Some probability inequalities of least-squares estimator in non linear regression model with strong mixing errors

被引：5

作者：

Yang, Wenzhi ^{[1
]}

Wang, Yiwei ^{[2
]}

Hu, Shuhe ^{[1
]}

机构：

[1] Anhui Univ, Sch Math Sci, Hefei, Anhui, Peoples R China

[2] Chinese Univ Hong Kong, Dept Syst Engn & Engn Management, Shatin, Hong Kong, Peoples R China

来源：

COMMUNICATIONS IN STATISTICS-THEORY AND METHODS | 2017年 / 46卷 / 01期

基金：

中国国家自然科学基金;

关键词：

Least-squares estimator; Non linear regression model; Strong mixing sequence; LARGE DEVIATION RESULT; SAMPLE QUANTILES; BAHADUR REPRESENTATION; CONVERGENCE; CONSISTENCY; SEQUENCES;

D O I：

10.1080/03610926.2014.988261

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 investigate the non linear regression model when the errors are strong mixing. Some probabilityinequalities of the least-squares estimator are presented by using moment information of errors. Meanwhile, for some p > 2, two examples are given when errors satisfy sup(n >= 1) E vertical bar xi(n)vertical bar(p) = infinity and sup(n >= 1) E vertical bar xi(n)vertical bar(p) = infinity, respectively. Then, the complete consistency of the least- squares estimator is obtained.

引用

页码：165 / 175

页数：11

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