Laplace Approximations for Posterior Expectations When the Mode Occurs at the Boundary of the Parameter Space

Authors: 
Alaattin Erkanli
Duke University

Jul 7 1992

This paper gives asymptotic expansions for posterior expectations when the mode is on the boundary of the parameter space. The idea, based on the divergence theorem, is to reduce the high-dimensional integrals over the parameters space to surface integrals over the boundary of the parameter space and then apply the usual interior-mode Laplace method to the latter integrals. It is shown that these approximations have second-order accuracy. The method is illustrated with applications to a two-sample binomial problem and a random-effects model.

Keywords: 

Second-order asymptotics, Bayesian inference, Tierney-Kadane approximation, Saddle-point approximation

Manuscript: 

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