Detecting rare and faint signals via thresholding maximum likelihood estimators

DOI10.1214/17-AOS1574zbMath1392.62163OpenAlexW2795544002WikidataQ130036338 ScholiaQ130036338MaRDI QIDQ1750291

Yumou Qiu, Dan Nettleton, Song Xi Chen

Publication date: 18 May 2018

Published in: The Annals of Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1214/17-aos1574

zbMATH Keywords

moderate deviationgeneralized linear modelfalse discovery proportiondetection boundarymultiple testing procedureRNA-seq data

Mathematics Subject Classification ID

Asymptotic properties of nonparametric inference (62G20) Hypothesis testing in multivariate analysis (62H15) Statistics of extreme values; tail inference (62G32)

Related Items (5)

Elastic-net Regularized High-dimensional Negative Binomial Regression: Consistency and Weak Signal Detection ⋮ Testing and signal identification for two-sample high-dimensional covariances via multi-level thresholding ⋮ Sharp optimality for high-dimensional covariance testing under sparse signals ⋮ Detecting rare and faint signals via thresholding maximum likelihood estimators ⋮ Statistical inference for high-dimensional pathway analysis with multiple responses

Uses Software

• DEseq
• QuasiSeq

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