Model choice using reversible jump Markov chain Monte Carlo

David I Hastie; Peter J Green

Model choice using reversible jump Markov chain Monte Carlo

David I Hastie
, Peter J Green

Research output: Contribution to journal › Article (Academic Journal) › peer-review

92 Citations (Scopus)

Abstract

We review the across-model simulation approach to computation for Bayesian model de-termination, based on the reversible jump Markov chain Monte Carlo method. Advantages, diculties and variations of the methods are discussed. We also discuss some limitations of the ideal Bayesian view of the model determination problem, for which no computational methods can provide a cure.

Original language	English
Pages (from-to)	309-338
Number of pages	30
Journal	Statistica Neerlandica
Volume	66
Issue number	3
Publication status	Published - Aug 2012

Keywords

across-model sampling;

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title = "Model choice using reversible jump Markov chain Monte Carlo",

abstract = "We review the across-model simulation approach to computation for Bayesian model de-termination, based on the reversible jump Markov chain Monte Carlo method. Advantages, diculties and variations of the methods are discussed. We also discuss some limitations of the ideal Bayesian view of the model determination problem, for which no computational methods can provide a cure.",

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AU - Hastie, David I

AU - Green, Peter J

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AB - We review the across-model simulation approach to computation for Bayesian model de-termination, based on the reversible jump Markov chain Monte Carlo method. Advantages, diculties and variations of the methods are discussed. We also discuss some limitations of the ideal Bayesian view of the model determination problem, for which no computational methods can provide a cure.

KW - across-model sampling;

M3 - Article (Academic Journal)

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SP - 309

EP - 338

JO - Statistica Neerlandica

JF - Statistica Neerlandica

IS - 3

ER -

Model choice using reversible jump Markov chain Monte Carlo

Abstract

Keywords

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