Chambers, Marcus J (1996) The Estimation of Continuous Parameter Long-Memory Time Series Models. Econometric Theory, 12 (2). pp. 374-390. DOI https://doi.org/10.1017/s0266466600006642
Chambers, Marcus J (1996) The Estimation of Continuous Parameter Long-Memory Time Series Models. Econometric Theory, 12 (2). pp. 374-390. DOI https://doi.org/10.1017/s0266466600006642
Chambers, Marcus J (1996) The Estimation of Continuous Parameter Long-Memory Time Series Models. Econometric Theory, 12 (2). pp. 374-390. DOI https://doi.org/10.1017/s0266466600006642
Abstract
<jats:p>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 longmemory parameter and is shown to be consistent and asymptotically normally distributed, and some issues associated with the computation of the spectral density are explored.</jats:p>
Item Type: | Article |
---|---|
Subjects: | H Social Sciences > HB Economic Theory |
Divisions: | Faculty of Social Sciences Faculty of Social Sciences > Economics, Department of |
SWORD Depositor: | Unnamed user with email elements@essex.ac.uk |
Depositing User: | Unnamed user with email elements@essex.ac.uk |
Date Deposited: | 07 Jul 2012 22:18 |
Last Modified: | 30 Oct 2024 20:02 |
URI: | http://repository.essex.ac.uk/id/eprint/2781 |