Graphical Comparison of MCMC Performance
Abstract
This paper presents a graphical method for comparing performance of Markov Chain Monte Carlo methods. Most researchers present comparisons of MCMC methods using tables of figures of merit; this paper presents a graphical alternative. It first discusses the computation of autocorrelation time, then uses this to construct a figure of merit, log density function evaluations per independent observation. Then, it demonstrates how one can plot this figure of merit against a tuning parameter in a grid of plots where columns represent sampling methods and rows represent distributions. This type of visualization makes it possible to convey a greater depth of information without overwhelming the user with numbers, allowing researchers to put their contributions into a broader context than is possible with a textual presentation.
Keywords
Cite
@article{arxiv.1011.4457,
title = {Graphical Comparison of MCMC Performance},
author = {Madeleine B. Thompson},
journal= {arXiv preprint arXiv:1011.4457},
year = {2010}
}