Journal of Mathematical Psychology volume 50, issue 2, P123-148 2006 DOI: 10.1016/j.jmp.2005.07.003 View full text
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George Karabatsos

Abstract: This article examines a Bayesian nonparametric approach to model selection and model testing, which is based on concepts from Bayesian decision theory and information theory. The approach can be used to evaluate the predictive-utility of any model that is either probabilistic or deterministic, with that model analyzed under either the Bayesian or classical-frequentist approach to statistical inference. Conditional on an observed set of data, generated from some unknown true sampling density, the approach iden…

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