X-Git-Url: https://git.auder.net/?p=valse.git;a=blobdiff_plain;f=pkg%2FR%2FconstructionModelesLassoMLE.R;h=692fbe190121eb99399b839376ed2c8e006d535c;hp=0584382fa4a602a2651d8022d1635bab6178ea7d;hb=6af1d4897dbab92a7be05068e0e15823378965d9;hpb=fb3557f39487d9631ffde30f20b70938d2a6ab0c

diff --git a/pkg/R/constructionModelesLassoMLE.R b/pkg/R/constructionModelesLassoMLE.R
index 0584382..692fbe1 100644
--- a/pkg/R/constructionModelesLassoMLE.R
+++ b/pkg/R/constructionModelesLassoMLE.R
@@ -17,7 +17,10 @@
 #' @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.
 #'
 #' @export
 constructionModelesLassoMLE <- function(phiInit, rhoInit, piInit, gamInit, mini,
@@ -102,7 +105,7 @@ constructionModelesLassoMLE <- function(phiInit, rhoInit, piInit, gamInit, mini,
   # For each lambda, computation of the parameters
   out <-
     if (ncores > 1) {
-      parLapply(cl, 1:length(S), computeAtLambda)
+      parallel::parLapply(cl, 1:length(S), computeAtLambda)
     } else {
       lapply(1:length(S), computeAtLambda)
     }