Abstract:
We consider the method of denoising the sparse signals based on the multiple hypothesis testing with the use of the FDR threshold. In the model with a white Gaussian noise we prove the consistency of the unbiased mean-square risk estimator.
Citation:
A. Yu. Zaspa, O. V. Shestakov, “Consistency of the risk estimate of the multiple hypothesis testing with the FDR threshold”, Vestnik TVGU. Ser. Prikl. Matem. [Herald of Tver State University. Ser. Appl. Math.], 2017, no. 1, 5–16
\Bibitem{ZasShe17}
\by A.~Yu.~Zaspa, O.~V.~Shestakov
\paper Consistency of the risk estimate of the multiple hypothesis testing with the FDR threshold
\jour Vestnik TVGU. Ser. Prikl. Matem. [Herald of Tver State University. Ser. Appl. Math.]
\yr 2017
\issue 1
\pages 5--16
\mathnet{http://mi.mathnet.ru/vtpmk119}
\crossref{https://doi.org/10.26456/vtpmk119}
\elib{https://elibrary.ru/item.asp?id=28786643}
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https://www.mathnet.ru/eng/vtpmk/y2017/i1/p5
This publication is cited in the following 3 articles:
M. O. Vorontsov, O. V. Shestakov, “Asimptoticheskaya normalnost i silnaya sostoyatelnost otsenki riska pri ispolzovanii FDR-poroga v usloviyakh slaboi zavisimosti”, Inform. i ee primen., 18:3 (2024), 69–79
S. I. Palionnaya, “Rate of Convergence of a Risk Estimator to the Normal Law in a Multiple Hypothesis Testing Problem Using the FDR Threshold”, MoscowUniv.Comput.Math.Cybern., 45:3 (2021), 114
Sofia Palionnaya, Oleg Shestakov, “Asymptotic Properties of MSE Estimate for the False Discovery Rate Controlling Procedures in Multiple Hypothesis Testing”, Mathematics, 8:11 (2020), 1913
Citation in format AMSBIB
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