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

Environmental and Ecological Statistics

DOI 10.1007/s10651-007-0037-9 6893_Link.pdf
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Abstract

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.

Additional Publication Details

Publication type:
Article
Publication Subtype:
Journal Article
Title:
Efficient implementation of the Metropolis-Hastings algorithm, with application to the Cormack?Jolly?Seber model
Series title:
Environmental and Ecological Statistics
Volume
15
Year Published:
2008
Language:
English
Contributing office(s):
Patuxent Wildlife Research Center
Description:
79-87
Larger Work Type:
Article
Larger Work Subtype:
Journal Article
Larger Work Title:
Environmental and Ecological Statistics
First page:
79
Last page:
87
Number of Pages:
9