Two-sample Bayesian nonparametric hypothesis testing

Abstract : In this article we describe Bayesian nonparametric procedures for two-sample hypothesis testing. Namely, given two sets of samples y^{(1)} iid F^{(1)} and y^{(2)} iid F^{(2)}, with F^{(1)}, F^{(2)} unknown, we wish to evaluate the evidence for the null hypothesis H_{0}:F^{(1)} = F^{(2)} versus the alternative. Our method is based upon a nonparametric Polya tree prior centered either subjectively or using an empirical procedure. We show that the Polya tree prior leads to an analytic expression for the marginal likelihood under the two hypotheses and hence an explicit measure of the probability of the null Pr(H_{0}|y^{(1)},y^{(2)}).
Type de document :
Rapport
[Research Report] 2009
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https://hal.inria.fr/hal-00733547
Contributeur : Francois Caron <>
Soumis le : mardi 18 septembre 2012 - 20:25:48
Dernière modification le : jeudi 11 janvier 2018 - 06:22:36

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  • HAL Id : hal-00733547, version 1

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Chris Holmes, Francois Caron, Jim Griffin, David A Stephens. Two-sample Bayesian nonparametric hypothesis testing. [Research Report] 2009. 〈hal-00733547〉

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