BAYESIAN-ANALYSIS OF 2 OVERDISPERSED POISSON REGRESSION-MODELS

被引：2

作者：

SCOLLNIK, DPM ^{[1
]}

机构：

[1] UNIV CALGARY,DEPT MATH & STAT,CALGARY,AB T2N 1N4,CANADA

来源：

COMMUNICATIONS IN STATISTICS-THEORY AND METHODS | 1995年 / 24卷 / 11期

基金：

英国医学研究理事会;

关键词：

ADAPTIVE REJECTION METROPOLIS SAMPLING; BAYESIAN INFERENCE; GIBBS SAMPLING; MARKOV CHAIN MONTE CARLO METHODS; OVERDISPERSION; POISSON MODELS; PREDICTION; REGRESSION;

D O I：

10.1080/03610929508831658

中图分类号：

O21 [概率论与数理统计]; C8 [统计学];

学科分类号：

020208 ; 070103 ; 0714 ;

摘要：

Shoukri and Consul (1989) and Scollnik (1995) have previously considered the Bayesian analysis of an overdispersed generalized Poisson model. Scollnik (1995) also considered the Bayesian analysis of an ordinary Poisson and overdispersed generalized Poisson mixture model. In this paper, we discuss the Bayesian analysis of these models when they are utilised in a regression context. Markov chain Monte Carlo methods are utilised, and an illustrative analysis is provided.

引用

页码：2901 / 2918

页数：18

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