# Ordering, Slicing And Splitting Monte Carlo Markov Chains

@inproceedings{Mira1998OrderingSA, title={Ordering, Slicing And Splitting Monte Carlo Markov Chains}, author={A. Mira}, year={1998} }

Markov chain Monte Carlo is a method of approximating the integral of a function f with respect to a distribution . A Markov chain that has as its stationary distribution is simulated producing samplesX1; X2; : : : . The integral is approximated by taking the average of f(Xn) over the sample path. The standard way to construct such Markov chains is the Metropolis-Hastings algorithm. The class P of all Markov chains having as their unique stationary distribution is very large, so it is important… Expand

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