A note on mean-field variational approximations in Bayesian probit models

Authors:
Artin Armagan;Russell L. Zaretzki
Affiliations:
Department of Statistical Science, Duke University, Durham, NC 27708, United States;Department of Statistics, Operations and Management Science, The University of Tennessee, Knoxville, TN 37996, United States
Venue:
Computational Statistics & Data Analysis
Year:
2011

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Abstract

We correct some conclusions presented by Consonni and Marin (2007) on the performance of mean-field variational approximations to Bayesian inferences in the case of a simple probit model. We show that some of their presentations are misleading and thus their results do not fairly present the performance of such approximations in terms of point estimation under the specified model.