Abstract
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.
Information
Published: 1 January 2004
First available in Project Euclid: 28 November 2007
zbMATH: 1268.65012
MathSciNet: MR2126910
Digital Object Identifier: 10.1214/lnms/1196285403
Subjects:
Primary:
65C60
Keywords:
Accept-Reject
,
Monte Carlo methods
,
recycling
,
stopping rule
,
uniform variable
Rights: Copyright © 2004, Institute of Mathematical Statistics
