R/selectiontotale.R

   1 #Return a list of outputs, for each lambda in grid: selected,Rho,Pi
   2 selectiontotale = function(phiInit,rhoInit,piInit,gamInit,mini,maxi,gamma,glambda,X,Y,seuil,tau)
   3 {
   4     cl = parallel::makeCluster( parallel::detectCores() / 4 )
   5     parallel::clusterExport(cl=cl,
   6         varlist=c("phiInit","rhoInit","gamInit","mini","maxi","glambda","X","Y","seuil","tau"),
   7         envir=environment())
   8     #Pour chaque lambda de la grille, on calcule les coefficients
   9     out = parLapply( 1:L, function(lambdaindex)
  10     {
  11         params = EMGLLF(phiInit,rhoInit,piInit,gamInit,mini,maxi,gamma,glambda[lambdaIndex],X,Y,tau)
  12
  13         p = dim(phiInit)[1]
  14         m = dim(phiInit)[2]
  15         #selectedVariables: list where element j contains vector of selected variables in [1,m]
  16         selectedVariables = lapply(1:p, function(j) {
  17             #from boolean matrix mxk of selected variables obtain the corresponding boolean m-vector,
  18             #and finally return the corresponding indices
  19             seq_len(m)[ apply( abs(params$phi[j,,]) > seuil, 1, any ) ]
  20         })
  21
  22         list("selected"=selectedVariables,"Rho"=params$Rho,"Pi"=params$Pi)
  23     })
  24     parallel::stopCluster(cl)
  25 }