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Diff for /imach/src/imach.c between versions 1.320 and 1.321

version 1.320, 2022/06/02 05:10:11 version 1.321, 2022/07/22 12:04:24
Line 1 Line 1
 /* $Id$  /* $Id$
   $State$    $State$
   $Log$    $Log$
     Revision 1.321  2022/07/22 12:04:24  brouard
     Summary: r28
   
     *  imach.c (Module): Output of Wald test in the htm file and not only in the log.
   
   Revision 1.320  2022/06/02 05:10:11  brouard    Revision 1.320  2022/06/02 05:10:11  brouard
   *** empty log message ***    *** empty log message ***
   
Line 7240  void printinghtml(char fileresu[], char Line 7245  void printinghtml(char fileresu[], char
       }        }
                 
        /* if(nqfveff+nqtveff 0) */ /* Test to be done */         /* if(nqfveff+nqtveff 0) */ /* Test to be done */
        fprintf(fichtm," ************\n<hr size=\"2\" color=\"#EC5E5E\">");         fprintf(fichtm," (model=%s) ************\n<hr size=\"2\" color=\"#EC5E5E\">",model);
        if(invalidvarcomb[k1]){         if(invalidvarcomb[k1]){
          fprintf(fichtm,"\n<h3>Combination (%d) ignored because no cases </h3>\n",k1);            fprintf(fichtm,"\n<h3>Combination (%d) ignored because no cases </h3>\n",k1); 
          printf("\nCombination (%d) ignored because no cases \n",k1);            printf("\nCombination (%d) ignored because no cases \n",k1); 
Line 7427  See page 'Matrix of variance-covariance Line 7432  See page 'Matrix of variance-covariance
         fprintf(fichtm," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);          fprintf(fichtm," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]);
       }        }
   
        fprintf(fichtm," ************\n<hr size=\"2\" color=\"#EC5E5E\">");         fprintf(fichtm," (model=%s) ************\n<hr size=\"2\" color=\"#EC5E5E\">",model);
   
        if(invalidvarcomb[k1]){         if(invalidvarcomb[k1]){
          fprintf(fichtm,"\n<h4>Combination (%d) ignored because no cases </h4>\n",k1);            fprintf(fichtm,"\n<h4>Combination (%d) ignored because no cases </h4>\n",k1); 
Line 7563  void printinggnuplot(char fileresu[], ch Line 7568  void printinggnuplot(char fileresu[], ch
         fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"V_"),cpt,k1,nres);          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,"\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 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\" font \"Helvetica,12\"\n",cpt,gplotlabel);          fprintf(ficgp,"set title \"Alive state %d %s model=%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_"),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); */          /* 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*/        /* k1-1 error should be nres-1*/
Line 12551  Please run with mle=-1 to get a correct Line 12556  Please run with mle=-1 to get a correct
       hesscov(matcov, hess, p, npar, delti, ftolhess, func);        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");        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(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>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 'Matrix of variance-covariance of one-step probabilities' and its graphs.\n</br>");
       fprintf(fichtm,"\n<table style=\"text-align:center; border: 1px solid\">");        fprintf(fichtm,"\n<table style=\"text-align:center; border: 1px solid\">");
       fprintf(fichtm, "\n<tr><th>Model=</th><th>1</th><th>+ age</th>");        fprintf(fichtm, "\n<tr><th>Model=</th><th>1</th><th>+ age</th>");
       if(nagesqr==1){        if(nagesqr==1){
Line 12581  Please run with mle=-1 to get a correct Line 12587  Please run with mle=-1 to get a correct
             fprintf(fichtm, "<td>%1d%1d</td>",i,k);              fprintf(fichtm, "<td>%1d%1d</td>",i,k);
             for(j=1; j <=ncovmodel; j++){              for(j=1; j <=ncovmodel; j++){
               wald=p[jk]/sqrt(matcov[jk][jk]);                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]));                printf("%12.7f(%12.7f) sqrt(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]));                fprintf(ficlog,"%12.7f(%12.7f) sqrt(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){                if(fabs(wald) > 1.96){
                 fprintf(fichtm, "<td><b>%12.7f</b> (%12.7f)</br>",p[jk],sqrt(matcov[jk][jk]));                  fprintf(fichtm, "<td><b>%12.7f</b></br> (%12.7f)</br>",p[jk],sqrt(matcov[jk][jk]));
                 fprintf(fichtm,"<b>W=%8.3f</b></br>",wald);  
               }else{                }else{
                 fprintf(fichtm, "<td>%12.7f (%12.7f)</br>",p[jk],sqrt(matcov[jk][jk]));                  fprintf(fichtm, "<td>%12.7f (%12.7f)</br>",p[jk],sqrt(matcov[jk][jk]));
                 fprintf(fichtm,"W=%8.3f</br>",wald);  
               }                }
                 fprintf(fichtm,"sqrt(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]));                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++;                 jk++; 
             }              }
Line 13191  Please run with mle=-1 to get a correct Line 13196  Please run with mle=-1 to get a correct
     for(k=1; k<=i1;k++){ /* For any combination of dummy covariates, fixed and varying */      for(k=1; k<=i1;k++){ /* For any combination of dummy covariates, fixed and varying */
       if(i1 != 1 && TKresult[nres]!= k)        if(i1 != 1 && TKresult[nres]!= k)
         continue;          continue;
       printf("\n#****** Result for:");        printf("\n# model %s \n#****** Result for:", model);
       fprintf(ficrest,"\n#****** Result for:");        fprintf(ficrest,"\n# model %s \n#****** Result for:", model);
       fprintf(ficlog,"\n#****** Result for:");        fprintf(ficlog,"\n# model %s \n#****** Result for:", model);
       for(j=1;j<=cptcoveff;j++){         for(j=1;j<=cptcoveff;j++){ 
         printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);          printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
         fprintf(ficrest,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);          fprintf(ficrest,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]);
Removed from v.1.320  
changed lines
  Added in v.1.321

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