R/selectVariables.R

   1 #' selectVariables
   2 #' It is a function which construct, for a given lambda, the sets of relevant variables.
   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)
   6 #' @param piInit    an initial estimator for pi (size : k)
   7 #' @param gamInit an initial estimator for gamma
   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
  11 #' @param glambda grid of regularization parameters
  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
  16 #'
  17 #' @return a list of outputs, for each lambda in grid: selected,Rho,Pi
  18 #'
  19 #' @examples TODO
  20 #'
  21 #' @export
  22 selectVariables = function(phiInit,rhoInit,piInit,gamInit,mini,maxi,gamma,glambda,X,Y,seuil,tau)
  23 {
  24     cl = parallel::makeCluster( parallel::detectCores() / 4 )
  25     parallel::clusterExport(cl=cl,
  26         varlist=c("phiInit","rhoInit","gamInit","mini","maxi","glambda","X","Y","seuil","tau"),
  27         envir=environment())
  28     #Pour chaque lambda de la grille, on calcule les coefficients
  29     out = parLapply( 1:L, function(lambdaindex)
  30     {
  31         params = EMGLLF(phiInit,rhoInit,piInit,gamInit,mini,maxi,gamma,glambda[lambdaIndex],X,Y,tau)
  32
  33         p = dim(phiInit)[1]
  34         m = dim(phiInit)[2]
  35         #selectedVariables: list where element j contains vector of selected variables in [1,m]
  36         selectedVariables = lapply(1:p, function(j) {
  37             #from boolean matrix mxk of selected variables obtain the corresponding boolean m-vector,
  38             #and finally return the corresponding indices
  39             seq_len(m)[ apply( abs(params$phi[j,,]) > seuil, 1, any ) ]
  40         })
  41
  42         list("selected"=selectedVariables,"Rho"=params$Rho,"Pi"=params$Pi)
  43     })
  44     parallel::stopCluster(cl)
  45 }