Gibbs sampling for marginal posterior expectations


Journal Article

In earlier work (Gelfand and Smith, 1990 and Gelfand et al, 1990) a sampling based approach using the Gibbs sampler was offered as a means for developing marginal posterior densities for a wide range of Bayesian problems several of which were previously inaccessible. Our purpose here is two-fold. First we flesh out the implementation of this approach for calculation of arbitrary expectations of interest. Secondly we offer comparison with perhaps the most prominent approach for calculating posterior expectations, analytic approximation involving application of the LaPlace method. Several illustrative examples are discussed as well. Clear advantages for the sampling based approach emerge. © 1991, Taylor & Francis Group, LLC. All rights reserved.

Full Text

Duke Authors

Cited Authors

  • Gelfand, AE; Smith, AF

Published Date

  • January 1, 1991

Published In

Volume / Issue

  • 20 / 5-6

Start / End Page

  • 1747 - 1766

Electronic International Standard Serial Number (EISSN)

  • 1532-415X

International Standard Serial Number (ISSN)

  • 0361-0926

Digital Object Identifier (DOI)

  • 10.1080/03610929108830595

Citation Source

  • Scopus