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.
作者
姚梅
王江峰
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)
出处
《数学学报（中文版）》
CSCD
北大核心
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)
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
left-truncated data
dependent data
conditional quantile
double-kernel local linear estimator
asymptotic normality
