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Gibbs sampling

In statistics, Gibbs sampling or a Gibbs sampler, also known in statistical mechanics as the heat bath algorithm, is a Markov chain Monte Carlo (MCMC) algorithm for sampling from a specified multivariateprobability distribution when direct sampling from the joint distribution is difficult, but sampling from the conditional distribution is more practical.

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