X-Git-Url: https://git.auder.net/?p=valse.git;a=blobdiff_plain;f=pkg%2FR%2Fmain.R;h=fecf51979584ffcb2cbe964839d7cda737ce4fc0;hp=64e058629859e8b1442e5a1110a2eb8670b554bf;hb=a3cbbaea1cc3c107e5ca62ed1ffe7b9499de0a91;hpb=96b591b7a76da9780e766ead693eb065281b6d62

diff --git a/pkg/R/main.R b/pkg/R/main.R
index 64e0586..fecf519 100644
--- a/pkg/R/main.R
+++ b/pkg/R/main.R
@@ -57,7 +57,7 @@ valse <- function(X, Y, procedure = "LassoMLE", selecMod = "DDSE", gamma = 1, mi
     # smallEM initializes parameters by k-means and regression model in each
     # component, doing this 20 times, and keeping the values maximizing the
     # likelihood after 10 iterations of the EM algorithm.
-    P <- initSmallEM(k, X, Y)
+    P <- initSmallEM(k, X, Y, fast)
     grid_lambda <- computeGridLambda(P$phiInit, P$rhoInit, P$piInit, P$gamInit, 
       X, Y, gamma, mini, maxi, eps, fast)
     if (length(grid_lambda) > size_coll_mod)