Translator Disclaimer
August 2011 Estimation and variable selection for generalized additive partial linear models
Li Wang, Xiang Liu, Hua Liang, Raymond J. Carroll
Ann. Statist. 39(4): 1827-1851 (August 2011). DOI: 10.1214/11-AOS885

Abstract

We study generalized additive partial linear models, proposing the use of polynomial spline smoothing for estimation of nonparametric functions, and deriving quasi-likelihood based estimators for the linear parameters. We establish asymptotic normality for the estimators of the parametric components. The procedure avoids solving large systems of equations as in kernel-based procedures and thus results in gains in computational simplicity. We further develop a class of variable selection procedures for the linear parameters by employing a nonconcave penalized quasi-likelihood, which is shown to have an asymptotic oracle property. Monte Carlo simulations and an empirical example are presented for illustration.

Citation

Download Citation

Li Wang. Xiang Liu. Hua Liang. Raymond J. Carroll. "Estimation and variable selection for generalized additive partial linear models." Ann. Statist. 39 (4) 1827 - 1851, August 2011. https://doi.org/10.1214/11-AOS885

Information

Published: August 2011
First available in Project Euclid: 26 July 2011

zbMATH: 1227.62053
MathSciNet: MR2893854
Digital Object Identifier: 10.1214/11-AOS885

Subjects:
Primary: 62G08
Secondary: 62G20, 62G99

Rights: Copyright © 2011 Institute of Mathematical Statistics

JOURNAL ARTICLE
25 PAGES


SHARE
Vol.39 • No. 4 • August 2011
Back to Top