#' selectVariables
#'
-#' It is a function which construct, for a given lambda, the sets of relevant variables.
+#' For a given lambda, construct the sets of relevant variables for each cluster.
#'
#' @param phiInit an initial estimator for phi (size: p*m*k)
#' @param rhoInit an initial estimator for rho (size: m*m*k)
#' @param thresh real, threshold to say a variable is relevant, by default = 1e-8
#' @param eps threshold to say that EM algorithm has converged
#' @param ncores Number or cores for parallel execution (1 to disable)
+#' @param fast boolean to enable or not the C function call
#'
#' @return a list of outputs, for each lambda in grid: selected,Rho,Pi
#'
-#' @examples TODO
-#'
#' @export
-#'
selectVariables <- function(phiInit, rhoInit, piInit, gamInit, mini, maxi, gamma,
glambda, X, Y, thresh = 1e-08, eps, ncores = 3, fast)
{
if (ncores > 1)
parallel::stopCluster(cl)
- print(out)
- # 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
+ # Suppress models which are computed twice
# sha1_array <- lapply(out, digest::sha1) out[ duplicated(sha1_array) ]
selec <- lapply(out, function(model) model$selected)
ind_dup <- duplicated(selec)