Permutation p-value approximation via generalized Stolarsky invariance

DOI10.48550/arXiv.1603.02757zbMath1415.62099arXiv1603.02757OpenAlexW2962799320MaRDI QIDQ151862

Hera He, Art B. Owen, Qingyuan Zhao, Kinjal Basu, Qingyuan Zhao, Art B. Owen, Kinjal Basu, Hera Y. He

Publication date: 9 March 2016

Published in: The Annals of Statistics (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1603.02757

zbMATH Keywords

hypothesis testingdiscrepancyquasi-Monte Carlogene sets

Mathematics Subject Classification ID

Nonparametric hypothesis testing (62G10) Applications of statistics to biology and medical sciences; meta analysis (62P10) Nonparametric statistical resampling methods (62G09) Models of societies, social and urban evolution (91D10) Irregularities of distribution, discrepancy (11K38)

Related Items (7)

Positive definiteness and the Stolarsky invariance principle ⋮ Calibration of posterior predictive p-values for model checking ⋮ Comparing a large number of multivariate distributions ⋮ Permutation testing in high-dimensional linear models: an empirical investigation ⋮ Permutation p-value approximation via generalized Stolarsky invariance ⋮ pipeGS ⋮ Geodesic distance Riesz energy on the sphere

Uses Software

• R

Cites Work

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• The Stolarsky principle and energy optimization on the sphere
• A simple proof of Stolarsky’s invariance principle
• Sums of Distances Between Points on a Sphere. II
• Testing Statistical Hypotheses
• Reproducible Research: A Bioinformatics Case Study

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