Abstract
This chapter is the first of a series of two on simulation methods based on Markov chains. Although the Metropolis–Hastings algorithm can be seen as one of the most general Markov chain Monte (MCMC) algorithms, it is also one of the simplest both to understand and explain, making it an ideal algorithm to start with.
“How absurdly simple!”, I cried.
“Quite so!”, said he, a little nettled. “Every problem becomes very childish when once it is explained to you.”
Arthur Conan Doyle
The Adventure of the Dancing Men
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Robert, C.P., Casella, G. (2010). Metropolis–Hastings Algorithms. In: Introducing Monte Carlo Methods with R. Use R. Springer, New York, NY. https://doi.org/10.1007/978-1-4419-1576-4_6
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DOI: https://doi.org/10.1007/978-1-4419-1576-4_6
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Print ISBN: 978-1-4419-1575-7
Online ISBN: 978-1-4419-1576-4
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