Adaptive Metropolis Algorithms
Adaptive Metropolis Algorithms is a Markov chain Monte Carlo method that iteratively refines its proposal distribution during sampling by dynamically adjusting the covariance structure of the proposal based on accumulated posterior samples to improve convergence and mixing in Bayesian inference.
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16.2K
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338
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2017–2026
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Adaptive Metropolis Algorithm
139
An Adaptive Metropolis Algorithm
Heikki Haario, Eero Saksman, Johanna Tamminen · Bernoulli · 2001 · 2.7K citations
Heikki Haario, Marko Laine, Antonietta Mira et al. · Statistics and Computing · 2006 · 1.5K citations
Christophe Andrieu, Johannes Thoms · Statistics and Computing · 2008 · 959 citations · Full text
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Irvine University
Cerritos, United States
13 h-index
15 publications
2.1K citations
University of California, Irvine
Irvine, United States
13 h-index
15 publications
2.1K citations

University of Amsterdam
Amsterdam, The Netherlands
10 h-index
10 publications
2.1K citations
Los Alamos National Laboratory
Los Alamos, United States
7 h-index
13 publications
3.9K citations

Centre National de la Recherche Scientifique
Paris, France
7 h-index
11 publications
670 citations

UNSW Sydney
Sydney, Australia
7 h-index
15 publications
1.5K citations
Lancaster University
Lancaster, United Kingdom
5 h-index
7 publications
2.3K citations

University of Jyväskylä
Jyväskylä, Finland
5 h-index
6 publications
2K citations
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13 publications · 2.6K citations
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7 publications · 2.9K citations
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CSDA · 5 publications · 165 citations
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JCGS · 4 publications · 1.2K citations
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4 publications · 569 citations
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