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:	05 Feb 2019 18:15
URI:	http://repository.essex.ac.uk/id/eprint/2781

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