期刊
COMPUTATIONAL STATISTICS & DATA ANALYSIS
卷 51, 期 12, 页码 5483-5493出版社
ELSEVIER
DOI: 10.1016/j.csda.2007.02.028
关键词
false discovery rate; mixture model; multiple testing procedure; Semi-parametric density estimation
A procedure to estimate a two-component mixture model where one component is known is proposed. The unknown part is estimated with a weighted kernel function. The weights are defined in an adaptive way. The convergence to a unique solution of our estimation procedure is proven. The procedure is compared with two classical approaches using simulation. In addition, the results obtained are applied to multiple testing procedure in order to estimate the posterior population probabilities and the local false discovery rate. (C) 2007 Elsevier B.V. All rights reserved.
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