MCMC, or Markov Chain Monte Carlo, is a class of algorithms used for sampling from probability distributions based on constructing a Markov chain. The significance of MCMC lies in its ability to draw samples from complex distributions that are difficult to analyze directly, making it an essential tool in Bayesian estimation and the computation of credible intervals.
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