Handbook of Markov Chain Monte Carlo

Edited by Steve Brooks, Andrew Gelman, Galin L. Jones and Xiao-Li Meng

Published by Chapman & Hall/CRC.

Table of Contents and Contributors

  1. Introduction to MCMC by Charles Geyer.

  2. A short history of Markov chain Monte Carlo: Subjective recollections from incomplete data by Christian Robert and George Casella

  3. Reversible jump Markov chain Monte Carlo by Yanan Fan and Scott A. Sisson

  4. Optimal proposal distributions and adaptive MCMC by Jeffrey S. Rosenthal

  5. MCMC Using Hamiltonian Dynamics by Radford Neal.

  6. Inference and Monitoring Convergence by Andrew Gelman and Kenneth Shirley

  7. Implementing MCMC: Estimating with confidence by James M. Flegal and Galin L. Jones

  8. Perfection within reach: Exact MCMC sampling by Radu V. Craiu and Xiao-Li Meng

  9. Spatial point processes by Mark Huber

  10. The data augmentation algorithm: Theory and methodology by James P. Hobert

  11. Importance sampling, simulated tempering and umbrella sampling by Charles Geyer.

  12. Likelihood-free Markov chain Monte Carlo Scott A. Sisson and Yanan Fan.

  13. MCMC in the analysis of genetic data on related individuals by Elizabeth Thompson.

  14. A Markov chain Monte Carlo based analysis of a multilevel model for functional MRI data by Brian Caffo, DuBois Bowman, Lynn Eberly and Susan Spear Bassett.

  15. Partially collapsed Gibbs sampling \& path-adaptive Metropolis-Hastings in high-energy astrophysics by David van Dyk and Taeyoung Park.

  16. Posterior exploration for computationally intensive forward models by Dave Higdon, C. Shane Reese, David Moulton, Jasper Vrugt and Colin Fox.

  17. Statistical ecology by Ruth King.

  18. Gaussian random field models for spatial data by Murali Haran.

  19. Modeling preference changes via a hidden Markov item response theory model by Jong Hee Park.

  20. Parallel Bayesian MCMC Imputation for Multiple Distributed Lag Models: A Case Study in Environmental Epidemiology by Brian Caffo, Roger Peng, Francesca Dominici, Thomas Louis and Scott Zeger.

  21. MCMC for state space models by Paul Fearnhead.

  22. MCMC in educational research by Roy Levy, Robert Mislevy and John T. Behrens

  23. Applications of MCMC in fisheries science by Russell B. Millar.

  24. Model comparison and simulation for hierarchical models: analyzing rural-urban migration in Thailand by Filiz Garip and Bruce Western.

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