左截断相依数据下条件分位数的双核局部线性估计  

Double-Kernel Local Linear Estimator of Conditional Quantile under Left-truncated and Dependent Data

作　　者：姚梅[1] 王江峰[2] 林路 Mei YAO;Jiang Feng WANG;Lu LIN(School of Mathematics,Hefei University of Technology,Hefei 230009,P.R.Chin;School of Statistics and Mathematics,Zhejiang Gongshang University,Hongzhou 310018,P.R.Chin;Zhongtai Securities Institute for Financial Studies,Shandong University,Jinan 250100,P.R.China)

机构地区：[1]合肥工业大学数学学院,合肥230009 [2]浙江工商大学统计与数学学院,杭州310018 [3]山东大学中泰证券金融研究院,济南250100

出　　处：《数学学报（中文版）》2018年第6期963-980,共18页Acta Mathematica Sinica：Chinese Series

基　　金：国家社会科学基金资助项目(16BTJ029)

摘　　要：本文在左截断相依数据下,利用局部线性估计的方法,先提出了条件分布函数的双核估计;然后利用该估计导出了条件分位数的双核局部线性估计,并建立了这些估计的渐近正态性结果;最后,通过模拟显示该估计在偏移和边界点调节上要比一般的核估计更好.We construct a double-kernel estimator of conditional distribution function by the local linear approach for left-truncated and dependent data, from which we derive the weighted double-kernel local linear estimator of conditional quantile. The asymptotic normality of the proposed estimators are also established. Finite-sample performance of the estimator is investigated via simulation, and is better than the general kernel estimation in bias and adaptation of edge effects.

关 键 词：左截断数据 相依数据 条件分位数 双核局部线性估计 渐近正态性 

分 类 号：O212.7[理学—概率论与数理统计]