Semiparametric analysis of long-range dependence in nonlinear regression

Ivanov, A and Leonenko, Nikolai N. ORCID: https://orcid.org/0000-0003-1932-4091 2008. Semiparametric analysis of long-range dependence in nonlinear regression. Journal of Statistical Planning and Inference 138 (6) , pp. 1733-1753. 10.1016/j.jspi.2007.06.027

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Abstract

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

Item Type:	Article
Date Type:	Publication
Status:	Published
Schools:	Mathematics
Subjects:	Q Science > QA Mathematics
Uncontrolled Keywords:	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
Publisher:	Elsevier
ISSN:	0378-3758
Last Modified:	18 Oct 2022 13:27
URI:	https://orca.cardiff.ac.uk/id/eprint/13959

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