X-Git-Url: https://git.auder.net/?p=valse.git;a=blobdiff_plain;f=pkg%2FR%2FconstructionModelesLassoMLE.R;h=b86498559d532c0fd6385781441d1c5db90bf944;hp=227dfdcfeb7c0a331b4c277eb4562435769f4931;hb=fb6e49cb85308c3f99cc98fe955aa7c36839c819;hpb=9fadef2bff80d4b0371962dea4b6de24086f230b

diff --git a/pkg/R/constructionModelesLassoMLE.R b/pkg/R/constructionModelesLassoMLE.R
index 227dfdc..b864985 100644
--- a/pkg/R/constructionModelesLassoMLE.R
+++ b/pkg/R/constructionModelesLassoMLE.R
@@ -31,11 +31,9 @@ constructionModelesLassoMLE = function(phiInit, rhoInit, piInit, gamInit, mini,
 		p = dim(phiInit)[1]
 		m = dim(phiInit)[2]
 		k = dim(phiInit)[3]
-
 		sel.lambda = S[[lambda]]$selected
 #		col.sel = which(colSums(sel.lambda)!=0) #if boolean matrix
 		col.sel <- which( sapply(sel.lambda,length) > 0 ) #if list of selected vars
-
 		if (length(col.sel) == 0)
 			return (NULL)
 
@@ -49,14 +47,16 @@ constructionModelesLassoMLE = function(phiInit, rhoInit, piInit, gamInit, mini,
 		piLambda = res$pi
 		phiLambda = array(0, dim = c(p,m,k))
 		for (j in seq_along(col.sel))
-			phiLambda[col.sel[j],,] = phiLambda2[j,,]
+			phiLambda[col.sel[j],sel.lambda[[j]],] = phiLambda2[j,sel.lambda[[j]],]
 		dimension = length(unlist(sel.lambda))
 
 		# Computation of the loglikelihood
 		densite = vector("double",n)
 		for (r in 1:k)
 		{
-			delta = (Y%*%rhoLambda[,,r] - (X[, col.sel]%*%phiLambda[col.sel,,r]))
+		  if (length(col.sel)==1){
+		    delta = (Y%*%rhoLambda[,,r] - (X[, col.sel]%*%t(phiLambda[col.sel,,r])))
+		  } else delta = (Y%*%rhoLambda[,,r] - (X[, col.sel]%*%phiLambda[col.sel,,r]))
 			densite = densite + piLambda[r] *
 				det(rhoLambda[,,r])/(sqrt(2*base::pi))^m * exp(-diag(tcrossprod(delta))/2.0)
 		}