Statistical estimation for heteroscedastic semiparametric regression model with random errors

被引：2

作者：

Ding, Liwang ^{[1
,2
]}

Chen, Ping ^{[1
]}

机构：

[1] Nanjing Univ Sci & Technol, Sch Sci, Nanjing 210094, Peoples R China

[2] Guangxi Univ Finance & Econ, Sch Informat & Stat, Nanning 530003, Peoples R China

来源：

JOURNAL OF NONPARAMETRIC STATISTICS | 2020年 / 32卷 / 04期

基金：

中国国家自然科学基金;

关键词：

Asymptotic normality; heteroscedastic semiparametric regression model; wavelet estimator; ϕ -mixing; WAVELET ESTIMATORS;

D O I：

10.1080/10485252.2020.1834553

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：

This paper is concerned with the estimating problem of heteroscedastic semiparametric regression model. We investigate the asymptotic normality for wavelet estimators of the slope parameter and the nonparametric component in the case of known error variance with phi-mixing random errors. Also, when the error variance is unknown, the asymptotic normality for the estimators of the slope parameter and the nonparametric component as well as variance function is considered under independent assumptions. Finally, the simulation study is provided to illustrate the feasibility of the theoretical result that we established.

引用

页码：940 / 969

页数：30

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