Note on the Sampling Distribution for the Metropolis-Hastings Algorithm
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چکیده
منابع مشابه
Note on the Sampling Distribution for the Metropolis-Hastings Algorithm
The Metropolis-Hastings algorithm has been important in the recent development of Bayes methods. This algorithm generates random draws from a target distribution utilizing a sampling (or proposal) distribution. This article compares the properties of three sampling distributions—the independence chain, the random walk chain, and the Taylored chain suggested by Geweke and Tanizaki (Geweke, J., T...
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1.1 Dimension Changing The Metropolis-Hastings-Green algorithm (as opposed to just MetropolisHastings with no Green) is useful for simulating probability distributions that are a mixture of distributions having supports of different dimension. An early example (predating Green’s general formulation) was an MCMC algorithm for simulating spatial point processes (Geyer and Møller, 1994). More wide...
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ژورنال
عنوان ژورنال: Communications in Statistics - Theory and Methods
سال: 2003
ISSN: 0361-0926,1532-415X
DOI: 10.1081/sta-120018828