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Original Articles

Asymptotic Normality of M-Estimators for Varying Coefficient Models with Longitudinal Data

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Pages 1422-1440
Received 24 Jul 2007
Accepted 04 Sep 2008
Published online: 27 Apr 2009
 

This article considers a nonparametric varying coefficient regression model with longitudinal observations. The relationship between the dependent variable and the covariates is assumed to be linear at a specific time point, but the coefficients are allowed to change over time. A general formulation is used to treat mean regression, median regression, quantile regression, and robust mean regression in one setting. The local M-estimators of the unknown coefficient functions are obtained by local linear method. The asymptotic distributions of M-estimators of unknown coefficient functions at both interior and boundary points are established. Various applications of the main results, including estimating conditional quantile coefficient functions and robustifying the mean regression coefficient functions are derived. Finite sample properties of our procedures are studied through Monte Carlo simulations.

Acknowledgments

This research is partially supported by National Natural Science Foundation of China (Grant No. 10671089), China Postdoctoral Science Foundation funded project, and Jiangsu Planned Projects for Postdoctoral Research Fund.

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