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Testing over a continuum of null hypotheses with False Discovery Rate control

Abstract : We consider statistical hypothesis testing simultaneously over a fairly general, possibly uncountably infinite, set of null hypotheses, under the assumption that a suitable single test (and corresponding $p$-value) is known for each individual hypothesis. We extend to this setting the notion of false discovery rate (FDR) as a measure of type I error. Our main result studies specific procedures based on the observation of the $p$-value process. Control of the FDR at a nominal level is ensured either under arbitrary dependence of $p$-values, or under the assumption that the finite dimensional distributions of the $p$-value process have positive correlations of a specific type (weak PRDS). Both cases generalize existing results established in the finite setting. Its interest is demonstrated in several non-parametric examples: testing the mean/signal in a Gaussian white noise model, testing the intensity of a Poisson process and testing the c.d.f. of i.i.d. random variables.
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Contributor : Etienne Roquain <>
Submitted on : Thursday, February 6, 2014 - 9:31:42 PM
Last modification on : Friday, March 27, 2020 - 3:57:56 AM
Document(s) archivé(s) le : Wednesday, May 7, 2014 - 4:40:30 AM


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Gilles Blanchard, Sylvain Delattre, Etienne Roquain. Testing over a continuum of null hypotheses with False Discovery Rate control. Bernoulli, Bernoulli Society for Mathematical Statistics and Probability, 2014, pp.304-333. ⟨10.3150/12-BEJ488⟩. ⟨hal-00632783v3⟩



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