Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
6932023 | Journal of Computational Physics | 2015 | 10 Pages |
Abstract
We study a method, Extra Chance Generalized Hybrid Monte Carlo, to avoid rejections in the Hybrid Monte Carlo method and related algorithms. In the spirit of delayed rejection, whenever a rejection would occur, extra work is done to find a fresh proposal that, hopefully, may be accepted. We present experiments that clearly indicate that the additional work per sample carried out in the extra chance approach clearly pays in terms of the quality of the samples generated.
Related Topics
Physical Sciences and Engineering
Computer Science
Computer Science Applications
Authors
Cédric M. Campos, J.M. Sanz-Serna,