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7064275b BA |
1 | #' selectVariables |
2 | #' It is a function which construct, for a given lambda, the sets of relevant variables. | |
e01c9b1f | 3 | #' |
4 | #' @param phiInit an initial estimator for phi (size: p*m*k) | |
5 | #' @param rhoInit an initial estimator for rho (size: m*m*k) | |
09ab3c16 | 6 | #' @param piInit an initial estimator for pi (size : k) |
e01c9b1f | 7 | #' @param gamInit an initial estimator for gamma |
09ab3c16 BA |
8 | #' @param mini minimum number of iterations in EM algorithm |
9 | #' @param maxi maximum number of iterations in EM algorithm | |
10 | #' @param gamma power in the penalty | |
e01c9b1f | 11 | #' @param glambda grid of regularization parameters |
09ab3c16 BA |
12 | #' @param X matrix of regressors |
13 | #' @param Y matrix of responses | |
14 | #' @param thres threshold to consider a coefficient to be equal to 0 | |
15 | #' @param tau threshold to say that EM algorithm has converged | |
e01c9b1f | 16 | #' |
7064275b | 17 | #' @return a list of outputs, for each lambda in grid: selected,Rho,Pi |
cad71b2c BA |
18 | #' |
19 | #' @examples TODO | |
e01c9b1f | 20 | #' |
cad71b2c | 21 | #' @export |
7064275b | 22 | selectVariables = function(phiInit,rhoInit,piInit,gamInit,mini,maxi,gamma,glambda,X,Y,seuil,tau) |
09ab3c16 | 23 | { |
07848d25 | 24 | #TODO: parameter ncores (chaque tâche peut aussi demander du parallélisme...) |
7064275b BA |
25 | cl = parallel::makeCluster( parallel::detectCores() / 4 ) |
26 | parallel::clusterExport(cl=cl, | |
27 | varlist=c("phiInit","rhoInit","gamInit","mini","maxi","glambda","X","Y","seuil","tau"), | |
28 | envir=environment()) | |
29 | #Pour chaque lambda de la grille, on calcule les coefficients | |
07848d25 | 30 | out = parLapply( seq_along(glambda), function(lambdaindex) |
09ab3c16 | 31 | { |
7064275b BA |
32 | p = dim(phiInit)[1] |
33 | m = dim(phiInit)[2] | |
07848d25 BA |
34 | |
35 | params = EMGLLF(phiInit,rhoInit,piInit,gamInit,mini,maxi,gamma,glambda[lambdaIndex],X,Y,tau) | |
36 | ||
7064275b BA |
37 | #selectedVariables: list where element j contains vector of selected variables in [1,m] |
38 | selectedVariables = lapply(1:p, function(j) { | |
39 | #from boolean matrix mxk of selected variables obtain the corresponding boolean m-vector, | |
40 | #and finally return the corresponding indices | |
41 | seq_len(m)[ apply( abs(params$phi[j,,]) > seuil, 1, any ) ] | |
42 | }) | |
09ab3c16 | 43 | |
7064275b BA |
44 | list("selected"=selectedVariables,"Rho"=params$Rho,"Pi"=params$Pi) |
45 | }) | |
46 | parallel::stopCluster(cl) | |
5955cc25 | 47 | out |
09ab3c16 | 48 | } |