Efficient moments-based permutation tests

Chunxiao Zhou, Huixia Judy Wang, Yongmei Michelle Wang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In this paper, we develop an efficient moments-based permutation test approach to improve the test's computational efficiency by approximating the permutation distribution of the test statistic with Pearson distribution series. This approach involves the calculation of the first four moments of the permutation distribution. We propose a novel recursive method to derive these moments theoretically and analytically without any permutation. Experimental results using different test statistics are demonstrated using simulated data and real data. The proposed strategy takes advantage of nonparametric permutation tests and parametric Pearson distribution approximation to achieve both accuracy and efficiency.

Original languageEnglish (US)
Title of host publicationAdvances in Neural Information Processing Systems 22 - Proceedings of the 2009 Conference
PublisherNeural Information Processing Systems
Pages2277-2285
Number of pages9
ISBN (Print)9781615679119
StatePublished - 2009
Event23rd Annual Conference on Neural Information Processing Systems, NIPS 2009 - Vancouver, BC, Canada
Duration: Dec 7 2009Dec 10 2009

Publication series

NameAdvances in Neural Information Processing Systems 22 - Proceedings of the 2009 Conference

Other

Other23rd Annual Conference on Neural Information Processing Systems, NIPS 2009
Country/TerritoryCanada
CityVancouver, BC
Period12/7/0912/10/09

ASJC Scopus subject areas

  • Information Systems

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