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Perfect posterior simulation for mixture and hidden Markov models
Published online by Cambridge University Press: 01 August 2010
Abstract
In this paper we present an application of the read-once coupling from the past algorithm to problems in Bayesian inference for latent statistical models. We describe a method for perfect simulation from the posterior distribution of the unknown mixture weights in a mixture model. Our method is extended to a more general mixture problem, where unknown parameters exist for the mixture components, and to a hidden Markov model.
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- Research Article
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- Copyright © London Mathematical Society 2010
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