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Markov chain Monte Carlo in practice / edited by W.R. Gilks, S. Richardson, and D.J. Spiegelhalter.

Contributor(s): Material type: TextTextPublisher: Boca Raton, Fla. : Chapman & Hall, 1998Description: xvii, 486 pages : illustrations ; 25 cmContent type:
  • text
Media type:
  • unmediated
Carrier type:
  • volume
ISBN:
  • 0412055511
  • 9780412055515
Subject(s): DDC classification:
  • 519.233 21
LOC classification:
  • QA274.7 .M355 1998
Contents:
Introducing Markov chain Monte Carlo / W.R. Gilks, S. Richardson and D.J. Spiegelhalter -- Hepatitis B : a case study in MCMC methods / D.J. Spiegelhalter ... [et al.] -- Markov chain concepts related to sampling algorithms / G.O. Roberts -- Introduction to general state-space Markov chain theory / L. Tierney -- Full conditional distributions / W.R. Gilks -- Strategies for improving MCMC / W.R. Gilks and G.O. Roberts -- Implementing MCMC / A.E. Raftery and S.M. Lewis -- Inference and monitoring convergence / A. Gelman -- Model determination using sampling-based methods / A.E. Gelfand -- Hypothesis testing and model selection / A.E. Raftery -- Model checking and model improvement / A. Gelman and X.-L. Meng -- Stochastic search variable selection / E.I. George and R.E. McCulloch -- Bayesian model comparison via jump diffusions / D.B. Phillips and A.F.M. Smith -- Estimation and optimization of functions / C.J. Geyer -- Stochastic EM : method and application / J. Diebolt and E.H.S. Ip -- Generalized linear mixed models / D.G. Clayton -- Hierarchical longitudinal modeling / B.P. Carlin -- Medical monitoring / C. Berzuini -- MCMC for nonlinear hierarchical models / J.E. Bennett, A. Racine-Poon and J.C. Wakefield -- Bayesian mapping of disease / A. Mollié -- MCMC in image analysis / P.J. Green -- Measurement error / S. Richardson -- Gibbs sampling methods in genetics / D.C. Thomas and W.J. Gauderman -- Mixtures of distributions : inference and estimation / C.P. Robert -- An archaeological example : radiocarbon dating / C. Litton and C. Buck.
Summary: "General state-space Markov chain theory has evolved to make it both more accessible and more powerful. Markov Chain Monte Carlo in Practice introduces MCMC methods and their applications while also providing some theoretical background. Considering the broad audience, the editors emphasize practice rather than theory and keep the technical content to a minimum. They offer step-by-step instructions for using the methods presented and show the importance of MCMC in real applications with examples ranging from the simple to the more complex in fields such as archaeology, astronomy, biostatistics, genetics, epidemiology, and image analysis."--Publisher description.
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Holdings
Item type Current library Call number Copy number Status Date due Barcode
Book City Campus City Campus Main Collection 519.233 MAR (Browse shelf(Opens below)) 1 Available A412138B

Previously published: London : Chapman & Hall, 1996.

Includes bibliographical references and index.

Introducing Markov chain Monte Carlo / W.R. Gilks, S. Richardson and D.J. Spiegelhalter -- Hepatitis B : a case study in MCMC methods / D.J. Spiegelhalter ... [et al.] -- Markov chain concepts related to sampling algorithms / G.O. Roberts -- Introduction to general state-space Markov chain theory / L. Tierney -- Full conditional distributions / W.R. Gilks -- Strategies for improving MCMC / W.R. Gilks and G.O. Roberts -- Implementing MCMC / A.E. Raftery and S.M. Lewis -- Inference and monitoring convergence / A. Gelman -- Model determination using sampling-based methods / A.E. Gelfand -- Hypothesis testing and model selection / A.E. Raftery -- Model checking and model improvement / A. Gelman and X.-L. Meng -- Stochastic search variable selection / E.I. George and R.E. McCulloch -- Bayesian model comparison via jump diffusions / D.B. Phillips and A.F.M. Smith -- Estimation and optimization of functions / C.J. Geyer -- Stochastic EM : method and application / J. Diebolt and E.H.S. Ip -- Generalized linear mixed models / D.G. Clayton -- Hierarchical longitudinal modeling / B.P. Carlin -- Medical monitoring / C. Berzuini -- MCMC for nonlinear hierarchical models / J.E. Bennett, A. Racine-Poon and J.C. Wakefield -- Bayesian mapping of disease / A. Mollié -- MCMC in image analysis / P.J. Green -- Measurement error / S. Richardson -- Gibbs sampling methods in genetics / D.C. Thomas and W.J. Gauderman -- Mixtures of distributions : inference and estimation / C.P. Robert -- An archaeological example : radiocarbon dating / C. Litton and C. Buck.

"General state-space Markov chain theory has evolved to make it both more accessible and more powerful. Markov Chain Monte Carlo in Practice introduces MCMC methods and their applications while also providing some theoretical background. Considering the broad audience, the editors emphasize practice rather than theory and keep the technical content to a minimum. They offer step-by-step instructions for using the methods presented and show the importance of MCMC in real applications with examples ranging from the simple to the more complex in fields such as archaeology, astronomy, biostatistics, genetics, epidemiology, and image analysis."--Publisher description.

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