Bayesian Approaches to Zero Inflated Poisson Model

Title & Authors
Bayesian Approaches to Zero Inflated Poisson Model
Lee, Ji-Ho; Choi, Tae-Ryon; Wo, Yoon-Sung;

Abstract
In this paper, we consider Bayesian approaches to zero inflated Poisson model, one of the popular models to analyze zero inflated count data. To generate posterior samples, we deal with a Markov Chain Monte Carlo method using a Gibbs sampler and an exact sampling method using an Inverse Bayes Formula(IBF). Posterior sampling algorithms using two methods are compared, and a convergence checking for a Gibbs sampler is discussed, in particular using posterior samples from IBF sampling. Based on these sampling methods, a real data analysis is performed for Trajan data (Marin et al., 1993) and our results are compared with existing Trajan data analysis. We also discuss model selection issues for Trajan data between the Poisson model and zero inflated Poisson model using various criteria. In addition, we complement the previous work by Rodrigues (2003) via further data analysis using a hierarchical Bayesian model.
Keywords
Gibbs sampler;Inverse Bayes Formula;Bayesian $\small{X^2}$ goodness of fit;DIC;hierarchical Bayesia model;
Language
Korean
Cited by
1.
카드뮴 반응용량 곡선에서의 기준용량 평가를 위한 베이지안 분석연구,이민제;최태련;김정선;우해동;

응용통계연구, 2013. vol.26. 3, pp.453-470
1.
Bayesian Analysis of Dose-Effect Relationship of Cadmium for Benchmark Dose Evaluation, Korean Journal of Applied Statistics, 2013, 26, 3, 453
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