+ # List (index k) of lists (index lambda) of models
+ models_list <-
+ if (ncores_outer > 1) {
+ parLapply(cl, kmin:kmax, computeModels)
+ } else {
+ lapply(kmin:kmax, computeModels)
+ }
+ if (ncores_outer > 1)
+ parallel::stopCluster(cl)
+
+ if (!requireNamespace("capushe", quietly = TRUE))
+ {
+ warning("'capushe' not available: returning all models")
+ return(models_list)
+ }
+
+ # Get summary 'tableauRecap' from models
+ tableauRecap <- do.call(rbind, lapply(seq_along(models_list), function(i)
+ {
+ models <- models_list[[i]]
+ # For a collection of models (same k, several lambda):
+ LLH <- sapply(models, function(model) model$llh[1])
+ k <- length(models[[1]]$pi)
+ sumPen <- sapply(models, function(model) k * (dim(model$rho)[1] + sum(model$phi[,
+ , 1] != 0) + 1) - 1)
+ data.frame(model = paste(i, ".", seq_along(models), sep = ""), pen = sumPen/n,
+ complexity = sumPen, contrast = -LLH)
+ }))
+ tableauRecap <- tableauRecap[which(tableauRecap[, 4] != Inf), ]
+ if (verbose == TRUE)
+ print(tableauRecap)
+ modSel <- capushe::capushe(tableauRecap, n)
+ indModSel <- if (selecMod == "DDSE")
+ as.numeric(modSel@DDSE@model) else if (selecMod == "Djump")
+ as.numeric(modSel@Djump@model) else if (selecMod == "BIC")
+ modSel@BIC_capushe$model else if (selecMod == "AIC")
+ modSel@AIC_capushe$model
+
+ mod <- as.character(tableauRecap[indModSel, 1])
+ listMod <- as.integer(unlist(strsplit(mod, "[.]")))
+ modelSel <- models_list[[listMod[1]]][[listMod[2]]]