X-Git-Url: https://git.auder.net/?p=valse.git;a=blobdiff_plain;f=pkg%2FR%2FconstructionModelesLassoMLE.R;h=1275ca3cc5d94c754ea3c741f605e78ac939e23a;hp=8f93fb8fbf406534cf2964200fc4342ccac59871;hb=ea5860f1b4fc91f06e371a0b26915198474a849d;hpb=96b591b7a76da9780e766ead693eb065281b6d62 diff --git a/pkg/R/constructionModelesLassoMLE.R b/pkg/R/constructionModelesLassoMLE.R index 8f93fb8..1275ca3 100644 --- a/pkg/R/constructionModelesLassoMLE.R +++ b/pkg/R/constructionModelesLassoMLE.R @@ -21,7 +21,7 @@ #' #' @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) { @@ -40,10 +40,10 @@ constructionModelesLassoMLE <- function(phiInit, rhoInit, piInit, gamInit, mini, 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]]$selected # col.sel = which(colSums(sel.lambda)!=0) #if boolean matrix col.sel <- which(sapply(sel.lambda, length) > 0) #if list of selected vars @@ -51,8 +51,8 @@ constructionModelesLassoMLE <- function(phiInit, rhoInit, piInit, gamInit, mini, return(NULL) # lambda == 0 because we compute the EMV: no penalization here - res <- EMGLLF(phiInit[col.sel, , ], rhoInit, piInit, gamInit, mini, maxi, - gamma, 0, X[, col.sel], Y, eps, fast) + res <- EMGLLF(array(phiInit,dim=c(p,m,k))[col.sel, , ], rhoInit, piInit, gamInit, + mini, maxi, gamma, 0, as.matrix(X[, col.sel]), Y, eps, fast) # Eval dimension from the result + selected phiLambda2 <- res$phi @@ -71,7 +71,7 @@ constructionModelesLassoMLE <- function(phiInit, rhoInit, piInit, gamInit, mini, { 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 * + densite <- densite + piLambda[r] * gdet(rhoLambda[, , r])/(sqrt(2 * base::pi))^m * exp(-diag(tcrossprod(delta))/2) } llhLambda <- c(sum(log(densite)), (dimension + m + 1) * k - 1)