Please use this identifier to cite or link to this item: http://hdl.handle.net/10553/42954
Title: Applying a bayesian hierarchical model in actuarial science: inference and ratemaking
Authors: Pérez-Sánchez, J. M. 
Sarabia Alegría, J. M.
Gómez Déniz, Emilio 
Vázquez Polo, Francisco José 
UNESCO Clasification: 1209 Estadística
Keywords: Métodos bayesianos
Issue Date: 2006
Publisher: World Scientific Publishing
Conference: 2005 5th Workshop of Spanish Scientific Association of Applied Economy on Distribution Models Theory 
Abstract: In a standard Bayesian model, a prior distribution is elicited for the structure parameter in order to obtain an estimate of this unknown parameter. The hierarchical model is a two way Bayesian one which incorporates a hyperprior distribution for some of the hyperparameters of the prior. In this way and under the Poisson-Gamma-Gamma model, a new distribution is obtained by computing the unconditional distribution of the random variable of interest. This distribution seems to provide a better fit to the data, given a policyholders' portfolio. Furthermore, Bayes premiums are thus obtained under a bonus-malus system and solve some of the problems of surcharges which appear in these systems when they are applied in a simple manner.
URI: http://hdl.handle.net/10553/42954
ISBN: 978-981-256-900-4
978-981-4477-40-6
9812569006
DOI: 10.1142/9789812772992_0013
Source: Distribution Models Theory / Edited By: Rafael Herrerías Pleguezuelo; José Callejón Céspedes and José Manuel Herrerías Velasco. ISBN 978-981-4477-40-6 (on-line), p. 233-241
Appears in Collections:Actas de congresos
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