Statistical Science

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

James M. Flegal, Murali Haran, and Galin L. Jones

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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.

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Statist. Sci., Volume 23, Number 2 (2008), 250-260.

First available in Project Euclid: 21 August 2008

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Convergence diagnostic Markov chain Monte Carlo standard errors


Flegal, James M.; Haran, Murali; Jones, Galin L. Markov Chain Monte Carlo: Can We Trust the Third Significant Figure?. Statist. Sci. 23 (2008), no. 2, 250--260. doi:10.1214/08-STS257.

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