X-Git-Url: https://git.auder.net/?p=valse.git;a=blobdiff_plain;f=pkg%2FR%2FcomputeGridLambda.R;fp=pkg%2FR%2FcomputeGridLambda.R;h=f087ba7167eb19267ecc7a5c9545f6596be9b22e;hp=ac0788a138dd4c28f61dcbf5de3b68da619c0f35;hb=f32535f2bc8d50470aa87204bbd7971805dbc9ef;hpb=7fd371e5317f9c61fe5a32daadbbac1c64b2dd31

diff --git a/pkg/R/computeGridLambda.R b/pkg/R/computeGridLambda.R
index ac0788a..f087ba7 100644
--- a/pkg/R/computeGridLambda.R
+++ b/pkg/R/computeGridLambda.R
@@ -1,4 +1,4 @@
-#' computeGridLambda 
+#' computeGridLambda
 #'
 #' Construct the data-driven grid for the regularization parameters used for the Lasso estimator
 #'
@@ -16,7 +16,7 @@
 #' @return the grid of regularization parameters
 #'
 #' @export
-computeGridLambda <- function(phiInit, rhoInit, piInit, gamInit, X, Y, gamma, mini, 
+computeGridLambda <- function(phiInit, rhoInit, piInit, gamInit, X, Y, gamma, mini,
   maxi, eps, fast)
 {
   n <- nrow(X)
@@ -24,7 +24,7 @@ computeGridLambda <- function(phiInit, rhoInit, piInit, gamInit, X, Y, gamma, mi
   m <- ncol(Y)
   k <- length(piInit)
 
-  list_EMG <- EMGLLF(phiInit, rhoInit, piInit, gamInit, mini, maxi, gamma, lambda = 0, 
+  list_EMG <- EMGLLF(phiInit, rhoInit, piInit, gamInit, mini, maxi, gamma, lambda = 0,
     X, Y, eps, fast)
 
   grid <- array(0, dim = c(p, m, k))