ESTIMATION IN LONG‐MEMORY TIME SERIES MODEL
- 1 January 1988
- journal article
- Published by Wiley in Journal of Time Series Analysis
- Vol. 9 (1) , 35-41
- https://doi.org/10.1111/j.1467-9892.1988.tb00451.x
Abstract
This study deals with the parameter estimation in long‐memory time series models. An unbiased and consistent estimator is proposed. The proposed estimator is based on a least‐squares method in the frequency domain, and it is computationally simple. Also, the Cramer–Rao lower bound is derived. The mean‐square error of the proposed estimator is order of O(1/N), where N is the number of samples. The accuracy of the estimates is verified using synthetic long‐memory time series data.Keywords
This publication has 7 references indexed in Scilit:
- Parameter Estimation and Hypothesis Testing in Spectral Analysis of Stationary Time SeriesPublished by Springer Nature ,1986
- Synthesis and Estimation of Random Fields Using Long-Correlation ModelsPublished by Institute of Electrical and Electronics Engineers (IEEE) ,1984
- Time Series: Data Analysis and Theory.Published by JSTOR ,1981
- Fractional differencingBiometrika, 1981
- Fractional DifferencingBiometrika, 1981
- AN INTRODUCTION TO LONG‐MEMORY TIME SERIES MODELS AND FRACTIONAL DIFFERENCINGJournal of Time Series Analysis, 1980
- Stochastic Modelling of Riverflow Time SeriesJournal of the Royal Statistical Society. Series A (General), 1977