X-Git-Url: https://git.auder.net/?p=valse.git;a=blobdiff_plain;f=pkg%2FR%2Fmain.R;h=d29fe699a3b3a58430adce7d35cba545ad99dd1d;hp=0a3487b0cb430097425ddeb9f563df8dfc9febd0;hb=82718d11dc4451896afa25328970ca2029925ae1;hpb=c3bf2821bce67c75504e303fae23dd41c00f06c8

diff --git a/pkg/R/main.R b/pkg/R/main.R
index 0a3487b..d29fe69 100644
--- a/pkg/R/main.R
+++ b/pkg/R/main.R
@@ -51,7 +51,7 @@ valse <- function(X, Y, procedure = "LassoMLE", selecMod = "DDSE", gamma = 1, mi
   computeModels <- function(k)
   {
     if (ncores_outer > 1) 
-      require("valse")  #nodes start with an empty environment
+      require("valse") #nodes start with an empty environment
 
     if (verbose) 
       print(paste("Parameters initialization for k =", k))
@@ -123,34 +123,29 @@ valse <- function(X, Y, procedure = "LassoMLE", selecMod = "DDSE", gamma = 1, mi
       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])
-    }
+    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
   }
-  Gam <- Gam/rowSums(Gam)
-  modelSel$affec <- apply(Gam, 1, which.max)
-  modelSel$proba <- Gam
+    
+  listMod <- as.integer(unlist(strsplit(as.character(indModSel), "[.]")))
+  modelSel <- models_list[[listMod[1]]][[listMod[2]]]
   modelSel$tableau <- tableauRecap
-
+  
   if (plot)
     print(plot_valse(X, Y, modelSel, n))