A fundamental theorem in hypothesis testing is the Neyman-Pearson (N-P) lemma, which creates the most powerful test of simple hypotheses. In this article, we establish Bayesian framework of hypothesis testing, and extend the Neyman-Pearson lemma to create the Bayesian most powerful test of general hypotheses, thus providing optimality theory to determine thresholds of Bayes factors. Unlike conventional Bayes tests, the proposed Bayesian test is able to control the type I error. To extend Neyman-Pearson lemma, the Bayesian most powerful test is created for general hypotheses.
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Univ Alaska Fairbanks, Dept Math & Stat, POB 756660, Fairbanks, AK 99775 USAUniv Alaska Fairbanks, Dept Math & Stat, POB 756660, Fairbanks, AK 99775 USA
Goddard, Scott D.
Johnson, Valen E.
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Texas A&M Univ, Dept Stat, College Stn, TX 77843 USAUniv Alaska Fairbanks, Dept Math & Stat, POB 756660, Fairbanks, AK 99775 USA
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Charles Univ, Fac Math & Phys, Dept Probabil & Math Stat, Prague 18675 8, Czech RepublicCharles Univ, Fac Math & Phys, Dept Probabil & Math Stat, Prague 18675 8, Czech Republic