Tvar[1]= 2 */
+/* Some documentation */
+ /* Design original data
+ * V1 V2 V3 V4 V5 V6 V7 V8 Weight ddb ddth d1st s1 V9 V10 V11 V12 s2 V9 V10 V11 V12
+ * < ncovcol=6 > nqv=2 (V7 V8) dv dv dv qtv dv dv dvv qtv
+ * ntv=3 nqtv=1
+ * cptcovn number of covariates (not including constant and age) = # of + plus 1 = 10+1=11
+ * For time varying covariate, quanti or dummies
+ * cotqvar[wav][iv(1 to nqtv)][i]= [1][12][i]=(V12) quanti
+ * cotvar[wav][ntv+iv][i]= [3+(1 to nqtv)][i]=(V12) quanti
+ * cotvar[wav][iv(1 to ntv)][i]= [1][1][i]=(V9) dummies at wav 1
+ * cotvar[wav][iv(1 to ntv)][i]= [1][2][i]=(V10) dummies at wav 1
+ * covar[k,i], value of kth fixed covariate dummy or quanti :
+ * 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
+ * k= 1 2 3 4 5 6 7 8 9 10 11
+ */
+/* According to the model, more columns can be added to covar by the product of covariates */
+/* 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
+ # 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
+*/
+/* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
+/* 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,*/
+ /* fixed or varying), 1 for age product, 2 for*/
+ /* product */
+/*Dummy[k]= 1 0 0 1 3 1 1 2 0 *//*Dummy[k] 0=dummy (0 1), 1 quantitative */
+ /*(single or product without age), 2 dummy*/
+ /* with age product, 3 quant with age product*/
+/*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 */
+/* nsq 1 2 */ /* Counting single quantit tv */
+/* TvarsQ[k] 5 2 */ /* Number of single quantitative cova */
+/* TvarsQind 1 6 */ /* position K of single quantitative cova */
+/* Tprod[i]=k 1 2 */ /* Position in model of the ith prod without age */
+/* cptcovage 1 2 */ /* Counting cov*age in the model equation */
+/* Tage[cptcovage]=k 5 8 */ /* Position in the model of ith cov*age */
+/* Tvard[1][1]@4={4,3,1,2} V4*V3 V1*V2 */ /* Position in model of the ith prod without age */
+/* 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 */
+/* TvarFind; TvarFind[1]=6, TvarFind[2]=7, TvarFind[3]=9 *//* Inverse V2(6) is first fixed (single or prod) */
+/* Type */
+/* V 1 2 3 4 5 */
+/* F F V V V */
+/* D Q D D Q */
+/* */
+int *TvarsD;
+int *TvarsDind;
+int *TvarsQ;
+int *TvarsQind;
+
+#define MAXRESULTLINESPONE 10+1
+int nresult=0;
+int parameterline=0; /* # of the parameter (type) line */
+int TKresult[MAXRESULTLINESPONE];
+int Tresult[MAXRESULTLINESPONE][NCOVMAX];/* For dummy variable , value (output) */
+int Tinvresult[MAXRESULTLINESPONE][NCOVMAX];/* For dummy variable , value (output) */
+int Tvresult[MAXRESULTLINESPONE][NCOVMAX]; /* For dummy variable , variable # (output) */
+double Tqresult[MAXRESULTLINESPONE][NCOVMAX]; /* For quantitative variable , value (output) */
+double Tqinvresult[MAXRESULTLINESPONE][NCOVMAX]; /* For quantitative variable , value (output) */
+int Tvqresult[MAXRESULTLINESPONE][NCOVMAX]; /* For quantitative variable , variable # (output) */
+
+/* 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
+ # 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
+*/
+/* int *TDvar; /\**< TDvar[1]=4, TDvarF[2]=3, TDvar[3]=6 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 *\/ */
+int *TvarF; /**< TvarF[1]=Tvar[6]=2, TvarF[2]=Tvar[7]=7, TvarF[3]=Tvar[9]=1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
+int *TvarFind; /**< TvarFind[1]=6, TvarFind[2]=7, Tvarind[3]=9 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
+int *TvarV; /**< TvarV[1]=Tvar[1]=5, TvarV[2]=Tvar[2]=4 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
+int *TvarVind; /**< TvarVind[1]=1, TvarVind[2]=2 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
+int *TvarA; /**< TvarA[1]=Tvar[5]=5, TvarA[2]=Tvar[8]=1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
+int *TvarAind; /**< TvarindA[1]=5, TvarAind[2]=8 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
+int *TvarFD; /**< TvarFD[1]=V1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
+int *TvarFDind; /* TvarFDind[1]=9 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
+int *TvarFQ; /* TvarFQ[1]=V2 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
+int *TvarFQind; /* TvarFQind[1]=6 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
+int *TvarVD; /* TvarVD[1]=V5 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
+int *TvarVDind; /* TvarVDind[1]=1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
+int *TvarVQ; /* TvarVQ[1]=V5 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple time varying quantitative variable */
+int *TvarVQind; /* TvarVQind[1]=1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple time varying quantitative variable */
+
+int *Tvarsel; /**< Selected covariates for output */
+double *Tvalsel; /**< Selected modality value of covariate for output */
+int *Typevar; /**< 0 for simple covariate (dummy, quantitative, fixed or varying), 1 for age product, 2 for product */
+int *Fixed; /** Fixed[k] 0=fixed, 1 varying, 2 fixed with age product, 3 varying with age product */
+int *Dummy; /** Dummy[k] 0=dummy (0 1), 1 quantitative (single or product without age), 2 dummy with age product, 3 quant with age product */
+int *DummyV; /** Dummy[v] 0=dummy (0 1), 1 quantitative */
+int *FixedV; /** FixedV[v] 0 fixed, 1 varying */
+int *Tage;
+int anyvaryingduminmodel=0; /**< Any varying dummy in Model=1 yes, 0 no, to avoid a loop on waves in freq */
+int *Tmodelind; /** Tmodelind[Tvaraff[3]]=9 for V1 position,Tvaraff[1]@9={4, 3, 1, 0, 0, 0, 0, 0, 0}, model=V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1*/
+int *TmodelInvind; /** Tmodelind[Tvaraff[3]]=9 for V1 position,Tvaraff[1]@9={4, 3, 1, 0, 0, 0, 0, 0, 0}, model=V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1*/
+int *TmodelInvQind; /** Tmodelqind[1]=1 for V5(quantitative varying) position,Tvaraff[1]@9={4, 3, 1, 0, 0, 0, 0, 0, 0}, model=V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
+int *Ndum; /** Freq of modality (tricode */
+/* int **codtab;*/ /**< codtab=imatrix(1,100,1,10); */
+int **Tvard;
+int *Tprod;/**< Gives the k position of the k1 product */
+/* Tprod[k1=1]=3(=V1*V4) for V2+V1+V1*V4+age*V3 */
+int *Tposprod; /**< Gives the k1 product from the k position */
+ /* if V2+V1+V1*V4+age*V3+V3*V2 TProd[k1=2]=5 (V3*V2) */
+ /* Tposprod[k]=k1 , Tposprod[3]=1, Tposprod[5(V3*V2)]=2 (2nd product without age) */
+int cptcovprod, *Tvaraff, *invalidvarcomb;
double *lsurv, *lpop, *tpop;
-double ftol=FTOL; /* Tolerance for computing Max Likelihood */
-double ftolhess; /* Tolerance for computing hessian */
+#define FD 1; /* Fixed dummy covariate */
+#define FQ 2; /* Fixed quantitative covariate */
+#define FP 3; /* Fixed product covariate */
+#define FPDD 7; /* Fixed product dummy*dummy covariate */
+#define FPDQ 8; /* Fixed product dummy*quantitative covariate */
+#define FPQQ 9; /* Fixed product quantitative*quantitative covariate */
+#define VD 10; /* Varying dummy covariate */
+#define VQ 11; /* Varying quantitative covariate */
+#define VP 12; /* Varying product covariate */
+#define VPDD 13; /* Varying product dummy*dummy covariate */
+#define VPDQ 14; /* Varying product dummy*quantitative covariate */
+#define VPQQ 15; /* Varying product quantitative*quantitative covariate */
+#define APFD 16; /* Age product * fixed dummy covariate */
+#define APFQ 17; /* Age product * fixed quantitative covariate */
+#define APVD 18; /* Age product * varying dummy covariate */
+#define APVQ 19; /* Age product * varying quantitative covariate */
+
+#define FTYPE 1; /* Fixed covariate */
+#define VTYPE 2; /* Varying covariate (loop in wave) */
+#define ATYPE 2; /* Age product covariate (loop in dh within wave)*/
+
+struct kmodel{
+ int maintype; /* main type */
+ int subtype; /* subtype */
+};
+struct kmodel modell[NCOVMAX];
+
+double ftol=FTOL; /**< Tolerance for computing Max Likelihood */
+double ftolhess; /**< Tolerance for computing hessian */
/**************** split *************************/
static int split( char *path, char *dirc, char *name, char *ext, char *finame )
{
- /* From a file name with full path (either Unix or Windows) we extract the directory (dirc)
+ /* From a file name with (full) path (either Unix or Windows) we extract the directory (dirc)
the name of the file (name), its extension only (ext) and its first part of the name (finame)
*/
char *ss; /* pointer */
- int l1, l2; /* length counters */
+ int l1=0, l2=0; /* length counters */
l1 = strlen(path ); /* length of path */
if ( l1 == 0 ) return( GLOCK_ERROR_NOPATH );
ss= strrchr( path, DIRSEPARATOR ); /* find last / */
- if ( ss == NULL ) { /* no directory, so use current */
+ if ( ss == NULL ) { /* no directory, so determine current directory */
+ strcpy( name, path ); /* we got the fullname name because no directory */
/*if(strrchr(path, ODIRSEPARATOR )==NULL)
printf("Warning you should use %s as a separator\n",DIRSEPARATOR);*/
/* get current working directory */
/* extern char* getcwd ( char *buf , int len);*/
- if ( getcwd( dirc, FILENAME_MAX ) == NULL ) {
+#ifdef WIN32
+ if (_getcwd( dirc, FILENAME_MAX ) == NULL ) {
+#else
+ if (getcwd(dirc, FILENAME_MAX) == NULL) {
+#endif
return( GLOCK_ERROR_GETCWD );
}
- strcpy( name, path ); /* we've got it */
- } else { /* strip direcotry from path */
+ /* got dirc from getcwd*/
+ printf(" DIRC = %s \n",dirc);
+ } else { /* strip directory from path */
ss++; /* after this, the filename */
l2 = strlen( ss ); /* length of filename */
if ( l2 == 0 ) return( GLOCK_ERROR_NOPATH );
strcpy( name, ss ); /* save file name */
strncpy( dirc, path, l1 - l2 ); /* now the directory */
- dirc[l1-l2] = 0; /* add zero */
+ dirc[l1-l2] = '\0'; /* add zero */
+ printf(" DIRC2 = %s \n",dirc);
}
+ /* We add a separator at the end of dirc if not exists */
l1 = strlen( dirc ); /* length of directory */
- /*#ifdef windows
- if ( dirc[l1-1] != '\\' ) { dirc[l1] = '\\'; dirc[l1+1] = 0; }
-#else
- if ( dirc[l1-1] != '/' ) { dirc[l1] = '/'; dirc[l1+1] = 0; }
-#endif
- */
+ if( dirc[l1-1] != DIRSEPARATOR ){
+ dirc[l1] = DIRSEPARATOR;
+ dirc[l1+1] = 0;
+ printf(" DIRC3 = %s \n",dirc);
+ }
ss = strrchr( name, '.' ); /* find last / */
if (ss >0){
ss++;
@@ -426,6 +1592,7 @@ static int split( char *path, char *dirc
strncpy( finame, name, l1-l2);
finame[l1-l2]= 0;
}
+
return( 0 ); /* we're done */
}
@@ -444,6 +1611,120 @@ void replace_back_to_slash(char *s, char
}
}
+char *trimbb(char *out, char *in)
+{ /* Trim multiple blanks in line but keeps first blanks if line starts with blanks */
+ char *s;
+ s=out;
+ while (*in != '\0'){
+ while( *in == ' ' && *(in+1) == ' '){ /* && *(in+1) != '\0'){*/
+ in++;
+ }
+ *out++ = *in++;
+ }
+ *out='\0';
+ return s;
+}
+
+/* char *substrchaine(char *out, char *in, char *chain) */
+/* { */
+/* /\* Substract chain 'chain' from 'in', return and output 'out' *\/ */
+/* char *s, *t; */
+/* t=in;s=out; */
+/* while ((*in != *chain) && (*in != '\0')){ */
+/* *out++ = *in++; */
+/* } */
+
+/* /\* *in matches *chain *\/ */
+/* while ((*in++ == *chain++) && (*in != '\0')){ */
+/* printf("*in = %c, *out= %c *chain= %c \n", *in, *out, *chain); */
+/* } */
+/* in--; chain--; */
+/* while ( (*in != '\0')){ */
+/* printf("Bef *in = %c, *out= %c *chain= %c \n", *in, *out, *chain); */
+/* *out++ = *in++; */
+/* printf("Aft *in = %c, *out= %c *chain= %c \n", *in, *out, *chain); */
+/* } */
+/* *out='\0'; */
+/* out=s; */
+/* return out; */
+/* } */
+char *substrchaine(char *out, char *in, char *chain)
+{
+ /* Substract chain 'chain' from 'in', return and output 'out' */
+ /* in="V1+V1*age+age*age+V2", chain="age*age" */
+
+ char *strloc;
+
+ strcpy (out, in);
+ strloc = strstr(out, chain); /* strloc points to out at age*age+V2 */
+ printf("Bef strloc=%s chain=%s out=%s \n", strloc, chain, out);
+ if(strloc != NULL){
+ /* will affect out */ /* strloc+strlenc(chain)=+V2 */ /* Will also work in Unicode */
+ memmove(strloc,strloc+strlen(chain), strlen(strloc+strlen(chain))+1);
+ /* strcpy (strloc, strloc +strlen(chain));*/
+ }
+ printf("Aft strloc=%s chain=%s in=%s out=%s \n", strloc, chain, in, out);
+ return out;
+}
+
+
+char *cutl(char *blocc, char *alocc, char *in, char occ)
+{
+ /* cuts string in into blocc and alocc where blocc ends before FIRST occurence of char 'occ'
+ and alocc starts after first occurence of char 'occ' : ex cutv(blocc,alocc,"abcdef2ghi2j",'2')
+ gives alocc="abcdef" and blocc="ghi2j".
+ If occ is not found blocc is null and alocc is equal to in. Returns blocc
+ */
+ char *s, *t;
+ t=in;s=in;
+ while ((*in != occ) && (*in != '\0')){
+ *alocc++ = *in++;
+ }
+ if( *in == occ){
+ *(alocc)='\0';
+ s=++in;
+ }
+
+ if (s == t) {/* occ not found */
+ *(alocc-(in-s))='\0';
+ in=s;
+ }
+ while ( *in != '\0'){
+ *blocc++ = *in++;
+ }
+
+ *blocc='\0';
+ return t;
+}
+char *cutv(char *blocc, char *alocc, char *in, char occ)
+{
+ /* cuts string in into blocc and alocc where blocc ends before LAST occurence of char 'occ'
+ and alocc starts after last occurence of char 'occ' : ex cutv(blocc,alocc,"abcdef2ghi2j",'2')
+ gives blocc="abcdef2ghi" and alocc="j".
+ If occ is not found blocc is null and alocc is equal to in. Returns alocc
+ */
+ char *s, *t;
+ t=in;s=in;
+ while (*in != '\0'){
+ while( *in == occ){
+ *blocc++ = *in++;
+ s=in;
+ }
+ *blocc++ = *in++;
+ }
+ if (s == t) /* occ not found */
+ *(blocc-(in-s))='\0';
+ else
+ *(blocc-(in-s)-1)='\0';
+ in=s;
+ while ( *in != '\0'){
+ *alocc++ = *in++;
+ }
+
+ *alocc='\0';
+ return s;
+}
+
int nbocc(char *s, char occ)
{
int i,j=0;
@@ -451,32 +1732,50 @@ int nbocc(char *s, char occ)
i=0;
lg=strlen(s);
for(i=0; i<= lg; i++) {
- if (s[i] == occ ) j++;
+ if (s[i] == occ ) j++;
}
return j;
}
-void cutv(char *u,char *v, char*t, char occ)
-{
- /* cuts string t into u and v where u ends before first occurence of char 'occ'
- and v starts after first occurence of char 'occ' : ex cutv(u,v,"abcdef2ghi2j",'2')
- gives u="abcedf" and v="ghi2j" */
- int i,lg,j,p=0;
- i=0;
- for(j=0; j<=strlen(t)-1; j++) {
- if((t[j]!= occ) && (t[j+1]== occ)) p=j+1;
- }
+/* void cutv(char *u,char *v, char*t, char occ) */
+/* { */
+/* /\* cuts string t into u and v where u ends before last occurence of char 'occ' */
+/* and v starts after last occurence of char 'occ' : ex cutv(u,v,"abcdef2ghi2j",'2') */
+/* gives u="abcdef2ghi" and v="j" *\/ */
+/* int i,lg,j,p=0; */
+/* i=0; */
+/* lg=strlen(t); */
+/* for(j=0; j<=lg-1; j++) { */
+/* if((t[j]!= occ) && (t[j+1]== occ)) p=j+1; */
+/* } */
- lg=strlen(t);
- for(j=0; j=(p+1))(v[j-p-1] = t[j]);
- }
+/* for(j=0; j<= lg; j++) { */
+/* if (j>=(p+1))(v[j-p-1] = t[j]); */
+/* } */
+/* } */
+
+#ifdef _WIN32
+char * strsep(char **pp, const char *delim)
+{
+ char *p, *q;
+
+ if ((p = *pp) == NULL)
+ return 0;
+ if ((q = strpbrk (p, delim)) != NULL)
+ {
+ *pp = q + 1;
+ *q = '\0';
+ }
+ else
+ *pp = 0;
+ return p;
}
+#endif
/********************** nrerror ********************/
@@ -585,7 +1884,9 @@ double **matrix(long nrl, long nrh, long
for (i=nrl+1; i<=nrh; i++) m[i]=m[i-1]+ncol;
return m;
- /* print *(*(m+1)+70) or print m[1][70]; print m+1 or print &(m[1])
+ /* print *(*(m+1)+70) or print m[1][70]; print m+1 or print &(m[1]) or &(m[1][0])
+m[i] = address of ith row of the table. &(m[i]) is its value which is another adress
+that of m[i][0]. In order to get the value p m[i][0] but it is unitialized.
*/
}
@@ -653,7 +1954,9 @@ char *subdirf(char fileres[])
/*************** function subdirf2 ***********/
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 */
/* Caution optionfilefiname is hidden */
strcpy(tmpout,optionfilefiname);
strcat(tmpout,"/");
@@ -674,6 +1977,42 @@ char *subdirf3(char fileres[], char *pre
strcat(tmpout,fileres);
return tmpout;
}
+
+/*************** function subdirfext ***********/
+char *subdirfext(char fileres[], char *preop, char *postop)
+{
+
+ strcpy(tmpout,preop);
+ strcat(tmpout,fileres);
+ strcat(tmpout,postop);
+ return tmpout;
+}
+
+/*************** function subdirfext3 ***********/
+char *subdirfext3(char fileres[], char *preop, char *postop)
+{
+
+ /* Caution optionfilefiname is hidden */
+ strcpy(tmpout,optionfilefiname);
+ strcat(tmpout,"/");
+ strcat(tmpout,preop);
+ strcat(tmpout,fileres);
+ strcat(tmpout,postop);
+ return tmpout;
+}
+
+char *asc_diff_time(long time_sec, char ascdiff[])
+{
+ long sec_left, days, hours, minutes;
+ days = (time_sec) / (60*60*24);
+ sec_left = (time_sec) % (60*60*24);
+ hours = (sec_left) / (60*60) ;
+ sec_left = (sec_left) %(60*60);
+ minutes = (sec_left) /60;
+ sec_left = (sec_left) % (60);
+ sprintf(ascdiff,"%ld day(s) %ld hour(s) %ld minute(s) %ld second(s)",days, hours, minutes, sec_left);
+ return ascdiff;
+}
/***************** f1dim *************************/
extern int ncom;
@@ -695,11 +2034,17 @@ double f1dim(double x)
/*****************brent *************************/
double brent(double ax, double bx, double cx, double (*f)(double), double tol, double *xmin)
-{
+{
+ /* Given a function f, and given a bracketing triplet of abscissas ax, bx, cx (such that bx is
+ * between ax and cx, and f(bx) is less than both f(ax) and f(cx) ), this routine isolates
+ * the minimum to a fractional precision of about tol using Brent’s method. The abscissa of
+ * the minimum is returned as xmin, and the minimum function value is returned as brent , the
+ * returned function value.
+ */
int iter;
double a,b,d,etemp;
- double fu,fv,fw,fx;
- double ftemp;
+ double fu=0,fv,fw,fx;
+ double ftemp=0.;
double p,q,r,tol1,tol2,u,v,w,x,xm;
double e=0.0;
@@ -713,7 +2058,7 @@ double brent(double ax, double bx, doubl
/* if (2.0*fabs(fp-(*fret)) <= ftol*(fabs(fp)+fabs(*fret)))*/
printf(".");fflush(stdout);
fprintf(ficlog,".");fflush(ficlog);
-#ifdef DEBUG
+#ifdef DEBUGBRENT
printf("br %d,x=%.10e xm=%.10e b=%.10e a=%.10e tol=%.10e tol1=%.10e tol2=%.10e x-xm=%.10e fx=%.12e fu=%.12e,fw=%.12e,ftemp=%.12e,ftol=%.12e\n",iter,x,xm,b,a,tol,tol1,tol2,(x-xm),fx,fu,fw,ftemp,ftol);
fprintf(ficlog,"br %d,x=%.10e xm=%.10e b=%.10e a=%.10e tol=%.10e tol1=%.10e tol2=%.10e x-xm=%.10e fx=%.12e fu=%.12e,fw=%.12e,ftemp=%.12e,ftol=%.12e\n",iter,x,xm,b,a,tol,tol1,tol2,(x-xm),fx,fu,fw,ftemp,ftol);
/* if ((fabs(x-xm) <= (tol2-0.5*(b-a)))||(2.0*fabs(fu-ftemp) <= ftol*1.e-2*(fabs(fu)+fabs(ftemp)))) { */
@@ -733,12 +2078,12 @@ double brent(double ax, double bx, doubl
etemp=e;
e=d;
if (fabs(p) >= fabs(0.5*q*etemp) || p <= q*(a-x) || p >= q*(b-x))
- d=CGOLD*(e=(x >= xm ? a-x : b-x));
+ d=CGOLD*(e=(x >= xm ? a-x : b-x));
else {
- d=p/q;
- u=x+d;
- if (u-a < tol2 || b-u < tol2)
- d=SIGN(tol1,xm-x);
+ d=p/q;
+ u=x+d;
+ if (u-a < tol2 || b-u < tol2)
+ d=SIGN(tol1,xm-x);
}
} else {
d=CGOLD*(e=(x >= xm ? a-x : b-x));
@@ -748,19 +2093,19 @@ double brent(double ax, double bx, doubl
if (fu <= fx) {
if (u >= x) a=x; else b=x;
SHFT(v,w,x,u)
- SHFT(fv,fw,fx,fu)
- } else {
- if (u < x) a=u; else b=u;
- if (fu <= fw || w == x) {
- v=w;
- w=u;
- fv=fw;
- fw=fu;
- } else if (fu <= fv || v == x || v == w) {
- v=u;
- fv=fu;
- }
- }
+ SHFT(fv,fw,fx,fu)
+ } else {
+ if (u < x) a=u; else b=u;
+ if (fu <= fw || w == x) {
+ v=w;
+ w=u;
+ fv=fw;
+ fw=fu;
+ } else if (fu <= fv || v == x || v == w) {
+ v=u;
+ fv=fu;
+ }
+ }
}
nrerror("Too many iterations in brent");
*xmin=x;
@@ -771,51 +2116,158 @@ double brent(double ax, double bx, doubl
void mnbrak(double *ax, double *bx, double *cx, double *fa, double *fb, double *fc,
double (*func)(double))
-{
+{ /* Given a function func , and given distinct initial points ax and bx , this routine searches in
+the downhill direction (defined by the function as evaluated at the initial points) and returns
+new points ax , bx , cx that bracket a minimum of the function. Also returned are the function
+values at the three points, fa, fb , and fc such that fa > fb and fb < fc.
+ */
double ulim,u,r,q, dum;
double fu;
-
- *fa=(*func)(*ax);
- *fb=(*func)(*bx);
+
+ double scale=10.;
+ int iterscale=0;
+
+ *fa=(*func)(*ax); /* xta[j]=pcom[j]+(*ax)*xicom[j]; fa=f(xta[j])*/
+ *fb=(*func)(*bx); /* xtb[j]=pcom[j]+(*bx)*xicom[j]; fb=f(xtb[j]) */
+
+
+ /* while(*fb != *fb){ /\* *ax should be ok, reducing distance to *ax *\/ */
+ /* printf("Warning mnbrak *fb = %lf, *bx=%lf *ax=%lf *fa==%lf iter=%d\n",*fb, *bx, *ax, *fa, iterscale++); */
+ /* *bx = *ax - (*ax - *bx)/scale; */
+ /* *fb=(*func)(*bx); /\* xtb[j]=pcom[j]+(*bx)*xicom[j]; fb=f(xtb[j]) *\/ */
+ /* } */
+
if (*fb > *fa) {
SHFT(dum,*ax,*bx,dum)
- SHFT(dum,*fb,*fa,dum)
- }
+ SHFT(dum,*fb,*fa,dum)
+ }
*cx=(*bx)+GOLD*(*bx-*ax);
*fc=(*func)(*cx);
- while (*fb > *fc) {
+#ifdef DEBUG
+ printf("mnbrak0 a=%lf *fa=%lf, b=%lf *fb=%lf, c=%lf *fc=%lf\n",*ax,*fa,*bx,*fb,*cx, *fc);
+ fprintf(ficlog,"mnbrak0 a=%lf *fa=%lf, b=%lf *fb=%lf, c=%lf *fc=%lf\n",*ax,*fa,*bx,*fb,*cx, *fc);
+#endif
+ while (*fb > *fc) { /* Declining a,b,c with fa> fb > fc. If fc=inf it exits and if flat fb=fc it exits too.*/
r=(*bx-*ax)*(*fb-*fc);
- q=(*bx-*cx)*(*fb-*fa);
+ q=(*bx-*cx)*(*fb-*fa); /* What if fa=inf */
u=(*bx)-((*bx-*cx)*q-(*bx-*ax)*r)/
- (2.0*SIGN(FMAX(fabs(q-r),TINY),q-r));
- ulim=(*bx)+GLIMIT*(*cx-*bx);
- if ((*bx-u)*(u-*cx) > 0.0) {
+ (2.0*SIGN(FMAX(fabs(q-r),TINY),q-r)); /* Minimum abscissa of a parabolic estimated from (a,fa), (b,fb) and (c,fc). */
+ ulim=(*bx)+GLIMIT*(*cx-*bx); /* Maximum abscissa where function should be evaluated */
+ if ((*bx-u)*(u-*cx) > 0.0) { /* if u_p is between b and c */
fu=(*func)(u);
- } else if ((*cx-u)*(u-ulim) > 0.0) {
+#ifdef DEBUG
+ /* f(x)=A(x-u)**2+f(u) */
+ double A, fparabu;
+ A= (*fb - *fa)/(*bx-*ax)/(*bx+*ax-2*u);
+ fparabu= *fa - A*(*ax-u)*(*ax-u);
+ printf("\nmnbrak (*ax=%.12f, *fa=%.12lf), (*bx=%.12f, *fb=%.12lf), (*cx=%.12f, *fc=%.12lf), (*u=%.12f, fu=%.12lf, fparabu=%.12f, q=%lf < %lf=r)\n",*ax,*fa,*bx,*fb,*cx,*fc,u,fu, fparabu,q,r);
+ fprintf(ficlog,"\nmnbrak (*ax=%.12f, *fa=%.12lf), (*bx=%.12f, *fb=%.12lf), (*cx=%.12f, *fc=%.12lf), (*u=%.12f, fu=%.12lf, fparabu=%.12f, q=%lf < %lf=r)\n",*ax,*fa,*bx,*fb,*cx,*fc,u,fu, fparabu,q,r);
+ /* And thus,it can be that fu > *fc even if fparabu < *fc */
+ /* mnbrak (*ax=7.666299858533, *fa=299039.693133272231), (*bx=8.595447774979, *fb=298976.598289369489),
+ (*cx=10.098840694817, *fc=298946.631474258087), (*u=9.852501168332, fu=298948.773013752128, fparabu=298945.434711494134) */
+ /* In that case, there is no bracket in the output! Routine is wrong with many consequences.*/
+#endif
+#ifdef MNBRAKORIGINAL
+#else
+/* if (fu > *fc) { */
+/* #ifdef DEBUG */
+/* printf("mnbrak4 fu > fc \n"); */
+/* fprintf(ficlog, "mnbrak4 fu > fc\n"); */
+/* #endif */
+/* /\* SHFT(u,*cx,*cx,u) /\\* ie a=c, c=u and u=c; in that case, next SHFT(a,b,c,u) will give a=b=b, b=c=u, c=u=c and *\\/ *\/ */
+/* /\* SHFT(*fa,*fc,fu,*fc) /\\* (b, u, c) is a bracket while test fb > fc will be fu > fc will exit *\\/ *\/ */
+/* dum=u; /\* Shifting c and u *\/ */
+/* u = *cx; */
+/* *cx = dum; */
+/* dum = fu; */
+/* fu = *fc; */
+/* *fc =dum; */
+/* } else { /\* end *\/ */
+/* #ifdef DEBUG */
+/* printf("mnbrak3 fu < fc \n"); */
+/* fprintf(ficlog, "mnbrak3 fu < fc\n"); */
+/* #endif */
+/* dum=u; /\* Shifting c and u *\/ */
+/* u = *cx; */
+/* *cx = dum; */
+/* dum = fu; */
+/* fu = *fc; */
+/* *fc =dum; */
+/* } */
+#ifdef DEBUGMNBRAK
+ double A, fparabu;
+ A= (*fb - *fa)/(*bx-*ax)/(*bx+*ax-2*u);
+ fparabu= *fa - A*(*ax-u)*(*ax-u);
+ printf("\nmnbrak35 ax=%lf fa=%lf bx=%lf fb=%lf, u=%lf fp=%lf fu=%lf < or >= fc=%lf cx=%lf, q=%lf < %lf=r \n",*ax, *fa, *bx,*fb,u,fparabu,fu,*fc,*cx,q,r);
+ fprintf(ficlog,"\nmnbrak35 ax=%lf fa=%lf bx=%lf fb=%lf, u=%lf fp=%lf fu=%lf < or >= fc=%lf cx=%lf, q=%lf < %lf=r \n",*ax, *fa, *bx,*fb,u,fparabu,fu,*fc,*cx,q,r);
+#endif
+ dum=u; /* Shifting c and u */
+ u = *cx;
+ *cx = dum;
+ dum = fu;
+ fu = *fc;
+ *fc =dum;
+#endif
+ } else if ((*cx-u)*(u-ulim) > 0.0) { /* u is after c but before ulim */
+#ifdef DEBUG
+ printf("\nmnbrak2 u=%lf after c=%lf but before ulim\n",u,*cx);
+ fprintf(ficlog,"\nmnbrak2 u=%lf after c=%lf but before ulim\n",u,*cx);
+#endif
fu=(*func)(u);
if (fu < *fc) {
- SHFT(*bx,*cx,u,*cx+GOLD*(*cx-*bx))
- SHFT(*fb,*fc,fu,(*func)(u))
- }
- } else if ((u-ulim)*(ulim-*cx) >= 0.0) {
+#ifdef DEBUG
+ printf("\nmnbrak2 u=%lf after c=%lf but before ulim=%lf AND fu=%lf < %lf=fc\n",u,*cx,ulim,fu, *fc);
+ fprintf(ficlog,"\nmnbrak2 u=%lf after c=%lf but before ulim=%lf AND fu=%lf < %lf=fc\n",u,*cx,ulim,fu, *fc);
+#endif
+ SHFT(*bx,*cx,u,*cx+GOLD*(*cx-*bx))
+ SHFT(*fb,*fc,fu,(*func)(u))
+#ifdef DEBUG
+ printf("\nmnbrak2 shift GOLD c=%lf",*cx+GOLD*(*cx-*bx));
+#endif
+ }
+ } else if ((u-ulim)*(ulim-*cx) >= 0.0) { /* u outside ulim (verifying that ulim is beyond c) */
+#ifdef DEBUG
+ printf("\nmnbrak2 u=%lf outside ulim=%lf (verifying that ulim is beyond c=%lf)\n",u,ulim,*cx);
+ fprintf(ficlog,"\nmnbrak2 u=%lf outside ulim=%lf (verifying that ulim is beyond c=%lf)\n",u,ulim,*cx);
+#endif
u=ulim;
fu=(*func)(u);
- } else {
+ } else { /* u could be left to b (if r > q parabola has a maximum) */
+#ifdef DEBUG
+ printf("\nmnbrak2 u=%lf could be left to b=%lf (if r=%lf > q=%lf parabola has a maximum)\n",u,*bx,r,q);
+ fprintf(ficlog,"\nmnbrak2 u=%lf could be left to b=%lf (if r=%lf > q=%lf parabola has a maximum)\n",u,*bx,r,q);
+#endif
u=(*cx)+GOLD*(*cx-*bx);
fu=(*func)(u);
- }
+#ifdef DEBUG
+ printf("\nmnbrak2 new u=%lf fu=%lf shifted gold left from c=%lf and b=%lf \n",u,fu,*cx,*bx);
+ fprintf(ficlog,"\nmnbrak2 new u=%lf fu=%lf shifted gold left from c=%lf and b=%lf \n",u,fu,*cx,*bx);
+#endif
+ } /* end tests */
SHFT(*ax,*bx,*cx,u)
- SHFT(*fa,*fb,*fc,fu)
- }
+ SHFT(*fa,*fb,*fc,fu)
+#ifdef DEBUG
+ printf("\nmnbrak2 shift (*ax=%.12f, *fa=%.12lf), (*bx=%.12f, *fb=%.12lf), (*cx=%.12f, *fc=%.12lf)\n",*ax,*fa,*bx,*fb,*cx,*fc);
+ fprintf(ficlog, "\nmnbrak2 shift (*ax=%.12f, *fa=%.12lf), (*bx=%.12f, *fb=%.12lf), (*cx=%.12f, *fc=%.12lf)\n",*ax,*fa,*bx,*fb,*cx,*fc);
+#endif
+ } /* end while; ie return (a, b, c, fa, fb, fc) such that a < b < c with f(a) > f(b) and fb < f(c) */
}
/*************** linmin ************************/
-
+/* Given an n -dimensional point p[1..n] and an n -dimensional direction xi[1..n] , moves and
+resets p to where the function func(p) takes on a minimum along the direction xi from p ,
+and replaces xi by the actual vector displacement that p was moved. Also returns as fret
+the value of func at the returned location p . This is actually all accomplished by calling the
+routines mnbrak and brent .*/
int ncom;
double *pcom,*xicom;
double (*nrfunc)(double []);
+#ifdef LINMINORIGINAL
void linmin(double p[], double xi[], int n, double *fret,double (*func)(double []))
+#else
+void linmin(double p[], double xi[], int n, double *fret,double (*func)(double []), int *flat)
+#endif
{
double brent(double ax, double bx, double cx,
double (*f)(double), double tol, double *xmin);
@@ -825,52 +2277,142 @@ void linmin(double p[], double xi[], int
int j;
double xx,xmin,bx,ax;
double fx,fb,fa;
-
+
+#ifdef LINMINORIGINAL
+#else
+ double scale=10., axs, xxs; /* Scale added for infinity */
+#endif
+
ncom=n;
pcom=vector(1,n);
xicom=vector(1,n);
nrfunc=func;
for (j=1;j<=n;j++) {
pcom[j]=p[j];
- xicom[j]=xi[j];
+ xicom[j]=xi[j]; /* Former scale xi[j] of currrent direction i */
}
- ax=0.0;
- xx=1.0;
- mnbrak(&ax,&xx,&bx,&fa,&fx,&fb,f1dim);
- *fret=brent(ax,xx,bx,f1dim,TOL,&xmin);
+
+#ifdef LINMINORIGINAL
+ xx=1.;
+#else
+ axs=0.0;
+ xxs=1.;
+ do{
+ xx= xxs;
+#endif
+ ax=0.;
+ mnbrak(&ax,&xx,&bx,&fa,&fx,&fb,f1dim); /* Outputs: xtx[j]=pcom[j]+(*xx)*xicom[j]; fx=f(xtx[j]) */
+ /* brackets with inputs ax=0 and xx=1, but points, pcom=p, and directions values, xicom=xi, are sent via f1dim(x) */
+ /* xt[x,j]=pcom[j]+x*xicom[j] f(ax) = f(xt(a,j=1,n)) = f(p(j) + 0 * xi(j)) and f(xx) = f(xt(x, j=1,n)) = f(p(j) + 1 * xi(j)) */
+ /* Outputs: fa=f(p(j)) and fx=f(p(j) + xxs * xi(j) ) and f(bx)= f(p(j)+ bx* xi(j)) */
+ /* Given input ax=axs and xx=xxs, xx might be too far from ax to get a finite f(xx) */
+ /* Searches on line, outputs (ax, xx, bx) such that fx < min(fa and fb) */
+ /* Find a bracket a,x,b in direction n=xi ie xicom, order may change. Scale is [0:xxs*xi[j]] et non plus [0:xi[j]]*/
+#ifdef LINMINORIGINAL
+#else
+ if (fx != fx){
+ xxs=xxs/scale; /* Trying a smaller xx, closer to initial ax=0 */
+ printf("|");
+ fprintf(ficlog,"|");
+#ifdef DEBUGLINMIN
+ printf("\nLinmin NAN : input [axs=%lf:xxs=%lf], mnbrak outputs fx=%lf <(fb=%lf and fa=%lf) with xx=%lf in [ax=%lf:bx=%lf] \n", axs, xxs, fx,fb, fa, xx, ax, bx);
+#endif
+ }
+ }while(fx != fx && xxs > 1.e-5);
+#endif
+
+#ifdef DEBUGLINMIN
+ printf("\nLinmin after mnbrak: ax=%12.7f xx=%12.7f bx=%12.7f fa=%12.2f fx=%12.2f fb=%12.2f\n", ax,xx,bx,fa,fx,fb);
+ fprintf(ficlog,"\nLinmin after mnbrak: ax=%12.7f xx=%12.7f bx=%12.7f fa=%12.2f fx=%12.2f fb=%12.2f\n", ax,xx,bx,fa,fx,fb);
+#endif
+#ifdef LINMINORIGINAL
+#else
+ if(fb == fx){ /* Flat function in the direction */
+ xmin=xx;
+ *flat=1;
+ }else{
+ *flat=0;
+#endif
+ /*Flat mnbrak2 shift (*ax=0.000000000000, *fa=51626.272983130431), (*bx=-1.618034000000, *fb=51590.149499362531), (*cx=-4.236068025156, *fc=51590.149499362531) */
+ *fret=brent(ax,xx,bx,f1dim,TOL,&xmin); /* Giving a bracketting triplet (ax, xx, bx), find a minimum, xmin, according to f1dim, *fret(xmin),*/
+ /* fa = f(p[j] + ax * xi[j]), fx = f(p[j] + xx * xi[j]), fb = f(p[j] + bx * xi[j]) */
+ /* fmin = f(p[j] + xmin * xi[j]) */
+ /* P+lambda n in that direction (lambdamin), with TOL between abscisses */
+ /* f1dim(xmin): for (j=1;j<=ncom;j++) xt[j]=pcom[j]+xmin*xicom[j]; */
#ifdef DEBUG
- printf("retour brent fret=%.12e xmin=%.12e\n",*fret,xmin);
- fprintf(ficlog,"retour brent fret=%.12e xmin=%.12e\n",*fret,xmin);
+ printf("retour brent from bracket (a=%lf fa=%lf, xx=%lf fx=%lf, b=%lf fb=%lf): fret=%lf xmin=%lf\n",ax,fa,xx,fx,bx,fb,*fret,xmin);
+ fprintf(ficlog,"retour brent from bracket (a=%lf fa=%lf, xx=%lf fx=%lf, b=%lf fb=%lf): fret=%lf xmin=%lf\n",ax,fa,xx,fx,bx,fb,*fret,xmin);
+#endif
+#ifdef LINMINORIGINAL
+#else
+ }
+#endif
+#ifdef DEBUGLINMIN
+ printf("linmin end ");
+ fprintf(ficlog,"linmin end ");
#endif
for (j=1;j<=n;j++) {
+#ifdef LINMINORIGINAL
xi[j] *= xmin;
- p[j] += xi[j];
+#else
+#ifdef DEBUGLINMIN
+ if(xxs <1.0)
+ printf(" before xi[%d]=%12.8f", j,xi[j]);
+#endif
+ xi[j] *= xmin*xxs; /* xi rescaled by xmin and number of loops: if xmin=-1.237 and xi=(1,0,...,0) xi=(-1.237,0,...,0) */
+#ifdef DEBUGLINMIN
+ if(xxs <1.0)
+ printf(" after xi[%d]=%12.8f, xmin=%12.8f, ax=%12.8f, xx=%12.8f, bx=%12.8f, xxs=%12.8f", j,xi[j], xmin, ax, xx, bx,xxs );
+#endif
+#endif
+ p[j] += xi[j]; /* Parameters values are updated accordingly */
}
+#ifdef DEBUGLINMIN
+ printf("\n");
+ printf("Comparing last *frec(xmin=%12.8f)=%12.8f from Brent and frec(0.)=%12.8f \n", xmin, *fret, (*func)(p));
+ fprintf(ficlog,"Comparing last *frec(xmin=%12.8f)=%12.8f from Brent and frec(0.)=%12.8f \n", xmin, *fret, (*func)(p));
+ for (j=1;j<=n;j++) {
+ printf(" xi[%d]= %14.10f p[%d]= %12.7f",j,xi[j],j,p[j]);
+ fprintf(ficlog," xi[%d]= %14.10f p[%d]= %12.7f",j,xi[j],j,p[j]);
+ if(j % ncovmodel == 0){
+ printf("\n");
+ fprintf(ficlog,"\n");
+ }
+ }
+#else
+#endif
free_vector(xicom,1,n);
free_vector(pcom,1,n);
}
-char *asc_diff_time(long time_sec, char ascdiff[])
-{
- long sec_left, days, hours, minutes;
- days = (time_sec) / (60*60*24);
- sec_left = (time_sec) % (60*60*24);
- hours = (sec_left) / (60*60) ;
- sec_left = (sec_left) %(60*60);
- minutes = (sec_left) /60;
- sec_left = (sec_left) % (60);
- sprintf(ascdiff,"%d day(s) %d hour(s) %d minute(s) %d second(s)",days, hours, minutes, sec_left);
- return ascdiff;
-}
/*************** powell ************************/
+/*
+Minimization of a function func of n variables. Input consists in an initial starting point
+p[1..n] ; an initial matrix xi[1..n][1..n] whose columns contain the initial set of di-
+rections (usually the n unit vectors); and ftol, the fractional tolerance in the function value
+such that failure to decrease by more than this amount in one iteration signals doneness. On
+output, p is set to the best point found, xi is the then-current direction set, fret is the returned
+function value at p , and iter is the number of iterations taken. The routine linmin is used.
+ */
+#ifdef LINMINORIGINAL
+#else
+ int *flatdir; /* Function is vanishing in that direction */
+ int flat=0, flatd=0; /* Function is vanishing in that direction */
+#endif
void powell(double p[], double **xi, int n, double ftol, int *iter, double *fret,
double (*func)(double []))
{
- void linmin(double p[], double xi[], int n, double *fret,
+#ifdef LINMINORIGINAL
+ void linmin(double p[], double xi[], int n, double *fret,
double (*func)(double []));
- int i,ibig,j;
+#else
+ void linmin(double p[], double xi[], int n, double *fret,
+ double (*func)(double []),int *flat);
+#endif
+ int i,ibig,j,jk,k;
double del,t,*pt,*ptt,*xit;
+ double directest;
double fp,fptt;
double *xits;
int niterf, itmp;
@@ -881,77 +2423,144 @@ void powell(double p[], double **xi, int
xits=vector(1,n);
*fret=(*func)(p);
for (j=1;j<=n;j++) pt[j]=p[j];
+ rcurr_time = time(NULL);
for (*iter=1;;++(*iter)) {
- fp=(*fret);
ibig=0;
del=0.0;
- last_time=curr_time;
- (void) gettimeofday(&curr_time,&tzp);
- printf("\nPowell iter=%d -2*LL=%.12f %ld sec. %ld sec.",*iter,*fret, curr_time.tv_sec-last_time.tv_sec, curr_time.tv_sec-start_time.tv_sec);fflush(stdout);
- /* fprintf(ficlog,"\nPowell iter=%d -2*LL=%.12f %ld sec. %ld sec.",*iter,*fret, curr_time.tv_sec-last_time.tv_sec, curr_time.tv_sec-start_time.tv_sec);
- fprintf(ficrespow,"%d %.12f %ld",*iter,*fret,curr_time.tv_sec-start_time.tv_sec);
- */
- for (i=1;i<=n;i++) {
- printf(" %d %.12f",i, p[i]);
- fprintf(ficlog," %d %.12lf",i, p[i]);
+ rlast_time=rcurr_time;
+ /* (void) gettimeofday(&curr_time,&tzp); */
+ rcurr_time = time(NULL);
+ curr_time = *localtime(&rcurr_time);
+ printf("\nPowell iter=%d -2*LL=%.12f 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);
+/* fprintf(ficrespow,"%d %.12f %ld",*iter,*fret,curr_time.tm_sec-start_time.tm_sec); */
+ fp=(*fret); /* From former iteration or initial value */
+ for (i=1;i<=n;i++) {
fprintf(ficrespow," %.12lf", p[i]);
}
+ fprintf(ficrespow,"\n");fflush(ficrespow);
+ printf("\n#model= 1 + age ");
+ fprintf(ficlog,"\n#model= 1 + age ");
+ if(nagesqr==1){
+ printf(" + age*age ");
+ fprintf(ficlog," + age*age ");
+ }
+ for(j=1;j <=ncovmodel-2;j++){
+ if(Typevar[j]==0) {
+ printf(" + V%d ",Tvar[j]);
+ fprintf(ficlog," + V%d ",Tvar[j]);
+ }else if(Typevar[j]==1) {
+ printf(" + V%d*age ",Tvar[j]);
+ fprintf(ficlog," + V%d*age ",Tvar[j]);
+ }else if(Typevar[j]==2) {
+ printf(" + V%d*V%d ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
+ fprintf(ficlog," + V%d*V%d ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
+ }
+ }
printf("\n");
+/* printf("12 47.0114589 0.0154322 33.2424412 0.3279905 2.3731903 */
+/* 13 -21.5392400 0.1118147 1.2680506 1.2973408 -1.0663662 */
fprintf(ficlog,"\n");
- fprintf(ficrespow,"\n");fflush(ficrespow);
- if(*iter <=3){
- tm = *localtime(&curr_time.tv_sec);
- strcpy(strcurr,asctime(&tm));
-/* asctime_r(&tm,strcurr); */
- forecast_time=curr_time;
+ for(i=1,jk=1; i <=nlstate; i++){
+ for(k=1; k <=(nlstate+ndeath); k++){
+ if (k != i) {
+ printf("%d%d ",i,k);
+ fprintf(ficlog,"%d%d ",i,k);
+ for(j=1; j <=ncovmodel; j++){
+ printf("%12.7f ",p[jk]);
+ fprintf(ficlog,"%12.7f ",p[jk]);
+ jk++;
+ }
+ printf("\n");
+ fprintf(ficlog,"\n");
+ }
+ }
+ }
+ if(*iter <=3 && *iter >1){
+ tml = *localtime(&rcurr_time);
+ strcpy(strcurr,asctime(&tml));
+ rforecast_time=rcurr_time;
itmp = strlen(strcurr);
if(strcurr[itmp-1]=='\n') /* Windows outputs with a new line */
strcurr[itmp-1]='\0';
- printf("\nConsidering the time needed for this last iteration #%d: %ld seconds,\n",*iter,curr_time.tv_sec-last_time.tv_sec);
- fprintf(ficlog,"\nConsidering the time needed for this last iteration #%d: %ld seconds,\n",*iter,curr_time.tv_sec-last_time.tv_sec);
+ printf("\nConsidering the time needed for the last iteration #%d: %ld seconds,\n",*iter,rcurr_time-rlast_time);
+ fprintf(ficlog,"\nConsidering the time needed for this last iteration #%d: %ld seconds,\n",*iter,rcurr_time-rlast_time);
for(niterf=10;niterf<=30;niterf+=10){
- forecast_time.tv_sec=curr_time.tv_sec+(niterf-*iter)*(curr_time.tv_sec-last_time.tv_sec);
- tmf = *localtime(&forecast_time.tv_sec);
-/* asctime_r(&tmf,strfor); */
- strcpy(strfor,asctime(&tmf));
+ rforecast_time=rcurr_time+(niterf-*iter)*(rcurr_time-rlast_time);
+ forecast_time = *localtime(&rforecast_time);
+ strcpy(strfor,asctime(&forecast_time));
itmp = strlen(strfor);
if(strfor[itmp-1]=='\n')
- strfor[itmp-1]='\0';
- printf(" - if your program needs %d iterations to converge, convergence will be \n reached in %s i.e.\n on %s (current time is %s);\n",niterf, asc_diff_time(forecast_time.tv_sec-curr_time.tv_sec,tmpout),strfor,strcurr);
- fprintf(ficlog," - if your program needs %d iterations to converge, convergence will be \n reached in %s i.e.\n on %s (current time is %s);\n",niterf, asc_diff_time(forecast_time.tv_sec-curr_time.tv_sec,tmpout),strfor,strcurr);
+ strfor[itmp-1]='\0';
+ printf(" - if your program needs %d iterations to converge, convergence will be \n reached in %s i.e.\n on %s (current time is %s);\n",niterf, asc_diff_time(rforecast_time-rcurr_time,tmpout),strfor,strcurr);
+ fprintf(ficlog," - if your program needs %d iterations to converge, convergence will be \n reached in %s i.e.\n on %s (current time is %s);\n",niterf, asc_diff_time(rforecast_time-rcurr_time,tmpout),strfor,strcurr);
}
}
- for (i=1;i<=n;i++) {
- for (j=1;j<=n;j++) xit[j]=xi[j][i];
+ for (i=1;i<=n;i++) { /* For each direction i */
+ for (j=1;j<=n;j++) xit[j]=xi[j][i]; /* Directions stored from previous iteration with previous scales */
fptt=(*fret);
#ifdef DEBUG
- printf("fret=%lf \n",*fret);
- fprintf(ficlog,"fret=%lf \n",*fret);
+ printf("fret=%lf, %lf, %lf \n", *fret, *fret, *fret);
+ fprintf(ficlog, "fret=%lf, %lf, %lf \n", *fret, *fret, *fret);
#endif
- printf("%d",i);fflush(stdout);
+ printf("%d",i);fflush(stdout); /* print direction (parameter) i */
fprintf(ficlog,"%d",i);fflush(ficlog);
- linmin(p,xit,n,fret,func);
- if (fabs(fptt-(*fret)) > del) {
- del=fabs(fptt-(*fret));
- ibig=i;
+#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]);
+ 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=%.12e",p[j]);
- fprintf(ficlog," p=%.12e",p[j]);
+ printf(" p(%d)=%.12e",j,p[j]);
+ fprintf(ficlog," p(%d)=%.12e",j,p[j]);
}
printf("\n");
fprintf(ficlog,"\n");
#endif
- }
- if (2.0*fabs(fp-(*fret)) <= ftol*(fabs(fp)+fabs(*fret))) {
+ } /* end loop on each direction i */
+ /* Convergence test will use last linmin estimation (fret) and compare former iteration (fp) */
+ /* But p and xit have been updated at the end of linmin, *fret corresponds to new p, xit */
+ /* New value of last point Pn is not computed, P(n-1) */
+ for(j=1;j<=n;j++) {
+ if(flatdir[j] >0){
+ printf(" p(%d)=%lf flat=%d ",j,p[j],flatdir[j]);
+ fprintf(ficlog," p(%d)=%lf flat=%d ",j,p[j],flatdir[j]);
+ }
+ /* printf("\n"); */
+ /* fprintf(ficlog,"\n"); */
+ }
+ /* if (2.0*fabs(fp-(*fret)) <= ftol*(fabs(fp)+fabs(*fret))) { /\* Did we reach enough precision? *\/ */
+ if (2.0*fabs(fp-(*fret)) <= ftol) { /* Did we reach enough precision? */
+ /* We could compare with a chi^2. chisquare(0.95,ddl=1)=3.84 */
+ /* By adding age*age in a model, the new -2LL should be lower and the difference follows a */
+ /* a chisquare statistics with 1 degree. To be significant at the 95% level, it should have */
+ /* decreased of more than 3.84 */
+ /* By adding age*age and V1*age the gain (-2LL) should be more than 5.99 (ddl=2) */
+ /* By using V1+V2+V3, the gain should be 7.82, compared with basic 1+age. */
+ /* By adding 10 parameters more the gain should be 18.31 */
+
+ /* Starting the program with initial values given by a former maximization will simply change */
+ /* the scales of the directions and the directions, because the are reset to canonical directions */
+ /* Thus the first calls to linmin will give new points and better maximizations until fp-(*fret) is */
+ /* under the tolerance value. If the tolerance is very small 1.e-9, it could last long. */
#ifdef DEBUG
int k[2],l;
k[0]=1;
@@ -975,192 +2584,805 @@ void powell(double p[], double **xi, int
}
#endif
-
free_vector(xit,1,n);
free_vector(xits,1,n);
free_vector(ptt,1,n);
free_vector(pt,1,n);
return;
- }
- if (*iter == ITMAX) nrerror("powell exceeding maximum iterations.");
- for (j=1;j<=n;j++) {
+ } /* enough precision */
+ if (*iter == ITMAX*n) nrerror("powell exceeding maximum iterations.");
+ for (j=1;j<=n;j++) { /* Computes the extrapolated point P_0 + 2 (P_n-P_0) */
ptt[j]=2.0*p[j]-pt[j];
xit[j]=p[j]-pt[j];
pt[j]=p[j];
}
- fptt=(*func)(ptt);
- if (fptt < fp) {
- t=2.0*(fp-2.0*(*fret)+fptt)*SQR(fp-(*fret)-del)-del*SQR(fp-fptt);
- if (t < 0.0) {
- linmin(p,xit,n,fret,func);
+ fptt=(*func)(ptt); /* f_3 */
+#ifdef NODIRECTIONCHANGEDUNTILNITER /* No change in drections until some iterations are done */
+ if (*iter <=4) {
+#else
+#endif
+#ifdef POWELLNOF3INFF1TEST /* skips test F3 0 */
+ /* mu² and del² are equal when f3=f1 */
+ /* f3 < f1 : mu² < del <= lambda^2 both test are equivalent */
+ /* f3 < f1 : mu² < lambda^2 < del then directtest is negative and powell t is positive */
+ /* f3 > f1 : lambda² < mu^2 < del then t is negative and directest >0 */
+ /* f3 > f1 : lambda² < del < mu^2 then t is positive and directest >0 */
+#ifdef NRCORIGINAL
+ t=2.0*(fp-2.0*(*fret)+fptt)*SQR(fp-(*fret)-del)- del*SQR(fp-fptt); /* Original Numerical Recipes in C*/
+#else
+ t=2.0*(fp-2.0*(*fret)+fptt)*SQR(fp-(*fret)-del); /* Intel compiler doesn't work on one line; bug reported */
+ t= t- del*SQR(fp-fptt);
+#endif
+ directest = fp-2.0*(*fret)+fptt - 2.0 * del; /* If delta was big enough we change it for a new direction */
+#ifdef DEBUG
+ printf("t1= %.12lf, t2= %.12lf, t=%.12lf directest=%.12lf\n", 2.0*(fp-2.0*(*fret)+fptt)*SQR(fp-(*fret)-del),del*SQR(fp-fptt),t,directest);
+ fprintf(ficlog,"t1= %.12lf, t2= %.12lf, t=%.12lf directest=%.12lf\n", 2.0*(fp-2.0*(*fret)+fptt)*SQR(fp-(*fret)-del),del*SQR(fp-fptt),t,directest);
+ printf("t3= %.12lf, t4= %.12lf, t3*= %.12lf, t4*= %.12lf\n",SQR(fp-(*fret)-del),SQR(fp-fptt),
+ (fp-(*fret)-del)*(fp-(*fret)-del),(fp-fptt)*(fp-fptt));
+ fprintf(ficlog,"t3= %.12lf, t4= %.12lf, t3*= %.12lf, t4*= %.12lf\n",SQR(fp-(*fret)-del),SQR(fp-fptt),
+ (fp-(*fret)-del)*(fp-(*fret)-del),(fp-fptt)*(fp-fptt));
+ printf("tt= %.12lf, t=%.12lf\n",2.0*(fp-2.0*(*fret)+fptt)*(fp-(*fret)-del)*(fp-(*fret)-del)-del*(fp-fptt)*(fp-fptt),t);
+ fprintf(ficlog, "tt= %.12lf, t=%.12lf\n",2.0*(fp-2.0*(*fret)+fptt)*(fp-(*fret)-del)*(fp-(*fret)-del)-del*(fp-fptt)*(fp-fptt),t);
+#endif
+#ifdef POWELLORIGINAL
+ if (t < 0.0) { /* Then we use it for new direction */
+#else
+ if (directest*t < 0.0) { /* Contradiction between both tests */
+ printf("directest= %.12lf (if <0 we include P0 Pn as new direction), t= %.12lf, f1= %.12lf,f2= %.12lf,f3= %.12lf, del= %.12lf\n",directest, t, fp,(*fret),fptt,del);
+ printf("f1-2f2+f3= %.12lf, f1-f2-del= %.12lf, f1-f3= %.12lf\n",fp-2.0*(*fret)+fptt, fp -(*fret) -del, fp-fptt);
+ fprintf(ficlog,"directest= %.12lf (if directest<0 or t<0 we include P0 Pn as new direction), t= %.12lf, f1= %.12lf,f2= %.12lf,f3= %.12lf, del= %.12lf\n",directest, t, fp,(*fret),fptt, del);
+ fprintf(ficlog,"f1-2f2+f3= %.12lf, f1-f2-del= %.12lf, f1-f3= %.12lf\n",fp-2.0*(*fret)+fptt, fp -(*fret) -del, fp-fptt);
+ }
+ if (directest < 0.0) { /* Then we use it for new direction */
+#endif
+#ifdef DEBUGLINMIN
+ printf("Before linmin in direction P%d-P0\n",n);
+ for (j=1;j<=n;j++) {
+ printf(" Before xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
+ fprintf(ficlog," Before xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
+ if(j % ncovmodel == 0){
+ printf("\n");
+ fprintf(ficlog,"\n");
+ }
+ }
+#endif
+#ifdef LINMINORIGINAL
+ linmin(p,xit,n,fret,func); /* computes minimum on the extrapolated direction: changes p and rescales xit.*/
+#else
+ linmin(p,xit,n,fret,func,&flat); /* computes minimum on the extrapolated direction: changes p and rescales xit.*/
+ flatdir[i]=flat; /* Function is vanishing in that direction i */
+#endif
+
+#ifdef DEBUGLINMIN
+ for (j=1;j<=n;j++) {
+ printf("After xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
+ fprintf(ficlog,"After xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
+ if(j % ncovmodel == 0){
+ printf("\n");
+ fprintf(ficlog,"\n");
+ }
+ }
+#endif
for (j=1;j<=n;j++) {
- xi[j][ibig]=xi[j][n];
- xi[j][n]=xit[j];
+ xi[j][ibig]=xi[j][n]; /* Replace direction with biggest decrease by last direction n */
+ xi[j][n]=xit[j]; /* and this nth direction by the by the average p_0 p_n */
+ }
+#ifdef LINMINORIGINAL
+#else
+ for (j=1, flatd=0;j<=n;j++) {
+ if(flatdir[j]>0)
+ flatd++;
+ }
+ if(flatd >0){
+ printf("%d flat directions: ",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(" %.12e",xit[j]);
- fprintf(ficlog," %.12e",xit[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
+ * (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;
+ 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;
+ }
+ for (k=1; k<=nsd;k++) { /* For single dummy covariates only */
+ /* Here comes the value of the covariate 'ij' after renumbering k with single dummy covariates */
+ cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,k)];
+ /* 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 varying covariates only */
+ /* Here comes the value of quantitative after renumbering k with single quantitative covariates */
+ cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k];
+ /* 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,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,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)];
+ /* 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,k)] * 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,k)] * 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]]; */
}
- printf("\n");
- fprintf(ficlog,"\n");
-#endif
}
- }
- }
-}
+ }
+ /*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 */
+}
-/**** Prevalence limit (stable prevalence) ****************/
-double **prevalim(double **prlim, int nlstate, double x[], double age, double **oldm, double **savm, double ftolpl, int ij)
+ /**** 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 by left multiplying the unit
- matrix by transitions matrix until convergence is reached */
+ /* 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;
- double min, max, maxmin, maxmax,sumnew=0.;
- double **matprod2();
- double **out, cov[NCOVMAX], **pmij();
+ int first=0;
+ double *min, *max, *meandiff, maxmax,sumnew=0.;
+ /* double **matprod2(); */ /* test */
+ double **out, cov[NCOVMAX+1], **bmij();
double **newm;
- double agefin, delaymax=50 ; /* Max number of years to converge */
+ 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 */
- for(agefin=age-stepm/YEARM; agefin>=age-delaymax; agefin=agefin-stepm/YEARM){
- newm=savm;
- /* Covariates have to be included here again */
- cov[2]=agefin;
- for (k=1; k<=cptcovn;k++) {
- cov[2+k]=nbcode[Tvar[k]][codtab[ij][Tvar[k]]];
- /* printf("ij=%d k=%d Tvar[k]=%d nbcode=%d cov=%lf codtab[ij][Tvar[k]]=%d \n",ij,k, Tvar[k],nbcode[Tvar[k]][codtab[ij][Tvar[k]]],cov[2+k], codtab[ij][Tvar[k]]);*/
- }
- for (k=1; k<=cptcovage;k++) cov[2+Tage[k]]=cov[2+Tage[k]]*cov[2];
- for (k=1; k<=cptcovprod;k++)
- cov[2+Tprod[k]]=nbcode[Tvard[k][1]][codtab[ij][Tvard[k][1]]]*nbcode[Tvard[k][2]][codtab[ij][Tvard[k][2]]];
-
- /*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]);*/
- out=matprod2(newm, pmij(pmmij,cov,ncovmodel,x,nlstate),1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm);
-
+ 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 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 )
{
- double s1, s2;
+ /* According to parameters values stored in x and the covariate's values stored in cov,
+ computes the probability to be observed in state j (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-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,j1, nc, ii, jj;
+ int i,j, nc, ii, jj;
- for(i=1; i<= nlstate; i++){
- for(j=1; ji s1=%.17e, s2=%.17e %lx %lx\n",s1,s2,s1,s2); */
- }
- ps[i][j]=s2;
- }
- }
- /*ps[3][2]=1;*/
-
- for(i=1; i<= nlstate; i++){
- s1=0;
- for(j=1; ji 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; ji} pij/pii=(1-pii)/pii and thus pii is known from s1 */
+ ps[i][i]=1./(s1+1.);
+ /* Computing other pijs */
+ for(j=1; j0.01){ /* 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-2))*ncovmodel
+ Computes ln(pij/pii) (lnpijopii), deduces pij/pii by exponentiation,
+ sums on j different of i to get 1-pii/pii, deduces pii, and then all pij.
+ Outputs ps[i][j] the probability to be observed in j being in j according to
+ the values of the covariates cov[nc] and corresponding parameter values x[nc+shiftij]
+ */
+ double s1, lnpijopii;
+ /*double t34;*/
+ int i,j, nc, ii, jj;
-/* for(ii=1; ii<= nlstate+ndeath; ii++){ */
-/* for(jj=1; jj<= nlstate+ndeath; jj++){ */
-/* printf("ddd %lf ",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;
+ for(i=1; i<= nlstate; i++){
+ for(j=1; ji 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; ji} 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> (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)];
+ /* printf("hpxij Dummy combi=%d k=%d TvarsD[%d]=V%d TvarsDind[%d]=%d nbcode=%d cov=%lf codtabm(%d,Tvar[%d])=%d \n",ij,k, k, TvarsD[k],k,TvarsDind[k],nbcode[TvarsD[k]][codtabm(ij,k)],cov[2+nagesqr+TvarsDind[k]], ij, k, codtabm(ij,k)); */
+ }
+ for (k=1; k<=nsq;k++) { /* For single varying covariates only */
+ /* Here comes the value of quantitative after renumbering k with single quantitative covariates */
+ cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k];
+ /* printf("hPxij Quantitative k=%d TvarsQind[%d]=%d, TvarsQ[%d]=V%d,Tqresult[%d][%d]=%f\n",k,k,TvarsQind[k],k,TvarsQ[k],nres,k,Tqresult[nres][k]); */
+ }
+ for (k=1; k<=cptcovage;k++){ /* 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*/
+ /* */
+ 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];
+ } 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]); */
+ }
+ for (k=1; k<=cptcovprod;k++){ /* For product without age */
+ /* printf("hPxij Prod ij=%d k=%d Tprod[%d]=%d Tvard[%d][1]=V%d, Tvard[%d][2]=V%d\n",ij,k,k,Tprod[k], k,Tvard[k][1], k,Tvard[k][2]); */
+ /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)]; */
+ if(Dummy[Tvard[k][1]==0]){
+ if(Dummy[Tvard[k][2]==0]){
+ cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)];
+ }else{
+ cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * Tqresult[nres][k];
+ }
+ }else{
+ if(Dummy[Tvard[k][2]==0]){
+ cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][2]][codtabm(ij,k)] * Tqinvresult[nres][Tvard[k][1]];
+ }else{
+ cov[2+nagesqr+Tprod[k]]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]];
+ }
+ }
+ }
+ /* 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];
- /*printf("i=%d j=%d h=%d po[i][j][h]=%f ",i,j,h,po[i][j][h]);
- */
+ /*if(h==nhstepm) printf("po[%d][%d][%d]=%f ",i,j,h,po[i][j][h]);*/
+ }
+ /*printf("h=%d ",h);*/
+ } /* end h */
+ /* printf("\n H=%d \n",h); */
+ return po;
+}
+
+/************* 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 a combination of dummy covariate 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;
+ 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;
+ 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,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,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,k)]*nbcode[Tvard[k][2]][codtabm(ij,k)];
+ if(Dummy[Tvard[k][1]==0]){
+ if(Dummy[Tvard[k][2]==0]){
+ cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)];
+ }else{
+ cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * Tqresult[nres][k];
+ }
+ }else{
+ if(Dummy[Tvard[k][2]==0]){
+ cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][2]][codtabm(ij,k)] * Tqinvresult[nres][Tvard[k][1]];
+ }else{
+ cov[2+nagesqr+Tprod[k]]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]];
+ }
+ }
+ }
+ /*printf("hxi cptcov=%d cptcode=%d\n",cptcov,cptcode);*/
+ /*printf("h=%d d=%d age=%f cov=%f\n",h,d,age,cov[2]);*/
+
+ /* Careful transposed matrix */
+ /* age is in cov[2], 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;
- double l, ll[NLSTATEMAX], cov[NCOVMAX];
+ int ioffset=0;
+ double l, ll[NLSTATEMAX+1], cov[NCOVMAX+1];
double **out;
- double sw; /* Sum of weights */
double lli; /* Individual log likelihood */
int s1, s2;
+ int iv=0, iqv=0, itv=0, iqtv=0 ; /* Index of varying covariate, fixed quantitative cov, time varying covariate, quantitative time varying covariate */
double bbh, survp;
long ipmx;
+ double agexact;
/*extern weight */
/* We are differentiating ll according to initial status */
/* for (i=1;i<=npar;i++) printf("%f ", x[i]);*/
/*for(i=1;i 1 the results are less biased than in previous versions.
- */
+ * 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;
@@ -1283,45 +3752,61 @@ double func( double *x)
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.
+ 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==-2) {
+
+ } else if ( s2==-1 ) { /* alive */
for (j=1,survp=0. ; j<=nlstate; j++)
- survp += out[s1][j];
- lli= survp;
- }
-
- else if (s2==-4) {
- for (j=3,survp=0. ; j<=nlstate; j++)
- survp += out[s1][j];
- lli= survp;
- }
-
- else if (s2==-5) {
- for (j=1,survp=0. ; j<=2; j++)
- survp += out[s1][j];
- lli= survp;
- }
-
-
+ 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 */
@@ -1329,15 +3814,24 @@ double func( double *x)
/*lli=(1.+bbh)*log(out[s1][s2])- bbh*log(savm[s1][s2]);*/
/*if(lli ==000.0)*/
/*printf("bbh= %f lli=%f savm=%f out=%f %d\n",bbh,lli,savm[s1][s2], out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]],i); */
- ipmx +=1;
+ ipmx +=1;
sw += weight[i];
ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
+ /* if (lli < log(mytinydouble)){ */
+ /* printf("Close to inf lli = %.10lf < %.10lf i= %d mi= %d, s[%d][i]=%d s1=%d s2=%d\n", lli,log(mytinydouble), i, mi,mw[mi][i], s[mw[mi][i]][i], s1,s2); */
+ /* fprintf(ficlog,"Close to inf lli = %.10lf i= %d mi= %d, s[mw[mi][i]][i]=%d\n", lli, i, mi,s[mw[mi][i]][i]); */
+ /* } */
} /* end of wave */
} /* end of individual */
} else if(mle==2){
for (i=1,ipmx=0, sw=0.; i<=imx; i++){
- for (k=1; k<=cptcovn;k++) cov[2+k]=covar[Tvar[k]][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];
+ }
for (ii=1;ii<=nlstate+ndeath;ii++)
for (j=1;j<=nlstate+ndeath;j++){
oldm[ii][j]=(ii==j ? 1.0 : 0.0);
@@ -1345,9 +3839,12 @@ double func( double *x)
}
for(d=0; d<=dh[mi][i]; d++){
newm=savm;
- cov[2]=agev[mw[mi][i]][i]+d*stepm/YEARM;
+ 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]=covar[Tvar[Tage[kk]]][i]*cov[2];
+ 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));
@@ -1366,7 +3863,7 @@ double func( double *x)
} /* 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+k]=covar[Tvar[k]][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++){
@@ -1375,9 +3872,12 @@ double func( double *x)
}
for(d=0; d 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 */
}
@@ -1431,7 +3938,7 @@ double func( double *x)
} /* 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+k]=covar[Tvar[k]][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++){
@@ -1440,9 +3947,12 @@ double func( double *x)
}
for(d=0; d nlstate && (mle <5) ){ /* Jackson */
lli=log(out[s1][s2] - savm[s1][s2]);
- } else if (mle==1){
+ } 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 */
@@ -1524,39 +4103,40 @@ double funcone( double *x)
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{ /* ml>=5 no inter-extrapolation no jackson =0.8a */
- lli=log(out[s1][s2]); /* Original formula */
+ } else{ /* mle=0 back to 1 */
+ lli= log((1.+bbh)*out[s1][s2]- bbh*savm[s1][s2]); /* linear interpolation */
+ /*lli=log(out[s1][s2]); */ /* Original formula */
} /* End of if */
ipmx +=1;
sw += weight[i];
ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
-/* printf("i=%6d s1=%1d s2=%1d mi=%1d mw=%1d dh=%3d prob=%10.6f w=%6.4f out=%10.6f sav=%10.6f\n",i,s1,s2,mi,mw[mi][i],dh[mi][i],exp(lli),weight[i],out[s1][s2],savm[s1][s2]); */
+ /*printf("i=%6d s1=%1d s2=%1d mi=%1d mw=%1d dh=%3d prob=%10.6f w=%6.4f out=%10.6f sav=%10.6f\n",i,s1,s2,mi,mw[mi][i],dh[mi][i],exp(lli),weight[i],out[s1][s2],savm[s1][s2]); */
if(globpr){
- fprintf(ficresilk,"%9d %6d %1d %1d %1d %1d %3d %10.6f %6.4f\
- %10.6f %10.6f %10.6f ", \
- num[i],i,s1,s2,mi,mw[mi][i],dh[mi][i],exp(lli),weight[i],
- 2*weight[i]*lli,out[s1][s2],savm[s1][s2]);
+ 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]));
for(k=1,llt=0.,l=0.; k<=nlstate; k++){
llt +=ll[k]*gipmx/gsw;
fprintf(ficresilk," %10.6f",-ll[k]*gipmx/gsw);
}
fprintf(ficresilk," %10.6f\n", -llt);
}
- } /* end of wave */
- } /* end of individual */
- for(k=1,l=0.; k<=nlstate; k++) l += ll[k];
- /* printf("l1=%f l2=%f ",ll[1],ll[2]); */
- l= l*ipmx/sw; /* To get the same order of magnitude as if weight=1 for every body */
- if(globpr==0){ /* First time we count the contributions and weights */
- gipmx=ipmx;
- gsw=sw;
- }
- return -l;
+ } /* end of wave */
+} /* end of individual */
+for(k=1,l=0.; k<=nlstate; k++) l += ll[k];
+/* printf("l1=%f l2=%f ",ll[1],ll[2]); */
+l= l*ipmx/sw; /* To get the same order of magnitude as if weight=1 for every body */
+if(globpr==0){ /* First time we count the contributions and weights */
+ gipmx=ipmx;
+ gsw=sw;
+}
+return -l;
}
/*************** function likelione ***********/
-void likelione(FILE *ficres,double p[], int npar, int nlstate, int *globpri, long *ipmx, double *sw, double *fretone, double (*funcone)(double []))
+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
@@ -1566,26 +4146,40 @@ void likelione(FILE *ficres,double p[],
int k;
if(*globpri !=0){ /* Just counts and sums, no printings */
- strcpy(fileresilk,"ilk");
- strcat(fileresilk,fileres);
+ 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) s1 s2 wave# effective_wave# number_of_matrices_product pij weight -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 i s1 s2 mi mw dh likeli weight 2wlli out sav ");
+ fprintf(ficresilk, "#individual(line's_record) count ageb ageend s1 s2 wave# effective_wave# number_of_matrices_product pij weight weight/gpw -2ln(pij)*weight 0pij_x 0pij_(x-stepm) cumulating_loglikeli_by_health_state(reweighted=-2ll*weightXnumber_of_contribs/sum_of_weights) and_total\n");
+ fprintf(ficresilk, "#num_i ageb agend i s1 s2 mi mw dh likeli weight %%weight 2wlli out sav ");
/* i,s1,s2,mi,mw[mi][i],dh[mi][i],exp(lli),weight[i],2*weight[i]*lli,out[s1][s2],savm[s1][s2]); */
for(k=1; k<=nlstate; k++)
fprintf(ficresilk," -2*gipw/gsw*weight*ll[%d]++",k);
fprintf(ficresilk," -2*gipw/gsw*weight*ll(total)\n");
}
- *fretone=(*funcone)(p);
+ *fretone=(*func)(p);
if(*globpri !=0){
fclose(ficresilk);
- fprintf(fichtm,"\n
File of contributions to the likelihood: %s
\n",subdirf(fileresilk),subdirf(fileresilk));
- fflush(fichtm);
- }
+ if (mle ==0)
+ fprintf(fichtm,"\n
File of contributions to the likelihood computed with initial parameters and mle = %d.",mle);
+ else if(mle >=1)
+ fprintf(fichtm,"\n
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: %s
\n",subdirf(fileresilk),subdirf(fileresilk));
+ fprintf(fichtm,"\n
Equation of the model: model=1+age+%s
\n",model);
+
+ for (k=1; k<= nlstate ; k++) {
+ fprintf(fichtm,"
- Probability p%dj by origin %d and destination j. Dot's sizes are related to corresponding weight: %s-p%dj.png
\
+",k,k,subdirf2(optionfilefiname,"ILK_"),k,subdirf2(optionfilefiname,"ILK_"),k,subdirf2(optionfilefiname,"ILK_"),k);
+ }
+ fprintf(fichtm,"
- The function drawn is -2Log(L) in Log scale: by state of origin %s-ori.png
\
+",subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"));
+ fprintf(fichtm,"
- and by state of destination %s-dest.png
\
+",subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"));
+ fflush(fichtm);
+ }
return;
}
@@ -1594,17 +4188,29 @@ void likelione(FILE *ficres,double p[],
void mlikeli(FILE *ficres,double p[], int npar, int ncovmodel, int nlstate, double ftol, double (*func)(double []))
{
- int i,j, iter;
+ 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");
+ strcpy(filerespow,"POW_");
strcat(filerespow,fileres);
if((ficrespow=fopen(filerespow,"w"))==NULL) {
printf("Problem with resultfile: %s\n", filerespow);
@@ -1615,36 +4221,129 @@ void mlikeli(FILE *ficres,double p[], in
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;ifunction = 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 = %d, -2 Log likelihood = %.12f\n",iter,func(p));
- fprintf(ficlog,"\n#Number of iterations = %d, -2 Log likelihood = %.12f \n",iter,func(p));
- fprintf(ficres,"#Number of iterations = %d, -2 Log likelihood = %.12f \n",iter,func(p));
+ printf("\n#Number of iterations & function calls = %d & %d, -2 Log likelihood = %.12f\n",iter, countcallfunc,func(p));
+ fprintf(ficlog,"\n#Number of iterations & function calls = %d & %d, -2 Log likelihood = %.12f\n",iter, countcallfunc,func(p));
+ fprintf(ficres,"#Number of iterations & function calls = %d & %d, -2 Log likelihood = %.12f\n",iter, countcallfunc,func(p));
}
/**** Computes Hessian and covariance matrix ***/
-void hesscov(double **matcov, double p[], int npar, double delti[], double ftolhess, double (*func)(double []))
+void hesscov(double **matcov, double **hess, double p[], int npar, double delti[], double ftolhess, double (*func)(double []))
{
double **a,**y,*x,pd;
- double **hess;
- int i, j,jk;
+ /* double **hess; */
+ int i, j;
int *indx;
double hessii(double p[], double delta, int theta, double delti[],double (*func)(double []),int npar);
- double hessij(double p[], double delti[], int i, int j,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);
+ /* 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);
+ printf("%d-",i);fflush(stdout);
+ fprintf(ficlog,"%d-",i);fflush(ficlog);
hess[i][i]=hessii(p,ftolhess,i,delti,func,npar);
@@ -1655,9 +4354,9 @@ void hesscov(double **matcov, double p[]
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,delti,i,j,func,npar);
+ 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]);*/
@@ -1691,71 +4390,96 @@ void hesscov(double **matcov, double p[]
fprintf(ficlog,"\n#Hessian matrix#\n");
for (i=1;i<=npar;i++) {
for (j=1;j<=npar;j++) {
- printf("%.3e ",hess[i][j]);
- fprintf(ficlog,"%.3e ",hess[i][j]);
+ printf("%.6e ",hess[i][j]);
+ fprintf(ficlog,"%.6e ",hess[i][j]);
}
printf("\n");
fprintf(ficlog,"\n");
}
+ /* printf("\n#Covariance matrix#\n"); */
+ /* fprintf(ficlog,"\n#Covariance matrix#\n"); */
+ /* for (i=1;i<=npar;i++) { */
+ /* for (j=1;j<=npar;j++) { */
+ /* printf("%.6e ",matcov[i][j]); */
+ /* fprintf(ficlog,"%.6e ",matcov[i][j]); */
+ /* } */
+ /* printf("\n"); */
+ /* fprintf(ficlog,"\n"); */
+ /* } */
+
/* Recompute Inverse */
- for (i=1;i<=npar;i++)
- for (j=1;j<=npar;j++) a[i][j]=matcov[i][j];
- ludcmp(a,npar,indx,&pd);
+ /* for (i=1;i<=npar;i++) */
+ /* for (j=1;j<=npar;j++) a[i][j]=matcov[i][j]; */
+ /* ludcmp(a,npar,indx,&pd); */
+
+ /* printf("\n#Hessian matrix recomputed#\n"); */
+
+ /* for (j=1;j<=npar;j++) { */
+ /* for (i=1;i<=npar;i++) x[i]=0; */
+ /* x[j]=1; */
+ /* lubksb(a,npar,indx,x); */
+ /* for (i=1;i<=npar;i++){ */
+ /* y[i][j]=x[i]; */
+ /* printf("%.3e ",y[i][j]); */
+ /* fprintf(ficlog,"%.3e ",y[i][j]); */
+ /* } */
+ /* printf("\n"); */
+ /* fprintf(ficlog,"\n"); */
+ /* } */
+
+ /* Verifying the inverse matrix */
+#ifdef DEBUGHESS
+ y=matprod2(y,hess,1,npar,1,npar,1,npar,matcov);
- /* printf("\n#Hessian matrix recomputed#\n");
+ printf("\n#Verification: multiplying the matrix of covariance by the Hessian matrix, should be unity:#\n");
+ fprintf(ficlog,"\n#Verification: multiplying the matrix of covariance by the Hessian matrix. Should be unity:#\n");
for (j=1;j<=npar;j++) {
- for (i=1;i<=npar;i++) x[i]=0;
- x[j]=1;
- lubksb(a,npar,indx,x);
for (i=1;i<=npar;i++){
- y[i][j]=x[i];
- printf("%.3e ",y[i][j]);
- fprintf(ficlog,"%.3e ",y[i][j]);
+ printf("%.2f ",y[i][j]);
+ fprintf(ficlog,"%.2f ",y[i][j]);
}
printf("\n");
fprintf(ficlog,"\n");
}
- */
+#endif
free_matrix(a,1,npar,1,npar);
free_matrix(y,1,npar,1,npar);
free_vector(x,1,npar);
free_ivector(indx,1,npar);
- free_matrix(hess,1,npar,1,npar);
+ /* free_matrix(hess,1,npar,1,npar); */
}
/*************** hessian matrix ****************/
double hessii(double x[], double delta, int theta, double delti[], double (*func)(double []), int npar)
-{
+{ /* Around values of x, computes the function func and returns the scales delti and hessian */
int i;
int l=1, lmax=20;
- double k1,k2;
- double p2[NPARMAX+1];
- double res;
+ double k1,k2, res, fx;
+ double p2[MAXPARM+1]; /* identical to x */
double delt=0.0001, delts, nkhi=10.,nkhif=1., khi=1.e-4;
- double fx;
int k=0,kmax=10;
double l1;
fx=func(x);
for (i=1;i<=npar;i++) p2[i]=x[i];
- for(l=0 ; l <=lmax; l++){
+ for(l=0 ; l <=lmax; l++){ /* Enlarging the zone around the Maximum */
l1=pow(10,l);
delts=delt;
for(k=1 ; k khi/nkhif) || (k2 >khi/nkhif)){ /* Keeps lastvalue before 3.84/2 KHI2 5% 1d.f. */
- k=kmax; l=lmax*10.;
+ k=kmax; l=lmax*10;
}
else if((k1 >khi/nkhi) || (k2 >khi/nkhi)){
delts=delt;
}
- }
+ } /* End loop k */
}
delti[theta]=delts;
return res;
}
-double hessij( double x[], double delti[], int thetai,int thetaj,double (*func)(double []),int npar)
+double hessij( double x[], double **hess, double delti[], int thetai,int thetaj,double (*func)(double []),int npar)
{
int i;
- int l=1, l1, lmax=20;
+ int l=1, lmax=20;
double k1,k2,k3,k4,res,fx;
- double p2[NPARMAX+1];
- int k;
+ double p2[MAXPARM+1];
+ int k, kmax=1;
+ double v1, v2, cv12, lc1, lc2;
+ int firstime=0;
+
fx=func(x);
- for (k=1; k<=2; k++) {
+ for (k=1; k<=kmax; k=k+10) {
for (i=1;i<=npar;i++) p2[i]=x[i];
- p2[thetai]=x[thetai]+delti[thetai]/k;
- p2[thetaj]=x[thetaj]+delti[thetaj]/k;
+ p2[thetai]=x[thetai]+delti[thetai]*k;
+ p2[thetaj]=x[thetaj]+delti[thetaj]*k;
k1=func(p2)-fx;
- p2[thetai]=x[thetai]+delti[thetai]/k;
- p2[thetaj]=x[thetaj]-delti[thetaj]/k;
+ p2[thetai]=x[thetai]+delti[thetai]*k;
+ p2[thetaj]=x[thetaj]-delti[thetaj]*k;
k2=func(p2)-fx;
- p2[thetai]=x[thetai]-delti[thetai]/k;
- p2[thetaj]=x[thetaj]+delti[thetaj]/k;
+ p2[thetai]=x[thetai]-delti[thetai]*k;
+ p2[thetaj]=x[thetaj]+delti[thetaj]*k;
k3=func(p2)-fx;
- p2[thetai]=x[thetai]-delti[thetai]/k;
- p2[thetaj]=x[thetaj]-delti[thetaj]/k;
+ p2[thetai]=x[thetai]-delti[thetai]*k;
+ p2[thetaj]=x[thetaj]-delti[thetaj]*k;
k4=func(p2)-fx;
- res=(k1-k2-k3+k4)/4.0/delti[thetai]*k/delti[thetaj]*k/2.; /* Because of L not 2*L */
-#ifdef DEBUG
- printf("%d %d k=%d, k1=%.12e k2=%.12e k3=%.12e k4=%.12e delti/k=%.12e deltj/k=%.12e, xi-de/k=%.12e xj-de/k=%.12e res=%.12e k1234=%.12e,k1-2=%.12e,k3-4=%.12e\n",thetai,thetaj,k,k1,k2,k3,k4,delti[thetai]/k,delti[thetaj]/k,x[thetai]-delti[thetai]/k,x[thetaj]-delti[thetaj]/k, res,k1-k2-k3+k4,k1-k2,k3-k4);
- 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);
+ 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 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)
{
@@ -1824,7 +4625,16 @@ void ludcmp(double **a, int n, int *indx
big=0.0;
for (j=1;j<=n;j++)
if ((temp=fabs(a[i][j])) > big) big=temp;
- if (big == 0.0) nrerror("Singular matrix in routine ludcmp");
+ 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++) {
@@ -1885,170 +4695,688 @@ void lubksb(double **a, int n, int *indx
}
}
-/************ Frequencies ********************/
-void freqsummary(char fileres[], int iagemin, int iagemax, int **s, double **agev, int nlstate, int imx, int *Tvaraff, int **nbcode, int *ncodemax,double **mint,double **anint, char strstart[])
-{ /* Some frequencies */
+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.;
- int i, m, jk, k1,i1, j1, bool, z1,z2,j;
+ 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 */
+
+ 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 *pp, **prop;
- double pos,posprop, k2, dateintsum=0,k2cpt=0;
- FILE *ficresp;
- char fileresp[FILENAMELENGTH];
-
+ 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,iagemax+3);
- strcpy(fileresp,"p");
- strcat(fileresp,fileres);
+ prop=matrix(1,nlstate,iagemin-AGEMARGE,iagemax+4+AGEMARGE);
+ posprop=vector(1,nlstate); /* Counting the number of transition starting from a live state per age */
+ pospropt=vector(1,nlstate); /* Counting the number of transition starting from a live state */
+ /* prop=matrix(1,nlstate,iagemin,iagemax+3); */
+ meanq=vector(1,nqfveff); /* Number of Quantitative Fixed Variables Effective */
+ 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);
}
- freq= ma3x(-5,nlstate+ndeath,-5,nlstate+ndeath,iagemin,iagemax+3);
+
+ 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,"\nIMaCh PHTM_ %s\n %s
%s \
+
\n \
+Title=%s
Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s
\n",\
+ fileresphtm,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model);
+ }
+ fprintf(ficresphtm,"Current page is file %s
\n\nFrequencies (weight=%d) and prevalence by age at begin of transition and dummy covariate value at beginning of transition
\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,"\nIMaCh PHTM_Frequency table %s\n %s
%s \
+,
\n \
+Title=%s
Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s
\n",\
+ fileresphtmfr,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model);
+ }
+ fprintf(ficresphtmfr,"Current page is file %s
\n\n(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)
Unknown status is -1
\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=cptcoveff;
+ /* j=ncoveff; /\* Only fixed dummy covariates *\/ */
+ j=cptcoveff; /* Only dummy covariates of the model */
if (cptcovn<1) {j=1;ncodemax[1]=1;}
+
+
+ /* Detects if a combination j1 is empty: for a multinomial variable like 3 education levels:
+ reference=low_education V1=0,V2=0
+ med_educ V1=1 V2=0,
+ high_educ V1=0 V2=1
+ Then V1=1 and V2=1 is a noisy combination that we want to exclude for the list 2**cptcoveff
+ */
+ dateintsum=0;
+ k2cpt=0;
- first=1;
-
- for(k1=1; k1<=j;k1++){
- for(i1=1; i1<=ncodemax[k1];i1++){
- j1++;
+ 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 */
+ }
+ first=1;
+ for (j1 = 1; j1 <= (int) pow(2,j); j1++){ /* Loop on all covariates combination of the model, excluding quantitatives, V4=0, V3=0 for example, fixed or varying covariates */
+ posproptt=0.;
/*printf("cptcoveff=%d Tvaraff=%d", cptcoveff,Tvaraff[1]);
scanf("%d", i);*/
for (i=-5; i<=nlstate+ndeath; i++)
- for (jk=-5; jk<=nlstate+ndeath; jk++)
+ for (s2=-5; s2<=nlstate+ndeath; s2++)
for(m=iagemin; m <= iagemax+3; m++)
- freq[i][jk][m]=0;
-
- for (i=1; i<=nlstate; i++)
- for(m=iagemin; m <= iagemax+3; m++)
- prop[i][m]=0;
+ freq[i][s2][m]=0;
- dateintsum=0;
- k2cpt=0;
- for (i=1; i<=imx; i++) {
+ 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 (cptcovn>0) {
- for (z1=1; z1<=cptcoveff; z1++)
- if (covar[Tvaraff[z1]][i]!= nbcode[Tvaraff[z1]][codtab[j1][z1]])
- bool=0;
- }
- if (bool==1){
- for(m=firstpass; m<=lastpass; m++){
- k2=anint[m][i]+(mint[m][i]/12.);
- /*if ((k2>=dateprev1) && (k2<=dateprev2)) {*/
- if(agev[m][i]==0) agev[m][i]=iagemax+1;
- if(agev[m][i]==1) agev[m][i]=iagemax+2;
- if (s[m][i]>0 && s[m][i]<=nlstate) prop[s[m][i]][(int)agev[m][i]] += weight[i];
- if (m1) && (agev[m][i]< (iagemax+3))) {
- dateintsum=dateintsum+k2;
+ 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 */
+ if (covar[Tvaraff[z1]][iind]!= nbcode[Tvaraff[z1]][codtabm(j1,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 */
+ } /* cptcovn > 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=firstpass && m <=lastpass){
+ k2=anint[m][iind]+(mint[m][iind]/12.);
+ /*if ((k2>=dateprev1) && (k2<=dateprev2)) {*/
+ if(agev[m][iind]==0) agev[m][iind]=iagemax+1; /* All ages equal to 0 are in iagemax+1 */
+ if(agev[m][iind]==1) agev[m][iind]=iagemax+2; /* All ages equal to 1 are in iagemax+2 */
+ if (s[m][iind]>0 && s[m][iind]<=nlstate) /* If status at wave m is known and a live state */
+ prop[s[m][iind]][(int)agev[m][iind]] += weight[iind]; /* At age of beginning of transition, where status is known */
+ if (m1) && (agev[m][iind]< (iagemax+3)) && (anint[m][iind]!=9999) && (mint[m][iind]!=99) && (j==0)) {
+ dateintsum=dateintsum+k2; /* on all covariates ?*/
k2cpt++;
+ /* printf("iind=%ld dateintmean = %lf dateintsum=%lf k2cpt=%lf k2=%lf\n",iind, dateintsum/k2cpt, dateintsum,k2cpt, k2); */
}
- /*}*/
- }
- }
- }
-
+ }else{
+ bool=1;
+ }/* end bool 2 */
+ } /* end m */
+ /* 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);*/
-fprintf(ficresp, "#Local time at start: %s", strstart);
- if (cptcovn>0) {
+ 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 ");
- for (z1=1; z1<=cptcoveff; z1++) fprintf(ficresp, "V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtab[j1][z1]]);
+ fprintf(ficresphtm, "\n
********** Variable ");
+ fprintf(ficresphtmfr, "\n
********** Variable ");
+ fprintf(ficlog, "\n#********** Variable ");
+ for (z1=1; z1<=cptcoveff; z1++){
+ if(!FixedV[Tvaraff[z1]]){
+ printf( "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
+ fprintf(ficresp, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
+ fprintf(ficresphtm, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
+ fprintf(ficresphtmfr, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
+ fprintf(ficlog, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
+ }else{
+ printf( "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
+ fprintf(ficresp, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
+ fprintf(ficresphtm, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
+ fprintf(ficresphtmfr, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
+ fprintf(ficlog, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
+ }
+ }
+ printf( "**********\n#");
fprintf(ficresp, "**********\n#");
+ fprintf(ficresphtm, "**********
\n");
+ fprintf(ficresphtmfr, "**********
\n");
+ fprintf(ficlog, "**********\n");
+ }
+ /*
+ 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)\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
\n", z1, m, meanqt[m][z1]); */
+ /* } */
+ /* } */
+
+ fprintf(ficresphtm,"
");
+ if((cptcoveff==0 && nj==1)|| nj==2 ) /* no covariate and first pass */
+ fprintf(ficresp, " Age");
+ if(nj==2) for (z1=1; z1<=cptcoveff; z1++) fprintf(ficresp, " V%d=%d",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,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, "Age | Prev(%d) | N(%d) | N | ",i,i);
}
- for(i=1; i<=nlstate;i++)
- fprintf(ficresp, " Age Prev(%d) N(%d) N",i,i);
- fprintf(ficresp, "\n");
+ if((cptcoveff==0 && nj==1)|| nj==2 ) fprintf(ficresp, "\n");
+ fprintf(ficresphtm, "\n");
- for(i=iagemin; i <= iagemax+3; i++){
- if(i==iagemax+3){
+ /* Header of frequency table by age */
+ fprintf(ficresphtmfr,"");
+ fprintf(ficresphtmfr,"Age | ");
+ for(s2=-1; s2 <=nlstate+ndeath; s2++){
+ for(m=-1; m <=nlstate+ndeath; m++){
+ if(s2!=0 && m!=0)
+ fprintf(ficresphtmfr,"%d%d | ",s2,m);
+ }
+ }
+ fprintf(ficresphtmfr, "\n");
+
+ /* For each age */
+ for(iage=iagemin; iage <= iagemax+3; iage++){
+ fprintf(ficresphtm,"");
+ if(iage==iagemax+1){
+ fprintf(ficlog,"1");
+ fprintf(ficresphtmfr,"
0 | ");
+ }else if(iage==iagemax+2){
+ fprintf(ficlog,"0");
+ fprintf(ficresphtmfr,"
---|
Unknown | ");
+ }else if(iage==iagemax+3){
fprintf(ficlog,"Total");
+ fprintf(ficresphtmfr,"
---|
Total | ");
}else{
if(first==1){
first=0;
printf("See log file for details...\n");
}
- fprintf(ficlog,"Age %d", i);
+ fprintf(ficresphtmfr,"
---|
%d | ",iage);
+ fprintf(ficlog,"Age %d", iage);
}
- for(jk=1; jk <=nlstate ; jk++){
- for(m=-1, pp[jk]=0; m <=nlstate+ndeath ; m++)
- pp[jk] += freq[jk][m][i];
+ for(s1=1; s1 <=nlstate ; s1++){
+ for(m=-1, pp[s1]=0; m <=nlstate+ndeath ; m++)
+ pp[s1] += freq[s1][m][iage];
}
- for(jk=1; jk <=nlstate ; jk++){
+ for(s1=1; s1 <=nlstate ; s1++){
for(m=-1, pos=0; m <=0 ; m++)
- pos += freq[jk][m][i];
- if(pp[jk]>=1.e-10){
+ pos += freq[s1][m][iage];
+ if(pp[s1]>=1.e-10){
if(first==1){
- printf(" %d.=%.0f loss[%d]=%.1f%%",jk,pp[jk],jk,100*pos/pp[jk]);
+ printf(" %d.=%.0f loss[%d]=%.1f%%",s1,pp[s1],s1,100*pos/pp[s1]);
}
- fprintf(ficlog," %d.=%.0f loss[%d]=%.1f%%",jk,pp[jk],jk,100*pos/pp[jk]);
+ 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%%",jk,pp[jk],jk);
- fprintf(ficlog," %d.=%.0f loss[%d]=NaNQ%%",jk,pp[jk],jk);
+ printf(" %d.=%.0f loss[%d]=NaNQ%%",s1,pp[s1],s1);
+ fprintf(ficlog," %d.=%.0f loss[%d]=NaNQ%%",s1,pp[s1],s1);
}
}
-
- for(jk=1; jk <=nlstate ; jk++){
- for(m=0, pp[jk]=0; m <=nlstate+ndeath; m++)
- pp[jk] += freq[jk][m][i];
- }
- for(jk=1,pos=0,posprop=0; jk <=nlstate ; jk++){
- pos += pp[jk];
- posprop += prop[jk][i];
+
+ 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,z1)]);
+ }
}
- for(jk=1; jk <=nlstate ; jk++){
+ for(s1=1; s1 <=nlstate ; s1++){
if(pos>=1.e-5){
if(first==1)
- printf(" %d.=%.0f prev[%d]=%.1f%%",jk,pp[jk],jk,100*pp[jk]/pos);
- fprintf(ficlog," %d.=%.0f prev[%d]=%.1f%%",jk,pp[jk],jk,100*pp[jk]/pos);
+ 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%%",jk,pp[jk],jk);
- fprintf(ficlog," %d.=%.0f prev[%d]=NaNQ%%",jk,pp[jk],jk);
+ printf(" %d.=%.0f prev[%d]=NaNQ%%",s1,pp[s1],s1);
+ fprintf(ficlog," %d.=%.0f prev[%d]=NaNQ%%",s1,pp[s1],s1);
}
- if( i <= iagemax){
+ if( iage <= iagemax){
if(pos>=1.e-5){
- fprintf(ficresp," %d %.5f %.0f %.0f",i,prop[jk][i]/posprop, prop[jk][i],posprop);
- /*probs[i][jk][j1]= pp[jk]/pos;*/
- /*printf("\ni=%d jk=%d j1=%d %.5f %.0f %.0f %f",i,jk,j1,pp[jk]/pos, pp[jk],pos,probs[i][jk][j1]);*/
+ 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,"%d | %.5f | %.0f | %.0f | ",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,"%d | NaNq | %.0f | %.0f | ",iage, prop[s1][iage],pospropta);
}
- else
- fprintf(ficresp," %d NaNq %.0f %.0f",i,prop[jk][i],posprop);
}
- }
-
- for(jk=-1; jk <=nlstate+ndeath; jk++)
- for(m=-1; m <=nlstate+ndeath; m++)
- if(freq[jk][m][i] !=0 ) {
- if(first==1)
- printf(" %d%d=%.0f",jk,m,freq[jk][m][i]);
- fprintf(ficlog," %d%d=%.0f",jk,m,freq[jk][m][i]);
+ 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(i <= iagemax)
- fprintf(ficresp,"\n");
+ if(s1!=0 && m!=0)
+ fprintf(ficresphtmfr,"%.0f | ",freq[s1][m][iage]);
+ }
+ } /* end loop s1 */
+ posproptt=0.;
+ for(s1=1; s1 <=nlstate; s1++){
+ posproptt += pospropt[s1];
+ }
+ fprintf(ficresphtmfr,"
\n ");
+ fprintf(ficresphtm,"\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,"Tot | ");
+ for(s1=1; s1 <=nlstate ; s1++){
+ if(posproptt < 1.e-5){
+ fprintf(ficresphtm,"Nanq | %.0f | %.0f | ",pospropt[s1],posproptt);
+ }else{
+ fprintf(ficresphtm,"%.5f | %.0f | %.0f | ",pospropt[s1]/posproptt,pospropt[s1],posproptt);
+ }
+ }
+ fprintf(ficresphtm,"
\n");
+ fprintf(ficresphtm,"
\n");
+ fprintf(ficresphtmfr,"
\n");
+ if(posproptt < 1.e-5){
+ fprintf(ficresphtm,"\n This combination (%d) is not valid and no result will be produced
",j1);
+ fprintf(ficresphtmfr,"\n This combination (%d) is not valid and no result will be produced
",j1);
+ fprintf(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 This combination (%d) is valid and result will be produced.
",j1);
+ invalidvarcomb[j1]=0;
+ }
+ fprintf(ficresphtmfr,"\n");
+ fprintf(ficlog,"\n");
+ if(j!=0){
+ printf("#Freqsummary: Starting values for combination j1=%d:\n", j1);
+ for(i=1,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);
- free_ma3x(freq,-5,nlstate+ndeath,-5,nlstate+ndeath, iagemin, iagemax+3);
+ 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);
- free_matrix(prop,1,nlstate,iagemin, iagemax+3);
- /* End of Freq */
+ /* 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 ********************/
@@ -2059,134 +5387,243 @@ void prevalence(double ***probs, double
We still use firstpass and lastpass as another selection.
*/
- int i, m, jk, k1, i1, j1, bool, z1,z2,j;
- double ***freq; /* Frequencies */
- double *pp, **prop;
- double pos,posprop;
+ 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,iagemax+3);
+ prop=matrix(1,nlstate,iagemin-AGEMARGE,iagemax+4+AGEMARGE);
/* freq=ma3x(-1,nlstate+ndeath,-1,nlstate+ndeath,iagemin,iagemax+3);*/
j1=0;
- j=cptcoveff;
+ /*j=cptcoveff;*/
if (cptcovn<1) {j=1;ncodemax[1]=1;}
- for(k1=1; k1<=j;k1++){
- for(i1=1; i1<=ncodemax[k1];i1++){
- j1++;
-
- for (i=1; i<=nlstate; i++)
- for(m=iagemin; m <= iagemax+3; m++)
- prop[i][m]=0.0;
-
- for (i=1; i<=imx; i++) { /* Each individual */
- bool=1;
- if (cptcovn>0) {
- for (z1=1; z1<=cptcoveff; z1++)
- if (covar[Tvaraff[z1]][i]!= nbcode[Tvaraff[z1]][codtab[j1][z1]])
+ first=0;
+ for(j1=1; j1<= (int) pow(2,cptcoveff);j1++){ /* For each combination of covariate */
+ for (i=1; i<=nlstate; i++)
+ for(iage=iagemin-AGEMARGE; iage <= iagemax+4+AGEMARGE; iage++)
+ prop[i][iage]=0.0;
+ printf("Prevalence combination of varying and fixed dummies %d\n",j1);
+ /* fprintf(ficlog," V%d=%d ",Tvaraff[j1],nbcode[Tvaraff[j1]][codtabm(k,j1)]); */
+ fprintf(ficlog,"Prevalence combination of varying and fixed dummies %d\n",j1);
+
+ for (i=1; i<=imx; i++) { /* Each individual */
+ bool=1;
+ /* for(m=firstpass; m<=lastpass; m++){/\* Other selection (we can limit to certain interviews*\/ */
+ for(mi=1; mi=firstpass && m <=lastpass){
y2=anint[m][i]+(mint[m][i]/12.); /* Fractional date in year */
if ((y2>=dateprev1) && (y2<=dateprev2)) { /* Here is the main selection (fractional years) */
if(agev[m][i]==0) agev[m][i]=iagemax+1;
if(agev[m][i]==1) agev[m][i]=iagemax+2;
- if((int)agev[m][i] iagemax+3) printf("Error on individual =%d agev[m][i]=%f m=%d\n",i, agev[m][i],m);
- if (s[m][i]>0 && s[m][i]<=nlstate) {
+ if((int)agev[m][i] iagemax+4+AGEMARGE){
+ printf("Error on individual # %d agev[m][i]=%f <%d-%d or > %d+3+%d m=%d; either change agemin or agemax or fix data\n",i, agev[m][i],iagemin,AGEMARGE, iagemax,AGEMARGE,m);
+ exit(1);
+ }
+ if (s[m][i]>0 && s[m][i]<=nlstate) {
/*if(i>4620) printf(" i=%d m=%d s[m][i]=%d (int)agev[m][i]=%d weight[i]=%f prop=%f\n",i,m,s[m][i],(int)agev[m][m],weight[i],prop[s[m][i]][(int)agev[m][i]]);*/
- prop[s[m][i]][(int)agev[m][i]] += weight[i];
- prop[s[m][i]][iagemax+3] += weight[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 */
- }
- }
- 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;
- }
- }
- }/* end jk */
- }/* end i */
- } /* end i1 */
- } /* end k1 */
+ } /* 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,iagemax+3);
+ free_matrix(prop,1,nlstate, iagemin-AGEMARGE,iagemax+4+AGEMARGE);
} /* End of prevalence */
/************* Waves Concatenation ***************/
void concatwav(int wav[], int **dh, int **bh, int **mw, int **s, double *agedc, double **agev, int firstpass, int lastpass, int imx, int nlstate, int stepm)
{
- /* Concatenates waves: wav[i] is the number of effective (useful waves) of individual i.
+ /* 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.
- */
+ and mw[mi+1][i]. dh depends on stepm. s[m][i] exists for any wave from firstpass to lastpass
+ */
- int i, mi, m;
+ 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;
+ int first=0, firstwo=0, firsthree=0, firstfour=0, firstfiv=0;
int j, k=0,jk, ju, jl;
double sum=0.;
first=0;
- jmin=1e+5;
+ firstwo=0;
+ firsthree=0;
+ firstfour=0;
+ jmin=100000;
jmax=-1;
jmean=0.;
- for(i=1; i<=imx; i++){
- mi=0;
- m=firstpass;
- while(s[m][i] <= nlstate){
- if(s[m][i]>=1 || s[m][i]==-2 || s[m][i]==-4 || s[m][i]==-5)
- mw[++mi][i]=m;
- if(m >=lastpass)
+
+/* 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
- m++;
+#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 */
- if (s[m][i] > nlstate){
+
+ /* mi is the last effective wave, m is lastpass, mw[j][i] gives the # of j-th effective wave for individual i */
+ /* After last pass */
+/* Treating death states */
+ if (s[m][i] > nlstate){ /* In a death state */
+ /* if( mint[m][i]==mdc[m][i] && anint[m][i]==andc[m][i]){ /\* same date of death and date of interview *\/ */
+ /* } */
mi++; /* Death is another wave */
/* if(mi==0) never been interviewed correctly before death */
- /* Only death is a correct wave */
+ /* Only death is a correct wave */
mw[mi][i]=m;
- }
-
- wav[i]=mi;
+ } /* 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! None valid information for:%ld line=%d (skipped) and may be others, see log file\n",num[i],i);
+ 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! None valid information for:%ld line=%d (skipped)\n",num[i],i);
+ 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 nlstate) { /* A death */
+ 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 */
@@ -2199,8 +5636,14 @@ void concatwav(int wav[], int **dh, int
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;
- if (j <= jmin) jmin=j;
+ 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);*/
@@ -2209,10 +5652,16 @@ void concatwav(int wav[], int **dh, int
else{
j= rint( (agev[mw[mi+1][i]][i]*12 - agev[mw[mi][i]][i]*12));
/* if (j<0) printf("%d %lf %lf %d %d %d\n", i,agev[mw[mi+1][i]][i], agev[mw[mi][i]][i],j,s[mw[mi][i]][i] ,s[mw[mi+1][i]][i]); */
-
+
k=k+1;
- if (j >= jmax) jmax=j;
- else if (j <= jmin)jmin=j;
+ if (j >= jmax) {
+ jmax=j;
+ ijmax=i;
+ }
+ else if (j <= jmin){
+ jmin=j;
+ ijmin=i;
+ }
/* if (j<10) printf("j=%d jmin=%d num=%d ",j,jmin,i); */
/*printf("%d %lf %d %d %d\n", i,agev[mw[mi][i]][i],j,s[mw[mi][i]][i] ,s[mw[mi+1][i]][i]);*/
if(j<0){
@@ -2230,7 +5679,7 @@ void concatwav(int wav[], int **dh, int
dh[mi][i]=jk;
bh[mi][i]=0;
}else{ /* We want a negative bias in order to only have interpolation ie
- * at the price of an extra matrix product in likelihood */
+ * to avoid the price of an extra matrix product in likelihood */
dh[mi][i]=jk+1;
bh[mi][i]=ju;
}
@@ -2255,97 +5704,217 @@ void concatwav(int wav[], int **dh, int
} /* end wave */
}
jmean=sum/k;
- printf("Delay (in months) between two waves Min=%d Max=%d Mean=%f\n\n ",jmin, jmax,jmean);
- fprintf(ficlog,"Delay (in months) between two waves Min=%d Max=%d Mean=%f\n\n ",jmin, jmax,jmean);
- }
+ 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 *Tvar, int **nbcode, int imx)
-{
-
- int Ndum[20],ij=1, k, j, i, maxncov=19;
- int cptcode=0;
- cptcoveff=0;
-
- for (k=0; k cptcode) cptcode=ij; /* getting the maximum of covariable
- Tvar[j]. If V=sex and male is 0 and
- female is 1, then cptcode=1.*/
- }
-
- for (i=0; i<=cptcode; i++) {
- if(Ndum[i]!=0) ncodemax[j]++; /* Nomber of modalities of the j th covariates. In fact ncodemax[j]=2 (dichotom. variables) but it can be more */
- }
-
- ij=1;
- for (i=1; i<=ncodemax[j]; i++) {
- for (k=0; k<= maxncov; k++) {
- if (Ndum[k] != 0) {
- nbcode[Tvar[j]][ij]=k;
- /* store the modality in an array. k is a modality. If we have model=V1+V1*sex then: nbcode[1][1]=0 ; nbcode[1][2]=1; nbcode[2][1]=0 ; nbcode[2][2]=1; */
-
- ij++;
- }
- if (ij > ncodemax[j]) break;
- }
- }
- }
+ 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);
+ */
- for (k=0; k< maxncov; k++) Ndum[k]=0;
+ 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 */
- for (i=1; i<=ncovmodel-2; i++) {
- /* 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];
- Ndum[ij]++;
- }
- ij=1;
- for (i=1; i<= maxncov; i++) {
- if((Ndum[i]!=0) && (i<=ncovcol)){
- Tvaraff[ij]=i; /*For printing */
- ij++;
+ /* 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++) { /* From model V1 + V2*age + V3 + V3*V4 keeps V1 + V3 = 2 only */
+ for (j=-1; (j < maxncov); j++) Ndum[j]=0;
+ if(Dummy[k]==0 && Typevar[k] !=1){ /* Dummy covariate and not age product */
+ switch(Fixed[k]) {
+ case 0: /* Testing on fixed dummy covariate, simple or product of fixed */
+ 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*/
+ 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){ /* Dummy 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(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 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++) { /* modmaxcovj is unknown here. Only Ndum[2(V2),3(age*V3), 5(V3*V2) 6(V1*V4) */
+ /*printf("Ndum[%d]=%d\n",i, Ndum[i]);*/
+ /* if((Ndum[i]!=0) && (i<=ncovcol)){ /\* Tvar[i] <= ncovmodel ? *\/ */
+ if(Ndum[Tvar[k]]!=0 && Dummy[k] == 0 && Typevar[k]==0){ /* Only Dummy and non empty in the model */
+ /* If product not in single variable we don't print results */
+ /*printf("diff Ndum[%d]=%d\n",i, Ndum[i]);*/
+ ++ij;/* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, */
+ Tvaraff[ij]=Tvar[k]; /* For printing combination *//* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, Tvar {5, 4, 3, 6, 5, 2, 7, 1, 1} Tvaraff={4, 3, 1} V4, V3, V1*/
+ Tmodelind[ij]=k; /* Tmodelind: index in model of dummies Tmodelind[1]=2 V4: pos=2; V3: pos=3, V1=9 {2, 3, 9, ?, ?,} */
+ TmodelInvind[ij]=Tvar[k]- ncovcol-nqv; /* Inverse TmodelInvind[2=V4]=2 second dummy varying cov (V4)4-1-1 {0, 2, 1, } TmodelInvind[3]=1 */
+ if(Fixed[k]!=0)
+ anyvaryingduminmodel=1;
+ /* }else if((Ndum[i]!=0) && (i<=ncovcol+nqv)){ */
+ /* Tvaraff[++ij]=-10; /\* Dont'n know how to treat quantitative variables yet *\/ */
+ /* }else if((Ndum[i]!=0) && (i<=ncovcol+nqv+ntv)){ */
+ /* Tvaraff[++ij]=i; /\*For printing (unclear) *\/ */
+ /* }else if((Ndum[i]!=0) && (i<=ncovcol+nqv+ntv+nqtv)){ */
+ /* Tvaraff[++ij]=-20; /\* Dont'n know how to treat quantitative variables yet *\/ */
+ }
+ } /* Tvaraff[1]@5 {3, 4, -20, 0, 0} Very strange */
+ /* ij--; */
+ /* cptcoveff=ij; /\*Number of total covariates*\/ */
+ *cptcov=ij; /*Number of total real effective covariates: effective
+ * because they can be excluded from the model and real
+ * if in the model but excluded because missing values, but how to get k from ij?*/
+ for(j=ij+1; j<= cptcovt; j++){
+ Tvaraff[j]=0;
+ Tmodelind[j]=0;
}
+ for(j=ntveff+1; j<= cptcovt; j++){
+ TmodelInvind[j]=0;
+ }
+ /* To be sorted */
+ ;
}
-
- cptcoveff=ij-1; /*Number of simple covariates*/
-}
+
/*********** Health Expectancies ****************/
-void evsij(char fileres[], double ***eij, double x[], int nlstate, int stepm, int bage, int fage, double **oldm, double **savm, int ij, int estepm,double delti[],double **matcov,char strstart[] )
+ void evsij(double ***eij, double x[], int nlstate, int stepm, int bage, int fage, double **oldm, double **savm, int cij, int estepm,char strstart[], int nres )
{
- /* Health expectancies */
- int i, j, nhstepm, hstepm, h, nstepm, k, cptj;
+ /* Health expectancies, no variances */
+ int i, j, nhstepm, hstepm, h, nstepm;
+ int nhstepma, nstepma; /* Decreasing with age */
double age, agelim, hf;
- double ***p3mat,***varhe;
- double **dnewm,**doldm;
- double *xp;
- double **gp, **gm;
- double ***gradg, ***trgradg;
- int theta;
+ double ***p3mat;
+ double eip;
- varhe=ma3x(1,nlstate*nlstate,1,nlstate*nlstate,(int) bage, (int) fage);
- xp=vector(1,npar);
- dnewm=matrix(1,nlstate*nlstate,1,npar);
- doldm=matrix(1,nlstate*nlstate,1,nlstate*nlstate);
-
- fprintf(ficreseij,"# Local time at start: %s", strstart);
- fprintf(ficreseij,"# Health expectancies\n");
+ /* pstamp(ficreseij); */
+ fprintf(ficreseij,"# (a) Life expectancies by health status at initial age and (b) health expectancies by health status at initial age\n");
fprintf(ficreseij,"# Age");
- for(i=1; i<=nlstate;i++)
- for(j=1; j<=nlstate;j++)
- fprintf(ficreseij," %1d-%1d (SE)",i,j);
+ for(i=1; i<=nlstate;i++){
+ for(j=1; j<=nlstate;j++){
+ fprintf(ficreseij," e%1d%1d ",i,j);
+ }
+ fprintf(ficreseij," e%1d. ",i);
+ }
fprintf(ficreseij,"\n");
+
if(estepm < stepm){
printf ("Problem %d lower than %d\n",estepm, stepm);
}
@@ -2365,7 +5934,7 @@ void evsij(char fileres[], double ***eij
/* 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
+ 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
@@ -2376,446 +5945,647 @@ void evsij(char fileres[], double ***eij
hstepm=hstepm/stepm; /* Typically in stepm units, if stepm=6 & estepm=24 , = 24/6 months = 4 */
agelim=AGESUP;
- for (age=bage; age<=fage; age ++){ /* If stepm=6 months */
- /* nhstepm age range expressed in number of stepm */
- nstepm=(int) rint((agelim-age)*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 */
- p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
- gradg=ma3x(0,nhstepm,1,npar,1,nlstate*nlstate);
- gp=matrix(0,nhstepm,1,nlstate*nlstate);
- gm=matrix(0,nhstepm,1,nlstate*nlstate);
-
+ /* If stepm=6 months */
/* Computed by stepm unit matrices, product of hstepm matrices, stored
in an array of nhstepm length: nhstepm=10, hstepm=4, stepm=6 months */
- hpxij(p3mat,nhstepm,age,hstepm,x,nlstate,stepm,oldm, savm, ij);
-
-
- hf=hstepm*stepm/YEARM; /* Duration of hstepm expressed in year unit. */
-
- /* Computing Variances of health expectancies */
-
- for(theta=1; theta <=npar; theta++){
- for(i=1; i<=npar; i++){
- xp[i] = x[i] + (i==theta ?delti[theta]:0);
- }
- hpxij(p3mat,nhstepm,age,hstepm,xp,nlstate,stepm,oldm,savm, ij);
-
- cptj=0;
- for(j=1; j<= nlstate; j++){
- for(i=1; i<=nlstate; i++){
- cptj=cptj+1;
- for(h=0, gp[h][cptj]=0.; h<=nhstepm-1; h++){
- gp[h][cptj] = (p3mat[i][j][h]+p3mat[i][j][h+1])/2.;
- }
- }
- }
-
-
- for(i=1; i<=npar; i++)
- xp[i] = x[i] - (i==theta ?delti[theta]:0);
- hpxij(p3mat,nhstepm,age,hstepm,xp,nlstate,stepm,oldm,savm, ij);
-
- cptj=0;
- for(j=1; j<= nlstate; j++){
- for(i=1;i<=nlstate;i++){
- cptj=cptj+1;
- for(h=0, gm[h][cptj]=0.; h<=nhstepm-1; h++){
-
- gm[h][cptj] = (p3mat[i][j][h]+p3mat[i][j][h+1])/2.;
- }
- }
- }
- for(j=1; j<= nlstate*nlstate; j++)
- for(h=0; h<=nhstepm-1; h++){
- gradg[h][theta][j]= (gp[h][j]-gm[h][j])/2./delti[theta];
- }
- }
-
-/* End theta */
-
- trgradg =ma3x(0,nhstepm,1,nlstate*nlstate,1,npar);
+
+/* 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(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 (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 */
- for(i=1;i<=nlstate*nlstate;i++)
- for(j=1;j<=nlstate*nlstate;j++)
- varhe[i][j][(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(i=1;i<=nlstate*nlstate;i++)
- for(j=1;j<=nlstate*nlstate;j++)
- varhe[i][j][(int)age] += doldm[i][j]*hf*hf;
- }
- }
+ /* If stepm=6 months */
+ /* Computed by stepm unit matrices, product of hstepma matrices, stored
+ in an array of nhstepma length: nhstepma=10, hstepm=4, stepm=6 months */
+
+ hpxij(p3mat,nhstepma,age,hstepm,x,nlstate,stepm,oldm, savm, cij, nres);
+
+ hf=hstepm*stepm/YEARM; /* Duration of hstepm expressed in year unit. */
+
+ printf("%d|",(int)age);fflush(stdout);
+ fprintf(ficlog,"%d|",(int)age);fflush(ficlog);
+
/* Computing expectancies */
for(i=1; i<=nlstate;i++)
for(j=1; j<=nlstate;j++)
for (h=0, eij[i][j][(int)age]=0; h<=nhstepm-1; h++){
eij[i][j][(int)age] += (p3mat[i][j][h]+p3mat[i][j][h+1])/2.0*hf;
-/* if((int)age==70)printf("i=%2d,j=%2d,h=%2d,age=%3d,%9.4f,%9.4f,%9.4f\n",i,j,h,(int)age,p3mat[i][j][h],hf,eij[i][j][(int)age]);*/
+ /* 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 );
- cptj=0;
- for(i=1; i<=nlstate;i++)
+ for(i=1; i<=nlstate;i++){
+ eip=0;
for(j=1; j<=nlstate;j++){
- cptj++;
- fprintf(ficreseij," %9.4f (%.4f)", eij[i][j][(int)age], sqrt(varhe[cptj][cptj][(int)age]) );
+ eip +=eij[i][j][(int)age];
+ fprintf(ficreseij,"%9.4f", eij[i][j][(int)age] );
}
+ fprintf(ficreseij,"%9.4f", eip );
+ }
fprintf(ficreseij,"\n");
-
- free_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(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
+
}
+ free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
printf("\n");
fprintf(ficlog,"\n");
-
- 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 ij, int estepm, int cptcov, int cptcod, int popbased, int mobilav, char strstart[])
+ void cvevsij(double ***eij, double x[], int nlstate, int stepm, int bage, int fage, double **oldm, double **savm, int cij, int estepm,double delti[],double **matcov,char strstart[], int nres )
+
{
- /* Variance of health expectancies */
- /* double **prevalim(double **prlim, int nlstate, double *xp, double age, double **oldm, double ** savm,double ftolpl);*/
- /* double **newm;*/
+ /* Covariances of health expectancies eij and of total life expectancies according
+ to initial status i, ei. .
+ */
+ int i, j, nhstepm, hstepm, h, nstepm, k, cptj, cptj2, i2, j2, ij, ji;
+ int nhstepma, nstepma; /* Decreasing with age */
+ double age, agelim, hf;
+ double ***p3matp, ***p3matm, ***varhe;
double **dnewm,**doldm;
- double **dnewmp,**doldmp;
- int i, j, nhstepm, hstepm, h, nstepm ;
- int k, cptcode;
- 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;
+ double *xp, *xm;
+ double **gp, **gm;
+ double ***gradg, ***trgradg;
int theta;
- char digit[4];
- char digitp[25];
- char fileresprobmorprev[FILENAMELENGTH];
+ double eip, vip;
- 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);
- }
+ 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");
- 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,fileres);
- 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);
- fprintf(ficresprobmorprev, "#Local time at start: %s", strstart);
- 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,"# 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(fichtm, "#Local time at start: %s", strstart);
- fprintf(fichtm,"\n Computing probabilities of dying over estepm months as a weighted average (i.e global mortality independent of initial healh state)
\n");
- fprintf(fichtm,"\n
%s
\n",digitp);
-/* } */
- varppt = matrix(nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
- fprintf(ficresvij, "#Local time at start: %s", strstart);
- fprintf(ficresvij,"# Variance and covariance of health expectancies e.j \n# (weighted average of eij where weights are the stable prevalence in health states i\n");
- fprintf(ficresvij,"# Age");
+ 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++)
- 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*/
+ 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 k years */
+ 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 every two years of age and if
+ means that if the survival funtion is printed only each two years of age and if
you sum them up and add 1 year (area under the trapezoids) you won't get the same
results. So we changed our mind and took the option of the best precision.
*/
hstepm=hstepm/stepm; /* Typically in stepm units, if stepm=6 & estepm=24 , = 24/6 months = 4 */
- agelim = AGESUP;
- for (age=bage; age<=fage; age ++){ /* If stepm=6 months */
- 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);
+ /* If stepm=6 months */
+ /* nhstepm age range expressed in number of stepm */
+ agelim=AGESUP;
+ nstepm=(int) rint((agelim-bage)*YEARM/stepm);
+ /* Typically if 20 years nstepm = 20*12/6=40 stepm */
+ /* if (stepm >= YEARM) hstepm=1;*/
+ nhstepm = nstepm/hstepm;/* Expressed in hstepm, typically nhstepm=40/4=10 */
+
+ p3matp=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
+ p3matm=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
+ gradg=ma3x(0,nhstepm,1,npar,1,nlstate*nlstate);
+ trgradg =ma3x(0,nhstepm,1,nlstate*nlstate,1,npar);
+ gp=matrix(0,nhstepm,1,nlstate*nlstate);
+ gm=matrix(0,nhstepm,1,nlstate*nlstate);
+ for (age=bage; age<=fage; age ++){
+ nstepma=(int) rint((agelim-bage)*YEARM/stepm); /* Biggest nstepm */
+ /* Typically if 20 years nstepm = 20*12/6=40 stepm */
+ /* if (stepm >= YEARM) hstepm=1;*/
+ nhstepma = nstepma/hstepm;/* Expressed in hstepm, typically nhstepma=40/4=10 */
+
+ /* If stepm=6 months */
+ /* Computed by stepm unit matrices, product of hstepma matrices, stored
+ in an array of nhstepma length: nhstepma=10, hstepm=4, stepm=6 months */
+
+ hf=hstepm*stepm/YEARM; /* Duration of hstepm expressed in year unit. */
+
+ /* Computing Variances of health expectancies */
+ /* Gradient is computed with plus gp and minus gm. Code is duplicated in order to
+ decrease memory allocation */
for(theta=1; theta <=npar; theta++){
- for(i=1; i<=npar; i++){ /* Computes gradient x + delta*/
+ for(i=1; i<=npar; i++){
xp[i] = x[i] + (i==theta ?delti[theta]:0);
+ xm[i] = x[i] - (i==theta ?delti[theta]:0);
}
- hpxij(p3mat,nhstepm,age,hstepm,xp,nlstate,stepm,oldm,savm, ij);
- prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ij);
-
- 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];
- }
- }
-
- 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];
- }
- }
- /* 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,gpp[j]=0.; i<= nlstate; i++)
- gpp[j] += prlim[i][i]*p3mat[i][j][1];
- }
- /* end probability of death */
-
- for(i=1; i<=npar; i++) /* Computes gradient x - delta */
- xp[i] = x[i] - (i==theta ?delti[theta]:0);
- hpxij(p3mat,nhstepm,age,hstepm,xp,nlstate,stepm,oldm,savm, ij);
- prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ij);
-
- 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(p3matp,nhstepm,age,hstepm,xp,nlstate,stepm,oldm,savm, cij, nres);
+ hpxij(p3matm,nhstepm,age,hstepm,xm,nlstate,stepm,oldm,savm, cij, nres);
+
for(j=1; j<= nlstate; j++){
- for(h=0; h<=nhstepm; h++){
- for(i=1, gm[h][j]=0.;i<=nlstate;i++)
- gm[h][j] += prlim[i][i]*p3mat[i][j][h];
+ for(i=1; i<=nlstate; i++){
+ for(h=0; h<=nhstepm-1; h++){
+ gp[h][(j-1)*nlstate + i] = (p3matp[i][j][h]+p3matp[i][j][h+1])/2.;
+ gm[h][(j-1)*nlstate + i] = (p3matm[i][j][h]+p3matm[i][j][h+1])/2.;
+ }
}
}
- /* This for computing probability of death (h=1 means
- computed over hstepm matrices product = hstepm*stepm months)
- as a weighted average of prlim.
- */
- for(j=nlstate+1;j<=nlstate+ndeath;j++){
- for(i=1,gmp[j]=0.; i<= nlstate; i++)
- gmp[j] += prlim[i][i]*p3mat[i][j][1];
- }
- /* end probability of death */
-
- for(j=1; j<= nlstate; j++) /* vareij */
- for(h=0; h<=nhstepm; h++){
- gradg[h][theta][j]= (gp[h][j]-gm[h][j])/2./delti[theta];
+
+ for(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];
}
-
- for(j=nlstate+1; j<= nlstate+ndeath; j++){ /* var mu */
- gradgp[theta][j]= (gpp[j]-gmp[j])/2./delti[theta];
- }
-
- } /* End theta */
-
- trgradg =ma3x(0,nhstepm,1,nlstate,1,npar); /* veij */
-
- for(h=0; h<=nhstepm; h++) /* veij */
- for(j=1; j<=nlstate;j++)
+ }/* 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(j=nlstate+1; j<=nlstate+ndeath;j++) /* mu */
- for(theta=1; theta <=npar; theta++)
- trgradgp[j][theta]=gradgp[theta][j];
-
-
- hf=hstepm*stepm/YEARM; /* Duration of hstepm expressed in year unit. */
- for(i=1;i<=nlstate;i++)
- for(j=1;j<=nlstate;j++)
- vareij[i][j][(int)age] =0.;
-
- for(h=0;h<=nhstepm;h++){
- for(k=0;k<=nhstepm;k++){
- matprod2(dnewm,trgradg[h],1,nlstate,1,npar,1,npar,matcov);
- matprod2(doldm,dnewm,1,nlstate,1,npar,1,nlstate,gradg[k]);
- for(i=1;i<=nlstate;i++)
- for(j=1;j<=nlstate;j++)
- vareij[i][j][(int)age] += doldm[i][j]*hf*hf;
- }
- }
-
- /* pptj */
- matprod2(dnewmp,trgradgp,nlstate+1,nlstate+ndeath,1,npar,1,npar,matcov);
- matprod2(doldmp,dnewmp,nlstate+1,nlstate+ndeath,1,npar,nlstate+1,nlstate+ndeath,gradgp);
- for(j=nlstate+1;j<=nlstate+ndeath;j++)
- for(i=nlstate+1;i<=nlstate+ndeath;i++)
- varppt[j][i]=doldmp[j][i];
- /* end ppptj */
- /* x centered again */
- hpxij(p3mat,nhstepm,age,hstepm,x,nlstate,stepm,oldm,savm, ij);
- prevalim(prlim,nlstate,x,age,oldm,savm,ftolpl,ij);
-
- 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];
+
+
+ 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;
}
}
-
- /* This for computing probability of death (h=1 means
- computed over hstepm (estepm) matrices product = hstepm*stepm months)
- as a weighted average of prlim.
- */
- for(j=nlstate+1;j<=nlstate+ndeath;j++){
- for(i=1,gmp[j]=0.;i<= nlstate; i++)
- gmp[j] += prlim[i][i]*p3mat[i][j][1];
- }
- /* end probability of death */
-
- 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");
+ /* 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]);*/
+
+ }
- fprintf(ficresvij,"%.0f ",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++){
- fprintf(ficresvij," %.4f", vareij[i][j][(int)age]);
+ 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(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,"\nset noparametric;set nolabel; set ter png small;set size 0.65, 0.65");
- /* for(j=nlstate+1; j<= nlstate+ndeath; j++){ *//* Only the first actually */
- fprintf(ficgp,"\n set log y; set nolog x;set xlabel \"Age\"; set ylabel \"Force of mortality (year-1)\";");
-/* 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 1 ",subdirf(fileresprobmorprev));
- fprintf(ficgp,"\n replot \"%s\" u 1:(($3+1.96*$4)) t \"95\%% interval\" w l 2 ",subdirf(fileresprobmorprev));
- fprintf(ficgp,"\n replot \"%s\" u 1:(($3-1.96*$4)) not w l 2 ",subdirf(fileresprobmorprev));
- fprintf(fichtm,"\n
File (multiple files are possible if covariates are present): %s\n",subdirf(fileresprobmorprev),subdirf(fileresprobmorprev));
- fprintf(fichtm,"\n
Probability is computed over estepm=%d months.
\n", estepm,subdirf3(optionfilefiname,"varmuptjgr",digitp),digit);
- /* fprintf(fichtm,"\n
Probability is computed over estepm=%d months and then divided by estepm and multiplied by %.0f in order to have the probability to die over a year
\n", stepm,YEARM,digitp,digit);
-*/
-/* fprintf(ficgp,"\nset out \"varmuptjgr%s%s%s.png\";replot;",digitp,optionfilefiname,digit); */
- fprintf(ficgp,"\nset out \"%s%s.png\";replot;\n",subdirf3(optionfilefiname,"varmuptjgr",digitp),digit);
-
+ fprintf(ficrescveij,"\n");
+
+ }
+ free_matrix(gm,0,nhstepm,1,nlstate*nlstate);
+ free_matrix(gp,0,nhstepm,1,nlstate*nlstate);
+ free_ma3x(gradg,0,nhstepm,1,npar,1,nlstate*nlstate);
+ free_ma3x(trgradg,0,nhstepm,1,nlstate*nlstate,1,npar);
+ free_ma3x(p3matm,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
+ free_ma3x(p3matp,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
+ printf("\n");
+ fprintf(ficlog,"\n");
+
+ free_vector(xm,1,npar);
free_vector(xp,1,npar);
- free_matrix(doldm,1,nlstate,1,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 */
+ 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");
+ for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
+ fprintf(ficresprobmorprev," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]);
+ }
+ for(j=1;j<=cptcoveff;j++)
+ fprintf(ficresprobmorprev,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(ij,j)]);
+ fprintf(ficresprobmorprev,"\n");
+
+ fprintf(ficresprobmorprev,"# Age cov=%-d",ij);
+ for(j=nlstate+1; j<=(nlstate+ndeath);j++){
+ fprintf(ficresprobmorprev," p.%-d SE",j);
+ for(i=1; i<=nlstate;i++)
+ fprintf(ficresprobmorprev," w%1d p%-d%-d",i,i,j);
+ }
+ fprintf(ficresprobmorprev,"\n");
+
+ fprintf(ficgp,"\n# Routine varevsij");
+ fprintf(ficgp,"\nunset title \n");
+ /* fprintf(fichtm, "#Local time at start: %s", strstart);*/
+ fprintf(fichtm,"\n Computing probabilities of dying over estepm months as a weighted average (i.e global mortality independent of initial healh state)
\n");
+ fprintf(fichtm,"\n
%s
\n",digitp);
+
+ varppt = matrix(nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
+ pstamp(ficresvij);
+ fprintf(ficresvij,"# Variance and covariance of health expectancies e.j \n# (weighted average of eij where weights are ");
+ if(popbased==1)
+ fprintf(ficresvij,"the age specific prevalence observed (cross-sectionally) in the population i.e cross-sectionally\n in each health state (popbased=1) (mobilav=%d\n",mobilav);
+ else
+ fprintf(ficresvij,"the age specific period (stable) prevalences in each health state \n");
+ fprintf(ficresvij,"# Age");
+ for(i=1; i<=nlstate;i++)
+ for(j=1; j<=nlstate;j++)
+ fprintf(ficresvij," Cov(e.%1d, e.%1d)",i,j);
+ fprintf(ficresvij,"\n");
+
+ xp=vector(1,npar);
+ dnewm=matrix(1,nlstate,1,npar);
+ doldm=matrix(1,nlstate,1,nlstate);
+ dnewmp= matrix(nlstate+1,nlstate+ndeath,1,npar);
+ doldmp= matrix(nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
+
+ gradgp=matrix(1,npar,nlstate+1,nlstate+ndeath);
+ gpp=vector(nlstate+1,nlstate+ndeath);
+ gmp=vector(nlstate+1,nlstate+ndeath);
+ trgradgp =matrix(nlstate+1,nlstate+ndeath,1,npar); /* mu or p point j*/
+
+ if(estepm < stepm){
+ printf ("Problem %d lower than %d\n",estepm, stepm);
+ }
+ else hstepm=estepm;
+ /* For example we decided to compute the life expectancy with the smallest unit */
+ /* hstepm beeing the number of stepms, if hstepm=1 the length of hstepm is stepm.
+ nhstepm is the number of hstepm from age to agelim
+ nstepm is the number of stepm from age to agelim.
+ Look at function hpijx to understand why because of memory size limitations,
+ we decided (b) to get a life expectancy respecting the most precise curvature of the
+ survival function given by stepm (the optimization length). Unfortunately it
+ means that if the survival funtion is printed every two years of age and if
+ you sum them up and add 1 year (area under the trapezoids) you won't get the same
+ results. So we changed our mind and took the option of the best precision.
+ */
+ hstepm=hstepm/stepm; /* Typically in stepm units, if stepm=6 & estepm=24 , = 24/6 months = 4 */
+ agelim = AGESUP;
+ for (age=bage; age<=fage; age ++){ /* If stepm=6 months */
+ nstepm=(int) rint((agelim-age)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
+ nhstepm = nstepm/hstepm;/* Expressed in hstepm, typically nhstepm=40/4=10 */
+ p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
+ gradg=ma3x(0,nhstepm,1,npar,1,nlstate);
+ gp=matrix(0,nhstepm,1,nlstate);
+ gm=matrix(0,nhstepm,1,nlstate);
+
+
+ for(theta=1; theta <=npar; theta++){
+ for(i=1; i<=npar; i++){ /* Computes gradient x + delta*/
+ xp[i] = x[i] + (i==theta ?delti[theta]:0);
+ }
+ /**< 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
File (multiple files are possible if covariates are present): %s\n",subdirf(fileresprobmorprev),subdirf(fileresprobmorprev));
+ fprintf(fichtm,"\n
Probability is computed over estepm=%d months.
\n", estepm,subdirf3(optionfilefiname,"VARMUPTJGR-",digitp),digit);
+ /* fprintf(fichtm,"\n
Probability is computed over estepm=%d months and then divided by estepm and multiplied by %.0f in order to have the probability to die over a year
\n", stepm,YEARM,digitp,digit);
+ */
+ /* fprintf(ficgp,"\nset out \"varmuptjgr%s%s%s.svg\";replot;",digitp,optionfilefiname,digit); */
+ fprintf(ficgp,"\nset out;\nset out \"%s%s.svg\";replot;set out;\n",subdirf3(optionfilefiname,"VARMUPTJGR-",digitp),digit);
+
+ free_vector(xp,1,npar);
+ free_matrix(doldm,1,nlstate,1,nlstate);
+ free_matrix(dnewm,1,nlstate,1,npar);
+ free_matrix(doldmp,nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
+ free_matrix(dnewmp,nlstate+1,nlstate+ndeath,1,npar);
+ free_matrix(varppt,nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
+ /* if (mobilav!=0) free_ma3x(mobaverage,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
+ fclose(ficresprobmorprev);
+ fflush(ficgp);
+ fflush(fichtm);
+ } /* end varevsij */
/************ Variance of prevlim ******************/
-void varprevlim(char fileres[], double **varpl, double **matcov, double x[], double delti[], int nlstate, int stepm, double bage, double fage, double **oldm, double **savm, double **prlim, double ftolpl, int ij, char strstart[])
+ 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 */
+ /* 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 **newm;
- double **dnewm,**doldm;
+
+ double **dnewmpar,**doldm;
int i, j, nhstepm, hstepm;
- int k, cptcode;
double *xp;
double *gp, *gm;
double **gradg, **trgradg;
+ double **mgm, **mgp;
double age,agelim;
int theta;
- fprintf(ficresvpl, "#Local time at start: %s", strstart);
- fprintf(ficresvpl,"# Standard deviation of stable prevalences \n");
- fprintf(ficresvpl,"# Age");
+
+ 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);
- dnewm=matrix(1,nlstate,1,npar);
+ dnewmpar=matrix(1,nlstate,1,npar);
doldm=matrix(1,nlstate,1,nlstate);
hstepm=1*YEARM; /* Every year of age */
@@ -2826,6 +6596,8 @@ void varprevlim(char fileres[], double *
if (stepm >= YEARM) hstepm=1;
nhstepm = nhstepm/hstepm; /* Typically 40/4=10 */
gradg=matrix(1,npar,1,nlstate);
+ mgp=matrix(1,npar,1,nlstate);
+ mgm=matrix(1,npar,1,nlstate);
gp=vector(1,nlstate);
gm=vector(1,nlstate);
@@ -2833,18 +6605,27 @@ void varprevlim(char fileres[], double *
for(i=1; i<=npar; i++){ /* Computes gradient */
xp[i] = x[i] + (i==theta ?delti[theta]:0);
}
- prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ij);
- for(i=1;i<=nlstate;i++)
+ /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ) */
+ /* prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres); */
+ /* else */
+ prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres);
+ for(i=1;i<=nlstate;i++){
gp[i] = prlim[i][i];
-
+ mgp[theta][i] = prlim[i][i];
+ }
for(i=1; i<=npar; i++) /* Computes gradient */
xp[i] = x[i] - (i==theta ?delti[theta]:0);
- prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ij);
- for(i=1;i<=nlstate;i++)
+ /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ) */
+ /* prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres); */
+ /* else */
+ prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres);
+ for(i=1;i<=nlstate;i++){
gm[i] = prlim[i][i];
-
+ mgm[theta][i] = prlim[i][i];
+ }
for(i=1;i<=nlstate;i++)
gradg[theta][i]= (gp[i]-gm[i])/2./delti[theta];
+ /* gradg[theta][2]= -gradg[theta][1]; */ /* For testing if nlstate=2 */
} /* End theta */
trgradg =matrix(1,nlstate,1,npar);
@@ -2852,114 +6633,267 @@ void varprevlim(char fileres[], double *
for(j=1; j<=nlstate;j++)
for(theta=1; theta <=npar; theta++)
trgradg[j][theta]=gradg[theta][j];
+ /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
+ /* printf("\nmgm mgp %d ",(int)age); */
+ /* for(j=1; j<=nlstate;j++){ */
+ /* printf(" %d ",j); */
+ /* for(theta=1; theta <=npar; theta++) */
+ /* printf(" %d %lf %lf",theta,mgm[theta][j],mgp[theta][j]); */
+ /* printf("\n "); */
+ /* } */
+ /* } */
+ /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
+ /* printf("\n gradg %d ",(int)age); */
+ /* for(j=1; j<=nlstate;j++){ */
+ /* printf("%d ",j); */
+ /* for(theta=1; theta <=npar; theta++) */
+ /* printf("%d %lf ",theta,gradg[theta][j]); */
+ /* printf("\n "); */
+ /* } */
+ /* } */
for(i=1;i<=nlstate;i++)
varpl[i][(int)age] =0.;
- matprod2(dnewm,trgradg,1,nlstate,1,npar,1,npar,matcov);
- matprod2(doldm,dnewm,1,nlstate,1,npar,1,nlstate,gradg);
+ 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 );
- for(i=1; i<=nlstate;i++)
+ 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(dnewm,1,nlstate,1,nlstate);
+ 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[])
+
+/************ 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)
{
- int i, j=0, i1, k1, l1, t, tj;
- int k2, l2, j1, z1;
- int k=0,l, cptcode;
- int first=1, first1;
- double cv12, mu1, mu2, lc1, lc2, v12, v21, v11, v22,v1,v2, c12, tnalp;
- double **dnewm,**doldm;
+ /* 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 **mu;
- double age,agelim, cov[NCOVMAX];
- double std=2.0; /* Number of standard deviation wide of confidence ellipsoids */
+ double **mgm, **mgp;
+ double age,agelim;
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,fileres);
- 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,fileres);
- 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);
- fprintf(ficresprob, "#Local time at start: %s", strstart);
- fprintf(ficresprob,"#One-step probabilities and stand. devi in ()\n");
- fprintf(ficresprob,"# Age");
- fprintf(ficresprobcov, "#Local time at start: %s", strstart);
- fprintf(ficresprobcov,"#One-step probabilities and covariance matrix\n");
- fprintf(ficresprobcov,"# Age");
- fprintf(ficresprobcor, "#Local time at start: %s", strstart);
- fprintf(ficresprobcor,"#One-step probabilities and correlation matrix\n");
- fprintf(ficresprobcov,"# Age");
+
+ 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 */
- for(i=1; i<=nlstate;i++)
- for(j=1; j<=(nlstate+ndeath);j++){
- fprintf(ficresprob," p%1d-%1d (SE)",i,j);
- fprintf(ficresprobcov," p%1d-%1d ",i,j);
- fprintf(ficresprobcor," p%1d-%1d ",i,j);
- }
- /* fprintf(ficresprob,"\n");
- fprintf(ficresprobcov,"\n");
- fprintf(ficresprobcor,"\n");
- */
- xp=vector(1,npar);
- dnewm=matrix(1,(nlstate)*(nlstate+ndeath),1,npar);
- doldm=matrix(1,(nlstate)*(nlstate+ndeath),1,(nlstate)*(nlstate+ndeath));
- mu=matrix(1,(nlstate)*(nlstate+ndeath), (int) bage, (int)fage);
- varpij=ma3x(1,nlstate*(nlstate+ndeath),1,nlstate*(nlstate+ndeath),(int) bage, (int) fage);
- first=1;
- fprintf(ficgp,"\n# Routine varprob");
- fprintf(fichtm,"\n Computing and drawing one step probabilities with their confidence intervals
\n");
- fprintf(fichtm,"\n");
+ 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);
+
+}
- fprintf(fichtm,"\n\n",optionfilehtmcov);
- fprintf(fichtmcov,"\nMatrix of variance-covariance of pairs of step probabilities
\n\
- file %s
\n",optionfilehtmcov);
- fprintf(fichtmcov,"\nEllipsoids of confidence centered on point (pij, pkl) are estimated\
+/************ Variance of one-step probabilities ******************/
+void varprob(char optionfilefiname[], double **matcov, double x[], double delti[], int nlstate, double bage, double fage, int ij, int *Tvar, int **nbcode, int *ncodemax, char strstart[])
+ {
+ int i, j=0, k1, l1, tj;
+ int k2, l2, j1, z1;
+ int k=0, l;
+ int first=1, first1, first2;
+ double cv12, mu1, mu2, lc1, lc2, v12, v21, v11, v22,v1,v2, c12, tnalp;
+ double **dnewm,**doldm;
+ double *xp;
+ double *gp, *gm;
+ double **gradg, **trgradg;
+ double **mu;
+ double age, cov[NCOVMAX+1];
+ double std=2.0; /* Number of standard deviation wide of confidence ellipsoids */
+ int theta;
+ char fileresprob[FILENAMELENGTH];
+ char fileresprobcov[FILENAMELENGTH];
+ char fileresprobcor[FILENAMELENGTH];
+ double ***varpij;
+
+ strcpy(fileresprob,"PROB_");
+ strcat(fileresprob,fileres);
+ if((ficresprob=fopen(fileresprob,"w"))==NULL) {
+ printf("Problem with resultfile: %s\n", fileresprob);
+ fprintf(ficlog,"Problem with resultfile: %s\n", fileresprob);
+ }
+ strcpy(fileresprobcov,"PROBCOV_");
+ strcat(fileresprobcov,fileresu);
+ if((ficresprobcov=fopen(fileresprobcov,"w"))==NULL) {
+ printf("Problem with resultfile: %s\n", fileresprobcov);
+ fprintf(ficlog,"Problem with resultfile: %s\n", fileresprobcov);
+ }
+ strcpy(fileresprobcor,"PROBCOR_");
+ strcat(fileresprobcor,fileresu);
+ if((ficresprobcor=fopen(fileresprobcor,"w"))==NULL) {
+ printf("Problem with resultfile: %s\n", fileresprobcor);
+ fprintf(ficlog,"Problem with resultfile: %s\n", fileresprobcor);
+ }
+ printf("Computing standard deviation of one-step probabilities: result on file '%s' \n",fileresprob);
+ fprintf(ficlog,"Computing standard deviation of one-step probabilities: result on file '%s' \n",fileresprob);
+ printf("Computing matrix of variance covariance of one-step probabilities: result on file '%s' \n",fileresprobcov);
+ fprintf(ficlog,"Computing matrix of variance covariance of one-step probabilities: result on file '%s' \n",fileresprobcov);
+ printf("and correlation matrix of one-step probabilities: result on file '%s' \n",fileresprobcor);
+ fprintf(ficlog,"and correlation matrix of one-step probabilities: result on file '%s' \n",fileresprobcor);
+ pstamp(ficresprob);
+ fprintf(ficresprob,"#One-step probabilities and stand. devi in ()\n");
+ fprintf(ficresprob,"# Age");
+ pstamp(ficresprobcov);
+ fprintf(ficresprobcov,"#One-step probabilities and covariance matrix\n");
+ fprintf(ficresprobcov,"# Age");
+ pstamp(ficresprobcor);
+ fprintf(ficresprobcor,"#One-step probabilities and correlation matrix\n");
+ fprintf(ficresprobcor,"# Age");
+
+
+ for(i=1; i<=nlstate;i++)
+ for(j=1; j<=(nlstate+ndeath);j++){
+ fprintf(ficresprob," p%1d-%1d (SE)",i,j);
+ fprintf(ficresprobcov," p%1d-%1d ",i,j);
+ fprintf(ficresprobcor," p%1d-%1d ",i,j);
+ }
+ /* fprintf(ficresprob,"\n");
+ fprintf(ficresprobcov,"\n");
+ fprintf(ficresprobcor,"\n");
+ */
+ xp=vector(1,npar);
+ dnewm=matrix(1,(nlstate)*(nlstate+ndeath),1,npar);
+ doldm=matrix(1,(nlstate)*(nlstate+ndeath),1,(nlstate)*(nlstate+ndeath));
+ mu=matrix(1,(nlstate)*(nlstate+ndeath), (int) bage, (int)fage);
+ varpij=ma3x(1,nlstate*(nlstate+ndeath),1,nlstate*(nlstate+ndeath),(int) bage, (int) fage);
+ first=1;
+ fprintf(ficgp,"\n# Routine varprob");
+ fprintf(fichtm,"\n Computing and drawing one step probabilities with their confidence intervals
\n");
+ fprintf(fichtm,"\n");
+
+ fprintf(fichtm,"\n 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\n",optionfilehtmcov,optionfilehtmcov);
+ fprintf(fichtmcov,"Current page is file %s
\n\nMatrix of variance-covariance of pairs of step probabilities
\n",optionfilehtmcov, optionfilehtmcov);
+ fprintf(fichtmcov,"\nEllipsoids of confidence centered on point (pij, pkl) are estimated \
and drawn. It helps understanding how is the covariance between two incidences.\
They are expressed in year-1 in order to be less dependent of stepm.
\n");
- fprintf(fichtmcov,"\n
Contour plot corresponding to x'cov-1x = 4 (where x is the column vector (pij,pkl)) are drawn. \
+ fprintf(fichtmcov,"\n
Contour plot corresponding to x'cov-1x = 4 (where x is the column vector (pij,pkl)) are drawn. \
It can be understood this way: if pij and pkl where uncorrelated the (2x2) matrix of covariance \
would have been (1/(var pij), 0 , 0, 1/(var pkl)), and the confidence interval would be 2 \
standard deviations wide on each axis.
\
@@ -2967,310 +6901,488 @@ standard deviations wide on each axis. <
and made the appropriate rotation to look at the uncorrelated principal directions.
\
To be simple, these graphs help to understand the significativity of each parameter in relation to a second other one.
\n");
- cov[1]=1;
- tj=cptcoveff;
- if (cptcovn<1) {tj=1;ncodemax[1]=1;}
- j1=0;
- for(t=1; t<=tj;t++){
- for(i1=1; i1<=ncodemax[t];i1++){
- j1++;
- if (cptcovn>0) {
- fprintf(ficresprob, "\n#********** Variable ");
- for (z1=1; z1<=cptcoveff; z1++) fprintf(ficresprob, "V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtab[j1][z1]]);
- fprintf(ficresprob, "**********\n#\n");
- fprintf(ficresprobcov, "\n#********** Variable ");
- for (z1=1; z1<=cptcoveff; z1++) fprintf(ficresprobcov, "V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtab[j1][z1]]);
- fprintf(ficresprobcov, "**********\n#\n");
-
- fprintf(ficgp, "\n#********** Variable ");
- for (z1=1; z1<=cptcoveff; z1++) fprintf(ficgp, " V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtab[j1][z1]]);
- fprintf(ficgp, "**********\n#\n");
-
-
- fprintf(fichtmcov, "\n
********** Variable ");
- for (z1=1; z1<=cptcoveff; z1++) fprintf(fichtm, "V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtab[j1][z1]]);
- fprintf(fichtmcov, "**********\n
");
-
- fprintf(ficresprobcor, "\n#********** Variable ");
- for (z1=1; z1<=cptcoveff; z1++) fprintf(ficresprobcor, "V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtab[j1][z1]]);
- fprintf(ficresprobcor, "**********\n#");
- }
-
- for (age=bage; age<=fage; age ++){
- cov[2]=age;
- for (k=1; k<=cptcovn;k++) {
- cov[2+k]=nbcode[Tvar[k]][codtab[j1][Tvar[k]]];
- }
- for (k=1; k<=cptcovage;k++) cov[2+Tage[k]]=cov[2+Tage[k]]*cov[2];
- for (k=1; k<=cptcovprod;k++)
- cov[2+Tprod[k]]=nbcode[Tvard[k][1]][codtab[ij][Tvard[k][1]]]*nbcode[Tvard[k][2]][codtab[ij][Tvard[k][2]]];
-
- 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(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);
- 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);
-
- 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=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++){
- 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 */
-
- /* Confidence intervalle of pij */
- /*
- fprintf(ficgp,"\nset noparametric;unset label");
- fprintf(ficgp,"\nset log y;unset log x; set xlabel \"Age\";set ylabel \"probability (year-1)\"");
- fprintf(ficgp,"\nset ter png small\nset size 0.65,0.65");
- fprintf(fichtm,"\n
Probability with confidence intervals expressed in year-1 :pijgr%s.png, ",optionfilefiname,optionfilefiname);
- fprintf(fichtm,"\n
",optionfilefiname);
- fprintf(ficgp,"\nset out \"pijgr%s.png\"",optionfilefiname);
- fprintf(ficgp,"\nplot \"%s\" every :::%d::%d u 1:2 \"\%%lf",k1,k2,xfilevarprob);
- */
+ cov[1]=1;
+ /* tj=cptcoveff; */
+ tj = (int) pow(2,cptcoveff);
+ if (cptcovn<1) {tj=1;ncodemax[1]=1;}
+ j1=0;
+ for(j1=1; j1<=tj;j1++){ /* For each valid combination of covariates or only once*/
+ if (cptcovn>0) {
+ fprintf(ficresprob, "\n#********** Variable ");
+ for (z1=1; z1<=cptcoveff; z1++) fprintf(ficresprob, "V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
+ fprintf(ficresprob, "**********\n#\n");
+ fprintf(ficresprobcov, "\n#********** Variable ");
+ for (z1=1; z1<=cptcoveff; z1++) fprintf(ficresprobcov, "V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
+ fprintf(ficresprobcov, "**********\n#\n");
+
+ fprintf(ficgp, "\n#********** Variable ");
+ for (z1=1; z1<=cptcoveff; z1++) fprintf(ficgp, " V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
+ fprintf(ficgp, "**********\n#\n");
+
+
+ fprintf(fichtmcov, "\n
********** Variable ");
+ /* for (z1=1; z1<=cptcoveff; z1++) fprintf(fichtm, "V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]); */
+ for (z1=1; z1<=cptcoveff; z1++) fprintf(fichtmcov, "V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
+ fprintf(fichtmcov, "**********\n
");
+
+ fprintf(ficresprobcor, "\n#********** Variable ");
+ for (z1=1; z1<=cptcoveff; z1++) fprintf(ficresprobcor, "V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,z1)]);
+ fprintf(ficresprobcor, "**********\n#");
+ if(invalidvarcomb[j1]){
+ fprintf(ficgp,"\n#Combination (%d) ignored because no cases \n",j1);
+ fprintf(fichtmcov,"\nCombination (%d) ignored because no cases
\n",j1);
+ continue;
+ }
+ }
+ gradg=matrix(1,npar,1,(nlstate)*(nlstate+ndeath));
+ trgradg=matrix(1,(nlstate)*(nlstate+ndeath),1,npar);
+ gp=vector(1,(nlstate)*(nlstate+ndeath));
+ gm=vector(1,(nlstate)*(nlstate+ndeath));
+ for (age=bage; age<=fage; age ++){
+ cov[2]=age;
+ if(nagesqr==1)
+ cov[3]= age*age;
+ for (k=1; k<=cptcovn;k++) {
+ cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(j1,k)];
+ /*cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(j1,Tvar[k])];*//* j1 1 2 3 4
+ * 1 1 1 1 1
+ * 2 2 1 1 1
+ * 3 1 2 1 1
+ */
+ /* nbcode[1][1]=0 nbcode[1][2]=1;*/
+ }
+ /* 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++)
+ cov[2+Tage[k]+nagesqr]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2];
+ for (k=1; k<=cptcovprod;k++)
+ cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)]*nbcode[Tvard[k][2]][codtabm(ij,k)];
+
+
+ for(theta=1; theta <=npar; theta++){
+ for(i=1; i<=npar; i++)
+ xp[i] = x[i] + (i==theta ?delti[theta]:(double)0);
+
+ pmij(pmmij,cov,ncovmodel,xp,nlstate);
+
+ k=0;
+ for(i=1; i<= (nlstate); i++){
+ for(j=1; j<=(nlstate+ndeath);j++){
+ k=k+1;
+ gp[k]=pmmij[i][j];
+ }
+ }
+
+ for(i=1; i<=npar; i++)
+ xp[i] = x[i] - (i==theta ?delti[theta]:(double)0);
+
+ pmij(pmmij,cov,ncovmodel,xp,nlstate);
+ k=0;
+ for(i=1; i<=(nlstate); i++){
+ for(j=1; j<=(nlstate+ndeath);j++){
+ k=k+1;
+ gm[k]=pmmij[i][j];
+ }
+ }
+
+ for(i=1; i<= (nlstate)*(nlstate+ndeath); i++)
+ gradg[theta][i]=(gp[i]-gm[i])/(double)2./delti[theta];
+ }
- /* Drawing ellipsoids of confidence of two variables p(k1-l1,k2-l2)*/
- first1=1;
- 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.;
- /* Eigen vectors */
- v11=(1./sqrt(1+(v1-lc1)*(v1-lc1)/cv12/cv12));
- /*v21=sqrt(1.-v11*v11); *//* error */
- v21=(lc1-v1)/cv12*v11;
- v12=-v21;
- v22=v11;
- tnalp=v21/v11;
- if(first1==1){
- first1=0;
- printf("%d %d%d-%d%d mu %.4e %.4e Var %.4e %.4e cor %.3f cov %.4e Eig %.3e %.3e 1stv %.3f %.3f tang %.3f\nOthers in log...\n",(int) age,k1,l1,k2,l2,mu1,mu2,v1,v2,c12,cv12,lc1,lc2,v11,v21,tnalp);
- }
- fprintf(ficlog,"%d %d%d-%d%d mu %.4e %.4e Var %.4e %.4e cor %.3f cov %.4e Eig %.3e %.3e 1stv %.3f %.3f tan %.3f\n",(int) age,k1,l1,k2,l2,mu1,mu2,v1,v2,c12,cv12,lc1,lc2,v11,v21,tnalp);
- /*printf(fignu*/
- /* mu1+ v11*lc1*cost + v12*lc2*sin(t) */
- /* mu2+ v21*lc1*cost + v22*lc2*sin(t) */
- if(first==1){
- first=0;
- fprintf(ficgp,"\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 png small\nset size 0.65,0.65");
- fprintf(fichtmcov,"\n
Ellipsoids of confidence cov(p%1d%1d,p%1d%1d) expressed in year-1\
- :\
-%s%d%1d%1d-%1d%1d.png, ",k1,l1,k2,l2,\
- subdirf2(optionfilefiname,"varpijgr"), j1,k1,l1,k2,l2,\
- subdirf2(optionfilefiname,"varpijgr"), j1,k1,l1,k2,l2);
- fprintf(fichtmcov,"\n
",subdirf2(optionfilefiname,"varpijgr"), j1,k1,l1,k2,l2);
- fprintf(fichtmcov,"\n
Correlation at age %d (%.3f),",(int) age, c12);
- fprintf(ficgp,"\nset out \"%s%d%1d%1d-%1d%1d.png\"",subdirf2(optionfilefiname,"varpijgr"), j1,k1,l1,k2,l2);
- fprintf(ficgp,"\nset label \"%d\" at %11.3e,%11.3e center",(int) age, mu1,mu2);
- fprintf(ficgp,"\n# Age %d, p%1d%1d - p%1d%1d",(int) age, k1,l1,k2,l2);
- fprintf(ficgp,"\nplot [-pi:pi] %11.3e+ %.3f*(%11.3e*%11.3e*cos(t)+%11.3e*%11.3e*sin(t)), %11.3e +%.3f*(%11.3e*%11.3e*cos(t)+%11.3e*%11.3e*sin(t)) not",\
- mu1,std,v11,sqrt(lc1),v12,sqrt(lc2),\
- mu2,std,v21,sqrt(lc1),v22,sqrt(lc2));
- }else{
- first=0;
- fprintf(fichtmcov," %d (%.3f),",(int) age, c12);
- fprintf(ficgp,"\n# Age %d, p%1d%1d - p%1d%1d",(int) age, k1,l1,k2,l2);
- fprintf(ficgp,"\nset label \"%d\" at %11.3e,%11.3e center",(int) age, mu1,mu2);
- fprintf(ficgp,"\nreplot %11.3e+ %.3f*(%11.3e*%11.3e*cos(t)+%11.3e*%11.3e*sin(t)), %11.3e +%.3f*(%11.3e*%11.3e*cos(t)+%11.3e*%11.3e*sin(t)) not",\
- mu1,std,v11,sqrt(lc1),v12,sqrt(lc2),\
- mu2,std,v21,sqrt(lc1),v22,sqrt(lc2));
- }/* if first */
- } /* age mod 5 */
- } /* end loop age */
- fprintf(ficgp,"\nset out \"%s%d%1d%1d-%1d%1d.png\";replot;",subdirf2(optionfilefiname,"varpijgr"), j1,k1,l1,k2,l2);
- first=1;
- } /*l12 */
- } /* k12 */
- } /*l1 */
- }/* k1 */
- } /* loop covariates */
- }
- 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_vector(xp,1,npar);
- fclose(ficresprob);
- fclose(ficresprobcov);
- fclose(ficresprobcor);
- fflush(ficgp);
- fflush(fichtmcov);
-}
+ for(j=1; j<=(nlstate)*(nlstate+ndeath);j++)
+ for(theta=1; theta <=npar; theta++)
+ trgradg[j][theta]=gradg[theta][j];
+
+ matprod2(dnewm,trgradg,1,(nlstate)*(nlstate+ndeath),1,npar,1,npar,matcov);
+ matprod2(doldm,dnewm,1,(nlstate)*(nlstate+ndeath),1,npar,1,(nlstate)*(nlstate+ndeath),gradg);
+
+ pmij(pmmij,cov,ncovmodel,x,nlstate);
+
+ k=0;
+ for(i=1; i<=(nlstate); i++){
+ for(j=1; j<=(nlstate+ndeath);j++){
+ k=k+1;
+ mu[k][(int) age]=pmmij[i][j];
+ }
+ }
+ for(i=1;i<=(nlstate)*(nlstate+ndeath);i++)
+ for(j=1;j<=(nlstate)*(nlstate+ndeath);j++)
+ varpij[i][j][(int)age] = doldm[i][j];
+
+ /*printf("\n%d ",(int)age);
+ for (i=1; i<=(nlstate)*(nlstate+ndeath);i++){
+ printf("%e [%e ;%e] ",gm[i],gm[i]-2*sqrt(doldm[i][i]),gm[i]+2*sqrt(doldm[i][i]));
+ fprintf(ficlog,"%e [%e ;%e] ",gm[i],gm[i]-2*sqrt(doldm[i][i]),gm[i]+2*sqrt(doldm[i][i]));
+ }*/
+
+ fprintf(ficresprob,"\n%d ",(int)age);
+ fprintf(ficresprobcov,"\n%d ",(int)age);
+ fprintf(ficresprobcor,"\n%d ",(int)age);
+
+ for (i=1; i<=(nlstate)*(nlstate+ndeath);i++)
+ fprintf(ficresprob,"%11.3e (%11.3e) ",mu[i][(int) age],sqrt(varpij[i][i][(int)age]));
+ for (i=1; i<=(nlstate)*(nlstate+ndeath);i++){
+ fprintf(ficresprobcov,"%11.3e ",mu[i][(int) age]);
+ fprintf(ficresprobcor,"%11.3e ",mu[i][(int) age]);
+ }
+ i=0;
+ for (k=1; k<=(nlstate);k++){
+ for (l=1; l<=(nlstate+ndeath);l++){
+ i++;
+ fprintf(ficresprobcov,"\n%d %d-%d",(int)age,k,l);
+ fprintf(ficresprobcor,"\n%d %d-%d",(int)age,k,l);
+ for (j=1; j<=i;j++){
+ /* printf(" k=%d l=%d i=%d j=%d\n",k,l,i,j);fflush(stdout); */
+ fprintf(ficresprobcov," %11.3e",varpij[i][j][(int)age]);
+ fprintf(ficresprobcor," %11.3e",varpij[i][j][(int) age]/sqrt(varpij[i][i][(int) age])/sqrt(varpij[j][j][(int)age]));
+ }
+ }
+ }/* end of loop for state */
+ } /* end of loop for age */
+ free_vector(gp,1,(nlstate+ndeath)*(nlstate+ndeath));
+ free_vector(gm,1,(nlstate+ndeath)*(nlstate+ndeath));
+ free_matrix(trgradg,1,(nlstate+ndeath)*(nlstate+ndeath),1,npar);
+ free_matrix(gradg,1,(nlstate+ndeath)*(nlstate+ndeath),1,npar);
+
+ /* Confidence intervalle of pij */
+ /*
+ fprintf(ficgp,"\nunset parametric;unset label");
+ fprintf(ficgp,"\nset log y;unset log x; set xlabel \"Age\";set ylabel \"probability (year-1)\"");
+ fprintf(ficgp,"\nset ter png small\nset size 0.65,0.65");
+ fprintf(fichtm,"\n
Probability with confidence intervals expressed in year-1 :pijgr%s.png, ",optionfilefiname,optionfilefiname);
+ fprintf(fichtm,"\n
",optionfilefiname);
+ fprintf(ficgp,"\nset out \"pijgr%s.png\"",optionfilefiname);
+ fprintf(ficgp,"\nplot \"%s\" every :::%d::%d u 1:2 \"\%%lf",k1,k2,xfilevarprob);
+ */
+
+ /* Drawing ellipsoids of confidence of two variables p(k1-l1,k2-l2)*/
+ first1=1;first2=2;
+ for (k2=1; k2<=(nlstate);k2++){
+ for (l2=1; l2<=(nlstate+ndeath);l2++){
+ if(l2==k2) continue;
+ j=(k2-1)*(nlstate+ndeath)+l2;
+ for (k1=1; k1<=(nlstate);k1++){
+ for (l1=1; l1<=(nlstate+ndeath);l1++){
+ if(l1==k1) continue;
+ i=(k1-1)*(nlstate+ndeath)+l1;
+ if(i<=j) continue;
+ for (age=bage; age<=fage; age ++){
+ if ((int)age %5==0){
+ v1=varpij[i][i][(int)age]/stepm*YEARM/stepm*YEARM;
+ v2=varpij[j][j][(int)age]/stepm*YEARM/stepm*YEARM;
+ cv12=varpij[i][j][(int)age]/stepm*YEARM/stepm*YEARM;
+ mu1=mu[i][(int) age]/stepm*YEARM ;
+ mu2=mu[j][(int) age]/stepm*YEARM;
+ c12=cv12/sqrt(v1*v2);
+ /* Computing eigen value of matrix of covariance */
+ lc1=((v1+v2)+sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
+ lc2=((v1+v2)-sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
+ if ((lc2 <0) || (lc1 <0) ){
+ if(first2==1){
+ first1=0;
+ printf("Strange: j1=%d One eigen value of 2x2 matrix of covariance is negative, lc1=%11.3e, lc2=%11.3e, v1=%11.3e, v2=%11.3e, cv12=%11.3e.\n It means that the matrix was not well estimated (varpij), for i=%2d, j=%2d, age=%4d .\n See files %s and %s. Probably WRONG RESULTS. See log file for details...\n", j1, lc1, lc2, v1, v2, cv12, i, j, (int)age,fileresprobcov, fileresprobcor);
+ }
+ fprintf(ficlog,"Strange: j1=%d One eigen value of 2x2 matrix of covariance is negative, lc1=%11.3e, lc2=%11.3e, v1=%11.3e, v2=%11.3e, cv12=%11.3e.\n It means that the matrix was not well estimated (varpij), for i=%2d, j=%2d, age=%4d .\n See files %s and %s. Probably WRONG RESULTS.\n", j1, lc1, lc2, v1, v2, cv12, i, j, (int)age,fileresprobcov, fileresprobcor);fflush(ficlog);
+ /* lc1=fabs(lc1); */ /* If we want to have them positive */
+ /* lc2=fabs(lc2); */
+ }
+
+ /* Eigen vectors */
+ 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
Ellipsoids of confidence cov(p%1d%1d,p%1d%1d) expressed in year-1\
+ : \
+%s_%d%1d%1d-%1d%1d.svg, ",k1,l1,k2,l2,\
+ subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2, \
+ subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
+ fprintf(fichtmcov,"\n
",subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
+ fprintf(fichtmcov,"\n
Correlation at age %d (%.3f),",(int) age, c12);
+ fprintf(ficgp,"\nset out \"%s_%d%1d%1d-%1d%1d.svg\"",subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
+ fprintf(ficgp,"\nset label \"%d\" at %11.3e,%11.3e center",(int) age, mu1,mu2);
+ fprintf(ficgp,"\n# Age %d, p%1d%1d - p%1d%1d",(int) age, k1,l1,k2,l2);
+ fprintf(ficgp,"\nplot [-pi:pi] %11.3e+ %.3f*(%11.3e*%11.3e*cos(t)+%11.3e*%11.3e*sin(t)), %11.3e +%.3f*(%11.3e*%11.3e*cos(t)+%11.3e*%11.3e*sin(t)) not", \
+ mu1,std,v11,sqrt(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 */
+ 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 fileres[], char title[], char datafile[], int firstpass, \
+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 estepm ,\
- double jprev1, double mprev1,double anprev1, \
- double jprev2, double mprev2,double anprev2){
- int jj1, k1, i1, cpt;
-
- fprintf(fichtm,"