--- imach/src/imach.c 2022/09/16 13:40:11 1.345 +++ imach/src/imach.c 2024/05/12 20:29:32 1.361 @@ -1,6 +1,60 @@ -/* $Id: imach.c,v 1.345 2022/09/16 13:40:11 brouard Exp $ +/* $Id: imach.c,v 1.361 2024/05/12 20:29:32 brouard Exp $ $State: Exp $ $Log: imach.c,v $ + Revision 1.361 2024/05/12 20:29:32 brouard + Summary: Version 0.99s5 + + * src/imach.c Version 0.99s5 In fact, the covariance of total life + expectancy e.. with a partial life expectancy e.j is high, + therefore the complete matrix of variance covariance has to be + included in the formula of the standard error of the proportion of + total life expectancy spent in a specific state: + var(X/Y)=mu_x^2/mu_y^2*(sigma_x^2/mu_x^2 -2 + sigma_xy/mu_x/mu_y+sigma^2/mu_y^2). Also an error with mle=-3 + made the program core dump. It is fixed in this version. + + Revision 1.360 2024/04/30 10:59:22 brouard + Summary: Version 0.99s4 and estimation of std of e.j/e.. + + Revision 1.359 2024/04/24 21:21:17 brouard + Summary: First IMaCh version using Brent Praxis software based on Buckhardt and Gegenfürtner C codes + + Revision 1.6 2024/04/24 21:10:29 brouard + Summary: First IMaCh version using Brent Praxis software based on Buckhardt and Gegenfürtner C codes + + Revision 1.5 2023/10/09 09:10:01 brouard + Summary: trying to reconsider + + Revision 1.4 2023/06/22 12:50:51 brouard + Summary: stil on going + + Revision 1.3 2023/06/22 11:28:07 brouard + *** empty log message *** + + Revision 1.2 2023/06/22 11:22:40 brouard + Summary: with svd but not working yet + + Revision 1.353 2023/05/08 18:48:22 brouard + *** empty log message *** + + Revision 1.352 2023/04/29 10:46:21 brouard + *** empty log message *** + + Revision 1.351 2023/04/29 10:43:47 brouard + Summary: 099r45 + + Revision 1.350 2023/04/24 11:38:06 brouard + *** empty log message *** + + Revision 1.349 2023/01/31 09:19:37 brouard + Summary: Improvements in models with age*Vn*Vm + + Revision 1.347 2022/09/18 14:36:44 brouard + Summary: version 0.99r42 + + Revision 1.346 2022/09/16 13:52:36 brouard + * src/imach.c (Module): 0.99r41 Was an error when product of timevarying and fixed. Using FixedV[of name] now. Thank you Feinuo + Revision 1.345 2022/09/16 13:40:11 brouard Summary: Version 0.99r41 @@ -1257,6 +1311,8 @@ Important routines /* #define POWELLORIGINAL /\* Don't use Directest to decide new direction but original Powell test *\/ */ /* #define MNBRAKORIGINAL /\* Don't use mnbrak fix *\/ */ /* #define FLATSUP *//* Suppresses directions where likelihood is flat */ +/* #define POWELLORIGINCONJUGATE /\* Don't use conjugate but biggest decrease if valuable *\/ */ +/* #define NOTMINFIT */ #include #include @@ -1308,7 +1364,7 @@ typedef struct { /* #include */ /* #define _(String) gettext (String) */ -#define MAXLINE 2048 /* Was 256 and 1024. Overflow with 312 with 2 states and 4 covariates. Should be ok */ +#define MAXLINE 16384 /* Was 256 and 1024 and 2048. Overflow with 312 with 2 states and 4 covariates. Should be ok */ #define GNUPLOTPROGRAM "gnuplot" #define GNUPLOTVERSION 5.1 @@ -1319,7 +1375,7 @@ double gnuplotversion=GNUPLOTVERSION; #define GLOCK_ERROR_NOPATH -1 /* empty path */ #define GLOCK_ERROR_GETCWD -2 /* cannot get cwd */ -#define MAXPARM 128 /**< Maximum number of parameters for the optimization */ +#define MAXPARM 216 /**< Maximum number of parameters for the optimization was 128 */ #define NPARMAX 64 /**< (nlstate+ndeath-1)*nlstate*ncovmodel */ #define NINTERVMAX 8 @@ -1349,12 +1405,12 @@ double gnuplotversion=GNUPLOTVERSION; #define ODIRSEPARATOR '\\' #endif -/* $Id: imach.c,v 1.345 2022/09/16 13:40:11 brouard Exp $ */ +/* $Id: imach.c,v 1.361 2024/05/12 20:29:32 brouard Exp $ */ /* $State: Exp $ */ #include "version.h" char version[]=__IMACH_VERSION__; -char copyright[]="September 2022,INED-EUROREVES-Institut de longevite-Japan Society for the Promotion of Science (Grant-in-Aid for Scientific Research 25293121), Intel Software 2015-2020, Nihon University 2021-202, INED 2000-2022"; -char fullversion[]="$Revision: 1.345 $ $Date: 2022/09/16 13:40:11 $"; +char copyright[]="April 2024,INED-EUROREVES-Institut de longevite-Japan Society for the Promotion of Science (Grant-in-Aid for Scientific Research 25293121), Intel Software 2015-2020, Nihon University 2021-202, INED 2000-2024"; +char fullversion[]="$Revision: 1.361 $ $Date: 2024/05/12 20:29:32 $"; char strstart[80]; char optionfilext[10], optionfilefiname[FILENAMELENGTH]; int erreur=0, nberr=0, nbwarn=0; /* Error number, number of errors number of warnings */ @@ -1367,12 +1423,18 @@ int cptcovt=0; /**< cptcovt: total numbe int cptcovs=0; /**< cptcovs number of SIMPLE covariates in the model V2+V1 =2 (dummy or quantit or time varying) */ int cptcovsnq=0; /**< cptcovsnq number of SIMPLE covariates in the model but non quantitative V2+V1 =2 */ int cptcovage=0; /**< Number of covariates with age: V3*age only =1 */ +int cptcovprodage=0; /**< Number of fixed covariates with age: V3*age or V2*V3*age 1 */ +int cptcovprodvage=0; /**< Number of varying covariates with age: V7*age or V7*V6*age */ +int cptcovdageprod=0; /**< Number of doubleproducts with age, since 0.99r44 only: age*Vn*Vm for gnuplot printing*/ int cptcovprodnoage=0; /**< Number of covariate products without age */ int cptcoveff=0; /* Total number of single dummy covariates (fixed or time varying) to vary for printing results (2**cptcoveff combinations of dummies)(computed in tricode as cptcov) */ int ncovf=0; /* Total number of effective fixed covariates (dummy or quantitative) in the model */ int ncovv=0; /* Total number of effective (wave) varying covariates (dummy or quantitative) in the model */ int ncovvt=0; /* Total number of effective (wave) varying covariates (dummy or quantitative or products [without age]) in the model */ -int ncova=0; /* Total number of effective (wave and stepm) varying with age covariates (dummy of quantitative) in the model */ +int ncovvta=0; /* +age*V6 + age*V7+ age*V6*V3 +age*V7*V3 + age*V6*V4 +age*V7*V4 Total number of expandend products [with age]) in the model */ +int ncovta=0; /*age*V3*V2 +age*V2+agev3+ageV4 +age*V6 + age*V7+ age*V6*V3 +age*V7*V3 + age*V6*V4 +age*V7*V4 Total number of expandend products [with age]) in the model */ +int ncova=0; /* Total number of effective (wave and stepm) varying with age covariates (single or product, dummy or quantitative) in the model */ +int ncovva=0; /* +age*V6 + age*V7+ge*V6*V3 +age*V7*V3 + age*V6*V4 +age*V7*V4 Total number of effective (wave and stepm) varying with age covariates (single or product, dummy or quantitative) in the model */ int nsd=0; /**< Total number of single dummy variables (output) */ int nsq=0; /**< Total number of single quantitative variables (output) */ int ncoveff=0; /* Total number of effective fixed dummy covariates in the model */ @@ -1395,7 +1457,8 @@ int *wav; /* Number of waves for this in int maxwav=0; /* Maxim number of waves */ int jmin=0, jmax=0; /* min, max spacing between 2 waves */ int ijmin=0, ijmax=0; /* Individuals having jmin and jmax */ -int gipmx=0, gsw=0; /* Global variables on the number of contributions +int gipmx = 0; +double gsw = 0; /* Global variables on the number of contributions to the likelihood and the sum of weights (done by funcone)*/ int mle=1, weightopt=0; int **mw; /* mw[mi][i] is number of the mi wave for this individual */ @@ -1459,6 +1522,7 @@ extern time_t time(); struct tm start_time, end_time, curr_time, last_time, forecast_time; time_t rstart_time, rend_time, rcurr_time, rlast_time, rforecast_time; /* raw time */ +time_t rlast_btime; /* raw time */ struct tm tm; char strcurr[80], strfor[80]; @@ -1562,27 +1626,32 @@ int **nbcode, *Tvar; /**< model=V2 => Tv # 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 */ -/* kmodel 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 */ -/*TnsdVar[Tvar] 1 2 3 */ -/*Tvaraff[nsd] 4 3 1 */ /* ID of single dummy cova fixed or timevary*/ -/*TvarsD[nsd] 4 3 1 */ /* ID of single dummy cova fixed or timevary*/ -/*TvarsDind[nsd] 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 */ +/* V5+V4+ V3+V4*V3 +V5*age+V2 +V1*V2+V1*age+V1+V4*V3*age */ +/* kmodel 1 2 3 4 5 6 7 8 9 10 */ +/*Typevar[k]= 0 0 0 2 1 0 2 1 0 3 *//*0 for simple covariate (dummy, quantitative,*/ + /* fixed or varying), 1 for age product, 2 for*/ + /* product without age, 3 for age and double product */ +/*Dummy[k]= 1 0 0 1 3 1 1 2 0 3 *//*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 6 */ +/* nsd 1 2 3 */ /* Counting single dummies covar fixed or tv */ +/*TnsdVar[Tvar] 1 2 3 */ +/*Tvaraff[nsd] 4 3 1 */ /* ID of single dummy cova fixed or timevary*/ +/*TvarsD[nsd] 4 3 1 */ /* ID of single dummy cova fixed or timevary*/ +/*TvarsDind[nsd] 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 3 */ /* Counting cov*age in the model equation */ +/* Tage[cptcovage]=k 5 8 10 */ /* Position in the model of ith cov*age */ +/* model="V2+V3+V4+V6+V7+V6*V2+V7*V2+V6*V3+V7*V3+V6*V4+V7*V4+age*V2+age*V3+age*V4+age*V6+age*V7+age*V6*V2+age*V6*V3+age*V7*V3+age*V6*V4+age*V7*V4\r"*/ +/* p Tvard[1][1]@21 = {6, 2, 7, 2, 6, 3, 7, 3, 6, 4, 7, 4, 0, 0, 0, 0, 0, 0, 0, 0, 0}*/ +/* p Tvard[2][1]@21 = {7, 2, 6, 3, 7, 3, 6, 4, 7, 4, 0 } */ +/* p Tvardk[1][1]@24 = {0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 6, 2, 7, 2, 6, 3, 7, 3, 6, 4, 7, 4, 0, 0}*/ +/* p Tvardk[1][1]@22 = {0, 0, 0, 0, 0, 0, 0, 0, 6, 2, 7, 2, 6, 3, 7, 3, 6, 4, 7, 4, 0, 0} */ +/* Tvard[1][1]@4={4,3,1,2} V4*V3 V1*V2 */ /* Position in model of the ith prod without age */ /* Tvardk[4][1]=4;Tvardk[4][2]=3;Tvardk[7][1]=1;Tvardk[7][2]=2 */ /* Variables of a prod at position in the model equation*/ /* 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) */ @@ -1632,14 +1701,18 @@ int *TvarVQ; /* TvarVQ[1]=V5 in V5+V4+V3 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 *TvarVV; /* We count ncovvt time varying covariates (single or products without age) and put their name into TvarVV */ int *TvarVVind; /* We count ncovvt time varying covariates (single or products without age) and put their name into TvarVV */ +int *TvarVVA; /* We count ncovvt time varying covariates (single or products with age) and put their name into TvarVVA */ +int *TvarVVAind; /* We count ncovvt time varying covariates (single or products without age) and put their name into TvarVV */ +int *TvarAVVA; /* We count ALL ncovta time varying covariates (single or products with age) and put their name into TvarVVA */ +int *TvarAVVAind; /* We count ALL ncovta time varying covariates (single or products without age) and put their name into TvarVV */ /*# ID V1 V2 weight birth death 1st s1 V3 V4 V5 2nd s2 */ - /* model V1+V3+age*V1+age*V3+V1*V3 */ - /* Tvar={1, 3, 1, 3, 6}, the 6 comes from the fact that there are already V1, V2, V3, V4, V5 native covariates */ - /* TvarVV={3,1,3}, for V3 and then the product V1*V3 is decomposed into V1 and V3 */ - /* TvarVVind={2,5,5}, for V3 and then the product V1*V3 is decomposed into V1 and V3 */ + /* model V1+V3+age*V1+age*V3+V1*V3 + V1*V3*age */ + /* Tvar={1, 3, 1, 3, 6, 6}, the 6 comes from the fact that there are already V1, V2, V3, V4, V5 native covariates */ + /* TvarVV={3,1,3,1,3}, for V3 and then the product V1*V3 is decomposed into V1 and V3 */ + /* TvarVVind={2,5,5,6,6}, for V3 and then the product V1*V3 is decomposed into V1 and V3 and V1*V3*age into 6,6 */ 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 *Typevar; /**< 0 for simple covariate (dummy, quantitative, fixed or varying), 1 for age product, 2 for product, 3 age*Vn*Vm */ 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 */ @@ -1776,6 +1849,20 @@ char *trimbb(char *out, char *in) return s; } +char *trimbtab(char *out, char *in) +{ /* Trim blanks or tabs in line but keeps first blanks if line starts with blanks */ + char *s; + s=out; + while (*in != '\0'){ + while( (*in == ' ' || *in == '\t')){ /* && *(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' *\/ */ @@ -1802,19 +1889,19 @@ char *trimbb(char *out, char *in) 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" */ + /* in="V1+V1*age+age*age+V2", chain="+age*age" out="V1+V1*age+V2" */ 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); + strcpy (out, in); /* out="V1+V1*age+age*age+V2" */ + strloc = strstr(out, chain); /* strloc points to out at "+age*age+V2" */ + printf("Bef strloc=%s chain=%s out=%s \n", strloc, chain, out); /* strloc=+age*age+V2 chain="+age*age", out="V1+V1*age+age*age+V2" */ 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));*/ + /* will affect out */ /* strloc+strlen(chain)=|+V2 = "V1+V1*age+age*age|+V2" */ /* Will also work in Unicodek */ + memmove(strloc,strloc+strlen(chain), strlen(strloc+strlen(chain))+1); /* move number of bytes corresponding to the length of "+V2" which is 3, plus one is 4 (including the null)*/ + /* equivalent to strcpy (strloc, strloc +strlen(chain)) if no overlap; Copies from "+V2" to V1+V1*age+ */ } - printf("Aft strloc=%s chain=%s in=%s out=%s \n", strloc, chain, in, out); + printf("Aft strloc=%s chain=%s in=%s out=%s \n", strloc, chain, in, out); /* strloc=+V2 chain="+age*age", in="V1+V1*age+age*age+V2", out="V1+V1*age+V2" */ return out; } @@ -1822,7 +1909,7 @@ char *substrchaine(char *out, char *in, 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') + and alocc starts after first occurence of char 'occ' : ex cutl(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 */ @@ -1888,6 +1975,28 @@ int nbocc(char *s, char occ) return j; } +int nboccstr(char *textin, char *chain) +{ + /* Counts the number of occurence of "chain" in string textin */ + /* in="+V7*V4+age*V2+age*V3+age*V4" chain="age" */ + char *strloc; + + int i,j=0; + + i=0; + + strloc=textin; /* strloc points to "^+V7*V4+age+..." in textin */ + for(;;) { + strloc= strstr(strloc,chain); /* strloc points to first character of chain in textin if found. Example strloc points^ to "+V7*V4+^age" in textin */ + if(strloc != NULL){ + strloc = strloc+strlen(chain); /* strloc points to "+V7*V4+age^" in textin */ + j++; + }else + break; + } + return j; + +} /* void cutv(char *u,char *v, char*t, char occ) */ /* { */ /* /\* cuts string t into u and v where u ends before last occurence of char 'occ' */ @@ -2536,6 +2645,1512 @@ void linmin(double p[], double xi[], int free_vector(pcom,1,n); } +/**** praxis gegen ****/ + +/* This has been tested by Visual C from Microsoft and works */ +/* meaning tha valgrind could be wrong */ +/*********************************************************************/ +/* f u n c t i o n p r a x i s */ +/* */ +/* praxis is a general purpose routine for the minimization of a */ +/* function in several variables. the algorithm used is a modifi- */ +/* cation of conjugate gradient search method by powell. the changes */ +/* are due to r.p. brent, who gives an algol-w program, which served */ +/* as a basis for this function. */ +/* */ +/* references: */ +/* - powell, m.j.d., 1964. an efficient method for finding */ +/* the minimum of a function in several variables without */ +/* calculating derivatives, computer journal, 7, 155-162 */ +/* - brent, r.p., 1973. algorithms for minimization without */ +/* derivatives, prentice hall, englewood cliffs. */ +/* */ +/* problems, suggestions or improvements are always wellcome */ +/* karl gegenfurtner 07/08/87 */ +/* c - version */ +/*********************************************************************/ +/* */ +/* usage: min = praxis(tol, macheps, h, n, prin, x, func) */ +/* macheps has been suppressed because it is replaced by DBL_EPSILON */ +/* and if it was an argument of praxis (as it is in original brent) */ +/* it should be declared external */ +/* usage: min = praxis(tol, h, n, prin, x, func) */ +/* was min = praxis(fun, x, n); */ +/* */ +/* fun the function to be minimized. fun is called from */ +/* praxis with x and n as arguments */ +/* x a double array containing the initial guesses for */ +/* the minimum, which will contain the solution on */ +/* return */ +/* n an integer specifying the number of unknown */ +/* parameters */ +/* min praxis returns the least calculated value of fun */ +/* */ +/* some additional global variables control some more aspects of */ +/* the inner workings of praxis. setting them is optional, they */ +/* are all set to some reasonable default values given below. */ +/* */ +/* prin controls the printed output from the routine. */ +/* 0 -> no output */ +/* 1 -> print only starting and final values */ +/* 2 -> detailed map of the minimization process */ +/* 3 -> print also eigenvalues and vectors of the */ +/* search directions */ +/* the default value is 1 */ +/* tol is the tolerance allowed for the precision of the */ +/* solution. praxis returns if the criterion */ +/* 2 * ||x[k]-x[k-1]|| <= sqrt(macheps) * ||x[k]|| + tol */ +/* is fulfilled more than ktm times. */ +/* the default value depends on the machine precision */ +/* ktm see just above. default is 1, and a value of 4 leads */ +/* to a very(!) cautious stopping criterion. */ +/* h0 or step is a steplength parameter and should be set equal */ +/* to the expected distance from the solution. */ +/* exceptionally small or large values of step lead to */ +/* slower convergence on the first few iterations */ +/* the default value for step is 1.0 */ +/* scbd is a scaling parameter. 1.0 is the default and */ +/* indicates no scaling. if the scales for the different */ +/* parameters are very different, scbd should be set to */ +/* a value of about 10.0. */ +/* illc should be set to true (1) if the problem is known to */ +/* be ill-conditioned. the default is false (0). this */ +/* variable is automatically set, when praxis finds */ +/* the problem to be ill-conditioned during iterations. */ +/* maxfun is the maximum number of calls to fun allowed. praxis */ +/* will return after maxfun calls to fun even when the */ +/* minimum is not yet found. the default value of 0 */ +/* indicates no limit on the number of calls. */ +/* this return condition is only checked every n */ +/* iterations. */ +/* */ +/*********************************************************************/ + +#include +#include +#include +#include /* for DBL_EPSILON */ +/* #include "machine.h" */ + + +/* extern void minfit(int n, double eps, double tol, double **ab, double q[]); */ +/* extern void minfit(int n, double eps, double tol, double ab[N][N], double q[]); */ +/* control parameters */ +/* control parameters */ +#define SQREPSILON 1.0e-19 +/* #define EPSILON 1.0e-8 */ /* in main */ + +double tol = SQREPSILON, + scbd = 1.0, + step = 1.0; +int ktm = 1, + /* prin = 2, */ + maxfun = 0, + illc = 0; + +/* some global variables */ +static int i, j, k, k2, nl, nf, kl, kt; +/* static double s; */ +double sl, dn, dmin, + fx, f1, lds, ldt, sf, df, + qf1, qd0, qd1, qa, qb, qc, + m2, m4, small_windows, vsmall, large, + vlarge, ldfac, t2; +/* static double d[N], y[N], z[N], */ +/* q0[N], q1[N], v[N][N]; */ + +static double *d, *y, *z; +static double *q0, *q1, **v; +double *tflin; /* used in flin: return (*fun)(tflin, n); */ +double *e; /* used in minfit, don't konw how to free memory and thus made global */ +/* static double s, sl, dn, dmin, */ +/* fx, f1, lds, ldt, sf, df, */ +/* qf1, qd0, qd1, qa, qb, qc, */ +/* m2, m4, small, vsmall, large, */ +/* vlarge, ldfac, t2; */ +/* static double d[N], y[N], z[N], */ +/* q0[N], q1[N], v[N][N]; */ + +/* these will be set by praxis to point to it's arguments */ +static int prin; /* added */ +static int n; +static double *x; +static double (*fun)(); +/* static double (*fun)(double *x, int n); */ + +/* these will be set by praxis to the global control parameters */ +/* static double h, macheps, t; */ +extern double macheps; +static double h; +static double t; + +static double +drandom() /* return random no between 0 and 1 */ +{ + return (double)(rand()%(8192*2))/(double)(8192*2); +} + +static void sort() /* d and v in descending order */ +{ + int k, i, j; + double s; + + for (i=1; i<=n-1; i++) { + k = i; s = d[i]; + for (j=i+1; j<=n; j++) { + if (d[j] > s) { + k = j; + s = d[j]; + } + } + if (k > i) { + d[k] = d[i]; + d[i] = s; + for (j=1; j<=n; j++) { + s = v[j][i]; + v[j][i] = v[j][k]; + v[j][k] = s; + } + } + } +} + +double randbrent ( int *naught ) +{ + double ran1, ran3[127], half; + int ran2, q, r, i, j; + int init=0; /* false */ + double rr; + /* REAL*8 RAN1,RAN3(127),HALF */ + + /* INTEGER RAN2,Q,R */ + /* LOGICAL INIT */ + /* DATA INIT/.FALSE./ */ + /* IF (INIT) GO TO 3 */ + if(!init){ +/* R = MOD(NAUGHT,8190) + 1 *//* 1804289383 rand () */ + r = *naught % 8190 + 1;/* printf(" naught r %d %d",*naught,r); */ + ran2=127; + for(i=ran2; i>0; i--){ +/* RAN2 = 128 */ +/* DO 2 I=1,127 */ + ran2 = ran2-1; +/* RAN2 = RAN2 - 1 */ + ran1 = -pow(2.0,55); +/* RAN1 = -2.D0**55 */ +/* DO 1 J=1,7 */ + for(j=1; j<=7;j++){ +/* R = MOD(1756*R,8191) */ + r = (1756*r) % 8191;/* printf(" i=%d (1756*r)%8191=%d",j,r); */ + q=r/32; +/* Q = R/32 */ +/* 1 RAN1 = (RAN1 + Q)*(1.0D0/256) */ + ran1 =(ran1+q)*(1.0/256); + } +/* 2 RAN3(RAN2) = RAN1 */ + ran3[ran2] = ran1; /* printf(" ran2=%d ran1=%.7g \n",ran2,ran1); */ + } +/* INIT = .TRUE. */ + init=1; +/* 3 IF (RAN2.EQ.1) RAN2 = 128 */ + } + if(ran2 == 0) ran2 = 126; + else ran2 = ran2 -1; + /* RAN2 = RAN2 - 1 */ + /* RAN1 = RAN1 + RAN3(RAN2) */ + ran1 = ran1 + ran3[ran2];/* printf("BIS ran2=%d ran1=%.7g \n",ran2,ran1); */ + half= 0.5; + /* HALF = .5D0 */ + /* IF (RAN1.GE.0.D0) HALF = -HALF */ + if(ran1 >= 0.) half =-half; + ran1 = ran1 +half; + ran3[ran2] = ran1; + rr= ran1+0.5; + /* RAN1 = RAN1 + HALF */ + /* RAN3(RAN2) = RAN1 */ + /* RANDOM = RAN1 + .5D0 */ +/* r = ( ( double ) ( *seed ) ) * 4.656612875E-10; */ + return rr; +} +static void matprint(char *s, double **v, int m, int n) +/* char *s; */ +/* double v[N][N]; */ +{ +#define INCX 8 + int i; + + int i2hi; + int ihi; + int ilo; + int i2lo; + int jlo=1; + int j; + int j2hi; + int jhi; + int j2lo; + ilo=1; + ihi=n; + jlo=1; + jhi=n; + + printf ("\n" ); + printf ("%s\n", s ); + for ( j2lo = jlo; j2lo <= jhi; j2lo = j2lo + INCX ) + { + j2hi = j2lo + INCX - 1; + if ( n < j2hi ) + { + j2hi = n; + } + if ( jhi < j2hi ) + { + j2hi = jhi; + } + + /* fprintf ( ficlog, "\n" ); */ + printf ("\n" ); +/* + For each column J in the current range... + + Write the header. +*/ + /* fprintf ( ficlog, " Col: "); */ + printf ("Col:"); + for ( j = j2lo; j <= j2hi; j++ ) + { + /* fprintf ( ficlog, " %7d ", j - 1 ); */ + /* printf (" %9d ", j - 1 ); */ + printf (" %9d ", j ); + } + /* fprintf ( ficlog, "\n" ); */ + /* fprintf ( ficlog, " Row\n" ); */ + /* fprintf ( ficlog, "\n" ); */ + printf ("\n" ); + printf (" Row\n" ); + printf ("\n" ); +/* + Determine the range of the rows in this strip. +*/ + if ( 1 < ilo ){ + i2lo = ilo; + }else{ + i2lo = 1; + } + if ( m < ihi ){ + i2hi = m; + }else{ + i2hi = ihi; + } + + for ( i = i2lo; i <= i2hi; i++ ){ +/* + Print out (up to) 5 entries in row I, that lie in the current strip. +*/ + /* fprintf ( ficlog, "%5d:", i - 1 ); */ + /* printf ("%5d:", i - 1 ); */ + printf ("%5d:", i ); + for ( j = j2lo; j <= j2hi; j++ ) + { + /* fprintf ( ficlog, " %14g", a[i-1+(j-1)*m] ); */ + /* printf ("%14.7g ", a[i-1+(j-1)*m] ); */ + /* printf("%14.7f ", v[i-1][j-1]); */ + printf("%14.7f ", v[i][j]); + /* fprintf ( stdout, " %14g", a[i-1+(j-1)*m] ); */ + } + /* fprintf ( ficlog, "\n" ); */ + printf ("\n" ); + } + } + + /* printf("%s\n", s); */ + /* for (k=0; k 0) { /* linear search */ + /* for (i=0; i F1. NITS CONTROLS THE NUMBER OF TIMES */ + /* AN ATTEMPT IS MADE TO HALVE THE INTERVAL. */ + /* SIDE EFFECTS: USES AND ALTERS X, FX, NF, NL. */ + /* IF J < 1 USES VARIABLES Q... . */ + /* USES H, N, T, M2, M4, LDT, DMIN, MACHEPS; */ + int k, i, dz; + double x2, xm, f0, f2, fm, d1, t2, sf1, sx1; + double s; + double macheps; + macheps=pow(16.0,-13.0); + sf1 = f1; sx1 = *x1; + k = 0; xm = 0.0; fm = f0 = fx; dz = *d2 < macheps; + /* h=1.0;*/ /* To be revised */ +#ifdef DEBUGPRAX + /* printf("min macheps=%14g h=%14g step=%14g t=%14g fx=%14g\n",macheps,h, step,t, fx); */ + /* Where is fx coming from */ + printf(" min macheps=%14g h=%14g t=%14g fx=%.9lf dirj=%d\n",macheps, h, t, fx, j); + matprint(" min vectors:",v,n,n); +#endif + /* find step size */ + s = 0.; + /* for (i=0; i s) t2 = s; + if (t2 < small_windows) t2 = small_windows; + if (t2 > 0.01*h) t2 = 0.01 * h; + if (fk && f1 <= fm) { + xm = *x1; + fm = f1; + } +#ifdef DEBUGPRAX + printf(" additional flin X1=%14.7f t2=%14.7f *f1=%14.7f fm=%14.7f fk=%d\n",*x1,t2,f1,fm,fk); +#endif + if (!fk || fabs(*x1) < t2) { + *x1 = (*x1 >= 0 ? t2 : -t2); + /* *x1 = (*x1 > 0 ? t2 : -t2); */ /* kind of error */ +#ifdef DEBUGPRAX + printf(" additional flin X1=%16.10e dirj=%d fk=%d\n",*x1, j, fk); +#endif + f1 = flin(*x1, j); +#ifdef DEBUGPRAX + printf(" after flin f1=%18.12e dirj=%d fk=%d\n",f1, j,fk); +#endif + } + if (f1 <= fm) { + xm = *x1; + fm = f1; + } +L0: /*L0 loop or next */ +/* + Evaluate FLIN at another point and estimate the second derivative. +*/ + if (dz) { + x2 = (f0 < f1 ? -(*x1) : 2*(*x1)); +#ifdef DEBUGPRAX + printf(" additional second flin x2=%14.8e x1=%14.8e f0=%14.8e f1=%18.12e dirj=%d\n",x2,*x1,f0,f1,j); +#endif + f2 = flin(x2, j); +#ifdef DEBUGPRAX + printf(" additional second flin x2=%16.10e x1=%16.10e f1=%18.12e f0=%18.10e f2=%18.10e fm=%18.10e\n",x2, *x1, f1,f0,f2,fm); +#endif + if (f2 <= fm) { + xm = x2; + fm = f2; + } + /* d2 is the curvature or double difference f1 doesn't seem to be accurately computed */ + *d2 = (x2*(f1-f0) - (*x1)*(f2-f0))/((*x1)*x2*((*x1)-x2)); +#ifdef DEBUGPRAX + double d11,d12; + d11=(f1-f0)/(*x1);d12=(f2-f0)/x2; + printf(" d11=%18.12e d12=%18.12e d11-d12=%18.12e x1-x2=%18.12e (d11-d12)/(x2-(*x1))=%18.12e\n", d11 ,d12, d11-d12, x2-(*x1), (d11-d12)/(x2-(*x1))); + printf(" original computing f1=%18.12e *d2=%16.10e f0=%18.12e f1-f0=%16.10e f2-f0=%16.10e\n",f1,*d2,f0,f1-f0, f2-f0); + double ff1=7.783920622852e+04; + double f1mf0=9.0344736236e-05; + *d2 = (f1mf0)/ (*x1)/((*x1)-x2) - (f2-f0)/x2/((*x1)-x2); + /* *d2 = (ff1-f0)/ (*x1)/((*x1)-x2) - (f2-f0)/x2/((*x1)-x2); */ + printf(" simpliff computing *d2=%16.10e f1mf0=%18.12e,f1=f0+f1mf0=%18.12e\n",*d2,f1mf0,f0+f1mf0); + *d2 = ((f1-f0)/ (*x1) - (f2-f0)/x2)/((*x1)-x2); + printf(" overlifi computing *d2=%16.10e\n",*d2); +#endif + *d2 = ((f1-f0)/ (*x1) - (f2-f0)/x2)/((*x1)-x2); + } +#ifdef DEBUGPRAX + printf(" additional second flin xm=%14.8e fm=%14.8e *d2=%14.8e\n",xm, fm,*d2); +#endif + /* + Estimate the first derivative at 0. + */ + d1 = (f1-f0)/(*x1) - *x1**d2; dz = 1; + /* + Predict the minimum. + */ + if (*d2 <= small_windows) { + x2 = (d1 < 0 ? h : -h); + } + else { + x2 = - 0.5*d1/(*d2); + } +#ifdef DEBUGPRAX + printf(" AT d1=%14.8e d2=%14.8e small=%14.8e dz=%d x1=%14.8e x2=%14.8e\n",d1,*d2,small_windows,dz,*x1,x2); +#endif + if (fabs(x2) > h) + x2 = (x2 > 0 ? h : -h); +L1: /* L1 or try loop */ +#ifdef DEBUGPRAX + printf(" AT predicted minimum flin x2=%14.8e x1=%14.8e K=%14d NITS=%14d dirj=%d\n",x2,*x1,k,nits,j); +#endif + f2 = flin(x2, j); /* x[i]+x2*v[i][j] */ +#ifdef DEBUGPRAX + printf(" after flin f0=%14.8e f1=%14.8e f2=%14.8e fm=%14.8e\n",f0,f1,f2, fm); +#endif + if ((k < nits) && (f2 > f0)) { +#ifdef DEBUGPRAX + printf(" NO SUCCESS SO TRY AGAIN;\n"); +#endif + k++; + if ((f0 < f1) && (*x1*x2 > 0.0)) + goto L0; /* or next */ + x2 *= 0.5; + goto L1; + } + nl++; +#ifdef DEBUGPRAX + printf(" bebeBE end of min x1=%14.8e x2=%14.8e f1=%14.8e f2=%14.8e f0=%14.8e fm=%14.8e d2=%14.8e\n",*x1, x2, f1, f2, f0, fm, *d2); +#endif + if (f2 > fm) x2 = xm; else fm = f2; + if (fabs(x2*(x2-*x1)) > small_windows) { + *d2 = (x2*(f1-f0) - *x1*(fm-f0))/(*x1*x2*(*x1-x2)); + } + else { + if (k > 0) *d2 = 0; + } +#ifdef DEBUGPRAX + printf(" bebe end of min x1=%14.8e fx=%14.8e d2=%14.8e\n",*x1, fx, *d2); +#endif + if (*d2 <= small_windows) *d2 = small_windows; + *x1 = x2; fx = fm; + if (sf1 < fx) { + fx = sf1; + *x1 = sx1; + } + /* + Update X for linear search. + */ +#ifdef DEBUGPRAX + printf(" end of min x1=%14.8e fx=%14.8e d2=%14.8e\n",*x1, fx, *d2); +#endif + + /* if (j != -1) */ + /* for (i=0; i 0) + for (i=1; i<=n; i++) + x[i] += (*x1)*v[i][j]; +} + +void quad() /* look for a minimum along the curve q0, q1, q2 */ +{ + int i; + double l, s; + + s = fx; fx = qf1; qf1 = s; qd1 = 0.0; + /* for (i=0; i0.0 && qd1>0.0 &&nl>=3*n*n) { +#ifdef DEBUGPRAX + printf(" QUAD before min value=%14.8e \n",qf1); +#endif + /* min(-1, 2, &s, &l, qf1, 1); */ + minny(0, 2, &s, &l, qf1, 1); + qa = l*(l-qd1)/(qd0*(qd0+qd1)); + qb = (l+qd0)*(qd1-l)/(qd0*qd1); + qc = l*(l+qd0)/(qd1*(qd0+qd1)); + } + else { + fx = qf1; qa = qb = 0.0; qc = 1.0; + } +#ifdef DEBUGPRAX + printf("after eventual min qd0=%14.8e qd1=%14.8e nl=%d\n",qd0, qd1,nl); +#endif + qd0 = qd1; + /* for (i=0; i x) x = y; +#ifdef DEBUGPRAX + printf(" I Y=%d %.7g",i,y); +#endif +#ifdef DEBUGPRAX + printf(" i=%d e(i) %.7g",i,e[i]); +#endif + } /* end i */ + /* + Accumulation of right hand transformations */ + /* for (i=n-1; i >= 0; i--) { */ /* FOR I := N STEP -1 UNTIL 1 DO */ + /* We should avoid the overflow in Golub */ + /* ab[n-1][n-1] = 1.0; */ + /* g = e[n-1]; */ + ab[n][n] = 1.0; + g = e[n]; + l = n; + + /* for (i=n; i >= 1; i--) { */ + for (i=n-1; i >= 1; i--) { /* n-1 loops, different from brent and golub*/ + if (g != 0.0) { + /* h = ab[i-1][i]*g; */ + h = ab[i][i+1]*g; + for (j=l; j<=n; j++) ab[j][i] = ab[i][j] / h; + for (j=l; j<=n; j++) { + /* h = ab[i][i+1]*g; */ + /* for (j=l; j= 0; k--) { */ + for (k=n; k>= 1; k--) { + kt = 0; +TestFsplitting: +#ifdef DEBUGPRAX + printf(" TestFsplitting: k=%d kt=%d\n",k,kt); + /* for(i=1;i<=n;i++)printf(" e(%d)=%.14f",i,e[i]);printf("\n"); */ +#endif + kt = kt+1; +/* TestFsplitting: */ + /* if (++kt > 30) { */ + if (kt > 30) { + e[k] = 0.0; + fprintf(stderr, "\n+++ MINFIT - Fatal error\n"); + fprintf ( stderr, " The QR algorithm failed to converge.\n" ); + } + /* for (l2=k; l2>=0; l2--) { */ + for (l2=k; l2>=1; l2--) { + l = l2; +#ifdef DEBUGPRAX + printf(" l e(l)< eps %d %.7g %.7g ",l,e[l], eps); +#endif + /* if (fabs(e[l]) <= eps) */ + if (fabs(e[l]) <= eps) + goto TestFconvergence; + /* if (fabs(q[l-1]) <= eps)*/ /* missing if ( 1 < l ){ *//* printf(" q(l-1)< eps %d %.7g %.7g ",l-1,q[l-2], eps); */ + if (fabs(q[l-1]) <= eps) + break; /* goto Cancellation; */ + } + Cancellation: +#ifdef DEBUGPRAX + printf(" Cancellation:\n"); +#endif + c = 0.0; s = 1.0; + for (i=l; i<=k; i++) { + f = s * e[i]; e[i] *= c; + /* f = s * e[i]; e[i] *= c; */ + if (fabs(f) <= eps) + goto TestFconvergence; + /* g = q[i]; */ + g = q[i]; + if (fabs(f) < fabs(g)) { + double fg = f/g; + h = fabs(g)*sqrt(1.0+fg*fg); + } + else { + double gf = g/f; + h = (f!=0.0 ? fabs(f)*sqrt(1.0+gf*gf) : 0.0); + } + /* COMMENT: THE ABOVE REPLACES Q(I):=H:=LONGSQRT(G*G+F*F) */ + /* WHICH MAY GIVE INCORRECT RESULTS IF THE */ + /* SQUARES UNDERFLOW OR IF F = G = 0; */ + + /* q[i] = h; */ + q[i] = h; + if (h == 0.0) { h = 1.0; g = 1.0; } + c = g/h; s = -f/h; + } +TestFconvergence: + #ifdef DEBUGPRAX + printf(" TestFconvergence: l=%d k=%d\n",l,k); +#endif + /* z = q[k]; */ + z = q[k]; + if (l == k) + goto Convergence; + /* shift from bottom 2x2 minor */ + /* x = q[l]; y = q[k-l]; g = e[k-1]; h = e[k]; */ /* Error */ + x = q[l]; y = q[k-1]; g = e[k-1]; h = e[k]; + f = ((y-z)*(y+z) + (g-h)*(g+h)) / (2.0*h*y); + g = sqrt(f*f+1.0); + if (f <= 0.0) + f = ((x-z)*(x+z) + h*(y/(f-g)-h))/x; + else + f = ((x-z)*(x+z) + h*(y/(f+g)-h))/x; + /* next qr transformation */ + s = c = 1.0; + for (i=l+1; i<=k; i++) { +#ifdef DEBUGPRAXQR + printf(" Before Mid TestFconvergence: l+1=%d i=%d k=%d h=%.6e e(i)=%14.8f e(i-1)=%14.8f\n",l+1,i,k, h, e[i],e[i-1]); +#endif + /* g = e[i]; y = q[i]; h = s*g; g *= c; */ + g = e[i]; y = q[i]; h = s*g; g *= c; + if (fabs(f) < fabs(h)) { + double fh = f/h; + z = fabs(h) * sqrt(1.0 + fh*fh); + } + else { + double hf = h/f; + z = (f!=0.0 ? fabs(f)*sqrt(1.0+hf*hf) : 0.0); + } + /* e[i-1] = z; */ + e[i-1] = z; +#ifdef DEBUGPRAXQR + printf(" Mid TestFconvergence: l+1=%d i=%d k=%d h=%.6e e(i)=%14.8f e(i-1)=%14.8f\n",l+1,i,k, h, e[i],e[i-1]); +#endif + if (z == 0.0) + f = z = 1.0; + c = f/z; s = h/z; + f = x*c + g*s; g = - x*s + g*c; h = y*s; + y *= c; + /* for (j=0; j 1) { + printf("\n------------- enter function praxis -----------\n"); + printf("... current parameter settings ...\n"); + printf("... scaling ... %20.10e\n", scbd); + printf("... tol ... %20.10e\n", t); + printf("... maxstep ... %20.10e\n", h); + printf("... illc ... %20u\n", illc); + printf("... ktm ... %20u\n", ktm); + printf("... maxfun ... %20u\n", maxfun); + } + if (prin) print2(); + +mloop: + biter++; /* Added to count the loops */ + /* sf = d[0]; */ + /* s = d[0] = 0.0; */ + printf("\n Big iteration %d \n",biter); + fprintf(ficlog,"\n Big iteration %d \n",biter); + sf = d[1]; + s = d[1] = 0.0; + + /* minimize along first direction V(*,1) */ +#ifdef DEBUGPRAX + printf(" Minimize along the first direction V(*,1). illc=%d\n",illc); + /* fprintf(ficlog," Minimize along the first direction V(*,1).\n"); */ +#endif +#ifdef DEBUGPRAX2 + printf("praxis4 macheps=%14g h=%14g step=%14g small=%14g t=%14g\n",macheps,h, h0,small_windows, t); +#endif + /* min(0, 2, &d[0], &s, fx, 0); /\* mac heps not global *\/ */ + minny(1, 2, &d[1], &s, fx, 0); /* mac heps not global */ +#ifdef DEBUGPRAX + printf("praxis5 macheps=%14g h=%14g looks at sign of s=%14g fx=%14g\n",macheps,h, s,fx); +#endif + if (s <= 0.0) + /* for (i=0; i < n; i++) */ + for (i=1; i <= n; i++) + v[i][1] = -v[i][1]; + /* if ((sf <= (0.9 * d[0])) || ((0.9 * sf) >= d[0])) */ + if ((sf <= (0.9 * d[1])) || ((0.9 * sf) >= d[1])) + /* for (i=1; i 0); +next: + kl = k; + df = 0.0; + if (illc) { /* random step to get off resolution valley */ +#ifdef DEBUGPRAX + printf(" A random step follows, to avoid resolution valleys.\n"); + matprint(" before rand, vectors:",v,n,n); +#endif + for (i=1; i<=n; i++) { +#ifdef NOBRENTRAND + r = drandom(); +#else + seed=i; + /* seed=i+1; */ +#ifdef DEBUGRAND + printf(" Random seed=%d, brent i=%d",seed,i); /* YYYY i=5 j=1 vji= -0.0001170073 */ +#endif + r = randbrent ( &seed ); +#endif +#ifdef DEBUGRAND + printf(" Random r=%.7g \n",r); +#endif + z[i] = (0.1 * ldt + t2 * pow(10.0,(double)kt)) * (r - 0.5); + /* z[i] = (0.1 * ldt + t2 * pow(10.0,(double)kt)) * (drandom() - 0.5); */ + + s = z[i]; + for (j=1; j <= n; j++) + x[j] += s * v[j][i]; + } +#ifdef DEBUGRAND + matprint(" after rand, vectors:",v,n,n); +#endif +#ifdef NR_SHIFT + fx = (*fun)((x-1), n); +#else + fx = (*fun)(x, n); +#endif + /* fx = (*func) ( (x-1) ); *//* This for func which is computed from x[1] and not from x[0] xm1=(x-1)*/ + nf++; + } + /* minimize along non-conjugate directions */ +#ifdef DEBUGPRAX + printf(" Minimize along the 'non-conjugate' directions (dots printed) V(*,%d),...,V(*,%d).\n",k,n); + /* fprintf(ficlog," Minimize along the 'non-conjugate' directions (dots printed) V(*,%d),...,V(*,%d).\n",k,n); */ +#endif + /* for (k2=k; k2 df(=%.9e) break illc=%d\n", k, macheps, fx, fabs ( 100.0 * macheps * fx ), df, illc); +#endif + illc = 1; + goto next; + } +#ifdef DEBUGPRAX + printf("\n SUCCESS, BREAKS inner loop K(=%d) because DF is big, fabs( 100.0 * machep(=%.10e) * fx(=%.9e) )=%.9e <= df(=%.9e) break illc=%d\n", k, macheps, fx, fabs ( 100.0 * macheps * fx ), df, illc); +#endif + + /* if ((k == 1) && (prin > 1)){ /\* be careful k=2 *\/ */ + if ((k == 2) && (prin > 1)){ /* be careful k=2 */ +#ifdef DEBUGPRAX + printf(" NEW D The second difference array d:\n" ); + /* fprintf(ficlog, " NEW D The second difference array d:\n" ); */ +#endif + vecprint(" NEW D The second difference array d:",d,n); + } + /* minimize along conjugate directions */ + /* + Minimize along the "conjugate" directions V(*,1),...,V(*,K-1). + */ +#ifdef DEBUGPRAX + printf("Minimize along the 'conjugate' directions V(*,1),...,V(*,K-1=%d).\n",k-1); + /* fprintf(ficlog,"Minimize along the 'conjugate' directions V(*,1),...,V(*,K-1=%d).\n",k-1); */ +#endif + /* for (k2=0; k2<=k-1; k2++) { */ + for (k2=1; k2<=k-1; k2++) { + s = 0.0; + /* min(k2-1, 2, &d[k2-1], &s, fx, 0); */ + minny(k2, 2, &d[k2], &s, fx, 0); + } + f1 = fx; + fx = sf; + lds = 0.0; + /* for (i=0; i small_windows) { +#ifdef DEBUGPRAX + printf("lds big enough to throw direction V(*,kl=%d). If no random step was taken, V(*,KL) is the 'non-conjugate' direction along which the greatest improvement was made.\n",kl); + matprint(" before shift new conjugate vectors:",v,n,n); +#endif + for (i=kl-1; i>=k; i--) { + /* for (j=0; j < n; j++) */ + for (j=1; j <= n; j++) + /* v[j][i+1] = v[j][i]; */ /* This is v[j][i+1]=v[j][i] i=kl-1 to k */ + v[j][i+1] = v[j][i]; /* This is v[j][i+1]=v[j][i] i=kl-1 to k */ + /* v[j][i+1] = v[j][i]; */ + /* d[i+1] = d[i];*/ /* last is d[k+1]= d[k] */ + d[i+1] = d[i]; /* last is d[k]= d[k-1] */ + } +#ifdef DEBUGPRAX + matprint(" after shift new conjugate vectors:",v,n,n); +#endif /* d[k] = 0.0; */ + d[k] = 0.0; + for (i=1; i <= n; i++) + v[i][k] = y[i] / lds; + /* v[i][k] = y[i] / lds; */ +#ifdef DEBUGPRAX + printf("Minimize along the new 'conjugate' direction V(*,k=%d), which is the normalized vector: (new x) - (old x). d2=%14.7g lds=%.10f\n",k,d[k],lds); + /* fprintf(ficlog,"Minimize along the new 'conjugate' direction V(*,k=%d), which is the normalized vector: (new x) - (old x).\n",k); */ + matprint(" before min new conjugate vectors:",v,n,n); +#endif + /* min(k-1, 4, &d[k-1], &lds, f1, 1); */ + minny(k, 4, &d[k], &lds, f1, 1); +#ifdef DEBUGPRAX + printf(" after min d(k)=%d %.7g lds=%14f\n",k,d[k],lds); + matprint(" after min vectors:",v,n,n); +#endif + if (lds <= 0.0) { + lds = -lds; +#ifdef DEBUGPRAX + printf(" lds changed sign lds=%.14f k=%d\n",lds,k); +#endif + /* for (i=0; i 0){ +#ifdef DEBUGPRAX + printf(" k=%d",k); + /* fprintf(ficlog," k=%d",k); */ +#endif + print2();/* n, x, prin, fx, nf, nl ); */ + } + t2 = 0.0; + /* for (i=0; i (0.5 * t2)) + kt = 0; + else + kt++; +#ifdef DEBUGPRAX + printf("if kt=%d >? ktm=%d gotoL2 loop\n",kt,ktm); +#endif + if (kt > ktm){ + if ( 0 < prin ){ + /* printf("\nr8vec_print\n X:\n"); */ + /* fprintf(ficlog,"\nr8vec_print\n X:\n"); */ + vecprint ("END X:", x, n ); + } + goto fret; + } +#ifdef DEBUGPRAX + matprint(" end of L2 loop vectors:",v,n,n); +#endif + + } + /* printf("The inner loop ends here.\n"); */ + /* fprintf(ficlog,"The inner loop ends here.\n"); */ + /* + The inner loop ends here. + + Try quadratic extrapolation in case we are in a curved valley. + */ +#ifdef DEBUGPRAX + printf("Try QUAD ratic extrapolation in case we are in a curved valley.\n"); +#endif + /* try quadratic extrapolation in case */ + /* we are stuck in a curved valley */ + quad(); + dn = 0.0; + /* for (i=0; i 2) + matprint(" NEW DIRECTIONS vectors:",v,n,n); + /* for (j=0; j 1.0) { /* scale axis to reduce condition number */ +#ifdef DEBUGPRAX + printf("Scale the axes to try to reduce the condition number.\n"); +#endif + /* fprintf(ficlog,"Scale the axes to try to reduce the condition number.\n"); */ + s = vlarge; + /* for (i=0; i z[i]) + s = z[i]; + } + /* for (i=0; i scbd) { + sl = 1.0 / scbd; + z[i] = scbd; + } + } + } + for (i=1; i<=n; i++) + /* for (j=0; j<=i-1; j++) { */ + /* for (j=1; j<=i; j++) { */ + for (j=1; j<=i-1; j++) { + s = v[i][j]; + v[i][j] = v[j][i]; + v[j][i] = s; + } +#ifdef DEBUGPRAX + printf(" Calculate a new set of orthogonal directions before repeating the main loop.\n Transpose V for MINFIT:...\n"); +#endif + /* + MINFIT finds the singular value decomposition of V. + + This gives the principal values and principal directions of the + approximating quadratic form without squaring the condition number. + */ + #ifdef DEBUGPRAX + printf(" MINFIT finds the singular value decomposition of V. \n This gives the principal values and principal directions of the\n approximating quadratic form without squaring the condition number...\n"); +#endif + + minfit(n, macheps, vsmall, v, d); + /* for(i=0; i 1.0) { +#ifdef DEBUGPRAX + printf(" Unscale the axes.\n"); +#endif + /* for (i=0; i large) + d[i] = vsmall; + else if ((dn * d[i]) < small_windows) + d[i] = vlarge; + else + d[i] = 1.0 / dni / dni; /* added for compatibility with buckhardt but not brent */ + /* d[i] = pow(dn * d[i],-2.0); */ + } +#ifdef DEBUGPRAX + vecprint ("\n Before sort Eigenvalues of a:",d,n ); +#endif + + sort(); /* the new eigenvalues and eigenvectors */ +#ifdef DEBUGPRAX + vecprint( " After sort the eigenvalues ....\n", d, n); + matprint( " After sort the eigenvectors....\n", v, n,n); +#endif +#ifdef DEBUGPRAX + printf(" Determine the smallest eigenvalue.\n"); +#endif + /* dmin = d[n-1]; */ + dmin = d[n]; + if (dmin < small_windows) + dmin = small_windows; + /* + The ratio of the smallest to largest eigenvalue determines whether + the system is ill conditioned. + */ + + /* illc = (m2 * d[0]) > dmin; */ + illc = (m2 * d[1]) > dmin; +#ifdef DEBUGPRAX + printf(" The ratio of the smallest to largest eigenvalue determines whether\n the system is ill conditioned=%d . dmin=%.10lf < m2=%.10lf * d[1]=%.10lf \n",illc, dmin,m2, d[1]); +#endif + + if ((prin > 2) && (scbd > 1.0)) + vecprint("\n The scale factors:",z,n); + if (prin > 2) + vecprint(" Principal values (EIGEN VALUES OF A) of the quadratic form:",d,n); + if (prin > 2) + matprint(" The principal axes (EIGEN VECTORS OF A:",v,n, n); + + if ((maxfun > 0) && (nf > maxfun)) { + if (prin) + printf("\n... maximum number of function calls reached ...\n"); + goto fret; + } +#ifdef DEBUGPRAX + printf("Goto main loop\n"); +#endif + goto mloop; /* back to main loop */ + +fret: + if (prin > 0) { + vecprint("\n X:", x, n); + /* printf("\n... ChiSq reduced to %20.10e ...\n", fx); */ + /* printf("... after %20u function calls.\n", nf); */ + } + free_vector(d, 1, n); + free_vector(y, 1, n); + free_vector(z, 1, n); + free_vector(q0, 1, n); + free_vector(q1, 1, n); + free_matrix(v, 1, n, 1, n); + /* double *d, *y, *z, */ + /* *q0, *q1, **v; */ + free_vector(tflin, 1, n); + /* double *tflin; /\* used in flin: return (*fun)(tflin, n); *\/ */ + free_vector(e, 1, n); + /* double *e; /\* used in minfit, don't konw how to free memory and thus made global *\/ */ + + return(fx); +} + +/* end praxis gegen */ /*************** powell ************************/ /* @@ -2567,7 +4182,8 @@ void powell(double p[], double **xi, int double fp,fptt; double *xits; int niterf, itmp; - + int Bigter=0, nBigterf=1; + pt=vector(1,n); ptt=vector(1,n); xit=vector(1,n); @@ -2580,14 +4196,17 @@ void powell(double p[], double **xi, int ibig=0; del=0.0; rlast_time=rcurr_time; + rlast_btime=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); */ - printf("\nPowell iter=%d -2*LL=%.12f gain=%.3lg %ld sec. %ld sec.",*iter,*fret,fp-*fret, rcurr_time-rlast_time, rcurr_time-rstart_time);fflush(stdout); - fprintf(ficlog,"\nPowell iter=%d -2*LL=%.12f gain=%.3lg %ld sec. %ld sec.",*iter,*fret,fp-*fret,rcurr_time-rlast_time, rcurr_time-rstart_time); fflush(ficlog); -/* fprintf(ficrespow,"%d %.12f %ld",*iter,*fret,curr_time.tm_sec-start_time.tm_sec); */ + /* Bigter=(*iter - *iter % ncovmodel)/ncovmodel +1; /\* Big iteration, i.e on ncovmodel cycle *\/ */ + Bigter=(*iter - (*iter-1) % n)/n +1; /* Big iteration, i.e on ncovmodel cycle */ + printf("\nPowell iter=%d Big Iter=%d -2*LL=%.12f gain=%.3lg %ld sec. %ld sec.",*iter,Bigter,*fret,fp-*fret, rcurr_time-rlast_time, rcurr_time-rstart_time);fflush(stdout); + fprintf(ficlog,"\nPowell iter=%d Big Iter=%d -2*LL=%.12f gain=%.3lg %ld sec. %ld sec.",*iter,Bigter,*fret,fp-*fret,rcurr_time-rlast_time, rcurr_time-rstart_time); fflush(ficlog); + fprintf(ficrespow,"%d %d %.12f %d",*iter,Bigter, *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]); @@ -2609,6 +4228,9 @@ void powell(double p[], double **xi, int }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]); + }else if(Typevar[j]==3) { + printf(" + V%d*V%d*age ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]); + fprintf(ficlog," + V%d*V%d*age ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]); } } printf("\n"); @@ -2639,20 +4261,23 @@ void powell(double p[], double **xi, int strcurr[itmp-1]='\0'; printf("\nConsidering the time needed for the last iteration #%d: %ld seconds,\n",*iter,rcurr_time-rlast_time); fprintf(ficlog,"\nConsidering the time needed for this last iteration #%d: %ld seconds,\n",*iter,rcurr_time-rlast_time); - for(niterf=10;niterf<=30;niterf+=10){ + for(nBigterf=1;nBigterf<=31;nBigterf+=10){ + niterf=nBigterf*ncovmodel; + /* rforecast_time=rcurr_time+(niterf-*iter)*(rcurr_time-rlast_time); */ rforecast_time=rcurr_time+(niterf-*iter)*(rcurr_time-rlast_time); forecast_time = *localtime(&rforecast_time); strcpy(strfor,asctime(&forecast_time)); itmp = strlen(strfor); if(strfor[itmp-1]=='\n') strfor[itmp-1]='\0'; - printf(" - if your program needs %d iterations to converge, convergence will be \n reached in %s i.e.\n on %s (current time is %s);\n",niterf, asc_diff_time(rforecast_time-rcurr_time,tmpout),strfor,strcurr); - fprintf(ficlog," - if your program needs %d iterations to converge, convergence will be \n reached in %s i.e.\n on %s (current time is %s);\n",niterf, asc_diff_time(rforecast_time-rcurr_time,tmpout),strfor,strcurr); + printf(" - if your program needs %d BIG iterations (%d iterations) to converge, convergence will be \n reached in %s i.e.\n on %s (current time is %s);\n",nBigterf, niterf, asc_diff_time(rforecast_time-rcurr_time,tmpout),strfor,strcurr); + fprintf(ficlog," - if your program needs %d BIG iterations (%d iterations) to converge, convergence will be \n reached in %s i.e.\n on %s (current time is %s);\n",nBigterf, niterf, asc_diff_time(rforecast_time-rcurr_time,tmpout),strfor,strcurr); } } - for (i=1;i<=n;i++) { /* For each direction i */ - for (j=1;j<=n;j++) xit[j]=xi[j][i]; /* Directions stored from previous iteration with previous scales */ - fptt=(*fret); + for (i=1;i<=n;i++) { /* For each direction i, maximisation after loading directions */ + for (j=1;j<=n;j++) xit[j]=xi[j][i]; /* Directions stored from previous iteration with previous scales. xi is not changed but one dim xit */ + + fptt=(*fret); /* Computes likelihood for parameters xit */ #ifdef DEBUG printf("fret=%lf, %lf, %lf \n", *fret, *fret, *fret); fprintf(ficlog, "fret=%lf, %lf, %lf \n", *fret, *fret, *fret); @@ -2660,37 +4285,39 @@ void powell(double p[], double **xi, int printf("%d",i);fflush(stdout); /* print direction (parameter) i */ fprintf(ficlog,"%d",i);fflush(ficlog); #ifdef LINMINORIGINAL - linmin(p,xit,n,fret,func); /* Point p[n]. xit[n] has been loaded for direction i as input.*/ + linmin(p,xit,n,fret,func); /* New point i minimizing in direction xit, i has coordinates p[j].*/ + /* xit[j] gives the n coordinates of direction i as input.*/ + /* *fret gives the maximum value on direction xit */ #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 */ + flatdir[i]=flat; /* Function is vanishing in that direction i */ #endif - /* Outputs are fret(new point p) p is updated and xit rescaled */ + /* 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; + /* 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(%d)=%.12e",j,p[j]); - fprintf(ficlog," p(%d)=%.12e",j,p[j]); + printf(" p(%d)=%.12e",j,p[j]); + fprintf(ficlog," p(%d)=%.12e",j,p[j]); } printf("\n"); fprintf(ficlog,"\n"); #endif } /* end loop on each direction i */ - /* Convergence test will use last linmin estimation (fret) and compare former iteration (fp) */ + /* Convergence test will use last linmin estimation (fret) and compare to 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++) { @@ -2745,13 +4372,19 @@ void powell(double p[], double **xi, int return; } /* enough precision */ if (*iter == ITMAX*n) nrerror("powell exceeding maximum iterations."); - for (j=1;j<=n;j++) { /* Computes the extrapolated point P_0 + 2 (P_n-P_0) */ + for (j=1;j<=n;j++) { /* Computes the extrapolated point and value f3, P_0 + 2 (P_n-P_0)=2Pn-P0 and xit is direction Pn-P0 */ ptt[j]=2.0*p[j]-pt[j]; - xit[j]=p[j]-pt[j]; - pt[j]=p[j]; - } + xit[j]=p[j]-pt[j]; /* Coordinate j of last direction xi_n=P_n-P_0 */ +#ifdef DEBUG + printf("\n %d xit=%12.7g p=%12.7g pt=%12.7g ",j,xit[j],p[j],pt[j]); +#endif + pt[j]=p[j]; /* New P0 is Pn */ + } +#ifdef DEBUG + printf("\n"); +#endif fptt=(*func)(ptt); /* f_3 */ -#ifdef NODIRECTIONCHANGEDUNTILNITER /* No change in drections until some iterations are done */ +#ifdef NODIRECTIONCHANGEDUNTILNITER /* No change in directions until some iterations are done */ if (*iter <=4) { #else #endif @@ -2770,10 +4403,10 @@ void powell(double p[], double **xi, int /* t=2.0*(fp-2.0*(*fret)+fptt)*SQR(fp-(*fret)-del)-del*SQR(fp-fptt); */ /* Even if 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 */ + /* 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 @@ -2793,14 +4426,14 @@ void powell(double p[], double **xi, int #endif #ifdef POWELLORIGINAL if (t < 0.0) { /* Then we use it for new direction */ -#else +#else /* Not POWELLOriginal but Brouard's */ 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("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 */ + if (directest < 0.0) { /* Then we use (P0, Pn) for new direction Xi_n or Xi_iBig */ #endif #ifdef DEBUGLINMIN printf("Before linmin in direction P%d-P0\n",n); @@ -2834,6 +4467,21 @@ void powell(double p[], double **xi, int 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 */ } + +/* #else */ +/* for (i=1;i<=n-1;i++) { */ +/* for (j=1;j<=n;j++) { */ +/* xi[j][i]=xi[j][i+1]; /\* Standard method of conjugate directions, not Powell who changes the nth direction by p0 pn . *\/ */ +/* } */ +/* } */ +/* for (j=1;j<=n;j++) { */ +/* xi[j][n]=xit[j]; /\* and this nth direction by the by the average p_0 p_n *\/ */ +/* } */ +/* /\* for (j=1;j<=n-1;j++) { *\/ */ +/* /\* xi[j][1]=xi[j][j+1]; /\\* Standard method of conjugate directions *\\/ *\/ */ +/* /\* xi[j][n]=xit[j]; /\\* and this nth direction by the by the average p_0 p_n *\\/ *\/ */ +/* /\* } *\/ */ +/* #endif */ #ifdef LINMINORIGINAL #else for (j=1, flatd=0;j<=n;j++) { @@ -2858,8 +4506,8 @@ void powell(double p[], double **xi, int free_vector(pt,1,n); return; #endif - } -#endif + } /* endif(flatd >0) */ +#endif /* LINMINORIGINAL */ 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); @@ -2874,6 +4522,8 @@ void powell(double p[], double **xi, int fprintf(ficlog,"\n"); #endif } /* end of t or directest negative */ + printf(" Directest is positive, P_n-P_0 does not increase the conjugacy. n=%d\n",n); + fprintf(ficlog," Directest is positive, P_n-P_0 does not increase the conjugacy. n=%d\n",n); #ifdef POWELLNOF3INFF1TEST #else } /* end if (fptt < fp) */ @@ -2948,7 +4598,7 @@ void powell(double p[], double **xi, int /* Model(2) V1 + V2 + V3 + V8 + V7*V8 + V5*V6 + V8*age + V3*age + age*age */ /* total number of covariates of the model nbocc(+)+1 = 8 excepting constant and age and age*age */ for(k1=1;k1<=cptcovt;k1++){ /* loop on model equation (including products) */ - if(Typevar[k1]==1){ /* A product with age */ + if(Typevar[k1]==1 || Typevar[k1]==3){ /* A product with age */ cov[2+nagesqr+k1]=precov[nres][k1]*cov[2]; }else{ cov[2+nagesqr+k1]=precov[nres][k1]; @@ -3082,7 +4732,9 @@ void powell(double p[], double **xi, int 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); */ + /* 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); @@ -3117,7 +4769,7 @@ void powell(double p[], double **xi, int /* 0.51326036147820708, 0.48673963852179264} */ /* If we start from prlim again, prlim tends to a constant matrix */ - int i, ii,j,k, k1; + int i, ii,j, k1; int first=0; double *min, *max, *meandiff, maxmax,sumnew=0.; /* double **matprod2(); */ /* test */ @@ -3158,7 +4810,7 @@ void powell(double p[], double **xi, int cov[3]= agefin*agefin;; } for(k1=1;k1<=cptcovt;k1++){ /* loop on model equation (including products) */ - if(Typevar[k1]==1){ /* A product with age */ + if(Typevar[k1]==1 || Typevar[k1]==3){ /* A product with age */ cov[2+nagesqr+k1]=precov[nres][k1]*cov[2]; }else{ cov[2+nagesqr+k1]=precov[nres][k1]; @@ -3384,9 +5036,9 @@ double **pmij(double **ps, double *cov, /* Computes the backward probability at age agefin, cov[2], and covariate combination 'ij'. In fact cov is already filled and x too. * Call to pmij(cov and x), call to cross prevalence, sums and inverses, left multiply, and returns in **ps as well as **bmij. */ - int i, ii, j,k; + int ii, j; - double **out, **pmij(); + double **pmij(); double sumnew=0.; double agefin; double k3=0.; /* constant of the w_x diagonal matrix (in order for B to sum to 1 even for death state) */ @@ -3599,11 +5251,11 @@ double ***hpxij(double ***po, int nhstep */ - int i, j, d, h, k, k1; + int i, j, d, h, k1; double **out, cov[NCOVMAX+1]; double **newm; double agexact; - double agebegin, ageend; + /*double agebegin, ageend;*/ /* Hstepm could be zero and should return the unit matrix */ for (i=1;i<=nlstate+ndeath;i++) @@ -3625,7 +5277,7 @@ double ***hpxij(double ***po, int nhstep /* Model(2) V1 + V2 + V3 + V8 + V7*V8 + V5*V6 + V8*age + V3*age + age*age */ /* total number of covariates of the model nbocc(+)+1 = 8 excepting constant and age and age*age */ for(k1=1;k1<=cptcovt;k1++){ /* loop on model equation (including products) */ - if(Typevar[k1]==1){ /* A product with age */ + if(Typevar[k1]==1 || Typevar[k1]==3){ /* A product with age */ cov[2+nagesqr+k1]=precov[nres][k1]*cov[2]; }else{ cov[2+nagesqr+k1]=precov[nres][k1]; @@ -3780,11 +5432,11 @@ double ***hbxij(double ***po, int nhstep The addresss of po (p3mat allocated to the dimension of nhstepm) should be stored for output */ - int i, j, d, h, k, k1; + int i, j, d, h, k1; double **out, cov[NCOVMAX+1], **bmij(); double **newm, ***newmm; double agexact; - double agebegin, ageend; + /*double agebegin, ageend;*/ double **oldm, **savm; newmm=po; /* To be saved */ @@ -3811,7 +5463,7 @@ double ***hbxij(double ***po, int nhstep } /** New code */ for(k1=1;k1<=cptcovt;k1++){ /* loop on model equation (including products) */ - if(Typevar[k1]==1){ /* A product with age */ + if(Typevar[k1]==1 || Typevar[k1]==3){ /* A product with age */ cov[2+nagesqr+k1]=precov[nres][k1]*cov[2]; }else{ cov[2+nagesqr+k1]=precov[nres][k1]; @@ -3996,18 +5648,6 @@ double func( double *x) iposold=ipos; cov[ioffset+ipos]=cotvarv; } - /* for(itv=1; itv <= ntveff; itv++){ /\* Varying dummy covariates (single??)*\/ */ - /* iv= Tvar[Tmodelind[ioffset-2-nagesqr-cptcovage+itv]]-ncovcol-nqv; /\* Counting the # varying covariate from 1 to ntveff *\/ */ - /* cov[ioffset+iv]=cotvar[mw[mi][i]][iv][i]; */ - /* k=ioffset-2-nagesqr-cptcovage+itv; /\* position in simple model *\/ */ - /* cov[ioffset+itv]=cotvar[mw[mi][i]][TmodelInvind[itv]][i]; */ - /* printf(" i=%d,mi=%d,itv=%d,TmodelInvind[itv]=%d,cotvar[mw[mi][i]][TmodelInvind[itv]][i]=%f\n", i, mi, itv, TmodelInvind[itv],cotvar[mw[mi][i]][TmodelInvind[itv]][i]); */ - /* } */ - /* for(iqtv=1; iqtv <= nqtveff; iqtv++){ /\* Varying quantitatives covariates *\/ */ - /* iv=TmodelInvQind[iqtv]; /\* Counting the # varying covariate from 1 to ntveff *\/ */ - /* /\* printf(" i=%d,mi=%d,iqtv=%d,TmodelInvQind[iqtv]=%d,cotqvar[mw[mi][i]][TmodelInvQind[iqtv]][i]=%f\n", i, mi, iqtv, TmodelInvQind[iqtv],cotqvar[mw[mi][i]][TmodelInvQind[iqtv]][i]); *\/ */ - /* cov[ioffset+ntveff+iqtv]=cotqvar[mw[mi][i]][TmodelInvQind[iqtv]][i]; */ - /* } */ /* for products of time varying to be done */ for (ii=1;ii<=nlstate+ndeath;ii++) for (j=1;j<=nlstate+ndeath;j++){ @@ -4023,12 +5663,30 @@ double func( double *x) cov[2]=agexact; if(nagesqr==1) cov[3]= agexact*agexact; /* Should be changed here */ - for (kk=1; kk<=cptcovage;kk++) { - if(!FixedV[Tvar[Tage[kk]]]) - cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact; /* Tage[kk] gives the data-covariate associated with age */ - else - cov[Tage[kk]+2+nagesqr]=cotvar[mw[mi][i]][Tvar[Tage[kk]]][i]*agexact; /* because cotvar starts now at first ncovcol+nqv+ (1 to nqtv) */ + /* for (kk=1; kk<=cptcovage;kk++) { */ + /* if(!FixedV[Tvar[Tage[kk]]]) */ + /* cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact; /\* Tage[kk] gives the data-covariate associated with age *\/ */ + /* else */ + /* cov[Tage[kk]+2+nagesqr]=cotvar[mw[mi][i]][Tvar[Tage[kk]]][i]*agexact; /\* because cotvar starts now at first ncovcol+nqv+ (1 to nqtv) *\/ */ + /* } */ + for(ncovva=1, iposold=0; ncovva <= ncovta ; ncovva++){ /* Time varying covariates with age including individual from products, product is computed dynamically */ + itv=TvarAVVA[ncovva]; /* TvarVV={3, 1, 3} gives the name of each varying covariate, exploding product Vn*Vm into Vn and then Vm */ + ipos=TvarAVVAind[ncovva]; /* TvarVVind={2, 5, 5] gives the position in the model of the ncovv th varying covariate*/ + if(FixedV[itv]!=0){ /* Not a fixed covariate? Could be a fixed covariate of a product with a higher than ncovcol+nqv, itv */ + cotvarv=cotvar[mw[mi][i]][TvarAVVA[ncovva]][i]; /* because cotvar starts now at first ncovcol+nqv+ntv+nqtv (1 to nqtv) */ + }else{ /* fixed covariate */ + cotvarv=covar[itv][i]; /* Error: TvarFind gives the name, that is the true column of fixed covariates, but Tvar of the model */ + } + if(ipos!=iposold){ /* Not a product or first of a product */ + cotvarvold=cotvarv; + }else{ /* A second product */ + cotvarv=cotvarv*cotvarvold; + } + iposold=ipos; + cov[ioffset+ipos]=cotvarv*agexact; + /* For products */ } + out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath, 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate)); savm=oldm; @@ -4297,7 +5955,7 @@ double func( double *x) double funcone( double *x) { /* Same as func but slower because of a lot of printf and if */ - int i, ii, j, k, mi, d, kk, kf=0; + int i, ii, j, k, mi, d, kv=0, kf=0; int ioffset=0; int ipos=0,iposold=0,ncovv=0; @@ -4333,7 +5991,7 @@ double funcone( double *x) /* Fixed */ /* for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i]; */ /* for (k=1; k<=ncoveff;k++){ /\* Simple and product fixed Dummy covariates without age* products *\/ */ - for (kf=1; kf<=ncovf;kf++){ /* Simple and product fixed covariates without age* products *//* Missing values are set to -1 but should be dropped */ + for (kf=1; kf<=ncovf;kf++){ /* V2 + V3 + V4 Simple and product fixed covariates without age* products *//* Missing values are set to -1 but should be dropped */ /* printf("Debug3 TvarFind[%d]=%d",kf, TvarFind[kf]); */ /* printf(" Tvar[TvarFind[kf]]=%d", Tvar[TvarFind[kf]]); */ /* printf(" i=%d covar[Tvar[TvarFind[kf]]][i]=%f\n",i,covar[Tvar[TvarFind[kf]]][i]); */ @@ -4390,35 +6048,117 @@ double funcone( double *x) * TvarFind[k] 1 0 0 0 0 0 0 0 0 */ /* Other model ncovcol=5 nqv=0 ntv=3 nqtv=0 nlstate=3 - /* V2 V3 V4 are fixed V6 V7 are timevarying so V8 and V5 are not in the model and product column will start at 9 Tvar[4]=6 + * V2 V3 V4 are fixed V6 V7 are timevarying so V8 and V5 are not in the model and product column will start at 9 Tvar[(v6*V2)6]=9 * FixedV[ncovcol+qv+ntv+nqtv] V5 - * V1 V2 V3 V4 V5 V6 V7 V8 - * 0 0 0 0 0 1 1 1 - * model= V2 + V3 + V4 + V6 + V7 + V6*V2 + V7*V2 + V6*V3 + V7*V3 + V6*V4 + V7*V4 - * kmodel 1 2 3 4 5 6 7 8 9 10 11 + * 3 V1 V2 V3 V4 V5 V6 V7 V8 V3*V2 V7*V2 V6*V3 V7*V3 V6*V4 V7*V4 + * 0 0 0 0 0 1 1 1 0, 0, 1,1, 1, 0, 1, 0, 1, 0, 1, 0} + * 3 0 0 0 0 0 1 1 1 0, 1 1 1 1 1} + * model= V2 + V3 + V4 + V6 + V7 + V6*V2 + V7*V2 + V6*V3 + V7*V3 + V6*V4 + V7*V4 + * +age*V2 +age*V3 +age*V4 +age*V6 + age*V7 + * +age*V6*V2 + age*V6*V3 +age*V7*V3 + age*V6*V4 +age*V7*V4 + * model2= V2 + V3 + V4 + V6 + V7 + V3*V2 + V7*V2 + V6*V3 + V7*V3 + V6*V4 + V7*V4 + * +age*V2 +age*V3 +age*V4 +age*V6 + age*V7 + * +age*V3*V2 + age*V6*V3 +age*V7*V3 + age*V6*V4 +age*V7*V4 + * model3= V2 + V3 + V4 + V6 + V7 + age*V3*V2 + V7*V2 + V6*V3 + V7*V3 + V6*V4 + V7*V4 + * +age*V2 +age*V3 +age*V4 +age*V6 + age*V7 + * +V3*V2 + age*V6*V3 +age*V7*V3 + age*V6*V4 +age*V7*V4 + * kmodel 1 2 3 4 5 6 7 8 9 10 11 + * 12 13 14 15 16 + * 17 18 19 20 21 + * Tvar[kmodel] 2 3 4 6 7 9 10 11 12 13 14 + * 2 3 4 6 7 + * 9 11 12 13 14 + * cptcovage=5+5 total of covariates with age + * Tage[cptcovage] age*V2=12 13 14 15 16 + *1 17 18 19 20 21 gives the position in model of covariates associated with age + *3 Tage[cptcovage] age*V3*V2=6 + *3 age*V2=12 13 14 15 16 + *3 age*V6*V3=18 19 20 21 + * Tvar[Tage[cptcovage]] Tvar[12]=2 3 4 6 Tvar[16]=7(age*V7) + * Tvar[17]age*V6*V2=9 Tvar[18]age*V6*V3=11 age*V7*V3=12 age*V6*V4=13 Tvar[21]age*V7*V4=14 + * 2 Tvar[17]age*V3*V2=9 Tvar[18]age*V6*V3=11 age*V7*V3=12 age*V6*V4=13 Tvar[21]age*V7*V4=14 + * 3 Tvar[Tage[cptcovage]] Tvar[6]=9 Tvar[12]=2 3 4 6 Tvar[16]=7(age*V7) + * 3 Tvar[18]age*V6*V3=11 age*V7*V3=12 age*V6*V4=13 Tvar[21]age*V7*V4=14 + * 3 Tage[cptcovage] age*V3*V2=6 age*V2=12 age*V3 13 14 15 16 + * age*V6*V3=18 19 20 21 gives the position in model of covariates associated with age + * 3 Tvar[17]age*V3*V2=9 Tvar[18]age*V6*V3=11 age*V7*V3=12 age*V6*V4=13 Tvar[21]age*V7*V4=14 + * Tvar= {2, 3, 4, 6, 7, + * 9, 10, 11, 12, 13, 14, + * Tvar[12]=2, 3, 4, 6, 7, + * Tvar[17]=9, 11, 12, 13, 14} + * Typevar[1]@21 = {0, 0, 0, 0, 0, + * 2, 2, 2, 2, 2, 2, + * 3 3, 2, 2, 2, 2, 2, + * 1, 1, 1, 1, 1, + * 3, 3, 3, 3, 3} + * 3 2, 3, 3, 3, 3} + * p Tposprod[1]@21 {0, 0, 0, 0, 0, 1, 2, 3, 4, 5, 6, 0, 0, 0, 0, 0, 1, 3, 4, 5, 6} Id of the prod at position k in the model + * p Tprod[1]@21 {6, 7, 8, 9, 10, 11, 0 } + * 3 Tposprod[1]@21 {0, 0, 0, 0, 0, 1, 2, 3, 4, 5, 6, 0, 0, 0, 0, 0, 1, 3, 4, 5, 6} + * 3 Tprod[1]@21 {17, 7, 8, 9, 10, 11, 0 } + * cptcovprod=11 (6+5) + * FixedV[Tvar[Tage[cptcovage]]]] FixedV[2]=0 FixedV[3]=0 0 1 (age*V7)Tvar[16]=1 FixedV[absolute] not [kmodel] + * FixedV[Tvar[17]=FixedV[age*V6*V2]=FixedV[9]=1 1 1 1 1 + * 3 FixedV[Tvar[17]=FixedV[age*V3*V2]=FixedV[9]=0 [11]=1 1 1 1 + * FixedV[] V1=0 V2=0 V3=0 v4=0 V5=0 V6=1 V7=1 v8=1 OK then model dependent + * 9=1 [V7*V2]=[10]=1 11=1 12=1 13=1 14=1 + * 3 9=0 [V7*V2]=[10]=1 11=1 12=1 13=1 14=1 + * cptcovdageprod=5 for gnuplot printing + * cptcovprodvage=6 + * ncova=15 1 2 3 4 5 + * 6 7 8 9 10 11 12 13 14 15 + * TvarA 2 3 4 6 7 + * 6 2 6 7 7 3 6 4 7 4 + * TvaAind 12 12 13 13 14 14 15 15 16 16 * ncovf 1 2 3 - * ncovvt=14 1 2 3 4 5 6 7 8 9 10 11 12 13 14 - * TvarVV[1]@14 = itv {6, 7, 6, 2, 7, 2, 6, 3, 7, 3, 6, 4, 7, 4} - * TvarVVind[1]@14= {4, 5, 6, 6, 7, 7, 8, 8, 9, 9, 10, 10, 11, 11} + * V6 V7 V6*V2 V7*V2 V6*V3 V7*V3 V6*V4 V7*V4 + * ncovvt=14 1 2 3 4 5 6 7 8 9 10 11 12 13 14 + * TvarVV[1]@14 = itv {V6=6, 7, V6*V2=6, 2, 7, 2, 6, 3, 7, 3, 6, 4, 7, 4} + * TvarVVind[1]@14= {4, 5, 6, 6, 7, 7, 8, 8, 9, 9, 10, 10, 11, 11} + * 3 ncovvt=12 V6 V7 V7*V2 V6*V3 V7*V3 V6*V4 V7*V4 + * 3 TvarVV[1]@12 = itv {6, 7, V7*V2=7, 2, 6, 3, 7, 3, 6, 4, 7, 4} + * 3 1 2 3 4 5 6 7 8 9 10 11 12 + * TvarVVind[1]@12= {V6 is in k=4, 5, 7,(4isV2)=7, 8, 8, 9, 9, 10,10, 11,11}TvarVVind[12]=k=11 + * TvarV 6, 7, 9, 10, 11, 12, 13, 14 + * 3 cptcovprodvage=6 + * 3 ncovta=15 +age*V3*V2+age*V2+agev3+ageV4 +age*V6 + age*V7 + age*V6*V3 +age*V7*V3 + age*V6*V4 +age*V7*V4 + * 3 TvarAVVA[1]@15= itva 3 2 2 3 4 6 7 6 3 7 3 6 4 7 4 + * 3 ncovta 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 + *?TvarAVVAind[1]@15= V3 is in k=2 1 1 2 3 4 5 4,2 5,2, 4,3 5 3}TvarVVAind[] + * TvarAVVAind[1]@15= V3 is in k=6 6 12 13 14 15 16 18 18 19,19, 20,20 21,21}TvarVVAind[] + * 3 ncovvta=10 +age*V6 + age*V7 + age*V6*V3 +age*V7*V3 + age*V6*V4 +age*V7*V4 + * 3 we want to compute =cotvar[mw[mi][i]][TvarVVA[ncovva]][i] at position TvarVVAind[ncovva] + * 3 TvarVVA[1]@10= itva 6 7 6 3 7 3 6 4 7 4 + * 3 ncovva 1 2 3 4 5 6 7 8 9 10 + * TvarVVAind[1]@10= V6 is in k=4 5 8,8 9, 9, 10,10 11 11}TvarVVAind[] + * TvarVVAind[1]@10= 15 16 18,18 19,19, 20,20 21 21}TvarVVAind[] + * TvarVA V3*V2=6 6 , 1, 2, 11, 12, 13, 14 * TvarFind[1]@14= {1, 2, 3, 0 } - * Tvar[1]@20= {2, 3, 4, 6, 7, 9, 10, 11, 12, 13, 14} + * Tvar[1]@21= {2, 3, 4, 6, 7, 9, 10, 11, 12, 13, 14, + * 2, 3, 4, 6, 7, + * 6, 8, 9, 10, 11} * TvarFind[itv] 0 0 0 * FixedV[itv] 1 1 1 0 1 0 1 0 1 0 0 + *? FixedV[itv] 1 1 1 0 1 0 1 0 1 0 1 0 1 0 * Tvar[TvarFind[ncovf]]=[1]=2 [2]=3 [4]=4 * Tvar[TvarFind[itv]] [0]=? ?ncovv 1 à ncovvt] * Not a fixed cotvar[mw][itv][i] 6 7 6 2 7, 2, 6, 3, 7, 3, 6, 4, 7, 4} - * fixed covar[itv] [6] [7] [6][2] + * fixed covar[itv] [6] [7] [6][2] */ - for(ncovv=1, iposold=0; ncovv <= ncovvt ; ncovv++){ /* Varying covariates (single and product but no age) including individual from products */ - itv=TvarVV[ncovv]; /* TvarVV={3, 1, 3} gives the name of each varying covariate, exploding product */ + for(ncovv=1, iposold=0; ncovv <= ncovvt ; ncovv++){ /* V6 V7 V7*V2 V6*V3 V7*V3 V6*V4 V7*V4 Time varying covariates (single and extended product but no age) including individual from products, product is computed dynamically */ + itv=TvarVV[ncovv]; /* TvarVV={3, 1, 3} gives the name of each varying covariate, or fixed covariate of a varying product after exploding product Vn*Vm into Vn and then Vm */ ipos=TvarVVind[ncovv]; /* TvarVVind={2, 5, 5] gives the position in the model of the ncovv th varying covariate*/ /* if(TvarFind[itv]==0){ /\* Not a fixed covariate? Could be a fixed covariate of a product with a higher than ncovcol+nqv, itv *\/ */ if(FixedV[itv]!=0){ /* Not a fixed covariate? Could be a fixed covariate of a product with a higher than ncovcol+nqv, itv */ + /* printf("DEBUG ncovv=%d, Varying TvarVV[ncovv]=%d\n",ncovv, TvarVV[ncovv]); */ cotvarv=cotvar[mw[mi][i]][TvarVV[ncovv]][i]; /* because cotvar starts now at first ncovcol+nqv+ntv+nqtv (1 to nqtv) */ + /* printf("DEBUG Varying cov[ioffset+ipos=%d]=%g \n",ioffset+ipos,cotvarv); */ }else{ /* fixed covariate */ /* cotvarv=covar[Tvar[TvarFind[itv]]][i]; /\* Error: TvarFind gives the name, that is the true column of fixed covariates, but Tvar of the model *\/ */ - cotvarv=covar[itv][i]; /* Error: TvarFind gives the name, that is the true column of fixed covariates, but Tvar of the model */ + /* printf("DEBUG ncovv=%d, Fixed TvarVV[ncovv]=%d\n",ncovv, TvarVV[ncovv]); */ + cotvarv=covar[itv][i]; /* Good: In V6*V3, 3 is fixed at position of the data */ + /* printf("DEBUG Fixed cov[ioffset+ipos=%d]=%g \n",ioffset+ipos,cotvarv); */ } if(ipos!=iposold){ /* Not a product or first of a product */ cotvarvold=cotvarv; @@ -4427,6 +6167,7 @@ double funcone( double *x) } iposold=ipos; cov[ioffset+ipos]=cotvarv; + /* printf("DEBUG Product cov[ioffset+ipos=%d] \n",ioffset+ipos); */ /* For products */ } /* for(itv=1; itv <= ntveff; itv++){ /\* Varying dummy covariates single *\/ */ @@ -4465,12 +6206,30 @@ double funcone( double *x) cov[2]=agexact; if(nagesqr==1) cov[3]= agexact*agexact; - for (kk=1; kk<=cptcovage;kk++) { - if(!FixedV[Tvar[Tage[kk]]]) - cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact; - else - cov[Tage[kk]+2+nagesqr]=cotvar[mw[mi][i]][Tvar[Tage[kk]]][i]*agexact; /* because cotvar starts now at first ncovcol+nqv+ (1 to nqtv) */ + for(ncovva=1, iposold=0; ncovva <= ncovta ; ncovva++){ /* Time varying covariates with age including individual from products, product is computed dynamically */ + itv=TvarAVVA[ncovva]; /* TvarVV={3, 1, 3} gives the name of each varying covariate, exploding product Vn*Vm into Vn and then Vm */ + ipos=TvarAVVAind[ncovva]; /* TvarVVind={2, 5, 5] gives the position in the model of the ncovv th varying covariate*/ + /* if(TvarFind[itv]==0){ /\* Not a fixed covariate? Could be a fixed covariate of a product with a higher than ncovcol+nqv, itv *\/ */ + if(FixedV[itv]!=0){ /* Not a fixed covariate? Could be a fixed covariate of a product with a higher than ncovcol+nqv, itv */ + /* printf("DEBUG ncovva=%d, Varying TvarAVVA[ncovva]=%d\n", ncovva, TvarAVVA[ncovva]); */ + cotvarv=cotvar[mw[mi][i]][TvarAVVA[ncovva]][i]; /* because cotvar starts now at first ncovcol+nqv+ntv+nqtv (1 to nqtv) */ + }else{ /* fixed covariate */ + /* cotvarv=covar[Tvar[TvarFind[itv]]][i]; /\* Error: TvarFind gives the name, that is the true column of fixed covariates, but Tvar of the model *\/ */ + /* printf("DEBUG ncovva=%d, Fixed TvarAVVA[ncovva]=%d\n", ncovva, TvarAVVA[ncovva]); */ + cotvarv=covar[itv][i]; /* Error: TvarFind gives the name, that is the true column of fixed covariates, but Tvar of the model */ + } + if(ipos!=iposold){ /* Not a product or first of a product */ + cotvarvold=cotvarv; + }else{ /* A second product */ + /* printf("DEBUG * \n"); */ + cotvarv=cotvarv*cotvarvold; + } + iposold=ipos; + /* printf("DEBUG Product cov[ioffset+ipos=%d] \n",ioffset+ipos); */ + cov[ioffset+ipos]=cotvarv*agexact; + /* For products */ } + /* printf("i=%d,mi=%d,d=%d,mw[mi][i]=%d\n",i, mi,d,mw[mi][i]); */ /* savm=pmij(pmmij,cov,ncovmodel,x,nlstate); */ out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath, @@ -4558,14 +6317,39 @@ double funcone( double *x) } iposold=ipos; } - for (kk=1; kk<=cptcovage;kk++) { - if(!FixedV[Tvar[Tage[kk]]]){ - fprintf(ficresilk," %g*age",covar[Tvar[Tage[kk]]][i]); - /* printf(" %g*age",covar[Tvar[Tage[kk]]][i]); */ - }else{ - fprintf(ficresilk," %g*age",cotvar[mw[mi][i]][Tvar[Tage[kk]]][i]);/* because cotvar starts now at first ncovcol+nqv+ (1 to nqtv) */ - /* printf(" %g*age",cotvar[mw[mi][i]][Tvar[Tage[kk]]][i]);/\* because cotvar starts now at first ncovcol+nqv+ (1 to nqtv) *\/ */ + /* for (kk=1; kk<=cptcovage;kk++) { */ + /* if(!FixedV[Tvar[Tage[kk]]]){ */ + /* fprintf(ficresilk," %g*age",covar[Tvar[Tage[kk]]][i]); */ + /* /\* printf(" %g*age",covar[Tvar[Tage[kk]]][i]); *\/ */ + /* }else{ */ + /* fprintf(ficresilk," %g*age",cotvar[mw[mi][i]][Tvar[Tage[kk]]][i]);/\* because cotvar starts now at first ncovcol+nqv+ (1 to nqtv) *\/ */ + /* /\* printf(" %g*age",cotvar[mw[mi][i]][Tvar[Tage[kk]]][i]);/\\* because cotvar starts now at first ncovcol+nqv+ (1 to nqtv) *\\/ *\/ */ + /* } */ + /* } */ + for(ncovva=1, iposold=0; ncovva <= ncovta ; ncovva++){ /* Time varying covariates with age including individual from products, product is computed dynamically */ + itv=TvarAVVA[ncovva]; /* TvarVV={3, 1, 3} gives the name of each varying covariate, exploding product Vn*Vm into Vn and then Vm */ + ipos=TvarAVVAind[ncovva]; /* TvarVVind={2, 5, 5] gives the position in the model of the ncovv th varying covariate*/ + /* if(TvarFind[itv]==0){ /\* Not a fixed covariate? Could be a fixed covariate of a product with a higher than ncovcol+nqv, itv *\/ */ + if(FixedV[itv]!=0){ /* Not a fixed covariate? Could be a fixed covariate of a product with a higher than ncovcol+nqv, itv */ + /* printf("DEBUG ncovva=%d, Varying TvarAVVA[ncovva]=%d\n", ncovva, TvarAVVA[ncovva]); */ + cotvarv=cotvar[mw[mi][i]][TvarAVVA[ncovva]][i]; /* because cotvar starts now at first ncovcol+nqv+ntv+nqtv (1 to nqtv) */ + }else{ /* fixed covariate */ + /* cotvarv=covar[Tvar[TvarFind[itv]]][i]; /\* Error: TvarFind gives the name, that is the true column of fixed covariates, but Tvar of the model *\/ */ + /* printf("DEBUG ncovva=%d, Fixed TvarAVVA[ncovva]=%d\n", ncovva, TvarAVVA[ncovva]); */ + cotvarv=covar[itv][i]; /* Error: TvarFind gives the name, that is the true column of fixed covariates, but Tvar of the model */ + } + if(ipos!=iposold){ /* Not a product or first of a product */ + cotvarvold=cotvarv; + }else{ /* A second product */ + /* printf("DEBUG * \n"); */ + cotvarv=cotvarv*cotvarvold; } + cotvarv=cotvarv*agexact; + fprintf(ficresilk," %g*age",cotvarv); + iposold=ipos; + /* printf("DEBUG Product cov[ioffset+ipos=%d] \n",ioffset+ipos); */ + cov[ioffset+ipos]=cotvarv; + /* For products */ } /* printf("\n"); */ /* } /\* End debugILK *\/ */ @@ -4659,9 +6443,10 @@ void likelione(FILE *ficres,double p[], fprintf(fichtm,"
- Probability p%dj by origin %d and destination j. Dot's sizes are related to corresponding weight: %s-p%dj.png
\n \ \n",k,k,subdirf2(optionfilefiname,"ILK_"),k,subdirf2(optionfilefiname,"ILK_"),k,subdirf2(optionfilefiname,"ILK_"),k); for(kf=1; kf <= ncovf; kf++){ /* For each simple dummy covariate of the model */ - /* kvar=Tvar[TvarFind[kf]]; */ /* variable */ - fprintf(fichtm,"
- Probability p%dj by origin %d and destination j with colored covariate V%d. Same dot size of all points but with a different color for transitions with dummy variable V%d=1 at beginning of transition (keeping former color for V%d=0): %s-p%dj.png
\ -",k,k,Tvar[TvarFind[kf]],Tvar[TvarFind[kf]],Tvar[TvarFind[kf]],subdirf2(optionfilefiname,"ILK_"),k,subdirf2(optionfilefiname,"ILK_"),k,subdirf2(optionfilefiname,"ILK_"),k,Tvar[TvarFind[kf]]); + kvar=Tvar[TvarFind[kf]]; /* variable */ + fprintf(fichtm,"
- Probability p%dj by origin %d and destination j with colored covariate V%d. Same dot size of all points but with a different color for transitions with dummy variable V%d=1 at beginning of transition (keeping former color for V%d=0): ",k,k,Tvar[TvarFind[kf]],Tvar[TvarFind[kf]],Tvar[TvarFind[kf]]); + fprintf(fichtm,"%s-p%dj-%d.png
",subdirf2(optionfilefiname,"ILK_"),k,kvar,subdirf2(optionfilefiname,"ILK_"),k,kvar); + fprintf(fichtm,"",subdirf2(optionfilefiname,"ILK_"),k,Tvar[TvarFind[kf]]); } for(ncovv=1, iposold=0; ncovv <= ncovvt ; ncovv++){ /* Loop on the time varying extended covariates (with extension of Vn*Vm */ ipos=TvarVVind[ncovv]; /* TvarVVind={2, 5, 5] gives the position in the model of the ncovv th varying covariate */ @@ -4720,28 +6505,29 @@ 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,k, jk, jkk=0, iter=0; + int i,j, jkk=0, iter=0; double **xi; - double fret; - double fretone; /* Only one call to likelihood */ + /*double fret;*/ + /*double fretone;*/ /* Only one call to likelihood */ /* char filerespow[FILENAMELENGTH];*/ - + + /*double * p1;*/ /* Shifted parameters from 0 instead of 1 */ #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 (i=1;i<=npar;i++) /* Starting with canonical directions j=1,n xi[i=1,n][j] */ for (j=1;j<=npar;j++) xi[i][j]=(i==j ? 1.0 : 0.0); - printf("Powell\n"); fprintf(ficlog,"Powell\n"); + printf("Powell-prax\n"); fprintf(ficlog,"Powell-prax\n"); strcpy(filerespow,"POW_"); strcat(filerespow,fileres); if((ficrespow=fopen(filerespow,"w"))==NULL) { @@ -4805,7 +6591,23 @@ void mlikeli(FILE *ficres,double p[], in } powell(p,xi,npar,ftol,&iter,&fret,flatdir,func); #else /* FLATSUP */ - powell(p,xi,npar,ftol,&iter,&fret,func); +/* powell(p,xi,npar,ftol,&iter,&fret,func);*/ +/* praxis ( t0, h0, n, prin, x, beale_f ); */ + int prin=1; + double h0=0.25; + double macheps; + double fmin; + macheps=pow(16.0,-13.0); +/* #include "praxis.h" */ + /* Be careful that praxis start at x[0] and powell start at p[1] */ + /* praxis ( ftol, h0, npar, prin, p, func ); */ +/* p1= (p+1); */ /* p *(p+1)@8 and p *(p1)@8 are equal p1[0]=p[1] */ +printf("Praxis Gegenfurtner \n"); +fprintf(ficlog, "Praxis Gegenfurtner\n");fflush(ficlog); +/* praxis ( ftol, h0, npar, prin, p1, func ); */ + /* fmin = praxis(1.e-5,macheps, h, n, prin, x, func); */ + fmin = praxis(ftol,macheps, h0, npar, prin, p, func); +printf("End Praxis\n"); #endif /* FLATSUP */ #ifdef LINMINORIGINAL @@ -5067,6 +6869,7 @@ double hessij( double x[], double **hess kmax=kmax+10; } if(kmax >=10 || firstime ==1){ + /* What are the thetai and thetaj? thetai/ncovmodel thetai=(thetai-thetai%ncovmodel)/ncovmodel +thetai%ncovmodel=(line,pos) */ 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); @@ -5935,7 +7738,7 @@ void prevalence(double ***probs, double int i, m, jk, j1, bool, z1,j, iv; int mi; /* Effective wave */ int iage; - double agebegin, ageend; + double agebegin; /*, ageend;*/ double **prop; double posprop; @@ -6174,10 +7977,10 @@ void concatwav(int wav[], int **dh, int if(j==0) j=1; /* Survives at least one month after exam */ else if(j<0){ nberr++; - printf("Error! Negative delay (%d to death) between waves %d and %d of individual %ld at line %d who is aged %.1f with statuses from %d to %d\n ",j,mw[mi][i],mw[mi+1][i],num[i], i,agev[mw[mi][i]][i],s[mw[mi][i]][i] ,s[mw[mi+1][i]][i]); + printf("Error! Negative delay (%d to death) between waves %d and %d of individual %ld (around line %d) who is aged %.1f with statuses from %d to %d\n ",j,mw[mi][i],mw[mi+1][i],num[i], i,agev[mw[mi][i]][i],s[mw[mi][i]][i] ,s[mw[mi+1][i]][i]); j=1; /* Temporary Dangerous patch */ printf(" We assumed that the date of interview was correct (and not the date of death) and postponed the death %d month(s) (one stepm) after the interview. You MUST fix the contradiction between dates.\n",stepm); - fprintf(ficlog,"Error! Negative delay (%d to death) between waves %d and %d of individual %ld at line %d who is aged %.1f with statuses from %d to %d\n ",j,mw[mi][i],mw[mi+1][i],num[i], i,agev[mw[mi][i]][i],s[mw[mi][i]][i] ,s[mw[mi+1][i]][i]); + fprintf(ficlog,"Error! Negative delay (%d to death) between waves %d and %d of individual %ld (around line %d) who is aged %.1f with statuses from %d to %d\n ",j,mw[mi][i],mw[mi+1][i],num[i], i,agev[mw[mi][i]][i],s[mw[mi][i]][i] ,s[mw[mi+1][i]][i]); fprintf(ficlog," We assumed that the date of interview was correct (and not the date of death) and postponed the death %d month(s) (one stepm) after the interview. You MUST fix the contradiction between dates.\n",stepm); } k=k+1; @@ -6211,8 +8014,8 @@ void concatwav(int wav[], int **dh, int /*printf("%d %lf %d %d %d\n", i,agev[mw[mi][i]][i],j,s[mw[mi][i]][i] ,s[mw[mi+1][i]][i]);*/ if(j<0){ nberr++; - printf("Error! Negative delay (%d) between waves %d and %d of individual %ld at line %d who is aged %.1f with statuses from %d to %d\n ",j,mw[mi][i],mw[mi+1][i],num[i], i,agev[mw[mi][i]][i],s[mw[mi][i]][i] ,s[mw[mi+1][i]][i]); - fprintf(ficlog,"Error! Negative delay (%d) between waves %d and %d of individual %ld at line %d who is aged %.1f with statuses from %d to %d\n ",j,mw[mi][i],mw[mi+1][i],num[i], i,agev[mw[mi][i]][i],s[mw[mi][i]][i] ,s[mw[mi+1][i]][i]); + printf("Error! Negative delay (%d) between waves %d and %d of individual %ld (around line %d) who is aged %.1f with statuses from %d to %d\n ",j,mw[mi][i],mw[mi+1][i],num[i], i,agev[mw[mi][i]][i],s[mw[mi][i]][i] ,s[mw[mi+1][i]][i]); + fprintf(ficlog,"Error! Negative delay (%d) between waves %d and %d of individual %ld (around line %d) who is aged %.1f with statuses from %d to %d\n ",j,mw[mi][i],mw[mi+1][i],num[i], i,agev[mw[mi][i]][i],s[mw[mi][i]][i] ,s[mw[mi+1][i]][i]); } sum=sum+j; } @@ -6281,7 +8084,7 @@ void concatwav(int wav[], int **dh, int for (k=1; k<=cptcovt; k++) { /* cptcovt: total number of covariates of the model (2) nbocc(+)+1 = 8 excepting constant and age and age*age */ for (j=-1; (j < maxncov); j++) Ndum[j]=0; /* printf("Testing k=%d, cptcovt=%d\n",k, cptcovt); */ - if(Dummy[k]==0 && Typevar[k] !=1 && Typevar[k] != 2){ /* Dummy covariate and not age product nor fixed product */ + if(Dummy[k]==0 && Typevar[k] !=1 && Typevar[k] != 3 && Typevar[k] != 2){ /* Dummy covariate and not age product nor fixed product */ switch(Fixed[k]) { case 0: /* Testing on fixed dummy covariate, simple or product of fixed */ modmaxcovj=0; @@ -6378,7 +8181,7 @@ void concatwav(int wav[], int **dh, int break; } /* end switch */ } /* end dummy test */ - if(Dummy[k]==1 && Typevar[k] !=1 && Fixed ==0){ /* Fixed Quantitative covariate and not age product */ + if(Dummy[k]==1 && Typevar[k] !=1 && Typevar[k] !=3 && Fixed ==0){ /* Fixed Quantitative covariate and not age product */ for (i=1; i<=imx; i++) { /* Loop on individuals: reads the data file to get the maximum value of the modality of this covariate Vj*/ if(Tvar[k]<=0 || Tvar[k]>=NCOVMAX){ printf("Error k=%d \n",k); @@ -6780,7 +8583,9 @@ void concatwav(int wav[], int **dh, int /************ 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 + /** Computes the matrix of variance covariance of health expectancies e.j= sum_i w_i e_ij where w_i depends of popbased, + * either cross-sectional or implied. + * return vareij[i][j][(int)age]=cov(e.i,e.j)=sum_h sum_k trgrad(h_p.i) V(theta) grad(k_p.k) Equation 20 * 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) @@ -6797,7 +8602,7 @@ void concatwav(int wav[], int **dh, int 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 **varppt; /**< for var e.. nlstate+1 to nlstate+ndeath */ double ***p3mat; double age,agelim, hf; /* double ***mobaverage; */ @@ -6865,7 +8670,7 @@ void concatwav(int wav[], int **dh, int 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); + varppt = matrix(nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath); /* In fact, currently a double */ pstamp(ficresvij); fprintf(ficresvij,"# Variance and covariance of health expectancies e.j \n# (weighted average of eij where weights are "); if(popbased==1) @@ -6934,7 +8739,7 @@ void concatwav(int wav[], int **dh, int prlim[i][i]=mobaverage[(int)age][i][ij]; } } - /**< Computes the shifted transition matrix \f$ {}{h}_p^{ij}x\f$ at horizon h. + /**< Computes the shifted plus (gp) 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 @@ -6943,14 +8748,14 @@ void concatwav(int wav[], int **dh, int 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]; + gp[h][j] += prlim[i][i]*p3mat[i][j][h]; /* gp[h][j]= w_i h_pij */ } } /* 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(j=nlstate+1;j<=nlstate+ndeath;j++){ /* Currently only once for theta plus p.3(age) Sum_i wi pi3*/ for(i=1,gpp[j]=0.; i<= nlstate; i++) gpp[j] += prlim[i][i]*p3mat[i][j][1]; } @@ -6972,9 +8777,9 @@ void concatwav(int wav[], int **dh, int } } - hpxij(p3mat,nhstepm,age,hstepm,xp,nlstate,stepm,oldm,savm, ij,nres); + hpxij(p3mat,nhstepm,age,hstepm,xp,nlstate,stepm,oldm,savm, ij,nres); /* Still minus */ - for(j=1; j<= nlstate; j++){ /* Sum of wi * eij = e.j */ + for(j=1; j<= nlstate; j++){ /* gm[h][j]= Sum_i of wi * pij = h_p.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]; @@ -6982,37 +8787,39 @@ void concatwav(int wav[], int **dh, int } /* This for computing probability of death (h=1 means computed over hstepm matrices product = hstepm*stepm months) - as a weighted average of prlim. + as a weighted average of prlim. j is death. gmp[3]=sum_i w_i*p_i3=p.3 minus theta */ - for(j=nlstate+1;j<=nlstate+ndeath;j++){ + for(j=nlstate+1;j<=nlstate+ndeath;j++){ /* Currently only once theta_minus p.3=Sum_i wi pi3*/ 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 + /**< Computing gradient of p.j matrix at horizon h and still for one parameter of vector theta + * equation 31 and 32 */ - for(j=1; j<= nlstate; j++) /* vareij */ + for(j=1; j<= nlstate; j++) /* computes grad p.j(x, over each h) where p.j is Sum_i w_i*pij(x over h) + * equation 24 */ 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) + /**< Gradient of overall mortality p.3 (or p.death) */ - for(j=nlstate+1; j<= nlstate+ndeath; j++){ /* var mu mortality from j */ + for(j=nlstate+1; j<= nlstate+ndeath; j++){ /* computes grad of p.3 from wi+pi3 grad p.3 (theta) */ 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 */ + /* We got the gradient matrix for each theta and each state j of gradg(h]theta][j)=grad(_hp.j(theta) */ + trgradg =ma3x(0,nhstepm,1,nlstate,1,npar); - for(h=0; h<=nhstepm; h++) /* veij */ + for(h=0; h<=nhstepm; h++) /* veij */ /* computes the transposed of grad (_hp.j(theta)*/ 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(j=nlstate+1; j<=nlstate+ndeath;j++) /* computes transposed of grad p.3 (theta)*/ for(theta=1; theta <=npar; theta++) trgradgp[j][theta]=gradgp[theta][j]; /**< as well as its transposed matrix @@ -7024,8 +8831,11 @@ void concatwav(int wav[], int **dh, int 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 + * and k (nhstepm) formula 32 of article + * Lievre-Brouard-Heathcote so that for each j, computes the cov(e.j,e.k) (formula 31). + * for given h and k computes trgradg[h](i,j) matcov (theta) gradg(k)(i,j) into vareij[i][j] which is + cov(e.i,e.j) and sums on h and k + * including the covariances. */ for(h=0;h<=nhstepm;h++){ @@ -7034,20 +8844,21 @@ void concatwav(int wav[], int **dh, int 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; + vareij[i][j][(int)age] += doldm[i][j]*hf*hf; /* This is vareij=sum_h sum_k trgrad(h_pij) V(theta) grad(k_pij) + including the covariances of e.j */ } } - /* pptj is p.3 or p.j = trgradgp by cov by gradgp, variance of - * p.j overall mortality formula 49 but computed directly because + /* Mortality: pptj is p.3 or p.death = trgradgp by cov by gradgp, variance of + * p.3=1-p..=1-sum i p.i overall mortality computed directly because * we compute the grad (wix pijx) instead of grad (pijx),even if - * wix is independent of theta. + * 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]; + varppt[j][i]=doldmp[j][i]; /* This is the variance of p.3 */ /* end ppptj */ /* x centered again */ @@ -7070,15 +8881,15 @@ void concatwav(int wav[], int **dh, int 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]; + gmp[j] += prlim[i][i]*p3mat[i][j][1]; /* gmp[j] is p.3 */ } /* 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])); + fprintf(ficresprobmorprev," %11.3e %11.3e",gmp[j], sqrt(varppt[j][j]));/* p.3 (STD p.3) */ for(i=1; i<=nlstate;i++){ - fprintf(ficresprobmorprev," %11.3e %11.3e ",prlim[i][i],p3mat[i][j][1]); + fprintf(ficresprobmorprev," %11.3e %11.3e ",prlim[i][i],p3mat[i][j][1]); /* wi, pi3 */ } } fprintf(ficresprobmorprev,"\n"); @@ -7404,7 +9215,7 @@ void varprob(char optionfilefiname[], do double ***varpij; strcpy(fileresprob,"PROB_"); - strcat(fileresprob,fileres); + strcat(fileresprob,fileresu); if((ficresprob=fopen(fileresprob,"w"))==NULL) { printf("Problem with resultfile: %s\n", fileresprob); fprintf(ficlog,"Problem with resultfile: %s\n", fileresprob); @@ -7561,7 +9372,7 @@ To be simple, these graphs help to under cov[3]= age*age; /* New code end of combination but for each resultline */ for(k1=1;k1<=cptcovt;k1++){ /* loop on model equation (including products) */ - if(Typevar[k1]==1){ /* A product with age */ + if(Typevar[k1]==1 || Typevar[k1] ==3){ /* A product with age */ cov[2+nagesqr+k1]=precov[nres][k1]*cov[2]; }else{ cov[2+nagesqr+k1]=precov[nres][k1]; @@ -7822,7 +9633,7 @@ void printinghtml(char fileresu[], char int popforecast, int mobilav, int prevfcast, int mobilavproj, int prevbcast, int estepm , \ double jprev1, double mprev1,double anprev1, double dateprev1, double dateprojd, double dateback1, \ double jprev2, double mprev2,double anprev2, double dateprev2, double dateprojf, double dateback2){ - int jj1, k1, i1, cpt, k4, nres; + int jj1, k1, cpt, nres; /* In fact some results are already printed in fichtm which is open */ fprintf(fichtm,"
    • Result files (first order: no variance)\n \
    • Result files (second order (variance)\n \ @@ -7959,21 +9770,21 @@ divided by h: hPij ",stepm,subdirf2(optionfilefiname,"PE_"),k1,nres,subdirf2(optionfilefiname,"PE_"),k1,nres,subdirf2(optionfilefiname,"PE_"),k1,nres); /* Survival functions (period) in state j */ for(cpt=1; cpt<=nlstate;cpt++){ - fprintf(fichtm,"
      \n- Survival functions in state %d. And probability to be observed in state %d being in state (1 to %d) at different ages. %s_%d-%d-%d.svg
      ", cpt, cpt, nlstate, subdirf2(optionfilefiname,"LIJ_"),cpt,k1,nres,subdirf2(optionfilefiname,"LIJ_"),cpt,k1,nres); + fprintf(fichtm,"
      \n- Survival functions in state %d. And probability to be observed in state %d being in state (1 to %d) at different ages. Mean times spent in state (or Life Expectancy or Health Expectancy etc.) are the areas under each curve. %s_%d-%d-%d.svg
      ", cpt, cpt, nlstate, subdirf2(optionfilefiname,"LIJ_"),cpt,k1,nres,subdirf2(optionfilefiname,"LIJ_"),cpt,k1,nres); fprintf(fichtm," (data from text file %s.txt)\n
      ",subdirf2(optionfilefiname,"PIJ_"),subdirf2(optionfilefiname,"PIJ_")); fprintf(fichtm,"",subdirf2(optionfilefiname,"LIJ_"),cpt,k1,nres); } /* State specific survival functions (period) */ for(cpt=1; cpt<=nlstate;cpt++){ fprintf(fichtm,"
      \n- Survival functions in state %d and in any other live state (total).\ - And probability to be observed in various states (up to %d) being in state %d at different ages. \ + And probability to be observed in various states (up to %d) being in state %d at different ages. Mean times spent in state (or Life Expectancy or Health Expectancy etc.) are the areas under each curve. \ %s_%d-%d-%d.svg
      ", cpt, nlstate, cpt, subdirf2(optionfilefiname,"LIJT_"),cpt,k1,nres,subdirf2(optionfilefiname,"LIJT_"),cpt,k1,nres); fprintf(fichtm," (data from text file %s.txt)\n
      ",subdirf2(optionfilefiname,"PIJ_"),subdirf2(optionfilefiname,"PIJ_")); fprintf(fichtm,"",subdirf2(optionfilefiname,"LIJT_"),cpt,k1,nres); } /* Period (forward stable) prevalence in each health state */ for(cpt=1; cpt<=nlstate;cpt++){ - fprintf(fichtm,"
      \n- Convergence to period (stable) prevalence in state %d. Or probability for a person being in state (1 to %d) at different ages, to be in state %d some years after. %s_%d-%d-%d.svg
      ", cpt, nlstate, cpt, subdirf2(optionfilefiname,"P_"),cpt,k1,nres,subdirf2(optionfilefiname,"P_"),cpt,k1,nres); + fprintf(fichtm,"
      \n- Convergence to period (stable) prevalence in state %d. Or probability for a person being in state (1 to %d) at different ages, to be alive in state %d some years after. %s_%d-%d-%d.svg
      ", cpt, nlstate, cpt, subdirf2(optionfilefiname,"P_"),cpt,k1,nres,subdirf2(optionfilefiname,"P_"),cpt,k1,nres); fprintf(fichtm," (data from text file %s.txt)\n
      ",subdirf2(optionfilefiname,"PIJ_"),subdirf2(optionfilefiname,"PIJ_")); fprintf(fichtm,"" ,subdirf2(optionfilefiname,"P_"),cpt,k1,nres); } @@ -7998,8 +9809,8 @@ divided by h: hPij /* Back projection of prevalence up to stable (mixed) back-prevalence in each health state */ for(cpt=1; cpt<=nlstate;cpt++){ fprintf(fichtm,"
      \n- Back projection of cross-sectional prevalence (estimated with cases observed from %.1f to %.1f and mobil_average=%d), \ - from year %.1f up to year %.1f (probably close to stable [mixed] back prevalence in state %d (randomness in cross-sectional prevalence is not taken into \ - account but can visually be appreciated). Or probability to have been in an state %d, knowing that the person was in either state (1 or %d) \ + from year %.1f up to year %.1f (probably close to stable [mixed] back prevalence in state %d). Randomness in cross-sectional prevalence is not taken into \ + account but can visually be appreciated. Or probability to have been in an state %d, knowing that the person was in either state (1 or %d) \ with weights corresponding to observed prevalence at different ages. %s_%d-%d-%d.svg", dateprev1, dateprev2, mobilavproj, dateback1, dateback2, cpt, cpt, nlstate, subdirf2(optionfilefiname,"PROJB_"),cpt,k1,nres,subdirf2(optionfilefiname,"PROJB_"),cpt,k1,nres); fprintf(fichtm," (data from text file %s.txt)\n
      ",subdirf2(optionfilefiname,"FB_"),subdirf2(optionfilefiname,"FB_")); fprintf(fichtm," ", subdirf2(optionfilefiname,"PROJB_"),cpt,k1,nres); @@ -8137,7 +9948,10 @@ prevalence (with 95%% confidence interva fprintf(fichtm,"",subdirf2(optionfilefiname,"V_"), cpt,k1,nres); } fprintf(fichtm,"\n
      - Total life expectancy by age and \ -health expectancies in each live states (1 to %d). If popbased=1 the smooth (due to the model) \ +health expectancies in each live state (1 to %d) with confidence intervals \ +on left y-scale as well as proportions of time spent in each live state \ +(with confidence intervals) on right y-scale 0 to 100%%.\ + If popbased=1 the smooth (due to the model) \ true period expectancies (those weighted with period prevalences are also\ drawn in addition to the population based expectancies computed using\ observed and cahotic prevalences: %s_%d-%d.svg",nlstate, subdirf2(optionfilefiname,"E_"),k1,nres,subdirf2(optionfilefiname,"E_"),k1,nres); @@ -8152,8 +9966,8 @@ true period expectancies (those weighted /******************* Gnuplot file **************/ void printinggnuplot(char fileresu[], char optionfilefiname[], double ageminpar, double agemaxpar, double bage, double fage , int prevfcast, int prevbcast, char pathc[], double p[], int offyear, int offbyear){ - char dirfileres[132],optfileres[132]; - char gplotcondition[132], gplotlabel[132]; + char dirfileres[256],optfileres[256]; + char gplotcondition[256], gplotlabel[256]; int cpt=0,k1=0,i=0,k=0,j=0,jk=0,k2=0,k3=0,k4=0,kf=0,kvar=0,kk=0,ipos=0,iposold=0,ij=0, ijp=0, l=0; int lv=0, vlv=0, kl=0; int ng=0; @@ -8221,14 +10035,24 @@ void printinggnuplot(char fileresu[], ch fprintf(ficgp,"\nset ter pngcairo size 640, 480"); /* if(debugILK==1){ */ for(kf=1; kf <= ncovf; kf++){ /* For each simple dummy covariate of the model */ - kvar=Tvar[TvarFind[kf]]; /* variable */ - k=18+Tvar[TvarFind[kf]];/*offset because there are 18 columns in the ILK_ file */ + kvar=Tvar[TvarFind[kf]]; /* variable name */ + /* k=18+Tvar[TvarFind[kf]];/\*offset because there are 18 columns in the ILK_ file but could be placed else where *\/ */ + /* k=18+kf;/\*offset because there are 18 columns in the ILK_ file *\/ */ + /* k=19+kf;/\*offset because there are 19 columns in the ILK_ file *\/ */ + k=16+nlstate+kf;/*offset because there are 19 columns in the ILK_ file, first cov Vn on col 21 with 4 living states */ for (i=1; i<= nlstate ; i ++) { fprintf(ficgp,"\nset out \"%s-p%dj-%d.png\";set ylabel \"Probability for each individual/wave\";",subdirf2(optionfilefiname,"ILK_"),i,kvar); fprintf(ficgp,"unset log;\n# For each simple dummy covariate of the model \n plot \"%s\"",subdirf(fileresilk)); - fprintf(ficgp," u 2:($5 == %d && $6==%d ? $10 : 1/0):($%d==0 ? 7 : 9):($%d==0 ? $6 : $6+4) t \"p%d%d V%d\" with points pt variable ps 0.4 lc variable \\\n",i,1,k,k,i,1,kvar); - for (j=2; j<= nlstate+ndeath ; j ++) { - fprintf(ficgp,",\\\n \"\" u 2:($5 == %d && $6==%d ? $10 : 1/0):($%d==0 ? 7 : 9):($%d==0 ? $6 : $6+4) t \"p%d%d V%d\" with points pt variable ps 0.4 lc variable ",i,j,k,k,i,j,kvar); + if(gnuplotversion >=5.2){ /* Former gnuplot versions do not have variable pointsize!! */ + fprintf(ficgp," u 2:($5 == %d && $6==%d ? $10 : 1/0):($%d==0 ? 7 : 9):($%d==0 ? $6 : $6+4) t \"p%d%d V%d\" with points pt variable ps 0.4 lc variable \\\n",i,1,k,k,i,1,kvar); + for (j=2; j<= nlstate+ndeath ; j ++) { + fprintf(ficgp,",\\\n \"\" u 2:($5 == %d && $6==%d ? $10 : 1/0):($%d==0 ? 7 : 9):($%d==0 ? $6 : $6+4) t \"p%d%d V%d\" with points pt variable ps 0.4 lc variable ",i,j,k,k,i,j,kvar); + } + }else{ + fprintf(ficgp," u 2:($5 == %d && $6==%d ? $10 : 1/0):($%d==0 ? $6 : $6+4) t \"p%d%d V%d\" with points pt 7 ps 0.4 lc variable \\\n",i,1,k,i,1,kvar); + for (j=2; j<= nlstate+ndeath ; j ++) { + fprintf(ficgp,",\\\n \"\" u 2:($5 == %d && $6==%d ? $10 : 1/0):($%d==0 ? $6 : $6+4) t \"p%d%d V%d\" with points pt 7 ps 0.4 lc variable ",i,j,k,i,j,kvar); + } } fprintf(ficgp,";\nset out; unset ylabel;\n"); } @@ -8258,6 +10082,7 @@ void printinggnuplot(char fileresu[], ch fprintf(ficgp,"\nset out \"%s-p%dj-%d.png\";set ylabel \"Probability for each individual/wave\";",subdirf2(optionfilefiname,"ILK_"),i,kvar); fprintf(ficgp,"unset log;\n# For each simple dummy covariate of the model \n plot \"%s\"",subdirf(fileresilk)); + /* printf("Before DebugILK gnuplotversion=%g >=5.2\n",gnuplotversion); */ if(gnuplotversion >=5.2){ /* Former gnuplot versions do not have variable pointsize!! */ /* printf("DebugILK gnuplotversion=%g >=5.2\n",gnuplotversion); */ fprintf(ficgp," u 2:($5 == %d && $6==%d ? $10 : 1/0):($%d==0 ? 7 : 9):($%d==0 ? $6 : $6+4) t \"p%d%d V%d\" with points pt variable ps 0.4 lc variable \\\n",i,1,k,k,i,1,kvar); @@ -8480,18 +10305,18 @@ void printinggnuplot(char fileresu[], ch for(vpopbased=0; vpopbased <= popbased; vpopbased++){ /* Done for vpopbased=0 and vpopbased=1 if popbased==1*/ fprintf(ficgp,"\nset label \"popbased %d %s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",vpopbased,gplotlabel); if(vpopbased==0){ - fprintf(ficgp,"set ylabel \"Years\" \nset ter svg size 640, 480\nplot [%.f:%.f] ",ageminpar,fage); + fprintf(ficgp,"set ylabel \"Years\" \nset ter svg size 640, 480\nunset ytics; unset y2tics; set ytics nomirror; set y2tics 0,10,100;set y2range [0:100];\nplot [%.f:%.f] ",ageminpar,fage); }else fprintf(ficgp,"\nreplot "); - for (i=1; i<= nlstate+1 ; i ++) { + for (i=1; i<= nlstate+1 ; i ++) { /* For state i-1=0 is LE, while i-1=1 to nlstate are origin state */ k=2*i; - fprintf(ficgp,"\"%s\" every :::%d::%d u 1:($2==%d && $4!=0 ?$4 : 1/0) \"%%lf %%lf %%lf",subdirf2(fileresu,"T_"),nres-1,nres-1, vpopbased); - for (j=1; j<= nlstate+1 ; j ++) { - if (j==i) fprintf(ficgp," %%lf (%%lf)"); - else fprintf(ficgp," %%*lf (%%*lf)"); + fprintf(ficgp,"\"%s\" every :::%d::%d u 1:($2==%d && $4!=0 ?$4 : 1/0) \"%%lf %%lf %%lf",subdirf2(fileresu,"T_"),nres-1,nres-1, vpopbased); /* for fixed variables age, popbased, mobilav */ + for (j=1; j<= nlstate+1 ; j ++) { /* e.. e.1 e.2 again j-1 is the state of end, wlim_i eij*/ + if (j==i) fprintf(ficgp," %%lf (%%lf)"); /* We want to read e.. i=1,j=1, e.1 i=2,j=2, e.2 i=3,j=3 */ + else fprintf(ficgp," %%*lf (%%*lf)"); /* skipping that field with a star */ } if (i== 1) fprintf(ficgp,"\" t\"TLE\" w l lt %d, \\\n",i); - else fprintf(ficgp,"\" t\"LE in state (%d)\" w l lt %d, \\\n",i-1,i+1); + else fprintf(ficgp,"\" t\"LE in state (%d)\" w l lt %d, \\\n",i-1,i+1); /* state=i-1=1 to nlstate */ fprintf(ficgp,"\"%s\" every :::%d::%d u 1:($2==%d && $4!=0 ? $4-$5*2 : 1/0) \"%%lf %%lf %%lf",subdirf2(fileresu,"T_"),nres-1,nres-1,vpopbased); for (j=1; j<= nlstate+1 ; j ++) { if (j==i) fprintf(ficgp," %%lf (%%lf)"); @@ -8503,9 +10328,39 @@ void printinggnuplot(char fileresu[], ch if (j==i) fprintf(ficgp," %%lf (%%lf)"); else fprintf(ficgp," %%*lf (%%*lf)"); } - if (i== (nlstate+1)) fprintf(ficgp,"\" t\"\" w l lt 0"); + if (i== (nlstate+1)) fprintf(ficgp,"\" t\"\" w l lt 0,\\\n"); /* ,\\\n added for th percentage graphs */ else fprintf(ficgp,"\" t\"\" w l lt 0,\\\n"); } /* state */ + /* again for the percentag spent in state i-1=1 to i-1=nlstate */ + for (i=2; i<= nlstate+1 ; i ++) { /* For state i-1=0 is LE, while i-1=1 to nlstate are origin state */ + k=2*i; + fprintf(ficgp,"\"%s\" every :::%d::%d u 1:($2==%d && ($4)<=1 && ($4)>=0 ?($4)*100. : 1/0) \"%%lf %%lf %%lf",subdirf2(fileresu,"T_"),nres-1,nres-1, vpopbased); /* for fixed variables age, popbased, mobilav */ + for (j=1; j<= nlstate ; j ++) + fprintf(ficgp," %%*lf (%%*lf)"); /* Skipping TLE and LE to read %LE only */ + for (j=1; j<= nlstate+1 ; j ++) { /* e.. e.1 e.2 again j-1 is the state of end, wlim_i eij*/ + if (j==i) fprintf(ficgp," %%lf (%%lf)"); /* We want to read e.. i=1,j=1, e.1 i=2,j=2, e.2 i=3,j=3 */ + else fprintf(ficgp," %%*lf (%%*lf)"); /* skipping that field with a star */ + } + if (i== 1) fprintf(ficgp,"\" t\"%%TLE\" w l lt %d axis x1y2, \\\n",i); /* Not used */ + else fprintf(ficgp,"\" t\"%%LE in state (%d)\" w l lw 2 lt %d axis x1y2, \\\n",i-1,i+1); /* state=i-1=1 to nlstate */ + fprintf(ficgp,"\"%s\" every :::%d::%d u 1:($2==%d && ($4-$5*2)<=1 && ($4-$5*2)>=0? ($4-$5*2)*100. : 1/0) \"%%lf %%lf %%lf",subdirf2(fileresu,"T_"),nres-1,nres-1,vpopbased); + for (j=1; j<= nlstate ; j ++) + fprintf(ficgp," %%*lf (%%*lf)"); /* Skipping TLE and LE to read %LE only */ + for (j=1; j<= nlstate+1 ; j ++) { + if (j==i) fprintf(ficgp," %%lf (%%lf)"); + else fprintf(ficgp," %%*lf (%%*lf)"); + } + fprintf(ficgp,"\" t\"\" w l lt 0 axis x1y2,"); + fprintf(ficgp,"\"%s\" every :::%d::%d u 1:($2==%d && ($4+$5*2)<=1 && ($4+$5*2)>=0 ? ($4+$5*2)*100. : 1/0) \"%%lf %%lf %%lf",subdirf2(fileresu,"T_"),nres-1,nres-1,vpopbased); + for (j=1; j<= nlstate ; j ++) + fprintf(ficgp," %%*lf (%%*lf)"); /* Skipping TLE and LE to read %LE only */ + for (j=1; j<= nlstate+1 ; j ++) { + if (j==i) fprintf(ficgp," %%lf (%%lf)"); + else fprintf(ficgp," %%*lf (%%*lf)"); + } + if (i== (nlstate+1)) fprintf(ficgp,"\" t\"\" w l lt 0 axis x1y2"); + else fprintf(ficgp,"\" t\"\" w l lt 0 axis x1y2,\\\n"); + } /* state for percent */ } /* vpopbased */ fprintf(ficgp,"\nset out;set out \"%s_%d-%d.svg\"; replot; set out; unset label;\n",subdirf2(optionfilefiname,"E_"),k1,nres); /* Buggy gnuplot */ } /* end nres */ @@ -8900,18 +10755,22 @@ set ter svg size 640, 480\nunset log y\n fprintf(ficgp," u %d:(",ioffset); kl=0; strcpy(gplotcondition,"("); - for (k=1; k<=cptcoveff; k++){ /* For each covariate writing the chain of conditions */ + /* for (k=1; k<=cptcoveff; k++){ /\* For each covariate writing the chain of conditions *\/ */ /* lv= decodtabm(k1,k,cptcoveff); /\* Should be the covariate value corresponding to combination k1 and covariate k *\/ */ - lv=codtabm(k1,TnsdVar[Tvaraff[k]]); + for (k=1; k<=cptcovs; k++){ /* For each covariate k get corresponding value lv for combination k1 */ + /* lv=codtabm(k1,TnsdVar[Tvaraff[k]]); */ + lv=Tvresult[nres][k]; + vlv=TinvDoQresult[nres][Tvresult[nres][k]]; /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */ /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */ /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */ /* vlv= nbcode[Tvaraff[k]][lv]; /\* Value of the modality of Tvaraff[k] *\/ */ - vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; + /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */ kl++; - sprintf(gplotcondition+strlen(gplotcondition),"$%d==%d && $%d==%d " ,kl,Tvaraff[k], kl+1, nbcode[Tvaraff[k]][lv]); + /* sprintf(gplotcondition+strlen(gplotcondition),"$%d==%d && $%d==%d " ,kl,Tvaraff[k], kl+1, nbcode[Tvaraff[k]][lv]); */ + sprintf(gplotcondition+strlen(gplotcondition),"$%d==%d && $%d==%d " ,kl,lv, kl+1, vlv ); kl++; - if(k 1) + if(k 1) sprintf(gplotcondition+strlen(gplotcondition)," && "); } strcpy(gplotcondition+strlen(gplotcondition),")"); @@ -8995,7 +10854,8 @@ set ter svg size 640, 480\nunset log y\n }else{ fprintf(ficgp,",\\\n '' "); } - if(cptcoveff ==0){ /* No covariate */ + /* if(cptcoveff ==0){ /\* No covariate *\/ */ + if(cptcovs ==0){ /* No covariate */ ioffset=2; /* Age is in 2 */ /*# yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/ /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */ @@ -9107,7 +10967,8 @@ set ter svg size 640, 480\nunset log y\n fprintf(ficgp,"#Number of graphics: first is logit, 2nd is probabilities, third is incidences per year\n"); fprintf(ficgp,"#model=1+age+%s \n",model); fprintf(ficgp,"# Type of graphic ng=%d\n",ng); - fprintf(ficgp,"# k1=1 to 2^%d=%d\n",cptcoveff,m);/* to be checked */ + /* fprintf(ficgp,"# k1=1 to 2^%d=%d\n",cptcoveff,m);/\* to be checked *\/ */ + fprintf(ficgp,"# k1=1 to 2^%d=%d\n",cptcovs,m);/* to be checked */ /* for(k1=1; k1 <=m; k1++) /\* For each combination of covariate *\/ */ for(nres=1; nres <= nresult; nres++){ /* For each resultline */ /* k1=nres; */ @@ -9232,6 +11093,31 @@ set ter svg size 640, 480\nunset log y\n } /* end Tprod */ } break; + case 3: + if(cptcovdageprod >0){ + /* if(j==Tprod[ijp]) { */ /* not necessary */ + /* printf("Tprod[%d]=%d, j=%d\n", ij, Tprod[ijp], j); */ + if(ijp <=cptcovprod) { /* Product Vn*Vm and age*VN*Vm*/ + if(DummyV[Tvardk[ijp][1]]==0){/* Vn is dummy */ + if(DummyV[Tvardk[ijp][2]]==0){/* Vn and Vm are dummy */ + /* fprintf(ficgp,"+p%d*%d*%d",i+j+2+nagesqr-1,nbcode[Tvard[ijp][1]][codtabm(k1,j)],nbcode[Tvard[ijp][2]][codtabm(k1,j)]); */ + fprintf(ficgp,"+p%d*%d*%d*x",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tinvresult[nres][Tvard[ijp][2]]); + }else{ /* Vn is dummy and Vm is quanti */ + /* fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,nbcode[Tvard[ijp][1]][codtabm(k1,j)],Tqinvresult[nres][Tvard[ijp][2]]); */ + fprintf(ficgp,"+p%d*%d*%f*x",i+j+2+nagesqr-1,Tinvresult[nres][Tvardk[ijp][1]],Tqinvresult[nres][Tvardk[ijp][2]]); + } + }else{ /* age* Vn*Vm Vn is quanti HERE */ + if(DummyV[Tvard[ijp][2]]==0){ + fprintf(ficgp,"+p%d*%d*%f*x",i+j+2+nagesqr-1,Tinvresult[nres][Tvardk[ijp][2]],Tqinvresult[nres][Tvardk[ijp][1]]); + }else{ /* Both quanti */ + fprintf(ficgp,"+p%d*%f*%f*x",i+j+2+nagesqr-1,Tqinvresult[nres][Tvardk[ijp][1]],Tqinvresult[nres][Tvardk[ijp][2]]); + } + } + ijp++; + } + /* } */ /* end Tprod */ + } + break; case 0: /* simple covariate */ /* fprintf(ficgp,"+p%d*%d",i+j+2+nagesqr-1,nbcode[Tvar[j]][codtabm(k1,j)]); /\* Valgrind bug nbcode *\/ */ @@ -9318,6 +11204,35 @@ set ter svg size 640, 480\nunset log y\n } /* end Tprod */ } /* end if */ break; + case 3: + if(cptcovdageprod >0){ + /* if(j==Tprod[ijp]) { /\* *\/ */ + /* printf("Tprod[%d]=%d, j=%d\n", ij, Tprod[ijp], j); */ + if(ijp <=cptcovprod) { /* Product */ + if(DummyV[Tvardk[ijp][1]]==0){/* Vn is dummy */ + if(DummyV[Tvardk[ijp][2]]==0){/* Vn and Vm are dummy */ + /* fprintf(ficgp,"+p%d*%d*%d",i+j+2+nagesqr-1,nbcode[Tvard[ijp][1]][codtabm(k1,j)],nbcode[Tvard[ijp][2]][codtabm(k1,j)]); */ + fprintf(ficgp,"+p%d*%d*%d*x",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tinvresult[nres][Tvardk[ijp][1]],Tinvresult[nres][Tvardk[ijp][2]]); + /* fprintf(ficgp,"+p%d*%d*%d",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tinvresult[nres][Tvard[ijp][2]]); */ + }else{ /* Vn is dummy and Vm is quanti */ + /* fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,nbcode[Tvard[ijp][1]][codtabm(k1,j)],Tqinvresult[nres][Tvard[ijp][2]]); */ + fprintf(ficgp,"+p%d*%d*%f*x",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tinvresult[nres][Tvardk[ijp][1]],Tqinvresult[nres][Tvardk[ijp][2]]); + /* fprintf(ficgp,"+p%d*%d*%f*x",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]); */ + } + }else{ /* Vn*Vm Vn is quanti */ + if(DummyV[Tvardk[ijp][2]]==0){ + fprintf(ficgp,"+p%d*%d*%f",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tinvresult[nres][Tvardk[ijp][2]],Tqinvresult[nres][Tvardk[ijp][1]]); + /* fprintf(ficgp,"+p%d*%d*%f*x",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][2]],Tqinvresult[nres][Tvard[ijp][1]]); */ + }else{ /* Both quanti */ + fprintf(ficgp,"+p%d*%f*%f",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tqinvresult[nres][Tvardk[ijp][1]],Tqinvresult[nres][Tvardk[ijp][2]]); + /* fprintf(ficgp,"+p%d*%f*%f*x",i+j+2+nagesqr-1,Tqinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]); */ + } + } + ijp++; + } + /* } /\* end Tprod *\/ */ + } /* end if */ + break; case 0: /* simple covariate */ /* fprintf(ficgp,"+p%d*%d",i+j+2+nagesqr-1,nbcode[Tvar[j]][codtabm(k1,j)]); /\* Valgrind bug nbcode *\/ */ @@ -9615,10 +11530,10 @@ void prevforecast(char fileres[], double */ /* double anprojd, mprojd, jprojd; */ /* double anprojf, mprojf, jprojf; */ - int yearp, stepsize, hstepm, nhstepm, j, k, cptcod, i, h, i1, k4, nres=0; + int yearp, stepsize, hstepm, nhstepm, j, k, i, h, nres=0; double agec; /* generic age */ - double agelim, ppij, yp,yp1,yp2; - double *popeffectif,*popcount; + double agelim, ppij; + /*double *popcount;*/ double ***p3mat; /* double ***mobaverage; */ char fileresf[FILENAMELENGTH]; @@ -9671,30 +11586,36 @@ void prevforecast(char fileres[], double /* date2dmy(dateintmean,&jintmean,&mintmean,&aintmean); */ /* date2dmy(dateprojd,&jprojd, &mprojd, &anprojd); */ /* date2dmy(dateprojf,&jprojf, &mprojf, &anprojf); */ - i1=pow(2,cptcoveff); - if (cptcovn < 1){i1=1;} + /* i1=pow(2,cptcoveff); */ + /* if (cptcovn < 1){i1=1;} */ fprintf(ficresf,"# Mean day of interviews %.lf/%.lf/%.lf (%.2f) between %.2f and %.2f \n",jintmean,mintmean,aintmean,dateintmean,dateprev1,dateprev2); fprintf(ficresf,"#****** Routine prevforecast **\n"); /* if (h==(int)(YEARM*yearp)){ */ - for(nres=1; nres <= nresult; nres++) /* For each resultline */ - for(k=1; k<=i1;k++){ /* We want to find the combination k corresponding to the values of the dummies given in this resut line (to be cleaned one day) */ - if(i1 != 1 && TKresult[nres]!= k) - continue; - if(invalidvarcomb[k]){ - printf("\nCombination (%d) projection ignored because no cases \n",k); - continue; - } + for(nres=1; nres <= nresult; nres++){ /* For each resultline */ + k=TKresult[nres]; + if(TKresult[nres]==0) k=1; /* To be checked for noresult */ + /* for(k=1; k<=i1;k++){ /\* We want to find the combination k corresponding to the values of the dummies given in this resut line (to be cleaned one day) *\/ */ + /* if(i1 != 1 && TKresult[nres]!= k) */ + /* continue; */ + /* if(invalidvarcomb[k]){ */ + /* printf("\nCombination (%d) projection ignored because no cases \n",k); */ + /* continue; */ + /* } */ fprintf(ficresf,"\n#****** hpijx=probability over h years, hp.jx is weighted by observed prev \n#"); - for(j=1;j<=cptcoveff;j++) { - /* fprintf(ficresf," V%d (=) %d",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,Tvaraff[j])]); */ - fprintf(ficresf," V%d (=) %d",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); - } - for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */ - fprintf(ficresf," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); + for(j=1;j<=cptcovs;j++){ + /* for(j=1;j<=cptcoveff;j++) { */ + /* /\* fprintf(ficresf," V%d (=) %d",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,Tvaraff[j])]); *\/ */ + /* fprintf(ficresf," V%d (=) %d",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */ + /* } */ + /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */ + /* fprintf(ficresf," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */ + /* } */ + fprintf(ficresf," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]); } + fprintf(ficresf," yearproj age"); for(j=1; j<=nlstate+ndeath;j++){ for(i=1; i<=nlstate;i++) @@ -9719,9 +11640,11 @@ void prevforecast(char fileres[], double } } fprintf(ficresf,"\n"); - for(j=1;j<=cptcoveff;j++) + /* for(j=1;j<=cptcoveff;j++) */ + for(j=1;j<=cptcovs;j++) + fprintf(ficresf,"%d %lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]); /* fprintf(ficresf,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,Tvaraff[j])]); /\* Tvaraff not correct *\/ */ - fprintf(ficresf,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); /* TnsdVar[Tvaraff] correct */ + /* fprintf(ficresf,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); /\* TnsdVar[Tvaraff] correct *\/ */ fprintf(ficresf,"%.f %.f ",anprojd+yearp,agec+h*hstepm/YEARM*stepm); for(j=1; j<=nlstate+ndeath;j++) { @@ -9758,10 +11681,10 @@ void prevforecast(char fileres[], double anback2 year of end of backprojection (same day and month as back1). prevacurrent and prev are prevalences. */ - int yearp, stepsize, hstepm, nhstepm, j, k, cptcod, i, h, i1, k4, nres=0; + int yearp, stepsize, hstepm, nhstepm, j, k, i, h, nres=0; double agec; /* generic age */ - double agelim, ppij, ppi, yp,yp1,yp2; /* ,jintmean,mintmean,aintmean;*/ - double *popeffectif,*popcount; + double agelim, ppij, ppi; /* ,jintmean,mintmean,aintmean;*/ + /*double *popcount;*/ double ***p3mat; /* double ***mobaverage; */ char fileresfb[FILENAMELENGTH]; @@ -9813,29 +11736,35 @@ void prevforecast(char fileres[], double /* if(jintmean==0) jintmean=1; */ /* if(mintmean==0) jintmean=1; */ - i1=pow(2,cptcoveff); - if (cptcovn < 1){i1=1;} + /* i1=pow(2,cptcoveff); */ + /* if (cptcovn < 1){i1=1;} */ fprintf(ficresfb,"# Mean day of interviews %.lf/%.lf/%.lf (%.2f) between %.2f and %.2f \n",jintmean,mintmean,aintmean,dateintmean,dateprev1,dateprev2); printf("# Mean day of interviews %.lf/%.lf/%.lf (%.2f) between %.2f and %.2f \n",jintmean,mintmean,aintmean,dateintmean,dateprev1,dateprev2); fprintf(ficresfb,"#****** Routine prevbackforecast **\n"); - for(nres=1; nres <= nresult; nres++) /* For each resultline */ - for(k=1; k<=i1;k++){ - if(i1 != 1 && TKresult[nres]!= k) - continue; - if(invalidvarcomb[k]){ - printf("\nCombination (%d) projection ignored because no cases \n",k); - continue; - } + for(nres=1; nres <= nresult; nres++){ /* For each resultline */ + k=TKresult[nres]; + if(TKresult[nres]==0) k=1; /* To be checked for noresult */ + /* for(k=1; k<=i1;k++){ */ + /* if(i1 != 1 && TKresult[nres]!= k) */ + /* continue; */ + /* if(invalidvarcomb[k]){ */ + /* printf("\nCombination (%d) projection ignored because no cases \n",k); */ + /* continue; */ + /* } */ fprintf(ficresfb,"\n#****** hbijx=probability over h years, hb.jx is weighted by observed prev \n#"); - for(j=1;j<=cptcoveff;j++) { - fprintf(ficresfb," V%d (=) %d",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); - } - for (k4=1; k4<= nsq; k4++){ /* For each selected (single) quantitative value */ - fprintf(ficresf," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); + for(j=1;j<=cptcovs;j++){ + /* for(j=1;j<=cptcoveff;j++) { */ + /* fprintf(ficresfb," V%d (=) %d",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */ + /* } */ + fprintf(ficresfb," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]); } + /* fprintf(ficrespij,"******\n"); */ + /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */ + /* fprintf(ficresfb," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */ + /* } */ fprintf(ficresfb," yearbproj age"); for(j=1; j<=nlstate+ndeath;j++){ for(i=1; i<=nlstate;i++) @@ -9866,8 +11795,10 @@ void prevforecast(char fileres[], double } } fprintf(ficresfb,"\n"); - for(j=1;j<=cptcoveff;j++) - fprintf(ficresfb,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); + /* for(j=1;j<=cptcoveff;j++) */ + for(j=1;j<=cptcovs;j++) + fprintf(ficresfb,"%d %lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]); + /* fprintf(ficresfb,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */ fprintf(ficresfb,"%.f %.f ",anbackd+yearp,agec-h*hstepm/YEARM*stepm); for(i=1; i<=nlstate+ndeath;i++) { ppij=0.;ppi=0.; @@ -10436,7 +12367,7 @@ void printinggnuplotmort(char fileresu[] char dirfileres[132],optfileres[132]; - int ng; + /*int ng;*/ /*#ifdef windows */ @@ -10460,7 +12391,7 @@ int readdata(char datafile[], int firsto /*-------- data file ----------*/ FILE *fic; char dummy[]=" "; - int i=0, j=0, n=0, iv=0, v; + int i = 0, j = 0, n = 0, iv = 0;/* , v;*/ int lstra; int linei, month, year,iout; int noffset=0; /* This is the offset if BOM data file */ @@ -10468,33 +12399,8 @@ int readdata(char datafile[], int firsto char stra[MAXLINE], strb[MAXLINE]; char *stratrunc; - DummyV=ivector(1,NCOVMAX); /* 1 to 3 */ - FixedV=ivector(1,NCOVMAX); /* 1 to 3 */ - for(v=1;v nlstate+ndeath){ + printf("Error in data around '%s' at line number %d for individual %d, '%s'\n Should be a state at wave %d. A state should be 1 to %d and not %ld.\n Fix your data file '%s'! Exiting.\n", strb, linei,i,line,j,nlstate+ndeath, lval, datafile);fflush(stdout); + fprintf(ficlog,"Error in data around '%s' at line number %d for individual %d, '%s'\n Should be a state at wave %d. A state should be 1 to %d and not %ld.\n Fix your data file '%s'! Exiting.\n", strb, linei,i,line,j,nlstate+ndeath, lval, datafile); fflush(ficlog); return 1; } } @@ -10852,14 +12762,15 @@ int decoderesult( char resultline[], int if (strlen(resultsav) >1){ j=nbocc(resultsav,'='); /**< j=Number of covariate values'=' in this resultline */ } - if(j == 0){ /* Resultline but no = */ + if(j == 0 && cptcovs== 0){ /* Resultline but no = and no covariate in the model */ TKresult[nres]=0; /* Combination for the nresult and the model */ return (0); } if( j != cptcovs ){ /* Be careful if a variable is in a product but not single */ - printf("ERROR: the number of variables in the resultline which is %d, differs from the number %d of single variables used in the model line, %s.\n",j, cptcovs, model); - fprintf(ficlog,"ERROR: the number of variables in the resultline which is %d, differs from the number %d of single variables used in the model line, %s.\n",j, cptcovs, model); - /* return 1;*/ + fprintf(ficlog,"ERROR: the number of variables in the resultline which is %d, differs from the number %d of single variables used in the model line, 1+age+%s.\n",j, cptcovs, model);fflush(ficlog); + printf("ERROR: the number of variables in the resultline which is %d, differs from the number %d of single variables used in the model line, 1+age+%s.\n",j, cptcovs, model);fflush(stdout); + if(j==0) + return 1; } for(k=1; k<=j;k++){ /* Loop on any covariate of the RESULT LINE */ if(nbocc(resultsav,'=') >1){ @@ -10918,7 +12829,7 @@ int decoderesult( char resultline[], int fprintf(ficlog,"Error in result line (Product with age): V%d is missing in result: %s according to model=1+age+%s (Tvarsel[k2=%d]=%d)\n",Tvar[k1], resultline, model, k2, Tvarsel[k2]); return 1; } - }else if(Typevar[k1]==2){ /* Product No age We want to get the position in the resultline of the product in the model line*/ + }else if(Typevar[k1]==2 || Typevar[k1]==3){ /* Product with or without age. We want to get the position in the resultline of the product in the model line*/ /* resultmodel[nres][of such a Vn * Vm product k1] is not unique, so can't exist, we feed Tvard[k1][1] and [2] */ match=0; /* printf("Decoderesult very first Product Tvardk[k1=%d][1]=%d Tvardk[k1=%d][2]=%d V%d * V%d\n",k1,Tvardk[k1][1],k1,Tvardk[k1][2],Tvardk[k1][1],Tvardk[k1][2]); */ @@ -10930,8 +12841,8 @@ int decoderesult( char resultline[], int } } if(match == 0){ - printf("Error in result line (Product without age first variable): V%d is missing in result: %s according to model=1+age+%s\n",Tvardk[k1][1], resultline, model); - fprintf(ficlog,"Error in result line (Product without age first variable): V%d is missing in result: %s according to model=1+age+%s\n",Tvardk[k1][1], resultline, model); + printf("Error in result line (Product without age first variable or double product with age): V%d is missing in result: %s according to model=1+age+%s\n",Tvardk[k1][1], resultline, model); + fprintf(ficlog,"Error in result line (Product without age first variable or double product with age): V%d is missing in result: %s according to model=1+age+%s\n",Tvardk[k1][1], resultline, model); return 1; } match=0; @@ -10944,8 +12855,8 @@ int decoderesult( char resultline[], int } } if(match == 0){ - printf("Error in result line (Product without age second variable): V%d is missing in result: %s according to model=1+age+%s\n",Tvardk[k1][2], resultline, model); - fprintf(ficlog,"Error in result line (Product without age second variable): V%d is missing in result : %s according to model=1+age+%s\n",Tvardk[k1][2], resultline, model); + printf("Error in result line (Product without age second variable or double product with age): V%d is missing in result: %s according to model=1+age+%s\n",Tvardk[k1][2], resultline, model); + fprintf(ficlog,"Error in result line (Product without age second variable or double product with age): V%d is missing in result : %s according to model=1+age+%s\n",Tvardk[k1][2], resultline, model); return 1; } }/* End of testing */ @@ -10957,7 +12868,7 @@ int decoderesult( char resultline[], int match=0; for(k1=1; k1<= cptcovt ;k1++){ /* loop on model: model line V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ if(Typevar[k1]==0){ /* Single only */ - if(Tvar[k1]==Tvarsel[k2]) { /* Tvar[2]=4 == Tvarsel[1]=4 */ + if(Tvar[k1]==Tvarsel[k2]) { /* Tvar[2]=4 == Tvarsel[1]=4 What if a product? */ resultmodel[nres][k1]=k2; /* k1th position in the model equation corresponds to k2th position in the result line. resultmodel[2]=1 resultmodel[1]=2 resultmodel[3]=3 resultmodel[6]=4 resultmodel[9]=5 */ modelresult[nres][k2]=k1; /* k1th position in the model equation corresponds to k2th position in the result line. modelresult[1]=2 modelresult[2]=1 modelresult[3]=3 remodelresult[4]=6 modelresult[5]=9 */ ++match; @@ -11042,22 +12953,31 @@ int decoderesult( char resultline[], int precov[nres][k1]=Tvalsel[k3q]; /* printf("Decoderesult Quantitative nres=%d,precov[nres=%d][k1=%d]=%.f V(k2q=V%d)= Tvalsel[%d]=%d, Tvarsel[%d]=%f\n",nres, nres, k1,precov[nres][k1], k2q, k3q, Tvarsel[k3q], k3q, Tvalsel[k3q]); */ k4q++;; - }else if( Dummy[k1]==2 ){ /* For dummy with age product */ - /* Tvar[k1]; */ /* Age variable */ + }else if( Dummy[k1]==2 ){ /* For dummy with age product "V2+V3+V4+V6+V7+V6*V2+V7*V2+V6*V3+V7*V3+V6*V4+V7*V4+age*V2+age*V3+age*V4+age*V6+age*V7+age*V6*V2+age*V6*V3+age*V7*V3+age*V6*V4+age*V7*V4\r"*/ + /* Tvar[k1]; */ /* Age variable */ /* 17 age*V6*V2 ?*/ /* Wrong we want the value of variable name Tvar[k1] */ - - k3= resultmodel[nres][k1]; /* nres=1 k1=2 resultmodel[2(V4)] = 1=k3 ; k1=3 resultmodel[3(V3)] = 2=k3*/ - k2=(int)Tvarsel[k3]; /* nres=1 k1=2=>k3=1 Tvarsel[resultmodel[2]]= Tvarsel[1] = 4=k2 (V4); k1=3=>k3=2 Tvarsel[2]=3 (V3)*/ - TinvDoQresult[nres][(int)Tvarsel[k3]]=Tvalsel[k3]; /* TinvDoQresult[nres][4]=1 */ - precov[nres][k1]=Tvalsel[k3]; + if(Typevar[k1]==2 || Typevar[k1]==3 ){ /* For product quant or dummy (with or without age) */ + precov[nres][k1]=TinvDoQresult[nres][Tvardk[k1][1]] * TinvDoQresult[nres][Tvardk[k1][2]]; + /* printf("Decoderesult Quantitative or Dummy (not with age) nres=%d k1=%d precov[nres=%d][k1=%d]=%.f V%d(=%.f) * V%d(=%.f) \n",nres, k1, nres, k1,precov[nres][k1], Tvardk[k1][1], TinvDoQresult[nres][Tvardk[k1][1]], Tvardk[k1][2], TinvDoQresult[nres][Tvardk[k1][2]]); */ + }else{ + k3= resultmodel[nres][k1]; /* nres=1 k1=2 resultmodel[2(V4)] = 1=k3 ; k1=3 resultmodel[3(V3)] = 2=k3*/ + k2=(int)Tvarsel[k3]; /* nres=1 k1=2=>k3=1 Tvarsel[resultmodel[2]]= Tvarsel[1] = 4=k2 (V4); k1=3=>k3=2 Tvarsel[2]=3 (V3)*/ + TinvDoQresult[nres][(int)Tvarsel[k3]]=Tvalsel[k3]; /* TinvDoQresult[nres][4]=1 */ + precov[nres][k1]=Tvalsel[k3]; + } /* printf("Decoderesult Dummy with age k=%d, k1=%d precov[nres=%d][k1=%d]=%.f Tvar[%d]=V%d k2=Tvarsel[%d]=%d Tvalsel[%d]=%d\n",k, k1, nres, k1,precov[nres][k1], k1, Tvar[k1], k3,(int)Tvarsel[k3], k3, (int)Tvalsel[k3]); */ }else if( Dummy[k1]==3 ){ /* For quant with age product */ - k3q= resultmodel[nres][k1]; /* resultmodel[1(V5)] = 25.1=k3q */ - k2q=(int)Tvarsel[k3q]; /* Tvarsel[resultmodel[1]]= Tvarsel[1] = 4=k2 */ - TinvDoQresult[nres][(int)Tvarsel[k3q]]=Tvalsel[k3q]; /* TinvDoQresult[nres][5]=25.1 */ - precov[nres][k1]=Tvalsel[k3q]; + if(Typevar[k1]==2 || Typevar[k1]==3 ){ /* For product quant or dummy (with or without age) */ + precov[nres][k1]=TinvDoQresult[nres][Tvardk[k1][1]] * TinvDoQresult[nres][Tvardk[k1][2]]; + /* printf("Decoderesult Quantitative or Dummy (not with age) nres=%d k1=%d precov[nres=%d][k1=%d]=%.f V%d(=%.f) * V%d(=%.f) \n",nres, k1, nres, k1,precov[nres][k1], Tvardk[k1][1], TinvDoQresult[nres][Tvardk[k1][1]], Tvardk[k1][2], TinvDoQresult[nres][Tvardk[k1][2]]); */ + }else{ + k3q= resultmodel[nres][k1]; /* resultmodel[1(V5)] = 25.1=k3q */ + k2q=(int)Tvarsel[k3q]; /* Tvarsel[resultmodel[1]]= Tvarsel[1] = 4=k2 */ + TinvDoQresult[nres][(int)Tvarsel[k3q]]=Tvalsel[k3q]; /* TinvDoQresult[nres][5]=25.1 */ + precov[nres][k1]=Tvalsel[k3q]; + } /* printf("Decoderesult Quantitative with age nres=%d, k1=%d, precov[nres=%d][k1=%d]=%f Tvar[%d]=V%d V(k2q=%d)= Tvarsel[%d]=%d, Tvalsel[%d]=%f\n",nres, k1, nres, k1,precov[nres][k1], k1, Tvar[k1], k2q, k3q, Tvarsel[k3q], k3q, Tvalsel[k3q]); */ - }else if(Typevar[k1]==2 ){ /* For product quant or dummy (not with age) */ + }else if(Typevar[k1]==2 || Typevar[k1]==3 ){ /* For product quant or dummy (with or without age) */ precov[nres][k1]=TinvDoQresult[nres][Tvardk[k1][1]] * TinvDoQresult[nres][Tvardk[k1][2]]; /* printf("Decoderesult Quantitative or Dummy (not with age) nres=%d k1=%d precov[nres=%d][k1=%d]=%.f V%d(=%.f) * V%d(=%.f) \n",nres, k1, nres, k1,precov[nres][k1], Tvardk[k1][1], TinvDoQresult[nres][Tvardk[k1][1]], Tvardk[k1][2], TinvDoQresult[nres][Tvardk[k1][2]]); */ }else{ @@ -11088,15 +13008,22 @@ int decodemodel( char model[], int lasto */ /* V2+V1+V4+V3*age Tvar[4]=3 ; V1+V2*age Tvar[2]=2; V1+V1*age Tvar[2]=1, Tage[1]=2 */ { - int i, j, k, ks, v; - int j1, k1, k2, k3, k4; - char modelsav[80]; - char stra[80], strb[80], strc[80], strd[80],stre[80]; + int i, j, k, ks;/* , v;*/ + int n,m; + int j1, k1, k11, k12, k2, k3, k4; + char modelsav[300]; + char stra[300], strb[300], strc[300], strd[300],stre[300],strf[300]; char *strpt; - + int **existcomb; + + existcomb=imatrix(1,NCOVMAX,1,NCOVMAX); + for(i=1;i<=NCOVMAX;i++) + for(j=1;j<=NCOVMAX;j++) + existcomb[i][j]=0; + /*removespace(model);*/ if (strlen(model) >1){ /* If there is at least 1 covariate */ - j=0, j1=0, k1=0, k2=-1, ks=0, cptcovn=0; + j=0, j1=0, k1=0, k12=0, k2=-1, ks=0, cptcovn=0; if (strstr(model,"AGE") !=0){ printf("Error. AGE must be in lower case 'age' model=1+age+%s. ",model); fprintf(ficlog,"Error. AGE must be in lower case model=1+age+%s. ",model);fflush(ficlog); @@ -11128,19 +13055,21 @@ int decodemodel( char model[], int lasto substrchaine(modelsav, model, "age*age"); }else nagesqr=0; - if (strlen(modelsav) >1){ + if (strlen(modelsav) >1){ /* V2 +V3 +V4 +V6 +V7 +V6*V2 +V7*V2 +V6*V3 +V7*V3 +V6*V4 +V7*V4 +age*V2 +age*V3 +age*V4 +age*V6 +age*V7 +age*V6*V2 +V7*V2 +age*V6*V3 +age*V7*V3 +age*V6*V4 +age*V7*V4 */ j=nbocc(modelsav,'+'); /**< j=Number of '+' */ j1=nbocc(modelsav,'*'); /**< j1=Number of '*' */ - cptcovs=j+1-j1; /**< Number of simple covariates V1+V1*age+V3 +V3*V4+age*age=> V1 + V3 =5-3=2 */ + cptcovs=0; /**< Number of simple covariates V1 +V1*age +V3 +V3*V4 +age*age => V1 + V3 =4+1-3=2 Wrong */ cptcovt= j+1; /* Number of total covariates in the model, not including * cst, age and age*age * V1+V1*age+ V3 + V3*V4+age*age=> 3+1=4*/ /* including age products which are counted in cptcovage. * but the covariates which are products must be treated * separately: ncovn=4- 2=2 (V1+V3). */ - cptcovprod=j1; /**< Number of products V1*V2 +v3*age = 2 */ + cptcovprod=0; /**< Number of products V1*V2 +v3*age = 2 */ + cptcovdageprod=0; /* Number of doouble products with age age*Vn*VM or Vn*age*Vm or Vn*Vm*age */ cptcovprodnoage=0; /**< Number of covariate products without age: V3*V4 =1 */ - + cptcovprodage=0; + /* cptcovprodage=nboccstr(modelsav,"age");*/ /* Design * V1 V2 V3 V4 V5 V6 V7 V8 V9 Weight @@ -11194,6 +13123,22 @@ int decodemodel( char model[], int lasto Tvar[k]=0; Tprod[k]=0; Tposprod[k]=0; } cptcovage=0; + + /* First loop in order to calculate */ + /* for age*VN*Vm + * Provides, Typevar[k], Tage[cptcovage], existcomb[n][m], FixedV[ncovcolt+k12] + * Tprod[k1]=k Tposprod[k]=k1; Tvard[k1][1] =m; + */ + /* Needs FixedV[Tvardk[k][1]] */ + /* For others: + * Sets Typevar[k]; + * Tvar[k]=ncovcol+nqv+ntv+nqtv+k11; + * Tposprod[k]=k11; + * Tprod[k11]=k; + * Tvardk[k][1] =m; + * Needs FixedV[Tvardk[k][1]] == 0 + */ + for(k=1; k<=cptcovt;k++){ /* Loop on total covariates of the model line */ cutl(stra,strb,modelsav,'+'); /* keeps in strb after the first '+' cutl from left to right modelsav==V2+V1+V5*age+V4+V3*age strb=V3*age stra=V2+V1V5*age+V4 */ /* "V5+V4+V3+V4*V3+V5*age+V1*age+V1" strb="V5" stra="V4+V3+V4*V3+V5*age+V1*age+V1" */ @@ -11201,66 +13146,196 @@ int decodemodel( char model[], int lasto strcpy(strb,modelsav); /* and analyzes it */ /* printf("i=%d a=%s b=%s sav=%s\n",i, stra,strb,modelsav);*/ /*scanf("%d",i);*/ - if (strchr(strb,'*')) { /**< Model includes a product V2+V1+V5*age+ V4+V3*age strb=V3*age */ - cutl(strc,strd,strb,'*'); /**< k=1 strd*strc Vm*Vn: strb=V3*age(input) strc=age strd=V3 ; V3*V2 strc=V2, strd=V3 */ - if (strcmp(strc,"age")==0) { /**< Model includes age: Vn*age */ - /* covar is not filled and then is empty */ - cptcovprod--; - cutl(stre,strb,strd,'V'); /* strd=V3(input): stre="3" */ - Tvar[k]=atoi(stre); /* V2+V1+V5*age+V4+V3*age Tvar[5]=3 ; V1+V2*age Tvar[2]=2; V1+V1*age Tvar[2]=1 */ - Typevar[k]=1; /* 1 for age product */ - cptcovage++; /* Counts the number of covariates which include age as a product */ - Tage[cptcovage]=k; /* V2+V1+V4+V3*age Tvar[4]=3, Tage[1] = 4 or V1+V1*age Tvar[2]=1, Tage[1]=2 */ - /*printf("stre=%s ", stre);*/ - } else if (strcmp(strd,"age")==0) { /* or age*Vn */ - cptcovprod--; - cutl(stre,strb,strc,'V'); - Tvar[k]=atoi(stre); - Typevar[k]=1; /* 1 for age product */ - cptcovage++; - Tage[cptcovage]=k; - } else { /* Age is not in the model product V2+V1+V1*V4+V3*age+V3*V2 strb=V3*V2*/ - /* loops on k1=1 (V3*V2) and k1=2 V4*V3 */ - cptcovn++; - cptcovprodnoage++;k1++; + if (strchr(strb,'*')) { /**< Model includes a product V2+V1+V5*age+ V4+V3*age strb=V3*age OR double product with age strb=age*V6*V2 or V6*V2*age or V6*age*V2 */ + cutl(strc,strd,strb,'*'); /**< k=1 strd*strc Vm*Vn: strb=V3*age(input) strc=age strd=V3 ; V3*V2 strc=V2, strd=V3 OR strb=age*V6*V2 strc=V6*V2 strd=age OR c=V2*age OR c=age*V2 */ + if(strchr(strc,'*')) { /**< Model with age and DOUBLE product: allowed since 0.99r44, strc=V6*V2 or V2*age or age*V2, strd=age or V6 or V6 */ + Typevar[k]=3; /* 3 for age and double product age*Vn*Vm varying of fixed */ + if(strstr(strc,"age")!=0) { /* It means that strc=V2*age or age*V2 and thus that strd=Vn */ + cutl(stre,strf,strc,'*') ; /* strf=age or Vm, stre=Vm or age. If strc=V6*V2 then strf=V6 and stre=V2 */ + strcpy(strc,strb); /* save strb(=age*Vn*Vm) into strc */ + /* We want strb=Vn*Vm */ + if(strcmp(strf,"age")==0){ /* strf is "age" so that stre=Vm =V2 . */ + strcpy(strb,strd); + strcat(strb,"*"); + strcat(strb,stre); + }else{ /* strf=Vm If strf=V6 then stre=V2 */ + strcpy(strb,strf); + strcat(strb,"*"); + strcat(strb,stre); + strcpy(strd,strb); /* in order for strd to not be "age" for next test (will be Vn*Vm */ + } + /* printf("DEBUG FIXED k=%d, Tage[k]=%d, Tvar[Tage[k]=%d,FixedV[Tvar[Tage[k]]]=%d\n",k,Tage[k],Tvar[Tage[k]],FixedV[Tvar[Tage[k]]]); */ + /* FixedV[Tvar[Tage[k]]]=0; /\* HERY not sure if V7*V4*age Fixed might not exist yet*\/ */ + }else{ /* strc=Vn*Vm (and strd=age) and should be strb=Vn*Vm but want to keep original strb double product */ + strcpy(stre,strb); /* save full b in stre */ + strcpy(strb,strc); /* save short c in new short b for next block strb=Vn*Vm*/ + strcpy(strf,strc); /* save short c in new short f */ + cutl(strc,strd,strf,'*'); /* We get strd=Vn and strc=Vm for next block (strb=Vn*Vm)*/ + /* strcpy(strc,stre);*/ /* save full e in c for future */ + } + cptcovdageprod++; /* double product with age Which product is it? */ + /* strcpy(strb,strc); /\* strb was age*V6*V2 or V6*V2*age or V6*age*V2 IS now V6*V2 or V2*age or age*V2 *\/ */ + /* cutl(strc,strd,strb,'*'); /\* strd= V6 or V2 or age and strc= V2 or age or V2 *\/ */ cutl(stre,strb,strc,'V'); /* strc= Vn, stre is n; strb=V3*V2 stre=3 strc=*/ - Tvar[k]=ncovcol+nqv+ntv+nqtv+k1; /* ncovcolt+k1; For model-covariate k tells which data-covariate to use but - because this model-covariate is a construction we invent a new column - which is after existing variables ncovcol+nqv+ntv+nqtv + k1 - If already ncovcol=4 and model= V2 + V1 + V1*V4 + age*V3 + V3*V2 - thus after V4 we invent V5 and V6 because age*V3 will be computed in 4 - Tvar[3=V1*V4]=4+1=5 Tvar[5=V3*V2]=4 + 2= 6, Tvar[4=age*V3]=3 etc */ - /* Please remark that the new variables are model dependent */ - /* If we have 4 variable but the model uses only 3, like in - * model= V1 + age*V1 + V2 + V3 + age*V2 + age*V3 + V1*V2 + V1*V3 - * k= 1 2 3 4 5 6 7 8 - * Tvar[k]=1 1 2 3 2 3 (5 6) (and not 4 5 because of V4 missing) - * Tage[kk] [1]= 2 [2]=5 [3]=6 kk=1 to cptcovage=3 - * Tvar[Tage[kk]][1]=2 [2]=2 [3]=3 - */ - Typevar[k]=2; /* 2 for product */ + n=atoi(stre); cutl(strc,strb,strd,'V'); /* strd was Vm, strc is m */ - Tprod[k1]=k; /* Tprod[1]=3(=V1*V4) for V2+V1+V1*V4+age*V3+V3*V2 */ - Tposprod[k]=k1; /* Tposprod[3]=1, Tposprod[2]=5 */ - Tvard[k1][1] =atoi(strc); /* m 1 for V1*/ - Tvardk[k][1] =atoi(strc); /* m 1 for V1*/ - Tvard[k1][2] =atoi(stre); /* n 4 for V4*/ - Tvardk[k][2] =atoi(stre); /* n 4 for V4*/ - k2=k2+2; /* k2 is initialize to -1, We want to store the n and m in Vn*Vm at the end of Tvar */ - /* Tvar[cptcovt+k2]=Tvard[k1][1]; /\* Tvar[(cptcovt=4+k2=1)=5]= 1 (V1) *\/ */ - /* Tvar[cptcovt+k2+1]=Tvard[k1][2]; /\* Tvar[(cptcovt=4+(k2=1)+1)=6]= 4 (V4) *\/ */ - /*ncovcol=4 and model=V2+V1+V1*V4+age*V3+V3*V2, Tvar[3]=5, Tvar[4]=6, cptcovt=5 */ - /* 1 2 3 4 5 | Tvar[5+1)=1, Tvar[7]=2 */ - if( FixedV[Tvardk[k][1]] == 0 && FixedV[Tvardk[k][2]] == 0){ /* If the product is a fixed covariate then we feed the new column with Vn*Vm */ - for (i=1; i<=lastobs;i++){/* For fixed product */ - /* Computes the new covariate which is a product of - covar[n][i]* covar[m][i] and stores it at ncovol+k1 May not be defined */ - covar[ncovcolt+k1][i]=covar[atoi(stre)][i]*covar[atoi(strc)][i]; + m=atoi(strc); + cptcovage++; /* Counts the number of covariates which include age as a product */ + Tage[cptcovage]=k; /* For age*V3*V2 gives the position in model of covariates associated with age Tage[1]=6 HERY too*/ + if(existcomb[n][m] == 0){ + /* r /home/brouard/Documents/Recherches/REVES/Zachary/Zach-2022/Feinuo_Sun/Feinuo-threeway/femV12V15_3wayintNBe.imach */ + printf("Warning in model combination V%d*V%d should exist in the model before adding V%d*V%d*age !\n",n,m,n,m); + fprintf(ficlog,"Warning in model combination V%d*V%d should exist in the model before adding V%d*V%d*age !\n",n,m,n,m); + fflush(ficlog); + k1++; /* The combination Vn*Vm will be in the model so we create it at k1 */ + k12++; + existcomb[n][m]=k1; + existcomb[m][n]=k1; + Tvar[k]=ncovcol+nqv+ntv+nqtv+k1; + Tprod[k1]=k; /* Tprod[1]=3(=V1*V4) for V2+V1+V1*V4+age*V3+V3*V2+ age*V6*V3 Gives the k position of the k1 double product Vn*Vm or age*Vn*Vm*/ + Tposprod[k]=k1; /* Tposprod[3]=1, Tposprod[2]=5 Gives the k1 double product Vn*Vm or age*Vn*Vm at the k position */ + Tvard[k1][1] =m; /* m 1 for V1*/ + Tvardk[k][1] =m; /* m 1 for V1*/ + Tvard[k1][2] =n; /* n 4 for V4*/ + Tvardk[k][2] =n; /* n 4 for V4*/ +/* Tvar[Tage[cptcovage]]=k1;*/ /* Tvar[6=age*V3*V2]=9 (new fixed covariate) */ /* We don't know about Fixed yet HERE */ + if( FixedV[Tvardk[k][1]] == 0 && FixedV[Tvardk[k][2]] == 0){ /* If the product is a fixed covariate then we feed the new column with Vn*Vm */ + for (i=1; i<=lastobs;i++){/* For fixed product */ + /* Computes the new covariate which is a product of + covar[n][i]* covar[m][i] and stores it at ncovol+k1 May not be defined */ + covar[ncovcolt+k1][i]=covar[atoi(stre)][i]*covar[atoi(strc)][i]; + } + cptcovprodage++; /* Counting the number of fixed covariate with age */ + FixedV[ncovcolt+k12]=0; /* We expand Vn*Vm */ + k12++; + FixedV[ncovcolt+k12]=0; + }else{ /*End of FixedV */ + cptcovprodvage++; /* Counting the number of varying covariate with age */ + FixedV[ncovcolt+k12]=1; /* We expand Vn*Vm */ + k12++; + FixedV[ncovcolt+k12]=1; + } + }else{ /* k1 Vn*Vm already exists */ + k11=existcomb[n][m]; + Tposprod[k]=k11; /* OK */ + Tvar[k]=Tvar[Tprod[k11]]; /* HERY */ + Tvardk[k][1]=m; + Tvardk[k][2]=n; + if( FixedV[Tvardk[k][1]] == 0 && FixedV[Tvardk[k][2]] == 0){ /* If the product is a fixed covariate then we feed the new column with Vn*Vm */ + /*cptcovage++;*/ /* Counts the number of covariates which include age as a product */ + cptcovprodage++; /* Counting the number of fixed covariate with age */ + /*Tage[cptcovage]=k;*/ /* For age*V3*V2 Tage[1]=V3*V3=9 HERY too*/ + Tvar[Tage[cptcovage]]=k1; + FixedV[ncovcolt+k12]=0; /* We expand Vn*Vm */ + k12++; + FixedV[ncovcolt+k12]=0; + }else{ /* Already exists but time varying (and age) */ + /*cptcovage++;*/ /* Counts the number of covariates which include age as a product */ + /*Tage[cptcovage]=k;*/ /* For age*V3*V2 Tage[1]=V3*V3=9 HERY too*/ + /* Tvar[Tage[cptcovage]]=k1; */ + cptcovprodvage++; + FixedV[ncovcolt+k12]=1; /* We expand Vn*Vm */ + k12++; + FixedV[ncovcolt+k12]=1; + } + } + /* Tage[cptcovage]=k; /\* V2+V1+V4+V3*age Tvar[4]=3, Tage[1] = 4 or V1+V1*age Tvar[2]=1, Tage[1]=2 *\/ */ + /* Tvar[k]=k11; /\* HERY *\/ */ + } else {/* simple product strb=age*Vn so that c=Vn and d=age, or strb=Vn*age so that c=age and d=Vn, or b=Vn*Vm so that c=Vm and d=Vn */ + cptcovprod++; + if (strcmp(strc,"age")==0) { /**< Model includes age: strb= Vn*age c=age d=Vn*/ + /* covar is not filled and then is empty */ + cutl(stre,strb,strd,'V'); /* strd=V3(input): stre="3" */ + Tvar[k]=atoi(stre); /* V2+V1+V5*age+V4+V3*age Tvar[5]=3 ; V1+V2*age Tvar[2]=2; V1+V1*age Tvar[2]=1 */ + Typevar[k]=1; /* 1 for age product */ + cptcovage++; /* Counts the number of covariates which include age as a product */ + Tage[cptcovage]=k; /* V2+V1+V4+V3*age Tvar[4]=3, Tage[1] = 4 or V1+V1*age Tvar[2]=1, Tage[1]=2 */ + if( FixedV[Tvar[k]] == 0){ + cptcovprodage++; /* Counting the number of fixed covariate with age */ + }else{ + cptcovprodvage++; /* Counting the number of fixedvarying covariate with age */ + } + /*printf("stre=%s ", stre);*/ + } else if (strcmp(strd,"age")==0) { /* strb= age*Vn c=Vn */ + cutl(stre,strb,strc,'V'); + Tvar[k]=atoi(stre); + Typevar[k]=1; /* 1 for age product */ + cptcovage++; + Tage[cptcovage]=k; + if( FixedV[Tvar[k]] == 0){ + cptcovprodage++; /* Counting the number of fixed covariate with age */ + }else{ + cptcovprodvage++; /* Counting the number of fixedvarying covariate with age */ } - } /*End of FixedV */ - } /* End age is not in the model */ - } /* End if model includes a product */ - else { /* not a product */ + }else{ /* for product Vn*Vm */ + Typevar[k]=2; /* 2 for product Vn*Vm */ + cutl(stre,strb,strc,'V'); /* strc= Vn, stre is n; strb=V3*V2 stre=3 strc=*/ + n=atoi(stre); + cutl(strc,strb,strd,'V'); /* strd was Vm, strc is m */ + m=atoi(strc); + k1++; + cptcovprodnoage++; + if(existcomb[n][m] != 0 || existcomb[m][n] != 0){ + printf("Warning in model combination V%d*V%d already exists in the model in position k1=%d!\n",n,m,existcomb[n][m]); + fprintf(ficlog,"Warning in model combination V%d*V%d already exists in the model in position k1=%d!\n",n,m,existcomb[n][m]); + fflush(ficlog); + k11=existcomb[n][m]; + Tvar[k]=ncovcol+nqv+ntv+nqtv+k11; + Tposprod[k]=k11; + Tprod[k11]=k; + Tvardk[k][1] =m; /* m 1 for V1*/ + /* Tvard[k11][1] =m; /\* n 4 for V4*\/ */ + Tvardk[k][2] =n; /* n 4 for V4*/ + /* Tvard[k11][2] =n; /\* n 4 for V4*\/ */ + }else{ /* combination Vn*Vm doesn't exist we create it (no age)*/ + existcomb[n][m]=k1; + existcomb[m][n]=k1; + Tvar[k]=ncovcol+nqv+ntv+nqtv+k1; /* ncovcolt+k1; For model-covariate k tells which data-covariate to use but + because this model-covariate is a construction we invent a new column + which is after existing variables ncovcol+nqv+ntv+nqtv + k1 + If already ncovcol=4 and model= V2 + V1 + V1*V4 + age*V3 + V3*V2 + thus after V4 we invent V5 and V6 because age*V3 will be computed in 4 + Tvar[3=V1*V4]=4+1=5 Tvar[5=V3*V2]=4 + 2= 6, Tvar[4=age*V3]=3 etc */ + /* Please remark that the new variables are model dependent */ + /* If we have 4 variable but the model uses only 3, like in + * model= V1 + age*V1 + V2 + V3 + age*V2 + age*V3 + V1*V2 + V1*V3 + * k= 1 2 3 4 5 6 7 8 + * Tvar[k]=1 1 2 3 2 3 (5 6) (and not 4 5 because of V4 missing) + * Tage[kk] [1]= 2 [2]=5 [3]=6 kk=1 to cptcovage=3 + * Tvar[Tage[kk]][1]=2 [2]=2 [3]=3 + */ + /* We need to feed some variables like TvarVV, but later on next loop because of ncovv (k2) is not correct */ + Tprod[k1]=k; /* Tprod[1]=3(=V1*V4) for V2+V1+V1*V4+age*V3+V3*V2 +V6*V2*age */ + Tposprod[k]=k1; /* Tposprod[3]=1, Tposprod[2]=5 */ + Tvard[k1][1] =m; /* m 1 for V1*/ + Tvardk[k][1] =m; /* m 1 for V1*/ + Tvard[k1][2] =n; /* n 4 for V4*/ + Tvardk[k][2] =n; /* n 4 for V4*/ + k2=k2+2; /* k2 is initialize to -1, We want to store the n and m in Vn*Vm at the end of Tvar */ + /* Tvar[cptcovt+k2]=Tvard[k1][1]; /\* Tvar[(cptcovt=4+k2=1)=5]= 1 (V1) *\/ */ + /* Tvar[cptcovt+k2+1]=Tvard[k1][2]; /\* Tvar[(cptcovt=4+(k2=1)+1)=6]= 4 (V4) *\/ */ + /*ncovcol=4 and model=V2+V1+V1*V4+age*V3+V3*V2, Tvar[3]=5, Tvar[4]=6, cptcovt=5 */ + /* 1 2 3 4 5 | Tvar[5+1)=1, Tvar[7]=2 */ + if( FixedV[Tvardk[k][1]] == 0 && FixedV[Tvardk[k][2]] == 0){ /* If the product is a fixed covariate then we feed the new column with Vn*Vm */ + for (i=1; i<=lastobs;i++){/* For fixed product */ + /* Computes the new covariate which is a product of + covar[n][i]* covar[m][i] and stores it at ncovol+k1 May not be defined */ + covar[ncovcolt+k1][i]=covar[atoi(stre)][i]*covar[atoi(strc)][i]; + } + /* TvarVV[k2]=n; */ + /* FixedV[ncovcolt+k2]=0; /\* or FixedV[Tvar[k]]=0; FixedV[TvarVV[ncovv]]=0 HERE *\/ */ + /* TvarVV[k2+1]=m; */ + /* FixedV[ncovcolt+k2]=0; /\* or FixedV[Tvar[k]]=0; FixedV[TvarVV[ncovv]]=0 HERE *\/ */ + }else{ /* not FixedV */ + /* TvarVV[k2]=n; */ + /* FixedV[ncovcolt+k2]=0; /\* or FixedV[Tvar[k]]=0; FixedV[TvarVV[ncovv]]=0 HERE *\/ */ + /* TvarVV[k2+1]=m; */ + /* FixedV[ncovcolt+k2]=0; /\* or FixedV[Tvar[k]]=0; FixedV[TvarVV[ncovv]]=0 HERE *\/ */ + } + } /* End of creation of Vn*Vm if not created by age*Vn*Vm earlier */ + } /* End of product Vn*Vm */ + } /* End of age*double product or simple product */ + }else { /* not a product */ /*printf("d=%s c=%s b=%s\n", strd,strc,strb);*/ /* scanf("%d",i);*/ cutl(strd,strc,strb,'V'); @@ -11273,9 +13348,12 @@ int decodemodel( char model[], int lasto /*printf("a=%s b=%s sav=%s\n", stra,strb,modelsav); scanf("%d",i);*/ } /* end of loop + on total covariates */ + + } /* end if strlen(modelsave == 0) age*age might exist */ } /* end if strlen(model == 0) */ - + cptcovs=cptcovt - cptcovdageprod - cptcovprod;/**< Number of simple covariates V1 +V1*age +V3 +V3*V4 +age*age + age*v4*V3=> V1 + V3 =4+1-3=2 */ + /*The number n of Vn is stored in Tvar. cptcovage =number of age covariate. Tage gives the position of age. cptcovprod= number of products. If model=V1+V1*age then Tvar[1]=1 Tvar[2]=1 cptcovage=1 Tage[1]=2 cptcovprod=0*/ @@ -11301,16 +13379,21 @@ int decodemodel( char model[], int lasto /* Tvar[k] is the value n of Vn with n varying for 1 to nvcol, or p Vp=Vn*Vm for product */ /* Computing effective variables, ie used by the model, that is from the cptcovt variables */ printf("Model=1+age+%s\n\ -Typevar: 0 for simple covariate (dummy, quantitative, fixed or varying), 1 for age product, 2 for product \n\ +Typevar: 0 for simple covariate (dummy, quantitative, fixed or varying), 1 for age product, 2 for product, 3 for double product with age \n\ Fixed[k] 0=fixed (product or simple), 1 varying, 2 fixed with age product, 3 varying with age product \n\ Dummy[k] 0=dummy (0 1), 1 quantitative (single or product without age), 2 dummy with age product, 3 quant with age product\n",model); fprintf(ficlog,"Model=1+age+%s\n\ -Typevar: 0 for simple covariate (dummy, quantitative, fixed or varying), 1 for age product, 2 for product \n\ +Typevar: 0 for simple covariate (dummy, quantitative, fixed or varying), 1 for age product, 2 for product, 3 for double product with age \n\ Fixed[k] 0=fixed (product or simple), 1 varying, 2 fixed with age product, 3 varying with age product \n\ Dummy[k] 0=dummy (0 1), 1 quantitative (single or product without age), 2 dummy with age product, 3 quant with age product\n",model); for(k=-1;k<=NCOVMAX; k++){ Fixed[k]=0; Dummy[k]=0;} for(k=1;k<=NCOVMAX; k++){TvarFind[k]=0; TvarVind[k]=0;} - for(k=1, ncovf=0, nsd=0, nsq=0, ncovv=0, ncova=0, ncoveff=0, nqfveff=0, ntveff=0, nqtveff=0, ncovvt=0;k<=cptcovt; k++){ /* or cptocvt loop on k from model */ + + + /* Second loop for calculating Fixed[k], Dummy[k]*/ + + + for(k=1, ncovf=0, nsd=0, nsq=0, ncovv=0,ncovva=0,ncovvta=0, ncova=0, ncoveff=0, nqfveff=0, ntveff=0, nqtveff=0, ncovvt=0;k<=cptcovt; k++){ /* or cptocvt loop on k from model */ if (Tvar[k] <=ncovcol && Typevar[k]==0 ){ /* Simple fixed dummy (<=ncovcol) covariates */ Fixed[k]= 0; Dummy[k]= 0; @@ -11326,17 +13409,6 @@ Dummy[k] 0=dummy (0 1), 1 quantitative ( TvarFD[ncoveff]=Tvar[k]; /* TvarFD[1]=V1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ TvarFDind[ncoveff]=k; /* TvarFDind[1]=9 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* }else if( Tvar[k] <=ncovcol && Typevar[k]==2){ /\* Product of fixed dummy (<=ncovcol) covariates For a fixed product k is higher than ncovcol *\/ */ - }else if( Tposprod[k]>0 && Typevar[k]==2 && FixedV[Tvardk[k][1]] == 0 && FixedV[Tvardk[k][2]] == 0){ /* Needs a fixed product Product of fixed dummy (<=ncovcol) covariates For a fixed product k is higher than ncovcol */ - Fixed[k]= 0; - Dummy[k]= 0; - ncoveff++; - ncovf++; - modell[k].maintype= FTYPE; - TvarF[ncovf]=Tvar[k]; - /* TnsdVar[Tvar[k]]=nsd; */ /* To be done */ - TvarFind[ncovf]=k; - TvarFD[ncoveff]=Tvar[k]; /* TvarFD[1]=V1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ - TvarFDind[ncoveff]=k; /* TvarFDind[1]=9 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ }else if( Tvar[k] <=ncovcol+nqv && Typevar[k]==0){/* Remind that product Vn*Vm are added in k Only simple fixed quantitative variable */ Fixed[k]= 0; Dummy[k]= 1; @@ -11398,186 +13470,396 @@ Dummy[k] 0=dummy (0 1), 1 quantitative ( TvarVQind[nqtveff]=k; /* TvarVQind[1]=1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple time varying quantitative variable */ TmodelInvQind[nqtveff]=Tvar[k]- ncovcol-nqv-ntv;/* Only simple time varying quantitative variable */ /* Tmodeliqind[k]=nqtveff;/\* Only simple time varying quantitative variable *\/ */ - /* printf("Quasi TmodelQind[%d]=%d,Tvar[TmodelQind[%d]]=V%d, ncovcol=%d, nqv=%d, ntv=%d,Tvar[k]- ncovcol-nqv-ntv=%d\n",nqtveff,k,nqtveff,Tvar[k], ncovcol, nqv, ntv, Tvar[k]- ncovcol-nqv-ntv); */ + /* printf("Quasi TmodelQind[%d]=%d,Tvar[TmodelQind[%d]]=V%d, ncovcol=%d, nqv=%d, ntv=%Ad,Tvar[k]- ncovcol-nqv-ntv=%d\n",nqtveff,k,nqtveff,Tvar[k], ncovcol, nqv, ntv, Tvar[k]- ncovcol-nqv-ntv); */ /* printf("Quasi TmodelInvQind[%d]=%d\n",k,Tvar[k]- ncovcol-nqv-ntv); */ }else if (Typevar[k] == 1) { /* product with age */ ncova++; TvarA[ncova]=Tvar[k]; TvarAind[ncova]=k; + /** Fixed[k] 0=fixed, 1 varying, 2 fixed with age product, 3 varying with age product */ + /** Dummy[k] 0=dummy (0 1), 1 quantitative (single or product without age), 2 dummy with age product, 3 quant with age product */ if (Tvar[k] <=ncovcol ){ /* Product age with fixed dummy covariatee */ Fixed[k]= 2; Dummy[k]= 2; modell[k].maintype= ATYPE; modell[k].subtype= APFD; + ncovta++; + TvarAVVA[ncovta]=Tvar[k]; /* (2)age*V3 */ + TvarAVVAind[ncovta]=k; /* ncoveff++; */ }else if( Tvar[k] <=ncovcol+nqv) { /* Remind that product Vn*Vm are added in k*/ Fixed[k]= 2; Dummy[k]= 3; modell[k].maintype= ATYPE; modell[k].subtype= APFQ; /* Product age * fixed quantitative */ + ncovta++; + TvarAVVA[ncovta]=Tvar[k]; /* */ + TvarAVVAind[ncovta]=k; /* nqfveff++; /\* Only simple fixed quantitative variable *\/ */ }else if( Tvar[k] <=ncovcol+nqv+ntv ){ Fixed[k]= 3; Dummy[k]= 2; modell[k].maintype= ATYPE; modell[k].subtype= APVD; /* Product age * varying dummy */ + ncovva++; + TvarVVA[ncovva]=Tvar[k]; /* (1)+age*V6 + (2)age*V7 */ + TvarVVAind[ncovva]=k; + ncovta++; + TvarAVVA[ncovta]=Tvar[k]; /* */ + TvarAVVAind[ncovta]=k; /* ntveff++; /\* Only simple time varying dummy variable *\/ */ }else if( Tvar[k] <=ncovcol+nqv+ntv+nqtv){ Fixed[k]= 3; Dummy[k]= 3; modell[k].maintype= ATYPE; modell[k].subtype= APVQ; /* Product age * varying quantitative */ + ncovva++; + TvarVVA[ncovva]=Tvar[k]; /* */ + TvarVVAind[ncovva]=k; + ncovta++; + TvarAVVA[ncovta]=Tvar[k]; /* (1)+age*V6 + (2)age*V7 */ + TvarAVVAind[ncovta]=k; /* nqtveff++;/\* Only simple time varying quantitative variable *\/ */ } - }else if (Typevar[k] == 2) { /* product Vn * Vm without age, V1+V3+age*V1+age*V3+V1*V3 looking at V1*V3, Typevar={0, 0, 1, 1, 2}, k=5, V1 is fixed, V3 is timevary, V5 is a product */ + }else if( Tposprod[k]>0 && Typevar[k]==2){ /* Detects if fixed product no age Vm*Vn */ + printf("MEMORY ERRORR k=%d Tposprod[k]=%d, Typevar[k]=%d\n ",k, Tposprod[k], Typevar[k]); + if(FixedV[Tvardk[k][1]] == 0 && FixedV[Tvardk[k][2]] == 0){ /* Needs a fixed product Product of fixed dummy (<=ncovcol) covariates For a fixed product k is higher than ncovcol V3*V2 */ + printf("MEMORY ERRORR k=%d Tvardk[k][1]=%d, Tvardk[k][2]=%d, FixedV[Tvardk[k][1]]=%d,FixedV[Tvardk[k][2]]=%d\n ",k,Tvardk[k][1],Tvardk[k][2],FixedV[Tvardk[k][1]],FixedV[Tvardk[k][2]]); + Fixed[k]= 0; + Dummy[k]= 0; + ncoveff++; + ncovf++; + /* ncovv++; */ + /* TvarVV[ncovv]=Tvardk[k][1]; */ + /* FixedV[ncovcolt+ncovv]=0; /\* or FixedV[TvarVV[ncovv]]=0 HERE *\/ */ + /* ncovv++; */ + /* TvarVV[ncovv]=Tvardk[k][2]; */ + /* FixedV[ncovcolt+ncovv]=0; /\* or FixedV[TvarVV[ncovv]]=0 HERE *\/ */ + modell[k].maintype= FTYPE; + TvarF[ncovf]=Tvar[k]; + /* TnsdVar[Tvar[k]]=nsd; */ /* To be done */ + TvarFind[ncovf]=k; + TvarFD[ncoveff]=Tvar[k]; /* TvarFD[1]=V1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ + TvarFDind[ncoveff]=k; /* TvarFDind[1]=9 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ + }else{/* product varying Vn * Vm without age, V1+V3+age*V1+age*V3+V1*V3 looking at V1*V3, Typevar={0, 0, 1, 1, 2}, k=5, V1 is fixed, V3 is timevary, V5 is a product */ + /*# ID V1 V2 weight birth death 1st s1 V3 V4 V5 2nd s2 */ + /* model V1+V3+age*V1+age*V3+V1*V3 + V1*V3*age*/ + /* Tvar={1, 3, 1, 3, 6, 6}, the 6 comes from the fact that there are already V1, V2, V3, V4, V5 native covariates */ + k1=Tposprod[k]; /* Position in the products of product k, Tposprod={0, 0, 0, 0, 1, 1} k1=1 first product but second time varying because of V3 */ + ncovvt++; + TvarVV[ncovvt]=Tvard[k1][1]; /* TvarVV[2]=V1 (because TvarVV[1] was V3, first time varying covariates */ + TvarVVind[ncovvt]=k; /* TvarVVind[2]=5 (because TvarVVind[2] was V1*V3 at position 5 */ + ncovvt++; + TvarVV[ncovvt]=Tvard[k1][2]; /* TvarVV[3]=V3 */ + TvarVVind[ncovvt]=k; /* TvarVVind[2]=5 (because TvarVVind[2] was V1*V3 at position 5 */ + + /** Fixed[k] 0=fixed, 1 varying, 2 fixed with age product, 3 varying with age product */ + /** Dummy[k] 0=dummy (0 1), 1 quantitative (single or product without age), 2 dummy with age product, 3 quant with age product */ + + if(Tvard[k1][1] <=ncovcol){ /* Vn is dummy fixed, (Tvard[1][1]=V1), (Tvard[1][1]=V3 time varying) */ + if(Tvard[k1][2] <=ncovcol){ /* Vm is dummy fixed */ + Fixed[k]= 1; + Dummy[k]= 0; + modell[k].maintype= FTYPE; + modell[k].subtype= FPDD; /* Product fixed dummy * fixed dummy */ + ncovf++; /* Fixed variables without age */ + TvarF[ncovf]=Tvar[k]; + TvarFind[ncovf]=k; + }else if(Tvard[k1][2] <=ncovcol+nqv){ /* Vm is quanti fixed */ + Fixed[k]= 0; /* Fixed product */ + Dummy[k]= 1; + modell[k].maintype= FTYPE; + modell[k].subtype= FPDQ; /* Product fixed dummy * fixed quantitative */ + ncovf++; /* Varying variables without age */ + TvarF[ncovf]=Tvar[k]; + TvarFind[ncovf]=k; + }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){ /* Vm is a time varying dummy covariate */ + Fixed[k]= 1; + Dummy[k]= 0; + modell[k].maintype= VTYPE; + modell[k].subtype= VPDD; /* Product fixed dummy * varying dummy */ + ncovv++; /* Varying variables without age */ + TvarV[ncovv]=Tvar[k]; /* TvarV[1]=Tvar[5]=5 because there is a V4 */ + TvarVind[ncovv]=k;/* TvarVind[1]=5 */ + }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){ /* Vm is a time varying quantitative covariate */ + Fixed[k]= 1; + Dummy[k]= 1; + modell[k].maintype= VTYPE; + modell[k].subtype= VPDQ; /* Product fixed dummy * varying quantitative */ + ncovv++; /* Varying variables without age */ + TvarV[ncovv]=Tvar[k]; + TvarVind[ncovv]=k; + } + }else if(Tvard[k1][1] <=ncovcol+nqv){ /* Vn is fixed quanti */ + if(Tvard[k1][2] <=ncovcol){ /* Vm is fixed dummy */ + Fixed[k]= 0; /* Fixed product */ + Dummy[k]= 1; + modell[k].maintype= FTYPE; + modell[k].subtype= FPDQ; /* Product fixed quantitative * fixed dummy */ + ncovf++; /* Fixed variables without age */ + TvarF[ncovf]=Tvar[k]; + TvarFind[ncovf]=k; + }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){ /* Vm is time varying */ + Fixed[k]= 1; + Dummy[k]= 1; + modell[k].maintype= VTYPE; + modell[k].subtype= VPDQ; /* Product fixed quantitative * varying dummy */ + ncovv++; /* Varying variables without age */ + TvarV[ncovv]=Tvar[k]; + TvarVind[ncovv]=k; + }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){ /* Vm is time varying quanti */ + Fixed[k]= 1; + Dummy[k]= 1; + modell[k].maintype= VTYPE; + modell[k].subtype= VPQQ; /* Product fixed quantitative * varying quantitative */ + ncovv++; /* Varying variables without age */ + TvarV[ncovv]=Tvar[k]; + TvarVind[ncovv]=k; + ncovv++; /* Varying variables without age */ + TvarV[ncovv]=Tvar[k]; + TvarVind[ncovv]=k; + } + }else if(Tvard[k1][1] <=ncovcol+nqv+ntv){ /* Vn is time varying dummy */ + if(Tvard[k1][2] <=ncovcol){ + Fixed[k]= 1; + Dummy[k]= 1; + modell[k].maintype= VTYPE; + modell[k].subtype= VPDD; /* Product time varying dummy * fixed dummy */ + ncovv++; /* Varying variables without age */ + TvarV[ncovv]=Tvar[k]; + TvarVind[ncovv]=k; + }else if(Tvard[k1][2] <=ncovcol+nqv){ + Fixed[k]= 1; + Dummy[k]= 1; + modell[k].maintype= VTYPE; + modell[k].subtype= VPDQ; /* Product time varying dummy * fixed quantitative */ + ncovv++; /* Varying variables without age */ + TvarV[ncovv]=Tvar[k]; + TvarVind[ncovv]=k; + }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){ + Fixed[k]= 1; + Dummy[k]= 0; + modell[k].maintype= VTYPE; + modell[k].subtype= VPDD; /* Product time varying dummy * time varying dummy */ + ncovv++; /* Varying variables without age */ + TvarV[ncovv]=Tvar[k]; + TvarVind[ncovv]=k; + }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){ + Fixed[k]= 1; + Dummy[k]= 1; + modell[k].maintype= VTYPE; + modell[k].subtype= VPDQ; /* Product time varying dummy * time varying quantitative */ + ncovv++; /* Varying variables without age */ + TvarV[ncovv]=Tvar[k]; + TvarVind[ncovv]=k; + } + }else if(Tvard[k1][1] <=ncovcol+nqv+ntv+nqtv){ /* Vn is time varying quanti */ + if(Tvard[k1][2] <=ncovcol){ + Fixed[k]= 1; + Dummy[k]= 1; + modell[k].maintype= VTYPE; + modell[k].subtype= VPDQ; /* Product time varying quantitative * fixed dummy */ + ncovv++; /* Varying variables without age */ + TvarV[ncovv]=Tvar[k]; + TvarVind[ncovv]=k; + }else if(Tvard[k1][2] <=ncovcol+nqv){ + Fixed[k]= 1; + Dummy[k]= 1; + modell[k].maintype= VTYPE; + modell[k].subtype= VPQQ; /* Product time varying quantitative * fixed quantitative */ + ncovv++; /* Varying variables without age */ + TvarV[ncovv]=Tvar[k]; + TvarVind[ncovv]=k; + }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){ + Fixed[k]= 1; + Dummy[k]= 1; + modell[k].maintype= VTYPE; + modell[k].subtype= VPDQ; /* Product time varying quantitative * time varying dummy */ + ncovv++; /* Varying variables without age */ + TvarV[ncovv]=Tvar[k]; + TvarVind[ncovv]=k; + }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){ + Fixed[k]= 1; + Dummy[k]= 1; + modell[k].maintype= VTYPE; + modell[k].subtype= VPQQ; /* Product time varying quantitative * time varying quantitative */ + ncovv++; /* Varying variables without age */ + TvarV[ncovv]=Tvar[k]; + TvarVind[ncovv]=k; + } + }else{ + printf("Error unknown type of covariate: Tvard[%d][1]=%d,Tvard[%d][2]=%d\n",k1,Tvard[k1][1],k1,Tvard[k1][2]); + fprintf(ficlog,"Error unknown type of covariate: Tvard[%d][1]=%d,Tvard[%d][2]=%d\n",k1,Tvard[k1][1],k1,Tvard[k1][2]); + } /*end k1*/ + } + }else if(Typevar[k] == 3){ /* product Vn * Vm with age, V1+V3+age*V1+age*V3+V1*V3 looking at V1*V3, Typevar={0, 0, 1, 1, 2}, k=5, V1 is fixed, V3 is timevary, V5 is a product */ /*# ID V1 V2 weight birth death 1st s1 V3 V4 V5 2nd s2 */ - /* model V1+V3+age*V1+age*V3+V1*V3 */ - /* Tvar={1, 3, 1, 3, 6}, the 6 comes from the fact that there are already V1, V2, V3, V4, V5 native covariates */ - k1=Tposprod[k]; /* Position in the products of product k, Tposprod={0, 0, 0, 0, 1} k1=1 first product but second time varying because of V3 */ - ncovvt++; - TvarVV[ncovvt]=Tvard[k1][1]; /* TvarVV[2]=V1 (because TvarVV[1] was V3, first time varying covariates */ - TvarVVind[ncovvt]=k; /* TvarVVind[2]=5 (because TvarVVind[2] was V1*V3 at position 5 */ - ncovvt++; - TvarVV[ncovvt]=Tvard[k1][2]; /* TvarVV[3]=V3 */ - TvarVVind[ncovvt]=k; /* TvarVVind[2]=5 (because TvarVVind[2] was V1*V3 at position 5 */ - + /* model V1+V3+age*V1+age*V3+V1*V3 + V1*V3*age*/ + /* Tvar={1, 3, 1, 3, 6, 6}, the 6 comes from the fact that there are already V1, V2, V3, V4, V5 native covariates */ + k1=Tposprod[k]; /* Position in the products of product k, Tposprod={0, 0, 0, 0, 1, 1} k1=1 first product but second time varying because of V3 */ + ncova++; + TvarA[ncova]=Tvard[k1][1]; /* TvarVV[2]=V1 (because TvarVV[1] was V3, first time varying covariates */ + TvarAind[ncova]=k; /* TvarVVind[2]=5 (because TvarVVind[2] was V1*V3 at position 5 */ + ncova++; + TvarA[ncova]=Tvard[k1][2]; /* TvarVV[3]=V3 */ + TvarAind[ncova]=k; /* TvarVVind[2]=5 (because TvarVVind[2] was V1*V3 at position 5 */ + /** Fixed[k] 0=fixed, 1 varying, 2 fixed with age product, 3 varying with age product */ + /** Dummy[k] 0=dummy (0 1), 1 quantitative (single or product without age), 2 dummy with age product, 3 quant with age product */ + if( FixedV[Tvardk[k][1]] == 0 && FixedV[Tvardk[k][2]] == 0){ + ncovta++; + TvarAVVA[ncovta]=Tvard[k1][1]; /* age*V6*V3 +age*V7*V3 + age*V6*V4 +age*V7*V4 */ + TvarAVVAind[ncovta]=k; + ncovta++; + TvarAVVA[ncovta]=Tvard[k1][2]; /* age*V6*V3 +age*V7*V3 + age*V6*V4 +age*V7*V4 */ + TvarAVVAind[ncovta]=k; + }else{ + ncovva++; /* HERY reached */ + TvarVVA[ncovva]=Tvard[k1][1]; /* age*V6*V3 +age*V7*V3 + age*V6*V4 +age*V7*V4 */ + TvarVVAind[ncovva]=k; + ncovva++; + TvarVVA[ncovva]=Tvard[k1][2]; /* */ + TvarVVAind[ncovva]=k; + ncovta++; + TvarAVVA[ncovta]=Tvard[k1][1]; /* age*V6*V3 +age*V7*V3 + age*V6*V4 +age*V7*V4 */ + TvarAVVAind[ncovta]=k; + ncovta++; + TvarAVVA[ncovta]=Tvard[k1][2]; /* age*V6*V3 +age*V7*V3 + age*V6*V4 +age*V7*V4 */ + TvarAVVAind[ncovta]=k; + } if(Tvard[k1][1] <=ncovcol){ /* Vn is dummy fixed, (Tvard[1][1]=V1), (Tvard[1][1]=V3 time varying) */ if(Tvard[k1][2] <=ncovcol){ /* Vm is dummy fixed */ - Fixed[k]= 1; - Dummy[k]= 0; + Fixed[k]= 2; + Dummy[k]= 2; modell[k].maintype= FTYPE; modell[k].subtype= FPDD; /* Product fixed dummy * fixed dummy */ - ncovf++; /* Fixed variables without age */ - TvarF[ncovf]=Tvar[k]; - TvarFind[ncovf]=k; + /* TvarF[ncova]=Tvar[k]; /\* Problem to solve *\/ */ + /* TvarFind[ncova]=k; */ }else if(Tvard[k1][2] <=ncovcol+nqv){ /* Vm is quanti fixed */ - Fixed[k]= 0; /* Fixed product */ - Dummy[k]= 1; + Fixed[k]= 2; /* Fixed product */ + Dummy[k]= 3; modell[k].maintype= FTYPE; modell[k].subtype= FPDQ; /* Product fixed dummy * fixed quantitative */ - ncovf++; /* Varying variables without age */ - TvarF[ncovf]=Tvar[k]; - TvarFind[ncovf]=k; + /* TvarF[ncova]=Tvar[k]; */ + /* TvarFind[ncova]=k; */ }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){ /* Vm is a time varying dummy covariate */ - Fixed[k]= 1; - Dummy[k]= 0; + Fixed[k]= 3; + Dummy[k]= 2; modell[k].maintype= VTYPE; modell[k].subtype= VPDD; /* Product fixed dummy * varying dummy */ - ncovv++; /* Varying variables without age */ - TvarV[ncovv]=Tvar[k]; /* TvarV[1]=Tvar[5]=5 because there is a V4 */ - TvarVind[ncovv]=k;/* TvarVind[1]=5 */ + TvarV[ncova]=Tvar[k]; /* TvarV[1]=Tvar[5]=5 because there is a V4 */ + TvarVind[ncova]=k;/* TvarVind[1]=5 */ }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){ /* Vm is a time varying quantitative covariate */ - Fixed[k]= 1; - Dummy[k]= 1; + Fixed[k]= 3; + Dummy[k]= 3; modell[k].maintype= VTYPE; modell[k].subtype= VPDQ; /* Product fixed dummy * varying quantitative */ - ncovv++; /* Varying variables without age */ - TvarV[ncovv]=Tvar[k]; - TvarVind[ncovv]=k; + /* ncovv++; /\* Varying variables without age *\/ */ + /* TvarV[ncovv]=Tvar[k]; */ + /* TvarVind[ncovv]=k; */ } }else if(Tvard[k1][1] <=ncovcol+nqv){ /* Vn is fixed quanti */ if(Tvard[k1][2] <=ncovcol){ /* Vm is fixed dummy */ - Fixed[k]= 0; /* Fixed product */ - Dummy[k]= 1; + Fixed[k]= 2; /* Fixed product */ + Dummy[k]= 2; modell[k].maintype= FTYPE; modell[k].subtype= FPDQ; /* Product fixed quantitative * fixed dummy */ - ncovf++; /* Fixed variables without age */ - TvarF[ncovf]=Tvar[k]; - TvarFind[ncovf]=k; + /* ncova++; /\* Fixed variables with age *\/ */ + /* TvarF[ncovf]=Tvar[k]; */ + /* TvarFind[ncovf]=k; */ }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){ /* Vm is time varying */ - Fixed[k]= 1; - Dummy[k]= 1; + Fixed[k]= 2; + Dummy[k]= 3; modell[k].maintype= VTYPE; modell[k].subtype= VPDQ; /* Product fixed quantitative * varying dummy */ - ncovv++; /* Varying variables without age */ - TvarV[ncovv]=Tvar[k]; - TvarVind[ncovv]=k; + /* ncova++; /\* Varying variables with age *\/ */ + /* TvarV[ncova]=Tvar[k]; */ + /* TvarVind[ncova]=k; */ }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){ /* Vm is time varying quanti */ - Fixed[k]= 1; - Dummy[k]= 1; + Fixed[k]= 3; + Dummy[k]= 2; modell[k].maintype= VTYPE; modell[k].subtype= VPQQ; /* Product fixed quantitative * varying quantitative */ - ncovv++; /* Varying variables without age */ - TvarV[ncovv]=Tvar[k]; - TvarVind[ncovv]=k; - ncovv++; /* Varying variables without age */ - TvarV[ncovv]=Tvar[k]; - TvarVind[ncovv]=k; + ncova++; /* Varying variables without age */ + TvarV[ncova]=Tvar[k]; + TvarVind[ncova]=k; + /* ncova++; /\* Varying variables without age *\/ */ + /* TvarV[ncova]=Tvar[k]; */ + /* TvarVind[ncova]=k; */ } }else if(Tvard[k1][1] <=ncovcol+nqv+ntv){ /* Vn is time varying dummy */ if(Tvard[k1][2] <=ncovcol){ - Fixed[k]= 1; - Dummy[k]= 1; + Fixed[k]= 2; + Dummy[k]= 2; modell[k].maintype= VTYPE; modell[k].subtype= VPDD; /* Product time varying dummy * fixed dummy */ - ncovv++; /* Varying variables without age */ - TvarV[ncovv]=Tvar[k]; - TvarVind[ncovv]=k; + /* ncova++; /\* Varying variables with age *\/ */ + /* TvarV[ncova]=Tvar[k]; */ + /* TvarVind[ncova]=k; */ }else if(Tvard[k1][2] <=ncovcol+nqv){ - Fixed[k]= 1; - Dummy[k]= 1; + Fixed[k]= 2; + Dummy[k]= 3; modell[k].maintype= VTYPE; modell[k].subtype= VPDQ; /* Product time varying dummy * fixed quantitative */ - ncovv++; /* Varying variables without age */ - TvarV[ncovv]=Tvar[k]; - TvarVind[ncovv]=k; + /* ncova++; /\* Varying variables with age *\/ */ + /* TvarV[ncova]=Tvar[k]; */ + /* TvarVind[ncova]=k; */ }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){ - Fixed[k]= 1; - Dummy[k]= 0; + Fixed[k]= 3; + Dummy[k]= 2; modell[k].maintype= VTYPE; modell[k].subtype= VPDD; /* Product time varying dummy * time varying dummy */ - ncovv++; /* Varying variables without age */ - TvarV[ncovv]=Tvar[k]; - TvarVind[ncovv]=k; + /* ncova++; /\* Varying variables with age *\/ */ + /* TvarV[ncova]=Tvar[k]; */ + /* TvarVind[ncova]=k; */ }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){ - Fixed[k]= 1; - Dummy[k]= 1; + Fixed[k]= 3; + Dummy[k]= 3; modell[k].maintype= VTYPE; modell[k].subtype= VPDQ; /* Product time varying dummy * time varying quantitative */ - ncovv++; /* Varying variables without age */ - TvarV[ncovv]=Tvar[k]; - TvarVind[ncovv]=k; + /* ncova++; /\* Varying variables with age *\/ */ + /* TvarV[ncova]=Tvar[k]; */ + /* TvarVind[ncova]=k; */ } }else if(Tvard[k1][1] <=ncovcol+nqv+ntv+nqtv){ /* Vn is time varying quanti */ if(Tvard[k1][2] <=ncovcol){ - Fixed[k]= 1; - Dummy[k]= 1; + Fixed[k]= 2; + Dummy[k]= 2; modell[k].maintype= VTYPE; modell[k].subtype= VPDQ; /* Product time varying quantitative * fixed dummy */ - ncovv++; /* Varying variables without age */ - TvarV[ncovv]=Tvar[k]; - TvarVind[ncovv]=k; + /* ncova++; /\* Varying variables with age *\/ */ + /* TvarV[ncova]=Tvar[k]; */ + /* TvarVind[ncova]=k; */ }else if(Tvard[k1][2] <=ncovcol+nqv){ - Fixed[k]= 1; - Dummy[k]= 1; + Fixed[k]= 2; + Dummy[k]= 3; modell[k].maintype= VTYPE; modell[k].subtype= VPQQ; /* Product time varying quantitative * fixed quantitative */ - ncovv++; /* Varying variables without age */ - TvarV[ncovv]=Tvar[k]; - TvarVind[ncovv]=k; + /* ncova++; /\* Varying variables with age *\/ */ + /* TvarV[ncova]=Tvar[k]; */ + /* TvarVind[ncova]=k; */ }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){ - Fixed[k]= 1; - Dummy[k]= 1; + Fixed[k]= 3; + Dummy[k]= 2; modell[k].maintype= VTYPE; modell[k].subtype= VPDQ; /* Product time varying quantitative * time varying dummy */ - ncovv++; /* Varying variables without age */ - TvarV[ncovv]=Tvar[k]; - TvarVind[ncovv]=k; + /* ncova++; /\* Varying variables with age *\/ */ + /* TvarV[ncova]=Tvar[k]; */ + /* TvarVind[ncova]=k; */ }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){ - Fixed[k]= 1; - Dummy[k]= 1; + Fixed[k]= 3; + Dummy[k]= 3; modell[k].maintype= VTYPE; modell[k].subtype= VPQQ; /* Product time varying quantitative * time varying quantitative */ - ncovv++; /* Varying variables without age */ - TvarV[ncovv]=Tvar[k]; - TvarVind[ncovv]=k; + /* ncova++; /\* Varying variables with age *\/ */ + /* TvarV[ncova]=Tvar[k]; */ + /* TvarVind[ncova]=k; */ } }else{ printf("Error unknown type of covariate: Tvard[%d][1]=%d,Tvard[%d][2]=%d\n",k1,Tvard[k1][1],k1,Tvard[k1][2]); fprintf(ficlog,"Error unknown type of covariate: Tvard[%d][1]=%d,Tvard[%d][2]=%d\n",k1,Tvard[k1][1],k1,Tvard[k1][2]); } /*end k1*/ - }else{ + } else{ printf("Error, current version can't treat for performance reasons, Tvar[%d]=%d, Typevar[%d]=%d\n", k, Tvar[k], k, Typevar[k]); fprintf(ficlog,"Error, current version can't treat for performance reasons, Tvar[%d]=%d, Typevar[%d]=%d\n", k, Tvar[k], k, Typevar[k]); } @@ -11585,6 +13867,7 @@ Dummy[k] 0=dummy (0 1), 1 quantitative ( /* printf(" modell[%d].maintype=%d, modell[%d].subtype=%d\n",k,modell[k].maintype,k,modell[k].subtype); */ fprintf(ficlog,"Decodemodel, k=%d, Tvar[%d]=V%d,Typevar=%d, Fixed=%d, Dummy=%d\n",k, k,Tvar[k],Typevar[k],Fixed[k],Dummy[k]); } + ncovvta=ncovva; /* Searching for doublons in the model */ for(k1=1; k1<= cptcovt;k1++){ for(k2=1; k2 %s
      Tit /* Calculates basic frequencies. Computes observed prevalence at single age and for any valid combination of covariates and prints on file fileres'p'. */ - freqsummary(fileres, p, pstart, agemin, agemax, s, agev, nlstate, imx, Tvaraff, invalidvarcomb, nbcode, ncodemax,mint,anint,strstart, \ + freqsummary(fileres, p, pstart, (double)agemin, agemax, s, agev, nlstate, imx, Tvaraff, invalidvarcomb, nbcode, ncodemax,mint,anint,strstart, \ firstpass, lastpass, stepm, weightopt, model); fprintf(fichtm,"\n"); @@ -13408,7 +15742,7 @@ Interval (in months) between two waves: #ifdef GSL printf("GSL optimization\n"); fprintf(ficlog,"Powell\n"); #else - printf("Powell\n"); fprintf(ficlog,"Powell\n"); + printf("Powell-mort\n"); fprintf(ficlog,"Powell-mort\n"); #endif strcpy(filerespow,"POW-MORT_"); strcat(filerespow,fileresu); @@ -13503,15 +15837,25 @@ Interval (in months) between two waves: gsl_multimin_fminimizer_free (sfm); /* p *(sfm.x.data) et p *(sfm.x.data+1) */ #endif #ifdef POWELL +#ifdef LINMINORIGINAL +#else /* LINMINORIGINAL */ + + flatdir=ivector(1,npar); + for (j=1;j<=npar;j++) flatdir[j]=0; +#endif /*LINMINORIGINAL */ powell(p,ximort,NDIM,ftol,&iter,&fret,gompertz); #endif fclose(ficrespow); +#ifdef LINMINORIGINAL +#else + free_ivector(flatdir,1,npar); +#endif /* LINMINORIGINAL*/ hesscov(matcov, hess, p, NDIM, delti, 1e-4, gompertz); for(i=1; i <=NDIM; i++) for(j=i+1;j<=NDIM;j++) - matcov[i][j]=matcov[j][i]; + matcov[i][j]=matcov[j][i]; printf("\nCovariance matrix\n "); fprintf(ficlog,"\nCovariance matrix\n "); @@ -13656,6 +16000,11 @@ Please run with mle=-1 to get a correct fprintf(ficres," + V%d*V%d ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]); fprintf(ficlog," + V%d*V%d ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]); fprintf(fichtm, "+ V%d*V%d",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]); + }else if(Typevar[j]==3) { /* TO VERIFY */ + printf(" + V%d*V%d*age ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]); + fprintf(ficres," + V%d*V%d*age ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]); + fprintf(ficlog," + V%d*V%d*age ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]); + fprintf(fichtm, "+ V%d*V%d*age",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]); } } printf("\n"); @@ -13715,6 +16064,8 @@ Please run with mle=-1 to get a correct fprintf(fichtm, "+ V%d*age",Tvar[j]); }else if(Typevar[j]==2) { fprintf(fichtm, "+ V%d*V%d",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]); + }else if(Typevar[j]==3) { /* TO VERIFY */ + fprintf(fichtm, "+ V%d*V%d*age",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]); } } fprintf(fichtm, "\n"); @@ -13772,7 +16123,7 @@ Please run with mle=-1 to get a correct } fprintf(ficres,"# Covariance matrix \n# 121 Var(a12)\n# 122 Cov(b12,a12) Var(b12)\n# ...\n# 232 Cov(b23,a12) Cov(b23,b12) ... Var (b23)\n"); - if(mle >= 1) /* To big for the screen */ + if(mle >= 1) /* Too big for the screen */ printf("# Covariance matrix \n# 121 Var(a12)\n# 122 Cov(b12,a12) Var(b12)\n# ...\n# 232 Cov(b23,a12) Cov(b23,b12) ... Var (b23)\n"); fprintf(ficlog,"# Covariance matrix \n# 121 Var(a12)\n# 122 Cov(b12,a12) Var(b12)\n# ...\n# 232 Cov(b23,a12) Cov(b23,b12) ... Var (b23)\n"); /* # 121 Var(a12)\n\ */ @@ -13958,7 +16309,7 @@ Please run with mle=-1 to get a correct } /* Results */ - /* Value of covariate in each resultine will be compututed (if product) and sorted according to model rank */ + /* Value of covariate in each resultine will be computed (if product) and sorted according to model rank */ /* It is precov[] because we need the varying age in order to compute the real cov[] of the model equation */ precov=matrix(1,MAXRESULTLINESPONE,1,NCOVMAX+1); endishere=0; @@ -14128,7 +16479,7 @@ Please run with mle=-1 to get a correct date2dmy(datebackf,&jbackf, &mbackf, &anbackf); } - printinggnuplot(fileresu, optionfilefiname,ageminpar,agemaxpar,bage, fage, prevfcast, prevbcast, pathc,p, (int)anprojd-bage, (int)anbackd-fage); + printinggnuplot(fileresu, optionfilefiname,ageminpar,agemaxpar,bage, fage, prevfcast, prevbcast, pathc,p, (int)anprojd-bage, (int)anbackd-fage);/* HERE valgrind Tvard*/ } printinghtml(fileresu,title,datafile, firstpass, lastpass, stepm, weightopt, \ model,imx,jmin,jmax,jmean,rfileres,popforecast,mobilav,prevfcast,mobilavproj,prevbcast, estepm, \ @@ -14278,18 +16629,21 @@ Please run with mle=-1 to get a correct pstamp(ficreseij); - i1=pow(2,cptcoveff); /* Number of combination of dummy covariates */ - if (cptcovn < 1){i1=1;} + /* i1=pow(2,cptcoveff); /\* Number of combination of dummy covariates *\/ */ + /* if (cptcovn < 1){i1=1;} */ - for(nres=1; nres <= nresult; nres++) /* For each resultline */ - for(k=1; k<=i1;k++){ /* For any combination of dummy covariates, fixed and varying */ - if(i1 != 1 && TKresult[nres]!= k) - continue; + for(nres=1; nres <= nresult; nres++){ /* For each resultline */ + /* for(k=1; k<=i1;k++){ /\* For any combination of dummy covariates, fixed and varying *\/ */ + /* if(i1 != 1 && TKresult[nres]!= k) */ + /* continue; */ fprintf(ficreseij,"\n#****** "); printf("\n#****** "); - for(j=1;j<=cptcoveff;j++) { - fprintf(ficreseij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); - printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); + for(j=1;j<=cptcovs;j++){ + /* for(j=1;j<=cptcoveff;j++) { */ + /* fprintf(ficreseij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */ + fprintf(ficreseij," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]); + printf(" V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]); + /* printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */ } for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */ printf(" V%d=%lg ",TvarsQ[j], TinvDoQresult[nres][TvarsQ[j]]); /* TvarsQ[j] gives the name of the jth quantitative (fixed or time v) */ @@ -14358,9 +16712,9 @@ Please run with mle=-1 to get a correct /* */ if(i1 != 1 && TKresult[nres]!= k) /* TKresult[nres] is the combination of this nres resultline. All the i1 combinations are not output */ continue; - printf("\n# model %s \n#****** Result for:", model); - fprintf(ficrest,"\n# model %s \n#****** Result for:", model); - fprintf(ficlog,"\n# model %s \n#****** Result for:", model); + printf("\n# model=1+age+%s \n#****** Result for:", model); /* HERE model is empty */ + fprintf(ficrest,"\n# model=1+age+%s \n#****** Result for:", model); + fprintf(ficlog,"\n# model=1+age+%s \n#****** Result for:", model); /* It might not be a good idea to mix dummies and quantitative */ /* for(j=1;j<=cptcoveff;j++){ /\* j=resultpos. Could be a loop on cptcovs: number of single dummy covariate in the result line as well as in the model *\/ */ for(j=1;j<=cptcovs;j++){ /* j=resultpos. Could be a loop on cptcovs: number of single covariate (dummy or quantitative) in the result line as well as in the model */ @@ -14468,16 +16822,21 @@ Please run with mle=-1 to get a correct for(vpopbased=0; vpopbased <= popbased; vpopbased++){ /* Done for vpopbased=0 and vpopbased=1 if popbased==1*/ oldm=oldms;savm=savms; /* ZZ Segmentation fault */ cptcod= 0; /* To be deleted */ - printf("varevsij vpopbased=%d \n",vpopbased); - fprintf(ficlog, "varevsij vpopbased=%d \n",vpopbased); + printf("varevsij vpopbased=%d popbased=%d \n",vpopbased,popbased); + fprintf(ficlog, "varevsij vpopbased=%d popbased=%d \n",vpopbased,popbased); + /* Call to varevsij to get cov(e.i, e.j)= vareij[i][j][(int)age]=sum_h sum_k trgrad(h_p.i) V(theta) grad(k_p.k) Equation 20 */ + /* Depending of popbased which changes the prevalences, either cross-sectional or period */ varevsij(optionfilefiname, vareij, matcov, p, delti, nlstate, stepm, (int) bage, (int) fage, oldm, savm, prlim, ftolpl, &ncvyear, k, estepm, cptcov,cptcod,vpopbased,mobilav, strstart, nres); /* cptcod not initialized Intel */ - fprintf(ficrest,"# Total life expectancy with std error and decomposition into time to be expected in each health state\n# (weighted average of eij where weights are "); + fprintf(ficrest,"# Total life expectancy with std error and decomposition into time to be expected in each state\n\ +# (these are weighted average of eij where weights are "); if(vpopbased==1) - fprintf(ficrest,"the age specific prevalence observed (cross-sectionally) in the population i.e cross-sectionally\n in each health state (popbased=1) (mobilav=%d)\n",mobilav); + fprintf(ficrest,"the age specific prevalence observed (cross-sectionally) in the population i.e cross-sectionally)\n in each health state (popbased=1) (mobilav=%d)\n",mobilav); else - fprintf(ficrest,"the age specific forward period (stable) prevalences in each health state \n"); + fprintf(ficrest,"the age specific forward period (stable) prevalences in each state) \n"); + fprintf(ficrest,"# with proportions of time spent in each state with standard error (on the right of the table.\n "); fprintf(ficrest,"# Age popbased mobilav e.. (std) "); /* Adding covariate values? */ for (i=1;i<=nlstate;i++) fprintf(ficrest,"e.%d (std) ",i); + for (i=1;i<=nlstate;i++) fprintf(ficrest," %% e.%d/e.. (std) ",i); fprintf(ficrest,"\n"); /* printf("Which p?\n"); for(i=1;i<=npar;i++)printf("p[i=%d]=%lf,",i,p[i]);printf("\n"); */ printf("Computing age specific forward period (stable) prevalences in each health state \n"); @@ -14503,17 +16862,36 @@ Please run with mle=-1 to get a correct /*ZZZ printf("%lf %lf ", prlim[i][i] ,eij[i][j][(int)age]);*/ /* printf("%lf %lf ", prlim[i][i] ,eij[i][j][(int)age]); */ } - epj[nlstate+1] +=epj[j]; + epj[nlstate+1] +=epj[j]; /* epp=sum_j epj = sum_j sum_i w_i e_ij */ } /* printf(" age %4.0f \n",age); */ - for(i=1, vepp=0.;i <=nlstate;i++) + for(i=1, vepp=0.;i <=nlstate;i++) /* Variance of total life expectancy e.. */ for(j=1;j <=nlstate;j++) - vepp += vareij[i][j][(int)age]; + vepp += vareij[i][j][(int)age]; /* sum_i sum_j cov(e.i, e.j) = var(e..) */ fprintf(ficrest," %7.3f (%7.3f)", epj[nlstate+1],sqrt(vepp)); + /* vareij[i][j] is the covariance cov(e.i, e.j) and vareij[j][j] is the variance of e.j */ for(j=1;j <=nlstate;j++){ fprintf(ficrest," %7.3f (%7.3f)", epj[j],sqrt(vareij[j][j][(int)age])); } + /* And proportion of time spent in state j */ + /* $$ E[r(X,Y)-E(r(X,Y))]^2=[\frac{1}{\mu_y} -\frac{\mu_x}{{\mu_y}^2}]' Var(X,Y)[\frac{1}{\mu_y} -\frac{\mu_x}{{\mu_y}^2}]$$ */ + /* \frac{\mu_x^2}{\mu_y^2} ( \frac{\sigma^2_x}{\mu_x^2}-2\frac{\sigma_{xy}}{\mu_x\mu_y} +\frac{\sigma^2_y}{\mu_y^2}) */ + /* \frac{e_{.i}^2}{e_{..}^2} ( \frac{\Var e_{.i}}{e_{.i}^2}-2\frac{\Var e_{.i} + \sum_{j\ne i} \Cov e_{.j},e_{.i}}{e_{.i}e_{..}} +\frac{\Var e_{..}}{e_{..}^2})*/ + /*\mu_x = epj[j], \sigma^2_x = vareij[j][j][(int)age] and \mu_y=epj[nlstate+1], \sigma^2_y=vepp \sigmaxy= */ + /* vareij[j][j][(int)age]/epj[nlstate+1]^2 + vepp/epj[nlstate+1]^4 */ + for(j=1;j <=nlstate;j++){ + /* fprintf(ficrest," %7.3f (%7.3f)", epj[j]/epj[nlstate+1], sqrt( vareij[j][j][(int)age]/epj[j]/epj[j] + vepp/epj[j]/epj[j]/epj[j]/epj[j] )); */ + /* fprintf(ficrest," %7.3f (%7.3f)", epj[j]/epj[nlstate+1], sqrt( vareij[j][j][(int)age]/epj[j]/epj[j] + vepp/epj[j]/epj[j]/epj[j]/epj[j] )); */ + + for(i=1,stdpercent=0.;i<=nlstate;i++){ /* Computing cov(e..,e.j)=cov(sum_i e.i,e.j)=sum_i cov(e.i, e.j) */ + stdpercent += vareij[i][j][(int)age]; + } + stdpercent= epj[j]*epj[j]/epj[nlstate+1]/epj[nlstate+1]* (vareij[j][j][(int)age]/epj[j]/epj[j]-2.*stdpercent/epj[j]/epj[nlstate+1]+ vepp/epj[nlstate+1]/epj[nlstate+1]); + /* stdpercent= epj[j]*epj[j]/epj[nlstate+1]/epj[nlstate+1]*(vareij[j][j][(int)age]/epj[j]/epj[j] + vepp/epj[nlstate+1]/epj[nlstate+1]); */ /* Without covariance */ + /* fprintf(ficrest," %7.3f (%7.3f)", epj[j]/epj[nlstate+1], sqrt( vareij[j][j][(int)age]/epj[nlstate+1]/epj[nlstate+1] + epj[j]*epj[j]*vepp/epj[nlstate+1]/epj[nlstate+1]/epj[nlstate+1]/epj[nlstate+1] )); */ + fprintf(ficrest," %7.3f (%7.3f)", epj[j]/epj[nlstate+1], sqrt(stdpercent)); + } fprintf(ficrest,"\n"); } } /* End vpopbased */ @@ -14533,7 +16911,7 @@ Please run with mle=-1 to get a correct free_vector(weight,firstobs,lastobs); - free_imatrix(Tvardk,1,NCOVMAX,1,2); + free_imatrix(Tvardk,0,NCOVMAX,1,2); free_imatrix(Tvard,1,NCOVMAX,1,2); free_imatrix(s,1,maxwav+1,firstobs,lastobs); free_matrix(anint,1,maxwav,firstobs,lastobs); @@ -14555,6 +16933,7 @@ Please run with mle=-1 to get a correct free_matrix(pmmij,1,nlstate+ndeath,1,nlstate+ndeath); } /* mle==-3 arrives here for freeing */ /* endfree:*/ + if(mle!=-3) free_matrix(precov, 1,MAXRESULTLINESPONE,1,NCOVMAX+1); /* Could be elsewhere ?*/ free_matrix(oldms, 1,nlstate+ndeath,1,nlstate+ndeath); free_matrix(newms, 1,nlstate+ndeath,1,nlstate+ndeath); free_matrix(savms, 1,nlstate+ndeath,1,nlstate+ndeath); @@ -14575,8 +16954,8 @@ Please run with mle=-1 to get a correct free_ivector(ncodemaxwundef,1,NCOVMAX); free_ivector(Dummy,-1,NCOVMAX); free_ivector(Fixed,-1,NCOVMAX); - free_ivector(DummyV,1,NCOVMAX); - free_ivector(FixedV,1,NCOVMAX); + free_ivector(DummyV,-1,NCOVMAX); + free_ivector(FixedV,-1,NCOVMAX); free_ivector(Typevar,-1,NCOVMAX); free_ivector(Tvar,1,NCOVMAX); free_ivector(TvarsQ,1,NCOVMAX); @@ -14598,6 +16977,10 @@ Please run with mle=-1 to get a correct free_ivector(TvarVDind,1,NCOVMAX); free_ivector(TvarVQ,1,NCOVMAX); free_ivector(TvarVQind,1,NCOVMAX); + free_ivector(TvarAVVA,1,NCOVMAX); + free_ivector(TvarAVVAind,1,NCOVMAX); + free_ivector(TvarVVA,1,NCOVMAX); + free_ivector(TvarVVAind,1,NCOVMAX); free_ivector(TvarVV,1,NCOVMAX); free_ivector(TvarVVind,1,NCOVMAX); @@ -14612,7 +16995,7 @@ Please run with mle=-1 to get a correct free_ivector(TmodelInvind,1,NCOVMAX); free_ivector(TmodelInvQind,1,NCOVMAX); - free_matrix(precov, 1,MAXRESULTLINESPONE,1,NCOVMAX+1); /* Could be elsewhere ?*/ + /* free_matrix(precov, 1,MAXRESULTLINESPONE,1,NCOVMAX+1); /\* Could be elsewhere ?*\/ */ free_imatrix(nbcode,0,NCOVMAX,0,NCOVMAX); /* free_imatrix(codtab,1,100,1,10); */