Presents illustrative applications in several areas, including biostatistics.
Introducing Markov Chain Monte Carlo W.R. Gilks, S. Richardson, and D.J. Spielgelhalter Hepatitis B: A Case Study in MCMC Methods D.J. Spielgelhalter, N.G. Best, W.R. Gilks, and H. Inskip 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. McColluch 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 Modelling B.P. Carlin Medical Monitoring C. Berzuini MCMC for Nonlinear Hierarchical Models J.E. Bennet, A. Racine-Poon, and J.C. Wakefield Bayesian Mapping of Disease A. MolliT 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 Index
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