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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… 
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Papers overview

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Highly Cited
2010
Highly Cited
2010
ABSTRACT We present an adaptive method for the automatic scaling of random-walk Metropolis–Hastings algorithms, which quickly and… 
2009
2009
Casella and Robert (1996) presented a general Rao--Blackwellisation principle for accept-reject and Metropolis-Hastings schemes… 
Highly Cited
2008
Highly Cited
2008
Abstract The ability to infer parameters of gene regulatory networks is emerging as a key problem in systems biology. The… 
Highly Cited
2005
Highly Cited
2005
Summary.  The paper considers high dimensional Metropolis and Langevin algorithms in their initial transient phase. In… 
Highly Cited
2005
Highly Cited
2004
Highly Cited
2004
Contributors. Lindsay Bremner, Nsizwa Dlamini, Mark Gevisser, Grace Khunou, Frederic Le Marcis, John Matshikiza, Achille Mbembe… 
Highly Cited
2002
Highly Cited
2002
Text entry has been a bottleneck of nontraditional computing devices. One of the promising methods is the virtual keyboard for… 
Highly Cited
1998
Highly Cited
1998
Abstract We study Bayesian models and methods for analysing network traffic counts in problems of inference about the traffic… 
Highly Cited
1995
Highly Cited
1995
Vision-based algorithms for locating lane boundaries without a prior model of the road being viewed need to be able to operate… 
Highly Cited
1987
Highly Cited
1987
Simulated annealing is a computational heuristic for obtaining approximate solutions to combinatorial optimization problems. It…