complexity = sumPen, contrast = -LLH)
}))
tableauRecap <- tableauRecap[which(tableauRecap[, 4] != Inf), ]
+
+
if (verbose == TRUE)
print(tableauRecap)
modSel <- capushe::capushe(tableauRecap, n)
modSel@AIC_capushe$model
}
-
- mod <- as.character(tableauRecap[indModSel, 1])
- listMod <- as.integer(unlist(strsplit(mod, "[.]")))
+ listMod <- as.integer(unlist(strsplit(as.character(indModSel), "[.]")))
modelSel <- models_list[[listMod[1]]][[listMod[2]]]
-
- ## Affectations
- Gam <- matrix(0, ncol = length(modelSel$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
-
+
if (plot)
print(plot_valse(X, Y, modelSel, n))