Efficient implementation of the Metropolis-Hastings algorithm, with application to the Cormack–Jolly–Seber model

被引：0
|
作者：
William A. Link
Richard J. Barker
机构：
[1] USGS Patuxent Wildlife Research Center,Department of Mathematics and Statistics
[2] University of Otago,undefined
来源：
Environmental and Ecological Statistics | 2008年 / 15卷
关键词：
Cormack–Jolly–Seber model; Mark-recapture analysis; Markov chain Monte Carlo; Metropolis-Hastings algorithm;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
Judicious choice of candidate generating distributions improves efficiency of the Metropolis-Hastings algorithm. In Bayesian applications, it is sometimes possible to identify an approximation to the target posterior distribution; this approximate posterior distribution is a good choice for candidate generation. These observations are applied to analysis of the Cormack–Jolly–Seber model and its extensions.
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页码：79 / 87
页数：8
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