MEASURING THE EFFECT OF OBSERVATIONS ON BAYES FACTORS
成果类型：
Article
署名作者：
PETTIT, LI; YOUNG, KDS
署名单位：
University of Surrey
刊物名称：
BIOMETRIKA
ISSN/ISSBN：
0006-3444
DOI：
10.1093/biomet/77.3.455
发表日期：
1990
页码：
455466
关键词：
摘要：
In this paper we consider a measure of the effect of single observations on a logarithmic Bayes factor defined via the difference in the logarithms of the Bayes factors conditional first on all the data and then omitting an observation. The measure is related to the conditional predictive ordinate. The form of the measure and examples of its use are presented for a variety of situations, normal samples, linear linear models, log linear models and the checking of distributional assumptions.
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