X-Git-Url: https://git.auder.net/?p=valse.git;a=blobdiff_plain;f=pkg%2FR%2FfilterModels.R;fp=pkg%2FR%2FfilterModels.R;h=2659ed468a8450f5d84e8d75280148acdb5da29a;hp=0000000000000000000000000000000000000000;hb=0eb161e3f3d018bce7d98fc85622d14910f89d43;hpb=2279a641f2bee1db586e7ab1e13726d111d5daaf

diff --git a/pkg/R/filterModels.R b/pkg/R/filterModels.R
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+#' Among a collection of models, this function constructs a subcollection of models with
+#' 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,
+#'				 and D1, a vector of corresponding dimensions
+#'
+#' @export
+filterModels = 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(LLF == b)
+		}
+	}
+
+	return (list(indices=indices,D1=D1))
+}