Markov Chain Monte Carlo in Practice

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W.R. Gilks (Institute of Public Health, Cambridge, UK) S. Richardson (Imperial College, London, UK)

Markov Chain Monte Carlo in Practice

W.R. Gilks (Institute of Public Health, Cambridge, UK), S. Richardson (Imperial College, London, UK), David Spiegelhalter (MRC Biostatistics Unit, Cambridge, UK) , Niels Keiding (University of Copenhagen, Denmark)

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English

Chapman & Hall/CRC
01 December 1995

Probability & statistics; Stochastics

Series: Chapman & Hall/CRC Interdisciplinary Statistics

In a family study of breast cancer, epidemiologists in Southern California increase the power for detecting

a gene-environment interaction. In Gambia, a study helps a vaccination program reduce the incidence of Hepatitis B carriage. Archaeologists in Austria place a Bronze Age site in its true temporal location on the calendar scale. And in France, researchers map a rare disease with relatively little variation.

Each of these studies applied Markov chain Monte Carlo methods to produce more accurate and inclusive results. General state-space Markov chain theory has seen several developments that have made it both more accessible and more powerful to the general statistician. Markov Chain Monte Carlo in Practice introduces MCMC methods and their applications, providing some theoretical background as well. The authors are researchers who have made key contributions in the recent

development of MCMC methodology and its application. Considering the broad audience, the editors emphasize practice rather than theory, keeping the technical content to a minimum. The examples range from the simplest application, Gibbs sampling, to more complex applications. The first chapter contains enough information to allow the reader to start applying MCMC in a basic way. The following chapters cover main issues, important concepts and results, techniques for implementing MCMC, improving its performance, assessing model adequacy, choosing between models, and applications and

their domains.

Markov Chain Monte Carlo in Practice is a thorough, clear introduction to the methodology and applications of this simple idea with enormous potential. It shows the importance of MCMC in real applications, such as archaeology, astronomy, biostatistics, genetics, epidemiology, and image analysis, and provides an excellent base for MCMC to be applied to other fields as well.

Edited by: W.R. Gilks (Institute of Public Health Cambridge UK), S. Richardson (Imperial College, London, UK), David Spiegelhalter (MRC Biostatistics Unit, Cambridge, UK), David Spiegelhalter (MRC Biostatistics Unit, Cambridge, UK)
Series edited by: Niels Keiding (University of Copenhagen Denmark)
Imprint: Chapman & Hall/CRC
Country of Publication: United Kingdom
Volume: 2
Dimensions: Height: 234mm, Width: 156mm, Spine: 31mm
Weight: 1.090kg
ISBN: 9780412055515
ISBN 10: 0412055511
Series: Chapman & Hall/CRC Interdisciplinary Statistics
Pages: 504
Publication Date: 01 December 1995
Audience: College/higher education , Professional and scholarly , Primary , Undergraduate
Format: Hardback
Publisher's Status: Active

W.R. Gilks Institute of Public Health, Cambridge, UK; S. Richardson Imperial College, London, UK; David Spiegelhalter MRC Biostatistics Unit, Cambridge, UK.

OUR STORE IS CLOSED ON ANZAC DAY: THURSDAY 25 APRIL

Markov Chain Monte Carlo in Practice

W.R. Gilks (Institute of Public Health, Cambridge, UK), S. Richardson (Imperial College, London, UK), David Spiegelhalter (MRC Biostatistics Unit, Cambridge, UK) , Niels Keiding (University of Copenhagen, Denmark)

$305

Hardback

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