Non-Convex Global Minimization and False Discovery Rate Control for the TREX

DOI10.1080/10618600.2017.1341414OpenAlexW2962770207MaRDI QIDQ3391128

Irina Gaynanova, Johannes Lederer, Jacob Bien, Christian L. Müller

Publication date: 28 March 2022

Published in: Journal of Computational and Graphical Statistics (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1604.06815

zbMATH Keywords

global optimizationmodel selectionsparsityhigh-dimensionaltuning parameter

Mathematics Subject Classification ID

Statistics (62-XX)

Related Items (2)

Tuning-free ridge estimators for high-dimensional generalized linear models ⋮ Prediction error bounds for linear regression with the TREX

Uses Software

• ggplot2
• ECOS
• SCS
• Glmnet

Cites Work

• Conic optimization via operator splitting and homogeneous self-dual embedding
• Controlling the false discovery rate via knockoffs
• Applications of second-order cone programming
• Square-root lasso: pivotal recovery of sparse signals via conic programming
• Scaled sparse linear regression
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