Wavelet-based Benjamini-Hochberg procedures for multiple testing under dependence

DOI10.3934/MBE.2020003zbMath1472.62068OpenAlexW2976773106WikidataQ91298241 ScholiaQ91298241MaRDI QIDQ2045650

Yanyan Li

Publication date: 13 August 2021

Published in: Mathematical Biosciences and Engineering (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.3934/mbe.2020003

zbMATH Keywords

order statisticshigh-dimensional dataHaar waveletcorrelated statistics

Mathematics Subject Classification ID

Nontrigonometric harmonic analysis involving wavelets and other special systems (42C40) Measures of association (correlation, canonical correlation, etc.) (62H20) Order statistics; empirical distribution functions (62G30) Numerical methods for wavelets (65T60) Paired and multiple comparisons; multiple testing (62J15)

Uses Software

• EFDR

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• On the Benjamini-Hochberg method
• On the false discovery rate and an asymptotically optimal rejection curve
• The control of the false discovery rate in multiple testing under dependency.
• Some results on false discovery rate in stepwise multiple testing procedures.
• A stochastic process approach to false discovery control.
• Two simple sufficient conditions for FDR control
• On false discovery control under dependence
• False discovery and false nondiscovery rates in single-step multiple testing procedures
• Large-Scale Multiple Testing under Dependence
• Incorporating the Empirical Null Hypothesis into the Benjamini-Hochberg Procedure
• The effect of correlation in false discovery rate estimation
• Adaptive linear step-up procedures that control the false discovery rate
• Ten Lectures on Wavelets
• Biorthogonal bases of compactly supported wavelets
• Weak convergence to fractional brownian motion and to the rosenblatt process
• Nonparametric Hypothesis Testing for a Spatial Signal
• Estimating False Discovery Proportion Under Arbitrary Covariance Dependence
• False Discovery Control for Random Fields
• Cross-Dimensional Inference of Dependent High-Dimensional Data
• Correlated z-Values and the Accuracy of Large-Scale Statistical Estimates
• Correlation and Large-Scale Simultaneous Significance Testing
• Estimating the Proportion of True Null Hypotheses, with application to DNA Microarray Data

This page was built for publication: Wavelet-based Benjamini-Hochberg procedures for multiple testing under dependence