Work

Markov Chain Monte Carlo: Can We Trust the Third Significant Figure?

Year: 2008

Type: article

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.

Source: Statistical Science

DOI: 10.1214/08-sts257

Authors: James M. Flegal, Murali Haran, Galin L. Jones

Institution: University of California, Riverside

Language: English

Topic: Markov Chains and Monte Carlo Methods

Subfield: Statistics and Probability

Field: Mathematics

Domain: Physical Sciences

Open Access status: bronze

Funder: National Science Foundation

Award: Output Analysis for Markov Chain Monte Carlo