## Coupling from the Past: a User's Guide (1997)

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Citations: | 27 - 2 self |

### BibTeX

@MISC{Propp97couplingfrom,

author = {James Propp and David Wilson},

title = {Coupling from the Past: a User's Guide},

year = {1997}

}

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### Abstract

. The Markov chain Monte Carlo method is a general technique for obtaining samples from a probability distribution. In earlier work, we showed that for many applications one can modify the Markov chain Monte Carlo method so as to remove all bias in the output resulting from the biased choice of an initial state for the chain; we have called this method Coupling From The Past (CFTP). Here we describe this method in a fashion that should make our ideas accessible to researchers from diverse areas. Our expository strategy is to avoid proofs and focus on sample applications. 1. Introduction In Markov chain Monte Carlo studies, one attempts to sample from a distribution ß by running a Markov chain whose unique steady-state distribution is ß. Ideally, one has proved a theorem that guarantees that the time for which one plans to run the chain is substantially greater than the mixing time of the chain, so that the distribution ~ ß that one's procedure actually samples from is known to be cl...