Cuts in Bayesian graphical models

被引：55
|
作者：
Plummer, Martyn [1 ]
机构：
[1] Int Agcy Res Canc, F-69372 Lyon, France
来源：
STATISTICS AND COMPUTING | 2015年 / 25卷 / 01期
关键词：
Bayesian inference; Cutting feedback; Multiple imputation; VS; SEQUENTIAL-ANALYSIS; REGRESSION; DISTRIBUTIONS; RISK;
D O I：
10.1007/s11222-014-9503-z
中图分类号：
TP301 [理论、方法];
学科分类号：
081202 ;
摘要：
The cut function defined by the OpenBUGS software is described as a "valve" that prevents feedback in Bayesian graphical models. It is shown that the MCMC algorithm applied by OpenBUGS in the presence of a cut function does not converge to a well-defined limiting distribution. However, it may be improved by using tempered transitions. The cut algorithm is compared with multiple imputation as a gold standard in a simple example.
引用
收藏
页码：37 / 43
页数：7
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