Author:
Glynn Peter W.,Wong Eugene W.
Abstract
This paper is concerned with how coupling can be used to enhance the efficiency of a certain class of terminating simulations, in Markov process settings in which the stationary distribution is known. We are able to theoretically establish that our coupling-based estimator is often more efficient than the naive estimator. In addition, we discuss extensions of our methodology to Markov process settings in which conventional coupling fails and show (for Doeblin chains) that knowledge of the stationary distribution is sometimes unnecessary.
Publisher
Cambridge University Press (CUP)
Subject
Industrial and Manufacturing Engineering,Management Science and Operations Research,Statistics, Probability and Uncertainty,Statistics and Probability
Cited by
4 articles.
订阅此论文施引文献
订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
1. Coupling control variates for Markov chain Monte Carlo;Journal of Computational Physics;2009-10
2. Exploiting regenerative structure to estimate finite time averages via simulation;ACM Transactions on Modeling and Computer Simulation;2007-04
3. TRANSIENT SIMULATION VIA EMPIRICALLY BASED COUPLING;Probability in the Engineering and Informational Sciences;1999-04
4. Coupling;Probability Towards 2000;1998