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Applying metropolis hastings in modeling languages

There are various ways to perform processing on posterior distribution in Markov Chain Monte Carlo (MCMC). One way is using the Metropolis-Hastings sampler. In order to implement the Metropolis-Hastings algorithm, we require standard uniform distribution, proposal distribution, and target distribution that is proportional to posterior probability. An example of Metropolis-Hastings is discussed in the following topic.

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