#'
#' @param phiInit an initial estimator for phi (size: p*m*k)
#' @param rhoInit an initial estimator for rho (size: m*m*k)
#'
#' @param phiInit an initial estimator for phi (size: p*m*k)
#' @param rhoInit an initial estimator for rho (size: m*m*k)
-#' @param mini\t\tminimum number of iterations in EM algorithm
-#' @param maxi\t\tmaximum number of iterations in EM algorithm
-#' @param gamma\t power in the penalty
+#' @param mini minimum number of iterations in EM algorithm
+#' @param maxi maximum number of iterations in EM algorithm
+#' @param gamma power in the penalty
#' @param ncores Number or cores for parallel execution (1 to disable)
#'
#' @return a list of outputs, for each lambda in grid: selected,Rho,Pi
#' @param ncores Number or cores for parallel execution (1 to disable)
#'
#' @return a list of outputs, for each lambda in grid: selected,Rho,Pi
#' @export
#'
selectVariables <- function(phiInit, rhoInit, piInit, gamInit, mini, maxi, gamma,
#' @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)
- 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
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
selec <- lapply(out, function(model) model$selected)
ind_dup <- duplicated(selec)
ind_uniq <- which(!ind_dup)
selec <- lapply(out, function(model) model$selected)
ind_dup <- duplicated(selec)
ind_uniq <- which(!ind_dup)