Regression Models under Competing Covariance Structures: A Bayesian Perspective

Jacek Osiewalski and Mark Steel

Annals of Economics and Statistics, 1993, issue 32, 65-79

Abstract: This paper develops Bayesian approaches to deal with linear elliptical regression models that differ in the covariance structure. A pretest method based on posterior model probabilities is compared with a pooling approach, and the data density is defined as a mixture of elliptical densities with weights that are unknown discrete parameters. An example with AR (1), MA (1) or uncorrelated errors is presented as an illustration of the ideas.

Date: 1993
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