#'
#' @export
constructionModelesLassoMLE <- function(phiInit, rhoInit, piInit, gamInit, mini,
- maxi, gamma, X, Y, eps, S, ncores = 3, fast = TRUE, verbose = FALSE)
+ maxi, gamma, X, Y, eps, S, ncores = 3, fast, verbose)
{
if (ncores > 1)
{
return(NULL)
# lambda == 0 because we compute the EMV: no penalization here
- res <- EMGLLF(phiInit[col.sel, , ], rhoInit, piInit, gamInit, mini, maxi,
- gamma, 0, X[, col.sel], Y, eps, fast)
+ 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)
# Eval dimension from the result + selected
phiLambda2 <- res$phi
{
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)
+ densite <- densite + piLambda[r] * det(rhoLambda[, , r])/(sqrt(2 * base::pi))^m *
+ exp(-diag(tcrossprod(delta))/2)
}
llhLambda <- c(sum(log(densite)), (dimension + m + 1) * k - 1)
list(phi = phiLambda, rho = rhoLambda, pi = piLambda, llh = llhLambda)