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The estimation of continuous parameter long-memory time series models

Chambers, MJ (1996) 'The estimation of continuous parameter long-memory time series models.' Econometric Theory, 12 (2). 374 - 390. ISSN 0266-4666

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Abstract

A class of univariate fractional ARIMA models with a continuous time parameter is developed for the purpose of modeling long-memory time series. The spectral density of discretely observed data is derived for both point observations (stock variables) and integral observations (flow variables). A frequency domain maximum likelihood method is proposed for estimating the long-memory parameter and is shown to be consistent and asymptotically normally distributed, and some issues associated with the computation of the spectral density are explored. © 1996 Cambridge University Press.

Item Type: Article
Subjects: H Social Sciences > HB Economic Theory
Divisions: Faculty of Social Sciences > Economics, Department of
Depositing User: Jim Jamieson
Date Deposited: 07 Jul 2012 22:18
Last Modified: 17 Aug 2017 18:11
URI: http://repository.essex.ac.uk/id/eprint/2781

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