X-Git-Url: https://git.auder.net/?p=valse.git;a=blobdiff_plain;f=R%2FgridLambda.R;h=855b4a6f8fa0ea5d9d0354eae97f0bf94b89689c;hp=66b6cc2eba16aed17403d0f9df8ce377c609abf2;hb=31463ab809c0195273ff2760606ea65361d721ab;hpb=39046da6016f15d625bd99cf0303ea8beb838c79

diff --git a/R/gridLambda.R b/R/gridLambda.R
index 66b6cc2..855b4a6 100644
--- a/R/gridLambda.R
+++ b/R/gridLambda.R
@@ -1,3 +1,14 @@
+#' Construct the data-driven grid for the regularization parameters used for the Lasso estimator
+#' @param phiInit value for phi
+#' @param rhoInt	value for rho
+#' @param piInit	value for pi
+#' @param gamInit value for gamma
+#' @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
+#' @return the grid of regularization parameters
+#' @export
+#-----------------------------------------------------------------------
 gridLambda = function(phiInit, rhoInit, piInit, gamInit, X, Y, gamma, mini, maxi, tau)
 {
 	n = nrow(X)
@@ -5,7 +16,7 @@ gridLambda = function(phiInit, rhoInit, piInit, gamInit, X, Y, gamma, mini, maxi
 	m = dim(phiInit)[2]
 	k = dim(phiInit)[3]
 
-	list_EMG = .Call("EMGLLF",phiInit,rhoInit,piInit,gamInit,mini,maxi,1,0,X,Y,tau)
+	list_EMG = .Call("EMGLLF_core",phiInit,rhoInit,piInit,gamInit,mini,maxi,1,0,X,Y,tau)
 
 	grid = array(0, dim=c(p,m,k))
 	for (i in 1:p)