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


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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.




Library of Congress subject headings for this publication:
Markov processes.
Monte Carlo method.