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Further Results on Bayesian Method of Moments Analysis of the Multiple Regression Model

Arnold Zellner and Justin Tobias
International Economic Review
Vol. 42, No. 1 (Feb., 2001), pp. 121-140
Stable URL: http://www.jstor.org/stable/2648721
Page Count: 20
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Further Results on Bayesian Method of Moments Analysis of the Multiple Regression Model
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Abstract

In this article we extend previous BMOM results by showing how information about a variance parameter and its relation to regression coefficients produces a rich class of postdata densities for regression parameters. Prediction and model selection techniques are also described. We also discuss the well-documented link between cross-entropy and the average log odds and then use this criterion in an experiment to compare results obtained from BMOM and Bayes approaches using data generated from known models.

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