R/modelSelection.R

   1 #' Among a collection of models, this function constructs a subcollection of models with
   2 #' models having strictly different dimensions, keeping the model which minimizes
   3 #' the likelihood if there were several with the same dimension
   4 #'
   5 #' @param LLF a matrix, the first column corresponds to likelihoods for several models
   6 #'        the second column corresponds to the dimensions of the corresponding models.
   7 #'
   8 #' @return a list with indices, a vector of indices selected models,
   9 #'         and D1, a vector of corresponding dimensions
  10 #' @export
  11 #'
  12 #' @examples
  13 modelSelection = function(LLF)
  14 {
  15   D = LLF[,2]
  16   D1 = unique(D)
  17
  18   indices = rep(1, length(D1))
  19   #select argmax MLE
  20   if (length(D1)>2)
  21   {
  22     for (i in 1:length(D1))
  23     {
  24       A = c()
  25       for (j in 1:length(D))
  26       {
  27         if(D[[j]]==D1[[i]])
  28           a = c(a, LLF[j,1])
  29       }
  30       b = max(a)
  31       #indices[i] : first indices of the binary vector where u_i ==1
  32       indices[i] = which.max(vec_bin(LLF,b)[[1]])
  33     }
  34   }
  35
  36   return (list(indices=indices,D1=D1))
  37 }