Open Access
VOL. 3 | 2008 Objective Bayes testing of Poisson versus inflated Poisson models
M. J. Bayarri, James O. Berger, Gauri S. Datta

Editor(s) Bertrand Clarke, Subhashis Ghosal

Inst. Math. Stat. (IMS) Collect., 2008: 105-121 (2008) DOI: 10.1214/074921708000000093


The Poisson distribution is often used as a standard model for count data. Quite often, however, such data sets are not well fit by a Poisson model because they have more zeros than are compatible with this model. For these situations, a zero-inflated Poisson (ZIP) distribution is often proposed. This article addresses testing a Poisson versus a ZIP model, using Bayesian methodology based on suitable objective priors. Specific choices of objective priors are justified and their properties investigated. The methodology is extended to include covariates in regression models. Several applications are given.


Published: 1 January 2008
First available in Project Euclid: 28 April 2008

MathSciNet: MR2459220

Digital Object Identifier: 10.1214/074921708000000093

Primary: 62F03 , 62F15

Keywords: Bayes factor , Jeffreys prior , Model selection

Rights: Copyright © 2008, Institute of Mathematical Statistics

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