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

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Sherlock, Chris, Fearnhead, Paul and Roberts, Gareth O. (2009) The random walk Metropolis : linking theory and practice through a case study. Working Paper. Coventry: University of Warwick. Centre for Research in Statistical Methodology. Working papers, Vol.2009 (No.16).

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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:

Working or Discussion Paper (Working Paper)

Subjects:

Q Science > QA Mathematics

Divisions:

Faculty of Science > Statistics

Library of Congress Subject Headings (LCSH):

Monte Carlo method, Markov processes, Random walks (Mathematics)

Series Name:

Working papers

Publisher:

University of Warwick. Centre for Research in Statistical Methodology

Place of Publication:

Coventry

Official Date:

2009

Dates:

Date	Event
2009	Published

Volume:

Vol.2009

Number:

No.16

Number of Pages:

Status:

Not Peer Reviewed

Access rights to Published version:

Open Access

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