Interruptible Exact Sampling in the Passive Case

Keith Crank and James Allen Fill
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Keith Crank: National Science Foundation
James Allen Fill: The Johns Hopkins University

Methodology and Computing in Applied Probability, 2002, vol. 4, issue 4, 359-376

Abstract: Abstract We establish, for various scenarios, whether or not interruptible exact stationary sampling is possible when a finite-state Markov chain can only be viewed passively. In particular, we prove that such sampling is not possible using a single copy of the chain. Such sampling is possible when enough copies of the chain are available, and we provide an algorithm that terminates with probability one.

Keywords: exact sampling; perfect simulation; passive case; Markov chain Monte Carlo; stopping time; interruptibility; reversibility; arborescence; tree distribution; Markov chain tree theorem; randomized algorithms; polynomial factorization (search for similar items in EconPapers)
Date: 2002
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DOI: 10.1023/A:1023514501208

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