On estimation error bounds of the Elastic Net when p ≫ n

DOI10.1080/02331888.2022.2060224OpenAlexW4224243158MaRDI QIDQ5089920

Hanzhong Liu, Jinzhu Jia

Publication date: 15 July 2022

Published in: Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/02331888.2022.2060224

zbMATH Keywords

Lassomodel selection consistencyestimation consistencyElastic Netnaive Elastic Net

Mathematics Subject Classification ID

Statistics (62-XX)

Cites Work

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• The sparsity and bias of the LASSO selection in high-dimensional linear regression
• Lasso-type recovery of sparse representations for high-dimensional data
• Least angle regression. (With discussion)
• Honest variable selection in linear and logistic regression models via \(\ell _{1}\) and \(\ell _{1}+\ell _{2}\) penalization
• The smooth-Lasso and other \(\ell _{1}+\ell _{2}\)-penalized methods
• Simultaneous analysis of Lasso and Dantzig selector
• Sharp Thresholds for High-Dimensional and Noisy Sparsity Recovery Using $\ell _{1}$-Constrained Quadratic Programming (Lasso)
• Minimax Rates of Estimation for High-Dimensional Linear Regression Over $\ell_q$-Balls
• Regularization and Variable Selection Via the Elastic Net
• Ridge Regression: Biased Estimation for Nonorthogonal Problems