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dc.contributor.author Guan, Zhong
dc.contributor.author Wu, Baolin
dc.contributor.author Zhao, Hongyu
dc.date.accessioned 2020-02-11T21:29:00Z
dc.date.available 2020-02-11T21:29:00Z
dc.date.issued 2008
dc.identifier.uri http://hdl.handle.net/2022/25181
dc.description.abstract Under a local dependence assumption about the p-values, an estimator of the proportion π0 of true null hypotheses, having a closed-form expression, is derived based on Bernšteǐn polynomial density estimation. A nonparametric estimator of false discovery rate (FDR) is then obtained. These estimators are proved to be consistent, asymptotically unbiased, and normal. Confidence intervals for π0 and the FDR are also given. The usefulness of the proposed method is demonstrated through simulations and its application to a microarray dataset. Keywords: Bernsteın polynomials, bioinformatics, density estimation, false discovery rate, local dependence, microarray, mixture model, multiple comparison en
dc.format.extent 19 pages
dc.format.mimetype PDF
dc.language.iso en en
dc.subject Mathematical statistics en
dc.subject Nonparametric statistics en
dc.title Nonparametric Estimator of False Discovery Rate Based on Bernšteǐn Polynomials en
dc.type Article en


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