...

diff --combined pkg/R/constructionModelesLassoMLE.R
index 0197e1a,78e11ad..16f58b6
--- 1/pkg/R/constructionModelesLassoMLE.R
--- 2/pkg/R/constructionModelesLassoMLE.R
+++ b/pkg/R/constructionModelesLassoMLE.R
@@@ -40,10 -40,10 +40,10 @@@ constructionModelesLassoMLE <- function
      if (verbose) 
        print(paste("Computations for lambda=", lambda))
  
-     n <- dim(X)[1]
-     p <- dim(phiInit)[1]
-     m <- dim(phiInit)[2]
-     k <- dim(phiInit)[3]
+     n <- nrow(X)
+     p <- ncol(X)
+     m <- ncol(Y)
+     k <- length(piInit)
      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
@@@ -51,8 -51,8 +51,8 @@@
        return(NULL)
  
      # lambda == 0 because we compute the EMV: no penalization here
-     res <- EMGLLF(array(phiInit[col.sel, , ],dim=c(length(col.sel),m,k)), rhoInit,
-       piInit, gamInit, mini, maxi, gamma, 0, as.matrix(X[, col.sel]), Y, eps, fast)
+     res <- EMGLLF(array(phiInit,dim=c(p,m,k))[col.sel, , ], rhoInit, piInit, gamInit,
+       mini, maxi, gamma, 0, as.matrix(X[, col.sel]), Y, eps, fast)
  
      # Eval dimension from the result + selected
      phiLambda2 <- res$phi
@@@ -65,7 -65,7 +65,7 @@@
  
      ## Computation of the loglikelihood
      # Precompute det(rhoLambda[,,r]) for r in 1...k
-     detRho <- sapply(1:k, function(r) det(rhoLambda[, , r]))
+     detRho <- sapply(1:k, function(r) gdet(rhoLambda[, , r]))
      sumLogLLH <- 0
      for (i in 1:n)
      {
@@@ -80,18 -80,7 +80,7 @@@
        norm_fact <- sum(gam)
        sumLogLLH <- sumLogLLH + log(norm_fact) - log((2 * base::pi)^(m/2))
      }
 -    llhLambda <- c(sumLogLLH/n, (dimension + m + 1) * k - 1)
 +    llhLambda <- c(-sumLogLLH/n, (dimension + m + 1) * k - 1)
-     # densite <- vector("double", n)
-     # for (r in 1:k)
-     # {
-     #   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(-rowSums(delta^2)/2)
-     # }
-     # llhLambda <- c(mean(log(densite)), (dimension + m + 1) * k - 1)
      list(phi = phiLambda, rho = rhoLambda, pi = piLambda, llh = llhLambda)
    }