QML estimators in linear regression models with functional coefficient autoregressive processes
type: Item
instance of: scholarly article
title: QML estimators in linear regression models with functional coefficient autoregressive processes
zbMATH Open document ID: 1189.62111
DOI: 10.1155/2010/956907
published in: Mathematical Problems in Engineering
publication date: 2010-06-29T00:00:00Z
full work available at URL: https://eudml.org/doc/227407
review text: Summary: This paper studies a linear regression model, whose errors are functional coefficient autoregressive processes. Firstly, the quasi-maximum likelihood (QML) estimators of some unknown parameters are given. Secondly, under general conditions, the asymptotic properties (existence, consistency, and asymptotic distributions) of the QML estimators are investigated. These results extend those of \textit{R. A. Maller} [Stochastic Processes Appl. 105, No. 1, 33--67(2003; Zbl 1075.60507)], \textit{J. S. White} [Ann. Math. Stat. 30, 831--834 (1959; Zbl 0133.42403)], \textit{P. J. Brockwell} and \textit{R. A. Davis} [Time series: theory and methods. NY: Springer (1987; Zbl 0604.62083)], and so on. Lastly, the validity and feasibility of the method are illuminated by a simulation example and a real example.
Mathematics Subject Classification ID: 62J05
Mathematics Subject Classification ID: 62M10
Mathematics Subject Classification ID: 62F10
zbMATH DE Number: 5728527
Wikidata QID: Q58653439
author: Hongchang Hu
MaRDI profile type: Publication
OpenAlex ID: W1995726632
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description: scientific article; zbMATH DE number 5728527