函数型部分线性复合分位数回归模型的估计（英文）  

Estimation in Functional Partial Linear Composite Quantile Regression Model

作　　者：余平[1,2] 张忠占[1] 杜江[1] 

机构地区：[1]北京工业大学应用数理学院,北京100124 [2]山西师范大学数学与计算机学院,临汾041000

出　　处：《应用概率统计》2017年第2期170-190,共21页Chinese Journal of Applied Probability and Statistics

基　　金：partly supported by the National Natural Science Foundation of China(Grant No.11271039);Education Ministry Funds for Doctor Supervisors and Fund from Collaborative Innovation Center on Capital Social Construction and Social Management(Grant No.006000546615539);supported by the National Natural Science Foundation of China(Grant No.11501018)

摘　　要：本文研究函数型部分线性复合分位数回归模型的估计问题.我们采用函数型主成分分析方法分析斜率函数,回归样条逼近非参数函数.在相当宽松的条件下给出斜率函数和非参数函数的收敛速度.最后通过理论模拟和实例分析来评价我们提出的方法.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.

关 键 词：函数型数据分析 样条估计 复合分位数回归 函数型主成分分析 

分 类 号：O212.7[理学—概率论与数理统计]