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Estimation In Long‐Memory Time Series Model

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  • R. L. Kashyap
  • Kie‐Bum Eom

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.

Suggested Citation

  • R. L. Kashyap & Kie‐Bum Eom, 1988. "Estimation In Long‐Memory Time Series Model," Journal of Time Series Analysis, Wiley Blackwell, vol. 9(1), pages 35-41, January.
    • Handle: RePEc:bla:jtsera:v:9:y:1988:i:1:p:35-41
    DOI: 10.1111/j.1467-9892.1988.tb00451.x
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