Evaluating maximum likelihood estimation methods to determine the Hurst coefficient
A maximum likelihood estimation method implemented in S-PLUS (S-MLE) to estimate the Hurst coefficient (H) is evaluated. The Hurst coefficient, with 0.5<H<1, characterizes long memory time series by quantifying the rate of decay of the autocorrelation function. S-MLE was developed to estimate H for fractionally differenced (fd) processes. However, in practice it is difficult to distinguish between fd processes and fractional Gaussian noise (fGn) processes. Thus, the method is evaluated for estimating H for both fd and fGn processes. S-MLE gave biased results of H for fGn processes of any length and for fd processes of lengths less than 210. A modified method is proposed to correct for this bias. It gives reliable estimates of H for both fd and fGn processes of length greater than or equal to 211.
Year of publication: |
1999
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Authors: | Kendziorski, C.M ; Bassingthwaighte, J.B ; Tonellato, P.J |
Published in: |
Physica A: Statistical Mechanics and its Applications. - Elsevier, ISSN 0378-4371. - Vol. 273.1999, 3, p. 439-451
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Publisher: |
Elsevier |
Subject: | Time series analysis | Autocorrelation function | Fractional ARIMA process | Fractional Gaussian noise | Hurst coefficient | Long memory |
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