Markov Chains of Infinite Order and Asymptotic Satisfaction of Balance: Application to the Adaptive Integration Method

Thumbnail Image

Date

Authors

Journal Title

Journal ISSN

Volume Title

Publisher

Abstract

Description

Adaptive Monte Carlo methods can be viewed as implementations of Markov chains with infinite memory. We derive a general condition for the convergence of a Monte Carlo method whose history dependence is contained within the simulated density distribution. In convergent cases, our result implies that the balance condition need only be satisfied asymptotically. As an example, we show that the adaptive integration method converges.
13 pages

Keywords

Computational Physics, Statistical Mechanics

Citation

URI

http://salesiana.dossiersoluciones.com/handle/123456789/86648

Consulte el texto completo en el siguiente enlace:

https://arxiv.org/abs/physics/0411150
 http://arxiv.org/abs/physics/0411150

Collections

arXiv