+ 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]]]
+
+ ## Affectations
+ Gam <- matrix(0, ncol = length(modelSel$pi), nrow = n)
+ for (i in 1:n)
+ {
+ for (r in 1:length(modelSel$pi))
+ {
+ sqNorm2 <- sum((Y[i, ] %*% modelSel$rho[, , r] - X[i, ] %*% modelSel$phi[, , r])^2)
+ Gam[i, r] <- modelSel$pi[r] * exp(-0.5 * sqNorm2) * gdet(modelSel$rho[, , r])
+ }
+ }
+ Gam <- Gam/rowSums(Gam)
+ modelSel$affec <- apply(Gam, 1, which.max)
+ modelSel$proba <- Gam
+ modelSel$tableau <- tableauRecap