Institute of Mathematical Statistics Lecture Notes - Monograph Series

Generalized Accept-Reject sampling schemes

George Casella, Christian P. Robert, and Martin T. Wells

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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.

Chapter information

Source
Anirban DasGupta, ed., A Festschrift for Herman Rubin (Beachwood, Ohio, USA: Institute of Mathematical Statistics, 2004), 342-347

Dates
First available in Project Euclid: 28 November 2007

Permanent link to this document
https://projecteuclid.org/euclid.lnms/1196285403

Digital Object Identifier
doi:10.1214/lnms/1196285403

Mathematical Reviews number (MathSciNet)
MR2126910

Zentralblatt MATH identifier
1268.65012

Subjects
Primary: 65C60: Computational problems in statistics

Keywords
Monte Carlo methods Accept-Reject stopping rule recycling uniform variable

Rights
Copyright © 2004, Institute of Mathematical Statistics

Citation

Casella, George; Robert, Christian P.; Wells, Martin T. Generalized Accept-Reject sampling schemes. A Festschrift for Herman Rubin, 342--347, Institute of Mathematical Statistics, Beachwood, Ohio, USA, 2004. doi:10.1214/lnms/1196285403. https://projecteuclid.org/euclid.lnms/1196285403


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