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[valse.git] / R / modelSelection.R

diff --git a/R/modelSelection.R b/R/modelSelection.R
index 5a79bb6..bc7eeae 100644 (file)
--- a/R/modelSelection.R
+++ b/R/modelSelection.R
@@ -3,34 +3,34 @@
 #' the likelihood if there were several with the same dimension
 #'
 #' @param LLF a matrix, the first column corresponds to likelihoods for several models
-#'        the second column corresponds to the dimensions of the corresponding models.
+#'                             the second column corresponds to the dimensions of the corresponding models.
 #'
 #' @return a list with indices, a vector of indices selected models, 
-#'         and D1, a vector of corresponding dimensions
+#'                              and D1, a vector of corresponding dimensions
 #' @export
 #'
 modelSelection = function(LLF)
 {
-  D = LLF[,2]
-  D1 = unique(D)
-  
-  indices = rep(1, length(D1))
-  #select argmax MLE
-  if (length(D1)>2)
-  {
-    for (i in 1:length(D1))
-    {
-      A = c()
-      for (j in 1:length(D))
-      {
-        if(D[[j]]==D1[[i]])
-          a = c(a, LLF[j,1])
-      }
-      b = max(a)
-      #indices[i] : first indices of the binary vector where u_i ==1
-      indices[i] = which.max(vec_bin(LLF,b)[[1]])
-    }
-  }
-  
-  return (list(indices=indices,D1=D1))
+       D = LLF[,2]
+       D1 = unique(D)
+
+       indices = rep(1, length(D1))
+       #select argmax MLE
+       if (length(D1)>2)
+       {
+               for (i in 1:length(D1))
+               {
+                       A = c()
+                       for (j in 1:length(D))
+                       {
+                               if(D[[j]]==D1[[i]])
+                                       a = c(a, LLF[j,1])
+                       }
+                       b = max(a)
+                       #indices[i] : first indices of the binary vector where u_i ==1
+                       indices[i] = which.max(vec_bin(LLF,b)[[1]])
+               }
+       }
+
+       return (list(indices=indices,D1=D1))
 }