The partial linear model in high dimensions
Statistics Theory
2013-07-04 v1 Applications
Statistics Theory
Abstract
Partial linear models have been widely used as flexible method for modelling linear components in conjunction with non-parametric ones. Despite the presence of the non-parametric part, the linear, parametric part can under certain conditions be estimated with parametric rate. In this paper, we consider a high-dimensional linear part. We show that it can be estimated with oracle rates, using the LASSO penalty for the linear part and a smoothness penalty for the nonparametric part.
Cite
@article{arxiv.1307.1067,
title = {The partial linear model in high dimensions},
author = {Patric Müller and Sara van de Geer},
journal= {arXiv preprint arXiv:1307.1067},
year = {2013}
}
Comments
48 pages, 16 figures, submitted to Scandinavian Journal of Statistics