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 prod uces a rich class of postdata densities for regression parameters, predicti on and model selection techniques are also described. We also discuss the w ell-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.