Experts has a new look! Let us know what you think of the updates.

Provide feedback
Home
Scholarly Works
The Lasso for High Dimensional Regression with a...
Journal article

The Lasso for High Dimensional Regression with a Possible Change Point

Abstract

We consider a high dimensional regression model with a possible change point due to a covariate threshold and develop the lasso estimator of regression coefficients as well as the threshold parameter. Our lasso estimator not only selects covariates but also selects a model between linear and threshold regression models. Under a sparsity assumption, we derive non-asymptotic oracle inequalities for both the prediction risk and the l1-estimation …

Authors

Lee S; Seo MH; Shin Y

Journal

Journal of the Royal Statistical Society Series B Statistical Methodology, Vol. 78, No. 1, pp. 193–210

Publisher

Oxford University Press (OUP)

Publication Date

January 1, 2016

DOI

10.1111/rssb.12108

ISSN

1369-7412

Labels