Weak consistency of M-estimator in linear regression model with asymptotically almost negatively associated errors

被引：5

作者：

Zhang, Yu ^{[1
,2
]}

Liu, Xinsheng ^{[1
,2
]}

Hu, Hongchang ^{[3
]}

机构：

[1] Nanjing Univ Aeronaut & Astronaut, State Key Lab Mech Control Mech Struct, Inst Nano Sci, Nanjing, Peoples R China

[2] Nanjing Univ Aeronaut & Astronaut, Dept Math, Nanjing, Peoples R China

[3] Hubei Normal Univ, Sch Math & Stat, Huangshi, Hubei, Peoples R China

来源：

COMMUNICATIONS IN STATISTICS-THEORY AND METHODS | 2020年 / 49卷 / 11期

基金：

中国国家自然科学基金;

关键词：

Asymptotically almost negatively associated; linear regression model; M-estimator; weak consistency; LARGE NUMBERS; RANDOM-VARIABLES; STRONG LAW; LOCATION;

D O I：

10.1080/03610926.2019.1584307

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 studies a linear regression model with asymptotically almost negatively associated (AANA, in short) random errors. Under some mild conditions, the weak consistency of M-estimator of the unknown parameter is investigated, which extend the corresponding results for independent random errors and negatively associated (NA, in short) random errors. At last, two simulation examples are presented to verify the weak consistency of M-estimator in the model.

引用

页码：2800 / 2816

页数：17

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