Diff for /imach/src/imach.c between versions 1.6 and 1.340

version 1.6, 2001/05/02 17:47:10 version 1.340, 2022/09/11 07:53:11
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      /* $Id$
 /*********************** Imach **************************************            $State$
   This program computes Healthy Life Expectancies from cross-longitudinal    $Log$
   data. Cross-longitudinal consist in a first survey ("cross") where    Revision 1.340  2022/09/11 07:53:11  brouard
   individuals from different ages are interviewed on their health status    Summary: Version imach 0.99r37
   or degree of  disability. At least a second wave of interviews  
   ("longitudinal") should  measure each new individual health status.    * imach.c (Module): Adding timevarying products of any kinds,
   Health expectancies are computed from the transistions observed between    should work before shifting cotvar from ncovcol+nqv columns in
   waves and are computed for each degree of severity of disability (number    order to have a correspondance between the column of cotvar and
   of life states). More degrees you consider, more time is necessary to    the id of column.
   reach the Maximum Likelihood of the parameters involved in the model.  
   The simplest model is the multinomial logistic model where pij is    Revision 1.339  2022/09/09 17:55:22  brouard
   the probabibility to be observed in state j at the second wave conditional    Summary: version 0.99r37
   to be observed in state i at the first wave. Therefore the model is:  
   log(pij/pii)= aij + bij*age+ cij*sex + etc , where 'age' is age and 'sex'    * imach.c (Module): Many improvements for fixing products of fixed
   is a covariate. If you want to have a more complex model than "constant and    timevarying as well as fixed * fixed, and test with quantitative
   age", you should modify the program where the markup    covariate.
     *Covariates have to be included here again* invites you to do it.  
   More covariates you add, less is the speed of the convergence.    Revision 1.338  2022/09/04 17:40:33  brouard
     Summary: 0.99r36
   The advantage that this computer programme claims, comes from that if the  
   delay between waves is not identical for each individual, or if some    * imach.c (Module): Now the easy runs i.e. without result or
   individual missed an interview, the information is not rounded or lost, but    model=1+age only did not work. The defautl combination should be 1
   taken into account using an interpolation or extrapolation.    and not 0 because everything hasn't been tranformed yet.
   hPijx is the probability to be  
   observed in state i at age x+h conditional to the observed state i at age    Revision 1.337  2022/09/02 14:26:02  brouard
   x. The delay 'h' can be split into an exact number (nh*stepm) of    Summary: version 0.99r35
   unobserved intermediate  states. This elementary transition (by month or  
   quarter trimester, semester or year) is model as a multinomial logistic.    * src/imach.c: Version 0.99r35 because it outputs same results with
   The hPx matrix is simply the matrix product of nh*stepm elementary matrices    1+age+V1+V1*age for females and 1+age for females only
   and the contribution of each individual to the likelihood is simply hPijx.    (education=1 noweight)
   
   Also this programme outputs the covariance matrix of the parameters but also    Revision 1.336  2022/08/31 09:52:36  brouard
   of the life expectancies. It also computes the prevalence limits.    *** empty log message ***
    
   Authors: Nicolas Brouard (brouard@ined.fr) and Agnès Lièvre (lievre@ined.fr).    Revision 1.335  2022/08/31 08:23:16  brouard
            Institut national d'études démographiques, Paris.    Summary: improvements...
   This software have been partly granted by Euro-REVES, a concerted action  
   from the European Union.    Revision 1.334  2022/08/25 09:08:41  brouard
   It is copyrighted identically to a GNU software product, ie programme and    Summary: In progress for quantitative
   software can be distributed freely for non commercial use. Latest version  
   can be accessed at http://euroreves.ined.fr/imach .    Revision 1.333  2022/08/21 09:10:30  brouard
   **********************************************************************/    * src/imach.c (Module): Version 0.99r33 A lot of changes in
      reassigning covariates: my first idea was that people will always
 #include <math.h>    use the first covariate V1 into the model but in fact they are
 #include <stdio.h>    producing data with many covariates and can use an equation model
 #include <stdlib.h>    with some of the covariate; it means that in a model V2+V3 instead
 #include <unistd.h>    of codtabm(k,Tvaraff[j]) which calculates for combination k, for
     three covariates (V1, V2, V3) the value of Tvaraff[j], but in fact
 #define MAXLINE 256    the equation model is restricted to two variables only (V2, V3)
 #define FILENAMELENGTH 80    and the combination for V2 should be codtabm(k,1) instead of
 /*#define DEBUG*/    (codtabm(k,2), and the code should be
 #define windows    codtabm(k,TnsdVar[Tvaraff[j]]. Many many changes have been
 #define GLOCK_ERROR_NOPATH              -1      /* empty path */    made. All of these should be simplified once a day like we did in
 #define GLOCK_ERROR_GETCWD              -2      /* cannot get cwd */    hpxij() for example by using precov[nres] which is computed in
     decoderesult for each nres of each resultline. Loop should be done
 #define MAXPARM 30 /* Maximum number of parameters for the optimization */    on the equation model globally by distinguishing only product with
 #define NPARMAX 64 /* (nlstate+ndeath-1)*nlstate*ncovmodel */    age (which are changing with age) and no more on type of
     covariates, single dummies, single covariates.
 #define NINTERVMAX 8  
 #define NLSTATEMAX 8 /* Maximum number of live states (for func) */    Revision 1.332  2022/08/21 09:06:25  brouard
 #define NDEATHMAX 8 /* Maximum number of dead states (for func) */    Summary: Version 0.99r33
 #define NCOVMAX 8 /* Maximum number of covariates */  
 #define MAXN 20000    * src/imach.c (Module): Version 0.99r33 A lot of changes in
 #define YEARM 12. /* Number of months per year */    reassigning covariates: my first idea was that people will always
 #define AGESUP 130    use the first covariate V1 into the model but in fact they are
 #define AGEBASE 40    producing data with many covariates and can use an equation model
     with some of the covariate; it means that in a model V2+V3 instead
     of codtabm(k,Tvaraff[j]) which calculates for combination k, for
 int nvar;    three covariates (V1, V2, V3) the value of Tvaraff[j], but in fact
 static int cptcov;    the equation model is restricted to two variables only (V2, V3)
 int cptcovn, cptcovage=0;    and the combination for V2 should be codtabm(k,1) instead of
 int npar=NPARMAX;    (codtabm(k,2), and the code should be
 int nlstate=2; /* Number of live states */    codtabm(k,TnsdVar[Tvaraff[j]]. Many many changes have been
 int ndeath=1; /* Number of dead states */    made. All of these should be simplified once a day like we did in
 int ncovmodel, ncov;     /* Total number of covariables including constant a12*1 +b12*x ncovmodel=2 */    hpxij() for example by using precov[nres] which is computed in
     decoderesult for each nres of each resultline. Loop should be done
 int *wav; /* Number of waves for this individuual 0 is possible */    on the equation model globally by distinguishing only product with
 int maxwav; /* Maxim number of waves */    age (which are changing with age) and no more on type of
 int mle, weightopt;    covariates, single dummies, single covariates.
 int **mw; /* mw[mi][i] is number of the mi wave for this individual */  
 int **dh; /* dh[mi][i] is number of steps between mi,mi+1 for this individual */    Revision 1.331  2022/08/07 05:40:09  brouard
 double **oldm, **newm, **savm; /* Working pointers to matrices */    *** empty log message ***
 double **oldms, **newms, **savms; /* Fixed working pointers to matrices */  
 FILE *fic,*ficpar, *ficparo,*ficres,  *ficrespl, *ficrespij, *ficrest;    Revision 1.330  2022/08/06 07:18:25  brouard
 FILE *ficgp, *fichtm;    Summary: last 0.99r31
 FILE *ficreseij;  
   char filerese[FILENAMELENGTH];    *  imach.c (Module): Version of imach using partly decoderesult to rebuild xpxij function
  FILE  *ficresvij;  
   char fileresv[FILENAMELENGTH];    Revision 1.329  2022/08/03 17:29:54  brouard
  FILE  *ficresvpl;    *  imach.c (Module): Many errors in graphs fixed with Vn*age covariates.
   char fileresvpl[FILENAMELENGTH];  
     Revision 1.328  2022/07/27 17:40:48  brouard
 #define NR_END 1    Summary: valgrind bug fixed by initializing to zero DummyV as well as Tage
 #define FREE_ARG char*  
 #define FTOL 1.0e-10    Revision 1.327  2022/07/27 14:47:35  brouard
     Summary: Still a problem for one-step probabilities in case of quantitative variables
 #define NRANSI  
 #define ITMAX 200    Revision 1.326  2022/07/26 17:33:55  brouard
     Summary: some test with nres=1
 #define TOL 2.0e-4  
     Revision 1.325  2022/07/25 14:27:23  brouard
 #define CGOLD 0.3819660    Summary: r30
 #define ZEPS 1.0e-10  
 #define SHFT(a,b,c,d) (a)=(b);(b)=(c);(c)=(d);    * imach.c (Module): Error cptcovn instead of nsd in bmij (was
     coredumped, revealed by Feiuno, thank you.
 #define GOLD 1.618034  
 #define GLIMIT 100.0    Revision 1.324  2022/07/23 17:44:26  brouard
 #define TINY 1.0e-20    *** empty log message ***
   
 static double maxarg1,maxarg2;    Revision 1.323  2022/07/22 12:30:08  brouard
 #define FMAX(a,b) (maxarg1=(a),maxarg2=(b),(maxarg1)>(maxarg2)? (maxarg1):(maxarg2))    *  imach.c (Module): Output of Wald test in the htm file and not only in the log.
 #define FMIN(a,b) (maxarg1=(a),maxarg2=(b),(maxarg1)<(maxarg2)? (maxarg1):(maxarg2))  
      Revision 1.322  2022/07/22 12:27:48  brouard
 #define SIGN(a,b) ((b)>0.0 ? fabs(a) : -fabs(a))    *  imach.c (Module): Output of Wald test in the htm file and not only in the log.
 #define rint(a) floor(a+0.5)  
     Revision 1.321  2022/07/22 12:04:24  brouard
 static double sqrarg;    Summary: r28
 #define SQR(a) ((sqrarg=(a)) == 0.0 ? 0.0 :sqrarg*sqrarg)  
 #define SWAP(a,b) {temp=(a);(a)=(b);(b)=temp;}    *  imach.c (Module): Output of Wald test in the htm file and not only in the log.
   
 int imx;    Revision 1.320  2022/06/02 05:10:11  brouard
 int stepm;    *** empty log message ***
 /* Stepm, step in month: minimum step interpolation*/  
     Revision 1.319  2022/06/02 04:45:11  brouard
 int m,nb;    * imach.c (Module): Adding the Wald tests from the log to the main
 int *num, firstpass=0, lastpass=4,*cod, *ncodemax, *Tage;    htm for better display of the maximum likelihood estimators.
 double **agev,*moisnais, *annais, *moisdc, *andc,**mint, **anint;  
 double **pmmij;    Revision 1.318  2022/05/24 08:10:59  brouard
     * imach.c (Module): Some attempts to find a bug of wrong estimates
 double *weight;    of confidencce intervals with product in the equation modelC
 int **s; /* Status */  
 double *agedc, **covar, idx;    Revision 1.317  2022/05/15 15:06:23  brouard
 int **nbcode, *Tcode, *Tvar, **codtab;    * imach.c (Module):  Some minor improvements
   
 double ftol=FTOL; /* Tolerance for computing Max Likelihood */    Revision 1.316  2022/05/11 15:11:31  brouard
 double ftolhess; /* Tolerance for computing hessian */    Summary: r27
   
     Revision 1.315  2022/05/11 15:06:32  brouard
 static  int split( char *path, char *dirc, char *name )    *** empty log message ***
 {  
    char *s;                             /* pointer */    Revision 1.314  2022/04/13 17:43:09  brouard
    int  l1, l2;                         /* length counters */    * imach.c (Module): Adding link to text data files
   
    l1 = strlen( path );                 /* length of path */    Revision 1.313  2022/04/11 15:57:42  brouard
    if ( l1 == 0 ) return( GLOCK_ERROR_NOPATH );    * imach.c (Module): Error in rewriting the 'r' file with yearsfproj or yearsbproj fixed
    s = strrchr( path, '\\' );           /* find last / */  
    if ( s == NULL ) {                   /* no directory, so use current */    Revision 1.312  2022/04/05 21:24:39  brouard
 #if     defined(__bsd__)                /* get current working directory */    *** empty log message ***
       extern char       *getwd( );  
     Revision 1.311  2022/04/05 21:03:51  brouard
       if ( getwd( dirc ) == NULL ) {    Summary: Fixed quantitative covariates
 #else  
       extern char       *getcwd( );            Fixed covariates (dummy or quantitative)
           with missing values have never been allowed but are ERRORS and
       if ( getcwd( dirc, FILENAME_MAX ) == NULL ) {          program quits. Standard deviations of fixed covariates were
 #endif          wrongly computed. Mean and standard deviations of time varying
          return( GLOCK_ERROR_GETCWD );          covariates are still not computed.
       }  
       strcpy( name, path );             /* we've got it */    Revision 1.310  2022/03/17 08:45:53  brouard
    } else {                             /* strip direcotry from path */    Summary: 99r25
       s++;                              /* after this, the filename */  
       l2 = strlen( s );                 /* length of filename */    Improving detection of errors: result lines should be compatible with
       if ( l2 == 0 ) return( GLOCK_ERROR_NOPATH );    the model.
       strcpy( name, s );                /* save file name */  
       strncpy( dirc, path, l1 - l2 );   /* now the directory */    Revision 1.309  2021/05/20 12:39:14  brouard
       dirc[l1-l2] = 0;                  /* add zero */    Summary: Version 0.99r24
    }  
    l1 = strlen( dirc );                 /* length of directory */    Revision 1.308  2021/03/31 13:11:57  brouard
    if ( dirc[l1-1] != '\\' ) { dirc[l1] = '\\'; dirc[l1+1] = 0; }    Summary: Version 0.99r23
    return( 0 );                         /* we're done */  
 }  
     * imach.c (Module): Still bugs in the result loop. Thank to Holly Benett
   
 /******************************************/    Revision 1.307  2021/03/08 18:11:32  brouard
     Summary: 0.99r22 fixed bug on result:
 void replace(char *s, char*t)  
 {    Revision 1.306  2021/02/20 15:44:02  brouard
   int i;    Summary: Version 0.99r21
   int lg=20;  
   i=0;    * imach.c (Module): Fix bug on quitting after result lines!
   lg=strlen(t);    (Module): Version 0.99r21
   for(i=0; i<= lg; i++) {  
     (s[i] = t[i]);    Revision 1.305  2021/02/20 15:28:30  brouard
     if (t[i]== '\\') s[i]='/';    * imach.c (Module): Fix bug on quitting after result lines!
   }  
 }    Revision 1.304  2021/02/12 11:34:20  brouard
     * imach.c (Module): The use of a Windows BOM (huge) file is now an error
 int nbocc(char *s, char occ)  
 {    Revision 1.303  2021/02/11 19:50:15  brouard
   int i,j=0;    *  (Module): imach.c Someone entered 'results:' instead of 'result:'. Now it is an error which is printed.
   int lg=20;  
   i=0;    Revision 1.302  2020/02/22 21:00:05  brouard
   lg=strlen(s);    *  (Module): imach.c Update mle=-3 (for computing Life expectancy
   for(i=0; i<= lg; i++) {    and life table from the data without any state)
   if  (s[i] == occ ) j++;  
   }    Revision 1.301  2019/06/04 13:51:20  brouard
   return j;    Summary: Error in 'r'parameter file backcast yearsbproj instead of yearsfproj
 }  
     Revision 1.300  2019/05/22 19:09:45  brouard
 void cutv(char *u,char *v, char*t, char occ)    Summary: version 0.99r19 of May 2019
 {  
   int i,lg,j,p=0;    Revision 1.299  2019/05/22 18:37:08  brouard
   i=0;    Summary: Cleaned 0.99r19
   for(j=0; j<=strlen(t)-1; j++) {  
     if((t[j]!= occ) && (t[j+1]== occ)) p=j+1;    Revision 1.298  2019/05/22 18:19:56  brouard
   }    *** empty log message ***
   
   lg=strlen(t);    Revision 1.297  2019/05/22 17:56:10  brouard
   for(j=0; j<p; j++) {    Summary: Fix bug by moving date2dmy and nhstepm which gaefin=-1
     (u[j] = t[j]);  
   }    Revision 1.296  2019/05/20 13:03:18  brouard
      u[p]='\0';    Summary: Projection syntax simplified
   
    for(j=0; j<= lg; j++) {  
     if (j>=(p+1))(v[j-p-1] = t[j]);    We can now start projections, forward or backward, from the mean date
   }    of inteviews up to or down to a number of years of projection:
 }    prevforecast=1 yearsfproj=15.3 mobil_average=0
     or
 /********************** nrerror ********************/    prevforecast=1 starting-proj-date=1/1/2007 final-proj-date=12/31/2017 mobil_average=0
     or
 void nrerror(char error_text[])    prevbackcast=1 yearsbproj=12.3 mobil_average=1
 {    or
   fprintf(stderr,"ERREUR ...\n");    prevbackcast=1 starting-back-date=1/10/1999 final-back-date=1/1/1985 mobil_average=1
   fprintf(stderr,"%s\n",error_text);  
   exit(1);    Revision 1.295  2019/05/18 09:52:50  brouard
 }    Summary: doxygen tex bug
 /*********************** vector *******************/  
 double *vector(int nl, int nh)    Revision 1.294  2019/05/16 14:54:33  brouard
 {    Summary: There was some wrong lines added
   double *v;  
   v=(double *) malloc((size_t)((nh-nl+1+NR_END)*sizeof(double)));    Revision 1.293  2019/05/09 15:17:34  brouard
   if (!v) nrerror("allocation failure in vector");    *** empty log message ***
   return v-nl+NR_END;  
 }    Revision 1.292  2019/05/09 14:17:20  brouard
     Summary: Some updates
 /************************ free vector ******************/  
 void free_vector(double*v, int nl, int nh)    Revision 1.291  2019/05/09 13:44:18  brouard
 {    Summary: Before ncovmax
   free((FREE_ARG)(v+nl-NR_END));  
 }    Revision 1.290  2019/05/09 13:39:37  brouard
     Summary: 0.99r18 unlimited number of individuals
 /************************ivector *******************************/  
 int *ivector(long nl,long nh)    The number n which was limited to 20,000 cases is now unlimited, from firstobs to lastobs. If the number is too for the virtual memory, probably an error will occur.
 {  
   int *v;    Revision 1.289  2018/12/13 09:16:26  brouard
   v=(int *) malloc((size_t)((nh-nl+1+NR_END)*sizeof(int)));    Summary: Bug for young ages (<-30) will be in r17
   if (!v) nrerror("allocation failure in ivector");  
   return v-nl+NR_END;    Revision 1.288  2018/05/02 20:58:27  brouard
 }    Summary: Some bugs fixed
   
 /******************free ivector **************************/    Revision 1.287  2018/05/01 17:57:25  brouard
 void free_ivector(int *v, long nl, long nh)    Summary: Bug fixed by providing frequencies only for non missing covariates
 {  
   free((FREE_ARG)(v+nl-NR_END));    Revision 1.286  2018/04/27 14:27:04  brouard
 }    Summary: some minor bugs
   
 /******************* imatrix *******************************/    Revision 1.285  2018/04/21 21:02:16  brouard
 int **imatrix(long nrl, long nrh, long ncl, long nch)    Summary: Some bugs fixed, valgrind tested
      /* allocate a int matrix with subscript range m[nrl..nrh][ncl..nch] */  
 {    Revision 1.284  2018/04/20 05:22:13  brouard
   long i, nrow=nrh-nrl+1,ncol=nch-ncl+1;    Summary: Computing mean and stdeviation of fixed quantitative variables
   int **m;  
      Revision 1.283  2018/04/19 14:49:16  brouard
   /* allocate pointers to rows */    Summary: Some minor bugs fixed
   m=(int **) malloc((size_t)((nrow+NR_END)*sizeof(int*)));  
   if (!m) nrerror("allocation failure 1 in matrix()");    Revision 1.282  2018/02/27 22:50:02  brouard
   m += NR_END;    *** empty log message ***
   m -= nrl;  
      Revision 1.281  2018/02/27 19:25:23  brouard
      Summary: Adding second argument for quitting
   /* allocate rows and set pointers to them */  
   m[nrl]=(int *) malloc((size_t)((nrow*ncol+NR_END)*sizeof(int)));    Revision 1.280  2018/02/21 07:58:13  brouard
   if (!m[nrl]) nrerror("allocation failure 2 in matrix()");    Summary: 0.99r15
   m[nrl] += NR_END;  
   m[nrl] -= ncl;    New Makefile with recent VirtualBox 5.26. Bug in sqrt negatve in imach.c
    
   for(i=nrl+1;i<=nrh;i++) m[i]=m[i-1]+ncol;    Revision 1.279  2017/07/20 13:35:01  brouard
      Summary: temporary working
   /* return pointer to array of pointers to rows */  
   return m;    Revision 1.278  2017/07/19 14:09:02  brouard
 }    Summary: Bug for mobil_average=0 and prevforecast fixed(?)
   
 /****************** free_imatrix *************************/    Revision 1.277  2017/07/17 08:53:49  brouard
 void free_imatrix(m,nrl,nrh,ncl,nch)    Summary: BOM files can be read now
       int **m;  
       long nch,ncl,nrh,nrl;    Revision 1.276  2017/06/30 15:48:31  brouard
      /* free an int matrix allocated by imatrix() */    Summary: Graphs improvements
 {  
   free((FREE_ARG) (m[nrl]+ncl-NR_END));    Revision 1.275  2017/06/30 13:39:33  brouard
   free((FREE_ARG) (m+nrl-NR_END));    Summary: Saito's color
 }  
     Revision 1.274  2017/06/29 09:47:08  brouard
 /******************* matrix *******************************/    Summary: Version 0.99r14
 double **matrix(long nrl, long nrh, long ncl, long nch)  
 {    Revision 1.273  2017/06/27 11:06:02  brouard
   long i, nrow=nrh-nrl+1, ncol=nch-ncl+1;    Summary: More documentation on projections
   double **m;  
     Revision 1.272  2017/06/27 10:22:40  brouard
   m=(double **) malloc((size_t)((nrow+NR_END)*sizeof(double*)));    Summary: Color of backprojection changed from 6 to 5(yellow)
   if (!m) nrerror("allocation failure 1 in matrix()");  
   m += NR_END;    Revision 1.271  2017/06/27 10:17:50  brouard
   m -= nrl;    Summary: Some bug with rint
   
   m[nrl]=(double *) malloc((size_t)((nrow*ncol+NR_END)*sizeof(double)));    Revision 1.270  2017/05/24 05:45:29  brouard
   if (!m[nrl]) nrerror("allocation failure 2 in matrix()");    *** empty log message ***
   m[nrl] += NR_END;  
   m[nrl] -= ncl;    Revision 1.269  2017/05/23 08:39:25  brouard
     Summary: Code into subroutine, cleanings
   for (i=nrl+1; i<=nrh; i++) m[i]=m[i-1]+ncol;  
   return m;    Revision 1.268  2017/05/18 20:09:32  brouard
 }    Summary: backprojection and confidence intervals of backprevalence
   
 /*************************free matrix ************************/    Revision 1.267  2017/05/13 10:25:05  brouard
 void free_matrix(double **m, long nrl, long nrh, long ncl, long nch)    Summary: temporary save for backprojection
 {  
   free((FREE_ARG)(m[nrl]+ncl-NR_END));    Revision 1.266  2017/05/13 07:26:12  brouard
   free((FREE_ARG)(m+nrl-NR_END));    Summary: Version 0.99r13 (improvements and bugs fixed)
 }  
     Revision 1.265  2017/04/26 16:22:11  brouard
 /******************* ma3x *******************************/    Summary: imach 0.99r13 Some bugs fixed
 double ***ma3x(long nrl, long nrh, long ncl, long nch, long nll, long nlh)  
 {    Revision 1.264  2017/04/26 06:01:29  brouard
   long i, j, nrow=nrh-nrl+1, ncol=nch-ncl+1, nlay=nlh-nll+1;    Summary: Labels in graphs
   double ***m;  
     Revision 1.263  2017/04/24 15:23:15  brouard
   m=(double ***) malloc((size_t)((nrow+NR_END)*sizeof(double*)));    Summary: to save
   if (!m) nrerror("allocation failure 1 in matrix()");  
   m += NR_END;    Revision 1.262  2017/04/18 16:48:12  brouard
   m -= nrl;    *** empty log message ***
   
   m[nrl]=(double **) malloc((size_t)((nrow*ncol+NR_END)*sizeof(double)));    Revision 1.261  2017/04/05 10:14:09  brouard
   if (!m[nrl]) nrerror("allocation failure 2 in matrix()");    Summary: Bug in E_ as well as in T_ fixed nres-1 vs k1-1
   m[nrl] += NR_END;  
   m[nrl] -= ncl;    Revision 1.260  2017/04/04 17:46:59  brouard
     Summary: Gnuplot indexations fixed (humm)
   for (i=nrl+1; i<=nrh; i++) m[i]=m[i-1]+ncol;  
     Revision 1.259  2017/04/04 13:01:16  brouard
   m[nrl][ncl]=(double *) malloc((size_t)((nrow*ncol*nlay+NR_END)*sizeof(double)));    Summary: Some errors to warnings only if date of death is unknown but status is death we could set to pi3
   if (!m[nrl][ncl]) nrerror("allocation failure 3 in matrix()");  
   m[nrl][ncl] += NR_END;    Revision 1.258  2017/04/03 10:17:47  brouard
   m[nrl][ncl] -= nll;    Summary: Version 0.99r12
   for (j=ncl+1; j<=nch; j++)  
     m[nrl][j]=m[nrl][j-1]+nlay;    Some cleanings, conformed with updated documentation.
    
   for (i=nrl+1; i<=nrh; i++) {    Revision 1.257  2017/03/29 16:53:30  brouard
     m[i][ncl]=m[i-1l][ncl]+ncol*nlay;    Summary: Temp
     for (j=ncl+1; j<=nch; j++)  
       m[i][j]=m[i][j-1]+nlay;    Revision 1.256  2017/03/27 05:50:23  brouard
   }    Summary: Temporary
   return m;  
 }    Revision 1.255  2017/03/08 16:02:28  brouard
     Summary: IMaCh version 0.99r10 bugs in gnuplot fixed
 /*************************free ma3x ************************/  
 void free_ma3x(double ***m, long nrl, long nrh, long ncl, long nch,long nll, long nlh)    Revision 1.254  2017/03/08 07:13:00  brouard
 {    Summary: Fixing data parameter line
   free((FREE_ARG)(m[nrl][ncl]+ nll-NR_END));  
   free((FREE_ARG)(m[nrl]+ncl-NR_END));    Revision 1.253  2016/12/15 11:59:41  brouard
   free((FREE_ARG)(m+nrl-NR_END));    Summary: 0.99 in progress
 }  
     Revision 1.252  2016/09/15 21:15:37  brouard
 /***************** f1dim *************************/    *** empty log message ***
 extern int ncom;  
 extern double *pcom,*xicom;    Revision 1.251  2016/09/15 15:01:13  brouard
 extern double (*nrfunc)(double []);    Summary: not working
    
 double f1dim(double x)    Revision 1.250  2016/09/08 16:07:27  brouard
 {    Summary: continue
   int j;  
   double f;    Revision 1.249  2016/09/07 17:14:18  brouard
   double *xt;    Summary: Starting values from frequencies
    
   xt=vector(1,ncom);    Revision 1.248  2016/09/07 14:10:18  brouard
   for (j=1;j<=ncom;j++) xt[j]=pcom[j]+x*xicom[j];    *** empty log message ***
   f=(*nrfunc)(xt);  
   free_vector(xt,1,ncom);    Revision 1.247  2016/09/02 11:11:21  brouard
   return f;    *** empty log message ***
 }  
     Revision 1.246  2016/09/02 08:49:22  brouard
 /*****************brent *************************/    *** empty log message ***
 double brent(double ax, double bx, double cx, double (*f)(double), double tol,  double *xmin)  
 {    Revision 1.245  2016/09/02 07:25:01  brouard
   int iter;    *** empty log message ***
   double a,b,d,etemp;  
   double fu,fv,fw,fx;    Revision 1.244  2016/09/02 07:17:34  brouard
   double ftemp;    *** empty log message ***
   double p,q,r,tol1,tol2,u,v,w,x,xm;  
   double e=0.0;    Revision 1.243  2016/09/02 06:45:35  brouard
      *** empty log message ***
   a=(ax < cx ? ax : cx);  
   b=(ax > cx ? ax : cx);    Revision 1.242  2016/08/30 15:01:20  brouard
   x=w=v=bx;    Summary: Fixing a lots
   fw=fv=fx=(*f)(x);  
   for (iter=1;iter<=ITMAX;iter++) {    Revision 1.241  2016/08/29 17:17:25  brouard
     xm=0.5*(a+b);    Summary: gnuplot problem in Back projection to fix
     tol2=2.0*(tol1=tol*fabs(x)+ZEPS);  
     /*          if (2.0*fabs(fp-(*fret)) <= ftol*(fabs(fp)+fabs(*fret)))*/    Revision 1.240  2016/08/29 07:53:18  brouard
     printf(".");fflush(stdout);    Summary: Better
 #ifdef DEBUG  
     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);    Revision 1.239  2016/08/26 15:51:03  brouard
     /*          if ((fabs(x-xm) <= (tol2-0.5*(b-a)))||(2.0*fabs(fu-ftemp) <= ftol*1.e-2*(fabs(fu)+fabs(ftemp)))) { */    Summary: Improvement in Powell output in order to copy and paste
 #endif  
     if (fabs(x-xm) <= (tol2-0.5*(b-a))){    Author:
       *xmin=x;  
       return fx;    Revision 1.238  2016/08/26 14:23:35  brouard
     }    Summary: Starting tests of 0.99
     ftemp=fu;  
     if (fabs(e) > tol1) {    Revision 1.237  2016/08/26 09:20:19  brouard
       r=(x-w)*(fx-fv);    Summary: to valgrind
       q=(x-v)*(fx-fw);  
       p=(x-v)*q-(x-w)*r;    Revision 1.236  2016/08/25 10:50:18  brouard
       q=2.0*(q-r);    *** empty log message ***
       if (q > 0.0) p = -p;  
       q=fabs(q);    Revision 1.235  2016/08/25 06:59:23  brouard
       etemp=e;    *** empty log message ***
       e=d;  
       if (fabs(p) >= fabs(0.5*q*etemp) || p <= q*(a-x) || p >= q*(b-x))    Revision 1.234  2016/08/23 16:51:20  brouard
         d=CGOLD*(e=(x >= xm ? a-x : b-x));    *** empty log message ***
       else {  
         d=p/q;    Revision 1.233  2016/08/23 07:40:50  brouard
         u=x+d;    Summary: not working
         if (u-a < tol2 || b-u < tol2)  
           d=SIGN(tol1,xm-x);    Revision 1.232  2016/08/22 14:20:21  brouard
       }    Summary: not working
     } else {  
       d=CGOLD*(e=(x >= xm ? a-x : b-x));    Revision 1.231  2016/08/22 07:17:15  brouard
     }    Summary: not working
     u=(fabs(d) >= tol1 ? x+d : x+SIGN(tol1,d));  
     fu=(*f)(u);    Revision 1.230  2016/08/22 06:55:53  brouard
     if (fu <= fx) {    Summary: Not working
       if (u >= x) a=x; else b=x;  
       SHFT(v,w,x,u)    Revision 1.229  2016/07/23 09:45:53  brouard
         SHFT(fv,fw,fx,fu)    Summary: Completing for func too
         } else {  
           if (u < x) a=u; else b=u;    Revision 1.228  2016/07/22 17:45:30  brouard
           if (fu <= fw || w == x) {    Summary: Fixing some arrays, still debugging
             v=w;  
             w=u;    Revision 1.226  2016/07/12 18:42:34  brouard
             fv=fw;    Summary: temp
             fw=fu;  
           } else if (fu <= fv || v == x || v == w) {    Revision 1.225  2016/07/12 08:40:03  brouard
             v=u;    Summary: saving but not running
             fv=fu;  
           }    Revision 1.224  2016/07/01 13:16:01  brouard
         }    Summary: Fixes
   }  
   nrerror("Too many iterations in brent");    Revision 1.223  2016/02/19 09:23:35  brouard
   *xmin=x;    Summary: temporary
   return fx;  
 }    Revision 1.222  2016/02/17 08:14:50  brouard
     Summary: Probably last 0.98 stable version 0.98r6
 /****************** mnbrak ***********************/  
     Revision 1.221  2016/02/15 23:35:36  brouard
 void mnbrak(double *ax, double *bx, double *cx, double *fa, double *fb, double *fc,    Summary: minor bug
             double (*func)(double))  
 {    Revision 1.219  2016/02/15 00:48:12  brouard
   double ulim,u,r,q, dum;    *** empty log message ***
   double fu;  
      Revision 1.218  2016/02/12 11:29:23  brouard
   *fa=(*func)(*ax);    Summary: 0.99 Back projections
   *fb=(*func)(*bx);  
   if (*fb > *fa) {    Revision 1.217  2015/12/23 17:18:31  brouard
     SHFT(dum,*ax,*bx,dum)    Summary: Experimental backcast
       SHFT(dum,*fb,*fa,dum)  
       }    Revision 1.216  2015/12/18 17:32:11  brouard
   *cx=(*bx)+GOLD*(*bx-*ax);    Summary: 0.98r4 Warning and status=-2
   *fc=(*func)(*cx);  
   while (*fb > *fc) {    Version 0.98r4 is now:
     r=(*bx-*ax)*(*fb-*fc);     - displaying an error when status is -1, date of interview unknown and date of death known;
     q=(*bx-*cx)*(*fb-*fa);     - permitting a status -2 when the vital status is unknown at a known date of right truncation.
     u=(*bx)-((*bx-*cx)*q-(*bx-*ax)*r)/    Older changes concerning s=-2, dating from 2005 have been supersed.
       (2.0*SIGN(FMAX(fabs(q-r),TINY),q-r));  
     ulim=(*bx)+GLIMIT*(*cx-*bx);    Revision 1.215  2015/12/16 08:52:24  brouard
     if ((*bx-u)*(u-*cx) > 0.0) {    Summary: 0.98r4 working
       fu=(*func)(u);  
     } else if ((*cx-u)*(u-ulim) > 0.0) {    Revision 1.214  2015/12/16 06:57:54  brouard
       fu=(*func)(u);    Summary: temporary not working
       if (fu < *fc) {  
         SHFT(*bx,*cx,u,*cx+GOLD*(*cx-*bx))    Revision 1.213  2015/12/11 18:22:17  brouard
           SHFT(*fb,*fc,fu,(*func)(u))    Summary: 0.98r4
           }  
     } else if ((u-ulim)*(ulim-*cx) >= 0.0) {    Revision 1.212  2015/11/21 12:47:24  brouard
       u=ulim;    Summary: minor typo
       fu=(*func)(u);  
     } else {    Revision 1.211  2015/11/21 12:41:11  brouard
       u=(*cx)+GOLD*(*cx-*bx);    Summary: 0.98r3 with some graph of projected cross-sectional
       fu=(*func)(u);  
     }    Author: Nicolas Brouard
     SHFT(*ax,*bx,*cx,u)  
       SHFT(*fa,*fb,*fc,fu)    Revision 1.210  2015/11/18 17:41:20  brouard
       }    Summary: Start working on projected prevalences  Revision 1.209  2015/11/17 22:12:03  brouard
 }    Summary: Adding ftolpl parameter
     Author: N Brouard
 /*************** linmin ************************/  
     We had difficulties to get smoothed confidence intervals. It was due
 int ncom;    to the period prevalence which wasn't computed accurately. The inner
 double *pcom,*xicom;    parameter ftolpl is now an outer parameter of the .imach parameter
 double (*nrfunc)(double []);    file after estepm. If ftolpl is small 1.e-4 and estepm too,
      computation are long.
 void linmin(double p[], double xi[], int n, double *fret,double (*func)(double []))  
 {    Revision 1.208  2015/11/17 14:31:57  brouard
   double brent(double ax, double bx, double cx,    Summary: temporary
                double (*f)(double), double tol, double *xmin);  
   double f1dim(double x);    Revision 1.207  2015/10/27 17:36:57  brouard
   void mnbrak(double *ax, double *bx, double *cx, double *fa, double *fb,    *** empty log message ***
               double *fc, double (*func)(double));  
   int j;    Revision 1.206  2015/10/24 07:14:11  brouard
   double xx,xmin,bx,ax;    *** empty log message ***
   double fx,fb,fa;  
      Revision 1.205  2015/10/23 15:50:53  brouard
   ncom=n;    Summary: 0.98r3 some clarification for graphs on likelihood contributions
   pcom=vector(1,n);  
   xicom=vector(1,n);    Revision 1.204  2015/10/01 16:20:26  brouard
   nrfunc=func;    Summary: Some new graphs of contribution to likelihood
   for (j=1;j<=n;j++) {  
     pcom[j]=p[j];    Revision 1.203  2015/09/30 17:45:14  brouard
     xicom[j]=xi[j];    Summary: looking at better estimation of the hessian
   }  
   ax=0.0;    Also a better criteria for convergence to the period prevalence And
   xx=1.0;    therefore adding the number of years needed to converge. (The
   mnbrak(&ax,&xx,&bx,&fa,&fx,&fb,f1dim);    prevalence in any alive state shold sum to one
   *fret=brent(ax,xx,bx,f1dim,TOL,&xmin);  
 #ifdef DEBUG    Revision 1.202  2015/09/22 19:45:16  brouard
   printf("retour brent fret=%.12e xmin=%.12e\n",*fret,xmin);    Summary: Adding some overall graph on contribution to likelihood. Might change
 #endif  
   for (j=1;j<=n;j++) {    Revision 1.201  2015/09/15 17:34:58  brouard
     xi[j] *= xmin;    Summary: 0.98r0
     p[j] += xi[j];  
   }    - Some new graphs like suvival functions
   free_vector(xicom,1,n);    - Some bugs fixed like model=1+age+V2.
   free_vector(pcom,1,n);  
 }    Revision 1.200  2015/09/09 16:53:55  brouard
     Summary: Big bug thanks to Flavia
 /*************** powell ************************/  
 void powell(double p[], double **xi, int n, double ftol, int *iter, double *fret,    Even model=1+age+V2. did not work anymore
             double (*func)(double []))  
 {    Revision 1.199  2015/09/07 14:09:23  brouard
   void linmin(double p[], double xi[], int n, double *fret,    Summary: 0.98q6 changing default small png format for graph to vectorized svg.
               double (*func)(double []));  
   int i,ibig,j;    Revision 1.198  2015/09/03 07:14:39  brouard
   double del,t,*pt,*ptt,*xit;    Summary: 0.98q5 Flavia
   double fp,fptt;  
   double *xits;    Revision 1.197  2015/09/01 18:24:39  brouard
   pt=vector(1,n);    *** empty log message ***
   ptt=vector(1,n);  
   xit=vector(1,n);    Revision 1.196  2015/08/18 23:17:52  brouard
   xits=vector(1,n);    Summary: 0.98q5
   *fret=(*func)(p);  
   for (j=1;j<=n;j++) pt[j]=p[j];    Revision 1.195  2015/08/18 16:28:39  brouard
   for (*iter=1;;++(*iter)) {    Summary: Adding a hack for testing purpose
     fp=(*fret);  
     ibig=0;    After reading the title, ftol and model lines, if the comment line has
     del=0.0;    a q, starting with #q, the answer at the end of the run is quit. It
     printf("\nPowell iter=%d -2*LL=%.12f",*iter,*fret);    permits to run test files in batch with ctest. The former workaround was
     for (i=1;i<=n;i++)    $ echo q | imach foo.imach
       printf(" %d %.12f",i, p[i]);  
     printf("\n");    Revision 1.194  2015/08/18 13:32:00  brouard
     for (i=1;i<=n;i++) {    Summary:  Adding error when the covariance matrix doesn't contain the exact number of lines required by the model line.
       for (j=1;j<=n;j++) xit[j]=xi[j][i];  
       fptt=(*fret);    Revision 1.193  2015/08/04 07:17:42  brouard
 #ifdef DEBUG    Summary: 0.98q4
       printf("fret=%lf \n",*fret);  
 #endif    Revision 1.192  2015/07/16 16:49:02  brouard
       printf("%d",i);fflush(stdout);    Summary: Fixing some outputs
       linmin(p,xit,n,fret,func);  
       if (fabs(fptt-(*fret)) > del) {    Revision 1.191  2015/07/14 10:00:33  brouard
         del=fabs(fptt-(*fret));    Summary: Some fixes
         ibig=i;  
       }    Revision 1.190  2015/05/05 08:51:13  brouard
 #ifdef DEBUG    Summary: Adding digits in output parameters (7 digits instead of 6)
       printf("%d %.12e",i,(*fret));  
       for (j=1;j<=n;j++) {    Fix 1+age+.
         xits[j]=FMAX(fabs(p[j]-pt[j]),1.e-5);  
         printf(" x(%d)=%.12e",j,xit[j]);    Revision 1.189  2015/04/30 14:45:16  brouard
       }    Summary: 0.98q2
       for(j=1;j<=n;j++)  
         printf(" p=%.12e",p[j]);    Revision 1.188  2015/04/30 08:27:53  brouard
       printf("\n");    *** empty log message ***
 #endif  
     }    Revision 1.187  2015/04/29 09:11:15  brouard
     if (2.0*fabs(fp-(*fret)) <= ftol*(fabs(fp)+fabs(*fret))) {    *** empty log message ***
 #ifdef DEBUG  
       int k[2],l;    Revision 1.186  2015/04/23 12:01:52  brouard
       k[0]=1;    Summary: V1*age is working now, version 0.98q1
       k[1]=-1;  
       printf("Max: %.12e",(*func)(p));    Some codes had been disabled in order to simplify and Vn*age was
       for (j=1;j<=n;j++)    working in the optimization phase, ie, giving correct MLE parameters,
         printf(" %.12e",p[j]);    but, as usual, outputs were not correct and program core dumped.
       printf("\n");  
       for(l=0;l<=1;l++) {    Revision 1.185  2015/03/11 13:26:42  brouard
         for (j=1;j<=n;j++) {    Summary: Inclusion of compile and links command line for Intel Compiler
           ptt[j]=p[j]+(p[j]-pt[j])*k[l];  
           printf("l=%d j=%d ptt=%.12e, xits=%.12e, p=%.12e, xit=%.12e", l,j,ptt[j],xits[j],p[j],xit[j]);    Revision 1.184  2015/03/11 11:52:39  brouard
         }    Summary: Back from Windows 8. Intel Compiler
         printf("func(ptt)=%.12e, deriv=%.12e\n",(*func)(ptt),(ptt[j]-p[j])/((*func)(ptt)-(*func)(p)));  
       }    Revision 1.183  2015/03/10 20:34:32  brouard
 #endif    Summary: 0.98q0, trying with directest, mnbrak fixed
   
     We use directest instead of original Powell test; probably no
       free_vector(xit,1,n);    incidence on the results, but better justifications;
       free_vector(xits,1,n);    We fixed Numerical Recipes mnbrak routine which was wrong and gave
       free_vector(ptt,1,n);    wrong results.
       free_vector(pt,1,n);  
       return;    Revision 1.182  2015/02/12 08:19:57  brouard
     }    Summary: Trying to keep directest which seems simpler and more general
     if (*iter == ITMAX) nrerror("powell exceeding maximum iterations.");    Author: Nicolas Brouard
     for (j=1;j<=n;j++) {  
       ptt[j]=2.0*p[j]-pt[j];    Revision 1.181  2015/02/11 23:22:24  brouard
       xit[j]=p[j]-pt[j];    Summary: Comments on Powell added
       pt[j]=p[j];  
     }    Author:
     fptt=(*func)(ptt);  
     if (fptt < fp) {    Revision 1.180  2015/02/11 17:33:45  brouard
       t=2.0*(fp-2.0*(*fret)+fptt)*SQR(fp-(*fret)-del)-del*SQR(fp-fptt);    Summary: Finishing move from main to function (hpijx and prevalence_limit)
       if (t < 0.0) {  
         linmin(p,xit,n,fret,func);    Revision 1.179  2015/01/04 09:57:06  brouard
         for (j=1;j<=n;j++) {    Summary: back to OS/X
           xi[j][ibig]=xi[j][n];  
           xi[j][n]=xit[j];    Revision 1.178  2015/01/04 09:35:48  brouard
         }    *** empty log message ***
 #ifdef DEBUG  
         printf("Direction changed  last moved %d in place of ibig=%d, new last is the average:\n",n,ibig);    Revision 1.177  2015/01/03 18:40:56  brouard
         for(j=1;j<=n;j++)    Summary: Still testing ilc32 on OSX
           printf(" %.12e",xit[j]);  
         printf("\n");    Revision 1.176  2015/01/03 16:45:04  brouard
 #endif    *** empty log message ***
       }  
     }    Revision 1.175  2015/01/03 16:33:42  brouard
   }    *** empty log message ***
 }  
     Revision 1.174  2015/01/03 16:15:49  brouard
 /**** Prevalence limit ****************/    Summary: Still in cross-compilation
   
 double **prevalim(double **prlim, int nlstate, double x[], double age, double **oldm, double **savm, double ftolpl, int ij)    Revision 1.173  2015/01/03 12:06:26  brouard
 {    Summary: trying to detect cross-compilation
   /* Computes the prevalence limit in each live state at age x by left multiplying the unit  
      matrix by transitions matrix until convergence is reached */    Revision 1.172  2014/12/27 12:07:47  brouard
     Summary: Back from Visual Studio and Intel, options for compiling for Windows XP
   int i, ii,j,k;  
   double min, max, maxmin, maxmax,sumnew=0.;    Revision 1.171  2014/12/23 13:26:59  brouard
   double **matprod2();    Summary: Back from Visual C
   double **out, cov[NCOVMAX], **pmij();  
   double **newm;    Still problem with utsname.h on Windows
   double agefin, delaymax=50 ; /* Max number of years to converge */  
     Revision 1.170  2014/12/23 11:17:12  brouard
   for (ii=1;ii<=nlstate+ndeath;ii++)    Summary: Cleaning some \%% back to %%
     for (j=1;j<=nlstate+ndeath;j++){  
       oldm[ii][j]=(ii==j ? 1.0 : 0.0);    The escape was mandatory for a specific compiler (which one?), but too many warnings.
     }  
     Revision 1.169  2014/12/22 23:08:31  brouard
    cov[1]=1.;    Summary: 0.98p
    
  /* Even if hstepm = 1, at least one multiplication by the unit matrix */    Outputs some informations on compiler used, OS etc. Testing on different platforms.
   for(agefin=age-stepm/YEARM; agefin>=age-delaymax; agefin=agefin-stepm/YEARM){  
     newm=savm;    Revision 1.168  2014/12/22 15:17:42  brouard
     /* Covariates have to be included here again */    Summary: update
      cov[2]=agefin;  
      Revision 1.167  2014/12/22 13:50:56  brouard
       for (k=1; k<=cptcovn;k++) {    Summary: Testing uname and compiler version and if compiled 32 or 64
         cov[2+k]=nbcode[Tvar[k]][codtab[ij][k]];  
     Testing on Linux 64
 /*printf("Tcode[ij]=%d nbcode=%d\n",Tcode[ij],nbcode[k][Tcode[ij]]);*/  
       }    Revision 1.166  2014/12/22 11:40:47  brouard
       for (k=1; k<=cptcovage;k++)    *** empty log message ***
         cov[2+Tage[k]]=cov[2+Tage[k]]*cov[2];  
        Revision 1.165  2014/12/16 11:20:36  brouard
     out=matprod2(newm, pmij(pmmij,cov,ncovmodel,x,nlstate),1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm);    Summary: After compiling on Visual C
   
     savm=oldm;    * imach.c (Module): Merging 1.61 to 1.162
     oldm=newm;  
     maxmax=0.;    Revision 1.164  2014/12/16 10:52:11  brouard
     for(j=1;j<=nlstate;j++){    Summary: Merging with Visual C after suppressing some warnings for unused variables. Also fixing Saito's bug 0.98Xn
       min=1.;  
       max=0.;    * imach.c (Module): Merging 1.61 to 1.162
       for(i=1; i<=nlstate; i++) {  
         sumnew=0;    Revision 1.163  2014/12/16 10:30:11  brouard
         for(k=1; k<=ndeath; k++) sumnew+=newm[i][nlstate+k];    * imach.c (Module): Merging 1.61 to 1.162
         prlim[i][j]= newm[i][j]/(1-sumnew);  
         max=FMAX(max,prlim[i][j]);    Revision 1.162  2014/09/25 11:43:39  brouard
         min=FMIN(min,prlim[i][j]);    Summary: temporary backup 0.99!
       }  
       maxmin=max-min;    Revision 1.1  2014/09/16 11:06:58  brouard
       maxmax=FMAX(maxmax,maxmin);    Summary: With some code (wrong) for nlopt
     }  
     if(maxmax < ftolpl){    Author:
       return prlim;  
     }    Revision 1.161  2014/09/15 20:41:41  brouard
   }    Summary: Problem with macro SQR on Intel compiler
 }  
     Revision 1.160  2014/09/02 09:24:05  brouard
 /*************** transition probabilities **********/    *** empty log message ***
   
 double **pmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate )    Revision 1.159  2014/09/01 10:34:10  brouard
 {    Summary: WIN32
   double s1, s2;    Author: Brouard
   /*double t34;*/  
   int i,j,j1, nc, ii, jj;    Revision 1.158  2014/08/27 17:11:51  brouard
     *** empty log message ***
     for(i=1; i<= nlstate; i++){  
     for(j=1; j<i;j++){    Revision 1.157  2014/08/27 16:26:55  brouard
       for (nc=1, s2=0.;nc <=ncovmodel; nc++){    Summary: Preparing windows Visual studio version
         /*s2 += param[i][j][nc]*cov[nc];*/    Author: Brouard
         s2 += x[(i-1)*nlstate*ncovmodel+(j-1)*ncovmodel+nc+(i-1)*(ndeath-1)*ncovmodel]*cov[nc];  
         /*printf("Int j<i s1=%.17e, s2=%.17e\n",s1,s2);*/    In order to compile on Visual studio, time.h is now correct and time_t
       }    and tm struct should be used. difftime should be used but sometimes I
       ps[i][j]=s2;    just make the differences in raw time format (time(&now).
       /*printf("s1=%.17e, s2=%.17e\n",s1,s2);*/    Trying to suppress #ifdef LINUX
     }    Add xdg-open for __linux in order to open default browser.
     for(j=i+1; j<=nlstate+ndeath;j++){  
       for (nc=1, s2=0.;nc <=ncovmodel; nc++){    Revision 1.156  2014/08/25 20:10:10  brouard
         s2 += x[(i-1)*nlstate*ncovmodel+(j-2)*ncovmodel+nc+(i-1)*(ndeath-1)*ncovmodel]*cov[nc];    *** empty log message ***
         /*printf("Int j>i s1=%.17e, s2=%.17e %lx %lx\n",s1,s2,s1,s2);*/  
       }    Revision 1.155  2014/08/25 18:32:34  brouard
       ps[i][j]=s2;    Summary: New compile, minor changes
     }    Author: Brouard
   }  
   for(i=1; i<= nlstate; i++){    Revision 1.154  2014/06/20 17:32:08  brouard
      s1=0;    Summary: Outputs now all graphs of convergence to period prevalence
     for(j=1; j<i; j++)  
       s1+=exp(ps[i][j]);    Revision 1.153  2014/06/20 16:45:46  brouard
     for(j=i+1; j<=nlstate+ndeath; j++)    Summary: If 3 live state, convergence to period prevalence on same graph
       s1+=exp(ps[i][j]);    Author: Brouard
     ps[i][i]=1./(s1+1.);  
     for(j=1; j<i; j++)    Revision 1.152  2014/06/18 17:54:09  brouard
       ps[i][j]= exp(ps[i][j])*ps[i][i];    Summary: open browser, use gnuplot on same dir than imach if not found in the path
     for(j=i+1; j<=nlstate+ndeath; j++)  
       ps[i][j]= exp(ps[i][j])*ps[i][i];    Revision 1.151  2014/06/18 16:43:30  brouard
     /* ps[i][nlstate+1]=1.-s1- ps[i][i];*/ /* Sum should be 1 */    *** empty log message ***
   } /* end i */  
     Revision 1.150  2014/06/18 16:42:35  brouard
   for(ii=nlstate+1; ii<= nlstate+ndeath; ii++){    Summary: If gnuplot is not in the path try on same directory than imach binary (OSX)
     for(jj=1; jj<= nlstate+ndeath; jj++){    Author: brouard
       ps[ii][jj]=0;  
       ps[ii][ii]=1;    Revision 1.149  2014/06/18 15:51:14  brouard
     }    Summary: Some fixes in parameter files errors
   }    Author: Nicolas Brouard
   
   /*   for(ii=1; ii<= nlstate+ndeath; ii++){    Revision 1.148  2014/06/17 17:38:48  brouard
     for(jj=1; jj<= nlstate+ndeath; jj++){    Summary: Nothing new
      printf("%lf ",ps[ii][jj]);    Author: Brouard
    }  
     printf("\n ");    Just a new packaging for OS/X version 0.98nS
     }  
     printf("\n ");printf("%lf ",cov[2]);*/    Revision 1.147  2014/06/16 10:33:11  brouard
 /*    *** empty log message ***
   for(i=1; i<= npar; i++) printf("%f ",x[i]);  
   goto end;*/    Revision 1.146  2014/06/16 10:20:28  brouard
     return ps;    Summary: Merge
 }    Author: Brouard
   
 /**************** Product of 2 matrices ******************/    Merge, before building revised version.
   
 double **matprod2(double **out, double **in,long nrl, long nrh, long ncl, long nch, long ncolol, long ncoloh, double **b)    Revision 1.145  2014/06/10 21:23:15  brouard
 {    Summary: Debugging with valgrind
   /* Computes the matric product of in(1,nrh-nrl+1)(1,nch-ncl+1) times    Author: Nicolas Brouard
      b(1,nch-ncl+1)(1,ncoloh-ncolol+1) into out(...) */  
   /* in, b, out are matrice of pointers which should have been initialized    Lot of changes in order to output the results with some covariates
      before: only the contents of out is modified. The function returns    After the Edimburgh REVES conference 2014, it seems mandatory to
      a pointer to pointers identical to out */    improve the code.
   long i, j, k;    No more memory valgrind error but a lot has to be done in order to
   for(i=nrl; i<= nrh; i++)    continue the work of splitting the code into subroutines.
     for(k=ncolol; k<=ncoloh; k++)    Also, decodemodel has been improved. Tricode is still not
       for(j=ncl,out[i][k]=0.; j<=nch; j++)    optimal. nbcode should be improved. Documentation has been added in
         out[i][k] +=in[i][j]*b[j][k];    the source code.
   
   return out;    Revision 1.143  2014/01/26 09:45:38  brouard
 }    Summary: Version 0.98nR (to be improved, but gives same optimization results as 0.98k. Nice, promising
   
     * imach.c (Module): Trying to merge old staffs together while being at Tokyo. Not tested...
 /************* Higher Matrix Product ***************/    (Module): Version 0.98nR Running ok, but output format still only works for three covariates.
   
 double ***hpxij(double ***po, int nhstepm, double age, int hstepm, double *x, int nlstate, int stepm, double **oldm, double **savm, int ij )    Revision 1.142  2014/01/26 03:57:36  brouard
 {    Summary: gnuplot changed plot w l 1 has to be changed to plot w l lt 2
   /* Computes the transition matrix starting at age 'age' over 'nhstepm*hstepm*stepm' month  
      duration (i.e. until    * imach.c (Module): Trying to merge old staffs together while being at Tokyo. Not tested...
      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    Revision 1.141  2014/01/26 02:42:01  brouard
      (typically every 2 years instead of every month which is too big).    * imach.c (Module): Trying to merge old staffs together while being at Tokyo. Not tested...
      Model is determined by parameters x and covariates have to be  
      included manually here.    Revision 1.140  2011/09/02 10:37:54  brouard
     Summary: times.h is ok with mingw32 now.
      */  
     Revision 1.139  2010/06/14 07:50:17  brouard
   int i, j, d, h, k;    After the theft of my laptop, I probably lost some lines of codes which were not uploaded to the CVS tree.
   double **out, cov[NCOVMAX];    I remember having already fixed agemin agemax which are pointers now but not cvs saved.
   double **newm;  
     Revision 1.138  2010/04/30 18:19:40  brouard
   /* Hstepm could be zero and should return the unit matrix */    *** empty log message ***
   for (i=1;i<=nlstate+ndeath;i++)  
     for (j=1;j<=nlstate+ndeath;j++){    Revision 1.137  2010/04/29 18:11:38  brouard
       oldm[i][j]=(i==j ? 1.0 : 0.0);    (Module): Checking covariates for more complex models
       po[i][j][0]=(i==j ? 1.0 : 0.0);    than V1+V2. A lot of change to be done. Unstable.
     }  
   /* Even if hstepm = 1, at least one multiplication by the unit matrix */    Revision 1.136  2010/04/26 20:30:53  brouard
   for(h=1; h <=nhstepm; h++){    (Module): merging some libgsl code. Fixing computation
     for(d=1; d <=hstepm; d++){    of likelione (using inter/intrapolation if mle = 0) in order to
       newm=savm;    get same likelihood as if mle=1.
       /* Covariates have to be included here again */    Some cleaning of code and comments added.
       cov[1]=1.;  
       cov[2]=age+((h-1)*hstepm + (d-1))*stepm/YEARM;    Revision 1.135  2009/10/29 15:33:14  brouard
       if (cptcovn>0){    (Module): Now imach stops if date of birth, at least year of birth, is not given. Some cleaning of the code.
       for (k=1; k<=cptcovn;k++) cov[2+k]=nbcode[Tvar[k]][codtab[ij][k]];  
     }    Revision 1.134  2009/10/29 13:18:53  brouard
       /*printf("hxi cptcov=%d cptcode=%d\n",cptcov,cptcode);*/    (Module): Now imach stops if date of birth, at least year of birth, is not given. Some cleaning of the code.
       /*printf("h=%d d=%d age=%f cov=%f\n",h,d,age,cov[2]);*/  
       out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath,    Revision 1.133  2009/07/06 10:21:25  brouard
                    pmij(pmmij,cov,ncovmodel,x,nlstate));    just nforces
       savm=oldm;  
       oldm=newm;    Revision 1.132  2009/07/06 08:22:05  brouard
     }    Many tings
     for(i=1; i<=nlstate+ndeath; i++)  
       for(j=1;j<=nlstate+ndeath;j++) {    Revision 1.131  2009/06/20 16:22:47  brouard
         po[i][j][h]=newm[i][j];    Some dimensions resccaled
         /*printf("i=%d j=%d h=%d po[i][j][h]=%f ",i,j,h,po[i][j][h]);  
          */    Revision 1.130  2009/05/26 06:44:34  brouard
       }    (Module): Max Covariate is now set to 20 instead of 8. A
   } /* end h */    lot of cleaning with variables initialized to 0. Trying to make
   return po;    V2+V3*age+V1+V4 strb=V3*age+V1+V4 working better.
 }  
     Revision 1.129  2007/08/31 13:49:27  lievre
     Modification of the way of exiting when the covariate is not binary in order to see on the window the error message before exiting
 /*************** log-likelihood *************/  
 double func( double *x)    Revision 1.128  2006/06/30 13:02:05  brouard
 {    (Module): Clarifications on computing e.j
   int i, ii, j, k, mi, d, kk;  
   double l, ll[NLSTATEMAX], cov[NCOVMAX];    Revision 1.127  2006/04/28 18:11:50  brouard
   double **out;    (Module): Yes the sum of survivors was wrong since
   double sw; /* Sum of weights */    imach-114 because nhstepm was no more computed in the age
   double lli; /* Individual log likelihood */    loop. Now we define nhstepma in the age loop.
   long ipmx;    (Module): In order to speed up (in case of numerous covariates) we
   /*extern weight */    compute health expectancies (without variances) in a first step
   /* We are differentiating ll according to initial status */    and then all the health expectancies with variances or standard
   /*  for (i=1;i<=npar;i++) printf("%f ", x[i]);*/    deviation (needs data from the Hessian matrices) which slows the
   /*for(i=1;i<imx;i++)    computation.
 printf(" %d\n",s[4][i]);    In the future we should be able to stop the program is only health
   */    expectancies and graph are needed without standard deviations.
   cov[1]=1.;  
     Revision 1.126  2006/04/28 17:23:28  brouard
   for(k=1; k<=nlstate; k++) ll[k]=0.;    (Module): Yes the sum of survivors was wrong since
   for (i=1,ipmx=0, sw=0.; i<=imx; i++){    imach-114 because nhstepm was no more computed in the age
     for (k=1; k<=cptcovn;k++) cov[2+k]=covar[Tvar[k]][i];    loop. Now we define nhstepma in the age loop.
        for(mi=1; mi<= wav[i]-1; mi++){    Version 0.98h
       for (ii=1;ii<=nlstate+ndeath;ii++)  
         for (j=1;j<=nlstate+ndeath;j++) oldm[ii][j]=(ii==j ? 1.0 : 0.0);    Revision 1.125  2006/04/04 15:20:31  lievre
             for(d=0; d<dh[mi][i]; d++){    Errors in calculation of health expectancies. Age was not initialized.
               newm=savm;    Forecasting file added.
               cov[2]=agev[mw[mi][i]][i]+d*stepm/YEARM;  
               for (kk=1; kk<=cptcovage;kk++) {    Revision 1.124  2006/03/22 17:13:53  lievre
                  cov[Tage[kk]+2]=covar[Tvar[Tage[kk]]][i]*cov[2];    Parameters are printed with %lf instead of %f (more numbers after the comma).
                  /*printf("%d %d",kk,Tage[kk]);*/    The log-likelihood is printed in the log file
               }  
               /*cov[4]=covar[1][i]*cov[2];scanf("%d", i);*/    Revision 1.123  2006/03/20 10:52:43  brouard
               /*cov[3]=pow(cov[2],2)/1000.;*/    * imach.c (Module): <title> changed, corresponds to .htm file
     name. <head> headers where missing.
           out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,  
                        1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));    * imach.c (Module): Weights can have a decimal point as for
           savm=oldm;    English (a comma might work with a correct LC_NUMERIC environment,
           oldm=newm;    otherwise the weight is truncated).
     Modification of warning when the covariates values are not 0 or
     1.
       } /* end mult */    Version 0.98g
      
       lli=log(out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]);    Revision 1.122  2006/03/20 09:45:41  brouard
       /* printf(" %f ",out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]);*/    (Module): Weights can have a decimal point as for
       ipmx +=1;    English (a comma might work with a correct LC_NUMERIC environment,
       sw += weight[i];    otherwise the weight is truncated).
       ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;    Modification of warning when the covariates values are not 0 or
     } /* end of wave */    1.
   } /* end of individual */    Version 0.98g
   
   for(k=1,l=0.; k<=nlstate; k++) l += ll[k];    Revision 1.121  2006/03/16 17:45:01  lievre
   /* printf("l1=%f l2=%f ",ll[1],ll[2]); */    * imach.c (Module): Comments concerning covariates added
   l= l*ipmx/sw; /* To get the same order of magnitude as if weight=1 for every body */  
   return -l;    * imach.c (Module): refinements in the computation of lli if
 }    status=-2 in order to have more reliable computation if stepm is
     not 1 month. Version 0.98f
   
 /*********** Maximum Likelihood Estimation ***************/    Revision 1.120  2006/03/16 15:10:38  lievre
     (Module): refinements in the computation of lli if
 void mlikeli(FILE *ficres,double p[], int npar, int ncovmodel, int nlstate, double ftol, double (*func)(double []))    status=-2 in order to have more reliable computation if stepm is
 {    not 1 month. Version 0.98f
   int i,j, iter;  
   double **xi,*delti;    Revision 1.119  2006/03/15 17:42:26  brouard
   double fret;    (Module): Bug if status = -2, the loglikelihood was
   xi=matrix(1,npar,1,npar);    computed as likelihood omitting the logarithm. Version O.98e
   for (i=1;i<=npar;i++)  
     for (j=1;j<=npar;j++)    Revision 1.118  2006/03/14 18:20:07  brouard
       xi[i][j]=(i==j ? 1.0 : 0.0);    (Module): varevsij Comments added explaining the second
   printf("Powell\n");    table of variances if popbased=1 .
   powell(p,xi,npar,ftol,&iter,&fret,func);    (Module): Covariances of eij, ekl added, graphs fixed, new html link.
     (Module): Function pstamp added
    printf("\n#Number of iterations = %d, -2 Log likelihood = %.12f\n",iter,func(p));    (Module): Version 0.98d
   fprintf(ficres,"#Number of iterations = %d, -2 Log likelihood = %.12f ",iter,func(p));  
     Revision 1.117  2006/03/14 17:16:22  brouard
 }    (Module): varevsij Comments added explaining the second
     table of variances if popbased=1 .
 /**** Computes Hessian and covariance matrix ***/    (Module): Covariances of eij, ekl added, graphs fixed, new html link.
 void hesscov(double **matcov, double p[], int npar, double delti[], double ftolhess, double (*func)(double []))    (Module): Function pstamp added
 {    (Module): Version 0.98d
   double  **a,**y,*x,pd;  
   double **hess;    Revision 1.116  2006/03/06 10:29:27  brouard
   int i, j,jk;    (Module): Variance-covariance wrong links and
   int *indx;    varian-covariance of ej. is needed (Saito).
   
   double hessii(double p[], double delta, int theta, double delti[]);    Revision 1.115  2006/02/27 12:17:45  brouard
   double hessij(double p[], double delti[], int i, int j);    (Module): One freematrix added in mlikeli! 0.98c
   void lubksb(double **a, int npar, int *indx, double b[]) ;  
   void ludcmp(double **a, int npar, int *indx, double *d) ;    Revision 1.114  2006/02/26 12:57:58  brouard
     (Module): Some improvements in processing parameter
     filename with strsep.
   hess=matrix(1,npar,1,npar);  
     Revision 1.113  2006/02/24 14:20:24  brouard
   printf("\nCalculation of the hessian matrix. Wait...\n");    (Module): Memory leaks checks with valgrind and:
   for (i=1;i<=npar;i++){    datafile was not closed, some imatrix were not freed and on matrix
     printf("%d",i);fflush(stdout);    allocation too.
     hess[i][i]=hessii(p,ftolhess,i,delti);  
     /*printf(" %f ",p[i]);*/    Revision 1.112  2006/01/30 09:55:26  brouard
   }    (Module): Back to gnuplot.exe instead of wgnuplot.exe
   
   for (i=1;i<=npar;i++) {    Revision 1.111  2006/01/25 20:38:18  brouard
     for (j=1;j<=npar;j++)  {    (Module): Lots of cleaning and bugs added (Gompertz)
       if (j>i) {    (Module): Comments can be added in data file. Missing date values
         printf(".%d%d",i,j);fflush(stdout);    can be a simple dot '.'.
         hess[i][j]=hessij(p,delti,i,j);  
         hess[j][i]=hess[i][j];    Revision 1.110  2006/01/25 00:51:50  brouard
       }    (Module): Lots of cleaning and bugs added (Gompertz)
     }  
   }    Revision 1.109  2006/01/24 19:37:15  brouard
   printf("\n");    (Module): Comments (lines starting with a #) are allowed in data.
   
   printf("\nInverting the hessian to get the covariance matrix. Wait...\n");    Revision 1.108  2006/01/19 18:05:42  lievre
      Gnuplot problem appeared...
   a=matrix(1,npar,1,npar);    To be fixed
   y=matrix(1,npar,1,npar);  
   x=vector(1,npar);    Revision 1.107  2006/01/19 16:20:37  brouard
   indx=ivector(1,npar);    Test existence of gnuplot in imach path
   for (i=1;i<=npar;i++)  
     for (j=1;j<=npar;j++) a[i][j]=hess[i][j];    Revision 1.106  2006/01/19 13:24:36  brouard
   ludcmp(a,npar,indx,&pd);    Some cleaning and links added in html output
   
   for (j=1;j<=npar;j++) {    Revision 1.105  2006/01/05 20:23:19  lievre
     for (i=1;i<=npar;i++) x[i]=0;    *** empty log message ***
     x[j]=1;  
     lubksb(a,npar,indx,x);    Revision 1.104  2005/09/30 16:11:43  lievre
     for (i=1;i<=npar;i++){    (Module): sump fixed, loop imx fixed, and simplifications.
       matcov[i][j]=x[i];    (Module): If the status is missing at the last wave but we know
     }    that the person is alive, then we can code his/her status as -2
   }    (instead of missing=-1 in earlier versions) and his/her
     contributions to the likelihood is 1 - Prob of dying from last
   printf("\n#Hessian matrix#\n");    health status (= 1-p13= p11+p12 in the easiest case of somebody in
   for (i=1;i<=npar;i++) {    the healthy state at last known wave). Version is 0.98
     for (j=1;j<=npar;j++) {  
       printf("%.3e ",hess[i][j]);    Revision 1.103  2005/09/30 15:54:49  lievre
     }    (Module): sump fixed, loop imx fixed, and simplifications.
     printf("\n");  
   }    Revision 1.102  2004/09/15 17:31:30  brouard
     Add the possibility to read data file including tab characters.
   /* Recompute Inverse */  
   for (i=1;i<=npar;i++)    Revision 1.101  2004/09/15 10:38:38  brouard
     for (j=1;j<=npar;j++) a[i][j]=matcov[i][j];    Fix on curr_time
   ludcmp(a,npar,indx,&pd);  
     Revision 1.100  2004/07/12 18:29:06  brouard
   /*  printf("\n#Hessian matrix recomputed#\n");    Add version for Mac OS X. Just define UNIX in Makefile
   
   for (j=1;j<=npar;j++) {    Revision 1.99  2004/06/05 08:57:40  brouard
     for (i=1;i<=npar;i++) x[i]=0;    *** empty log message ***
     x[j]=1;  
     lubksb(a,npar,indx,x);    Revision 1.98  2004/05/16 15:05:56  brouard
     for (i=1;i<=npar;i++){    New version 0.97 . First attempt to estimate force of mortality
       y[i][j]=x[i];    directly from the data i.e. without the need of knowing the health
       printf("%.3e ",y[i][j]);    state at each age, but using a Gompertz model: log u =a + b*age .
     }    This is the basic analysis of mortality and should be done before any
     printf("\n");    other analysis, in order to test if the mortality estimated from the
   }    cross-longitudinal survey is different from the mortality estimated
   */    from other sources like vital statistic data.
   
   free_matrix(a,1,npar,1,npar);    The same imach parameter file can be used but the option for mle should be -3.
   free_matrix(y,1,npar,1,npar);  
   free_vector(x,1,npar);    AgneÌ€s, who wrote this part of the code, tried to keep most of the
   free_ivector(indx,1,npar);    former routines in order to include the new code within the former code.
   free_matrix(hess,1,npar,1,npar);  
     The output is very simple: only an estimate of the intercept and of
     the slope with 95% confident intervals.
 }  
     Current limitations:
 /*************** hessian matrix ****************/    A) Even if you enter covariates, i.e. with the
 double hessii( double x[], double delta, int theta, double delti[])    model= V1+V2 equation for example, the programm does only estimate a unique global model without covariates.
 {    B) There is no computation of Life Expectancy nor Life Table.
   int i;  
   int l=1, lmax=20;    Revision 1.97  2004/02/20 13:25:42  lievre
   double k1,k2;    Version 0.96d. Population forecasting command line is (temporarily)
   double p2[NPARMAX+1];    suppressed.
   double res;  
   double delt, delts, nkhi=10.,nkhif=1., khi=1.e-4;    Revision 1.96  2003/07/15 15:38:55  brouard
   double fx;    * imach.c (Repository): Errors in subdirf, 2, 3 while printing tmpout is
   int k=0,kmax=10;    rewritten within the same printf. Workaround: many printfs.
   double l1;  
     Revision 1.95  2003/07/08 07:54:34  brouard
   fx=func(x);    * imach.c (Repository):
   for (i=1;i<=npar;i++) p2[i]=x[i];    (Repository): Using imachwizard code to output a more meaningful covariance
   for(l=0 ; l <=lmax; l++){    matrix (cov(a12,c31) instead of numbers.
     l1=pow(10,l);  
     delts=delt;    Revision 1.94  2003/06/27 13:00:02  brouard
     for(k=1 ; k <kmax; k=k+1){    Just cleaning
       delt = delta*(l1*k);  
       p2[theta]=x[theta] +delt;    Revision 1.93  2003/06/25 16:33:55  brouard
       k1=func(p2)-fx;    (Module): On windows (cygwin) function asctime_r doesn't
       p2[theta]=x[theta]-delt;    exist so I changed back to asctime which exists.
       k2=func(p2)-fx;    (Module): Version 0.96b
       /*res= (k1-2.0*fx+k2)/delt/delt; */  
       res= (k1+k2)/delt/delt/2.; /* Divided by because L and not 2*L */    Revision 1.92  2003/06/25 16:30:45  brouard
          (Module): On windows (cygwin) function asctime_r doesn't
 #ifdef DEBUG    exist so I changed back to asctime which exists.
       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);  
 #endif    Revision 1.91  2003/06/25 15:30:29  brouard
       /*if(fabs(k1-2.0*fx+k2) <1.e-13){ */    * imach.c (Repository): Duplicated warning errors corrected.
       if((k1 <khi/nkhi/2.) || (k2 <khi/nkhi/2.)){    (Repository): Elapsed time after each iteration is now output. It
         k=kmax;    helps to forecast when convergence will be reached. Elapsed time
       }    is stamped in powell.  We created a new html file for the graphs
       else if((k1 >khi/nkhif) || (k2 >khi/nkhif)){ /* Keeps lastvalue before 3.84/2 KHI2 5% 1d.f. */    concerning matrix of covariance. It has extension -cov.htm.
         k=kmax; l=lmax*10.;  
       }    Revision 1.90  2003/06/24 12:34:15  brouard
       else if((k1 >khi/nkhi) || (k2 >khi/nkhi)){    (Module): Some bugs corrected for windows. Also, when
         delts=delt;    mle=-1 a template is output in file "or"mypar.txt with the design
       }    of the covariance matrix to be input.
     }  
   }    Revision 1.89  2003/06/24 12:30:52  brouard
   delti[theta]=delts;    (Module): Some bugs corrected for windows. Also, when
   return res;    mle=-1 a template is output in file "or"mypar.txt with the design
      of the covariance matrix to be input.
 }  
     Revision 1.88  2003/06/23 17:54:56  brouard
 double hessij( double x[], double delti[], int thetai,int thetaj)    * 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.
 {  
   int i;    Revision 1.87  2003/06/18 12:26:01  brouard
   int l=1, l1, lmax=20;    Version 0.96
   double k1,k2,k3,k4,res,fx;  
   double p2[NPARMAX+1];    Revision 1.86  2003/06/17 20:04:08  brouard
   int k;    (Module): Change position of html and gnuplot routines and added
     routine fileappend.
   fx=func(x);  
   for (k=1; k<=2; k++) {    Revision 1.85  2003/06/17 13:12:43  brouard
     for (i=1;i<=npar;i++) p2[i]=x[i];    * imach.c (Repository): Check when date of death was earlier that
     p2[thetai]=x[thetai]+delti[thetai]/k;    current date of interview. It may happen when the death was just
     p2[thetaj]=x[thetaj]+delti[thetaj]/k;    prior to the death. In this case, dh was negative and likelihood
     k1=func(p2)-fx;    was wrong (infinity). We still send an "Error" but patch by
      assuming that the date of death was just one stepm after the
     p2[thetai]=x[thetai]+delti[thetai]/k;    interview.
     p2[thetaj]=x[thetaj]-delti[thetaj]/k;    (Repository): Because some people have very long ID (first column)
     k2=func(p2)-fx;    we changed int to long in num[] and we added a new lvector for
      memory allocation. But we also truncated to 8 characters (left
     p2[thetai]=x[thetai]-delti[thetai]/k;    truncation)
     p2[thetaj]=x[thetaj]+delti[thetaj]/k;    (Repository): No more line truncation errors.
     k3=func(p2)-fx;  
      Revision 1.84  2003/06/13 21:44:43  brouard
     p2[thetai]=x[thetai]-delti[thetai]/k;    * imach.c (Repository): Replace "freqsummary" at a correct
     p2[thetaj]=x[thetaj]-delti[thetaj]/k;    place. It differs from routine "prevalence" which may be called
     k4=func(p2)-fx;    many times. Probs is memory consuming and must be used with
     res=(k1-k2-k3+k4)/4.0/delti[thetai]*k/delti[thetaj]*k/2.; /* Because of L not 2*L */    parcimony.
 #ifdef DEBUG    Version 0.95a3 (should output exactly the same maximization than 0.8a2)
     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);  
 #endif    Revision 1.83  2003/06/10 13:39:11  lievre
   }    *** empty log message ***
   return res;  
 }    Revision 1.82  2003/06/05 15:57:20  brouard
     Add log in  imach.c and  fullversion number is now printed.
 /************** Inverse of matrix **************/  
 void ludcmp(double **a, int n, int *indx, double *d)  */
 {  /*
   int i,imax,j,k;     Interpolated Markov Chain
   double big,dum,sum,temp;  
   double *vv;    Short summary of the programme:
      
   vv=vector(1,n);    This program computes Healthy Life Expectancies or State-specific
   *d=1.0;    (if states aren't health statuses) Expectancies from
   for (i=1;i<=n;i++) {    cross-longitudinal data. Cross-longitudinal data consist in: 
     big=0.0;  
     for (j=1;j<=n;j++)    -1- a first survey ("cross") where individuals from different ages
       if ((temp=fabs(a[i][j])) > big) big=temp;    are interviewed on their health status or degree of disability (in
     if (big == 0.0) nrerror("Singular matrix in routine ludcmp");    the case of a health survey which is our main interest)
     vv[i]=1.0/big;  
   }    -2- at least a second wave of interviews ("longitudinal") which
   for (j=1;j<=n;j++) {    measure each change (if any) in individual health status.  Health
     for (i=1;i<j;i++) {    expectancies are computed from the time spent in each health state
       sum=a[i][j];    according to a model. More health states you consider, more time is
       for (k=1;k<i;k++) sum -= a[i][k]*a[k][j];    necessary to reach the Maximum Likelihood of the parameters involved
       a[i][j]=sum;    in the model.  The simplest model is the multinomial logistic model
     }    where pij is the probability to be observed in state j at the second
     big=0.0;    wave conditional to be observed in state i at the first
     for (i=j;i<=n;i++) {    wave. Therefore the model is: log(pij/pii)= aij + bij*age+ cij*sex +
       sum=a[i][j];    etc , where 'age' is age and 'sex' is a covariate. If you want to
       for (k=1;k<j;k++)    have a more complex model than "constant and age", you should modify
         sum -= a[i][k]*a[k][j];    the program where the markup *Covariates have to be included here
       a[i][j]=sum;    again* invites you to do it.  More covariates you add, slower the
       if ( (dum=vv[i]*fabs(sum)) >= big) {    convergence.
         big=dum;  
         imax=i;    The advantage of this computer programme, compared to a simple
       }    multinomial logistic model, is clear when the delay between waves is not
     }    identical for each individual. Also, if a individual missed an
     if (j != imax) {    intermediate interview, the information is lost, but taken into
       for (k=1;k<=n;k++) {    account using an interpolation or extrapolation.  
         dum=a[imax][k];  
         a[imax][k]=a[j][k];    hPijx is the probability to be observed in state i at age x+h
         a[j][k]=dum;    conditional to the observed state i at age x. The delay 'h' can be
       }    split into an exact number (nh*stepm) of unobserved intermediate
       *d = -(*d);    states. This elementary transition (by month, quarter,
       vv[imax]=vv[j];    semester or year) is modelled as a multinomial logistic.  The hPx
     }    matrix is simply the matrix product of nh*stepm elementary matrices
     indx[j]=imax;    and the contribution of each individual to the likelihood is simply
     if (a[j][j] == 0.0) a[j][j]=TINY;    hPijx.
     if (j != n) {  
       dum=1.0/(a[j][j]);    Also this programme outputs the covariance matrix of the parameters but also
       for (i=j+1;i<=n;i++) a[i][j] *= dum;    of the life expectancies. It also computes the period (stable) prevalence.
     }  
   }  Back prevalence and projections:
   free_vector(vv,1,n);  /* Doesn't work */  
 ;   - back_prevalence_limit(double *p, double **bprlim, double ageminpar,
 }     double agemaxpar, double ftolpl, int *ncvyearp, double
      dateprev1,double dateprev2, int firstpass, int lastpass, int
 void lubksb(double **a, int n, int *indx, double b[])     mobilavproj)
 {  
   int i,ii=0,ip,j;      Computes the back prevalence limit for any combination of
   double sum;      covariate values k at any age between ageminpar and agemaxpar and
        returns it in **bprlim. In the loops,
   for (i=1;i<=n;i++) {  
     ip=indx[i];     - **bprevalim(**bprlim, ***mobaverage, nlstate, *p, age, **oldm,
     sum=b[ip];         **savm, **dnewm, **doldm, **dsavm, ftolpl, ncvyearp, k);
     b[ip]=b[i];  
     if (ii)     - hBijx Back Probability to be in state i at age x-h being in j at x
       for (j=ii;j<=i-1;j++) sum -= a[i][j]*b[j];     Computes for any combination of covariates k and any age between bage and fage 
     else if (sum) ii=i;     p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
     b[i]=sum;                          oldm=oldms;savm=savms;
   }  
   for (i=n;i>=1;i--) {     - hbxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k, nres);
     sum=b[i];       Computes the transition matrix starting at age 'age' over
     for (j=i+1;j<=n;j++) sum -= a[i][j]*b[j];       'nhstepm*hstepm*stepm' months (i.e. until
     b[i]=sum/a[i][i];       age (in years)  age+nhstepm*hstepm*stepm/12) by multiplying
   }       nhstepm*hstepm matrices. 
 }  
        Returns p3mat[i][j][h] after calling
 /************ Frequencies ********************/       p3mat[i][j][h]=matprod2(newm,
 void  freqsummary(char fileres[], int agemin, int agemax, int **s, double **agev, int nlstate, int imx, int *Tvar, int **nbcode, int *ncodemax)       bmij(pmmij,cov,ncovmodel,x,nlstate,prevacurrent, dnewm, doldm,
 {  /* Some frequencies */       dsavm,ij),\ 1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath,
         oldm);
   int i, m, jk, k1, i1, j1, bool, z1,z2,j;  
   double ***freq; /* Frequencies */  Important routines
   double *pp;  
   double pos;  - func (or funcone), computes logit (pij) distinguishing
   FILE *ficresp;    o fixed variables (single or product dummies or quantitative);
   char fileresp[FILENAMELENGTH];    o varying variables by:
      (1) wave (single, product dummies, quantitative), 
   pp=vector(1,nlstate);     (2) by age (can be month) age (done), age*age (done), age*Vn where Vn can be:
          % fixed dummy (treated) or quantitative (not done because time-consuming);
   strcpy(fileresp,"p");         % varying dummy (not done) or quantitative (not done);
   strcat(fileresp,fileres);  - Tricode which tests the modality of dummy variables (in order to warn with wrong or empty modalities)
   if((ficresp=fopen(fileresp,"w"))==NULL) {    and returns the number of efficient covariates cptcoveff and modalities nbcode[Tvar[k]][1]= 0 and nbcode[Tvar[k]][2]= 1 usually.
     printf("Problem with prevalence resultfile: %s\n", fileresp);  - printinghtml which outputs results like life expectancy in and from a state for a combination of modalities of dummy variables
     exit(0);    o There are 2**cptcoveff combinations of (0,1) for cptcoveff variables. Outputting only combinations with people, eÌliminating 1 1 if
   }      race White (0 0), Black vs White (1 0), Hispanic (0 1) and 1 1 being meaningless.
   freq= ma3x(-1,nlstate+ndeath,-1,nlstate+ndeath,agemin,agemax+3);  
   j1=0;  
     
   j=cptcovn;    Authors: Nicolas Brouard (brouard@ined.fr) and AgneÌ€s LieÌ€vre (lievre@ined.fr).
   if (cptcovn<1) {j=1;ncodemax[1]=1;}             Institut national d'eÌtudes deÌmographiques, Paris.
     This software have been partly granted by Euro-REVES, a concerted action
   for(k1=1; k1<=j;k1++){    from the European Union.
    for(i1=1; i1<=ncodemax[k1];i1++){    It is copyrighted identically to a GNU software product, ie programme and
        j1++;    software can be distributed freely for non commercial use. Latest version
     can be accessed at http://euroreves.ined.fr/imach .
         for (i=-1; i<=nlstate+ndeath; i++)    
          for (jk=-1; jk<=nlstate+ndeath; jk++)      Help to debug: LD_PRELOAD=/usr/local/lib/libnjamd.so ./imach foo.imach
            for(m=agemin; m <= agemax+3; m++)    or better on gdb : set env LD_PRELOAD=/usr/local/lib/libnjamd.so
              freq[i][jk][m]=0;    
            **********************************************************************/
        for (i=1; i<=imx; i++) {  /*
          bool=1;    main
          if  (cptcovn>0) {    read parameterfile
            for (z1=1; z1<=cptcovn; z1++)    read datafile
              if (covar[Tvar[z1]][i]!= nbcode[Tvar[z1]][codtab[j1][z1]]) bool=0;    concatwav
          }    freqsummary
           if (bool==1) {    if (mle >= 1)
            for(m=firstpass; m<=lastpass-1; m++){      mlikeli
              if(agev[m][i]==0) agev[m][i]=agemax+1;    print results files
              if(agev[m][i]==1) agev[m][i]=agemax+2;    if mle==1 
              freq[s[m][i]][s[m+1][i]][(int)agev[m][i]] += weight[i];       computes hessian
              freq[s[m][i]][s[m+1][i]][(int) agemax+3] += weight[i];    read end of parameter file: agemin, agemax, bage, fage, estepm
            }        begin-prev-date,...
          }    open gnuplot file
        }    open html file
         if  (cptcovn>0) {    period (stable) prevalence      | pl_nom    1-1 2-2 etc by covariate
          fprintf(ficresp, "\n#Variable");     for age prevalim()             | #****** V1=0  V2=1  V3=1  V4=0 ******
          for (z1=1; z1<=cptcovn; z1++) fprintf(ficresp, " V%d=%d",Tvar[z1],nbcode[Tvar[z1]][codtab[j1][z1]]);                                    | 65 1 0 2 1 3 1 4 0  0.96326 0.03674
        }      freexexit2 possible for memory heap.
        fprintf(ficresp, "\n#");  
        for(i=1; i<=nlstate;i++)    h Pij x                         | pij_nom  ficrestpij
          fprintf(ficresp, " Age Prev(%d) N(%d) N",i,i);     # Cov Agex agex+h hpijx with i,j= 1-1 1-2     1-3     2-1     2-2     2-3
        fprintf(ficresp, "\n");         1  85   85    1.00000             0.00000 0.00000 0.00000 1.00000 0.00000
                 1  85   86    0.68299             0.22291 0.09410 0.71093 0.00000 0.28907
   for(i=(int)agemin; i <= (int)agemax+3; i++){  
     if(i==(int)agemax+3)         1  65   99    0.00364             0.00322 0.99314 0.00350 0.00310 0.99340
       printf("Total");         1  65  100    0.00214             0.00204 0.99581 0.00206 0.00196 0.99597
     else    variance of p one-step probabilities varprob  | prob_nom   ficresprob #One-step probabilities and stand. devi in ()
       printf("Age %d", i);     Standard deviation of one-step probabilities | probcor_nom   ficresprobcor #One-step probabilities and correlation matrix
     for(jk=1; jk <=nlstate ; jk++){     Matrix of variance covariance of one-step probabilities |  probcov_nom ficresprobcov #One-step probabilities and covariance matrix
       for(m=-1, pp[jk]=0; m <=nlstate+ndeath ; m++)  
         pp[jk] += freq[jk][m][i];    forecasting if prevfcast==1 prevforecast call prevalence()
     }    health expectancies
     for(jk=1; jk <=nlstate ; jk++){    Variance-covariance of DFLE
       for(m=-1, pos=0; m <=0 ; m++)    prevalence()
         pos += freq[jk][m][i];     movingaverage()
       if(pp[jk]>=1.e-10)    varevsij() 
         printf(" %d.=%.0f loss[%d]=%.1f%%",jk,pp[jk],jk,100*pos/pp[jk]);    if popbased==1 varevsij(,popbased)
       else    total life expectancies
         printf(" %d.=%.0f loss[%d]=NaNQ%%",jk,pp[jk],jk);    Variance of period (stable) prevalence
     }   end
     for(jk=1; jk <=nlstate ; jk++){  */
       for(m=1, pp[jk]=0; m <=nlstate+ndeath; m++)  
         pp[jk] += freq[jk][m][i];  /* #define DEBUG */
     }  /* #define DEBUGBRENT */
     for(jk=1,pos=0; jk <=nlstate ; jk++)  /* #define DEBUGLINMIN */
       pos += pp[jk];  /* #define DEBUGHESS */
     for(jk=1; jk <=nlstate ; jk++){  #define DEBUGHESSIJ
       if(pos>=1.e-5)  /* #define LINMINORIGINAL  /\* Don't use loop on scale in linmin (accepting nan) *\/ */
         printf(" %d.=%.0f prev[%d]=%.1f%%",jk,pp[jk],jk,100*pp[jk]/pos);  #define POWELL /* Instead of NLOPT */
       else  #define POWELLNOF3INFF1TEST /* Skip test */
         printf(" %d.=%.0f prev[%d]=NaNQ%%",jk,pp[jk],jk);  /* #define POWELLORIGINAL /\* Don't use Directest to decide new direction but original Powell test *\/ */
       if( i <= (int) agemax){  /* #define MNBRAKORIGINAL /\* Don't use mnbrak fix *\/ */
         if(pos>=1.e-5)  /* #define FLATSUP  *//* Suppresses directions where likelihood is flat */
           fprintf(ficresp," %d %.5f %.0f %.0f",i,pp[jk]/pos, pp[jk],pos);  
       else  #include <math.h>
           fprintf(ficresp," %d NaNq %.0f %.0f",i,pp[jk],pos);  #include <stdio.h>
       }  #include <stdlib.h>
     }  #include <string.h>
     for(jk=-1; jk <=nlstate+ndeath; jk++)  #include <ctype.h>
       for(m=-1; m <=nlstate+ndeath; m++)  
         if(freq[jk][m][i] !=0 ) printf(" %d%d=%.0f",jk,m,freq[jk][m][i]);  #ifdef _WIN32
     if(i <= (int) agemax)  #include <io.h>
       fprintf(ficresp,"\n");  #include <windows.h>
     printf("\n");  #include <tchar.h>
     }  #else
     }  #include <unistd.h>
  }  #endif
    
   fclose(ficresp);  #include <limits.h>
   free_ma3x(freq,-1,nlstate+ndeath,-1,nlstate+ndeath,(int) agemin,(int) agemax+3);  #include <sys/types.h>
   free_vector(pp,1,nlstate);  
   #if defined(__GNUC__)
 }  /* End of Freq */  #include <sys/utsname.h> /* Doesn't work on Windows */
   #endif
 /************* Waves Concatenation ***************/  
   #include <sys/stat.h>
 void  concatwav(int wav[], int **dh, int **mw, int **s, double *agedc, double **agev, int  firstpass, int lastpass, int imx, int nlstate, int stepm)  #include <errno.h>
 {  /* extern int errno; */
   /* Concatenates waves: wav[i] is the number of effective (useful waves) of individual i.  
      Death is a valid wave (if date is known).  /* #ifdef LINUX */
      mw[mi][i] is the mi (mi=1 to wav[i])  effective wave of individual i  /* #include <time.h> */
      dh[m][i] of dh[mw[mi][i][i] is the delay between two effective waves m=mw[mi][i]  /* #include "timeval.h" */
      and mw[mi+1][i]. dh depends on stepm.  /* #else */
      */  /* #include <sys/time.h> */
   /* #endif */
   int i, mi, m;  
   int j, k=0,jk, ju, jl,jmin=1e+5, jmax=-1;  #include <time.h>
 float sum=0.;  
   #ifdef GSL
   for(i=1; i<=imx; i++){  #include <gsl/gsl_errno.h>
     mi=0;  #include <gsl/gsl_multimin.h>
     m=firstpass;  #endif
     while(s[m][i] <= nlstate){  
       if(s[m][i]>=1)  
         mw[++mi][i]=m;  #ifdef NLOPT
       if(m >=lastpass)  #include <nlopt.h>
         break;  typedef struct {
       else    double (* function)(double [] );
         m++;  } myfunc_data ;
     }/* end while */  #endif
     if (s[m][i] > nlstate){  
       mi++;     /* Death is another wave */  /* #include <libintl.h> */
       /* if(mi==0)  never been interviewed correctly before death */  /* #define _(String) gettext (String) */
          /* Only death is a correct wave */  
       mw[mi][i]=m;  #define MAXLINE 2048 /* Was 256 and 1024. Overflow with 312 with 2 states and 4 covariates. Should be ok */
     }  
   #define GNUPLOTPROGRAM "gnuplot"
     wav[i]=mi;  /*#define GNUPLOTPROGRAM "..\\gp37mgw\\wgnuplot"*/
     if(mi==0)  #define FILENAMELENGTH 256
       printf("Warning, no any valid information for:%d line=%d\n",num[i],i);  
   }  #define GLOCK_ERROR_NOPATH              -1      /* empty path */
   #define GLOCK_ERROR_GETCWD              -2      /* cannot get cwd */
   for(i=1; i<=imx; i++){  
     for(mi=1; mi<wav[i];mi++){  #define MAXPARM 128 /**< Maximum number of parameters for the optimization */
       if (stepm <=0)  #define NPARMAX 64 /**< (nlstate+ndeath-1)*nlstate*ncovmodel */
         dh[mi][i]=1;  
       else{  #define NINTERVMAX 8
         if (s[mw[mi+1][i]][i] > nlstate) {  #define NLSTATEMAX 8 /**< Maximum number of live states (for func) */
           j= rint(agedc[i]*12-agev[mw[mi][i]][i]*12);  #define NDEATHMAX 8 /**< Maximum number of dead states (for func) */
           if(j=0) j=1;  /* Survives at least one month after exam */  #define NCOVMAX 30  /**< Maximum number of covariates used in the model, including generated covariates V1*V2 or V1*age */
         }  #define codtabm(h,k)  (1 & (h-1) >> (k-1))+1
         else{  /*#define decodtabm(h,k,cptcoveff)= (h <= (1<<cptcoveff)?(((h-1) >> (k-1)) & 1) +1 : -1)*/
           j= rint( (agev[mw[mi+1][i]][i]*12 - agev[mw[mi][i]][i]*12));  #define decodtabm(h,k,cptcoveff) (((h-1) >> (k-1)) & 1) +1 
           k=k+1;  /*#define MAXN 20000 */ /* Should by replaced by nobs, real number of observations and unlimited */
           if (j >= jmax) jmax=j;  #define YEARM 12. /**< Number of months per year */
           else if (j <= jmin)jmin=j;  /* #define AGESUP 130 */
           sum=sum+j;  /* #define AGESUP 150 */
         }  #define AGESUP 200
         jk= j/stepm;  #define AGEINF 0
         jl= j -jk*stepm;  #define AGEMARGE 25 /* Marge for agemin and agemax for(iage=agemin-AGEMARGE; iage <= agemax+3+AGEMARGE; iage++) */
         ju= j -(jk+1)*stepm;  #define AGEBASE 40
         if(jl <= -ju)  #define AGEOVERFLOW 1.e20
           dh[mi][i]=jk;  #define AGEGOMP 10 /**< Minimal age for Gompertz adjustment */
         else  #ifdef _WIN32
           dh[mi][i]=jk+1;  #define DIRSEPARATOR '\\'
         if(dh[mi][i]==0)  #define CHARSEPARATOR "\\"
           dh[mi][i]=1; /* At least one step */  #define ODIRSEPARATOR '/'
       }  #else
     }  #define DIRSEPARATOR '/'
   }  #define CHARSEPARATOR "/"
   printf("Delay (in months) between two waves Min=%d Max=%d Mean=%f\n\n ",jmin, jmax,sum/k);  #define ODIRSEPARATOR '\\'
 }  #endif
 /*********** Tricode ****************************/  
 void tricode(int *Tvar, int **nbcode, int imx)  /* $Id$ */
 {  /* $State$ */
   int Ndum[80],ij=1, k, j, i, Ntvar[20];  #include "version.h"
   int cptcode=0;  char version[]=__IMACH_VERSION__;
   for (k=0; k<79; k++) Ndum[k]=0;  char copyright[]="September 2022,INED-EUROREVES-Institut de longevite-Japan Society for the Promotion of Science (Grant-in-Aid for Scientific Research 25293121), Intel Software 2015-2020, Nihon University 2021-202, INED 2000-2022";
   for (k=1; k<=7; k++) ncodemax[k]=0;  char fullversion[]="$Revision$ $Date$"; 
   char strstart[80];
   for (j=1; j<=cptcovn; j++) {  char optionfilext[10], optionfilefiname[FILENAMELENGTH];
     for (i=1; i<=imx; i++) {  int erreur=0, nberr=0, nbwarn=0; /* Error number, number of errors number of warnings  */
       ij=(int)(covar[Tvar[j]][i]);  int nagesqr=0, nforce=0; /* nagesqr=1 if model is including age*age, number of forces */
       Ndum[ij]++;  /* Number of covariates model (1)=V2+V1+ V3*age+V2*V4 */
       if (ij > cptcode) cptcode=ij;  /* Model(2)  V1 + V2 + V3 + V8 + V7*V8 + V5*V6 + V8*age + V3*age + age*age */
     }  int cptcovn=0; /**< cptcovn decodemodel: number of covariates k of the models excluding age*products =6 and age*age but including products */
     /*printf("cptcode=%d cptcovn=%d ",cptcode,cptcovn);*/  int cptcovt=0; /**< cptcovt: total number of covariates of the model (2) nbocc(+)+1 = 8 excepting constant and age and age*age */
     for (i=0; i<=cptcode; i++) {  int cptcovs=0; /**< cptcovs number of SIMPLE covariates in the model V2+V1 =2 (dummy or quantit or time varying) */
       if(Ndum[i]!=0) ncodemax[j]++;  int cptcovsnq=0; /**< cptcovsnq number of SIMPLE covariates in the model but non quantitative V2+V1 =2 */
     }  int cptcovage=0; /**< Number of covariates with age: V3*age only =1 */
    int cptcovprodnoage=0; /**< Number of covariate products without age */   
     ij=1;  int cptcoveff=0; /* Total number of single dummy covariates (fixed or time varying) to vary for printing results (2**cptcoveff combinations of dummies)(computed in tricode as cptcov) */
     for (i=1; i<=ncodemax[j]; i++) {  int ncovf=0; /* Total number of effective fixed covariates (dummy or quantitative) in the model */
       for (k=0; k<=79; k++) {  int ncovv=0; /* Total number of effective (wave) varying covariates (dummy or quantitative) in the model */
         if (Ndum[k] != 0) {  int ncovvt=0; /* Total number of effective (wave) varying covariates (dummy or quantitative or products [without age]) in the model */
           nbcode[Tvar[j]][ij]=k;  int ncova=0; /* Total number of effective (wave and stepm) varying with age covariates (dummy of quantitative) in the model */
           ij++;  int nsd=0; /**< Total number of single dummy variables (output) */
         }  int nsq=0; /**< Total number of single quantitative variables (output) */
         if (ij > ncodemax[j]) break;  int ncoveff=0; /* Total number of effective fixed dummy covariates in the model */
       }    int nqfveff=0; /**< nqfveff Number of Quantitative Fixed Variables Effective */
     }  int ntveff=0; /**< ntveff number of effective time varying variables */
   }    int nqtveff=0; /**< ntqveff number of effective time varying quantitative variables */
    int cptcov=0; /* Working variable */
 }  int firstobs=1, lastobs=10; /* nobs = lastobs-firstobs+1 declared globally ;*/
   int nobs=10;  /* Number of observations in the data lastobs-firstobs */
 /*********** Health Expectancies ****************/  int ncovcombmax=NCOVMAX; /* Maximum calculated number of covariate combination = pow(2, cptcoveff) */
   int npar=NPARMAX; /* Number of parameters (nlstate+ndeath-1)*nlstate*ncovmodel; */
 void evsij(char fileres[], double ***eij, double x[], int nlstate, int stepm, int bage, int fage, double **oldm, double **savm, int ij)  int nlstate=2; /* Number of live states */
 {  int ndeath=1; /* Number of dead states */
   /* Health expectancies */  int ncovmodel=0, ncovcol=0;     /* Total number of covariables including constant a12*1 +b12*x ncovmodel=2 */
   int i, j, nhstepm, hstepm, h;  int nqv=0, ntv=0, nqtv=0;    /* Total number of quantitative variables, time variable (dummy), quantitative and time variable*/
   double age, agelim,hf;  int ncovcolt=0; /* ncovcolt=ncovcol+nqv+ntv+nqtv; total of covariates in the data, not in the model equation*/ 
   double ***p3mat;  int popbased=0;
    
   fprintf(ficreseij,"# Health expectancies\n");  int *wav; /* Number of waves for this individuual 0 is possible */
   fprintf(ficreseij,"# Age");  int maxwav=0; /* Maxim number of waves */
   for(i=1; i<=nlstate;i++)  int jmin=0, jmax=0; /* min, max spacing between 2 waves */
     for(j=1; j<=nlstate;j++)  int ijmin=0, ijmax=0; /* Individuals having jmin and jmax */ 
       fprintf(ficreseij," %1d-%1d",i,j);  int gipmx=0, gsw=0; /* Global variables on the number of contributions 
   fprintf(ficreseij,"\n");                     to the likelihood and the sum of weights (done by funcone)*/
   int mle=1, weightopt=0;
   hstepm=1*YEARM; /*  Every j years of age (in month) */  int **mw; /* mw[mi][i] is number of the mi wave for this individual */
   hstepm=hstepm/stepm; /* Typically in stepm units, if j= 2 years, = 2/6 months = 4 */  int **dh; /* dh[mi][i] is number of steps between mi,mi+1 for this individual */
   int **bh; /* bh[mi][i] is the bias (+ or -) for this individual if the delay between
   agelim=AGESUP;             * wave mi and wave mi+1 is not an exact multiple of stepm. */
   for (age=bage; age<=fage; age ++){ /* If stepm=6 months */  int countcallfunc=0;  /* Count the number of calls to func */
     /* nhstepm age range expressed in number of stepm */  int selected(int kvar); /* Is covariate kvar selected for printing results */
     nhstepm=(int) rint((agelim-age)*YEARM/stepm);  
     /* Typically if 20 years = 20*12/6=40 stepm */  double jmean=1; /* Mean space between 2 waves */
     if (stepm >= YEARM) hstepm=1;  double **matprod2(); /* test */
     nhstepm = nhstepm/hstepm;/* Expressed in hstepm, typically 40/4=10 */  double **oldm, **newm, **savm; /* Working pointers to matrices */
     p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);  double **oldms, **newms, **savms; /* Fixed working pointers to matrices */
     /* Computed by stepm unit matrices, product of hstepm matrices, stored  double   **ddnewms, **ddoldms, **ddsavms; /* for freeing later */
        in an array of nhstepm length: nhstepm=10, hstepm=4, stepm=6 months */  
     hpxij(p3mat,nhstepm,age,hstepm,x,nlstate,stepm,oldm, savm, ij);    /*FILE *fic ; */ /* Used in readdata only */
   FILE *ficpar, *ficparo,*ficres, *ficresp, *ficresphtm, *ficresphtmfr, *ficrespl, *ficresplb,*ficrespij, *ficrespijb, *ficrest,*ficresf, *ficresfb,*ficrespop;
   FILE *ficlog, *ficrespow;
     for(i=1; i<=nlstate;i++)  int globpr=0; /* Global variable for printing or not */
       for(j=1; j<=nlstate;j++)  double fretone; /* Only one call to likelihood */
         for (h=0, eij[i][j][(int)age]=0; h<=nhstepm; h++){  long ipmx=0; /* Number of contributions */
           eij[i][j][(int)age] +=p3mat[i][j][h];  double sw; /* Sum of weights */
         }  char filerespow[FILENAMELENGTH];
      char fileresilk[FILENAMELENGTH]; /* File of individual contributions to the likelihood */
     hf=1;  FILE *ficresilk;
     if (stepm >= YEARM) hf=stepm/YEARM;  FILE *ficgp,*ficresprob,*ficpop, *ficresprobcov, *ficresprobcor;
     fprintf(ficreseij,"%.0f",age );  FILE *ficresprobmorprev;
     for(i=1; i<=nlstate;i++)  FILE *fichtm, *fichtmcov; /* Html File */
       for(j=1; j<=nlstate;j++){  FILE *ficreseij;
         fprintf(ficreseij," %.4f", hf*eij[i][j][(int)age]);  char filerese[FILENAMELENGTH];
       }  FILE *ficresstdeij;
     fprintf(ficreseij,"\n");  char fileresstde[FILENAMELENGTH];
     free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);  FILE *ficrescveij;
   }  char filerescve[FILENAMELENGTH];
 }  FILE  *ficresvij;
   char fileresv[FILENAMELENGTH];
 /************ 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)  char title[MAXLINE];
 {  char model[MAXLINE]; /**< The model line */
   /* Variance of health expectancies */  char optionfile[FILENAMELENGTH], datafile[FILENAMELENGTH],  filerespl[FILENAMELENGTH],  fileresplb[FILENAMELENGTH];
   /*  double **prevalim(double **prlim, int nlstate, double *xp, double age, double **oldm, double ** savm,double ftolpl);*/  char plotcmd[FILENAMELENGTH], pplotcmd[FILENAMELENGTH];
   double **newm;  char tmpout[FILENAMELENGTH],  tmpout2[FILENAMELENGTH]; 
   double **dnewm,**doldm;  char command[FILENAMELENGTH];
   int i, j, nhstepm, hstepm, h;  int  outcmd=0;
   int k, cptcode;  
    double *xp;  char fileres[FILENAMELENGTH], filerespij[FILENAMELENGTH], filerespijb[FILENAMELENGTH], filereso[FILENAMELENGTH], rfileres[FILENAMELENGTH];
   double **gp, **gm;  char fileresu[FILENAMELENGTH]; /* fileres without r in front */
   double ***gradg, ***trgradg;  char filelog[FILENAMELENGTH]; /* Log file */
   double ***p3mat;  char filerest[FILENAMELENGTH];
   double age,agelim;  char fileregp[FILENAMELENGTH];
   int theta;  char popfile[FILENAMELENGTH];
   
    fprintf(ficresvij,"# Covariances of life expectancies\n");  char optionfilegnuplot[FILENAMELENGTH], optionfilehtm[FILENAMELENGTH], optionfilehtmcov[FILENAMELENGTH] ;
   fprintf(ficresvij,"# Age");  
   for(i=1; i<=nlstate;i++)  /* struct timeval start_time, end_time, curr_time, last_time, forecast_time; */
     for(j=1; j<=nlstate;j++)  /* struct timezone tzp; */
       fprintf(ficresvij," Cov(e%1d, e%1d)",i,j);  /* extern int gettimeofday(); */
   fprintf(ficresvij,"\n");  struct tm tml, *gmtime(), *localtime();
   
   xp=vector(1,npar);  extern time_t time();
   dnewm=matrix(1,nlstate,1,npar);  
   doldm=matrix(1,nlstate,1,nlstate);  struct tm start_time, end_time, curr_time, last_time, forecast_time;
    time_t  rstart_time, rend_time, rcurr_time, rlast_time, rforecast_time; /* raw time */
   hstepm=1*YEARM; /* Every year of age */  struct tm tm;
   hstepm=hstepm/stepm; /* Typically in stepm units, if j= 2 years, = 2/6 months = 4 */  
   agelim = AGESUP;  char strcurr[80], strfor[80];
   for (age=bage; age<=fage; age ++){ /* If stepm=6 months */  
     nhstepm=(int) rint((agelim-age)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */  char *endptr;
     if (stepm >= YEARM) hstepm=1;  long lval;
     nhstepm = nhstepm/hstepm; /* Typically 40/4=10 */  double dval;
     p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);  
     gradg=ma3x(0,nhstepm,1,npar,1,nlstate);  #define NR_END 1
     gp=matrix(0,nhstepm,1,nlstate);  #define FREE_ARG char*
     gm=matrix(0,nhstepm,1,nlstate);  #define FTOL 1.0e-10
   
     for(theta=1; theta <=npar; theta++){  #define NRANSI 
       for(i=1; i<=npar; i++){ /* Computes gradient */  #define ITMAX 200
         xp[i] = x[i] + (i==theta ?delti[theta]:0);  #define ITPOWMAX 20 /* This is now multiplied by the number of parameters */ 
       }  
       hpxij(p3mat,nhstepm,age,hstepm,xp,nlstate,stepm,oldm,savm, ij);    #define TOL 2.0e-4 
       prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ij);  
       for(j=1; j<= nlstate; j++){  #define CGOLD 0.3819660 
         for(h=0; h<=nhstepm; h++){  #define ZEPS 1.0e-10 
           for(i=1, gp[h][j]=0.;i<=nlstate;i++)  #define SHFT(a,b,c,d) (a)=(b);(b)=(c);(c)=(d); 
             gp[h][j] += prlim[i][i]*p3mat[i][j][h];  
         }  #define GOLD 1.618034 
       }  #define GLIMIT 100.0 
      #define TINY 1.0e-20 
       for(i=1; i<=npar; i++) /* Computes gradient */  
         xp[i] = x[i] - (i==theta ?delti[theta]:0);  static double maxarg1,maxarg2;
       hpxij(p3mat,nhstepm,age,hstepm,xp,nlstate,stepm,oldm,savm, ij);    #define FMAX(a,b) (maxarg1=(a),maxarg2=(b),(maxarg1)>(maxarg2)? (maxarg1):(maxarg2))
       prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ij);  #define FMIN(a,b) (maxarg1=(a),maxarg2=(b),(maxarg1)<(maxarg2)? (maxarg1):(maxarg2))
       for(j=1; j<= nlstate; j++){    
         for(h=0; h<=nhstepm; h++){  #define SIGN(a,b) ((b)>0.0 ? fabs(a) : -fabs(a))
           for(i=1, gm[h][j]=0.;i<=nlstate;i++)  #define rint(a) floor(a+0.5)
             gm[h][j] += prlim[i][i]*p3mat[i][j][h];  /* http://www.thphys.uni-heidelberg.de/~robbers/cmbeasy/doc/html/myutils_8h-source.html */
         }  #define mytinydouble 1.0e-16
       }  /* #define DEQUAL(a,b) (fabs((a)-(b))<mytinydouble) */
       for(j=1; j<= nlstate; j++)  /* http://www.thphys.uni-heidelberg.de/~robbers/cmbeasy/doc/html/mynrutils_8h-source.html */
         for(h=0; h<=nhstepm; h++){  /* static double dsqrarg; */
           gradg[h][theta][j]= (gp[h][j]-gm[h][j])/2./delti[theta];  /* #define DSQR(a) (DEQUAL((dsqrarg=(a)),0.0) ? 0.0 : dsqrarg*dsqrarg) */
         }  static double sqrarg;
     } /* End theta */  #define SQR(a) ((sqrarg=(a)) == 0.0 ? 0.0 :sqrarg*sqrarg)
   #define SWAP(a,b) {temp=(a);(a)=(b);(b)=temp;} 
     trgradg =ma3x(0,nhstepm,1,nlstate,1,npar);  int agegomp= AGEGOMP;
   
     for(h=0; h<=nhstepm; h++)  int imx; 
       for(j=1; j<=nlstate;j++)  int stepm=1;
         for(theta=1; theta <=npar; theta++)  /* Stepm, step in month: minimum step interpolation*/
           trgradg[h][j][theta]=gradg[h][theta][j];  
   int estepm;
     for(i=1;i<=nlstate;i++)  /* Estepm, step in month to interpolate survival function in order to approximate Life Expectancy*/
       for(j=1;j<=nlstate;j++)  
         vareij[i][j][(int)age] =0.;  int m,nb;
     for(h=0;h<=nhstepm;h++){  long *num;
       for(k=0;k<=nhstepm;k++){  int firstpass=0, lastpass=4,*cod, *cens;
         matprod2(dnewm,trgradg[h],1,nlstate,1,npar,1,npar,matcov);  int *ncodemax;  /* ncodemax[j]= Number of modalities of the j th
         matprod2(doldm,dnewm,1,nlstate,1,npar,1,nlstate,gradg[k]);                     covariate for which somebody answered excluding 
         for(i=1;i<=nlstate;i++)                     undefined. Usually 2: 0 and 1. */
           for(j=1;j<=nlstate;j++)  int *ncodemaxwundef;  /* ncodemax[j]= Number of modalities of the j th
             vareij[i][j][(int)age] += doldm[i][j];                               covariate for which somebody answered including 
       }                               undefined. Usually 3: -1, 0 and 1. */
     }  double **agev,*moisnais, *annais, *moisdc, *andc,**mint, **anint;
     h=1;  double **pmmij, ***probs; /* Global pointer */
     if (stepm >= YEARM) h=stepm/YEARM;  double ***mobaverage, ***mobaverages; /* New global variable */
     fprintf(ficresvij,"%.0f ",age );  double **precov; /* New global variable to store for each resultline, values of model covariates given by the resultlines (in order to speed up)  */
     for(i=1; i<=nlstate;i++)  double *ageexmed,*agecens;
       for(j=1; j<=nlstate;j++){  double dateintmean=0;
         fprintf(ficresvij," %.4f", h*vareij[i][j][(int)age]);    double anprojd, mprojd, jprojd; /* For eventual projections */
       }    double anprojf, mprojf, jprojf;
     fprintf(ficresvij,"\n");  
     free_matrix(gp,0,nhstepm,1,nlstate);    double anbackd, mbackd, jbackd; /* For eventual backprojections */
     free_matrix(gm,0,nhstepm,1,nlstate);    double anbackf, mbackf, jbackf;
     free_ma3x(gradg,0,nhstepm,1,npar,1,nlstate);    double jintmean,mintmean,aintmean;  
     free_ma3x(trgradg,0,nhstepm,1,nlstate,1,npar);  double *weight;
     free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);  int **s; /* Status */
   } /* End age */  double *agedc;
    double  **covar; /**< covar[j,i], value of jth covariate for individual i,
   free_vector(xp,1,npar);                    * covar=matrix(0,NCOVMAX,1,n); 
   free_matrix(doldm,1,nlstate,1,npar);                    * cov[Tage[kk]+2]=covar[Tvar[Tage[kk]]][i]*age; */
   free_matrix(dnewm,1,nlstate,1,nlstate);  double **coqvar; /* Fixed quantitative covariate nqv */
   double ***cotvar; /* Time varying covariate ntv */
 }  double ***cotqvar; /* Time varying quantitative covariate itqv */
   double  idx; 
 /************ Variance of prevlim ******************/  int **nbcode, *Tvar; /**< model=V2 => Tvar[1]= 2 */
 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)  /* Some documentation */
 {        /*   Design original data
   /* Variance of prevalence limit */         *  V1   V2   V3   V4  V5  V6  V7  V8  Weight ddb ddth d1st s1 V9 V10 V11 V12 s2 V9 V10 V11 V12 
   /*  double **prevalim(double **prlim, int nlstate, double *xp, double age, double **oldm, double ** savm,double ftolpl);*/         *  <          ncovcol=6   >   nqv=2 (V7 V8)                   dv dv  dv  qtv    dv dv  dvv qtv
   double **newm;         *                                                             ntv=3     nqtv=1
   double **dnewm,**doldm;         *  cptcovn number of covariates (not including constant and age or age*age) = number of plus sign + 1 = 10+1=11
   int i, j, nhstepm, hstepm;         * For time varying covariate, quanti or dummies
   int k, cptcode;         *       cotqvar[wav][iv(1 to nqtv)][i]= [1][12][i]=(V12) quanti
   double *xp;         *       cotvar[wav][ntv+iv][i]= [3+(1 to nqtv)][i]=(V12) quanti
   double *gp, *gm;         *       cotvar[wav][iv(1 to ntv)][i]= [1][1][i]=(V9) dummies at wav 1
   double **gradg, **trgradg;         *       cotvar[wav][iv(1 to ntv)][i]= [1][2][i]=(V10) dummies at wav 1
   double age,agelim;         *       covar[Vk,i], value of the Vkth fixed covariate dummy or quanti for individual i:
   int theta;         *       covar[1][i]= (V1), covar[4][i]=(V4), covar[8][i]=(V8)
             * Model V2 + V1 + V3*age + V3 + V5*V6 + V7*V8 + V8*age + V8 + V9 + V9*age + V10
   fprintf(ficresvpl,"# Standard deviation of prevalences limit\n");         *   k=  1    2      3       4     5       6      7        8   9     10       11 
   fprintf(ficresvpl,"# Age");         */
   for(i=1; i<=nlstate;i++)  /* According to the model, more columns can be added to covar by the product of covariates */
       fprintf(ficresvpl," %1d-%1d",i,i);  /* ncovcol=1(Males=0 Females=1) nqv=1(raedyrs) ntv=2(withoutiadl=0 withiadl=1, witoutadl=0 withoutadl=1) nqtv=1(bmi) nlstate=3 ndeath=1
   fprintf(ficresvpl,"\n");    # States 1=Coresidence, 2 Living alone, 3 Institution
     # V1=sex, V2=raedyrs Quant Fixed, State=livarnb4..livarnb11, V3=iadl4..iald11, V4=adlw4..adlw11, V5=r4bmi..r11bmi
   xp=vector(1,npar);  */
   dnewm=matrix(1,nlstate,1,npar);  /*             V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
   doldm=matrix(1,nlstate,1,nlstate);  /*    k        1  2   3   4     5    6    7     8    9 */
    /*Typevar[k]=  0  0   0   2     1    0    2     1    0 *//*0 for simple covariate (dummy, quantitative,*/
   hstepm=1*YEARM; /* Every year of age */                                                           /* fixed or varying), 1 for age product, 2 for*/
   hstepm=hstepm/stepm; /* Typically in stepm units, if j= 2 years, = 2/6 months = 4 */                                                           /* product */
   agelim = AGESUP;  /*Dummy[k]=    1  0   0   1     3    1    1     2    0 *//*Dummy[k] 0=dummy (0 1), 1 quantitative */
   for (age=bage; age<=fage; age ++){ /* If stepm=6 months */                                                           /*(single or product without age), 2 dummy*/
     nhstepm=(int) rint((agelim-age)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */                                                           /* with age product, 3 quant with age product*/
     if (stepm >= YEARM) hstepm=1;  /*Tvar[k]=     5  4   3   6     5    2    7     1    1 */
     nhstepm = nhstepm/hstepm; /* Typically 40/4=10 */  /*    nsd         1   2                              3 */ /* Counting single dummies covar fixed or tv */
     gradg=matrix(1,npar,1,nlstate);  /*TnsdVar[Tvar]   1   2                              3 */ 
     gp=vector(1,nlstate);  /*Tvaraff[nsd]     4   3                              1 */ /* ID of single dummy cova fixed or timevary*/
     gm=vector(1,nlstate);  /*TvarsD[nsd]     4   3                              1 */ /* ID of single dummy cova fixed or timevary*/
   /*TvarsDind[nsd]  2   3                              9 */ /* position K of single dummy cova */
     for(theta=1; theta <=npar; theta++){  /*    nsq      1                     2                 */ /* Counting single quantit tv */
       for(i=1; i<=npar; i++){ /* Computes gradient */  /* TvarsQ[k]   5                     2                 */ /* Number of single quantitative cova */
         xp[i] = x[i] + (i==theta ?delti[theta]:0);  /* TvarsQind   1                     6                 */ /* position K of single quantitative cova */
       }  /* Tprod[i]=k             1               2            */ /* Position in model of the ith prod without age */
       prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ij);  /* cptcovage                    1               2      */ /* Counting cov*age in the model equation */
       for(i=1;i<=nlstate;i++)  /* Tage[cptcovage]=k            5               8      */ /* Position in the model of ith cov*age */
         gp[i] = prlim[i][i];  /* Tvard[1][1]@4={4,3,1,2}    V4*V3 V1*V2              */ /* Position in model of the ith prod without age */
      /* Tvardk[4][1]=4;Tvardk[4][2]=3;Tvardk[7][1]=1;Tvardk[7][2]=2 */ /* Variables of a prod at position in the model equation*/
       for(i=1; i<=npar; i++) /* Computes gradient */  /* TvarF TvarF[1]=Tvar[6]=2,  TvarF[2]=Tvar[7]=7, TvarF[3]=Tvar[9]=1  ID of fixed covariates or product V2, V1*V2, V1 */
         xp[i] = x[i] - (i==theta ?delti[theta]:0);  /* TvarFind;  TvarFind[1]=6,  TvarFind[2]=7, TvarFind[3]=9 *//* Inverse V2(6) is first fixed (single or prod)  */
       prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ij);  /* Type                    */
       for(i=1;i<=nlstate;i++)  /* V         1  2  3  4  5 */
         gm[i] = prlim[i][i];  /*           F  F  V  V  V */
   /*           D  Q  D  D  Q */
       for(i=1;i<=nlstate;i++)  /*                         */
         gradg[theta][i]= (gp[i]-gm[i])/2./delti[theta];  int *TvarsD;
     } /* End theta */  int *TnsdVar;
   int *TvarsDind;
     trgradg =matrix(1,nlstate,1,npar);  int *TvarsQ;
   int *TvarsQind;
     for(j=1; j<=nlstate;j++)  
       for(theta=1; theta <=npar; theta++)  #define MAXRESULTLINESPONE 10+1
         trgradg[j][theta]=gradg[theta][j];  int nresult=0;
   int parameterline=0; /* # of the parameter (type) line */
     for(i=1;i<=nlstate;i++)  int TKresult[MAXRESULTLINESPONE]; /* TKresult[nres]=k for each resultline nres give the corresponding combination of dummies */
       varpl[i][(int)age] =0.;  int resultmodel[MAXRESULTLINESPONE][NCOVMAX];/* resultmodel[k1]=k3: k1th position in the model corresponds to the k3 position in the resultline */
     matprod2(dnewm,trgradg,1,nlstate,1,npar,1,npar,matcov);  int modelresult[MAXRESULTLINESPONE][NCOVMAX];/* modelresult[k3]=k1: k1th position in the model corresponds to the k3 position in the resultline */
     matprod2(doldm,dnewm,1,nlstate,1,npar,1,nlstate,gradg);  int Tresult[MAXRESULTLINESPONE][NCOVMAX];/* Tresult[nres][result_position]= value of the dummy variable at the result_position in the nres resultline */
     for(i=1;i<=nlstate;i++)  int Tinvresult[MAXRESULTLINESPONE][NCOVMAX];/* Tinvresult[nres][Name of a dummy variable]= value of the variable in the result line  */
       varpl[i][(int)age] = doldm[i][i]; /* Covariances are useless */  double TinvDoQresult[MAXRESULTLINESPONE][NCOVMAX];/* TinvDoQresult[nres][Name of a Dummy or Q variable]= value of the variable in the result line */
   int Tvresult[MAXRESULTLINESPONE][NCOVMAX]; /* Tvresult[nres][result_position]= name of the dummy variable at the result_position in the nres resultline */
     fprintf(ficresvpl,"%.0f ",age );  double Tqresult[MAXRESULTLINESPONE][NCOVMAX]; /* Tqresult[nres][result_position]= value of the variable at the result_position in the nres resultline */
     for(i=1; i<=nlstate;i++)  double Tqinvresult[MAXRESULTLINESPONE][NCOVMAX]; /* For quantitative variable , value (output) */
       fprintf(ficresvpl," %.5f (%.5f)",prlim[i][i],sqrt(varpl[i][(int)age]));  int Tvqresult[MAXRESULTLINESPONE][NCOVMAX]; /* Tvqresult[nres][result_position]= id of the variable at the result_position in the nres resultline */
     fprintf(ficresvpl,"\n");  
     free_vector(gp,1,nlstate);  /* ncovcol=1(Males=0 Females=1) nqv=1(raedyrs) ntv=2(withoutiadl=0 withiadl=1, witoutadl=0 withoutadl=1) nqtv=1(bmi) nlstate=3 ndeath=1
     free_vector(gm,1,nlstate);    # States 1=Coresidence, 2 Living alone, 3 Institution
     free_matrix(gradg,1,npar,1,nlstate);    # V1=sex, V2=raedyrs Quant Fixed, State=livarnb4..livarnb11, V3=iadl4..iald11, V4=adlw4..adlw11, V5=r4bmi..r11bmi
     free_matrix(trgradg,1,nlstate,1,npar);  */
   } /* End age */  /* int *TDvar; /\**< TDvar[1]=4,  TDvarF[2]=3, TDvar[3]=6  in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 *\/ */
   int *TvarF; /**< TvarF[1]=Tvar[6]=2,  TvarF[2]=Tvar[7]=7, TvarF[3]=Tvar[9]=1  in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
   free_vector(xp,1,npar);  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 */
   free_matrix(doldm,1,nlstate,1,npar);  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 */
   free_matrix(dnewm,1,nlstate,1,nlstate);  int *TvarVind; /**< TvarVind[1]=1, TvarVind[2]=2  in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
   int *TvarA; /**< TvarA[1]=Tvar[5]=5, TvarA[2]=Tvar[8]=1  in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
 }  int *TvarAind; /**< TvarindA[1]=5, TvarAind[2]=8  in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
   int *TvarFD; /**< TvarFD[1]=V1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
   int *TvarFDind; /* TvarFDind[1]=9 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
   int *TvarFQ; /* TvarFQ[1]=V2 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
 /***********************************************/  int *TvarFQind; /* TvarFQind[1]=6 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
 /**************** Main Program *****************/  int *TvarVD; /* TvarVD[1]=V5 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
 /***********************************************/  int *TvarVDind; /* TvarVDind[1]=1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
   int *TvarVQ; /* TvarVQ[1]=V5 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple time varying quantitative variable */
 /*int main(int argc, char *argv[])*/  int *TvarVQind; /* TvarVQind[1]=1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple time varying quantitative variable */
 int main()  int *TvarVV; /* We count ncovvt time varying covariates (single or products without age) and put their name into TvarVV */
 {  int *TvarVVind; /* We count ncovvt time varying covariates (single or products without age) and put their name into TvarVV */
         /*#  ID           V1     V2          weight               birth   death   1st    s1      V3      V4      V5       2nd  s2 */
   int i,j, k, n=MAXN,iter,m,size,cptcode, aaa, cptcod;        /* model V1+V3+age*V1+age*V3+V1*V3 */
   double agedeb, agefin,hf;        /*  Tvar={1, 3, 1, 3, 6}, the 6 comes from the fact that there are already V1, V2, V3, V4, V5 native covariates */
   double agemin=1.e20, agemax=-1.e20;        /* TvarVV={3,1,3}, for V3 and then the product V1*V3 is decomposed into V1 and V3 */             
         /* TvarVVind={2,5,5}, for V3 and then the product V1*V3 is decomposed into V1 and V3 */          
   double fret;  int *Tvarsel; /**< Selected covariates for output */
   double **xi,tmp,delta;  double *Tvalsel; /**< Selected modality value of covariate for output */
   int *Typevar; /**< 0 for simple covariate (dummy, quantitative, fixed or varying), 1 for age product, 2 for  product */
   double dum; /* Dummy variable */  int *Fixed; /** Fixed[k] 0=fixed, 1 varying, 2 fixed with age product, 3 varying with age product */ 
   double ***p3mat;  int *Dummy; /** Dummy[k] 0=dummy (0 1), 1 quantitative (single or product without age), 2 dummy with age product, 3 quant with age product */ 
   int *indx;  int *DummyV; /** Dummy[v] 0=dummy (0 1), 1 quantitative */
   char line[MAXLINE], linepar[MAXLINE];  int *FixedV; /** FixedV[v] 0 fixed, 1 varying */
   char title[MAXLINE];  int *Tage;
   char optionfile[FILENAMELENGTH], datafile[FILENAMELENGTH],  filerespl[FILENAMELENGTH];  int anyvaryingduminmodel=0; /**< Any varying dummy in Model=1 yes, 0 no, to avoid a loop on waves in freq */ 
   char fileres[FILENAMELENGTH], filerespij[FILENAMELENGTH], filereso[FILENAMELENGTH];  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*/
   char filerest[FILENAMELENGTH];  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*/ 
   char fileregp[FILENAMELENGTH];  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  */
   char path[80],pathc[80],pathcd[80],pathtot[80],model[20];  int *Ndum; /** Freq of modality (tricode */
   int firstobs=1, lastobs=10;  /* int **codtab;*/ /**< codtab=imatrix(1,100,1,10); */
   int sdeb, sfin; /* Status at beginning and end */  int **Tvard;
   int c,  h , cpt,l;  int **Tvardk;
   int ju,jl, mi;  int *Tprod;/**< Gives the k position of the k1 product */
   int i1,j1, k1,k2,k3,jk,aa,bb, stepsize;  /* Tprod[k1=1]=3(=V1*V4) for V2+V1+V1*V4+age*V3  */
   int jnais,jdc,jint4,jint1,jint2,jint3,**outcome,**adl,*tab;  int *Tposprod; /**< Gives the k1 product from the k position */
       /* if  V2+V1+V1*V4+age*V3+V3*V2   TProd[k1=2]=5 (V3*V2) */
   int hstepm, nhstepm;     /* Tposprod[k]=k1 , Tposprod[3]=1, Tposprod[5(V3*V2)]=2 (2nd product without age) */
   double bage, fage, age, agelim, agebase;  int cptcovprod, *Tvaraff, *invalidvarcomb;
   double ftolpl=FTOL;  double *lsurv, *lpop, *tpop;
   double **prlim;  
   double *severity;  #define FD 1; /* Fixed dummy covariate */
   double ***param; /* Matrix of parameters */  #define FQ 2; /* Fixed quantitative covariate */
   double  *p;  #define FP 3; /* Fixed product covariate */
   double **matcov; /* Matrix of covariance */  #define FPDD 7; /* Fixed product dummy*dummy covariate */
   double ***delti3; /* Scale */  #define FPDQ 8; /* Fixed product dummy*quantitative covariate */
   double *delti; /* Scale */  #define FPQQ 9; /* Fixed product quantitative*quantitative covariate */
   double ***eij, ***vareij;  #define VD 10; /* Varying dummy covariate */
   double **varpl; /* Variances of prevalence limits by age */  #define VQ 11; /* Varying quantitative covariate */
   double *epj, vepp;  #define VP 12; /* Varying product covariate */
   char version[80]="Imach version 62c, May 1999, INED-EUROREVES ";  #define VPDD 13; /* Varying product dummy*dummy covariate */
   char *alph[]={"a","a","b","c","d","e"}, str[4];  #define VPDQ 14; /* Varying product dummy*quantitative covariate */
   #define VPQQ 15; /* Varying product quantitative*quantitative covariate */
   char z[1]="c", occ;  #define APFD 16; /* Age product * fixed dummy covariate */
 #include <sys/time.h>  #define APFQ 17; /* Age product * fixed quantitative covariate */
 #include <time.h>  #define APVD 18; /* Age product * varying dummy covariate */
   char stra[80], strb[80], strc[80], strd[80],stre[80],modelsav[80];  #define APVQ 19; /* Age product * varying quantitative covariate */
   /* long total_usecs;  
   struct timeval start_time, end_time;  #define FTYPE 1; /* Fixed covariate */
    #define VTYPE 2; /* Varying covariate (loop in wave) */
   gettimeofday(&start_time, (struct timezone*)0); */ /* at first time */  #define ATYPE 2; /* Age product covariate (loop in dh within wave)*/
   
   struct kmodel{
   printf("\nIMACH, Version 0.64a");          int maintype; /* main type */
   printf("\nEnter the parameter file name: ");          int subtype; /* subtype */
   };
 #ifdef windows  struct kmodel modell[NCOVMAX];
   scanf("%s",pathtot);  
   getcwd(pathcd, size);  double ftol=FTOL; /**< Tolerance for computing Max Likelihood */
   /*cygwin_split_path(pathtot,path,optionfile);  double ftolhess; /**< Tolerance for computing hessian */
     printf("pathtot=%s, path=%s, optionfile=%s\n",pathtot,path,optionfile);*/  
   /* cutv(path,optionfile,pathtot,'\\');*/  /**************** split *************************/
   static  int split( char *path, char *dirc, char *name, char *ext, char *finame )
 split(pathtot, path,optionfile);  {
   chdir(path);    /* From a file name with (full) path (either Unix or Windows) we extract the directory (dirc)
   replace(pathc,path);       the name of the file (name), its extension only (ext) and its first part of the name (finame)
 #endif    */ 
 #ifdef unix    char  *ss;                            /* pointer */
   scanf("%s",optionfile);    int   l1=0, l2=0;                             /* length counters */
 #endif  
     l1 = strlen(path );                   /* length of path */
 /*-------- arguments in the command line --------*/    if ( l1 == 0 ) return( GLOCK_ERROR_NOPATH );
     ss= strrchr( path, DIRSEPARATOR );            /* find last / */
   strcpy(fileres,"r");    if ( ss == NULL ) {                   /* no directory, so determine current directory */
   strcat(fileres, optionfile);      strcpy( name, path );               /* we got the fullname name because no directory */
       /*if(strrchr(path, ODIRSEPARATOR )==NULL)
   /*---------arguments file --------*/        printf("Warning you should use %s as a separator\n",DIRSEPARATOR);*/
       /* get current working directory */
   if((ficpar=fopen(optionfile,"r"))==NULL)    {      /*    extern  char* getcwd ( char *buf , int len);*/
     printf("Problem with optionfile %s\n",optionfile);  #ifdef WIN32
     goto end;      if (_getcwd( dirc, FILENAME_MAX ) == NULL ) {
   }  #else
           if (getcwd(dirc, FILENAME_MAX) == NULL) {
   strcpy(filereso,"o");  #endif
   strcat(filereso,fileres);        return( GLOCK_ERROR_GETCWD );
   if((ficparo=fopen(filereso,"w"))==NULL) {      }
     printf("Problem with Output resultfile: %s\n", filereso);goto end;      /* got dirc from getcwd*/
   }      printf(" DIRC = %s \n",dirc);
     } else {                              /* strip directory from path */
   /* Reads comments: lines beginning with '#' */      ss++;                               /* after this, the filename */
   while((c=getc(ficpar))=='#' && c!= EOF){      l2 = strlen( ss );                  /* length of filename */
     ungetc(c,ficpar);      if ( l2 == 0 ) return( GLOCK_ERROR_NOPATH );
     fgets(line, MAXLINE, ficpar);      strcpy( name, ss );         /* save file name */
     puts(line);      strncpy( dirc, path, l1 - l2 );     /* now the directory */
     fputs(line,ficparo);      dirc[l1-l2] = '\0';                 /* add zero */
   }      printf(" DIRC2 = %s \n",dirc);
   ungetc(c,ficpar);    }
     /* We add a separator at the end of dirc if not exists */
   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);    l1 = strlen( dirc );                  /* length of directory */
   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);    if( dirc[l1-1] != DIRSEPARATOR ){
   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);      dirc[l1] =  DIRSEPARATOR;
       dirc[l1+1] = 0; 
   covar=matrix(0,NCOVMAX,1,n);          printf(" DIRC3 = %s \n",dirc);
   if (strlen(model)<=1) cptcovn=0;    }
   else {    ss = strrchr( name, '.' );            /* find last / */
     j=0;    if (ss >0){
     j=nbocc(model,'+');      ss++;
     cptcovn=j+1;      strcpy(ext,ss);                     /* save extension */
   }      l1= strlen( name);
       l2= strlen(ss)+1;
   ncovmodel=2+cptcovn;      strncpy( finame, name, l1-l2);
   nvar=ncovmodel-1; /* Suppressing age as a basic covariate */      finame[l1-l2]= 0;
      }
   /* Read guess parameters */  
   /* Reads comments: lines beginning with '#' */    return( 0 );                          /* we're done */
   while((c=getc(ficpar))=='#' && c!= EOF){  }
     ungetc(c,ficpar);  
     fgets(line, MAXLINE, ficpar);  
     puts(line);  /******************************************/
     fputs(line,ficparo);  
   }  void replace_back_to_slash(char *s, char*t)
   ungetc(c,ficpar);  {
      int i;
   param= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);    int lg=0;
     for(i=1; i <=nlstate; i++)    i=0;
     for(j=1; j <=nlstate+ndeath-1; j++){    lg=strlen(t);
       fscanf(ficpar,"%1d%1d",&i1,&j1);    for(i=0; i<= lg; i++) {
       fprintf(ficparo,"%1d%1d",i1,j1);      (s[i] = t[i]);
       printf("%1d%1d",i,j);      if (t[i]== '\\') s[i]='/';
       for(k=1; k<=ncovmodel;k++){    }
         fscanf(ficpar," %lf",&param[i][j][k]);  }
         printf(" %lf",param[i][j][k]);  
         fprintf(ficparo," %lf",param[i][j][k]);  char *trimbb(char *out, char *in)
       }  { /* Trim multiple blanks in line but keeps first blanks if line starts with blanks */
       fscanf(ficpar,"\n");    char *s;
       printf("\n");    s=out;
       fprintf(ficparo,"\n");    while (*in != '\0'){
     }      while( *in == ' ' && *(in+1) == ' '){ /* && *(in+1) != '\0'){*/
          in++;
   npar= (nlstate+ndeath-1)*nlstate*ncovmodel;      }
   p=param[1][1];      *out++ = *in++;
      }
   /* Reads comments: lines beginning with '#' */    *out='\0';
   while((c=getc(ficpar))=='#' && c!= EOF){    return s;
     ungetc(c,ficpar);  }
     fgets(line, MAXLINE, ficpar);  
     puts(line);  /* char *substrchaine(char *out, char *in, char *chain) */
     fputs(line,ficparo);  /* { */
   }  /*   /\* Substract chain 'chain' from 'in', return and output 'out' *\/ */
   ungetc(c,ficpar);  /*   char *s, *t; */
   /*   t=in;s=out; */
   delti3= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);  /*   while ((*in != *chain) && (*in != '\0')){ */
   delti=vector(1,npar); /* Scale of each paramater (output from hesscov) */  /*     *out++ = *in++; */
   for(i=1; i <=nlstate; i++){  /*   } */
     for(j=1; j <=nlstate+ndeath-1; j++){  
       fscanf(ficpar,"%1d%1d",&i1,&j1);  /*   /\* *in matches *chain *\/ */
       printf("%1d%1d",i,j);  /*   while ((*in++ == *chain++) && (*in != '\0')){ */
       fprintf(ficparo,"%1d%1d",i1,j1);  /*     printf("*in = %c, *out= %c *chain= %c \n", *in, *out, *chain);  */
       for(k=1; k<=ncovmodel;k++){  /*   } */
         fscanf(ficpar,"%le",&delti3[i][j][k]);  /*   in--; chain--; */
         printf(" %le",delti3[i][j][k]);  /*   while ( (*in != '\0')){ */
         fprintf(ficparo," %le",delti3[i][j][k]);  /*     printf("Bef *in = %c, *out= %c *chain= %c \n", *in, *out, *chain);  */
       }  /*     *out++ = *in++; */
       fscanf(ficpar,"\n");  /*     printf("Aft *in = %c, *out= %c *chain= %c \n", *in, *out, *chain);  */
       printf("\n");  /*   } */
       fprintf(ficparo,"\n");  /*   *out='\0'; */
     }  /*   out=s; */
   }  /*   return out; */
   delti=delti3[1][1];  /* } */
    char *substrchaine(char *out, char *in, char *chain)
   /* Reads comments: lines beginning with '#' */  {
   while((c=getc(ficpar))=='#' && c!= EOF){    /* Substract chain 'chain' from 'in', return and output 'out' */
     ungetc(c,ficpar);    /* in="V1+V1*age+age*age+V2", chain="age*age" */
     fgets(line, MAXLINE, ficpar);  
     puts(line);    char *strloc;
     fputs(line,ficparo);  
   }    strcpy (out, in); 
   ungetc(c,ficpar);    strloc = strstr(out, chain); /* strloc points to out at age*age+V2 */
      printf("Bef strloc=%s chain=%s out=%s \n", strloc, chain, out);
   matcov=matrix(1,npar,1,npar);    if(strloc != NULL){ 
   for(i=1; i <=npar; i++){      /* will affect out */ /* strloc+strlenc(chain)=+V2 */ /* Will also work in Unicode */
     fscanf(ficpar,"%s",&str);      memmove(strloc,strloc+strlen(chain), strlen(strloc+strlen(chain))+1);
     printf("%s",str);      /* strcpy (strloc, strloc +strlen(chain));*/
     fprintf(ficparo,"%s",str);    }
     for(j=1; j <=i; j++){    printf("Aft strloc=%s chain=%s in=%s out=%s \n", strloc, chain, in, out);
       fscanf(ficpar," %le",&matcov[i][j]);    return out;
       printf(" %.5le",matcov[i][j]);  }
       fprintf(ficparo," %.5le",matcov[i][j]);  
     }  
     fscanf(ficpar,"\n");  char *cutl(char *blocc, char *alocc, char *in, char occ)
     printf("\n");  {
     fprintf(ficparo,"\n");    /* cuts string in into blocc and alocc where blocc ends before FIRST occurence of char 'occ' 
   }       and alocc starts after first occurence of char 'occ' : ex cutv(blocc,alocc,"abcdef2ghi2j",'2')
   for(i=1; i <=npar; i++)       gives alocc="abcdef" and blocc="ghi2j".
     for(j=i+1;j<=npar;j++)       If occ is not found blocc is null and alocc is equal to in. Returns blocc
       matcov[i][j]=matcov[j][i];    */
        char *s, *t;
   printf("\n");    t=in;s=in;
     while ((*in != occ) && (*in != '\0')){
       *alocc++ = *in++;
     /*-------- data file ----------*/    }
     if((ficres =fopen(fileres,"w"))==NULL) {    if( *in == occ){
       printf("Problem with resultfile: %s\n", fileres);goto end;      *(alocc)='\0';
     }      s=++in;
     fprintf(ficres,"#%s\n",version);    }
       
     if((fic=fopen(datafile,"r"))==NULL)    {    if (s == t) {/* occ not found */
       printf("Problem with datafile: %s\n", datafile);goto end;      *(alocc-(in-s))='\0';
     }      in=s;
     }
     n= lastobs;    while ( *in != '\0'){
     severity = vector(1,maxwav);      *blocc++ = *in++;
     outcome=imatrix(1,maxwav+1,1,n);    }
     num=ivector(1,n);  
     moisnais=vector(1,n);    *blocc='\0';
     annais=vector(1,n);    return t;
     moisdc=vector(1,n);  }
     andc=vector(1,n);  char *cutv(char *blocc, char *alocc, char *in, char occ)
     agedc=vector(1,n);  {
     cod=ivector(1,n);    /* cuts string in into blocc and alocc where blocc ends before LAST occurence of char 'occ' 
     weight=vector(1,n);       and alocc starts after last occurence of char 'occ' : ex cutv(blocc,alocc,"abcdef2ghi2j",'2')
     for(i=1;i<=n;i++) weight[i]=1.0; /* Equal weights, 1 by default */       gives blocc="abcdef2ghi" and alocc="j".
     mint=matrix(1,maxwav,1,n);       If occ is not found blocc is null and alocc is equal to in. Returns alocc
     anint=matrix(1,maxwav,1,n);    */
     s=imatrix(1,maxwav+1,1,n);    char *s, *t;
     adl=imatrix(1,maxwav+1,1,n);        t=in;s=in;
     tab=ivector(1,NCOVMAX);    while (*in != '\0'){
     ncodemax=ivector(1,8);      while( *in == occ){
         *blocc++ = *in++;
     i=1;        s=in;
     while (fgets(line, MAXLINE, fic) != NULL)    {      }
       if ((i >= firstobs) && (i <=lastobs)) {      *blocc++ = *in++;
            }
         for (j=maxwav;j>=1;j--){    if (s == t) /* occ not found */
           cutv(stra, strb,line,' '); s[j][i]=atoi(strb);      *(blocc-(in-s))='\0';
           strcpy(line,stra);    else
           cutv(stra, strb,line,'/'); anint[j][i]=(double)(atoi(strb)); strcpy(line,stra);      *(blocc-(in-s)-1)='\0';
           cutv(stra, strb,line,' '); mint[j][i]=(double)(atoi(strb)); strcpy(line,stra);    in=s;
         }    while ( *in != '\0'){
              *alocc++ = *in++;
         cutv(stra, strb,line,'/'); andc[i]=(double)(atoi(strb)); strcpy(line,stra);    }
         cutv(stra, strb,line,' '); moisdc[i]=(double)(atoi(strb)); strcpy(line,stra);  
     *alocc='\0';
         cutv(stra, strb,line,'/'); annais[i]=(double)(atoi(strb)); strcpy(line,stra);    return s;
         cutv(stra, strb,line,' '); moisnais[i]=(double)(atoi(strb)); strcpy(line,stra);  }
   
         cutv(stra, strb,line,' '); weight[i]=(double)(atoi(strb)); strcpy(line,stra);  int nbocc(char *s, char occ)
         for (j=ncov;j>=1;j--){  {
           cutv(stra, strb,line,' '); covar[j][i]=(double)(atoi(strb)); strcpy(line,stra);    int i,j=0;
         }    int lg=20;
         num[i]=atol(stra);    i=0;
     lg=strlen(s);
         /*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]));*/    for(i=0; i<= lg; i++) {
       if  (s[i] == occ ) j++;
         i=i+1;    }
       }    return j;
     }  }
   
     /*scanf("%d",i);*/  /* void cutv(char *u,char *v, char*t, char occ) */
   imx=i-1; /* Number of individuals */  /* { */
   /*   /\* cuts string t into u and v where u ends before last occurence of char 'occ'  */
   /* Calculation of the number of parameter from char model*/  /*      and v starts after last occurence of char 'occ' : ex cutv(u,v,"abcdef2ghi2j",'2') */
   Tvar=ivector(1,15);      /*      gives u="abcdef2ghi" and v="j" *\/ */
   Tage=ivector(1,15);        /*   int i,lg,j,p=0; */
      /*   i=0; */
   if (strlen(model) >1){  /*   lg=strlen(t); */
     j=0, j1=0;  /*   for(j=0; j<=lg-1; j++) { */
     j=nbocc(model,'+');  /*     if((t[j]!= occ) && (t[j+1]== occ)) p=j+1; */
     j1=nbocc(model,'*');  /*   } */
     cptcovn=j+1;  
      /*   for(j=0; j<p; j++) { */
     strcpy(modelsav,model);  /*     (u[j] = t[j]); */
     if (j==0) {  /*   } */
       if (j1==0){  /*      u[p]='\0'; */
        cutv(stra,strb,modelsav,'V');  
        Tvar[1]=atoi(strb);  /*    for(j=0; j<= lg; j++) { */
       }  /*     if (j>=(p+1))(v[j-p-1] = t[j]); */
       else if (j1==1) {  /*   } */
        cutv(stra,strb,modelsav,'*');  /* } */
        /*      printf("stra=%s strb=%s modelsav=%s ",stra,strb,modelsav);*/  
        Tage[1]=1; cptcovage++;  #ifdef _WIN32
        if (strcmp(stra,"age")==0) {  char * strsep(char **pp, const char *delim)
          cutv(strd,strc,strb,'V');  {
          Tvar[1]=atoi(strc);    char *p, *q;
        }           
        else if (strcmp(strb,"age")==0) {    if ((p = *pp) == NULL)
          cutv(strd,strc,stra,'V');      return 0;
          Tvar[1]=atoi(strc);    if ((q = strpbrk (p, delim)) != NULL)
        }    {
        else {printf("Error"); exit(0);}      *pp = q + 1;
       }      *q = '\0';
     }    }
     else {    else
       for(i=j; i>=1;i--){      *pp = 0;
         cutv(stra,strb,modelsav,'+');    return p;
         /*printf("%s %s %s\n", stra,strb,modelsav);*/  }
         if (strchr(strb,'*')) {  #endif
           cutv(strd,strc,strb,'*');  
           if (strcmp(strc,"age")==0) {  /********************** nrerror ********************/
             cutv(strb,stre,strd,'V');  
             Tvar[i+1]=atoi(stre);  void nrerror(char error_text[])
             cptcovage++;  {
             Tage[cptcovage]=i+1;    fprintf(stderr,"ERREUR ...\n");
             printf("stre=%s ", stre);    fprintf(stderr,"%s\n",error_text);
           }    exit(EXIT_FAILURE);
           else if (strcmp(strd,"age")==0) {  }
             cutv(strb,stre,strc,'V');  /*********************** vector *******************/
             Tvar[i+1]=atoi(stre);  double *vector(int nl, int nh)
             cptcovage++;  {
             Tage[cptcovage]=i+1;    double *v;
           }    v=(double *) malloc((size_t)((nh-nl+1+NR_END)*sizeof(double)));
           else {    if (!v) nrerror("allocation failure in vector");
             cutv(strb,stre,strc,'V');    return v-nl+NR_END;
             Tvar[i+1]=ncov+1;  }
             cutv(strb,strc,strd,'V');  
             for (k=1; k<=lastobs;k++)  /************************ free vector ******************/
               covar[ncov+1][k]=covar[atoi(stre)][k]*covar[atoi(strc)][k];  void free_vector(double*v, int nl, int nh)
           }  {
         }    free((FREE_ARG)(v+nl-NR_END));
         else {  }
           cutv(strd,strc,strb,'V');  
           /* printf("%s %s %s", strd,strc,strb);*/  /************************ivector *******************************/
   int *ivector(long nl,long nh)
         Tvar[i+1]=atoi(strc);  {
         }    int *v;
         strcpy(modelsav,stra);      v=(int *) malloc((size_t)((nh-nl+1+NR_END)*sizeof(int)));
       }    if (!v) nrerror("allocation failure in ivector");
       cutv(strd,strc,stra,'V');    return v-nl+NR_END;
       Tvar[1]=atoi(strc);  }
     }  
   }  /******************free ivector **************************/
   void free_ivector(int *v, long nl, long nh)
   /* printf("tvar=%d %d cptcovage=%d %d",Tvar[1],Tvar[2],cptcovage,Tage[1]);  {
      scanf("%d ",i);*/    free((FREE_ARG)(v+nl-NR_END));
     fclose(fic);  }
   
    if(mle==1){  /************************lvector *******************************/
     if (weightopt != 1) { /* Maximisation without weights*/  long *lvector(long nl,long nh)
       for(i=1;i<=n;i++) weight[i]=1.0;  {
     }    long *v;
     /*-calculation of age at interview from date of interview and age at death -*/    v=(long *) malloc((size_t)((nh-nl+1+NR_END)*sizeof(long)));
     agev=matrix(1,maxwav,1,imx);    if (!v) nrerror("allocation failure in ivector");
        return v-nl+NR_END;
     for (i=1; i<=imx; i++)  {  }
       agedc[i]=(moisdc[i]/12.+andc[i])-(moisnais[i]/12.+annais[i]);  
       for(m=1; (m<= maxwav); m++){  /******************free lvector **************************/
         if(s[m][i] >0){  void free_lvector(long *v, long nl, long nh)
           if (s[m][i] == nlstate+1) {  {
             if(agedc[i]>0)    free((FREE_ARG)(v+nl-NR_END));
               if(moisdc[i]!=99 && andc[i]!=9999)  }
               agev[m][i]=agedc[i];  
             else{  /******************* imatrix *******************************/
               printf("Warning negative age at death: %d line:%d\n",num[i],i);  int **imatrix(long nrl, long nrh, long ncl, long nch) 
               agev[m][i]=-1;       /* allocate a int matrix with subscript range m[nrl..nrh][ncl..nch] */ 
             }  { 
           }    long i, nrow=nrh-nrl+1,ncol=nch-ncl+1; 
           else if(s[m][i] !=9){ /* Should no more exist */    int **m; 
             agev[m][i]=(mint[m][i]/12.+1./24.+anint[m][i])-(moisnais[i]/12.+1./24.+annais[i]);    
             if(mint[m][i]==99 || anint[m][i]==9999)    /* allocate pointers to rows */ 
               agev[m][i]=1;    m=(int **) malloc((size_t)((nrow+NR_END)*sizeof(int*))); 
             else if(agev[m][i] <agemin){    if (!m) nrerror("allocation failure 1 in matrix()"); 
               agemin=agev[m][i];    m += NR_END; 
               /*printf(" Min anint[%d][%d]=%.2f annais[%d]=%.2f, agemin=%.2f\n",m,i,anint[m][i], i,annais[i], agemin);*/    m -= nrl; 
             }    
             else if(agev[m][i] >agemax){    
               agemax=agev[m][i];    /* allocate rows and set pointers to them */ 
              /* printf(" anint[%d][%d]=%.0f annais[%d]=%.0f, agemax=%.0f\n",m,i,anint[m][i], i,annais[i], agemax);*/    m[nrl]=(int *) malloc((size_t)((nrow*ncol+NR_END)*sizeof(int))); 
             }    if (!m[nrl]) nrerror("allocation failure 2 in matrix()"); 
             /*agev[m][i]=anint[m][i]-annais[i];*/    m[nrl] += NR_END; 
             /*   agev[m][i] = age[i]+2*m;*/    m[nrl] -= ncl; 
           }    
           else { /* =9 */    for(i=nrl+1;i<=nrh;i++) m[i]=m[i-1]+ncol; 
             agev[m][i]=1;    
             s[m][i]=-1;    /* return pointer to array of pointers to rows */ 
           }    return m; 
         }  } 
         else /*= 0 Unknown */  
           agev[m][i]=1;  /****************** free_imatrix *************************/
       }  void free_imatrix(m,nrl,nrh,ncl,nch)
            int **m;
     }        long nch,ncl,nrh,nrl; 
     for (i=1; i<=imx; i++)  {       /* free an int matrix allocated by imatrix() */ 
       for(m=1; (m<= maxwav); m++){  { 
         if (s[m][i] > (nlstate+ndeath)) {    free((FREE_ARG) (m[nrl]+ncl-NR_END)); 
           printf("Error: Wrong value in nlstate or ndeath\n");      free((FREE_ARG) (m+nrl-NR_END)); 
           goto end;  } 
         }  
       }  /******************* matrix *******************************/
     }  double **matrix(long nrl, long nrh, long ncl, long nch)
   {
 printf("Total number of individuals= %d, Agemin = %.2f, Agemax= %.2f\n\n", imx, agemin, agemax);    long i, nrow=nrh-nrl+1, ncol=nch-ncl+1;
     double **m;
     free_vector(severity,1,maxwav);  
     free_imatrix(outcome,1,maxwav+1,1,n);    m=(double **) malloc((size_t)((nrow+NR_END)*sizeof(double*)));
     free_vector(moisnais,1,n);    if (!m) nrerror("allocation failure 1 in matrix()");
     free_vector(annais,1,n);    m += NR_END;
     free_matrix(mint,1,maxwav,1,n);    m -= nrl;
     free_matrix(anint,1,maxwav,1,n);  
     free_vector(moisdc,1,n);    m[nrl]=(double *) malloc((size_t)((nrow*ncol+NR_END)*sizeof(double)));
     free_vector(andc,1,n);    if (!m[nrl]) nrerror("allocation failure 2 in matrix()");
     m[nrl] += NR_END;
        m[nrl] -= ncl;
     wav=ivector(1,imx);  
     dh=imatrix(1,lastpass-firstpass+1,1,imx);    for (i=nrl+1; i<=nrh; i++) m[i]=m[i-1]+ncol;
     mw=imatrix(1,lastpass-firstpass+1,1,imx);    return m;
        /* print *(*(m+1)+70) or print m[1][70]; print m+1 or print &(m[1]) or &(m[1][0])
     /* Concatenates waves */  m[i] = address of ith row of the table. &(m[i]) is its value which is another adress
       concatwav(wav, dh, mw, s, agedc, agev,  firstpass, lastpass, imx, nlstate, stepm);  that of m[i][0]. In order to get the value p m[i][0] but it is unitialized.
      */
   }
       Tcode=ivector(1,100);  
    nbcode=imatrix(1,nvar,1,8);    /*************************free matrix ************************/
    ncodemax[1]=1;  void free_matrix(double **m, long nrl, long nrh, long ncl, long nch)
    if (cptcovn > 0) tricode(Tvar,nbcode,imx);  {
      free((FREE_ARG)(m[nrl]+ncl-NR_END));
    codtab=imatrix(1,100,1,10);    free((FREE_ARG)(m+nrl-NR_END));
    h=0;  }
    m=pow(2,cptcovn);  
    /******************* ma3x *******************************/
    for(k=1;k<=cptcovn; k++){  double ***ma3x(long nrl, long nrh, long ncl, long nch, long nll, long nlh)
      for(i=1; i <=(m/pow(2,k));i++){  {
        for(j=1; j <= ncodemax[k]; j++){    long i, j, nrow=nrh-nrl+1, ncol=nch-ncl+1, nlay=nlh-nll+1;
          for(cpt=1; cpt <=(m/pow(2,cptcovn+1-k)); cpt++){    double ***m;
            h++;  
            if (h>m) h=1;codtab[h][k]=j;    m=(double ***) malloc((size_t)((nrow+NR_END)*sizeof(double*)));
          }    if (!m) nrerror("allocation failure 1 in matrix()");
        }    m += NR_END;
      }    m -= nrl;
    }  
     m[nrl]=(double **) malloc((size_t)((nrow*ncol+NR_END)*sizeof(double)));
    /* for(i=1; i <=m ;i++){    if (!m[nrl]) nrerror("allocation failure 2 in matrix()");
      for(k=1; k <=cptcovn; k++){    m[nrl] += NR_END;
        printf("i=%d k=%d %d ",i,k,codtab[i][k]);    m[nrl] -= ncl;
      }  
      printf("\n");    for (i=nrl+1; i<=nrh; i++) m[i]=m[i-1]+ncol;
    }  
    scanf("%d",i);*/    m[nrl][ncl]=(double *) malloc((size_t)((nrow*ncol*nlay+NR_END)*sizeof(double)));
        if (!m[nrl][ncl]) nrerror("allocation failure 3 in matrix()");
    /* Calculates basic frequencies. Computes observed prevalence at single age    m[nrl][ncl] += NR_END;
        and prints on file fileres'p'. */    m[nrl][ncl] -= nll;
    freqsummary(fileres, agemin, agemax, s, agev, nlstate, imx,Tvar,nbcode, ncodemax);    for (j=ncl+1; j<=nch; j++) 
       m[nrl][j]=m[nrl][j-1]+nlay;
     pmmij= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */    
     oldms= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */    for (i=nrl+1; i<=nrh; i++) {
     newms= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */      m[i][ncl]=m[i-1l][ncl]+ncol*nlay;
     savms= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */      for (j=ncl+1; j<=nch; j++) 
     oldm=oldms; newm=newms; savm=savms; /* Keeps fixed addresses to free */        m[i][j]=m[i][j-1]+nlay;
        }
     /* For Powell, parameters are in a vector p[] starting at p[1]    return m; 
        so we point p on param[1][1] so that p[1] maps on param[1][1][1] */    /*  gdb: p *(m+1) <=> p m[1] and p (m+1) <=> p (m+1) <=> p &(m[1])
     p=param[1][1]; /* *(*(*(param +1)+1)+0) */             &(m[i][j][k]) <=> *((*(m+i) + j)+k)
        */
     mlikeli(ficres,p, npar, ncovmodel, nlstate, ftol, func);  }
   
      /*************************free ma3x ************************/
     /*--------- results files --------------*/  void free_ma3x(double ***m, long nrl, long nrh, long ncl, long nch,long nll, long nlh)
     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);  {
        free((FREE_ARG)(m[nrl][ncl]+ nll-NR_END));
    jk=1;    free((FREE_ARG)(m[nrl]+ncl-NR_END));
    fprintf(ficres,"# Parameters\n");    free((FREE_ARG)(m+nrl-NR_END));
    printf("# Parameters\n");  }
    for(i=1,jk=1; i <=nlstate; i++){  
      for(k=1; k <=(nlstate+ndeath); k++){  /*************** function subdirf ***********/
        if (k != i)  char *subdirf(char fileres[])
          {  {
            printf("%d%d ",i,k);    /* Caution optionfilefiname is hidden */
            fprintf(ficres,"%1d%1d ",i,k);    strcpy(tmpout,optionfilefiname);
            for(j=1; j <=ncovmodel; j++){    strcat(tmpout,"/"); /* Add to the right */
              printf("%f ",p[jk]);    strcat(tmpout,fileres);
              fprintf(ficres,"%f ",p[jk]);    return tmpout;
              jk++;  }
            }  
            printf("\n");  /*************** function subdirf2 ***********/
            fprintf(ficres,"\n");  char *subdirf2(char fileres[], char *preop)
          }  {
      }    /* Example subdirf2(optionfilefiname,"FB_") with optionfilefiname="texte", result="texte/FB_texte"
    }   Errors in subdirf, 2, 3 while printing tmpout is
    rewritten within the same printf. Workaround: many printfs */
     /* Computing hessian and covariance matrix */    /* Caution optionfilefiname is hidden */
     ftolhess=ftol; /* Usually correct */    strcpy(tmpout,optionfilefiname);
     hesscov(matcov, p, npar, delti, ftolhess, func);    strcat(tmpout,"/");
     fprintf(ficres,"# Scales\n");    strcat(tmpout,preop);
     printf("# Scales\n");    strcat(tmpout,fileres);
      for(i=1,jk=1; i <=nlstate; i++){    return tmpout;
       for(j=1; j <=nlstate+ndeath; j++){  }
         if (j!=i) {  
           fprintf(ficres,"%1d%1d",i,j);  /*************** function subdirf3 ***********/
           printf("%1d%1d",i,j);  char *subdirf3(char fileres[], char *preop, char *preop2)
           for(k=1; k<=ncovmodel;k++){  {
             printf(" %.5e",delti[jk]);    
             fprintf(ficres," %.5e",delti[jk]);    /* Caution optionfilefiname is hidden */
             jk++;    strcpy(tmpout,optionfilefiname);
           }    strcat(tmpout,"/");
           printf("\n");    strcat(tmpout,preop);
           fprintf(ficres,"\n");    strcat(tmpout,preop2);
         }    strcat(tmpout,fileres);
       }    return tmpout;
       }  }
       
     k=1;  /*************** function subdirfext ***********/
     fprintf(ficres,"# Covariance\n");  char *subdirfext(char fileres[], char *preop, char *postop)
     printf("# Covariance\n");  {
     for(i=1;i<=npar;i++){    
       /*  if (k>nlstate) k=1;    strcpy(tmpout,preop);
       i1=(i-1)/(ncovmodel*nlstate)+1;    strcat(tmpout,fileres);
       fprintf(ficres,"%s%d%d",alph[k],i1,tab[i]);    strcat(tmpout,postop);
       printf("%s%d%d",alph[k],i1,tab[i]);*/    return tmpout;
       fprintf(ficres,"%3d",i);  }
       printf("%3d",i);  
       for(j=1; j<=i;j++){  /*************** function subdirfext3 ***********/
         fprintf(ficres," %.5e",matcov[i][j]);  char *subdirfext3(char fileres[], char *preop, char *postop)
         printf(" %.5e",matcov[i][j]);  {
       }    
       fprintf(ficres,"\n");    /* Caution optionfilefiname is hidden */
       printf("\n");    strcpy(tmpout,optionfilefiname);
       k++;    strcat(tmpout,"/");
     }    strcat(tmpout,preop);
        strcat(tmpout,fileres);
     while((c=getc(ficpar))=='#' && c!= EOF){    strcat(tmpout,postop);
       ungetc(c,ficpar);    return tmpout;
       fgets(line, MAXLINE, ficpar);  }
       puts(line);   
       fputs(line,ficparo);  char *asc_diff_time(long time_sec, char ascdiff[])
     }  {
     ungetc(c,ficpar);    long sec_left, days, hours, minutes;
      days = (time_sec) / (60*60*24);
     fscanf(ficpar,"agemin=%lf agemax=%lf bage=%lf fage=%lf\n",&agemin,&agemax, &bage, &fage);    sec_left = (time_sec) % (60*60*24);
        hours = (sec_left) / (60*60) ;
     if (fage <= 2) {    sec_left = (sec_left) %(60*60);
       bage = agemin;    minutes = (sec_left) /60;
       fage = agemax;    sec_left = (sec_left) % (60);
     }    sprintf(ascdiff,"%ld day(s) %ld hour(s) %ld minute(s) %ld second(s)",days, hours, minutes, sec_left);  
     return ascdiff;
     fprintf(ficres,"# agemin agemax for life expectancy, bage fage (if mle==0 ie no data nor Max likelihood).\n");  }
     fprintf(ficres,"agemin=%.0f agemax=%.0f bage=%.0f fage=%.0f\n",agemin,agemax,bage,fage);  
 /*------------ gnuplot -------------*/  /***************** f1dim *************************/
 chdir(pathcd);  extern int ncom; 
   if((ficgp=fopen("graph.plt","w"))==NULL) {  extern double *pcom,*xicom;
     printf("Problem with file graph.gp");goto end;  extern double (*nrfunc)(double []); 
   }   
 #ifdef windows  double f1dim(double x) 
   fprintf(ficgp,"cd \"%s\" \n",pathc);  { 
 #endif    int j; 
 m=pow(2,cptcovn);    double f;
      double *xt; 
  /* 1eme*/   
   for (cpt=1; cpt<= nlstate ; cpt ++) {    xt=vector(1,ncom); 
    for (k1=1; k1<= m ; k1 ++) {    for (j=1;j<=ncom;j++) xt[j]=pcom[j]+x*xicom[j]; 
     f=(*nrfunc)(xt); 
 #ifdef windows    free_vector(xt,1,ncom); 
     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);    return f; 
 #endif  } 
 #ifdef unix  
 fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability\" \nplot [%.f:%.f] \"vpl%s\" u 1:2 \"\%%lf",agemin,fage,fileres);  /*****************brent *************************/
 #endif  double brent(double ax, double bx, double cx, double (*f)(double), double tol,  double *xmin) 
   {
 for (i=1; i<= nlstate ; i ++) {    /* Given a function f, and given a bracketing triplet of abscissas ax, bx, cx (such that bx is
   if (i==cpt) fprintf(ficgp," \%%lf (\%%lf)");     * between ax and cx, and f(bx) is less than both f(ax) and f(cx) ), this routine isolates
   else fprintf(ficgp," \%%*lf (\%%*lf)");     * the minimum to a fractional precision of about tol using Brent’s method. The abscissa of
 }     * the minimum is returned as xmin, and the minimum function value is returned as brent , the
     fprintf(ficgp,"\" t\"Stationary prevalence\" w l 0,\"vpl%s\" every :::%d::%d u 1:($2+2*$3) \"\%%lf",fileres,k1-1,k1-1);     * returned function value. 
     for (i=1; i<= nlstate ; i ++) {    */
   if (i==cpt) fprintf(ficgp," \%%lf (\%%lf)");    int iter; 
   else fprintf(ficgp," \%%*lf (\%%*lf)");    double a,b,d,etemp;
 }    double fu=0,fv,fw,fx;
   fprintf(ficgp,"\" t\"95\%% CI\" w l 1,\"vpl%s\" every :::%d::%d u 1:($2-2*$3) \"\%%lf",fileres,k1-1,k1-1);    double ftemp=0.;
      for (i=1; i<= nlstate ; i ++) {    double p,q,r,tol1,tol2,u,v,w,x,xm; 
   if (i==cpt) fprintf(ficgp," \%%lf (\%%lf)");    double e=0.0; 
   else fprintf(ficgp," \%%*lf (\%%*lf)");   
 }      a=(ax < cx ? ax : cx); 
      fprintf(ficgp,"\" t\"\" w l 1,\"p%s\" every :::%d::%d u 1:($%d) t\"Observed prevalence \" w l 2",fileres,k1-1,k1-1,2+4*(cpt-1));    b=(ax > cx ? ax : cx); 
 #ifdef unix    x=w=v=bx; 
 fprintf(ficgp,"\nset ter gif small size 400,300");    fw=fv=fx=(*f)(x); 
 #endif    for (iter=1;iter<=ITMAX;iter++) { 
 fprintf(ficgp,"\nset out \"v%s%d%d.gif\" \nreplot\n\n",strtok(optionfile, "."),cpt,k1);      xm=0.5*(a+b); 
    }      tol2=2.0*(tol1=tol*fabs(x)+ZEPS); 
   }      /*          if (2.0*fabs(fp-(*fret)) <= ftol*(fabs(fp)+fabs(*fret)))*/
   /*2 eme*/      printf(".");fflush(stdout);
       fprintf(ficlog,".");fflush(ficlog);
   for (k1=1; k1<= m ; k1 ++) {  #ifdef DEBUGBRENT
     fprintf(ficgp,"set ylabel \"Years\" \nset ter gif small size 400,300\nplot [%.f:%.f] ",agemin,fage);      printf("br %d,x=%.10e xm=%.10e b=%.10e a=%.10e tol=%.10e tol1=%.10e tol2=%.10e x-xm=%.10e fx=%.12e fu=%.12e,fw=%.12e,ftemp=%.12e,ftol=%.12e\n",iter,x,xm,b,a,tol,tol1,tol2,(x-xm),fx,fu,fw,ftemp,ftol);
          fprintf(ficlog,"br %d,x=%.10e xm=%.10e b=%.10e a=%.10e tol=%.10e tol1=%.10e tol2=%.10e x-xm=%.10e fx=%.12e fu=%.12e,fw=%.12e,ftemp=%.12e,ftol=%.12e\n",iter,x,xm,b,a,tol,tol1,tol2,(x-xm),fx,fu,fw,ftemp,ftol);
     for (i=1; i<= nlstate+1 ; i ++) {      /*          if ((fabs(x-xm) <= (tol2-0.5*(b-a)))||(2.0*fabs(fu-ftemp) <= ftol*1.e-2*(fabs(fu)+fabs(ftemp)))) { */
       k=2*i;  #endif
       fprintf(ficgp,"\"t%s\" every :::%d::%d u 1:2 \"\%%lf",fileres,k1-1,k1-1);      if (fabs(x-xm) <= (tol2-0.5*(b-a))){ 
       for (j=1; j<= nlstate+1 ; j ++) {        *xmin=x; 
   if (j==i) fprintf(ficgp," \%%lf (\%%lf)");        return fx; 
   else fprintf(ficgp," \%%*lf (\%%*lf)");      } 
 }        ftemp=fu;
       if (i== 1) fprintf(ficgp,"\" t\"TLE\" w l ,");      if (fabs(e) > tol1) { 
       else fprintf(ficgp,"\" t\"LE in state (%d)\" w l ,",i-1);        r=(x-w)*(fx-fv); 
     fprintf(ficgp,"\"t%s\" every :::%d::%d u 1:($2-$3*2) \"\%%lf",fileres,k1-1,k1-1);        q=(x-v)*(fx-fw); 
       for (j=1; j<= nlstate+1 ; j ++) {        p=(x-v)*q-(x-w)*r; 
         if (j==i) fprintf(ficgp," \%%lf (\%%lf)");        q=2.0*(q-r); 
         else fprintf(ficgp," \%%*lf (\%%*lf)");        if (q > 0.0) p = -p; 
 }          q=fabs(q); 
       fprintf(ficgp,"\" t\"\" w l 0,");        etemp=e; 
      fprintf(ficgp,"\"t%s\" every :::%d::%d u 1:($2+$3*2) \"\%%lf",fileres,k1-1,k1-1);        e=d; 
       for (j=1; j<= nlstate+1 ; j ++) {        if (fabs(p) >= fabs(0.5*q*etemp) || p <= q*(a-x) || p >= q*(b-x)) 
   if (j==i) fprintf(ficgp," \%%lf (\%%lf)");                                  d=CGOLD*(e=(x >= xm ? a-x : b-x)); 
   else fprintf(ficgp," \%%*lf (\%%*lf)");        else { 
 }                                    d=p/q; 
       if (i== (nlstate+1)) fprintf(ficgp,"\" t\"\" w l 0");                                  u=x+d; 
       else fprintf(ficgp,"\" t\"\" w l 0,");                                  if (u-a < tol2 || b-u < tol2) 
     }                                          d=SIGN(tol1,xm-x); 
     fprintf(ficgp,"\nset out \"e%s%d.gif\" \nreplot\n\n",strtok(optionfile, "."),k1);        } 
   }      } else { 
          d=CGOLD*(e=(x >= xm ? a-x : b-x)); 
   /*3eme*/      } 
       u=(fabs(d) >= tol1 ? x+d : x+SIGN(tol1,d)); 
   for (k1=1; k1<= m ; k1 ++) {      fu=(*f)(u); 
     for (cpt=1; cpt<= nlstate ; cpt ++) {      if (fu <= fx) { 
       k=2+nlstate*(cpt-1);        if (u >= x) a=x; else b=x; 
       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);        SHFT(v,w,x,u) 
       for (i=1; i< nlstate ; i ++) {        SHFT(fv,fw,fx,fu) 
         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);      } else { 
       }        if (u < x) a=u; else b=u; 
       fprintf(ficgp,"\nset out \"exp%s%d%d.gif\" \nreplot\n\n",strtok(optionfile, "."),cpt,k1);        if (fu <= fw || w == x) { 
     }                                  v=w; 
   }                                  w=u; 
                                    fv=fw; 
   /* CV preval stat */                                  fw=fu; 
   for (k1=1; k1<= m ; k1 ++) {        } else if (fu <= fv || v == x || v == w) { 
     for (cpt=1; cpt<nlstate ; cpt ++) {                                  v=u; 
       k=3;                                  fv=fu; 
       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/($%d",agemin,agemax,fileres,k1,k+cpt+1,k+1);        } 
       for (i=1; i< nlstate ; i ++)      } 
         fprintf(ficgp,"+$%d",k+i+1);    } 
       fprintf(ficgp,")) t\"prev(%d,%d)\" w l",cpt,cpt+1);    nrerror("Too many iterations in brent"); 
          *xmin=x; 
       l=3+(nlstate+ndeath)*cpt;    return fx; 
       fprintf(ficgp,",\"pij%s\" u ($1==%d ? ($3):1/0):($%d/($%d",fileres,k1,l+cpt+1,l+1);  } 
       for (i=1; i< nlstate ; i ++) {  
         l=3+(nlstate+ndeath)*cpt;  /****************** mnbrak ***********************/
         fprintf(ficgp,"+$%d",l+i+1);  
       }  void mnbrak(double *ax, double *bx, double *cx, double *fa, double *fb, double *fc, 
       fprintf(ficgp,")) t\"prev(%d,%d)\" w l\n",cpt+1,cpt+1);                double (*func)(double)) 
       fprintf(ficgp,"set out \"p%s%d%d.gif\" \nreplot\n\n",strtok(optionfile, "."),cpt,k1);  { /* Given a function func , and given distinct initial points ax and bx , this routine searches in
     }  the downhill direction (defined by the function as evaluated at the initial points) and returns
   }  new points ax , bx , cx that bracket a minimum of the function. Also returned are the function
   values at the three points, fa, fb , and fc such that fa > fb and fb < fc.
   /* proba elementaires */     */
    for(i=1,jk=1; i <=nlstate; i++){    double ulim,u,r,q, dum;
     for(k=1; k <=(nlstate+ndeath); k++){    double fu; 
       if (k != i) {  
         for(j=1; j <=ncovmodel; j++){    double scale=10.;
           /*fprintf(ficgp,"%s%1d%1d=%f ",alph[j],i,k,p[jk]);*/    int iterscale=0;
           /*fprintf(ficgp,"%s",alph[1]);*/  
           fprintf(ficgp,"p%d=%f ",jk,p[jk]);    *fa=(*func)(*ax); /*  xta[j]=pcom[j]+(*ax)*xicom[j]; fa=f(xta[j])*/
           jk++;    *fb=(*func)(*bx); /*  xtb[j]=pcom[j]+(*bx)*xicom[j]; fb=f(xtb[j]) */
           fprintf(ficgp,"\n");  
         }  
       }    /* while(*fb != *fb){ /\* *ax should be ok, reducing distance to *ax *\/ */
     }    /*   printf("Warning mnbrak *fb = %lf, *bx=%lf *ax=%lf *fa==%lf iter=%d\n",*fb, *bx, *ax, *fa, iterscale++); */
     }    /*   *bx = *ax - (*ax - *bx)/scale; */
     /*   *fb=(*func)(*bx);  /\*  xtb[j]=pcom[j]+(*bx)*xicom[j]; fb=f(xtb[j]) *\/ */
   for(jk=1; jk <=m; jk++) {    /* } */
   fprintf(ficgp,"\nset ter gif small size 400,300\nset log y\nplot  [%.f:%.f] ",agemin,agemax);  
    i=1;    if (*fb > *fa) { 
    for(k2=1; k2<=nlstate; k2++) {      SHFT(dum,*ax,*bx,dum) 
      k3=i;      SHFT(dum,*fb,*fa,dum) 
      for(k=1; k<=(nlstate+ndeath); k++) {    } 
        if (k != k2){    *cx=(*bx)+GOLD*(*bx-*ax); 
         fprintf(ficgp," exp(p%d+p%d*x",i,i+1);    *fc=(*func)(*cx); 
   #ifdef DEBUG
         for(j=3; j <=ncovmodel; j++)    printf("mnbrak0 a=%lf *fa=%lf, b=%lf *fb=%lf, c=%lf *fc=%lf\n",*ax,*fa,*bx,*fb,*cx, *fc);
           fprintf(ficgp,"+p%d*%d",i+j-1,nbcode[Tvar[j-2]][codtab[jk][j-2]]);    fprintf(ficlog,"mnbrak0 a=%lf *fa=%lf, b=%lf *fb=%lf, c=%lf *fc=%lf\n",*ax,*fa,*bx,*fb,*cx, *fc);
         fprintf(ficgp,")/(1");  #endif
            while (*fb > *fc) { /* Declining a,b,c with fa> fb > fc. If fc=inf it exits and if flat fb=fc it exits too.*/
         for(k1=1; k1 <=nlstate; k1++){        r=(*bx-*ax)*(*fb-*fc); 
           fprintf(ficgp,"+exp(p%d+p%d*x",k3+(k1-1)*ncovmodel,k3+(k1-1)*ncovmodel+1);      q=(*bx-*cx)*(*fb-*fa); /* What if fa=inf */
           for(j=3; j <=ncovmodel; j++)      u=(*bx)-((*bx-*cx)*q-(*bx-*ax)*r)/ 
             fprintf(ficgp,"+p%d*%d",k3+(k1-1)*ncovmodel+1+j-2,nbcode[Tvar[j-2]][codtab[jk][j-2]]);        (2.0*SIGN(FMAX(fabs(q-r),TINY),q-r)); /* Minimum abscissa of a parabolic estimated from (a,fa), (b,fb) and (c,fc). */
           fprintf(ficgp,")");      ulim=(*bx)+GLIMIT*(*cx-*bx); /* Maximum abscissa where function should be evaluated */
         }      if ((*bx-u)*(u-*cx) > 0.0) { /* if u_p is between b and c */
         fprintf(ficgp,") t \"p%d%d\" ", k2,k);        fu=(*func)(u); 
         if ((k+k2)!= (nlstate*2+ndeath)) fprintf(ficgp,",");  #ifdef DEBUG
         i=i+ncovmodel;        /* f(x)=A(x-u)**2+f(u) */
        }        double A, fparabu; 
      }        A= (*fb - *fa)/(*bx-*ax)/(*bx+*ax-2*u);
    }        fparabu= *fa - A*(*ax-u)*(*ax-u);
    fprintf(ficgp,"\nset out \"pe%s%d.gif\" \nreplot\n\n",strtok(optionfile, "."),jk);        printf("\nmnbrak (*ax=%.12f, *fa=%.12lf), (*bx=%.12f, *fb=%.12lf), (*cx=%.12f, *fc=%.12lf),  (*u=%.12f, fu=%.12lf, fparabu=%.12f, q=%lf < %lf=r)\n",*ax,*fa,*bx,*fb,*cx,*fc,u,fu, fparabu,q,r);
   }        fprintf(ficlog,"\nmnbrak (*ax=%.12f, *fa=%.12lf), (*bx=%.12f, *fb=%.12lf), (*cx=%.12f, *fc=%.12lf),  (*u=%.12f, fu=%.12lf, fparabu=%.12f, q=%lf < %lf=r)\n",*ax,*fa,*bx,*fb,*cx,*fc,u,fu, fparabu,q,r);
            /* And thus,it can be that fu > *fc even if fparabu < *fc */
   fclose(ficgp);        /* mnbrak (*ax=7.666299858533, *fa=299039.693133272231), (*bx=8.595447774979, *fb=298976.598289369489),
              (*cx=10.098840694817, *fc=298946.631474258087),  (*u=9.852501168332, fu=298948.773013752128, fparabu=298945.434711494134) */
 chdir(path);        /* In that case, there is no bracket in the output! Routine is wrong with many consequences.*/
     free_matrix(agev,1,maxwav,1,imx);  #endif 
     free_ivector(wav,1,imx);  #ifdef MNBRAKORIGINAL
     free_imatrix(dh,1,lastpass-firstpass+1,1,imx);  #else
     free_imatrix(mw,1,lastpass-firstpass+1,1,imx);  /*       if (fu > *fc) { */
      /* #ifdef DEBUG */
     free_imatrix(s,1,maxwav+1,1,n);  /*       printf("mnbrak4  fu > fc \n"); */
      /*       fprintf(ficlog, "mnbrak4 fu > fc\n"); */
      /* #endif */
     free_ivector(num,1,n);  /*      /\* 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 *\\/  *\/ */
     free_vector(agedc,1,n);  /*      /\* SHFT(*fa,*fc,fu,*fc) /\\* (b, u, c) is a bracket while test fb > fc will be fu > fc  will exit *\\/ *\/ */
     free_vector(weight,1,n);  /*      dum=u; /\* Shifting c and u *\/ */
     /*free_matrix(covar,1,NCOVMAX,1,n);*/  /*      u = *cx; */
     fclose(ficparo);  /*      *cx = dum; */
     fclose(ficres);  /*      dum = fu; */
    }  /*      fu = *fc; */
      /*      *fc =dum; */
    /*________fin mle=1_________*/  /*       } else { /\* end *\/ */
      /* #ifdef DEBUG */
   /*       printf("mnbrak3  fu < fc \n"); */
    /*       fprintf(ficlog, "mnbrak3 fu < fc\n"); */
     /* No more information from the sample is required now */  /* #endif */
   /* Reads comments: lines beginning with '#' */  /*      dum=u; /\* Shifting c and u *\/ */
   while((c=getc(ficpar))=='#' && c!= EOF){  /*      u = *cx; */
     ungetc(c,ficpar);  /*      *cx = dum; */
     fgets(line, MAXLINE, ficpar);  /*      dum = fu; */
     puts(line);  /*      fu = *fc; */
     fputs(line,ficparo);  /*      *fc =dum; */
   }  /*       } */
   ungetc(c,ficpar);  #ifdef DEBUGMNBRAK
                     double A, fparabu; 
   fscanf(ficpar,"agemin=%lf agemax=%lf bage=%lf fage=%lf\n",&agemin,&agemax, &bage, &fage);       A= (*fb - *fa)/(*bx-*ax)/(*bx+*ax-2*u);
   printf("agemin=%.0f agemax=%.0f bage=%.0f fage=%.0f\n",agemin,agemax, bage, fage);       fparabu= *fa - A*(*ax-u)*(*ax-u);
   fprintf(ficparo,"agemin=%.0f agemax=%.0f bage=%.0f fage=%.0f\n",agemin,agemax,bage,fage);       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);
 /*--------- index.htm --------*/       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
   if((fichtm=fopen("index.htm","w"))==NULL)    {        dum=u; /* Shifting c and u */
     printf("Problem with index.htm \n");goto end;        u = *cx;
   }        *cx = dum;
         dum = fu;
  fprintf(fichtm,"<body><ul> Imach, Version 0.64a<hr> <li>Outputs files<br><br>\n        fu = *fc;
         - Observed prevalence in each state: <a href=\"p%s\">p%s</a> <br>\n        *fc =dum;
 - Estimated parameters and the covariance matrix: <a href=\"%s\">%s</a> <br>  #endif
         - Stationary prevalence in each state: <a href=\"pl%s\">pl%s</a> <br>      } else if ((*cx-u)*(u-ulim) > 0.0) { /* u is after c but before ulim */
         - Transition probabilities: <a href=\"pij%s\">pij%s</a><br>  #ifdef DEBUG
         - Copy of the parameter file: <a href=\"o%s\">o%s</a><br>        printf("\nmnbrak2  u=%lf after c=%lf but before ulim\n",u,*cx);
         - Life expectancies by age and initial health status: <a href=\"e%s\">e%s</a> <br>        fprintf(ficlog,"\nmnbrak2  u=%lf after c=%lf but before ulim\n",u,*cx);
         - Variances of life expectancies by age and initial health status: <a href=\"v%s\">v%s</a><br>  #endif
         - Health expectancies with their variances: <a href=\"t%s\">t%s</a> <br>        fu=(*func)(u); 
         - Standard deviation of stationary prevalences: <a href=\"vpl%s\">vpl%s</a> <br><br>",fileres,fileres,fileres,fileres,fileres,fileres,fileres,fileres,fileres,fileres,fileres,fileres,fileres,fileres,fileres,fileres,fileres,fileres);        if (fu < *fc) { 
   #ifdef DEBUG
  fprintf(fichtm," <li>Graphs</li>\n<p>");                                  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);
  m=cptcovn;  #endif
  if (cptcovn < 1) {m=1;ncodemax[1]=1;}                            SHFT(*bx,*cx,u,*cx+GOLD*(*cx-*bx)) 
                                   SHFT(*fb,*fc,fu,(*func)(u)) 
  j1=0;  #ifdef DEBUG
  for(k1=1; k1<=m;k1++){                                          printf("\nmnbrak2 shift GOLD c=%lf",*cx+GOLD*(*cx-*bx));
    for(i1=1; i1<=ncodemax[k1];i1++){  #endif
        j1++;        } 
        if (cptcovn > 0) {      } else if ((u-ulim)*(ulim-*cx) >= 0.0) { /* u outside ulim (verifying that ulim is beyond c) */
          fprintf(fichtm,"<hr>************ Results for covariates");  #ifdef DEBUG
          for (cpt=1; cpt<=cptcovn;cpt++)        printf("\nmnbrak2  u=%lf outside ulim=%lf (verifying that ulim is beyond c=%lf)\n",u,ulim,*cx);
            fprintf(fichtm," V%d=%d ",Tvar[cpt],nbcode[Tvar[cpt]][codtab[j1][cpt]]);        fprintf(ficlog,"\nmnbrak2  u=%lf outside ulim=%lf (verifying that ulim is beyond c=%lf)\n",u,ulim,*cx);
          fprintf(fichtm," ************\n<hr>");  #endif
        }        u=ulim; 
        fprintf(fichtm,"<br>- Probabilities: pe%s%d.gif<br>        fu=(*func)(u); 
 <img src=\"pe%s%d.gif\">",strtok(optionfile, "."),j1,strtok(optionfile, "."),j1);          } else { /* u could be left to b (if r > q parabola has a maximum) */
        for(cpt=1; cpt<nlstate;cpt++){  #ifdef DEBUG
          fprintf(fichtm,"<br>- Prevalence of disability : p%s%d%d.gif<br>        printf("\nmnbrak2  u=%lf could be left to b=%lf (if r=%lf > q=%lf parabola has a maximum)\n",u,*bx,r,q);
 <img src=\"p%s%d%d.gif\">",strtok(optionfile, "."),cpt,j1,strtok(optionfile, "."),cpt,j1);        fprintf(ficlog,"\nmnbrak2  u=%lf could be left to b=%lf (if r=%lf > q=%lf parabola has a maximum)\n",u,*bx,r,q);
        }  #endif
     for(cpt=1; cpt<=nlstate;cpt++) {        u=(*cx)+GOLD*(*cx-*bx); 
        fprintf(fichtm,"<br>- Observed and stationary prevalence (with confident        fu=(*func)(u); 
 interval) in state (%d): v%s%d%d.gif <br>  #ifdef DEBUG
 <img src=\"v%s%d%d.gif\">",cpt,strtok(optionfile, "."),cpt,j1,strtok(optionfile, "."),cpt,j1);          printf("\nmnbrak2 new u=%lf fu=%lf shifted gold left from c=%lf and b=%lf \n",u,fu,*cx,*bx);
      }        fprintf(ficlog,"\nmnbrak2 new u=%lf fu=%lf shifted gold left from c=%lf and b=%lf \n",u,fu,*cx,*bx);
      for(cpt=1; cpt<=nlstate;cpt++) {  #endif
         fprintf(fichtm,"\n<br>- Health life expectancies by age and initial health state (%d): exp%s%d%d.gif <br>      } /* end tests */
 <img src=\"exp%s%d%d.gif\">",cpt,strtok(optionfile, "."),cpt,j1,strtok(optionfile, "."),cpt,j1);      SHFT(*ax,*bx,*cx,u) 
      }      SHFT(*fa,*fb,*fc,fu) 
      fprintf(fichtm,"\n<br>- Total life expectancy by age and  #ifdef DEBUG
 health expectancies in states (1) and (2): e%s%d.gif<br>        printf("\nmnbrak2 shift (*ax=%.12f, *fa=%.12lf), (*bx=%.12f, *fb=%.12lf), (*cx=%.12f, *fc=%.12lf)\n",*ax,*fa,*bx,*fb,*cx,*fc);
 <img src=\"e%s%d.gif\">",strtok(optionfile, "."),j1,strtok(optionfile, "."),j1);        fprintf(ficlog, "\nmnbrak2 shift (*ax=%.12f, *fa=%.12lf), (*bx=%.12f, *fb=%.12lf), (*cx=%.12f, *fc=%.12lf)\n",*ax,*fa,*bx,*fb,*cx,*fc);
 fprintf(fichtm,"\n</body>");  #endif
    }    } /* end while; ie return (a, b, c, fa, fb, fc) such that a < b < c with f(a) > f(b) and fb < f(c) */
  }  } 
 fclose(fichtm);  
   /*************** linmin ************************/
   /*--------------- Prevalence limit --------------*/  /* Given an n -dimensional point p[1..n] and an n -dimensional direction xi[1..n] , moves and
    resets p to where the function func(p) takes on a minimum along the direction xi from p ,
   strcpy(filerespl,"pl");  and replaces xi by the actual vector displacement that p was moved. Also returns as fret
   strcat(filerespl,fileres);  the value of func at the returned location p . This is actually all accomplished by calling the
   if((ficrespl=fopen(filerespl,"w"))==NULL) {  routines mnbrak and brent .*/
     printf("Problem with Prev limit resultfile: %s\n", filerespl);goto end;  int ncom; 
   }  double *pcom,*xicom;
   printf("Computing prevalence limit: result on file '%s' \n", filerespl);  double (*nrfunc)(double []); 
   fprintf(ficrespl,"#Prevalence limit\n");   
   fprintf(ficrespl,"#Age ");  #ifdef LINMINORIGINAL
   for(i=1; i<=nlstate;i++) fprintf(ficrespl,"%d-%d ",i,i);  void linmin(double p[], double xi[], int n, double *fret,double (*func)(double [])) 
   fprintf(ficrespl,"\n");  #else
    void linmin(double p[], double xi[], int n, double *fret,double (*func)(double []), int *flat) 
   prlim=matrix(1,nlstate,1,nlstate);  #endif
   pmmij= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */  { 
   oldms= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */    double brent(double ax, double bx, double cx, 
   newms= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */                 double (*f)(double), double tol, double *xmin); 
   savms= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */    double f1dim(double x); 
   oldm=oldms; newm=newms; savm=savms; /* Keeps fixed addresses to free */    void mnbrak(double *ax, double *bx, double *cx, double *fa, double *fb, 
   k=0;                double *fc, double (*func)(double)); 
   agebase=agemin;    int j; 
   agelim=agemax;    double xx,xmin,bx,ax; 
   ftolpl=1.e-10;    double fx,fb,fa;
   i1=cptcovn;  
   if (cptcovn < 1){i1=1;}  #ifdef LINMINORIGINAL
   #else
   for(cptcov=1;cptcov<=i1;cptcov++){    double scale=10., axs, xxs; /* Scale added for infinity */
     for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){  #endif
         k=k+1;    
         /*printf("cptcov=%d cptcod=%d codtab=%d nbcode=%d\n",cptcov, cptcod,Tcode[cptcode],codtab[cptcod][cptcov]);*/    ncom=n; 
         fprintf(ficrespl,"\n#******");    pcom=vector(1,n); 
         for(j=1;j<=cptcovn;j++)    xicom=vector(1,n); 
           fprintf(ficrespl," V%d=%d ",Tvar[j],nbcode[Tvar[j]][codtab[k][j]]);    nrfunc=func; 
         fprintf(ficrespl,"******\n");    for (j=1;j<=n;j++) { 
              pcom[j]=p[j]; 
         for (age=agebase; age<=agelim; age++){      xicom[j]=xi[j]; /* Former scale xi[j] of currrent direction i */
           prevalim(prlim, nlstate, p, age, oldm, savm,ftolpl,k);    } 
           fprintf(ficrespl,"%.0f",age );  
           for(i=1; i<=nlstate;i++)  #ifdef LINMINORIGINAL
           fprintf(ficrespl," %.5f", prlim[i][i]);    xx=1.;
           fprintf(ficrespl,"\n");  #else
         }    axs=0.0;
       }    xxs=1.;
     }    do{
   fclose(ficrespl);      xx= xxs;
   /*------------- h Pij x at various ages ------------*/  #endif
        ax=0.;
   strcpy(filerespij,"pij");  strcat(filerespij,fileres);      mnbrak(&ax,&xx,&bx,&fa,&fx,&fb,f1dim);  /* Outputs: xtx[j]=pcom[j]+(*xx)*xicom[j]; fx=f(xtx[j]) */
   if((ficrespij=fopen(filerespij,"w"))==NULL) {      /* brackets with inputs ax=0 and xx=1, but points, pcom=p, and directions values, xicom=xi, are sent via f1dim(x) */
     printf("Problem with Pij resultfile: %s\n", filerespij);goto end;      /* xt[x,j]=pcom[j]+x*xicom[j]  f(ax) = f(xt(a,j=1,n)) = f(p(j) + 0 * xi(j)) and  f(xx) = f(xt(x, j=1,n)) = f(p(j) + 1 * xi(j))   */
   }      /* Outputs: fa=f(p(j)) and fx=f(p(j) + xxs * xi(j) ) and f(bx)= f(p(j)+ bx* xi(j)) */
   printf("Computing pij: result on file '%s' \n", filerespij);      /* Given input ax=axs and xx=xxs, xx might be too far from ax to get a finite f(xx) */
        /* Searches on line, outputs (ax, xx, bx) such that fx < min(fa and fb) */
   stepsize=(int) (stepm+YEARM-1)/YEARM;      /* 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]]*/
   if (stepm<=24) stepsize=2;  #ifdef LINMINORIGINAL
   #else
   agelim=AGESUP;      if (fx != fx){
   hstepm=stepsize*YEARM; /* Every year of age */                          xxs=xxs/scale; /* Trying a smaller xx, closer to initial ax=0 */
   hstepm=hstepm/stepm; /* Typically 2 years, = 2/6 months = 4 */                          printf("|");
                            fprintf(ficlog,"|");
   k=0;  #ifdef DEBUGLINMIN
   for(cptcov=1;cptcov<=i1;cptcov++){                          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);
     for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){  #endif
       k=k+1;      }
         fprintf(ficrespij,"\n#****** ");    }while(fx != fx && xxs > 1.e-5);
         for(j=1;j<=cptcovn;j++)  #endif
           fprintf(ficrespij,"V%d=%d ",Tvar[j],nbcode[Tvar[j]][codtab[k][j]]);    
         fprintf(ficrespij,"******\n");  #ifdef DEBUGLINMIN
            printf("\nLinmin after mnbrak: ax=%12.7f xx=%12.7f bx=%12.7f fa=%12.2f fx=%12.2f fb=%12.2f\n",  ax,xx,bx,fa,fx,fb);
         for (agedeb=fage; agedeb>=bage; agedeb--){ /* If stepm=6 months */    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);
           nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */  #endif
           nhstepm = nhstepm/hstepm; /* Typically 40/4=10 */  #ifdef LINMINORIGINAL
           p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);  #else
           oldm=oldms;savm=savms;    if(fb == fx){ /* Flat function in the direction */
           hpxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k);        xmin=xx;
           fprintf(ficrespij,"# Age");      *flat=1;
           for(i=1; i<=nlstate;i++)    }else{
             for(j=1; j<=nlstate+ndeath;j++)      *flat=0;
               fprintf(ficrespij," %1d-%1d",i,j);  #endif
           fprintf(ficrespij,"\n");                  /*Flat mnbrak2 shift (*ax=0.000000000000, *fa=51626.272983130431), (*bx=-1.618034000000, *fb=51590.149499362531), (*cx=-4.236068025156, *fc=51590.149499362531) */
           for (h=0; h<=nhstepm; h++){    *fret=brent(ax,xx,bx,f1dim,TOL,&xmin); /* Giving a bracketting triplet (ax, xx, bx), find a minimum, xmin, according to f1dim, *fret(xmin),*/
             fprintf(ficrespij,"%d %.0f %.0f",k,agedeb, agedeb+ h*hstepm/YEARM*stepm );    /* fa = f(p[j] + ax * xi[j]), fx = f(p[j] + xx * xi[j]), fb = f(p[j] + bx * xi[j]) */
             for(i=1; i<=nlstate;i++)    /* fmin = f(p[j] + xmin * xi[j]) */
               for(j=1; j<=nlstate+ndeath;j++)    /* P+lambda n in that direction (lambdamin), with TOL between abscisses */
                 fprintf(ficrespij," %.5f", p3mat[i][j][h]);    /* f1dim(xmin): for (j=1;j<=ncom;j++) xt[j]=pcom[j]+xmin*xicom[j]; */
             fprintf(ficrespij,"\n");  #ifdef DEBUG
           }    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_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);    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);
           fprintf(ficrespij,"\n");  #endif
         }  #ifdef LINMINORIGINAL
     }  #else
   }                          }
   #endif
   fclose(ficrespij);  #ifdef DEBUGLINMIN
     printf("linmin end ");
   /*---------- Health expectancies and variances ------------*/    fprintf(ficlog,"linmin end ");
   #endif
   strcpy(filerest,"t");    for (j=1;j<=n;j++) { 
   strcat(filerest,fileres);  #ifdef LINMINORIGINAL
   if((ficrest=fopen(filerest,"w"))==NULL) {      xi[j] *= xmin; 
     printf("Problem with total LE resultfile: %s\n", filerest);goto end;  #else
   }  #ifdef DEBUGLINMIN
   printf("Computing Total LEs with variances: file '%s' \n", filerest);      if(xxs <1.0)
         printf(" before xi[%d]=%12.8f", j,xi[j]);
   #endif
   strcpy(filerese,"e");      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) */
   strcat(filerese,fileres);  #ifdef DEBUGLINMIN
   if((ficreseij=fopen(filerese,"w"))==NULL) {      if(xxs <1.0)
     printf("Problem with Health Exp. resultfile: %s\n", filerese); exit(0);        printf(" after xi[%d]=%12.8f, xmin=%12.8f, ax=%12.8f, xx=%12.8f, bx=%12.8f, xxs=%12.8f", j,xi[j], xmin, ax, xx, bx,xxs );
   }  #endif
   printf("Computing Health Expectancies: result on file '%s' \n", filerese);  #endif
       p[j] += xi[j]; /* Parameters values are updated accordingly */
  strcpy(fileresv,"v");    } 
   strcat(fileresv,fileres);  #ifdef DEBUGLINMIN
   if((ficresvij=fopen(fileresv,"w"))==NULL) {    printf("\n");
     printf("Problem with variance resultfile: %s\n", fileresv);exit(0);    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));
   printf("Computing Variance-covariance of DFLEs: file '%s' \n", fileresv);    for (j=1;j<=n;j++) { 
       printf(" xi[%d]= %14.10f p[%d]= %12.7f",j,xi[j],j,p[j]);
   k=0;      fprintf(ficlog," xi[%d]= %14.10f p[%d]= %12.7f",j,xi[j],j,p[j]);
   for(cptcov=1;cptcov<=i1;cptcov++){      if(j % ncovmodel == 0){
     for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){        printf("\n");
       k=k+1;        fprintf(ficlog,"\n");
       fprintf(ficrest,"\n#****** ");      }
       for(j=1;j<=cptcovn;j++)    }
         fprintf(ficrest,"V%d=%d ",Tvar[j],nbcode[Tvar[j]][codtab[k][j]]);  #else
       fprintf(ficrest,"******\n");  #endif
     free_vector(xicom,1,n); 
       fprintf(ficreseij,"\n#****** ");    free_vector(pcom,1,n); 
       for(j=1;j<=cptcovn;j++)  } 
         fprintf(ficreseij,"V%d=%d ",j,nbcode[j][codtab[k][j]]);  
       fprintf(ficreseij,"******\n");  
   /*************** powell ************************/
       fprintf(ficresvij,"\n#****** ");  /*
       for(j=1;j<=cptcovn;j++)  Minimization of a function func of n variables. Input consists in an initial starting point
         fprintf(ficresvij,"V%d=%d ",j,nbcode[j][codtab[k][j]]);  p[1..n] ; an initial matrix xi[1..n][1..n]  whose columns contain the initial set of di-
       fprintf(ficresvij,"******\n");  rections (usually the n unit vectors); and ftol, the fractional tolerance in the function value
   such that failure to decrease by more than this amount in one iteration signals doneness. On
       eij=ma3x(1,nlstate,1,nlstate,(int) bage, (int) fage);  output, p is set to the best point found, xi is the then-current direction set, fret is the returned
       oldm=oldms;savm=savms;  function value at p , and iter is the number of iterations taken. The routine linmin is used.
       evsij(fileres, eij, p, nlstate, stepm, (int) bage, (int)fage, oldm, savm, k);     */
       vareij=ma3x(1,nlstate,1,nlstate,(int) bage, (int) fage);  #ifdef LINMINORIGINAL
       oldm=oldms;savm=savms;  #else
       varevsij(fileres, vareij, matcov, p, delti, nlstate, stepm, (int) bage, (int) fage, oldm, savm, prlim, ftolpl,k);          int *flatdir; /* Function is vanishing in that direction */
                int flat=0, flatd=0; /* Function is vanishing in that direction */
       fprintf(ficrest,"#Total LEs with variances: e.. (std) ");  #endif
       for (i=1;i<=nlstate;i++) fprintf(ficrest,"e.%d (std) ",i);  void powell(double p[], double **xi, int n, double ftol, int *iter, double *fret, 
       fprintf(ficrest,"\n");              double (*func)(double [])) 
          { 
       hf=1;  #ifdef LINMINORIGINAL
       if (stepm >= YEARM) hf=stepm/YEARM;   void linmin(double p[], double xi[], int n, double *fret, 
       epj=vector(1,nlstate+1);                double (*func)(double [])); 
       for(age=bage; age <=fage ;age++){  #else 
         prevalim(prlim, nlstate, p, age, oldm, savm,ftolpl,k);   void linmin(double p[], double xi[], int n, double *fret,
         fprintf(ficrest," %.0f",age);               double (*func)(double []),int *flat); 
         for(j=1, epj[nlstate+1]=0.;j <=nlstate;j++){  #endif
           for(i=1, epj[j]=0.;i <=nlstate;i++) {   int i,ibig,j,jk,k; 
             epj[j] += prlim[i][i]*hf*eij[i][j][(int)age];    double del,t,*pt,*ptt,*xit;
           }    double directest;
           epj[nlstate+1] +=epj[j];    double fp,fptt;
         }    double *xits;
         for(i=1, vepp=0.;i <=nlstate;i++)    int niterf, itmp;
           for(j=1;j <=nlstate;j++)  
             vepp += vareij[i][j][(int)age];    pt=vector(1,n); 
         fprintf(ficrest," %.2f (%.2f)", epj[nlstate+1],hf*sqrt(vepp));    ptt=vector(1,n); 
         for(j=1;j <=nlstate;j++){    xit=vector(1,n); 
           fprintf(ficrest," %.2f (%.2f)", epj[j],hf*sqrt(vareij[j][j][(int)age]));    xits=vector(1,n); 
         }    *fret=(*func)(p); 
         fprintf(ficrest,"\n");    for (j=1;j<=n;j++) pt[j]=p[j]; 
       }    rcurr_time = time(NULL);
     }    fp=(*fret); /* Initialisation */
   }    for (*iter=1;;++(*iter)) { 
              ibig=0; 
  fclose(ficreseij);      del=0.0; 
  fclose(ficresvij);      rlast_time=rcurr_time;
   fclose(ficrest);      /* (void) gettimeofday(&curr_time,&tzp); */
   fclose(ficpar);      rcurr_time = time(NULL);  
   free_vector(epj,1,nlstate+1);      curr_time = *localtime(&rcurr_time);
   /*  scanf("%d ",i); */      /* printf("\nPowell iter=%d -2*LL=%.12f gain=%.12f=%.3g %ld sec. %ld sec.",*iter,*fret, fp-*fret,fp-*fret, rcurr_time-rlast_time, rcurr_time-rstart_time);fflush(stdout); */
       /* fprintf(ficlog,"\nPowell iter=%d -2*LL=%.12f gain=%.12f=%.3g %ld sec. %ld sec.",*iter,*fret, fp-*fret,fp-*fret,rcurr_time-rlast_time, rcurr_time-rstart_time); fflush(ficlog); */
   /*------- Variance limit prevalence------*/        printf("\nPowell iter=%d -2*LL=%.12f gain=%.3lg %ld sec. %ld sec.",*iter,*fret,fp-*fret, rcurr_time-rlast_time, rcurr_time-rstart_time);fflush(stdout);
       fprintf(ficlog,"\nPowell iter=%d -2*LL=%.12f gain=%.3lg %ld sec. %ld sec.",*iter,*fret,fp-*fret,rcurr_time-rlast_time, rcurr_time-rstart_time); fflush(ficlog);
 strcpy(fileresvpl,"vpl");  /*     fprintf(ficrespow,"%d %.12f %ld",*iter,*fret,curr_time.tm_sec-start_time.tm_sec); */
   strcat(fileresvpl,fileres);      fp=(*fret); /* From former iteration or initial value */
   if((ficresvpl=fopen(fileresvpl,"w"))==NULL) {      for (i=1;i<=n;i++) {
     printf("Problem with variance prev lim resultfile: %s\n", fileresvpl);        fprintf(ficrespow," %.12lf", p[i]);
     exit(0);      }
   }      fprintf(ficrespow,"\n");fflush(ficrespow);
   printf("Computing Variance-covariance of Prevalence limit: file '%s' \n", fileresvpl);      printf("\n#model=  1      +     age ");
       fprintf(ficlog,"\n#model=  1      +     age ");
  k=0;      if(nagesqr==1){
  for(cptcov=1;cptcov<=i1;cptcov++){          printf("  + age*age  ");
    for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){          fprintf(ficlog,"  + age*age  ");
      k=k+1;      }
      fprintf(ficresvpl,"\n#****** ");      for(j=1;j <=ncovmodel-2;j++){
      for(j=1;j<=cptcovn;j++)        if(Typevar[j]==0) {
        fprintf(ficresvpl,"V%d=%d ",Tvar[j],nbcode[Tvar[j]][codtab[k][j]]);          printf("  +      V%d  ",Tvar[j]);
      fprintf(ficresvpl,"******\n");          fprintf(ficlog,"  +      V%d  ",Tvar[j]);
              }else if(Typevar[j]==1) {
      varpl=matrix(1,nlstate,(int) bage, (int) fage);          printf("  +    V%d*age ",Tvar[j]);
      oldm=oldms;savm=savms;          fprintf(ficlog,"  +    V%d*age ",Tvar[j]);
      varprevlim(fileres, varpl, matcov, p, delti, nlstate, stepm, (int) bage, (int) fage, oldm, savm, prlim, ftolpl,k);        }else if(Typevar[j]==2) {
    }          printf("  +    V%d*V%d ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
  }          fprintf(ficlog,"  +    V%d*V%d ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
         }
   fclose(ficresvpl);      }
       printf("\n");
   /*---------- End : free ----------------*/  /*     printf("12   47.0114589    0.0154322   33.2424412    0.3279905    2.3731903  */
   free_matrix(varpl,1,nlstate,(int) bage, (int)fage);  /* 13  -21.5392400    0.1118147    1.2680506    1.2973408   -1.0663662  */
        fprintf(ficlog,"\n");
   free_ma3x(vareij,1,nlstate,1,nlstate,(int) bage, (int)fage);      for(i=1,jk=1; i <=nlstate; i++){
   free_ma3x(eij,1,nlstate,1,nlstate,(int) bage, (int)fage);        for(k=1; k <=(nlstate+ndeath); k++){
            if (k != i) {
              printf("%d%d ",i,k);
   free_matrix(pmmij,1,nlstate+ndeath,1,nlstate+ndeath);            fprintf(ficlog,"%d%d ",i,k);
   free_matrix(oldms, 1,nlstate+ndeath,1,nlstate+ndeath);            for(j=1; j <=ncovmodel; j++){
   free_matrix(newms, 1,nlstate+ndeath,1,nlstate+ndeath);              printf("%12.7f ",p[jk]);
   free_matrix(savms, 1,nlstate+ndeath,1,nlstate+ndeath);              fprintf(ficlog,"%12.7f ",p[jk]);
                jk++; 
   free_matrix(matcov,1,npar,1,npar);            }
   free_vector(delti,1,npar);            printf("\n");
              fprintf(ficlog,"\n");
   free_ma3x(param,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);          }
         }
   printf("End of Imach\n");      }
   /*  gettimeofday(&end_time, (struct timezone*)0);*/  /* after time */      if(*iter <=3 && *iter >1){
          tml = *localtime(&rcurr_time);
   /* printf("Total time was %d Sec. %d uSec.\n", end_time.tv_sec -start_time.tv_sec, end_time.tv_usec -start_time.tv_usec);*/        strcpy(strcurr,asctime(&tml));
   /*printf("Total time was %d uSec.\n", total_usecs);*/        rforecast_time=rcurr_time; 
   /*------ End -----------*/        itmp = strlen(strcurr);
         if(strcurr[itmp-1]=='\n')  /* Windows outputs with a new line */
  end:          strcurr[itmp-1]='\0';
 #ifdef windows        printf("\nConsidering the time needed for the last iteration #%d: %ld seconds,\n",*iter,rcurr_time-rlast_time);
  chdir(pathcd);        fprintf(ficlog,"\nConsidering the time needed for this last iteration #%d: %ld seconds,\n",*iter,rcurr_time-rlast_time);
 #endif        for(niterf=10;niterf<=30;niterf+=10){
  system("wgnuplot graph.plt");          rforecast_time=rcurr_time+(niterf-*iter)*(rcurr_time-rlast_time);
           forecast_time = *localtime(&rforecast_time);
 #ifdef windows          strcpy(strfor,asctime(&forecast_time));
   while (z[0] != 'q') {          itmp = strlen(strfor);
     chdir(pathcd);          if(strfor[itmp-1]=='\n')
     printf("\nType e to edit output files, c to start again, and q for exiting: ");            strfor[itmp-1]='\0';
     scanf("%s",z);          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);
     if (z[0] == 'c') system("./imach");          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);
     else if (z[0] == 'e') {        }
       chdir(path);      }
       system("index.htm");      for (i=1;i<=n;i++) { /* For each direction i */
     }        for (j=1;j<=n;j++) xit[j]=xi[j][i]; /* Directions stored from previous iteration with previous scales */
     else if (z[0] == 'q') exit(0);        fptt=(*fret); 
   }  #ifdef DEBUG
 #endif        printf("fret=%lf, %lf, %lf \n", *fret, *fret, *fret);
 }        fprintf(ficlog, "fret=%lf, %lf, %lf \n", *fret, *fret, *fret);
   #endif
         printf("%d",i);fflush(stdout); /* print direction (parameter) i */
         fprintf(ficlog,"%d",i);fflush(ficlog);
   #ifdef LINMINORIGINAL
         linmin(p,xit,n,fret,func); /* Point p[n]. xit[n] has been loaded for direction i as input.*/
   #else
         linmin(p,xit,n,fret,func,&flat); /* Point p[n]. xit[n] has been loaded for direction i as input.*/
                           flatdir[i]=flat; /* Function is vanishing in that direction i */
   #endif
                           /* Outputs are fret(new point p) p is updated and xit rescaled */
         if (fabs(fptt-(*fret)) > del) { /* We are keeping the max gain on each of the n directions */
                                   /* because that direction will be replaced unless the gain del is small */
                                   /* in comparison with the 'probable' gain, mu^2, with the last average direction. */
                                   /* Unless the n directions are conjugate some gain in the determinant may be obtained */
                                   /* with the new direction. */
                                   del=fabs(fptt-(*fret)); 
                                   ibig=i; 
         } 
   #ifdef DEBUG
         printf("%d %.12e",i,(*fret));
         fprintf(ficlog,"%d %.12e",i,(*fret));
         for (j=1;j<=n;j++) {
                                   xits[j]=FMAX(fabs(p[j]-pt[j]),1.e-5);
                                   printf(" x(%d)=%.12e",j,xit[j]);
                                   fprintf(ficlog," x(%d)=%.12e",j,xit[j]);
         }
         for(j=1;j<=n;j++) {
                                   printf(" p(%d)=%.12e",j,p[j]);
                                   fprintf(ficlog," p(%d)=%.12e",j,p[j]);
         }
         printf("\n");
         fprintf(ficlog,"\n");
   #endif
       } /* end loop on each direction i */
       /* Convergence test will use last linmin estimation (fret) and compare former iteration (fp) */ 
       /* But p and xit have been updated at the end of linmin, *fret corresponds to new p, xit  */
       /* New value of last point Pn is not computed, P(n-1) */
       for(j=1;j<=n;j++) {
         if(flatdir[j] >0){
           printf(" p(%d)=%lf flat=%d ",j,p[j],flatdir[j]);
           fprintf(ficlog," p(%d)=%lf flat=%d ",j,p[j],flatdir[j]);
         }
         /* printf("\n"); */
         /* fprintf(ficlog,"\n"); */
       }
       /* if (2.0*fabs(fp-(*fret)) <= ftol*(fabs(fp)+fabs(*fret))) { /\* Did we reach enough precision? *\/ */
       if (2.0*fabs(fp-(*fret)) <= ftol) { /* Did we reach enough precision? */
         /* We could compare with a chi^2. chisquare(0.95,ddl=1)=3.84 */
         /* By adding age*age in a model, the new -2LL should be lower and the difference follows a */
         /* a chisquare statistics with 1 degree. To be significant at the 95% level, it should have */
         /* decreased of more than 3.84  */
         /* By adding age*age and V1*age the gain (-2LL) should be more than 5.99 (ddl=2) */
         /* By using V1+V2+V3, the gain should be  7.82, compared with basic 1+age. */
         /* By adding 10 parameters more the gain should be 18.31 */
                           
         /* Starting the program with initial values given by a former maximization will simply change */
         /* the scales of the directions and the directions, because the are reset to canonical directions */
         /* Thus the first calls to linmin will give new points and better maximizations until fp-(*fret) is */
         /* under the tolerance value. If the tolerance is very small 1.e-9, it could last long.  */
   #ifdef DEBUG
         int k[2],l;
         k[0]=1;
         k[1]=-1;
         printf("Max: %.12e",(*func)(p));
         fprintf(ficlog,"Max: %.12e",(*func)(p));
         for (j=1;j<=n;j++) {
           printf(" %.12e",p[j]);
           fprintf(ficlog," %.12e",p[j]);
         }
         printf("\n");
         fprintf(ficlog,"\n");
         for(l=0;l<=1;l++) {
           for (j=1;j<=n;j++) {
             ptt[j]=p[j]+(p[j]-pt[j])*k[l];
             printf("l=%d j=%d ptt=%.12e, xits=%.12e, p=%.12e, xit=%.12e", l,j,ptt[j],xits[j],p[j],xit[j]);
             fprintf(ficlog,"l=%d j=%d ptt=%.12e, xits=%.12e, p=%.12e, xit=%.12e", l,j,ptt[j],xits[j],p[j],xit[j]);
           }
           printf("func(ptt)=%.12e, deriv=%.12e\n",(*func)(ptt),(ptt[j]-p[j])/((*func)(ptt)-(*func)(p)));
           fprintf(ficlog,"func(ptt)=%.12e, deriv=%.12e\n",(*func)(ptt),(ptt[j]-p[j])/((*func)(ptt)-(*func)(p)));
         }
   #endif
   
         free_vector(xit,1,n); 
         free_vector(xits,1,n); 
         free_vector(ptt,1,n); 
         free_vector(pt,1,n); 
         return; 
       } /* enough precision */ 
       if (*iter == ITMAX*n) nrerror("powell exceeding maximum iterations."); 
       for (j=1;j<=n;j++) { /* Computes the extrapolated point P_0 + 2 (P_n-P_0) */
         ptt[j]=2.0*p[j]-pt[j]; 
         xit[j]=p[j]-pt[j]; 
         pt[j]=p[j]; 
       } 
       fptt=(*func)(ptt); /* f_3 */
   #ifdef NODIRECTIONCHANGEDUNTILNITER  /* No change in drections until some iterations are done */
                   if (*iter <=4) {
   #else
   #endif
   #ifdef POWELLNOF3INFF1TEST    /* skips test F3 <F1 */
   #else
       if (fptt < fp) { /* If extrapolated point is better, decide if we keep that new direction or not */
   #endif
         /* (x1 f1=fp), (x2 f2=*fret), (x3 f3=fptt), (xm fm) */
         /* From x1 (P0) distance of x2 is at h and x3 is 2h */
         /* Let f"(x2) be the 2nd derivative equal everywhere.  */
         /* Then the parabolic through (x1,f1), (x2,f2) and (x3,f3) */
         /* will reach at f3 = fm + h^2/2 f"m  ; f" = (f1 -2f2 +f3 ) / h**2 */
         /* Conditional for using this new direction is that mu^2 = (f1-2f2+f3)^2 /2 < del or directest <0 */
         /* also  lamda^2=(f1-f2)^2/mu² is a parasite solution of powell */
         /* For powell, inclusion of this average direction is only if t(del)<0 or del inbetween mu^2 and lambda^2 */
         /* t=2.0*(fp-2.0*(*fret)+fptt)*SQR(fp-(*fret)-del)-del*SQR(fp-fptt); */
         /*  Even if f3 <f1, directest can be negative and t >0 */
         /* mu² and del² are equal when f3=f1 */
                           /* f3 < f1 : mu² < del <= lambda^2 both test are equivalent */
                           /* f3 < f1 : mu² < lambda^2 < del then directtest is negative and powell t is positive */
                           /* f3 > f1 : lambda² < mu^2 < del then t is negative and directest >0  */
                           /* f3 > f1 : lambda² < del < mu^2 then t is positive and directest >0  */
   #ifdef NRCORIGINAL
         t=2.0*(fp-2.0*(*fret)+fptt)*SQR(fp-(*fret)-del)- del*SQR(fp-fptt); /* Original Numerical Recipes in C*/
   #else
         t=2.0*(fp-2.0*(*fret)+fptt)*SQR(fp-(*fret)-del); /* Intel compiler doesn't work on one line; bug reported */
         t= t- del*SQR(fp-fptt);
   #endif
         directest = fp-2.0*(*fret)+fptt - 2.0 * del; /* If delta was big enough we change it for a new direction */
   #ifdef DEBUG
         printf("t1= %.12lf, t2= %.12lf, t=%.12lf  directest=%.12lf\n", 2.0*(fp-2.0*(*fret)+fptt)*SQR(fp-(*fret)-del),del*SQR(fp-fptt),t,directest);
         fprintf(ficlog,"t1= %.12lf, t2= %.12lf, t=%.12lf directest=%.12lf\n", 2.0*(fp-2.0*(*fret)+fptt)*SQR(fp-(*fret)-del),del*SQR(fp-fptt),t,directest);
         printf("t3= %.12lf, t4= %.12lf, t3*= %.12lf, t4*= %.12lf\n",SQR(fp-(*fret)-del),SQR(fp-fptt),
                (fp-(*fret)-del)*(fp-(*fret)-del),(fp-fptt)*(fp-fptt));
         fprintf(ficlog,"t3= %.12lf, t4= %.12lf, t3*= %.12lf, t4*= %.12lf\n",SQR(fp-(*fret)-del),SQR(fp-fptt),
                (fp-(*fret)-del)*(fp-(*fret)-del),(fp-fptt)*(fp-fptt));
         printf("tt= %.12lf, t=%.12lf\n",2.0*(fp-2.0*(*fret)+fptt)*(fp-(*fret)-del)*(fp-(*fret)-del)-del*(fp-fptt)*(fp-fptt),t);
         fprintf(ficlog, "tt= %.12lf, t=%.12lf\n",2.0*(fp-2.0*(*fret)+fptt)*(fp-(*fret)-del)*(fp-(*fret)-del)-del*(fp-fptt)*(fp-fptt),t);
   #endif
   #ifdef POWELLORIGINAL
         if (t < 0.0) { /* Then we use it for new direction */
   #else
         if (directest*t < 0.0) { /* Contradiction between both tests */
                                   printf("directest= %.12lf (if <0 we include P0 Pn as new direction), t= %.12lf, f1= %.12lf,f2= %.12lf,f3= %.12lf, del= %.12lf\n",directest, t, fp,(*fret),fptt,del);
           printf("f1-2f2+f3= %.12lf, f1-f2-del= %.12lf, f1-f3= %.12lf\n",fp-2.0*(*fret)+fptt, fp -(*fret) -del, fp-fptt);
           fprintf(ficlog,"directest= %.12lf (if directest<0 or t<0 we include P0 Pn as new direction), t= %.12lf, f1= %.12lf,f2= %.12lf,f3= %.12lf, del= %.12lf\n",directest, t, fp,(*fret),fptt, del);
           fprintf(ficlog,"f1-2f2+f3= %.12lf, f1-f2-del= %.12lf, f1-f3= %.12lf\n",fp-2.0*(*fret)+fptt, fp -(*fret) -del, fp-fptt);
         } 
         if (directest < 0.0) { /* Then we use it for new direction */
   #endif
   #ifdef DEBUGLINMIN
           printf("Before linmin in direction P%d-P0\n",n);
           for (j=1;j<=n;j++) {
             printf(" Before xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
             fprintf(ficlog," Before xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
             if(j % ncovmodel == 0){
               printf("\n");
               fprintf(ficlog,"\n");
             }
           }
   #endif
   #ifdef LINMINORIGINAL
           linmin(p,xit,n,fret,func); /* computes minimum on the extrapolated direction: changes p and rescales xit.*/
   #else
           linmin(p,xit,n,fret,func,&flat); /* computes minimum on the extrapolated direction: changes p and rescales xit.*/
           flatdir[i]=flat; /* Function is vanishing in that direction i */
   #endif
           
   #ifdef DEBUGLINMIN
           for (j=1;j<=n;j++) { 
             printf("After xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
             fprintf(ficlog,"After xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
             if(j % ncovmodel == 0){
               printf("\n");
               fprintf(ficlog,"\n");
             }
           }
   #endif
           for (j=1;j<=n;j++) { 
             xi[j][ibig]=xi[j][n]; /* Replace direction with biggest decrease by last direction n */
             xi[j][n]=xit[j];      /* and this nth direction by the by the average p_0 p_n */
           }
   #ifdef LINMINORIGINAL
   #else
           for (j=1, flatd=0;j<=n;j++) {
             if(flatdir[j]>0)
               flatd++;
           }
           if(flatd >0){
             printf("%d flat directions: ",flatd);
             fprintf(ficlog,"%d flat directions :",flatd);
             for (j=1;j<=n;j++) { 
               if(flatdir[j]>0){
                 printf("%d ",j);
                 fprintf(ficlog,"%d ",j);
               }
             }
             printf("\n");
             fprintf(ficlog,"\n");
   #ifdef FLATSUP
             free_vector(xit,1,n); 
             free_vector(xits,1,n); 
             free_vector(ptt,1,n); 
             free_vector(pt,1,n); 
             return;
   #endif
           }
   #endif
           printf("Gaining to use new average direction of P0 P%d instead of biggest increase direction %d :\n",n,ibig);
           fprintf(ficlog,"Gaining to use new average direction of P0 P%d instead of biggest increase direction %d :\n",n,ibig);
           
   #ifdef DEBUG
           printf("Direction changed  last moved %d in place of ibig=%d, new last is the average:\n",n,ibig);
           fprintf(ficlog,"Direction changed  last moved %d in place of ibig=%d, new last is the average:\n",n,ibig);
           for(j=1;j<=n;j++){
             printf(" %lf",xit[j]);
             fprintf(ficlog," %lf",xit[j]);
           }
           printf("\n");
           fprintf(ficlog,"\n");
   #endif
         } /* end of t or directest negative */
   #ifdef POWELLNOF3INFF1TEST
   #else
         } /* end if (fptt < fp)  */
   #endif
   #ifdef NODIRECTIONCHANGEDUNTILNITER  /* No change in drections until some iterations are done */
       } /*NODIRECTIONCHANGEDUNTILNITER  No change in drections until some iterations are done */
   #else
   #endif
                   } /* loop iteration */ 
   } 
     
   /**** Prevalence limit (stable or period prevalence)  ****************/
     
     double **prevalim(double **prlim, int nlstate, double x[], double age, double **oldm, double **savm, double ftolpl, int *ncvyear, int ij, int nres)
     {
       /**< Computes the prevalence limit in each live state at age x and for covariate combination ij . Nicely done
        *   (and selected quantitative values in nres)
        *  by left multiplying the unit
        *  matrix by transitions matrix until convergence is reached with precision ftolpl 
        * Wx= Wx-1 Px-1= Wx-2 Px-2 Px-1  = Wx-n Px-n ... Px-2 Px-1 I
        * Wx is row vector: population in state 1, population in state 2, population dead
        * or prevalence in state 1, prevalence in state 2, 0
        * newm is the matrix after multiplications, its rows are identical at a factor.
        * Inputs are the parameter, age, a tolerance for the prevalence limit ftolpl.
        * Output is prlim.
        * Initial matrix pimij 
        */
     /* {0.85204250825084937, 0.13044499163996345, 0.017512500109187184, */
     /* 0.090851990222114765, 0.88271245433047185, 0.026435555447413338, */
     /*  0,                   0                  , 1} */
     /*
      * and after some iteration: */
     /* {0.45504275246439968, 0.42731458730878791, 0.11764266022681241, */
     /*  0.45201005341706885, 0.42865420071559901, 0.11933574586733192, */
     /*  0,                   0                  , 1} */
     /* And prevalence by suppressing the deaths are close to identical rows in prlim: */
     /* {0.51571254859325999, 0.4842874514067399, */
     /*  0.51326036147820708, 0.48673963852179264} */
     /* If we start from prlim again, prlim tends to a constant matrix */
       
       int i, ii,j,k, k1;
     double *min, *max, *meandiff, maxmax,sumnew=0.;
     /* double **matprod2(); */ /* test */
     double **out, cov[NCOVMAX+1], **pmij(); /* **pmmij is a global variable feeded with oldms etc */
     double **newm;
     double agefin, delaymax=200. ; /* 100 Max number of years to converge */
     int ncvloop=0;
     int first=0;
     
     min=vector(1,nlstate);
     max=vector(1,nlstate);
     meandiff=vector(1,nlstate);
   
           /* Starting with matrix unity */
     for (ii=1;ii<=nlstate+ndeath;ii++)
       for (j=1;j<=nlstate+ndeath;j++){
         oldm[ii][j]=(ii==j ? 1.0 : 0.0);
       }
     
     cov[1]=1.;
     
     /* Even if hstepm = 1, at least one multiplication by the unit matrix */
     /* Start at agefin= age, computes the matrix of passage and loops decreasing agefin until convergence is reached */
     for(agefin=age-stepm/YEARM; agefin>=age-delaymax; agefin=agefin-stepm/YEARM){
       ncvloop++;
       newm=savm;
       /* Covariates have to be included here again */
       cov[2]=agefin;
        if(nagesqr==1){
         cov[3]= agefin*agefin;
        }
        /* Model(2)  V1 + V2 + V3 + V8 + V7*V8 + V5*V6 + V8*age + V3*age + age*age */
        /* total number of covariates of the model nbocc(+)+1 = 8 excepting constant and age and age*age */
        for(k1=1;k1<=cptcovt;k1++){ /* loop on model equation (including products) */ 
          if(Typevar[k1]==1){ /* A product with age */
            cov[2+nagesqr+k1]=precov[nres][k1]*cov[2];
          }else{
            cov[2+nagesqr+k1]=precov[nres][k1];
          }
        }/* End of loop on model equation */
        
   /* Start of old code (replaced by a loop on position in the model equation */
       /* for (k=1; k<=nsd;k++) { /\* For single dummy covariates only of the model *\/ */
       /*                  /\* 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,TvarsD[k])]; *\/ */
       /*   cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,TnsdVar[TvarsD[k]])]; */
       /*   /\* model = 1 +age + V1*V3 + age*V1 + V2 + V1 + age*V2 + V3 + V3*age + V1*V2  */
       /*    * k                  1        2      3    4      5      6     7        8 */
       /*    *cov[]   1    2      3        4      5    6      7      8     9       10 */
       /*    *TypeVar[k]          2        1      0    0      1      0     1        2 */
       /*    *Dummy[k]            0        2      0    0      2      0     2        0 */
       /*    *Tvar[k]             4        1      2    1      2      3     3        5 */
       /*    *nsd=3                              (1)  (2)           (3) */
       /*    *TvarsD[nsd]                      [1]=2    1             3 */
       /*    *TnsdVar                          [2]=2 [1]=1         [3]=3 */
       /*    *TvarsDind[nsd](=k)               [1]=3 [2]=4         [3]=6 */
       /*    *Tage[]                  [1]=1                  [2]=2      [3]=3 */
       /*    *Tvard[]       [1][1]=1                                           [2][1]=1 */
       /*    *                   [1][2]=3                                           [2][2]=2 */
       /*    *Tprod[](=k)     [1]=1                                              [2]=8 */
       /*    *TvarsDp(=Tvar)   [1]=1            [2]=2             [3]=3          [4]=5 */
       /*    *TvarD (=k)       [1]=1            [2]=3 [3]=4       [3]=6          [4]=6 */
       /*    *TvarsDpType */
       /*    *si model= 1 + age + V3 + V2*age + V2 + V3*age */
       /*    * nsd=1              (1)           (2) */
       /*    *TvarsD[nsd]          3             2 */
       /*    *TnsdVar           (3)=1          (2)=2 */
       /*    *TvarsDind[nsd](=k)  [1]=1        [2]=3 */
       /*    *Tage[]                  [1]=2           [2]= 3    */
       /*    *\/ */
       /*   /\* cov[++k1]=nbcode[TvarsD[k]][codtabm(ij,k)]; *\/ */
       /*   /\* printf("prevalim Dummy combi=%d k=%d TvarsD[%d]=V%d TvarsDind[%d]=%d nbcode=%d cov=%lf codtabm(%d,Tvar[%d])=%d \n",ij,k, k, TvarsD[k],k,TvarsDind[k],nbcode[TvarsD[k]][codtabm(ij,k)],cov[2+nagesqr+TvarsDind[k]], ij, k, codtabm(ij,k)); *\/ */
       /* } */
       /* for (k=1; k<=nsq;k++) { /\* For single quantitative varying covariates only of the model *\/ */
       /*                  /\* Here comes the value of quantitative after renumbering k with single quantitative covariates *\/ */
       /*   /\* Tqresult[nres][result_position]= value of the variable at the result_position in the nres resultline                                 *\/ */
       /*   /\* cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k]; *\/ */
       /*   cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][resultmodel[nres][k1]] */
       /*   /\* cov[++k1]=Tqresult[nres][k];  *\/ */
       /*   /\* printf("prevalim Quantitative k=%d  TvarsQind[%d]=%d, TvarsQ[%d]=V%d,Tqresult[%d][%d]=%f\n",k,k,TvarsQind[k],k,TvarsQ[k],nres,k,Tqresult[nres][k]); *\/ */
       /* } */
       /* for (k=1; k<=cptcovage;k++){  /\* For product with age *\/ */
       /*   if(Dummy[Tage[k]]==2){ /\* dummy with age *\/ */
       /*  cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,Tvar[Tage[k]])]*cov[2]; */
       /*  /\* cov[++k1]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2]; *\/ */
       /*   } else if(Dummy[Tage[k]]==3){ /\* quantitative with age *\/ */
       /*  cov[2+nagesqr+Tage[k]]=Tqresult[nres][k]; */
       /*  /\* cov[++k1]=Tqresult[nres][k];  *\/ */
       /*   } */
       /*   /\* printf("prevalim Age combi=%d k=%d  Tage[%d]=V%d Tqresult[%d][%d]=%f\n",ij,k,k,Tage[k],nres,k,Tqresult[nres][k]); *\/ */
       /* } */
       /* for (k=1; k<=cptcovprod;k++){ /\* For product without age *\/ */
       /*   /\* printf("prevalim Prod ij=%d k=%d  Tprod[%d]=%d Tvard[%d][1]=V%d, Tvard[%d][2]=V%d\n",ij,k,k,Tprod[k], k,Tvard[k][1], k,Tvard[k][2]); *\/ */
       /*   if(Dummy[Tvard[k][1]]==0){ */
       /*  if(Dummy[Tvard[k][2]]==0){ */
       /*    cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])]; */
       /*    /\* cov[++k1]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)]; *\/ */
       /*  }else{ */
       /*    cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * Tqresult[nres][k]; */
       /*    /\* cov[++k1]=nbcode[Tvard[k][1]][codtabm(ij,k)] * Tqresult[nres][k]; *\/ */
       /*  } */
       /*   }else{ */
       /*  if(Dummy[Tvard[k][2]]==0){ */
       /*    cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])] * Tqinvresult[nres][Tvard[k][1]]; */
       /*    /\* cov[++k1]=nbcode[Tvard[k][2]][codtabm(ij,k)] * Tqinvresult[nres][Tvard[k][1]]; *\/ */
       /*  }else{ */
       /*    cov[2+nagesqr+Tprod[k]]=Tqinvresult[nres][Tvard[k][1]]*  Tqinvresult[nres][Tvard[k][2]]; */
       /*    /\* cov[++k1]=Tqinvresult[nres][Tvard[k][1]]*  Tqinvresult[nres][Tvard[k][2]]; *\/ */
       /*  } */
       /*   } */
       /* } /\* End product without age *\/ */
   /* ENd of old code */
       /*printf("ij=%d cptcovprod=%d tvar=%d ", ij, cptcovprod, Tvar[1]);*/
       /*printf("ij=%d cov[3]=%lf cov[4]=%lf \n",ij, cov[3],cov[4]);*/
       /*printf("ij=%d cov[3]=%lf \n",ij, cov[3]);*/
       /* savm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
       /* out=matprod2(newm, pmij(pmmij,cov,ncovmodel,x,nlstate),1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); /\* Bug Valgrind *\/ */
       /* age and covariate values of ij are in 'cov' */
       out=matprod2(newm, pmij(pmmij,cov,ncovmodel,x,nlstate),1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); /* Bug Valgrind */
       
       savm=oldm;
       oldm=newm;
   
       for(j=1; j<=nlstate; j++){
         max[j]=0.;
         min[j]=1.;
       }
       for(i=1;i<=nlstate;i++){
         sumnew=0;
         for(k=1; k<=ndeath; k++) sumnew+=newm[i][nlstate+k];
         for(j=1; j<=nlstate; j++){ 
           prlim[i][j]= newm[i][j]/(1-sumnew);
           max[j]=FMAX(max[j],prlim[i][j]);
           min[j]=FMIN(min[j],prlim[i][j]);
         }
       }
   
       maxmax=0.;
       for(j=1; j<=nlstate; j++){
         meandiff[j]=(max[j]-min[j])/(max[j]+min[j])*2.; /* mean difference for each column */
         maxmax=FMAX(maxmax,meandiff[j]);
         /* printf(" age= %d meandiff[%d]=%f, agefin=%d max[%d]=%f min[%d]=%f maxmax=%f\n", (int)age, j, meandiff[j],(int)agefin, j, max[j], j, min[j],maxmax); */
       } /* j loop */
       *ncvyear= (int)age- (int)agefin;
       /* printf("maxmax=%lf maxmin=%lf ncvloop=%d, age=%d, agefin=%d ncvyear=%d \n", maxmax, maxmin, ncvloop, (int)age, (int)agefin, *ncvyear); */
       if(maxmax < ftolpl){
         /* printf("maxmax=%lf ncvloop=%ld, age=%d, agefin=%d ncvyear=%d \n", maxmax, ncvloop, (int)age, (int)agefin, *ncvyear); */
         free_vector(min,1,nlstate);
         free_vector(max,1,nlstate);
         free_vector(meandiff,1,nlstate);
         return prlim;
       }
     } /* agefin loop */
       /* After some age loop it doesn't converge */
     if(!first){
       first=1;
       printf("Warning: the stable prevalence at age %d did not converge with the required precision (%g > ftolpl=%g) within %.d years and %d loops. Try to lower 'ftolpl'. Youngest age to start was %d=(%d-%d). Others in log file only...\n", (int)age, maxmax, ftolpl, *ncvyear, ncvloop, (int)(agefin+stepm/YEARM),  (int)(age-stepm/YEARM), (int)delaymax);
       fprintf(ficlog, "Warning: the stable prevalence at age %d did not converge with the required precision (%g > ftolpl=%g) within %.d years and %d loops. Try to lower 'ftolpl'. Youngest age to start was %d=(%d-%d).\n", (int)age, maxmax, ftolpl, *ncvyear, ncvloop, (int)(agefin+stepm/YEARM),  (int)(age-stepm/YEARM), (int)delaymax);
     }else if (first >=1 && first <10){
       fprintf(ficlog, "Warning: the stable prevalence at age %d did not converge with the required precision (%g > ftolpl=%g) within %.d years and %d loops. Try to lower 'ftolpl'. Youngest age to start was %d=(%d-%d).\n", (int)age, maxmax, ftolpl, *ncvyear, ncvloop, (int)(agefin+stepm/YEARM),  (int)(age-stepm/YEARM), (int)delaymax);
       first++;
     }else if (first ==10){
       fprintf(ficlog, "Warning: the stable prevalence at age %d did not converge with the required precision (%g > ftolpl=%g) within %.d years and %d loops. Try to lower 'ftolpl'. Youngest age to start was %d=(%d-%d).\n", (int)age, maxmax, ftolpl, *ncvyear, ncvloop, (int)(agefin+stepm/YEARM),  (int)(age-stepm/YEARM), (int)delaymax);
       printf("Warning: the stable prevalence dit not converge. This warning came too often, IMaCh will stop notifying, even in its log file. Look at the graphs to appreciate the non convergence.\n");
       fprintf(ficlog,"Warning: the stable prevalence no convergence; too many cases, giving up noticing, even in log file\n");
       first++;
     }
   
     /* Try to lower 'ftol', for example from 1.e-8 to 6.e-9.\n", ftolpl, (int)age, (int)delaymax, (int)agefin, ncvloop, (int)age-(int)agefin); */
     free_vector(min,1,nlstate);
     free_vector(max,1,nlstate);
     free_vector(meandiff,1,nlstate);
     
     return prlim; /* should not reach here */
   }
   
   
    /**** Back Prevalence limit (stable or period prevalence)  ****************/
   
    /* double **bprevalim(double **bprlim, double ***prevacurrent, int nlstate, double x[], double age, double ageminpar, double agemaxpar, double **oldm, double **savm, double **dnewm, double **doldm, double **dsavm, double ftolpl, int *ncvyear, int ij) */
    /* double **bprevalim(double **bprlim, double ***prevacurrent, int nlstate, double x[], double age, double **oldm, double **savm, double **dnewm, double **doldm, double **dsavm, double ftolpl, int *ncvyear, int ij) */
     double **bprevalim(double **bprlim, double ***prevacurrent, int nlstate, double x[], double age, double ftolpl, int *ncvyear, int ij, int nres)
   {
     /* Computes the prevalence limit in each live state at age x and for covariate combination ij (<=2**cptcoveff) by left multiplying the unit
        matrix by transitions matrix until convergence is reached with precision ftolpl */
     /* Wx= Wx-1 Px-1= Wx-2 Px-2 Px-1  = Wx-n Px-n ... Px-2 Px-1 I */
     /* Wx is row vector: population in state 1, population in state 2, population dead */
     /* or prevalence in state 1, prevalence in state 2, 0 */
     /* newm is the matrix after multiplications, its rows are identical at a factor */
     /* Initial matrix pimij */
     /* {0.85204250825084937, 0.13044499163996345, 0.017512500109187184, */
     /* 0.090851990222114765, 0.88271245433047185, 0.026435555447413338, */
     /*  0,                   0                  , 1} */
     /*
      * and after some iteration: */
     /* {0.45504275246439968, 0.42731458730878791, 0.11764266022681241, */
     /*  0.45201005341706885, 0.42865420071559901, 0.11933574586733192, */
     /*  0,                   0                  , 1} */
     /* And prevalence by suppressing the deaths are close to identical rows in prlim: */
     /* {0.51571254859325999, 0.4842874514067399, */
     /*  0.51326036147820708, 0.48673963852179264} */
     /* If we start from prlim again, prlim tends to a constant matrix */
   
     int i, ii,j,k, k1;
     int first=0;
     double *min, *max, *meandiff, maxmax,sumnew=0.;
     /* double **matprod2(); */ /* test */
     double **out, cov[NCOVMAX+1], **bmij();
     double **newm;
     double         **dnewm, **doldm, **dsavm;  /* for use */
     double         **oldm, **savm;  /* for use */
   
     double agefin, delaymax=200. ; /* 100 Max number of years to converge */
     int ncvloop=0;
     
     min=vector(1,nlstate);
     max=vector(1,nlstate);
     meandiff=vector(1,nlstate);
   
     dnewm=ddnewms; doldm=ddoldms; dsavm=ddsavms;
     oldm=oldms; savm=savms;
     
     /* Starting with matrix unity */
     for (ii=1;ii<=nlstate+ndeath;ii++)
       for (j=1;j<=nlstate+ndeath;j++){
         oldm[ii][j]=(ii==j ? 1.0 : 0.0);
       }
     
     cov[1]=1.;
     
     /* Even if hstepm = 1, at least one multiplication by the unit matrix */
     /* Start at agefin= age, computes the matrix of passage and loops decreasing agefin until convergence is reached */
     /* for(agefin=age+stepm/YEARM; agefin<=age+delaymax; agefin=agefin+stepm/YEARM){ /\* A changer en age *\/ */
     /* for(agefin=age; agefin<AGESUP; agefin=agefin+stepm/YEARM){ /\* A changer en age *\/ */
     for(agefin=age; agefin<FMIN(AGESUP,age+delaymax); agefin=agefin+stepm/YEARM){ /* A changer en age */
       ncvloop++;
       newm=savm; /* oldm should be kept from previous iteration or unity at start */
                   /* newm points to the allocated table savm passed by the function it can be written, savm could be reallocated */
       /* Covariates have to be included here again */
       cov[2]=agefin;
       if(nagesqr==1){
         cov[3]= agefin*agefin;;
       }
       for(k1=1;k1<=cptcovt;k1++){ /* loop on model equation (including products) */ 
         if(Typevar[k1]==1){ /* A product with age */
           cov[2+nagesqr+k1]=precov[nres][k1]*cov[2];
         }else{
           cov[2+nagesqr+k1]=precov[nres][k1];
         }
       }/* End of loop on model equation */
   
   /* Old code */ 
   
       /* 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,TvarsD[k])]; */
       /*   /\* printf("bprevalim Dummy agefin=%.0f combi=%d k=%d TvarsD[%d]=V%d TvarsDind[%d]=%d nbcode=%d cov[%d]=%lf codtabm(%d,Tvar[%d])=%d \n",agefin,ij,k, k, TvarsD[k],k,TvarsDind[k],nbcode[TvarsD[k]][codtabm(ij,k)],2+nagesqr+TvarsDind[k],cov[2+nagesqr+TvarsDind[k]], ij, k, codtabm(ij,k)); *\/ */
       /* } */
       /* /\* for (k=1; k<=cptcovn;k++) { *\/ */
       /* /\*   /\\* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,Tvar[k])]; *\\/ *\/ */
       /* /\*   cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,k)]; *\/ */
       /* /\*   /\\* printf("prevalim ij=%d k=%d Tvar[%d]=%d nbcode=%d cov=%lf codtabm(%d,Tvar[%d])=%d \n",ij,k, k, Tvar[k],nbcode[Tvar[k]][codtabm(ij,Tvar[k])],cov[2+k], ij, k, codtabm(ij,Tvar[k])]); *\\/ *\/ */
       /* /\* } *\/ */
       /* for (k=1; k<=nsq;k++) { /\* For single varying covariates only *\/ */
       /*                  /\* Here comes the value of quantitative after renumbering k with single quantitative covariates *\/ */
       /*   cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k];  */
       /*   /\* printf("prevalim Quantitative k=%d  TvarsQind[%d]=%d, TvarsQ[%d]=V%d,Tqresult[%d][%d]=%f\n",k,k,TvarsQind[k],k,TvarsQ[k],nres,k,Tqresult[nres][k]); *\/ */
       /* } */
       /* /\* for (k=1; k<=cptcovage;k++) cov[2+nagesqr+Tage[k]]=nbcode[Tvar[k]][codtabm(ij,k)]*cov[2]; *\/ */
       /* /\* for (k=1; k<=cptcovprod;k++) /\\* Useless *\\/ *\/ */
       /* /\*   /\\* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])]; *\\/ *\/ */
       /* /\*   cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)]; *\/ */
       /* for (k=1; k<=cptcovage;k++){  /\* For product with age *\/ */
       /*   /\* if(Dummy[Tvar[Tage[k]]]== 2){ /\\* dummy with age *\\/ ERROR ???*\/ */
       /*   if(Dummy[Tage[k]]== 2){ /\* dummy with age *\/ */
       /*  cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,Tvar[Tage[k]])]*cov[2]; */
       /*   } else if(Dummy[Tage[k]]== 3){ /\* quantitative with age *\/ */
       /*  cov[2+nagesqr+Tage[k]]=Tqresult[nres][k]; */
       /*   } */
       /*   /\* printf("prevalim Age combi=%d k=%d  Tage[%d]=V%d Tqresult[%d][%d]=%f\n",ij,k,k,Tage[k],nres,k,Tqresult[nres][k]); *\/ */
       /* } */
       /* for (k=1; k<=cptcovprod;k++){ /\* For product without age *\/ */
       /*   /\* printf("prevalim Prod ij=%d k=%d  Tprod[%d]=%d Tvard[%d][1]=V%d, Tvard[%d][2]=V%d\n",ij,k,k,Tprod[k], k,Tvard[k][1], k,Tvard[k][2]); *\/ */
       /*   if(Dummy[Tvard[k][1]]==0){ */
       /*  if(Dummy[Tvard[k][2]]==0){ */
       /*    cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])]; */
       /*  }else{ */
       /*    cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * Tqresult[nres][k]; */
       /*  } */
       /*   }else{ */
       /*  if(Dummy[Tvard[k][2]]==0){ */
       /*    cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])] * Tqinvresult[nres][Tvard[k][1]]; */
       /*  }else{ */
       /*    cov[2+nagesqr+Tprod[k]]=Tqinvresult[nres][Tvard[k][1]]*  Tqinvresult[nres][Tvard[k][2]]; */
       /*  } */
       /*   } */
       /* } */
       
       /*printf("ij=%d cptcovprod=%d tvar=%d ", ij, cptcovprod, Tvar[1]);*/
       /*printf("ij=%d cov[3]=%lf cov[4]=%lf \n",ij, cov[3],cov[4]);*/
       /*printf("ij=%d cov[3]=%lf \n",ij, cov[3]);*/
       /* savm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
       /* out=matprod2(newm, pmij(pmmij,cov,ncovmodel,x,nlstate),1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); /\* Bug Valgrind *\/ */
                   /* ij should be linked to the correct index of cov */
                   /* age and covariate values ij are in 'cov', but we need to pass
                    * ij for the observed prevalence at age and status and covariate
                    * number:  prevacurrent[(int)agefin][ii][ij]
                    */
       /* out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, bmij(pmmij,cov,ncovmodel,x,nlstate,prevacurrent, ageminpar, agemaxpar, dnewm, doldm, dsavm,ij)); /\* Bug Valgrind *\/ */
       /* out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, bmij(pmmij,cov,ncovmodel,x,nlstate,prevacurrent, dnewm, doldm, dsavm,ij)); /\* Bug Valgrind *\/ */
       out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, bmij(pmmij,cov,ncovmodel,x,nlstate,prevacurrent,ij)); /* Bug Valgrind */
       /* if((int)age == 86 || (int)age == 87){ */
       /*   printf(" Backward prevalim age=%d agefin=%d \n", (int) age, (int) agefin); */
       /*   for(i=1; i<=nlstate+ndeath; i++) { */
       /*  printf("%d newm= ",i); */
       /*  for(j=1;j<=nlstate+ndeath;j++) { */
       /*    printf("%f ",newm[i][j]); */
       /*  } */
       /*  printf("oldm * "); */
       /*  for(j=1;j<=nlstate+ndeath;j++) { */
       /*    printf("%f ",oldm[i][j]); */
       /*  } */
       /*  printf(" bmmij "); */
       /*  for(j=1;j<=nlstate+ndeath;j++) { */
       /*    printf("%f ",pmmij[i][j]); */
       /*  } */
       /*  printf("\n"); */
       /*   } */
       /* } */
       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, could be nan! */
         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); */
       } /* i 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;
       }
     } /* agefin 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 (after stepm years) 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] or probability to be observed in j being in i according to
        the values of the covariates cov[nc] and corresponding parameter values x[nc+shiftij]
        Sum on j ps[i][j] should equal to 1.
     */
     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("Debug pmij() i=%d j=%d nc=%d s1=%.17f, lnpijopii=%.17f\n",i,j,nc, 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) */
         /* printf("Debug pmij() i=%d j=%d nc=%d s1=%.17f, lnpijopii=%.17f\n",i,j,nc, s1,lnpijopii); */
       }
     }
     
     for(i=1; i<= nlstate; i++){
       s1=0;
       for(j=1; j<i; j++){
         /* printf("debug1 %d %d ps=%lf exp(ps)=%lf \n",i,j,ps[i][j],exp(ps[i][j])); */
         s1+=exp(ps[i][j]); /* In fact sums pij/pii */
       }
       for(j=i+1; j<=nlstate+ndeath; j++){
         /* printf("debug2 %d %d ps=%lf exp(ps)=%lf \n",i,j,ps[i][j],exp(ps[i][j])); */
         s1+=exp(ps[i][j]); /* In fact sums pij/pii */
       }
       /* 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];/* Bug valgrind */
       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; /* Pointer is unchanged since its call */
   }
   
   /*************** 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, cov[2], and covariate combination 'ij'. In fact cov is already filled and x too.
      * Call to pmij(cov and x), call to cross prevalence, sums and inverses, left multiply, and returns in **ps as well as **bmij.
      */
     int i, ii, j,k;
     
     double **out, **pmij();
     double sumnew=0.;
     double agefin;
     double k3=0.; /* constant of the w_x diagonal matrix (in order for B to sum to 1 even for death state) */
     double **dnewm, **dsavm, **doldm;
     double **bbmij;
     
     doldm=ddoldms; /* global pointers */
     dnewm=ddnewms;
     dsavm=ddsavms;
   
     /* Debug */
     /* printf("Bmij ij=%d, cov[2}=%f\n", ij, cov[2]); */
     agefin=cov[2];
     /* Bx = Diag(w_x) P_x Diag(Sum_i w^i_x p^ij_x */
     /* bmij *//* age is cov[2], ij is included in cov, but we need for
        the observed prevalence (with this covariate ij) at beginning of transition */
     /* dsavm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
   
     /* P_x */
     pmmij=pmij(pmmij,cov,ncovmodel,x,nlstate); /*This is forward probability from agefin to agefin + stepm *//* Bug valgrind */
     /* outputs pmmij which is a stochastic matrix in row */
   
     /* Diag(w_x) */
     /* Rescaling the cross-sectional prevalence: Problem with prevacurrent which can be zero */
     sumnew=0.;
     /*for (ii=1;ii<=nlstate+ndeath;ii++){*/
     for (ii=1;ii<=nlstate;ii++){ /* Only on live states */
       /* printf(" agefin=%d, ii=%d, ij=%d, prev=%f\n",(int)agefin,ii, ij, prevacurrent[(int)agefin][ii][ij]); */
       sumnew+=prevacurrent[(int)agefin][ii][ij];
     }
     if(sumnew >0.01){  /* At least some value in the prevalence */
       for (ii=1;ii<=nlstate+ndeath;ii++){
         for (j=1;j<=nlstate+ndeath;j++)
           doldm[ii][j]=(ii==j ? prevacurrent[(int)agefin][ii][ij]/sumnew : 0.0);
       }
     }else{
       for (ii=1;ii<=nlstate+ndeath;ii++){
         for (j=1;j<=nlstate+ndeath;j++)
         doldm[ii][j]=(ii==j ? 1./nlstate : 0.0);
       }
       /* if(sumnew <0.9){ */
       /*   printf("Problem internal bmij B: sum on i wi <0.9: j=%d, sum_i wi=%lf,agefin=%d\n",j,sumnew, (int)agefin); */
       /* } */
     }
     k3=0.0;  /* We put the last diagonal to 0 */
     for (ii=nlstate+1;ii<=nlstate+ndeath;ii++){
         doldm[ii][ii]= k3;
     }
     /* End doldm, At the end doldm is diag[(w_i)] */
     
     /* Left product of this diag matrix by pmmij=Px (dnewm=dsavm*doldm): diag[(w_i)*Px */
     bbmij=matprod2(dnewm, doldm,1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, pmmij); /* was a Bug Valgrind */
   
     /* Diag(Sum_i w^i_x p^ij_x, should be the prevalence at age x+stepm */
     /* w1 p11 + w2 p21 only on live states N1./N..*N11/N1. + N2./N..*N21/N2.=(N11+N21)/N..=N.1/N.. */
     for (j=1;j<=nlstate+ndeath;j++){
       sumnew=0.;
       for (ii=1;ii<=nlstate;ii++){
         /* sumnew+=dsavm[ii][j]*prevacurrent[(int)agefin][ii][ij]; */
         sumnew+=pmmij[ii][j]*doldm[ii][ii]; /* Yes prevalence at beginning of transition */
       } /* sumnew is (N11+N21)/N..= N.1/N.. = sum on i of w_i pij */
       for (ii=1;ii<=nlstate+ndeath;ii++){
           /* if(agefin >= agemaxpar && agefin <= agemaxpar+stepm/YEARM){ */
           /*      dsavm[ii][j]=(ii==j ? 1./sumnew : 0.0); */
           /* }else if(agefin >= agemaxpar+stepm/YEARM){ */
           /*      dsavm[ii][j]=(ii==j ? 1./sumnew : 0.0); */
           /* }else */
         dsavm[ii][j]=(ii==j ? 1./sumnew : 0.0);
       } /*End ii */
     } /* End j, At the end dsavm is diag[1/(w_1p1i+w_2 p2i)] for ALL states even if the sum is only for live states */
   
     ps=matprod2(ps, dnewm,1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, dsavm); /* was a Bug Valgrind */
     /* ps is now diag[w_i] * Px * diag [1/(w_1p1i+w_2 p2i)] */
     /* end bmij */
     return ps; /*pointer is unchanged */
   }
   /*************** 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 prevbcast */ /* 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 )
   {
     /* Already optimized with precov.
        Computes the transition matrix starting at age 'age' and dummies values in each resultline (loop on ij to find the corresponding combination) to 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, k1;
     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;
         }
         /* Model(2)  V1 + V2 + V3 + V8 + V7*V8 + V5*V6 + V8*age + V3*age + age*age */
         /* total number of covariates of the model nbocc(+)+1 = 8 excepting constant and age and age*age */
         for(k1=1;k1<=cptcovt;k1++){ /* loop on model equation (including products) */ 
           if(Typevar[k1]==1){ /* A product with age */
             cov[2+nagesqr+k1]=precov[nres][k1]*cov[2];
           }else{
             cov[2+nagesqr+k1]=precov[nres][k1];
           }
         }/* End of loop on model equation */
           /* Old code */ 
   /*      if( Dummy[k1]==0 && Typevar[k1]==0 ){ /\* Single dummy  *\/ */
   /* /\*     V(Tvarsel)=Tvalsel=Tresult[nres][pos](value); V(Tvresult[nres][pos] (variable): V(variable)=value) *\/ */
   /* /\*       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 *\\/ *\/ */
   /*      /\* codtabm(ij,k)  (1 & (ij-1) >> (k-1))+1 *\/ */
   /* /\*             V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 *\/ */
   /* /\*    k        1  2   3   4     5    6    7     8    9 *\/ */
   /* /\*Tvar[k]=     5  4   3   6     5    2    7     1    1 *\/ */
   /* /\*    nsd         1   2                              3 *\/ /\* Counting single dummies covar fixed or tv *\/ */
   /* /\*TvarsD[nsd]     4   3                              1 *\/ /\* ID of single dummy cova fixed or timevary*\/ */
   /* /\*TvarsDind[k]    2   3                              9 *\/ /\* position K of single dummy cova *\/ */
   /*        /\* cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,k)];or [codtabm(ij,TnsdVar[TvarsD[k]] *\/ */
   /*        cov[2+nagesqr+k1]=Tresult[nres][resultmodel[nres][k1]]; */
   /*        /\* printf("hpxij Dummy combi=%d k=%d TvarsD[%d]=V%d TvarsDind[%d]=%d nbcode=%d cov=%lf codtabm(%d,TnsdVar[TvarsD[%d])=%d \n",ij,k, k, TvarsD[k],k,TvarsDind[k],nbcode[TvarsD[k]][codtabm(ij,TnsdVar[TvarsD[k]])],cov[2+nagesqr+TvarsDind[k]], ij, k, codtabm(ij,TnsdVar[TvarsD[k]])); *\/ */
   /*        printf("hpxij Dummy combi=%d k1=%d Tvar[%d]=V%d cov[2+%d+%d]=%lf resultmodel[nres][%d]=%d nres/nresult=%d/%d \n",ij,k1,k1, Tvar[k1],nagesqr,k1,cov[2+nagesqr+k1],k1,resultmodel[nres][k1],nres,nresult); */
   /*        printf("hpxij new Dummy precov[nres=%d][k1=%d]=%.4f\n", nres, k1, precov[nres][k1]); */
   /*      }else if( Dummy[k1]==1 && Typevar[k1]==0 ){ /\* Single quantitative variables  *\/ */
   /*        /\* resultmodel[nres][k1]=k3: k1th position in the model correspond to the k3 position in the resultline *\/ */
   /*        cov[2+nagesqr+k1]=Tqresult[nres][resultmodel[nres][k1]];  */
   /*        /\* 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 k1=%d resultmodel[nres][%d]=%d,Tqresult[%d][%d]=%f\n",k1,k1,resultmodel[nres][k1],nres,resultmodel[nres][k1],Tqresult[nres][resultmodel[nres][k1]]); */
   /*        printf("hpxij new Quanti precov[nres=%d][k1=%d]=%.4f\n", nres, k1, precov[nres][k1]); */
   /*      }else if( Dummy[k1]==2 ){ /\* For dummy with age product *\/ */
   /*        /\* Tvar[k1] Variable in the age product age*V1 is 1 *\/ */
   /*        /\* [Tinvresult[nres][V1] is its value in the resultline nres *\/ */
   /*        cov[2+nagesqr+k1]=TinvDoQresult[nres][Tvar[k1]]*cov[2]; */
   /*        printf("DhPxij Dummy with age k1=%d Tvar[%d]=%d TinvDoQresult[nres=%d][%d]=%.f age=%.2f,cov[2+%d+%d]=%.3f\n",k1,k1,Tvar[k1],nres,TinvDoQresult[nres][Tvar[k1]],cov[2],nagesqr,k1,cov[2+nagesqr+k1]); */
   /*        printf("hpxij new Dummy with age product precov[nres=%d][k1=%d]=%.4f * age=%.2f\n", nres, k1, precov[nres][k1], cov[2]); */
   
   /*        /\* cov[2+nagesqr+k1]=Tresult[nres][resultmodel[nres][k1]];    *\/ */
   /*        /\* for (k=1; k<=cptcovage;k++){ /\\* For product with age V1+V1*age +V4 +age*V3 *\\/ *\/ */
   /*        /\* 1+2 Tage[1]=2 TVar[2]=1 Dummy[2]=2, Tage[2]=4 TVar[4]=3 Dummy[4]=3 quant*\/ */
   /*        /\* *\/ */
   /* /\*             V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 *\/ */
   /* /\*    k        1  2   3   4     5    6    7     8    9 *\/ */
   /* /\*Tvar[k]=     5  4   3   6     5    2    7     1    1 *\/ */
   /* /\*cptcovage=2                   1               2      *\/ */
   /* /\*Tage[k]=                      5               8      *\/   */
   /*      }else if( Dummy[k1]==3 ){ /\* For quant with age product *\/ */
   /*        cov[2+nagesqr+k1]=Tresult[nres][resultmodel[nres][k1]];        */
   /*        printf("QhPxij Quant with age k1=%d resultmodel[nres][%d]=%d,Tqresult[%d][%d]=%f\n",k1,k1,resultmodel[nres][k1],nres,resultmodel[nres][k1],Tqresult[nres][resultmodel[nres][k1]]); */
   /*        printf("hpxij new Quanti with age product precov[nres=%d][k1=%d] * age=%.2f\n", nres, k1, precov[nres][k1], cov[2]); */
   /*        /\* if(Dummy[Tage[k]]== 2){ /\\* dummy with age *\\/ *\/ */
   /*        /\* /\\* if(Dummy[Tvar[Tage[k]]]== 2){ /\\\* dummy with age *\\\/ *\\/ *\/ */
   /*        /\*   /\\* 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,TnsdVar[TvarsD[Tvar[Tage[k]]]])]*cov[2]; *\\/ *\/ */
   /*        /\*   cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,TnsdVar[TvarsD[Tvar[Tage[k]]]])]*cov[2]; *\/ */
   /*        /\*   printf("hPxij Age combi=%d k=%d cptcovage=%d Tage[%d]=%d Tvar[Tage[%d]]=V%d nbcode[Tvar[Tage[k]]][codtabm(ij,TnsdVar[Tvar[Tage[k]]]])]=%d nres=%d\n",ij,k,cptcovage,k,Tage[k],k,Tvar[Tage[k]], nbcode[Tvar[Tage[k]]][codtabm(ij,TnsdVar[Tvar[Tage[k]]])],nres); *\/ */
   /*        /\* } else if(Dummy[Tage[k]]== 3){ /\\* quantitative with age *\\/ *\/ */
   /*        /\*   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]); *\/ */
   /*      }else if(Typevar[k1]==2 ){ /\* For product (not with age) *\/ */
   /* /\*       for (k=1; k<=cptcovprod;k++){ /\\*  For product without age *\\/ *\/ */
   /* /\* /\\*             V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 *\\/ *\/ */
   /* /\* /\\*    k        1  2   3   4     5    6    7     8    9 *\\/ *\/ */
   /* /\* /\\*Tvar[k]=     5  4   3   6     5    2    7     1    1 *\\/ *\/ */
   /* /\* /\\*cptcovprod=1            1               2            *\\/ *\/ */
   /* /\* /\\*Tprod[]=                4               7            *\\/ *\/ */
   /* /\* /\\*Tvard[][1]             4               1             *\\/ *\/ */
   /* /\* /\\*Tvard[][2]               3               2           *\\/ *\/ */
             
   /*        /\* printf("hPxij Prod ij=%d k=%d  Tprod[%d]=%d Tvard[%d][1]=V%d, Tvard[%d][2]=V%d nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])]=%d nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][1])]=%d\n",ij,k,k,Tprod[k], k,Tvard[k][1], k,Tvard[k][2],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)]; *\/ */
   /*        cov[2+nagesqr+k1]=TinvDoQresult[nres][Tvardk[k1][1]] * TinvDoQresult[nres][Tvardk[k1][2]];     */
   /*        printf("hPxij Prod ij=%d k1=%d  cov[2+%d+%d]=%.5f Tvard[%d][1]=V%d * Tvard[%d][2]=V%d ; TinvDoQresult[nres][Tvardk[k1][1]]=%.4f * TinvDoQresult[nres][Tvardk[k1][1]]=%.4f\n",ij,k1,nagesqr,k1,cov[2+nagesqr+k1],k1,Tvardk[k1][1], k1,Tvardk[k1][2], TinvDoQresult[nres][Tvardk[k1][1]], TinvDoQresult[nres][Tvardk[k1][2]]); */
   /*        printf("hpxij new Product no age product precov[nres=%d][k1=%d]=%.4f\n", nres, k1, precov[nres][k1]); */
   
   /*        /\* if(Dummy[Tvardk[k1][1]]==0){ *\/ */
   /*        /\*   if(Dummy[Tvardk[k1][2]]==0){ /\\* Product of dummies *\\/ *\/ */
   /*            /\* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)]; *\/ */
   /*            /\* cov[2+nagesqr+k1]=Tinvresult[nres][Tvardk[k1][1]] * Tinvresult[nres][Tvardk[k1][2]];   *\/ */
   /*            /\* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,TnsdVar[Tvard[k][1]])] * nbcode[Tvard[k][2]][codtabm(ij,TnsdVar[Tvard[k][2]])]; *\/ */
   /*          /\* }else{ /\\* Product of dummy by quantitative *\\/ *\/ */
   /*            /\* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,TnsdVar[Tvard[k][1]])] * Tqresult[nres][k]; *\/ */
   /*            /\* cov[2+nagesqr+k1]=Tresult[nres][Tinvresult[nres][Tvardk[k1][1]]] * Tqresult[nres][Tinvresult[nres][Tvardk[k1][2]]]; *\/ */
   /*        /\*   } *\/ */
   /*        /\* }else{ /\\* Product of quantitative by...*\\/ *\/ */
   /*        /\*   if(Dummy[Tvard[k][2]]==0){  /\\* quant by dummy *\\/ *\/ */
   /*        /\*     /\\* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][2]][codtabm(ij,TnsdVar[Tvard[k][2]])] * Tqinvresult[nres][Tvard[k][1]]; *\\/ *\/ */
   /*        /\*     cov[2+nagesqr+k1]=Tqresult[nres][Tinvresult[nres][Tvardk[k1][1]]] * Tresult[nres][Tinvresult[nres][Tvardk[k1][2]]]  ; *\/ */
   /*        /\*   }else{ /\\* Product of two quant *\\/ *\/ */
   /*        /\*     /\\* cov[2+nagesqr+Tprod[k]]=Tqinvresult[nres][Tvard[k][1]]*  Tqinvresult[nres][Tvard[k][2]]; *\\/ *\/ */
   /*        /\*     cov[2+nagesqr+k1]=Tqresult[nres][Tinvresult[nres][Tvardk[k1][1]]] * Tqresult[nres][Tinvresult[nres][Tvardk[k1][2]]]  ; *\/ */
   /*        /\*   } *\/ */
   /*        /\* }/\\*end of products quantitative *\\/ *\/ */
   /*      }/\*end of products *\/ */
         /* } /\* End of loop on model equation *\/ */
         /* 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, int nres )
   {
     /* For dummy covariates given in each resultline (for historical, computes the corresponding combination 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. Then we use a call to bmij(x and cov)
        The addresss of po (p3mat allocated to the dimension of nhstepm) should be stored for output
     */
   
     int i, j, d, h, k, k1;
     double **out, cov[NCOVMAX+1], **bmij();
     double **newm, ***newmm;
     double agexact;
     double agebegin, ageend;
     double **oldm, **savm;
   
     newmm=po; /* To be saved */
     oldm=oldms;savm=savms; /* Global pointers */
     /* 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)  )*stepm/YEARM; /* age just before transition, d or d-1? */
         /* agexact=age+((h-1)*hstepm + (d-1))*stepm/YEARM; /\* age just before transition *\/ */
           /* Debug */
         /* printf("hBxij age=%lf, agexact=%lf\n", age, agexact); */
         cov[2]=agexact;
         if(nagesqr==1){
           cov[3]= agexact*agexact;
         }
         /** New code */
         for(k1=1;k1<=cptcovt;k1++){ /* loop on model equation (including products) */ 
           if(Typevar[k1]==1){ /* A product with age */
             cov[2+nagesqr+k1]=precov[nres][k1]*cov[2];
           }else{
             cov[2+nagesqr+k1]=precov[nres][k1];
           }
         }/* End of loop on model equation */
         /** End of new code */
     /** This was old code */
         /* for (k=1; k<=nsd;k++){ /\* For single dummy covariates only *\//\* cptcovn error *\/ */
         /* /\*    cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,k)]; *\/ */
         /* /\* /\\* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,Tvar[k])]; *\\/ *\/ */
         /*        cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,TvarsD[k])];/\* Bug valgrind *\/ */
         /*   /\* printf("hbxij Dummy agexact=%.0f combi=%d k=%d TvarsD[%d]=V%d TvarsDind[%d]=%d nbcode=%d cov[%d]=%lf codtabm(%d,Tvar[%d])=%d \n",agexact,ij,k, k, TvarsD[k],k,TvarsDind[k],nbcode[TvarsD[k]][codtabm(ij,k)],2+nagesqr+TvarsDind[k],cov[2+nagesqr+TvarsDind[k]], ij, k, codtabm(ij,k)); *\/ */
         /* } */
         /* 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++){ /\* Should start at cptcovn+1 *\//\* For product with age *\/ */
         /*        /\* if(Dummy[Tvar[Tage[k]]]== 2){ /\\* dummy with age error!!!*\\/ *\/ */
         /*        if(Dummy[Tage[k]]== 2){ /\* dummy with age *\/ */
         /*          cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,Tvar[Tage[k]])]*cov[2]; */
         /*        } else if(Dummy[Tage[k]]== 3){ /\* quantitative with age *\/ */
         /*          cov[2+nagesqr+Tage[k]]=Tqresult[nres][k];  */
         /*        } */
         /*        /\* printf("hBxij Age combi=%d k=%d  Tage[%d]=V%d Tqresult[%d][%d]=%f\n",ij,k,k,Tage[k],nres,k,Tqresult[nres][k]); *\/ */
         /* } */
         /* for (k=1; k<=cptcovprod;k++){ /\* Useless because included in cptcovn *\/ */
         /*        cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])]*nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])]; */
         /*        if(Dummy[Tvard[k][1]]==0){ */
         /*          if(Dummy[Tvard[k][2]]==0){ */
         /*            cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][1])]; */
         /*          }else{ */
         /*            cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * Tqresult[nres][k]; */
         /*          } */
         /*        }else{ */
         /*          if(Dummy[Tvard[k][2]]==0){ */
         /*            cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])] * Tqinvresult[nres][Tvard[k][1]]; */
         /*          }else{ */
         /*            cov[2+nagesqr+Tprod[k]]=Tqinvresult[nres][Tvard[k][1]]*  Tqinvresult[nres][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]);*\/ */
   /** End of old code */
         
         /* Careful transposed matrix */
         /* age is in cov[2], prevacurrent at beginning of transition. */
         /* 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);/* Bug valgrind */
         /* 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 %.1f ",h, agexact); */
     } /* end h */
     /* printf("\n H=%d nhs=%d \n",h, nhstepm); */
     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, kf=0;
     int ioffset=0;
     int ipos=0,iposold=0,ncovv=0;
   
     double cotvarv, cotvarvold;
     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;
     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]);
     */
   
     ++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 (kf=1; kf<=ncovf;kf++){ /* For each fixed covariate dummu or quant or prod */
           /* # V1=sex, V2=raedyrs Quant Fixed, State=livarnb4..livarnb11, V3=iadl4..iald11, V4=adlw4..adlw11, V5=r4bmi..r11bmi */
           /*             V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
           /*  TvarF[1]=Tvar[6]=2,  TvarF[2]=Tvar[7]=7, TvarF[3]=Tvar[9]=1  ID of fixed covariates or product V2, V1*V2, V1 */
           /* TvarFind;  TvarFind[1]=6,  TvarFind[2]=7, TvarFind[3]=9 *//* Inverse V2(6) is first fixed (single or prod)  */
           cov[ioffset+TvarFind[kf]]=covar[Tvar[TvarFind[kf]]][i];/* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, only V1 is fixed (TvarFind[1]=6)*/
           /* V1*V2 (7)  TvarFind[2]=7, TvarFind[3]=9 */
         }
         /* In model V2+V1*V4+age*V3+V3*V2 Tvar[1] is V2, Tvar[2=V1*V4] 
            is 5, Tvar[3=age*V3] should not be computed because of age Tvar[4=V3*V2]=6 
            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-ncovcol-nqv][i] because (-ncovcol-nqv) in the data
            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++){  /* Varying with waves */
         /* Wave varying (but not age varying) */
           /* for(k=1; k <= ncovv ; k++){ /\* Varying  covariates in the model (single and product but no age )"V5+V4+V3+V4*V3+V5*age+V1*age+V1" +TvarVind 1,2,3,4(V4*V3)  Tvar[1]@7{5, 4, 3, 6, 5, 1, 1 ; 6 because the created covar is after V5 and is 6, minus 1+1, 3,2,1,4 positions in cotvar*\/ */
           /*   /\* cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]][i]; but where is the crossproduct? *\/ */
           /*   cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]-ncovcol-nqv][i]; */
           /* } */
           for(ncovv=1, iposold=0; ncovv <= ncovvt ; ncovv++){ /* Varying  covariates (single and product but no age )*/
             itv=TvarVV[ncovv]; /*  TvarVV={3, 1, 3} gives the name of each varying covariate */
             ipos=TvarVVind[ncovv]; /* TvarVVind={2, 5, 5] gives the position in the model of the ncovv th varying covariate*/
             if(TvarFind[itv]==0){ /* Not a fixed covariate */
               cotvarv=cotvar[mw[mi][i]][TvarVV[ncovv]-ncovcol-nqv][i];  /* cotvar[wav][ntv+iv][i] */
             }else{ /* fixed covariate */
               cotvarv=covar[Tvar[TvarFind[itv]]][i];
             }
             if(ipos!=iposold){ /* Not a product or first of a product */
               cotvarvold=cotvarv;
             }else{ /* A second product */
               cotvarv=cotvarv*cotvarvold;
             }
             iposold=ipos;
             cov[ioffset+ipos]=cotvarv;
           }
           /* 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 products of time varying to be done */
           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++){
             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; /* -ntv because cotvar starts at ntv */ 
             }
             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("num[i], i=%d, 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++){
         ioffset=2+nagesqr ;
         for (k=1; k<=ncovf;k++)
           cov[ioffset+TvarFind[k]]=covar[Tvar[TvarFind[k]]][i];
         for(mi=1; mi<= wav[i]-1; mi++){
           for(k=1; k <= ncovv ; k++){
             cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]-ncovcol-nqv][i]; /* Cotvar starts at ntv */
           }
           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++) {
               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; /* -ntv because cotvar starts at ntv */ 
             }
             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++) {
               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; /* -ntv because cotvar starts at ntv */ 
             }
           
             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, kf=0;
     int ioffset=0;
     int ipos=0,iposold=0,ncovv=0;
   
     double cotvarv, cotvarvold;
     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++){
       /* 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+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 (kf=1; kf<=ncovf;kf++){ /* Simple and product fixed covariates without age* products *//* Missing values are set to -1 but should be dropped */
         /* printf("Debug3 TvarFind[%d]=%d",kf, TvarFind[kf]); */
         /* printf(" Tvar[TvarFind[kf]]=%d", Tvar[TvarFind[kf]]); */
         /* printf(" i=%d covar[Tvar[TvarFind[kf]]][i]=%f\n",i,covar[Tvar[TvarFind[kf]]][i]); */
         cov[ioffset+TvarFind[kf]]=covar[Tvar[TvarFind[kf]]][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  */
       }
         /* In model V2+V1*V4+age*V3+V3*V2 Tvar[1] is V2, Tvar[2=V1*V4] 
            is 5, Tvar[3=age*V3] should not be computed because of age Tvar[4=V3*V2]=6 
            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 in the DATA 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]
         */
       /* This part may be useless now because everythin should be in covar */
       /* 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) *//* V1+V3+age*V1+age*V3+V1*V3 with V4 tv and V5 tvq k= 1 to 5 and extra at V(5+1)=6 for V1*V3 */
         /* 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]; */
         /* } */
         
         /*#  ID           V1     V2          weight               birth   death   1st    s1      V3      V4      V5       2nd  s2 */
         /* model V1+V3+age*V1+age*V3+V1*V3 */
         /*  Tvar={1, 3, 1, 3, 6}, the 6 comes from the fact that there are already V1, V2, V3, V4, V5 native covariates */
         /*  TvarVV[1]=V3 (first time varying in the model equation, TvarVV[2]=V1 (in V1*V3) TvarVV[3]=3(V3)  */
         /* We need the position of the time varying or product in the model */
         /* TvarVVind={2,5,5}, for V3 at position 2 and then the product V1*V3 is decomposed into V1 and V3 but at same position 5 */             
         /* TvarVV gives the variable name */
         /* Other example V1 + V3 + V5 + age*V1  + age*V3 + age*V5 + V1*V3  + V3*V5  + V1*V5 
         *      k=         1   2     3     4         5        6        7       8        9
         *  varying            1     2                                 3       4        5
         *  ncovv              1     2                                3 4     5 6      7 8
         *  TvarVV            V3     5                                1 3     3 5      1 5
         * TvarVVind           2     3                                7 7     8 8      9 9
         * TvarFind[k]     1   0     0     0         0        0        0       0        0
         * cotvar starts at ntv=2 (because of V3 V4)
         */
         for(ncovv=1, iposold=0; ncovv <= ncovvt ; ncovv++){ /* Varying  covariates (single and product but no age) including individual from products */
           itv=TvarVV[ncovv]; /*  TvarVV={3, 1, 3} gives the name of each varying covariate */
           ipos=TvarVVind[ncovv]; /* TvarVVind={2, 5, 5] gives the position in the model of the ncovv th varying covariate*/
           if(TvarFind[itv]==0){ /* Not a fixed covariate */
             cotvarv=cotvar[mw[mi][i]][TvarVV[ncovv]-ncovcol-nqv][i];  /* cotvar[wav][ntv+iv][i] */
           }else{ /* fixed covariate */
             cotvarv=covar[Tvar[TvarFind[itv]]][i];
           }
           if(ipos!=iposold){ /* Not a product or first of a product */
             cotvarvold=cotvarv;
           }else{ /* A second product */
             cotvarv=cotvarv*cotvarvold;
           }
           iposold=ipos;
           cov[ioffset+ipos]=cotvarv;
           /* For products */
         }
         /* for(itv=1; itv <= ntveff; itv++){ /\* Varying dummy covariates single *\/ */
         /*        iv=TvarVDind[itv]; /\* iv, position in the model equation of time varying covariate itv *\/ */
         /*        /\*         "V1+V3+age*V1+age*V3+V1*V3" with V3 time varying *\/ */
         /*        /\*           1  2   3      4      5                         *\/ */
         /*        /\*itv           1                                           *\/ */
         /*        /\* TvarVInd[1]= 2                                           *\/ */
         /*        /\* iv= Tvar[Tmodelind[itv]]-ncovcol-nqv;  /\\* Counting the # varying covariate from 1 to ntveff *\\/ *\/ */
         /*        /\* iv= Tvar[Tmodelind[ioffset-2-nagesqr-cptcovage+itv]]-ncovcol-nqv; *\/ */
         /*        /\* cov[ioffset+iv]=cotvar[mw[mi][i]][iv][i]; *\/ */
         /*        /\* k=ioffset-2-nagesqr-cptcovage+itv; /\\* position in simple model *\\/ *\/ */
         /*        /\* cov[ioffset+iv]=cotvar[mw[mi][i]][TmodelInvind[itv]][i]; *\/ */
         /*        cov[ioffset+iv]=cotvar[mw[mi][i]][itv][i]; */
         /*        /\* printf(" i=%d,mi=%d,itv=%d,TmodelInvind[itv]=%d,cotvar[mw[mi][i]][itv][i]=%f\n", i, mi, itv, TvarVDind[itv],cotvar[mw[mi][i]][itv][i]); *\/ */
         /* } */
         /* for(iqtv=1; iqtv <= nqtveff; iqtv++){ /\* Varying quantitatives covariates *\/ */
         /*        iv=TmodelInvQind[iqtv]; /\* Counting the # varying covariate from 1 to ntveff *\/ */
         /*        /\* printf(" i=%d,mi=%d,iqtv=%d,TmodelInvQind[iqtv]=%d,cotqvar[mw[mi][i]][TmodelInvQind[iqtv]][i]=%f\n", i, mi, iqtv, TmodelInvQind[iqtv],cotqvar[mw[mi][i]][TmodelInvQind[iqtv]][i]); *\/ */
         /*        cov[ioffset+ntveff+iqtv]=cotqvar[mw[mi][i]][TmodelInvQind[iqtv]][i]; */
         /* } */
         for (ii=1;ii<=nlstate+ndeath;ii++)
           for (j=1;j<=nlstate+ndeath;j++){
             oldm[ii][j]=(ii==j ? 1.0 : 0.0);
             savm[ii][j]=(ii==j ? 1.0 : 0.0);
           }
         
         agebegin=agev[mw[mi][i]][i]; /* Age at beginning of effective wave */
         ageend=agev[mw[mi][i]][i] + (dh[mi][i])*stepm/YEARM; /* Age at end of effective wave and at the end of transition */
         for(d=0; d<dh[mi][i]; d++){  /* Delay between two effective waves */
         /* for(d=0; d<=0; d++){  /\* Delay between two effective waves Only one matrix to speed up*\/ */
           /*dh[m][i] or dh[mw[mi][i]][i] is the delay between two effective waves m=mw[mi][i]
             and mw[mi+1][i]. dh depends on stepm.*/
           newm=savm;
           agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;  /* Here d is needed */
           cov[2]=agexact;
           if(nagesqr==1)
             cov[3]= agexact*agexact;
           for (kk=1; kk<=cptcovage;kk++) {
             if(!FixedV[Tvar[Tage[kk]]])
               cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
             else
               cov[Tage[kk]+2+nagesqr]=cotvar[mw[mi][i]][Tvar[Tage[kk]]-ncovcol-nqv][i]*agexact;
           }
           /* printf("i=%d,mi=%d,d=%d,mw[mi][i]=%d\n",i, mi,d,mw[mi][i]); */
           /* savm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
           out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
                        1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
           /* out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath, */
           /*           1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate)); */
           savm=oldm;
           oldm=newm;
         } /* end mult */
           /*lli=log(out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]);*/ /* 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];
         /* if(s2==-1){ */
         /*        printf(" ERROR 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("Funcone num[i]=%ld i=%6d V= ", num[i], i);
         for (kf=1; kf<=ncovf;kf++){ /* Simple and product fixed covariates without age* products *//* Missing values are set to -1 but should be dropped */
           printf("%g",covar[Tvar[TvarFind[kf]]][i]);
         }
         for(ncovv=1, iposold=0; ncovv <= ncovvt ; ncovv++){ /* Varying  covariates (single and product but no age) including individual from products */
           ipos=TvarVVind[ncovv]; /* TvarVVind={2, 5, 5] gives the position in the model of the ncovv th varying covariate*/
           if(ipos!=iposold){ /* Not a product or first of a product */
             printf(" %g",cov[ioffset+ipos]);
           }else{
             printf("*");
           }
           iposold=ipos;
         }
         for (kk=1; kk<=cptcovage;kk++) {
           if(!FixedV[Tvar[Tage[kk]]])
             printf(" %g*age",covar[Tvar[Tage[kk]]][i]);
           else
             printf(" %g*age",cotvar[mw[mi][i]][Tvar[Tage[kk]]-ncovcol-nqv][i]);
         }
         printf(" s1=%1d s2=%1d mi=%1d mw=%1d dh=%3d prob=%10.6f w=%6.4f out=%10.6f sav=%10.6f\n",s1,s2,mi,mw[mi][i],dh[mi][i],exp(lli),weight[i],(s2==-1? -1: out[s1][s2]),(s2==-1? -1: 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,(s2==-1? -1: out[s1][s2]),(s2==-1? -1: savm[s1][s2]));
    /*     printf("%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,(s2==-1? -1: out[s1][s2]),(s2==-1? -1: 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);
             /* printf(" %10.6f",-ll[k]*gipmx/gsw); */
           }
           fprintf(ficresilk," %10.6f\n", -llt);
           /* printf(" %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 (*func)(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=(*func)(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));
       fprintf(fichtm,"\n<br>Equation of the model: <b>model=1+age+%s</b><br>\n",model); 
         
       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,k, jk, jkk=0, 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
   #ifdef LINMINORIGINAL
   #else /* LINMINORIGINAL */
     
     flatdir=ivector(1,npar); 
     for (j=1;j<=npar;j++) flatdir[j]=0; 
   #endif /*LINMINORIGINAL */
   
   #ifdef FLATSUP
     powell(p,xi,npar,ftol,&iter,&fret,flatdir,func);
     /* reorganizing p by suppressing flat directions */
     for(i=1, jk=1; i <=nlstate; i++){
       for(k=1; k <=(nlstate+ndeath); k++){
         if (k != i) {
           printf("%d%d flatdir[%d]=%d",i,k,jk, flatdir[jk]);
           if(flatdir[jk]==1){
             printf(" To be skipped %d%d flatdir[%d]=%d ",i,k,jk, flatdir[jk]);
           }
           for(j=1; j <=ncovmodel; j++){
             printf("%12.7f ",p[jk]);
             jk++; 
           }
           printf("\n");
         }
       }
     }
   /* skipping */
     /* for(i=1, jk=1, jkk=1;(flatdir[jk]==0)&& (i <=nlstate); i++){ */
     for(i=1, jk=1, jkk=1;i <=nlstate; i++){
       for(k=1; k <=(nlstate+ndeath); k++){
         if (k != i) {
           printf("%d%d flatdir[%d]=%d",i,k,jk, flatdir[jk]);
           if(flatdir[jk]==1){
             printf(" To be skipped %d%d flatdir[%d]=%d jk=%d p[%d] ",i,k,jk, flatdir[jk],jk, jk);
             for(j=1; j <=ncovmodel;  jk++,j++){
               printf(" p[%d]=%12.7f",jk, p[jk]);
               /*q[jjk]=p[jk];*/
             }
           }else{
             printf(" To be kept %d%d flatdir[%d]=%d jk=%d q[%d]=p[%d] ",i,k,jk, flatdir[jk],jk, jkk, jk);
             for(j=1; j <=ncovmodel;  jk++,jkk++,j++){
               printf(" p[%d]=%12.7f=q[%d]",jk, p[jk],jkk);
               /*q[jjk]=p[jk];*/
             }
           }
           printf("\n");
         }
         fflush(stdout);
       }
     }
     powell(p,xi,npar,ftol,&iter,&fret,flatdir,func);
   #else  /* FLATSUP */
     powell(p,xi,npar,ftol,&iter,&fret,func);
   #endif  /* FLATSUP */
   
   #ifdef LINMINORIGINAL
   #else
         free_ivector(flatdir,1,npar); 
   #endif  /* LINMINORIGINAL*/
   #endif /* POWELL */
   
   #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
   #ifdef FLATSUP
     /* npared = npar -flatd/ncovmodel; */
     /* xired= matrix(1,npared,1,npared); */
     /* paramred= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel); */
     /* powell(pred,xired,npared,ftol,&iter,&fret,flatdir,func); */
     /* free_matrix(xire,1,npared,1,npared); */
   #else  /* FLATSUP */
   #endif /* FLATSUP */
     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){
         printf(" Singular Hessian matrix at row %d:\n",i);
         for (j=1;j<=n;j++) {
           printf(" a[%d][%d]=%f,",i,j,a[i][j]);
           fprintf(ficlog," a[%d][%d]=%f,",i,j,a[i][j]);
         }
         fflush(ficlog);
         fclose(ficlog);
         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);
   }
   
   void date2dmy(double date,double *day, double *month, double *year){
     double yp=0., yp1=0., yp2=0.;
     
     yp1=modf(date,&yp);/* extracts integral of date in yp  and
                           fractional in yp1 */
     *year=yp;
     yp2=modf((yp1*12),&yp);
     *month=yp;
     yp1=modf((yp2*30.5),&yp);
     *day=yp;
     if(*day==0) *day=1;
     if(*month==0) *month=1;
   }
   
   
   
   /************ Frequencies ********************/
   void  freqsummary(char fileres[], double p[], double pstart[], int iagemin, int iagemax, int **s, double **agev, int nlstate, int imx, \
                     int *Tvaraff, int *invalidvarcomb, int **nbcode, int *ncodemax,double **mint,double **anint, char strstart[], \
                     int firstpass,  int lastpass, int stepm, int weightopt, char model[])
   {  /* Some frequencies as well as proposing some starting values */
     /* Frequencies of any combination of dummy covariate used in the model equation */ 
     int i, m, jk, j1, bool, z1,j, nj, nl, k, iv, jj=0, s1=1, s2=1;
     int iind=0, iage=0;
     int mi; /* Effective wave */
     int first;
     double ***freq; /* Frequencies */
     double *x, *y, a=0.,b=0.,r=1., sa=0., sb=0.; /* for regression, y=b+m*x and r is the correlation coefficient */
     int no=0, linreg(int ifi, int ila, int *no, const double x[], const double y[], double* a, double* b, double* r, double* sa, double * sb);
     double *meanq, *stdq, *idq;
     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+4+AGEMARGE); 
     posprop=vector(1,nlstate); /* Counting the number of transition starting from a live state per age */ 
     pospropt=vector(1,nlstate); /* Counting the number of transition starting from a live state */ 
     /* prop=matrix(1,nlstate,iagemin,iagemax+3); */
     meanq=vector(1,nqfveff); /* Number of Quantitative Fixed Variables Effective */
     stdq=vector(1,nqfveff); /* Number of Quantitative Fixed Variables Effective */
     idq=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 (weight=%d) and prevalence by age at begin of transition and dummy covariate value at beginning of transition</h4>\n",fileresphtm, fileresphtm, weightopt);
     
     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>(weight=%d) 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,weightopt);
     
     y= vector(iagemin-AGEMARGE,iagemax+4+AGEMARGE);
     x= vector(iagemin-AGEMARGE,iagemax+4+AGEMARGE);
     freq= ma3x(-5,nlstate+ndeath,-5,nlstate+ndeath,iagemin-AGEMARGE,iagemax+4+AGEMARGE);
     j1=0;
     
     /* j=ncoveff;  /\* Only fixed dummy covariates *\/ */
     j=cptcoveff;  /* Only simple dummy covariates used in the model */
     /* j=cptcovn;  /\* 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**cptcovn 
     */
     dateintsum=0;
     k2cpt=0;
   
     if(cptcoveff == 0 )
       nl=1;  /* Constant and age model only */
     else
       nl=2;
   
     /* if a constant only model, one pass to compute frequency tables and to write it on ficresp */
     /* Loop on nj=1 or 2 if dummy covariates j!=0
      *   Loop on j1(1 to 2**cptcoveff) covariate combination
      *     freq[s1][s2][iage] =0.
      *     Loop on iind
      *       ++freq[s1][s2][iage] weighted
      *     end iind
      *     if covariate and j!0
      *       headers Variable on one line
      *     endif cov j!=0
      *     header of frequency table by age
      *     Loop on age
      *       pp[s1]+=freq[s1][s2][iage] weighted
      *       pos+=freq[s1][s2][iage] weighted
      *       Loop on s1 initial state
      *         fprintf(ficresp
      *       end s1
      *     end age
      *     if j!=0 computes starting values
      *     end compute starting values
      *   end j1
      * end nl 
      */
     for (nj = 1; nj <= nl; nj++){   /* nj= 1 constant model, nl number of loops. */
       if(nj==1)
         j=0;  /* First pass for the constant */
       else{
         j=cptcoveff; /* Other passes for the covariate values number of simple covariates in the model V2+V1 =2 (simple dummy fixed or time varying) */
       }
       first=1;
       for (j1 = 1; j1 <= (int) pow(2,j); j1++){ /* Loop on all dummy covariates combination of the model, ie excluding quantitatives, V4=0, V3=0 for example, fixed or varying covariates */
         posproptt=0.;
         /*printf("cptcovn=%d Tvaraff=%d", cptcovn,Tvaraff[1]);
           scanf("%d", i);*/
         for (i=-5; i<=nlstate+ndeath; i++)  
           for (s2=-5; s2<=nlstate+ndeath; s2++)  
             for(m=iagemin; m <= iagemax+3; m++)
               freq[i][s2][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++) { /* zeroing for each combination j1 as well as for the total */
           idq[z1]=0.;
           meanq[z1]=0.;
           stdq[z1]=0.;
         }
         /* for (z1=1; z1<= nqtveff; z1++) { */
         /*   for(m=1;m<=lastpass;m++){ */
         /*          meanqt[m][z1]=0.; */
         /*        } */
         /* }       */
         /* dateintsum=0; */
         /* k2cpt=0; */
         
         /* For that combination of covariates j1 (V4=1 V3=0 for example), 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<=cptcoveff; z1++) { /* loops on covariates in the model */
                   /* if(Tvaraff[z1] ==-20){ */
                   /*       /\* sumnew+=cotvar[mw[mi][iind]][z1][iind]; *\/ */
                   /* }else  if(Tvaraff[z1] ==-10){ */
                   /*       /\* sumnew+=coqvar[z1][iind]; *\/ */
                   /* }else  */ /* TODO TODO codtabm(j1,z1) or codtabm(j1,Tvaraff[z1]]z1)*/
                   /* if( iind >=imx-3) printf("Searching error iind=%d Tvaraff[z1]=%d covar[Tvaraff[z1]][iind]=%.f TnsdVar[Tvaraff[z1]]=%d, cptcoveff=%d, cptcovs=%d \n",iind, Tvaraff[z1], covar[Tvaraff[z1]][iind],TnsdVar[Tvaraff[z1]],cptcoveff, cptcovs); */
                   if(Tvaraff[z1]<1 || Tvaraff[z1]>=NCOVMAX)
                     printf("Error Tvaraff[z1]=%d<1 or >=%d, cptcoveff=%d model=1+age+%s\n",Tvaraff[z1],NCOVMAX, cptcoveff, model);
                   if (covar[Tvaraff[z1]][iind]!= nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]){ /* for combination j1 of covariates */
                     /* Tests if the value of the covariate z1 for this individual iind responded to combination j1 (V4=1 V3=0) */
                     bool=0; /* bool should be equal to 1 to be selected, one covariate value failed */
                     /* printf("bool=%d i=%d, z1=%d, Tvaraff[%d]=%d, covar[Tvarff][%d]=%2f, codtabm(%d,%d)=%d, nbcode[Tvaraff][codtabm(%d,%d)=%d, j1=%d\n", */
                     /*   bool,i,z1, z1, Tvaraff[z1],i,covar[Tvaraff[z1]][i],j1,z1,codtabm(j1,z1),*/
                     /*   j1,z1,nbcode[Tvaraff[z1]][codtabm(j1,z1)],j1);*/
                     /* For j1=7 in V1+V2+V3+V4 = 0 1 1 0 and codtabm(7,3)=1 and nbcde[3][?]=1*/
                   } /* Onlyf fixed */
                 } /* end z1 */
               } /* cptcoveff > 0 */
             } /* end any */
           }/* end j==0 */
           if (bool==1){ /* We selected an individual iind satisfying combination j1 (V4=1 V3=0) or all fixed covariates */
             /* for(m=firstpass; m<=lastpass; m++){ */
             for(mi=1; mi<wav[iind];mi++){ /* For each 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; /* Good */
                       if (cotvar[m][iv][iind]!= nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]) /* iv=1 to ntv, right modality. If covariate's 
                                                                                         value is -1, we don't select. It differs from the 
                                                                                         constant and age model which counts them. */
                         bool=0; /* not selected */
                     }else if( Fixed[Tmodelind[z1]]== 0) { /* fixed */
                       /* i1=Tvaraff[z1]; */
                       /* i2=TnsdVar[i1]; */
                       /* i3=nbcode[i1][i2]; */
                       /* i4=covar[i1][iind]; */
                       /* if(i4 != i3){ */
                       if (covar[Tvaraff[z1]][iind]!= nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]) { /* Bug valgrind */
                         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){ /*Selected */
                 /* 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 */
                     for (z1=1; z1<= nqfveff; z1++) { /* Quantitative variables, calculating mean on known values only */
                       if(!isnan(covar[ncovcol+z1][iind])){
                         idq[z1]=idq[z1]+weight[iind];
                         meanq[z1]+=covar[ncovcol+z1][iind]*weight[iind];  /* Computes mean of quantitative with selected filter */
                         /* stdq[z1]+=covar[ncovcol+z1][iind]*covar[ncovcol+z1][iind]*weight[iind]*weight[iind]; *//*error*/
                         stdq[z1]+=covar[ncovcol+z1][iind]*covar[ncovcol+z1][iind]*weight[iind]; /* *weight[iind];*/  /* Computes mean of quantitative with selected filter */
                       }
                     }
                     /* if((int)agev[m][iind] == 55) */
                     /*   printf("j=%d, j1=%d Age %d, iind=%d, num=%09ld m=%d\n",j,j1,(int)agev[m][iind],iind, num[iind],m); */
                     /* 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); */
                 }
               }else{
                 bool=1;
               }/* end bool 2 */
             } /* end m */
             /* for (z1=1; z1<= nqfveff; z1++) { /\* Quantitative variables, calculating mean *\/ */
             /*   idq[z1]=idq[z1]+weight[iind]; */
             /*   meanq[z1]+=covar[ncovcol+z1][iind]*weight[iind];  /\* Computes mean of quantitative with selected filter *\/ */
             /*   stdq[z1]+=covar[ncovcol+z1][iind]*covar[ncovcol+z1][iind]*weight[iind]*weight[iind]; /\* *weight[iind];*\/  /\* Computes mean of quantitative with selected filter *\/ */
             /* } */
           } /* end bool */
         } /* end iind = 1 to imx */
         /* prop[s][age] is fed 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);*/
         if(cptcoveff==0 && nj==1) /* no covariate and first pass */
           pstamp(ficresp);
         if  (cptcoveff>0 && j!=0){
           pstamp(ficresp);
           printf( "\n#********** Variable "); 
           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(!FixedV[Tvaraff[z1]]){
               printf( "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
               fprintf(ficresp, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
               fprintf(ficresphtm, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
               fprintf(ficresphtmfr, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
               fprintf(ficlog, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
             }else{
               printf( "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
               fprintf(ficresp, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
               fprintf(ficresphtm, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
               fprintf(ficresphtmfr, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
               fprintf(ficlog, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
             }
           }
           printf( "**********\n#");
           fprintf(ficresp, "**********\n#");
           fprintf(ficresphtm, "**********</h3>\n");
           fprintf(ficresphtmfr, "**********</h3>\n");
           fprintf(ficlog, "**********\n");
         }
         /*
           Printing means of quantitative variables if any
         */
         for (z1=1; z1<= nqfveff; z1++) {
           fprintf(ficlog,"Mean of fixed quantitative variable V%d on %.3g (weighted) individuals sum=%f", ncovcol+z1, idq[z1], meanq[z1]);
           fprintf(ficlog,", mean=%.3g\n",meanq[z1]/idq[z1]);
           if(weightopt==1){
             printf(" Weighted mean and standard deviation of");
             fprintf(ficlog," Weighted mean and standard deviation of");
             fprintf(ficresphtmfr," Weighted mean and standard deviation of");
           }
           /* mu = \frac{w x}{\sum w}
              var = \frac{\sum w (x-mu)^2}{\sum w} = \frac{w x^2}{\sum w} - mu^2 
           */
           printf(" fixed quantitative variable V%d on  %.3g (weighted) representatives of the population : %8.5g (%8.5g)\n", ncovcol+z1, idq[z1],meanq[z1]/idq[z1], sqrt(stdq[z1]/idq[z1]-meanq[z1]*meanq[z1]/idq[z1]/idq[z1]));
           fprintf(ficlog," fixed quantitative variable V%d on  %.3g (weighted) representatives of the population : %8.5g (%8.5g)\n", ncovcol+z1, idq[z1],meanq[z1]/idq[z1], sqrt(stdq[z1]/idq[z1]-meanq[z1]*meanq[z1]/idq[z1]/idq[z1]));
           fprintf(ficresphtmfr," fixed quantitative variable V%d on %.3g (weighted) representatives of the population : %8.5g (%8.5g)<p>\n", ncovcol+z1, idq[z1],meanq[z1]/idq[z1], sqrt(stdq[z1]/idq[z1]-meanq[z1]*meanq[z1]/idq[z1]/idq[z1]));
         }
         /* for (z1=1; z1<= nqtveff; z1++) { */
         /*        for(m=1;m<=lastpass;m++){ */
         /*          fprintf(ficresphtmfr,"V quantitative id %d, pass id=%d, mean=%f<p>\n", z1, m, meanqt[m][z1]); */
         /*   } */
         /* } */
   
         fprintf(ficresphtm,"<table style=\"text-align:center; border: 1px solid\">");
         if((cptcoveff==0 && nj==1)|| nj==2 ) /* no covariate and first pass */
           fprintf(ficresp, " Age");
         if(nj==2) for (z1=1; z1<=cptcoveff; z1++) {
             printf(" V%d=%d, z1=%d, Tvaraff[z1]=%d, j1=%d, TnsdVar[Tvaraff[%d]]=%d |",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])], z1, Tvaraff[z1], j1,z1,TnsdVar[Tvaraff[z1]]);
             fprintf(ficresp, " V%d=%d",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
           }
         for(i=1; i<=nlstate;i++) {
           if((cptcoveff==0 && nj==1)|| nj==2 ) fprintf(ficresp," 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);
         }
         if((cptcoveff==0 && nj==1)|| nj==2 ) 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(s2=-1; s2 <=nlstate+ndeath; s2++){
           for(m=-1; m <=nlstate+ndeath; m++){
             if(s2!=0 && m!=0)
               fprintf(ficresphtmfr,"<th>%d%d</th> ",s2,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(s1=1; s1 <=nlstate ; s1++){
             for(m=-1, pp[s1]=0; m <=nlstate+ndeath ; m++)
               pp[s1] += freq[s1][m][iage]; 
           }
           for(s1=1; s1 <=nlstate ; s1++){
             for(m=-1, pos=0; m <=0 ; m++)
               pos += freq[s1][m][iage];
             if(pp[s1]>=1.e-10){
               if(first==1){
                 printf(" %d.=%.0f loss[%d]=%.1f%%",s1,pp[s1],s1,100*pos/pp[s1]);
               }
               fprintf(ficlog," %d.=%.0f loss[%d]=%.1f%%",s1,pp[s1],s1,100*pos/pp[s1]);
             }else{
               if(first==1)
                 printf(" %d.=%.0f loss[%d]=NaNQ%%",s1,pp[s1],s1);
               fprintf(ficlog," %d.=%.0f loss[%d]=NaNQ%%",s1,pp[s1],s1);
             }
           }
         
           for(s1=1; s1 <=nlstate ; s1++){ 
             /* posprop[s1]=0; */
             for(m=0, pp[s1]=0; m <=nlstate+ndeath; m++)/* Summing on all ages */
               pp[s1] += freq[s1][m][iage];
           }       /* pp[s1] is the total number of transitions starting from state s1 and any ending status until this age */
         
           for(s1=1,pos=0, pospropta=0.; s1 <=nlstate ; s1++){
             pos += pp[s1]; /* pos is the total number of transitions until this age */
             posprop[s1] += prop[s1][iage]; /* prop is the number of transitions from a live state
                                               from s1 at age iage prop[s[m][iind]][(int)agev[m][iind]] += weight[iind] */
             pospropta += prop[s1][iage]; /* prop is the number of transitions from a live state
                                             from s1 at age iage prop[s[m][iind]][(int)agev[m][iind]] += weight[iind] */
           }
           
           /* Writing ficresp */
           if(cptcoveff==0 && nj==1){ /* no covariate and first pass */
             if( iage <= iagemax){
               fprintf(ficresp," %d",iage);
             }
           }else if( nj==2){
             if( iage <= iagemax){
               fprintf(ficresp," %d",iage);
               for (z1=1; z1<=cptcoveff; z1++) fprintf(ficresp, " %d %d",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
             }
           }
           for(s1=1; s1 <=nlstate ; s1++){
             if(pos>=1.e-5){
               if(first==1)
                 printf(" %d.=%.0f prev[%d]=%.1f%%",s1,pp[s1],s1,100*pp[s1]/pos);
               fprintf(ficlog," %d.=%.0f prev[%d]=%.1f%%",s1,pp[s1],s1,100*pp[s1]/pos);
             }else{
               if(first==1)
                 printf(" %d.=%.0f prev[%d]=NaNQ%%",s1,pp[s1],s1);
               fprintf(ficlog," %d.=%.0f prev[%d]=NaNQ%%",s1,pp[s1],s1);
             }
             if( iage <= iagemax){
               if(pos>=1.e-5){
                 if(cptcoveff==0 && nj==1){ /* no covariate and first pass */
                   fprintf(ficresp," %.5f %.0f %.0f",prop[s1][iage]/pospropta, prop[s1][iage],pospropta);
                 }else if( nj==2){
                   fprintf(ficresp," %.5f %.0f %.0f",prop[s1][iage]/pospropta, prop[s1][iage],pospropta);
                 }
                 fprintf(ficresphtm,"<th>%d</th><td>%.5f</td><td>%.0f</td><td>%.0f</td>",iage,prop[s1][iage]/pospropta, prop[s1][iage],pospropta);
                 /*probs[iage][s1][j1]= pp[s1]/pos;*/
                 /*printf("\niage=%d s1=%d j1=%d %.5f %.0f %.0f %f",iage,s1,j1,pp[s1]/pos, pp[s1],pos,probs[iage][s1][j1]);*/
               } else{
                 if((cptcoveff==0 && nj==1)|| nj==2 ) fprintf(ficresp," NaNq %.0f %.0f",prop[s1][iage],pospropta);
                 fprintf(ficresphtm,"<th>%d</th><td>NaNq</td><td>%.0f</td><td>%.0f</td>",iage, prop[s1][iage],pospropta);
               }
             }
             pospropt[s1] +=posprop[s1];
           } /* end loop s1 */
           /* pospropt=0.; */
           for(s1=-1; s1 <=nlstate+ndeath; s1++){
             for(m=-1; m <=nlstate+ndeath; m++){
               if(freq[s1][m][iage] !=0 ) { /* minimizing output */
                 if(first==1){
                   printf(" %d%d=%.0f",s1,m,freq[s1][m][iage]);
                 }
                 /* printf(" %d%d=%.0f",s1,m,freq[s1][m][iage]); */
                 fprintf(ficlog," %d%d=%.0f",s1,m,freq[s1][m][iage]);
               }
               if(s1!=0 && m!=0)
                 fprintf(ficresphtmfr,"<td>%.0f</td> ",freq[s1][m][iage]);
             }
           } /* end loop s1 */
           posproptt=0.; 
           for(s1=1; s1 <=nlstate; s1++){
             posproptt += pospropt[s1];
           }
           fprintf(ficresphtmfr,"</tr>\n ");
           fprintf(ficresphtm,"</tr>\n");
           if((cptcoveff==0 && nj==1)|| nj==2 ) {
             if(iage <= iagemax)
               fprintf(ficresp,"\n");
           }
           if(first==1)
             printf("Others in log...\n");
           fprintf(ficlog,"\n");
         } /* end loop age iage */
         
         fprintf(ficresphtm,"<tr><th>Tot</th>");
         for(s1=1; s1 <=nlstate ; s1++){
           if(posproptt < 1.e-5){
             fprintf(ficresphtm,"<td>Nanq</td><td>%.0f</td><td>%.0f</td>",pospropt[s1],posproptt); 
           }else{
             fprintf(ficresphtm,"<td>%.5f</td><td>%.0f</td><td>%.0f</td>",pospropt[s1]/posproptt,pospropt[s1],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(ficlog,"#  This combination (%d) is not valid and no result will be produced\n",j1);
           printf("#  This combination (%d) is not valid and no result will be produced\n",j1);
           invalidvarcomb[j1]=1;
         }else{
           fprintf(ficresphtm,"\n <p> This combination (%d) is valid and result will be produced (or no resultline).</p>",j1);
           invalidvarcomb[j1]=0;
         }
         fprintf(ficresphtmfr,"</table>\n");
         fprintf(ficlog,"\n");
         if(j!=0){
           printf("#Freqsummary: Starting values for combination j1=%d:\n", j1);
           for(i=1,s1=1; i <=nlstate; i++){
             for(k=1; k <=(nlstate+ndeath); k++){
               if (k != i) {
                 for(jj=1; jj <=ncovmodel; jj++){ /* For counting s1 */
                   if(jj==1){  /* Constant case (in fact cste + age) */
                     if(j1==1){ /* All dummy covariates to zero */
                       freq[i][k][iagemax+4]=freq[i][k][iagemax+3]; /* Stores case 0 0 0 */
                       freq[i][i][iagemax+4]=freq[i][i][iagemax+3]; /* Stores case 0 0 0 */
                       printf("%d%d ",i,k);
                       fprintf(ficlog,"%d%d ",i,k);
                       printf("%12.7f ln(%.0f/%.0f)= %f, OR=%f sd=%f \n",p[s1],freq[i][k][iagemax+3],freq[i][i][iagemax+3], log(freq[i][k][iagemax+3]/freq[i][i][iagemax+3]),freq[i][k][iagemax+3]/freq[i][i][iagemax+3], sqrt(1/freq[i][k][iagemax+3]+1/freq[i][i][iagemax+3]));
                       fprintf(ficlog,"%12.7f ln(%.0f/%.0f)= %12.7f \n",p[s1],freq[i][k][iagemax+3],freq[i][i][iagemax+3], log(freq[i][k][iagemax+3]/freq[i][i][iagemax+3]));
                       pstart[s1]= log(freq[i][k][iagemax+3]/freq[i][i][iagemax+3]);
                     }
                   }else if((j1==1) && (jj==2 || nagesqr==1)){ /* age or age*age parameter without covariate V4*age (to be done later) */
                     for(iage=iagemin; iage <= iagemax+3; iage++){
                       x[iage]= (double)iage;
                       y[iage]= log(freq[i][k][iage]/freq[i][i][iage]);
                       /* printf("i=%d, k=%d, s1=%d, j1=%d, jj=%d, y[%d]=%f\n",i,k,s1,j1,jj, iage, y[iage]); */
                     }
                     /* Some are not finite, but linreg will ignore these ages */
                     no=0;
                     linreg(iagemin,iagemax,&no,x,y,&a,&b,&r, &sa, &sb ); /* y= a+b*x with standard errors */
                     pstart[s1]=b;
                     pstart[s1-1]=a;
                   }else if( j1!=1 && (j1==2 || (log(j1-1.)/log(2.)-(int)(log(j1-1.)/log(2.))) <0.010) && ( TvarsDind[(int)(log(j1-1.)/log(2.))+1]+2+nagesqr == jj)  && Dummy[jj-2-nagesqr]==0){ /* We want only if the position, jj, in model corresponds to unique covariate equal to 1 in j1 combination */ 
                     printf("j1=%d, jj=%d, (int)(log(j1-1.)/log(2.))+1=%d, TvarsDind[(int)(log(j1-1.)/log(2.))+1]=%d\n",j1, jj,(int)(log(j1-1.)/log(2.))+1,TvarsDind[(int)(log(j1-1.)/log(2.))+1]);
                     printf("j1=%d, jj=%d, (log(j1-1.)/log(2.))+1=%f, TvarsDind[(int)(log(j1-1.)/log(2.))+1]=%d\n",j1, jj,(log(j1-1.)/log(2.))+1,TvarsDind[(int)(log(j1-1.)/log(2.))+1]);
                     pstart[s1]= log((freq[i][k][iagemax+3]/freq[i][i][iagemax+3])/(freq[i][k][iagemax+4]/freq[i][i][iagemax+4]));
                     printf("%d%d ",i,k);
                     fprintf(ficlog,"%d%d ",i,k);
                     printf("s1=%d,i=%d,k=%d,p[%d]=%12.7f ln((%.0f/%.0f)/(%.0f/%.0f))= %f, OR=%f sd=%f \n",s1,i,k,s1,p[s1],freq[i][k][iagemax+3],freq[i][i][iagemax+3],freq[i][k][iagemax+4],freq[i][i][iagemax+4], log((freq[i][k][iagemax+3]/freq[i][i][iagemax+3])/(freq[i][k][iagemax+4]/freq[i][i][iagemax+4])),(freq[i][k][iagemax+3]/freq[i][i][iagemax+3])/(freq[i][k][iagemax+4]/freq[i][i][iagemax+4]), sqrt(1/freq[i][k][iagemax+3]+1/freq[i][i][iagemax+3]+1/freq[i][k][iagemax+4]+1/freq[i][i][iagemax+4]));
                   }else{ /* Other cases, like quantitative fixed or varying covariates */
                     ;
                   }
                   /* printf("%12.7f )", param[i][jj][k]); */
                   /* fprintf(ficlog,"%12.7f )", param[i][jj][k]); */
                   s1++; 
                 } /* end jj */
               } /* end k!= i */
             } /* end k */
           } /* end i, s1 */
         } /* end j !=0 */
       } /* end selected combination of covariate j1 */
       if(j==0){ /* We can estimate starting values from the occurences in each case */
         printf("#Freqsummary: Starting values for the constants:\n");
         fprintf(ficlog,"\n");
         for(i=1,s1=1; i <=nlstate; i++){
           for(k=1; k <=(nlstate+ndeath); k++){
             if (k != i) {
               printf("%d%d ",i,k);
               fprintf(ficlog,"%d%d ",i,k);
               for(jj=1; jj <=ncovmodel; jj++){
                 pstart[s1]=p[s1]; /* Setting pstart to p values by default */
                 if(jj==1){ /* Age has to be done */
                   pstart[s1]= log(freq[i][k][iagemax+3]/freq[i][i][iagemax+3]);
                   printf("%12.7f ln(%.0f/%.0f)= %12.7f ",p[s1],freq[i][k][iagemax+3],freq[i][i][iagemax+3], log(freq[i][k][iagemax+3]/freq[i][i][iagemax+3]));
                   fprintf(ficlog,"%12.7f ln(%.0f/%.0f)= %12.7f ",p[s1],freq[i][k][iagemax+3],freq[i][i][iagemax+3], log(freq[i][k][iagemax+3]/freq[i][i][iagemax+3]));
                 }
                 /* printf("%12.7f )", param[i][jj][k]); */
                 /* fprintf(ficlog,"%12.7f )", param[i][jj][k]); */
                 s1++; 
               }
               printf("\n");
               fprintf(ficlog,"\n");
             }
           }
         } /* end of state i */
         printf("#Freqsummary\n");
         fprintf(ficlog,"\n");
         for(s1=-1; s1 <=nlstate+ndeath; s1++){
           for(s2=-1; s2 <=nlstate+ndeath; s2++){
             /* param[i]|j][k]= freq[s1][s2][iagemax+3] */
             printf(" %d%d=%.0f",s1,s2,freq[s1][s2][iagemax+3]);
             fprintf(ficlog," %d%d=%.0f",s1,s2,freq[s1][s2][iagemax+3]);
             /* if(freq[s1][s2][iage] !=0 ) { /\* minimizing output *\/ */
             /*   printf(" %d%d=%.0f",s1,s2,freq[s1][s2][iagemax+3]); */
             /*   fprintf(ficlog," %d%d=%.0f",s1,s2,freq[s1][s2][iagemax+3]); */
             /* } */
           }
         } /* end loop s1 */
         
         printf("\n");
         fprintf(ficlog,"\n");
       } /* end j=0 */
     } /* end j */
   
     if(mle == -2){  /* We want to use these values as starting values */
       for(i=1, jk=1; i <=nlstate; i++){
         for(j=1; j <=nlstate+ndeath; j++){
           if(j!=i){
             /*ca[0]= k+'a'-1;ca[1]='\0';*/
             printf("%1d%1d",i,j);
             fprintf(ficparo,"%1d%1d",i,j);
             for(k=1; k<=ncovmodel;k++){
               /*    printf(" %lf",param[i][j][k]); */
               /*    fprintf(ficparo," %lf",param[i][j][k]); */
               p[jk]=pstart[jk];
               printf(" %f ",pstart[jk]);
               fprintf(ficparo," %f ",pstart[jk]);
               jk++;
             }
             printf("\n");
             fprintf(ficparo,"\n");
           }
         }
       }
     } /* end mle=-2 */
     dateintmean=dateintsum/k2cpt; 
     date2dmy(dateintmean,&jintmean,&mintmean,&aintmean);
     
     fclose(ficresp);
     fclose(ficresphtm);
     fclose(ficresphtmfr);
     free_vector(idq,1,nqfveff);
     free_vector(meanq,1,nqfveff);
     free_vector(stdq,1,nqfveff);
     free_matrix(meanqt,1,lastpass,1,nqtveff);
     free_vector(x, iagemin-AGEMARGE, iagemax+4+AGEMARGE);
     free_vector(y, iagemin-AGEMARGE, iagemax+4+AGEMARGE);
     free_ma3x(freq,-5,nlstate+ndeath,-5,nlstate+ndeath, iagemin-AGEMARGE, iagemax+4+AGEMARGE);
     free_vector(pospropt,1,nlstate);
     free_vector(posprop,1,nlstate);
     free_matrix(prop,1,nlstate,iagemin-AGEMARGE, iagemax+4+AGEMARGE);
     free_vector(pp,1,nlstate);
     /* End of freqsummary */
   }
   
   /* Simple linear regression */
   int linreg(int ifi, int ila, int *no, const double x[], const double y[], double* a, double* b, double* r, double* sa, double * sb) {
   
     /* y=a+bx regression */
     double   sumx = 0.0;                        /* sum of x                      */
     double   sumx2 = 0.0;                       /* sum of x**2                   */
     double   sumxy = 0.0;                       /* sum of x * y                  */
     double   sumy = 0.0;                        /* sum of y                      */
     double   sumy2 = 0.0;                       /* sum of y**2                   */
     double   sume2 = 0.0;                       /* sum of square or residuals */
     double yhat;
     
     double denom=0;
     int i;
     int ne=*no;
     
     for ( i=ifi, ne=0;i<=ila;i++) {
       if(!isfinite(x[i]) || !isfinite(y[i])){
         /* printf(" x[%d]=%f, y[%d]=%f\n",i,x[i],i,y[i]); */
         continue;
       }
       ne=ne+1;
       sumx  += x[i];       
       sumx2 += x[i]*x[i];  
       sumxy += x[i] * y[i];
       sumy  += y[i];      
       sumy2 += y[i]*y[i]; 
       denom = (ne * sumx2 - sumx*sumx);
       /* printf("ne=%d, i=%d,x[%d]=%f, y[%d]=%f sumx=%f, sumx2=%f, sumxy=%f, sumy=%f, sumy2=%f, denom=%f\n",ne,i,i,x[i],i,y[i], sumx, sumx2,sumxy, sumy, sumy2,denom); */
     } 
     
     denom = (ne * sumx2 - sumx*sumx);
     if (denom == 0) {
       // vertical, slope m is infinity
       *b = INFINITY;
       *a = 0;
       if (r) *r = 0;
       return 1;
     }
     
     *b = (ne * sumxy  -  sumx * sumy) / denom;
     *a = (sumy * sumx2  -  sumx * sumxy) / denom;
     if (r!=NULL) {
       *r = (sumxy - sumx * sumy / ne) /          /* compute correlation coeff     */
         sqrt((sumx2 - sumx*sumx/ne) *
              (sumy2 - sumy*sumy/ne));
     }
     *no=ne;
     for ( i=ifi, ne=0;i<=ila;i++) {
       if(!isfinite(x[i]) || !isfinite(y[i])){
         /* printf(" x[%d]=%f, y[%d]=%f\n",i,x[i],i,y[i]); */
         continue;
       }
       ne=ne+1;
       yhat = y[i] - *a -*b* x[i];
       sume2  += yhat * yhat ;       
       
       denom = (ne * sumx2 - sumx*sumx);
       /* printf("ne=%d, i=%d,x[%d]=%f, y[%d]=%f sumx=%f, sumx2=%f, sumxy=%f, sumy=%f, sumy2=%f, denom=%f\n",ne,i,i,x[i],i,y[i], sumx, sumx2,sumxy, sumy, sumy2,denom); */
     } 
     *sb = sqrt(sume2/(double)(ne-2)/(sumx2 - sumx * sumx /(double)ne));
     *sa= *sb * sqrt(sumx2/ne);
     
     return 0; 
   }
   
   /************ Prevalence ********************/
   void prevalence(double ***probs, double agemin, double agemax, int **s, double **agev, int nlstate, int imx, int *Tvar, int **nbcode, int *ncodemax,double **mint,double **anint, double dateprev1,double dateprev2, int firstpass, int lastpass)
   {  
     /* Compute observed prevalence between dateprev1 and dateprev2 by counting the number of people
        in each health status at the date of interview (if between dateprev1 and dateprev2).
        We still use firstpass and lastpass as another selection.
     */
    
     int i, m, jk, j1, bool, z1,j, iv;
     int mi; /* Effective wave */
     int iage;
     double agebegin, ageend;
   
     double **prop;
     double posprop; 
     double  y2; /* in fractional years */
     int iagemin, iagemax;
     int first; /** to stop verbosity which is redirected to log file */
   
     iagemin= (int) agemin;
     iagemax= (int) agemax;
     /*pp=vector(1,nlstate);*/
     prop=matrix(1,nlstate,iagemin-AGEMARGE,iagemax+4+AGEMARGE); 
     /*  freq=ma3x(-1,nlstate+ndeath,-1,nlstate+ndeath,iagemin,iagemax+3);*/
     j1=0;
     
     /*j=cptcoveff;*/
     if (cptcovn<1) {j=1;ncodemax[1]=1;}
     
     first=0;
     for(j1=1; j1<= (int) pow(2,cptcoveff);j1++){ /* For each combination of simple dummy covariates */
       for (i=1; i<=nlstate; i++)  
         for(iage=iagemin-AGEMARGE; iage <= iagemax+4+AGEMARGE; iage++)
           prop[i][iage]=0.0;
       printf("Prevalence combination of varying and fixed dummies %d\n",j1);
       /* fprintf(ficlog," V%d=%d ",Tvaraff[j1],nbcode[Tvaraff[j1]][codtabm(k,j1)]); */
       fprintf(ficlog,"Prevalence combination of varying and fixed dummies %d\n",j1);
       
       for (i=1; i<=imx; i++) { /* Each individual */
         bool=1;
         /* for(m=firstpass; m<=lastpass; m++){/\* Other selection (we can limit to certain interviews*\/ */
         for(mi=1; mi<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,TnsdVar[Tvaraff[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,TnsdVar[Tvaraff[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+4+AGEMARGE){
                   printf("Error on individual # %d agev[m][i]=%f <%d-%d or > %d+3+%d  m=%d; either change agemin or agemax or fix data\n",i, agev[m][i],iagemin,AGEMARGE, iagemax,AGEMARGE,m); 
                   exit(1);
                 }
                 if (s[m][i]>0 && s[m][i]<=nlstate) { 
                   /*if(i>4620) printf(" i=%d m=%d s[m][i]=%d (int)agev[m][i]=%d weight[i]=%f prop=%f\n",i,m,s[m][i],(int)agev[m][m],weight[i],prop[s[m][i]][(int)agev[m][i]]);*/
                   prop[s[m][i]][(int)agev[m][i]] += weight[i];/* At age of beginning of transition, where status is known */
                   prop[s[m][i]][iagemax+3] += weight[i]; 
                 } /* end valid statuses */ 
               } /* end selection of dates */
             } /* end selection of waves */
           } /* end bool */
         } /* end wave */
       } /* end individual */
       for(i=iagemin; i <= iagemax+3; i++){  
         for(jk=1,posprop=0; jk <=nlstate ; jk++) { 
           posprop += prop[jk][i]; 
         } 
         
         for(jk=1; jk <=nlstate ; jk++){       
           if( i <=  iagemax){ 
             if(posprop>=1.e-5){ 
               probs[i][jk][j1]= prop[jk][i]/posprop;
             } else{
               if(!first){
                 first=1;
                 printf("Warning Observed prevalence doesn't sum to 1 for state %d: probs[%d][%d][%d]=%lf because of lack of cases\nSee others in log file...\n",jk,i,jk, j1,probs[i][jk][j1]);
               }else{
                 fprintf(ficlog,"Warning Observed prevalence doesn't sum to 1 for state %d: probs[%d][%d][%d]=%lf because of lack of cases.\n",jk,i,jk, j1,probs[i][jk][j1]);
               }
             }
           } 
         }/* end jk */ 
       }/* end i */ 
        /*} *//* end i1 */
     } /* end j1 */
     
     /*  free_ma3x(freq,-1,nlstate+ndeath,-1,nlstate+ndeath, iagemin, iagemax+3);*/
     /*free_vector(pp,1,nlstate);*/
     free_matrix(prop,1,nlstate, iagemin-AGEMARGE,iagemax+4+AGEMARGE);
   }  /* End of prevalence */
   
   /************* Waves Concatenation ***************/
   
   void  concatwav(int wav[], int **dh, int **bh,  int **mw, int **s, double *agedc, double **agev, int  firstpass, int lastpass, int imx, int nlstate, int stepm)
   {
     /* Concatenates waves: wav[i] is the number of effective (useful waves in the sense that a non interview is useless) 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. s[m][i] exists for any wave from firstpass to lastpass
     */
   
     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;  /* Loop on waves */
       while(s[m][i] <= nlstate){  /* a live state or unknown 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; /* Valid wave: incrementing mi and updating mi; mw[mi] is the wave number of mi_th valid transition   */
           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){ /* no death date and known date of interview, case -2 (vital status unknown is warned later */
             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 1-p_{%d%d} .\nOthers in log file only\n",num[i],i,lastpass,(int)mint[m][i],(int)anint[m][i], (int) moisdc[i], (int) andc[i], s[m][i], m, i, m, s[m][i], nlstate+ndeath);
               firsthree=1;
             }else if(firsthree >=1 && firsthree < 10){
               fprintf(ficlog,"Information! Unknown status for individual %ld line=%d occurred at last wave %d at known date %d/%d. Please, check if your unknown date of death %d/%d means a live state %d at wave %d. This case(%d)/wave(%d) contributes to the likelihood as 1-p_{%d%d} .\n",num[i],i,lastpass,(int)mint[m][i],(int)anint[m][i], (int) moisdc[i], (int) andc[i], s[m][i], m, i, m, s[m][i], nlstate+ndeath);
               firsthree++;
             }else if(firsthree == 10){
               printf("Information, too many Information flags: no more reported to log either\n");
               fprintf(ficlog,"Information, too many Information flags: no more reported to log either\n");
               firsthree++;
             }else{
               firsthree++;
             }
             mw[++mi][i]=m; /* Valid transition with unknown status */
             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?not a transition */
               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;
       } /* else not in a death state */
   #ifndef DISPATCHINGKNOWNDEATHAFTERLASTWAVE
       else if ((int) andc[i] != 9999) {  /* Date of death is known */
         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.)){ /* month of death occured before last wave month 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 on %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 on %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 );
             }
               s[m][i]=nlstate+1; /* Fixing the status as death. Be careful if multiple death states */
           }else{ /* Month of Death occured afer last wave month, 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 with status %d. Potential bias if other individuals are still alive on this date but ignored. This case (%d)/wave (%d) is skipped, no contribution to likelihood. Please add a new fictitious wave at the date of last vital status scan, with a dead status. See documentation\nOthers in log file only\n",num[i],i,(int) moisdc[i], (int) andc[i], lastpass,(int)mint[m][i],(int)anint[m][i], s[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 with status %d. Potential bias if other individuals are still alive on this date but ignored. This case (%d)/wave (%d) is skipped, no contribution to likelihood. Please add a new fictitious wave at the date of last vital status scan, with a dead status. See documentation\n\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{ /* if date of interview is unknown */
           /* 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 with status %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], s[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  with status %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], s[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 */
           
     printf("Information, you have to check %d informations which haven't been logged!\n",firsthree);
     fprintf(ficlog,"Information, you have to check %d informations which haven't been logged!\n",firsthree);
   
   
     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, but what if date is unknown? */
             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 */
      for (k=1; k <= maxncov; k++)
        for(j=1; j<=2; j++)
          nbcode[k][j]=0; /* Valgrind */
   
      /* Loop on covariates without age and products and no quantitative variable */
      for (k=1; k<=cptcovt; k++) { /* cptcovt: total number of covariates of the model (2) nbocc(+)+1 = 8 excepting constant and age and age*age */
        for (j=-1; (j < maxncov); j++) Ndum[j]=0;
        printf("Testing k=%d, cptcovt=%d\n",k, cptcovt);
        if(Dummy[k]==0 && Typevar[k] !=1 && Typevar[k] != 2){ /* Dummy covariate and not age product nor fixed product */ 
          switch(Fixed[k]) {
          case 0: /* Testing on fixed dummy covariate, simple or product of fixed */
            modmaxcovj=0;
            modmincovj=0;
            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*/
              /* printf("Waiting for error tricode Tvar[%d]=%d i=%d (int)(covar[Tvar[k]][i]=%d\n",k,Tvar[k], i, (int)(covar[Tvar[k]][i])); */
              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 <0 || ij >1 ){
                printf("ERROR, IMaCh doesn't treat covariate with missing values V%d=-1, individual %d will be skipped.\n",Tvar[k],i);
                fprintf(ficlog,"ERROR, currently IMaCh doesn't treat covariate with missing values V%d=-1, individual %d will be skipped.\n",Tvar[k],i);
                fflush(ficlog);
                exit(1);
              }
              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*/
            /* Skipping the case of missing values by reducing nbcode to 0 and 1 and not -1, 0, 1 */
            /* model=V1+V2+V3, if V2=-1, 0 or 1, then nbcode[2][1]=0 and nbcode[2][2]=1 instead of
             * nbcode[2][1]=-1, nbcode[2][2]=0 and nbcode[2][3]=1 */
            /*, could be restored in the future */
            for (i=0; i<=1; 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 . Could be -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 */
        if(Dummy[k]==1 && Typevar[k] !=1){ /* Quantitative covariate and not age product */ 
          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*/
            if(Tvar[k]<=0 || Tvar[k]>=NCOVMAX){
              printf("Error k=%d \n",k);
              exit(1);
            }
            if(isnan(covar[Tvar[k]][i])){
              printf("ERROR, IMaCh doesn't treat fixed quantitative covariate with missing values V%d=., individual %d will be skipped.\n",Tvar[k],i);
              fprintf(ficlog,"ERROR, currently IMaCh doesn't treat covariate with missing values V%d=., individual %d will be skipped.\n",Tvar[k],i);
              fflush(ficlog);
              exit(1);
            }
          }
        } /* end Quanti */
      } /* end of loop on model-covariate k. nbcode[Tvark][1]=-1, nbcode[Tvark][1]=0 and nbcode[Tvark][2]=1 sets the value of covariate k*/  
     
      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++) { /* cptcovt: total number of covariates of the model (2) nbocc(+)+1 = 8 excepting constant and age and age*age */
        /* 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 simple and non empty in the model */
          /* Typevar[k] =0 for simple covariate (dummy, quantitative, fixed or varying), 1 for age product, 2 for product */
          /* Dummy[k] 0=dummy (0 1), 1 quantitative (single or product without age), 2 dummy with age product, 3 quant with age product*/
          /* 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, *//* V5 quanti, V2 quanti, V4, V3, V1 dummies */
          /* k=       1    2   3     4       5       6      7       8        9  */
          /* Tvar[k]= 5    4    3    6       5       2      7       1        1  */
          /* ij            1    2                                            3  */  
          /* Tvaraff[ij]=  4    3                                            1  */
          /* Tmodelind[ij]=2    3                                            9  */
          /* TmodelInvind[ij]=2 1                                            1  */
          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; /* cptcov= Number of total real effective simple dummies (fixed or time  arying) effective (used as cptcoveff in other functions)
                   * 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 */
     /* cij is the combination in the list of combination of dummy covariates */
     /* strstart is a string of time at start of computing */
     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 which relies in memory size consideration
        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 */
       /* printf("HELLO evsij Entering hpxij age=%d cij=%d hstepm=%d x[1]=%f nres=%d\n",(int) age, cij, hstepm, x[1], nres); */
       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. .
     */
     /* Very time consuming function, but already optimized with precov */
     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;
         }
       }
       /* if((int)age ==50){ */
       /*   printf(" age=%d cij=%d nres=%d varhe[%d][%d]=%f ",(int)age, cij, nres, 1,2,varhe[1][2]); */
       /* } */
       /* 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]);*/
                                           
           }
   
       /* Standard deviation of expectancies ij */         
       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");
                   
       /* Variance of expectancies ij */           
       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 first=0;
      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");
   
      /* We use TinvDoQresult[nres][resultmodel[nres][j] we sort according to the equation model and the resultline: it is a choice */
      /* for (j=1; j<= nsq; j++){ /\* For each selected (single) quantitative value *\/ /\* To be done*\/ */
      /*   fprintf(ficresprobmorprev," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
      /* } */
      for (j=1; j<= cptcovs; j++){ /* For each selected (single) quantitative value */ /* To be done*/
        fprintf(ficresprobmorprev," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
      }
      /* for(j=1;j<=cptcoveff;j++)  */
      /*   fprintf(ficresprobmorprev," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(ij,TnsdVar[Tvaraff[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);
          }
          /**< Computes the prevalence limit with parameter theta shifted of delta up to ftolpl precision and 
           * returns into prlim .
           */
          prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij, nres);
   
          /* If popbased = 1 we use crossection prevalences. Previous step is useless but prlim is created */
          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];
            }
          }
          /**< Computes the shifted transition matrix \f$ {}{h}_p^{ij}x\f$ at horizon h.
           */                      
          hpxij(p3mat,nhstepm,age,hstepm,xp,nlstate,stepm,oldm,savm, ij,nres);  /* Returns p3mat[i][j][h] for h=0 to nhstepm */
          /**< And for each alive state j, sums over i \f$ w^i_x {}{h}_p^{ij}x\f$, which are the probability
           * at horizon h in state j including mortality.
           */
          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 shifted+ probability of death (h=1 means
             computed over hstepm matrices product = hstepm*stepm months) 
             as a weighted average of prlim(i) * p(i,j) p.3=w1*p13 + w2*p23 .
          */
          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];
          }
          
          /* Again with minus shift */
                           
          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 shifting computations */
   
          /**< Computing gradient matrix at horizon h 
           */
          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];
            }
          /**< Gradient of overall mortality p.3 (or p.j) 
           */
          for(j=nlstate+1; j<= nlstate+ndeath; j++){ /* var mu mortality from j */
            gradgp[theta][j]= (gpp[j]-gmp[j])/2./delti[theta];
          }
                           
        } /* End theta */
        
        /* We got the gradient matrix for each theta and state j */                
        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];
        /**< as well as its transposed matrix 
         */                
                   
        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.;
   
        /* Computing trgradg by matcov by gradg at age and summing over h
         * and k (nhstepm) formula 15 of article
         * Lievre-Brouard-Heathcote
         */
        
        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 is p.3 or p.j = trgradgp by cov by gradgp, variance of
         * p.j overall mortality formula 49 but computed directly because
         * we compute the grad (wix pijx) instead of grad (pijx),even if
         * wix is independent of theta.
         */
        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 fileresvpl[], FILE *ficresvpl, double **varpl, double **matcov, double x[], double delti[], int nlstate, int stepm, double bage, double fage, double **oldm, double **savm, double **prlim, double ftolpl, int *ncvyearp, int ij, char strstart[], int nres)
   {
     /* 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 **dnewmpar,**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 (forward 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);
     dnewmpar=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(dnewmpar,trgradg,1,nlstate,1,npar,1,npar,matcov);
       matprod2(doldm,dnewmpar,1,nlstate,1,npar,1,nlstate,gradg);
       }else{
       matprod2(dnewmpar,trgradg,1,nlstate,1,npar,1,npar,matcov);
       matprod2(doldm,dnewmpar,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]));
         /* for(j=1;j<=nlstate;j++) */
         /*        fprintf(ficresvpl," %d %.5f ",j,prlim[j][i]); */
       }
       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(dnewmpar,1,nlstate,1,nlstate);
   
   }
   
   
   /************ Variance of backprevalence limit ******************/
    void varbrevlim(char fileresvbl[], FILE  *ficresvbl, double **varbpl, double **matcov, double x[], double delti[], int nlstate, int stepm, double bage, double fage, double **oldm, double **savm, double **bprlim, double ftolpl, int mobilavproj, int *ncvyearp, int ij, char strstart[], int nres)
   {
     /* Variance of backward 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 **dnewmpar,**doldm;
     int i, j, nhstepm, hstepm;
     double *xp;
     double *gp, *gm;
     double **gradg, **trgradg;
     double **mgm, **mgp;
     double age,agelim;
     int theta;
     
     pstamp(ficresvbl);
     fprintf(ficresvbl,"# Standard deviation of back (stable) prevalences \n");
     fprintf(ficresvbl,"# Age ");
     if(nresult >=1)
       fprintf(ficresvbl," Result# ");
     for(i=1; i<=nlstate;i++)
         fprintf(ficresvbl," %1d-%1d",i,i);
     fprintf(ficresvbl,"\n");
   
     xp=vector(1,npar);
     dnewmpar=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 = AGEINF;
     for (age=fage; age>=bage; age --){ /* If stepm=6 months */
       nhstepm=(int) rint((age-agelim)*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(mobilavproj > 0 )
           bprevalim(bprlim, mobaverage,nlstate,xp,age,ftolpl,ncvyearp,ij,nres);
         else
           bprevalim(bprlim, mobaverage,nlstate,xp,age,ftolpl,ncvyearp,ij,nres);
         for(i=1;i<=nlstate;i++){
           gp[i] = bprlim[i][i];
           mgp[theta][i] = bprlim[i][i];
         }
        for(i=1; i<=npar; i++) /* Computes gradient */
           xp[i] = x[i] - (i==theta ?delti[theta]:0);
          if(mobilavproj > 0 )
           bprevalim(bprlim, mobaverage,nlstate,xp,age,ftolpl,ncvyearp,ij,nres);
          else
           bprevalim(bprlim, mobaverage,nlstate,xp,age,ftolpl,ncvyearp,ij,nres);
         for(i=1;i<=nlstate;i++){
           gm[i] = bprlim[i][i];
           mgm[theta][i] = bprlim[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++)
         varbpl[i][(int)age] =0.;
       if((int)age==79 ||(int)age== 80  ||(int)age== 81){
       matprod2(dnewmpar,trgradg,1,nlstate,1,npar,1,npar,matcov);
       matprod2(doldm,dnewmpar,1,nlstate,1,npar,1,nlstate,gradg);
       }else{
       matprod2(dnewmpar,trgradg,1,nlstate,1,npar,1,npar,matcov);
       matprod2(doldm,dnewmpar,1,nlstate,1,npar,1,nlstate,gradg);
       }
       for(i=1;i<=nlstate;i++)
         varbpl[i][(int)age] = doldm[i][i]; /* Covariances are useless */
   
       fprintf(ficresvbl,"%.0f ",age );
       if(nresult >=1)
         fprintf(ficresvbl,"%d ",nres );
       for(i=1; i<=nlstate;i++)
         fprintf(ficresvbl," %.5f (%.5f)",bprlim[i][i],sqrt(varbpl[i][(int)age]));
       fprintf(ficresvbl,"\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(dnewmpar,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;
      int nres=0; /* New */
      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. File %s</li>\n",optionfilehtmcov,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(nres=1;nres <=nresult; nres++){ /* For each resultline */
      for(j1=1; j1<=tj;j1++){ /* For any combination of dummy covariates, fixed and varying */
        printf("Varprob  TKresult[nres]=%d j1=%d, nres=%d, cptcovn=%d, cptcoveff=%d tj=%d cptcovs=%d\n",  TKresult[nres], j1, nres, cptcovn, cptcoveff, tj, cptcovs);
        if(tj != 1 && TKresult[nres]!= j1)
          continue;
   
      /* for(j1=1; j1<=tj;j1++){  /\* For each valid combination of covariates or only once*\/ */
        /* for(nres=1;nres <=1; nres++){ /\* For each resultline *\/ */
        /* /\* for(nres=1;nres <=nresult; nres++){ /\\* For each resultline *\\/ *\/ */
        if  (cptcovn>0) {
          fprintf(ficresprob, "\n#********** Variable ");
          fprintf(ficresprobcov, "\n#********** Variable "); 
          fprintf(ficgp, "\n#********** Variable ");
          fprintf(fichtmcov, "\n<hr  size=\"2\" color=\"#EC5E5E\">********** Variable "); 
          fprintf(ficresprobcor, "\n#********** Variable ");    
   
          /* Including quantitative variables of the resultline to be done */
          for (z1=1; z1<=cptcovs; z1++){ /* Loop on each variable of this resultline  */
            printf("Varprob modelresult[%d][%d]=%d model=1+age+%s \n",nres, z1, modelresult[nres][z1], model);
            fprintf(ficlog,"Varprob modelresult[%d][%d]=%d model=1+age+%s \n",nres, z1, modelresult[nres][z1], model);
            /* fprintf(ficlog,"Varprob modelresult[%d][%d]=%d model=1+age+%s resultline[%d]=%s \n",nres, z1, modelresult[nres][z1], model, nres, resultline[nres]); */
            if(Dummy[modelresult[nres][z1]]==0){/* Dummy variable of the variable in position modelresult in the model corresponding to z1 in resultline  */
              if(Fixed[modelresult[nres][z1]]==0){ /* Fixed referenced to model equation */
                fprintf(ficresprob,"V%d=%d ",Tvresult[nres][z1],Tresult[nres][z1]); /* Output of each value for the combination TKresult[nres], ordere by the covariate values in the resultline  */
                fprintf(ficresprobcov,"V%d=%d ",Tvresult[nres][z1],Tresult[nres][z1]); /* Output of each value for the combination TKresult[nres], ordere by the covariate values in the resultline  */
                fprintf(ficgp,"V%d=%d ",Tvresult[nres][z1],Tresult[nres][z1]); /* Output of each value for the combination TKresult[nres], ordere by the covariate values in the resultline  */
                fprintf(fichtmcov,"V%d=%d ",Tvresult[nres][z1],Tresult[nres][z1]); /* Output of each value for the combination TKresult[nres], ordere by the covariate values in the resultline  */
                fprintf(ficresprobcor,"V%d=%d ",Tvresult[nres][z1],Tresult[nres][z1]); /* Output of each value for the combination TKresult[nres], ordere by the covariate values in the resultline  */
                fprintf(ficresprob,"fixed ");
                fprintf(ficresprobcov,"fixed ");
                fprintf(ficgp,"fixed ");
                fprintf(fichtmcov,"fixed ");
                fprintf(ficresprobcor,"fixed ");
              }else{
                fprintf(ficresprob,"varyi ");
                fprintf(ficresprobcov,"varyi ");
                fprintf(ficgp,"varyi ");
                fprintf(fichtmcov,"varyi ");
                fprintf(ficresprobcor,"varyi ");
              }
            }else if(Dummy[modelresult[nres][z1]]==1){ /* Quanti variable */
              /* For each selected (single) quantitative value */
              fprintf(ficresprob," V%d=%lg ",Tvqresult[nres][z1],Tqresult[nres][z1]);
              if(Fixed[modelresult[nres][z1]]==0){ /* Fixed */
                fprintf(ficresprob,"fixed ");
                fprintf(ficresprobcov,"fixed ");
                fprintf(ficgp,"fixed ");
                fprintf(fichtmcov,"fixed ");
                fprintf(ficresprobcor,"fixed ");
              }else{
                fprintf(ficresprob,"varyi ");
                fprintf(ficresprobcov,"varyi ");
                fprintf(ficgp,"varyi ");
                fprintf(fichtmcov,"varyi ");
                fprintf(ficresprobcor,"varyi ");
              }
            }else{
              printf("Error in varprob() Dummy[modelresult[%d][%d]]=%d, modelresult[%d][%d]=V%d cptcovs=%d, cptcoveff=%d \n", nres, z1, Dummy[modelresult[nres][z1]],nres,z1,modelresult[nres][z1],cptcovs, cptcoveff);  /* end if dummy  or quanti */
              fprintf(ficlog,"Error in varprob() Dummy[modelresult[%d][%d]]=%d, modelresult[%d][%d]=V%d cptcovs=%d, cptcoveff=%d \n", nres, z1, Dummy[modelresult[nres][z1]],nres,z1,modelresult[nres][z1],cptcovs, cptcoveff);  /* end if dummy  or quanti */
              exit(1);
            }
          } /* End loop on variable of this resultline */
          /* for (z1=1; z1<=cptcoveff; z1++) fprintf(ficresprob, "V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]); */
          fprintf(ficresprob, "**********\n#\n");
          fprintf(ficresprobcov, "**********\n#\n");
          fprintf(ficgp, "**********\n#\n");
          fprintf(fichtmcov, "**********\n<hr size=\"2\" color=\"#EC5E5E\">");
          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 ++){ /* Fo each age we feed the model equation with covariates, using precov as in hpxij() ? */
          cov[2]=age;
          if(nagesqr==1)
            cov[3]= age*age;
          /* New code end of combination but for each resultline */
          for(k1=1;k1<=cptcovt;k1++){ /* loop on model equation (including products) */ 
            if(Typevar[k1]==1){ /* A product with age */
              cov[2+nagesqr+k1]=precov[nres][k1]*cov[2];
            }else{
              cov[2+nagesqr+k1]=precov[nres][k1];
            }
          }/* End of loop on model equation */
   /* Old code */
          /* /\* for (k=1; k<=cptcovn;k++) { *\/ */
          /* /\*    cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(j1,k)]; *\/ */
          /* for (k=1; k<=nsd;k++) { /\* For single dummy covariates only *\/ */
          /*        /\* Here comes the value of the covariate 'j1' after renumbering k with single dummy covariates *\/ */
          /*        cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(j1,TnsdVar[TvarsD[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;*\/ */
          /* } */
          /* /\* V2+V1+V4+V3*age Tvar[4]=3 ; V1+V2*age Tvar[2]=2; V1+V1*age Tvar[2]=1, Tage[1]=2 *\/ */
          /* /\* ) p nbcode[Tvar[Tage[k]]][(1 & (ij-1) >> (k-1))+1] *\/ */
          /* /\*for (k=1; k<=cptcovage;k++) cov[2+Tage[k]]=cov[2+Tage[k]]*cov[2]; *\/ */
          /* for (k=1; k<=cptcovage;k++){  /\* For product with age *\/ */
          /*        if(Dummy[Tage[k]]==2){ /\* dummy with age *\/ */
          /*          cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(j1,TnsdVar[Tvar[Tage[k]]])]*cov[2]; */
          /*          /\* cov[++k1]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2]; *\/ */
          /*        } else if(Dummy[Tage[k]]==3){ /\* quantitative with age *\/ */
          /*          printf("Internal IMaCh error, don't know which value for quantitative covariate with age, Tage[k]%d, k=%d, Tvar[Tage[k]]=V%d, age=%d\n",Tage[k],k ,Tvar[Tage[k]], (int)cov[2]); */
          /*          /\* cov[2+nagesqr+Tage[k]]=meanq[k]/idq[k]*cov[2];/\\* Using the mean of quantitative variable Tvar[Tage[k]] /\\* Tqresult[nres][k]; *\\/ *\/ */
          /*          /\* exit(1); *\/ */
          /*          /\* cov[++k1]=Tqresult[nres][k];  *\/ */
          /*        } */
          /*        /\* cov[2+Tage[k]+nagesqr]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2]; *\/ */
          /* } */
          /* for (k=1; k<=cptcovprod;k++){/\* For product without age *\/ */
          /*        if(Dummy[Tvard[k][1]]==0){ */
          /*          if(Dummy[Tvard[k][2]]==0){ */
          /*            cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(j1,TnsdVar[Tvard[k][1]])] * nbcode[Tvard[k][2]][codtabm(j1,TnsdVar[Tvard[k][2]])]; */
          /*            /\* cov[++k1]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)]; *\/ */
          /*          }else{ /\* Should we use the mean of the quantitative variables? *\/ */
          /*            cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(j1,TnsdVar[Tvard[k][1]])] * Tqresult[nres][resultmodel[nres][k]]; */
          /*            /\* cov[++k1]=nbcode[Tvard[k][1]][codtabm(ij,k)] * Tqresult[nres][k]; *\/ */
          /*          } */
          /*        }else{ */
          /*          if(Dummy[Tvard[k][2]]==0){ */
          /*            cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][2]][codtabm(j1,TnsdVar[Tvard[k][2]])] * Tqinvresult[nres][TnsdVar[Tvard[k][1]]]; */
          /*            /\* cov[++k1]=nbcode[Tvard[k][2]][codtabm(ij,k)] * Tqinvresult[nres][Tvard[k][1]]; *\/ */
          /*          }else{ */
          /*            cov[2+nagesqr+Tprod[k]]=Tqinvresult[nres][TnsdVar[Tvard[k][1]]]*  Tqinvresult[nres][TnsdVar[Tvard[k][2]]]; */
          /*            /\* cov[++k1]=Tqinvresult[nres][Tvard[k][1]]*  Tqinvresult[nres][Tvard[k][2]]; *\/ */
          /*          } */
          /*        } */
          /*        /\* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)]*nbcode[Tvard[k][2]][codtabm(ij,k)]; *\/ */
          /* } */                  
   /* For each age and combination of dummy covariates we slightly move the parameters of delti in order to get the gradient*/                     
          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 */
                    if(1+(v1-lc1)*(v1-lc1)/cv12/cv12 <1.e-5){
                      printf(" Error sqrt of a negative number: %lf\n",1+(v1-lc1)*(v1-lc1)/cv12/cv12);
                      fprintf(ficlog," Error sqrt of a negative number: %lf\n",1+(v1-lc1)*(v1-lc1)/cv12/cv12);
                      v11=(1./sqrt(fabs(1+(v1-lc1)*(v1-lc1)/cv12/cv12)));
                    }else
                      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<p><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(fabs(lc1)),v12,sqrt(fabs(lc2)), \
                              mu2,std,v21,sqrt(fabs(lc1)),v22,sqrt(fabs(lc2))); /* For gnuplot only */
                    }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(fabs(lc2)),   \
                              mu2,std,v21,sqrt(lc1),v22,sqrt(fabs(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 */
      } /* loop on nres */
      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 mobilav, int prevfcast, int mobilavproj, int prevbcast, int estepm , \
                     double jprev1, double mprev1,double anprev1, double dateprev1, double dateprojd, double dateback1, \
                     double jprev2, double mprev2,double anprev2, double dateprev2, double dateprojf, double dateback2){
     int jj1, k1, i1, cpt, k4, nres;
     /* In fact some results are already printed in fichtm which is open */
      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 (cross-sectional 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 (forward) prevalence in each health state: <a href=\"%s\">%s</a> <br>\n",
              subdirf2(fileresu,"PL_"),subdirf2(fileresu,"PL_"));
      fprintf(fichtm,"\
    - Backward 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_"));
      }
   
   
      m=pow(2,cptcoveff);
      if (cptcovn < 1) {m=1;ncodemax[1]=1;}
   
      fprintf(fichtm," \n<ul><li><b>Graphs (first order)</b></li><p>");
   
      jj1=0;
   
      fprintf(fichtm," \n<ul>");
      for(nres=1; nres <= nresult; nres++){ /* For each resultline */
        /* k1=nres; */
        k1=TKresult[nres];
        if(TKresult[nres]==0)k1=1; /* To be checked for no result */
      /* for(k1=1; k1<=m;k1++){ /\* For each combination of covariate *\/ */
      /*   if(m != 1 && TKresult[nres]!= k1) */
      /*     continue; */
        jj1++;
        if (cptcovn > 0) {
          fprintf(fichtm,"\n<li><a  size=\"1\" color=\"#EC5E5E\" href=\"#rescov");
          for (cpt=1; cpt<=cptcovs;cpt++){ /**< cptcovs number of SIMPLE covariates in the model V2+V1 =2 (dummy or quantit or time varying) */
            fprintf(fichtm,"_V%d=%lg_",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
          }
          /* for (cpt=1; cpt<=cptcoveff;cpt++){  */
          /*        fprintf(fichtm,"_V%d=%d_",Tvresult[nres][cpt],(int)Tresult[nres][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,"\">");
          
          /* if(nqfveff+nqtveff 0) */ /* Test to be done */
          fprintf(fichtm,"************ Results for covariates");
          for (cpt=1; cpt<=cptcovs;cpt++){ 
            fprintf(fichtm," V%d=%lg ",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
          }
          /* fprintf(fichtm,"************ Results for covariates"); */
          /* for (cpt=1; cpt<=cptcoveff;cpt++){  */
          /*        fprintf(fichtm," V%d=%d ",Tvresult[nres][cpt],(int)Tresult[nres][cpt]); */
          /* } */
          /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
          /*        fprintf(fichtm," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
          /* } */
          if(invalidvarcomb[k1]){
            fprintf(fichtm," Warning Combination (%d) ignored because no cases ",k1); 
            continue;
          }
          fprintf(fichtm,"</a></li>");
        } /* cptcovn >0 */
      }
      fprintf(fichtm," \n</ul>");
   
      jj1=0;
   
      for(nres=1; nres <= nresult; nres++){ /* For each resultline */
        /* k1=nres; */
        k1=TKresult[nres];
        if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
      /* for(k1=1; k1<=m;k1++){ /\* For each combination of covariate *\/ */
      /*   if(m != 1 && TKresult[nres]!= k1) */
      /*     continue; */
   
        /* for(i1=1; i1<=ncodemax[k1];i1++){ */
        jj1++;
        if (cptcovn > 0) {
          fprintf(fichtm,"\n<p><a name=\"rescov");
          for (cpt=1; cpt<=cptcovs;cpt++){ 
            fprintf(fichtm,"_V%d=%lg_",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][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,"\"</a>");
    
          fprintf(fichtm,"<hr  size=\"2\" color=\"#EC5E5E\">************ Results for covariates");
          for (cpt=1; cpt<=cptcovs;cpt++){ 
            fprintf(fichtm," V%d=%lg ",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
            printf(" V%d=%lg ",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
            /* 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); */
          }
          /* if(nqfveff+nqtveff 0) */ /* Test to be done */
          fprintf(fichtm," (model=1+age+%s) ************\n<hr size=\"2\" color=\"#EC5E5E\">",model);
          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: logit(pij)=log(pij/pii)= aij+ bij age+%s) as a function of age: <a href=\"%s_%d-1-%d.svg\">%s_%d-1-%d.svg</a><br> \
   <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. And probability to be observed 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>", cpt, cpt, nlstate, subdirf2(optionfilefiname,"LIJ_"),cpt,k1,nres,subdirf2(optionfilefiname,"LIJ_"),cpt,k1,nres);
          fprintf(fichtm," (data from text file  <a href=\"%s.txt\">%s.txt</a>)\n<br>",subdirf2(optionfilefiname,"PIJ_"),subdirf2(optionfilefiname,"PIJ_"));
          fprintf(fichtm,"<img src=\"%s_%d-%d-%d.svg\">",subdirf2(optionfilefiname,"LIJ_"),cpt,k1,nres);
        }
        /* State specific survival functions (period) */
        for(cpt=1; cpt<=nlstate;cpt++){
          fprintf(fichtm,"<br>\n- Survival functions in state %d and in any other live state (total).\
    And probability to be observed in various states (up to %d) being in state %d at different ages.       \
    <a href=\"%s_%d-%d-%d.svg\">%s_%d-%d-%d.svg</a><br> ", cpt, nlstate, cpt, subdirf2(optionfilefiname,"LIJT_"),cpt,k1,nres,subdirf2(optionfilefiname,"LIJT_"),cpt,k1,nres);
          fprintf(fichtm," (data from text file  <a href=\"%s.txt\">%s.txt</a>)\n<br>",subdirf2(optionfilefiname,"PIJ_"),subdirf2(optionfilefiname,"PIJ_"));
          fprintf(fichtm,"<img src=\"%s_%d-%d-%d.svg\">",subdirf2(optionfilefiname,"LIJT_"),cpt,k1,nres);
        }
        /* Period (forward 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 for a person being in state (1 to %d) at different ages, to be in state %d some years after. <a href=\"%s_%d-%d-%d.svg\">%s_%d-%d-%d.svg</a><br>", cpt, nlstate, cpt, subdirf2(optionfilefiname,"P_"),cpt,k1,nres,subdirf2(optionfilefiname,"P_"),cpt,k1,nres);
          fprintf(fichtm," (data from text file  <a href=\"%s.txt\">%s.txt</a>)\n<br>",subdirf2(optionfilefiname,"PIJ_"),subdirf2(optionfilefiname,"PIJ_"));
         fprintf(fichtm,"<img src=\"%s_%d-%d-%d.svg\">" ,subdirf2(optionfilefiname,"P_"),cpt,k1,nres);
        }
        if(prevbcast==1){
          /* Backward prevalence in each health state */
          for(cpt=1; cpt<=nlstate;cpt++){
            fprintf(fichtm,"<br>\n- Convergence to mixed (stable) back prevalence in state %d. Or probability for a person to be in state %d at a younger age, knowing that she/he was in state (1 to %d) at different older ages. <a href=\"%s_%d-%d-%d.svg\">%s_%d-%d-%d.svg</a><br>", cpt, cpt, nlstate, subdirf2(optionfilefiname,"PB_"),cpt,k1,nres,subdirf2(optionfilefiname,"PB_"),cpt,k1,nres);
            fprintf(fichtm," (data from text file  <a href=\"%s.txt\">%s.txt</a>)\n<br>",subdirf2(optionfilefiname,"PIJB_"),subdirf2(optionfilefiname,"PIJB_"));
            fprintf(fichtm,"<img src=\"%s_%d-%d-%d.svg\">" ,subdirf2(optionfilefiname,"PB_"),cpt,k1,nres);
          }
        }
        if(prevfcast==1){
          /* Projection of prevalence up to period (forward 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 and mobil_average=%d), from year %.1f up to year %.1f tending to period (stable) forward prevalence in state %d. Or probability to be in state %d being in an observed weighted state (from 1 to %d). <a href=\"%s_%d-%d-%d.svg\">%s_%d-%d-%d.svg</a>", dateprev1, dateprev2, mobilavproj, dateprojd, dateprojf, cpt, cpt, nlstate, subdirf2(optionfilefiname,"PROJ_"),cpt,k1,nres,subdirf2(optionfilefiname,"PROJ_"),cpt,k1,nres);
            fprintf(fichtm," (data from text file  <a href=\"%s.txt\">%s.txt</a>)\n<br>",subdirf2(optionfilefiname,"F_"),subdirf2(optionfilefiname,"F_"));
            fprintf(fichtm,"<img src=\"%s_%d-%d-%d.svg\">",
                    subdirf2(optionfilefiname,"PROJ_"),cpt,k1,nres);
          }
        }
        if(prevbcast==1){
         /* Back projection of prevalence up to stable (mixed) back-prevalence in each health state */
          for(cpt=1; cpt<=nlstate;cpt++){
            fprintf(fichtm,"<br>\n- Back projection of cross-sectional prevalence (estimated with cases observed from %.1f to %.1f and mobil_average=%d), \
    from year %.1f up to year %.1f (probably close to stable [mixed] back prevalence in state %d (randomness in cross-sectional prevalence is not taken into \
    account but can visually be appreciated). Or probability to have been in an state %d, knowing that the person was in either state (1 or %d) \
   with weights corresponding to observed prevalence at different ages. <a href=\"%s_%d-%d-%d.svg\">%s_%d-%d-%d.svg</a>", dateprev1, dateprev2, mobilavproj, dateback1, dateback2, cpt, cpt, nlstate, subdirf2(optionfilefiname,"PROJB_"),cpt,k1,nres,subdirf2(optionfilefiname,"PROJB_"),cpt,k1,nres);
            fprintf(fichtm," (data from text file  <a href=\"%s.txt\">%s.txt</a>)\n<br>",subdirf2(optionfilefiname,"FB_"),subdirf2(optionfilefiname,"FB_"));
            fprintf(fichtm," <img src=\"%s_%d-%d-%d.svg\">", subdirf2(optionfilefiname,"PROJB_"),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>",cpt,nlstate,subdirf2(optionfilefiname,"EXP_"),cpt,k1,nres,subdirf2(optionfilefiname,"EXP_"),cpt,k1,nres);
          fprintf(fichtm," (data from text file  <a href=\"%s.txt\"> %s.txt</a>)\n<br>",subdirf2(optionfilefiname,"E_"),subdirf2(optionfilefiname,"E_"));
          fprintf(fichtm,"<img src=\"%s_%d-%d-%d.svg\">", subdirf2(optionfilefiname,"EXP_"),cpt,k1,nres );
        }
        /* } /\* end i1 *\/ */
      }/* End k1=nres */
      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 forward (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 forward (period) 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=1+age+%s (instead of .)<br><br></li>\n",popforecast, stepm, model); */
      fflush(fichtm);
   
      m=pow(2,cptcoveff);
      if (cptcovn < 1) {m=1;ncodemax[1]=1;}
   
      fprintf(fichtm," <ul><li><b>Graphs (second order)</b></li><p>");
   
     jj1=0;
   
      fprintf(fichtm," \n<ul>");
      for(nres=1; nres <= nresult; nres++){ /* For each resultline */
        /* k1=nres; */
        k1=TKresult[nres];
        /* for(k1=1; k1<=m;k1++){ /\* For each combination of covariate *\/ */
        /* if(m != 1 && TKresult[nres]!= k1) */
        /*   continue; */
        jj1++;
        if (cptcovn > 0) {
          fprintf(fichtm,"\n<li><a  size=\"1\" color=\"#EC5E5E\" href=\"#rescovsecond");
          for (cpt=1; cpt<=cptcovs;cpt++){ 
            fprintf(fichtm,"_V%d=%lg_",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
          }
          fprintf(fichtm,"\">");
          
          /* if(nqfveff+nqtveff 0) */ /* Test to be done */
          fprintf(fichtm,"************ Results for covariates");
          for (cpt=1; cpt<=cptcovs;cpt++){ 
            fprintf(fichtm," V%d=%lg ",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
          }
          if(invalidvarcomb[k1]){
            fprintf(fichtm," Warning Combination (%d) ignored because no cases ",k1); 
            continue;
          }
          fprintf(fichtm,"</a></li>");
        } /* cptcovn >0 */
      } /* End nres */
      fprintf(fichtm," \n</ul>");
   
      jj1=0;
   
      for(nres=1; nres <= nresult; nres++){ /* For each resultline */
        /* k1=nres; */
        k1=TKresult[nres];
        if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
        /* for(k1=1; k1<=m;k1++){ */
        /* if(m != 1 && TKresult[nres]!= k1) */
        /*   continue; */
        /* for(i1=1; i1<=ncodemax[k1];i1++){ */
        jj1++;
        if (cptcovn > 0) {
          fprintf(fichtm,"\n<p><a name=\"rescovsecond");
          for (cpt=1; cpt<=cptcovs;cpt++){ 
            fprintf(fichtm,"_V%d=%lg_",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
          }
          fprintf(fichtm,"\"</a>");
          
          fprintf(fichtm,"<hr  size=\"2\" color=\"#EC5E5E\">************ Results for covariates");
          for (cpt=1; cpt<=cptcovs;cpt++){  /**< cptcoveff number of variables */
            fprintf(fichtm," V%d=%lg ",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
            printf(" V%d=%lg ",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
            /* fprintf(fichtm," V%d=%d ",Tvaraff[cpt],nbcode[Tvaraff[cpt]][codtabm(jj1,cpt)]); */
          }
   
          fprintf(fichtm," (model=1+age+%s) ************\n<hr size=\"2\" color=\"#EC5E5E\">",model);
   
          if(invalidvarcomb[k1]){
            fprintf(fichtm,"\n<h4>Combination (%d) ignored because no cases </h4>\n",k1); 
            continue;
          }
        } /* If cptcovn >0 */
        for(cpt=1; cpt<=nlstate;cpt++) {
          fprintf(fichtm,"\n<br>- Observed (cross-sectional with mov_average=%d) 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>",mobilav,cpt,subdirf2(optionfilefiname,"V_"),cpt,k1,nres,subdirf2(optionfilefiname,"V_"),cpt,k1,nres);
          fprintf(fichtm," (data from text file  <a href=\"%s\">%s</a>)\n <br>",subdirf2(fileresu,"VPL_"),subdirf2(fileresu,"VPL_"));
          fprintf(fichtm,"<img src=\"%s_%d-%d-%d.svg\">",subdirf2(optionfilefiname,"V_"), cpt,k1,nres);
        }
        fprintf(fichtm,"\n<br>- Total life expectancy by age and \
   health expectancies in each live states (1 to %d). 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>",nlstate, subdirf2(optionfilefiname,"E_"),k1,nres,subdirf2(optionfilefiname,"E_"),k1,nres);
        fprintf(fichtm," (data from text file <a href=\"%s.txt\">%s.txt</a>) \n<br>",subdirf2(optionfilefiname,"T_"),subdirf2(optionfilefiname,"T_"));
        fprintf(fichtm,"<img src=\"%s_%d-%d.svg\">",subdirf2(optionfilefiname,"E_"),k1,nres);
        /* } /\* end i1 *\/ */
     }/* End nres */
      fprintf(fichtm,"</ul>");
      fflush(fichtm);
   }
   
   /******************* Gnuplot file **************/
   void printinggnuplot(char fileresu[], char optionfilefiname[], double ageminpar, double agemaxpar, double bage, double fage , int prevfcast, int prevbcast, char pathc[], double p[], int offyear, int offbyear){
   
     char dirfileres[132],optfileres[132];
     char gplotcondition[132], gplotlabel[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 iyearc=1; /* variable column for year of projection  */
     int iagec=1; /* variable column for age of projection  */
     int nres=0; /* Index of resultline */
     int istart=1; /* For starting graphs in projections */
   
   /*   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);
   
     /* diagram of the model */
     fprintf(ficgp,"\n#Diagram of the model \n");
     fprintf(ficgp,"\ndelta=0.03;delta2=0.07;unset arrow;\n");
     fprintf(ficgp,"yoff=(%d > 2? 0:1);\n",nlstate);
     fprintf(ficgp,"\n#Peripheral arrows\nset for [i=1:%d] for [j=1:%d] arrow i*10+j from cos(pi*((1-(%d/2)*2./%d)/2+(i-1)*2./%d))-(i!=j?(i-j)/abs(i-j)*delta:0), yoff +sin(pi*((1-(%d/2)*2./%d)/2+(i-1)*2./%d)) + (i!=j?(i-j)/abs(i-j)*delta:0) rto -0.95*(cos(pi*((1-(%d/2)*2./%d)/2+(i-1)*2./%d))+(i!=j?(i-j)/abs(i-j)*delta:0) - cos(pi*((1-(%d/2)*2./%d)/2+(j-1)*2./%d)) + (i!=j?(i-j)/abs(i-j)*delta2:0)), -0.95*(sin(pi*((1-(%d/2)*2./%d)/2+(i-1)*2./%d)) + (i!=j?(i-j)/abs(i-j)*delta:0) - sin(pi*((1-(%d/2)*2./%d)/2+(j-1)*2./%d))+( i!=j?(i-j)/abs(i-j)*delta2:0)) ls (i < j? 1:2)\n",nlstate,nlstate,nlstate,nlstate,nlstate,nlstate,nlstate,nlstate,nlstate,nlstate,nlstate,nlstate,nlstate,nlstate,nlstate,nlstate,nlstate,nlstate,nlstate,nlstate);
   
     fprintf(ficgp,"\n#Centripete arrows (turning in other direction (1-i) instead of (i-1)) \nset for [i=1:%d] arrow (%d+1)*10+i from cos(pi*((1-(%d/2)*2./%d)/2+(1-i)*2./%d))-(i!=j?(i-j)/abs(i-j)*delta:0), yoff +sin(pi*((1-(%d/2)*2./%d)/2+(1-i)*2./%d)) + (i!=j?(i-j)/abs(i-j)*delta:0) rto -0.80*(cos(pi*((1-(%d/2)*2./%d)/2+(1-i)*2./%d))+(i!=j?(i-j)/abs(i-j)*delta:0)  ), -0.80*(sin(pi*((1-(%d/2)*2./%d)/2+(1-i)*2./%d)) + (i!=j?(i-j)/abs(i-j)*delta:0) + yoff ) ls 4\n",nlstate,nlstate,nlstate,nlstate,nlstate,nlstate,nlstate,nlstate,nlstate,nlstate,nlstate,nlstate,nlstate,nlstate);
     fprintf(ficgp,"\n#show arrow\nunset label\n");
     fprintf(ficgp,"\n#States labels, starting from 2 (2-i) instead of (1-i), was (i-1)\nset for [i=1:%d] label i sprintf(\"State %%d\",i) center at cos(pi*((1-(%d/2)*2./%d)/2+(2-i)*2./%d)), yoff+sin(pi*((1-(%d/2)*2./%d)/2+(2-i)*2./%d)) font \"helvetica, 16\" tc rgbcolor \"blue\"\n",nlstate,nlstate,nlstate,nlstate,nlstate,nlstate,nlstate);
     fprintf(ficgp,"\nset label %d+1 sprintf(\"State %%d\",%d+1) center at 0.,0.  font \"helvetica, 16\" tc rgbcolor \"red\"\n",nlstate,nlstate);
     fprintf(ficgp,"\n#show label\nunset border;unset xtics; unset ytics;\n");
     fprintf(ficgp,"\n\nset ter svg size 640, 480;set out \"%s_.svg\" \n",subdirf2(optionfilefiname,"D_"));
     fprintf(ficgp,"unset log y; plot [-1.2:1.2][yoff-1.2:1.2] 1/0 not; set out;reset;\n");
   
     /* 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 */
           k1=TKresult[nres];
           if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
           /* plot [100000000000000000000:-100000000000000000000] "mysbiaspar/vplrmysbiaspar.txt to check */
           /* if(m != 1 && TKresult[nres]!= k1) */
           /*   continue; */
           /* We are interested in selected combination by the resultline */
           /* printf("\n# 1st: Period (stable) prevalence with CI: 'VPL_' files and live state =%d ", cpt); */
           fprintf(ficgp,"\n# 1st: Forward (stable period) prevalence with CI: 'VPL_' files  and live state =%d ", cpt);
           strcpy(gplotlabel,"(");
           for (k=1; k<=cptcovs; k++){    /* For each covariate k get corresponding value lv for combination k1 */
             fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
             sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
   
           /* 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 *\\/ *\/ */
           /*   lv=codtabm(k1,TnsdVar[Tvaraff[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]; /\* 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); */
           /*   sprintf(gplotlabel+strlen(gplotlabel)," 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]); */
           /*   sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
           }
           strcpy(gplotlabel+strlen(gplotlabel),")");
           /* printf("\n#\n"); */
           fprintf(ficgp,"\n#\n");
           if(invalidvarcomb[k1]){
             /*k1=k1-1;*/ /* To be checked */
             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 label \"Alive state %d %s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",cpt,gplotlabel); */
           fprintf(ficgp,"set title \"Alive state %d %s model=1+age+%s\" font \"Helvetica,12\"\n",cpt,gplotlabel,model);
           fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability\" \nset ter svg size 640, 480\nplot [%.f:%.f] \"%s\" every :::%d::%d u 1:($2==%d ? $3:1/0) \"%%lf %%lf",ageminpar,fage,subdirf2(fileresu,"VPL_"),nres-1,nres-1,nres);
           /* 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); */
         /* k1-1 error should be nres-1*/
           for (i=1; i<= nlstate ; i ++) {
             if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
             else        fprintf(ficgp," %%*lf (%%*lf)");
           }
           fprintf(ficgp,"\" t\"Forward prevalence\" w l lt 0,\"%s\" every :::%d::%d u 1:($2==%d ? $3+1.96*$4 : 1/0) \"%%lf %%lf",subdirf2(fileresu,"VPL_"),nres-1,nres-1,nres);
           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*$4 : 1/0) \"%%lf %%lf",subdirf2(fileresu,"VPL_"),nres-1,nres-1,nres); 
           for (i=1; i<= nlstate ; i ++) {
             if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
             else fprintf(ficgp," %%*lf (%%*lf)");
           }  
           /* fprintf(ficgp,"\" t\"\" w l lt 1,\"%s\" every :::%d::%d u 1:($%d) t\"Observed prevalence\" w l lt 2",subdirf2(fileresu,"P_"),k1-1,k1-1,2+4*(cpt-1)); */
           
           fprintf(ficgp,"\" t\"\" w l lt 1,\"%s\" u 1:((",subdirf2(fileresu,"P_"));
           if(cptcoveff ==0){
             fprintf(ficgp,"$%d)) t 'Observed prevalence in state %d' with line lt 3",      2+3*(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 *\/ */
               lv=codtabm(k1,TnsdVar[Tvaraff[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];
               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)? $%d : 1/0) t 'Observed prevalence in state %d' w l lt 2",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][lv], \
                         2+cptcoveff*2+3*(cpt-1),  cpt );  /* 4 or 6 ?*/
               }else{
                 fprintf(ficgp,"$%d==%d && $%d==%d && ",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][lv]);
                 kl++;
               }
             } /* end covariate */
           } /* end if no covariate */
   
           if(prevbcast==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 *\/ */
                 lv=codtabm(k1,TnsdVar[Tvaraff[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]; */
                 vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])];
                 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]][codtabm(k1,TnsdVar[Tvaraff[k]])]);
                   kl++;
                 }
               } /* end covariate */
             } /* end if no covariate */
             if(prevbcast == 1){
               fprintf(ficgp,", \"%s\" every :::%d::%d u 1:($2==%d ? $3:1/0) \"%%lf %%lf",subdirf2(fileresu,"VBL_"),nres-1,nres-1,nres);
               /* k1-1 error should be nres-1*/
               for (i=1; i<= nlstate ; i ++) {
                 if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
                 else        fprintf(ficgp," %%*lf (%%*lf)");
               }
               fprintf(ficgp,"\" t\"Backward (stable) prevalence\" w l lt 6 dt 3,\"%s\" every :::%d::%d u 1:($2==%d ? $3+1.96*$4 : 1/0) \"%%lf %%lf",subdirf2(fileresu,"VBL_"),nres-1,nres-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 4,\"%s\" every :::%d::%d u 1:($2==%d ? $3-1.96*$4 : 1/0) \"%%lf %%lf",subdirf2(fileresu,"VBL_"),nres-1,nres-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 4");
             } /* end if backprojcast */
           } /* end if prevbcast */
           /* fprintf(ficgp,"\nset out ;unset label;\n"); */
           fprintf(ficgp,"\nset out ;unset title;\n");
         } /* nres */
       /* } /\* k1 *\/ */
     } /* cpt */
   
     
     /*2 eme*/
     /* for (k1=1; k1<= m ; k1 ++){   */
       for(nres=1; nres <= nresult; nres++){ /* For each resultline */
         k1=TKresult[nres];
         if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
         /* if(m != 1 && TKresult[nres]!= k1) */
         /*        continue; */
         fprintf(ficgp,"\n# 2nd: Total life expectancy with CI: 't' files ");
         strcpy(gplotlabel,"(");
         for (k=1; k<=cptcovs; k++){    /* For each covariate k get corresponding value lv for combination k1 */
           fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
           sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
         /* 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 *\\/ *\/ */
         /*        lv=codtabm(k1,TnsdVar[Tvaraff[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]; *\/ */
         /*        vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
         /*        fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
         /*        sprintf(gplotlabel+strlen(gplotlabel)," 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]); */
         /*        sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
         }
         strcpy(gplotlabel+strlen(gplotlabel),")");
         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*/
           fprintf(ficgp,"\nset label \"popbased %d %s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",vpopbased,gplotlabel);
           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_"),nres-1,nres-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_"),nres-1,nres-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_"),nres-1,nres-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; unset label;\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 */
         k1=TKresult[nres];
         if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
         /* if(m != 1 && TKresult[nres]!= k1) */
         /*        continue; */
   
         for (cpt=1; cpt<= nlstate ; cpt ++) { /* Fragile no verification of covariate values */
           fprintf(ficgp,"\n\n# 3d: Life expectancy with EXP_ files:  combination=%d state=%d",k1, cpt);
           strcpy(gplotlabel,"(");
           for (k=1; k<=cptcovs; k++){    /* For each covariate k get corresponding value lv for combination k1 */
             fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
             sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
           /* 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 *\\/ *\/ */
           /*   lv= codtabm(k1,TnsdVar[Tvaraff[k]]); /\* 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]; *\/ */
           /*   vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
           /*   fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
           /*   sprintf(gplotlabel+strlen(gplotlabel)," 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][resultmodel[nres][k4]]); */
           /*   sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][resultmodel[nres][k4]]); */
           }
           strcpy(gplotlabel+strlen(gplotlabel),")");
           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 label \"%s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",gplotlabel);
           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_"),nres-1,nres-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_"),nres-1,nres-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_"),nres-1,nres-1,k+nlstate,cpt);
         }
         fprintf(ficgp,"\nunset label;\n");
       } /* 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 */
         k1=TKresult[nres];
         if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
         /* if(m != 1 && TKresult[nres]!= k1) */
         /*        continue; */
         for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state cpt*/
           strcpy(gplotlabel,"(");
           fprintf(ficgp,"\n#\n#\n# Survival functions in state %d : 'LIJ_' files, cov=%d state=%d", cpt, k1, cpt);
           for (k=1; k<=cptcovs; k++){    /* For each covariate k get corresponding value lv for combination k1 */
             fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
             sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
           /* for (k=1; k<=cptcoveff; k++){    /\* For each covariate and each value *\/ */
           /*   lv=codtabm(k1,TnsdVar[Tvaraff[k]]); */
           /*   /\* 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]; *\/ */
           /*   vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
           /*   fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
           /*   sprintf(gplotlabel+strlen(gplotlabel)," 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][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
           /*   sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
           }       
           strcpy(gplotlabel+strlen(gplotlabel),")");
           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 label \"Alive state %d %s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",cpt,gplotlabel);
           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; unset label;\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 */
         k1=TKresult[nres];
         if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
         /* if(m != 1 && TKresult[nres]!= k1) */
         /*        continue; */
         for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each inital state  */
           strcpy(gplotlabel,"(");
           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<=cptcovs; k++){    /* For each covariate k get corresponding value lv for combination k1 */
             fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
             sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
           /* for (k=1; k<=cptcoveff; k++){    /\* For each covariate and each value *\/ */
           /*   lv=codtabm(k1,TnsdVar[Tvaraff[k]]); */
           /*   /\* 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]; *\/ */
           /*   vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
           /*   fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
           /*   sprintf(gplotlabel+strlen(gplotlabel)," 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][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
           /*   sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
           }       
           strcpy(gplotlabel+strlen(gplotlabel),")");
           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 label \"Alive state %d %s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",cpt,gplotlabel);
           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; unset label;\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 */
        k1=TKresult[nres];
        if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
        /* if(m != 1 && TKresult[nres]!= k1) */
        /*  continue; */
       for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state of arrival */
         strcpy(gplotlabel,"(");      
         fprintf(ficgp,"\n#\n#\n#CV preval stable (forward): 'pij' files, covariatecombination#=%d state=%d",k1, cpt);
         for (k=1; k<=cptcovs; k++){    /* For each covariate k get corresponding value lv for combination k1 */
           fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
           sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
         /* 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 *\\/ *\/ */
         /*        lv=codtabm(k1,TnsdVar[Tvaraff[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]; *\/ */
         /*        vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
         /*        fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
         /*        sprintf(gplotlabel+strlen(gplotlabel)," 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][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
         /*        sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
         } 
         strcpy(gplotlabel+strlen(gplotlabel),")");
         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 label \"Alive state %d %s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",cpt,gplotlabel);
         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 ++){ /* State of origin */
           if(i==1)
             fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJ_"));
           else
             fprintf(ficgp,", '' ");
           l=(nlstate+ndeath)*(i-1)+1; /* 1, 1+ nlstate+ndeath, 1+2*(nlstate+ndeath) */
           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; unset label;\n");
       } /* end cpt state*/ 
     } /* end covariate */  
     
     
   /* 7eme */
     if(prevbcast == 1){
       /* CV backward prevalence  for each covariate */
       /* for (k1=1; k1<= m ; k1 ++) /\* For each covariate combination if any *\/ */
       for(nres=1; nres <= nresult; nres++){ /* For each resultline */
         k1=TKresult[nres];
         if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
         /* if(m != 1 && TKresult[nres]!= k1) */
         /*        continue; */
         for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life origin state */
           strcpy(gplotlabel,"(");      
           fprintf(ficgp,"\n#\n#\n#CV Backward stable prevalence: 'pijb' files, covariatecombination#=%d state=%d",k1, cpt);
           for (k=1; k<=cptcovs; k++){    /* For each covariate k get corresponding value lv for combination k1 */
             fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
             sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
           /* 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 *\\/ *\/ */
           /*   lv=codtabm(k1,TnsdVar[Tvaraff[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]; *\/ */
           /*   vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
           /*   fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
           /*   sprintf(gplotlabel+strlen(gplotlabel)," 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][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
           /*   sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
           }       
           strcpy(gplotlabel+strlen(gplotlabel),")");
           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 label \"Origin alive state %d %s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",cpt,gplotlabel);
           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 ++){ /* State of arrival */
             if(i==1)
               fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJB_"));
             else
               fprintf(ficgp,", '' ");
             /* l=(nlstate+ndeath)*(i-1)+1; */
             l=(nlstate+ndeath)*(cpt-1)+1; /* fixed for i; cpt=1 1, cpt=2 1+ nlstate+ndeath, 1+2*(nlstate+ndeath) */
             /* fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d/($%d",k1,k+l+(cpt-1),k+l); /\* a veÌrifier *\/ */
             /* fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d/($%d",k1,k+l+(cpt-1),k+l+(cpt-1)+i-1); /\* a veÌrifier *\/ */
             fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d",k1,k+l+i-1); /* To be verified */
             /* 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",cpt,i);
           } /* nlstate */
           fprintf(ficgp,"\nset out; unset label;\n");
         } /* end cpt state*/ 
       } /* end covariate */  
     } /* End if prevbcast */
     
     /* 8eme */
     if(prevfcast==1){
       /* Projection from cross-sectional to forward stable (period) prevalence for each covariate */
       
       /* for (k1=1; k1<= m ; k1 ++) /\* For each covariate combination if any *\/ */
       for(nres=1; nres <= nresult; nres++){ /* For each resultline */
         k1=TKresult[nres];
         if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
         /* if(m != 1 && TKresult[nres]!= k1) */
         /*        continue; */
         for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state */
           strcpy(gplotlabel,"(");      
           fprintf(ficgp,"\n#\n#\n#Projection of prevalence to forward stable prevalence (period): 'PROJ_' files, covariatecombination#=%d state=%d",k1, cpt);
           for (k=1; k<=cptcovs; k++){    /* For each covariate k get corresponding value lv for combination k1 */
             fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
             sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
           /* 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 *\\/ *\/ */
           /*   lv=codtabm(k1,TnsdVar[Tvaraff[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]; *\/ */
           /*   vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
           /*   fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
           /*   sprintf(gplotlabel+strlen(gplotlabel)," 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][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
           /*   sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
           }       
           strcpy(gplotlabel+strlen(gplotlabel),")");
           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 label \"Alive state %d %s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",cpt,gplotlabel);
           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 *\/ */
           istart=nlstate+1; /* Could be one if by state, but nlstate+1 is w.i projection only */
           /*istart=1;*/ /* Could be one if by state, but nlstate+1 is w.i projection only */
           for (i=istart; 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==istart){
               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)):1 t 'pw.%d' with line lc variable ",        \
                         ioffset+(cpt-1)*(nlstate+1)+1+(i-1),  ioffset+1+(i-1)+(nlstate+1)*nlstate,cpt );
                 fprintf(ficgp,",\\\n '' ");
                 fprintf(ficgp," u %d:(",ioffset); 
                 fprintf(ficgp," (($1-$2) == %d ) ? $%d/(1.-$%d) : 1/0):1 with labels center not ", \
                        offyear,                           \
                         ioffset+(cpt-1)*(nlstate+1)+1+(i-1),  ioffset+1+(i-1)+(nlstate+1)*nlstate );
               }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 */
               ioffset=2*cptcoveff+2; /* Age is in 4 or 6 or etc.*/
               /*#  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 */
               iyearc=ioffset-1;
               iagec=ioffset;
               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 *\/ */
                 lv=codtabm(k1,TnsdVar[Tvaraff[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] *\/ */
                 vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[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):%d t 'p.%d' with line lc variable", gplotcondition, \
                         ioffset+(cpt-1)*(nlstate+1)+1+(i-1),  ioffset+1+(i-1)+(nlstate+1)*nlstate,iyearc, cpt );
                 fprintf(ficgp,",\\\n '' ");
                 fprintf(ficgp," u %d:(",iagec); 
                 fprintf(ficgp,"%s && (($%d-$%d) == %d ) ? $%d/(1.-$%d) : 1/0):%d with labels center not ", gplotcondition, \
                         iyearc, iagec, offyear,                           \
                         ioffset+(cpt-1)*(nlstate+1)+1+(i-1),  ioffset+1+(i-1)+(nlstate+1)*nlstate, iyearc );
   /*  '' u 6:(($1==1 && $2==0  && $3==2 && $4==0) && (($5-$6) == 1947) ? $10/(1.-$22) : 1/0):5 with labels center boxed not*/
               }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; unset label;\n");
         } /* end cpt state*/
       } /* end covariate */
     } /* End if prevfcast */
     
     if(prevbcast==1){
       /* Back projection from cross-sectional to stable (mixed) for each covariate */
       
       /* for (k1=1; k1<= m ; k1 ++) /\* For each covariate combination if any *\/ */
       for(nres=1; nres <= nresult; nres++){ /* For each resultline */
        k1=TKresult[nres];
        if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
          /* if(m != 1 && TKresult[nres]!= k1) */
          /*       continue; */
         for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state */
           strcpy(gplotlabel,"(");      
           fprintf(ficgp,"\n#\n#\n#Back projection of prevalence to stable (mixed) back prevalence: 'BPROJ_' files, covariatecombination#=%d originstate=%d",k1, cpt);
           for (k=1; k<=cptcovs; k++){    /* For each covariate k get corresponding value lv for combination k1 */
             fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
             sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
           /* 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 *\\/ *\/ */
           /*   lv= codtabm(k1,TnsdVar[Tvaraff[k]]); /\* 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]; *\/ */
           /*   vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
           /*   fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
           /*   sprintf(gplotlabel+strlen(gplotlabel)," 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][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
           /*   sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
           }       
           strcpy(gplotlabel+strlen(gplotlabel),")");
           fprintf(ficgp,"\n#\n");
           if(invalidvarcomb[k1]){
             fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1); 
             continue;
           }
           
           fprintf(ficgp,"# hbijx=backprobability over h years, hb.jx is weighted by observed prev at destination state\n ");
           fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"PROJB_"),cpt,k1,nres);
           fprintf(ficgp,"set label \"Origin alive state %d %s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",cpt,gplotlabel);
           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 *\/ */
           istart=nlstate+1; /* Could be one if by state, but nlstate+1 is w.i projection only */
           /*istart=1;*/ /* Could be one if by state, but nlstate+1 is w.i projection only */
           for (i=istart; 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==istart){
               fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"FB_"));
             }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)):1 t 'bw%d' with line lc variable ", \
                         ioffset+(cpt-1)*(nlstate+1)+1+(i-1),  ioffset+1+(i-1)+(nlstate+1)*nlstate,cpt );
                 fprintf(ficgp,",\\\n '' ");
                 fprintf(ficgp," u %d:(",ioffset); 
                 fprintf(ficgp," (($1-$2) == %d ) ? $%d : 1/0):1 with labels center not ", \
                        offbyear,                          \
                         ioffset+(cpt-1)*(nlstate+1)+1+(i-1) );
               }else
                 fprintf(ficgp," $%d/(1.-$%d)) t 'b%d%d' with line ",      \
                         ioffset+(cpt-1)*(nlstate+1)+1+(i-1),  ioffset+1+(i-1)+(nlstate+1)*nlstate,cpt,i );
             }else{ /* more than 2 covariates */
               ioffset=2*cptcoveff+2; /* Age is in 4 or 6 or etc.*/
               /*#  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 */
               iyearc=ioffset-1;
               iagec=ioffset;
               fprintf(ficgp," u %d:(",ioffset); 
               kl=0;
               strcpy(gplotcondition,"(");
               for (k=1; k<=cptcovs; k++){    /* For each covariate k of the resultline, get corresponding value lv for combination k1 */
                 if(Dummy[modelresult[nres][k]]==0){  /* To be verified */
                   /* 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 *\/ */
                   /* lv= codtabm(k1,TnsdVar[Tvaraff[k]]); /\* Should be the covariate value corresponding to combination k1 and covariate k *\/ */
                   lv=Tvresult[nres][k];
                   vlv=TinvDoQresult[nres][Tvresult[nres][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] *\/ */
                   /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
                   kl++;
                   /* sprintf(gplotcondition+strlen(gplotcondition),"$%d==%d && $%d==%d " ,kl,Tvaraff[k], kl+1, nbcode[Tvaraff[k]][lv]); */
                   sprintf(gplotcondition+strlen(gplotcondition),"$%d==%d && $%d==%lg " ,kl,Tvresult[nres][k], kl+1,TinvDoQresult[nres][Tvresult[nres][k]]);
                   kl++;
                   if(k <cptcovs && cptcovs>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 : 1/0):%d t 'bw%d' with line lc variable", gplotcondition, \
                         ioffset+(cpt-1)*(nlstate+1)+1+(i-1),iyearc,cpt );
                 fprintf(ficgp,",\\\n '' ");
                 fprintf(ficgp," u %d:(",iagec); 
                 /* fprintf(ficgp,"%s && (($5-$6) == %d ) ? $%d/(1.-$%d) : 1/0):5 with labels center not ", gplotcondition, \ */
                 fprintf(ficgp,"%s && (($%d-$%d) == %d ) ? $%d : 1/0):%d with labels center not ", gplotcondition, \
                         iyearc,iagec,offbyear,                            \
                         ioffset+(cpt-1)*(nlstate+1)+1+(i-1), iyearc );
   /*  '' u 6:(($1==1 && $2==0  && $3==2 && $4==0) && (($5-$6) == 1947) ? $10/(1.-$22) : 1/0):5 with labels center boxed not*/
               }else{
                 /* fprintf(ficgp,"%s ? $%d/(1.-$%d) : 1/0) t 'p%d%d' with line ", gplotcondition, \ */
                 fprintf(ficgp,"%s ? $%d : 1/0) t 'b%d%d' with line ", gplotcondition, \
                         ioffset+(cpt-1)*(nlstate+1)+1+(i-1), cpt,i );
               }
             } /* end if covariate */
           } /* nlstate */
           fprintf(ficgp,"\nset out; unset label;\n");
         } /* end cpt state*/
       } /* end covariate */
     } /* End if prevbcast */
     
     
     /* 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=1+age+%s \n",model);
       fprintf(ficgp,"# Type of graphic ng=%d\n",ng);
       fprintf(ficgp,"#   k1=1 to 2^%d=%d\n",cptcoveff,m);/* to be checked */
       /* for(k1=1; k1 <=m; k1++)  /\* For each combination of covariate *\/ */
       for(nres=1; nres <= nresult; nres++){ /* For each resultline */
        /* k1=nres; */
         k1=TKresult[nres];
         if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
         fprintf(ficgp,"\n\n# Resultline k1=%d ",k1);
         strcpy(gplotlabel,"(");
         /*sprintf(gplotlabel+strlen(gplotlabel)," Dummy combination %d ",k1);*/
         for (k=1; k<=cptcovs; k++){  /**< cptcovs number of SIMPLE covariates in the model V2+V1 =2 (dummy or quantit or time varying) */
           /* for each resultline nres, and position k, Tvresult[nres][k] gives the name of the variable and
              TinvDoQresult[nres][Tvresult[nres][k]] gives its value double or integer) */
           fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
           sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
         }
         /* if(m != 1 && TKresult[nres]!= k1) */
         /*        continue; */
         /* fprintf(ficgp,"\n\n# Combination of dummy  k1=%d which is ",k1); */
         /* strcpy(gplotlabel,"("); */
         /* /\*sprintf(gplotlabel+strlen(gplotlabel)," Dummy combination %d ",k1);*\/ */
         /* 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 *\\/ *\/ */
         /*        lv= codtabm(k1,TnsdVar[Tvaraff[k]]); /\* 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]; *\/ */
         /*        vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
         /*        fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
         /*        sprintf(gplotlabel+strlen(gplotlabel)," 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][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
         /*        sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
         /* }       */
         strcpy(gplotlabel+strlen(gplotlabel),")");
         fprintf(ficgp,"\n#\n");
         fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" ",subdirf2(optionfilefiname,"PE_"),k1,ng,nres);
         fprintf(ficgp,"\nset key outside ");
         /* fprintf(ficgp,"\nset label \"%s\" at graph 1.2,0.5 center rotate font \"Helvetica,12\"\n",gplotlabel); */
         fprintf(ficgp,"\nset title \"%s\" font \"Helvetica,12\"\n",gplotlabel);
         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); */
                 switch(Typevar[j]){
                 case 1:
                   if(cptcovage >0){ /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, 2 V5 and V1 */
                     if(j==Tage[ij]) { /* Product by age  To be looked at!!*//* Bug valgrind */
                       if(ij <=cptcovage) { /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, 2 V5 and V1 */
                         if(DummyV[j]==0){/* Bug valgrind */
                           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(k1,Tvar[j-2])]); */
                         }
                         ij++;
                       }
                     }
                   }
                   break;
                 case 2:
                   if(cptcovprod >0){
                     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(k1,j)],nbcode[Tvard[ijp][2]][codtabm(k1,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(k1,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++;
                       }
                     } /* end Tprod */
                   }
                   break;
                 case 0:
                   /* simple covariate */
                   /* fprintf(ficgp,"+p%d*%d",i+j+2+nagesqr-1,nbcode[Tvar[j]][codtabm(k1,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(k1,Tvar[j-2])]); */
                   }
                  /* end simple */
                   break;
                 default:
                   break;
                 } /* end switch */
               } /* end j */
             }else{ /* k=k2 */
               if(ng !=1 ){ /* For logit formula of log p11 is more difficult to get */
                 fprintf(ficgp," (1.");i=i-ncovmodel;
               }else
                 i=i-ncovmodel;
             }
             
             if(ng != 1){
               fprintf(ficgp,")/(1");
               
               for(cpt=1; cpt <=nlstate; cpt++){ 
                 if(nagesqr==0)
                   fprintf(ficgp,"+exp(p%d+p%d*x",k3+(cpt-1)*ncovmodel,k3+(cpt-1)*ncovmodel+1);
                 else /* nagesqr =1 */
                   fprintf(ficgp,"+exp(p%d+p%d*x+p%d*x*x",k3+(cpt-1)*ncovmodel,k3+(cpt-1)*ncovmodel+1,k3+(cpt-1)*ncovmodel+1+nagesqr);
                  
                 ij=1;
                 ijp=1;
                 /* for(j=3; j <=ncovmodel-nagesqr; j++){ */
                 for(j=1; j <=cptcovt; j++) { /* For each covariate of the simplified model */
                   switch(Typevar[j]){
                   case 1:
                     if(cptcovage >0){ 
                       if(j==Tage[ij]) { /* Bug valgrind */
                         if(ij <=cptcovage) { /* Bug valgrind */
                           if(DummyV[j]==0){/* Bug valgrind */
                             /* fprintf(ficgp,"+p%d*%d*x",k3+(cpt-1)*ncovmodel+1+j-2+nagesqr,nbcode[Tvar[j-2]][codtabm(k1,j-2)]); */
                             /* fprintf(ficgp,"+p%d*%d*x",k3+(cpt-1)*ncovmodel+1+j+nagesqr,nbcode[Tvar[j]][codtabm(k1,j)]); */
                             fprintf(ficgp,"+p%d*%d*x",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tinvresult[nres][Tvar[j]]);
                             /* fprintf(ficgp,"+p%d*%d*x",i+j+2+nagesqr-1,Tinvresult[nres][Tvar[j]]);; */
                             /* fprintf(ficgp,"+p%d*%d*x",k3+(cpt-1)*ncovmodel+1+j-2+nagesqr,nbcode[Tvar[j-2]][codtabm(k1,Tvar[j-2])]); */
                           }else{ /* quantitative */
                             /* fprintf(ficgp,"+p%d*%f*x",i+j+2+nagesqr-1,Tqinvresult[nres][Tvar[j]]); /\* Tqinvresult in decoderesult *\/ */
                             fprintf(ficgp,"+p%d*%f*x",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tqinvresult[nres][Tvar[j]]); /* Tqinvresult in decoderesult */
                             /* 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(k1,Tvar[j-2])]); */
                           }
                           ij++;
                         }
                       }
                     }
                     break;
                   case 2:
                     if(cptcovprod >0){
                       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(k1,j)],nbcode[Tvard[ijp][2]][codtabm(k1,j)]); */
                               fprintf(ficgp,"+p%d*%d*%d",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tinvresult[nres][Tvard[ijp][1]],Tinvresult[nres][Tvard[ijp][2]]);
                               /* 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(k1,j)],Tqinvresult[nres][Tvard[ijp][2]]); */
                               fprintf(ficgp,"+p%d*%d*%f",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tinvresult[nres][Tvard[ijp][1]],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",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tinvresult[nres][Tvard[ijp][2]],Tqinvresult[nres][Tvard[ijp][1]]);
                               /* 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",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tqinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]);
                               /* fprintf(ficgp,"+p%d*%f*%f",i+j+2+nagesqr-1,Tqinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]); */
                             } 
                           }
                           ijp++;
                         }
                       } /* end Tprod */
                     } /* end if */
                     break;
                   case 0: 
                     /* simple covariate */
                     /* fprintf(ficgp,"+p%d*%d",i+j+2+nagesqr-1,nbcode[Tvar[j]][codtabm(k1,j)]); /\* Valgrind bug nbcode *\/ */
                     if(Dummy[j]==0){
                       /* fprintf(ficgp,"+p%d*%d",i+j+2+nagesqr-1,Tinvresult[nres][Tvar[j]]); /\*  *\/ */
                       fprintf(ficgp,"+p%d*%d",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tinvresult[nres][Tvar[j]]); /*  */
                       /* fprintf(ficgp,"+p%d*%d",i+j+2+nagesqr-1,Tinvresult[nres][Tvar[j]]); /\*  *\/ */
                     }else{ /* quantitative */
                       fprintf(ficgp,"+p%d*%f",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tqinvresult[nres][Tvar[j]]); /* */
                       /* 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(k1,Tvar[j-2])]); */
                     }
                     /* end simple */
                     /* fprintf(ficgp,"+p%d*%d",k3+(cpt-1)*ncovmodel+1+j-2+nagesqr,nbcode[Tvar[j-2]][codtabm(k1,j-2)]);/\* Valgrind bug nbcode *\/ */
                     break;
                   default:
                     break;
                   } /* end switch */
                 }
                 fprintf(ficgp,")");
               }
               fprintf(ficgp,")");
               if(ng ==2)
                 fprintf(ficgp," w l lw 2 lt (%d*%d+%d)%%%d+1 dt %d t \"p%d%d\" ", nlstate+ndeath, k2, k, nlstate+ndeath, k2, k2,k);
               else /* ng= 3 */
                 fprintf(ficgp," w l lw 2 lt (%d*%d+%d)%%%d+1 dt %d t \"i%d%d\" ",  nlstate+ndeath, k2, k, nlstate+ndeath, k2, k2,k);
             }else{ /* end ng <> 1 */
               if( k !=k2) /* logit p11 is hard to draw */
                 fprintf(ficgp," w l lw 2 lt (%d*%d+%d)%%%d+1 dt %d t \"logit(p%d%d)\" ",  nlstate+ndeath, k2, k, nlstate+ndeath, k2, 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; unset label;set key default;\n"); */
         fprintf(ficgp,"\n set out; unset title;set key default;\n");
       } /* end resultline */
     } /* 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;
      int firstA1=0, firstA2=0;
   
      double sum=0., sumr=0.;
      double age;
      double *sumnewp, *sumnewm, *sumnewmr;
      double *agemingood, *agemaxgood; 
      double *agemingoodr, *agemaxgoodr; 
     
     
      /* 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);
      sumnewmr = vector(1,ncovcombmax);
      agemingood = vector(1,ncovcombmax);  
      agemingoodr = vector(1,ncovcombmax); 
      agemaxgood = vector(1,ncovcombmax);
      agemaxgoodr = vector(1,ncovcombmax);
   
      for (cptcod=1;cptcod<=ncovcombmax;cptcod++){
        sumnewm[cptcod]=0.; sumnewmr[cptcod]=0.;
        sumnewp[cptcod]=0.;
        agemingood[cptcod]=0, agemingoodr[cptcod]=0;
        agemaxgood[cptcod]=0, agemaxgoodr[cptcod]=0;
      }
      if (cptcovn<1) ncovcombmax=1; /* At least 1 pass */
     
      if(mobilav==-1 || mobilav==1||mobilav ==3 ||mobilav==5 ||mobilav== 7){
        if(mobilav==1 || 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 (cptcod=1;cptcod<=ncovcombmax;cptcod++){
              sumnewm[cptcod]=0.;
              for (i=1; i<=nlstate;i++){
                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;
                sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
              } /* end i */
              if(sumnewm[cptcod] >1.e-3) mobaverage[(int)age][i][cptcod]=mobaverage[(int)age][i][cptcod]/sumnewm[cptcod]; /* Rescaling to sum one */
            } /* end cptcod */
          }/* end age */
        }/* end mob */
      }else{
        printf("Error internal in movingaverage, mobilav=%d.\n",mobilav);
        return -1;
      }
   
      for (cptcod=1;cptcod<=ncovcombmax;cptcod++){ /* for each combination */
        /* 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;
        }
   
        for (age=fage-(mob-1)/2; age>=bage+(mob-1)/2; age--){ /*looking for the youngest and oldest good age */
          sumnewm[cptcod]=0.;
          sumnewmr[cptcod]=0.;
          for (i=1; i<=nlstate;i++){
            sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
            sumnewmr[cptcod]+=probs[(int)age][i][cptcod];
          }
          if(fabs(sumnewmr[cptcod] - 1.) <= 1.e-3) { /* good without smoothing */
            agemingoodr[cptcod]=age;
          }
          if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
              agemingood[cptcod]=age;
          }
        } /* age */
        for (age=bage+(mob-1)/2; age<=fage-(mob-1)/2; age++){ /*looking for the youngest and oldest good age */
          sumnewm[cptcod]=0.;
          sumnewmr[cptcod]=0.;
          for (i=1; i<=nlstate;i++){
            sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
            sumnewmr[cptcod]+=probs[(int)age][i][cptcod];
          }
          if(fabs(sumnewmr[cptcod] - 1.) <= 1.e-3) { /* good without smoothing */
            agemaxgoodr[cptcod]=age;
          }
          if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
            agemaxgood[cptcod]=age;
          }
        } /* age */
        /* Thus we have agemingood and agemaxgood as well as goodr for raw (preobs) */
        /* but they will change */
        firstA1=0;firstA2=0;
        for (age=fage-(mob-1)/2; age>=bage; age--){/* From oldest to youngest, filling up to the youngest */
          sumnewm[cptcod]=0.;
          sumnewmr[cptcod]=0.;
          for (i=1; i<=nlstate;i++){
            sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
            sumnewmr[cptcod]+=probs[(int)age][i][cptcod];
          }
          if(mobilav==-1){ /* Forcing raw ages if good else agemingood */
            if(fabs(sumnewmr[cptcod] - 1.) <= 1.e-3) { /* good without smoothing */
              agemaxgoodr[cptcod]=age;  /* age min */
              for (i=1; i<=nlstate;i++)
                mobaverage[(int)age][i][cptcod]=probs[(int)age][i][cptcod];
            }else{ /* bad we change the value with the values of good ages */
              for (i=1; i<=nlstate;i++){
                mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemaxgoodr[cptcod]][i][cptcod];
              } /* i */
            } /* end bad */
          }else{
            if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
              agemaxgood[cptcod]=age;
            }else{ /* bad we change the value with the values of good ages */
              for (i=1; i<=nlstate;i++){
                mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemaxgood[cptcod]][i][cptcod];
              } /* i */
            } /* end bad */
          }/* end else */
          sum=0.;sumr=0.;
          for (i=1; i<=nlstate;i++){
            sum+=mobaverage[(int)age][i][cptcod];
            sumr+=probs[(int)age][i][cptcod];
          }
          if(fabs(sum - 1.) > 1.e-3) { /* bad */
            if(!firstA1){
              firstA1=1;
              printf("Moving average A1: For this combination of covariate cptcod=%d, we can't get a smoothed prevalence which sums to one (%f) at any descending age! age=%d, could you increase bage=%d. Others in log file...\n",cptcod,sumr, (int)age, (int)bage);
            }
            fprintf(ficlog,"Moving average A1: For this combination of covariate cptcod=%d, we can't get a smoothed prevalence which sums to one (%f) at any descending age! age=%d, could you increase bage=%d\n",cptcod,sumr, (int)age, (int)bage);
          } /* end bad */
          /* else{ /\* We found some ages summing to one, we will smooth the oldest *\/ */
          if(fabs(sumr - 1.) > 1.e-3) { /* bad */
            if(!firstA2){
              firstA2=1;
              printf("Moving average A2: For this combination of covariate cptcod=%d, the raw prevalence doesn't sums to one (%f) even with smoothed values at young ages! age=%d, could you increase bage=%d. Others in log file...\n",cptcod,sumr, (int)age, (int)bage);
            }
            fprintf(ficlog,"Moving average A2: For this combination of covariate cptcod=%d, the raw prevalence doesn't sums to one (%f) even with smoothed values at young ages! age=%d, could you increase bage=%d\n",cptcod,sumr, (int)age, (int)bage);
          } /* end bad */
        }/* age */
   
        for (age=bage+(mob-1)/2; age<=fage; age++){/* From youngest, finding the oldest wrong */
          sumnewm[cptcod]=0.;
          sumnewmr[cptcod]=0.;
          for (i=1; i<=nlstate;i++){
            sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
            sumnewmr[cptcod]+=probs[(int)age][i][cptcod];
          } 
          if(mobilav==-1){ /* Forcing raw ages if good else agemingood */
            if(fabs(sumnewmr[cptcod] - 1.) <= 1.e-3) { /* good */
              agemingoodr[cptcod]=age;
              for (i=1; i<=nlstate;i++)
                mobaverage[(int)age][i][cptcod]=probs[(int)age][i][cptcod];
            }else{ /* bad we change the value with the values of good ages */
              for (i=1; i<=nlstate;i++){
                mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemingoodr[cptcod]][i][cptcod];
              } /* i */
            } /* end bad */
          }else{
            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 */
          }/* end else */
          sum=0.;sumr=0.;
          for (i=1; i<=nlstate;i++){
            sum+=mobaverage[(int)age][i][cptcod];
            sumr+=mobaverage[(int)age][i][cptcod];
          }
          if(fabs(sum - 1.) > 1.e-3) { /* bad */
            printf("Moving average B1: For this combination of covariate cptcod=%d, we can't get a smoothed prevalence which sums to one (%f) at any descending age! age=%d, could you decrease fage=%d?\n",cptcod, sum, (int) age, (int)fage);
          } /* end bad */
          /* else{ /\* We found some ages summing to one, we will smooth the oldest *\/ */
          if(fabs(sumr - 1.) > 1.e-3) { /* bad */
            printf("Moving average B2: For this combination of covariate cptcod=%d, the raw prevalence doesn't sums to one (%f) even with smoothed values at young ages! age=%d, could you increase fage=%d\n",cptcod,sumr, (int)age, (int)fage);
          } /* end bad */
        }/* age */
   
                   
        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(agemaxgoodr,1, ncovcombmax);
      free_vector(agemaxgood,1, ncovcombmax);
      free_vector(agemingood,1, ncovcombmax);
      free_vector(agemingoodr,1, ncovcombmax);
      free_vector(sumnewmr,1, ncovcombmax);
      free_vector(sumnewm,1, ncovcombmax);
      free_vector(sumnewp,1, ncovcombmax);
      return 0;
    }/* End movingaverage */
    
   
    
   /************** Forecasting ******************/
   /* void prevforecast(char fileres[], double dateintmean, double anprojd, double mprojd, double jprojd, double ageminpar, double agemax, double dateprev1, double dateprev2, int mobilav, double ***prev, double bage, double fage, int firstpass, int lastpass, double anprojf, double p[], int cptcoveff)*/
   void prevforecast(char fileres[], double dateintmean, double dateprojd, double dateprojf, double ageminpar, double agemax, double dateprev1, double dateprev2, int mobilav, double ***prev, double bage, double fage, int firstpass, int lastpass, double p[], int cptcoveff){
     /* dateintemean, mean date of interviews
        dateprojd, year, month, day of starting projection 
        dateprojf date of end of projection;year of end of projection (same day and month as proj1).
        agemin, agemax range of age
        dateprev1 dateprev2 range of dates during which prevalence is computed
     */
     /* double anprojd, mprojd, jprojd; */
     /* double anprojf, mprojf, jprojf; */
     int yearp, stepsize, hstepm, nhstepm, j, k, cptcod, i, h, i1, k4, nres=0;
     double agec; /* generic age */
     double agelim, ppij, yp,yp1,yp2;
     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;   
     }
     if(estepm > stepm){ /* Yes every two year */
       stepsize=2;
     }
     hstepm=hstepm/stepm;
   
     
     /* yp1=modf(dateintmean,&yp);/\* extracts integral of datemean in yp  and */
     /*                              fractional in yp1 *\/ */
     /* aintmean=yp; */
     /* yp2=modf((yp1*12),&yp); */
     /* mintmean=yp; */
     /* yp1=modf((yp2*30.5),&yp); */
     /* jintmean=yp; */
     /* if(jintmean==0) jintmean=1; */
     /* if(mintmean==0) mintmean=1; */
   
   
     /* date2dmy(dateintmean,&jintmean,&mintmean,&aintmean); */
     /* date2dmy(dateprojd,&jprojd, &mprojd, &anprojd); */
     /* date2dmy(dateprojf,&jprojf, &mprojf, &anprojf); */
     i1=pow(2,cptcoveff);
     if (cptcovn < 1){i1=1;}
     
     fprintf(ficresf,"# Mean day of interviews %.lf/%.lf/%.lf (%.2f) between %.2f and %.2f \n",jintmean,mintmean,aintmean,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++){ /* We want to find the combination k corresponding to the values of the dummies given in this resut line (to be cleaned one day) */
       if(i1 != 1 && TKresult[nres]!= k)
         continue;
       if(invalidvarcomb[k]){
         printf("\nCombination (%d) projection ignored because no cases \n",k); 
         continue;
       }
       fprintf(ficresf,"\n#****** hpijx=probability over h years, hp.jx is weighted by observed prev \n#");
       for(j=1;j<=cptcoveff;j++) {
         /* fprintf(ficresf," V%d (=) %d",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,Tvaraff[j])]); */
         fprintf(ficresf," V%d (=) %d",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[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<=(anprojf-anprojd);yearp +=stepsize) {
         fprintf(ficresf,"\n");
         fprintf(ficresf,"\n# Forecasting at date %.lf/%.lf/%.lf ",jprojd,mprojd,anprojd+yearp);   
         /* for (agec=fage; agec>=(ageminpar-1); agec--){  */
         for (agec=fage; agec>=(bage); 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;
           /* We compute pii at age agec over nhstepm);*/
           hpxij(p3mat,nhstepm,agec,hstepm,p,nlstate,stepm,oldm,savm, k,nres);
           /* Then we print p3mat for h corresponding to the right agec+h*stepms=yearp */
           for (h=0; h<=nhstepm; h++){
             if (h*hstepm/YEARM*stepm ==yearp) {
               break;
             }
           }
           fprintf(ficresf,"\n");
           for(j=1;j<=cptcoveff;j++) 
             /* fprintf(ficresf,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,Tvaraff[j])]); /\* Tvaraff not correct *\/ */
             fprintf(ficresf,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); /* TnsdVar[Tvaraff]  correct */
           fprintf(ficresf,"%.f %.f ",anprojd+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]*prev[(int)agec][i][k];
               else { /* even if mobilav==-1 we use mobaverage, probs may not sums to 1 */
                   ppij=ppij+p3mat[i][j][h]*probs[(int)(agec)][i][k];
               }
               fprintf(ficresf," %.3f", p3mat[i][j][h]);
             } /* end i */
             fprintf(ficresf," %.3f", ppij);
           }/* end j */
           free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
         } /* end agec */
         /* diffyear=(int) anproj1+yearp-ageminpar-1; */
         /*printf("Prevforecast %d+%d-%d=diffyear=%d\n",(int) anproj1, (int)yearp,(int)ageminpar,(int) anproj1-(int)ageminpar);*/
       } /* 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 ***prevacurrent, double anback1, double mback1, double jback1, double ageminpar, double agemax, double dateprev1, double dateprev2, int mobilav, double bage, double fage, int firstpass, int lastpass, double anback2, double p[], int cptcoveff){ */
    void prevbackforecast(char fileres[], double ***prevacurrent, double dateintmean, double dateprojd, double dateprojf, double ageminpar, double agemax, double dateprev1, double dateprev2, int mobilav, double bage, double fage, int firstpass, int lastpass, double p[], int cptcoveff){
     /* back1, year, month, day of starting backprojection
        agemin, agemax range of age
        dateprev1 dateprev2 range of dates during which prevalence is computed
        anback2 year of end of backprojection (same day and month as back1).
        prevacurrent and prev are prevalences.
     */
     int yearp, stepsize, hstepm, nhstepm, j, k, cptcod, i, h, i1, k4, nres=0;
     double agec; /* generic age */
     double agelim, ppij, ppi, yp,yp1,yp2; /* ,jintmean,mintmean,aintmean;*/
     double *popeffectif,*popcount;
     double ***p3mat;
     /* double ***mobaverage; */
     char fileresfb[FILENAMELENGTH];
    
     agelim=AGEINF;
     /* 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); */
   
     /*Do we need to compute prevalence again?*/
   
     /* 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("\nComputing back forecasting: result on file '%s', please wait... \n", fileresfb);
     fprintf(ficlog,"\nComputing back forecasting: result on file '%s', please wait... \n", fileresfb);
     
     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;   
     }
     if(estepm >= stepm){ /* Yes every two year */
       stepsize=2;
     }
     
     hstepm=hstepm/stepm;
     /* yp1=modf(dateintmean,&yp);/\* extracts integral of datemean in yp  and */
     /*                              fractional in yp1 *\/ */
     /* aintmean=yp; */
     /* yp2=modf((yp1*12),&yp); */
     /* mintmean=yp; */
     /* yp1=modf((yp2*30.5),&yp); */
     /* jintmean=yp; */
     /* if(jintmean==0) jintmean=1; */
     /* if(mintmean==0) jintmean=1; */
     
     i1=pow(2,cptcoveff);
     if (cptcovn < 1){i1=1;}
     
     fprintf(ficresfb,"# Mean day of interviews %.lf/%.lf/%.lf (%.2f) between %.2f and %.2f \n",jintmean,mintmean,aintmean,dateintmean,dateprev1,dateprev2);
     printf("# Mean day of interviews %.lf/%.lf/%.lf (%.2f) between %.2f and %.2f \n",jintmean,mintmean,aintmean,dateintmean,dateprev1,dateprev2);
     
     fprintf(ficresfb,"#****** Routine prevbackforecast **\n");
     
     for(nres=1; nres <= nresult; nres++) /* For each resultline */
     for(k=1; k<=i1;k++){
       if(i1 != 1 && TKresult[nres]!= k)
         continue;
       if(invalidvarcomb[k]){
         printf("\nCombination (%d) projection ignored because no cases \n",k); 
         continue;
       }
       fprintf(ficresfb,"\n#****** hbijx=probability over h years, hb.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,TnsdVar[Tvaraff[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(ficresfb," yearbproj age");
       for(j=1; j<=nlstate+ndeath;j++){
         for(i=1; i<=nlstate;i++)
           fprintf(ficresfb," b%d%d",i,j);
         fprintf(ficresfb," b.%d",j);
       }
       for (yearp=0; yearp>=(anbackf-anbackd);yearp -=stepsize) {
         /* for (yearp=0; yearp<=(anproj2-anproj1);yearp +=stepsize) {  */
         fprintf(ficresfb,"\n");
         fprintf(ficresfb,"\n# Back Forecasting at date %.lf/%.lf/%.lf ",jbackd,mbackd,anbackd+yearp);
         /* printf("\n# Back Forecasting at date %.lf/%.lf/%.lf ",jback1,mback1,anback1+yearp); */
         /* for (agec=bage; agec<=agemax-1; agec++){  /\* testing *\/ */
         for (agec=bage; agec<=fage; agec++){  /* testing */
           /* We compute bij at age agec over nhstepm, nhstepm decreases when agec increases because of agemax;*/
           nhstepm=(int) (agec-agelim) *YEARM/stepm;/*     nhstepm=(int) rint((agec-agelim)*YEARM/stepm);*/
           nhstepm = nhstepm/hstepm;
           p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
           oldm=oldms;savm=savms;
           /* computes hbxij at age agec over 1 to nhstepm */
           /* printf("####prevbackforecast debug  agec=%.2f nhstepm=%d\n",agec, nhstepm);fflush(stdout); */
           hbxij(p3mat,nhstepm,agec,hstepm,p,prevacurrent,nlstate,stepm, k, nres);
           /* hpxij(p3mat,nhstepm,agec,hstepm,p,             nlstate,stepm,oldm,savm, k,nres); */
           /* Then we print p3mat for h corresponding to the right agec+h*stepms=yearp */
           /* printf(" agec=%.2f\n",agec);fflush(stdout); */
           for (h=0; h<=nhstepm; h++){
             if (h*hstepm/YEARM*stepm ==-yearp) {
               break;
             }
           }
           fprintf(ficresfb,"\n");
           for(j=1;j<=cptcoveff;j++)
             fprintf(ficresfb,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]);
           fprintf(ficresfb,"%.f %.f ",anbackd+yearp,agec-h*hstepm/YEARM*stepm);
           for(i=1; i<=nlstate+ndeath;i++) {
             ppij=0.;ppi=0.;
             for(j=1; j<=nlstate;j++) {
               /* if (mobilav==1) */
               ppij=ppij+p3mat[i][j][h]*prevacurrent[(int)agec][j][k];
               ppi=ppi+prevacurrent[(int)agec][j][k];
               /* ppij=ppij+p3mat[i][j][h]*mobaverage[(int)agec][j][k]; */
               /* ppi=ppi+mobaverage[(int)agec][j][k]; */
                 /* else { */
                 /*        ppij=ppij+p3mat[i][j][h]*probs[(int)(agec)][i][k]; */
                 /* } */
               fprintf(ficresfb," %.3f", p3mat[i][j][h]);
             } /* end j */
             if(ppi <0.99){
               printf("Error in prevbackforecast, prevalence doesn't sum to 1 for state %d: %3f\n",i, ppi);
               fprintf(ficlog,"Error in prevbackforecast, prevalence doesn't sum to 1 for state %d: %3f\n",i, ppi);
             }
             fprintf(ficresfb," %.3f", ppij);
           }/* end j */
           free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
         } /* end agec */
       } /* end yearp */
     } /* end k */
     
     /* 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");
           
   }
   
   /* Variance of prevalence limit: varprlim */
    void varprlim(char fileresu[], int nresult, double ***prevacurrent, int mobilavproj, double bage, double fage, double **prlim, int *ncvyearp, double ftolpl, double p[], double **matcov, double *delti, int stepm, int cptcoveff){
       /*------- Variance of forward period (stable) prevalence------*/   
    
      char fileresvpl[FILENAMELENGTH];  
      FILE *ficresvpl;
      double **oldm, **savm;
      double **varpl; /* Variances of prevalence limits by age */   
      int i1, k, nres, j ;
      
       strcpy(fileresvpl,"VPL_");
       strcat(fileresvpl,fileresu);
       if((ficresvpl=fopen(fileresvpl,"w"))==NULL) {
         printf("Problem with variance of forward period (stable) prevalence  resultfile: %s\n", fileresvpl);
         exit(0);
       }
       printf("Computing Variance-covariance of forward period (stable) prevalence: file '%s' ...", fileresvpl);fflush(stdout);
       fprintf(ficlog, "Computing Variance-covariance of forward 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 */
          k=TKresult[nres];
          if(TKresult[nres]==0) k=1; /* To be checked for noresult */
        /* for(k=1; k<=i1;k++){ /\* We find the combination equivalent to result line values of dummies *\/ */
         if(i1 != 1 && TKresult[nres]!= k)
           continue;
         fprintf(ficresvpl,"\n#****** ");
         printf("\n#****** ");
         fprintf(ficlog,"\n#****** ");
         for(j=1;j<=cptcovs;j++) {
           fprintf(ficresvpl,"V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
           fprintf(ficlog,"V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
           printf("V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
           /* fprintf(ficlog,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
           /* printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
         }
         /* for (j=1; j<= nsq; j++){ /\* For each selected (single) quantitative value *\/ */
         /*        printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
         /*        fprintf(ficresvpl," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
         /*        fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
         /* }       */
         fprintf(ficresvpl,"******\n");
         printf("******\n");
         fprintf(ficlog,"******\n");
         
         varpl=matrix(1,nlstate,(int) bage, (int) fage);
         oldm=oldms;savm=savms;
         varprevlim(fileresvpl, ficresvpl, varpl, matcov, p, delti, nlstate, stepm, (int) bage, (int) fage, oldm, savm, prlim, ftolpl, ncvyearp, k, strstart, nres);
         free_matrix(varpl,1,nlstate,(int) bage, (int)fage);
         /*}*/
       }
       
       fclose(ficresvpl);
       printf("done variance-covariance of forward period prevalence\n");fflush(stdout);
       fprintf(ficlog,"done variance-covariance of forward period prevalence\n");fflush(ficlog);
   
    }
   /* Variance of back prevalence: varbprlim */
    void varbprlim(char fileresu[], int nresult, double ***prevacurrent, int mobilavproj, double bage, double fage, double **bprlim, int *ncvyearp, double ftolpl, double p[], double **matcov, double *delti, int stepm, int cptcoveff){
         /*------- Variance of back (stable) prevalence------*/
   
      char fileresvbl[FILENAMELENGTH];  
      FILE  *ficresvbl;
   
      double **oldm, **savm;
      double **varbpl; /* Variances of back prevalence limits by age */   
      int i1, k, nres, j ;
   
      strcpy(fileresvbl,"VBL_");
      strcat(fileresvbl,fileresu);
      if((ficresvbl=fopen(fileresvbl,"w"))==NULL) {
        printf("Problem with variance of back (stable) prevalence  resultfile: %s\n", fileresvbl);
        exit(0);
      }
      printf("Computing Variance-covariance of back (stable) prevalence: file '%s' ...", fileresvbl);fflush(stdout);
      fprintf(ficlog, "Computing Variance-covariance of back (stable) prevalence: file '%s' ...", fileresvbl);fflush(ficlog);
      
      
      i1=pow(2,cptcoveff);
      if (cptcovn < 1){i1=1;}
      
      for(nres=1; nres <= nresult; nres++){ /* For each resultline */
        k=TKresult[nres];
        if(TKresult[nres]==0) k=1; /* To be checked for noresult */
       /* for(k=1; k<=i1;k++){ */
       /*    if(i1 != 1 && TKresult[nres]!= k) */
       /*   continue; */
          fprintf(ficresvbl,"\n#****** ");
          printf("\n#****** ");
          fprintf(ficlog,"\n#****** ");
          for (j=1; j<= cptcovs; j++){ /* For each selected (single) quantitative value */
            printf(" V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][resultmodel[nres][j]]);
            fprintf(ficresvbl," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][resultmodel[nres][j]]);
            fprintf(ficlog," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][resultmodel[nres][j]]);
          /* for(j=1;j<=cptcoveff;j++) { */
          /*        fprintf(ficresvbl,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
          /*        fprintf(ficlog,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
          /*        printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
          /* } */
          /* for (j=1; j<= nsq; j++){ /\* For each selected (single) quantitative value *\/ */
          /*        printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
          /*        fprintf(ficresvbl," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
          /*        fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
          }
          fprintf(ficresvbl,"******\n");
          printf("******\n");
          fprintf(ficlog,"******\n");
          
          varbpl=matrix(1,nlstate,(int) bage, (int) fage);
          oldm=oldms;savm=savms;
          
          varbrevlim(fileresvbl, ficresvbl, varbpl, matcov, p, delti, nlstate, stepm, (int) bage, (int) fage, oldm, savm, bprlim, ftolpl, mobilavproj, ncvyearp, k, strstart, nres);
          free_matrix(varbpl,1,nlstate,(int) bage, (int)fage);
          /*}*/
        }
      
      fclose(ficresvbl);
      printf("done variance-covariance of back prevalence\n");fflush(stdout);
      fprintf(ficlog,"done variance-covariance of back prevalence\n");fflush(ficlog);
   
    } /* End of varbprlim */
   
   /************** 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=0.0,B=0.,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;
     }
     L=0.0;
     /* agegomp=AGEGOMP; */
     /* 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++) {
       /* mu(a)=mu(agecomp)*exp(teta*(age-agegomp))
          mu(a)=x[1]*exp(x[2]*(age-agegomp)); x[1] and x[2] are per year.
        * L= Product mu(agedeces)exp(-\int_ageexam^agedc mu(u) du ) for a death between agedc (in month) 
        *   and agedc +1 month, cens[i]=0: log(x[1]/YEARM)
        * +
        * exp(-\int_ageexam^agecens mu(u) du ) when censored, cens[i]=1
        */
        if (wav[i] > 1 || agedc[i] < AGESUP) {
          if (cens[i] == 1){
            A=-x[1]/(x[2])*(exp(x[2]*(agecens[i]-agegomp))-exp(x[2]*(ageexmed[i]-agegomp)));
          } else if (cens[i] == 0){
           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);
         } else
            printf("Gompertz cens[%d] neither 1 nor 0\n",i);
         /*if (wav[i] > 1 && agecens[i] > 15) {*/ /* ??? */
          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=0.,B=0.,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;
     int noffset=0; /* This is the offset if BOM data file */
     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<NCOVMAX;v++){
       DummyV[v]=0;
       FixedV[v]=0;
     }
   
     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]);
     }
     
     ncovcolt=ncovcol+nqv+ntv+nqtv; /* total of covariates in the data, not in the model equation */
     
     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;
     }
   
       /* Is it a BOM UTF-8 Windows file? */
     /* First data line */
     linei=0;
     while(fgets(line, MAXLINE, fic)) {
       noffset=0;
       if( line[0] == (char)0xEF && line[1] == (char)0xBB) /* EF BB BF */
       {
         noffset=noffset+3;
         printf("# Data file '%s'  is an UTF8 BOM file, please convert to UTF8 or ascii file and rerun.\n",datafile);fflush(stdout);
         fprintf(ficlog,"# Data file '%s'  is an UTF8 BOM file, please convert to UTF8 or ascii file and rerun.\n",datafile);
         fflush(ficlog); return 1;
       }
       /*    else if( line[0] == (char)0xFE && line[1] == (char)0xFF)*/
       else if( line[0] == (char)0xFF && line[1] == (char)0xFE)
       {
         noffset=noffset+2;
         printf("# Error Data file '%s'  is a huge UTF16BE BOM file, please convert to UTF8 or ascii file (for example with dos2unix) and rerun.\n",datafile);fflush(stdout);
         fprintf(ficlog,"# Error Data file '%s'  is a huge UTF16BE BOM file, please convert to UTF8 or ascii file (for example with dos2unix) and rerun.\n",datafile);
         fflush(ficlog); return 1;
       }
       else if( line[0] == 0 && line[1] == 0)
       {
         if( line[2] == (char)0xFE && line[3] == (char)0xFF){
           noffset=noffset+4;
           printf("# Error Data file '%s'  is a huge UTF16BE BOM file, please convert to UTF8 or ascii file (for example with dos2unix) and rerun.\n",datafile);fflush(stdout);
           fprintf(ficlog,"# Error Data file '%s'  is a huge UTF16BE BOM file, please convert to UTF8 or ascii file (for example with dos2unix) and rerun.\n",datafile);
           fflush(ficlog); return 1;
         }
       } else{
         ;/*printf(" Not a BOM file\n");*/
       }
           /* If line starts with a # it is a comment */
       if (line[noffset] == '#') {
         linei=linei+1;
         break;
       }else{
         break;
       }
     }
     fclose(fic);
     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;
     }
     /* Not a Bom file */
     
     i=1;
     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 of wave %d (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,iv,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 of wave %d (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,iv,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;
         /* if( (int)anint[j][i]+ (int)(mint[j][i])/12. < (int) (moisnais[i]/12.+annais[i])){ */
         /*        printf("Warning reading data around '%s' at line number %d for individual %d, '%s'\nThe date of interview (%2d/%4d) at wave %d occurred before the date of birth (%2d/%4d).\n",strb, linei,i, line, mint[j][i],anint[j][i], moisnais[i],annais[i]); */
         /*        fprintf(ficlog,"Warning reading data around '%s' at line number %d for individual %d, '%s'\nThe date of interview (%2d/%4d) at wave %d occurred before the date of birth (%2d/%4d).\n",strb, linei,i, line, mint[j][i],anint[j][i], moisnais[i],annais[i]); */
         /* } */
         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);
       for (j=1;j<=maxwav;j++){
         if( (int)anint[j][i]+ (int)(mint[j][i])/12. < (int) (moisnais[i]/12.+annais[i])){
           printf("Warning reading data around '%s' at line number %d for individual %d, '%s'\nThe date of interview (%2d/%4d) at wave %d occurred before the date of birth (%2d/%4d).\n",strb, linei,i, line, (int)mint[j][i],(int)anint[j][i], j,(int)moisnais[i],(int)annais[i]);
           fprintf(ficlog,"Warning reading data around '%s' at line number %d for individual %d, '%s'\nThe date of interview (%2d/%4d) at wave %d occurred before the date of birth (%2d/%4d).\n",strb, linei,i, line, (int)mint[j][i],(int)anint[j][i], j, (int)moisnais[i],(int)annais[i]);
         }
       }
   
       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;
           coqvar[iv][i]=NAN; 
           covar[ncovcol+iv][i]=NAN; /* including qvar in standard covar for performance reasons */ 
         }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);
   
     strcpy(resultsav,resultline);
     printf("Decoderesult resultsav=\"%s\" resultline=\"%s\"\n", resultsav, resultline);
     if (strlen(resultsav) >1){
       j=nbocc(resultsav,'='); /**< j=Number of covariate values'=' in this resultline */
     }
     if(j == 0){ /* Resultline but no = */
       TKresult[nres]=0; /* Combination for the nresult and the model */
       return (0);
     }
     if( j != cptcovs ){ /* Be careful if a variable is in a product but not single */
       printf("ERROR: the number of variables in the resultline which is %d, differs from the number %d of single variables used in the model line, %s.\n",j, cptcovs, model);
       fprintf(ficlog,"ERROR: the number of variables in the resultline which is %d, differs from the number %d of single variables used in the model line, %s.\n",j, cptcovs, model);
       /* return 1;*/
     }
     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 ' ' (stra is the rest of the resultline to be analyzed in the next loop *//*     resultsav= "V4=1 V5=25.1 V3=0" stra= "V5=25.1 V3=0" strb= "V4=1" */
         /* If resultsav= "V4= 1 V5=25.1 V3=0" with a blank then strb="V4=" and stra="1 V5=25.1 V3=0" */
         cutl(strc,strd,strb,'=');  /* strb:"V4=1" strc="1" strd="V4" */
         /* If a blank, then strc="V4=" and strd='\0' */
         if(strc[0]=='\0'){
         printf("Error in resultline, probably a blank after the \"%s\", \"result:%s\", stra=\"%s\" resultsav=\"%s\"\n",strb,resultline, stra, resultsav);
           fprintf(ficlog,"Error in resultline, probably a blank after the \"V%s=\", resultline=%s\n",strb,resultline);
           return 1;
         }
       }else
         cutl(strc,strd,resultsav,'=');
       Tvalsel[k]=atof(strc); /* 1 */ /* Tvalsel of k is the float value of the kth covariate appearing in this result line */
       
       cutl(strc,stre,strd,'V'); /* strd='V4' strc=4 stre='V' */;
       Tvarsel[k]=atoi(strc);  /* 4 */ /* Tvarsel is the id of the kth covariate in the result line Tvarsel[1] in "V4=1.." is 4.*/
       /* 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 */
     /* Feeds resultmodel[nres][k1]=k2 for k1th product covariate with age in the model equation fed by the index k2 of the resutline*/
     for(k1=1; k1<= cptcovt ;k1++){ /* Loop on MODEL LINE V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
       if(Typevar[k1]==0){ /* Single covariate in model */
         /* 0 for simple covariate (dummy, quantitative, fixed or varying), 1 for age product, 2 for  product */
         match=0;
         for(k2=1; k2 <=j;k2++){/* Loop on resultline. In result line V4=1 V5=24.1 V3=1  V2=8 V1=0 */
           if(Tvar[k1]==Tvarsel[k2]) {/* Tvar is coming from the model, Tvarsel from the result. Tvar[1]=5 == Tvarsel[2]=5   */
             modelresult[nres][k2]=k1;/* modelresult[2]=1 modelresult[1]=2  modelresult[3]=3  modelresult[6]=4 modelresult[9]=5 */
             match=1; /* modelresult of k2 variable of resultline is identical to k1 variable of the model good */
             break;
           }
         }
         if(match == 0){
           printf("Error in result line (Dummy single): V%d is missing in result: %s according to model=1+age+%s. Tvar[k1=%d]=%d is different from Tvarsel[k2=%d]=%d.\n",Tvar[k1], resultline, model,k1, Tvar[k1], k2, Tvarsel[k2]);
           fprintf(ficlog,"Error in result line (Dummy single): V%d is missing in result: %s according to model=1+age+%s\n",Tvar[k1], resultline, model);
           return 1;
         }
       }else if(Typevar[k1]==1){ /* Product with age We want to get the position k2 in the resultline of the product k1 in the model line*/
         /* We feed resultmodel[k1]=k2; */
         match=0;
         for(k2=1; k2 <=j;k2++){/* Loop on resultline.  jth occurence of = signs in the result line. In result line V4=1 V5=24.1 V3=1  V2=8 V1=0 */
           if(Tvar[k1]==Tvarsel[k2]) {/* Tvar is coming from the model, Tvarsel from the result. Tvar[1]=5 == Tvarsel[2]=5   */
             modelresult[nres][k2]=k1;/* we found a Vn=1 corrresponding to Vn*age in the model modelresult[2]=1 modelresult[1]=2  modelresult[3]=3  modelresult[6]=4 modelresult[9]=5 */
             resultmodel[nres][k1]=k2; /* Added here */
             printf("Decoderesult first modelresult[k2=%d]=%d (k1) V%d*AGE\n",k2,k1,Tvar[k1]);
             match=1; /* modelresult of k2 variable of resultline is identical to k1 variable of the model good */
             break;
           }
         }
         if(match == 0){
           printf("Error in result line (Product with age): V%d is missing in result: %s according to model=1+age+%s (Tvarsel[k2=%d]=%d)\n",Tvar[k1], resultline, model, k2, Tvarsel[k2]);
           fprintf(ficlog,"Error in result line (Product with age): V%d is missing in result: %s according to model=1+age+%s (Tvarsel[k2=%d]=%d)\n",Tvar[k1], resultline, model, k2, Tvarsel[k2]);
         return 1;
         }
       }else if(Typevar[k1]==2){ /* Product No age We want to get the position in the resultline of the product in the model line*/
         /* resultmodel[nres][of such a Vn * Vm product k1] is not unique, so can't exist, we feed Tvard[k1][1] and [2] */ 
         match=0;
         printf("Decoderesult very first Product Tvardk[k1=%d][1]=%d Tvardk[k1=%d][2]=%d V%d * V%d\n",k1,Tvardk[k1][1],k1,Tvardk[k1][2],Tvardk[k1][1],Tvardk[k1][2]);
         for(k2=1; k2 <=j;k2++){/* Loop on resultline. In result line V4=1 V5=24.1 V3=1  V2=8 V1=0 */
           if(Tvardk[k1][1]==Tvarsel[k2]) {/* Tvardk is coming from the model, Tvarsel from the result. Tvar[1]=5 == Tvarsel[2]=5   */
             /* modelresult[k2]=k1; */
             printf("Decoderesult first Product modelresult[k2=%d]=%d (k1) V%d * \n",k2,k1,Tvarsel[k2]);
             match=1; /* modelresult of k2 variable of resultline is identical to k1 variable of the model good */
           }
         }
         if(match == 0){
           printf("Error in result line (Product without age first variable): V%d is missing in result: %s according to model=1+age+%s\n",Tvardk[k1][1], resultline, model);
           fprintf(ficlog,"Error in result line (Product without age first variable): V%d is missing in result: %s according to model=1+age+%s\n",Tvardk[k1][1], resultline, model);
           return 1;
         }
         match=0;
         for(k2=1; k2 <=j;k2++){/* Loop on resultline. In result line V4=1 V5=24.1 V3=1  V2=8 V1=0 */
           if(Tvardk[k1][2]==Tvarsel[k2]) {/* Tvardk is coming from the model, Tvarsel from the result. Tvar[1]=5 == Tvarsel[2]=5   */
             /* modelresult[k2]=k1;*/
             printf("Decoderesult second Product modelresult[k2=%d]=%d (k1) * V%d \n ",k2,k1,Tvarsel[k2]);
             match=1; /* modelresult of k2 variable of resultline is identical to k1 variable of the model good */
             break;
           }
         }
         if(match == 0){
           printf("Error in result line (Product without age second variable): V%d is missing in result: %s according to model=1+age+%s\n",Tvardk[k1][2], resultline, model);
           fprintf(ficlog,"Error in result line (Product without age second variable): V%d is missing in result : %s according to model=1+age+%s\n",Tvardk[k1][2], resultline, model);
           return 1;
         }
       }/* End of testing */
     }/* End loop cptcovt */
     /* Checking for missing or useless values in comparison of current model needs */
     /* Feeds resultmodel[nres][k1]=k2 for single covariate (k1) in the model equation */
     for(k2=1; k2 <=j;k2++){ /* j or cptcovs is the number of single covariates used either in the model line as well as in the result line (dummy or quantitative)
                              * Loop on resultline variables: result line V4=1 V5=24.1 V3=1  V2=8 V1=0 */
       match=0;
       for(k1=1; k1<= cptcovt ;k1++){ /* loop on model: model line V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
         if(Typevar[k1]==0){ /* Single only */
           if(Tvar[k1]==Tvarsel[k2]) { /* Tvar[2]=4 == Tvarsel[1]=4   */
             resultmodel[nres][k1]=k2;  /* k1th position in the model equation corresponds to k2th position in the result line. resultmodel[2]=1 resultmodel[1]=2  resultmodel[3]=3  resultmodel[6]=4 resultmodel[9]=5 */
             modelresult[nres][k2]=k1; /* k1th position in the model equation corresponds to k2th position in the result line. modelresult[1]=2 modelresult[2]=1  modelresult[3]=3  remodelresult[4]=6 modelresult[5]=9 */
             ++match;
           }
         }
       }
       if(match == 0){
         printf("Error in result line: variable V%d is missing in model; result: %s, model=1+age+%s\n",Tvarsel[k2], resultline, model);
         fprintf(ficlog,"Error in result line: variable V%d is missing in model; result: %s, model=1+age+%s\n",Tvarsel[k2], resultline, model);
         return 1;
       }else if(match > 1){
         printf("Error in result line: %d doubled; result: %s, model=1+age+%s\n",k2, resultline, model);
         fprintf(ficlog,"Error in result line: %d doubled; result: %s, model=1+age+%s\n",k2, resultline, model);
         return 1;
       }
     }
     /* cptcovres=j /\* Number of variables in the resultline is equal to cptcovs and thus useless *\/     */
     /* 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 */
     /* nres=1st result line: V4=1 V5=25.1 V3=0  V2=8 V1=1 */
     /* should correspond to the combination 6 of dummy: V4=1, V3=0, V1=1 => V4*2**(0) + V3*2**(1) + V1*2**(2) = 1*1 + 0*2 + 1*4 = 5 + (1offset) = 6*/
     /* nres=2nd 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 (nres=2)*/
     /*    5 0 0 1 */
     /*    6 1 0 1 */ /* V4=1, V3=0, V1=1 (nres=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++){ /* cptcovt number of covariates (excluding 1 and age or age*age) in the MODEL equation.
                                                      * loop on position k1 in the MODEL LINE */
       /* k counting number of combination of single dummies in the equation model */
       /* k4 counting single dummies in the equation model */
       /* k4q counting single quantitatives in the equation model */
       if( Dummy[k1]==0 && Typevar[k1]==0 ){ /* Dummy and Single, k1 is sorting according to MODEL, but k3 to resultline */
          /* k4+1= (not always if quant in model) position in the resultline V(Tvarsel)=Tvalsel=Tresult[nres][pos](value); V(Tvresult[nres][pos] (variable): V(variable)=value) */
         /* modelresult[k3]=k1: k3th position in the result line corresponds to the k1 position in the model line (doesn't work with products)*/
         /* Value in the (current nres) resultline of the variable at the k1th position in the model equation resultmodel[nres][k1]= k3 */
         /* resultmodel[nres][k1]=k3: k1th position in the model correspond to the k3 position in the resultline                        */
         /*      k3 is the position in the nres result line of the k1th variable of the model equation                                  */
         /* Tvarsel[k3]: Name of the variable at the k3th position in the result line.                                                  */
         /* Tvalsel[k3]: Value of the variable at the k3th position in the result line.                                                 */
         /* Tresult[nres][result_position]= value of the dummy variable at the result_position in the nres resultline                   */
         /* Tvresult[nres][result_position]= name of the dummy variable at the result_position in the nres resultline                     */
         /* Tinvresult[nres][Name of a dummy variable]= value of the variable in the result line                                        */
         /* TinvDoQresult[nres][Name of a Dummy or Q variable]= value of the variable in the result line                                                      */
         k3= resultmodel[nres][k1]; /* From position k1 in model get position k3 in result line */
         /* nres=1 k1=2 resultmodel[2(V4)] = 1=k3 ; k1=3 resultmodel[3(V3)] = 2=k3*/
         k2=(int)Tvarsel[k3]; /* from position k3 in resultline get name k2: nres=1 k1=2=>k3=1 Tvarsel[resultmodel[2]]= Tvarsel[1] = 4=k2 (V4); k1=3=>k3=2 Tvarsel[2]=3 (V3)*/
         k+=Tvalsel[k3]*pow(2,k4);  /* nres=1 k1=2 Tvalsel[1]=1 (V4=1); k1=3 k3=2 Tvalsel[2]=0 (V3=0) */
         TinvDoQresult[nres][(int)Tvarsel[k3]]=Tvalsel[k3]; /* TinvDoQresult[nres][Name]=Value; stores the value into the name of the variable. */
         /* Tinvresult[nres][4]=1 */
         /* Tresult[nres][k4+1]=Tvalsel[k3];/\* Tresult[nres=2][1]=1(V4=1)  Tresult[nres=2][2]=0(V3=0) *\/ */
         Tresult[nres][k3]=Tvalsel[k3];/* Tresult[nres=2][1]=1(V4=1)  Tresult[nres=2][2]=0(V3=0) */
         /* Tvresult[nres][k4+1]=(int)Tvarsel[k3];/\* Tvresult[nres][1]=4 Tvresult[nres][3]=1 *\/ */
         Tvresult[nres][k3]=(int)Tvarsel[k3];/* Tvresult[nres][1]=4 Tvresult[nres][3]=1 */
         Tinvresult[nres][(int)Tvarsel[k3]]=Tvalsel[k3]; /* Tinvresult[nres][4]=1 */
         precov[nres][k1]=Tvalsel[k3]; /* Value from resultline of the variable at the k1 position in the model */
         printf("Decoderesult Dummy k=%d, k1=%d precov[nres=%d][k1=%d]=%.f V(k2=V%d)= Tvalsel[%d]=%d, 2**(%d)\n",k, k1, nres, k1,precov[nres][k1], k2, k3, (int)Tvalsel[k3], k4);
         k4++;;
       }else if( Dummy[k1]==1 && Typevar[k1]==0 ){ /* Quantitative and single */
         /* Tqresult[nres][result_position]= value of the variable at the result_position in the nres resultline                                 */
         /* Tvqresult[nres][result_position]= id of the variable at the result_position in the nres resultline                                 */
         /* Tqinvresult[nres][Name of a quantitative variable]= value of the variable in the result line                                                      */
         k3q= resultmodel[nres][k1]; /* resultmodel[1(V5)] = 5 =k3q */
         k2q=(int)Tvarsel[k3q]; /*  Name of variable at k3q th position in the resultline */
         /* Tvarsel[resultmodel[1]]= Tvarsel[1] = 4=k2 */
         /* Tqresult[nres][k4q+1]=Tvalsel[k3q]; /\* Tqresult[nres][1]=25.1 *\/ */
         /* Tvresult[nres][k4q+1]=(int)Tvarsel[k3q];/\* Tvresult[nres][1]=4 Tvresult[nres][3]=1 *\/ */
         /* Tvqresult[nres][k4q+1]=(int)Tvarsel[k3q]; /\* Tvqresult[nres][1]=5 *\/ */
         Tqresult[nres][k3q]=Tvalsel[k3q]; /* Tqresult[nres][1]=25.1 */
         Tvresult[nres][k3q]=(int)Tvarsel[k3q];/* Tvresult[nres][1]=4 Tvresult[nres][3]=1 */
         Tvqresult[nres][k3q]=(int)Tvarsel[k3q]; /* Tvqresult[nres][1]=5 */
         Tqinvresult[nres][(int)Tvarsel[k3q]]=Tvalsel[k3q]; /* Tqinvresult[nres][5]=25.1 */
         TinvDoQresult[nres][(int)Tvarsel[k3q]]=Tvalsel[k3q]; /* Tqinvresult[nres][5]=25.1 */
         precov[nres][k1]=Tvalsel[k3q];
         printf("Decoderesult Quantitative nres=%d,precov[nres=%d][k1=%d]=%.f V(k2q=V%d)= Tvalsel[%d]=%d, Tvarsel[%d]=%f\n",nres, nres, k1,precov[nres][k1], k2q, k3q, Tvarsel[k3q], k3q, Tvalsel[k3q]);
         k4q++;;
       }else if( Dummy[k1]==2 ){ /* For dummy with age product */
         /* Tvar[k1]; */ /* Age variable */
         /* Wrong we want the value of variable name Tvar[k1] */
         
         k3= resultmodel[nres][k1]; /* nres=1 k1=2 resultmodel[2(V4)] = 1=k3 ; k1=3 resultmodel[3(V3)] = 2=k3*/
         k2=(int)Tvarsel[k3]; /* nres=1 k1=2=>k3=1 Tvarsel[resultmodel[2]]= Tvarsel[1] = 4=k2 (V4); k1=3=>k3=2 Tvarsel[2]=3 (V3)*/
         TinvDoQresult[nres][(int)Tvarsel[k3]]=Tvalsel[k3]; /* TinvDoQresult[nres][4]=1 */
         precov[nres][k1]=Tvalsel[k3];
         printf("Decoderesult Dummy with age k=%d, k1=%d precov[nres=%d][k1=%d]=%.f Tvar[%d]=V%d k2=Tvarsel[%d]=%d Tvalsel[%d]=%d\n",k, k1, nres, k1,precov[nres][k1], k1, Tvar[k1], k3,(int)Tvarsel[k3], k3, (int)Tvalsel[k3]);
       }else if( Dummy[k1]==3 ){ /* For quant with age product */
         k3q= resultmodel[nres][k1]; /* resultmodel[1(V5)] = 25.1=k3q */
         k2q=(int)Tvarsel[k3q]; /*  Tvarsel[resultmodel[1]]= Tvarsel[1] = 4=k2 */
         TinvDoQresult[nres][(int)Tvarsel[k3q]]=Tvalsel[k3q]; /* TinvDoQresult[nres][5]=25.1 */
         precov[nres][k1]=Tvalsel[k3q];
         printf("Decoderesult Quantitative with age nres=%d, k1=%d, precov[nres=%d][k1=%d]=%f Tvar[%d]=V%d V(k2q=%d)= Tvarsel[%d]=%d, Tvalsel[%d]=%f\n",nres, k1, nres, k1,precov[nres][k1], k1,  Tvar[k1], k2q, k3q, Tvarsel[k3q], k3q, Tvalsel[k3q]);
       }else if(Typevar[k1]==2 ){ /* For product quant or dummy (not with age) */
         precov[nres][k1]=TinvDoQresult[nres][Tvardk[k1][1]] * TinvDoQresult[nres][Tvardk[k1][2]];      
         printf("Decoderesult Quantitative or Dummy (not with age) nres=%d k1=%d precov[nres=%d][k1=%d]=%.f V%d(=%.f) * V%d(=%.f) \n",nres, k1, nres, k1,precov[nres][k1], Tvardk[k1][1], TinvDoQresult[nres][Tvardk[k1][1]], Tvardk[k1][2], TinvDoQresult[nres][Tvardk[k1][2]]);
       }else{
         printf("Error Decoderesult probably a product  Dummy[%d]==%d && Typevar[%d]==%d\n", k1, Dummy[k1], k1, Typevar[k1]);
         fprintf(ficlog,"Error Decoderesult probably a product  Dummy[%d]==%d && Typevar[%d]==%d\n", k1, Dummy[k1], k1, Typevar[k1]);
       }
     }
     
     TKresult[nres]=++k; /* Number of combinations of dummies for the nresult and the model =Tvalsel[k3]*pow(2,k4) + 1*/
     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
           * ncovcolt=ncovcol+nqv+ntv+nqtv total of covariates in the data, not in the model equation
           * - 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+nqv+ntv+nqtv) 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 .
           */
   /* V2+V1+V4+V3*age Tvar[4]=3 ; V1+V2*age Tvar[2]=2; V1+V1*age Tvar[2]=1, Tage[1]=2 */
   {
     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=1+age+%s ",model);
         fprintf(ficlog,"Error. 'v' must be in upper case model=1+age+%s ",model);fflush(ficlog);
         return 1;
       }
       strcpy(modelsav,model); 
       if ((strpt=strstr(model,"age*age")) !=0){
         printf(" strpt=%s, model=1+age+%s\n",strpt, model);
         if(strpt != model){
           printf("Error in model: 'model=1+age+%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=1+age+%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? Tvars(orted)
          * 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 line */
           cutl(stra,strb,modelsav,'+'); /* keeps in strb after the first '+' cutl from left to right
                                            modelsav==V2+V1+V5*age+V4+V3*age strb=V3*age stra=V2+V1V5*age+V4 */    /* <model> "V5+V4+V3+V4*V3+V5*age+V1*age+V1" strb="V5" stra="V4+V3+V4*V3+V5*age+V1*age+V1" */
           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+V5*age+ V4+V3*age strb=V3*age */
             cutl(strc,strd,strb,'*'); /**< k=1 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+V5*age+V4+V3*age Tvar[5]=3 ; V1+V2*age Tvar[2]=2; V1+V1*age Tvar[2]=1 */
               Typevar[k]=1;  /* 1 for age product */
               cptcovage++; /* Counts the number of covariates which include age as a product */
               Tage[cptcovage]=k;  /*  V2+V1+V4+V3*age 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; /* ncovcolt+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
                                                   thus after V4 we invent V5 and V6 because age*V3 will be computed in 4
                                                   Tvar[3=V1*V4]=4+1=5 Tvar[5=V3*V2]=4 + 2= 6, Tvar[4=age*V3]=3 etc */
               /* Please remark that the new variables are model dependent */
               /* If we have 4 variable but the model uses only 3, like in
                * model= V1 + age*V1 + V2 + V3 + age*V2 + age*V3 + V1*V2 + V1*V3
                *  k=     1     2       3   4     5        6        7       8
                * Tvar[k]=1     1       2   3     2        3       (5       6) (and not 4 5 because of V4 missing)
                * Tage[kk]    [1]= 2           [2]=5      [3]=6                  kk=1 to cptcovage=3
                * Tvar[Tage[kk]][1]=2          [2]=2      [3]=3
                */
               Typevar[k]=2;  /* 2 for product */
               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; /* Tposprod[3]=1, Tposprod[2]=5 */
               Tvard[k1][1] =atoi(strc); /* m 1 for V1*/
               Tvardk[k][1] =atoi(strc); /* m 1 for V1*/
               Tvard[k1][2] =atoi(stre); /* n 4 for V4*/
               Tvardk[k][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   */
               if( FixedV[Tvardk[k][1]] == 0 && FixedV[Tvardk[k][2]] == 0){ /* If the product is a fixed covariate then we feed the new column with Vn*Vm */
                 for (i=1; i<=lastobs;i++){/* For fixed product */
                 /* 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[ncovcolt+k1][i]=covar[atoi(stre)][i]*covar[atoi(strc)][i];
                 }
               } /*End of FixedV */
             } /* End age is not in the model */
           } /* End if model includes a product */
           else { /* not a product */
             /*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        0
      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=1+age+%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=1+age+%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, ncovvt=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;
         TnsdVar[Tvar[k]]=nsd;
         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 For a fixed product k is higher than ncovcol *\/ */
       }else if( Tposprod[k]>0  &&  Typevar[k]==2 && FixedV[Tvardk[k][1]] == 0 && FixedV[Tvardk[k][2]] == 0){ /* Needs a fixed product Product of fixed dummy (<=ncovcol) covariates For a fixed product k is higher than ncovcol */
         Fixed[k]= 0;
         Dummy[k]= 0;
         ncoveff++;
         ncovf++;
         modell[k].maintype= FTYPE;
         TvarF[ncovf]=Tvar[k];
         /* TnsdVar[Tvar[k]]=nsd; */ /* To be done */
         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]; /* Gives the variable name (extended to products) of first nsq simple quantitative covariates (fixed or time vary see below */
         TvarsQind[nsq]=k;    /* Gives the position in the model equation of the first nsq simple quantitative covariates (fixed or time vary) */
         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 */
         /*#  ID           V1     V2          weight               birth   death   1st    s1      V3      V4      V5       2nd  s2 */
         /* model V1+V3+age*V1+age*V3+V1*V3 */
         /*  Tvar={1, 3, 1, 3, 6}, the 6 comes from the fact that there are already V1, V2, V3, V4, V5 native covariates */
         ncovvt++;
         TvarVV[ncovvt]=Tvar[k];  /*  TvarVV[1]=V3 (first time varying in the model equation  */
         TvarVVind[ncovvt]=k;    /*  TvarVVind[1]=2 (second position in the model equation  */
   
         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;
         TnsdVar[Tvar[k]]=nsd; /* To be verified */
         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*/
         /*#  ID           V1     V2          weight               birth   death   1st    s1      V3      V4      V5       2nd  s2 */
         /* model V1+V3+age*V1+age*V3+V1*V3 */
         /*  Tvar={1, 3, 1, 3, 6}, the 6 comes from the fact that there are already V1, V2, V3, V4, V5 native covariates */
         ncovvt++;
         TvarVV[ncovvt]=Tvar[k];  /*  TvarVV[1]=V3 (first time varying in the model equation  */
         TvarVVind[ncovvt]=k;  /*  TvarVV[1]=V3 (first time varying in the model equation  */
         
         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]; /* k=1 Tvar=5 nsq=1 TvarsQ[1]=5 */ /* Gives the variable name (extended to products) of first nsq simple quantitative covariates (fixed or time vary here) */
         TvarsQind[nsq]=k; /* For single quantitative covariate gives the model position of each single quantitative covariate *//* Gives the position in the model equation of the first nsq simple quantitative covariates (fixed or time vary) */
         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 Vn * Vm without age, V1+V3+age*V1+age*V3+V1*V3 looking at V1*V3, Typevar={0, 0, 1, 1, 2}, k=5, V1 is fixed, V3 is timevary, V5 is a product  */
         /*#  ID           V1     V2          weight               birth   death   1st    s1      V3      V4      V5       2nd  s2 */
         /* model V1+V3+age*V1+age*V3+V1*V3 */
         /*  Tvar={1, 3, 1, 3, 6}, the 6 comes from the fact that there are already V1, V2, V3, V4, V5 native covariates */
         k1=Tposprod[k];  /* Position in the products of product k, Tposprod={0, 0, 0, 0, 1} k1=1 first product but second time varying because of V3 */
         ncovvt++;
         TvarVV[ncovvt]=Tvard[k1][1];  /*  TvarVV[2]=V1 (because TvarVV[1] was V3, first time varying covariates */
         TvarVVind[ncovvt]=k;  /*  TvarVVind[2]=5 (because TvarVVind[2] was V1*V3 at position 5 */
         ncovvt++;
         TvarVV[ncovvt]=Tvard[k1][2];  /*  TvarVV[3]=V3 */
         TvarVVind[ncovvt]=k;  /*  TvarVVind[2]=5 (because TvarVVind[2] was V1*V3 at position 5 */
   
   
         if(Tvard[k1][1] <=ncovcol){ /* Vn is dummy fixed, (Tvard[1][1]=V1), (Tvard[1][1]=V3 time varying) */
           if(Tvard[k1][2] <=ncovcol){ /* Vm is dummy fixed */
             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){ /* Vm is quanti fixed */
             Fixed[k]= 0;  /* Fixed product */
             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){ /* Vm is a time varying dummy covariate */
             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];  /* TvarV[1]=Tvar[5]=5 because there is a V4 */
             TvarVind[ncovv]=k;/* TvarVind[1]=5 */ 
           }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){ /* Vm is a time varying quantitative covariate */
             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){ /* Vn is fixed quanti  */
           if(Tvard[k1][2] <=ncovcol){ /* Vm is fixed dummy */
             Fixed[k]= 0;  /*  Fixed product */
             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){ /* Vm is time varying */
             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){ /* Vm is time varying quanti */
             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){ /* Vn is time varying dummy */
           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){ /* Vn is time varying quanti */
           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]==Typevar[k2]) && (Fixed[k1]==Fixed[k2]) && (Dummy[k1]==Dummy[k2] )){
           if((Typevar[k1] == 0 || Typevar[k1] == 1)){ /* Simple or age product */
             if(Tvar[k1]==Tvar[k2]){
               printf("Error duplication in the model=1+age+%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[k1],Dummy[k1]);
               fprintf(ficlog,"Error duplication in the model=1+age+%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[k1],Dummy[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=1+age+%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=1+age+%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("Warning (#%d)! Date of death (month %2d and year %4d) of individual %ld on line %d was unknown but status is a death state %d at wave %d. If you don't know the vital status, please enter -2. If he/she is still alive but don't know the state, please code with '-1 or '.'. Here, we do not believe in a death, skipped.\nOther similar cases in log file\n", *nberr,(int)moisdc[i],(int)andc[i],num[i],i,s[m][i],m);
           }
           fprintf(ficlog,"Warning (#%d)! Date of death (month %2d and year %4d) of individual %ld on line %d was unknown but status is a death state %d at wave %d. If you don't know the vital status, please enter -2. If he/she is still alive but don't know the state, please code with '-1 or '.'. Here, we do not believe in a death, skipped.\n", *nberr,(int)moisdc[i],(int)andc[i],num[i],i,s[m][i],m);
           s[m][i]=-1;  /* Droping the death status */
         }
         if((int)moisdc[i]==99 && (int)andc[i]!=9999 && s[m][i]>nlstate){
           (*nberr)++;
           printf("Error (#%d)! Month of death of individual %ld on line %d was unknown (%2d) (year of death is %4d) and status is a death state %d at wave %d. Please impute an arbitrary (or not) month and rerun. Currently this transition to death will be skipped (status is set to -2).\nOther similar cases in log file\n", *nberr, num[i],i,(int)moisdc[i],(int)andc[i],s[m][i],m);
           fprintf(ficlog,"Error (#%d)! Month of death of individual %ld on line %d was unknown (%2d) (year of death is %4d) and status is a death state %d at wave %d. Please impute an arbitrary (or not) month and rerun. Currently this transition to death will be skipped (status is set to -2).\n", *nberr, num[i],i,(int)moisdc[i],(int)andc[i],s[m][i],m);
           s[m][i]=-2; /* 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 <stdint.h>
   
     /* #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
   
      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  (forward period or forward stable prevalence) --------------*/
     /* Computes the prevalence limit for each combination of the dummy covariates */
     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 forward period (stable) prevalence resultfile: %s\n", filerespl);return 1;
       fprintf(ficlog,"Problem with forward period (stable) prevalence resultfile: %s\n", filerespl);return 1;
     }
     printf("\nComputing forward period (stable) prevalence: result on file '%s' \n", filerespl);
     fprintf(ficlog,"\nComputing forward period (stable) prevalence: result on file '%s' \n", filerespl);
     pstamp(ficrespl);
     fprintf(ficrespl,"# Forward 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 */
         k=TKresult[nres];
         if(TKresult[nres]==0) k=1; /* To be checked for noresult */
         /* if(i1 != 1 && TKresult[nres]!= k) /\* We found the combination k corresponding to the resultline value of dummies *\/ */
         /*        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<=cptcovs ;j++) {/**< cptcovs number of SIMPLE covariates in the model or resultline V2+V1 =2 (dummy or quantit or time varying) */
           /* fprintf(ficrespl," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,Tvaraff[j])]); /\* Here problem for varying dummy*\/ */
           /* printf(" V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
           /* fprintf(ficlog," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
           fprintf(ficrespl," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
           printf(" V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
           fprintf(ficlog," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][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,TnsdVar[Tvaraff[j]])]); */
         /* } */
         for(j=1;j<=cptcovs;j++) { /* New the quanti variable is added */
           fprintf(ficrespl,"V%d %lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][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++){ */
           /**< Computes the prevalence limit in each live state at age x and for covariate combination (k and) nres */
           prevalim(prlim, nlstate, p, age, oldm, savm, ftolpl, ncvyearp, k, nres); /* Nicely done */
           fprintf(ficrespl,"%.0f ",age );
           /* for(j=1;j<=cptcoveff;j++) */
           /*   fprintf(ficrespl,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
           for(j=1;j<=cptcovs;j++)
             fprintf(ficrespl,"%d %lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][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 */
       } /* nres */
     /* } /\* for each combination *\/ */
     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  (backward 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 backward prevalence resultfile: %s\n", fileresplb);return 1;
       fprintf(ficlog,"Problem with backward prevalence resultfile: %s\n", fileresplb);return 1;
     }
     printf("Computing backward prevalence: result on file '%s' \n", fileresplb);
     fprintf(ficlog,"Computing backward prevalence: result on file '%s' \n", fileresplb);
     pstamp(ficresplb);
     fprintf(ficresplb,"# Backward 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 *\/ */
         k=TKresult[nres];
         if(TKresult[nres]==0) k=1; /* To be checked for noresult */
        /* if(i1 != 1 && TKresult[nres]!= k) */
        /*         continue; */
        /* /\*printf("cptcov=%d cptcod=%d codtab=%d\n",cptcov, cptcod,codtabm(cptcod,cptcov));*\/ */
         fprintf(ficresplb,"#******");
         printf("#******");
         fprintf(ficlog,"#******");
         for(j=1;j<=cptcovs ;j++) {/**< cptcovs number of SIMPLE covariates in the model or resultline V2+V1 =2 (dummy or quantit or time varying) */
           printf(" V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
           fprintf(ficresplb," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
           fprintf(ficlog," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
         }
         /* for(j=1;j<=cptcoveff ;j++) {/\* all covariates *\/ */
         /*        fprintf(ficresplb," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
         /*        printf(" V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
         /*        fprintf(ficlog," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
         /* } */
         /* for (j=1; j<= nsq; j++){ /\* For each selected (single) quantitative value *\/ */
         /*        printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
         /*        fprintf(ficresplb," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
         /*        fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[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<=cptcovs;j++) {
           fprintf(ficresplb,"V%d %lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][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);
             /* printf("TOTOT\n"); */
             /* exit(1); */
           }
           fprintf(ficresplb,"%.0f ",age );
           for(j=1;j<=cptcovs;j++)
             fprintf(ficresplb,"%d %lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][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 */
         /*fprintf(ficresplb,"\n");*/ /* Seems to be necessary for gnuplot only if two result lines and no covariate. */
       /* } /\* 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 ------------*/
     /* to be optimized with precov */
     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 */
       k=TKresult[nres];
       if(TKresult[nres]==0) k=1; /* To be checked for noresult */
       /* for(k=1; k<=i1;k++){ */
       /* if(i1 != 1 && TKresult[nres]!= k) */
       /*  continue; */
       fprintf(ficrespij,"\n#****** ");
       for(j=1;j<=cptcovs;j++){
         fprintf(ficrespij," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
         /* fprintf(ficrespij,"@wV%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[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 ------------*/
       /* To be optimized with precov */
     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=AGEINF; /* was 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 Bij x Back probability to be in state i at age x-h being in j at x: B1j+B2j+...=1 ");
     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 */
       k=TKresult[nres];
       if(TKresult[nres]==0) k=1; /* To be checked for noresult */
       /* for(k=1; k<=i1;k++){ /\* For any combination of dummy covariates, fixed and varying *\/ */
       /*    if(i1 != 1 && TKresult[nres]!= k) */
       /*  continue; */
       fprintf(ficrespijb,"\n#****** ");
       for(j=1;j<=cptcovs;j++){
         fprintf(ficrespijb," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
         /* for(j=1;j<=cptcoveff;j++) */
         /*        fprintf(ficrespijb,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
         /* for (j=1; j<= nsq; j++){ /\* For each selected (single) quantitative value *\/ */
         /*        fprintf(ficrespijb," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
       }
       fprintf(ficrespijb,"******\n");
       if(invalidvarcomb[k]){  /* Is it necessary here? */
         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+0.1)-1; /* Typically 20 years = 20*12/6=40 or 55*12/24=27.5-1.1=>27 */
         nhstepm = nhstepm/hstepm; /* Typically 40/4=10, because estepm=24 stepm=6 => hstepm=24/6=4 or 28*/
         
         /*          nhstepm=nhstepm*YEARM; aff par mois*/
         
         p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); /* We can't have it at an upper level because of nhstepm */
         /* and memory limitations if stepm is small */
         
         /* 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, nres);/* Bug valgrind */
         /* hbxij(p3mat,nhstepm,agedeb,hstepm,p,prevacurrent,nlstate,stepm,oldm,savm, dnewm, doldm, dsavm, k); */
         fprintf(ficrespijb,"# Cov Agex agex-h hbijx 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]);/* Bug valgrind */
           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, iter=0,m,size=100, cptcod; /* Suppressing because nobs */
     /* 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;
     int endishere=0;
     int noffset=0;
     int ncurrv=0; /* Temporary variable */
     
     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; */
     double wald;
   
     char line[MAXLINE];
     char path[MAXLINE],pathc[MAXLINE],pathcd[MAXLINE],pathtot[MAXLINE];
   
     char  modeltemp[MAXLINE];
     char resultline[MAXLINE], resultlineori[MAXLINE];
     
     char pathr[MAXLINE], pathimach[MAXLINE]; 
     char *tok, *val; /* pathtot */
     /* int firstobs=1, lastobs=10; /\* nobs = lastobs-firstobs declared globally ;*\/ */
     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 */
     /* double anprojd, mprojd, jprojd; /\* For eventual projections *\/ */
     /* double anprojf, mprojf, jprojf; */
     /* double jintmean,mintmean,aintmean;   */
     int prvforecast = 0; /* Might be 1 (date of beginning of projection is a choice or 2 is the dateintmean */
     int prvbackcast = 0; /* Might be 1 (date of beginning of projection is a choice or 2 is the dateintmean */
     double yrfproj= 10.0; /* Number of years of forward projections */
     double yrbproj= 10.0; /* Number of years of backward projections */
     int prevbcast=0; /* defined as global for mlikeli and mle, replacing backcast */
     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, param[i][j][k] param=ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel) 
                       state of origin, state of destination including death, for each covariate: constante, age, and V1 V2 etc. */
     double ***paramstart; /* Matrix of starting parameter values */
     double  *p, *pstart; /* p=param[1][1] pstart is for starting values guessed by freqsummary */
     double **matcov; /* Matrix of covariance */
     double **hess; /* Hessian matrix */
     double ***delti3; /* Scale */
     double *delti; /* Scale */
     double ***eij, ***vareij;
     double **varpl; /* Variances of prevalence limits by age */
   
     double *epj, vepp;
   
     double dateprev1, dateprev2;
     double jproj1=1,mproj1=1,anproj1=2000,jproj2=1,mproj2=1,anproj2=2000, dateproj1=0, dateproj2=0, dateprojd=0, dateprojf=0;
     double jback1=1,mback1=1,anback1=2000,jback2=1,mback2=1,anback2=2000, dateback1=0, dateback2=0, datebackd=0, datebackf=0;
   
   
     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 if (argc<=2){
       strcpy(pathtot,argv[1]);
     }
     else{
       strcpy(pathtot,argv[1]);
       strcpy(z,argv[2]);
       printf("\nargv[2]=%s z=%c\n",argv[2],z[0]);
     }
     /*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;
     }
         /*-------- 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;
       fflush(ficlog);
       goto end;
     }
     fprintf(ficres,"#IMaCh %s\n",version);
   
                                         
     /* Reads comments: lines beginning with '#' */
     numlinepar=0;
     /* Is it a BOM UTF-8 Windows file? */
     /* First parameter line */
     while(fgets(line, MAXLINE, ficpar)) {
       noffset=0;
       if( line[0] == (char)0xEF && line[1] == (char)0xBB) /* EF BB BF */
       {
         noffset=noffset+3;
         printf("# File is an UTF8 Bom.\n"); // 0xBF
       }
   /*    else if( line[0] == (char)0xFE && line[1] == (char)0xFF)*/
       else if( line[0] == (char)0xFF && line[1] == (char)0xFE)
       {
         noffset=noffset+2;
         printf("# File is an UTF16BE BOM file\n");
       }
       else if( line[0] == 0 && line[1] == 0)
       {
         if( line[2] == (char)0xFE && line[3] == (char)0xFF){
           noffset=noffset+4;
           printf("# File is an UTF16BE BOM file\n");
         }
       } else{
         ;/*printf(" Not a BOM file\n");*/
       }
     
       /* If line starts with a # it is a comment */
       if (line[noffset] == '#') {
         numlinepar++;
         fputs(line,stdout);
         fputs(line,ficparo);
         fputs(line,ficres);
         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");
         fprintf(ficlog,"Should be 5 parameters\n");
       }
       numlinepar++;
       printf("title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", title, datafile, lastobs, firstpass,lastpass);
       fprintf(ficparo,"title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", title, datafile, lastobs, firstpass,lastpass);
       fprintf(ficres,"title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", title, datafile, lastobs, firstpass,lastpass);
       fprintf(ficlog,"title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", title, datafile, lastobs, firstpass,lastpass);
     }
     /* Second parameter line */
     while(fgets(line, MAXLINE, ficpar)) {
       /* while(fscanf(ficpar,"%[^\n]", line)) { */
       /* If line starts with a # it is a comment. Strangely fgets reads the EOL and fputs doesn't */
       if (line[0] == '#') {
         numlinepar++;
         printf("%s",line);
         fprintf(ficres,"%s",line);
         fprintf(ficparo,"%s",line);
         fprintf(ficlog,"%s",line);
         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);
         fprintf(ficlog,"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");
         fprintf(ficlog,"but line=%s\n",line);
       }
       if( lastpass > maxwav){
         printf("Error (lastpass = %d) > (maxwav = %d)\n",lastpass, maxwav);
         fprintf(ficlog,"Error (lastpass = %d) > (maxwav = %d)\n",lastpass, maxwav);
         fflush(ficlog);
         goto end;
       }
         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);
       fprintf(ficparo,"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);
       fprintf(ficres,"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, 0, weightopt);
       fprintf(ficlog,"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++;
         printf("%s",line);
         fprintf(ficres,"%s",line);
         fprintf(ficparo,"%s",line);
         fprintf(ficlog,"%s",line);
         continue;
       }else
         break;
     }
     if((num_filled=sscanf(line,"model=1+age%[^.\n]", model)) !=EOF){
       if (num_filled != 1){
         printf("ERROR %d: Model should be at minimum 'model=1+age+' instead of '%s'\n",num_filled, line);
         fprintf(ficlog,"ERROR %d: Model should be at minimum 'model=1+age+' instead of '%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=1+age+%s\n",model, modeltemp, model);fflush(stdout); */
       printf("model=1+age+%s\n",model);fflush(stdout);
       fprintf(ficparo,"model=1+age+%s\n",model);fflush(stdout);
       fprintf(ficres,"model=1+age+%s\n",model);fflush(stdout);
       fprintf(ficlog,"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 without space \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 vectors and subdiagonal covariance matrix.\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,firstobs,lastobs);  /**< used in readdata */
     if(nqv>=1)coqvar=matrix(1,nqv,firstobs,lastobs);  /**< Fixed quantitative covariate */
     if(nqtv>=1)cotqvar=ma3x(1,maxwav,1,nqtv,firstobs,lastobs);  /**< Time varying quantitative covariate */
     if(ntv+nqtv>=1)cotvar=ma3x(1,maxwav,1,ntv+nqtv,firstobs,lastobs);  /**< Time varying covariate (dummy and quantitative)*/
     /* if(ntv+nqtv>=1)cotvar=ma3x(1,maxwav,ncovcol+nqv+1,ncovcol+nqv+ntv+nqtv,firstobs,lastobs);  /\**< Might be better *\/ */
     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==-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);
       paramstart= 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++;
           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);
           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",&param[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 parameters values */
       p=param[1][1];
       pstart=paramstart[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);
       
     }    /* End of mle != -3 */
     
     /*  Main data
      */
     nobs=lastobs-firstobs+1; /* was = 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=lvector(firstobs,lastobs);
     moisnais=vector(firstobs,lastobs);
     annais=vector(firstobs,lastobs);
     moisdc=vector(firstobs,lastobs);
     andc=vector(firstobs,lastobs);
     weight=vector(firstobs,lastobs);
     agedc=vector(firstobs,lastobs);
     cod=ivector(firstobs,lastobs);
     for(i=firstobs;i<=lastobs;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,firstobs,lastobs);
     anint=matrix(1,maxwav,firstobs,lastobs);
     s=imatrix(1,maxwav+1,firstobs,lastobs); /* s[i][j] health state for wave i and individual j */
     /* printf("BUG ncovmodel=%d NCOVMAX=%d 2**ncovmodel=%f BUG\n",ncovmodel,NCOVMAX,pow(2,ncovmodel)); */
     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); /*  */
     TnsdVar=ivector(1,NCOVMAX); /*  */
       /* for(i=1; i<=NCOVMAX;i++) TnsdVar[i]=3; */
     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); /*  */
     TvarVV=ivector(1,NCOVMAX); /*  */
     TvarVVind=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) */
     Tvardk=imatrix(1,NCOVMAX,1,2);
     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
                              */  
     for(i=1;i<NCOVMAX;i++)
       Tage[i]=0;
     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,firstobs,lastobs);
     free_vector(annais,firstobs,lastobs);
     /* 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,firstobs,lastobs);
     free_vector(andc,firstobs,lastobs);
   
     /* 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]; as well as calculate cptcoveff or number of total effective dummy covariates*/
     }
     
     ncovcombmax=pow(2,cptcoveff);
     invalidvarcomb=ivector(0, ncovcombmax); 
     for(i=0;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   *  h-1\k-1  4  3  2  1          
              *______________________________   *______________________
              *     1 i=1 1 i=1 1 i=1 1 i=1 1   *     0     0  0  0  0 
              *     2     2     1     1     1   *     1     0  0  0  1 
              *     3 i=2 1     2     1     1   *     2     0  0  1  0 
              *     4     2     2     1     1   *     3     0  0  1  1 
              *     5 i=3 1 i=2 1     2     1   *     4     0  1  0  0 
              *     6     2     1     2     1   *     5     0  1  0  1 
              *     7 i=4 1     2     2     1   *     6     0  1  1  0 
              *     8     2     2     2     1   *     7     0  1  1  1 
              *     9 i=5 1 i=3 1 i=2 1     2   *     8     1  0  0  0 
              *    10     2     1     1     2   *     9     1  0  0  1 
              *    11 i=6 1     2     1     2   *    10     1  0  1  0 
              *    12     2     2     1     2   *    11     1  0  1  1 
              *    13 i=7 1 i=4 1     2     2   *    12     1  1  0  0  
              *    14     2     1     2     2   *    13     1  1  0  1 
              *    15 i=8 1     2     2     2   *    14     1  1  1  0 
              *    16     2     2     2     2   *    15     1  1  1  1          
              */                                     
     /* 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<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 longeÌviteÌ-2013-2022-Japan Society for the Promotion of Sciences 日本学術振興会 \
   (<a href=https://www.jsps.go.jp/english/e-grants/>Grant-in-Aid for Scientific Research 25293121</a>) - \
   <a href=https://software.intel.com/en-us>Intel Software 2015-2018</a></font><br> \n", optionfilehtm);
     
     fprintf(fichtm,"<hr size=\"2\" color=\"#EC5E5E\"> \n\
   <font size=\"2\">IMaCh-%s <br> %s</font> \
   <hr size=\"2\" color=\"#EC5E5E\"> \n\
   This file: <a href=\"%s\">%s</a></br>Title=%s <br>Datafile=<a href=\"%s\">%s</a> 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",\
             version,fullversion,optionfilehtm,optionfilehtm,title,datafile,datafile,firstpass,lastpass,stepm, weightopt, model, \
             optionfilefiname,optionfilext,optionfilefiname,optionfilext,\
             fileres,fileres,\
             filelog,filelog,optionfilegnuplot,optionfilegnuplot,strstart);
     fflush(fichtm);
   
     strcpy(pathr,path);
     strcat(pathr,optionfilefiname);
   #ifdef WIN32
     _chdir(optionfilefiname); /* Move to directory named optionfile */
   #else
     chdir(optionfilefiname); /* Move to directory named optionfile */
   #endif
             
     
     /* Calculates basic frequencies. Computes observed prevalence at single age 
                    and for any valid combination of covariates
        and prints on file fileres'p'. */
     freqsummary(fileres, p, pstart, agemin, agemax, s, agev, nlstate, imx, Tvaraff, invalidvarcomb, nbcode, ncodemax,mint,anint,strstart, \
                 firstpass, lastpass,  stepm,  weightopt, model);
   
     fprintf(fichtm,"\n");
     fprintf(fichtm,"<h4>Parameter line 2</h4><ul><li>Tolerance for the convergence of the likelihood: ftol=%g \n<li>Interval for the elementary matrix (in month): stepm=%d",\
             ftol, stepm);
     fprintf(fichtm,"\n<li>Number of fixed dummy covariates: ncovcol=%d ", ncovcol);
     ncurrv=1;
     for(i=ncurrv; i <=ncovcol; i++) fprintf(fichtm,"V%d ", i);
     fprintf(fichtm,"\n<li> Number of fixed quantitative variables: nqv=%d ", nqv); 
     ncurrv=i;
     for(i=ncurrv; i <=ncurrv-1+nqv; i++) fprintf(fichtm,"V%d ", i);
     fprintf(fichtm,"\n<li> Number of time varying (wave varying) dummy covariates: ntv=%d ", ntv);
     ncurrv=i;
     for(i=ncurrv; i <=ncurrv-1+ntv; i++) fprintf(fichtm,"V%d ", i);
     fprintf(fichtm,"\n<li>Number of time varying  quantitative covariates: nqtv=%d ", nqtv);
     ncurrv=i;
     for(i=ncurrv; i <=ncurrv-1+nqtv; i++) fprintf(fichtm,"V%d ", i);
     fprintf(fichtm,"\n<li>Weights column \n<br>Number of alive states: nlstate=%d <br>Number of death states (not really implemented): ndeath=%d \n<li>Number of waves: maxwav=%d \n<li>Parameter for maximization (1), using parameter values (0), for design of parameters and variance-covariance matrix: mle=%d \n<li>Does the weight column be taken into account (1), or not (0): weight=%d</ul>\n", \
              nlstate, ndeath, maxwav, mle, weightopt);
   
     fprintf(fichtm,"<h4> Diagram of states <a href=\"%s_.svg\">%s_.svg</a></h4> \n\
   <img src=\"%s_.svg\">", subdirf2(optionfilefiname,"D_"),subdirf2(optionfilefiname,"D_"),subdirf2(optionfilefiname,"D_"));
   
     
     fprintf(fichtm,"\n<h4>Some descriptive statistics </h4>\n<br>Number of (used) 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(firstobs,lastobs);
       ageexmed=vector(firstobs,lastobs);
       agecens=vector(firstobs,lastobs);
       dcwave=ivector(firstobs,lastobs);
                   
       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(agegomp,AGESUP);
       lpop=vector(agegomp,AGESUP);
       tpop=vector(agegomp,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,agegomp,AGESUP);
       free_vector(lpop,agegomp,AGESUP);
       free_vector(tpop,agegomp,AGESUP);
       free_matrix(ximort,1,NDIM,1,NDIM);
       free_ivector(dcwave,firstobs,lastobs);
       free_vector(agecens,firstobs,lastobs);
       free_vector(ageexmed,firstobs,lastobs);
       free_ivector(cens,firstobs,lastobs);
   #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);
             /* exit(0); */
       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"); /* Printing model equation */
       fprintf(ficlog,"# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
   
       printf("#model=  1      +     age ");
       fprintf(ficres,"#model=  1      +     age ");
       fprintf(ficlog,"#model=  1      +     age ");
       fprintf(fichtm,"\n<ul><li> model=1+age+%s\n \
   </ul>", model);
   
       fprintf(fichtm,"\n<table style=\"text-align:center; border: 1px solid\">\n");
       fprintf(fichtm, "<tr><th>Model=</th><th>1</th><th>+ age</th>");
       if(nagesqr==1){
         printf("  + age*age  ");
         fprintf(ficres,"  + age*age  ");
         fprintf(ficlog,"  + age*age  ");
         fprintf(fichtm, "<th>+ age*age</th>");
       }
       for(j=1;j <=ncovmodel-2;j++){
         if(Typevar[j]==0) {
           printf("  +      V%d  ",Tvar[j]);
           fprintf(ficres,"  +      V%d  ",Tvar[j]);
           fprintf(ficlog,"  +      V%d  ",Tvar[j]);
           fprintf(fichtm, "<th>+ V%d</th>",Tvar[j]);
         }else if(Typevar[j]==1) {
           printf("  +    V%d*age ",Tvar[j]);
           fprintf(ficres,"  +    V%d*age ",Tvar[j]);
           fprintf(ficlog,"  +    V%d*age ",Tvar[j]);
           fprintf(fichtm, "<th>+  V%d*age</th>",Tvar[j]);
         }else if(Typevar[j]==2) {
           printf("  +    V%d*V%d ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
           fprintf(ficres,"  +    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(fichtm, "<th>+  V%d*V%d</th>",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
         }
       }
       printf("\n");
       fprintf(ficres,"\n");
       fprintf(ficlog,"\n");
       fprintf(fichtm, "</tr>");
       fprintf(fichtm, "\n");
       
       
       for(i=1,jk=1; i <=nlstate; i++){
         for(k=1; k <=(nlstate+ndeath); k++){
           if (k != i) {
             fprintf(fichtm, "<tr>");
             printf("%d%d ",i,k);
             fprintf(ficlog,"%d%d ",i,k);
             fprintf(ficres,"%1d%1d ",i,k);
             fprintf(fichtm, "<td>%1d%1d</td>",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]);
               fprintf(fichtm, "<td>%12.7f</td>",p[jk]);
               jk++; 
             }
             printf("\n");
             fprintf(ficlog,"\n");
             fprintf(ficres,"\n");
             fprintf(fichtm, "</tr>\n");
           }
         }
       }
       /* fprintf(fichtm,"</tr>\n"); */
       fprintf(fichtm,"</table>\n");
       fprintf(fichtm, "\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");
         fprintf(fichtm, "\n<p>The Wald test results are output only if the maximimzation of the Likelihood is performed (mle=1)\n</br>Parameters, Wald tests and Wald-based confidence intervals\n</br> W is simply the result of the division of the parameter by the square root of covariance of the parameter.\n</br> And Wald-based confidence intervals plus and minus 1.96 * W \n </br> It might be better to visualize the covariance matrix. See the page '<a href=\"%s\">Matrix of variance-covariance of one-step probabilities and its graphs</a>'.\n</br>",optionfilehtmcov);
         fprintf(fichtm,"\n<table style=\"text-align:center; border: 1px solid\">");
         fprintf(fichtm, "\n<tr><th>Model=</th><th>1</th><th>+ age</th>");
         if(nagesqr==1){
           printf("  + age*age  ");
           fprintf(ficres,"  + age*age  ");
           fprintf(ficlog,"  + age*age  ");
           fprintf(fichtm, "<th>+ age*age</th>");
         }
         for(j=1;j <=ncovmodel-2;j++){
           if(Typevar[j]==0) {
             printf("  +      V%d  ",Tvar[j]);
             fprintf(fichtm, "<th>+ V%d</th>",Tvar[j]);
           }else if(Typevar[j]==1) {
             printf("  +    V%d*age ",Tvar[j]);
             fprintf(fichtm, "<th>+  V%d*age</th>",Tvar[j]);
           }else if(Typevar[j]==2) {
             fprintf(fichtm, "<th>+  V%d*V%d</th>",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
           }
         }
         fprintf(fichtm, "</tr>\n");
    
         for(i=1,jk=1; i <=nlstate; i++){
           for(k=1; k <=(nlstate+ndeath); k++){
             if (k != i) {
               fprintf(fichtm, "<tr valign=top>");
               printf("%d%d ",i,k);
               fprintf(ficlog,"%d%d ",i,k);
               fprintf(fichtm, "<td>%1d%1d</td>",i,k);
               for(j=1; j <=ncovmodel; j++){
                 wald=p[jk]/sqrt(matcov[jk][jk]);
                 printf("%12.7f(%12.7f) W=%8.3f CI=[%12.7f ; %12.7f] ",p[jk],sqrt(matcov[jk][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(%12.7f) W=%8.3f CI=[%12.7f ; %12.7f] ",p[jk],sqrt(matcov[jk][jk]), p[jk]/sqrt(matcov[jk][jk]), p[jk]-1.96*sqrt(matcov[jk][jk]),p[jk]+1.96*sqrt(matcov[jk][jk]));
                 if(fabs(wald) > 1.96){
                   fprintf(fichtm, "<td><b>%12.7f</b></br> (%12.7f)</br>",p[jk],sqrt(matcov[jk][jk]));
                 }else{
                   fprintf(fichtm, "<td>%12.7f (%12.7f)</br>",p[jk],sqrt(matcov[jk][jk]));
                 }
                 fprintf(fichtm,"W=%8.3f</br>",wald);
                 fprintf(fichtm,"[%12.7f;%12.7f]</br></td>", p[jk]-1.96*sqrt(matcov[jk][jk]),p[jk]+1.96*sqrt(matcov[jk][jk]));
                 jk++; 
               }
               printf("\n");
               fprintf(ficlog,"\n");
               fprintf(fichtm, "</tr>\n");
             }
           }
         }
       } /* end of hesscov and Wald tests */
       fprintf(fichtm,"</table>\n");
       
       /*  */
       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);
           fputs(line,ficres);
           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(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((num_filled=sscanf(line,"begin-prev-date=%lf/%lf/%lf end-prev-date=%lf/%lf/%lf mov_average=%d\n",&jprev1, &mprev1,&anprev1,&jprev2, &mprev2,&anprev2,&mobilav)) !=EOF){
         
         if (num_filled != 7) {
           printf("Error: Not 7 (data)parameters in line but %d, for example:begin-prev-date=1/1/1990 end-prev-date=1/6/2004  mov_average=0\n, your line=%s . Probably you are running an older format.\n",num_filled,line);
           fprintf(ficlog,"Error: Not 7 (data)parameters in line but %d, for example:begin-prev-date=1/1/1990 end-prev-date=1/6/2004  mov_average=0\n, your line=%s . Probably you are running an older format.\n",num_filled,line);
           goto end;
         }
         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(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);
         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(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;
       }
       
       
       dateprev1=anprev1+(mprev1-1)/12.+(jprev1-1)/365.;
       dateprev2=anprev2+(mprev2-1)/12.+(jprev2-1)/365.;
       
       if((num_filled=sscanf(line,"pop_based=%d\n",&popbased)) !=EOF){
         if (num_filled != 1) {
           printf("Error: Not 1 (data)parameters in line but %d, for example:pop_based=0\n, your line=%s . Probably you are running an older format.\n",num_filled,line);
           fprintf(ficlog,"Error: Not 1 (data)parameters in line but %d, for example: pop_based=1\n, your line=%s . Probably you are running an older format.\n",num_filled,line);
           goto end;
         }
         printf("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);   
       }
        
       /* Results */
       /* Value of covariate in each resultine will be compututed (if product) and sorted according to model rank */
       /* It is precov[] because we need the varying age in order to compute the real cov[] of the model equation */  
       precov=matrix(1,MAXRESULTLINESPONE,1,NCOVMAX+1);
       endishere=0;
       nresult=0;
       parameterline=0;
       do{
         if(!fgets(line, MAXLINE, ficpar)){
           endishere=1;
           parameterline=15;
         }else if (line[0] == '#') {
           /* If line starts with a # it is a comment */
           numlinepar++;
           fputs(line,stdout);
           fputs(line,ficparo);
           fputs(line,ficlog);
           fputs(line,ficres);
           continue;
         }else if(sscanf(line,"prevforecast=%[^\n]\n",modeltemp))
           parameterline=11;
         else if(sscanf(line,"prevbackcast=%[^\n]\n",modeltemp))
           parameterline=12;
         else if(sscanf(line,"result:%[^\n]\n",modeltemp)){
           parameterline=13;
         }
         else{
           parameterline=14;
         }
         switch (parameterline){ /* =0 only if only comments */
         case 11:
           if((num_filled=sscanf(line,"prevforecast=%d starting-proj-date=%lf/%lf/%lf final-proj-date=%lf/%lf/%lf mobil_average=%d\n",&prevfcast,&jproj1,&mproj1,&anproj1,&jproj2,&mproj2,&anproj2,&mobilavproj)) !=EOF && (num_filled == 8)){
                     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.*/
             dateproj1=anproj1+(mproj1-1)/12.+(jproj1-1)/365.;
             dateproj2=anproj2+(mproj2-1)/12.+(jproj2-1)/365.;
             prvforecast = 1;
           } 
           else if((num_filled=sscanf(line,"prevforecast=%d yearsfproj=%lf mobil_average=%d\n",&prevfcast,&yrfproj,&mobilavproj)) !=EOF){/* && (num_filled == 3))*/
             printf("prevforecast=%d yearsfproj=%.2lf mobil_average=%d\n",prevfcast,yrfproj,mobilavproj);
             fprintf(ficlog,"prevforecast=%d yearsfproj=%.2lf mobil_average=%d\n",prevfcast,yrfproj,mobilavproj);
             fprintf(ficres,"prevforecast=%d yearsfproj=%.2lf mobil_average=%d\n",prevfcast,yrfproj,mobilavproj);
             prvforecast = 2;
           }
           else {
             printf("Error: Not 8 (data)parameters in line but %d, for example:prevforecast=1 starting-proj-date=1/1/1990 final-proj-date=1/1/2000 mobil_average=0\nnor 3 (data)parameters, for example:prevforecast=1 yearsfproj=10 mobil_average=0. Your line=%s . You are running probably an older format.\n, ",num_filled,line);
             fprintf(ficlog,"Error: Not 8 (data)parameters in line but %d, for example:prevforecast=1 starting-proj-date=1/1/1990 final-proj-date=1/1/2000 mobil_average=0\nnor 3 (data)parameters, for example:prevforecast=1 yearproj=10 mobil_average=0. Your line=%s . You are running probably an older format.\n, ",num_filled,line);
             goto end;
           }
           break;
         case 12:
           if((num_filled=sscanf(line,"prevbackcast=%d starting-back-date=%lf/%lf/%lf final-back-date=%lf/%lf/%lf mobil_average=%d\n",&prevbcast,&jback1,&mback1,&anback1,&jback2,&mback2,&anback2,&mobilavproj)) !=EOF && (num_filled == 8)){
             fprintf(ficparo,"prevbackcast=%d starting-back-date=%.lf/%.lf/%.lf final-back-date=%.lf/%.lf/%.lf mobil_average=%d\n",prevbcast,jback1,mback1,anback1,jback2,mback2,anback2,mobilavproj);
             printf("prevbackcast=%d starting-back-date=%.lf/%.lf/%.lf final-back-date=%.lf/%.lf/%.lf mobil_average=%d\n",prevbcast,jback1,mback1,anback1,jback2,mback2,anback2,mobilavproj);
             fprintf(ficlog,"prevbackcast=%d starting-back-date=%.lf/%.lf/%.lf final-back-date=%.lf/%.lf/%.lf mobil_average=%d\n",prevbcast,jback1,mback1,anback1,jback2,mback2,anback2,mobilavproj);
             fprintf(ficres,"prevbackcast=%d starting-back-date=%.lf/%.lf/%.lf final-back-date=%.lf/%.lf/%.lf mobil_average=%d\n",prevbcast,jback1,mback1,anback1,jback2,mback2,anback2,mobilavproj);
             /* day and month of back2 are not used but only year anback2.*/
             dateback1=anback1+(mback1-1)/12.+(jback1-1)/365.;
             dateback2=anback2+(mback2-1)/12.+(jback2-1)/365.;
             prvbackcast = 1;
           } 
           else if((num_filled=sscanf(line,"prevbackcast=%d yearsbproj=%lf mobil_average=%d\n",&prevbcast,&yrbproj,&mobilavproj)) ==3){/* && (num_filled == 3))*/
             printf("prevbackcast=%d yearsbproj=%.2lf mobil_average=%d\n",prevbcast,yrbproj,mobilavproj);
             fprintf(ficlog,"prevbackcast=%d yearsbproj=%.2lf mobil_average=%d\n",prevbcast,yrbproj,mobilavproj);
             fprintf(ficres,"prevbackcast=%d yearsbproj=%.2lf mobil_average=%d\n",prevbcast,yrbproj,mobilavproj);
             prvbackcast = 2;
           }
           else {
             printf("Error: Not 8 (data)parameters in line but %d, for example:prevbackcast=1 starting-back-date=1/1/1990 final-back-date=1/1/2000 mobil_average=0\nnor 3 (data)parameters, for example:prevbackcast=1 yearsbproj=10 mobil_average=0. Your line=%s . You are running probably an older format.\n, ",num_filled,line);
             fprintf(ficlog,"Error: Not 8 (data)parameters in line but %d, for example:prevbackcast=1 starting-back-date=1/1/1990 final-back-date=1/1/2000 mobil_average=0\nnor 3 (data)parameters, for example:prevbackcast=1 yearbproj=10 mobil_average=0. Your line=%s . You are running probably an older format.\n, ",num_filled,line);
             goto end;
           }
           break;
         case 13:
           num_filled=sscanf(line,"result:%[^\n]\n",resultlineori);
           nresult++; /* Sum of resultlines */
           printf("Result %d: result:%s\n",nresult, resultlineori);
           /* removefirstspace(&resultlineori); */
           
           if(strstr(resultlineori,"v") !=0){
             printf("Error. 'v' must be in upper case 'V' result: %s ",resultlineori);
             fprintf(ficlog,"Error. 'v' must be in upper case result: %s ",resultlineori);fflush(ficlog);
             return 1;
           }
           trimbb(resultline, resultlineori); /* Suppressing double blank in the resultline */
           printf("Decoderesult resultline=\"%s\" resultlineori=\"%s\"\n", resultline, resultlineori);
           if(nresult > MAXRESULTLINESPONE-1){
             printf("ERROR: Current version of IMaCh limits the number of resultlines to %d, you used %d\nYou can use the 'r' parameter file '%s' which uses option mle=0 to get other results. ",MAXRESULTLINESPONE-1,nresult,rfileres);
             fprintf(ficlog,"ERROR: Current version of IMaCh limits the number of resultlines to %d, you used %d\nYou can use the 'r' parameter file '%s' which uses option mle=0 to get other results. ",MAXRESULTLINESPONE-1,nresult,rfileres);
             goto end;
           }
           
           if(!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);
           } else
             goto end;
           break;
         case 14:
           printf("Error: Unknown command '%s'\n",line);
           fprintf(ficlog,"Error: Unknown command '%s'\n",line);
           if(line[0] == ' ' || line[0] == '\n'){
             printf("It should not be an empty line '%s'\n",line);
             fprintf(ficlog,"It should not be an empty line '%s'\n",line);
           }         
           if(ncovmodel >=2 && nresult==0 ){
             printf("ERROR: no result lines! It should be at minimum 'result: V2=0 V1=1 or result:.' %s\n",line);
             fprintf(ficlog,"ERROR: no result lines! It should be at minimum 'result: V2=0 V1=1 or result:.' %s\n",line);
           }
           /* goto end; */
           break;
         case 15:
           printf("End of resultlines.\n");
           fprintf(ficlog,"End of resultlines.\n");
           break;
         default: /* parameterline =0 */
           nresult=1;
           decoderesult(".",nresult ); /* No covariate */
         } /* End switch parameterline */
       }while(endishere==0); /* End do */
       
       /* 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, (int)anproj1-(int)agemin, (int)anback1-(int)agemax+1); */
         /* It seems that anprojd which is computed from the mean year at interview which is known yet because of freqsummary */
         /* date2dmy(dateintmean,&jintmean,&mintmean,&aintmean); */ /* Done in freqsummary */
         if(prvforecast==1){
           dateprojd=(jproj1+12*mproj1+365*anproj1)/365;
           jprojd=jproj1;
           mprojd=mproj1;
           anprojd=anproj1;
           dateprojf=(jproj2+12*mproj2+365*anproj2)/365;
           jprojf=jproj2;
           mprojf=mproj2;
           anprojf=anproj2;
         } else if(prvforecast == 2){
           dateprojd=dateintmean;
           date2dmy(dateprojd,&jprojd, &mprojd, &anprojd);
           dateprojf=dateintmean+yrfproj;
           date2dmy(dateprojf,&jprojf, &mprojf, &anprojf);
         }
         if(prvbackcast==1){
           datebackd=(jback1+12*mback1+365*anback1)/365;
           jbackd=jback1;
           mbackd=mback1;
           anbackd=anback1;
           datebackf=(jback2+12*mback2+365*anback2)/365;
           jbackf=jback2;
           mbackf=mback2;
           anbackf=anback2;
         } else if(prvbackcast == 2){
           datebackd=dateintmean;
           date2dmy(datebackd,&jbackd, &mbackd, &anbackd);
           datebackf=dateintmean-yrbproj;
           date2dmy(datebackf,&jbackf, &mbackf, &anbackf);
         }
         
         printinggnuplot(fileresu, optionfilefiname,ageminpar,agemaxpar,bage, fage, prevfcast, prevbcast, pathc,p, (int)anprojd-bage, (int)anbackd-fage);
       }
       printinghtml(fileresu,title,datafile, firstpass, lastpass, stepm, weightopt, \
                    model,imx,jmin,jmax,jmean,rfileres,popforecast,mobilav,prevfcast,mobilavproj,prevbcast, estepm, \
                    jprev1,mprev1,anprev1,dateprev1, dateprojd, datebackd,jprev2,mprev2,anprev2,dateprev2,dateprojf, datebackf);
                   
       /*------------ 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,firstobs,lastobs);
       free_vector(agedc,firstobs,lastobs);
       /*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);
       /* Computes the prevalence limit for each combination k of the dummy covariates by calling prevalim(k) */
       prevalence_limit(p, prlim,  ageminpar, agemaxpar, ftolpl, &ncvyear);
       fclose(ficrespl);
   
       /*------------- h Pij x at various ages ------------*/
       /*#include "hpijx.h"*/
       /** h Pij x Probability to be in state j at age x+h being in i at x, for each combination k of dummies in the model line or to nres?*/
       /* calls hpxij with combination k */
       hPijx(p, bage, fage);
       fclose(ficrespij);
       
       /* ncovcombmax=  pow(2,cptcoveff); */
       /*-------------- Variance of one-step probabilities for a combination ij or for nres ?---*/
       k=1;
       varprob(optionfilefiname, matcov, p, delti, nlstate, bage, fage,k,Tvar,nbcode, ncodemax,strstart);
       
       /* Prevalence for each covariate combination in probs[age][status][cov] */
       probs= ma3x(AGEINF,AGESUP,1,nlstate+ndeath, 1,ncovcombmax);
       for(i=AGEINF;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(AGEINF, AGESUP,1,nlstate+ndeath, 1,ncovcombmax);
         for(i=AGEINF;i<=AGESUP;i++)
           for(j=1;j<=nlstate+ndeath;j++)
             for(k=1;k<=ncovcombmax;k++)
               mobaverages[i][j][k]=0.;
         mobaverage=mobaverages;
         if (mobilav!=0) {
           printf("Movingaveraging observed prevalence\n");
           fprintf(ficlog,"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);
           }
         } else if (mobilavproj !=0) {
           printf("Movingaveraging projected observed prevalence\n");
           fprintf(ficlog,"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);
           }
         }else{
           printf("Internal error moving average\n");
           fflush(stdout);
           exit(1);
         }
       }/* end if moving average */
       
       /*---------- Forecasting ------------------*/
       if(prevfcast==1){ 
         /*   /\*    if(stepm ==1){*\/ */
         /*   /\*  anproj1, mproj1, jproj1 either read explicitly or yrfproj *\/ */
         /*This done previously after freqsummary.*/
         /*   dateprojd=(jproj1+12*mproj1+365*anproj1)/365; */
         /*   dateprojf=(jproj2+12*mproj2+365*anproj2)/365; */
         
         /* } else if (prvforecast==2){ */
         /*   /\*    if(stepm ==1){*\/ */
         /*   /\*  anproj1, mproj1, jproj1 either read explicitly or yrfproj *\/ */
         /* } */
         /*prevforecast(fileresu, dateintmean, anproj1, mproj1, jproj1, agemin, agemax, dateprev1, dateprev2, mobilavproj, mobaverage, bage, fage, firstpass, lastpass, anproj2, p, cptcoveff);*/
         prevforecast(fileresu,dateintmean, dateprojd, dateprojf, agemin, agemax, dateprev1, dateprev2, mobilavproj, mobaverage, bage, fage, firstpass, lastpass, p, cptcoveff);
       }
   
       /* Prevbcasting */
       if(prevbcast==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);
   
         /* /\* prevbackforecast(fileresu, mobaverage, anback1, mback1, jback1, agemin, agemax, dateprev1, dateprev2, *\/ */
         /* /\*                   mobilavproj, bage, fage, firstpass, lastpass, anback2, p, cptcoveff); *\/ */
         /* prevbackforecast(fileresu, mobaverage, anback1, mback1, jback1, agemin, agemax, dateprev1, dateprev2, */
         /*                       mobilavproj, bage, fage, firstpass, lastpass, anback2, p, cptcoveff); */
         prevbackforecast(fileresu, mobaverage, dateintmean, dateprojd, dateprojf, agemin, agemax, dateprev1, dateprev2,
                          mobilavproj, bage, fage, firstpass, lastpass, p, cptcoveff);
   
         
         varbprlim(fileresu, nresult, mobaverage, mobilavproj, bage, fage, bprlim, &ncvyear, ftolpl, p, matcov, delti, stepm, cptcoveff);
   
         
         free_matrix(bprlim,1,nlstate,1,nlstate); /*here or after loop ? */
         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);
       }    /* end  Prevbcasting */
    
    
       /* ------ 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(i1 != 1 && TKresult[nres]!= k)
           continue;
         fprintf(ficreseij,"\n#****** ");
         printf("\n#****** ");
         for(j=1;j<=cptcoveff;j++) {
           fprintf(ficreseij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]);
           printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]);
         }
         for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
           printf(" V%d=%lg ",TvarsQ[j], TinvDoQresult[nres][TvarsQ[j]]); /* TvarsQ[j] gives the name of the jth quantitative (fixed or time v) */
           fprintf(ficreseij,"V%d=%lg ",TvarsQ[j], TinvDoQresult[nres][TvarsQ[j]]);
         }
         fprintf(ficreseij,"******\n");
         printf("******\n");
         
         eij=ma3x(1,nlstate,1,nlstate,(int) bage, (int) fage);
         oldm=oldms;savm=savms;
         /* printf("HELLO Entering evsij bage=%d fage=%d k=%d estepm=%d nres=%d\n",(int) bage, (int)fage, k, estepm, nres); */
         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 ------------*/
       /* Should be moved in a function */         
       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);
   
       i1=pow(2,cptcoveff); /* Number of combination of dummy covariates */
       if (cptcovn < 1){i1=1;}
       
       for(nres=1; nres <= nresult; nres++) /* For each resultline, find the combination and output results according to the values of dummies and then quanti.  */
       for(k=1; k<=i1;k++){ /* For any combination of dummy covariates, fixed and varying. For each nres and each value at position k
                             * we know Tresult[nres][result_position]= value of the dummy variable at the result_position in the nres resultline
                             * Tvqresult[nres][result_position]= id of the variable at the result_position in the nres resultline 
                             * and Tqresult[nres][result_position]= value of the variable at the result_position in the nres resultline */
         /* */
         if(i1 != 1 && TKresult[nres]!= k) /* TKresult[nres] is the combination of this nres resultline. All the i1 combinations are not output */
           continue;
         printf("\n# model %s \n#****** Result for:", model);
         fprintf(ficrest,"\n# model %s \n#****** Result for:", model);
         fprintf(ficlog,"\n# model %s \n#****** Result for:", model);
         /* It might not be a good idea to mix dummies and quantitative */
         /* for(j=1;j<=cptcoveff;j++){ /\* j=resultpos. Could be a loop on cptcovs: number of single dummy covariate in the result line as well as in the model *\/ */
         for(j=1;j<=cptcovs;j++){ /* j=resultpos. Could be a loop on cptcovs: number of single covariate (dummy or quantitative) in the result line as well as in the model */
           /* printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); /\* Output by variables in the resultline *\/ */
           /* Tvaraff[j] is the name of the dummy variable in position j in the equation model:
            * Tvaraff[1]@9={4, 3, 0, 0, 0, 0, 0, 0, 0}, in model=V5+V4+V3+V4*V3+V5*age
            * (V5 is quanti) V4 and V3 are dummies
            * TnsdVar[4] is the position 1 and TnsdVar[3]=2 in codtabm(k,l)(V4  V3)=V4  V3
            *                                                              l=1 l=2
            *                                                           k=1  1   1   0   0
            *                                                           k=2  2   1   1   0
            *                                                           k=3 [1] [2]  0   1
            *                                                           k=4  2   2   1   1
            * If nres=1 result: V3=1 V4=0 then k=3 and outputs
            * If nres=2 result: V4=1 V3=0 then k=2 and outputs
            * nres=1 =>k=3 j=1 V4= nbcode[4][codtabm(3,1)=1)=0; j=2  V3= nbcode[3][codtabm(3,2)=2]=1
            * nres=2 =>k=2 j=1 V4= nbcode[4][codtabm(2,1)=2)=1; j=2  V3= nbcode[3][codtabm(2,2)=1]=0
            */
           /* Tvresult[nres][j] Name of the variable at position j in this resultline */
           /* Tresult[nres][j] Value of this variable at position j could be a float if quantitative  */
   /* We give up with the combinations!! */
           printf("\n j=%d In computing T_ Dummy[modelresult[%d][%d]]=%d, modelresult[%d][%d]=%d cptcovs=%d, cptcoveff=%d Fixed[modelresult[nres][j]]=%d\n", j, nres, j, Dummy[modelresult[nres][j]],nres,j,modelresult[nres][j],cptcovs, cptcoveff,Fixed[modelresult[nres][j]]);  /* end if dummy  or quanti */
   
           if(Dummy[modelresult[nres][j]]==0){/* Dummy variable of the variable in position modelresult in the model corresponding to j in resultline  */
             printf("V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][j]); /* Output of each value for the combination TKresult[nres], ordere by the covariate values in the resultline  */
             fprintf(ficlog,"V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][j]); /* Output of each value for the combination TKresult[nres], ordere by the covariate values in the resultline  */
             fprintf(ficrest,"V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][j]); /* Output of each value for the combination TKresult[nres], ordere by the covariate values in the resultline  */
             if(Fixed[modelresult[nres][j]]==0){ /* Fixed */
               printf("fixed ");fprintf(ficlog,"fixed ");fprintf(ficrest,"fixed ");
             }else{
               printf("varyi ");fprintf(ficlog,"varyi ");fprintf(ficrest,"varyi ");
             }
             /* fprintf(ficrest,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
             /* fprintf(ficlog,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
           }else if(Dummy[modelresult[nres][j]]==1){ /* Quanti variable */
             /* For each selected (single) quantitative value */
             printf(" V%d=%lg ",Tvqresult[nres][j],Tqresult[nres][j]);
             fprintf(ficlog," V%d=%lg ",Tvqresult[nres][j],Tqresult[nres][j]);
             fprintf(ficrest," V%d=%lg ",Tvqresult[nres][j],Tqresult[nres][j]);
             if(Fixed[modelresult[nres][j]]==0){ /* Fixed */
               printf("fixed ");fprintf(ficlog,"fixed ");fprintf(ficrest,"fixed ");
             }else{
               printf("varyi ");fprintf(ficlog,"varyi ");fprintf(ficrest,"varyi ");
             }
           }else{
             printf("Error in computing T_ Dummy[modelresult[%d][%d]]=%d, modelresult[%d][%d]=%d cptcovs=%d, cptcoveff=%d \n", nres, j, Dummy[modelresult[nres][j]],nres,j,modelresult[nres][j],cptcovs, cptcoveff);  /* end if dummy  or quanti */
             fprintf(ficlog,"Error in computing T_ Dummy[modelresult[%d][%d]]=%d, modelresult[%d][%d]=%d cptcovs=%d, cptcoveff=%d \n", nres, j, Dummy[modelresult[nres][j]],nres,j,modelresult[nres][j],cptcovs, cptcoveff);  /* end if dummy  or quanti */
             exit(1);
           }
         } /* End loop for each variable in the resultline */
         /* for (j=1; j<= nsq; j++){ /\* For each selected (single) quantitative value *\/ */
         /*        printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); /\* Wrong j is not in the equation model *\/ */
         /*        fprintf(ficrest," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
         /*        fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
         /* }       */
         fprintf(ficrest,"******\n");
         fprintf(ficlog,"******\n");
         printf("******\n");
         
         fprintf(ficresstdeij,"\n#****** ");
         fprintf(ficrescveij,"\n#****** ");
         /* It could have been: for(j=1;j<=cptcoveff;j++) {printf("V=%d=%lg",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);} */
         /* But it won't be sorted and depends on how the resultline is ordered */
         for(j=1;j<=cptcoveff;j++) {
           fprintf(ficresstdeij,"V%d=%d ",Tvresult[nres][j],Tresult[nres][j]);
           /* fprintf(ficresstdeij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
           /* fprintf(ficrescveij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
         }
         for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value, TvarsQind gives the position of a quantitative in model equation  */
           fprintf(ficresstdeij," V%d=%lg ",Tvar[TvarsQind[j]],Tqresult[nres][resultmodel[nres][TvarsQind[j]]]);
           fprintf(ficrescveij," V%d=%lg ",Tvar[TvarsQind[j]],Tqresult[nres][resultmodel[nres][TvarsQind[j]]]);
         } 
         fprintf(ficresstdeij,"******\n");
         fprintf(ficrescveij,"******\n");
         
         fprintf(ficresvij,"\n#****** ");
         /* pstamp(ficresvij); */
         for(j=1;j<=cptcoveff;j++) 
           fprintf(ficresvij,"V%d=%d ",Tvresult[nres][j],Tresult[nres][j]);
           /* fprintf(ficresvij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[TnsdVar[Tvaraff[j]]])]); */
         for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
           /* fprintf(ficresvij," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]); /\* To solve *\/ */
           fprintf(ficresvij," V%d=%lg ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); /* Solved */
         } 
         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);
         
         epj=vector(1,nlstate+1);
         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 forward period (stable) prevalences in each health state \n");
           fprintf(ficrest,"# Age popbased mobilav e.. (std) "); /* Adding covariate values? */
           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"); */
           printf("Computing age specific forward period (stable) prevalences in each health state \n");
           fprintf(ficlog,"Computing age specific forward 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_vector(epj,1,nlstate+1);
         free_ma3x(eij,1,nlstate,1,nlstate,(int) bage, (int)fage);
         free_ma3x(vareij,1,nlstate,1,nlstate,(int) bage, (int)fage);
         printf("done selection\n");fflush(stdout);
         fprintf(ficlog,"done selection\n");fflush(ficlog);
         
       } /* End k selection or end covariate selection for nres */
   
       printf("done State-specific expectancies\n");fflush(stdout);
       fprintf(ficlog,"done State-specific expectancies\n");fflush(ficlog);
   
       /* variance-covariance of forward period prevalence */
       varprlim(fileresu, nresult, mobaverage, mobilavproj, bage, fage, prlim, &ncvyear, ftolpl, p, matcov, delti, stepm, cptcoveff);
   
       
       free_vector(weight,firstobs,lastobs);
       free_imatrix(Tvardk,1,NCOVMAX,1,2);
       free_imatrix(Tvard,1,NCOVMAX,1,2);
       free_imatrix(s,1,maxwav+1,firstobs,lastobs);
       free_matrix(anint,1,maxwav,firstobs,lastobs); 
       free_matrix(mint,1,maxwav,firstobs,lastobs);
       free_ivector(cod,firstobs,lastobs);
       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,AGEINF, AGESUP,1,nlstate+ndeath, 1,ncovcombmax); /* We need to have a squared matrix with prevalence of the dead! */
       free_ma3x(probs,AGEINF,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);
     if(ntv+nqtv>=1)free_ma3x(cotvar,1,maxwav,1,ntv+nqtv,firstobs,lastobs);
     if(nqtv>=1)free_ma3x(cotqvar,1,maxwav,1,nqtv,firstobs,lastobs);
     if(nqv>=1)free_matrix(coqvar,1,nqv,firstobs,lastobs);
     free_matrix(covar,0,NCOVMAX,firstobs,lastobs);
     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(paramstart,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
     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(TnsdVar,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(TvarVV,1,NCOVMAX);
     free_ivector(TvarVVind,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,0,ncovcombmax);
     free_ivector(Tage,1,NCOVMAX);
     free_ivector(Tmodelind,1,NCOVMAX);
     free_ivector(TmodelInvind,1,NCOVMAX);
     free_ivector(TmodelInvQind,1,NCOVMAX);
   
     free_matrix(precov, 1,MAXRESULTLINESPONE,1,NCOVMAX+1); /* Could be elsewhere ?*/
   
     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 -----------*/
     
   
   /* Executes gnuplot */
     
     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);
     strcpy(pplotcmd,plotcmd);
     
     if((outcmd=system(plotcmd)) != 0){
       printf("Error in 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);
         strcpy(plotcmd,pplotcmd);
       }
     }
     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);
   #else
         sprintf(pplotcmd, "%s", optionfilehtm);
   #endif
         printf("Starting browser with: %s",pplotcmd);fflush(stdout);
         system(pplotcmd);
       }
       else if (z[0] == 'g') system(plotcmd);
       else if (z[0] == 'q') exit(0);
     }
   end:
     while (z[0] != 'q') {
       printf("\nType  q for exiting: "); fflush(stdout);
       scanf("%s",z);
     }
     printf("End\n");
     exit(0);
   }

Removed from v.1.6  
changed lines
  Added in v.1.340


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