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version 1.11, 2001/05/17 16:07:14
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version 1.249, 2016/09/07 17:14:18
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/* $Id$ |
| /*********************** Imach **************************************
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$State$ |
| This program computes Healthy Life Expectancies from cross-longitudinal
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$Log$ |
| data. Cross-longitudinal consist in a first survey ("cross") where
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Revision 1.249 2016/09/07 17:14:18 brouard |
| individuals from different ages are interviewed on their health status
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Summary: Starting values from frequencies |
| or degree of disability. At least a second wave of interviews
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| ("longitudinal") should measure each new individual health status.
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Revision 1.248 2016/09/07 14:10:18 brouard |
| Health expectancies are computed from the transistions observed between
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*** empty log message *** |
| waves and are computed for each degree of severity of disability (number
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| of life states). More degrees you consider, more time is necessary to
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Revision 1.247 2016/09/02 11:11:21 brouard |
| reach the Maximum Likelihood of the parameters involved in the model.
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*** empty log message *** |
| The simplest model is the multinomial logistic model where pij is
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| the probabibility to be observed in state j at the second wave conditional
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Revision 1.246 2016/09/02 08:49:22 brouard |
| to be observed in state i at the first wave. Therefore the model is:
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*** empty log message *** |
| log(pij/pii)= aij + bij*age+ cij*sex + etc , where 'age' is age and 'sex'
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| is a covariate. If you want to have a more complex model than "constant and
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Revision 1.245 2016/09/02 07:25:01 brouard |
| age", you should modify the program where the markup
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*** empty log message *** |
| *Covariates have to be included here again* invites you to do it.
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| More covariates you add, less is the speed of the convergence.
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Revision 1.244 2016/09/02 07:17:34 brouard |
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*** empty log message *** |
| The advantage that this computer programme claims, comes from that if the
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| delay between waves is not identical for each individual, or if some
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Revision 1.243 2016/09/02 06:45:35 brouard |
| individual missed an interview, the information is not rounded or lost, but
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*** empty log message *** |
| taken into account using an interpolation or extrapolation.
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| hPijx is the probability to be
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Revision 1.242 2016/08/30 15:01:20 brouard |
| observed in state i at age x+h conditional to the observed state i at age
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Summary: Fixing a lots |
| x. The delay 'h' can be split into an exact number (nh*stepm) of
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| unobserved intermediate states. This elementary transition (by month or
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Revision 1.241 2016/08/29 17:17:25 brouard |
| quarter trimester, semester or year) is model as a multinomial logistic.
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Summary: gnuplot problem in Back projection to fix |
| The hPx matrix is simply the matrix product of nh*stepm elementary matrices
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| and the contribution of each individual to the likelihood is simply hPijx.
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Revision 1.240 2016/08/29 07:53:18 brouard |
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Summary: Better |
| Also this programme outputs the covariance matrix of the parameters but also
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| of the life expectancies. It also computes the prevalence limits.
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Revision 1.239 2016/08/26 15:51:03 brouard |
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Summary: Improvement in Powell output in order to copy and paste |
| Authors: Nicolas Brouard (brouard@ined.fr) and Agnès Lièvre (lievre@ined.fr).
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| Institut national d'études démographiques, Paris.
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Author: |
| This software have been partly granted by Euro-REVES, a concerted action
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| from the European Union.
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Revision 1.238 2016/08/26 14:23:35 brouard |
| It is copyrighted identically to a GNU software product, ie programme and
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Summary: Starting tests of 0.99 |
| software can be distributed freely for non commercial use. Latest version
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| can be accessed at http://euroreves.ined.fr/imach .
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Revision 1.237 2016/08/26 09:20:19 brouard |
| **********************************************************************/
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Summary: to valgrind |
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| #include <math.h>
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Revision 1.236 2016/08/25 10:50:18 brouard |
| #include <stdio.h>
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*** empty log message *** |
| #include <stdlib.h>
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| #include <unistd.h>
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Revision 1.235 2016/08/25 06:59:23 brouard |
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*** empty log message *** |
| #define MAXLINE 256
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| #define FILENAMELENGTH 80
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Revision 1.234 2016/08/23 16:51:20 brouard |
| /*#define DEBUG*/
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*** empty log message *** |
| #define windows
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| #define GLOCK_ERROR_NOPATH -1 /* empty path */
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Revision 1.233 2016/08/23 07:40:50 brouard |
| #define GLOCK_ERROR_GETCWD -2 /* cannot get cwd */
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Summary: not working |
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| #define MAXPARM 30 /* Maximum number of parameters for the optimization */
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Revision 1.232 2016/08/22 14:20:21 brouard |
| #define NPARMAX 64 /* (nlstate+ndeath-1)*nlstate*ncovmodel */
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Summary: not working |
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| #define NINTERVMAX 8
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Revision 1.231 2016/08/22 07:17:15 brouard |
| #define NLSTATEMAX 8 /* Maximum number of live states (for func) */
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Summary: not working |
| #define NDEATHMAX 8 /* Maximum number of dead states (for func) */
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| #define NCOVMAX 8 /* Maximum number of covariates */
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Revision 1.230 2016/08/22 06:55:53 brouard |
| #define MAXN 20000
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Summary: Not working |
| #define YEARM 12. /* Number of months per year */
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| #define AGESUP 130
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Revision 1.229 2016/07/23 09:45:53 brouard |
| #define AGEBASE 40
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Summary: Completing for func too |
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Revision 1.228 2016/07/22 17:45:30 brouard |
| int nvar;
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Summary: Fixing some arrays, still debugging |
| int cptcovn, cptcovage=0, cptcoveff=0,cptcov;
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| int npar=NPARMAX;
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Revision 1.226 2016/07/12 18:42:34 brouard |
| int nlstate=2; /* Number of live states */
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Summary: temp |
| int ndeath=1; /* Number of dead states */
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| int ncovmodel, ncov; /* Total number of covariables including constant a12*1 +b12*x ncovmodel=2 */
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Revision 1.225 2016/07/12 08:40:03 brouard |
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Summary: saving but not running |
| int *wav; /* Number of waves for this individuual 0 is possible */
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| int maxwav; /* Maxim number of waves */
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Revision 1.224 2016/07/01 13:16:01 brouard |
| int jmin, jmax; /* min, max spacing between 2 waves */
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Summary: Fixes |
| int mle, weightopt;
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| int **mw; /* mw[mi][i] is number of the mi wave for this individual */
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Revision 1.223 2016/02/19 09:23:35 brouard |
| int **dh; /* dh[mi][i] is number of steps between mi,mi+1 for this individual */
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Summary: temporary |
| double jmean; /* Mean space between 2 waves */
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| double **oldm, **newm, **savm; /* Working pointers to matrices */
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Revision 1.222 2016/02/17 08:14:50 brouard |
| double **oldms, **newms, **savms; /* Fixed working pointers to matrices */
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Summary: Probably last 0.98 stable version 0.98r6 |
| FILE *fic,*ficpar, *ficparo,*ficres, *ficrespl, *ficrespij, *ficrest;
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| FILE *ficgp, *fichtm;
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Revision 1.221 2016/02/15 23:35:36 brouard |
| FILE *ficreseij;
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Summary: minor bug |
| char filerese[FILENAMELENGTH];
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| FILE *ficresvij;
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Revision 1.219 2016/02/15 00:48:12 brouard |
| char fileresv[FILENAMELENGTH];
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*** empty log message *** |
| FILE *ficresvpl;
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| char fileresvpl[FILENAMELENGTH];
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Revision 1.218 2016/02/12 11:29:23 brouard |
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Summary: 0.99 Back projections |
| #define NR_END 1
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| #define FREE_ARG char*
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Revision 1.217 2015/12/23 17:18:31 brouard |
| #define FTOL 1.0e-10
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Summary: Experimental backcast |
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| #define NRANSI
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Revision 1.216 2015/12/18 17:32:11 brouard |
| #define ITMAX 200
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Summary: 0.98r4 Warning and status=-2 |
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| #define TOL 2.0e-4
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Version 0.98r4 is now: |
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- displaying an error when status is -1, date of interview unknown and date of death known; |
| #define CGOLD 0.3819660
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- permitting a status -2 when the vital status is unknown at a known date of right truncation. |
| #define ZEPS 1.0e-10
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Older changes concerning s=-2, dating from 2005 have been supersed. |
| #define SHFT(a,b,c,d) (a)=(b);(b)=(c);(c)=(d);
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Revision 1.215 2015/12/16 08:52:24 brouard |
| #define GOLD 1.618034
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Summary: 0.98r4 working |
| #define GLIMIT 100.0
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| #define TINY 1.0e-20
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Revision 1.214 2015/12/16 06:57:54 brouard |
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Summary: temporary not working |
| static double maxarg1,maxarg2;
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| #define FMAX(a,b) (maxarg1=(a),maxarg2=(b),(maxarg1)>(maxarg2)? (maxarg1):(maxarg2))
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Revision 1.213 2015/12/11 18:22:17 brouard |
| #define FMIN(a,b) (maxarg1=(a),maxarg2=(b),(maxarg1)<(maxarg2)? (maxarg1):(maxarg2))
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Summary: 0.98r4 |
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| #define SIGN(a,b) ((b)>0.0 ? fabs(a) : -fabs(a))
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Revision 1.212 2015/11/21 12:47:24 brouard |
| #define rint(a) floor(a+0.5)
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Summary: minor typo |
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| static double sqrarg;
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Revision 1.211 2015/11/21 12:41:11 brouard |
| #define SQR(a) ((sqrarg=(a)) == 0.0 ? 0.0 :sqrarg*sqrarg)
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Summary: 0.98r3 with some graph of projected cross-sectional |
| #define SWAP(a,b) {temp=(a);(a)=(b);(b)=temp;}
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Author: Nicolas Brouard |
| int imx;
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| int stepm;
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Revision 1.210 2015/11/18 17:41:20 brouard |
| /* Stepm, step in month: minimum step interpolation*/
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Summary: Start working on projected prevalences |
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| int m,nb;
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Revision 1.209 2015/11/17 22:12:03 brouard |
| int *num, firstpass=0, lastpass=4,*cod, *ncodemax, *Tage;
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Summary: Adding ftolpl parameter |
| double **agev,*moisnais, *annais, *moisdc, *andc,**mint, **anint;
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Author: N Brouard |
| double **pmmij;
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We had difficulties to get smoothed confidence intervals. It was due |
| double *weight;
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to the period prevalence which wasn't computed accurately. The inner |
| int **s; /* Status */
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parameter ftolpl is now an outer parameter of the .imach parameter |
| double *agedc, **covar, idx;
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file after estepm. If ftolpl is small 1.e-4 and estepm too, |
| int **nbcode, *Tcode, *Tvar, **codtab, **Tvard, *Tprod, cptcovprod, *Tvaraff;
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computation are long. |
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| double ftol=FTOL; /* Tolerance for computing Max Likelihood */
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Revision 1.208 2015/11/17 14:31:57 brouard |
| double ftolhess; /* Tolerance for computing hessian */
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Summary: temporary |
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| /**************** split *************************/
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Revision 1.207 2015/10/27 17:36:57 brouard |
| static int split( char *path, char *dirc, char *name )
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*** empty log message *** |
| {
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| char *s; /* pointer */
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Revision 1.206 2015/10/24 07:14:11 brouard |
| int l1, l2; /* length counters */
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*** empty log message *** |
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| l1 = strlen( path ); /* length of path */
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Revision 1.205 2015/10/23 15:50:53 brouard |
| if ( l1 == 0 ) return( GLOCK_ERROR_NOPATH );
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Summary: 0.98r3 some clarification for graphs on likelihood contributions |
| s = strrchr( path, '\\' ); /* find last / */
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| if ( s == NULL ) { /* no directory, so use current */
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Revision 1.204 2015/10/01 16:20:26 brouard |
| #if defined(__bsd__) /* get current working directory */
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Summary: Some new graphs of contribution to likelihood |
| extern char *getwd( );
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Revision 1.203 2015/09/30 17:45:14 brouard |
| if ( getwd( dirc ) == NULL ) {
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Summary: looking at better estimation of the hessian |
| #else
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| extern char *getcwd( );
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Also a better criteria for convergence to the period prevalence And |
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therefore adding the number of years needed to converge. (The |
| if ( getcwd( dirc, FILENAME_MAX ) == NULL ) {
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prevalence in any alive state shold sum to one |
| #endif
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| return( GLOCK_ERROR_GETCWD );
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Revision 1.202 2015/09/22 19:45:16 brouard |
| }
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Summary: Adding some overall graph on contribution to likelihood. Might change |
| strcpy( name, path ); /* we've got it */
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| } else { /* strip direcotry from path */
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Revision 1.201 2015/09/15 17:34:58 brouard |
| s++; /* after this, the filename */
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Summary: 0.98r0 |
| l2 = strlen( s ); /* length of filename */
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| if ( l2 == 0 ) return( GLOCK_ERROR_NOPATH );
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- Some new graphs like suvival functions |
| strcpy( name, s ); /* save file name */
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- Some bugs fixed like model=1+age+V2. |
| strncpy( dirc, path, l1 - l2 ); /* now the directory */
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| dirc[l1-l2] = 0; /* add zero */
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Revision 1.200 2015/09/09 16:53:55 brouard |
| }
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Summary: Big bug thanks to Flavia |
| l1 = strlen( dirc ); /* length of directory */
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| if ( dirc[l1-1] != '\\' ) { dirc[l1] = '\\'; dirc[l1+1] = 0; }
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Even model=1+age+V2. did not work anymore |
| return( 0 ); /* we're done */
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| }
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Revision 1.199 2015/09/07 14:09:23 brouard |
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Summary: 0.98q6 changing default small png format for graph to vectorized svg. |
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| /******************************************/
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Revision 1.198 2015/09/03 07:14:39 brouard |
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Summary: 0.98q5 Flavia |
| void replace(char *s, char*t)
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| {
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Revision 1.197 2015/09/01 18:24:39 brouard |
| int i;
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*** empty log message *** |
| int lg=20;
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| i=0;
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Revision 1.196 2015/08/18 23:17:52 brouard |
| lg=strlen(t);
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Summary: 0.98q5 |
| for(i=0; i<= lg; i++) {
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| (s[i] = t[i]);
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Revision 1.195 2015/08/18 16:28:39 brouard |
| if (t[i]== '\\') s[i]='/';
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Summary: Adding a hack for testing purpose |
| }
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| }
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After reading the title, ftol and model lines, if the comment line has |
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a q, starting with #q, the answer at the end of the run is quit. It |
| int nbocc(char *s, char occ)
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permits to run test files in batch with ctest. The former workaround was |
| {
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$ echo q | imach foo.imach |
| int i,j=0;
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| int lg=20;
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Revision 1.194 2015/08/18 13:32:00 brouard |
| i=0;
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Summary: Adding error when the covariance matrix doesn't contain the exact number of lines required by the model line. |
| lg=strlen(s);
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| for(i=0; i<= lg; i++) {
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Revision 1.193 2015/08/04 07:17:42 brouard |
| if (s[i] == occ ) j++;
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Summary: 0.98q4 |
| }
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| return j;
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Revision 1.192 2015/07/16 16:49:02 brouard |
| }
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Summary: Fixing some outputs |
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| void cutv(char *u,char *v, char*t, char occ)
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Revision 1.191 2015/07/14 10:00:33 brouard |
| {
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Summary: Some fixes |
| int i,lg,j,p=0;
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| i=0;
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Revision 1.190 2015/05/05 08:51:13 brouard |
| for(j=0; j<=strlen(t)-1; j++) {
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Summary: Adding digits in output parameters (7 digits instead of 6) |
| if((t[j]!= occ) && (t[j+1]== occ)) p=j+1;
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| }
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Fix 1+age+. |
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| lg=strlen(t);
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Revision 1.189 2015/04/30 14:45:16 brouard |
| for(j=0; j<p; j++) {
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Summary: 0.98q2 |
| (u[j] = t[j]);
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| }
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Revision 1.188 2015/04/30 08:27:53 brouard |
| u[p]='\0';
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*** empty log message *** |
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| for(j=0; j<= lg; j++) {
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Revision 1.187 2015/04/29 09:11:15 brouard |
| if (j>=(p+1))(v[j-p-1] = t[j]);
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*** empty log message *** |
| }
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| }
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Revision 1.186 2015/04/23 12:01:52 brouard |
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Summary: V1*age is working now, version 0.98q1 |
| /********************** nrerror ********************/
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Some codes had been disabled in order to simplify and Vn*age was |
| void nrerror(char error_text[])
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working in the optimization phase, ie, giving correct MLE parameters, |
| {
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but, as usual, outputs were not correct and program core dumped. |
| fprintf(stderr,"ERREUR ...\n");
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| fprintf(stderr,"%s\n",error_text);
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Revision 1.185 2015/03/11 13:26:42 brouard |
| exit(1);
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Summary: Inclusion of compile and links command line for Intel Compiler |
| }
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|
| /*********************** vector *******************/
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Revision 1.184 2015/03/11 11:52:39 brouard |
| double *vector(int nl, int nh)
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Summary: Back from Windows 8. Intel Compiler |
| {
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| double *v;
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Revision 1.183 2015/03/10 20:34:32 brouard |
| v=(double *) malloc((size_t)((nh-nl+1+NR_END)*sizeof(double)));
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Summary: 0.98q0, trying with directest, mnbrak fixed |
| if (!v) nrerror("allocation failure in vector");
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| return v-nl+NR_END;
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We use directest instead of original Powell test; probably no |
| }
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incidence on the results, but better justifications; |
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We fixed Numerical Recipes mnbrak routine which was wrong and gave |
| /************************ free vector ******************/
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wrong results. |
| void free_vector(double*v, int nl, int nh)
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| {
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Revision 1.182 2015/02/12 08:19:57 brouard |
| free((FREE_ARG)(v+nl-NR_END));
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Summary: Trying to keep directest which seems simpler and more general |
| }
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Author: Nicolas Brouard |
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| /************************ivector *******************************/
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Revision 1.181 2015/02/11 23:22:24 brouard |
| int *ivector(long nl,long nh)
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Summary: Comments on Powell added |
| {
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| int *v;
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Author: |
| v=(int *) malloc((size_t)((nh-nl+1+NR_END)*sizeof(int)));
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| if (!v) nrerror("allocation failure in ivector");
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Revision 1.180 2015/02/11 17:33:45 brouard |
| return v-nl+NR_END;
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Summary: Finishing move from main to function (hpijx and prevalence_limit) |
| }
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Revision 1.179 2015/01/04 09:57:06 brouard |
| /******************free ivector **************************/
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Summary: back to OS/X |
| void free_ivector(int *v, long nl, long nh)
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| {
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Revision 1.178 2015/01/04 09:35:48 brouard |
| free((FREE_ARG)(v+nl-NR_END));
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*** empty log message *** |
| }
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Revision 1.177 2015/01/03 18:40:56 brouard |
| /******************* imatrix *******************************/
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Summary: Still testing ilc32 on OSX |
| int **imatrix(long nrl, long nrh, long ncl, long nch)
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| /* allocate a int matrix with subscript range m[nrl..nrh][ncl..nch] */
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Revision 1.176 2015/01/03 16:45:04 brouard |
| {
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*** empty log message *** |
| long i, nrow=nrh-nrl+1,ncol=nch-ncl+1;
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| int **m;
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Revision 1.175 2015/01/03 16:33:42 brouard |
|
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*** empty log message *** |
| /* allocate pointers to rows */
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| m=(int **) malloc((size_t)((nrow+NR_END)*sizeof(int*)));
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Revision 1.174 2015/01/03 16:15:49 brouard |
| if (!m) nrerror("allocation failure 1 in matrix()");
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Summary: Still in cross-compilation |
| m += NR_END;
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| m -= nrl;
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Revision 1.173 2015/01/03 12:06:26 brouard |
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Summary: trying to detect cross-compilation |
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| /* allocate rows and set pointers to them */
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Revision 1.172 2014/12/27 12:07:47 brouard |
| m[nrl]=(int *) malloc((size_t)((nrow*ncol+NR_END)*sizeof(int)));
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Summary: Back from Visual Studio and Intel, options for compiling for Windows XP |
| if (!m[nrl]) nrerror("allocation failure 2 in matrix()");
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| m[nrl] += NR_END;
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Revision 1.171 2014/12/23 13:26:59 brouard |
| m[nrl] -= ncl;
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Summary: Back from Visual C |
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| for(i=nrl+1;i<=nrh;i++) m[i]=m[i-1]+ncol;
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Still problem with utsname.h on Windows |
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| /* return pointer to array of pointers to rows */
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Revision 1.170 2014/12/23 11:17:12 brouard |
| return m;
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Summary: Cleaning some \%% back to %% |
| }
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The escape was mandatory for a specific compiler (which one?), but too many warnings. |
| /****************** free_imatrix *************************/
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| void free_imatrix(m,nrl,nrh,ncl,nch)
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Revision 1.169 2014/12/22 23:08:31 brouard |
| int **m;
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Summary: 0.98p |
| long nch,ncl,nrh,nrl;
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| /* free an int matrix allocated by imatrix() */
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Outputs some informations on compiler used, OS etc. Testing on different platforms. |
| {
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| free((FREE_ARG) (m[nrl]+ncl-NR_END));
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Revision 1.168 2014/12/22 15:17:42 brouard |
| free((FREE_ARG) (m+nrl-NR_END));
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Summary: update |
| }
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Revision 1.167 2014/12/22 13:50:56 brouard |
| /******************* matrix *******************************/
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Summary: Testing uname and compiler version and if compiled 32 or 64 |
| double **matrix(long nrl, long nrh, long ncl, long nch)
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|
| {
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Testing on Linux 64 |
| long i, nrow=nrh-nrl+1, ncol=nch-ncl+1;
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| double **m;
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Revision 1.166 2014/12/22 11:40:47 brouard |
|
|
*** empty log message *** |
| m=(double **) malloc((size_t)((nrow+NR_END)*sizeof(double*)));
|
|
| if (!m) nrerror("allocation failure 1 in matrix()");
|
Revision 1.165 2014/12/16 11:20:36 brouard |
| m += NR_END;
|
Summary: After compiling on Visual C |
| m -= nrl;
|
|
|
|
* imach.c (Module): Merging 1.61 to 1.162 |
| m[nrl]=(double *) malloc((size_t)((nrow*ncol+NR_END)*sizeof(double)));
|
|
| if (!m[nrl]) nrerror("allocation failure 2 in matrix()");
|
Revision 1.164 2014/12/16 10:52:11 brouard |
| m[nrl] += NR_END;
|
Summary: Merging with Visual C after suppressing some warnings for unused variables. Also fixing Saito's bug 0.98Xn |
| m[nrl] -= ncl;
|
|
|
|
* imach.c (Module): Merging 1.61 to 1.162 |
| for (i=nrl+1; i<=nrh; i++) m[i]=m[i-1]+ncol;
|
|
| return m;
|
Revision 1.163 2014/12/16 10:30:11 brouard |
| }
|
* imach.c (Module): Merging 1.61 to 1.162 |
|
|
|
| /*************************free matrix ************************/
|
Revision 1.162 2014/09/25 11:43:39 brouard |
| void free_matrix(double **m, long nrl, long nrh, long ncl, long nch)
|
Summary: temporary backup 0.99! |
| {
|
|
| free((FREE_ARG)(m[nrl]+ncl-NR_END));
|
Revision 1.1 2014/09/16 11:06:58 brouard |
| free((FREE_ARG)(m+nrl-NR_END));
|
Summary: With some code (wrong) for nlopt |
| }
|
|
|
|
Author: |
| /******************* ma3x *******************************/
|
|
| double ***ma3x(long nrl, long nrh, long ncl, long nch, long nll, long nlh)
|
Revision 1.161 2014/09/15 20:41:41 brouard |
| {
|
Summary: Problem with macro SQR on Intel compiler |
| long i, j, nrow=nrh-nrl+1, ncol=nch-ncl+1, nlay=nlh-nll+1;
|
|
| double ***m;
|
Revision 1.160 2014/09/02 09:24:05 brouard |
|
|
*** empty log message *** |
| m=(double ***) malloc((size_t)((nrow+NR_END)*sizeof(double*)));
|
|
| if (!m) nrerror("allocation failure 1 in matrix()");
|
Revision 1.159 2014/09/01 10:34:10 brouard |
| m += NR_END;
|
Summary: WIN32 |
| m -= nrl;
|
Author: Brouard |
|
|
|
| m[nrl]=(double **) malloc((size_t)((nrow*ncol+NR_END)*sizeof(double)));
|
Revision 1.158 2014/08/27 17:11:51 brouard |
| if (!m[nrl]) nrerror("allocation failure 2 in matrix()");
|
*** empty log message *** |
| m[nrl] += NR_END;
|
|
| m[nrl] -= ncl;
|
Revision 1.157 2014/08/27 16:26:55 brouard |
|
|
Summary: Preparing windows Visual studio version |
| for (i=nrl+1; i<=nrh; i++) m[i]=m[i-1]+ncol;
|
Author: Brouard |
|
|
|
| m[nrl][ncl]=(double *) malloc((size_t)((nrow*ncol*nlay+NR_END)*sizeof(double)));
|
In order to compile on Visual studio, time.h is now correct and time_t |
| if (!m[nrl][ncl]) nrerror("allocation failure 3 in matrix()");
|
and tm struct should be used. difftime should be used but sometimes I |
| m[nrl][ncl] += NR_END;
|
just make the differences in raw time format (time(&now). |
| m[nrl][ncl] -= nll;
|
Trying to suppress #ifdef LINUX |
| for (j=ncl+1; j<=nch; j++)
|
Add xdg-open for __linux in order to open default browser. |
| m[nrl][j]=m[nrl][j-1]+nlay;
|
|
|
|
Revision 1.156 2014/08/25 20:10:10 brouard |
| for (i=nrl+1; i<=nrh; i++) {
|
*** empty log message *** |
| m[i][ncl]=m[i-1l][ncl]+ncol*nlay;
|
|
| for (j=ncl+1; j<=nch; j++)
|
Revision 1.155 2014/08/25 18:32:34 brouard |
| m[i][j]=m[i][j-1]+nlay;
|
Summary: New compile, minor changes |
| }
|
Author: Brouard |
| return m;
|
|
| }
|
Revision 1.154 2014/06/20 17:32:08 brouard |
|
|
Summary: Outputs now all graphs of convergence to period prevalence |
| /*************************free ma3x ************************/
|
|
| void free_ma3x(double ***m, long nrl, long nrh, long ncl, long nch,long nll, long nlh)
|
Revision 1.153 2014/06/20 16:45:46 brouard |
| {
|
Summary: If 3 live state, convergence to period prevalence on same graph |
| free((FREE_ARG)(m[nrl][ncl]+ nll-NR_END));
|
Author: Brouard |
| free((FREE_ARG)(m[nrl]+ncl-NR_END));
|
|
| free((FREE_ARG)(m+nrl-NR_END));
|
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 |
|
|
|
| /***************** f1dim *************************/
|
Revision 1.151 2014/06/18 16:43:30 brouard |
| extern int ncom;
|
*** empty log message *** |
| extern double *pcom,*xicom;
|
|
| extern double (*nrfunc)(double []);
|
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) |
| double f1dim(double x)
|
Author: brouard |
| {
|
|
| int j;
|
Revision 1.149 2014/06/18 15:51:14 brouard |
| double f;
|
Summary: Some fixes in parameter files errors |
| double *xt;
|
Author: Nicolas Brouard |
|
|
|
| xt=vector(1,ncom);
|
Revision 1.148 2014/06/17 17:38:48 brouard |
| for (j=1;j<=ncom;j++) xt[j]=pcom[j]+x*xicom[j];
|
Summary: Nothing new |
| f=(*nrfunc)(xt);
|
Author: Brouard |
| free_vector(xt,1,ncom);
|
|
| return f;
|
Just a new packaging for OS/X version 0.98nS |
| }
|
|
|
|
Revision 1.147 2014/06/16 10:33:11 brouard |
| /*****************brent *************************/
|
*** empty log message *** |
| double brent(double ax, double bx, double cx, double (*f)(double), double tol, double *xmin)
|
|
| {
|
Revision 1.146 2014/06/16 10:20:28 brouard |
| int iter;
|
Summary: Merge |
| double a,b,d,etemp;
|
Author: Brouard |
| double fu,fv,fw,fx;
|
|
| double ftemp;
|
Merge, before building revised version. |
| double p,q,r,tol1,tol2,u,v,w,x,xm;
|
|
| double e=0.0;
|
Revision 1.145 2014/06/10 21:23:15 brouard |
|
|
Summary: Debugging with valgrind |
| a=(ax < cx ? ax : cx);
|
Author: Nicolas Brouard |
| b=(ax > cx ? ax : cx);
|
|
| x=w=v=bx;
|
Lot of changes in order to output the results with some covariates |
| fw=fv=fx=(*f)(x);
|
After the Edimburgh REVES conference 2014, it seems mandatory to |
| for (iter=1;iter<=ITMAX;iter++) {
|
improve the code. |
| xm=0.5*(a+b);
|
No more memory valgrind error but a lot has to be done in order to |
| tol2=2.0*(tol1=tol*fabs(x)+ZEPS);
|
continue the work of splitting the code into subroutines. |
| /* if (2.0*fabs(fp-(*fret)) <= ftol*(fabs(fp)+fabs(*fret)))*/
|
Also, decodemodel has been improved. Tricode is still not |
| printf(".");fflush(stdout);
|
optimal. nbcode should be improved. Documentation has been added in |
| #ifdef DEBUG
|
the source code. |
| 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);
|
|
| /* if ((fabs(x-xm) <= (tol2-0.5*(b-a)))||(2.0*fabs(fu-ftemp) <= ftol*1.e-2*(fabs(fu)+fabs(ftemp)))) { */
|
Revision 1.143 2014/01/26 09:45:38 brouard |
| #endif
|
Summary: Version 0.98nR (to be improved, but gives same optimization results as 0.98k. Nice, promising |
| if (fabs(x-xm) <= (tol2-0.5*(b-a))){
|
|
| *xmin=x;
|
* imach.c (Module): Trying to merge old staffs together while being at Tokyo. Not tested... |
| return fx;
|
(Module): Version 0.98nR Running ok, but output format still only works for three covariates. |
| }
|
|
| ftemp=fu;
|
Revision 1.142 2014/01/26 03:57:36 brouard |
| if (fabs(e) > tol1) {
|
Summary: gnuplot changed plot w l 1 has to be changed to plot w l lt 2 |
| r=(x-w)*(fx-fv);
|
|
| q=(x-v)*(fx-fw);
|
* imach.c (Module): Trying to merge old staffs together while being at Tokyo. Not tested... |
| p=(x-v)*q-(x-w)*r;
|
|
| q=2.0*(q-r);
|
Revision 1.141 2014/01/26 02:42:01 brouard |
| if (q > 0.0) p = -p;
|
* imach.c (Module): Trying to merge old staffs together while being at Tokyo. Not tested... |
| q=fabs(q);
|
|
| etemp=e;
|
Revision 1.140 2011/09/02 10:37:54 brouard |
| e=d;
|
Summary: times.h is ok with mingw32 now. |
| 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));
|
Revision 1.139 2010/06/14 07:50:17 brouard |
| else {
|
After the theft of my laptop, I probably lost some lines of codes which were not uploaded to the CVS tree. |
| d=p/q;
|
I remember having already fixed agemin agemax which are pointers now but not cvs saved. |
| u=x+d;
|
|
| if (u-a < tol2 || b-u < tol2)
|
Revision 1.138 2010/04/30 18:19:40 brouard |
| d=SIGN(tol1,xm-x);
|
*** empty log message *** |
| }
|
|
| } else {
|
Revision 1.137 2010/04/29 18:11:38 brouard |
| d=CGOLD*(e=(x >= xm ? a-x : b-x));
|
(Module): Checking covariates for more complex models |
| }
|
than V1+V2. A lot of change to be done. Unstable. |
| u=(fabs(d) >= tol1 ? x+d : x+SIGN(tol1,d));
|
|
| fu=(*f)(u);
|
Revision 1.136 2010/04/26 20:30:53 brouard |
| if (fu <= fx) {
|
(Module): merging some libgsl code. Fixing computation |
| if (u >= x) a=x; else b=x;
|
of likelione (using inter/intrapolation if mle = 0) in order to |
| SHFT(v,w,x,u)
|
get same likelihood as if mle=1. |
| SHFT(fv,fw,fx,fu)
|
Some cleaning of code and comments added. |
| } else {
|
|
| if (u < x) a=u; else b=u;
|
Revision 1.135 2009/10/29 15:33:14 brouard |
| if (fu <= fw || w == x) {
|
(Module): Now imach stops if date of birth, at least year of birth, is not given. Some cleaning of the code. |
| v=w;
|
|
| w=u;
|
Revision 1.134 2009/10/29 13:18:53 brouard |
| fv=fw;
|
(Module): Now imach stops if date of birth, at least year of birth, is not given. Some cleaning of the code. |
| fw=fu;
|
|
| } else if (fu <= fv || v == x || v == w) {
|
Revision 1.133 2009/07/06 10:21:25 brouard |
| v=u;
|
just nforces |
| fv=fu;
|
|
| }
|
Revision 1.132 2009/07/06 08:22:05 brouard |
| }
|
Many tings |
| }
|
|
| nrerror("Too many iterations in brent");
|
Revision 1.131 2009/06/20 16:22:47 brouard |
| *xmin=x;
|
Some dimensions resccaled |
| return fx;
|
|
| }
|
Revision 1.130 2009/05/26 06:44:34 brouard |
|
|
(Module): Max Covariate is now set to 20 instead of 8. A |
| /****************** mnbrak ***********************/
|
lot of cleaning with variables initialized to 0. Trying to make |
|
|
V2+V3*age+V1+V4 strb=V3*age+V1+V4 working better. |
| void mnbrak(double *ax, double *bx, double *cx, double *fa, double *fb, double *fc,
|
|
| double (*func)(double))
|
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 |
| double ulim,u,r,q, dum;
|
|
| double fu;
|
Revision 1.128 2006/06/30 13:02:05 brouard |
|
|
(Module): Clarifications on computing e.j |
| *fa=(*func)(*ax);
|
|
| *fb=(*func)(*bx);
|
Revision 1.127 2006/04/28 18:11:50 brouard |
| if (*fb > *fa) {
|
(Module): Yes the sum of survivors was wrong since |
| SHFT(dum,*ax,*bx,dum)
|
imach-114 because nhstepm was no more computed in the age |
| SHFT(dum,*fb,*fa,dum)
|
loop. Now we define nhstepma in the age loop. |
| }
|
(Module): In order to speed up (in case of numerous covariates) we |
| *cx=(*bx)+GOLD*(*bx-*ax);
|
compute health expectancies (without variances) in a first step |
| *fc=(*func)(*cx);
|
and then all the health expectancies with variances or standard |
| while (*fb > *fc) {
|
deviation (needs data from the Hessian matrices) which slows the |
| r=(*bx-*ax)*(*fb-*fc);
|
computation. |
| q=(*bx-*cx)*(*fb-*fa);
|
In the future we should be able to stop the program is only health |
| u=(*bx)-((*bx-*cx)*q-(*bx-*ax)*r)/
|
expectancies and graph are needed without standard deviations. |
| (2.0*SIGN(FMAX(fabs(q-r),TINY),q-r));
|
|
| ulim=(*bx)+GLIMIT*(*cx-*bx);
|
Revision 1.126 2006/04/28 17:23:28 brouard |
| if ((*bx-u)*(u-*cx) > 0.0) {
|
(Module): Yes the sum of survivors was wrong since |
| fu=(*func)(u);
|
imach-114 because nhstepm was no more computed in the age |
| } else if ((*cx-u)*(u-ulim) > 0.0) {
|
loop. Now we define nhstepma in the age loop. |
| fu=(*func)(u);
|
Version 0.98h |
| if (fu < *fc) {
|
|
| SHFT(*bx,*cx,u,*cx+GOLD*(*cx-*bx))
|
Revision 1.125 2006/04/04 15:20:31 lievre |
| SHFT(*fb,*fc,fu,(*func)(u))
|
Errors in calculation of health expectancies. Age was not initialized. |
| }
|
Forecasting file added. |
| } else if ((u-ulim)*(ulim-*cx) >= 0.0) {
|
|
| u=ulim;
|
Revision 1.124 2006/03/22 17:13:53 lievre |
| fu=(*func)(u);
|
Parameters are printed with %lf instead of %f (more numbers after the comma). |
| } else {
|
The log-likelihood is printed in the log file |
| u=(*cx)+GOLD*(*cx-*bx);
|
|
| fu=(*func)(u);
|
Revision 1.123 2006/03/20 10:52:43 brouard |
| }
|
* imach.c (Module): <title> changed, corresponds to .htm file |
| SHFT(*ax,*bx,*cx,u)
|
name. <head> headers where missing. |
| SHFT(*fa,*fb,*fc,fu)
|
|
| }
|
* 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). |
| /*************** linmin ************************/
|
Modification of warning when the covariates values are not 0 or |
|
|
1. |
| int ncom;
|
Version 0.98g |
| double *pcom,*xicom;
|
|
| double (*nrfunc)(double []);
|
Revision 1.122 2006/03/20 09:45:41 brouard |
|
|
(Module): Weights can have a decimal point as for |
| void linmin(double p[], double xi[], int n, double *fret,double (*func)(double []))
|
English (a comma might work with a correct LC_NUMERIC environment, |
| {
|
otherwise the weight is truncated). |
| double brent(double ax, double bx, double cx,
|
Modification of warning when the covariates values are not 0 or |
| double (*f)(double), double tol, double *xmin);
|
1. |
| double f1dim(double x);
|
Version 0.98g |
| void mnbrak(double *ax, double *bx, double *cx, double *fa, double *fb,
|
|
| double *fc, double (*func)(double));
|
Revision 1.121 2006/03/16 17:45:01 lievre |
| int j;
|
* imach.c (Module): Comments concerning covariates added |
| double xx,xmin,bx,ax;
|
|
| double fx,fb,fa;
|
* imach.c (Module): refinements in the computation of lli if |
|
|
status=-2 in order to have more reliable computation if stepm is |
| ncom=n;
|
not 1 month. Version 0.98f |
| pcom=vector(1,n);
|
|
| xicom=vector(1,n);
|
Revision 1.120 2006/03/16 15:10:38 lievre |
| nrfunc=func;
|
(Module): refinements in the computation of lli if |
| for (j=1;j<=n;j++) {
|
status=-2 in order to have more reliable computation if stepm is |
| pcom[j]=p[j];
|
not 1 month. Version 0.98f |
| xicom[j]=xi[j];
|
|
| }
|
Revision 1.119 2006/03/15 17:42:26 brouard |
| ax=0.0;
|
(Module): Bug if status = -2, the loglikelihood was |
| xx=1.0;
|
computed as likelihood omitting the logarithm. Version O.98e |
| mnbrak(&ax,&xx,&bx,&fa,&fx,&fb,f1dim);
|
|
| *fret=brent(ax,xx,bx,f1dim,TOL,&xmin);
|
Revision 1.118 2006/03/14 18:20:07 brouard |
| #ifdef DEBUG
|
(Module): varevsij Comments added explaining the second |
| printf("retour brent fret=%.12e xmin=%.12e\n",*fret,xmin);
|
table of variances if popbased=1 . |
| #endif
|
(Module): Covariances of eij, ekl added, graphs fixed, new html link. |
| for (j=1;j<=n;j++) {
|
(Module): Function pstamp added |
| xi[j] *= xmin;
|
(Module): Version 0.98d |
| p[j] += xi[j];
|
|
| }
|
Revision 1.117 2006/03/14 17:16:22 brouard |
| free_vector(xicom,1,n);
|
(Module): varevsij Comments added explaining the second |
| free_vector(pcom,1,n);
|
table of variances if popbased=1 . |
| }
|
(Module): Covariances of eij, ekl added, graphs fixed, new html link. |
|
|
(Module): Function pstamp added |
| /*************** powell ************************/
|
(Module): Version 0.98d |
| void powell(double p[], double **xi, int n, double ftol, int *iter, double *fret,
|
|
| double (*func)(double []))
|
Revision 1.116 2006/03/06 10:29:27 brouard |
| {
|
(Module): Variance-covariance wrong links and |
| void linmin(double p[], double xi[], int n, double *fret,
|
varian-covariance of ej. is needed (Saito). |
| double (*func)(double []));
|
|
| int i,ibig,j;
|
Revision 1.115 2006/02/27 12:17:45 brouard |
| double del,t,*pt,*ptt,*xit;
|
(Module): One freematrix added in mlikeli! 0.98c |
| double fp,fptt;
|
|
| double *xits;
|
Revision 1.114 2006/02/26 12:57:58 brouard |
| pt=vector(1,n);
|
(Module): Some improvements in processing parameter |
| ptt=vector(1,n);
|
filename with strsep. |
| xit=vector(1,n);
|
|
| xits=vector(1,n);
|
Revision 1.113 2006/02/24 14:20:24 brouard |
| *fret=(*func)(p);
|
(Module): Memory leaks checks with valgrind and: |
| for (j=1;j<=n;j++) pt[j]=p[j];
|
datafile was not closed, some imatrix were not freed and on matrix |
| for (*iter=1;;++(*iter)) {
|
allocation too. |
| fp=(*fret);
|
|
| ibig=0;
|
Revision 1.112 2006/01/30 09:55:26 brouard |
| del=0.0;
|
(Module): Back to gnuplot.exe instead of wgnuplot.exe |
| printf("\nPowell iter=%d -2*LL=%.12f",*iter,*fret);
|
|
| for (i=1;i<=n;i++)
|
Revision 1.111 2006/01/25 20:38:18 brouard |
| printf(" %d %.12f",i, p[i]);
|
(Module): Lots of cleaning and bugs added (Gompertz) |
| printf("\n");
|
(Module): Comments can be added in data file. Missing date values |
| for (i=1;i<=n;i++) {
|
can be a simple dot '.'. |
| for (j=1;j<=n;j++) xit[j]=xi[j][i];
|
|
| fptt=(*fret);
|
Revision 1.110 2006/01/25 00:51:50 brouard |
| #ifdef DEBUG
|
(Module): Lots of cleaning and bugs added (Gompertz) |
| printf("fret=%lf \n",*fret);
|
|
| #endif
|
Revision 1.109 2006/01/24 19:37:15 brouard |
| printf("%d",i);fflush(stdout);
|
(Module): Comments (lines starting with a #) are allowed in data. |
| linmin(p,xit,n,fret,func);
|
|
| if (fabs(fptt-(*fret)) > del) {
|
Revision 1.108 2006/01/19 18:05:42 lievre |
| del=fabs(fptt-(*fret));
|
Gnuplot problem appeared... |
| ibig=i;
|
To be fixed |
| }
|
|
| #ifdef DEBUG
|
Revision 1.107 2006/01/19 16:20:37 brouard |
| printf("%d %.12e",i,(*fret));
|
Test existence of gnuplot in imach path |
| for (j=1;j<=n;j++) {
|
|
| xits[j]=FMAX(fabs(p[j]-pt[j]),1.e-5);
|
Revision 1.106 2006/01/19 13:24:36 brouard |
| printf(" x(%d)=%.12e",j,xit[j]);
|
Some cleaning and links added in html output |
| }
|
|
| for(j=1;j<=n;j++)
|
Revision 1.105 2006/01/05 20:23:19 lievre |
| printf(" p=%.12e",p[j]);
|
*** empty log message *** |
| printf("\n");
|
|
| #endif
|
Revision 1.104 2005/09/30 16:11:43 lievre |
| }
|
(Module): sump fixed, loop imx fixed, and simplifications. |
| if (2.0*fabs(fp-(*fret)) <= ftol*(fabs(fp)+fabs(*fret))) {
|
(Module): If the status is missing at the last wave but we know |
| #ifdef DEBUG
|
that the person is alive, then we can code his/her status as -2 |
| int k[2],l;
|
(instead of missing=-1 in earlier versions) and his/her |
| k[0]=1;
|
contributions to the likelihood is 1 - Prob of dying from last |
| k[1]=-1;
|
health status (= 1-p13= p11+p12 in the easiest case of somebody in |
| printf("Max: %.12e",(*func)(p));
|
the healthy state at last known wave). Version is 0.98 |
| for (j=1;j<=n;j++)
|
|
| printf(" %.12e",p[j]);
|
Revision 1.103 2005/09/30 15:54:49 lievre |
| printf("\n");
|
(Module): sump fixed, loop imx fixed, and simplifications. |
| for(l=0;l<=1;l++) {
|
|
| for (j=1;j<=n;j++) {
|
Revision 1.102 2004/09/15 17:31:30 brouard |
| ptt[j]=p[j]+(p[j]-pt[j])*k[l];
|
Add the possibility to read data file including tab characters. |
| printf("l=%d j=%d ptt=%.12e, xits=%.12e, p=%.12e, xit=%.12e", l,j,ptt[j],xits[j],p[j],xit[j]);
|
|
| }
|
Revision 1.101 2004/09/15 10:38:38 brouard |
| printf("func(ptt)=%.12e, deriv=%.12e\n",(*func)(ptt),(ptt[j]-p[j])/((*func)(ptt)-(*func)(p)));
|
Fix on curr_time |
| }
|
|
| #endif
|
Revision 1.100 2004/07/12 18:29:06 brouard |
|
|
Add version for Mac OS X. Just define UNIX in Makefile |
|
|
|
| free_vector(xit,1,n);
|
Revision 1.99 2004/06/05 08:57:40 brouard |
| free_vector(xits,1,n);
|
*** empty log message *** |
| free_vector(ptt,1,n);
|
|
| free_vector(pt,1,n);
|
Revision 1.98 2004/05/16 15:05:56 brouard |
| return;
|
New version 0.97 . First attempt to estimate force of mortality |
| }
|
directly from the data i.e. without the need of knowing the health |
| if (*iter == ITMAX) nrerror("powell exceeding maximum iterations.");
|
state at each age, but using a Gompertz model: log u =a + b*age . |
| for (j=1;j<=n;j++) {
|
This is the basic analysis of mortality and should be done before any |
| ptt[j]=2.0*p[j]-pt[j];
|
other analysis, in order to test if the mortality estimated from the |
| xit[j]=p[j]-pt[j];
|
cross-longitudinal survey is different from the mortality estimated |
| pt[j]=p[j];
|
from other sources like vital statistic data. |
| }
|
|
| fptt=(*func)(ptt);
|
The same imach parameter file can be used but the option for mle should be -3. |
| if (fptt < fp) {
|
|
| t=2.0*(fp-2.0*(*fret)+fptt)*SQR(fp-(*fret)-del)-del*SQR(fp-fptt);
|
Agnès, who wrote this part of the code, tried to keep most of the |
| if (t < 0.0) {
|
former routines in order to include the new code within the former code. |
| linmin(p,xit,n,fret,func);
|
|
| for (j=1;j<=n;j++) {
|
The output is very simple: only an estimate of the intercept and of |
| xi[j][ibig]=xi[j][n];
|
the slope with 95% confident intervals. |
| xi[j][n]=xit[j];
|
|
| }
|
Current limitations: |
| #ifdef DEBUG
|
A) Even if you enter covariates, i.e. with the |
| printf("Direction changed last moved %d in place of ibig=%d, new last is the average:\n",n,ibig);
|
model= V1+V2 equation for example, the programm does only estimate a unique global model without covariates. |
| for(j=1;j<=n;j++)
|
B) There is no computation of Life Expectancy nor Life Table. |
| printf(" %.12e",xit[j]);
|
|
| printf("\n");
|
Revision 1.97 2004/02/20 13:25:42 lievre |
| #endif
|
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. |
| /**** Prevalence limit ****************/
|
|
|
|
Revision 1.95 2003/07/08 07:54:34 brouard |
| double **prevalim(double **prlim, int nlstate, double x[], double age, double **oldm, double **savm, double ftolpl, int ij)
|
* imach.c (Repository): |
| {
|
(Repository): Using imachwizard code to output a more meaningful covariance |
| /* Computes the prevalence limit in each live state at age x by left multiplying the unit
|
matrix (cov(a12,c31) instead of numbers. |
| matrix by transitions matrix until convergence is reached */
|
|
|
|
Revision 1.94 2003/06/27 13:00:02 brouard |
| int i, ii,j,k;
|
Just cleaning |
| double min, max, maxmin, maxmax,sumnew=0.;
|
|
| double **matprod2();
|
Revision 1.93 2003/06/25 16:33:55 brouard |
| double **out, cov[NCOVMAX], **pmij();
|
(Module): On windows (cygwin) function asctime_r doesn't |
| double **newm;
|
exist so I changed back to asctime which exists. |
| double agefin, delaymax=50 ; /* Max number of years to converge */
|
(Module): Version 0.96b |
|
|
|
| for (ii=1;ii<=nlstate+ndeath;ii++)
|
Revision 1.92 2003/06/25 16:30:45 brouard |
| for (j=1;j<=nlstate+ndeath;j++){
|
(Module): On windows (cygwin) function asctime_r doesn't |
| oldm[ii][j]=(ii==j ? 1.0 : 0.0);
|
exist so I changed back to asctime which exists. |
| }
|
|
|
|
Revision 1.91 2003/06/25 15:30:29 brouard |
| cov[1]=1.;
|
* imach.c (Repository): Duplicated warning errors corrected. |
|
|
(Repository): Elapsed time after each iteration is now output. It |
| /* Even if hstepm = 1, at least one multiplication by the unit matrix */
|
helps to forecast when convergence will be reached. Elapsed time |
| for(agefin=age-stepm/YEARM; agefin>=age-delaymax; agefin=agefin-stepm/YEARM){
|
is stamped in powell. We created a new html file for the graphs |
| newm=savm;
|
concerning matrix of covariance. It has extension -cov.htm. |
| /* Covariates have to be included here again */
|
|
| cov[2]=agefin;
|
Revision 1.90 2003/06/24 12:34:15 brouard |
|
|
(Module): Some bugs corrected for windows. Also, when |
| for (k=1; k<=cptcovn;k++) {
|
mle=-1 a template is output in file "or"mypar.txt with the design |
| cov[2+k]=nbcode[Tvar[k]][codtab[ij][Tvar[k]]];
|
of the covariance matrix to be input. |
| /*printf("ij=%d Tvar[k]=%d nbcode=%d cov=%lf\n",ij, Tvar[k],nbcode[Tvar[k]][codtab[ij][Tvar[k]]],cov[2+k]);*/
|
|
| }
|
Revision 1.89 2003/06/24 12:30:52 brouard |
| for (k=1; k<=cptcovage;k++)
|
(Module): Some bugs corrected for windows. Also, when |
| cov[2+Tage[k]]=cov[2+Tage[k]]*cov[2];
|
mle=-1 a template is output in file "or"mypar.txt with the design |
| for (k=1; k<=cptcovprod;k++)
|
of the covariance matrix to be input. |
| cov[2+Tprod[k]]=nbcode[Tvard[k][1]][codtab[ij][Tvard[k][1]]]*nbcode[Tvard[k][2]][codtab[ij][Tvard[k][2]]];
|
|
|
|
Revision 1.88 2003/06/23 17:54:56 brouard |
| /*printf("ij=%d cptcovprod=%d tvar=%d ", ij, cptcovprod, Tvar[1]);*/
|
* 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. |
| /*printf("ij=%d cov[3]=%lf cov[4]=%lf \n",ij, cov[3],cov[4]);*/
|
|
|
|
Revision 1.87 2003/06/18 12:26:01 brouard |
| out=matprod2(newm, pmij(pmmij,cov,ncovmodel,x,nlstate),1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm);
|
Version 0.96 |
|
|
|
| savm=oldm;
|
Revision 1.86 2003/06/17 20:04:08 brouard |
| oldm=newm;
|
(Module): Change position of html and gnuplot routines and added |
| maxmax=0.;
|
routine fileappend. |
| for(j=1;j<=nlstate;j++){
|
|
| min=1.;
|
Revision 1.85 2003/06/17 13:12:43 brouard |
| max=0.;
|
* imach.c (Repository): Check when date of death was earlier that |
| for(i=1; i<=nlstate; i++) {
|
current date of interview. It may happen when the death was just |
| sumnew=0;
|
prior to the death. In this case, dh was negative and likelihood |
| for(k=1; k<=ndeath; k++) sumnew+=newm[i][nlstate+k];
|
was wrong (infinity). We still send an "Error" but patch by |
| prlim[i][j]= newm[i][j]/(1-sumnew);
|
assuming that the date of death was just one stepm after the |
| max=FMAX(max,prlim[i][j]);
|
interview. |
| min=FMIN(min,prlim[i][j]);
|
(Repository): Because some people have very long ID (first column) |
| }
|
we changed int to long in num[] and we added a new lvector for |
| maxmin=max-min;
|
memory allocation. But we also truncated to 8 characters (left |
| maxmax=FMAX(maxmax,maxmin);
|
truncation) |
| }
|
(Repository): No more line truncation errors. |
| if(maxmax < ftolpl){
|
|
| return prlim;
|
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. |
| /*************** transition probabilities **********/
|
Version 0.95a3 (should output exactly the same maximization than 0.8a2) |
|
|
|
| double **pmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate )
|
Revision 1.83 2003/06/10 13:39:11 lievre |
| {
|
*** empty log message *** |
| double s1, s2;
|
|
| /*double t34;*/
|
Revision 1.82 2003/06/05 15:57:20 brouard |
| int i,j,j1, nc, ii, jj;
|
Add log in imach.c and fullversion number is now printed. |
|
|
|
| for(i=1; i<= nlstate; i++){
|
*/ |
| for(j=1; j<i;j++){
|
/* |
| for (nc=1, s2=0.;nc <=ncovmodel; nc++){
|
Interpolated Markov Chain |
| /*s2 += param[i][j][nc]*cov[nc];*/
|
|
| s2 += x[(i-1)*nlstate*ncovmodel+(j-1)*ncovmodel+nc+(i-1)*(ndeath-1)*ncovmodel]*cov[nc];
|
Short summary of the programme: |
| /*printf("Int j<i s1=%.17e, s2=%.17e\n",s1,s2);*/
|
|
| }
|
This program computes Healthy Life Expectancies or State-specific |
| ps[i][j]=s2;
|
(if states aren't health statuses) Expectancies from |
| /*printf("s1=%.17e, s2=%.17e\n",s1,s2);*/
|
cross-longitudinal data. Cross-longitudinal data consist in: |
| }
|
|
| for(j=i+1; j<=nlstate+ndeath;j++){
|
-1- a first survey ("cross") where individuals from different ages |
| for (nc=1, s2=0.;nc <=ncovmodel; nc++){
|
are interviewed on their health status or degree of disability (in |
| s2 += x[(i-1)*nlstate*ncovmodel+(j-2)*ncovmodel+nc+(i-1)*(ndeath-1)*ncovmodel]*cov[nc];
|
the case of a health survey which is our main interest) |
| /*printf("Int j>i s1=%.17e, s2=%.17e %lx %lx\n",s1,s2,s1,s2);*/
|
|
| }
|
-2- at least a second wave of interviews ("longitudinal") which |
| ps[i][j]=s2;
|
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 |
| for(i=1; i<= nlstate; i++){
|
necessary to reach the Maximum Likelihood of the parameters involved |
| s1=0;
|
in the model. The simplest model is the multinomial logistic model |
| for(j=1; j<i; j++)
|
where pij is the probability to be observed in state j at the second |
| s1+=exp(ps[i][j]);
|
wave conditional to be observed in state i at the first |
| for(j=i+1; j<=nlstate+ndeath; j++)
|
wave. Therefore the model is: log(pij/pii)= aij + bij*age+ cij*sex + |
| s1+=exp(ps[i][j]);
|
etc , where 'age' is age and 'sex' is a covariate. If you want to |
| ps[i][i]=1./(s1+1.);
|
have a more complex model than "constant and age", you should modify |
| for(j=1; j<i; j++)
|
the program where the markup *Covariates have to be included here |
| ps[i][j]= exp(ps[i][j])*ps[i][i];
|
again* invites you to do it. More covariates you add, slower the |
| for(j=i+1; j<=nlstate+ndeath; j++)
|
convergence. |
| ps[i][j]= exp(ps[i][j])*ps[i][i];
|
|
| /* ps[i][nlstate+1]=1.-s1- ps[i][i];*/ /* Sum should be 1 */
|
The advantage of this computer programme, compared to a simple |
| } /* end i */
|
multinomial logistic model, is clear when the delay between waves is not |
|
|
identical for each individual. Also, if a individual missed an |
| for(ii=nlstate+1; ii<= nlstate+ndeath; ii++){
|
intermediate interview, the information is lost, but taken into |
| for(jj=1; jj<= nlstate+ndeath; jj++){
|
account using an interpolation or extrapolation. |
| ps[ii][jj]=0;
|
|
| ps[ii][ii]=1;
|
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, |
| /* for(ii=1; ii<= nlstate+ndeath; ii++){
|
semester or year) is modelled as a multinomial logistic. The hPx |
| for(jj=1; jj<= nlstate+ndeath; jj++){
|
matrix is simply the matrix product of nh*stepm elementary matrices |
| printf("%lf ",ps[ii][jj]);
|
and the contribution of each individual to the likelihood is simply |
| }
|
hPijx. |
| printf("\n ");
|
|
| }
|
Also this programme outputs the covariance matrix of the parameters but also |
| printf("\n ");printf("%lf ",cov[2]);*/
|
of the life expectancies. It also computes the period (stable) prevalence. |
| /*
|
|
| for(i=1; i<= npar; i++) printf("%f ",x[i]);
|
Back prevalence and projections: |
| goto end;*/
|
|
| return ps;
|
- back_prevalence_limit(double *p, double **bprlim, double ageminpar, |
| }
|
double agemaxpar, double ftolpl, int *ncvyearp, double |
|
|
dateprev1,double dateprev2, int firstpass, int lastpass, int |
| /**************** Product of 2 matrices ******************/
|
mobilavproj) |
|
|
|
| double **matprod2(double **out, double **in,long nrl, long nrh, long ncl, long nch, long ncolol, long ncoloh, double **b)
|
Computes the back prevalence limit for any combination of |
| {
|
covariate values k at any age between ageminpar and agemaxpar and |
| /* Computes the matric product of in(1,nrh-nrl+1)(1,nch-ncl+1) times
|
returns it in **bprlim. In the loops, |
| b(1,nch-ncl+1)(1,ncoloh-ncolol+1) into out(...) */
|
|
| /* in, b, out are matrice of pointers which should have been initialized
|
- **bprevalim(**bprlim, ***mobaverage, nlstate, *p, age, **oldm, |
| before: only the contents of out is modified. The function returns
|
**savm, **dnewm, **doldm, **dsavm, ftolpl, ncvyearp, k); |
| a pointer to pointers identical to out */
|
|
| long i, j, k;
|
- hBijx Back Probability to be in state i at age x-h being in j at x |
| for(i=nrl; i<= nrh; i++)
|
Computes for any combination of covariates k and any age between bage and fage |
| for(k=ncolol; k<=ncoloh; k++)
|
p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); |
| for(j=ncl,out[i][k]=0.; j<=nch; j++)
|
oldm=oldms;savm=savms; |
| out[i][k] +=in[i][j]*b[j][k];
|
|
|
|
- hbxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k); |
| return out;
|
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. |
| /************* Higher Matrix Product ***************/
|
|
|
|
Returns p3mat[i][j][h] after calling |
| double ***hpxij(double ***po, int nhstepm, double age, int hstepm, double *x, int nlstate, int stepm, double **oldm, double **savm, int ij )
|
p3mat[i][j][h]=matprod2(newm, |
| {
|
bmij(pmmij,cov,ncovmodel,x,nlstate,prevacurrent, dnewm, doldm, |
| /* Computes the transition matrix starting at age 'age' over 'nhstepm*hstepm*stepm' month
|
dsavm,ij),\ 1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, |
| duration (i.e. until
|
oldm); |
| age (in years) age+nhstepm*stepm/12) by multiplying nhstepm*hstepm matrices.
|
|
| Output is stored in matrix po[i][j][h] for h every 'hstepm' step
|
Important routines |
| (typically every 2 years instead of every month which is too big).
|
|
| Model is determined by parameters x and covariates have to be
|
- func (or funcone), computes logit (pij) distinguishing |
| included manually here.
|
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: |
| int i, j, d, h, k;
|
% fixed dummy (treated) or quantitative (not done because time-consuming); |
| double **out, cov[NCOVMAX];
|
% varying dummy (not done) or quantitative (not done); |
| double **newm;
|
- 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. |
| /* Hstepm could be zero and should return the unit matrix */
|
- printinghtml which outputs results like life expectancy in and from a state for a combination of modalities of dummy variables |
| for (i=1;i<=nlstate+ndeath;i++)
|
o There are 2*cptcoveff combinations of (0,1) for cptcoveff variables. Outputting only combinations with people, éliminating 1 1 if |
| for (j=1;j<=nlstate+ndeath;j++){
|
race White (0 0), Black vs White (1 0), Hispanic (0 1) and 1 1 being meaningless. |
| 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 */
|
Authors: Nicolas Brouard (brouard@ined.fr) and Agnès Lièvre (lievre@ined.fr). |
| for(h=1; h <=nhstepm; h++){
|
Institut national d'études démographiques, Paris. |
| for(d=1; d <=hstepm; d++){
|
This software have been partly granted by Euro-REVES, a concerted action |
| newm=savm;
|
from the European Union. |
| /* Covariates have to be included here again */
|
It is copyrighted identically to a GNU software product, ie programme and |
| cov[1]=1.;
|
software can be distributed freely for non commercial use. Latest version |
| cov[2]=age+((h-1)*hstepm + (d-1))*stepm/YEARM;
|
can be accessed at http://euroreves.ined.fr/imach . |
| for (k=1; k<=cptcovn;k++) cov[2+k]=nbcode[Tvar[k]][codtab[ij][Tvar[k]]];
|
|
| for (k=1; k<=cptcovage;k++)
|
Help to debug: LD_PRELOAD=/usr/local/lib/libnjamd.so ./imach foo.imach |
| cov[2+Tage[k]]=cov[2+Tage[k]]*cov[2];
|
or better on gdb : set env LD_PRELOAD=/usr/local/lib/libnjamd.so |
| for (k=1; k<=cptcovprod;k++)
|
|
| cov[2+Tprod[k]]=nbcode[Tvard[k][1]][codtab[ij][Tvard[k][1]]]*nbcode[Tvard[k][2]][codtab[ij][Tvard[k][2]]];
|
**********************************************************************/ |
|
|
/* |
|
|
main |
| /*printf("hxi cptcov=%d cptcode=%d\n",cptcov,cptcode);*/
|
read parameterfile |
| /*printf("h=%d d=%d age=%f cov=%f\n",h,d,age,cov[2]);*/
|
read datafile |
| out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath,
|
concatwav |
| pmij(pmmij,cov,ncovmodel,x,nlstate));
|
freqsummary |
| savm=oldm;
|
if (mle >= 1) |
| oldm=newm;
|
mlikeli |
| }
|
print results files |
| for(i=1; i<=nlstate+ndeath; i++)
|
if mle==1 |
| for(j=1;j<=nlstate+ndeath;j++) {
|
computes hessian |
| po[i][j][h]=newm[i][j];
|
read end of parameter file: agemin, agemax, bage, fage, estepm |
| /*printf("i=%d j=%d h=%d po[i][j][h]=%f ",i,j,h,po[i][j][h]);
|
begin-prev-date,... |
| */
|
open gnuplot file |
| }
|
open html file |
| } /* end h */
|
period (stable) prevalence | pl_nom 1-1 2-2 etc by covariate |
| return po;
|
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. |
|
|
|
| /*************** log-likelihood *************/
|
h Pij x | pij_nom ficrestpij |
| double func( double *x)
|
# 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 |
| int i, ii, j, k, mi, d, kk;
|
1 85 86 0.68299 0.22291 0.09410 0.71093 0.00000 0.28907 |
| double l, ll[NLSTATEMAX], cov[NCOVMAX];
|
|
| double **out;
|
1 65 99 0.00364 0.00322 0.99314 0.00350 0.00310 0.99340 |
| double sw; /* Sum of weights */
|
1 65 100 0.00214 0.00204 0.99581 0.00206 0.00196 0.99597 |
| double lli; /* Individual log likelihood */
|
variance of p one-step probabilities varprob | prob_nom ficresprob #One-step probabilities and stand. devi in () |
| long ipmx;
|
Standard deviation of one-step probabilities | probcor_nom ficresprobcor #One-step probabilities and correlation matrix |
| /*extern weight */
|
Matrix of variance covariance of one-step probabilities | probcov_nom ficresprobcov #One-step probabilities and covariance matrix |
| /* We are differentiating ll according to initial status */
|
|
| /* for (i=1;i<=npar;i++) printf("%f ", x[i]);*/
|
forecasting if prevfcast==1 prevforecast call prevalence() |
| /*for(i=1;i<imx;i++)
|
health expectancies |
| printf(" %d\n",s[4][i]);
|
Variance-covariance of DFLE |
| */
|
prevalence() |
| cov[1]=1.;
|
movingaverage() |
|
|
varevsij() |
| for(k=1; k<=nlstate; k++) ll[k]=0.;
|
if popbased==1 varevsij(,popbased) |
| for (i=1,ipmx=0, sw=0.; i<=imx; i++){
|
total life expectancies |
| for (k=1; k<=cptcovn;k++) cov[2+k]=covar[Tvar[k]][i];
|
Variance of period (stable) prevalence |
| for(mi=1; mi<= wav[i]-1; mi++){
|
end |
| 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++){
|
/* #define DEBUG */ |
| newm=savm;
|
/* #define DEBUGBRENT */ |
| cov[2]=agev[mw[mi][i]][i]+d*stepm/YEARM;
|
/* #define DEBUGLINMIN */ |
| for (kk=1; kk<=cptcovage;kk++) {
|
/* #define DEBUGHESS */ |
| cov[Tage[kk]+2]=covar[Tvar[Tage[kk]]][i]*cov[2];
|
#define DEBUGHESSIJ |
| }
|
/* #define LINMINORIGINAL /\* Don't use loop on scale in linmin (accepting nan) *\/ */ |
|
|
#define POWELL /* Instead of NLOPT */ |
| out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
|
#define POWELLNOF3INFF1TEST /* Skip test */ |
| 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
|
/* #define POWELLORIGINAL /\* Don't use Directest to decide new direction but original Powell test *\/ */ |
| savm=oldm;
|
/* #define MNBRAKORIGINAL /\* Don't use mnbrak fix *\/ */ |
| oldm=newm;
|
|
|
|
#include <math.h> |
|
|
#include <stdio.h> |
| } /* end mult */
|
#include <stdlib.h> |
|
|
#include <string.h> |
| lli=log(out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]);
|
#include <ctype.h> |
| /* printf(" %f ",out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]);*/
|
|
| ipmx +=1;
|
#ifdef _WIN32 |
| sw += weight[i];
|
#include <io.h> |
| ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
|
#include <windows.h> |
| } /* end of wave */
|
#include <tchar.h> |
| } /* end of individual */
|
#else |
|
|
#include <unistd.h> |
| for(k=1,l=0.; k<=nlstate; k++) l += ll[k];
|
#endif |
| /* 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 */
|
#include <limits.h> |
| return -l;
|
#include <sys/types.h> |
| }
|
|
|
|
#if defined(__GNUC__) |
|
|
#include <sys/utsname.h> /* Doesn't work on Windows */ |
| /*********** Maximum Likelihood Estimation ***************/
|
#endif |
|
|
|
| void mlikeli(FILE *ficres,double p[], int npar, int ncovmodel, int nlstate, double ftol, double (*func)(double []))
|
#include <sys/stat.h> |
| {
|
#include <errno.h> |
| int i,j, iter;
|
/* extern int errno; */ |
| double **xi,*delti;
|
|
| double fret;
|
/* #ifdef LINUX */ |
| xi=matrix(1,npar,1,npar);
|
/* #include <time.h> */ |
| for (i=1;i<=npar;i++)
|
/* #include "timeval.h" */ |
| for (j=1;j<=npar;j++)
|
/* #else */ |
| xi[i][j]=(i==j ? 1.0 : 0.0);
|
/* #include <sys/time.h> */ |
| printf("Powell\n");
|
/* #endif */ |
| powell(p,xi,npar,ftol,&iter,&fret,func);
|
|
|
|
#include <time.h> |
| 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 GSL |
|
|
#include <gsl/gsl_errno.h> |
| }
|
#include <gsl/gsl_multimin.h> |
|
|
#endif |
| /**** Computes Hessian and covariance matrix ***/
|
|
| void hesscov(double **matcov, double p[], int npar, double delti[], double ftolhess, double (*func)(double []))
|
|
| {
|
#ifdef NLOPT |
| double **a,**y,*x,pd;
|
#include <nlopt.h> |
| double **hess;
|
typedef struct { |
| int i, j,jk;
|
double (* function)(double [] ); |
| int *indx;
|
} myfunc_data ; |
|
|
#endif |
| double hessii(double p[], double delta, int theta, double delti[]);
|
|
| double hessij(double p[], double delti[], int i, int j);
|
/* #include <libintl.h> */ |
| void lubksb(double **a, int npar, int *indx, double b[]) ;
|
/* #define _(String) gettext (String) */ |
| void ludcmp(double **a, int npar, int *indx, double *d) ;
|
|
|
|
#define MAXLINE 1024 /* Was 256. Overflow with 312 with 2 states and 4 covariates. Should be ok */ |
|
|
|
| hess=matrix(1,npar,1,npar);
|
#define GNUPLOTPROGRAM "gnuplot" |
|
|
/*#define GNUPLOTPROGRAM "..\\gp37mgw\\wgnuplot"*/ |
| printf("\nCalculation of the hessian matrix. Wait...\n");
|
#define FILENAMELENGTH 132 |
| for (i=1;i<=npar;i++){
|
|
| printf("%d",i);fflush(stdout);
|
#define GLOCK_ERROR_NOPATH -1 /* empty path */ |
| hess[i][i]=hessii(p,ftolhess,i,delti);
|
#define GLOCK_ERROR_GETCWD -2 /* cannot get cwd */ |
| /*printf(" %f ",p[i]);*/
|
|
| }
|
#define MAXPARM 128 /**< Maximum number of parameters for the optimization */ |
|
|
#define NPARMAX 64 /**< (nlstate+ndeath-1)*nlstate*ncovmodel */ |
| for (i=1;i<=npar;i++) {
|
|
| for (j=1;j<=npar;j++) {
|
#define NINTERVMAX 8 |
| if (j>i) {
|
#define NLSTATEMAX 8 /**< Maximum number of live states (for func) */ |
| printf(".%d%d",i,j);fflush(stdout);
|
#define NDEATHMAX 8 /**< Maximum number of dead states (for func) */ |
| hess[i][j]=hessij(p,delti,i,j);
|
#define NCOVMAX 20 /**< Maximum number of covariates, including generated covariates V1*V2 */ |
| hess[j][i]=hess[i][j];
|
#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 |
| printf("\n");
|
#define YEARM 12. /**< Number of months per year */ |
|
|
/* #define AGESUP 130 */ |
| printf("\nInverting the hessian to get the covariance matrix. Wait...\n");
|
#define AGESUP 150 |
|
|
#define AGEMARGE 25 /* Marge for agemin and agemax for(iage=agemin-AGEMARGE; iage <= agemax+3+AGEMARGE; iage++) */ |
| a=matrix(1,npar,1,npar);
|
#define AGEBASE 40 |
| y=matrix(1,npar,1,npar);
|
#define AGEOVERFLOW 1.e20 |
| x=vector(1,npar);
|
#define AGEGOMP 10 /**< Minimal age for Gompertz adjustment */ |
| indx=ivector(1,npar);
|
#ifdef _WIN32 |
| for (i=1;i<=npar;i++)
|
#define DIRSEPARATOR '\\' |
| for (j=1;j<=npar;j++) a[i][j]=hess[i][j];
|
#define CHARSEPARATOR "\\" |
| ludcmp(a,npar,indx,&pd);
|
#define ODIRSEPARATOR '/' |
|
|
#else |
| for (j=1;j<=npar;j++) {
|
#define DIRSEPARATOR '/' |
| for (i=1;i<=npar;i++) x[i]=0;
|
#define CHARSEPARATOR "/" |
| x[j]=1;
|
#define ODIRSEPARATOR '\\' |
| lubksb(a,npar,indx,x);
|
#endif |
| for (i=1;i<=npar;i++){
|
|
| matcov[i][j]=x[i];
|
/* $Id$ */ |
| }
|
/* $State$ */ |
| }
|
#include "version.h" |
|
|
char version[]=__IMACH_VERSION__; |
| printf("\n#Hessian matrix#\n");
|
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"; |
| for (i=1;i<=npar;i++) {
|
char fullversion[]="$Revision$ $Date$"; |
| for (j=1;j<=npar;j++) {
|
char strstart[80]; |
| printf("%.3e ",hess[i][j]);
|
char optionfilext[10], optionfilefiname[FILENAMELENGTH]; |
| }
|
int erreur=0, nberr=0, nbwarn=0; /* Error number, number of errors number of warnings */ |
| printf("\n");
|
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) */ |
| /* Recompute Inverse */
|
int cptcovt=0; /**< cptcovt number of covariates added in the model (excepting constant and age) */ |
| for (i=1;i<=npar;i++)
|
int cptcovs=0; /**< cptcovs number of simple covariates in the model V2+V1 =2 */ |
| for (j=1;j<=npar;j++) a[i][j]=matcov[i][j];
|
int cptcovsnq=0; /**< cptcovsnq number of simple covariates in the model but non quantitative V2+V1 =2 */ |
| ludcmp(a,npar,indx,&pd);
|
int cptcovage=0; /**< Number of covariates with age: V3*age only =1 */ |
|
|
int cptcovprodnoage=0; /**< Number of covariate products without age */ |
| /* printf("\n#Hessian matrix recomputed#\n");
|
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 */ |
| for (j=1;j<=npar;j++) {
|
int ncovv=0; /* Total number of effective (wave) varying covariates (dummy or quantitative) in the model */ |
| for (i=1;i<=npar;i++) x[i]=0;
|
int ncova=0; /* Total number of effective (wave and stepm) varying with age covariates (dummy of quantitative) in the model */ |
| x[j]=1;
|
int nsd=0; /**< Total number of single dummy variables (output) */ |
| lubksb(a,npar,indx,x);
|
int nsq=0; /**< Total number of single quantitative variables (output) */ |
| for (i=1;i<=npar;i++){
|
int ncoveff=0; /* Total number of effective fixed dummy covariates in the model */ |
| y[i][j]=x[i];
|
int nqfveff=0; /**< nqfveff Number of Quantitative Fixed Variables Effective */ |
| printf("%.3e ",y[i][j]);
|
int ntveff=0; /**< ntveff number of effective time varying variables */ |
| }
|
int nqtveff=0; /**< ntqveff number of effective time varying quantitative variables */ |
| printf("\n");
|
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 */ |
| free_matrix(a,1,npar,1,npar);
|
int ndeath=1; /* Number of dead states */ |
| free_matrix(y,1,npar,1,npar);
|
int ncovmodel=0, ncovcol=0; /* Total number of covariables including constant a12*1 +b12*x ncovmodel=2 */ |
| free_vector(x,1,npar);
|
int nqv=0, ntv=0, nqtv=0; /* Total number of quantitative variables, time variable (dummy), quantitative and time variable */ |
| free_ivector(indx,1,npar);
|
int popbased=0; |
| free_matrix(hess,1,npar,1,npar);
|
|
|
|
int *wav; /* Number of waves for this individuual 0 is possible */ |
|
|
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 */ |
| /*************** hessian matrix ****************/
|
int gipmx=0, gsw=0; /* Global variables on the number of contributions |
| double hessii( double x[], double delta, int theta, double delti[])
|
to the likelihood and the sum of weights (done by funcone)*/ |
| {
|
int mle=1, weightopt=0; |
| int i;
|
int **mw; /* mw[mi][i] is number of the mi wave for this individual */ |
| int l=1, lmax=20;
|
int **dh; /* dh[mi][i] is number of steps between mi,mi+1 for this individual */ |
| double k1,k2;
|
int **bh; /* bh[mi][i] is the bias (+ or -) for this individual if the delay between |
| double p2[NPARMAX+1];
|
* wave mi and wave mi+1 is not an exact multiple of stepm. */ |
| double res;
|
int countcallfunc=0; /* Count the number of calls to func */ |
| double delt, delts, nkhi=10.,nkhif=1., khi=1.e-4;
|
int selected(int kvar); /* Is covariate kvar selected for printing results */ |
| double fx;
|
|
| int k=0,kmax=10;
|
double jmean=1; /* Mean space between 2 waves */ |
| double l1;
|
double **matprod2(); /* test */ |
|
|
double **oldm, **newm, **savm; /* Working pointers to matrices */ |
| fx=func(x);
|
double **oldms, **newms, **savms; /* Fixed working pointers to matrices */ |
| for (i=1;i<=npar;i++) p2[i]=x[i];
|
double **ddnewms, **ddoldms, **ddsavms; /* for freeing later */ |
| for(l=0 ; l <=lmax; l++){
|
|
| l1=pow(10,l);
|
/*FILE *fic ; */ /* Used in readdata only */ |
| delts=delt;
|
FILE *ficpar, *ficparo,*ficres, *ficresp, *ficresphtm, *ficresphtmfr, *ficrespl, *ficresplb,*ficrespij, *ficrespijb, *ficrest,*ficresf, *ficresfb,*ficrespop; |
| for(k=1 ; k <kmax; k=k+1){
|
FILE *ficlog, *ficrespow; |
| delt = delta*(l1*k);
|
int globpr=0; /* Global variable for printing or not */ |
| p2[theta]=x[theta] +delt;
|
double fretone; /* Only one call to likelihood */ |
| k1=func(p2)-fx;
|
long ipmx=0; /* Number of contributions */ |
| p2[theta]=x[theta]-delt;
|
double sw; /* Sum of weights */ |
| k2=func(p2)-fx;
|
char filerespow[FILENAMELENGTH]; |
| /*res= (k1-2.0*fx+k2)/delt/delt; */
|
char fileresilk[FILENAMELENGTH]; /* File of individual contributions to the likelihood */ |
| res= (k1+k2)/delt/delt/2.; /* Divided by because L and not 2*L */
|
FILE *ficresilk; |
|
|
FILE *ficgp,*ficresprob,*ficpop, *ficresprobcov, *ficresprobcor; |
| #ifdef DEBUG
|
FILE *ficresprobmorprev; |
| 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);
|
FILE *fichtm, *fichtmcov; /* Html File */ |
| #endif
|
FILE *ficreseij; |
| /*if(fabs(k1-2.0*fx+k2) <1.e-13){ */
|
char filerese[FILENAMELENGTH]; |
| if((k1 <khi/nkhi/2.) || (k2 <khi/nkhi/2.)){
|
FILE *ficresstdeij; |
| k=kmax;
|
char fileresstde[FILENAMELENGTH]; |
| }
|
FILE *ficrescveij; |
| else if((k1 >khi/nkhif) || (k2 >khi/nkhif)){ /* Keeps lastvalue before 3.84/2 KHI2 5% 1d.f. */
|
char filerescve[FILENAMELENGTH]; |
| k=kmax; l=lmax*10.;
|
FILE *ficresvij; |
| }
|
char fileresv[FILENAMELENGTH]; |
| else if((k1 >khi/nkhi) || (k2 >khi/nkhi)){
|
FILE *ficresvpl; |
| delts=delt;
|
char fileresvpl[FILENAMELENGTH]; |
| }
|
char title[MAXLINE]; |
| }
|
char model[MAXLINE]; /**< The model line */ |
| }
|
char optionfile[FILENAMELENGTH], datafile[FILENAMELENGTH], filerespl[FILENAMELENGTH], fileresplb[FILENAMELENGTH]; |
| delti[theta]=delts;
|
char plotcmd[FILENAMELENGTH], pplotcmd[FILENAMELENGTH]; |
| return res;
|
char tmpout[FILENAMELENGTH], tmpout2[FILENAMELENGTH]; |
|
|
char command[FILENAMELENGTH]; |
| }
|
int outcmd=0; |
|
|
|
| double hessij( double x[], double delti[], int thetai,int thetaj)
|
char fileres[FILENAMELENGTH], filerespij[FILENAMELENGTH], filerespijb[FILENAMELENGTH], filereso[FILENAMELENGTH], rfileres[FILENAMELENGTH]; |
| {
|
char fileresu[FILENAMELENGTH]; /* fileres without r in front */ |
| int i;
|
char filelog[FILENAMELENGTH]; /* Log file */ |
| int l=1, l1, lmax=20;
|
char filerest[FILENAMELENGTH]; |
| double k1,k2,k3,k4,res,fx;
|
char fileregp[FILENAMELENGTH]; |
| double p2[NPARMAX+1];
|
char popfile[FILENAMELENGTH]; |
| int k;
|
|
|
|
char optionfilegnuplot[FILENAMELENGTH], optionfilehtm[FILENAMELENGTH], optionfilehtmcov[FILENAMELENGTH] ; |
| fx=func(x);
|
|
| for (k=1; k<=2; k++) {
|
/* struct timeval start_time, end_time, curr_time, last_time, forecast_time; */ |
| for (i=1;i<=npar;i++) p2[i]=x[i];
|
/* struct timezone tzp; */ |
| p2[thetai]=x[thetai]+delti[thetai]/k;
|
/* extern int gettimeofday(); */ |
| p2[thetaj]=x[thetaj]+delti[thetaj]/k;
|
struct tm tml, *gmtime(), *localtime(); |
| k1=func(p2)-fx;
|
|
|
|
extern time_t time(); |
| p2[thetai]=x[thetai]+delti[thetai]/k;
|
|
| p2[thetaj]=x[thetaj]-delti[thetaj]/k;
|
struct tm start_time, end_time, curr_time, last_time, forecast_time; |
| k2=func(p2)-fx;
|
time_t rstart_time, rend_time, rcurr_time, rlast_time, rforecast_time; /* raw time */ |
|
|
struct tm tm; |
| p2[thetai]=x[thetai]-delti[thetai]/k;
|
|
| p2[thetaj]=x[thetaj]+delti[thetaj]/k;
|
char strcurr[80], strfor[80]; |
| k3=func(p2)-fx;
|
|
|
|
char *endptr; |
| p2[thetai]=x[thetai]-delti[thetai]/k;
|
long lval; |
| p2[thetaj]=x[thetaj]-delti[thetaj]/k;
|
double dval; |
| k4=func(p2)-fx;
|
|
| res=(k1-k2-k3+k4)/4.0/delti[thetai]*k/delti[thetaj]*k/2.; /* Because of L not 2*L */
|
#define NR_END 1 |
| #ifdef DEBUG
|
#define FREE_ARG char* |
| 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);
|
#define FTOL 1.0e-10 |
| #endif
|
|
| }
|
#define NRANSI |
| return res;
|
#define ITMAX 200 |
| }
|
#define ITPOWMAX 20 /* This is now multiplied by the number of parameters */ |
|
|
|
| /************** Inverse of matrix **************/
|
#define TOL 2.0e-4 |
| void ludcmp(double **a, int n, int *indx, double *d)
|
|
| {
|
#define CGOLD 0.3819660 |
| int i,imax,j,k;
|
#define ZEPS 1.0e-10 |
| double big,dum,sum,temp;
|
#define SHFT(a,b,c,d) (a)=(b);(b)=(c);(c)=(d); |
| double *vv;
|
|
|
|
#define GOLD 1.618034 |
| vv=vector(1,n);
|
#define GLIMIT 100.0 |
| *d=1.0;
|
#define TINY 1.0e-20 |
| for (i=1;i<=n;i++) {
|
|
| big=0.0;
|
static double maxarg1,maxarg2; |
| for (j=1;j<=n;j++)
|
#define FMAX(a,b) (maxarg1=(a),maxarg2=(b),(maxarg1)>(maxarg2)? (maxarg1):(maxarg2)) |
| if ((temp=fabs(a[i][j])) > big) big=temp;
|
#define FMIN(a,b) (maxarg1=(a),maxarg2=(b),(maxarg1)<(maxarg2)? (maxarg1):(maxarg2)) |
| if (big == 0.0) nrerror("Singular matrix in routine ludcmp");
|
|
| vv[i]=1.0/big;
|
#define SIGN(a,b) ((b)>0.0 ? fabs(a) : -fabs(a)) |
| }
|
#define rint(a) floor(a+0.5) |
| for (j=1;j<=n;j++) {
|
/* http://www.thphys.uni-heidelberg.de/~robbers/cmbeasy/doc/html/myutils_8h-source.html */ |
| for (i=1;i<j;i++) {
|
#define mytinydouble 1.0e-16 |
| sum=a[i][j];
|
/* #define DEQUAL(a,b) (fabs((a)-(b))<mytinydouble) */ |
| for (k=1;k<i;k++) sum -= a[i][k]*a[k][j];
|
/* http://www.thphys.uni-heidelberg.de/~robbers/cmbeasy/doc/html/mynrutils_8h-source.html */ |
| a[i][j]=sum;
|
/* static double dsqrarg; */ |
| }
|
/* #define DSQR(a) (DEQUAL((dsqrarg=(a)),0.0) ? 0.0 : dsqrarg*dsqrarg) */ |
| big=0.0;
|
static double sqrarg; |
| for (i=j;i<=n;i++) {
|
#define SQR(a) ((sqrarg=(a)) == 0.0 ? 0.0 :sqrarg*sqrarg) |
| sum=a[i][j];
|
#define SWAP(a,b) {temp=(a);(a)=(b);(b)=temp;} |
| for (k=1;k<j;k++)
|
int agegomp= AGEGOMP; |
| sum -= a[i][k]*a[k][j];
|
|
| a[i][j]=sum;
|
int imx; |
| if ( (dum=vv[i]*fabs(sum)) >= big) {
|
int stepm=1; |
| big=dum;
|
/* Stepm, step in month: minimum step interpolation*/ |
| imax=i;
|
|
| }
|
int estepm; |
| }
|
/* Estepm, step in month to interpolate survival function in order to approximate Life Expectancy*/ |
| if (j != imax) {
|
|
| for (k=1;k<=n;k++) {
|
int m,nb; |
| dum=a[imax][k];
|
long *num; |
| a[imax][k]=a[j][k];
|
int firstpass=0, lastpass=4,*cod, *cens; |
| a[j][k]=dum;
|
int *ncodemax; /* ncodemax[j]= Number of modalities of the j th |
| }
|
covariate for which somebody answered excluding |
| *d = -(*d);
|
undefined. Usually 2: 0 and 1. */ |
| vv[imax]=vv[j];
|
int *ncodemaxwundef; /* ncodemax[j]= Number of modalities of the j th |
| }
|
covariate for which somebody answered including |
| indx[j]=imax;
|
undefined. Usually 3: -1, 0 and 1. */ |
| if (a[j][j] == 0.0) a[j][j]=TINY;
|
double **agev,*moisnais, *annais, *moisdc, *andc,**mint, **anint; |
| if (j != n) {
|
double **pmmij, ***probs; /* Global pointer */ |
| dum=1.0/(a[j][j]);
|
double ***mobaverage, ***mobaverages; /* New global variable */ |
| for (i=j+1;i<=n;i++) a[i][j] *= dum;
|
double *ageexmed,*agecens; |
| }
|
double dateintmean=0; |
| }
|
|
| free_vector(vv,1,n); /* Doesn't work */
|
double *weight; |
| ;
|
int **s; /* Status */ |
| }
|
double *agedc; |
|
|
double **covar; /**< covar[j,i], value of jth covariate for individual i, |
| void lubksb(double **a, int n, int *indx, double b[])
|
* covar=matrix(0,NCOVMAX,1,n); |
| {
|
* cov[Tage[kk]+2]=covar[Tvar[Tage[kk]]][i]*age; */ |
| int i,ii=0,ip,j;
|
double **coqvar; /* Fixed quantitative covariate iqv */ |
| double sum;
|
double ***cotvar; /* Time varying covariate itv */ |
|
|
double ***cotqvar; /* Time varying quantitative covariate itqv */ |
| for (i=1;i<=n;i++) {
|
double idx; |
| ip=indx[i];
|
int **nbcode, *Tvar; /**< model=V2 => Tvar[1]= 2 */ |
| sum=b[ip];
|
/* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ |
| b[ip]=b[i];
|
/*k 1 2 3 4 5 6 7 8 9 */ |
| if (ii)
|
/*Tvar[k]= 5 4 3 6 5 2 7 1 1 */ |
| for (j=ii;j<=i-1;j++) sum -= a[i][j]*b[j];
|
/* Tndvar[k] 1 2 3 4 5 */ |
| else if (sum) ii=i;
|
/*TDvar 4 3 6 7 1 */ /* For outputs only; combination of dummies fixed or varying */ |
| b[i]=sum;
|
/* Tns[k] 1 2 2 4 5 */ /* Number of single cova */ |
| }
|
/* TvarsD[k] 1 2 3 */ /* Number of single dummy cova */ |
| for (i=n;i>=1;i--) {
|
/* TvarsDind 2 3 9 */ /* position K of single dummy cova */ |
| sum=b[i];
|
/* TvarsQ[k] 1 2 */ /* Number of single quantitative cova */ |
| for (j=i+1;j<=n;j++) sum -= a[i][j]*b[j];
|
/* TvarsQind 1 6 */ /* position K of single quantitative cova */ |
| b[i]=sum/a[i][i];
|
/* Tprod[i]=k 4 7 */ |
| }
|
/* Tage[i]=k 5 8 */ |
| }
|
/* */ |
|
|
/* Type */ |
| /************ Frequencies ********************/
|
/* V 1 2 3 4 5 */ |
| void freqsummary(char fileres[], int agemin, int agemax, int **s, double **agev, int nlstate, int imx, int *Tvar, int **nbcode, int *ncodemax)
|
/* F F V V V */ |
| { /* Some frequencies */
|
/* D Q D D Q */ |
|
|
/* */ |
| int i, m, jk, k1, i1, j1, bool, z1,z2,j;
|
int *TvarsD; |
| double ***freq; /* Frequencies */
|
int *TvarsDind; |
| double *pp;
|
int *TvarsQ; |
| double pos;
|
int *TvarsQind; |
| FILE *ficresp;
|
|
| char fileresp[FILENAMELENGTH];
|
#define MAXRESULTLINES 10 |
|
|
int nresult=0; |
| pp=vector(1,nlstate);
|
int TKresult[MAXRESULTLINES]; |
|
|
int Tresult[MAXRESULTLINES][NCOVMAX];/* For dummy variable , value (output) */ |
| strcpy(fileresp,"p");
|
int Tinvresult[MAXRESULTLINES][NCOVMAX];/* For dummy variable , value (output) */ |
| strcat(fileresp,fileres);
|
int Tvresult[MAXRESULTLINES][NCOVMAX]; /* For dummy variable , variable # (output) */ |
| if((ficresp=fopen(fileresp,"w"))==NULL) {
|
double Tqresult[MAXRESULTLINES][NCOVMAX]; /* For quantitative variable , value (output) */ |
| printf("Problem with prevalence resultfile: %s\n", fileresp);
|
double Tqinvresult[MAXRESULTLINES][NCOVMAX]; /* For quantitative variable , value (output) */ |
| exit(0);
|
int Tvqresult[MAXRESULTLINES][NCOVMAX]; /* For quantitative variable , variable # (output) */ |
| }
|
|
| freq= ma3x(-1,nlstate+ndeath,-1,nlstate+ndeath,agemin,agemax+3);
|
/* 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 *\/ */ |
| j1=0;
|
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 */ |
| j=cptcoveff;
|
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 */ |
| if (cptcovn<1) {j=1;ncodemax[1]=1;}
|
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 */ |
| for(k1=1; k1<=j;k1++){
|
int *TvarAind; /**< TvarindA[1]=5, TvarAind[2]=8 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ |
| for(i1=1; i1<=ncodemax[k1];i1++){
|
int *TvarFD; /**< TvarFD[1]=V1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ |
| j1++;
|
int *TvarFDind; /* TvarFDind[1]=9 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ |
| /*printf("cptcoveff=%d Tvaraff=%d", cptcoveff,Tvaraff[1]);
|
int *TvarFQ; /* TvarFQ[1]=V2 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */ |
| scanf("%d", i);*/
|
int *TvarFQind; /* TvarFQind[1]=6 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */ |
| for (i=-1; i<=nlstate+ndeath; i++)
|
int *TvarVD; /* TvarVD[1]=V5 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */ |
| for (jk=-1; jk<=nlstate+ndeath; jk++)
|
int *TvarVDind; /* TvarVDind[1]=1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */ |
| for(m=agemin; m <= agemax+3; m++)
|
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 */ |
| freq[i][jk][m]=0;
|
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 */ |
|
|
|
| for (i=1; i<=imx; i++) {
|
int *Tvarsel; /**< Selected covariates for output */ |
| bool=1;
|
double *Tvalsel; /**< Selected modality value of covariate for output */ |
| if (cptcovn>0) {
|
int *Typevar; /**< 0 for simple covariate (dummy, quantitative, fixed or varying), 1 for age product, 2 for product */ |
| for (z1=1; z1<=cptcoveff; z1++)
|
int *Fixed; /** Fixed[k] 0=fixed, 1 varying, 2 fixed with age product, 3 varying with age product */ |
| if (covar[Tvaraff[z1]][i]!= nbcode[Tvaraff[z1]][codtab[j1][z1]])
|
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 */ |
| bool=0;
|
int *DummyV; /** Dummy[v] 0=dummy (0 1), 1 quantitative */ |
| }
|
int *FixedV; /** FixedV[v] 0 fixed, 1 varying */ |
| if (bool==1) {
|
int *Tage; |
| for(m=firstpass; m<=lastpass-1; m++){
|
int anyvaryingduminmodel=0; /**< Any varying dummy in Model=1 yes, 0 no, to avoid a loop on waves in freq */ |
| if(agev[m][i]==0) agev[m][i]=agemax+1;
|
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*/ |
| if(agev[m][i]==1) agev[m][i]=agemax+2;
|
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*/ |
| freq[s[m][i]][s[m+1][i]][(int)agev[m][i]] += weight[i];
|
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 */ |
| freq[s[m][i]][s[m+1][i]][(int) agemax+3] += weight[i];
|
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 */ |
| if (cptcovn>0) {
|
/* Tprod[k1=1]=3(=V1*V4) for V2+V1+V1*V4+age*V3 */ |
| fprintf(ficresp, "\n#********** Variable ");
|
int *Tposprod; /**< Gives the k1 product from the k position */ |
| for (z1=1; z1<=cptcoveff; z1++) fprintf(ficresp, "V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtab[j1][z1]]);
|
/* if V2+V1+V1*V4+age*V3+V3*V2 TProd[k1=2]=5 (V3*V2) */ |
| fprintf(ficresp, "**********\n#");
|
/* Tposprod[k]=k1 , Tposprod[3]=1, Tposprod[5(V3*V2)]=2 (2nd product without age) */ |
| }
|
int cptcovprod, *Tvaraff, *invalidvarcomb; |
| for(i=1; i<=nlstate;i++)
|
double *lsurv, *lpop, *tpop; |
| fprintf(ficresp, " Age Prev(%d) N(%d) N",i,i);
|
|
| fprintf(ficresp, "\n");
|
#define FD 1; /* Fixed dummy covariate */ |
|
|
#define FQ 2; /* Fixed quantitative covariate */ |
| for(i=(int)agemin; i <= (int)agemax+3; i++){
|
#define FP 3; /* Fixed product covariate */ |
| if(i==(int)agemax+3)
|
#define FPDD 7; /* Fixed product dummy*dummy covariate */ |
| printf("Total");
|
#define FPDQ 8; /* Fixed product dummy*quantitative covariate */ |
| else
|
#define FPQQ 9; /* Fixed product quantitative*quantitative covariate */ |
| printf("Age %d", i);
|
#define VD 10; /* Varying dummy covariate */ |
| for(jk=1; jk <=nlstate ; jk++){
|
#define VQ 11; /* Varying quantitative covariate */ |
| for(m=-1, pp[jk]=0; m <=nlstate+ndeath ; m++)
|
#define VP 12; /* Varying product covariate */ |
| pp[jk] += freq[jk][m][i];
|
#define VPDD 13; /* Varying product dummy*dummy covariate */ |
| }
|
#define VPDQ 14; /* Varying product dummy*quantitative covariate */ |
| for(jk=1; jk <=nlstate ; jk++){
|
#define VPQQ 15; /* Varying product quantitative*quantitative covariate */ |
| for(m=-1, pos=0; m <=0 ; m++)
|
#define APFD 16; /* Age product * fixed dummy covariate */ |
| pos += freq[jk][m][i];
|
#define APFQ 17; /* Age product * fixed quantitative covariate */ |
| if(pp[jk]>=1.e-10)
|
#define APVD 18; /* Age product * varying dummy covariate */ |
| printf(" %d.=%.0f loss[%d]=%.1f%%",jk,pp[jk],jk,100*pos/pp[jk]);
|
#define APVQ 19; /* Age product * varying quantitative covariate */ |
| else
|
|
| printf(" %d.=%.0f loss[%d]=NaNQ%%",jk,pp[jk],jk);
|
#define FTYPE 1; /* Fixed covariate */ |
| }
|
#define VTYPE 2; /* Varying covariate (loop in wave) */ |
| for(jk=1; jk <=nlstate ; jk++){
|
#define ATYPE 2; /* Age product covariate (loop in dh within wave)*/ |
| for(m=1, pp[jk]=0; m <=nlstate+ndeath; m++)
|
|
| pp[jk] += freq[jk][m][i];
|
struct kmodel{ |
| }
|
int maintype; /* main type */ |
| for(jk=1,pos=0; jk <=nlstate ; jk++)
|
int subtype; /* subtype */ |
| pos += pp[jk];
|
}; |
| for(jk=1; jk <=nlstate ; jk++){
|
struct kmodel modell[NCOVMAX]; |
| if(pos>=1.e-5)
|
|
| printf(" %d.=%.0f prev[%d]=%.1f%%",jk,pp[jk],jk,100*pp[jk]/pos);
|
double ftol=FTOL; /**< Tolerance for computing Max Likelihood */ |
| else
|
double ftolhess; /**< Tolerance for computing hessian */ |
| printf(" %d.=%.0f prev[%d]=NaNQ%%",jk,pp[jk],jk);
|
|
| if( i <= (int) agemax){
|
/**************** split *************************/ |
| if(pos>=1.e-5)
|
static int split( char *path, char *dirc, char *name, char *ext, char *finame ) |
| fprintf(ficresp," %d %.5f %.0f %.0f",i,pp[jk]/pos, pp[jk],pos);
|
{ |
| else
|
/* From a file name with (full) path (either Unix or Windows) we extract the directory (dirc) |
| fprintf(ficresp," %d NaNq %.0f %.0f",i,pp[jk],pos);
|
the name of the file (name), its extension only (ext) and its first part of the name (finame) |
| }
|
*/ |
| }
|
char *ss; /* pointer */ |
| for(jk=-1; jk <=nlstate+ndeath; jk++)
|
int l1=0, l2=0; /* length counters */ |
| for(m=-1; m <=nlstate+ndeath; m++)
|
|
| if(freq[jk][m][i] !=0 ) printf(" %d%d=%.0f",jk,m,freq[jk][m][i]);
|
l1 = strlen(path ); /* length of path */ |
| if(i <= (int) agemax)
|
if ( l1 == 0 ) return( GLOCK_ERROR_NOPATH ); |
| fprintf(ficresp,"\n");
|
ss= strrchr( path, DIRSEPARATOR ); /* find last / */ |
| printf("\n");
|
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 */ |
| fclose(ficresp);
|
/* extern char* getcwd ( char *buf , int len);*/ |
| free_ma3x(freq,-1,nlstate+ndeath,-1,nlstate+ndeath,(int) agemin,(int) agemax+3);
|
#ifdef WIN32 |
| free_vector(pp,1,nlstate);
|
if (_getcwd( dirc, FILENAME_MAX ) == NULL ) { |
|
|
#else |
| } /* End of Freq */
|
if (getcwd(dirc, FILENAME_MAX) == NULL) { |
|
|
#endif |
| /************* Waves Concatenation ***************/
|
return( GLOCK_ERROR_GETCWD ); |
|
|
} |
| void concatwav(int wav[], int **dh, int **mw, int **s, double *agedc, double **agev, int firstpass, int lastpass, int imx, int nlstate, int stepm)
|
/* got dirc from getcwd*/ |
| {
|
printf(" DIRC = %s \n",dirc); |
| /* Concatenates waves: wav[i] is the number of effective (useful waves) of individual i.
|
} else { /* strip directory from path */ |
| Death is a valid wave (if date is known).
|
ss++; /* after this, the filename */ |
| mw[mi][i] is the mi (mi=1 to wav[i]) effective wave of individual i
|
l2 = strlen( ss ); /* length of filename */ |
| dh[m][i] of dh[mw[mi][i][i] is the delay between two effective waves m=mw[mi][i]
|
if ( l2 == 0 ) return( GLOCK_ERROR_NOPATH ); |
| and mw[mi+1][i]. dh depends on stepm.
|
strcpy( name, ss ); /* save file name */ |
| */
|
strncpy( dirc, path, l1 - l2 ); /* now the directory */ |
|
|
dirc[l1-l2] = '\0'; /* add zero */ |
| int i, mi, m;
|
printf(" DIRC2 = %s \n",dirc); |
| /* int j, k=0,jk, ju, jl,jmin=1e+5, jmax=-1;
|
} |
| double sum=0., jmean=0.;*/
|
/* We add a separator at the end of dirc if not exists */ |
|
|
l1 = strlen( dirc ); /* length of directory */ |
| int j, k=0,jk, ju, jl;
|
if( dirc[l1-1] != DIRSEPARATOR ){ |
| double sum=0.;
|
dirc[l1] = DIRSEPARATOR; |
| jmin=1e+5;
|
dirc[l1+1] = 0; |
| jmax=-1;
|
printf(" DIRC3 = %s \n",dirc); |
| jmean=0.;
|
} |
| for(i=1; i<=imx; i++){
|
ss = strrchr( name, '.' ); /* find last / */ |
| mi=0;
|
if (ss >0){ |
| m=firstpass;
|
ss++; |
| while(s[m][i] <= nlstate){
|
strcpy(ext,ss); /* save extension */ |
| if(s[m][i]>=1)
|
l1= strlen( name); |
| mw[++mi][i]=m;
|
l2= strlen(ss)+1; |
| if(m >=lastpass)
|
strncpy( finame, name, l1-l2); |
| break;
|
finame[l1-l2]= 0; |
| else
|
} |
| m++;
|
|
| }/* end while */
|
return( 0 ); /* we're done */ |
| if (s[m][i] > nlstate){
|
} |
| mi++; /* Death is another wave */
|
|
| /* if(mi==0) never been interviewed correctly before death */
|
|
| /* Only death is a correct wave */
|
/******************************************/ |
| mw[mi][i]=m;
|
|
| }
|
void replace_back_to_slash(char *s, char*t) |
|
|
{ |
| wav[i]=mi;
|
int i; |
| if(mi==0)
|
int lg=0; |
| printf("Warning, no any valid information for:%d line=%d\n",num[i],i);
|
i=0; |
| }
|
lg=strlen(t); |
|
|
for(i=0; i<= lg; i++) { |
| for(i=1; i<=imx; i++){
|
(s[i] = t[i]); |
| for(mi=1; mi<wav[i];mi++){
|
if (t[i]== '\\') s[i]='/'; |
| if (stepm <=0)
|
} |
| dh[mi][i]=1;
|
} |
| else{
|
|
| if (s[mw[mi+1][i]][i] > nlstate) {
|
char *trimbb(char *out, char *in) |
| if (agedc[i] < 2*AGESUP) {
|
{ /* Trim multiple blanks in line but keeps first blanks if line starts with blanks */ |
| j= rint(agedc[i]*12-agev[mw[mi][i]][i]*12);
|
char *s; |
| if(j==0) j=1; /* Survives at least one month after exam */
|
s=out; |
| k=k+1;
|
while (*in != '\0'){ |
| if (j >= jmax) jmax=j;
|
while( *in == ' ' && *(in+1) == ' '){ /* && *(in+1) != '\0'){*/ |
| if (j <= jmin) jmin=j;
|
in++; |
| sum=sum+j;
|
} |
| if (j<0) printf("j=%d num=%d ",j,i);
|
*out++ = *in++; |
| }
|
} |
| }
|
*out='\0'; |
| else{
|
return s; |
| j= rint( (agev[mw[mi+1][i]][i]*12 - agev[mw[mi][i]][i]*12));
|
} |
| k=k+1;
|
|
| if (j >= jmax) jmax=j;
|
/* char *substrchaine(char *out, char *in, char *chain) */ |
| else if (j <= jmin)jmin=j;
|
/* { */ |
| sum=sum+j;
|
/* /\* Substract chain 'chain' from 'in', return and output 'out' *\/ */ |
| }
|
/* char *s, *t; */ |
| jk= j/stepm;
|
/* t=in;s=out; */ |
| jl= j -jk*stepm;
|
/* while ((*in != *chain) && (*in != '\0')){ */ |
| ju= j -(jk+1)*stepm;
|
/* *out++ = *in++; */ |
| if(jl <= -ju)
|
/* } */ |
| dh[mi][i]=jk;
|
|
| else
|
/* /\* *in matches *chain *\/ */ |
| dh[mi][i]=jk+1;
|
/* while ((*in++ == *chain++) && (*in != '\0')){ */ |
| if(dh[mi][i]==0)
|
/* printf("*in = %c, *out= %c *chain= %c \n", *in, *out, *chain); */ |
| dh[mi][i]=1; /* At least one step */
|
/* } */ |
| }
|
/* in--; chain--; */ |
| }
|
/* while ( (*in != '\0')){ */ |
| }
|
/* printf("Bef *in = %c, *out= %c *chain= %c \n", *in, *out, *chain); */ |
| jmean=sum/k;
|
/* *out++ = *in++; */ |
| printf("Delay (in months) between two waves Min=%d Max=%d Mean=%f\n\n ",jmin, jmax,jmean);
|
/* printf("Aft *in = %c, *out= %c *chain= %c \n", *in, *out, *chain); */ |
| }
|
/* } */ |
| /*********** Tricode ****************************/
|
/* *out='\0'; */ |
| void tricode(int *Tvar, int **nbcode, int imx)
|
/* out=s; */ |
| {
|
/* return out; */ |
| int Ndum[20],ij=1, k, j, i;
|
/* } */ |
| int cptcode=0;
|
char *substrchaine(char *out, char *in, char *chain) |
| cptcoveff=0;
|
{ |
|
|
/* Substract chain 'chain' from 'in', return and output 'out' */ |
| for (k=0; k<19; k++) Ndum[k]=0;
|
/* in="V1+V1*age+age*age+V2", chain="age*age" */ |
| for (k=1; k<=7; k++) ncodemax[k]=0;
|
|
|
|
char *strloc; |
| for (j=1; j<=(cptcovn+2*cptcovprod); j++) {
|
|
| for (i=1; i<=imx; i++) {
|
strcpy (out, in); |
| ij=(int)(covar[Tvar[j]][i]);
|
strloc = strstr(out, chain); /* strloc points to out at age*age+V2 */ |
| Ndum[ij]++;
|
printf("Bef strloc=%s chain=%s out=%s \n", strloc, chain, out); |
| /*printf("i=%d ij=%d Ndum[ij]=%d imx=%d",i,ij,Ndum[ij],imx);*/
|
if(strloc != NULL){ |
| if (ij > cptcode) cptcode=ij;
|
/* 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));*/ |
| for (i=0; i<=cptcode; i++) {
|
} |
| if(Ndum[i]!=0) ncodemax[j]++;
|
printf("Aft strloc=%s chain=%s in=%s out=%s \n", strloc, chain, in, out); |
| }
|
return out; |
| ij=1;
|
} |
|
|
|
|
|
|
| for (i=1; i<=ncodemax[j]; i++) {
|
char *cutl(char *blocc, char *alocc, char *in, char occ) |
| for (k=0; k<=19; k++) {
|
{ |
| if (Ndum[k] != 0) {
|
/* cuts string in into blocc and alocc where blocc ends before FIRST occurence of char 'occ' |
| nbcode[Tvar[j]][ij]=k;
|
and alocc starts after first occurence of char 'occ' : ex cutv(blocc,alocc,"abcdef2ghi2j",'2') |
| ij++;
|
gives blocc="abcdef" and alocc="ghi2j". |
| }
|
If occ is not found blocc is null and alocc is equal to in. Returns blocc |
| if (ij > ncodemax[j]) break;
|
*/ |
| }
|
char *s, *t; |
| }
|
t=in;s=in; |
| }
|
while ((*in != occ) && (*in != '\0')){ |
|
|
*alocc++ = *in++; |
| for (k=0; k<19; k++) Ndum[k]=0;
|
} |
|
|
if( *in == occ){ |
| for (i=1; i<=ncovmodel; i++) {
|
*(alocc)='\0'; |
| ij=Tvar[i];
|
s=++in; |
| Ndum[ij]++;
|
} |
| }
|
|
|
|
if (s == t) {/* occ not found */ |
| ij=1;
|
*(alocc-(in-s))='\0'; |
| for (i=1; i<=10; i++) {
|
in=s; |
| if((Ndum[i]!=0) && (i<=ncov)){
|
} |
| Tvaraff[ij]=i;
|
while ( *in != '\0'){ |
| ij++;
|
*blocc++ = *in++; |
| }
|
} |
| }
|
|
|
|
*blocc='\0'; |
| cptcoveff=ij-1;
|
return t; |
| }
|
} |
|
|
char *cutv(char *blocc, char *alocc, char *in, char occ) |
| /*********** Health Expectancies ****************/
|
{ |
|
|
/* cuts string in into blocc and alocc where blocc ends before LAST occurence of char 'occ' |
| void evsij(char fileres[], double ***eij, double x[], int nlstate, int stepm, int bage, int fage, double **oldm, double **savm, int ij)
|
and alocc starts after last occurence of char 'occ' : ex cutv(blocc,alocc,"abcdef2ghi2j",'2') |
| {
|
gives blocc="abcdef2ghi" and alocc="j". |
| /* Health expectancies */
|
If occ is not found blocc is null and alocc is equal to in. Returns alocc |
| int i, j, nhstepm, hstepm, h;
|
*/ |
| double age, agelim,hf;
|
char *s, *t; |
| double ***p3mat;
|
t=in;s=in; |
|
|
while (*in != '\0'){ |
| fprintf(ficreseij,"# Health expectancies\n");
|
while( *in == occ){ |
| fprintf(ficreseij,"# Age");
|
*blocc++ = *in++; |
| for(i=1; i<=nlstate;i++)
|
s=in; |
| for(j=1; j<=nlstate;j++)
|
} |
| fprintf(ficreseij," %1d-%1d",i,j);
|
*blocc++ = *in++; |
| fprintf(ficreseij,"\n");
|
} |
|
|
if (s == t) /* occ not found */ |
| hstepm=1*YEARM; /* Every j years of age (in month) */
|
*(blocc-(in-s))='\0'; |
| hstepm=hstepm/stepm; /* Typically in stepm units, if j= 2 years, = 2/6 months = 4 */
|
else |
|
|
*(blocc-(in-s)-1)='\0'; |
| agelim=AGESUP;
|
in=s; |
| for (age=bage; age<=fage; age ++){ /* If stepm=6 months */
|
while ( *in != '\0'){ |
| /* nhstepm age range expressed in number of stepm */
|
*alocc++ = *in++; |
| nhstepm=(int) rint((agelim-age)*YEARM/stepm);
|
} |
| /* Typically if 20 years = 20*12/6=40 stepm */
|
|
| if (stepm >= YEARM) hstepm=1;
|
*alocc='\0'; |
| nhstepm = nhstepm/hstepm;/* Expressed in hstepm, typically 40/4=10 */
|
return s; |
| p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
|
} |
| /* Computed by stepm unit matrices, product of hstepm matrices, stored
|
|
| in an array of nhstepm length: nhstepm=10, hstepm=4, stepm=6 months */
|
int nbocc(char *s, char occ) |
| hpxij(p3mat,nhstepm,age,hstepm,x,nlstate,stepm,oldm, savm, ij);
|
{ |
|
|
int i,j=0; |
|
|
int lg=20; |
| for(i=1; i<=nlstate;i++)
|
i=0; |
| for(j=1; j<=nlstate;j++)
|
lg=strlen(s); |
| for (h=0, eij[i][j][(int)age]=0; h<=nhstepm; h++){
|
for(i=0; i<= lg; i++) { |
| eij[i][j][(int)age] +=p3mat[i][j][h];
|
if (s[i] == occ ) j++; |
| }
|
} |
|
|
return j; |
| hf=1;
|
} |
| if (stepm >= YEARM) hf=stepm/YEARM;
|
|
| fprintf(ficreseij,"%.0f",age );
|
/* void cutv(char *u,char *v, char*t, char occ) */ |
| for(i=1; i<=nlstate;i++)
|
/* { */ |
| for(j=1; j<=nlstate;j++){
|
/* /\* cuts string t into u and v where u ends before last occurence of char 'occ' */ |
| fprintf(ficreseij," %.4f", hf*eij[i][j][(int)age]);
|
/* and v starts after last occurence of char 'occ' : ex cutv(u,v,"abcdef2ghi2j",'2') */ |
| }
|
/* gives u="abcdef2ghi" and v="j" *\/ */ |
| fprintf(ficreseij,"\n");
|
/* int i,lg,j,p=0; */ |
| free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
|
/* i=0; */ |
| }
|
/* lg=strlen(t); */ |
| }
|
/* for(j=0; j<=lg-1; j++) { */ |
|
|
/* if((t[j]!= occ) && (t[j+1]== occ)) p=j+1; */ |
| /************ 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, int ij)
|
|
| {
|
/* for(j=0; j<p; j++) { */ |
| /* Variance of health expectancies */
|
/* (u[j] = t[j]); */ |
| /* double **prevalim(double **prlim, int nlstate, double *xp, double age, double **oldm, double ** savm,double ftolpl);*/
|
/* } */ |
| double **newm;
|
/* u[p]='\0'; */ |
| double **dnewm,**doldm;
|
|
| int i, j, nhstepm, hstepm, h;
|
/* for(j=0; j<= lg; j++) { */ |
| int k, cptcode;
|
/* if (j>=(p+1))(v[j-p-1] = t[j]); */ |
| double *xp;
|
/* } */ |
| double **gp, **gm;
|
/* } */ |
| double ***gradg, ***trgradg;
|
|
| double ***p3mat;
|
#ifdef _WIN32 |
| double age,agelim;
|
char * strsep(char **pp, const char *delim) |
| int theta;
|
{ |
|
|
char *p, *q; |
| fprintf(ficresvij,"# Covariances of life expectancies\n");
|
|
| fprintf(ficresvij,"# Age");
|
if ((p = *pp) == NULL) |
| for(i=1; i<=nlstate;i++)
|
return 0; |
| for(j=1; j<=nlstate;j++)
|
if ((q = strpbrk (p, delim)) != NULL) |
| fprintf(ficresvij," Cov(e%1d, e%1d)",i,j);
|
{ |
| fprintf(ficresvij,"\n");
|
*pp = q + 1; |
|
|
*q = '\0'; |
| xp=vector(1,npar);
|
} |
| dnewm=matrix(1,nlstate,1,npar);
|
else |
| doldm=matrix(1,nlstate,1,nlstate);
|
*pp = 0; |
|
|
return p; |
| hstepm=1*YEARM; /* Every year of age */
|
} |
| hstepm=hstepm/stepm; /* Typically in stepm units, if j= 2 years, = 2/6 months = 4 */
|
#endif |
| agelim = AGESUP;
|
|
| for (age=bage; age<=fage; age ++){ /* If stepm=6 months */
|
/********************** nrerror ********************/ |
| nhstepm=(int) rint((agelim-age)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
|
|
| if (stepm >= YEARM) hstepm=1;
|
void nrerror(char error_text[]) |
| nhstepm = nhstepm/hstepm; /* Typically 40/4=10 */
|
{ |
| p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
|
fprintf(stderr,"ERREUR ...\n"); |
| gradg=ma3x(0,nhstepm,1,npar,1,nlstate);
|
fprintf(stderr,"%s\n",error_text); |
| gp=matrix(0,nhstepm,1,nlstate);
|
exit(EXIT_FAILURE); |
| gm=matrix(0,nhstepm,1,nlstate);
|
} |
|
|
/*********************** vector *******************/ |
| for(theta=1; theta <=npar; theta++){
|
double *vector(int nl, int nh) |
| for(i=1; i<=npar; i++){ /* Computes gradient */
|
{ |
| xp[i] = x[i] + (i==theta ?delti[theta]:0);
|
double *v; |
| }
|
v=(double *) malloc((size_t)((nh-nl+1+NR_END)*sizeof(double))); |
| hpxij(p3mat,nhstepm,age,hstepm,xp,nlstate,stepm,oldm,savm, ij);
|
if (!v) nrerror("allocation failure in vector"); |
| prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ij);
|
return v-nl+NR_END; |
| for(j=1; j<= nlstate; j++){
|
} |
| for(h=0; h<=nhstepm; h++){
|
|
| for(i=1, gp[h][j]=0.;i<=nlstate;i++)
|
/************************ free vector ******************/ |
| gp[h][j] += prlim[i][i]*p3mat[i][j][h];
|
void free_vector(double*v, int nl, int nh) |
| }
|
{ |
| }
|
free((FREE_ARG)(v+nl-NR_END)); |
|
|
} |
| for(i=1; i<=npar; i++) /* Computes gradient */
|
|
| xp[i] = x[i] - (i==theta ?delti[theta]:0);
|
/************************ivector *******************************/ |
| hpxij(p3mat,nhstepm,age,hstepm,xp,nlstate,stepm,oldm,savm, ij);
|
int *ivector(long nl,long nh) |
| prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ij);
|
{ |
| for(j=1; j<= nlstate; j++){
|
int *v; |
| for(h=0; h<=nhstepm; h++){
|
v=(int *) malloc((size_t)((nh-nl+1+NR_END)*sizeof(int))); |
| for(i=1, gm[h][j]=0.;i<=nlstate;i++)
|
if (!v) nrerror("allocation failure in ivector"); |
| gm[h][j] += prlim[i][i]*p3mat[i][j][h];
|
return v-nl+NR_END; |
| }
|
} |
| }
|
|
| for(j=1; j<= nlstate; j++)
|
/******************free ivector **************************/ |
| for(h=0; h<=nhstepm; h++){
|
void free_ivector(int *v, long nl, long nh) |
| gradg[h][theta][j]= (gp[h][j]-gm[h][j])/2./delti[theta];
|
{ |
| }
|
free((FREE_ARG)(v+nl-NR_END)); |
| } /* End theta */
|
} |
|
|
|
| trgradg =ma3x(0,nhstepm,1,nlstate,1,npar);
|
/************************lvector *******************************/ |
|
|
long *lvector(long nl,long nh) |
| for(h=0; h<=nhstepm; h++)
|
{ |
| for(j=1; j<=nlstate;j++)
|
long *v; |
| for(theta=1; theta <=npar; theta++)
|
v=(long *) malloc((size_t)((nh-nl+1+NR_END)*sizeof(long))); |
| trgradg[h][j][theta]=gradg[h][theta][j];
|
if (!v) nrerror("allocation failure in ivector"); |
|
|
return v-nl+NR_END; |
| for(i=1;i<=nlstate;i++)
|
} |
| for(j=1;j<=nlstate;j++)
|
|
| vareij[i][j][(int)age] =0.;
|
/******************free lvector **************************/ |
| for(h=0;h<=nhstepm;h++){
|
void free_lvector(long *v, long nl, long nh) |
| for(k=0;k<=nhstepm;k++){
|
{ |
| matprod2(dnewm,trgradg[h],1,nlstate,1,npar,1,npar,matcov);
|
free((FREE_ARG)(v+nl-NR_END)); |
| matprod2(doldm,dnewm,1,nlstate,1,npar,1,nlstate,gradg[k]);
|
} |
| for(i=1;i<=nlstate;i++)
|
|
| for(j=1;j<=nlstate;j++)
|
/******************* imatrix *******************************/ |
| vareij[i][j][(int)age] += doldm[i][j];
|
int **imatrix(long nrl, long nrh, long ncl, long nch) |
| }
|
/* allocate a int matrix with subscript range m[nrl..nrh][ncl..nch] */ |
| }
|
{ |
| h=1;
|
long i, nrow=nrh-nrl+1,ncol=nch-ncl+1; |
| if (stepm >= YEARM) h=stepm/YEARM;
|
int **m; |
| fprintf(ficresvij,"%.0f ",age );
|
|
| for(i=1; i<=nlstate;i++)
|
/* allocate pointers to rows */ |
| for(j=1; j<=nlstate;j++){
|
m=(int **) malloc((size_t)((nrow+NR_END)*sizeof(int*))); |
| fprintf(ficresvij," %.4f", h*vareij[i][j][(int)age]);
|
if (!m) nrerror("allocation failure 1 in matrix()"); |
| }
|
m += NR_END; |
| fprintf(ficresvij,"\n");
|
m -= nrl; |
| free_matrix(gp,0,nhstepm,1,nlstate);
|
|
| free_matrix(gm,0,nhstepm,1,nlstate);
|
|
| free_ma3x(gradg,0,nhstepm,1,npar,1,nlstate);
|
/* allocate rows and set pointers to them */ |
| free_ma3x(trgradg,0,nhstepm,1,nlstate,1,npar);
|
m[nrl]=(int *) malloc((size_t)((nrow*ncol+NR_END)*sizeof(int))); |
| free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
|
if (!m[nrl]) nrerror("allocation failure 2 in matrix()"); |
| } /* End age */
|
m[nrl] += NR_END; |
|
|
m[nrl] -= ncl; |
| free_vector(xp,1,npar);
|
|
| free_matrix(doldm,1,nlstate,1,npar);
|
for(i=nrl+1;i<=nrh;i++) m[i]=m[i-1]+ncol; |
| free_matrix(dnewm,1,nlstate,1,nlstate);
|
|
|
|
/* return pointer to array of pointers to rows */ |
| }
|
return m; |
|
|
} |
| /************ 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, int ij)
|
/****************** free_imatrix *************************/ |
| {
|
void free_imatrix(m,nrl,nrh,ncl,nch) |
| /* Variance of prevalence limit */
|
int **m; |
| /* double **prevalim(double **prlim, int nlstate, double *xp, double age, double **oldm, double ** savm,double ftolpl);*/
|
long nch,ncl,nrh,nrl; |
| double **newm;
|
/* free an int matrix allocated by imatrix() */ |
| double **dnewm,**doldm;
|
{ |
| int i, j, nhstepm, hstepm;
|
free((FREE_ARG) (m[nrl]+ncl-NR_END)); |
| int k, cptcode;
|
free((FREE_ARG) (m+nrl-NR_END)); |
| double *xp;
|
} |
| double *gp, *gm;
|
|
| double **gradg, **trgradg;
|
/******************* matrix *******************************/ |
| double age,agelim;
|
double **matrix(long nrl, long nrh, long ncl, long nch) |
| int theta;
|
{ |
|
|
long i, nrow=nrh-nrl+1, ncol=nch-ncl+1; |
| fprintf(ficresvpl,"# Standard deviation of prevalences limit\n");
|
double **m; |
| fprintf(ficresvpl,"# Age");
|
|
| for(i=1; i<=nlstate;i++)
|
m=(double **) malloc((size_t)((nrow+NR_END)*sizeof(double*))); |
| fprintf(ficresvpl," %1d-%1d",i,i);
|
if (!m) nrerror("allocation failure 1 in matrix()"); |
| fprintf(ficresvpl,"\n");
|
m += NR_END; |
|
|
m -= nrl; |
| xp=vector(1,npar);
|
|
| dnewm=matrix(1,nlstate,1,npar);
|
m[nrl]=(double *) malloc((size_t)((nrow*ncol+NR_END)*sizeof(double))); |
| doldm=matrix(1,nlstate,1,nlstate);
|
if (!m[nrl]) nrerror("allocation failure 2 in matrix()"); |
|
|
m[nrl] += NR_END; |
| hstepm=1*YEARM; /* Every year of age */
|
m[nrl] -= ncl; |
| hstepm=hstepm/stepm; /* Typically in stepm units, if j= 2 years, = 2/6 months = 4 */
|
|
| agelim = AGESUP;
|
for (i=nrl+1; i<=nrh; i++) m[i]=m[i-1]+ncol; |
| for (age=bage; age<=fage; age ++){ /* If stepm=6 months */
|
return m; |
| nhstepm=(int) rint((agelim-age)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
|
/* print *(*(m+1)+70) or print m[1][70]; print m+1 or print &(m[1]) or &(m[1][0]) |
| if (stepm >= YEARM) hstepm=1;
|
m[i] = address of ith row of the table. &(m[i]) is its value which is another adress |
| nhstepm = nhstepm/hstepm; /* Typically 40/4=10 */
|
that of m[i][0]. In order to get the value p m[i][0] but it is unitialized. |
| gradg=matrix(1,npar,1,nlstate);
|
*/ |
| gp=vector(1,nlstate);
|
} |
| gm=vector(1,nlstate);
|
|
|
|
/*************************free matrix ************************/ |
| for(theta=1; theta <=npar; theta++){
|
void free_matrix(double **m, long nrl, long nrh, long ncl, long nch) |
| for(i=1; i<=npar; i++){ /* Computes gradient */
|
{ |
| xp[i] = x[i] + (i==theta ?delti[theta]:0);
|
free((FREE_ARG)(m[nrl]+ncl-NR_END)); |
| }
|
free((FREE_ARG)(m+nrl-NR_END)); |
| prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ij);
|
} |
| for(i=1;i<=nlstate;i++)
|
|
| gp[i] = prlim[i][i];
|
/******************* ma3x *******************************/ |
|
|
double ***ma3x(long nrl, long nrh, long ncl, long nch, long nll, long nlh) |
| for(i=1; i<=npar; i++) /* Computes gradient */
|
{ |
| xp[i] = x[i] - (i==theta ?delti[theta]:0);
|
long i, j, nrow=nrh-nrl+1, ncol=nch-ncl+1, nlay=nlh-nll+1; |
| prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ij);
|
double ***m; |
| for(i=1;i<=nlstate;i++)
|
|
| gm[i] = prlim[i][i];
|
m=(double ***) malloc((size_t)((nrow+NR_END)*sizeof(double*))); |
|
|
if (!m) nrerror("allocation failure 1 in matrix()"); |
| for(i=1;i<=nlstate;i++)
|
m += NR_END; |
| gradg[theta][i]= (gp[i]-gm[i])/2./delti[theta];
|
m -= nrl; |
| } /* End theta */
|
|
|
|
m[nrl]=(double **) malloc((size_t)((nrow*ncol+NR_END)*sizeof(double))); |
| trgradg =matrix(1,nlstate,1,npar);
|
if (!m[nrl]) nrerror("allocation failure 2 in matrix()"); |
|
|
m[nrl] += NR_END; |
| for(j=1; j<=nlstate;j++)
|
m[nrl] -= ncl; |
| for(theta=1; theta <=npar; theta++)
|
|
| trgradg[j][theta]=gradg[theta][j];
|
for (i=nrl+1; i<=nrh; i++) m[i]=m[i-1]+ncol; |
|
|
|
| for(i=1;i<=nlstate;i++)
|
m[nrl][ncl]=(double *) malloc((size_t)((nrow*ncol*nlay+NR_END)*sizeof(double))); |
| varpl[i][(int)age] =0.;
|
if (!m[nrl][ncl]) nrerror("allocation failure 3 in matrix()"); |
| matprod2(dnewm,trgradg,1,nlstate,1,npar,1,npar,matcov);
|
m[nrl][ncl] += NR_END; |
| matprod2(doldm,dnewm,1,nlstate,1,npar,1,nlstate,gradg);
|
m[nrl][ncl] -= nll; |
| for(i=1;i<=nlstate;i++)
|
for (j=ncl+1; j<=nch; j++) |
| varpl[i][(int)age] = doldm[i][i]; /* Covariances are useless */
|
m[nrl][j]=m[nrl][j-1]+nlay; |
|
|
|
| fprintf(ficresvpl,"%.0f ",age );
|
for (i=nrl+1; i<=nrh; i++) { |
| for(i=1; i<=nlstate;i++)
|
m[i][ncl]=m[i-1l][ncl]+ncol*nlay; |
| fprintf(ficresvpl," %.5f (%.5f)",prlim[i][i],sqrt(varpl[i][(int)age]));
|
for (j=ncl+1; j<=nch; j++) |
| fprintf(ficresvpl,"\n");
|
m[i][j]=m[i][j-1]+nlay; |
| free_vector(gp,1,nlstate);
|
} |
| free_vector(gm,1,nlstate);
|
return m; |
| free_matrix(gradg,1,npar,1,nlstate);
|
/* gdb: p *(m+1) <=> p m[1] and p (m+1) <=> p (m+1) <=> p &(m[1]) |
| free_matrix(trgradg,1,nlstate,1,npar);
|
&(m[i][j][k]) <=> *((*(m+i) + j)+k) |
| } /* End age */
|
*/ |
|
|
} |
| free_vector(xp,1,npar);
|
|
| free_matrix(doldm,1,nlstate,1,npar);
|
/*************************free ma3x ************************/ |
| free_matrix(dnewm,1,nlstate,1,nlstate);
|
void free_ma3x(double ***m, long nrl, long nrh, long ncl, long nch,long nll, long nlh) |
|
|
{ |
| }
|
free((FREE_ARG)(m[nrl][ncl]+ nll-NR_END)); |
|
|
free((FREE_ARG)(m[nrl]+ncl-NR_END)); |
|
|
free((FREE_ARG)(m+nrl-NR_END)); |
|
|
} |
| /***********************************************/
|
|
| /**************** Main Program *****************/
|
/*************** function subdirf ***********/ |
| /***********************************************/
|
char *subdirf(char fileres[]) |
|
|
{ |
| /*int main(int argc, char *argv[])*/
|
/* Caution optionfilefiname is hidden */ |
| int main()
|
strcpy(tmpout,optionfilefiname); |
| {
|
strcat(tmpout,"/"); /* Add to the right */ |
|
|
strcat(tmpout,fileres); |
| int i,j, k, n=MAXN,iter,m,size,cptcode, cptcod;
|
return tmpout; |
| double agedeb, agefin,hf;
|
} |
| double agemin=1.e20, agemax=-1.e20;
|
|
|
|
/*************** function subdirf2 ***********/ |
| double fret;
|
char *subdirf2(char fileres[], char *preop) |
| double **xi,tmp,delta;
|
{ |
|
|
|
| double dum; /* Dummy variable */
|
/* Caution optionfilefiname is hidden */ |
| double ***p3mat;
|
strcpy(tmpout,optionfilefiname); |
| int *indx;
|
strcat(tmpout,"/"); |
| char line[MAXLINE], linepar[MAXLINE];
|
strcat(tmpout,preop); |
| char title[MAXLINE];
|
strcat(tmpout,fileres); |
| char optionfile[FILENAMELENGTH], datafile[FILENAMELENGTH], filerespl[FILENAMELENGTH], optionfilehtm[FILENAMELENGTH];
|
return tmpout; |
| char fileres[FILENAMELENGTH], filerespij[FILENAMELENGTH], filereso[FILENAMELENGTH];
|
} |
| char filerest[FILENAMELENGTH];
|
|
| char fileregp[FILENAMELENGTH];
|
/*************** function subdirf3 ***********/ |
| char path[80],pathc[80],pathcd[80],pathtot[80],model[20];
|
char *subdirf3(char fileres[], char *preop, char *preop2) |
| int firstobs=1, lastobs=10;
|
{ |
| int sdeb, sfin; /* Status at beginning and end */
|
|
| int c, h , cpt,l;
|
/* Caution optionfilefiname is hidden */ |
| int ju,jl, mi;
|
strcpy(tmpout,optionfilefiname); |
| int i1,j1, k1,k2,k3,jk,aa,bb, stepsize, ij;
|
strcat(tmpout,"/"); |
| int jnais,jdc,jint4,jint1,jint2,jint3,**outcome,**adl,*tab;
|
strcat(tmpout,preop); |
|
|
strcat(tmpout,preop2); |
| int hstepm, nhstepm;
|
strcat(tmpout,fileres); |
| double bage, fage, age, agelim, agebase;
|
return tmpout; |
| double ftolpl=FTOL;
|
} |
| double **prlim;
|
|
| double *severity;
|
/*************** function subdirfext ***********/ |
| double ***param; /* Matrix of parameters */
|
char *subdirfext(char fileres[], char *preop, char *postop) |
| double *p;
|
{ |
| double **matcov; /* Matrix of covariance */
|
|
| double ***delti3; /* Scale */
|
strcpy(tmpout,preop); |
| double *delti; /* Scale */
|
strcat(tmpout,fileres); |
| double ***eij, ***vareij;
|
strcat(tmpout,postop); |
| double **varpl; /* Variances of prevalence limits by age */
|
return tmpout; |
| double *epj, vepp;
|
} |
| char version[80]="Imach version 64b, May 2001, INED-EUROREVES ";
|
|
| char *alph[]={"a","a","b","c","d","e"}, str[4];
|
/*************** function subdirfext3 ***********/ |
|
|
char *subdirfext3(char fileres[], char *preop, char *postop) |
| char z[1]="c", occ;
|
{ |
| #include <sys/time.h>
|
|
| #include <time.h>
|
/* Caution optionfilefiname is hidden */ |
| char stra[80], strb[80], strc[80], strd[80],stre[80],modelsav[80];
|
strcpy(tmpout,optionfilefiname); |
| /* long total_usecs;
|
strcat(tmpout,"/"); |
| struct timeval start_time, end_time;
|
strcat(tmpout,preop); |
|
|
strcat(tmpout,fileres); |
| gettimeofday(&start_time, (struct timezone*)0); */ /* at first time */
|
strcat(tmpout,postop); |
|
|
return tmpout; |
|
|
} |
| printf("\nIMACH, Version 0.64b");
|
|
| printf("\nEnter the parameter file name: ");
|
char *asc_diff_time(long time_sec, char ascdiff[]) |
|
|
{ |
| #ifdef windows
|
long sec_left, days, hours, minutes; |
| scanf("%s",pathtot);
|
days = (time_sec) / (60*60*24); |
| getcwd(pathcd, size);
|
sec_left = (time_sec) % (60*60*24); |
| /*cygwin_split_path(pathtot,path,optionfile);
|
hours = (sec_left) / (60*60) ; |
| printf("pathtot=%s, path=%s, optionfile=%s\n",pathtot,path,optionfile);*/
|
sec_left = (sec_left) %(60*60); |
| /* cutv(path,optionfile,pathtot,'\\');*/
|
minutes = (sec_left) /60; |
|
|
sec_left = (sec_left) % (60); |
| split(pathtot, path,optionfile);
|
sprintf(ascdiff,"%ld day(s) %ld hour(s) %ld minute(s) %ld second(s)",days, hours, minutes, sec_left); |
| chdir(path);
|
return ascdiff; |
| replace(pathc,path);
|
} |
| #endif
|
|
| #ifdef unix
|
/***************** f1dim *************************/ |
| scanf("%s",optionfile);
|
extern int ncom; |
| #endif
|
extern double *pcom,*xicom; |
|
|
extern double (*nrfunc)(double []); |
| /*-------- arguments in the command line --------*/
|
|
|
|
double f1dim(double x) |
| strcpy(fileres,"r");
|
{ |
| strcat(fileres, optionfile);
|
int j; |
|
|
double f; |
| /*---------arguments file --------*/
|
double *xt; |
|
|
|
| if((ficpar=fopen(optionfile,"r"))==NULL) {
|
xt=vector(1,ncom); |
| printf("Problem with optionfile %s\n",optionfile);
|
for (j=1;j<=ncom;j++) xt[j]=pcom[j]+x*xicom[j]; |
| goto end;
|
f=(*nrfunc)(xt); |
| }
|
free_vector(xt,1,ncom); |
|
|
return f; |
| strcpy(filereso,"o");
|
} |
| strcat(filereso,fileres);
|
|
| if((ficparo=fopen(filereso,"w"))==NULL) {
|
/*****************brent *************************/ |
| printf("Problem with Output resultfile: %s\n", filereso);goto end;
|
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 |
| /* Reads comments: lines beginning with '#' */
|
* between ax and cx, and f(bx) is less than both f(ax) and f(cx) ), this routine isolates |
| while((c=getc(ficpar))=='#' && c!= EOF){
|
* the minimum to a fractional precision of about tol using Brent’s method. The abscissa of |
| ungetc(c,ficpar);
|
* the minimum is returned as xmin, and the minimum function value is returned as brent , the |
| fgets(line, MAXLINE, ficpar);
|
* returned function value. |
| puts(line);
|
*/ |
| fputs(line,ficparo);
|
int iter; |
| }
|
double a,b,d,etemp; |
| ungetc(c,ficpar);
|
double fu=0,fv,fw,fx; |
|
|
double ftemp=0.; |
| 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\nmodel=%s\n",title, datafile, &lastobs, &firstpass,&lastpass,&ftol, &stepm, &ncov, &nlstate,&ndeath, &maxwav, &mle, &weightopt,model);
|
double p,q,r,tol1,tol2,u,v,w,x,xm; |
| 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\nmodel=%s\n", title, datafile, lastobs, firstpass,lastpass,ftol, stepm, ncov, nlstate,ndeath, maxwav, mle, weightopt,model);
|
double e=0.0; |
| 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\nmodel=%s\n", title, datafile, lastobs, firstpass,lastpass,ftol,stepm,ncov,nlstate,ndeath,maxwav, mle, weightopt,model);
|
|
|
|
a=(ax < cx ? ax : cx); |
| covar=matrix(0,NCOVMAX,1,n);
|
b=(ax > cx ? ax : cx); |
| cptcovn=0;
|
x=w=v=bx; |
| if (strlen(model)>1) cptcovn=nbocc(model,'+')+1;
|
fw=fv=fx=(*f)(x); |
|
|
for (iter=1;iter<=ITMAX;iter++) { |
| ncovmodel=2+cptcovn;
|
xm=0.5*(a+b); |
| nvar=ncovmodel-1; /* Suppressing age as a basic covariate */
|
tol2=2.0*(tol1=tol*fabs(x)+ZEPS); |
|
|
/* if (2.0*fabs(fp-(*fret)) <= ftol*(fabs(fp)+fabs(*fret)))*/ |
| /* Read guess parameters */
|
printf(".");fflush(stdout); |
| /* Reads comments: lines beginning with '#' */
|
fprintf(ficlog,".");fflush(ficlog); |
| while((c=getc(ficpar))=='#' && c!= EOF){
|
#ifdef DEBUGBRENT |
| ungetc(c,ficpar);
|
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); |
| fgets(line, MAXLINE, ficpar);
|
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); |
| puts(line);
|
/* if ((fabs(x-xm) <= (tol2-0.5*(b-a)))||(2.0*fabs(fu-ftemp) <= ftol*1.e-2*(fabs(fu)+fabs(ftemp)))) { */ |
| fputs(line,ficparo);
|
#endif |
| }
|
if (fabs(x-xm) <= (tol2-0.5*(b-a))){ |
| ungetc(c,ficpar);
|
*xmin=x; |
|
|
return fx; |
| param= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
|
} |
| for(i=1; i <=nlstate; i++)
|
ftemp=fu; |
| for(j=1; j <=nlstate+ndeath-1; j++){
|
if (fabs(e) > tol1) { |
| fscanf(ficpar,"%1d%1d",&i1,&j1);
|
r=(x-w)*(fx-fv); |
| fprintf(ficparo,"%1d%1d",i1,j1);
|
q=(x-v)*(fx-fw); |
| printf("%1d%1d",i,j);
|
p=(x-v)*q-(x-w)*r; |
| for(k=1; k<=ncovmodel;k++){
|
q=2.0*(q-r); |
| fscanf(ficpar," %lf",¶m[i][j][k]);
|
if (q > 0.0) p = -p; |
| printf(" %lf",param[i][j][k]);
|
q=fabs(q); |
| fprintf(ficparo," %lf",param[i][j][k]);
|
etemp=e; |
| }
|
e=d; |
| fscanf(ficpar,"\n");
|
if (fabs(p) >= fabs(0.5*q*etemp) || p <= q*(a-x) || p >= q*(b-x)) |
| printf("\n");
|
d=CGOLD*(e=(x >= xm ? a-x : b-x)); |
| fprintf(ficparo,"\n");
|
else { |
| }
|
d=p/q; |
|
|
u=x+d; |
| npar= (nlstate+ndeath-1)*nlstate*ncovmodel;
|
if (u-a < tol2 || b-u < tol2) |
| p=param[1][1];
|
d=SIGN(tol1,xm-x); |
|
|
} |
| /* Reads comments: lines beginning with '#' */
|
} else { |
| while((c=getc(ficpar))=='#' && c!= EOF){
|
d=CGOLD*(e=(x >= xm ? a-x : b-x)); |
| ungetc(c,ficpar);
|
} |
| fgets(line, MAXLINE, ficpar);
|
u=(fabs(d) >= tol1 ? x+d : x+SIGN(tol1,d)); |
| puts(line);
|
fu=(*f)(u); |
| fputs(line,ficparo);
|
if (fu <= fx) { |
| }
|
if (u >= x) a=x; else b=x; |
| ungetc(c,ficpar);
|
SHFT(v,w,x,u) |
|
|
SHFT(fv,fw,fx,fu) |
| delti3= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
|
} else { |
| delti=vector(1,npar); /* Scale of each paramater (output from hesscov) */
|
if (u < x) a=u; else b=u; |
| for(i=1; i <=nlstate; i++){
|
if (fu <= fw || w == x) { |
| for(j=1; j <=nlstate+ndeath-1; j++){
|
v=w; |
| fscanf(ficpar,"%1d%1d",&i1,&j1);
|
w=u; |
| printf("%1d%1d",i,j);
|
fv=fw; |
| fprintf(ficparo,"%1d%1d",i1,j1);
|
fw=fu; |
| for(k=1; k<=ncovmodel;k++){
|
} else if (fu <= fv || v == x || v == w) { |
| fscanf(ficpar,"%le",&delti3[i][j][k]);
|
v=u; |
| printf(" %le",delti3[i][j][k]);
|
fv=fu; |
| fprintf(ficparo," %le",delti3[i][j][k]);
|
} |
| }
|
} |
| fscanf(ficpar,"\n");
|
} |
| printf("\n");
|
nrerror("Too many iterations in brent"); |
| fprintf(ficparo,"\n");
|
*xmin=x; |
| }
|
return fx; |
| }
|
} |
| delti=delti3[1][1];
|
|
|
|
/****************** mnbrak ***********************/ |
| /* Reads comments: lines beginning with '#' */
|
|
| while((c=getc(ficpar))=='#' && c!= EOF){
|
void mnbrak(double *ax, double *bx, double *cx, double *fa, double *fb, double *fc, |
| ungetc(c,ficpar);
|
double (*func)(double)) |
| fgets(line, MAXLINE, ficpar);
|
{ /* Given a function func , and given distinct initial points ax and bx , this routine searches in |
| puts(line);
|
the downhill direction (defined by the function as evaluated at the initial points) and returns |
| fputs(line,ficparo);
|
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. |
| ungetc(c,ficpar);
|
*/ |
|
|
double ulim,u,r,q, dum; |
| matcov=matrix(1,npar,1,npar);
|
double fu; |
| for(i=1; i <=npar; i++){
|
|
| fscanf(ficpar,"%s",&str);
|
double scale=10.; |
| printf("%s",str);
|
int iterscale=0; |
| fprintf(ficparo,"%s",str);
|
|
| for(j=1; j <=i; j++){
|
*fa=(*func)(*ax); /* xta[j]=pcom[j]+(*ax)*xicom[j]; fa=f(xta[j])*/ |
| fscanf(ficpar," %le",&matcov[i][j]);
|
*fb=(*func)(*bx); /* xtb[j]=pcom[j]+(*bx)*xicom[j]; fb=f(xtb[j]) */ |
| printf(" %.5le",matcov[i][j]);
|
|
| fprintf(ficparo," %.5le",matcov[i][j]);
|
|
| }
|
/* while(*fb != *fb){ /\* *ax should be ok, reducing distance to *ax *\/ */ |
| fscanf(ficpar,"\n");
|
/* printf("Warning mnbrak *fb = %lf, *bx=%lf *ax=%lf *fa==%lf iter=%d\n",*fb, *bx, *ax, *fa, iterscale++); */ |
| printf("\n");
|
/* *bx = *ax - (*ax - *bx)/scale; */ |
| fprintf(ficparo,"\n");
|
/* *fb=(*func)(*bx); /\* xtb[j]=pcom[j]+(*bx)*xicom[j]; fb=f(xtb[j]) *\/ */ |
| }
|
/* } */ |
| for(i=1; i <=npar; i++)
|
|
| for(j=i+1;j<=npar;j++)
|
if (*fb > *fa) { |
| matcov[i][j]=matcov[j][i];
|
SHFT(dum,*ax,*bx,dum) |
|
|
SHFT(dum,*fb,*fa,dum) |
| printf("\n");
|
} |
|
|
*cx=(*bx)+GOLD*(*bx-*ax); |
|
|
*fc=(*func)(*cx); |
| /*-------- data file ----------*/
|
#ifdef DEBUG |
| if((ficres =fopen(fileres,"w"))==NULL) {
|
printf("mnbrak0 a=%lf *fa=%lf, b=%lf *fb=%lf, c=%lf *fc=%lf\n",*ax,*fa,*bx,*fb,*cx, *fc); |
| printf("Problem with resultfile: %s\n", fileres);goto end;
|
fprintf(ficlog,"mnbrak0 a=%lf *fa=%lf, b=%lf *fb=%lf, c=%lf *fc=%lf\n",*ax,*fa,*bx,*fb,*cx, *fc); |
| }
|
#endif |
| fprintf(ficres,"#%s\n",version);
|
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); |
| if((fic=fopen(datafile,"r"))==NULL) {
|
q=(*bx-*cx)*(*fb-*fa); /* What if fa=inf */ |
| printf("Problem with datafile: %s\n", datafile);goto end;
|
u=(*bx)-((*bx-*cx)*q-(*bx-*ax)*r)/ |
| }
|
(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 */ |
| n= lastobs;
|
if ((*bx-u)*(u-*cx) > 0.0) { /* if u_p is between b and c */ |
| severity = vector(1,maxwav);
|
fu=(*func)(u); |
| outcome=imatrix(1,maxwav+1,1,n);
|
#ifdef DEBUG |
| num=ivector(1,n);
|
/* f(x)=A(x-u)**2+f(u) */ |
| moisnais=vector(1,n);
|
double A, fparabu; |
| annais=vector(1,n);
|
A= (*fb - *fa)/(*bx-*ax)/(*bx+*ax-2*u); |
| moisdc=vector(1,n);
|
fparabu= *fa - A*(*ax-u)*(*ax-u); |
| andc=vector(1,n);
|
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); |
| agedc=vector(1,n);
|
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); |
| cod=ivector(1,n);
|
/* And thus,it can be that fu > *fc even if fparabu < *fc */ |
| weight=vector(1,n);
|
/* mnbrak (*ax=7.666299858533, *fa=299039.693133272231), (*bx=8.595447774979, *fb=298976.598289369489), |
| for(i=1;i<=n;i++) weight[i]=1.0; /* Equal weights, 1 by default */
|
(*cx=10.098840694817, *fc=298946.631474258087), (*u=9.852501168332, fu=298948.773013752128, fparabu=298945.434711494134) */ |
| mint=matrix(1,maxwav,1,n);
|
/* In that case, there is no bracket in the output! Routine is wrong with many consequences.*/ |
| anint=matrix(1,maxwav,1,n);
|
#endif |
| s=imatrix(1,maxwav+1,1,n);
|
#ifdef MNBRAKORIGINAL |
| adl=imatrix(1,maxwav+1,1,n);
|
#else |
| tab=ivector(1,NCOVMAX);
|
/* if (fu > *fc) { */ |
| ncodemax=ivector(1,8);
|
/* #ifdef DEBUG */ |
|
|
/* printf("mnbrak4 fu > fc \n"); */ |
| i=1;
|
/* fprintf(ficlog, "mnbrak4 fu > fc\n"); */ |
| while (fgets(line, MAXLINE, fic) != NULL) {
|
/* #endif */ |
| if ((i >= firstobs) && (i <=lastobs)) {
|
/* /\* 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 *\\/ *\/ */ |
| for (j=maxwav;j>=1;j--){
|
/* dum=u; /\* Shifting c and u *\/ */ |
| cutv(stra, strb,line,' '); s[j][i]=atoi(strb);
|
/* u = *cx; */ |
| strcpy(line,stra);
|
/* *cx = dum; */ |
| cutv(stra, strb,line,'/'); anint[j][i]=(double)(atoi(strb)); strcpy(line,stra);
|
/* dum = fu; */ |
| cutv(stra, strb,line,' '); mint[j][i]=(double)(atoi(strb)); strcpy(line,stra);
|
/* fu = *fc; */ |
| }
|
/* *fc =dum; */ |
|
|
/* } else { /\* end *\/ */ |
| cutv(stra, strb,line,'/'); andc[i]=(double)(atoi(strb)); strcpy(line,stra);
|
/* #ifdef DEBUG */ |
| cutv(stra, strb,line,' '); moisdc[i]=(double)(atoi(strb)); strcpy(line,stra);
|
/* printf("mnbrak3 fu < fc \n"); */ |
|
|
/* fprintf(ficlog, "mnbrak3 fu < fc\n"); */ |
| cutv(stra, strb,line,'/'); annais[i]=(double)(atoi(strb)); strcpy(line,stra);
|
/* #endif */ |
| cutv(stra, strb,line,' '); moisnais[i]=(double)(atoi(strb)); strcpy(line,stra);
|
/* dum=u; /\* Shifting c and u *\/ */ |
|
|
/* u = *cx; */ |
| cutv(stra, strb,line,' '); weight[i]=(double)(atoi(strb)); strcpy(line,stra);
|
/* *cx = dum; */ |
| for (j=ncov;j>=1;j--){
|
/* dum = fu; */ |
| cutv(stra, strb,line,' '); covar[j][i]=(double)(atoi(strb)); strcpy(line,stra);
|
/* fu = *fc; */ |
| }
|
/* *fc =dum; */ |
| num[i]=atol(stra);
|
/* } */ |
|
|
#ifdef DEBUGMNBRAK |
| /*printf("%d %.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]));*/
|
double A, fparabu; |
|
|
A= (*fb - *fa)/(*bx-*ax)/(*bx+*ax-2*u); |
| i=i+1;
|
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 |
| /*scanf("%d",i);*/
|
dum=u; /* Shifting c and u */ |
| imx=i-1; /* Number of individuals */
|
u = *cx; |
|
|
*cx = dum; |
| /* Calculation of the number of parameter from char model*/
|
dum = fu; |
| Tvar=ivector(1,15);
|
fu = *fc; |
| Tprod=ivector(1,15);
|
*fc =dum; |
| Tvaraff=ivector(1,15);
|
#endif |
| Tvard=imatrix(1,15,1,2);
|
} else if ((*cx-u)*(u-ulim) > 0.0) { /* u is after c but before ulim */ |
| Tage=ivector(1,15);
|
#ifdef DEBUG |
|
|
printf("\nmnbrak2 u=%lf after c=%lf but before ulim\n",u,*cx); |
| if (strlen(model) >1){
|
fprintf(ficlog,"\nmnbrak2 u=%lf after c=%lf but before ulim\n",u,*cx); |
| j=0, j1=0, k1=1, k2=1;
|
#endif |
| j=nbocc(model,'+');
|
fu=(*func)(u); |
| j1=nbocc(model,'*');
|
if (fu < *fc) { |
| cptcovn=j+1;
|
#ifdef DEBUG |
| cptcovprod=j1;
|
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 |
| strcpy(modelsav,model);
|
SHFT(*bx,*cx,u,*cx+GOLD*(*cx-*bx)) |
| if ((strcmp(model,"age")==0) || (strcmp(model,"age*age")==0)){
|
SHFT(*fb,*fc,fu,(*func)(u)) |
| printf("Error. Non available option model=%s ",model);
|
#ifdef DEBUG |
| goto end;
|
printf("\nmnbrak2 shift GOLD c=%lf",*cx+GOLD*(*cx-*bx)); |
| }
|
#endif |
|
|
} |
| for(i=(j+1); i>=1;i--){
|
} else if ((u-ulim)*(ulim-*cx) >= 0.0) { /* u outside ulim (verifying that ulim is beyond c) */ |
| cutv(stra,strb,modelsav,'+');
|
#ifdef DEBUG |
| if (nbocc(modelsav,'+')==0) strcpy(strb,modelsav);
|
printf("\nmnbrak2 u=%lf outside ulim=%lf (verifying that ulim is beyond c=%lf)\n",u,ulim,*cx); |
| /* printf("i=%d a=%s b=%s sav=%s\n",i, stra,strb,modelsav);*/
|
fprintf(ficlog,"\nmnbrak2 u=%lf outside ulim=%lf (verifying that ulim is beyond c=%lf)\n",u,ulim,*cx); |
| /*scanf("%d",i);*/
|
#endif |
| if (strchr(strb,'*')) {
|
u=ulim; |
| cutv(strd,strc,strb,'*');
|
fu=(*func)(u); |
| if (strcmp(strc,"age")==0) {
|
} else { /* u could be left to b (if r > q parabola has a maximum) */ |
| cptcovprod--;
|
#ifdef DEBUG |
| cutv(strb,stre,strd,'V');
|
printf("\nmnbrak2 u=%lf could be left to b=%lf (if r=%lf > q=%lf parabola has a maximum)\n",u,*bx,r,q); |
| Tvar[i]=atoi(stre);
|
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); |
| cptcovage++;
|
#endif |
| Tage[cptcovage]=i;
|
u=(*cx)+GOLD*(*cx-*bx); |
| /*printf("stre=%s ", stre);*/
|
fu=(*func)(u); |
| }
|
#ifdef DEBUG |
| else if (strcmp(strd,"age")==0) {
|
printf("\nmnbrak2 new u=%lf fu=%lf shifted gold left from c=%lf and b=%lf \n",u,fu,*cx,*bx); |
| cptcovprod--;
|
fprintf(ficlog,"\nmnbrak2 new u=%lf fu=%lf shifted gold left from c=%lf and b=%lf \n",u,fu,*cx,*bx); |
| cutv(strb,stre,strc,'V');
|
#endif |
| Tvar[i]=atoi(stre);
|
} /* end tests */ |
| cptcovage++;
|
SHFT(*ax,*bx,*cx,u) |
| Tage[cptcovage]=i;
|
SHFT(*fa,*fb,*fc,fu) |
| }
|
#ifdef DEBUG |
| else {
|
printf("\nmnbrak2 shift (*ax=%.12f, *fa=%.12lf), (*bx=%.12f, *fb=%.12lf), (*cx=%.12f, *fc=%.12lf)\n",*ax,*fa,*bx,*fb,*cx,*fc); |
| cutv(strb,stre,strc,'V');
|
fprintf(ficlog, "\nmnbrak2 shift (*ax=%.12f, *fa=%.12lf), (*bx=%.12f, *fb=%.12lf), (*cx=%.12f, *fc=%.12lf)\n",*ax,*fa,*bx,*fb,*cx,*fc); |
| Tvar[i]=ncov+k1;
|
#endif |
| cutv(strb,strc,strd,'V');
|
} /* end while; ie return (a, b, c, fa, fb, fc) such that a < b < c with f(a) > f(b) and fb < f(c) */ |
| Tprod[k1]=i;
|
} |
| Tvard[k1][1]=atoi(strc);
|
|
| Tvard[k1][2]=atoi(stre);
|
/*************** linmin ************************/ |
| Tvar[cptcovn+k2]=Tvard[k1][1];
|
/* Given an n -dimensional point p[1..n] and an n -dimensional direction xi[1..n] , moves and |
| Tvar[cptcovn+k2+1]=Tvard[k1][2];
|
resets p to where the function func(p) takes on a minimum along the direction xi from p , |
| for (k=1; k<=lastobs;k++)
|
and replaces xi by the actual vector displacement that p was moved. Also returns as fret |
| covar[ncov+k1][k]=covar[atoi(stre)][k]*covar[atoi(strc)][k];
|
the value of func at the returned location p . This is actually all accomplished by calling the |
| k1++;
|
routines mnbrak and brent .*/ |
| k2=k2+2;
|
int ncom; |
| }
|
double *pcom,*xicom; |
| }
|
double (*nrfunc)(double []); |
| else {
|
|
| /*printf("d=%s c=%s b=%s\n", strd,strc,strb);*/
|
#ifdef LINMINORIGINAL |
| /* scanf("%d",i);*/
|
void linmin(double p[], double xi[], int n, double *fret,double (*func)(double [])) |
| cutv(strd,strc,strb,'V');
|
#else |
| Tvar[i]=atoi(strc);
|
void linmin(double p[], double xi[], int n, double *fret,double (*func)(double []), int *flat) |
| }
|
#endif |
| strcpy(modelsav,stra);
|
{ |
| /*printf("a=%s b=%s sav=%s\n", stra,strb,modelsav);
|
double brent(double ax, double bx, double cx, |
| scanf("%d",i);*/
|
double (*f)(double), double tol, double *xmin); |
| }
|
double f1dim(double x); |
| }
|
void mnbrak(double *ax, double *bx, double *cx, double *fa, double *fb, |
|
|
double *fc, double (*func)(double)); |
| /*printf("tvar1=%d tvar2=%d tvar3=%d cptcovage=%d Tage=%d",Tvar[1],Tvar[2],Tvar[3],cptcovage,Tage[1]);
|
int j; |
| printf("cptcovprod=%d ", cptcovprod);
|
double xx,xmin,bx,ax; |
| scanf("%d ",i);*/
|
double fx,fb,fa; |
| fclose(fic);
|
|
|
|
#ifdef LINMINORIGINAL |
| /* if(mle==1){*/
|
#else |
| if (weightopt != 1) { /* Maximisation without weights*/
|
double scale=10., axs, xxs; /* Scale added for infinity */ |
| for(i=1;i<=n;i++) weight[i]=1.0;
|
#endif |
| }
|
|
| /*-calculation of age at interview from date of interview and age at death -*/
|
ncom=n; |
| agev=matrix(1,maxwav,1,imx);
|
pcom=vector(1,n); |
|
|
xicom=vector(1,n); |
| for (i=1; i<=imx; i++) {
|
nrfunc=func; |
| agedc[i]=(moisdc[i]/12.+andc[i])-(moisnais[i]/12.+annais[i]);
|
for (j=1;j<=n;j++) { |
| for(m=1; (m<= maxwav); m++){
|
pcom[j]=p[j]; |
| if(s[m][i] >0){
|
xicom[j]=xi[j]; /* Former scale xi[j] of currrent direction i */ |
| if (s[m][i] == nlstate+1) {
|
} |
| if(agedc[i]>0)
|
|
| if(moisdc[i]!=99 && andc[i]!=9999)
|
#ifdef LINMINORIGINAL |
| agev[m][i]=agedc[i];
|
xx=1.; |
| else {
|
#else |
| if (andc[i]!=9999){
|
axs=0.0; |
| printf("Warning negative age at death: %d line:%d\n",num[i],i);
|
xxs=1.; |
| agev[m][i]=-1;
|
do{ |
| }
|
xx= xxs; |
| }
|
#endif |
| }
|
ax=0.; |
| else if(s[m][i] !=9){ /* Should no more exist */
|
mnbrak(&ax,&xx,&bx,&fa,&fx,&fb,f1dim); /* Outputs: xtx[j]=pcom[j]+(*xx)*xicom[j]; fx=f(xtx[j]) */ |
| agev[m][i]=(mint[m][i]/12.+1./24.+anint[m][i])-(moisnais[i]/12.+1./24.+annais[i]);
|
/* brackets with inputs ax=0 and xx=1, but points, pcom=p, and directions values, xicom=xi, are sent via f1dim(x) */ |
| if(mint[m][i]==99 || anint[m][i]==9999)
|
/* 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)) */ |
| agev[m][i]=1;
|
/* Outputs: fa=f(p(j)) and fx=f(p(j) + xxs * xi(j) ) and f(bx)= f(p(j)+ bx* xi(j)) */ |
| else if(agev[m][i] <agemin){
|
/* Given input ax=axs and xx=xxs, xx might be too far from ax to get a finite f(xx) */ |
| agemin=agev[m][i];
|
/* Searches on line, outputs (ax, xx, bx) such that fx < min(fa and fb) */ |
| /*printf(" Min anint[%d][%d]=%.2f annais[%d]=%.2f, agemin=%.2f\n",m,i,anint[m][i], i,annais[i], agemin);*/
|
/* 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(agev[m][i] >agemax){
|
#else |
| agemax=agev[m][i];
|
if (fx != fx){ |
| /* printf(" anint[%d][%d]=%.0f annais[%d]=%.0f, agemax=%.0f\n",m,i,anint[m][i], i,annais[i], agemax);*/
|
xxs=xxs/scale; /* Trying a smaller xx, closer to initial ax=0 */ |
| }
|
printf("|"); |
| /*agev[m][i]=anint[m][i]-annais[i];*/
|
fprintf(ficlog,"|"); |
| /* agev[m][i] = age[i]+2*m;*/
|
#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); |
| else { /* =9 */
|
#endif |
| agev[m][i]=1;
|
} |
| s[m][i]=-1;
|
}while(fx != fx && xxs > 1.e-5); |
| }
|
#endif |
| }
|
|
| else /*= 0 Unknown */
|
#ifdef DEBUGLINMIN |
| agev[m][i]=1;
|
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 |
| for (i=1; i<=imx; i++) {
|
#else |
| for(m=1; (m<= maxwav); m++){
|
if(fb == fx){ /* Flat function in the direction */ |
| if (s[m][i] > (nlstate+ndeath)) {
|
xmin=xx; |
| printf("Error: Wrong value in nlstate or ndeath\n");
|
*flat=1; |
| goto end;
|
}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),*/ |
| printf("Total number of individuals= %d, Agemin = %.2f, Agemax= %.2f\n\n", imx, agemin, agemax);
|
/* 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]) */ |
| free_vector(severity,1,maxwav);
|
/* P+lambda n in that direction (lambdamin), with TOL between abscisses */ |
| free_imatrix(outcome,1,maxwav+1,1,n);
|
/* f1dim(xmin): for (j=1;j<=ncom;j++) xt[j]=pcom[j]+xmin*xicom[j]; */ |
| free_vector(moisnais,1,n);
|
#ifdef DEBUG |
| free_vector(annais,1,n);
|
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); |
| free_matrix(mint,1,maxwav,1,n);
|
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); |
| free_matrix(anint,1,maxwav,1,n);
|
#endif |
| free_vector(moisdc,1,n);
|
#ifdef LINMINORIGINAL |
| free_vector(andc,1,n);
|
#else |
|
|
} |
|
|
#endif |
| wav=ivector(1,imx);
|
#ifdef DEBUGLINMIN |
| dh=imatrix(1,lastpass-firstpass+1,1,imx);
|
printf("linmin end "); |
| mw=imatrix(1,lastpass-firstpass+1,1,imx);
|
fprintf(ficlog,"linmin end "); |
|
|
#endif |
| /* Concatenates waves */
|
for (j=1;j<=n;j++) { |
| concatwav(wav, dh, mw, s, agedc, agev, firstpass, lastpass, imx, nlstate, stepm);
|
#ifdef LINMINORIGINAL |
|
|
xi[j] *= xmin; |
|
|
#else |
| Tcode=ivector(1,100);
|
#ifdef DEBUGLINMIN |
| nbcode=imatrix(0,NCOVMAX,0,NCOVMAX);
|
if(xxs <1.0) |
| ncodemax[1]=1;
|
printf(" before xi[%d]=%12.8f", j,xi[j]); |
| if (cptcovn > 0) tricode(Tvar,nbcode,imx);
|
#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) */ |
| codtab=imatrix(1,100,1,10);
|
#ifdef DEBUGLINMIN |
| h=0;
|
if(xxs <1.0) |
| m=pow(2,cptcoveff);
|
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 |
| for(k=1;k<=cptcoveff; k++){
|
#endif |
| for(i=1; i <=(m/pow(2,k));i++){
|
p[j] += xi[j]; /* Parameters values are updated accordingly */ |
| for(j=1; j <= ncodemax[k]; j++){
|
} |
| for(cpt=1; cpt <=(m/pow(2,cptcoveff+1-k)); cpt++){
|
#ifdef DEBUGLINMIN |
| h++;
|
printf("\n"); |
| if (h>m) h=1;codtab[h][k]=j;
|
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"); |
| /*for(i=1; i <=m ;i++){
|
fprintf(ficlog,"\n"); |
| for(k=1; k <=cptcovn; k++){
|
} |
| printf("i=%d k=%d %d %d",i,k,codtab[i][k], cptcoveff);
|
} |
| }
|
#else |
| printf("\n");
|
#endif |
| }
|
free_vector(xicom,1,n); |
| scanf("%d",i);*/
|
free_vector(pcom,1,n); |
|
|
} |
| /* Calculates basic frequencies. Computes observed prevalence at single age
|
|
| and prints on file fileres'p'. */
|
|
| freqsummary(fileres, agemin, agemax, s, agev, nlstate, imx,Tvar,nbcode, ncodemax);
|
/*************** powell ************************/ |
|
|
/* |
| pmmij= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
|
Minimization of a function func of n variables. Input consists of an initial starting point |
| oldms= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
|
p[1..n] ; an initial matrix xi[1..n][1..n] , whose columns contain the initial set of di- |
| newms= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
|
rections (usually the n unit vectors); and ftol , the fractional tolerance in the function value |
| savms= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
|
such that failure to decrease by more than this amount on one iteration signals doneness. On |
| oldm=oldms; newm=newms; savm=savms; /* Keeps fixed addresses to free */
|
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. |
| /* 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] */
|
#ifdef LINMINORIGINAL |
| p=param[1][1]; /* *(*(*(param +1)+1)+0) */
|
#else |
|
|
int *flatdir; /* Function is vanishing in that direction */ |
| if(mle==1){
|
int flat=0, flatd=0; /* Function is vanishing in that direction */ |
| mlikeli(ficres,p, npar, ncovmodel, nlstate, ftol, func);
|
#endif |
| }
|
void powell(double p[], double **xi, int n, double ftol, int *iter, double *fret, |
|
|
double (*func)(double [])) |
| /*--------- results files --------------*/
|
{ |
| fprintf(ficres,"\ntitle=%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\nmodel=%s\n", title, datafile, lastobs, firstpass,lastpass,ftol, stepm, ncov, nlstate, ndeath, maxwav, mle,weightopt,model);
|
#ifdef LINMINORIGINAL |
|
|
void linmin(double p[], double xi[], int n, double *fret, |
| jk=1;
|
double (*func)(double [])); |
| fprintf(ficres,"# Parameters\n");
|
#else |
| printf("# Parameters\n");
|
void linmin(double p[], double xi[], int n, double *fret, |
| for(i=1,jk=1; i <=nlstate; i++){
|
double (*func)(double []),int *flat); |
| for(k=1; k <=(nlstate+ndeath); k++){
|
#endif |
| if (k != i)
|
int i,ibig,j,jk,k; |
| {
|
double del,t,*pt,*ptt,*xit; |
| printf("%d%d ",i,k);
|
double directest; |
| fprintf(ficres,"%1d%1d ",i,k);
|
double fp,fptt; |
| for(j=1; j <=ncovmodel; j++){
|
double *xits; |
| printf("%f ",p[jk]);
|
int niterf, itmp; |
| fprintf(ficres,"%f ",p[jk]);
|
#ifdef LINMINORIGINAL |
| jk++;
|
#else |
| }
|
|
| printf("\n");
|
flatdir=ivector(1,n); |
| fprintf(ficres,"\n");
|
for (j=1;j<=n;j++) flatdir[j]=0; |
| }
|
#endif |
| }
|
|
| }
|
pt=vector(1,n); |
| if(mle==1){
|
ptt=vector(1,n); |
| /* Computing hessian and covariance matrix */
|
xit=vector(1,n); |
| ftolhess=ftol; /* Usually correct */
|
xits=vector(1,n); |
| hesscov(matcov, p, npar, delti, ftolhess, func);
|
*fret=(*func)(p); |
| }
|
for (j=1;j<=n;j++) pt[j]=p[j]; |
| fprintf(ficres,"# Scales\n");
|
rcurr_time = time(NULL); |
| printf("# Scales\n");
|
for (*iter=1;;++(*iter)) { |
| for(i=1,jk=1; i <=nlstate; i++){
|
fp=(*fret); /* From former iteration or initial value */ |
| for(j=1; j <=nlstate+ndeath; j++){
|
ibig=0; |
| if (j!=i) {
|
del=0.0; |
| fprintf(ficres,"%1d%1d",i,j);
|
rlast_time=rcurr_time; |
| printf("%1d%1d",i,j);
|
/* (void) gettimeofday(&curr_time,&tzp); */ |
| for(k=1; k<=ncovmodel;k++){
|
rcurr_time = time(NULL); |
| printf(" %.5e",delti[jk]);
|
curr_time = *localtime(&rcurr_time); |
| fprintf(ficres," %.5e",delti[jk]);
|
printf("\nPowell iter=%d -2*LL=%.12f %ld sec. %ld sec.",*iter,*fret, rcurr_time-rlast_time, rcurr_time-rstart_time);fflush(stdout); |
| jk++;
|
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); */ |
| printf("\n");
|
for (i=1;i<=n;i++) { |
| fprintf(ficres,"\n");
|
fprintf(ficrespow," %.12lf", p[i]); |
| }
|
} |
| }
|
fprintf(ficrespow,"\n");fflush(ficrespow); |
| }
|
printf("\n#model= 1 + age "); |
|
|
fprintf(ficlog,"\n#model= 1 + age "); |
| k=1;
|
if(nagesqr==1){ |
| fprintf(ficres,"# Covariance\n");
|
printf(" + age*age "); |
| printf("# Covariance\n");
|
fprintf(ficlog," + age*age "); |
| for(i=1;i<=npar;i++){
|
} |
| /* if (k>nlstate) k=1;
|
for(j=1;j <=ncovmodel-2;j++){ |
| i1=(i-1)/(ncovmodel*nlstate)+1;
|
if(Typevar[j]==0) { |
| fprintf(ficres,"%s%d%d",alph[k],i1,tab[i]);
|
printf(" + V%d ",Tvar[j]); |
| printf("%s%d%d",alph[k],i1,tab[i]);*/
|
fprintf(ficlog," + V%d ",Tvar[j]); |
| fprintf(ficres,"%3d",i);
|
}else if(Typevar[j]==1) { |
| printf("%3d",i);
|
printf(" + V%d*age ",Tvar[j]); |
| for(j=1; j<=i;j++){
|
fprintf(ficlog," + V%d*age ",Tvar[j]); |
| fprintf(ficres," %.5e",matcov[i][j]);
|
}else if(Typevar[j]==2) { |
| printf(" %.5e",matcov[i][j]);
|
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]); |
| fprintf(ficres,"\n");
|
} |
| printf("\n");
|
} |
| k++;
|
printf("\n"); |
| }
|
/* printf("12 47.0114589 0.0154322 33.2424412 0.3279905 2.3731903 */ |
|
|
/* 13 -21.5392400 0.1118147 1.2680506 1.2973408 -1.0663662 */ |
| while((c=getc(ficpar))=='#' && c!= EOF){
|
fprintf(ficlog,"\n"); |
| ungetc(c,ficpar);
|
for(i=1,jk=1; i <=nlstate; i++){ |
| fgets(line, MAXLINE, ficpar);
|
for(k=1; k <=(nlstate+ndeath); k++){ |
| puts(line);
|
if (k != i) { |
| fputs(line,ficparo);
|
printf("%d%d ",i,k); |
| }
|
fprintf(ficlog,"%d%d ",i,k); |
| ungetc(c,ficpar);
|
for(j=1; j <=ncovmodel; j++){ |
|
|
printf("%12.7f ",p[jk]); |
| fscanf(ficpar,"agemin=%lf agemax=%lf bage=%lf fage=%lf\n",&agemin,&agemax, &bage, &fage);
|
fprintf(ficlog,"%12.7f ",p[jk]); |
|
|
jk++; |
| if (fage <= 2) {
|
} |
| bage = agemin;
|
printf("\n"); |
| fage = agemax;
|
fprintf(ficlog,"\n"); |
| }
|
} |
|
|
} |
| 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);
|
if(*iter <=3 && *iter >1){ |
|
|
tml = *localtime(&rcurr_time); |
|
|
strcpy(strcurr,asctime(&tml)); |
| /*------------ gnuplot -------------*/
|
rforecast_time=rcurr_time; |
| chdir(pathcd);
|
itmp = strlen(strcurr); |
| if((ficgp=fopen("graph.plt","w"))==NULL) {
|
if(strcurr[itmp-1]=='\n') /* Windows outputs with a new line */ |
| printf("Problem with file graph.gp");goto end;
|
strcurr[itmp-1]='\0'; |
| }
|
printf("\nConsidering the time needed for the last iteration #%d: %ld seconds,\n",*iter,rcurr_time-rlast_time); |
| #ifdef windows
|
fprintf(ficlog,"\nConsidering the time needed for this last iteration #%d: %ld seconds,\n",*iter,rcurr_time-rlast_time); |
| fprintf(ficgp,"cd \"%s\" \n",pathc);
|
for(niterf=10;niterf<=30;niterf+=10){ |
| #endif
|
rforecast_time=rcurr_time+(niterf-*iter)*(rcurr_time-rlast_time); |
| m=pow(2,cptcoveff);
|
forecast_time = *localtime(&rforecast_time); |
|
|
strcpy(strfor,asctime(&forecast_time)); |
| /* 1eme*/
|
itmp = strlen(strfor); |
| for (cpt=1; cpt<= nlstate ; cpt ++) {
|
if(strfor[itmp-1]=='\n') |
| for (k1=1; k1<= m ; k1 ++) {
|
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); |
| #ifdef windows
|
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); |
| fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability\" \nset ter gif small size 400,300\nplot [%.f:%.f] \"vpl%s\" every :::%d::%d u 1:2 \"\%%lf",agemin,fage,fileres,k1-1,k1-1);
|
} |
| #endif
|
} |
| #ifdef unix
|
for (i=1;i<=n;i++) { /* For each direction i */ |
| fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability\" \nplot [%.f:%.f] \"vpl%s\" u 1:2 \"\%%lf",agemin,fage,fileres);
|
for (j=1;j<=n;j++) xit[j]=xi[j][i]; /* Directions stored from previous iteration with previous scales */ |
| #endif
|
fptt=(*fret); |
|
|
#ifdef DEBUG |
| for (i=1; i<= nlstate ; i ++) {
|
printf("fret=%lf, %lf, %lf \n", *fret, *fret, *fret); |
| if (i==cpt) fprintf(ficgp," \%%lf (\%%lf)");
|
fprintf(ficlog, "fret=%lf, %lf, %lf \n", *fret, *fret, *fret); |
| else fprintf(ficgp," \%%*lf (\%%*lf)");
|
#endif |
| }
|
printf("%d",i);fflush(stdout); /* print direction (parameter) i */ |
| fprintf(ficgp,"\" t\"Stationary prevalence\" w l 0,\"vpl%s\" every :::%d::%d u 1:($2+2*$3) \"\%%lf",fileres,k1-1,k1-1);
|
fprintf(ficlog,"%d",i);fflush(ficlog); |
| for (i=1; i<= nlstate ; i ++) {
|
#ifdef LINMINORIGINAL |
| if (i==cpt) fprintf(ficgp," \%%lf (\%%lf)");
|
linmin(p,xit,n,fret,func); /* Point p[n]. xit[n] has been loaded for direction i as input.*/ |
| else fprintf(ficgp," \%%*lf (\%%*lf)");
|
#else |
| }
|
linmin(p,xit,n,fret,func,&flat); /* Point p[n]. xit[n] has been loaded for direction i as input.*/ |
| fprintf(ficgp,"\" t\"95\%% CI\" w l 1,\"vpl%s\" every :::%d::%d u 1:($2-2*$3) \"\%%lf",fileres,k1-1,k1-1);
|
flatdir[i]=flat; /* Function is vanishing in that direction i */ |
| for (i=1; i<= nlstate ; i ++) {
|
#endif |
| if (i==cpt) fprintf(ficgp," \%%lf (\%%lf)");
|
/* Outputs are fret(new point p) p is updated and xit rescaled */ |
| else fprintf(ficgp," \%%*lf (\%%*lf)");
|
if (fabs(fptt-(*fret)) > del) { /* We are keeping the max gain on each of the n directions */ |
| }
|
/* because that direction will be replaced unless the gain del is small */ |
| fprintf(ficgp,"\" t\"\" w l 1,\"p%s\" every :::%d::%d u 1:($%d) t\"Observed prevalence \" w l 2",fileres,k1-1,k1-1,2+4*(cpt-1));
|
/* in comparison with the 'probable' gain, mu^2, with the last average direction. */ |
| #ifdef unix
|
/* Unless the n directions are conjugate some gain in the determinant may be obtained */ |
| fprintf(ficgp,"\nset ter gif small size 400,300");
|
/* with the new direction. */ |
| #endif
|
del=fabs(fptt-(*fret)); |
| fprintf(ficgp,"\nset out \"v%s%d%d.gif\" \nreplot\n\n",strtok(optionfile, "."),cpt,k1);
|
ibig=i; |
| }
|
} |
| }
|
#ifdef DEBUG |
| /*2 eme*/
|
printf("%d %.12e",i,(*fret)); |
|
|
fprintf(ficlog,"%d %.12e",i,(*fret)); |
| for (k1=1; k1<= m ; k1 ++) {
|
for (j=1;j<=n;j++) { |
| fprintf(ficgp,"set ylabel \"Years\" \nset ter gif small size 400,300\nplot [%.f:%.f] ",agemin,fage);
|
xits[j]=FMAX(fabs(p[j]-pt[j]),1.e-5); |
|
|
printf(" x(%d)=%.12e",j,xit[j]); |
| for (i=1; i<= nlstate+1 ; i ++) {
|
fprintf(ficlog," x(%d)=%.12e",j,xit[j]); |
| k=2*i;
|
} |
| fprintf(ficgp,"\"t%s\" every :::%d::%d u 1:2 \"\%%lf",fileres,k1-1,k1-1);
|
for(j=1;j<=n;j++) { |
| for (j=1; j<= nlstate+1 ; j ++) {
|
printf(" p(%d)=%.12e",j,p[j]); |
| if (j==i) fprintf(ficgp," \%%lf (\%%lf)");
|
fprintf(ficlog," p(%d)=%.12e",j,p[j]); |
| else fprintf(ficgp," \%%*lf (\%%*lf)");
|
} |
| }
|
printf("\n"); |
| if (i== 1) fprintf(ficgp,"\" t\"TLE\" w l ,");
|
fprintf(ficlog,"\n"); |
| else fprintf(ficgp,"\" t\"LE in state (%d)\" w l ,",i-1);
|
#endif |
| fprintf(ficgp,"\"t%s\" every :::%d::%d u 1:($2-$3*2) \"\%%lf",fileres,k1-1,k1-1);
|
} /* end loop on each direction i */ |
| for (j=1; j<= nlstate+1 ; j ++) {
|
/* Convergence test will use last linmin estimation (fret) and compare former iteration (fp) */ |
| if (j==i) fprintf(ficgp," \%%lf (\%%lf)");
|
/* But p and xit have been updated at the end of linmin, *fret corresponds to new p, xit */ |
| else fprintf(ficgp," \%%*lf (\%%*lf)");
|
/* New value of last point Pn is not computed, P(n-1) */ |
| }
|
for(j=1;j<=n;j++) { |
| fprintf(ficgp,"\" t\"\" w l 0,");
|
if(flatdir[j] >0){ |
| fprintf(ficgp,"\"t%s\" every :::%d::%d u 1:($2+$3*2) \"\%%lf",fileres,k1-1,k1-1);
|
printf(" p(%d)=%lf flat=%d ",j,p[j],flatdir[j]); |
| for (j=1; j<= nlstate+1 ; j ++) {
|
fprintf(ficlog," p(%d)=%lf flat=%d ",j,p[j],flatdir[j]); |
| if (j==i) fprintf(ficgp," \%%lf (\%%lf)");
|
} |
| else fprintf(ficgp," \%%*lf (\%%*lf)");
|
/* printf("\n"); */ |
| }
|
/* fprintf(ficlog,"\n"); */ |
| if (i== (nlstate+1)) fprintf(ficgp,"\" t\"\" w l 0");
|
} |
| else fprintf(ficgp,"\" t\"\" w l 0,");
|
/* 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? */ |
| fprintf(ficgp,"\nset out \"e%s%d.gif\" \nreplot\n\n",strtok(optionfile, "."),k1);
|
/* 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 */ |
| /*3eme*/
|
/* decreased of more than 3.84 */ |
|
|
/* By adding age*age and V1*age the gain (-2LL) should be more than 5.99 (ddl=2) */ |
| for (k1=1; k1<= m ; k1 ++) {
|
/* By using V1+V2+V3, the gain should be 7.82, compared with basic 1+age. */ |
| for (cpt=1; cpt<= nlstate ; cpt ++) {
|
/* By adding 10 parameters more the gain should be 18.31 */ |
| k=2+nlstate*(cpt-1);
|
|
| fprintf(ficgp,"set ter gif small size 400,300\nplot [%.f:%.f] \"e%s\" every :::%d::%d u 1:%d t \"e%d1\" w l",agemin,fage,fileres,k1-1,k1-1,k,cpt);
|
/* Starting the program with initial values given by a former maximization will simply change */ |
| for (i=1; i< nlstate ; i ++) {
|
/* the scales of the directions and the directions, because the are reset to canonical directions */ |
| fprintf(ficgp,",\"e%s\" every :::%d::%d u 1:%d t \"e%d%d\" w l",fileres,k1-1,k1-1,k+i,cpt,i+1);
|
/* 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. */ |
| fprintf(ficgp,"\nset out \"exp%s%d%d.gif\" \nreplot\n\n",strtok(optionfile, "."),cpt,k1);
|
#ifdef DEBUG |
| }
|
int k[2],l; |
| }
|
k[0]=1; |
|
|
k[1]=-1; |
| /* CV preval stat */
|
printf("Max: %.12e",(*func)(p)); |
| for (k1=1; k1<= m ; k1 ++) {
|
fprintf(ficlog,"Max: %.12e",(*func)(p)); |
| for (cpt=1; cpt<nlstate ; cpt ++) {
|
for (j=1;j<=n;j++) { |
| k=3;
|
printf(" %.12e",p[j]); |
| fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability\" \nset ter gif small size 400,300\nplot [%.f:%.f] \"pij%s\" u ($1==%d ? ($3):1/0):($%d/($%d",agemin,agemax,fileres,k1,k+cpt+1,k+1);
|
fprintf(ficlog," %.12e",p[j]); |
| for (i=1; i< nlstate ; i ++)
|
} |
| fprintf(ficgp,"+$%d",k+i+1);
|
printf("\n"); |
| fprintf(ficgp,")) t\"prev(%d,%d)\" w l",cpt,cpt+1);
|
fprintf(ficlog,"\n"); |
|
|
for(l=0;l<=1;l++) { |
| l=3+(nlstate+ndeath)*cpt;
|
for (j=1;j<=n;j++) { |
| fprintf(ficgp,",\"pij%s\" u ($1==%d ? ($3):1/0):($%d/($%d",fileres,k1,l+cpt+1,l+1);
|
ptt[j]=p[j]+(p[j]-pt[j])*k[l]; |
| for (i=1; i< nlstate ; i ++) {
|
printf("l=%d j=%d ptt=%.12e, xits=%.12e, p=%.12e, xit=%.12e", l,j,ptt[j],xits[j],p[j],xit[j]); |
| l=3+(nlstate+ndeath)*cpt;
|
fprintf(ficlog,"l=%d j=%d ptt=%.12e, xits=%.12e, p=%.12e, xit=%.12e", l,j,ptt[j],xits[j],p[j],xit[j]); |
| fprintf(ficgp,"+$%d",l+i+1);
|
} |
| }
|
printf("func(ptt)=%.12e, deriv=%.12e\n",(*func)(ptt),(ptt[j]-p[j])/((*func)(ptt)-(*func)(p))); |
| fprintf(ficgp,")) t\"prev(%d,%d)\" w l\n",cpt+1,cpt+1);
|
fprintf(ficlog,"func(ptt)=%.12e, deriv=%.12e\n",(*func)(ptt),(ptt[j]-p[j])/((*func)(ptt)-(*func)(p))); |
| fprintf(ficgp,"set out \"p%s%d%d.gif\" \nreplot\n\n",strtok(optionfile, "."),cpt,k1);
|
} |
| }
|
#endif |
| }
|
|
|
|
#ifdef LINMINORIGINAL |
| /* proba elementaires */
|
#else |
| for(i=1,jk=1; i <=nlstate; i++){
|
free_ivector(flatdir,1,n); |
| for(k=1; k <=(nlstate+ndeath); k++){
|
#endif |
| if (k != i) {
|
free_vector(xit,1,n); |
| for(j=1; j <=ncovmodel; j++){
|
free_vector(xits,1,n); |
| /*fprintf(ficgp,"%s%1d%1d=%f ",alph[j],i,k,p[jk]);*/
|
free_vector(ptt,1,n); |
| /*fprintf(ficgp,"%s",alph[1]);*/
|
free_vector(pt,1,n); |
| fprintf(ficgp,"p%d=%f ",jk,p[jk]);
|
return; |
| jk++;
|
} /* enough precision */ |
| fprintf(ficgp,"\n");
|
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]; |
|
|
} |
| for(jk=1; jk <=m; jk++) {
|
fptt=(*func)(ptt); /* f_3 */ |
| fprintf(ficgp,"\nset ter gif small size 400,300\nset log y\nplot [%.f:%.f] ",agemin,agemax);
|
#ifdef NODIRECTIONCHANGEDUNTILNITER /* No change in drections until some iterations are done */ |
| i=1;
|
if (*iter <=4) { |
| for(k2=1; k2<=nlstate; k2++) {
|
#else |
| k3=i;
|
#endif |
| for(k=1; k<=(nlstate+ndeath); k++) {
|
#ifdef POWELLNOF3INFF1TEST /* skips test F3 <F1 */ |
| if (k != k2){
|
#else |
| fprintf(ficgp," exp(p%d+p%d*x",i,i+1);
|
if (fptt < fp) { /* If extrapolated point is better, decide if we keep that new direction or not */ |
| ij=1;
|
#endif |
| for(j=3; j <=ncovmodel; j++) {
|
/* (x1 f1=fp), (x2 f2=*fret), (x3 f3=fptt), (xm fm) */ |
| if(((j-2)==Tage[ij]) &&(ij <=cptcovage)) {
|
/* From x1 (P0) distance of x2 is at h and x3 is 2h */ |
| fprintf(ficgp,"+p%d*%d*x",i+j-1,nbcode[Tvar[j-2]][codtab[jk][Tvar[j-2]]]);
|
/* Let f"(x2) be the 2nd derivative equal everywhere. */ |
| ij++;
|
/* 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 */ |
| else
|
/* Conditional for using this new direction is that mu^2 = (f1-2f2+f3)^2 /2 < del or directest <0 */ |
| fprintf(ficgp,"+p%d*%d",i+j-1,nbcode[Tvar[j-2]][codtab[jk][j-2]]);
|
/* 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 */ |
| fprintf(ficgp,")/(1");
|
/* 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 */ |
| for(k1=1; k1 <=nlstate; k1++){
|
/* mu² and del² are equal when f3=f1 */ |
| fprintf(ficgp,"+exp(p%d+p%d*x",k3+(k1-1)*ncovmodel,k3+(k1-1)*ncovmodel+1);
|
/* f3 < f1 : mu² < del <= lambda^2 both test are equivalent */ |
| ij=1;
|
/* f3 < f1 : mu² < lambda^2 < del then directtest is negative and powell t is positive */ |
| for(j=3; j <=ncovmodel; j++){
|
/* f3 > f1 : lambda² < mu^2 < del then t is negative and directest >0 */ |
| if(((j-2)==Tage[ij]) &&(ij <=cptcovage)) {
|
/* f3 > f1 : lambda² < del < mu^2 then t is positive and directest >0 */ |
| fprintf(ficgp,"+p%d*%d*x",k3+(k1-1)*ncovmodel+1+j-2,nbcode[Tvar[j-2]][codtab[jk][Tvar[j-2]]]);
|
#ifdef NRCORIGINAL |
| ij++;
|
t=2.0*(fp-2.0*(*fret)+fptt)*SQR(fp-(*fret)-del)- del*SQR(fp-fptt); /* Original Numerical Recipes in C*/ |
| }
|
#else |
| else
|
t=2.0*(fp-2.0*(*fret)+fptt)*SQR(fp-(*fret)-del); /* Intel compiler doesn't work on one line; bug reported */ |
| fprintf(ficgp,"+p%d*%d",k3+(k1-1)*ncovmodel+1+j-2,nbcode[Tvar[j-2]][codtab[jk][j-2]]);
|
t= t- del*SQR(fp-fptt); |
| }
|
#endif |
| fprintf(ficgp,")");
|
directest = fp-2.0*(*fret)+fptt - 2.0 * del; /* If delta was big enough we change it for a new direction */ |
| }
|
#ifdef DEBUG |
| fprintf(ficgp,") t \"p%d%d\" ", k2,k);
|
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); |
| if ((k+k2)!= (nlstate*2+ndeath)) fprintf(ficgp,",");
|
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); |
| i=i+ncovmodel;
|
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)); |
| fprintf(ficgp,"\nset out \"pe%s%d.gif\" \nreplot\n\n",strtok(optionfile, "."),jk);
|
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 |
| fclose(ficgp);
|
#ifdef POWELLORIGINAL |
|
|
if (t < 0.0) { /* Then we use it for new direction */ |
| chdir(path);
|
#else |
| free_matrix(agev,1,maxwav,1,imx);
|
if (directest*t < 0.0) { /* Contradiction between both tests */ |
| free_ivector(wav,1,imx);
|
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); |
| free_imatrix(dh,1,lastpass-firstpass+1,1,imx);
|
printf("f1-2f2+f3= %.12lf, f1-f2-del= %.12lf, f1-f3= %.12lf\n",fp-2.0*(*fret)+fptt, fp -(*fret) -del, fp-fptt); |
| free_imatrix(mw,1,lastpass-firstpass+1,1,imx);
|
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); |
| free_imatrix(s,1,maxwav+1,1,n);
|
} |
|
|
if (directest < 0.0) { /* Then we use it for new direction */ |
|
|
#endif |
| free_ivector(num,1,n);
|
#ifdef DEBUGLINMIN |
| free_vector(agedc,1,n);
|
printf("Before linmin in direction P%d-P0\n",n); |
| free_vector(weight,1,n);
|
for (j=1;j<=n;j++) { |
| /*free_matrix(covar,1,NCOVMAX,1,n);*/
|
printf(" Before xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]); |
| fclose(ficparo);
|
fprintf(ficlog," Before xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]); |
| fclose(ficres);
|
if(j % ncovmodel == 0){ |
| /* }*/
|
printf("\n"); |
|
|
fprintf(ficlog,"\n"); |
| /*________fin mle=1_________*/
|
} |
|
|
} |
|
|
#endif |
|
|
#ifdef LINMINORIGINAL |
| /* No more information from the sample is required now */
|
linmin(p,xit,n,fret,func); /* computes minimum on the extrapolated direction: changes p and rescales xit.*/ |
| /* Reads comments: lines beginning with '#' */
|
#else |
| while((c=getc(ficpar))=='#' && c!= EOF){
|
linmin(p,xit,n,fret,func,&flat); /* computes minimum on the extrapolated direction: changes p and rescales xit.*/ |
| ungetc(c,ficpar);
|
flatdir[i]=flat; /* Function is vanishing in that direction i */ |
| fgets(line, MAXLINE, ficpar);
|
#endif |
| puts(line);
|
|
| fputs(line,ficparo);
|
#ifdef DEBUGLINMIN |
| }
|
for (j=1;j<=n;j++) { |
| ungetc(c,ficpar);
|
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]); |
| fscanf(ficpar,"agemin=%lf agemax=%lf bage=%lf fage=%lf\n",&agemin,&agemax, &bage, &fage);
|
if(j % ncovmodel == 0){ |
| printf("agemin=%.0f agemax=%.0f bage=%.0f fage=%.0f\n",agemin,agemax, bage, fage);
|
printf("\n"); |
| fprintf(ficparo,"agemin=%.0f agemax=%.0f bage=%.0f fage=%.0f\n",agemin,agemax,bage,fage);
|
fprintf(ficlog,"\n"); |
| /*--------- index.htm --------*/
|
} |
|
|
} |
| strcpy(optionfilehtm,optionfile);
|
#endif |
| strcat(optionfilehtm,".htm");
|
for (j=1;j<=n;j++) { |
| if((fichtm=fopen(optionfilehtm,"w"))==NULL) {
|
xi[j][ibig]=xi[j][n]; /* Replace direction with biggest decrease by last direction n */ |
| printf("Problem with %s \n",optionfilehtm);goto end;
|
xi[j][n]=xit[j]; /* and this nth direction by the by the average p_0 p_n */ |
| }
|
} |
|
|
#ifdef LINMINORIGINAL |
| fprintf(fichtm,"<body><ul> <font size=\"6\">Imach, Version 0.64b </font> <hr size=\"2\" color=\"#EC5E5E\">
|
#else |
| Titre=%s <br>Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=%s<br>
|
for (j=1, flatd=0;j<=n;j++) { |
| Total number of observations=%d <br>
|
if(flatdir[j]>0) |
| Interval (in months) between two waves: Min=%d Max=%d Mean=%.2lf<br>
|
flatd++; |
| <hr size=\"2\" color=\"#EC5E5E\">
|
} |
| <li>Outputs files<br><br>\n
|
if(flatd >0){ |
| - Observed prevalence in each state: <a href=\"p%s\">p%s</a> <br>\n
|
printf("%d flat directions\n",flatd); |
| - Estimated parameters and the covariance matrix: <a href=\"%s\">%s</a> <br>
|
fprintf(ficlog,"%d flat directions\n",flatd); |
| - Stationary prevalence in each state: <a href=\"pl%s\">pl%s</a> <br>
|
for (j=1;j<=n;j++) { |
| - Transition probabilities: <a href=\"pij%s\">pij%s</a><br>
|
if(flatdir[j]>0){ |
| - Copy of the parameter file: <a href=\"o%s\">o%s</a><br>
|
printf("%d ",j); |
| - Life expectancies by age and initial health status: <a href=\"e%s\">e%s</a> <br>
|
fprintf(ficlog,"%d ",j); |
| - Variances of life expectancies by age and initial health status: <a href=\"v%s\">v%s</a><br>
|
} |
| - Health expectancies with their variances: <a href=\"t%s\">t%s</a> <br>
|
} |
| - Standard deviation of stationary prevalences: <a href=\"vpl%s\">vpl%s</a> <br><br>",title,datafile,firstpass,lastpass,stepm, weightopt,model,imx,jmin,jmax,jmean,fileres,fileres,fileres,fileres,fileres,fileres,fileres,fileres,fileres,fileres,fileres,fileres,fileres,fileres,fileres,fileres,fileres,fileres);
|
printf("\n"); |
|
|
fprintf(ficlog,"\n"); |
| fprintf(fichtm," <li>Graphs</li><p>");
|
} |
|
|
#endif |
| m=cptcoveff;
|
printf("Gaining to use new average direction of P0 P%d instead of biggest increase direction %d :\n",n,ibig); |
| if (cptcovn < 1) {m=1;ncodemax[1]=1;}
|
fprintf(ficlog,"Gaining to use new average direction of P0 P%d instead of biggest increase direction %d :\n",n,ibig); |
|
|
|
| j1=0;
|
#ifdef DEBUG |
| for(k1=1; k1<=m;k1++){
|
printf("Direction changed last moved %d in place of ibig=%d, new last is the average:\n",n,ibig); |
| for(i1=1; i1<=ncodemax[k1];i1++){
|
fprintf(ficlog,"Direction changed last moved %d in place of ibig=%d, new last is the average:\n",n,ibig); |
| j1++;
|
for(j=1;j<=n;j++){ |
| if (cptcovn > 0) {
|
printf(" %lf",xit[j]); |
| fprintf(fichtm,"<hr size=\"2\" color=\"#EC5E5E\">************ Results for covariates");
|
fprintf(ficlog," %lf",xit[j]); |
| for (cpt=1; cpt<=cptcoveff;cpt++)
|
} |
| fprintf(fichtm," V%d=%d ",Tvaraff[cpt],nbcode[Tvaraff[cpt]][codtab[j1][cpt]]);
|
printf("\n"); |
| fprintf(fichtm," ************\n<hr size=\"2\" color=\"#EC5E5E\">");
|
fprintf(ficlog,"\n"); |
| }
|
#endif |
| fprintf(fichtm,"<br>- Probabilities: pe%s%d.gif<br>
|
} /* end of t or directest negative */ |
| <img src=\"pe%s%d.gif\">",strtok(optionfile, "."),j1,strtok(optionfile, "."),j1);
|
#ifdef POWELLNOF3INFF1TEST |
| for(cpt=1; cpt<nlstate;cpt++){
|
#else |
| fprintf(fichtm,"<br>- Prevalence of disability : p%s%d%d.gif<br>
|
} /* end if (fptt < fp) */ |
| <img src=\"p%s%d%d.gif\">",strtok(optionfile, "."),cpt,j1,strtok(optionfile, "."),cpt,j1);
|
#endif |
| }
|
#ifdef NODIRECTIONCHANGEDUNTILNITER /* No change in drections until some iterations are done */ |
| for(cpt=1; cpt<=nlstate;cpt++) {
|
} /*NODIRECTIONCHANGEDUNTILNITER No change in drections until some iterations are done */ |
| fprintf(fichtm,"<br>- Observed and stationary prevalence (with confident
|
#else |
| interval) in state (%d): v%s%d%d.gif <br>
|
#endif |
| <img src=\"v%s%d%d.gif\">",cpt,strtok(optionfile, "."),cpt,j1,strtok(optionfile, "."),cpt,j1);
|
} /* loop iteration */ |
| }
|
} |
| for(cpt=1; cpt<=nlstate;cpt++) {
|
|
| fprintf(fichtm,"\n<br>- Health life expectancies by age and initial health state (%d): exp%s%d%d.gif <br>
|
/**** Prevalence limit (stable or period prevalence) ****************/ |
| <img src=\"exp%s%d%d.gif\">",cpt,strtok(optionfile, "."),cpt,j1,strtok(optionfile, "."),cpt,j1);
|
|
| }
|
double **prevalim(double **prlim, int nlstate, double x[], double age, double **oldm, double **savm, double ftolpl, int *ncvyear, int ij, int nres) |
| fprintf(fichtm,"\n<br>- Total life expectancy by age and
|
{ |
| health expectancies in states (1) and (2): e%s%d.gif<br>
|
/* Computes the prevalence limit in each live state at age x and for covariate combination ij |
| <img src=\"e%s%d.gif\">",strtok(optionfile, "."),j1,strtok(optionfile, "."),j1);
|
(and selected quantitative values in nres) |
| fprintf(fichtm,"\n</body>");
|
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 */ |
| fclose(fichtm);
|
/* Wx is row vector: population in state 1, population in state 2, population dead */ |
|
|
/* or prevalence in state 1, prevalence in state 2, 0 */ |
| /*--------------- Prevalence limit --------------*/
|
/* newm is the matrix after multiplications, its rows are identical at a factor */ |
|
|
/* Initial matrix pimij */ |
| strcpy(filerespl,"pl");
|
/* {0.85204250825084937, 0.13044499163996345, 0.017512500109187184, */ |
| strcat(filerespl,fileres);
|
/* 0.090851990222114765, 0.88271245433047185, 0.026435555447413338, */ |
| if((ficrespl=fopen(filerespl,"w"))==NULL) {
|
/* 0, 0 , 1} */ |
| printf("Problem with Prev limit resultfile: %s\n", filerespl);goto end;
|
/* |
| }
|
* and after some iteration: */ |
| printf("Computing prevalence limit: result on file '%s' \n", filerespl);
|
/* {0.45504275246439968, 0.42731458730878791, 0.11764266022681241, */ |
| fprintf(ficrespl,"#Prevalence limit\n");
|
/* 0.45201005341706885, 0.42865420071559901, 0.11933574586733192, */ |
| fprintf(ficrespl,"#Age ");
|
/* 0, 0 , 1} */ |
| for(i=1; i<=nlstate;i++) fprintf(ficrespl,"%d-%d ",i,i);
|
/* And prevalence by suppressing the deaths are close to identical rows in prlim: */ |
| fprintf(ficrespl,"\n");
|
/* {0.51571254859325999, 0.4842874514067399, */ |
|
|
/* 0.51326036147820708, 0.48673963852179264} */ |
| prlim=matrix(1,nlstate,1,nlstate);
|
/* If we start from prlim again, prlim tends to a constant matrix */ |
| pmmij= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
|
|
| oldms= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
|
int i, ii,j,k; |
| newms= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
|
double *min, *max, *meandiff, maxmax,sumnew=0.; |
| savms= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
|
/* double **matprod2(); */ /* test */ |
| oldm=oldms; newm=newms; savm=savms; /* Keeps fixed addresses to free */
|
double **out, cov[NCOVMAX+1], **pmij(); /* **pmmij is a global variable feeded with oldms etc */ |
| k=0;
|
double **newm; |
| agebase=agemin;
|
double agefin, delaymax=200. ; /* 100 Max number of years to converge */ |
| agelim=agemax;
|
int ncvloop=0; |
| ftolpl=1.e-10;
|
|
| i1=cptcoveff;
|
min=vector(1,nlstate); |
| if (cptcovn < 1){i1=1;}
|
max=vector(1,nlstate); |
|
|
meandiff=vector(1,nlstate); |
| for(cptcov=1;cptcov<=i1;cptcov++){
|
|
| for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){
|
/* Starting with matrix unity */ |
| k=k+1;
|
for (ii=1;ii<=nlstate+ndeath;ii++) |
| /*printf("cptcov=%d cptcod=%d codtab=%d nbcode=%d\n",cptcov, cptcod,Tcode[cptcode],codtab[cptcod][cptcov]);*/
|
for (j=1;j<=nlstate+ndeath;j++){ |
| fprintf(ficrespl,"\n#******");
|
oldm[ii][j]=(ii==j ? 1.0 : 0.0); |
| for(j=1;j<=cptcoveff;j++)
|
} |
| fprintf(ficrespl," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtab[k][j]]);
|
|
| fprintf(ficrespl,"******\n");
|
cov[1]=1.; |
|
|
|
| for (age=agebase; age<=agelim; age++){
|
/* Even if hstepm = 1, at least one multiplication by the unit matrix */ |
| prevalim(prlim, nlstate, p, age, oldm, savm,ftolpl,k);
|
/* Start at agefin= age, computes the matrix of passage and loops decreasing agefin until convergence is reached */ |
| fprintf(ficrespl,"%.0f",age );
|
for(agefin=age-stepm/YEARM; agefin>=age-delaymax; agefin=agefin-stepm/YEARM){ |
| for(i=1; i<=nlstate;i++)
|
ncvloop++; |
| fprintf(ficrespl," %.5f", prlim[i][i]);
|
newm=savm; |
| fprintf(ficrespl,"\n");
|
/* Covariates have to be included here again */ |
| }
|
cov[2]=agefin; |
| }
|
if(nagesqr==1) |
| }
|
cov[3]= agefin*agefin;; |
| fclose(ficrespl);
|
for (k=1; k<=nsd;k++) { /* For single dummy covariates only */ |
| /*------------- h Pij x at various ages ------------*/
|
/* 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)]; |
| strcpy(filerespij,"pij"); strcat(filerespij,fileres);
|
/* 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)); */ |
| if((ficrespij=fopen(filerespij,"w"))==NULL) {
|
} |
| printf("Problem with Pij resultfile: %s\n", filerespij);goto end;
|
for (k=1; k<=nsq;k++) { /* For single varying covariates only */ |
| }
|
/* Here comes the value of quantitative after renumbering k with single quantitative covariates */ |
| printf("Computing pij: result on file '%s' \n", filerespij);
|
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]); */ |
| stepsize=(int) (stepm+YEARM-1)/YEARM;
|
} |
| if (stepm<=24) stepsize=2;
|
for (k=1; k<=cptcovage;k++){ /* For product with age */ |
|
|
if(Dummy[Tvar[Tage[k]]]){ |
| agelim=AGESUP;
|
cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2]; |
| hstepm=stepsize*YEARM; /* Every year of age */
|
} else{ |
| hstepm=hstepm/stepm; /* Typically 2 years, = 2/6 months = 4 */
|
cov[2+nagesqr+Tage[k]]=Tqresult[nres][k]; |
|
|
} |
| k=0;
|
/* 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(cptcov=1;cptcov<=i1;cptcov++){
|
} |
| for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){
|
for (k=1; k<=cptcovprod;k++){ /* For product without age */ |
| k=k+1;
|
/* 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]); */ |
| fprintf(ficrespij,"\n#****** ");
|
if(Dummy[Tvard[k][1]==0]){ |
| for(j=1;j<=cptcoveff;j++)
|
if(Dummy[Tvard[k][2]==0]){ |
| fprintf(ficrespij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtab[k][j]]);
|
cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)]; |
| fprintf(ficrespij,"******\n");
|
}else{ |
|
|
cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * Tqresult[nres][k]; |
| for (agedeb=fage; agedeb>=bage; agedeb--){ /* If stepm=6 months */
|
} |
| nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
|
}else{ |
| nhstepm = nhstepm/hstepm; /* Typically 40/4=10 */
|
if(Dummy[Tvard[k][2]==0]){ |
| p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
|
cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][2]][codtabm(ij,k)] * Tqinvresult[nres][Tvard[k][1]]; |
| oldm=oldms;savm=savms;
|
}else{ |
| hpxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k);
|
cov[2+nagesqr+Tprod[k]]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]]; |
| fprintf(ficrespij,"# Age");
|
} |
| for(i=1; i<=nlstate;i++)
|
} |
| for(j=1; j<=nlstate+ndeath;j++)
|
} |
| fprintf(ficrespij," %1d-%1d",i,j);
|
/*printf("ij=%d cptcovprod=%d tvar=%d ", ij, cptcovprod, Tvar[1]);*/ |
| fprintf(ficrespij,"\n");
|
/*printf("ij=%d cov[3]=%lf cov[4]=%lf \n",ij, cov[3],cov[4]);*/ |
| for (h=0; h<=nhstepm; h++){
|
/*printf("ij=%d cov[3]=%lf \n",ij, cov[3]);*/ |
| fprintf(ficrespij,"%d %.0f %.0f",k,agedeb, agedeb+ h*hstepm/YEARM*stepm );
|
/* savm=pmij(pmmij,cov,ncovmodel,x,nlstate); */ |
| for(i=1; i<=nlstate;i++)
|
/* out=matprod2(newm, pmij(pmmij,cov,ncovmodel,x,nlstate),1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); /\* Bug Valgrind *\/ */ |
| for(j=1; j<=nlstate+ndeath;j++)
|
/* age and covariate values of ij are in 'cov' */ |
| fprintf(ficrespij," %.5f", p3mat[i][j][h]);
|
out=matprod2(newm, pmij(pmmij,cov,ncovmodel,x,nlstate),1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); /* Bug Valgrind */ |
| fprintf(ficrespij,"\n");
|
|
| }
|
savm=oldm; |
| free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
|
oldm=newm; |
| fprintf(ficrespij,"\n");
|
|
| }
|
for(j=1; j<=nlstate; j++){ |
| }
|
max[j]=0.; |
| }
|
min[j]=1.; |
|
|
} |
| fclose(ficrespij);
|
for(i=1;i<=nlstate;i++){ |
|
|
sumnew=0; |
| /*---------- Health expectancies and variances ------------*/
|
for(k=1; k<=ndeath; k++) sumnew+=newm[i][nlstate+k]; |
|
|
for(j=1; j<=nlstate; j++){ |
| strcpy(filerest,"t");
|
prlim[i][j]= newm[i][j]/(1-sumnew); |
| strcat(filerest,fileres);
|
max[j]=FMAX(max[j],prlim[i][j]); |
| if((ficrest=fopen(filerest,"w"))==NULL) {
|
min[j]=FMIN(min[j],prlim[i][j]); |
| printf("Problem with total LE resultfile: %s\n", filerest);goto end;
|
} |
| }
|
} |
| printf("Computing Total LEs with variances: file '%s' \n", filerest);
|
|
|
|
maxmax=0.; |
|
|
for(j=1; j<=nlstate; j++){ |
| strcpy(filerese,"e");
|
meandiff[j]=(max[j]-min[j])/(max[j]+min[j])*2.; /* mean difference for each column */ |
| strcat(filerese,fileres);
|
maxmax=FMAX(maxmax,meandiff[j]); |
| if((ficreseij=fopen(filerese,"w"))==NULL) {
|
/* 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); */ |
| printf("Problem with Health Exp. resultfile: %s\n", filerese); exit(0);
|
} /* j loop */ |
| }
|
*ncvyear= (int)age- (int)agefin; |
| printf("Computing Health Expectancies: result on file '%s' \n", filerese);
|
/* 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){ |
| strcpy(fileresv,"v");
|
/* printf("maxmax=%lf ncvloop=%ld, age=%d, agefin=%d ncvyear=%d \n", maxmax, ncvloop, (int)age, (int)agefin, *ncvyear); */ |
| strcat(fileresv,fileres);
|
free_vector(min,1,nlstate); |
| if((ficresvij=fopen(fileresv,"w"))==NULL) {
|
free_vector(max,1,nlstate); |
| printf("Problem with variance resultfile: %s\n", fileresv);exit(0);
|
free_vector(meandiff,1,nlstate); |
| }
|
return prlim; |
| printf("Computing Variance-covariance of DFLEs: file '%s' \n", fileresv);
|
} |
|
|
} /* age loop */ |
| k=0;
|
/* After some age loop it doesn't converge */ |
| for(cptcov=1;cptcov<=i1;cptcov++){
|
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\ |
| for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){
|
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); |
| k=k+1;
|
/* 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); */ |
| fprintf(ficrest,"\n#****** ");
|
free_vector(min,1,nlstate); |
| for(j=1;j<=cptcoveff;j++)
|
free_vector(max,1,nlstate); |
| fprintf(ficrest,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtab[k][j]]);
|
free_vector(meandiff,1,nlstate); |
| fprintf(ficrest,"******\n");
|
|
|
|
return prlim; /* should not reach here */ |
| fprintf(ficreseij,"\n#****** ");
|
} |
| for(j=1;j<=cptcoveff;j++)
|
|
| fprintf(ficreseij,"V%d=%d ",j,nbcode[j][codtab[k][j]]);
|
|
| fprintf(ficreseij,"******\n");
|
/**** Back Prevalence limit (stable or period prevalence) ****************/ |
|
|
|
| fprintf(ficresvij,"\n#****** ");
|
/* 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) */ |
| for(j=1;j<=cptcoveff;j++)
|
/* 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) */ |
| fprintf(ficresvij,"V%d=%d ",j,nbcode[j][codtab[k][j]]);
|
double **bprevalim(double **bprlim, double ***prevacurrent, int nlstate, double x[], double age, double ftolpl, int *ncvyear, int ij, int nres) |
| fprintf(ficresvij,"******\n");
|
{ |
|
|
/* Computes the prevalence limit in each live state at age x and covariate ij by left multiplying the unit |
| eij=ma3x(1,nlstate,1,nlstate,(int) bage, (int) fage);
|
matrix by transitions matrix until convergence is reached with precision ftolpl */ |
| oldm=oldms;savm=savms;
|
/* Wx= Wx-1 Px-1= Wx-2 Px-2 Px-1 = Wx-n Px-n ... Px-2 Px-1 I */ |
| evsij(fileres, eij, p, nlstate, stepm, (int) bage, (int)fage, oldm, savm, k);
|
/* Wx is row vector: population in state 1, population in state 2, population dead */ |
| vareij=ma3x(1,nlstate,1,nlstate,(int) bage, (int) fage);
|
/* or prevalence in state 1, prevalence in state 2, 0 */ |
| oldm=oldms;savm=savms;
|
/* newm is the matrix after multiplications, its rows are identical at a factor */ |
| varevsij(fileres, vareij, matcov, p, delti, nlstate, stepm, (int) bage, (int) fage, oldm, savm, prlim, ftolpl,k);
|
/* Initial matrix pimij */ |
|
|
/* {0.85204250825084937, 0.13044499163996345, 0.017512500109187184, */ |
| fprintf(ficrest,"#Total LEs with variances: e.. (std) ");
|
/* 0.090851990222114765, 0.88271245433047185, 0.026435555447413338, */ |
| for (i=1;i<=nlstate;i++) fprintf(ficrest,"e.%d (std) ",i);
|
/* 0, 0 , 1} */ |
| fprintf(ficrest,"\n");
|
/* |
|
|
* and after some iteration: */ |
| hf=1;
|
/* {0.45504275246439968, 0.42731458730878791, 0.11764266022681241, */ |
| if (stepm >= YEARM) hf=stepm/YEARM;
|
/* 0.45201005341706885, 0.42865420071559901, 0.11933574586733192, */ |
| epj=vector(1,nlstate+1);
|
/* 0, 0 , 1} */ |
| for(age=bage; age <=fage ;age++){
|
/* And prevalence by suppressing the deaths are close to identical rows in prlim: */ |
| prevalim(prlim, nlstate, p, age, oldm, savm,ftolpl,k);
|
/* {0.51571254859325999, 0.4842874514067399, */ |
| fprintf(ficrest," %.0f",age);
|
/* 0.51326036147820708, 0.48673963852179264} */ |
| for(j=1, epj[nlstate+1]=0.;j <=nlstate;j++){
|
/* If we start from prlim again, prlim tends to a constant matrix */ |
| for(i=1, epj[j]=0.;i <=nlstate;i++) {
|
|
| epj[j] += prlim[i][i]*hf*eij[i][j][(int)age];
|
int i, ii,j,k; |
| }
|
int first=0; |
| epj[nlstate+1] +=epj[j];
|
double *min, *max, *meandiff, maxmax,sumnew=0.; |
| }
|
/* double **matprod2(); */ /* test */ |
| for(i=1, vepp=0.;i <=nlstate;i++)
|
double **out, cov[NCOVMAX+1], **bmij(); |
| for(j=1;j <=nlstate;j++)
|
double **newm; |
| vepp += vareij[i][j][(int)age];
|
double **dnewm, **doldm, **dsavm; /* for use */ |
| fprintf(ficrest," %.2f (%.2f)", epj[nlstate+1],hf*sqrt(vepp));
|
double **oldm, **savm; /* for use */ |
| for(j=1;j <=nlstate;j++){
|
|
| fprintf(ficrest," %.2f (%.2f)", epj[j],hf*sqrt(vareij[j][j][(int)age]));
|
double agefin, delaymax=200. ; /* 100 Max number of years to converge */ |
| }
|
int ncvloop=0; |
| fprintf(ficrest,"\n");
|
|
| }
|
min=vector(1,nlstate); |
| }
|
max=vector(1,nlstate); |
| }
|
meandiff=vector(1,nlstate); |
|
|
|
| fclose(ficreseij);
|
dnewm=ddnewms; doldm=ddoldms; dsavm=ddsavms; |
| fclose(ficresvij);
|
oldm=oldms; savm=savms; |
| fclose(ficrest);
|
|
| fclose(ficpar);
|
/* Starting with matrix unity */ |
| free_vector(epj,1,nlstate+1);
|
for (ii=1;ii<=nlstate+ndeath;ii++) |
| /* scanf("%d ",i); */
|
for (j=1;j<=nlstate+ndeath;j++){ |
|
|
oldm[ii][j]=(ii==j ? 1.0 : 0.0); |
| /*------- Variance limit prevalence------*/
|
} |
|
|
|
| strcpy(fileresvpl,"vpl");
|
cov[1]=1.; |
| strcat(fileresvpl,fileres);
|
|
| if((ficresvpl=fopen(fileresvpl,"w"))==NULL) {
|
/* Even if hstepm = 1, at least one multiplication by the unit matrix */ |
| printf("Problem with variance prev lim resultfile: %s\n", fileresvpl);
|
/* Start at agefin= age, computes the matrix of passage and loops decreasing agefin until convergence is reached */ |
| exit(0);
|
/* 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 */ |
| printf("Computing Variance-covariance of Prevalence limit: file '%s' \n", fileresvpl);
|
ncvloop++; |
|
|
newm=savm; /* oldm should be kept from previous iteration or unity at start */ |
| k=0;
|
/* newm points to the allocated table savm passed by the function it can be written, savm could be reallocated */ |
| for(cptcov=1;cptcov<=i1;cptcov++){
|
/* Covariates have to be included here again */ |
| for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){
|
cov[2]=agefin; |
| k=k+1;
|
if(nagesqr==1) |
| fprintf(ficresvpl,"\n#****** ");
|
cov[3]= agefin*agefin;; |
| for(j=1;j<=cptcoveff;j++)
|
for (k=1; k<=nsd;k++) { /* For single dummy covariates only */ |
| fprintf(ficresvpl,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtab[k][j]]);
|
/* Here comes the value of the covariate 'ij' after renumbering k with single dummy covariates */ |
| fprintf(ficresvpl,"******\n");
|
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)); */ |
| varpl=matrix(1,nlstate,(int) bage, (int) fage);
|
} |
| oldm=oldms;savm=savms;
|
/* for (k=1; k<=cptcovn;k++) { */ |
| varprevlim(fileres, varpl, matcov, p, delti, nlstate, stepm, (int) bage, (int) fage, oldm, savm, prlim, ftolpl,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])]); *\/ */ |
|
|
/* } */ |
| fclose(ficresvpl);
|
for (k=1; k<=nsq;k++) { /* For single varying covariates only */ |
|
|
/* Here comes the value of quantitative after renumbering k with single quantitative covariates */ |
| /*---------- End : free ----------------*/
|
cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k]; |
| free_matrix(varpl,1,nlstate,(int) bage, (int)fage);
|
/* 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]); */ |
|
|
} |
| free_ma3x(vareij,1,nlstate,1,nlstate,(int) bage, (int)fage);
|
/* for (k=1; k<=cptcovage;k++) cov[2+nagesqr+Tage[k]]=nbcode[Tvar[k]][codtabm(ij,k)]*cov[2]; */ |
| free_ma3x(eij,1,nlstate,1,nlstate,(int) bage, (int)fage);
|
/* 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)]; */ |
| free_matrix(pmmij,1,nlstate+ndeath,1,nlstate+ndeath);
|
for (k=1; k<=cptcovage;k++){ /* For product with age */ |
| free_matrix(oldms, 1,nlstate+ndeath,1,nlstate+ndeath);
|
if(Dummy[Tvar[Tage[k]]]){ |
| free_matrix(newms, 1,nlstate+ndeath,1,nlstate+ndeath);
|
cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2]; |
| free_matrix(savms, 1,nlstate+ndeath,1,nlstate+ndeath);
|
} else{ |
|
|
cov[2+nagesqr+Tage[k]]=Tqresult[nres][k]; |
| free_matrix(matcov,1,npar,1,npar);
|
} |
| free_vector(delti,1,npar);
|
/* 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]); */ |
|
|
} |
| free_ma3x(param,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
|
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]); */ |
| printf("End of Imach\n");
|
if(Dummy[Tvard[k][1]==0]){ |
| /* gettimeofday(&end_time, (struct timezone*)0);*/ /* after time */
|
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)]; |
| /* 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);*/
|
}else{ |
| /*printf("Total time was %d uSec.\n", total_usecs);*/
|
cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * Tqresult[nres][k]; |
| /*------ End -----------*/
|
} |
|
|
}else{ |
| end:
|
if(Dummy[Tvard[k][2]==0]){ |
| #ifdef windows
|
cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][2]][codtabm(ij,k)] * Tqinvresult[nres][Tvard[k][1]]; |
| chdir(pathcd);
|
}else{ |
| #endif
|
cov[2+nagesqr+Tprod[k]]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]]; |
| /*system("wgnuplot graph.plt");*/
|
} |
| /*system("../gp37mgw/wgnuplot graph.plt");*/
|
} |
| /*system("cd ../gp37mgw");*/
|
} |
| system("..\\gp37mgw\\wgnuplot graph.plt");
|
|
|
|
/*printf("ij=%d cptcovprod=%d tvar=%d ", ij, cptcovprod, Tvar[1]);*/ |
| #ifdef windows
|
/*printf("ij=%d cov[3]=%lf cov[4]=%lf \n",ij, cov[3],cov[4]);*/ |
| while (z[0] != 'q') {
|
/*printf("ij=%d cov[3]=%lf \n",ij, cov[3]);*/ |
| chdir(pathcd);
|
/* savm=pmij(pmmij,cov,ncovmodel,x,nlstate); */ |
| printf("\nType e to edit output files, c to start again, and q for exiting: ");
|
/* out=matprod2(newm, pmij(pmmij,cov,ncovmodel,x,nlstate),1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); /\* Bug Valgrind *\/ */ |
| scanf("%s",z);
|
/* ij should be linked to the correct index of cov */ |
| if (z[0] == 'c') system("./imach");
|
/* age and covariate values ij are in 'cov', but we need to pass |
| else if (z[0] == 'e') {
|
* ij for the observed prevalence at age and status and covariate |
| chdir(path);
|
* number: prevacurrent[(int)agefin][ii][ij] |
| system(optionfilehtm);
|
*/ |
| }
|
/* 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 *\/ */ |
| else if (z[0] == 'q') exit(0);
|
/* 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 */ |
| #endif
|
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 ***************/ |
| |
|
| |
double **pmij(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(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++){ |
| |
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(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++){ |
| |
ps[ii][jj]=0; |
| |
ps[ii][ii]=1; |
| |
} |
| |
} |
| |
/* 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,int nrl, int nrh, int ncl, int nch, int ncolol, int ncoloh, double **b) |
| |
{ |
| |
/* 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 */ |
| |
int i, j, k; |
| |
for(i=nrl; i<= nrh; i++) |
| |
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, int ij, int nres ) |
| |
{ |
| |
/* 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 |
| |
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; |
| |
|
| |
/* 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 */ |
| |
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,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]; |
| |
/*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, kk; |
| |
int ioffset=0; |
| |
double l, ll[NLSTATEMAX+1], cov[NCOVMAX+1]; |
| |
double **out; |
| |
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]); |
| |
*/ |
| |
|
| |
++countcallfunc; |
| |
|
| |
cov[1]=1.; |
| |
|
| |
for(k=1; k<=nlstate; k++) ll[k]=0.; |
| |
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 */ |
| |
|
| |
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; |
| |
/*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; |
| |
} |
| |
|
| |
|
| |
/*************** 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 ncovmodel, int nlstate, double ftol, double (*func)(double [])) |
| |
{ |
| |
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"); 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 |
| |
|
| |
#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 **hess, double p[], int npar, double delti[], double ftolhess, double (*func)(double [])) |
| |
{ |
| |
double **a,**y,*x,pd; |
| |
/* double **hess; */ |
| |
int i, j; |
| |
int *indx; |
| |
|
| |
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) ; |
| |
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); |
| |
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); |
| |
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); |
| |
x=vector(1,npar); |
| |
indx=ivector(1,npar); |
| |
for (i=1;i<=npar;i++) |
| |
for (j=1;j<=npar;j++) a[i][j]=hess[i][j]; |
| |
ludcmp(a,npar,indx,&pd); |
| |
|
| |
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++){ |
| |
matcov[i][j]=x[i]; |
| |
} |
| |
} |
| |
|
| |
printf("\n#Hessian matrix#\n"); |
| |
fprintf(ficlog,"\n#Hessian matrix#\n"); |
| |
for (i=1;i<=npar;i++) { |
| |
for (j=1;j<=npar;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); */ |
| |
|
| |
/* 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#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++){ |
| |
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); */ |
| |
|
| |
|
| |
} |
| |
|
| |
/*************** hessian matrix ****************/ |
| |
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, 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++){ /* 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; /* 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 2 because L and not 2*L */ |
| |
|
| |
#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; |
| |
} |
| |
else if((k1 >khi/nkhi) || (k2 >khi/nkhi)){ |
| |
delts=delt; |
| |
} |
| |
} /* End loop k */ |
| |
} |
| |
delti[theta]=delts; |
| |
return res; |
| |
|
| |
} |
| |
|
| |
double hessij( double x[], double **hess, 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]; |
| |
int k, kmax=1; |
| |
double v1, v2, cv12, lc1, lc2; |
| |
|
| |
int firstime=0; |
| |
|
| |
fx=func(x); |
| |
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; |
| |
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 */ |
| |
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) |
| |
{ |
| |
int i,imax,j,k; |
| |
double big,dum,sum,temp; |
| |
double *vv; |
| |
|
| |
vv=vector(1,n); |
| |
*d=1.0; |
| |
for (i=1;i<=n;i++) { |
| |
big=0.0; |
| |
for (j=1;j<=n;j++) |
| |
if ((temp=fabs(a[i][j])) > big) big=temp; |
| |
if (big == 0.0) nrerror("Singular matrix in routine ludcmp"); |
| |
vv[i]=1.0/big; |
| |
} |
| |
for (j=1;j<=n;j++) { |
| |
for (i=1;i<j;i++) { |
| |
sum=a[i][j]; |
| |
for (k=1;k<i;k++) sum -= a[i][k]*a[k][j]; |
| |
a[i][j]=sum; |
| |
} |
| |
big=0.0; |
| |
for (i=j;i<=n;i++) { |
| |
sum=a[i][j]; |
| |
for (k=1;k<j;k++) |
| |
sum -= a[i][k]*a[k][j]; |
| |
a[i][j]=sum; |
| |
if ( (dum=vv[i]*fabs(sum)) >= big) { |
| |
big=dum; |
| |
imax=i; |
| |
} |
| |
} |
| |
if (j != imax) { |
| |
for (k=1;k<=n;k++) { |
| |
dum=a[imax][k]; |
| |
a[imax][k]=a[j][k]; |
| |
a[j][k]=dum; |
| |
} |
| |
*d = -(*d); |
| |
vv[imax]=vv[j]; |
| |
} |
| |
indx[j]=imax; |
| |
if (a[j][j] == 0.0) a[j][j]=TINY; |
| |
if (j != n) { |
| |
dum=1.0/(a[j][j]); |
| |
for (i=j+1;i<=n;i++) a[i][j] *= dum; |
| |
} |
| |
} |
| |
free_vector(vv,1,n); /* Doesn't work */ |
| |
; |
| |
} |
| |
|
| |
void lubksb(double **a, int n, int *indx, double b[]) |
| |
{ |
| |
int i,ii=0,ip,j; |
| |
double sum; |
| |
|
| |
for (i=1;i<=n;i++) { |
| |
ip=indx[i]; |
| |
sum=b[ip]; |
| |
b[ip]=b[i]; |
| |
if (ii) |
| |
for (j=ii;j<=i-1;j++) sum -= a[i][j]*b[j]; |
| |
else if (sum) ii=i; |
| |
b[i]=sum; |
| |
} |
| |
for (i=n;i>=1;i--) { |
| |
sum=b[i]; |
| |
for (j=i+1;j<=n;j++) sum -= a[i][j]*b[j]; |
| |
b[i]=sum/a[i][i]; |
| |
} |
| |
} |
| |
|
| |
void pstamp(FILE *fichier) |
| |
{ |
| |
fprintf(fichier,"# %s.%s\n#IMaCh version %s, %s\n#%s\n# %s", optionfilefiname,optionfilext,version,copyright, fullversion, strstart); |
| |
} |
| |
|
| |
/************ Frequencies ********************/ |
| |
void freqsummary(char fileres[], 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 */ |
| |
|
| |
int i, m, jk, j1, bool, z1,j, k, iv; |
| |
int iind=0, iage=0; |
| |
int mi; /* Effective wave */ |
| |
int first; |
| |
double ***freq; /* Frequencies */ |
| |
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); |
| |
prop=matrix(1,nlstate,iagemin-AGEMARGE,iagemax+3+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</title></head>\n <body><font size=\"2\">%s <br> %s</font> \ |
| |
<hr size=\"2\" color=\"#EC5E5E\"> \n \ |
| |
Title=%s <br>Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s<br>\n",\ |
| |
fileresphtm,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model); |
| |
} |
| |
fprintf(ficresphtm,"Current page is file <a href=\"%s\">%s</a><br>\n\n<h4>Frequencies and prevalence by age at begin of transition and dummy covariate value at beginning of transition</h4>\n",fileresphtm, fileresphtm); |
| |
|
| |
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,"<html><head>\n<title>IMaCh PHTM_Frequency table %s</title></head>\n <body><font size=\"2\">%s <br> %s</font> \ |
| |
<hr size=\"2\" color=\"#EC5E5E\"> \n \ |
| |
Title=%s <br>Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s<br>\n",\ |
| |
fileresphtmfr,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model); |
| |
} |
| |
fprintf(ficresphtmfr,"Current page is file <a href=\"%s\">%s</a><br>\n\n<h4>Frequencies of all effective transitions of the model, by age at begin of transition, and covariate value at the begin of transition (if the covariate is a varying covariate) </h4>Unknown status is -1<br/>\n",fileresphtmfr, fileresphtmfr); |
| |
|
| |
freq= ma3x(-5,nlstate+ndeath,-5,nlstate+ndeath,iagemin-AGEMARGE,iagemax+3+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; |
| |
|
| |
for (j = 0; j <= cptcoveff; j+=cptcoveff){ |
| |
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 (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++) { |
| |
/* 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)]){ |
| |
/* Tests if this individual iind responded to j1 (V4=1 V3=0) */ |
| |
bool=0; |
| |
/* 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<wav[iind];mi++){ /* For that wave */ |
| |
m=mw[mi][iind]; |
| |
if(j!=0){ |
| |
if(anyvaryingduminmodel==1){ /* Some are varying covariates */ |
| |
for (z1=1; z1<=cptcoveff; z1++) { |
| |
if( Fixed[Tmodelind[z1]]==1){ |
| |
iv= Tvar[Tmodelind[z1]]-ncovcol-nqv; |
| |
if (cotvar[m][iv][iind]!= nbcode[Tvaraff[z1]][codtabm(j1,z1)]) /* iv=1 to ntv, right modality */ |
| |
bool=0; /* not selected */ |
| |
}else if( Fixed[Tmodelind[z1]]== 0) { /* fixed */ |
| |
if (covar[Tvaraff[z1]][iind]!= nbcode[Tvaraff[z1]][codtabm(j1,z1)]) { |
| |
bool=0; |
| |
} |
| |
} |
| |
} |
| |
}/* Some are varying covariates, we tried to speed up if all fixed covariates in the model, avoiding waves loop */ |
| |
} /* end j==0 */ |
| |
/* bool =0 we keep that guy which corresponds to the combination of dummy values */ |
| |
if(bool==1){ |
| |
/* dh[m][iind] or dh[mw[mi][iind]][iind] is the delay between two effective (mi) waves m=mw[mi][iind] |
| |
and mw[mi+1][iind]. dh depends on stepm. */ |
| |
agebegin=agev[m][iind]; /* Age at beginning of wave before transition*/ |
| |
ageend=agev[m][iind]+(dh[m][iind])*stepm/YEARM; /* Age at end of wave and transition */ |
| |
if(m >=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 (m<lastpass) { |
| |
/* if(s[m][iind]==4 && s[m+1][iind]==4) */ |
| |
/* printf(" num=%ld m=%d, iind=%d s1=%d s2=%d agev at m=%d\n", num[iind], m, iind,s[m][iind],s[m+1][iind], (int)agev[m][iind]); */ |
| |
if(s[m][iind]==-1) |
| |
printf(" num=%ld m=%d, iind=%d s1=%d s2=%d agev at m=%d agebegin=%.2f ageend=%.2f, agemed=%d\n", num[iind], m, iind,s[m][iind],s[m+1][iind], (int)agev[m][iind],agebegin, ageend, (int)((agebegin+ageend)/2.)); |
| |
freq[s[m][iind]][s[m+1][iind]][(int)agev[m][iind]] += weight[iind]; /* At age of beginning of transition, where status is known */ |
| |
/* freq[s[m][iind]][s[m+1][iind]][(int)((agebegin+ageend)/2.)] += weight[iind]; */ |
| |
freq[s[m][iind]][s[m+1][iind]][iagemax+3] += weight[iind]; /* Total is in iagemax+3 *//* At age of beginning of transition, where status is known */ |
| |
} |
| |
} /* end if between passes */ |
| |
if ((agev[m][iind]>1) && (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); */ |
| |
} |
| |
} /* 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){ |
| |
fprintf(ficresp, "\n#********** Variable "); |
| |
fprintf(ficresphtm, "\n<br/><br/><h3>********** Variable "); |
| |
fprintf(ficresphtmfr, "\n<br/><br/><h3>********** Variable "); |
| |
fprintf(ficlog, "\n#********** Variable "); |
| |
for (z1=1; z1<=cptcoveff; z1++){ |
| |
if(DummyV[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{ |
| |
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)]); |
| |
} |
| |
} |
| |
fprintf(ficresp, "**********\n#"); |
| |
fprintf(ficresphtm, "**********</h3>\n"); |
| |
fprintf(ficresphtmfr, "**********</h3>\n"); |
| |
fprintf(ficlog, "**********\n"); |
| |
} |
| |
fprintf(ficresphtm,"<table style=\"text-align:center; border: 1px solid\">"); |
| |
for(i=1; i<=nlstate;i++) { |
| |
fprintf(ficresp, " Age Prev(%d) N(%d) N ",i,i); |
| |
fprintf(ficresphtm, "<th>Age</th><th>Prev(%d)</th><th>N(%d)</th><th>N</th>",i,i); |
| |
} |
| |
fprintf(ficresp, "\n"); |
| |
fprintf(ficresphtm, "\n"); |
| |
|
| |
/* Header of frequency table by age */ |
| |
fprintf(ficresphtmfr,"<table style=\"text-align:center; border: 1px solid\">"); |
| |
fprintf(ficresphtmfr,"<th>Age</th> "); |
| |
for(jk=-1; jk <=nlstate+ndeath; jk++){ |
| |
for(m=-1; m <=nlstate+ndeath; m++){ |
| |
if(jk!=0 && m!=0) |
| |
fprintf(ficresphtmfr,"<th>%d%d</th> ",jk,m); |
| |
} |
| |
} |
| |
fprintf(ficresphtmfr, "\n"); |
| |
|
| |
/* For each age */ |
| |
for(iage=iagemin; iage <= iagemax+3; iage++){ |
| |
fprintf(ficresphtm,"<tr>"); |
| |
if(iage==iagemax+1){ |
| |
fprintf(ficlog,"1"); |
| |
fprintf(ficresphtmfr,"<tr><th>0</th> "); |
| |
}else if(iage==iagemax+2){ |
| |
fprintf(ficlog,"0"); |
| |
fprintf(ficresphtmfr,"<tr><th>Unknown</th> "); |
| |
}else if(iage==iagemax+3){ |
| |
fprintf(ficlog,"Total"); |
| |
fprintf(ficresphtmfr,"<tr><th>Total</th> "); |
| |
}else{ |
| |
if(first==1){ |
| |
first=0; |
| |
printf("See log file for details...\n"); |
| |
} |
| |
fprintf(ficresphtmfr,"<tr><th>%d</th> ",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,"<th>%d</th><td>%.5f</td><td>%.0f</td><td>%.0f</td>",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,"<th>%d</th><td>NaNq</td><td>%.0f</td><td>%.0f</td>",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]); |
| |
} |
| |
fprintf(ficlog," %d%d=%.0f",jk,m,freq[jk][m][iage]); |
| |
} |
| |
if(jk!=0 && m!=0) |
| |
fprintf(ficresphtmfr,"<td>%.0f</td> ",freq[jk][m][iage]); |
| |
} |
| |
} /* end loop jk */ |
| |
posproptt=0.; |
| |
for(jk=1; jk <=nlstate; jk++){ |
| |
posproptt += pospropt[jk]; |
| |
} |
| |
fprintf(ficresphtmfr,"</tr>\n "); |
| |
if(iage <= iagemax){ |
| |
fprintf(ficresp,"\n"); |
| |
fprintf(ficresphtm,"</tr>\n"); |
| |
} |
| |
if(first==1) |
| |
printf("Others in log...\n"); |
| |
fprintf(ficlog,"\n"); |
| |
} /* end loop age iage */ |
| |
fprintf(ficresphtm,"<tr><th>Tot</th>"); |
| |
for(jk=1; jk <=nlstate ; jk++){ |
| |
if(posproptt < 1.e-5){ |
| |
fprintf(ficresphtm,"<td>Nanq</td><td>%.0f</td><td>%.0f</td>",pospropt[jk],posproptt); |
| |
}else{ |
| |
fprintf(ficresphtm,"<td>%.5f</td><td>%.0f</td><td>%.0f</td>",pospropt[jk]/posproptt,pospropt[jk],posproptt); |
| |
} |
| |
} |
| |
fprintf(ficresphtm,"</tr>\n"); |
| |
fprintf(ficresphtm,"</table>\n"); |
| |
fprintf(ficresphtmfr,"</table>\n"); |
| |
if(posproptt < 1.e-5){ |
| |
fprintf(ficresphtm,"\n <p><b> This combination (%d) is not valid and no result will be produced</b></p>",j1); |
| |
fprintf(ficresphtmfr,"\n <p><b> This combination (%d) is not valid and no result will be produced</b></p>",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 <p> This combination (%d) is valid and result will be produced.</p>",j1); |
| |
invalidvarcomb[j1]=0; |
| |
} |
| |
fprintf(ficresphtmfr,"</table>\n"); |
| |
} /* end selected combination of covariate j1 */ |
| |
if(j==0){ /* We can estimate starting values from the occurences in each case */ |
| |
for(jk=-1; jk <=nlstate+ndeath; jk++){ |
| |
for(m=-1; m <=nlstate+ndeath; m++){ |
| |
/* param[i]|j][k]= freq[jk][m][iagemax+3] */ |
| |
if(freq[jk][m][iage] !=0 ) { /* minimizing output */ |
| |
if(first==1){ |
| |
printf(" %d%d=%.0f",jk,m,freq[jk][m][iage]); |
| |
} |
| |
fprintf(ficlog," %d%d=%.0f",jk,m,freq[jk][m][iage]); |
| |
} |
| |
} |
| |
} /* end loop jk */ |
| |
} |
| |
} /* end j */ |
| |
dateintmean=dateintsum/k2cpt; |
| |
|
| |
fclose(ficresp); |
| |
fclose(ficresphtm); |
| |
fclose(ficresphtmfr); |
| |
free_vector(meanq,1,nqfveff); |
| |
free_matrix(meanqt,1,lastpass,1,nqtveff); |
| |
free_ma3x(freq,-5,nlstate+ndeath,-5,nlstate+ndeath, iagemin-AGEMARGE, iagemax+3+AGEMARGE); |
| |
free_vector(pospropt,1,nlstate); |
| |
free_vector(posprop,1,nlstate); |
| |
free_matrix(prop,1,nlstate,iagemin-AGEMARGE, iagemax+3+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+3+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+3+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<wav[i];mi++){ /* For this wave too look where individual can be counted V4=0 V3=0 */ |
| |
m=mw[mi][i]; |
| |
/* Tmodelind[z1]=k is the position of the varying covariate in the model, but which # within 1 to ntv? */ |
| |
/* Tvar[Tmodelind[z1]] is the n of Vn; n-ncovcol-nqv is the first time varying covariate or iv */ |
| |
for (z1=1; z1<=cptcoveff; z1++){ |
| |
if( Fixed[Tmodelind[z1]]==1){ |
| |
iv= Tvar[Tmodelind[z1]]-ncovcol-nqv; |
| |
if (cotvar[m][iv][i]!= nbcode[Tvaraff[z1]][codtabm(j1,z1)]) /* iv=1 to ntv, right modality */ |
| |
bool=0; |
| |
}else if( Fixed[Tmodelind[z1]]== 0) /* fixed */ |
| |
if (covar[Tvaraff[z1]][i]!= nbcode[Tvaraff[z1]][codtabm(j1,z1)]) { |
| |
bool=0; |
| |
} |
| |
} |
| |
if(bool==1){ /* Otherwise we skip that wave/person */ |
| |
agebegin=agev[m][i]; /* Age at beginning of wave before transition*/ |
| |
/* ageend=agev[m][i]+(dh[m][i])*stepm/YEARM; /\* Age at end of wave and transition *\/ */ |
| |
if(m >=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] <iagemin-AGEMARGE || (int)agev[m][i] >iagemax+3+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+3+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] 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=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){ /* 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; |
| |
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 |
| |
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 */ |
| |
|
| |
/* 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 */ |
| |
mw[mi][i]=m; |
| |
} |
| |
#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<wav[i];mi++){ |
| |
if (stepm <=0) |
| |
dh[mi][i]=1; |
| |
else{ |
| |
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; |
| |
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(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 */ |
| |
} |
| |
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(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, no variances */ |
| |
int i, j, nhstepm, hstepm, h, nstepm; |
| |
int nhstepma, nstepma; /* Decreasing with age */ |
| |
double age, agelim, hf; |
| |
double ***p3mat; |
| |
double eip; |
| |
|
| |
/* 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," e%1d%1d ",i,j); |
| |
} |
| |
fprintf(ficreseij," e%1d. ",i); |
| |
} |
| |
fprintf(ficreseij,"\n"); |
| |
|
| |
|
| |
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; |
| |
/* 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 */ |
| |
|
| |
/* 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-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]);*/ |
| |
|
| |
} |
| |
|
| |
fprintf(ficreseij,"%3.0f",age ); |
| |
for(i=1; i<=nlstate;i++){ |
| |
eip=0; |
| |
for(j=1; j<=nlstate;j++){ |
| |
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); |
| |
printf("\n"); |
| |
fprintf(ficlog,"\n"); |
| |
|
| |
} |
| |
|
| |
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 ) |
| |
|
| |
{ |
| |
/* 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; |
| |
double *xp, *xm; |
| |
double **gp, **gm; |
| |
double ***gradg, ***trgradg; |
| |
int theta; |
| |
|
| |
double eip, vip; |
| |
|
| |
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(ficresstdeij," e%1d%1d (SE)",i,j); |
| |
fprintf(ficresstdeij," e%1d. ",i); |
| |
} |
| |
fprintf(ficresstdeij,"\n"); |
| |
|
| |
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"); |
| |
|
| |
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++){ |
| |
xp[i] = x[i] + (i==theta ?delti[theta]:0); |
| |
xm[i] = x[i] - (i==theta ?delti[theta]:0); |
| |
} |
| |
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(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(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 */ |
| |
|
| |
|
| |
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(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; |
| |
} |
| |
} |
| |
|
| |
/* 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++){ |
| |
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(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(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<li><h4> Computing probabilities of dying over estepm months as a weighted average (i.e global mortality independent of initial healh state)</h4></li>\n"); |
| |
fprintf(fichtm,"\n<br>%s <br>\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<br> File (multiple files are possible if covariates are present): <A href=\"%s\">%s</a>\n",subdirf(fileresprobmorprev),subdirf(fileresprobmorprev)); |
| |
fprintf(fichtm,"\n<br> Probability is computed over estepm=%d months. <br> <img src=\"%s%s.svg\"> <br>\n", estepm,subdirf3(optionfilefiname,"VARMUPTJGR-",digitp),digit); |
| |
/* fprintf(fichtm,"\n<br> Probability is computed over estepm=%d months and then divided by estepm and multiplied by %.0f in order to have the probability to die over a year <br> <img src=\"varmuptjgr%s%s.svg\"> <br>\n", stepm,YEARM,digitp,digit); |
| |
*/ |
| |
/* 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, int *ncvyearp, int ij, char strstart[], int nres) |
| |
{ |
| |
/* 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; |
| |
double *xp; |
| |
double *gp, *gm; |
| |
double **gradg, **trgradg; |
| |
double **mgm, **mgp; |
| |
double age,agelim; |
| |
int theta; |
| |
|
| |
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"); |
| |
|
| |
xp=vector(1,npar); |
| |
dnewm=matrix(1,nlstate,1,npar); |
| |
doldm=matrix(1,nlstate,1,nlstate); |
| |
|
| |
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 */ |
| |
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); |
| |
|
| |
for(theta=1; theta <=npar; theta++){ |
| |
for(i=1; i<=npar; i++){ /* Computes gradient */ |
| |
xp[i] = x[i] + (i==theta ?delti[theta]:0); |
| |
} |
| |
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); |
| |
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); |
| |
|
| |
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 */ |
| |
|
| |
free_vector(xp,1,npar); |
| |
free_matrix(doldm,1,nlstate,1,npar); |
| |
free_matrix(dnewm,1,nlstate,1,nlstate); |
| |
|
| |
} |
| |
|
| |
/************ 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<li><h4> Computing and drawing one step probabilities with their confidence intervals</h4></li>\n"); |
| |
fprintf(fichtm,"\n"); |
| |
|
| |
fprintf(fichtm,"\n<li><h4> <a href=\"%s\">Matrix of variance-covariance of one-step probabilities (drawings)</a></h4> this page is important in order to visualize confidence intervals and especially correlation between disability and recovery, or more generally, way in and way back.</li>\n",optionfilehtmcov); |
| |
fprintf(fichtmcov,"Current page is file <a href=\"%s\">%s</a><br>\n\n<h4>Matrix of variance-covariance of pairs of step probabilities</h4>\n",optionfilehtmcov, optionfilehtmcov); |
| |
fprintf(fichtmcov,"\nEllipsoids of confidence centered on point (p<inf>ij</inf>, p<inf>kl</inf>) are estimated \ |
| |
and drawn. It helps understanding how is the covariance between two incidences.\ |
| |
They are expressed in year<sup>-1</sup> in order to be less dependent of stepm.<br>\n"); |
| |
fprintf(fichtmcov,"\n<br> Contour plot corresponding to x'cov<sup>-1</sup>x = 4 (where x is the column vector (pij,pkl)) are drawn. \ |
| |
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. <br>\ |
| |
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.<br>\ |
| |
To be simple, these graphs help to understand the significativity of each parameter in relation to a second other one.<br> \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<hr size=\"2\" color=\"#EC5E5E\">********** Variable "); |
| |
for (z1=1; z1<=cptcoveff; z1++) fprintf(fichtm, "V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]); |
| |
fprintf(fichtmcov, "**********\n<hr size=\"2\" color=\"#EC5E5E\">"); |
| |
|
| |
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<h3>Combination (%d) ignored because no cases </h3>\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<br>Probability with confidence intervals expressed in year<sup>-1</sup> :<a href=\"pijgr%s.png\">pijgr%s.png</A>, ",optionfilefiname,optionfilefiname); |
| |
fprintf(fichtm,"\n<br><img src=\"pijgr%s.png\"> ",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<br>Ellipsoids of confidence cov(p%1d%1d,p%1d%1d) expressed in year<sup>-1</sup>\ |
| |
:<a href=\"%s_%d%1d%1d-%1d%1d.svg\"> \ |
| |
%s_%d%1d%1d-%1d%1d.svg</A>, ",k1,l1,k2,l2,\ |
| |
subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2, \ |
| |
subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2); |
| |
fprintf(fichtmcov,"\n<br><img src=\"%s_%d%1d%1d-%1d%1d.svg\"> ",subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2); |
| |
fprintf(fichtmcov,"\n<br> 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,"<ul><li><a href='#firstorder'>Result files (first order: no variance)</a>\n \ |
| |
<li><a href='#secondorder'>Result files (second order (variance)</a>\n \ |
| |
</ul>"); |
| |
fprintf(fichtm,"<ul><li> model=1+age+%s\n \ |
| |
</ul>", model); |
| |
fprintf(fichtm,"<ul><li><h4><a name='firstorder'>Result files (first order: no variance)</a></h4>\n"); |
| |
fprintf(fichtm,"<li>- Observed frequency between two states (during the period defined between %.lf/%.lf/%.lf and %.lf/%.lf/%.lf): <a href=\"%s\">%s</a> (html file)<br/>\n", |
| |
jprev1, mprev1,anprev1,jprev2, mprev2,anprev2,subdirfext3(optionfilefiname,"PHTMFR_",".htm"),subdirfext3(optionfilefiname,"PHTMFR_",".htm")); |
| |
fprintf(fichtm,"<li> - Observed prevalence in each state (during the period defined between %.lf/%.lf/%.lf and %.lf/%.lf/%.lf): <a href=\"%s\">%s</a> (html file) ", |
| |
jprev1, mprev1,anprev1,jprev2, mprev2,anprev2,subdirfext3(optionfilefiname,"PHTM_",".htm"),subdirfext3(optionfilefiname,"PHTM_",".htm")); |
| |
fprintf(fichtm,", <a href=\"%s\">%s</a> (text file) <br>\n",subdirf2(fileresu,"P_"),subdirf2(fileresu,"P_")); |
| |
fprintf(fichtm,"\ |
| |
- Estimated transition probabilities over %d (stepm) months: <a href=\"%s\">%s</a><br>\n ", |
| |
stepm,subdirf2(fileresu,"PIJ_"),subdirf2(fileresu,"PIJ_")); |
| |
fprintf(fichtm,"\ |
| |
- Estimated back transition probabilities over %d (stepm) months: <a href=\"%s\">%s</a><br>\n ", |
| |
stepm,subdirf2(fileresu,"PIJB_"),subdirf2(fileresu,"PIJB_")); |
| |
fprintf(fichtm,"\ |
| |
- Period (stable) prevalence in each health state: <a href=\"%s\">%s</a> <br>\n", |
| |
subdirf2(fileresu,"PL_"),subdirf2(fileresu,"PL_")); |
| |
fprintf(fichtm,"\ |
| |
- Period (stable) back prevalence in each health state: <a href=\"%s\">%s</a> <br>\n", |
| |
subdirf2(fileresu,"PLB_"),subdirf2(fileresu,"PLB_")); |
| |
fprintf(fichtm,"\ |
| |
- (a) Life expectancies by health status at initial age, e<sub>i.</sub> (b) health expectancies by health status at initial age, e<sub>ij</sub> . If one or more covariates are included, specific tables for each value of the covariate are output in sequences within the same file (estepm=%2d months): \ |
| |
<a href=\"%s\">%s</a> <br>\n", |
| |
estepm,subdirf2(fileresu,"E_"),subdirf2(fileresu,"E_")); |
| |
if(prevfcast==1){ |
| |
fprintf(fichtm,"\ |
| |
- Prevalence projections by age and states: \ |
| |
<a href=\"%s\">%s</a> <br>\n</li>", subdirf2(fileresu,"F_"),subdirf2(fileresu,"F_")); |
| |
} |
| |
|
| |
fprintf(fichtm," \n<ul><li><b>Graphs</b></li><p>"); |
| |
|
| |
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(TKresult[nres]!= k1) |
| |
continue; |
| |
|
| |
/* for(i1=1; i1<=ncodemax[k1];i1++){ */ |
| |
jj1++; |
| |
if (cptcovn > 0) { |
| |
fprintf(fichtm,"<hr size=\"2\" color=\"#EC5E5E\">************ 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<hr size=\"2\" color=\"#EC5E5E\">"); |
| |
if(invalidvarcomb[k1]){ |
| |
fprintf(fichtm,"\n<h3>Combination (%d) ignored because no cases </h3>\n",k1); |
| |
printf("\nCombination (%d) ignored because no cases \n",k1); |
| |
continue; |
| |
} |
| |
} |
| |
/* aij, bij */ |
| |
fprintf(fichtm,"<br>- Logit model (yours is: 1+age+%s), for example: logit(pij)=log(pij/pii)= aij+ bij age + V1 age + etc. as a function of age: <a href=\"%s_%d-1-%d.svg\">%s_%d-1-%d.svg</a><br> \ |
| |
<img src=\"%s_%d-1-%d.svg\">",model,subdirf2(optionfilefiname,"PE_"),k1,nres,subdirf2(optionfilefiname,"PE_"),k1,nres,subdirf2(optionfilefiname,"PE_"),k1,nres); |
| |
/* Pij */ |
| |
fprintf(fichtm,"<br>\n- P<sub>ij</sub> or conditional probabilities to be observed in state j being in state i, %d (stepm) months before: <a href=\"%s_%d-2-%d.svg\">%s_%d-2-%d.svg</a><br> \ |
| |
<img src=\"%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,"<br>\n- I<sub>ij</sub> 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 <sub>h</sub>P<sub>ij</sub> \ |
| |
divided by h: <sub>h</sub>P<sub>ij</sub>/h : <a href=\"%s_%d-3-%d.svg\">%s_%d-3-%d.svg</a><br> \ |
| |
<img src=\"%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,"<br>\n- Survival functions in state %d. Or probability to survive in state %d being in state (1 to %d) at different ages. <a href=\"%s_%d-%d-%d.svg\">%s_%d-%d-%d.svg</a><br> \ |
| |
<img src=\"%s_%d-%d-%d.svg\">", cpt, cpt, nlstate, subdirf2(optionfilefiname,"LIJ_"),cpt,k1,nres,subdirf2(optionfilefiname,"LIJ_"),cpt,k1,nres,subdirf2(optionfilefiname,"LIJ_"),cpt,k1,nres); |
| |
} |
| |
/* State specific survival functions (period) */ |
| |
for(cpt=1; cpt<=nlstate;cpt++){ |
| |
fprintf(fichtm,"<br>\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. \ |
| |
<a href=\"%s_%d-%d-%d.svg\">%s_%d%d-%d.svg</a><br> <img src=\"%s_%d-%d-%d.svg\">", cpt, nlstate, cpt, subdirf2(optionfilefiname,"LIJT_"),cpt,k1,nres,subdirf2(optionfilefiname,"LIJT_"),cpt,k1,nres,subdirf2(optionfilefiname,"LIJT_"),cpt,k1,nres); |
| |
} |
| |
/* Period (stable) prevalence in each health state */ |
| |
for(cpt=1; cpt<=nlstate;cpt++){ |
| |
fprintf(fichtm,"<br>\n- Convergence to period (stable) prevalence in state %d. Or probability to be in state %d being in state (1 to %d) at different ages. <a href=\"%s_%d-%d-%d.svg\">%s_%d-%d-%d.svg</a><br> \ |
| |
<img src=\"%s_%d-%d-%d.svg\">", cpt, cpt, nlstate, subdirf2(optionfilefiname,"P_"),cpt,k1,nres,subdirf2(optionfilefiname,"P_"),cpt,k1,nres,subdirf2(optionfilefiname,"P_"),cpt,k1,nres); |
| |
} |
| |
if(backcast==1){ |
| |
/* Period (stable) back prevalence in each health state */ |
| |
for(cpt=1; cpt<=nlstate;cpt++){ |
| |
fprintf(fichtm,"<br>\n- Convergence to period (stable) back prevalence in state %d. Or probability to be in state %d being in state (1 to %d) at different ages. <a href=\"%s_%d-%d-%d.svg\">%s_%d-%d-%d.svg</a><br> \ |
| |
<img src=\"%s_%d-%d-%d.svg\">", cpt, cpt, nlstate, subdirf2(optionfilefiname,"PB_"),cpt,k1,nres,subdirf2(optionfilefiname,"PB_"),cpt,k1,nres,subdirf2(optionfilefiname,"PB_"),cpt,k1,nres); |
| |
} |
| |
} |
| |
if(prevfcast==1){ |
| |
/* Projection of prevalence up to period (stable) prevalence in each health state */ |
| |
for(cpt=1; cpt<=nlstate;cpt++){ |
| |
fprintf(fichtm,"<br>\n- Projection of cross-sectional prevalence (estimated with cases observed from %.1f to %.1f) up to period (stable) prevalence in state %d. Or probability to be in state %d being in state (1 to %d) at different ages. <a href=\"%s_%d-%d-%d.svg\">%s_%d-%d-%d.svg</a><br> \ |
| |
<img src=\"%s_%d-%d-%d.svg\">", dateprev1, dateprev2, cpt, cpt, nlstate, subdirf2(optionfilefiname,"PROJ_"),cpt,k1,nres,subdirf2(optionfilefiname,"PROJ_"),cpt,k1,nres,subdirf2(optionfilefiname,"PROJ_"),cpt,k1,nres); |
| |
} |
| |
} |
| |
|
| |
for(cpt=1; cpt<=nlstate;cpt++) { |
| |
fprintf(fichtm,"\n<br>- Life expectancy by health state (%d) at initial age and its decomposition into health expectancies in each alive state (1 to %d) (or area under each survival functions): <a href=\"%s_%d-%d-%d.svg\">%s_%d-%d-%d.svg</a> <br> \ |
| |
<img src=\"%s_%d-%d-%d.svg\">",cpt,nlstate,subdirf2(optionfilefiname,"EXP_"),cpt,k1,nres,subdirf2(optionfilefiname,"EXP_"),cpt,k1,nres,subdirf2(optionfilefiname,"EXP_"),cpt,k1,nres); |
| |
} |
| |
/* } /\* end i1 *\/ */ |
| |
}/* End k1 */ |
| |
fprintf(fichtm,"</ul>"); |
| |
|
| |
fprintf(fichtm,"\ |
| |
\n<br><li><h4> <a name='secondorder'>Result files (second order: variances)</a></h4>\n\ |
| |
- Parameter file with estimated parameters and covariance matrix: <a href=\"%s\">%s</a> <br> \ |
| |
- 95%% confidence intervals and Wald tests of the estimated parameters are in the log file if optimization has been done (mle != 0).<br> \ |
| |
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: <a href=\"%s\">%s</a> <br>\n", |
| |
subdirf2(fileresu,"PROB_"),subdirf2(fileresu,"PROB_")); |
| |
fprintf(fichtm,"\ |
| |
- Variance-covariance of one-step probabilities: <a href=\"%s\">%s</a> <br>\n", |
| |
subdirf2(fileresu,"PROBCOV_"),subdirf2(fileresu,"PROBCOV_")); |
| |
|
| |
fprintf(fichtm,"\ |
| |
- Correlation matrix of one-step probabilities: <a href=\"%s\">%s</a> <br>\n", |
| |
subdirf2(fileresu,"PROBCOR_"),subdirf2(fileresu,"PROBCOR_")); |
| |
fprintf(fichtm,"\ |
| |
- Variances and covariances of health expectancies by age and <b>initial health status</b> (cov(e<sup>ij</sup>,e<sup>kl</sup>)(estepm=%2d months): \ |
| |
<a href=\"%s\">%s</a> <br>\n</li>", |
| |
estepm,subdirf2(fileresu,"CVE_"),subdirf2(fileresu,"CVE_")); |
| |
fprintf(fichtm,"\ |
| |
- (a) Health expectancies by health status at initial age (e<sup>ij</sup>) and standard errors (in parentheses) (b) life expectancies and standard errors (e<sup>i.</sup>=e<sup>i1</sup>+e<sup>i2</sup>+...)(estepm=%2d months): \ |
| |
<a href=\"%s\">%s</a> <br>\n</li>", |
| |
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), e<sup>ij</sup> are weighted by the period prevalences in each state i (if popbased=1, an additional computation is done using the cross-sectional prevalences, i.e population based) (estepm=%d months): <a href=\"%s\">%s</a><br>\n", |
| |
estepm, subdirf2(fileresu,"V_"),subdirf2(fileresu,"V_")); |
| |
fprintf(fichtm,"\ |
| |
- Total life expectancy and total health expectancies to be spent in each health state e<sup>.j</sup> with their standard errors (if popbased=1, an additional computation is done using the cross-sectional prevalences, i.e population based) (estepm=%d months): <a href=\"%s\">%s</a> <br>\n", |
| |
estepm, subdirf2(fileresu,"T_"),subdirf2(fileresu,"T_")); |
| |
fprintf(fichtm,"\ |
| |
- Standard deviation of period (stable) prevalences: <a href=\"%s\">%s</a> <br>\n",\ |
| |
subdirf2(fileresu,"VPL_"),subdirf2(fileresu,"VPL_")); |
| |
|
| |
/* if(popforecast==1) fprintf(fichtm,"\n */ |
| |
/* - Prevalences forecasting: <a href=\"f%s\">f%s</a> <br>\n */ |
| |
/* - Population forecasting (if popforecast=1): <a href=\"pop%s\">pop%s</a> <br>\n */ |
| |
/* <br>",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 .)<br><br></li>\n",popforecast, stepm, model); */ |
| |
fflush(fichtm); |
| |
fprintf(fichtm," <ul><li><b>Graphs</b></li><p>"); |
| |
|
| |
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(TKresult[nres]!= k1) |
| |
continue; |
| |
/* for(i1=1; i1<=ncodemax[k1];i1++){ */ |
| |
jj1++; |
| |
if (cptcovn > 0) { |
| |
fprintf(fichtm,"<hr size=\"2\" color=\"#EC5E5E\">************ 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<hr size=\"2\" color=\"#EC5E5E\">"); |
| |
|
| |
if(invalidvarcomb[k1]){ |
| |
fprintf(fichtm,"\n<h4>Combination (%d) ignored because no cases </h4>\n",k1); |
| |
continue; |
| |
} |
| |
} |
| |
for(cpt=1; cpt<=nlstate;cpt++) { |
| |
fprintf(fichtm,"\n<br>- Observed (cross-sectional) and period (incidence based) \ |
| |
prevalence (with 95%% confidence interval) in state (%d): <a href=\"%s_%d-%d-%d.svg\"> %s_%d-%d-%d.svg</a>\n <br>\ |
| |
<img src=\"%s_%d-%d-%d.svg\">",cpt,subdirf2(optionfilefiname,"V_"),cpt,k1,nres,subdirf2(optionfilefiname,"V_"),cpt,k1,nres,subdirf2(optionfilefiname,"V_"),cpt,k1,nres); |
| |
} |
| |
fprintf(fichtm,"\n<br>- 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: <a href=\"%s_%d-%d.svg\">%s_%d-%d.svg</a>\n<br>\ |
| |
<img src=\"%s_%d-%d.svg\">",subdirf2(optionfilefiname,"E_"),k1,nres,subdirf2(optionfilefiname,"E_"),k1,nres,subdirf2(optionfilefiname,"E_"),k1,nres); |
| |
/* } /\* end i1 *\/ */ |
| |
}/* End k1 */ |
| |
}/* End nres */ |
| |
fprintf(fichtm,"</ul>"); |
| |
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(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(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(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(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(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(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(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(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 <cptcoveff && cptcoveff>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(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(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<imx;i++) popeffectif[popage[i]]=popcount[i]; */ |
| |
/* } */ |
| |
|
| |
/* for(cptcov=1,k=0;cptcov<=i2;cptcov++){ */ |
| |
/* for(cptcod=1;cptcod<=ncodemax[cptcoveff];cptcod++){ */ |
| |
/* k=k+1; */ |
| |
/* fprintf(ficrespop,"\n#******"); */ |
| |
/* for(j=1;j<=cptcoveff;j++) { */ |
| |
/* fprintf(ficrespop," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]); */ |
| |
/* } */ |
| |
/* fprintf(ficrespop,"******\n"); */ |
| |
/* fprintf(ficrespop,"# Age"); */ |
| |
/* for(j=1; j<=nlstate+ndeath;j++) fprintf(ficrespop," P.%d",j); */ |
| |
/* if (popforecast==1) fprintf(ficrespop," [Population]"); */ |
| |
|
| |
/* for (cpt=0; cpt<=0;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(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(ll<jj){ |
| |
if(itimes==1){ |
| |
printf(" Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj); |
| |
fprintf(ficparo," Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj); |
| |
}else{ |
| |
printf(" 0."); |
| |
fprintf(ficparo," 0."); |
| |
} |
| |
}else{ |
| |
if(itimes==1){ |
| |
printf(" Var(%s%1d%1d)",ca,i,j); |
| |
fprintf(ficparo," Var(%s%1d%1d)",ca,i,j); |
| |
}else{ |
| |
printf(" 0."); |
| |
fprintf(ficparo," 0."); |
| |
} |
| |
} |
| |
} |
| |
} /* end lk */ |
| |
} /* end lj */ |
| |
} /* end li */ |
| |
printf("\n"); |
| |
fprintf(ficparo,"\n"); |
| |
numlinepar++; |
| |
} /* end k*/ |
| |
} /*end j */ |
| |
} /* end i */ |
| |
} /* end itimes */ |
| |
|
| |
} /* end of prwizard */ |
| |
/******************* Gompertz Likelihood ******************************/ |
| |
double gompertz(double x[]) |
| |
{ |
| |
double A,B,L=0.0,sump=0.,num=0.; |
| |
int i,n=0; /* n is the size of the sample */ |
| |
|
| |
for (i=1;i<=imx ; 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]);*/ |
| |
|
| |
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,"<ul><li><h4>Result files </h4>\n Force of mortality. Parameters of the Gompertz fit (with confidence interval in brackets):<br>"); |
| |
fprintf(fichtm," mu(age) =%lf*exp(%lf*(age-%d)) per year<br><br>",p[1],p[2],agegomp); |
| |
for (i=1;i<=2;i++) |
| |
fprintf(fichtm," p[%d] = %lf [%f ; %f]<br>\n",i,p[i],p[i]-2*sqrt(matcov[i][i]),p[i]+2*sqrt(matcov[i][i])); |
| |
fprintf(fichtm,"<br><br><img src=\"graphmort.svg\">"); |
| |
fprintf(fichtm,"</ul>"); |
| |
|
| |
fprintf(fichtm,"<ul><li><h4>Life table</h4>\n <br>"); |
| |
|
| |
fprintf(fichtm,"\nAge l<inf>x</inf> q<inf>x</inf> d(x,x+1) L<inf>x</inf> T<inf>x</inf> e<infx</inf><br>"); |
| |
|
| |
for (k=agegomp;k<(agemortsup-2);k++) |
| |
fprintf(fichtm,"%d %.0lf %lf %.0lf %.0lf %.0lf %lf<br>\n",k,lsurv[k],p[1]*exp(p[2]*(k-agegomp)),(p[1]*exp(p[2]*(k-agegomp)))*lsurv[k],lpop[k],tpop[k],tpop[k]/lsurv[k]); |
| |
|
| |
|
| |
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 != 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 <k1;k2++){ |
| |
if((Typevar[k1]==Typevar[k2]) && (Fixed[Tvar[k1]]==Fixed[Tvar[k2]]) && (Dummy[Tvar[k1]]==Dummy[Tvar[k2]] )){ |
| |
if((Typevar[k1] == 0 || Typevar[k1] == 1)){ /* Simple or age product */ |
| |
if(Tvar[k1]==Tvar[k2]){ |
| |
printf("Error duplication in the model=%s at positions (+) %d and %d, Tvar[%d]=V%d, Tvar[%d]=V%d, Typevar=%d, Fixed=%d, Dummy=%d\n", model, k1,k2, k1, Tvar[k1], k2, Tvar[k2],Typevar[k1],Fixed[Tvar[k1]],Dummy[Tvar[k1]]); |
| |
fprintf(ficlog,"Error duplication in the model=%s at positions (+) %d and %d, Tvar[%d]=V%d, Tvar[%d]=V%d, Typevar=%d, Fixed=%d, Dummy=%d\n", model, k1,k2, k1, Tvar[k1], k2, Tvar[k2],Typevar[k1],Fixed[Tvar[k1]],Dummy[Tvar[k1]]); fflush(ficlog); |
| |
return(1); |
| |
} |
| |
}else if (Typevar[k1] ==2){ |
| |
k3=Tposprod[k1]; |
| |
k4=Tposprod[k2]; |
| |
if( ((Tvard[k3][1]== Tvard[k4][1])&&(Tvard[k3][2]== Tvard[k4][2])) || ((Tvard[k3][1]== Tvard[k4][2])&&(Tvard[k3][2]== Tvard[k4][1])) ){ |
| |
printf("Error duplication in the model=%s at positions (+) %d and %d, V%d*V%d, Typevar=%d, Fixed=%d, Dummy=%d\n",model, k1,k2, Tvard[k3][1], Tvard[k3][2],Typevar[k1],Fixed[Tvar[k1]],Dummy[Tvar[k1]]); |
| |
fprintf(ficlog,"Error duplication in the model=%s at positions (+) %d and %d, V%d*V%d, Typevar=%d, Fixed=%d, Dummy=%d\n",model, k1,k2, Tvard[k3][1], Tvard[k3][2],Typevar[k1],Fixed[Tvar[k1]],Dummy[Tvar[k1]]); fflush(ficlog); |
| |
return(1); |
| |
} |
| |
} |
| |
} |
| |
} |
| |
} |
| |
printf("ncoveff=%d, nqfveff=%d, ntveff=%d, nqtveff=%d, cptcovn=%d\n",ncoveff,nqfveff,ntveff,nqtveff,cptcovn); |
| |
fprintf(ficlog,"ncoveff=%d, nqfveff=%d, ntveff=%d, nqtveff=%d, cptcovn=%d\n",ncoveff,nqfveff,ntveff,nqtveff,cptcovn); |
| |
printf("ncovf=%d, ncovv=%d, ncova=%d, nsd=%d, nsq=%d\n",ncovf,ncovv,ncova,nsd,nsq); |
| |
fprintf(ficlog,"ncovf=%d, ncovv=%d, ncova=%d, nsd=%d, nsq=%d\n",ncovf,ncovv,ncova,nsd, nsq); |
| |
return (0); /* with covar[new additional covariate if product] and Tage if age */ |
| |
/*endread:*/ |
| |
printf("Exiting decodemodel: "); |
| |
return (1); |
| |
} |
| |
|
| |
int calandcheckages(int imx, int maxwav, double *agemin, double *agemax, int *nberr, int *nbwarn ) |
| |
{/* Check ages at death */ |
| |
int i, m; |
| |
int firstone=0; |
| |
|
| |
for (i=1; i<=imx; i++) { |
| |
for(m=2; (m<= maxwav); m++) { |
| |
if (((int)mint[m][i]== 99) && (s[m][i] <= nlstate)){ |
| |
anint[m][i]=9999; |
| |
if (s[m][i] != -2) /* Keeping initial status of unknown vital status */ |
| |
s[m][i]=-1; |
| |
} |
| |
if((int)moisdc[i]==99 && (int)andc[i]==9999 && s[m][i]>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<lastpass); m++){ |
| |
printf("%ld %d %.lf %d %d\n", num[i],(covar[1][i]),agev[m][i],s[m][i],s[m+1][i]); |
| |
} |
| |
|
| |
}*/ |
| |
|
| |
|
| |
printf("Total number of individuals= %d, Agemin = %.2f, Agemax= %.2f\n\n", imx, *agemin, *agemax); |
| |
fprintf(ficlog,"Total number of individuals= %d, Agemin = %.2f, Agemax= %.2f\n\n", imx, *agemin, *agemax); |
| |
|
| |
return (0); |
| |
/* endread:*/ |
| |
printf("Exiting calandcheckages: "); |
| |
return (1); |
| |
} |
| |
|
| |
#if defined(_MSC_VER) |
| |
/*printf("Visual C++ compiler: %s \n;", _MSC_FULL_VER);*/ |
| |
/*fprintf(ficlog, "Visual C++ compiler: %s \n;", _MSC_FULL_VER);*/ |
| |
//#include "stdafx.h" |
| |
//#include <stdio.h> |
| |
//#include <tchar.h> |
| |
//#include <windows.h> |
| |
//#include <iostream> |
| |
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 <gnu/libc-version.h> /* Only on gnu */ |
| |
#endif |
| |
struct utsname sysInfo; |
| |
int cross = CROSS; |
| |
if (cross){ |
| |
printf("Cross-"); |
| |
if(logged) fprintf(ficlog, "Cross-"); |
| |
} |
| |
#endif |
| |
|
| |
#include <stdint.h> |
| |
|
| |
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(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(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(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(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]; |
| |
|
| |
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 **bprlim; |
| |
double ***param; /* Matrix of parameters */ |
| |
double *p; |
| |
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; |
| |
|
| |
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"; |
| |
|
| |
/*char *strt;*/ |
| |
char strtend[80]; |
| |
|
| |
|
| |
/* 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); |
| |
#endif |
| |
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)); */ |
| |
|
| |
/* */ |
| |
strcpy(fileres,"r"); |
| |
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 */ |
| |
|
| |
/* Main ---------arguments file --------*/ |
| |
|
| |
if((ficpar=fopen(optionfile,"r"))==NULL) { |
| |
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,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); |
| |
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); |
| |
|
| |
|
| |
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; |
| |
} |
| |
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;i<nlstate;i++){ */ |
| |
/* /\*reducing xi for 1 to npar to 1 to ncovmodel; *\/ */ |
| |
/* mlikeli(ficres,p, ncovmodel, ncovmodel, nlstate, ftol, funcnoprod); */ |
| |
/* } */ |
| |
prwizard(ncovmodel, nlstate, ndeath, model, ficparo); |
| |
printf(" You chose mle=-1, look at file %s for a template of covariance matrix \n",filereso); |
| |
fprintf(ficlog," You chose mle=-1, look at file %s for a template of covariance matrix \n",filereso); |
| |
free_ma3x(delti3,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel); |
| |
fclose (ficparo); |
| |
fclose (ficlog); |
| |
goto end; |
| |
exit(0); |
| |
} else if(mle==-2) { /* Guessing from means */ |
| |
prwizard(ncovmodel, nlstate, ndeath, model, ficparo); |
| |
printf(" You chose mle=-2, look at file %s for a template of covariance matrix \n",filereso); |
| |
fprintf(ficlog," You chose mle=-2, look at file %s for a template of covariance matrix \n",filereso); |
| |
|
| |
} else if(mle==-5) { /* Main Wizard */ |
| |
prwizard(ncovmodel, nlstate, ndeath, model, ficparo); |
| |
printf(" You chose mle=-3, look at file %s for a template of covariance matrix \n",filereso); |
| |
fprintf(ficlog," You chose mle=-3, look at file %s for a template of covariance matrix \n",filereso); |
| |
param= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel); |
| |
matcov=matrix(1,npar,1,npar); |
| |
hess=matrix(1,npar,1,npar); |
| |
} else{ /* Begin of mle != -1 or -5 */ |
| |
/* Read guessed parameters */ |
| |
/* Reads comments: lines beginning with '#' */ |
| |
while((c=getc(ficpar))=='#' && c!= EOF){ |
| |
ungetc(c,ficpar); |
| |
fgets(line, MAXLINE, ficpar); |
| |
numlinepar++; |
| |
fputs(line,stdout); |
| |
fputs(line,ficparo); |
| |
fputs(line,ficlog); |
| |
} |
| |
ungetc(c,ficpar); |
| |
|
| |
param= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel); |
| |
for(i=1; i <=nlstate; i++){ |
| |
j=0; |
| |
for(jj=1; jj <=nlstate+ndeath; jj++){ |
| |
if(jj==i) continue; |
| |
j++; |
| |
fscanf(ficpar,"%1d%1d",&i1,&j1); |
| |
if ((i1 != i) || (j1 != jj)){ |
| |
printf("Error in line parameters number %d, %1d%1d instead of %1d%1d \n \ |
| |
It might be a problem of design; if ncovcol and the model are correct\n \ |
| |
run imach with mle=-1 to get a correct template of the parameter file.\n",numlinepar, i,j, i1, j1); |
| |
exit(1); |
| |
} |
| |
fprintf(ficparo,"%1d%1d",i1,j1); |
| |
if(mle==1) |
| |
printf("%1d%1d",i,jj); |
| |
fprintf(ficlog,"%1d%1d",i,jj); |
| |
for(k=1; k<=ncovmodel;k++){ |
| |
fscanf(ficpar," %lf",¶m[i][j][k]); |
| |
if(mle==1){ |
| |
printf(" %lf",param[i][j][k]); |
| |
fprintf(ficlog," %lf",param[i][j][k]); |
| |
} |
| |
else |
| |
fprintf(ficlog," %lf",param[i][j][k]); |
| |
fprintf(ficparo," %lf",param[i][j][k]); |
| |
} |
| |
fscanf(ficpar,"\n"); |
| |
numlinepar++; |
| |
if(mle==1) |
| |
printf("\n"); |
| |
fprintf(ficlog,"\n"); |
| |
fprintf(ficparo,"\n"); |
| |
} |
| |
} |
| |
fflush(ficlog); |
| |
|
| |
/* Reads scales values */ |
| |
p=param[1][1]; |
| |
|
| |
/* Reads comments: lines beginning with '#' */ |
| |
while((c=getc(ficpar))=='#' && c!= EOF){ |
| |
ungetc(c,ficpar); |
| |
fgets(line, MAXLINE, ficpar); |
| |
numlinepar++; |
| |
fputs(line,stdout); |
| |
fputs(line,ficparo); |
| |
fputs(line,ficlog); |
| |
} |
| |
ungetc(c,ficpar); |
| |
|
| |
for(i=1; i <=nlstate; i++){ |
| |
for(j=1; j <=nlstate+ndeath-1; j++){ |
| |
fscanf(ficpar,"%1d%1d",&i1,&j1); |
| |
if ( (i1-i) * (j1-j) != 0){ |
| |
printf("Error in line parameters number %d, %1d%1d instead of %1d%1d \n",numlinepar, i,j, i1, j1); |
| |
exit(1); |
| |
} |
| |
printf("%1d%1d",i,j); |
| |
fprintf(ficparo,"%1d%1d",i1,j1); |
| |
fprintf(ficlog,"%1d%1d",i1,j1); |
| |
for(k=1; k<=ncovmodel;k++){ |
| |
fscanf(ficpar,"%le",&delti3[i][j][k]); |
| |
printf(" %le",delti3[i][j][k]); |
| |
fprintf(ficparo," %le",delti3[i][j][k]); |
| |
fprintf(ficlog," %le",delti3[i][j][k]); |
| |
} |
| |
fscanf(ficpar,"\n"); |
| |
numlinepar++; |
| |
printf("\n"); |
| |
fprintf(ficparo,"\n"); |
| |
fprintf(ficlog,"\n"); |
| |
} |
| |
} |
| |
fflush(ficlog); |
| |
|
| |
/* Reads covariance matrix */ |
| |
delti=delti3[1][1]; |
| |
|
| |
|
| |
/* free_ma3x(delti3,1,nlstate,1,nlstate+ndeath-1,1,ncovmodel); */ /* Hasn't to to freed here otherwise delti is no more allocated */ |
| |
|
| |
/* Reads comments: lines beginning with '#' */ |
| |
while((c=getc(ficpar))=='#' && c!= EOF){ |
| |
ungetc(c,ficpar); |
| |
fgets(line, MAXLINE, ficpar); |
| |
numlinepar++; |
| |
fputs(line,stdout); |
| |
fputs(line,ficparo); |
| |
fputs(line,ficlog); |
| |
} |
| |
ungetc(c,ficpar); |
| |
|
| |
matcov=matrix(1,npar,1,npar); |
| |
hess=matrix(1,npar,1,npar); |
| |
for(i=1; i <=npar; i++) |
| |
for(j=1; j <=npar; j++) matcov[i][j]=0.; |
| |
|
| |
/* Scans npar lines */ |
| |
for(i=1; i <=npar; i++){ |
| |
count=fscanf(ficpar,"%1d%1d%d",&i1,&j1,&jk); |
| |
if(count != 3){ |
| |
printf("Error! Error in parameter file %s at line %d after line starting with %1d%1d%1d\n\ |
| |
This is probably because your covariance matrix doesn't \n contain exactly %d lines corresponding to your model line '1+age+%s'.\n\ |
| |
Please run with mle=-1 to get a correct covariance matrix.\n",optionfile,numlinepar, i1,j1,jk, npar, model); |
| |
fprintf(ficlog,"Error! Error in parameter file %s at line %d after line starting with %1d%1d%1d\n\ |
| |
This is probably because your covariance matrix doesn't \n contain exactly %d lines corresponding to your model line '1+age+%s'.\n\ |
| |
Please run with mle=-1 to get a correct covariance matrix.\n",optionfile,numlinepar, i1,j1,jk, npar, model); |
| |
exit(1); |
| |
}else{ |
| |
if(mle==1) |
| |
printf("%1d%1d%d",i1,j1,jk); |
| |
} |
| |
fprintf(ficlog,"%1d%1d%d",i1,j1,jk); |
| |
fprintf(ficparo,"%1d%1d%d",i1,j1,jk); |
| |
for(j=1; j <=i; j++){ |
| |
fscanf(ficpar," %le",&matcov[i][j]); |
| |
if(mle==1){ |
| |
printf(" %.5le",matcov[i][j]); |
| |
} |
| |
fprintf(ficlog," %.5le",matcov[i][j]); |
| |
fprintf(ficparo," %.5le",matcov[i][j]); |
| |
} |
| |
fscanf(ficpar,"\n"); |
| |
numlinepar++; |
| |
if(mle==1) |
| |
printf("\n"); |
| |
fprintf(ficlog,"\n"); |
| |
fprintf(ficparo,"\n"); |
| |
} |
| |
/* End of read covariance matrix npar lines */ |
| |
for(i=1; i <=npar; i++) |
| |
for(j=i+1;j<=npar;j++) |
| |
matcov[i][j]=matcov[j][i]; |
| |
|
| |
if(mle==1) |
| |
printf("\n"); |
| |
fprintf(ficlog,"\n"); |
| |
|
| |
fflush(ficlog); |
| |
|
| |
/*-------- Rewriting parameter file ----------*/ |
| |
strcpy(rfileres,"r"); /* "Rparameterfile */ |
| |
strcat(rfileres,optionfilefiname); /* Parameter file first name*/ |
| |
strcat(rfileres,"."); /* */ |
| |
strcat(rfileres,optionfilext); /* Other files have txt extension */ |
| |
if((ficres =fopen(rfileres,"w"))==NULL) { |
| |
printf("Problem writing new parameter file: %s\n", rfileres);goto end; |
| |
fprintf(ficlog,"Problem writing new parameter file: %s\n", rfileres);goto end; |
| |
} |
| |
fprintf(ficres,"#%s\n",version); |
| |
} /* End of mle != -3 */ |
| |
|
| |
/* Main data |
| |
*/ |
| |
n= lastobs; |
| |
num=lvector(1,n); |
| |
moisnais=vector(1,n); |
| |
annais=vector(1,n); |
| |
moisdc=vector(1,n); |
| |
andc=vector(1,n); |
| |
weight=vector(1,n); |
| |
agedc=vector(1,n); |
| |
cod=ivector(1,n); |
| |
for(i=1;i<=n;i++){ |
| |
num[i]=0; |
| |
moisnais[i]=0; |
| |
annais[i]=0; |
| |
moisdc[i]=0; |
| |
andc[i]=0; |
| |
agedc[i]=0; |
| |
cod[i]=0; |
| |
weight[i]=1.0; /* Equal weights, 1 by default */ |
| |
} |
| |
mint=matrix(1,maxwav,1,n); |
| |
anint=matrix(1,maxwav,1,n); |
| |
s=imatrix(1,maxwav+1,1,n); /* s[i][j] health state for wave i and individual j */ |
| |
tab=ivector(1,NCOVMAX); |
| |
ncodemax=ivector(1,NCOVMAX); /* Number of code per covariate; if O and 1 only, 2**ncov; V1+V2+V3+V4=>16 */ |
| |
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) |
| |
*/ |
| |
|
| |
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 */ |
| |
} |
| |
|
| |
/*-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); |
| |
|
| |
/* 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<ncovcombmax;i++) |
| |
invalidvarcomb[i]=0; |
| |
|
| |
/* Nbcode gives the value of the lth modality (currently 1 to 2) of jth covariate, in |
| |
V2+V1*age, there are 3 covariates Tvar[2]=1 (V1).*/ |
| |
/* 1 to ncodemax[j] which is the maximum value of this jth covariate */ |
| |
|
| |
/* codtab=imatrix(1,100,1,10);*/ /* codtab[h,k]=( (h-1) - mod(k-1,2**(k-1) )/2**(k-1) */ |
| |
/*printf(" codtab[1,1],codtab[100,10]=%d,%d\n", codtab[1][1],codtabm(100,10));*/ |
| |
/* codtab gives the value 1 or 2 of the hth combination of k covariates (1 or 2).*/ |
| |
/* nbcode[Tvaraff[j]][codtabm(h,j)]) : if there are only 2 modalities for a covariate j, |
| |
* codtabm(h,j) gives its value classified at position h and nbcode gives how it is coded |
| |
* (currently 0 or 1) in the data. |
| |
* In a loop on h=1 to 2**k, and a loop on j (=1 to k), we get the value of |
| |
* corresponding modality (h,j). |
| |
*/ |
| |
|
| |
h=0; |
| |
/*if (cptcovn > 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<<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,"<html><head>\n<title>IMaCh Cov %s</title></head>\n <body><font size=\"2\">%s <br> %s</font> \ |
| |
<hr size=\"2\" color=\"#EC5E5E\"> \n\ |
| |
Title=%s <br>Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s<br>\n",\ |
| |
optionfilehtmcov,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model); |
| |
} |
| |
|
| |
fprintf(fichtm,"<html><head>\n<head>\n<meta charset=\"utf-8\"/><meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\" />\n<title>IMaCh %s</title></head>\n <body><font size=\"7\"><a href=http:/euroreves.ined.fr/imach>IMaCh for Interpolated Markov Chain</a> </font><br>\n<font size=\"3\">Sponsored by Copyright (C) 2002-2015 <a href=http://www.ined.fr>INED</a>-EUROREVES-Institut de longévité-2013-2016-Japan Society for the Promotion of Sciences 日本å¦è¡“振興会 (<a href=https://www.jsps.go.jp/english/e-grants/>Grant-in-Aid for Scientific Research 25293121</a>) - <a href=https://software.intel.com/en-us>Intel Software 2015-2018</a></font><br> \ |
| |
<hr size=\"2\" color=\"#EC5E5E\"> \n\ |
| |
<font size=\"2\">IMaCh-%s <br> %s</font> \ |
| |
<hr size=\"2\" color=\"#EC5E5E\"> \n\ |
| |
Title=%s <br>Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s<br>\n\ |
| |
\n\ |
| |
<hr size=\"2\" color=\"#EC5E5E\">\ |
| |
<ul><li><h4>Parameter files</h4>\n\ |
| |
- Parameter file: <a href=\"%s.%s\">%s.%s</a><br>\n\ |
| |
- Copy of the parameter file: <a href=\"o%s\">o%s</a><br>\n\ |
| |
- Log file of the run: <a href=\"%s\">%s</a><br>\n\ |
| |
- Gnuplot file name: <a href=\"%s\">%s</a><br>\n\ |
| |
- Date and time at start: %s</ul>\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, agemin, agemax, s, agev, nlstate, imx, Tvaraff, invalidvarcomb, nbcode, ncodemax,mint,anint,strstart, \ |
| |
firstpass, lastpass, stepm, weightopt, model); |
| |
|
| |
fprintf(fichtm,"\n"); |
| |
fprintf(fichtm,"<br>Total number of observations=%d <br>\n\ |
| |
Youngest age at first (selected) pass %.2f, oldest age %.2f<br>\n\ |
| |
Interval (in months) between two waves: Min=%d Max=%d Mean=%.2lf<br>\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); |
| |
} |
| |
|
| |
/* 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); |
| |
} |
| |
|
| |
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; it<NDIM; it++){ |
| |
p[it+1]=gsl_vector_get(sfm->x,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); |
| |
|
| |
hesscov(matcov, hess, p, NDIM, delti, 1e-4, gompertz); |
| |
|
| |
for(i=1; i <=NDIM; i++) |
| |
for(j=i+1;j<=NDIM;j++) |
| |
matcov[i][j]=matcov[j][i]; |
| |
|
| |
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])); |
| |
} |
| |
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; |
| |
} |
| |
|
| |
for (k=agegomp;k<agemortsup;k++) |
| |
lsurv[k+1]=lsurv[k]-lsurv[k]*(p[1]*exp(p[2]*(k-agegomp))); |
| |
|
| |
for (k=agegomp;k<agemortsup;k++){ |
| |
lpop[k]=(lsurv[k]+lsurv[k+1])/2.; |
| |
sumlpop=sumlpop+lpop[k]; |
| |
} |
| |
|
| |
tpop[agegomp]=sumlpop; |
| |
for (k=agegomp;k<(agemortsup-3);k++){ |
| |
/* tpop[k+1]=2;*/ |
| |
tpop[k+1]=tpop[k]-lpop[k]; |
| |
} |
| |
|
| |
|
| |
printf("\nAge lx qx dx Lx Tx e(x)\n"); |
| |
for (k=agegomp;k<(agemortsup-2);k++) |
| |
printf("%d %.0lf %lf %.0lf %.0lf %.0lf %lf\n",k,lsurv[k],p[1]*exp(p[2]*(k-agegomp)),(p[1]*exp(p[2]*(k-agegomp)))*lsurv[k],lpop[k],tpop[k],tpop[k]/lsurv[k]); |
| |
|
| |
|
| |
replace_back_to_slash(pathc,pathcd); /* Even gnuplot wants a / */ |
| |
ageminpar=50; |
| |
agemaxpar=100; |
| |
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{ |
| |
printf("Warning! ageminpar %f and agemaxpar %f have been fixed because for simplification until it is fixed...\n\n",ageminpar,agemaxpar); |
| |
fprintf(ficlog,"Warning! ageminpar %f and agemaxpar %f have been fixed because for simplification until it is fixed...\n\n",ageminpar,agemaxpar); |
| |
printinggnuplotmort(fileresu, optionfilefiname,ageminpar,agemaxpar,fage, pathc,p); |
| |
} |
| |
printinghtmlmort(fileresu,title,datafile, firstpass, lastpass, \ |
| |
stepm, weightopt,\ |
| |
model,imx,p,matcov,agemortsup); |
| |
|
| |
free_vector(lsurv,1,AGESUP); |
| |
free_vector(lpop,1,AGESUP); |
| |
free_vector(tpop,1,AGESUP); |
| |
free_matrix(ximort,1,NDIM,1,NDIM); |
| |
free_ivector(cens,1,n); |
| |
free_vector(agecens,1,n); |
| |
free_ivector(dcwave,1,n); |
| |
#ifdef GSL |
| |
#endif |
| |
} /* Endof if mle==-3 mortality only */ |
| |
/* Standard */ |
| |
else{ /* For mle !=- 3, could be 0 or 1 or 4 etc. */ |
| |
globpr=0;/* Computes sum of likelihood for globpr=1 and funcone */ |
| |
/* Computes likelihood for initial parameters, uses funcone to compute gpimx and gsw */ |
| |
likelione(ficres, p, npar, nlstate, &globpr, &ipmx, &sw, &fretone, funcone); /* Prints the contributions to the likelihood */ |
| |
printf("First Likeli=%12.6f ipmx=%ld sw=%12.6f",fretone,ipmx,sw); |
| |
for (k=1; k<=npar;k++) |
| |
printf(" %d %8.5f",k,p[k]); |
| |
printf("\n"); |
| |
if(mle>=1){ /* Could be 1 or 2, Real Maximization */ |
| |
/* mlikeli uses func not funcone */ |
| |
/* for(i=1;i<nlstate;i++){ */ |
| |
/* /\*reducing xi for 1 to npar to 1 to ncovmodel; *\/ */ |
| |
/* mlikeli(ficres,p, ncovmodel, ncovmodel, nlstate, ftol, funcnoprod); */ |
| |
/* } */ |
| |
mlikeli(ficres,p, npar, ncovmodel, nlstate, ftol, func); |
| |
} |
| |
if(mle==0) {/* No optimization, will print the likelihoods for the datafile */ |
| |
globpr=0;/* Computes sum of likelihood for globpr=1 and funcone */ |
| |
/* Computes likelihood for initial parameters, uses funcone to compute gpimx and gsw */ |
| |
likelione(ficres, p, npar, nlstate, &globpr, &ipmx, &sw, &fretone, funcone); /* Prints the contributions to the likelihood */ |
| |
} |
| |
globpr=1; /* again, to print the individual contributions using computed gpimx and gsw */ |
| |
likelione(ficres, p, npar, nlstate, &globpr, &ipmx, &sw, &fretone, funcone); /* Prints the contributions to the likelihood */ |
| |
printf("Second Likeli=%12.6f ipmx=%ld sw=%12.6f",fretone,ipmx,sw); |
| |
for (k=1; k<=npar;k++) |
| |
printf(" %d %8.5f",k,p[k]); |
| |
printf("\n"); |
| |
|
| |
/*--------- results files --------------*/ |
| |
fprintf(ficres,"title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\nftol=%e stepm=%d ncovcol=%d nqv=%d ntv=%d nqtv=%d nlstate=%d ndeath=%d maxwav=%d mle= 0 weight=%d\nmodel=1+age+%s.\n", title, datafile, lastobs, firstpass,lastpass,ftol, stepm, ncovcol, nqv, ntv, nqtv, nlstate, ndeath, maxwav, weightopt,model); |
| |
|
| |
|
| |
fprintf(ficres,"# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n"); |
| |
printf("# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n"); |
| |
fprintf(ficlog,"# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\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); |
| |
fprintf(ficres,"%1d%1d ",i,k); |
| |
for(j=1; j <=ncovmodel; j++){ |
| |
printf("%12.7f ",p[jk]); |
| |
fprintf(ficlog,"%12.7f ",p[jk]); |
| |
fprintf(ficres,"%12.7f ",p[jk]); |
| |
jk++; |
| |
} |
| |
printf("\n"); |
| |
fprintf(ficlog,"\n"); |
| |
fprintf(ficres,"\n"); |
| |
} |
| |
} |
| |
} |
| |
if(mle != 0){ |
| |
/* Computing hessian and covariance matrix only at a peak of the Likelihood, that is after optimization */ |
| |
ftolhess=ftol; /* Usually correct */ |
| |
hesscov(matcov, hess, p, npar, delti, ftolhess, func); |
| |
printf("Parameters and 95%% confidence intervals\n W is simply the result of the division of the parameter by the square root of covariance of the parameter.\n And Wald-based confidence intervals plus and minus 1.96 * W .\n But be careful that parameters are highly correlated because incidence of disability is highly correlated to incidence of recovery.\n It might be better to visualize the covariance matrix. See the page 'Matrix of variance-covariance of one-step probabilities' and its graphs.\n"); |
| |
fprintf(ficlog, "Parameters, Wald tests and Wald-based confidence intervals\n W is simply the result of the division of the parameter by the square root of covariance of the parameter.\n And Wald-based confidence intervals plus and minus 1.96 * W \n It might be better to visualize the covariance matrix. See the page 'Matrix of variance-covariance of one-step probabilities' and its graphs.\n"); |
| |
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 W=%8.3f CI=[%12.7f ; %12.7f] ",p[jk], p[jk]/sqrt(matcov[jk][jk]), p[jk]-1.96*sqrt(matcov[jk][jk]),p[jk]+1.96*sqrt(matcov[jk][jk])); |
| |
fprintf(ficlog,"%12.7f W=%8.3f CI=[%12.7f ; %12.7f] ",p[jk], p[jk]/sqrt(matcov[jk][jk]), p[jk]-1.96*sqrt(matcov[jk][jk]),p[jk]+1.96*sqrt(matcov[jk][jk])); |
| |
jk++; |
| |
} |
| |
printf("\n"); |
| |
fprintf(ficlog,"\n"); |
| |
} |
| |
} |
| |
} |
| |
} /* end of hesscov and Wald tests */ |
| |
|
| |
/* */ |
| |
fprintf(ficres,"# Scales (for hessian or gradient estimation)\n"); |
| |
printf("# Scales (for hessian or gradient estimation)\n"); |
| |
fprintf(ficlog,"# Scales (for hessian or gradient estimation)\n"); |
| |
for(i=1,jk=1; i <=nlstate; i++){ |
| |
for(j=1; j <=nlstate+ndeath; j++){ |
| |
if (j!=i) { |
| |
fprintf(ficres,"%1d%1d",i,j); |
| |
printf("%1d%1d",i,j); |
| |
fprintf(ficlog,"%1d%1d",i,j); |
| |
for(k=1; k<=ncovmodel;k++){ |
| |
printf(" %.5e",delti[jk]); |
| |
fprintf(ficlog," %.5e",delti[jk]); |
| |
fprintf(ficres," %.5e",delti[jk]); |
| |
jk++; |
| |
} |
| |
printf("\n"); |
| |
fprintf(ficlog,"\n"); |
| |
fprintf(ficres,"\n"); |
| |
} |
| |
} |
| |
} |
| |
|
| |
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<jj){ |
| |
if(itimes==1){ |
| |
if(mle>=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; |
| |
} |
| |
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); |
| |
fputs(line,stdout); |
| |
fputs(line,ficparo); |
| |
} |
| |
ungetc(c,ficpar); |
| |
|
| |
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); |
| |
} |
| |
ungetc(c,ficpar); |
| |
|
| |
|
| |
dateprev1=anprev1+(mprev1-1)/12.+(jprev1-1)/365.; |
| |
dateprev2=anprev2+(mprev2-1)/12.+(jprev2-1)/365.; |
| |
|
| |
fscanf(ficpar,"pop_based=%d\n",&popbased); |
| |
fprintf(ficlog,"pop_based=%d\n",popbased); |
| |
fprintf(ficparo,"pop_based=%d\n",popbased); |
| |
fprintf(ficres,"pop_based=%d\n",popbased); |
| |
|
| |
while((c=getc(ficpar))=='#' && c!= EOF){ |
| |
ungetc(c,ficpar); |
| |
fgets(line, MAXLINE, ficpar); |
| |
fputs(line,stdout); |
| |
fputs(line,ficres); |
| |
fputs(line,ficparo); |
| |
} |
| |
ungetc(c,ficpar); |
| |
|
| |
fscanf(ficpar,"prevforecast=%d starting-proj-date=%lf/%lf/%lf final-proj-date=%lf/%lf/%lf mobil_average=%d\n",&prevfcast,&jproj1,&mproj1,&anproj1,&jproj2,&mproj2,&anproj2,&mobilavproj); |
| |
fprintf(ficparo,"prevforecast=%d starting-proj-date=%.lf/%.lf/%.lf final-proj-date=%.lf/%.lf/%.lf mobil_average=%d\n",prevfcast,jproj1,mproj1,anproj1,jproj2,mproj2,anproj2,mobilavproj); |
| |
printf("prevforecast=%d starting-proj-date=%.lf/%.lf/%.lf final-proj-date=%.lf/%.lf/%.lf mobil_average=%d\n",prevfcast,jproj1,mproj1,anproj1,jproj2,mproj2,anproj2,mobilavproj); |
| |
fprintf(ficlog,"prevforecast=%d starting-proj-date=%.lf/%.lf/%.lf final-proj-date=%.lf/%.lf/%.lf mobil_average=%d\n",prevfcast,jproj1,mproj1,anproj1,jproj2,mproj2,anproj2,mobilavproj); |
| |
fprintf(ficres,"prevforecast=%d starting-proj-date=%.lf/%.lf/%.lf final-proj-date=%.lf/%.lf/%.lf mobil_average=%d\n",prevfcast,jproj1,mproj1,anproj1,jproj2,mproj2,anproj2,mobilavproj); |
| |
/* day and month of proj2 are not used but only year anproj2.*/ |
| |
|
| |
while((c=getc(ficpar))=='#' && c!= EOF){ |
| |
ungetc(c,ficpar); |
| |
fgets(line, MAXLINE, ficpar); |
| |
fputs(line,stdout); |
| |
fputs(line,ficparo); |
| |
fputs(line,ficres); |
| |
} |
| |
ungetc(c,ficpar); |
| |
|
| |
fscanf(ficpar,"backcast=%d starting-back-date=%lf/%lf/%lf final-back-date=%lf/%lf/%lf mobil_average=%d\n",&backcast,&jback1,&mback1,&anback1,&jback2,&mback2,&anback2,&mobilavproj); |
| |
fprintf(ficparo,"backcast=%d starting-back-date=%.lf/%.lf/%.lf final-back-date=%.lf/%.lf/%.lf mobil_average=%d\n",backcast,jback1,mback1,anback1,jback2,mback2,anback2,mobilavproj); |
| |
fprintf(ficlog,"backcast=%d starting-back-date=%.lf/%.lf/%.lf final-back-date=%.lf/%.lf/%.lf mobil_average=%d\n",backcast,jback1,mback1,anback1,jback2,mback2,anback2,mobilavproj); |
| |
fprintf(ficres,"backcast=%d starting-back-date=%.lf/%.lf/%.lf final-back-date=%.lf/%.lf/%.lf mobil_average=%d\n",backcast,jback1,mback1,anback1,jback2,mback2,anback2,mobilavproj); |
| |
/* day and month of proj2 are not used but only year anproj2.*/ |
| |
|
| |
/* Results */ |
| |
nresult=0; |
| |
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); |
| |
fputs(line,ficres); |
| |
continue; |
| |
}else |
| |
break; |
| |
} |
| |
if (!feof(ficpar)) |
| |
while((num_filled=sscanf(line,"result:%[^\n]\n",resultline)) !=EOF){ |
| |
if (num_filled == 0){ |
| |
resultline[0]='\0'; |
| |
break; |
| |
} else if (num_filled != 1){ |
| |
printf("ERROR %d: result line should be at minimum 'result=' %s\n",num_filled, line); |
| |
} |
| |
nresult++; /* Sum of resultlines */ |
| |
printf("Result %d: result=%s\n",nresult, resultline); |
| |
if(nresult > 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 */ |
| |
|
| |
|
| |
|
| |
/* freqsummary(fileres, agemin, agemax, s, agev, nlstate, imx,Tvaraff,nbcode, ncodemax,mint,anint); */ |
| |
/* ,dateprev1,dateprev2,jprev1, mprev1,anprev1,jprev2, mprev2,anprev2); */ |
| |
|
| |
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_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------------ */ |
| |
|
| |
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); |
| |
|
| |
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(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); |
| |
|
| |
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); |
| |
|
| |
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); |
| |
} |
| |
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); |
| |
|
| |
/*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(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 */ |
| |
|
| |
printf("done State-specific expectancies\n");fflush(stdout); |
| |
fprintf(ficlog,"done State-specific expectancies\n");fflush(ficlog); |
| |
|
| |
/*------- 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;} |
| |
|
| |
for(nres=1; nres <= nresult; nres++) /* For each resultline */ |
| |
for(k=1; k<=i1;k++){ |
| |
if(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_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 */ |
| |
/*(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,"<br>Local time at start %s<br>Local time at end %s<br>\n</body></html>",strstart, strtend); |
| |
fclose(fichtm); |
| |
fprintf(fichtmcov,"<br>Local time at start %s<br>Local time at end %s<br>\n</body></html>",strstart, strtend); |
| |
fclose(fichtmcov); |
| |
fclose(ficgp); |
| |
fclose(ficlog); |
| |
/*------ End -----------*/ |
| |
|
| |
|
| |
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 |
| |
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(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"); */ |
| |
if (z[0] == 'e') { |
| |
#ifdef __APPLE__ |
| |
sprintf(pplotcmd, "open %s", optionfilehtm); |
| |
#elif __linux |
| |
sprintf(pplotcmd, "xdg-open %s", optionfilehtm); |
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#else |
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sprintf(pplotcmd, "%s", optionfilehtm); |
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#endif |
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printf("Starting browser with: %s",pplotcmd);fflush(stdout); |
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system(pplotcmd); |
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} |
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else if (z[0] == 'g') system(plotcmd); |
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else if (z[0] == 'q') exit(0); |
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} |
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end: |
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while (z[0] != 'q') { |
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printf("\nType q for exiting: "); fflush(stdout); |
| |
scanf("%s",z); |
| |
} |
| |
} |
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