Asymptotic Normality of Estimators in Partially Linear Varying Coefficient Models
Received:October 12, 2006  Revised:July 13, 2007
Key Words: asymptotic normality   Heteroscedasticity   profile least-squares approach   partially linear varying coefficient model   local linear smoothing.  
Fund Project:the National Natural Science Foundation of China (No.10431010).
Author NameAffiliation
WEI Chuan Hua Department of Statistics, School of Science, Central University for Nationalities, Beijing 100081, China 
WU Xi Zhi School of Statistics, Renmin University of China, Beijing 100872, China 
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Abstract:
      Partially linear varying coefficient model is a generalization of partially linear model and varying coefficient model and is frequently used in statistical modeling. In this paper, we construct estimators of the parametric and nonparametric components by Profile least-squares procedure which is based on local linear smoothing. The resulting estimators are shown to be asymptotically normal with heteroscedastic error.
Citation:
DOI:10.3770/j.issn:1000-341X.2008.04.017
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