Permutation $p$-value approximation via generalized Stolarsky invariance

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Permutation p-value approximation via generalized Stolarsky invariance

Abstract: When it is necessary to approximate a small permutation pvalue p, then simulation is very costly. For linear statistics, a Gaussian approximation p̂1 reduces to the volume of a spherical cap. Using Stolarsky’s (1973) invariance principle from discrepancy theory, we get a formula for the mean of (p̂1− p)2 over all spherical caps. From a theorem of Brauchart and Dick (2013) we get such a ...

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Outline. This is an online supplement to the article “Permutation pvalue approximation via generalized Stolarsky invariance”. The section numbers pick up where the main article left off. Section 11 contains all but the shortest proofs of results in the main document. Section 12 investigates the effect of unbalanced sample sizes on the moments of the reference disributions. Section 13 analyzes t...

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Numerical function approximation over a Boolean domain is a classical problem with wide application to data modeling tasks and various forms of learning. A great many function approximation algorithms have been devised over the years. Because the goal is to produce an approximating function that has low expected error, algorithms are typically guided by error reduction. This guiding force, to r...

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ژورنال

عنوان ژورنال: The Annals of Statistics

سال: 2019

ISSN: 0090-5364

DOI: 10.1214/18-aos1702