Minimising MCMC variance via diffusion limits, with an application to simulated tempering

23Citations
Citations of this article
19Readers
Mendeley users who have this article in their library.

Abstract

We derive new results comparing the asymptotic variance of diffusions by writing them as appropriate limits of discrete-time birth-death chains which themselves satisfy Peskun orderings. We then apply our results to simulated tempering algorithms to establish which choice of inverse temperatures minimises the asymptotic variance of all functionals and thus leads to the most efficient MCMC algorithm. © Institute of Mathematical Statistics, 2014.

Cite

CITATION STYLE

APA

Roberts, G. O., & Rosenthal, J. S. (2014). Minimising MCMC variance via diffusion limits, with an application to simulated tempering. Annals of Applied Probability, 24(1), 131–149. https://doi.org/10.1214/12-AAP918

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free