X-Git-Url: https://git.auder.net/?p=valse.git;a=blobdiff_plain;f=pkg%2FR%2FcomputeGridLambda.R;fp=pkg%2FR%2FcomputeGridLambda.R;h=ac0788a138dd4c28f61dcbf5de3b68da619c0f35;hp=8449d1074a75a32b310f6e11147f08d2c9e0324e;hb=6279ba8656582370e7242ff9e77d22c23fe8ca04;hpb=5a47894523d56550ce55a27230cf577dbcd1f681

diff --git a/pkg/R/computeGridLambda.R b/pkg/R/computeGridLambda.R
index 8449d10..ac0788a 100644
--- a/pkg/R/computeGridLambda.R
+++ b/pkg/R/computeGridLambda.R
@@ -11,13 +11,13 @@
 #' @param gamma power of weights in the penalty
 #' @param mini minimum number of iterations in EM algorithm
 #' @param maxi maximum number of iterations in EM algorithm
-#' @param tau threshold to stop EM algorithm
+#' @param eps threshold to stop EM algorithm
 #'
 #' @return the grid of regularization parameters
 #'
 #' @export
 computeGridLambda <- function(phiInit, rhoInit, piInit, gamInit, X, Y, gamma, mini, 
-  maxi, tau, fast)
+  maxi, eps, fast)
 {
   n <- nrow(X)
   p <- ncol(X)
@@ -25,7 +25,8 @@ computeGridLambda <- function(phiInit, rhoInit, piInit, gamInit, X, Y, gamma, mi
   k <- length(piInit)
 
   list_EMG <- EMGLLF(phiInit, rhoInit, piInit, gamInit, mini, maxi, gamma, lambda = 0, 
-    X, Y, tau, fast)
+    X, Y, eps, fast)
+
   grid <- array(0, dim = c(p, m, k))
   for (j in 1:p)
   {