On spike and slab empirical Bayes multiple testing
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Publication:2215749
DOI10.1214/19-AOS1897zbMath1455.62035arXiv1808.09748MaRDI QIDQ2215749
Etienne Roquain, Ismaël Castillo
Publication date: 14 December 2020
Published in: The Annals of Statistics (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/1808.09748
Nonparametric hypothesis testing (62G10) Empirical decision procedures; empirical Bayes procedures (62C12) Paired and multiple comparisons; multiple testing (62J15)
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Heteroscedasticity-Adjusted Ranking and Thresholding for Large-Scale Multiple Testing ⋮ False discovery rate control with unknown null distribution: is it possible to mimic the oracle? ⋮ Empirical Bayes cumulative \(\ell\)-value multiple testing procedure for sparse sequences ⋮ Powerful multiple testing of paired null hypotheses using a latent graph model ⋮ Optimal false discovery control of minimax estimators ⋮ Foundations of Bayesian inference for complex statistical models. Abstracts from the workshop held May 2--8, 2021 (hybrid meeting) ⋮ Variational Bayes for High-Dimensional Linear Regression With Sparse Priors ⋮ Large-scale multiple hypothesis testing with the normal-beta prime prior ⋮ Uncertainty quantification for robust variable selection and multiple testing
Uses Software
Cites Work
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- SLOPE is adaptive to unknown sparsity and asymptotically minimax
- The horseshoe estimator: posterior concentration around nearly black vectors
- Distribution-free multiple testing
- Bayes and empirical-Bayes multiplicity adjustment in the variable-selection problem
- Asymptotic Bayes-optimality under sparsity of some multiple testing procedures
- On false discovery rate thresholding for classification under sparsity
- Microarrays, empirical Bayes and the two-groups model
- SLOPE-adaptive variable selection via convex optimization
- The positive false discovery rate: A Bayesian interpretation and the \(q\)-value
- Uncertainty quantification for the horseshoe (with discussion)
- Empirical Bayes analysis of spike and slab posterior distributions
- Convergence rates of posterior distributions.
- Rates of convergence of posterior distributions.
- The control of the false discovery rate in multiple testing under dependency.
- Needles and straw in haystacks: Empirical Bayes estimates of possibly sparse sequences
- Needles and straw in a haystack: posterior concentration for possibly sparse sequences
- Spike and slab empirical Bayes sparse credible sets
- Needles and straw in a haystack: robust confidence for possibly sparse sequences
- General maximum likelihood empirical Bayes estimation of normal means
- Adaptive posterior contraction rates for the horseshoe
- Size, power and false discovery rates
- Dependency and false discovery rate: asymptotics
- On optimality of Bayesian testimation in the normal means problem
- Stepup procedures controlling generalized FWER and generalized FDR
- Adapting to unknown sparsity by controlling the false discovery rate
- Calibration and empirical Bayes variable selection
- A nonparametric empirical Bayes framework for large-scale multiple testing
- Large-Scale Multiple Testing under Dependence
- Simultaneous Testing of Grouped Hypotheses: Finding Needles in Multiple Haystacks
- Adaptive linear step-up procedures that control the false discovery rate
- Oracle and Adaptive Compound Decision Rules for False Discovery Rate Control
- Bayesian Variable Selection in Linear Regression
- Empirical Bayes Analysis of a Microarray Experiment
- A Bayesian Discovery Procedure
- Optimal Sample Size for Multiple Testing
- Covariate-Assisted Ranking and Screening for Large-Scale Two-Sample Inference
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