Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
416254 | Computational Statistics & Data Analysis | 2016 | 11 Pages |
Abstract
A powerful test procedure is proposed for multiple hypotheses for the false discovery rate (FDR) control. The proposed procedure is a weighted pp-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
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Physical Sciences and Engineering
Computer Science
Computational Theory and Mathematics
Authors
Haibing Zhao, Wing Kam Fung,