#' Among a collection of models, this function constructs a subcollection of models with
-#' models having strictly different dimensions, keeping the model which minimizes
+#' models having strictly different dimensions, keeping the model which minimizes
#' 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.
#'
-#' @return a list with indices, a vector of indices selected models,
+#' @return a list with indices, a vector of indices selected models,
#' and D1, a vector of corresponding dimensions
#' @export
#'
}
b = max(a)
#indices[i] : first indices of the binary vector where u_i ==1
- indices[i] = which.max(vec_bin(LLF,b)[[1]])
+ indices[i] = which.max(LLF == b)
}
}
return (list(indices=indices,D1=D1))
}
+
+#TODO:
+## Programme qui sélectionne un modèle
+## proposer à l'utilisation différents critères (BIC, AIC, slope heuristic)