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引用本文:��ƽ,����ռ,�Ž�.�����Ͳ������Ը��Ϸ�λ���ع�ģ�͵Ĺ���[J].应用概率统计,2017,34(2):170-190.
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Estimation in Functional Partial Linear Composite Quantile Regression Model
YU Ping,ZHANG ZhongZhan,DU Jiang.Estimation in Functional Partial Linear Composite Quantile Regression Model[J].Chinese Journal of Applied Probability and Statisties,2017,34(2):170-190.
Authors:YU Ping  ZHANG ZhongZhan  DU Jiang
Institution:College of Applied Sciences, Beijing University of Technology, School of Mathematics and Computer Science, Shanxi Normal University; College of Applied Sciences, Beijing University of Technology; College of Applied Sciences, Beijing University of Technology
Abstract:This paper studies estimation in functional partial linear composite quantile regression model in which the dependent variable is related to both a function-valued random variable in linear form and a real-valued random variable in nonparametric form. The functional principal component analysis and regression splines are employed to estimate the slope function and the nonparametric function respectively, and the convergence rates of the estimators are obtained under some regularity conditions. Simulation studies and a real data example are presented for illustration of the performance of the proposed estimators.
Keywords:functional data analysis  spline estimate  composite quantile regression  functional principal component analysis  
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