Proximal operator for the sorted \(\ell_1\) norm: application to testing procedures based on SLOPE

DOI10.1016/j.jspi.2022.02.005zbMath1497.62186OpenAlexW4214551463WikidataQ113869772 ScholiaQ113869772MaRDI QIDQ2156800

Patrick J. C. Tardivel, Xavier Dupuis

Publication date: 20 July 2022

Published in: Journal of Statistical Planning and Inference (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.jspi.2022.02.005

zbMATH Keywords

SLOPEfalse discovery rateproximal operatorsorted \(\ell_1\) norm

Mathematics Subject Classification ID

Ridge regression; shrinkage estimators (Lasso) (62J07) Linear regression; mixed models (62J05) Paired and multiple comparisons; multiple testing (62J15)

Cites Work

• Convex polytopes and enumeration
• SLOPE-adaptive variable selection via convex optimization
• Some results on false discovery rate in stepwise multiple testing procedures.
• On the asymptotic properties of SLOPE
• Angle sums of Schläfli orthoschemes
• A sharper Bonferroni procedure for multiple tests of significance
• Algorithmic Analysis and Statistical Estimation of SLOPE via Approximate Message Passing
• Simple expressions of the LASSO and SLOPE estimators in low-dimension
• Simultaneous Regression Shrinkage, Variable Selection, and Supervised Clustering of Predictors with OSCAR
• Signal Recovery by Proximal Forward-Backward Splitting
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