Explaining the perfect sampler

algorithm for generating a sample from the exact stationary distribution of a Markov chain. In 1998, Fill proposed another so-called perfect sampling · algorithm. These algorithms have enormous potential in Markov Chain Monte Carlo (MCMC) problems because they eliminate the need to monitor convergence and mixing of the chain. This article provides a brief introduction to the algorithms, with an emphasis on understanding rather than technical detail