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Exact Sampling from a Continuous State Space
Author(s) -
Murdoch D. J.,
Green P. J.
Publication year - 1998
Publication title -
scandinavian journal of statistics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.359
H-Index - 65
eISSN - 1467-9469
pISSN - 0303-6898
DOI - 10.1111/1467-9469.00116
Subject(s) - markov chain monte carlo , sampling (signal processing) , mathematics , markov chain , state space , coupling (piping) , monte carlo method , monotone polygon , gibbs sampling , state (computer science) , importance sampling , rejection sampling , statistical physics , algorithm , statistics , hybrid monte carlo , computer science , bayesian probability , physics , geometry , filter (signal processing) , computer vision , engineering , mechanical engineering
Propp & Wilson (1996) described a protocol, called coupling from the past, for exact sampling from a target distribution using a coupled Markov chain Monte Carlo algorithm. In this paper we extend coupling from the past to various MCMC samplers on a continuous state space; rather than following the monotone sampling device of Propp & Wilson, our approach uses methods related to gamma‐coupling and rejection sampling to simulate the chain, and direct accounting of sample paths.