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Regression Models under Competing Covariance Structures: A Bayesian Perspective

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.
Year of publication:
1993
Authors: OSIEWALSKI, Jacek ; STEEL, Mark F.J.
Published in:
Annales d'Economie et de Statistique. - École Nationale de la Statistique et de l'Admnistration Économique (ENSAE). - 1993, 32, p. 65-79
Publisher: École Nationale de la Statistique et de l'Admnistration Économique (ENSAE)
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Extent:
application/pdf
Type of publication: Article
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Persistent link: https://www.econbiz.de/10005066254
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