Consistency for the least squares estimator in nonlinear regression model

被引：11

作者：

Hu, SH ^{[1
]}

机构：

[1] Anhui Univ, Dept Math, Hefei 230039, Peoples R China

来源：

STATISTICS & PROBABILITY LETTERS | 2004年 / 67卷 / 02期

基金：

中国国家自然科学基金;

关键词：

nonlinear regression model; least-squares estimator; dependent error; consistency; consistency rate;

D O I：

10.1016/j.spl.2003.11.020

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：

The consistency problems of the least-squares estimator theta(n) for parameter theta in nonlinear regression model are resolved perfectly. Assuming that the tth absolute moments of the model errors are finite, for t greater than or equal to 2 and the errors satisfy general dependent conditions, we obtain the same probability inequality as that in Ivanov (Theory Probab. Appl. 21 (1976) 557) which has independent identically distributed errors; for 1 < t < 2, we first obtain weak consistency and weak consistency rate of On. (C) 2003 Elsevier B.V. All rights reserved.

引用

页码：183 / 192

页数：10

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