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Estimating the false discovery rate using the stochastic approximation algorithm

Zhang, Jian, Liang, Faming (2008) Estimating the false discovery rate using the stochastic approximation algorithm. Biometrika, 95 (4). pp. 961-977. ISSN 0006-3444. (doi:10.1093/biomet/asn036) (KAR id:31582)

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http://dx.doi.org/10.1093/biomet/asn036

Abstract

Testing of multiple hypotheses involves statistics that are strongly dependent in some applications,

a new method for estimating the false discovery rate of multiple hypothesis tests, in which the

between the unknown density and its estimator using the stochastic approximation algorithm,

applicable under general dependence between test statistics. Numerical comparisons between our

method achieves more accurate control of the false discovery rate in almost all scenarios.

Item Type: Article
DOI/Identification number: 10.1093/biomet/asn036
Uncontrolled keywords: Ensemble averaging; False discovery rate; Microarray data analysis; Multiple hypothesis testing;Stochastic approximation.
Subjects: Q Science > QA Mathematics (inc Computing science)
Q Science > QA Mathematics (inc Computing science) > QA276 Mathematical statistics
Divisions: Faculties > Sciences > School of Mathematics Statistics and Actuarial Science
Faculties > Sciences > School of Mathematics Statistics and Actuarial Science > Statistics
Depositing User: Jian Zhang
Date Deposited: 11 Oct 2012 16:57 UTC
Last Modified: 13 Feb 2020 04:04 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/31582 (The current URI for this page, for reference purposes)
Zhang, Jian: https://orcid.org/0000-0001-8405-2323
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