#' @param fast TRUE to use compiled C code, FALSE for R code only
#' @param verbose TRUE to show some execution traces
#'
-#' @return a list with several models, defined by phi, rho, pi, llh
+#' @return a list with several models, defined by phi (the regression parameter reparametrized),
+#' rho (the covariance parameter reparametrized), pi (the proportion parameter is the mixture model), llh
+#' (the value of the loglikelihood function for this estimator on the training dataset). The list is given
+#' for several levels of sparsity, given by several regularization parameters computed automatically,
+#' and several ranks (between rank.min and rank.max).
#'
#' @export
constructionModelesLassoRank <- function(S, k, mini, maxi, X, Y, eps, rank.min, rank.max,
# For each lambda in the grid we compute the estimators
out <-
if (ncores > 1) {
- parLapply(cl, seq_len(length(S) * Size), computeAtLambda)
+ parallel::parLapply(cl, seq_len(length(S) * Size), computeAtLambda)
} else {
lapply(seq_len(length(S) * Size), computeAtLambda)
}