#' @export
#'
selectVariables <- function(phiInit, rhoInit, piInit, gamInit, mini, maxi, gamma,
- glambda, X, Y, thresh = 1e-08, eps, ncores = 3, fast = TRUE)
+ glambda, X, Y, thresh = 1e-08, eps, ncores = 3, fast)
{
if (ncores > 1) {
cl <- parallel::makeCluster(ncores, outfile = "")
}
# For each lambda in the grid, we compute the coefficients
- out <- if (ncores > 1)
- parLapply(cl, glambda, computeCoefs) else lapply(glambda, computeCoefs)
+ out <-
+ if (ncores > 1) {
+ parLapply(cl, glambda, computeCoefs)
+ } else {
+ lapply(glambda, computeCoefs)
+ }
if (ncores > 1)
parallel::stopCluster(cl)
# Suppress models which are computed twice En fait, ca ca fait la comparaison de
# tous les parametres On veut juste supprimer ceux qui ont les memes variables
- # sélectionnées sha1_array <- lapply(out, digest::sha1) out[
- # duplicated(sha1_array) ]
+ # sélectionnées
+ # sha1_array <- lapply(out, digest::sha1) out[ duplicated(sha1_array) ]
selec <- lapply(out, function(model) model$selected)
ind_dup <- duplicated(selec)
ind_uniq <- which(!ind_dup)