Reversible jump methods for generalised linear models and generalised linear mixed models

被引：10
|
作者：
Forster, Jonathan J. [2 ]
Gill, Roger C. [3 ]
Overstall, Antony M. [1 ]
机构：
[1] Univ Southampton, S3RI, Southampton, Hants, England
[2] Univ Southampton, Sch Math, Southampton, Hants, England
[3] Oxford Nanopore Technol Ltd, Oxford, England
来源：
STATISTICS AND COMPUTING | 2012年 / 22卷 / 01期
基金：
英国工程与自然科学研究理事会;
关键词：
Generalised linear models; Generalised linear mixed models; Bayesian model determination; Reversible jump; BAYESIAN VARIABLE SELECTION;
D O I：
10.1007/s11222-010-9210-3
中图分类号：
TP301 [理论、方法];
学科分类号：
081202 ;
摘要：
A reversible jump algorithm for Bayesian model determination among generalised linear models, under relatively diffuse prior distributions for the model parameters, is proposed. Orthogonal projections of the current linear predictor are used so that knowledge from the current model parameters is used to make effective proposals. This idea is generalised to moves of a reversible jump algorithm for model determination among generalised linear mixed models. Therefore, this algorithm exploits the full flexibility available in the reversible jump method. The algorithm is demonstrated via two examples and compared to existing methods.
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页码：107 / 120
页数：14
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