Estimación bayesiana en la familia Pareto generalizada

The generalized Pareto family of distributions with scale parameter > 0 andk form, has been used for modeling surplus over a given threshold, even though theparametric estimation in this family has some problems. In this work we study theBayesian approach for estimating parameters and k when no...

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Main Author: Sánchez Gómez, Rubén
Format: Artículo
Language: Español
Published: 2015
Online Access: http://revistas.ucr.ac.cr/index.php/matematica/article/view/289
http://hdl.handle.net/10669/12939
Summary: The generalized Pareto family of distributions with scale parameter > 0 andk form, has been used for modeling surplus over a given threshold, even though theparametric estimation in this family has some problems. In this work we study theBayesian approach for estimating parameters and k when no a priori informationis available and we discuss the case when there is previous information. We presenta simulation study in order to analyze the performance of the Bayesian methodology,employing non informative a priori distributions and the methods available in theliterature. This study shows that the Bayesian estimation performs better than otherproposed methods, in terms of bias and aquare root of the mean quadratic error. Theestimation methodologies analized are applied to real data sets.Keywords: Generalized Pareto family, estimation methods, Monte Carlo study.