Metropolis-hastings Algorithm
The Metropolis-Hastings Algorithm is a Markov chain Monte Carlo method that generates samples from a probability distribution by constructing a Markov chain with a specified stationary distribution, using a proposal distribution and an acceptance criterion to ensure convergence to the target distribution.
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249
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Metropolis-hastingsMetropolis-hastings Method
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Monte Carlo sampling methods using Markov chains and their applications
W. Keith Hastings · Biometrika · 1970 · 15.2K citations
Markov Chains for Exploring Posterior Distributions
Luke Tierney · The Annals of Statistics · 1994 · 3.5K citations · Full text
An Adaptive Metropolis Algorithm
Heikki Haario, Eero Saksman, Johanna Tamminen · Bernoulli · 2001 · 2.7K citations
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University of Warwick
Coventry, United Kingdom
24 h-index
45 publications
3.2K citations
University of Cambridge
Cambridge, United Kingdom
24 h-index
56 publications
10.2K citations

University of Toronto
Toronto, Canada
22 h-index
38 publications
24.5K citations

Centre National de la Recherche Scientifique
Paris, France
21 h-index
56 publications
2.9K citations
Lancaster University
Lancaster, United Kingdom
19 h-index
32 publications
5K citations
University of Oxford
Oxford, United Kingdom
17 h-index
36 publications
3K citations
University of Washington
Seattle, United States
16 h-index
33 publications
9.7K citations
University College London
London, United Kingdom
16 h-index
34 publications
4.9K citations
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JCGS · 41 publications · 7.8K citations
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Repository · 50 publications · 2.4K citations
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