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.

引用

页码：79 / 87

页数：8

共 8 条

[1]

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[2]

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[3]

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[4]

Cormack RM(1965)Explicit estimates from capture–recapture data with both death and immigration–stochastic model Biometrika 52 225-247

[5]

Link WA(1965)A note on the multiple–recapture census Biometrika 52 249-259

[6]

Barker RJ(undefined)undefined undefined undefined undefined-undefined

[7]

Jolly GM(undefined)undefined undefined undefined undefined-undefined

[8]

Seber GAF(undefined)undefined undefined undefined undefined-undefined

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