A powerful FDR control procedure for multiple hypotheses

Haibing Zhao and Wing Kam Fung

Computational Statistics & Data Analysis, 2016, vol. 98, issue C, 60-70

Abstract: A powerful test procedure is proposed for multiple hypotheses for the false discovery rate (FDR) control. The proposed procedure is a weighted p-value procedure which explores false null hypotheses information. It is theoretically shown to control the FDR and be more powerful than the widely used plug-in BH procedure. When there are unknown parameters estimated from the data, the asymptotic properties of the proposed procedure are discussed. The extensive simulation studies further verify the theoretical results. A real data is analyzed to illustrate the proposed method.

Keywords: FDR; Multiple comparisons; Power (search for similar items in EconPapers)
Date: 2016
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Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:csdana:v:98:y:2016:i:c:p:60-70

DOI: 10.1016/j.csda.2015.12.013

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