Introduction to Monte Carlo methods

David J C MacKay

This chapter describes a sequence of Monte Carlo methods: importance sampling, rejection sampling, the Metropolis method, and Gibbs sampling. For each method, we discuss whether the method is expected to be useful for high--dimensional problems such as arise in inference with graphical models. After the methods have been described, the terminology of Markov chain Monte Carlo methods is presented. The chapter concludes with a discussion of advanced methods, including methods for reducing random walk behaviour.

erice.ps.gz. | <- UK | Canada -> | erice.ps.gz.

@Incollection{MacKay97:erice,
  author = 	 "D. J. C.  MacKay",
  title = 	 "Introduction to {M}onte {C}arlo Methods",
  publisher = "Kluwer Academic Press",
booktitle={Learning in Graphical Models},
  year = 	 "1998",
  editor = 	 "M. I. Jordan",
  pages = 	 "175-204",
series={NATO Science Series}
}