Abstract
Markov Chain Monte Carlo (MCMC) is a computer-intensive statistical tool that has received considerable attention over the past few years. Using MCMC theory, it is often quite simple to write efficient algorithms for sampling from extremely complicated target distributions; thus, it is not difficult to understand why these techniques have found important applications in a vast number of different areas. Although the literature on MCMC methods is growing rapidly, the excellent book by Gilks, Richardson and Spiegelhalter (1996) provides a good starting point for the interested reader.
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© 2000 Springer Science+Business Media New York
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Andersson, H., Britton, T. (2000). Markov Chain Monte Carlo. In: Stochastic Epidemic Models and Their Statistical Analysis. Lecture Notes in Statistics, vol 151. Springer, New York, NY. https://doi.org/10.1007/978-1-4612-1158-7_11
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DOI: https://doi.org/10.1007/978-1-4612-1158-7_11
Publisher Name: Springer, New York, NY
Print ISBN: 978-0-387-95050-1
Online ISBN: 978-1-4612-1158-7
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