Journal of Probability and Statistics
Volume 2012 (2012), Article ID 131085, 20 pages
Research Article

Least Absolute Deviation Estimate for Functional Coefficient Partially Linear Regression Models

1School of Mathematics and Statistics, Wuhan University, Wuhan 430072, China
2School of Mathematics and Statistics, Central China Normal University, Wuhan 430079, China

Received 5 August 2012; Revised 10 October 2012; Accepted 1 November 2012

Academic Editor: Artur Lemonte

Copyright © 2012 Yanqin Feng et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


The functional coefficient partially linear regression model is a useful generalization of the nonparametric model, partial linear model, and varying coefficient model. In this paper, the local linear technique and the method are employed to estimate all the functions in the functional coefficient partially linear regression model. The asymptotic properties of the proposed estimators are studied. Simulation studies are conducted to show the validity of the estimate procedure.