Mean–square risk analysis for the use of multiple hypothesis testing methods for threshold selection under weak dependence

Recieved: 12/19/2023

Accepted: 12/25/2023

Published: 04/02/2024

Keywords: threshold processing, multiple hypothesis testing, mean-square risk

To cite this article

Vorontsov M. O. Mean–square risk analysis for the use of multiple hypothesis testing methods for threshold selection under weak dependence. // Moscow University Journal. Series 15. Computational Mathematics and Cybernetics. 2024. N 2, p.18-24 https://doi.org/10.55959/MSU/0137-0782-15-2024-47-2-18-24.

This work is licensed under a Сreative Commons Atribiution - NonCommercial 4.0 International (CC BY-NC 4.0)

Vorontsov M. O. (Lomonosov Moscow State University (MSU))

Abstract

The paper considers an approach to solving the problem of removing noise in a large data set from the sparsity class mp under condition of weak dependence. The approach is based on the method of controlling the false discovery rate (FDR). An upper asymptotic bound for the mean-square risk is obtained.