Bayesian inference for irreducible diffusion processes using the pseudo-marginal approach

Osnat Stramer; Matthew Bognar

doi:10.1214/11-BA608

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Bayesian inference for irreducible diffusion processes using the pseudo-marginal approach

Journal article

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Peer reviewed

Bayesian inference for irreducible diffusion processes using the pseudo-marginal approach

Osnat Stramer and Matthew Bognar

Bayesian analysis, Vol.6(2), pp.231-258

2011

DOI: 10.1214/11-BA608

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Abstract

In this article we examine two relatively new MCMC methods which allow for Bayesian inference in diffusion models. First, the Monte Carlo within Metropolis (MCWM) algorithm (O'neil, et al. 2000) uses an importance sampling approximation for the likelihood and yields a Markov chain. Our simulation study shows that there exists a limiting stationary distribution that can be made arbitrarily ``close'' to the posterior distribution (MCWM is

Details

Title: Subtitle: Bayesian inference for irreducible diffusion processes using the pseudo-marginal approach
Creators: Osnat Stramer
Matthew Bognar
Resource Type: Journal article
Publication Details: Bayesian analysis, Vol.6(2), pp.231-258
DOI: 10.1214/11-BA608
ISSN: 1931-6690
eISSN: 1931-6690
Language: English
Date published: 2011
Academic Unit: Statistics and Actuarial Science
Record Identifier: 9983986099202771

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