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

被引：1

作者：

Link, William A. ^{[1
]}

Barker, Richard J. ^{[2
]}

机构：

[1] USGS Patuxent Wildlife Res Ctr, Laurel, MD 20708 USA

[2] Univ Otago, Dept Math & Stat, Dunedin, New Zealand

来源：

ENVIRONMENTAL AND ECOLOGICAL STATISTICS | 2008年 / 15卷 / 01期

关键词：

Cormack-Jolly-Seber model; Mark-recapture analysis; Markov chain Monte Carlo; Metropolis-Hastings algorithm;

D O I：

10.1007/s10651-007-0037-9

中图分类号：

X [环境科学、安全科学];

学科分类号：

08 ; 0830 ;

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.

引用

页码：79 / 87

页数：9

共 6 条

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