We analyze the convergence to stationarity of a simple nonreversible
Markov chain that serves as a model for several nonreversible Markov chain
sampling methods that are used in practice. Our theoretical and numerical
results show that nonreversibility can indeed lead to improvements over the
diffusive behavior of simple Markov chain sampling schemes. The analysis uses
both probabilistic techniques and an explicit diagonalization.
Publié le : 2000-08-14
Classification:
Nonreversible Markov chain,
Markov chain Monte Carlo,
Metropolis algorithm,
60J10,
65U05
@article{1019487508,
author = {Diaconis, Persi and Holmes, Susan and Neal, Radford M.},
title = {Analysis of a nonreversible Markov chain sampler},
journal = {Ann. Appl. Probab.},
volume = {10},
number = {2},
year = {2000},
pages = { 726-752},
language = {en},
url = {http://dml.mathdoc.fr/item/1019487508}
}
Diaconis, Persi; Holmes, Susan; Neal, Radford M. Analysis of a nonreversible Markov chain sampler. Ann. Appl. Probab., Tome 10 (2000) no. 2, pp. 726-752. http://gdmltest.u-ga.fr/item/1019487508/