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Evaluating maximum likelihood estimation methods to determine the Hurst coeficient

机译:评估最大似然估计方法以确定赫斯特系数

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摘要

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.
机译:评估了在S-PLUS(S-MLE)中实现的用于估计赫斯特系数(H)的最大似然估计方法。 0.5 10 的fd过程,S-MLE给出H的偏差结果。提出了一种修正方法来纠正这种偏差。对于长度大于或等于2 11 的fd和fGn过程,它给出了H的可靠估计。

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