Markov Chain Monte Carlo: Can We Trust the Third Significant Figure?
Presented by James Marshall Flegal - University of California, Riverside, Department of Statistics
Date: Thursday, September 13th, 2012
Time: 10:30 AM – 12:00 PM Pacific / 1:30 PM – 3:00 PM Eastern
Host Location: Santa Monica, Forum 1225
Other Locations: Pittsburgh, room 6202 & Washington, DC, room 7128
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.
James Flegal is an Assistant Professor of Statistics at the University of California, Riverside. He received his Ph.D. from the School of Statistics at the University of Minnesota in 2008. His research interests include statistical computing, Markov chain Monte Carlo, Bayesian statistical methods, and Monte Carlo standard errors. Prior to graduate school, James attended Northwestern University where he earned a B.S. in Mechanical Engineering in 1999. His professional career outside of academia includes modeling furnace systems with computational fluid dynamics algorithms and designing welded fabrications for a heavy equipment manufacturer.
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