Electronic Communications in Probability
- Electron. Commun. Probab.
- Volume 7 (2002), paper no. 15, 141-155.
Fill's Algorithm for Absolutely Continuous Stochastically Monotone Kernels
Fill, Machida, Murdoch, and Rosenthal (2000) presented their algorithm and its variants to extend the perfect sampling algorithm of Fill (1998) to chains on continuous state spaces. We consider their algorithm for absolutely continuous stochastically monotone kernels, and show the correctness of the algorithm under a set of certain regularity conditions. These conditions succeed in relaxing the previously known hypotheses sufficient for their algorithm to apply.
Electron. Commun. Probab., Volume 7 (2002), paper no. 15, 141-155.
Accepted: 5 August 2002
First available in Project Euclid: 16 May 2016
Permanent link to this document
Digital Object Identifier
Mathematical Reviews number (MathSciNet)
Zentralblatt MATH identifier
Primary: 60J10: Markov chains (discrete-time Markov processes on discrete state spaces) 68U20: Simulation [See also 65Cxx]
Secondary: 60G40: Stopping times; optimal stopping problems; gambling theory [See also 62L15, 91A60] 65C05: Monte Carlo methods 65C10: Random number generation 65C40: Computational Markov chains
Markov chain Monte Carlo Fill's algorithm perfect sampling exact sampling rejection sampling stochastic monotonicity partially ordered set monotone coupling absolutely continuous Markov kernel regularity conditions
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Machida, Motoya. Fill's Algorithm for Absolutely Continuous Stochastically Monotone Kernels. Electron. Commun. Probab. 7 (2002), paper no. 15, 141--155. doi:10.1214/ECP.v7-1056. https://projecteuclid.org/euclid.ecp/1463434782