Research Colloquia, Department of Statistics Thursday, January 18, 2001 4:30 PM in MATH 175 Professor Jaya Satagopan Purdue University will speak on On the Harmonic Mean Estimator of Marginal Probability Abstract The Bayes factor is a useful summary for model selection. Calculation of this measure involves evaluating the marginal or integrated likelihood, which can be estimated from the output of Markov Chain Monte Carlo (MCMC) and other posterior simulation methods using the harmonic mean estimator. While this is a simulation-consistent estimator, it can have infinite variance. In this talk I will describe a method to stabilize the harmonic mean estimator. Under this approach, the parameter space is reduced such that the modified estimator involves a harmonic mean of heavier tailed densities, thus resulting in a finite variance estimator. I will discuss general conditions under which this reduction is applicable and illustrate the proposed method through several examples. *This is a joint work with Michael Newton and Adrian Raftery. Refreshments will be available in MATH Library at 4:15 p.m.

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