[KSCI] Korea Science Citation Index Service

Bayesian Parameter :Estimation and Variable Selection in Random Effects Generalised Linear Models for Count Data

Oh, Man-Suk (Department of Statistics, Ewha Womans University)
Park, Tae-Sung (Department of Statistics, Seoul National University)

Publication Information

Journal of the Korean Statistical Society / v.31, no.1, 2002 , pp. 93-107 More about this Journal

Abstract

Random effects generalised linear models are useful for analysing clustered count data in which responses are usually correlated. We propose a Bayesian approach to parameter estimation and variable selection in random effects generalised linear models for count data. A simple Gibbs sampling algorithm for parameter estimation is presented and a simple and efficient variable selection is done by using the Gibbs outputs. An illustrative example is provided.

Keywords

Correlated data; Markov chain Monte Carlo; density estimation; Bayes factor; repeated measurements.;

Citations & Related Records

Reference

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