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.

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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
Source:	RePEc - Research Papers in Economics

Persistent link: https://www.econbiz.de/10005066254