X-Git-Url: https://git.auder.net/?p=valse.git;a=blobdiff_plain;f=pkg%2FR%2FconstructionModelesLassoMLE.R;h=0584382fa4a602a2651d8022d1635bab6178ea7d;hp=d2a16bc0f40a3e7e9f679035fd3404e0912448d8;hb=fb3557f39487d9631ffde30f20b70938d2a6ab0c;hpb=923ed737d0fa335b858204b813c964432488abbe diff --git a/pkg/R/constructionModelesLassoMLE.R b/pkg/R/constructionModelesLassoMLE.R index d2a16bc..0584382 100644 --- a/pkg/R/constructionModelesLassoMLE.R +++ b/pkg/R/constructionModelesLassoMLE.R @@ -1,7 +1,7 @@ -#' constructionModelesLassoMLE +#' constructionModelesLassoMLE #' #' Construct a collection of models with the Lasso-MLE procedure. -#' +#' #' @param phiInit an initialization for phi, get by initSmallEM.R #' @param rhoInit an initialization for rho, get by initSmallEM.R #' @param piInit an initialization for pi, get by initSmallEM.R @@ -16,28 +16,28 @@ #' @param ncores Number of cores, by default = 3 #' @param fast TRUE to use compiled C code, FALSE for R code only #' @param verbose TRUE to show some execution traces -#' +#' #' @return a list with several models, defined by phi, rho, pi, llh #' #' @export -constructionModelesLassoMLE <- function(phiInit, rhoInit, piInit, gamInit, mini, - maxi, gamma, X, Y, eps, S, ncores = 3, fast, verbose) +constructionModelesLassoMLE <- function(phiInit, rhoInit, piInit, gamInit, mini, + maxi, gamma, X, Y, eps, S, ncores, fast, verbose) { if (ncores > 1) { cl <- parallel::makeCluster(ncores, outfile = "") - parallel::clusterExport(cl, envir = environment(), varlist = c("phiInit", - "rhoInit", "gamInit", "mini", "maxi", "gamma", "X", "Y", "eps", "S", + parallel::clusterExport(cl, envir = environment(), varlist = c("phiInit", + "rhoInit", "gamInit", "mini", "maxi", "gamma", "X", "Y", "eps", "S", "ncores", "fast", "verbose")) } # Individual model computation computeAtLambda <- function(lambda) { - if (ncores > 1) + if (ncores > 1) require("valse") #nodes start with an empty environment - if (verbose) + if (verbose) print(paste("Computations for lambda=", lambda)) n <- nrow(X) @@ -47,12 +47,13 @@ constructionModelesLassoMLE <- function(phiInit, rhoInit, piInit, gamInit, mini, sel.lambda <- S[[lambda]]$selected # col.sel = which(colSums(sel.lambda)!=0) #if boolean matrix col.sel <- which(sapply(sel.lambda, length) > 0) #if list of selected vars - if (length(col.sel) == 0) + if (length(col.sel) == 0) return(NULL) # lambda == 0 because we compute the EMV: no penalization here - res <- EMGLLF(array(phiInit,dim=c(p,m,k))[col.sel, , ], rhoInit, piInit, gamInit, - mini, maxi, gamma, 0, as.matrix(X[, col.sel]), Y, eps, fast) + res <- EMGLLF(array(phiInit[col.sel, , ], dim=c(length(col.sel),m,k)), + rhoInit, piInit, gamInit, mini, maxi, gamma, 0, + as.matrix(X[, col.sel]), Y, eps, fast) # Eval dimension from the result + selected phiLambda2 <- res$phi @@ -88,7 +89,7 @@ constructionModelesLassoMLE <- function(phiInit, rhoInit, piInit, gamInit, mini, # log(piLambda[r]) + log(detRho[r]) - 0.5 * # sum((Y[i, ] %*% rhoLambda[, , r] - X[i, ] %*% phiLambda[, , r])^2) # }) - # + # # #logGam <- logGam - max(logGam) #adjust without changing proportions -> change the LLH # gam <- exp(logGam) # norm_fact <- sum(gam) @@ -106,7 +107,7 @@ constructionModelesLassoMLE <- function(phiInit, rhoInit, piInit, gamInit, mini, lapply(1:length(S), computeAtLambda) } - if (ncores > 1) + if (ncores > 1) parallel::stopCluster(cl) out