Distributional consistency of the lasso by perturbation bootstrap

被引：2
|
作者：
Das, Debraj [1 ]
Lahiri, S. N. [2 ]
机构：
[1] Indian Stat Inst, Theoret Stat & Math Unit, 7 SJS Sansanwal Marg, Delhi 110016, India
[2] North Carolina State Univ, Dept Stat, 2311 Stinson Dr, Raleigh, NC 27695 USA
来源：
BIOMETRIKA | 2019年 / 106卷 / 04期
基金：
美国国家科学基金会;
关键词：
Distributional consistency; Lasso; Paired bootstrap; Perturbation bootstrap; Residual bootstrap; ADAPTIVE LASSO; LIKELIHOOD; SELECTION;
D O I：
10.1093/biomet/asz029
中图分类号：
Q [生物科学];
学科分类号：
07 ; 0710 ; 09 ;
摘要：
The lasso is a popular estimation procedure in multiple linear regression. We develop and establish the validity of a perturbation bootstrap method for approximating the distribution of the lasso estimator in a heteroscedastic linear regression model. We allow the underlying covariates to be either random or nonrandom, and show that the proposed bootstrap method works irrespective of the nature of the covariates. We also investigate finite-sample properties of the proposed bootstrap method in a moderately large simulation study.
引用
收藏
页码：957 / 964
页数：8
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