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