Mathematical Problems in Engineering
Volume 2010 (2010), Article ID 956907, 30 pages
Research Article

QML Estimators in Linear Regression Models with Functional Coefficient Autoregressive Processes

School of Mathematics and Statistics, Hubei Normal University, Huangshi 435002, China

Received 30 December 2009; Revised 19 March 2010; Accepted 6 April 2010

Academic Editor: Massimo Scalia

Copyright © 2010 Hongchang Hu. 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.


This paper studies a linear regression model, whose errors are functional coefficient autoregressive processes. Firstly, the quasi-maximum likelihood (QML) estimators of some unknown parameters are given. Secondly, under general conditions, the asymptotic properties (existence, consistency, and asymptotic distributions) of the QML estimators are investigated. These results extend those of Maller (2003), White (1959), Brockwell and Davis (1987), and so on. Lastly, the validity and feasibility of the method are illuminated by a simulation example and a real example.