Markov chain Monte Carlo

A family of algorithms that draw samples from high-dimensional probability distributions by constructing a Markov chain whose stationary distribution is the target distribution. The Metropolis-Hastings algorithm and Gibbs sampler are principal examples; MCMC is the dominant computational tool in Bayesian posterior inference.