Metropolis–Hastings algorithm

Known as: Metropolis method, Metropolis sampling, Metropolis-Hastings algorithm 
In statistics and in statistical physics, the Metropolis–Hastings algorithm is a Markov chain Monte Carlo (MCMC) method for obtaining a sequence of… (More)
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2018
2018
The dimension and the complexity of inference problems have dramatically increased in statistical signal processing. It thus… (More)
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2015
2015
This article is a self-contained introduction to the MetropolisHastings algorithm, this ubiquitous tool for producing dependent… (More)
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2013
2013
Markov Chain Monte Carlo methods are widely used in signal processing and communications for statistical inference and stochastic… (More)
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2007
2007
Dynamic causal modelling (DCM) is a modelling framework used to describe causal interactions in dynamical systems. It was… (More)
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2004
2004
This paper proposes methods to improve Monte Carlo estimates when the Independent Metropolis-Hastings Algorithm (IMHA) is used… (More)
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2002
2002
The Metropolis-Hastings algorithm transforms a given stochastic matrix into a reversible stochastic matrix with a prescribed… (More)
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Highly Cited
2001
Highly Cited
2001
This article provides a framework for estimating the marginal likelihood for the purpose of Bayesian model comparisons . The… (More)
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1998
1998
This paper deals with the asymptotic properties of the Metropolis-Hastings algorithm, when the distribution of interest is… (More)
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Highly Cited
1998
Highly Cited
1998
A proper choice of a proposal distribution for Markov chain Monte Carlo methods, for example for the Metropolis±Hastings… (More)
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Highly Cited
1995
Highly Cited
1995
Your use of the JSTOR archive indicates your acceptance of JSTOR's Terms and Conditions of Use, available at http://www.jstor.org… (More)
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