Markov Chain Monte Carlo

Markov Chain Monte Carlo (MCMC) is a method for sampling from complex probability distributions when direct sampling is difficult. It builds a Markov chain whose long-run behavior matches the target distribution. By running the chain long enough, the collected samples approximate the true distribution, allowing estimation of expectations or probabilities.