Markov Chain Monte Carlo: Can We Trust the Third Significant Figure?
Statistics Theory
2009-09-29 v5 Computation
Statistics Theory
Abstract
Current reporting of results based on Markov chain Monte Carlo computations could be improved. In particular, a measure of the accuracy of the resulting estimates is rarely reported. Thus we have little ability to objectively assess the quality of the reported estimates. We address this issue in that we discuss why Monte Carlo standard errors are important, how they can be easily calculated in Markov chain Monte Carlo and how they can be used to decide when to stop the simulation. We compare their use to a popular alternative in the context of two examples.
Cite
@article{arxiv.math/0703746,
title = {Markov Chain Monte Carlo: Can We Trust the Third Significant Figure?},
author = {James M. Flegal and Murali Haran and Galin L. Jones},
journal= {arXiv preprint arXiv:math/0703746},
year = {2009}
}
Comments
Published in at http://dx.doi.org/10.1214/08-STS257 the Statistical Science (http://www.imstat.org/sts/) by the Institute of Mathematical Statistics (http://www.imstat.org)