MCMC Markov chain Monte Carlo?

Markov chain Monte Carlo strategies involve a class of algorithms for examining from a probability distribution. By building a Markov chain that has the ideal dispersion as its equilibrium appropriation, one can acquire a sample of the desired distribution by recording states from the chain. Markov chain Monte Carlo (MCMC) is a simulation technique that can be utilized to track down the posterior distribution and to sample from it. Hence, it is utilized to fit a model and to draw tests from the joint back appropriation of the model boundaries.