期刊
JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION
卷 100, 期 471, 页码 1077-1089出版社
AMER STATISTICAL ASSOC
DOI: 10.1198/016214505000000664
关键词
automatic sampling; convergence assessment; efficient chains; reference priors; reversible jump; software
The last 10 years have witnessed the development of sampling frameworks that permit the construction of Markov chains that simultaneously traverse both parameter and model space. Substantial methodological progress has been made during this period. In this article we present a survey of the current state of the art and evaluate some of the most recent advances in this field. We also discuss future research perspectives in the context of the drive to develop sampling mechanisms with high degrees of both efficiency and automation.
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