What is Gibbs?

Gibbs sampling is a Markov Chain Monte Carlo (MCMC) algorithm used for approximating the joint probability distribution of multiple random variables when direct sampling is difficult. It iteratively samples each variable conditional on the current values of the other variables, eventually converging to the target distribution. It is commonly used in Bayesian statistics, image processing, and other fields where high-dimensional probability distributions need to be explored.