Variable selection in high-dimensional partly linear additive models

• Main Author: Lian, Heng
• Other Authors: School of Physical and Mathematical Sciences
• Format: Article
• Language: English
• Published: 2013
• Subjects: DRNTU::Science::Mathematics::Statistics
• Online Access: https://hdl.handle.net/10356/97695; http://hdl.handle.net/10220/17096
• Institution: Nanyang Technological University

Semiparametric models are particularly useful for high-dimensional regression problems. In this paper, we focus on partly linear additive models with a large number of predictors (can be larger than the sample size) and consider model estimation and variable selection based on polynomial spline expa...