Statistical inference for a heteroscedastic regression model with φ-mixing errors

被引：3

作者：

Ding, Liwang ^{[1
,2
]}

Chen, Ping ^{[1
]}

Yongming, Li ^{[3
]}

机构：

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

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

[3] Shangrao Normal Univ, Sch Math & Comp Sci, Shangrao, Peoples R China

来源：

COMMUNICATIONS IN STATISTICS-SIMULATION AND COMPUTATION | 2022年 / 51卷 / 08期

基金：

中国国家自然科学基金;

关键词：

Asymptotic normality; Wavelet estimation; Heteroscedastic regression model; phi-mixing random variable; ASYMPTOTIC NORMALITY; SAMPLE QUANTILES; ESTIMATOR; SUMS;

D O I：

10.1080/03610918.2020.1747074

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：

In this paper, we mainly study the asymptotic normality of wavelet estimators in the heteroscedastic regression model with phi-mixing errors. Under some suitable conditions, the asymptotic normality of the wavelet estimators of g and f in the heteroscedastic regression model with phi-mixing errors are obtained, which generalize or improve the corresponding ones for alpha-mixing random variables and martingale difference sequence in some sense. Also, the simulation study of the finite samples provided in this paper shows the validity of our results.

引用

页码：4658 / 4676

页数：19

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