Distributional consistency of the lasso by perturbation bootstrap

Debraj Das and S N Lahiri

Biometrika, 2019, vol. 106, issue 4, 957-964

Abstract: SummaryThe 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.

Keywords: Distributional consistency; Lasso; Paired bootstrap; Perturbation bootstrap; Residual bootstrap (search for similar items in EconPapers)
Date: 2019
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