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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Paper provided by Iowa State University, Department of Economics in its series Staff General Research Papers with number
12021.
Length: Date of creation: 27 Aug 2004 Date of revision: Publication status: Published in International Economic Review, 2001, Vol. 42, No. 1, pp. 121-139. Handle: RePEc:isu:genres:12021
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