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The random walk Metropolis : linking theory and practice through a case study.

Sherlock, Chris and Fearnhead, Paul and Roberts, Gareth (2010) The random walk Metropolis : linking theory and practice through a case study. Statistical Science, 25 (2). pp. 172-190. ISSN 0883-4237

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    Abstract

    The random walk Metropolis (RWM) is one of the most common Markov Chain Monte Carlo algorithms in practical use today. Its theoretical properties have been extensively explored for certain classes of target, and a number of results with important practical implications have been derived. This article draws together a selection of new and existing key results and concepts and describes their implications. The impact of each new idea on algorithm efficiency is demonstrated for the practical example of the Markov modulated Poisson process (MMPP). A reparameterisation of the MMPP which leads to a highly efficient RWM within Gibbs algorithm in certain circumstances is also developed.

    Item Type: Article
    Journal or Publication Title: Statistical Science
    Uncontrolled Keywords: Random walk Metropolis ; Metropolis-Hastings ; MCMC ; adaptive MCMC ; MMPP
    Subjects: Q Science > QA Mathematics
    Departments: Faculty of Science and Technology > Mathematics and Statistics
    ID Code: 26838
    Deposited By: Prof Paul Fearnhead
    Deposited On: 27 Jul 2009 16:44
    Refereed?: No
    Published?: Published
    Last Modified: 09 Oct 2013 15:41
    Identification Number:
    URI: http://eprints.lancs.ac.uk/id/eprint/26838

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