The Markov Chain Monte Carlo (MCMC) is a type of algorithmic sampling from a probability distribution. This method creates samples from multi-dimensional variables which are then used to evaluate its expected value.
Examples of MCMC methods include:
- Metropolis-Hastings algorithm
- Gibbs sampling
- Metropolis-adjusted Langevin algorithm
- Slice sampling
- Multiple-try metropolis
- Reversible jump