Some optimality properties of FDR controlling rules under sparsity

DOI10.1214/13-EJS808zbMath1337.62184MaRDI QIDQ1951159

Florian Frommlet, Małgorzata Bogdan

Publication date: 29 May 2013

Published in: Electronic Journal of Statistics (Search for Journal in Brave)

Full work available at URL: https://projecteuclid.org/euclid.ejs/1368193534

zbMATH Keywords

asymptotic optimalitymultiple testingBayes riskfalse discovery ratetwo groups model

Mathematics Subject Classification ID

Bayesian inference (62F15) Bayesian problems; characterization of Bayes procedures (62C10) Minimax procedures in statistical decision theory (62C20) Empirical decision procedures; empirical Bayes procedures (62C12) Paired and multiple comparisons; multiple testing (62J15) Compound decision problems in statistical decision theory (62C25)

Related Items

Group SLOPE – Adaptive Selection of Groups of Predictors, SLOPE-adaptive variable selection via convex optimization, On the asymptotic properties of SLOPE

Uses Software

• EbayesThresh
• EBayesThresh

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Estimating the proportion of false null hypotheses among a large number of independently tested hypotheses
• Statistics for high-dimensional data. Methods, theory and applications.
• Asymptotic Bayes-optimality under sparsity of some multiple testing procedures
• On optimality of the Benjamini-Hochberg procedure for the false discovery rate
• On false discovery rate thresholding for classification under sparsity
• Optimal rates of convergence for estimating the null density and proportion of nonnull effects in large-scale multiple testing
• Microarrays, empirical Bayes and the two-groups model
• On the false discovery rate and an asymptotically optimal rejection curve
• Estimating the dimension of a model
• Minimax risk over \(l_ p\)-balls for \(l_ q\)-error
• The positive false discovery rate: A Bayesian interpretation and the \(q\)-value
• Higher criticism for detecting sparse heterogeneous mixtures.
• Needles and straw in haystacks: Empirical Bayes estimates of possibly sparse sequences
• False discovery rate control with multivariate \(p\)-values
• Optimal weighting for false discovery rate control
• Asymptotic behavior of Bayes tests and Bayes risk
• Modified versions of the Bayesian information criterion for sparse generalized linear models
• An exploration of aspects of Bayesian multiple testing
• Asymptotic minimaxity of false discovery rate thresholding for sparse exponential data
• Power-enhanced multiple decision functions controlling family-wise error and false discovery rates
• Adapting to unknown sparsity by controlling the false discovery rate
• On optimality of stepdown and stepup multiple test procedures
• Generalizations of the familywise error rate
• Calibration and empirical Bayes variable selection
• A Theory of some Multiple Decision Problems, I
• Oracle and Adaptive Compound Decision Rules for False Discovery Rate Control
• To How Many Simultaneous Hypothesis Tests Can Normal, Student'stor Bootstrap Calibration Be Applied?
• Operating Characteristics and Extensions of the False Discovery Rate Procedure
• Estimating the Null and the Proportion of Nonnull Effects in Large-Scale Multiple Comparisons
• Error Distribution for Gene Expression Data