Open Access
November 2017 A new rejection sampling method without using hat function
Hongsheng Dai
Bernoulli 23(4A): 2434-2465 (November 2017). DOI: 10.3150/16-BEJ814

Abstract

This paper proposes a new exact simulation method, which simulates a realisation from a proposal density and then uses exact simulation of a Langevin diffusion to check whether the proposal should be accepted or rejected. Comparing to the existing coupling from the past method, the new method does not require constructing fast coalescence Markov chains. Comparing to the existing rejection sampling method, the new method does not require the proposal density function to bound the target density function. The new method is much more efficient than existing methods for certain problems. An application on exact simulation of the posterior of finite mixture models is presented.

Citation

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Hongsheng Dai. "A new rejection sampling method without using hat function." Bernoulli 23 (4A) 2434 - 2465, November 2017. https://doi.org/10.3150/16-BEJ814

Information

Received: 1 May 2014; Revised: 1 October 2015; Published: November 2017
First available in Project Euclid: 9 May 2017

zbMATH: 06778246
MathSciNet: MR3648035
Digital Object Identifier: 10.3150/16-BEJ814

Keywords: Conditioned Brownian motion , Coupling from the past , diffusion bridges , exact Monte Carlo simulation , Langevin diffusion , Mixture models , rejection sampling

Rights: Copyright © 2017 Bernoulli Society for Mathematical Statistics and Probability

Vol.23 • No. 4A • November 2017
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