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
Show full item record

Page view(s)

60
checked on Mar 16, 2024

Google ScholarTM

Check

Altmetric


Share



Export metadata



Items in accedaCRIS are protected by copyright, with all rights reserved, unless otherwise indicated.