Abstract
The paper studies the behaviour of three different R/S statistic algorithms for Hurst-index estimation in self-similar and long-range dependent discrete time series. The accuracy of the algorithms under convergence and aggregation in time is obtained and compared. The results show that static blocks implementations of the R/S statistic present better accuracy than those based on a dynamic blocks implementation. The accuracy is obtained with the use of synthetic fGn and FARIMA(0,d,0) self-similar traces. The behavior of the algorithms for well-known LAN traces is also accomplished. Identification of current software tools and fields of science using the dynamic blocks approach is also accomplished.
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