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Generalized Accept-Reject Sampling Schemes

Casella, George; Robert, Christian P.; Wells, Martin T. (2004), Generalized Accept-Reject Sampling Schemes, in Rubin, Herman; DasGupta, Anirban, A Festschrift for Herman Rubin, Institute of Mathematical Statistics : Beachwood (Ohio), p. 342-347. http://dx.doi.org/10.1214/lnms/1196285403

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Type
Chapitre d'ouvrage
Date
2004
Book title
A Festschrift for Herman Rubin
Book author
Rubin, Herman; DasGupta, Anirban
Publisher
Institute of Mathematical Statistics
Series title
Lecture Notes Monograph Series
Series number
45
Published in
Beachwood (Ohio)
ISBN
0-940600-61-7
Number of pages
417
Pages
342-347
Publication identifier
Metadata
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Author(s)
Casella, George
Robert, Christian P.
Wells, Martin T.
Abstract (EN)
This paper extends the Accept-Reject algorithm to allow the proposal distribution to change at each iteration. We first establish a necessary and sufficient condition for this generalized Accept-Reject algorithm to be valid, and then show how the resulting estimator can be improved by Rao-Blackwellization. An application of these results is to the perfect sampling technique of Fill (1998), An interruptible algorithm for perfect sampling via Markov chains, which is a generalized Accept-Reject algorithm.
Subjects / Keywords
Monte Carlo methods; Accept-Reject; stopping rule; recycling; uniform variable