Distributional consistency of the lasso by perturbation bootstrap

Authors

Debraj Das, Indian Statistical Institute (Delhi Centre)
S. N. Lahiri, NC State University

Article Type

Research Article

Publication Title

Biometrika

Abstract

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.

First Page

957

Last Page

964

DOI

10.1093/biomet/asz029

Publication Date

12-1-2019

Comments

Open Access, Green

Recommended Citation

Das, Debraj and Lahiri, S. N., "Distributional consistency of the lasso by perturbation bootstrap" (2019). Journal Articles. 580.
https://digitalcommons.isical.ac.in/journal-articles/580