EL USO DE RECOCIDO SIMULADO PARA LA SELECCION DEL MEJOR MODELO DE REGRESION: EL CASO L2

Abstract

In many problems is needed to fit a regression model. For using effectively different adjustment criteria one of the problems to be solved is how to select the best regression model. Commonly when the method of the Least Squares is used assuming the normallity of the errors. In this paper we suggest to solve this problem by using a Simulated Annealling based heuristics. The method look for the disminution of the residual sum of squares using it as objective function. Algorithms are developed and
an evaluation of the proposals is made by analyzing classic examples from text books. The behavior of them seems to be adequate because they identify the best fitted models.