Adaptive Lasso in high-dimensional settings

DOI10.1080/10485250902984875zbMath1167.62063OpenAlexW1987941704MaRDI QIDQ3391785

Yanbiao Xiang, Caiya Zhang, Zheng Yan Lin

Publication date: 13 August 2009

Published in: Journal of Nonparametric Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/10485250902984875

zbMATH Keywords

oracle propertyadaptive Lassohigh-dimensional setting

Mathematics Subject Classification ID

Asymptotic properties of parametric estimators (62F12) Ridge regression; shrinkage estimators (Lasso) (62J07) Linear regression; mixed models (62J05)

Related Items (1)

Asymtotics of Dantzig selector for a general single-index model

Cites Work

• The Adaptive Lasso and Its Oracle Properties
• Asymptotics for Lasso-type estimators.
• Nonconcave penalized likelihood with a diverging number of parameters.
• Least angle regression. (With discussion)
• Asymptotic properties of bridge estimators in sparse high-dimensional regression models
• High-dimensional graphs and variable selection with the Lasso
• Variable Selection via Nonconcave Penalized Likelihood and its Oracle Properties

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