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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| Official URL http://dx.doi.org/10.1093/biomet/asn036 |
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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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