Semiparametric analysis of long-range dependence in nonlinear regression

被引：22

作者：

Ivanov, A. V. ^{[2
]}

Leonenko, N. N. ^{[1
]}

机构：

[1] Cardiff Univ, Cardiff Sch Math, Cardiff CF24 4AG, S Glam, Wales

[2] Natl Tech Univ, Kyiv Polytech Inst, UA-03056 Kiev, Ukraine

来源：

JOURNAL OF STATISTICAL PLANNING AND INFERENCE | 2008年 / 138卷 / 06期

基金：

英国工程与自然科学研究理事会; 澳大利亚研究理事会;

关键词：

asymptotic inference; consistency; dependence parameter; least squares estimate (LSE); long-range dependence; non-linear regression; vector parameter; rate of convergence; semi-parametric estimate; time-domain estimate;

D O I：

10.1016/j.jspi.2007.06.027

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 establishes consistency and asymptotic distribution theory for the least squares estimate of a vector parameter of non-linear regression with long-range dependent noise. A covariance-based estimate of the memory parameter is proposed. The consistency of the estimate is established. (c) 2007 Elsevier B.V. All rights reserved.

引用

页码：1733 / 1753

页数：21

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