q]; /* Tvarsel[resultmodel[2]]= Tvarsel[1] = 4=k2 */ + Tqresult[nres][k4q+1]=Tvalsel[k3q]; /* Tqresult[nres][1]=25.1 */ + Tvqresult[nres][k4q+1]=(int)Tvarsel[k3q]; /* Tvqresult[nres][1]=5 */ + Tqinvresult[nres][(int)Tvarsel[k3q]]=Tvalsel[k3q]; /* Tqinvresult[nres][5]=25.1 */ + printf("Decoderesult Quantitative nres=%d, V(k2q=V%d)= Tvalsel[%d]=%d, Tvarsel[%d]=%f\n",nres, k2q, k3q, Tvarsel[k3q], k3q, Tvalsel[k3q]); + k4q++;; + } + } + + TKresult[nres]=++k; /* Combination for the nresult and the model */ + return (0); +} + +int decodemodel( char model[], int lastobs) + /**< This routine decodes the model and returns: + * Model V1+V2+V3+V8+V7*V8+V5*V6+V8*age+V3*age+age*age + * - nagesqr = 1 if age*age in the model, otherwise 0. + * - cptcovt total number of covariates of the model nbocc(+)+1 = 8 excepting constant and age and age*age + * - cptcovn or number of covariates k of the models excluding age*products =6 and age*age + * - cptcovage number of covariates with age*products =2 + * - cptcovs number of simple covariates + * - 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 + * which is a new column after the 9 (ncovcol) variables. + * - if k is a product Vn*Vm covar[k][i] is filled with correct values for each individual + * - Tprod[l] gives the kth covariates of the product Vn*Vm l=1 to cptcovprod-cptcovage + * Tprod[1]@2 {5, 6}: position of first product V7*V8 is 5, and second V5*V6 is 6. + * - Tvard[k] p Tvard[1][1]@4 {7, 8, 5, 6} for V7*V8 and V5*V6 . + */ +{ + int i, j, k, ks, v; + int j1, k1, k2, k3, k4; + char modelsav[80]; + char stra[80], strb[80], strc[80], strd[80],stre[80]; + char *strpt; + + /*removespace(model);*/ + if (strlen(model) >1){ /* If there is at least 1 covariate */ + j=0, j1=0, k1=0, k2=-1, ks=0, cptcovn=0; + if (strstr(model,"AGE") !=0){ + printf("Error. AGE must be in lower case 'age' model=1+age+%s. ",model); + fprintf(ficlog,"Error. AGE must be in lower case model=1+age+%s. ",model);fflush(ficlog); + return 1; + } + if (strstr(model,"v") !=0){ + printf("Error. 'v' must be in upper case 'V' model=%s ",model); + fprintf(ficlog,"Error. 'v' must be in upper case model=%s ",model);fflush(ficlog); + return 1; + } + strcpy(modelsav,model); + if ((strpt=strstr(model,"age*age")) !=0){ + printf(" strpt=%s, model=%s\n",strpt, model); + if(strpt != model){ + printf("Error in model: 'model=%s'; 'age*age' should in first place before other covariates\n \ + 'model=1+age+age*age+V1.' or 'model=1+age+age*age+V1+V1*age.', please swap as well as \n \ + corresponding column of parameters.\n",model); + fprintf(ficlog,"Error in model: 'model=%s'; 'age*age' should in first place before other covariates\n \ + 'model=1+age+age*age+V1.' or 'model=1+age+age*age+V1+V1*age.', please swap as well as \n \ + corresponding column of parameters.\n",model); fflush(ficlog); + return 1; + } + nagesqr=1; + if (strstr(model,"+age*age") !=0) + substrchaine(modelsav, model, "+age*age"); + else if (strstr(model,"age*age+") !=0) + substrchaine(modelsav, model, "age*age+"); + else + substrchaine(modelsav, model, "age*age"); + }else + nagesqr=0; + if (strlen(modelsav) >1){ + j=nbocc(modelsav,'+'); /**< j=Number of '+' */ + j1=nbocc(modelsav,'*'); /**< j1=Number of '*' */ + cptcovs=j+1-j1; /**< Number of simple covariates V1+V1*age+V3 +V3*V4+age*age=> V1 + V3 =5-3=2 */ + cptcovt= j+1; /* Number of total covariates in the model, not including + * cst, age and age*age + * V1+V1*age+ V3 + V3*V4+age*age=> 3+1=4*/ + /* including age products which are counted in cptcovage. + * but the covariates which are products must be treated + * separately: ncovn=4- 2=2 (V1+V3). */ + cptcovprod=j1; /**< Number of products V1*V2 +v3*age = 2 */ + cptcovprodnoage=0; /**< Number of covariate products without age: V3*V4 =1 */ + + + /* Design + * V1 V2 V3 V4 V5 V6 V7 V8 V9 Weight + * < ncovcol=8 > + * Model V2 + V1 + V3*age + V3 + V5*V6 + V7*V8 + V8*age + V8 + * k= 1 2 3 4 5 6 7 8 + * cptcovn number of covariates (not including constant and age ) = # of + plus 1 = 7+1=8 + * covar[k,i], value of kth covariate if not including age for individual i: + * covar[1][i]= (V1), covar[4][i]=(V4), covar[8][i]=(V8) + * Tvar[k] # of the kth covariate: Tvar[1]=2 Tvar[2]=1 Tvar[4]=3 Tvar[8]=8 + * if multiplied by age: V3*age Tvar[3=V3*age]=3 (V3) Tvar[7]=8 and + * Tage[++cptcovage]=k + * if products, new covar are created after ncovcol with k1 + * Tvar[k]=ncovcol+k1; # of the kth covariate product: Tvar[5]=ncovcol+1=10 Tvar[6]=ncovcol+1=11 + * Tprod[k1]=k; Tprod[1]=5 Tprod[2]= 6; gives the position of the k1th product + * 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 + * Tvar[cptcovn+k2]=Tvard[k1][1];Tvar[cptcovn+k2+1]=Tvard[k1][2]; + * Tvar[8+1]=5;Tvar[8+2]=6;Tvar[8+3]=7;Tvar[8+4]=8 inverted + * V1 V2 V3 V4 V5 V6 V7 V8 V9 V10 V11 + * < ncovcol=8 > + * Model V2 + V1 + V3*age + V3 + V5*V6 + V7*V8 + V8*age + V8 d1 d1 d2 d2 + * k= 1 2 3 4 5 6 7 8 9 10 11 12 + * Tvar[k]= 2 1 3 3 10 11 8 8 5 6 7 8 + * p Tvar[1]@12={2, 1, 3, 3, 11, 10, 8, 8, 7, 8, 5, 6} + * p Tprod[1]@2={ 6, 5} + *p Tvard[1][1]@4= {7, 8, 5, 6} + * covar[k][i]= V2 V1 ? V3 V5*V6? V7*V8? ? V8 + * cov[Tage[kk]+2]=covar[Tvar[Tage[kk]]][i]*cov[2]; + *How to reorganize? + * Model V1 + V2 + V3 + V8 + V5*V6 + V7*V8 + V3*age + V8*age + * Tvars {2, 1, 3, 3, 11, 10, 8, 8, 7, 8, 5, 6} + * {2, 1, 4, 8, 5, 6, 3, 7} + * Struct [] + */ + + /* This loop fills the array Tvar from the string 'model'.*/ + /* j is the number of + signs in the model V1+V2+V3 j=2 i=3 to 1 */ + /* modelsav=V2+V1+V4+age*V3 strb=age*V3 stra=V2+V1+V4 */ + /* k=4 (age*V3) Tvar[k=4]= 3 (from V3) Tage[cptcovage=1]=4 */ + /* k=3 V4 Tvar[k=3]= 4 (from V4) */ + /* k=2 V1 Tvar[k=2]= 1 (from V1) */ + /* k=1 Tvar[1]=2 (from V2) */ + /* k=5 Tvar[5] */ + /* for (k=1; k<=cptcovn;k++) { */ + /* cov[2+k]=nbcode[Tvar[k]][codtabm(ij,Tvar[k])]; */ + /* } */ + /* for (k=1; k<=cptcovage;k++) cov[2+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,Tvar[Tage[k])]]*cov[2]; */ + /* + * Treating invertedly V2+V1+V3*age+V2*V4 is as if written V2*V4 +V3*age + V1 + V2 */ + for(k=cptcovt; k>=1;k--){ /**< Number of covariates not including constant and age, neither age*age*/ + Tvar[k]=0; Tprod[k]=0; Tposprod[k]=0; + } + cptcovage=0; + for(k=1; k<=cptcovt;k++){ /* Loop on total covariates of the model */ + cutl(stra,strb,modelsav,'+'); /* keeps in strb after the first '+' + modelsav==V2+V1+V4+V3*age strb=V3*age stra=V2+V1+V4 */ + if (nbocc(modelsav,'+')==0) strcpy(strb,modelsav); /* and analyzes it */ + /* printf("i=%d a=%s b=%s sav=%s\n",i, stra,strb,modelsav);*/ + /*scanf("%d",i);*/ + if (strchr(strb,'*')) { /**< Model includes a product V2+V1+V4+V3*age strb=V3*age */ + cutl(strc,strd,strb,'*'); /**< strd*strc Vm*Vn: strb=V3*age(input) strc=age strd=V3 ; V3*V2 strc=V2, strd=V3 */ + if (strcmp(strc,"age")==0) { /**< Model includes age: Vn*age */ + /* covar is not filled and then is empty */ + cptcovprod--; + cutl(stre,strb,strd,'V'); /* strd=V3(input): stre="3" */ + Tvar[k]=atoi(stre); /* V2+V1+V4+V3*age Tvar[4]=3 ; V1+V2*age Tvar[2]=2; V1+V1*age Tvar[2]=1 */ + Typevar[k]=1; /* 1 for age product */ + cptcovage++; /* Sums the number of covariates which include age as a product */ + Tage[cptcovage]=k; /* Tvar[4]=3, Tage[1] = 4 or V1+V1*age Tvar[2]=1, Tage[1]=2 */ + /*printf("stre=%s ", stre);*/ + } else if (strcmp(strd,"age")==0) { /* or age*Vn */ + cptcovprod--; + cutl(stre,strb,strc,'V'); + Tvar[k]=atoi(stre); + Typevar[k]=1; /* 1 for age product */ + cptcovage++; + Tage[cptcovage]=k; + } else { /* Age is not in the model product V2+V1+V1*V4+V3*age+V3*V2 strb=V3*V2*/ + /* loops on k1=1 (V3*V2) and k1=2 V4*V3 */ + cptcovn++; + cptcovprodnoage++;k1++; + cutl(stre,strb,strc,'V'); /* strc= Vn, stre is n; strb=V3*V2 stre=3 strc=*/ + Tvar[k]=ncovcol+nqv+ntv+nqtv+k1; /* For model-covariate k tells which data-covariate to use but + because this model-covariate is a construction we invent a new column + which is after existing variables ncovcol+nqv+ntv+nqtv + k1 + If already ncovcol=4 and model=V2+V1+V1*V4+age*V3+V3*V2 + Tvar[3=V1*V4]=4+1 Tvar[5=V3*V2]=4 + 2= 6, etc */ + Typevar[k]=2; /* 2 for double fixed dummy covariates */ + cutl(strc,strb,strd,'V'); /* strd was Vm, strc is m */ + Tprod[k1]=k; /* Tprod[1]=3(=V1*V4) for V2+V1+V1*V4+age*V3+V3*V2 */ + Tposprod[k]=k1; /* Tpsprod[3]=1, Tposprod[2]=5 */ + Tvard[k1][1] =atoi(strc); /* m 1 for V1*/ + Tvard[k1][2] =atoi(stre); /* n 4 for V4*/ + k2=k2+2; /* k2 is initialize to -1, We want to store the n and m in Vn*Vm at the end of Tvar */ + /* Tvar[cptcovt+k2]=Tvard[k1][1]; /\* Tvar[(cptcovt=4+k2=1)=5]= 1 (V1) *\/ */ + /* Tvar[cptcovt+k2+1]=Tvard[k1][2]; /\* Tvar[(cptcovt=4+(k2=1)+1)=6]= 4 (V4) *\/ */ + /*ncovcol=4 and model=V2+V1+V1*V4+age*V3+V3*V2, Tvar[3]=5, Tvar[4]=6, cptcovt=5 */ + /* 1 2 3 4 5 | Tvar[5+1)=1, Tvar[7]=2 */ + for (i=1; i<=lastobs;i++){ + /* Computes the new covariate which is a product of + covar[n][i]* covar[m][i] and stores it at ncovol+k1 May not be defined */ + covar[ncovcol+k1][i]=covar[atoi(stre)][i]*covar[atoi(strc)][i]; + } + } /* End age is not in the model */ + } /* End if model includes a product */ + else { /* no more sum */ + /*printf("d=%s c=%s b=%s\n", strd,strc,strb);*/ + /* scanf("%d",i);*/ + cutl(strd,strc,strb,'V'); + ks++; /**< Number of simple covariates dummy or quantitative, fixe or varying */ + cptcovn++; /** V4+V3+V5: V4 and V3 timevarying dummy covariates, V5 timevarying quantitative */ + Tvar[k]=atoi(strd); + Typevar[k]=0; /* 0 for simple covariates */ + } + strcpy(modelsav,stra); /* modelsav=V2+V1+V4 stra=V2+V1+V4 */ + /*printf("a=%s b=%s sav=%s\n", stra,strb,modelsav); + scanf("%d",i);*/ + } /* end of loop + on total covariates */ + } /* end if strlen(modelsave == 0) age*age might exist */ + } /* end if strlen(model == 0) */ + + /*The number n of Vn is stored in Tvar. cptcovage =number of age covariate. Tage gives the position of age. cptcovprod= number of products. + If model=V1+V1*age then Tvar[1]=1 Tvar[2]=1 cptcovage=1 Tage[1]=2 cptcovprod=0*/ + + /* printf("tvar1=%d tvar2=%d tvar3=%d cptcovage=%d Tage=%d",Tvar[1],Tvar[2],Tvar[3],cptcovage,Tage[1]); + printf("cptcovprod=%d ", cptcovprod); + fprintf(ficlog,"cptcovprod=%d ", cptcovprod); + scanf("%d ",i);*/ + + +/* Until here, decodemodel knows only the grammar (simple, product, age*) of the model but not what kind + of variable (dummy vs quantitative, fixed vs time varying) is behind. But we know the # of each. */ +/* ncovcol= 1, nqv=1 | ntv=2, nqtv= 1 = 5 possible variables data: 2 fixed 3, varying + model= V5 + V4 +V3 + V4*V3 + V5*age + V2 + V1*V2 + V1*age + V5*age, V1 is not used saving its place + k = 1 2 3 4 5 6 7 8 9 + Tvar[k]= 5 4 3 1+1+2+1+1=6 5 2 7 1 5 + Typevar[k]= 0 0 0 2 1 0 2 1 1 + Fixed[k] 1 1 1 1 3 0 0 or 2 2 3 + Dummy[k] 1 0 0 0 3 1 1 2 3 + Tmodelind[combination of covar]=k; +*/ +/* Dispatching between quantitative and time varying covariates */ + /* If Tvar[k] >ncovcol it is a product */ + /* Tvar[k] is the value n of Vn with n varying for 1 to nvcol, or p Vp=Vn*Vm for product */ + /* Computing effective variables, ie used by the model, that is from the cptcovt variables */ + printf("Model=%s\n\ +Typevar: 0 for simple covariate (dummy, quantitative, fixed or varying), 1 for age product, 2 for product \n\ +Fixed[k] 0=fixed (product or simple), 1 varying, 2 fixed with age product, 3 varying with age product \n\ +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); + fprintf(ficlog,"Model=%s\n\ +Typevar: 0 for simple covariate (dummy, quantitative, fixed or varying), 1 for age product, 2 for product \n\ +Fixed[k] 0=fixed (product or simple), 1 varying, 2 fixed with age product, 3 varying with age product \n\ +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); + for(k=1;k<=cptcovt; k++){ Fixed[k]=0; Dummy[k]=0;} + 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 */ + if (Tvar[k] <=ncovcol && Typevar[k]==0 ){ /* Simple fixed dummy (<=ncovcol) covariates */ + Fixed[k]= 0; + Dummy[k]= 0; + ncoveff++; + ncovf++; + nsd++; + modell[k].maintype= FTYPE; + TvarsD[nsd]=Tvar[k]; + TvarsDind[nsd]=k; + TvarF[ncovf]=Tvar[k]; + TvarFind[ncovf]=k; + TvarFD[ncoveff]=Tvar[k]; /* TvarFD[1]=V1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ + TvarFDind[ncoveff]=k; /* TvarFDind[1]=9 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ + }else if( Tvar[k] <=ncovcol && Typevar[k]==2){ /* Product of fixed dummy (<=ncovcol) covariates */ + Fixed[k]= 0; + Dummy[k]= 0; + ncoveff++; + ncovf++; + modell[k].maintype= FTYPE; + TvarF[ncovf]=Tvar[k]; + TvarFind[ncovf]=k; + TvarFD[ncoveff]=Tvar[k]; /* TvarFD[1]=V1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ + TvarFDind[ncoveff]=k; /* TvarFDind[1]=9 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ + }else if( Tvar[k] <=ncovcol+nqv && Typevar[k]==0){/* Remind that product Vn*Vm are added in k Only simple fixed quantitative variable */ + Fixed[k]= 0; + Dummy[k]= 1; + nqfveff++; + modell[k].maintype= FTYPE; + modell[k].subtype= FQ; + nsq++; + TvarsQ[nsq]=Tvar[k]; + TvarsQind[nsq]=k; + ncovf++; + TvarF[ncovf]=Tvar[k]; + TvarFind[ncovf]=k; + 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 */ + 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 */ + }else if( Tvar[k] <=ncovcol+nqv+ntv && Typevar[k]==0){/* Only simple time varying dummy variables */ + Fixed[k]= 1; + Dummy[k]= 0; + ntveff++; /* Only simple time varying dummy variable */ + modell[k].maintype= VTYPE; + modell[k].subtype= VD; + nsd++; + TvarsD[nsd]=Tvar[k]; + TvarsDind[nsd]=k; + ncovv++; /* Only simple time varying variables */ + TvarV[ncovv]=Tvar[k]; + 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 */ + 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 */ + 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 */ + 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); + printf("Quasi TmodelInvind[%d]=%d\n",k,Tvar[k]- ncovcol-nqv); + }else if( Tvar[k] <=ncovcol+nqv+ntv+nqtv && Typevar[k]==0){ /* Only simple time varying quantitative variable V5*/ + Fixed[k]= 1; + Dummy[k]= 1; + nqtveff++; + modell[k].maintype= VTYPE; + modell[k].subtype= VQ; + ncovv++; /* Only simple time varying variables */ + nsq++; + TvarsQ[nsq]=Tvar[k]; + TvarsQind[nsq]=k; + TvarV[ncovv]=Tvar[k]; + TvarVind[ncovv]=k; /* TvarVind[1]=1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Any time varying singele */ + 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 */ + 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 */ + TmodelInvQind[nqtveff]=Tvar[k]- ncovcol-nqv-ntv;/* Only simple time varying quantitative variable */ + /* Tmodeliqind[k]=nqtveff;/\* Only simple time varying quantitative variable *\/ */ + 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); + printf("Quasi TmodelInvQind[%d]=%d\n",k,Tvar[k]- ncovcol-nqv-ntv); + }else if (Typevar[k] == 1) { /* product with age */ + ncova++; + TvarA[ncova]=Tvar[k]; + TvarAind[ncova]=k; + if (Tvar[k] <=ncovcol ){ /* Product age with fixed dummy covariatee */ + Fixed[k]= 2; + Dummy[k]= 2; + modell[k].maintype= ATYPE; + modell[k].subtype= APFD; + /* ncoveff++; */ + }else if( Tvar[k] <=ncovcol+nqv) { /* Remind that product Vn*Vm are added in k*/ + Fixed[k]= 2; + Dummy[k]= 3; + modell[k].maintype= ATYPE; + modell[k].subtype= APFQ; /* Product age * fixed quantitative */ + /* nqfveff++; /\* Only simple fixed quantitative variable *\/ */ + }else if( Tvar[k] <=ncovcol+nqv+ntv ){ + Fixed[k]= 3; + Dummy[k]= 2; + modell[k].maintype= ATYPE; + modell[k].subtype= APVD; /* Product age * varying dummy */ + /* ntveff++; /\* Only simple time varying dummy variable *\/ */ + }else if( Tvar[k] <=ncovcol+nqv+ntv+nqtv){ + Fixed[k]= 3; + Dummy[k]= 3; + modell[k].maintype= ATYPE; + modell[k].subtype= APVQ; /* Product age * varying quantitative */ + /* nqtveff++;/\* Only simple time varying quantitative variable *\/ */ + } + }else if (Typevar[k] == 2) { /* product without age */ + k1=Tposprod[k]; + if(Tvard[k1][1] <=ncovcol){ + if(Tvard[k1][2] <=ncovcol){ + Fixed[k]= 1; + Dummy[k]= 0; + modell[k].maintype= FTYPE; + modell[k].subtype= FPDD; /* Product fixed dummy * fixed dummy */ + ncovf++; /* Fixed variables without age */ + TvarF[ncovf]=Tvar[k]; + TvarFind[ncovf]=k; + }else if(Tvard[k1][2] <=ncovcol+nqv){ + Fixed[k]= 0; /* or 2 ?*/ + Dummy[k]= 1; + modell[k].maintype= FTYPE; + modell[k].subtype= FPDQ; /* Product fixed dummy * fixed quantitative */ + ncovf++; /* Varying variables without age */ + TvarF[ncovf]=Tvar[k]; + TvarFind[ncovf]=k; + }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){ + Fixed[k]= 1; + Dummy[k]= 0; + modell[k].maintype= VTYPE; + modell[k].subtype= VPDD; /* Product fixed dummy * varying dummy */ + ncovv++; /* Varying variables without age */ + TvarV[ncovv]=Tvar[k]; + TvarVind[ncovv]=k; + }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){ + Fixed[k]= 1; + Dummy[k]= 1; + modell[k].maintype= VTYPE; + modell[k].subtype= VPDQ; /* Product fixed dummy * varying quantitative */ + ncovv++; /* Varying variables without age */ + TvarV[ncovv]=Tvar[k]; + TvarVind[ncovv]=k; + } + }else if(Tvard[k1][1] <=ncovcol+nqv){ + if(Tvard[k1][2] <=ncovcol){ + Fixed[k]= 0; /* or 2 ?*/ + Dummy[k]= 1; + modell[k].maintype= FTYPE; + modell[k].subtype= FPDQ; /* Product fixed quantitative * fixed dummy */ + ncovf++; /* Fixed variables without age */ + TvarF[ncovf]=Tvar[k]; + TvarFind[ncovf]=k; + }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){ + Fixed[k]= 1; + Dummy[k]= 1; + modell[k].maintype= VTYPE; + modell[k].subtype= VPDQ; /* Product fixed quantitative * varying dummy */ + ncovv++; /* Varying variables without age */ + TvarV[ncovv]=Tvar[k]; + TvarVind[ncovv]=k; + }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){ + Fixed[k]= 1; + Dummy[k]= 1; + modell[k].maintype= VTYPE; + modell[k].subtype= VPQQ; /* Product fixed quantitative * varying quantitative */ + ncovv++; /* Varying variables without age */ + TvarV[ncovv]=Tvar[k]; + TvarVind[ncovv]=k; + ncovv++; /* Varying variables without age */ + TvarV[ncovv]=Tvar[k]; + TvarVind[ncovv]=k; + } + }else if(Tvard[k1][1] <=ncovcol+nqv+ntv){ + if(Tvard[k1][2] <=ncovcol){ + Fixed[k]= 1; + Dummy[k]= 1; + modell[k].maintype= VTYPE; + modell[k].subtype= VPDD; /* Product time varying dummy * fixed dummy */ + ncovv++; /* Varying variables without age */ + TvarV[ncovv]=Tvar[k]; + TvarVind[ncovv]=k; + }else if(Tvard[k1][2] <=ncovcol+nqv){ + Fixed[k]= 1; + Dummy[k]= 1; + modell[k].maintype= VTYPE; + modell[k].subtype= VPDQ; /* Product time varying dummy * fixed quantitative */ + ncovv++; /* Varying variables without age */ + TvarV[ncovv]=Tvar[k]; + TvarVind[ncovv]=k; + }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){ + Fixed[k]= 1; + Dummy[k]= 0; + modell[k].maintype= VTYPE; + modell[k].subtype= VPDD; /* Product time varying dummy * time varying dummy */ + ncovv++; /* Varying variables without age */ + TvarV[ncovv]=Tvar[k]; + TvarVind[ncovv]=k; + }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){ + Fixed[k]= 1; + Dummy[k]= 1; + modell[k].maintype= VTYPE; + modell[k].subtype= VPDQ; /* Product time varying dummy * time varying quantitative */ + ncovv++; /* Varying variables without age */ + TvarV[ncovv]=Tvar[k]; + TvarVind[ncovv]=k; + } + }else if(Tvard[k1][1] <=ncovcol+nqv+ntv+nqtv){ + if(Tvard[k1][2] <=ncovcol){ + Fixed[k]= 1; + Dummy[k]= 1; + modell[k].maintype= VTYPE; + modell[k].subtype= VPDQ; /* Product time varying quantitative * fixed dummy */ + ncovv++; /* Varying variables without age */ + TvarV[ncovv]=Tvar[k]; + TvarVind[ncovv]=k; + }else if(Tvard[k1][2] <=ncovcol+nqv){ + Fixed[k]= 1; + Dummy[k]= 1; + modell[k].maintype= VTYPE; + modell[k].subtype= VPQQ; /* Product time varying quantitative * fixed quantitative */ + ncovv++; /* Varying variables without age */ + TvarV[ncovv]=Tvar[k]; + TvarVind[ncovv]=k; + }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){ + Fixed[k]= 1; + Dummy[k]= 1; + modell[k].maintype= VTYPE; + modell[k].subtype= VPDQ; /* Product time varying quantitative * time varying dummy */ + ncovv++; /* Varying variables without age */ + TvarV[ncovv]=Tvar[k]; + TvarVind[ncovv]=k; + }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){ + Fixed[k]= 1; + Dummy[k]= 1; + modell[k].maintype= VTYPE; + modell[k].subtype= VPQQ; /* Product time varying quantitative * time varying quantitative */ + ncovv++; /* Varying variables without age */ + TvarV[ncovv]=Tvar[k]; + TvarVind[ncovv]=k; + } + }else{ + printf("Error unknown type of covariate: Tvard[%d][1]=%d,Tvard[%d][2]=%d\n",k1,Tvard[k1][1],k1,Tvard[k1][2]); + fprintf(ficlog,"Error unknown type of covariate: Tvard[%d][1]=%d,Tvard[%d][2]=%d\n",k1,Tvard[k1][1],k1,Tvard[k1][2]); + } /*end k1*/ + }else{ + printf("Error, current version can't treat for performance reasons, Tvar[%d]=%d, Typevar[%d]=%d\n", k, Tvar[k], k, Typevar[k]); + fprintf(ficlog,"Error, current version can't treat for performance reasons, Tvar[%d]=%d, Typevar[%d]=%d\n", k, Tvar[k], k, Typevar[k]); + } + 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]); + printf(" modell[%d].maintype=%d, modell[%d].subtype=%d\n",k,modell[k].maintype,k,modell[k].subtype); + 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]); + } + /* Searching for doublons in the model */ + for(k1=1; k1<= cptcovt;k1++){ + for(k2=1; k2 nlstate){ + *nberr = *nberr + 1; + if(firstone == 0){ + firstone=1; + printf("Error! Date of death (month %2d and year %4d) of individual %ld on line %d was unknown, you must set an arbitrary year of death or he/she is skipped and results can be biased (%d) because status is a death state %d at wave %d. Wave dropped.\nOther similar cases in log file\n",(int)moisdc[i],(int)andc[i],num[i],i, *nberr,s[m][i],m); + } + fprintf(ficlog,"Error! Date of death (month %2d and year %4d) of individual %ld on line %d was unknown, you must set an arbitrary year of death or he/she is skipped and results can be biased (%d) because status is a death state %d at wave %d. Wave dropped.\n",(int)moisdc[i],(int)andc[i],num[i],i, *nberr,s[m][i],m); + s[m][i]=-1; + } + if((int)moisdc[i]==99 && (int)andc[i]!=9999 && s[m][i]>nlstate){ + (*nberr)++; + printf("Error! Month of death of individual %ld on line %d was unknown %2d, you should set it otherwise the information on the death is skipped and results are biased.\n",num[i],i,(int)moisdc[i]); + fprintf(ficlog,"Error! Month of death of individual %ld on line %d was unknown %f, you should set it otherwise the information on the death is skipped and results are biased.\n",num[i],i,moisdc[i]); + s[m][i]=-1; /* We prefer to skip it (and to skip it in version 0.8a1 too */ + } + } + } + + for (i=1; i<=imx; i++) { + agedc[i]=(moisdc[i]/12.+andc[i])-(moisnais[i]/12.+annais[i]); + for(m=firstpass; (m<= lastpass); m++){ + 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 */ + if (s[m][i] >= nlstate+1) { + if(agedc[i]>0){ + if((int)moisdc[i]!=99 && (int)andc[i]!=9999){ + agev[m][i]=agedc[i]; + /*if(moisdc[i]==99 && andc[i]==9999) s[m][i]=-1;*/ + }else { + if ((int)andc[i]!=9999){ + nbwarn++; + printf("Warning negative age at death: %ld line:%d\n",num[i],i); + fprintf(ficlog,"Warning negative age at death: %ld line:%d\n",num[i],i); + agev[m][i]=-1; + } + } + } /* agedc > 0 */ + } /* end if */ + else if(s[m][i] !=9){ /* Standard case, age in fractional + years but with the precision of a month */ + agev[m][i]=(mint[m][i]/12.+1./24.+anint[m][i])-(moisnais[i]/12.+1./24.+annais[i]); + if((int)mint[m][i]==99 || (int)anint[m][i]==9999) + agev[m][i]=1; + else if(agev[m][i] < *agemin){ + *agemin=agev[m][i]; + printf(" Min anint[%d][%d]=%.2f annais[%d]=%.2f, agemin=%.2f\n",m,i,anint[m][i], i,annais[i], *agemin); + } + else if(agev[m][i] >*agemax){ + *agemax=agev[m][i]; + /* printf(" Max anint[%d][%d]=%.0f annais[%d]=%.0f, agemax=%.2f\n",m,i,anint[m][i], i,annais[i], *agemax);*/ + } + /*agev[m][i]=anint[m][i]-annais[i];*/ + /* agev[m][i] = age[i]+2*m;*/ + } /* en if 9*/ + else { /* =9 */ + /* printf("Debug num[%d]=%ld s[%d][%d]=%d\n",i,num[i], m,i, s[m][i]); */ + agev[m][i]=1; + s[m][i]=-1; + } + } + else if(s[m][i]==0) /*= 0 Unknown */ + agev[m][i]=1; + else{ + printf("Warning, num[%d]=%ld, s[%d][%d]=%d\n", i, num[i], m, i,s[m][i]); + fprintf(ficlog, "Warning, num[%d]=%ld, s[%d][%d]=%d\n", i, num[i], m, i,s[m][i]); + agev[m][i]=0; + } + } /* End for lastpass */ + } + + for (i=1; i<=imx; i++) { + for(m=firstpass; (m<=lastpass); m++){ + if (s[m][i] > (nlstate+ndeath)) { + (*nberr)++; + 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); + 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); + return 1; + } + } + } + + /*for (i=1; i<=imx; i++){ + for (m=firstpass; (m +//#include +//#include +//#include +typedef BOOL(WINAPI *LPFN_ISWOW64PROCESS) (HANDLE, PBOOL); + +LPFN_ISWOW64PROCESS fnIsWow64Process; + +BOOL IsWow64() +{ + BOOL bIsWow64 = FALSE; + + //typedef BOOL (APIENTRY *LPFN_ISWOW64PROCESS) + // (HANDLE, PBOOL); + + //LPFN_ISWOW64PROCESS fnIsWow64Process; + + HMODULE module = GetModuleHandle(_T("kernel32")); + const char funcName[] = "IsWow64Process"; + fnIsWow64Process = (LPFN_ISWOW64PROCESS) + GetProcAddress(module, funcName); + + if (NULL != fnIsWow64Process) + { + if (!fnIsWow64Process(GetCurrentProcess(), + &bIsWow64)) + //throw std::exception("Unknown error"); + printf("Unknown error\n"); + } + return bIsWow64 != FALSE; +} +#endif + +void syscompilerinfo(int logged) + { + /* #include "syscompilerinfo.h"*/ + /* command line Intel compiler 32bit windows, XP compatible:*/ + /* /GS /W3 /Gy + /Zc:wchar_t /Zi /O2 /Fd"Release\vc120.pdb" /D "WIN32" /D "NDEBUG" /D + "_CONSOLE" /D "_LIB" /D "_USING_V110_SDK71_" /D "_UNICODE" /D + "UNICODE" /Qipo /Zc:forScope /Gd /Oi /MT /Fa"Release\" /EHsc /nologo + /Fo"Release\" /Qprof-dir "Release\" /Fp"Release\IMaCh.pch" + */ + /* 64 bits */ + /* + /GS /W3 /Gy + /Zc:wchar_t /Zi /O2 /Fd"x64\Release\vc120.pdb" /D "WIN32" /D "NDEBUG" + /D "_CONSOLE" /D "_LIB" /D "_UNICODE" /D "UNICODE" /Qipo /Zc:forScope + /Oi /MD /Fa"x64\Release\" /EHsc /nologo /Fo"x64\Release\" /Qprof-dir + "x64\Release\" /Fp"x64\Release\IMaCh.pch" */ + /* Optimization are useless and O3 is slower than O2 */ + /* + /GS /W3 /Gy /Zc:wchar_t /Zi /O3 /Fd"x64\Release\vc120.pdb" /D "WIN32" + /D "NDEBUG" /D "_CONSOLE" /D "_LIB" /D "_UNICODE" /D "UNICODE" /Qipo + /Zc:forScope /Oi /MD /Fa"x64\Release\" /EHsc /nologo /Qparallel + /Fo"x64\Release\" /Qprof-dir "x64\Release\" /Fp"x64\Release\IMaCh.pch" + */ + /* Link is */ /* /OUT:"visual studio + 2013\Projects\IMaCh\Release\IMaCh.exe" /MANIFEST /NXCOMPAT + /PDB:"visual studio + 2013\Projects\IMaCh\Release\IMaCh.pdb" /DYNAMICBASE + "kernel32.lib" "user32.lib" "gdi32.lib" "winspool.lib" + "comdlg32.lib" "advapi32.lib" "shell32.lib" "ole32.lib" + "oleaut32.lib" "uuid.lib" "odbc32.lib" "odbccp32.lib" + /MACHINE:X86 /OPT:REF /SAFESEH /INCREMENTAL:NO + /SUBSYSTEM:CONSOLE",5.01" /MANIFESTUAC:"level='asInvoker' + uiAccess='false'" + /ManifestFile:"Release\IMaCh.exe.intermediate.manifest" /OPT:ICF + /NOLOGO /TLBID:1 + */ +#if defined __INTEL_COMPILER +#if defined(__GNUC__) + struct utsname sysInfo; /* For Intel on Linux and OS/X */ +#endif +#elif defined(__GNUC__) +#ifndef __APPLE__ +#include /* Only on gnu */ +#endif + struct utsname sysInfo; + int cross = CROSS; + if (cross){ + printf("Cross-"); + if(logged) fprintf(ficlog, "Cross-"); + } +#endif + +#include + + printf("Compiled with:");if(logged)fprintf(ficlog,"Compiled with:"); +#if defined(__clang__) + printf(" Clang/LLVM");if(logged)fprintf(ficlog," Clang/LLVM"); /* Clang/LLVM. ---------------------------------------------- */ +#endif +#if defined(__ICC) || defined(__INTEL_COMPILER) + printf(" Intel ICC/ICPC");if(logged)fprintf(ficlog," Intel ICC/ICPC");/* Intel ICC/ICPC. ------------------------------------------ */ +#endif +#if defined(__GNUC__) || defined(__GNUG__) + printf(" GNU GCC/G++");if(logged)fprintf(ficlog," GNU GCC/G++");/* GNU GCC/G++. --------------------------------------------- */ +#endif +#if defined(__HP_cc) || defined(__HP_aCC) + printf(" Hewlett-Packard C/aC++");if(logged)fprintf(fcilog," Hewlett-Packard C/aC++"); /* Hewlett-Packard C/aC++. ---------------------------------- */ +#endif +#if defined(__IBMC__) || defined(__IBMCPP__) + printf(" IBM XL C/C++"); if(logged) fprintf(ficlog," IBM XL C/C++");/* IBM XL C/C++. -------------------------------------------- */ +#endif +#if defined(_MSC_VER) + printf(" Microsoft Visual Studio");if(logged)fprintf(ficlog," Microsoft Visual Studio");/* Microsoft Visual Studio. --------------------------------- */ +#endif +#if defined(__PGI) + printf(" Portland Group PGCC/PGCPP");if(logged) fprintf(ficlog," Portland Group PGCC/PGCPP");/* Portland Group PGCC/PGCPP. ------------------------------- */ +#endif +#if defined(__SUNPRO_C) || defined(__SUNPRO_CC) + printf(" Oracle Solaris Studio");if(logged)fprintf(ficlog," Oracle Solaris Studio\n");/* Oracle Solaris Studio. ----------------------------------- */ +#endif + printf(" for "); if (logged) fprintf(ficlog, " for "); + +// http://stackoverflow.com/questions/4605842/how-to-identify-platform-compiler-from-preprocessor-macros +#ifdef _WIN32 // note the underscore: without it, it's not msdn official! + // Windows (x64 and x86) + printf("Windows (x64 and x86) ");if(logged) fprintf(ficlog,"Windows (x64 and x86) "); +#elif __unix__ // all unices, not all compilers + // Unix + printf("Unix ");if(logged) fprintf(ficlog,"Unix "); +#elif __linux__ + // linux + printf("linux ");if(logged) fprintf(ficlog,"linux "); +#elif __APPLE__ + // Mac OS, not sure if this is covered by __posix__ and/or __unix__ though.. + printf("Mac OS ");if(logged) fprintf(ficlog,"Mac OS "); +#endif + +/* __MINGW32__ */ +/* __CYGWIN__ */ +/* __MINGW64__ */ +// http://msdn.microsoft.com/en-us/library/b0084kay.aspx +/* _MSC_VER //the Visual C++ compiler is 17.00.51106.1, the _MSC_VER macro evaluates to 1700. Type cl /? */ +/* _MSC_FULL_VER //the Visual C++ compiler is 15.00.20706.01, the _MSC_FULL_VER macro evaluates to 150020706 */ +/* _WIN64 // Defined for applications for Win64. */ +/* _M_X64 // Defined for compilations that target x64 processors. */ +/* _DEBUG // Defined when you compile with /LDd, /MDd, and /MTd. */ + +#if UINTPTR_MAX == 0xffffffff + printf(" 32-bit"); if(logged) fprintf(ficlog," 32-bit");/* 32-bit */ +#elif UINTPTR_MAX == 0xffffffffffffffff + printf(" 64-bit"); if(logged) fprintf(ficlog," 64-bit");/* 64-bit */ +#else + printf(" wtf-bit"); if(logged) fprintf(ficlog," wtf-bit");/* wtf */ +#endif + +#if defined(__GNUC__) +# if defined(__GNUC_PATCHLEVEL__) +# define __GNUC_VERSION__ (__GNUC__ * 10000 \ + + __GNUC_MINOR__ * 100 \ + + __GNUC_PATCHLEVEL__) +# else +# define __GNUC_VERSION__ (__GNUC__ * 10000 \ + + __GNUC_MINOR__ * 100) +# endif + printf(" using GNU C version %d.\n", __GNUC_VERSION__); + if(logged) fprintf(ficlog, " using GNU C version %d.\n", __GNUC_VERSION__); + + if (uname(&sysInfo) != -1) { + printf("Running on: %s %s %s %s %s\n",sysInfo.sysname, sysInfo.nodename, sysInfo.release, sysInfo.version, sysInfo.machine); + if(logged) fprintf(ficlog,"Running on: %s %s %s %s %s\n ",sysInfo.sysname, sysInfo.nodename, sysInfo.release, sysInfo.version, sysInfo.machine); + } + else + perror("uname() error"); + //#ifndef __INTEL_COMPILER +#if !defined (__INTEL_COMPILER) && !defined(__APPLE__) + printf("GNU libc version: %s\n", gnu_get_libc_version()); + if(logged) fprintf(ficlog,"GNU libc version: %s\n", gnu_get_libc_version()); +#endif +#endif + + // void main() + // { +#if defined(_MSC_VER) + if (IsWow64()){ + printf("\nThe program (probably compiled for 32bit) is running under WOW64 (64bit) emulation.\n"); + if (logged) fprintf(ficlog, "\nThe program (probably compiled for 32bit) is running under WOW64 (64bit) emulation.\n"); + } + else{ + printf("\nThe program is not running under WOW64 (i.e probably on a 64bit Windows).\n"); + if (logged) fprintf(ficlog, "\nThe programm is not running under WOW64 (i.e probably on a 64bit Windows).\n"); + } + // printf("\nPress Enter to continue..."); + // getchar(); + // } + +#endif + + +} + +int prevalence_limit(double *p, double **prlim, double ageminpar, double agemaxpar, double ftolpl, int *ncvyearp){ + /*--------------- Prevalence limit (period or stable prevalence) --------------*/ + int i, j, k, i1, k4=0, nres=0 ; + /* double ftolpl = 1.e-10; */ + double age, agebase, agelim; + double tot; + + strcpy(filerespl,"PL_"); + strcat(filerespl,fileresu); + if((ficrespl=fopen(filerespl,"w"))==NULL) { + printf("Problem with period (stable) prevalence resultfile: %s\n", filerespl);return 1; + fprintf(ficlog,"Problem with period (stable) prevalence resultfile: %s\n", filerespl);return 1; + } + printf("\nComputing period (stable) prevalence: result on file '%s' \n", filerespl); + fprintf(ficlog,"\nComputing period (stable) prevalence: result on file '%s' \n", filerespl); + pstamp(ficrespl); + fprintf(ficrespl,"# Period (stable) prevalence. Precision given by ftolpl=%g \n", ftolpl); + fprintf(ficrespl,"#Age "); + for(i=1; i<=nlstate;i++) fprintf(ficrespl,"%d-%d ",i,i); + fprintf(ficrespl,"\n"); + + /* prlim=matrix(1,nlstate,1,nlstate);*/ /* back in main */ + + agebase=ageminpar; + agelim=agemaxpar; + + /* i1=pow(2,ncoveff); */ + i1=pow(2,cptcoveff); /* Number of combination of dummy covariates */ + if (cptcovn < 1){i1=1;} + + for(k=1; k<=i1;k++){ /* For each combination k of dummy covariates in the model */ + for(nres=1; nres <= nresult; nres++){ /* For each resultline */ + if(i1 != 1 && TKresult[nres]!= k) + continue; + + /* for(cptcov=1,k=0;cptcov<=i1;cptcov++){ */ + /* for(cptcov=1,k=0;cptcov<=1;cptcov++){ */ + //for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){ + /* k=k+1; */ + /* to clean */ + //printf("cptcov=%d cptcod=%d codtab=%d\n",cptcov, cptcod,codtabm(cptcod,cptcov)); + fprintf(ficrespl,"#******"); + printf("#******"); + fprintf(ficlog,"#******"); + for(j=1;j<=cptcoveff ;j++) {/* all covariates */ + fprintf(ficrespl," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]); /* Here problem for varying dummy*/ + printf(" V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]); + fprintf(ficlog," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]); + } + for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */ + printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); + fprintf(ficrespl," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); + fprintf(ficlog," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); + } + fprintf(ficrespl,"******\n"); + printf("******\n"); + fprintf(ficlog,"******\n"); + if(invalidvarcomb[k]){ + printf("\nCombination (%d) ignored because no case \n",k); + fprintf(ficrespl,"#Combination (%d) ignored because no case \n",k); + fprintf(ficlog,"\nCombination (%d) ignored because no case \n",k); + continue; + } + + fprintf(ficrespl,"#Age "); + for(j=1;j<=cptcoveff;j++) { + fprintf(ficrespl,"V%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]); + } + for(i=1; i<=nlstate;i++) fprintf(ficrespl," %d-%d ",i,i); + fprintf(ficrespl,"Total Years_to_converge\n"); + + for (age=agebase; age<=agelim; age++){ + /* for (age=agebase; age<=agebase; age++){ */ + prevalim(prlim, nlstate, p, age, oldm, savm, ftolpl, ncvyearp, k, nres); + fprintf(ficrespl,"%.0f ",age ); + for(j=1;j<=cptcoveff;j++) + fprintf(ficrespl,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]); + tot=0.; + for(i=1; i<=nlstate;i++){ + tot += prlim[i][i]; + fprintf(ficrespl," %.5f", prlim[i][i]); + } + fprintf(ficrespl," %.3f %d\n", tot, *ncvyearp); + } /* Age */ + /* was end of cptcod */ + } /* cptcov */ + } /* nres */ + return 0; +} + +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){ + /*--------------- Back Prevalence limit (period or stable prevalence) --------------*/ + + /* Computes the back prevalence limit for any combination of covariate values + * at any age between ageminpar and agemaxpar + */ + int i, j, k, i1, nres=0 ; + /* double ftolpl = 1.e-10; */ + double age, agebase, agelim; + double tot; + /* double ***mobaverage; */ + /* double **dnewm, **doldm, **dsavm; /\* for use *\/ */ + + strcpy(fileresplb,"PLB_"); + strcat(fileresplb,fileresu); + if((ficresplb=fopen(fileresplb,"w"))==NULL) { + printf("Problem with period (stable) back prevalence resultfile: %s\n", fileresplb);return 1; + fprintf(ficlog,"Problem with period (stable) back prevalence resultfile: %s\n", fileresplb);return 1; + } + printf("Computing period (stable) back prevalence: result on file '%s' \n", fileresplb); + fprintf(ficlog,"Computing period (stable) back prevalence: result on file '%s' \n", fileresplb); + pstamp(ficresplb); + fprintf(ficresplb,"# Period (stable) back prevalence. Precision given by ftolpl=%g \n", ftolpl); + fprintf(ficresplb,"#Age "); + for(i=1; i<=nlstate;i++) fprintf(ficresplb,"%d-%d ",i,i); + fprintf(ficresplb,"\n"); + + + /* prlim=matrix(1,nlstate,1,nlstate);*/ /* back in main */ + + agebase=ageminpar; + agelim=agemaxpar; + + + i1=pow(2,cptcoveff); + if (cptcovn < 1){i1=1;} + + for(nres=1; nres <= nresult; nres++){ /* For each resultline */ + for(k=1; k<=i1;k++){ /* For any combination of dummy covariates, fixed and varying */ + if(i1 != 1 && TKresult[nres]!= k) + continue; + //printf("cptcov=%d cptcod=%d codtab=%d\n",cptcov, cptcod,codtabm(cptcod,cptcov)); + fprintf(ficresplb,"#******"); + printf("#******"); + fprintf(ficlog,"#******"); + for(j=1;j<=cptcoveff ;j++) {/* all covariates */ + fprintf(ficresplb," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]); + printf(" V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]); + fprintf(ficlog," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]); + } + for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */ + printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]); + fprintf(ficresplb," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]); + fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]); + } + fprintf(ficresplb,"******\n"); + printf("******\n"); + fprintf(ficlog,"******\n"); + if(invalidvarcomb[k]){ + printf("\nCombination (%d) ignored because no cases \n",k); + fprintf(ficresplb,"#Combination (%d) ignored because no cases \n",k); + fprintf(ficlog,"\nCombination (%d) ignored because no cases \n",k); + continue; + } + + fprintf(ficresplb,"#Age "); + for(j=1;j<=cptcoveff;j++) { + fprintf(ficresplb,"V%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]); + } + for(i=1; i<=nlstate;i++) fprintf(ficresplb," %d-%d ",i,i); + fprintf(ficresplb,"Total Years_to_converge\n"); + + + for (age=agebase; age<=agelim; age++){ + /* for (age=agebase; age<=agebase; age++){ */ + if(mobilavproj > 0){ + /* bprevalim(bprlim, mobaverage, nlstate, p, age, ageminpar, agemaxpar, oldm, savm, doldm, dsavm, ftolpl, ncvyearp, k); */ + /* bprevalim(bprlim, mobaverage, nlstate, p, age, oldm, savm, dnewm, doldm, dsavm, ftolpl, ncvyearp, k); */ + bprevalim(bprlim, mobaverage, nlstate, p, age, ftolpl, ncvyearp, k, nres); + }else if (mobilavproj == 0){ + 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); + 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); + exit(1); + }else{ + /* bprevalim(bprlim, probs, nlstate, p, age, oldm, savm, dnewm, doldm, dsavm, ftolpl, ncvyearp, k); */ + bprevalim(bprlim, probs, nlstate, p, age, ftolpl, ncvyearp, k,nres); + } + fprintf(ficresplb,"%.0f ",age ); + for(j=1;j<=cptcoveff;j++) + fprintf(ficresplb,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]); + tot=0.; + for(i=1; i<=nlstate;i++){ + tot += bprlim[i][i]; + fprintf(ficresplb," %.5f", bprlim[i][i]); + } + fprintf(ficresplb," %.3f %d\n", tot, *ncvyearp); + } /* Age */ + /* was end of cptcod */ + } /* end of any combination */ + } /* end of nres */ + /* hBijx(p, bage, fage); */ + /* fclose(ficrespijb); */ + + return 0; +} + +int hPijx(double *p, int bage, int fage){ + /*------------- h Pij x at various ages ------------*/ + + int stepsize; + int agelim; + int hstepm; + int nhstepm; + int h, i, i1, j, k, k4, nres=0; + + double agedeb; + double ***p3mat; + + strcpy(filerespij,"PIJ_"); strcat(filerespij,fileresu); + if((ficrespij=fopen(filerespij,"w"))==NULL) { + printf("Problem with Pij resultfile: %s\n", filerespij); return 1; + fprintf(ficlog,"Problem with Pij resultfile: %s\n", filerespij); return 1; + } + printf("Computing pij: result on file '%s' \n", filerespij); + fprintf(ficlog,"Computing pij: result on file '%s' \n", filerespij); + + stepsize=(int) (stepm+YEARM-1)/YEARM; + /*if (stepm<=24) stepsize=2;*/ + + agelim=AGESUP; + hstepm=stepsize*YEARM; /* Every year of age */ + hstepm=hstepm/stepm; /* Typically 2 years, = 2/6 months = 4 */ + + /* hstepm=1; aff par mois*/ + pstamp(ficrespij); + fprintf(ficrespij,"#****** h Pij x Probability to be in state j at age x+h being in i at x "); + i1= pow(2,cptcoveff); + /* for(cptcov=1,k=0;cptcov<=i1;cptcov++){ */ + /* /\*for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){*\/ */ + /* k=k+1; */ + for(nres=1; nres <= nresult; nres++) /* For each resultline */ + for(k=1; k<=i1;k++){ + if(i1 != 1 && TKresult[nres]!= k) + continue; + fprintf(ficrespij,"\n#****** "); + for(j=1;j<=cptcoveff;j++) + fprintf(ficrespij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]); + for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */ + printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); + fprintf(ficrespij," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); + } + fprintf(ficrespij,"******\n"); + + for (agedeb=fage; agedeb>=bage; agedeb--){ /* If stepm=6 months */ + nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */ + nhstepm = nhstepm/hstepm; /* Typically 40/4=10 */ + + /* nhstepm=nhstepm*YEARM; aff par mois*/ + + p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); + oldm=oldms;savm=savms; + hpxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k, nres); + fprintf(ficrespij,"# Cov Agex agex+h hpijx with i,j="); + for(i=1; i<=nlstate;i++) + for(j=1; j<=nlstate+ndeath;j++) + fprintf(ficrespij," %1d-%1d",i,j); + fprintf(ficrespij,"\n"); + for (h=0; h<=nhstepm; h++){ + /*agedebphstep = agedeb + h*hstepm/YEARM*stepm;*/ + fprintf(ficrespij,"%d %3.f %3.f",k, agedeb, agedeb + h*hstepm/YEARM*stepm ); + for(i=1; i<=nlstate;i++) + for(j=1; j<=nlstate+ndeath;j++) + fprintf(ficrespij," %.5f", p3mat[i][j][h]); + fprintf(ficrespij,"\n"); + } + free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); + fprintf(ficrespij,"\n"); + } + /*}*/ + } + return 0; +} + + int hBijx(double *p, int bage, int fage, double ***prevacurrent){ + /*------------- h Bij x at various ages ------------*/ + + int stepsize; + /* int agelim; */ + int ageminl; + int hstepm; + int nhstepm; + int h, i, i1, j, k, nres; + + double agedeb; + double ***p3mat; + + strcpy(filerespijb,"PIJB_"); strcat(filerespijb,fileresu); + if((ficrespijb=fopen(filerespijb,"w"))==NULL) { + printf("Problem with Pij back resultfile: %s\n", filerespijb); return 1; + fprintf(ficlog,"Problem with Pij back resultfile: %s\n", filerespijb); return 1; + } + printf("Computing pij back: result on file '%s' \n", filerespijb); + fprintf(ficlog,"Computing pij back: result on file '%s' \n", filerespijb); + + stepsize=(int) (stepm+YEARM-1)/YEARM; + /*if (stepm<=24) stepsize=2;*/ + + /* agelim=AGESUP; */ + ageminl=30; + hstepm=stepsize*YEARM; /* Every year of age */ + hstepm=hstepm/stepm; /* Typically 2 years, = 2/6 months = 4 */ + + /* hstepm=1; aff par mois*/ + pstamp(ficrespijb); + fprintf(ficrespijb,"#****** h Pij x Back Probability to be in state i at age x-h being in j at x "); + i1= pow(2,cptcoveff); + /* for(cptcov=1,k=0;cptcov<=i1;cptcov++){ */ + /* /\*for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){*\/ */ + /* k=k+1; */ + for(nres=1; nres <= nresult; nres++){ /* For each resultline */ + for(k=1; k<=i1;k++){ /* For any combination of dummy covariates, fixed and varying */ + if(i1 != 1 && TKresult[nres]!= k) + continue; + fprintf(ficrespijb,"\n#****** "); + for(j=1;j<=cptcoveff;j++) + fprintf(ficrespijb,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]); + for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */ + fprintf(ficrespijb," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]); + } + fprintf(ficrespijb,"******\n"); + if(invalidvarcomb[k]){ + fprintf(ficrespijb,"\n#Combination (%d) ignored because no cases \n",k); + continue; + } + + /* for (agedeb=fage; agedeb>=bage; agedeb--){ /\* If stepm=6 months *\/ */ + for (agedeb=bage; agedeb<=fage; agedeb++){ /* If stepm=6 months and estepm=24 (2 years) */ + /* nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); /\* Typically 20 years = 20*12/6=40 *\/ */ + nhstepm=(int) rint((agedeb-ageminl)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */ + nhstepm = nhstepm/hstepm; /* Typically 40/4=10, because estepm=24 stepm=6 => hstepm=24/6=4 */ + + /* nhstepm=nhstepm*YEARM; aff par mois*/ + + p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); + /* oldm=oldms;savm=savms; */ + /* hbxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k); */ + hbxij(p3mat,nhstepm,agedeb,hstepm,p,prevacurrent,nlstate,stepm, k); + /* hbxij(p3mat,nhstepm,agedeb,hstepm,p,prevacurrent,nlstate,stepm,oldm,savm, dnewm, doldm, dsavm, k); */ + fprintf(ficrespijb,"# Cov Agex agex-h hpijx with i,j="); + for(i=1; i<=nlstate;i++) + for(j=1; j<=nlstate+ndeath;j++) + fprintf(ficrespijb," %1d-%1d",i,j); + fprintf(ficrespijb,"\n"); + for (h=0; h<=nhstepm; h++){ + /*agedebphstep = agedeb + h*hstepm/YEARM*stepm;*/ + fprintf(ficrespijb,"%d %3.f %3.f",k, agedeb, agedeb - h*hstepm/YEARM*stepm ); + /* fprintf(ficrespijb,"%d %3.f %3.f",k, agedeb, agedeb + h*hstepm/YEARM*stepm ); */ + for(i=1; i<=nlstate;i++) + for(j=1; j<=nlstate+ndeath;j++) + fprintf(ficrespijb," %.5f", p3mat[i][j][h]); + fprintf(ficrespijb,"\n"); + } + free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); + fprintf(ficrespijb,"\n"); + } /* end age deb */ + } /* end combination */ + } /* end nres */ + return 0; + } /* hBijx */ + + +/***********************************************/ +/**************** Main Program *****************/ +/***********************************************/ + +int main(int argc, char *argv[]) +{ +#ifdef GSL + const gsl_multimin_fminimizer_type *T; + size_t iteri = 0, it; + int rval = GSL_CONTINUE; + int status = GSL_SUCCESS; + double ssval; +#endif + int movingaverage(double ***probs, double bage,double fage, double ***mobaverage, int mobilav); + int i,j, k, n=MAXN,iter=0,m,size=100, cptcod; + int ncvyear=0; /* Number of years needed for the period prevalence to converge */ + int jj, ll, li, lj, lk; + int numlinepar=0; /* Current linenumber of parameter file */ + int num_filled; + int itimes; + int NDIM=2; + int vpopbased=0; + int nres=0; + + char ca[32], cb[32]; + /* FILE *fichtm; *//* Html File */ + /* FILE *ficgp;*/ /*Gnuplot File */ + struct stat info; + double agedeb=0.; + + double ageminpar=AGEOVERFLOW,agemin=AGEOVERFLOW, agemaxpar=-AGEOVERFLOW, agemax=-AGEOVERFLOW; + double ageminout=-AGEOVERFLOW,agemaxout=AGEOVERFLOW; /* Smaller Age range redefined after movingaverage */ + + double fret; + double dum=0.; /* Dummy variable */ + double ***p3mat; + /* double ***mobaverage; */ + + char line[MAXLINE]; + char path[MAXLINE],pathc[MAXLINE],pathcd[MAXLINE],pathtot[MAXLINE]; + + char modeltemp[MAXLINE]; + char resultline[MAXLINE]; - int hstepm, nhstepm; - double bage, fage, age, agelim, agebase; + char pathr[MAXLINE], pathimach[MAXLINE]; + char *tok, *val; /* pathtot */ + int firstobs=1, lastobs=10; + int c, h , cpt, c2; + int jl=0; + int i1, j1, jk, stepsize=0; + int count=0; + + int *tab; + int mobilavproj=0 , prevfcast=0 ; /* moving average of prev, If prevfcast=1 prevalence projection */ + int backcast=0; + int mobilav=0,popforecast=0; + int hstepm=0, nhstepm=0; + int agemortsup; + float sumlpop=0.; + double jprev1=1, mprev1=1,anprev1=2000,jprev2=1, mprev2=1,anprev2=2000; + double jpyram=1, mpyram=1,anpyram=2000,jpyram1=1, mpyram1=1,anpyram1=2000; + + double bage=0, fage=110., age, agelim=0., agebase=0.; double ftolpl=FTOL; double **prlim; - double *severity; + double **bprlim; double ***param; /* Matrix of parameters */ - double *p; + double ***paramstart; /* Matrix of starting parameter values */ + double *p, *pstart; /* p=param[1][1] pstart is for starting values guessed by freqsummary */ double **matcov; /* Matrix of covariance */ + double **hess; /* Hessian matrix */ double ***delti3; /* Scale */ double *delti; /* Scale */ double ***eij, ***vareij; double **varpl; /* Variances of prevalence limits by age */ double *epj, vepp; - char version[80]="Imach version 0.64, May 2000, INED-EUROREVES "; - char *alph[]={"a","a","b","c","d","e"}, str[4]; + + double dateprev1, dateprev2,jproj1=1,mproj1=1,anproj1=2000,jproj2=1,mproj2=1,anproj2=2000; + double jback1=1,mback1=1,anback1=2000,jback2=1,mback2=1,anback2=2000; + + double **ximort; + char *alph[]={"a","a","b","c","d","e"}, str[4]="1234"; + int *dcwave; + char z[1]="c"; -#include -#include - /* long total_usecs; - struct timeval start_time, end_time; - - gettimeofday(&start_time, (struct timezone*)0); */ /* at first time */ + /*char *strt;*/ + char strtend[80]; - printf("\nIMACH, Version 0.64"); - printf("\nEnter the parameter file name: "); -#define windows 1 -#ifdef windows - scanf("%s",pathtot); +/* setlocale (LC_ALL, ""); */ +/* bindtextdomain (PACKAGE, LOCALEDIR); */ +/* textdomain (PACKAGE); */ +/* setlocale (LC_CTYPE, ""); */ +/* setlocale (LC_MESSAGES, ""); */ + + /* gettimeofday(&start_time, (struct timezone*)0); */ /* at first time */ + rstart_time = time(NULL); + /* (void) gettimeofday(&start_time,&tzp);*/ + start_time = *localtime(&rstart_time); + curr_time=start_time; + /*tml = *localtime(&start_time.tm_sec);*/ + /* strcpy(strstart,asctime(&tml)); */ + strcpy(strstart,asctime(&start_time)); + +/* printf("Localtime (at start)=%s",strstart); */ +/* tp.tm_sec = tp.tm_sec +86400; */ +/* tm = *localtime(&start_time.tm_sec); */ +/* tmg.tm_year=tmg.tm_year +dsign*dyear; */ +/* tmg.tm_mon=tmg.tm_mon +dsign*dmonth; */ +/* tmg.tm_hour=tmg.tm_hour + 1; */ +/* tp.tm_sec = mktime(&tmg); */ +/* strt=asctime(&tmg); */ +/* printf("Time(after) =%s",strstart); */ +/* (void) time (&time_value); +* printf("time=%d,t-=%d\n",time_value,time_value-86400); +* tm = *localtime(&time_value); +* strstart=asctime(&tm); +* printf("tim_value=%d,asctime=%s\n",time_value,strstart); +*/ + + nberr=0; /* Number of errors and warnings */ + nbwarn=0; +#ifdef WIN32 + _getcwd(pathcd, size); +#else getcwd(pathcd, size); - cut(path,optionfile,pathtot); - chdir(path); - replace(pathc,path); #endif -#ifdef unix - scanf("%s",optionfile); + syscompilerinfo(0); + printf("\nIMaCh version %s, %s\n%s",version, copyright, fullversion); + if(argc <=1){ + printf("\nEnter the parameter file name: "); + if(!fgets(pathr,FILENAMELENGTH,stdin)){ + printf("ERROR Empty parameter file name\n"); + goto end; + } + i=strlen(pathr); + if(pathr[i-1]=='\n') + pathr[i-1]='\0'; + i=strlen(pathr); + if(i >= 1 && pathr[i-1]==' ') {/* This may happen when dragging on oS/X! */ + pathr[i-1]='\0'; + } + i=strlen(pathr); + if( i==0 ){ + printf("ERROR Empty parameter file name\n"); + goto end; + } + for (tok = pathr; tok != NULL; ){ + printf("Pathr |%s|\n",pathr); + while ((val = strsep(&tok, "\"" )) != NULL && *val == '\0'); + printf("val= |%s| pathr=%s\n",val,pathr); + strcpy (pathtot, val); + if(pathr[0] == '\0') break; /* Dirty */ + } + } + else{ + strcpy(pathtot,argv[1]); + } + /*if(getcwd(pathcd, MAXLINE)!= NULL)printf ("Error pathcd\n");*/ + /*cygwin_split_path(pathtot,path,optionfile); + printf("pathtot=%s, path=%s, optionfile=%s\n",pathtot,path,optionfile);*/ + /* cutv(path,optionfile,pathtot,'\\');*/ + + /* Split argv[0], imach program to get pathimach */ + printf("\nargv[0]=%s argv[1]=%s, \n",argv[0],argv[1]); + split(argv[0],pathimach,optionfile,optionfilext,optionfilefiname); + printf("\nargv[0]=%s pathimach=%s, \noptionfile=%s \noptionfilext=%s \noptionfilefiname=%s\n",argv[0],pathimach,optionfile,optionfilext,optionfilefiname); + /* strcpy(pathimach,argv[0]); */ + /* Split argv[1]=pathtot, parameter file name to get path, optionfile, extension and name */ + split(pathtot,path,optionfile,optionfilext,optionfilefiname); + printf("\npathtot=%s,\npath=%s,\noptionfile=%s \noptionfilext=%s \noptionfilefiname=%s\n",pathtot,path,optionfile,optionfilext,optionfilefiname); +#ifdef WIN32 + _chdir(path); /* Can be a relative path */ + if(_getcwd(pathcd,MAXLINE) > 0) /* So pathcd is the full path */ +#else + chdir(path); /* Can be a relative path */ + if (getcwd(pathcd, MAXLINE) > 0) /* So pathcd is the full path */ #endif + printf("Current directory %s!\n",pathcd); + strcpy(command,"mkdir "); + strcat(command,optionfilefiname); + if((outcmd=system(command)) != 0){ + printf("Directory already exists (or can't create it) %s%s, err=%d\n",path,optionfilefiname,outcmd); + /* fprintf(ficlog,"Problem creating directory %s%s\n",path,optionfilefiname); */ + /* fclose(ficlog); */ +/* exit(1); */ + } +/* if((imk=mkdir(optionfilefiname))<0){ */ +/* perror("mkdir"); */ +/* } */ + + /*-------- arguments in the command line --------*/ + + /* Main Log file */ + strcat(filelog, optionfilefiname); + strcat(filelog,".log"); /* */ + if((ficlog=fopen(filelog,"w"))==NULL) { + printf("Problem with logfile %s\n",filelog); + goto end; + } + fprintf(ficlog,"Log filename:%s\n",filelog); + fprintf(ficlog,"Version %s %s",version,fullversion); + fprintf(ficlog,"\nEnter the parameter file name: \n"); + fprintf(ficlog,"pathimach=%s\npathtot=%s\n\ + path=%s \n\ + optionfile=%s\n\ + optionfilext=%s\n\ + optionfilefiname='%s'\n",pathimach,pathtot,path,optionfile,optionfilext,optionfilefiname); + + syscompilerinfo(1); + + printf("Local time (at start):%s",strstart); + fprintf(ficlog,"Local time (at start): %s",strstart); + fflush(ficlog); +/* (void) gettimeofday(&curr_time,&tzp); */ +/* printf("Elapsed time %d\n", asc_diff_time(curr_time.tm_sec-start_time.tm_sec,tmpout)); */ -/*-------- arguments in the command line --------*/ - + /* */ strcpy(fileres,"r"); - strcat(fileres, optionfile); + strcat(fileres, optionfilefiname); + strcat(fileresu, optionfilefiname); /* Without r in front */ + strcat(fileres,".txt"); /* Other files have txt extension */ + strcat(fileresu,".txt"); /* Other files have txt extension */ - /*---------arguments file --------*/ + /* Main ---------arguments file --------*/ if((ficpar=fopen(optionfile,"r"))==NULL) { - printf("Problem with optionfile %s\n",optionfile); - goto end; + printf("Problem with optionfile '%s' with errno='%s'\n",optionfile,strerror(errno)); + fprintf(ficlog,"Problem with optionfile '%s' with errno='%s'\n",optionfile,strerror(errno)); + fflush(ficlog); + /* goto end; */ + exit(70); } - strcpy(filereso,"o"); - strcat(filereso,fileres); - if((ficparo=fopen(filereso,"w"))==NULL) { - printf("Problem with Output resultfile: %s\n", filereso);goto end; - } - -/*--------- index.htm --------*/ - - if((fichtm=fopen("index.htm","w"))==NULL) { - printf("Problem with index.htm \n");goto end; - } - - fprintf(fichtm,"
        • Outputs files

          \n - - Observed prevalence in each state: p%s
          \n -- Estimated parameters and the covariance matrix: %s
          - - Stationary prevalence in each state: pl%s
          - - Transition probabilities: pij%s
          - - Copy of the parameter file: o%s
          - - Life expectancies by age and initial health status: e%s
          - - Variances of life expectancies by age and initial health status: v%s
          - - Health expectancies with their variances: t%s
          - - Standard deviation of stationary prevalences: vpl%s

          ",fileres,fileres,fileres,fileres,fileres,fileres,fileres,fileres,fileres,fileres,fileres,fileres,fileres,fileres,fileres,fileres,fileres,fileres); - - fprintf(fichtm,"
        • Graphs

          "); - -for(cpt=1; cpt -
          ",strtok(optionfile, "."),strtok(optionfile, "."),cpt); - for(cpt=1; cpt<=nlstate;cpt++) - fprintf(fichtm,"- Observed and stationary prevalence (with confident -interval) in state (%d): v%s%d.gif
          -
          ",cpt,strtok(optionfile, "."),cpt,strtok(optionfile, "."),cpt); - - for(cpt=1; cpt<=nlstate;cpt++) - fprintf(fichtm,"- Health life expectancies by age and initial health state (%d): exp%s%d.gif
          -
          ",cpt,strtok(optionfile, "."),cpt,strtok(optionfile, "."),cpt); - - fprintf(fichtm,"- Total life expectancy by age and - health expectancies in states (1) and (2): e%s.gif
          -
        ",strtok(optionfile, "."),strtok(optionfile, ".")); -fclose(fichtm); + strcpy(filereso,"o"); + strcat(filereso,fileresu); + if((ficparo=fopen(filereso,"w"))==NULL) { /* opened on subdirectory */ + printf("Problem with Output resultfile: %s\n", filereso); + fprintf(ficlog,"Problem with Output resultfile: %s\n", filereso); + fflush(ficlog); + goto end; + } /* Reads comments: lines beginning with '#' */ + numlinepar=0; + + /* First parameter line */ + while(fgets(line, MAXLINE, ficpar)) { + /* If line starts with a # it is a comment */ + if (line[0] == '#') { + numlinepar++; + fputs(line,stdout); + fputs(line,ficparo); + fputs(line,ficlog); + continue; + }else + break; + } + if((num_filled=sscanf(line,"title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", \ + title, datafile, &lastobs, &firstpass,&lastpass)) !=EOF){ + if (num_filled != 5) { + printf("Should be 5 parameters\n"); + } + numlinepar++; + printf("title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", title, datafile, lastobs, firstpass,lastpass); + } + /* Second parameter line */ + while(fgets(line, MAXLINE, ficpar)) { + /* If line starts with a # it is a comment */ + if (line[0] == '#') { + numlinepar++; + fputs(line,stdout); + fputs(line,ficparo); + fputs(line,ficlog); + continue; + }else + break; + } + 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", \ + &ftol, &stepm, &ncovcol, &nqv, &ntv, &nqtv, &nlstate, &ndeath, &maxwav, &mle, &weightopt)) !=EOF){ + if (num_filled != 11) { + 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"); + printf("but line=%s\n",line); + } + 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); + } + /* ftolpl=6*ftol*1.e5; /\* 6.e-3 make convergences in less than 80 loops for the prevalence limit *\/ */ + /*ftolpl=6.e-4; *//* 6.e-3 make convergences in less than 80 loops for the prevalence limit */ + /* Third parameter line */ + while(fgets(line, MAXLINE, ficpar)) { + /* If line starts with a # it is a comment */ + if (line[0] == '#') { + numlinepar++; + fputs(line,stdout); + fputs(line,ficparo); + fputs(line,ficlog); + continue; + }else + break; + } + if((num_filled=sscanf(line,"model=1+age%[^.\n]", model)) !=EOF){ + if (num_filled == 0) + model[0]='\0'; + else if (num_filled != 1){ + printf("ERROR %d: Model should be at minimum 'model=1+age.' %s\n",num_filled, line); + fprintf(ficlog,"ERROR %d: Model should be at minimum 'model=1+age.' %s\n",num_filled, line); + model[0]='\0'; + goto end; + } + else{ + if (model[0]=='+'){ + for(i=1; i<=strlen(model);i++) + modeltemp[i-1]=model[i]; + strcpy(model,modeltemp); + } + } + /* printf(" model=1+age%s modeltemp= %s, model=%s\n",model, modeltemp, model);fflush(stdout); */ + printf("model=1+age+%s\n",model);fflush(stdout); + } + /* 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); */ + /* numlinepar=numlinepar+3; /\* In general *\/ */ + /* 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); */ + 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); + 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); + fflush(ficlog); + /* if(model[0]=='#'|| model[0]== '\0'){ */ + if(model[0]=='#'){ + printf("Error in 'model' line: model should start with 'model=1+age+' and end with '.' \n \ + 'model=1+age+.' or 'model=1+age+V1.' or 'model=1+age+age*age+V1+V1*age.' or \n \ + 'model=1+age+V1+V2.' or 'model=1+age+V1+V2+V1*V2.' etc. \n"); \ + if(mle != -1){ + printf("Fix the model line and run imach with mle=-1 to get a correct template of the parameter file.\n"); + exit(1); + } + } while((c=getc(ficpar))=='#' && c!= EOF){ ungetc(c,ficpar); fgets(line, MAXLINE, ficpar); - puts(line); + numlinepar++; + if(line[1]=='q'){ /* This #q will quit imach (the answer is q) */ + z[0]=line[1]; + } + /* printf("****line [1] = %c \n",line[1]); */ + fputs(line, stdout); + //puts(line); fputs(line,ficparo); + fputs(line,ficlog); } ungetc(c,ficpar); - fscanf(ficpar,"title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\nftol=%lf stepm=%d ncov=%d nlstate=%d ndeath=%d maxwav=%d mle=%d weight=%d\n",title, datafile, &lastobs, &firstpass,&lastpass,&ftol, &stepm, &ncov, &nlstate,&ndeath, &maxwav, &mle, &weightopt); - printf("title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\nftol=%e stepm=%d ncov=%d nlstate=%d ndeath=%d maxwav=%d mle=%d weight=%d\n", title, datafile, lastobs, firstpass,lastpass,ftol, stepm, ncov, nlstate,ndeath, maxwav, mle, weightopt); - fprintf(ficparo,"title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\nftol=%e stepm=%d ncov=%d nlstate=%d ndeath=%d maxwav=%d mle=%d weight=%d\n", title, datafile, lastobs, firstpass,lastpass,ftol,stepm,ncov,nlstate,ndeath,maxwav, mle, weightopt); - - nvar=ncov-1; /* Suppressing age as a basic covariate */ - - /* Read guess parameters */ - /* Reads comments: lines beginning with '#' */ - while((c=getc(ficpar))=='#' && c!= EOF){ - ungetc(c,ficpar); - fgets(line, MAXLINE, ficpar); - puts(line); - fputs(line,ficparo); + + covar=matrix(0,NCOVMAX,1,n); /**< used in readdata */ + coqvar=matrix(1,nqv,1,n); /**< Fixed quantitative covariate */ + cotvar=ma3x(1,maxwav,1,ntv+nqtv,1,n); /**< Time varying covariate (dummy and quantitative)*/ + cotqvar=ma3x(1,maxwav,1,nqtv,1,n); /**< Time varying quantitative covariate */ + cptcovn=0; /*Number of covariates, i.e. number of '+' in model statement plus one, indepently of n in Vn*/ + /* v1+v2+v3+v2*v4+v5*age makes cptcovn = 5 + v1+v2*age+v2*v3 makes cptcovn = 3 + */ + if (strlen(model)>1) + 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*/ + else + ncovmodel=2; /* Constant and age */ + nforce= (nlstate+ndeath-1)*nlstate; /* Number of forces ij from state i to j */ + npar= nforce*ncovmodel; /* Number of parameters like aij*/ + if(npar >MAXPARM || nlstate >NLSTATEMAX || ndeath >NDEATHMAX || ncovmodel>NCOVMAX){ + 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); + 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); + fflush(stdout); + fclose (ficlog); + goto end; } - ungetc(c,ficpar); - - param= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncov); - for(i=1; i <=nlstate; i++) - for(j=1; j <=nlstate+ndeath-1; j++){ - fscanf(ficpar,"%1d%1d",&i1,&j1); - fprintf(ficparo,"%1d%1d",i1,j1); - printf("%1d%1d",i,j); - for(k=1; k<=ncov;k++){ - fscanf(ficpar," %lf",¶m[i][j][k]); - printf(" %lf",param[i][j][k]); - fprintf(ficparo," %lf",param[i][j][k]); + delti3= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel); + delti=delti3[1][1]; + /*delti=vector(1,npar); *//* Scale of each paramater (output from hesscov)*/ + if(mle==-1){ /* Print a wizard for help writing covariance matrix */ +/* We could also provide initial parameters values giving by simple logistic regression + * only one way, that is without matrix product. We will have nlstate maximizations */ + /* for(i=1;i16 */ + ncodemaxwundef=ivector(1,NCOVMAX); /* Number of code per covariate; if - 1 O and 1 only, 2**ncov; V1+V2+V3+V4=>16 */ + + /* Reads data from file datafile */ + if (readdata(datafile, firstobs, lastobs, &imx)==1) + goto end; + + /* Calculation of the number of parameters from char model */ + /* modelsav=V2+V1+V4+age*V3 strb=age*V3 stra=V2+V1+V4 + k=4 (age*V3) Tvar[k=4]= 3 (from V3) Tag[cptcovage=1]=4 + k=3 V4 Tvar[k=3]= 4 (from V4) + k=2 V1 Tvar[k=2]= 1 (from V1) + k=1 Tvar[1]=2 (from V2) + */ - matcov=matrix(1,npar,1,npar); - for(i=1; i <=npar; i++){ - fscanf(ficpar,"%s",&str); - printf("%s",str); - fprintf(ficparo,"%s",str); - for(j=1; j <=i; j++){ - fscanf(ficpar," %le",&matcov[i][j]); - printf(" %.5le",matcov[i][j]); - fprintf(ficparo," %.5le",matcov[i][j]); - } - fscanf(ficpar,"\n"); - printf("\n"); - fprintf(ficparo,"\n"); + Tvar=ivector(1,NCOVMAX); /* Was 15 changed to NCOVMAX. */ + TvarsDind=ivector(1,NCOVMAX); /* */ + TvarsD=ivector(1,NCOVMAX); /* */ + TvarsQind=ivector(1,NCOVMAX); /* */ + TvarsQ=ivector(1,NCOVMAX); /* */ + TvarF=ivector(1,NCOVMAX); /* */ + TvarFind=ivector(1,NCOVMAX); /* */ + TvarV=ivector(1,NCOVMAX); /* */ + TvarVind=ivector(1,NCOVMAX); /* */ + TvarA=ivector(1,NCOVMAX); /* */ + TvarAind=ivector(1,NCOVMAX); /* */ + TvarFD=ivector(1,NCOVMAX); /* */ + TvarFDind=ivector(1,NCOVMAX); /* */ + TvarFQ=ivector(1,NCOVMAX); /* */ + TvarFQind=ivector(1,NCOVMAX); /* */ + TvarVD=ivector(1,NCOVMAX); /* */ + TvarVDind=ivector(1,NCOVMAX); /* */ + TvarVQ=ivector(1,NCOVMAX); /* */ + TvarVQind=ivector(1,NCOVMAX); /* */ + + Tvalsel=vector(1,NCOVMAX); /* */ + Tvarsel=ivector(1,NCOVMAX); /* */ + Typevar=ivector(-1,NCOVMAX); /* -1 to 2 */ + Fixed=ivector(-1,NCOVMAX); /* -1 to 3 */ + Dummy=ivector(-1,NCOVMAX); /* -1 to 3 */ + /* V2+V1+V4+age*V3 is a model with 4 covariates (3 plus signs). + For each model-covariate stores the data-covariate id. Tvar[1]=2, Tvar[2]=1, Tvar[3]=4, + Tvar[4=age*V3] is 3 and 'age' is recorded in Tage. + */ + /* For model-covariate k tells which data-covariate to use but + because this model-covariate is a construction we invent a new column + ncovcol + k1 + If already ncovcol=4 and model=V2+V1+V1*V4+age*V3 + Tvar[3=V1*V4]=4+1 etc */ + Tprod=ivector(1,NCOVMAX); /* Gives the k position of the k1 product */ + Tposprod=ivector(1,NCOVMAX); /* Gives the k1 product from the k position */ + /* Tprod[k1=1]=3(=V1*V4) for V2+V1+V1*V4+age*V3 + if V2+V1+V1*V4+age*V3+V3*V2 TProd[k1=2]=5 (V3*V2) + Tposprod[k]=k1 , Tposprod[3]=1, Tposprod[5]=2 + */ + Tvaraff=ivector(1,NCOVMAX); /* Unclear */ + 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 + * For V3*V2 (in V2+V1+V1*V4+age*V3+V3*V2), V3*V2 position is 2nd. + * Tvard[k1=2][1]=3 (V3) Tvard[k1=2][2]=2(V2) */ + Tage=ivector(1,NCOVMAX); /* Gives the covariate id of covariates associated with age: V2 + V1 + age*V4 + V3*age + 4 covariates (3 plus signs) + Tage[1=V3*age]= 4; Tage[2=age*V4] = 3 + */ + Tmodelind=ivector(1,NCOVMAX);/** gives the k model position of an + * individual dummy, fixed or varying: + * Tmodelind[Tvaraff[3]]=9,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 , + * V1 df, V2 qf, V3 & V4 dv, V5 qv + * Tmodelind[1]@9={9,0,3,2,}*/ + TmodelInvind=ivector(1,NCOVMAX); /* TmodelInvind=Tvar[k]- ncovcol-nqv={5-2-1=2,*/ + TmodelInvQind=ivector(1,NCOVMAX);/** gives the k model position of an + * individual quantitative, fixed or varying: + * Tmodelqind[1]=1,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*/ +/* Main decodemodel */ + + + if(decodemodel(model, lastobs) == 1) /* In order to get Tvar[k] V4+V3+V5 p Tvar[1]@3 = {4, 3, 5}*/ + goto end; + + if((double)(lastobs-imx)/(double)imx > 1.10){ + nbwarn++; + 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); + 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); + } + /* if(mle==1){*/ + if (weightopt != 1) { /* Maximisation without weights. We can have weights different from 1 but want no weight*/ + for(i=1;i<=imx;i++) weight[i]=1.0; /* changed to imx */ } - for(i=1; i <=npar; i++) - for(j=i+1;j<=npar;j++) - matcov[i][j]=matcov[j][i]; + + /*-calculation of age at interview from date of interview and age at death -*/ + agev=matrix(1,maxwav,1,imx); + + if(calandcheckages(imx, maxwav, &agemin, &agemax, &nberr, &nbwarn) == 1) + goto end; + + + agegomp=(int)agemin; + free_vector(moisnais,1,n); + free_vector(annais,1,n); + /* free_matrix(mint,1,maxwav,1,n); + free_matrix(anint,1,maxwav,1,n);*/ + /* free_vector(moisdc,1,n); */ + /* free_vector(andc,1,n); */ + /* */ + + wav=ivector(1,imx); + /* dh=imatrix(1,lastpass-firstpass+1,1,imx); */ + /* bh=imatrix(1,lastpass-firstpass+1,1,imx); */ + /* mw=imatrix(1,lastpass-firstpass+1,1,imx); */ + 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.*/ + bh=imatrix(1,lastpass-firstpass+2,1,imx); + mw=imatrix(1,lastpass-firstpass+2,1,imx); - printf("\n"); + /* Concatenates waves */ + /* Concatenates waves: wav[i] is the number of effective (useful waves) of individual i. + Death is a valid wave (if date is known). + mw[mi][i] is the number of (mi=1 to wav[i]) effective wave out of mi of individual i + dh[m][i] or dh[mw[mi][i]][i] is the delay between two effective waves m=mw[mi][i] + and mw[mi+1][i]. dh depends on stepm. + */ + + concatwav(wav, dh, bh, mw, s, agedc, agev, firstpass, lastpass, imx, nlstate, stepm); + /* Concatenates waves */ + + free_vector(moisdc,1,n); + free_vector(andc,1,n); + + /* Routine tricode is to calculate cptcoveff (real number of unique covariates) and to associate covariable number and modality */ + nbcode=imatrix(0,NCOVMAX,0,NCOVMAX); + ncodemax[1]=1; + Ndum =ivector(-1,NCOVMAX); + cptcoveff=0; + if (ncovmodel-nagesqr > 2 ){ /* That is if covariate other than cst, age and age*age */ + tricode(&cptcoveff,Tvar,nbcode,imx, Ndum); /**< Fills nbcode[Tvar[j]][l]; */ + } + + ncovcombmax=pow(2,cptcoveff); + invalidvarcomb=ivector(1, ncovcombmax); + for(i=1;i 0) */ + m=pow(2,cptcoveff); + + /**< codtab(h,k) k = codtab[h,k]=( (h-1) - mod(k-1,2**(k-1) )/2**(k-1) + 1 + * For k=4 covariates, h goes from 1 to m=2**k + * codtabm(h,k)= (1 & (h-1) >> (k-1)) + 1; + * #define codtabm(h,k) (1 & (h-1) >> (k-1))+1 + * h\k 1 2 3 4 + *______________________________ + * 1 i=1 1 i=1 1 i=1 1 i=1 1 + * 2 2 1 1 1 + * 3 i=2 1 2 1 1 + * 4 2 2 1 1 + * 5 i=3 1 i=2 1 2 1 + * 6 2 1 2 1 + * 7 i=4 1 2 2 1 + * 8 2 2 2 1 + * 9 i=5 1 i=3 1 i=2 1 2 + * 10 2 1 1 2 + * 11 i=6 1 2 1 2 + * 12 2 2 1 2 + * 13 i=7 1 i=4 1 2 2 + * 14 2 1 2 2 + * 15 i=8 1 2 2 2 + * 16 2 2 2 2 + */ + /* How to do the opposite? From combination h (=1 to 2**k) how to get the value on the covariates? */ + /* from h=5 and m, we get then number of covariates k=log(m)/log(2)=4 + * and the value of each covariate? + * V1=1, V2=1, V3=2, V4=1 ? + * h-1=4 and 4 is 0100 or reverse 0010, and +1 is 1121 ok. + * h=6, 6-1=5, 5 is 0101, 1010, 2121, V1=2nd, V2=1st, V3=2nd, V4=1st. + * In order to get the real value in the data, we use nbcode + * nbcode[Tvar[3][2nd]]=1 and nbcode[Tvar[4][1]]=0 + * We are keeping this crazy system in order to be able (in the future?) + * to have more than 2 values (0 or 1) for a covariate. + * #define codtabm(h,k) (1 & (h-1) >> (k-1))+1 + * h=6, k=2? h-1=5=0101, reverse 1010, +1=2121, k=2nd position: value is 1: codtabm(6,2)=1 + * bbbbbbbb + * 76543210 + * h-1 00000101 (6-1=5) + *(h-1)>>(k-1)= 00000010 >> (2-1) = 1 right shift + * & + * 1 00000001 (1) + * 00000000 = 1 & ((h-1) >> (k-1)) + * +1= 00000001 =1 + * + * h=14, k=3 => h'=h-1=13, k'=k-1=2 + * h' 1101 =2^3+2^2+0x2^1+2^0 + * >>k' 11 + * & 00000001 + * = 00000001 + * +1 = 00000010=2 = codtabm(14,3) + * Reverse h=6 and m=16? + * cptcoveff=log(16)/log(2)=4 covariate: 6-1=5=0101 reversed=1010 +1=2121 =>V1=2, V2=1, V3=2, V4=1. + * for (j=1 to cptcoveff) Vj=decodtabm(j,h,cptcoveff) + * decodtabm(h,j,cptcoveff)= (((h-1) >> (j-1)) & 1) +1 + * decodtabm(h,j,cptcoveff)= (h <= (1<> (j-1)) & 1) +1 : -1) + * V3=decodtabm(14,3,2**4)=2 + * h'=13 1101 =2^3+2^2+0x2^1+2^0 + *(h-1) >> (j-1) 0011 =13 >> 2 + * &1 000000001 + * = 000000001 + * +1= 000000010 =2 + * 2211 + * V1=1+1, V2=0+1, V3=1+1, V4=1+1 + * V3=2 + * codtabm and decodtabm are identical + */ + + + free_ivector(Ndum,-1,NCOVMAX); + + + + /* Initialisation of ----------- gnuplot -------------*/ + strcpy(optionfilegnuplot,optionfilefiname); + if(mle==-3) + strcat(optionfilegnuplot,"-MORT_"); + strcat(optionfilegnuplot,".gp"); + + if((ficgp=fopen(optionfilegnuplot,"w"))==NULL) { + printf("Problem with file %s",optionfilegnuplot); + } + else{ + fprintf(ficgp,"\n# IMaCh-%s\n", version); + fprintf(ficgp,"# %s\n", optionfilegnuplot); + //fprintf(ficgp,"set missing 'NaNq'\n"); + fprintf(ficgp,"set datafile missing 'NaNq'\n"); + } + /* fclose(ficgp);*/ + + + /* Initialisation of --------- index.htm --------*/ + + strcpy(optionfilehtm,optionfilefiname); /* Main html file */ + if(mle==-3) + strcat(optionfilehtm,"-MORT_"); + strcat(optionfilehtm,".htm"); + if((fichtm=fopen(optionfilehtm,"w"))==NULL) { + printf("Problem with %s \n",optionfilehtm); + exit(0); + } + + strcpy(optionfilehtmcov,optionfilefiname); /* Only for matrix of covariance */ + strcat(optionfilehtmcov,"-cov.htm"); + if((fichtmcov=fopen(optionfilehtmcov,"w"))==NULL) { + printf("Problem with %s \n",optionfilehtmcov), exit(0); + } + else{ + fprintf(fichtmcov,"\nIMaCh Cov %s\n %s
        %s
        \ +
        \n\ +Title=%s
        Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s
        \n",\ + optionfilehtmcov,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model); + } + + fprintf(fichtm,"\n\n\nIMaCh %s\n IMaCh for Interpolated Markov Chain
        \nSponsored by Copyright (C) 2002-2015 INED-EUROREVES-Institut de longévité-2013-2016-Japan Society for the Promotion of Sciences 日本学術振興会 (Grant-in-Aid for Scientific Research 25293121) - Intel Software 2015-2018
        \ +
        \n\ +IMaCh-%s
        %s
        \ +
        \n\ +Title=%s
        Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s
        \n\ +\n\ +
        \ +
        • Parameter files

          \n\ + - Parameter file: %s.%s
          \n\ + - Copy of the parameter file: o%s
          \n\ + - Log file of the run: %s
          \n\ + - Gnuplot file name: %s
          \n\ + - Date and time at start: %s
        \n",\ + optionfilehtm,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model,\ + optionfilefiname,optionfilext,optionfilefiname,optionfilext,\ + fileres,fileres,\ + filelog,filelog,optionfilegnuplot,optionfilegnuplot,strstart); + fflush(fichtm); + + strcpy(pathr,path); + strcat(pathr,optionfilefiname); +#ifdef WIN32 + _chdir(optionfilefiname); /* Move to directory named optionfile */ +#else + chdir(optionfilefiname); /* Move to directory named optionfile */ +#endif + + /* Calculates basic frequencies. Computes observed prevalence at single age + and for any valid combination of covariates + and prints on file fileres'p'. */ + freqsummary(fileres, p, pstart, agemin, agemax, s, agev, nlstate, imx, Tvaraff, invalidvarcomb, nbcode, ncodemax,mint,anint,strstart, \ + firstpass, lastpass, stepm, weightopt, model); + + fprintf(fichtm,"\n"); + fprintf(fichtm,"
        Total number of observations=%d
        \n\ +Youngest age at first (selected) pass %.2f, oldest age %.2f
        \n\ +Interval (in months) between two waves: Min=%d Max=%d Mean=%.2lf
        \n",\ + imx,agemin,agemax,jmin,jmax,jmean); + pmmij= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */ + oldms= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */ + newms= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */ + savms= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */ + oldm=oldms; newm=newms; savm=savms; /* Keeps fixed addresses to free */ + + /* For Powell, parameters are in a vector p[] starting at p[1] + so we point p on param[1][1] so that p[1] maps on param[1][1][1] */ + p=param[1][1]; /* *(*(*(param +1)+1)+0) */ + + globpr=0; /* To get the number ipmx of contributions and the sum of weights*/ + /* For mortality only */ + if (mle==-3){ + ximort=matrix(1,NDIM,1,NDIM); + for(i=1;i<=NDIM;i++) + for(j=1;j<=NDIM;j++) + ximort[i][j]=0.; + /* ximort=gsl_matrix_alloc(1,NDIM,1,NDIM); */ + cens=ivector(1,n); + ageexmed=vector(1,n); + agecens=vector(1,n); + dcwave=ivector(1,n); + + for (i=1; i<=imx; i++){ + dcwave[i]=-1; + for (m=firstpass; m<=lastpass; m++) + if (s[m][i]>nlstate) { + dcwave[i]=m; + /* printf("i=%d j=%d s=%d dcwave=%d\n",i,j, s[j][i],dcwave[i]);*/ + break; + } + } + + for (i=1; i<=imx; i++) { + if (wav[i]>0){ + ageexmed[i]=agev[mw[1][i]][i]; + j=wav[i]; + agecens[i]=1.; + + if (ageexmed[i]> 1 && wav[i] > 0){ + agecens[i]=agev[mw[j][i]][i]; + cens[i]= 1; + }else if (ageexmed[i]< 1) + cens[i]= -1; + if (agedc[i]< AGESUP && agedc[i]>1 && dcwave[i]>firstpass && dcwave[i]<=lastpass) + cens[i]=0 ; + } + else cens[i]=-1; + } + + for (i=1;i<=NDIM;i++) { + for (j=1;j<=NDIM;j++) + ximort[i][j]=(i == j ? 1.0 : 0.0); + } + + /*p[1]=0.0268; p[NDIM]=0.083;*/ + /*printf("%lf %lf", p[1], p[2]);*/ + + +#ifdef GSL + printf("GSL optimization\n"); fprintf(ficlog,"Powell\n"); +#else + printf("Powell\n"); fprintf(ficlog,"Powell\n"); +#endif + strcpy(filerespow,"POW-MORT_"); + strcat(filerespow,fileresu); + if((ficrespow=fopen(filerespow,"w"))==NULL) { + printf("Problem with resultfile: %s\n", filerespow); + fprintf(ficlog,"Problem with resultfile: %s\n", filerespow); + } +#ifdef GSL + fprintf(ficrespow,"# GSL optimization\n# iter -2*LL"); +#else + fprintf(ficrespow,"# Powell\n# iter -2*LL"); +#endif + /* for (i=1;i<=nlstate;i++) + for(j=1;j<=nlstate+ndeath;j++) + if(j!=i)fprintf(ficrespow," p%1d%1d",i,j); + */ + fprintf(ficrespow,"\n"); +#ifdef GSL + /* gsl starts here */ + T = gsl_multimin_fminimizer_nmsimplex; + gsl_multimin_fminimizer *sfm = NULL; + gsl_vector *ss, *x; + gsl_multimin_function minex_func; + + /* Initial vertex size vector */ + ss = gsl_vector_alloc (NDIM); + + if (ss == NULL){ + GSL_ERROR_VAL ("failed to allocate space for ss", GSL_ENOMEM, 0); + } + /* Set all step sizes to 1 */ + gsl_vector_set_all (ss, 0.001); + + /* Starting point */ + + x = gsl_vector_alloc (NDIM); + + if (x == NULL){ + gsl_vector_free(ss); + GSL_ERROR_VAL ("failed to allocate space for x", GSL_ENOMEM, 0); + } - if(mle==1){ - /*-------- data file ----------*/ - if((ficres =fopen(fileres,"w"))==NULL) { - printf("Problem with resultfile: %s\n", fileres);goto end; + /* Initialize method and iterate */ + /* p[1]=0.0268; p[NDIM]=0.083; */ + /* gsl_vector_set(x, 0, 0.0268); */ + /* gsl_vector_set(x, 1, 0.083); */ + gsl_vector_set(x, 0, p[1]); + gsl_vector_set(x, 1, p[2]); + + minex_func.f = &gompertz_f; + minex_func.n = NDIM; + minex_func.params = (void *)&p; /* ??? */ + + sfm = gsl_multimin_fminimizer_alloc (T, NDIM); + gsl_multimin_fminimizer_set (sfm, &minex_func, x, ss); + + printf("Iterations beginning .....\n\n"); + printf("Iter. # Intercept Slope -Log Likelihood Simplex size\n"); + + iteri=0; + while (rval == GSL_CONTINUE){ + iteri++; + status = gsl_multimin_fminimizer_iterate(sfm); + + if (status) printf("error: %s\n", gsl_strerror (status)); + fflush(0); + + if (status) + break; + + rval = gsl_multimin_test_size (gsl_multimin_fminimizer_size (sfm), 1e-6); + ssval = gsl_multimin_fminimizer_size (sfm); + + if (rval == GSL_SUCCESS) + printf ("converged to a local maximum at\n"); + + printf("%5d ", iteri); + for (it = 0; it < NDIM; it++){ + printf ("%10.5f ", gsl_vector_get (sfm->x, it)); + } + printf("f() = %-10.5f ssize = %.7f\n", sfm->fval, ssval); } - fprintf(ficres,"#%s\n",version); - if((fic=fopen(datafile,"r"))==NULL) { - printf("Problem with datafile: %s\n", datafile);goto end; + printf("\n\n Please note: Program should be run many times with varying starting points to detemine global maximum\n\n"); + + gsl_vector_free(x); /* initial values */ + gsl_vector_free(ss); /* inital step size */ + for (it=0; itx,it); + fprintf(ficrespow," %.12lf", p[it]); } + gsl_multimin_fminimizer_free (sfm); /* p *(sfm.x.data) et p *(sfm.x.data+1) */ +#endif +#ifdef POWELL + powell(p,ximort,NDIM,ftol,&iter,&fret,gompertz); +#endif + fclose(ficrespow); - n= lastobs; - severity = vector(1,maxwav); - outcome=imatrix(1,maxwav+1,1,n); - num=ivector(1,n); - moisnais=vector(1,n); - annais=vector(1,n); - moisdc=vector(1,n); - andc=vector(1,n); - agedc=vector(1,n); - cod=ivector(1,n); - weight=vector(1,n); - for(i=1;i<=n;i++) weight[i]=1.0; /* Equal weights, 1 by default */ - mint=matrix(1,maxwav,1,n); - anint=matrix(1,maxwav,1,n); - covar=matrix(1,NCOVMAX,1,n); - s=imatrix(1,maxwav+1,1,n); - adl=imatrix(1,maxwav+1,1,n); - tab=ivector(1,NCOVMAX); - i=1; - while (fgets(line, MAXLINE, fic) != NULL) { - if ((i >= firstobs) && (i 0){ - if (s[m][i] == nlstate+1) { - if(agedc[i]>0) - agev[m][i]=agedc[i]; - else{ - printf("Warning negative age at death: %d line:%d\n",num[i],i); - agev[m][i]=-1; - } - } - else if(s[m][i] !=9){ /* Should no more exist */ - agev[m][i]=(mint[m][i]/12.+1./24.+anint[m][i])-(moisnais[i]/12.+1./24.+annais[i]); - if(mint[m][i]==99 || anint[m][i]==9999) - agev[m][i]=1; - else if(agev[m][i] agemax){ - agemax=agev[m][i]; - /* printf(" anint[%d][%d]=%.0f annais[%d]=%.0f, agemax=%.0f\n",m,i,anint[m][i], i,annais[i], agemax);*/ - } - /*agev[m][i]=anint[m][i]-annais[i];*/ - /* agev[m][i] = age[i]+2*m;*/ - } - else { /* =9 */ - agev[m][i]=1; - s[m][i]=-1; - } - } - else /*= 0 Unknown */ - agev[m][i]=1; + printf("\nCovariance matrix\n "); + fprintf(ficlog,"\nCovariance matrix\n "); + for(i=1; i <=NDIM; i++) { + for(j=1;j<=NDIM;j++){ + printf("%f ",matcov[i][j]); + fprintf(ficlog,"%f ",matcov[i][j]); } + printf("\n "); fprintf(ficlog,"\n "); + } + printf("iter=%d MLE=%f Eq=%lf*exp(%lf*(age-%d))\n",iter,-gompertz(p),p[1],p[2],agegomp); + for (i=1;i<=NDIM;i++) { + printf("%f [%f ; %f]\n",p[i],p[i]-2*sqrt(matcov[i][i]),p[i]+2*sqrt(matcov[i][i])); + fprintf(ficlog,"%f [%f ; %f]\n",p[i],p[i]-2*sqrt(matcov[i][i]),p[i]+2*sqrt(matcov[i][i])); } - for (i=1; i<=imx; i++) { - for(m=1; (m<= maxwav); m++){ - if (s[m][i] > (nlstate+ndeath)) { - printf("Error: Wrong value in nlstate or ndeath\n"); - goto end; - } - } + lsurv=vector(1,AGESUP); + lpop=vector(1,AGESUP); + tpop=vector(1,AGESUP); + lsurv[agegomp]=100000; + + for (k=agegomp;k<=AGESUP;k++) { + agemortsup=k; + if (p[1]*exp(p[2]*(k-agegomp))>1) break; } - -printf("Total number of individuals= %d, Agemin = %.2f, Agemax= %.2f\n\n", imx, agemin, agemax); - - free_vector(severity,1,maxwav); - free_imatrix(outcome,1,maxwav+1,1,n); - free_vector(moisnais,1,n); - free_vector(annais,1,n); - free_matrix(mint,1,maxwav,1,n); - free_matrix(anint,1,maxwav,1,n); - free_vector(moisdc,1,n); - free_vector(andc,1,n); - - - wav=ivector(1,imx); - dh=imatrix(1,lastpass-firstpass+1,1,imx); - mw=imatrix(1,lastpass-firstpass+1,1,imx); - - /* Concatenates waves */ - concatwav(wav, dh, mw, s, agedc, agev, firstpass, lastpass, imx, nlstate, stepm); - /* Calculates basic frequencies. Computes observed prevalence at single age - and prints on file fileres'p'. */ - freqsummary(fileres, agemin, agemax, s, agev, nlstate, imx); - - pmmij= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */ - oldms= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */ - newms= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */ - savms= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */ - oldm=oldms; newm=newms; savm=savms; /* Keeps fixed addresses to free */ - - /* For Powell, parameters are in a vector p[] starting at p[1] - so we point p on param[1][1] so that p[1] maps on param[1][1][1] */ - p=param[1][1]; /* *(*(*(param +1)+1)+0) */ + for (k=agegomp;k=1){ /* Could be 1 or 2, Real Maximization */ + /* mlikeli uses func not funcone */ + /* for(i=1;inlstate) k=1; - i1=(i-1)/(ncov*nlstate)+1; - fprintf(ficres,"%s%d%d",alph[k],i1,tab[i]); - printf("%s%d%d",alph[k],i1,tab[i]);*/ - fprintf(ficres,"%3d",i); - printf("%3d",i); - for(j=1; j<=i;j++){ - fprintf(ficres," %.5e",matcov[i][j]); - printf(" %.5e",matcov[i][j]); + 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"); + if(mle >= 1) /* To big for the screen */ + 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"); + 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"); + /* # 121 Var(a12)\n\ */ + /* # 122 Cov(b12,a12) Var(b12)\n\ */ + /* # 131 Cov(a13,a12) Cov(a13,b12, Var(a13)\n\ */ + /* # 132 Cov(b13,a12) Cov(b13,b12, Cov(b13,a13) Var(b13)\n\ */ + /* # 212 Cov(a21,a12) Cov(a21,b12, Cov(a21,a13) Cov(a21,b13) Var(a21)\n\ */ + /* # 212 Cov(b21,a12) Cov(b21,b12, Cov(b21,a13) Cov(b21,b13) Cov(b21,a21) Var(b21)\n\ */ + /* # 232 Cov(a23,a12) Cov(a23,b12, Cov(a23,a13) Cov(a23,b13) Cov(a23,a21) Cov(a23,b21) Var(a23)\n\ */ + /* # 232 Cov(b23,a12) Cov(b23,b12) ... Var (b23)\n" */ + + + /* Just to have a covariance matrix which will be more understandable + even is we still don't want to manage dictionary of variables + */ + for(itimes=1;itimes<=2;itimes++){ + jj=0; + for(i=1; i <=nlstate; i++){ + for(j=1; j <=nlstate+ndeath; j++){ + if(j==i) continue; + for(k=1; k<=ncovmodel;k++){ + jj++; + ca[0]= k+'a'-1;ca[1]='\0'; + if(itimes==1){ + if(mle>=1) + printf("#%1d%1d%d",i,j,k); + fprintf(ficlog,"#%1d%1d%d",i,j,k); + fprintf(ficres,"#%1d%1d%d",i,j,k); + }else{ + if(mle>=1) + printf("%1d%1d%d",i,j,k); + fprintf(ficlog,"%1d%1d%d",i,j,k); + fprintf(ficres,"%1d%1d%d",i,j,k); + } + ll=0; + for(li=1;li <=nlstate; li++){ + for(lj=1;lj <=nlstate+ndeath; lj++){ + if(lj==li) continue; + for(lk=1;lk<=ncovmodel;lk++){ + ll++; + if(ll<=jj){ + cb[0]= lk +'a'-1;cb[1]='\0'; + if(ll=1) + printf(" Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj); + fprintf(ficlog," Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj); + fprintf(ficres," Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj); + }else{ + if(mle>=1) + printf(" %.5e",matcov[jj][ll]); + fprintf(ficlog," %.5e",matcov[jj][ll]); + fprintf(ficres," %.5e",matcov[jj][ll]); + } + }else{ + if(itimes==1){ + if(mle>=1) + printf(" Var(%s%1d%1d)",ca,i,j); + fprintf(ficlog," Var(%s%1d%1d)",ca,i,j); + fprintf(ficres," Var(%s%1d%1d)",ca,i,j); + }else{ + if(mle>=1) + printf(" %.7e",matcov[jj][ll]); + fprintf(ficlog," %.7e",matcov[jj][ll]); + fprintf(ficres," %.7e",matcov[jj][ll]); + } + } + } + } /* end lk */ + } /* end lj */ + } /* end li */ + if(mle>=1) + printf("\n"); + fprintf(ficlog,"\n"); + fprintf(ficres,"\n"); + numlinepar++; + } /* end k*/ + } /*end j */ + } /* end i */ + } /* end itimes */ + + fflush(ficlog); + fflush(ficres); + while(fgets(line, MAXLINE, ficpar)) { + /* If line starts with a # it is a comment */ + if (line[0] == '#') { + numlinepar++; + fputs(line,stdout); + fputs(line,ficparo); + fputs(line,ficlog); + continue; + }else + break; + } + + /* while((c=getc(ficpar))=='#' && c!= EOF){ */ + /* ungetc(c,ficpar); */ + /* fgets(line, MAXLINE, ficpar); */ + /* fputs(line,stdout); */ + /* fputs(line,ficparo); */ + /* } */ + /* ungetc(c,ficpar); */ + + estepm=0; + 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){ + + if (num_filled != 6) { + 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); + 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); + goto end; } - fprintf(ficres,"\n"); - printf("\n"); - k++; + printf("agemin=%lf agemax=%lf bage=%lf fage=%lf estepm=%d ftolpl=%lf\n",ageminpar,agemaxpar, bage, fage, estepm, ftolpl); + } + /* ftolpl=6*ftol*1.e5; /\* 6.e-3 make convergences in less than 80 loops for the prevalence limit *\/ */ + /*ftolpl=6.e-4;*/ /* 6.e-3 make convergences in less than 80 loops for the prevalence limit */ + + /* fscanf(ficpar,"agemin=%lf agemax=%lf bage=%lf fage=%lf estepm=%d ftolpl=%\n",&ageminpar,&agemaxpar, &bage, &fage, &estepm); */ + if (estepm==0 || estepm < stepm) estepm=stepm; + if (fage <= 2) { + bage = ageminpar; + fage = agemaxpar; } + fprintf(ficres,"# agemin agemax for life expectancy, bage fage (if mle==0 ie no data nor Max likelihood).\n"); + fprintf(ficres,"agemin=%.0f agemax=%.0f bage=%.0f fage=%.0f estepm=%d ftolpl=%e\n",ageminpar,agemaxpar,bage,fage, estepm, ftolpl); + fprintf(ficparo,"agemin=%.0f agemax=%.0f bage=%.0f fage=%.0f estepm=%d, ftolpl=%e\n",ageminpar,agemaxpar,bage,fage, estepm, ftolpl); + + /* Other stuffs, more or less useful */ while((c=getc(ficpar))=='#' && c!= EOF){ ungetc(c,ficpar); fgets(line, MAXLINE, ficpar); - puts(line); + fputs(line,stdout); fputs(line,ficparo); } ungetc(c,ficpar); - - fscanf(ficpar,"agemin=%lf agemax=%lf bage=%lf fage=%lf\n",&agemin,&agemax, &bage, &fage); - if (fage <= 2) { - bage = agemin; - fage = agemax; + fscanf(ficpar,"begin-prev-date=%lf/%lf/%lf end-prev-date=%lf/%lf/%lf mov_average=%d\n",&jprev1, &mprev1,&anprev1,&jprev2, &mprev2,&anprev2,&mobilav); + 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); + 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); + printf("begin-prev-date=%.lf/%.lf/%.lf end-prev-date=%.lf/%.lf/%.lf mov_average=%d\n",jprev1, mprev1,anprev1,jprev2, mprev2,anprev2,mobilav); + 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); + + while((c=getc(ficpar))=='#' && c!= EOF){ + ungetc(c,ficpar); + fgets(line, MAXLINE, ficpar); + fputs(line,stdout); + fputs(line,ficparo); } - - fprintf(ficres,"# agemin agemax for life expectancy, bage fage (if mle==0 ie no data nor Max likelihood).\n"); - fprintf(ficres,"agemin=%.0f agemax=%.0f bage=%.0f fage=%.0f\n",agemin,agemax,bage,fage); -/*------------ gnuplot -------------*/ -chdir(pathcd); - if((ficgp=fopen("graph.gp","w"))==NULL) { - printf("Problem with file graph.gp");goto end; - } -#ifdef windows - fprintf(ficgp,"cd \"%s\" \n",pathc); -#endif - /* 1eme*/ - - for (cpt=1; cpt<= nlstate ; cpt ++) { -#ifdef windows - fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability\" \nset ter gif small size 400,300\nplot [%.f:%.f] \"vpl%s\" u 1:%d \"\%%lf",agemin,fage,fileres,cpt*2); -#endif -#ifdef unix -fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability\" \nplot [%.f:%.f] \"vpl%s\" u 1:%d \"\%%lf",agemin,fage,fileres,cpt*2); -#endif - for (i=1; i<= nlstate ; i ++) fprintf(ficgp," \%%lf (\%%lf)"); - fprintf(ficgp,"\" t\"Stationary prevalence\" w l 0,\"vpl%s\" u 1:($%d+2*$%d) \"\%%lf",fileres,2*cpt,cpt*2+1); - for (i=1; i<= nlstate ; i ++) fprintf(ficgp," \%%lf (\%%lf)"); - fprintf(ficgp,"\" t\"95\%% CI\" w l 1,\"vpl%s\" u 1:($%d-2*$%d) \"\%%lf",fileres,2*cpt,2*cpt+1); - for (i=1; i<= nlstate ; i ++) fprintf(ficgp," \%%lf (\%%lf)"); - fprintf(ficgp,"\" t\"\" w l 1,\"p%s\" u 1:($%d) t\"Observed prevalence \" w l 2",fileres,2+4*(cpt-1)); -#ifdef unix -fprintf(ficgp,"\nset ter gif small size 400,300"); -#endif -fprintf(ficgp,"\nset out \"v%s%d.gif\" \nreplot\n\n",strtok(optionfile, "."),cpt); - - } - /*2 eme*/ - - fprintf(ficgp,"set ylabel \"Years\" \nset ter gif small size 400,300\nplot [%.f:%.f] ",agemin,fage); - for (i=1; i<= nlstate+1 ; i ++) { -k=2*i; - fprintf(ficgp,"\"t%s\" u 1:%d \"\%%lf \%%lf (\%%lf) \%%lf (\%%lf)",fileres,k); - for (j=1; j< nlstate ; j ++) fprintf(ficgp," \%%lf (\%%lf)"); - if (i== 1) fprintf(ficgp,"\" t\"TLE\" w l ,"); - else fprintf(ficgp,"\" t\"LE in state (%d)\" w l ,",i-1); - fprintf(ficgp,"\"t%s\" u 1:($%d-2*$%d) \"\%%lf \%%lf (\%%lf) \%%lf (\%%lf)",fileres,k,k+1); - for (j=1; j< nlstate ; j ++) fprintf(ficgp," \%%lf (\%%lf)"); - fprintf(ficgp,"\" t\"\" w l 0,"); -fprintf(ficgp,"\"t%s\" u 1:($%d+2*$%d) \"\%%lf \%%lf (\%%lf) \%%lf (\%%lf)",fileres,k,k+1); - for (j=1; j< nlstate ; j ++) fprintf(ficgp," \%%lf (\%%lf)"); - if (i== (nlstate+1)) fprintf(ficgp,"\" t\"\" w l 0"); -else fprintf(ficgp,"\" t\"\" w l 0,"); - } - fprintf(ficgp,"\nset out \"e%s.gif\" \nreplot\n\n",strtok(optionfile, ".")); - - /*3eme*/ -for (cpt=1; cpt<= nlstate ; cpt ++) { - k=2+nlstate*(cpt-1); - fprintf(ficgp,"set ter gif small size 400,300\nplot [%.f:%.f] \"e%s\" u 1:%d t \"e%d1\" w l",agemin,fage,fileres,k,cpt); -for (i=1; i< nlstate ; i ++) { -fprintf(ficgp,",\"e%s\" u 1:%d t \"e%d%d\" w l",fileres,k+1,cpt,i+1); -} -fprintf(ficgp,"\nset out \"ex%s%d.gif\" \nreplot\n\n",strtok(optionfile, "."),cpt); -} - -/* CV preval stat */ -for (cpt=1; cpt MAXRESULTLINES){ + printf("ERROR: Current version of IMaCh limits the number of resultlines to %d, you used %d\n",MAXRESULTLINES,nresult); + fprintf(ficlog,"ERROR: Current version of IMaCh limits the number of resultlines to %d, you used %d\n",MAXRESULTLINES,nresult); + goto end; + } + decoderesult(resultline, nresult); /* Fills TKresult[nresult] combination and Tresult[nresult][k4+1] combination values */ + fprintf(ficparo,"result: %s\n",resultline); + fprintf(ficres,"result: %s\n",resultline); + fprintf(ficlog,"result: %s\n",resultline); + while(fgets(line, MAXLINE, ficpar)) { + /* If line starts with a # it is a comment */ + if (line[0] == '#') { + numlinepar++; + fputs(line,stdout); + fputs(line,ficparo); + fputs(line,ficres); + fputs(line,ficlog); + continue; + }else + break; + } + if (feof(ficpar)) + break; + else{ /* Processess output results for this combination of covariate values */ + } + } /* end while */ - fclose(ficgp); - -chdir(path); - free_matrix(agev,1,maxwav,1,imx); - free_ivector(wav,1,imx); - free_imatrix(dh,1,lastpass-firstpass+1,1,imx); - free_imatrix(mw,1,lastpass-firstpass+1,1,imx); - - free_imatrix(s,1,maxwav+1,1,n); + /* freqsummary(fileres, agemin, agemax, s, agev, nlstate, imx,Tvaraff,nbcode, ncodemax,mint,anint); */ + /* ,dateprev1,dateprev2,jprev1, mprev1,anprev1,jprev2, mprev2,anprev2); */ - free_ivector(num,1,n); + replace_back_to_slash(pathc,pathcd); /* Even gnuplot wants a / */ + if(ageminpar == AGEOVERFLOW ||agemaxpar == -AGEOVERFLOW){ + printf("Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\ +This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\ +Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar); + fprintf(ficlog,"Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\ +This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\ +Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar); + }else{ + printinggnuplot(fileresu, optionfilefiname,ageminpar,agemaxpar,fage, prevfcast, backcast, pathc,p); + } + printinghtml(fileresu,title,datafile, firstpass, lastpass, stepm, weightopt, \ + model,imx,jmin,jmax,jmean,rfileres,popforecast,prevfcast,backcast, estepm, \ + jprev1,mprev1,anprev1,dateprev1,jprev2,mprev2,anprev2,dateprev2); + + /*------------ free_vector -------------*/ + /* chdir(path); */ + + /* free_ivector(wav,1,imx); */ /* Moved after last prevalence call */ + /* free_imatrix(dh,1,lastpass-firstpass+2,1,imx); */ + /* free_imatrix(bh,1,lastpass-firstpass+2,1,imx); */ + /* free_imatrix(mw,1,lastpass-firstpass+2,1,imx); */ + free_lvector(num,1,n); free_vector(agedc,1,n); - free_vector(weight,1,n); - free_matrix(covar,1,NCOVMAX,1,n); + /*free_matrix(covar,0,NCOVMAX,1,n);*/ + /*free_matrix(covar,1,NCOVMAX,1,n);*/ fclose(ficparo); fclose(ficres); - } + + + /* Other results (useful)*/ + + + /*--------------- Prevalence limit (period or stable prevalence) --------------*/ + /*#include "prevlim.h"*/ /* Use ficrespl, ficlog */ + prlim=matrix(1,nlstate,1,nlstate); + prevalence_limit(p, prlim, ageminpar, agemaxpar, ftolpl, &ncvyear); + fclose(ficrespl); + + /*------------- h Pij x at various ages ------------*/ + /*#include "hpijx.h"*/ + hPijx(p, bage, fage); + fclose(ficrespij); + + /* ncovcombmax= pow(2,cptcoveff); */ + /*-------------- Variance of one-step probabilities---*/ + k=1; + varprob(optionfilefiname, matcov, p, delti, nlstate, bage, fage,k,Tvar,nbcode, ncodemax,strstart); + + /* Prevalence for each covariates in probs[age][status][cov] */ + probs= ma3x(1,AGESUP,1,nlstate+ndeath, 1,ncovcombmax); + for(i=1;i<=AGESUP;i++) + for(j=1;j<=nlstate+ndeath;j++) /* ndeath is useless but a necessity to be compared with mobaverages */ + for(k=1;k<=ncovcombmax;k++) + probs[i][j][k]=0.; + prevalence(probs, ageminpar, agemaxpar, s, agev, nlstate, imx, Tvar, nbcode, ncodemax, mint, anint, dateprev1, dateprev2, firstpass, lastpass); + if (mobilav!=0 ||mobilavproj !=0 ) { + mobaverages= ma3x(1, AGESUP,1,nlstate+ndeath, 1,ncovcombmax); + for(i=1;i<=AGESUP;i++) + for(j=1;j<=nlstate;j++) + for(k=1;k<=ncovcombmax;k++) + mobaverages[i][j][k]=0.; + mobaverage=mobaverages; + if (mobilav!=0) { + printf("Movingaveraging observed prevalence\n"); + if (movingaverage(probs, ageminpar, agemaxpar, mobaverage, mobilav)!=0){ + fprintf(ficlog," Error in movingaverage mobilav=%d\n",mobilav); + printf(" Error in movingaverage mobilav=%d\n",mobilav); + } + } + /* /\* Prevalence for each covariates in probs[age][status][cov] *\/ */ + /* prevalence(probs, ageminpar, agemaxpar, s, agev, nlstate, imx, Tvar, nbcode, ncodemax, mint, anint, dateprev1, dateprev2, firstpass, lastpass); */ + else if (mobilavproj !=0) { + printf("Movingaveraging projected observed prevalence\n"); + if (movingaverage(probs, ageminpar, agemaxpar, mobaverage, mobilavproj)!=0){ + fprintf(ficlog," Error in movingaverage mobilavproj=%d\n",mobilavproj); + printf(" Error in movingaverage mobilavproj=%d\n",mobilavproj); + } + } + }/* end if moving average */ + + /*---------- Forecasting ------------------*/ + /*if((stepm == 1) && (strcmp(model,".")==0)){*/ + if(prevfcast==1){ + /* if(stepm ==1){*/ + prevforecast(fileresu, anproj1, mproj1, jproj1, agemin, agemax, dateprev1, dateprev2, mobilavproj, bage, fage, firstpass, lastpass, anproj2, p, cptcoveff); + } + if(backcast==1){ + ddnewms=matrix(1,nlstate+ndeath,1,nlstate+ndeath); + ddoldms=matrix(1,nlstate+ndeath,1,nlstate+ndeath); + ddsavms=matrix(1,nlstate+ndeath,1,nlstate+ndeath); + + /*--------------- Back Prevalence limit (period or stable prevalence) --------------*/ + + bprlim=matrix(1,nlstate,1,nlstate); + back_prevalence_limit(p, bprlim, ageminpar, agemaxpar, ftolpl, &ncvyear, dateprev1, dateprev2, firstpass, lastpass, mobilavproj); + fclose(ficresplb); + + hBijx(p, bage, fage, mobaverage); + fclose(ficrespijb); + free_matrix(bprlim,1,nlstate,1,nlstate); /*here or after loop ? */ + + /* prevbackforecast(fileresu, anback1, mback1, jback1, agemin, agemax, dateprev1, dateprev2, mobilavproj, + bage, fage, firstpass, lastpass, anback2, p, cptcoveff); */ + free_matrix(ddnewms, 1, nlstate+ndeath, 1, nlstate+ndeath); + free_matrix(ddsavms, 1, nlstate+ndeath, 1, nlstate+ndeath); + free_matrix(ddoldms, 1, nlstate+ndeath, 1, nlstate+ndeath); + } + + + /* ------ Other prevalence ratios------------ */ - /*________fin mle=1_________*/ - - + free_ivector(wav,1,imx); + free_imatrix(dh,1,lastpass-firstpass+2,1,imx); + free_imatrix(bh,1,lastpass-firstpass+2,1,imx); + free_imatrix(mw,1,lastpass-firstpass+2,1,imx); + + + /*---------- Health expectancies, no variances ------------*/ + + strcpy(filerese,"E_"); + strcat(filerese,fileresu); + if((ficreseij=fopen(filerese,"w"))==NULL) { + printf("Problem with Health Exp. resultfile: %s\n", filerese); exit(0); + fprintf(ficlog,"Problem with Health Exp. resultfile: %s\n", filerese); exit(0); + } + printf("Computing Health Expectancies: result on file '%s' ...", filerese);fflush(stdout); + fprintf(ficlog,"Computing Health Expectancies: result on file '%s' ...", filerese);fflush(ficlog); - /* No more information from the sample is required now */ - /* Reads comments: lines beginning with '#' */ - while((c=getc(ficpar))=='#' && c!= EOF){ - ungetc(c,ficpar); - fgets(line, MAXLINE, ficpar); - puts(line); - fputs(line,ficparo); - } - ungetc(c,ficpar); - - fscanf(ficpar,"agemin=%lf agemax=%lf bage=%lf fage=%lf\n",&agemin,&agemax, &bage, &fage); - printf("agemin=%.0f agemax=%.0f bage=%.0f fage=%.0f\n",agemin,agemax, bage, fage); - fprintf(ficparo,"agemin=%.0f agemax=%.0f bage=%.0f fage=%.0f\n",agemin,agemax,bage,fage); + pstamp(ficreseij); + + i1=pow(2,cptcoveff); /* Number of combination of dummy covariates */ + if (cptcovn < 1){i1=1;} + + for(nres=1; nres <= nresult; nres++) /* For each resultline */ + for(k=1; k<=i1;k++){ /* For any combination of dummy covariates, fixed and varying */ + if(i1 != 1 && TKresult[nres]!= k) + continue; + fprintf(ficreseij,"\n#****** "); + printf("\n#****** "); + for(j=1;j<=cptcoveff;j++) { + fprintf(ficreseij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]); + printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]); + } + for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */ + printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]); + fprintf(ficreseij," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]); + } + fprintf(ficreseij,"******\n"); + printf("******\n"); + + eij=ma3x(1,nlstate,1,nlstate,(int) bage, (int) fage); + oldm=oldms;savm=savms; + evsij(eij, p, nlstate, stepm, (int) bage, (int)fage, oldm, savm, k, estepm, strstart, nres); + + free_ma3x(eij,1,nlstate,1,nlstate,(int) bage, (int)fage); + } + fclose(ficreseij); + printf("done evsij\n");fflush(stdout); + fprintf(ficlog,"done evsij\n");fflush(ficlog); + + /*---------- State-specific expectancies and variances ------------*/ + + + strcpy(filerest,"T_"); + strcat(filerest,fileresu); + if((ficrest=fopen(filerest,"w"))==NULL) { + printf("Problem with total LE resultfile: %s\n", filerest);goto end; + fprintf(ficlog,"Problem with total LE resultfile: %s\n", filerest);goto end; + } + printf("Computing Total Life expectancies with their standard errors: file '%s' ...\n", filerest); fflush(stdout); + fprintf(ficlog,"Computing Total Life expectancies with their standard errors: file '%s' ...\n", filerest); fflush(ficlog); + + + strcpy(fileresstde,"STDE_"); + strcat(fileresstde,fileresu); + if((ficresstdeij=fopen(fileresstde,"w"))==NULL) { + printf("Problem with State specific Exp. and std errors resultfile: %s\n", fileresstde); exit(0); + fprintf(ficlog,"Problem with State specific Exp. and std errors resultfile: %s\n", fileresstde); exit(0); + } + printf(" Computing State-specific Expectancies and standard errors: result on file '%s' \n", fileresstde); + fprintf(ficlog," Computing State-specific Expectancies and standard errors: result on file '%s' \n", fileresstde); - /*--------------- Prevalence limit --------------*/ - - strcpy(filerespl,"pl"); - strcat(filerespl,fileres); - if((ficrespl=fopen(filerespl,"w"))==NULL) { - printf("Problem with Prev limit resultfile: %s\n", filerespl);goto end; - } - printf("Computing prevalence limit: result on file '%s' \n", filerespl); - fprintf(ficrespl,"#Prevalence limit\n"); - fprintf(ficrespl,"#Age "); - for(i=1; i<=nlstate;i++) fprintf(ficrespl,"%d-%d ",i,i); - fprintf(ficrespl,"\n"); - - prlim=matrix(1,nlstate,1,nlstate); - pmmij= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */ - oldms= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */ - newms= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */ - savms= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */ - oldm=oldms; newm=newms; savm=savms; /* Keeps fixed addresses to free */ - - agebase=agemin; - agelim=agemax; - ftolpl=1.e-10; - for (age=agebase; age<=agelim; age++){ - prevalim(prlim, nlstate, p, age, oldm, savm,ftolpl); - fprintf(ficrespl,"%.0f",age ); - for(i=1; i<=nlstate;i++) - fprintf(ficrespl," %.5f", prlim[i][i]); - fprintf(ficrespl,"\n"); - } - fclose(ficrespl); - - /*------------- h Pij x at various ages ------------*/ - - strcpy(filerespij,"pij"); strcat(filerespij,fileres); - if((ficrespij=fopen(filerespij,"w"))==NULL) { - printf("Problem with Pij resultfile: %s\n", filerespij);goto end; - } - printf("Computing pij: result on file '%s' \n", filerespij); - stepsize=(int) (stepm+YEARM-1)/YEARM; - if (stepm<=24) stepsize=2; + strcpy(filerescve,"CVE_"); + strcat(filerescve,fileresu); + if((ficrescveij=fopen(filerescve,"w"))==NULL) { + printf("Problem with Covar. State-specific Exp. resultfile: %s\n", filerescve); exit(0); + fprintf(ficlog,"Problem with Covar. State-specific Exp. resultfile: %s\n", filerescve); exit(0); + } + printf(" Computing Covar. of State-specific Expectancies: result on file '%s' \n", filerescve); + fprintf(ficlog," Computing Covar. of State-specific Expectancies: result on file '%s' \n", filerescve); - agelim=AGESUP; - hstepm=stepsize*YEARM; /* Every year of age */ - hstepm=hstepm/stepm; /* Typically 2 years, = 2/6 months = 4 */ - for (agedeb=fage; agedeb>=bage; agedeb--){ /* If stepm=6 months */ - nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */ - nhstepm = nhstepm/hstepm; /* Typically 40/4=10 */ - p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); - oldm=oldms;savm=savms; - hpxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm); - fprintf(ficrespij,"# Age"); - for(i=1; i<=nlstate;i++) - for(j=1; j<=nlstate+ndeath;j++) - fprintf(ficrespij," %1d-%1d",i,j); - fprintf(ficrespij,"\n"); - for (h=0; h<=nhstepm; h++){ - fprintf(ficrespij,"%.0f %.0f",agedeb, agedeb+ h*hstepm/YEARM*stepm ); - for(i=1; i<=nlstate;i++) - for(j=1; j<=nlstate+ndeath;j++) - fprintf(ficrespij," %.5f", p3mat[i][j][h]); - fprintf(ficrespij,"\n"); + strcpy(fileresv,"V_"); + strcat(fileresv,fileresu); + if((ficresvij=fopen(fileresv,"w"))==NULL) { + printf("Problem with variance resultfile: %s\n", fileresv);exit(0); + fprintf(ficlog,"Problem with variance resultfile: %s\n", fileresv);exit(0); } - free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); - fprintf(ficrespij,"\n"); - } - fclose(ficrespij); + printf(" Computing Variance-covariance of State-specific Expectancies: file '%s' ... ", fileresv);fflush(stdout); + fprintf(ficlog," Computing Variance-covariance of State-specific Expectancies: file '%s' ... ", fileresv);fflush(ficlog); - /*---------- Health expectancies and variances ------------*/ - - eij=ma3x(1,nlstate,1,nlstate,(int) bage, (int) fage); - oldm=oldms;savm=savms; - evsij(fileres, eij, p, nlstate, stepm, (int) bage, (int)fage, oldm, savm); - - vareij=ma3x(1,nlstate,1,nlstate,(int) bage, (int) fage); - oldm=oldms;savm=savms; - varevsij(fileres, vareij, matcov, p, delti, nlstate, stepm, (int) bage, (int) fage, oldm, savm, prlim, ftolpl); + /*for(cptcov=1,k=0;cptcov<=i1;cptcov++){ + for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){*/ + + i1=pow(2,cptcoveff); /* Number of combination of dummy covariates */ + if (cptcovn < 1){i1=1;} + + for(nres=1; nres <= nresult; nres++) /* For each resultline */ + for(k=1; k<=i1;k++){ /* For any combination of dummy covariates, fixed and varying */ + if(i1 != 1 && TKresult[nres]!= k) + continue; + printf("\n#****** Result for:"); + fprintf(ficrest,"\n#****** Result for:"); + fprintf(ficlog,"\n#****** Result for:"); + for(j=1;j<=cptcoveff;j++){ + printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]); + fprintf(ficrest,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]); + fprintf(ficlog,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]); + } + for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */ + printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]); + fprintf(ficrest," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]); + fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]); + } + fprintf(ficrest,"******\n"); + fprintf(ficlog,"******\n"); + printf("******\n"); + + fprintf(ficresstdeij,"\n#****** "); + fprintf(ficrescveij,"\n#****** "); + for(j=1;j<=cptcoveff;j++) { + fprintf(ficresstdeij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]); + fprintf(ficrescveij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]); + } + for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */ + fprintf(ficresstdeij," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]); + fprintf(ficrescveij," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]); + } + fprintf(ficresstdeij,"******\n"); + fprintf(ficrescveij,"******\n"); + + fprintf(ficresvij,"\n#****** "); + /* pstamp(ficresvij); */ + for(j=1;j<=cptcoveff;j++) + fprintf(ficresvij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]); + for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */ + fprintf(ficresvij," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]); + } + fprintf(ficresvij,"******\n"); + + eij=ma3x(1,nlstate,1,nlstate,(int) bage, (int) fage); + oldm=oldms;savm=savms; + printf(" cvevsij "); + fprintf(ficlog, " cvevsij "); + cvevsij(eij, p, nlstate, stepm, (int) bage, (int)fage, oldm, savm, k, estepm, delti, matcov, strstart, nres); + printf(" end cvevsij \n "); + fprintf(ficlog, " end cvevsij \n "); + + /* + */ + /* goto endfree; */ + + vareij=ma3x(1,nlstate,1,nlstate,(int) bage, (int) fage); + pstamp(ficrest); + + + for(vpopbased=0; vpopbased <= popbased; vpopbased++){ /* Done for vpopbased=0 and vpopbased=1 if popbased==1*/ + oldm=oldms;savm=savms; /* ZZ Segmentation fault */ + cptcod= 0; /* To be deleted */ + printf("varevsij vpopbased=%d \n",vpopbased); + fprintf(ficlog, "varevsij vpopbased=%d \n",vpopbased); + 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 */ + 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 "); + if(vpopbased==1) + 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); + else + fprintf(ficrest,"the age specific period (stable) prevalences in each health state \n"); + fprintf(ficrest,"# Age popbased mobilav e.. (std) "); + for (i=1;i<=nlstate;i++) fprintf(ficrest,"e.%d (std) ",i); + fprintf(ficrest,"\n"); + /* printf("Which p?\n"); for(i=1;i<=npar;i++)printf("p[i=%d]=%lf,",i,p[i]);printf("\n"); */ + epj=vector(1,nlstate+1); + printf("Computing age specific period (stable) prevalences in each health state \n"); + fprintf(ficlog,"Computing age specific period (stable) prevalences in each health state \n"); + for(age=bage; age <=fage ;age++){ + prevalim(prlim, nlstate, p, age, oldm, savm, ftolpl, &ncvyear, k, nres); /*ZZ Is it the correct prevalim */ + if (vpopbased==1) { + if(mobilav ==0){ + for(i=1; i<=nlstate;i++) + prlim[i][i]=probs[(int)age][i][k]; + }else{ /* mobilav */ + for(i=1; i<=nlstate;i++) + prlim[i][i]=mobaverage[(int)age][i][k]; + } + } + + fprintf(ficrest," %4.0f %d %d",age, vpopbased, mobilav); + /* fprintf(ficrest," %4.0f %d %d %d %d",age, vpopbased, mobilav,Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]); */ /* to be done */ + /* printf(" age %4.0f ",age); */ + for(j=1, epj[nlstate+1]=0.;j <=nlstate;j++){ + for(i=1, epj[j]=0.;i <=nlstate;i++) { + epj[j] += prlim[i][i]*eij[i][j][(int)age]; + /*ZZZ printf("%lf %lf ", prlim[i][i] ,eij[i][j][(int)age]);*/ + /* printf("%lf %lf ", prlim[i][i] ,eij[i][j][(int)age]); */ + } + epj[nlstate+1] +=epj[j]; + } + /* printf(" age %4.0f \n",age); */ + + for(i=1, vepp=0.;i <=nlstate;i++) + for(j=1;j <=nlstate;j++) + vepp += vareij[i][j][(int)age]; + fprintf(ficrest," %7.3f (%7.3f)", epj[nlstate+1],sqrt(vepp)); + for(j=1;j <=nlstate;j++){ + fprintf(ficrest," %7.3f (%7.3f)", epj[j],sqrt(vareij[j][j][(int)age])); + } + fprintf(ficrest,"\n"); + } + } /* End vpopbased */ + free_ma3x(eij,1,nlstate,1,nlstate,(int) bage, (int)fage); + free_ma3x(vareij,1,nlstate,1,nlstate,(int) bage, (int)fage); + free_vector(epj,1,nlstate+1); + printf("done selection\n");fflush(stdout); + fprintf(ficlog,"done selection\n");fflush(ficlog); + + /*}*/ + } /* End k selection */ - strcpy(filerest,"t"); - strcat(filerest,fileres); - if((ficrest=fopen(filerest,"w"))==NULL) { - printf("Problem with total LE resultfile: %s\n", filerest);goto end; - } - printf("Computing Total LEs with variances: file '%s' \n", filerest); - fprintf(ficrest,"#Total LEs with variances: e.. (std) "); - for (i=1;i<=nlstate;i++) fprintf(ficrest,"e.%d (std) ",i); - fprintf(ficrest,"\n"); - - hf=1; - if (stepm >= YEARM) hf=stepm/YEARM; - epj=vector(1,nlstate+1); - for(age=bage; age <=fage ;age++){ - prevalim(prlim, nlstate, p, age, oldm, savm,ftolpl); - fprintf(ficrest," %.0f",age); - for(j=1, epj[nlstate+1]=0.;j <=nlstate;j++){ - for(i=1, epj[j]=0.;i <=nlstate;i++) { - epj[j] += prlim[i][i]*hf*eij[i][j][(int)age]; - } - epj[nlstate+1] +=epj[j]; - } - for(i=1, vepp=0.;i <=nlstate;i++) - for(j=1;j <=nlstate;j++) - vepp += vareij[i][j][(int)age]; - fprintf(ficrest," %.2f (%.2f)", epj[nlstate+1],hf*sqrt(vepp)); - for(j=1;j <=nlstate;j++){ - fprintf(ficrest," %.2f (%.2f)", epj[j],hf*sqrt(vareij[j][j][(int)age])); - } - fprintf(ficrest,"\n"); - } - fclose(ficrest); - fclose(ficpar); - free_vector(epj,1,nlstate+1); + printf("done State-specific expectancies\n");fflush(stdout); + fprintf(ficlog,"done State-specific expectancies\n");fflush(ficlog); - /*------- Variance limit prevalence------*/ + /*------- Variance of period (stable) prevalence------*/ + + strcpy(fileresvpl,"VPL_"); + strcat(fileresvpl,fileresu); + if((ficresvpl=fopen(fileresvpl,"w"))==NULL) { + printf("Problem with variance of period (stable) prevalence resultfile: %s\n", fileresvpl); + exit(0); + } + printf("Computing Variance-covariance of period (stable) prevalence: file '%s' ...", fileresvpl);fflush(stdout); + fprintf(ficlog, "Computing Variance-covariance of period (stable) prevalence: file '%s' ...", fileresvpl);fflush(ficlog); + + /*for(cptcov=1,k=0;cptcov<=i1;cptcov++){ + for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){*/ + + i1=pow(2,cptcoveff); + if (cptcovn < 1){i1=1;} - varpl=matrix(1,nlstate,(int) bage, (int) fage); - oldm=oldms;savm=savms; - varprevlim(fileres, varpl, matcov, p, delti, nlstate, stepm, (int) bage, (int) fage, oldm, savm, prlim, ftolpl); - - - free_matrix(varpl,1,nlstate,(int) bage, (int)fage); - - free_ma3x(vareij,1,nlstate,1,nlstate,(int) bage, (int)fage); - free_ma3x(eij,1,nlstate,1,nlstate,(int) bage, (int)fage); - - - free_matrix(pmmij,1,nlstate+ndeath,1,nlstate+ndeath); + for(nres=1; nres <= nresult; nres++) /* For each resultline */ + for(k=1; k<=i1;k++){ + if(i1 != 1 && TKresult[nres]!= k) + continue; + fprintf(ficresvpl,"\n#****** "); + printf("\n#****** "); + fprintf(ficlog,"\n#****** "); + for(j=1;j<=cptcoveff;j++) { + fprintf(ficresvpl,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]); + fprintf(ficlog,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]); + printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]); + } + for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */ + printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]); + fprintf(ficresvpl," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]); + fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]); + } + fprintf(ficresvpl,"******\n"); + printf("******\n"); + fprintf(ficlog,"******\n"); + + varpl=matrix(1,nlstate,(int) bage, (int) fage); + oldm=oldms;savm=savms; + varprevlim(fileres, varpl, matcov, p, delti, nlstate, stepm, (int) bage, (int) fage, oldm, savm, prlim, ftolpl, &ncvyear, k, strstart, nres); + free_matrix(varpl,1,nlstate,(int) bage, (int)fage); + /*}*/ + } + + fclose(ficresvpl); + printf("done variance-covariance of period prevalence\n");fflush(stdout); + fprintf(ficlog,"done variance-covariance of period prevalence\n");fflush(ficlog); + + free_vector(weight,1,n); + free_imatrix(Tvard,1,NCOVMAX,1,2); + free_imatrix(s,1,maxwav+1,1,n); + free_matrix(anint,1,maxwav,1,n); + free_matrix(mint,1,maxwav,1,n); + free_ivector(cod,1,n); + free_ivector(tab,1,NCOVMAX); + fclose(ficresstdeij); + fclose(ficrescveij); + fclose(ficresvij); + fclose(ficrest); + fclose(ficpar); + + + /*---------- End : free ----------------*/ + if (mobilav!=0 ||mobilavproj !=0) + free_ma3x(mobaverages,1, AGESUP,1,nlstate+ndeath, 1,ncovcombmax); /* We need to have a squared matrix with prevalence of the dead! */ + free_ma3x(probs,1,AGESUP,1,nlstate+ndeath, 1,ncovcombmax); + free_matrix(prlim,1,nlstate,1,nlstate); /*here or after loop ? */ + free_matrix(pmmij,1,nlstate+ndeath,1,nlstate+ndeath); + } /* mle==-3 arrives here for freeing */ + /* endfree:*/ free_matrix(oldms, 1,nlstate+ndeath,1,nlstate+ndeath); free_matrix(newms, 1,nlstate+ndeath,1,nlstate+ndeath); free_matrix(savms, 1,nlstate+ndeath,1,nlstate+ndeath); - + free_ma3x(cotqvar,1,maxwav,1,nqtv,1,n); + free_ma3x(cotvar,1,maxwav,1,ntv+nqtv,1,n); + free_matrix(coqvar,1,maxwav,1,n); + free_matrix(covar,0,NCOVMAX,1,n); free_matrix(matcov,1,npar,1,npar); - free_vector(delti,1,npar); - - free_ma3x(param,1,nlstate,1, nlstate+ndeath-1,1,ncov); - - printf("End of Imach\n"); + free_matrix(hess,1,npar,1,npar); + /*free_vector(delti,1,npar);*/ + free_ma3x(delti3,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel); + free_matrix(agev,1,maxwav,1,imx); + free_ma3x(param,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel); + + free_ivector(ncodemax,1,NCOVMAX); + free_ivector(ncodemaxwundef,1,NCOVMAX); + free_ivector(Dummy,-1,NCOVMAX); + free_ivector(Fixed,-1,NCOVMAX); + free_ivector(DummyV,1,NCOVMAX); + free_ivector(FixedV,1,NCOVMAX); + free_ivector(Typevar,-1,NCOVMAX); + free_ivector(Tvar,1,NCOVMAX); + free_ivector(TvarsQ,1,NCOVMAX); + free_ivector(TvarsQind,1,NCOVMAX); + free_ivector(TvarsD,1,NCOVMAX); + free_ivector(TvarsDind,1,NCOVMAX); + free_ivector(TvarFD,1,NCOVMAX); + free_ivector(TvarFDind,1,NCOVMAX); + free_ivector(TvarF,1,NCOVMAX); + free_ivector(TvarFind,1,NCOVMAX); + free_ivector(TvarV,1,NCOVMAX); + free_ivector(TvarVind,1,NCOVMAX); + free_ivector(TvarA,1,NCOVMAX); + free_ivector(TvarAind,1,NCOVMAX); + free_ivector(TvarFQ,1,NCOVMAX); + free_ivector(TvarFQind,1,NCOVMAX); + free_ivector(TvarVD,1,NCOVMAX); + free_ivector(TvarVDind,1,NCOVMAX); + free_ivector(TvarVQ,1,NCOVMAX); + free_ivector(TvarVQind,1,NCOVMAX); + free_ivector(Tvarsel,1,NCOVMAX); + free_vector(Tvalsel,1,NCOVMAX); + free_ivector(Tposprod,1,NCOVMAX); + free_ivector(Tprod,1,NCOVMAX); + free_ivector(Tvaraff,1,NCOVMAX); + free_ivector(invalidvarcomb,1,ncovcombmax); + free_ivector(Tage,1,NCOVMAX); + free_ivector(Tmodelind,1,NCOVMAX); + free_ivector(TmodelInvind,1,NCOVMAX); + free_ivector(TmodelInvQind,1,NCOVMAX); + + free_imatrix(nbcode,0,NCOVMAX,0,NCOVMAX); + /* free_imatrix(codtab,1,100,1,10); */ + fflush(fichtm); + fflush(ficgp); + + + if((nberr >0) || (nbwarn>0)){ + printf("End of Imach with %d errors and/or %d warnings. Please look at the log file for details.\n",nberr,nbwarn); + fprintf(ficlog,"End of Imach with %d errors and/or warnings %d. Please look at the log file for details.\n",nberr,nbwarn); + }else{ + printf("End of Imach\n"); + fprintf(ficlog,"End of Imach\n"); + } + printf("See log file on %s\n",filelog); /* gettimeofday(&end_time, (struct timezone*)0);*/ /* after time */ - - /* printf("Total time was %d Sec. %d uSec.\n", end_time.tv_sec -start_time.tv_sec, end_time.tv_usec -start_time.tv_usec);*/ - /*printf("Total time was %d uSec.\n", total_usecs);*/ + /*(void) gettimeofday(&end_time,&tzp);*/ + rend_time = time(NULL); + end_time = *localtime(&rend_time); + /* tml = *localtime(&end_time.tm_sec); */ + strcpy(strtend,asctime(&end_time)); + printf("Local time at start %s\nLocal time at end %s",strstart, strtend); + fprintf(ficlog,"Local time at start %s\nLocal time at end %s\n",strstart, strtend); + printf("Total time used %s\n", asc_diff_time(rend_time -rstart_time,tmpout)); + + printf("Total time was %.0lf Sec.\n", difftime(rend_time,rstart_time)); + fprintf(ficlog,"Total time used %s\n", asc_diff_time(rend_time -rstart_time,tmpout)); + fprintf(ficlog,"Total time was %.0lf Sec.\n", difftime(rend_time,rstart_time)); + /* printf("Total time was %d uSec.\n", total_usecs);*/ +/* if(fileappend(fichtm,optionfilehtm)){ */ + fprintf(fichtm,"
        Local time at start %s
        Local time at end %s
        \n",strstart, strtend); + fclose(fichtm); + fprintf(fichtmcov,"
        Local time at start %s
        Local time at end %s
        \n",strstart, strtend); + fclose(fichtmcov); + fclose(ficgp); + fclose(ficlog); /*------ End -----------*/ - - end: -#ifdef windows - chdir(pathcd); + + + printf("Before Current directory %s!\n",pathcd); +#ifdef WIN32 + if (_chdir(pathcd) != 0) + printf("Can't move to directory %s!\n",path); + if(_getcwd(pathcd,MAXLINE) > 0) +#else + if(chdir(pathcd) != 0) + printf("Can't move to directory %s!\n", path); + if (getcwd(pathcd, MAXLINE) > 0) #endif - system("gnuplot graph.gp"); - -#ifdef windows + printf("Current directory %s!\n",pathcd); + /*strcat(plotcmd,CHARSEPARATOR);*/ + sprintf(plotcmd,"gnuplot"); +#ifdef _WIN32 + sprintf(plotcmd,"\"%sgnuplot.exe\"",pathimach); +#endif + if(!stat(plotcmd,&info)){ + printf("Error or gnuplot program not found: '%s'\n",plotcmd);fflush(stdout); + if(!stat(getenv("GNUPLOTBIN"),&info)){ + printf("Error or gnuplot program not found: '%s' Environment GNUPLOTBIN not set.\n",plotcmd);fflush(stdout); + }else + strcpy(pplotcmd,plotcmd); +#ifdef __unix + strcpy(plotcmd,GNUPLOTPROGRAM); + if(!stat(plotcmd,&info)){ + printf("Error gnuplot program not found: '%s'\n",plotcmd);fflush(stdout); + }else + strcpy(pplotcmd,plotcmd); +#endif + }else + strcpy(pplotcmd,plotcmd); + + sprintf(plotcmd,"%s %s",pplotcmd, optionfilegnuplot); + printf("Starting graphs with: '%s'\n",plotcmd);fflush(stdout); + + if((outcmd=system(plotcmd)) != 0){ + printf("gnuplot command might not be in your path: '%s', err=%d\n", plotcmd, outcmd); + printf("\n Trying if gnuplot resides on the same directory that IMaCh\n"); + sprintf(plotcmd,"%sgnuplot %s", pathimach, optionfilegnuplot); + if((outcmd=system(plotcmd)) != 0) + printf("\n Still a problem with gnuplot command %s, err=%d\n", plotcmd, outcmd); + } + printf(" Successful, please wait..."); while (z[0] != 'q') { - chdir(pathcd); - printf("\nType e to edit output files, c to start again, and q for exiting: "); + /* chdir(path); */ + printf("\nType e to edit results with your browser, g to graph again and q for exit: "); scanf("%s",z); - if (z[0] == 'c') system("./imach"); - else if (z[0] == 'e') { - chdir(path); - system("index.htm"); +/* if (z[0] == 'c') system("./imach"); */ + if (z[0] == 'e') { +#ifdef __APPLE__ + sprintf(pplotcmd, "open %s", optionfilehtm); +#elif __linux + sprintf(pplotcmd, "xdg-open %s", optionfilehtm); +#else + sprintf(pplotcmd, "%s", optionfilehtm); +#endif + printf("Starting browser with: %s",pplotcmd);fflush(stdout); + system(pplotcmd); } + else if (z[0] == 'g') system(plotcmd); else if (z[0] == 'q') exit(0); } -#endif +end: + while (z[0] != 'q') { + printf("\nType q for exiting: "); fflush(stdout); + scanf("%s",z); + } } -