Weighted nonparametric regression estimation with truncated and dependent data

被引：4

作者：

Liang, Han-Ying ^{[1
]}

机构：

[1] Tongji Univ, Dept Math, Shanghai 200092, Peoples R China

来源：

JOURNAL OF NONPARAMETRIC STATISTICS | 2012年 / 24卷 / 04期

基金：

中国国家自然科学基金;

关键词：

asymptotic normality; weighted Nadaraya-Watson type estimator; conditional mean function; truncated data; alpha-mixing; CONVERGENCE;

D O I：

10.1080/10485252.2012.721516

中图分类号：

O21 [概率论与数理统计]; C8 [统计学];

学科分类号：

020208 ; 070103 ; 0714 ;

摘要：

By applying the empirical likelihood method, we construct a new weighted Nadaraya-Watson type estimator of the conditional mean function for a left truncation model. The function includes the regression function, conditional moment as well as conditional distribution function. Under strong mixing assumptions, we obtain the asymptotic normality and weak consistency of the estimator. Finite sample behaviour of the estimator is investigated via simulations too.

引用

页码：1051 / 1073

页数：23

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