Asymptotic normality and strong consistency of LS estimators in the EV regression model with NA errors

被引：25

作者：

Miao, Yu ^{[1
]}

Zhao, Fangfang ^{[1
]}

Wang, Ke ^{[1
]}

Chen, Yanping ^{[1
]}

机构：

[1] Henan Normal Univ, Coll Math & Informat Sci, Xinxiang 453007, Henan, Peoples R China

来源：

STATISTICAL PAPERS | 2013年 / 54卷 / 01期

基金：

中国国家自然科学基金;

关键词：

EV model; Asymptotic normality; Strong consistency; LS estimator; Negatively associated sequence; RANDOM-VARIABLES; WEIGHTED SUMS; CONVERGENCE; LAW;

D O I：

10.1007/s00362-011-0418-x

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 article, the asymptotic normality and strong consistency of the least square estimators for the unknown parameters in the simple linear errors in variables model are established under the assumptions that the errors are stationary negatively associated sequences.

引用

下载

页码：193 / 206

页数：14

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