Metropolis-Hastings algorithm
2016-08-23
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http://en.wikipedia.org/wiki/Metropolis-Hastings_algorithm
Metropolis-Hastings algorithm is a Markov chain Monte Carlo method for obtaining a sequence of random samples from a probability distribution for which direct sampling is difficult. The sequence can be used to
approximate the distribution.
The following code is a simple implementation of Metropolis-Hastings algorithm, these code is compiled under linux operation system. and can also be used in Windows OS.
The metropolis_demo.cpp is a demo for sampling a gaussian distribution.
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Metropolis-Hastings algorithm is a Markov chain Monte Carlo method for obtaining a sequence of random samples from a probability distribution for which direct sampling is difficult. The sequence can be used to
approximate the distribution.
The following code is a simple implementation of Metropolis-Hastings algorithm, these code is compiled under linux operation system. and can also be used in Windows OS.
The metropolis_demo.cpp is a demo for sampling a gaussian distribution.
Run metropoli
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