Further Results on Bayesian Method of Moments Analysis of the Multiple Regression Model
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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|Date of creation:||01 Jan 2001|
|Date of revision:|
|Publication status:||Published in International Economic Review 2001, vol. 42, pp. 121-139|
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