most citedThe sparsity and bias of the Lasso selection in high-dimensional linear regression

510 citations · 550 across the 2 of their papers we have counts for

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2 papers

math.ST2008★ 510 cited

The sparsity and bias of the Lasso selection in high-dimensional linear regression

Cun-Hui Zhang, Jian Huang

Meinshausen and Buhlmann [Ann. Statist. 34 (2006) 1436--1462] showed that, for neighborhood selection in Gaussian graphical models, under a neighborhood stability condition, the LA…

math.ST2007★ 40 cited

Asymptotic oracle properties of SCAD-penalized least squares estimators

Jian Huang, Huiliang Xie

We study the asymptotic properties of the SCAD-penalized least squares estimator in sparse, high-dimensional, linear regression models when the number of covariates may increase wi…