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Estimation in semiparametric mixture model in multiple testing setup
Người báo cáo: Nguyễn Văn Hạnh

Thời gian: 14h, Thứ 4, ngày 27/4/2016
Địa điểm: Phòng số 6, nhà A14, Viện Toán học, 18 Hoàng Quốc Việt, Hà Nội
Tóm tắt: In a multiple testing context, we consider a semiparametric mixture model with two components. One component is assumed to be known and corresponds to the distribution of p-values under the null hypothesis with prior probability theta. The other component f is nonparametric and stands for the distribution under the alternative hypothesis. The problem of estimating the parameters theta and f of the model appears from the false discovery rate control procedures. We exhibit asymptotically efficient estimators of theta. We propose and study the asymptotic properties of two different estimators for the unknown component f.

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