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Markov chain Monte Carlo

Known as: Monte Carlo markov chain, Markov Chain Monte Carlo Simulations, Markov clustering 
In statistics, Markov chain Monte Carlo (MCMC) methods are a class of algorithms for sampling from a probability distribution based on constructing a… Expand
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Papers overview

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Review
2011
Review
2011
Probabilistic inference is an attractive approach to uncertain reasoning and empirical learning in artificial intelligence… Expand
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Highly Cited
2008
Highly Cited
2008
Low-rank matrix approximation methods provide one of the simplest and most effective approaches to collaborative filtering. Such… Expand
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Review
2008
Review
2008
the current edition is intended to provide practitioners with a comprehensive resource for the use of software package Stata… Expand
Review
1998
Review
1998
The Markov chain Monte Carlo (MCMC) method, as a computer-intensive statistical tool, has enjoyed an enormous upsurge in interest… Expand
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Highly Cited
1997
Highly Cited
1997
INTRODUCING MARKOV CHAIN MONTE CARLO Introduction The Problem Markov Chain Monte Carlo Implementation Discussion HEPATITIS B: A… Expand
Highly Cited
1997
Highly Cited
1997
Introduction Stochastic simulation Introduction Generation of Discrete Random Quantities Generation of Continuous Random… Expand
Highly Cited
1996
Highly Cited
1996
Highly Cited
1995
Review
1994
Review
1994
Abstract A critical issue for users of Markov chain Monte Carlo (MCMC) methods in applications is how to determine when it is… Expand
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Review
1991
Review
1991
Markov chain Monte Carlo (e. g., the Metropolis algorithm and Gibbs sampler) is a general tool for simulation of complex… Expand