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

By:
and
DOI: 10.1007/s10651-007-0037-9

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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. ?? Springer Science+Business Media, LLC 2007.

Additional Publication Details

Publication type:
Conference Paper
Publication Subtype:
Conference Paper
Title:
Efficient implementation of the Metropolis-Hastings algorithm, with application to the Cormack-Jolly-Seber model
DOI:
10.1007/s10651-007-0037-9
Volume
15
Issue:
1
Year Published:
2008
Language:
English
Larger Work Title:
Environmental and Ecological Statistics
First page:
79
Last page:
87
Number of Pages:
9