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Explaining the Gibbs Sampler

 

作者: George Casella,   EdwardI. George,  

 

期刊: The American Statistician  （Taylor Available online 1992）
卷期: Volume 46, issue 3  

页码: 167-174

 

ISSN:0003-1305

 

年代: 1992

 

DOI:10.1080/00031305.1992.10475878

 

出版商: Taylor & Francis Group

 

关键词: Data augmentation;Markov chains;Monte Carlo methods;Resampling techniques

 

数据来源: Taylor

 

摘要:

Computer-intensive algorithms, such as the Gibbs sampler, have become increasingly popular statistical tools, both in applied and theoretical work. The properties of such algorithms, however, may sometimes not be obvious. Here we give a simple explanation of how and why the Gibbs sampler works. We analytically establish its properties in a simple case and provide insight for more complicated cases. There are also a number of examples.

 

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