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- W2337642657 abstract "We propose a semiparametric mixture model to estimate local false discovery rates in multiple testing problems. The two pilars of the proposed approach are Efron's empirical null principle and log-concave density estimation for the alternative distribution. Compared to existing methods, our method can be easily extended to high dimension. Simulation results show that our method outperforms other existing methods and we illustrate its use via case studies in astronomy and microarray." @default.
- W2337642657 created "2016-06-24" @default.
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- W2337642657 date "2016-04-14" @default.
- W2337642657 modified "2023-10-18" @default.
- W2337642657 title "A semiparametric mixture method for local false discovery rate estimation" @default.
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- W2337642657 doi "https://doi.org/10.48550/arxiv.1604.04264" @default.
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