Improved generic acceptance function for Multi-point Metropolis algorithm

DOI

10.2991/emeit.2012.4How to use a DOI?

Keywords

MCMC, Metropolis Hastings, Multi-point, Detailed Balance Condition,

Abstract

The key of designing MCMC algorithm is the choice of acceptance function. In this work, Selection criteria of acceptance function is given, and an improved Multi-point Metropolis algorithm with generic acceptance function is proposed, which is called GAF-MPM. Then GAF-MPM is showed to satisfy Detailed Balance Condition to ensure its convergence, the strict proof is given in this work. Further, several different acceptance functions are given, and we discuss the effect on the convergence speed, acceptance rate of the samples and the correlation due to the choice of different acceptance functions. Finally, its correctness and effectiveness is proven through numerical experiments.

Copyright

© 2012, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Yinghua Zhang
AU  - Wensheng Zhang
PY  - 2012/09
DA  - 2012/09
TI  - Improved generic acceptance function for Multi-point Metropolis algorithm
BT  - Proceedings of the 2nd International Conference on Electronic & Mechanical Engineering and Information Technology (EMEIT 2012)
PB  - Atlantis Press
SP  - 16
EP  - 21
SN  - 1951-6851
UR  - https://doi.org/10.2991/emeit.2012.4
DO  - 10.2991/emeit.2012.4
ID  - Zhang2012/09
ER  -