منابع مشابه
Estimating the Hurst Exponent
The Hurst Exponent is a dimensionless estimator for the self-similarity of a time series. Initially defined by Harold Edwin Hurst to develop a law for regularities of the Nile water level, it now has applications in medicine and finance. Meaningful values are in the range [0, 1]. Different methods for estimating the Hurst Exponent have been evaluated: The classical “Rescaled Range” method devel...
متن کاملThe graphical methods for estimating Hurst parameter of self-similar network traffic
The modern high-speed network traffic exhibits the self-similarity. The degree of selfsimilarity is measured by the Hurst parameter. In this paper are used two graphical techniques for estimating Hurst parameter of pseudo-random self-similar sequences, based on the fractional Gaussian noise (FGN) method. The analyses show that the FGN method always produces self-similar sequences, with relative...
متن کاملHurst Parameter Estimation for Epileptic Seizure Detection
Estimation of the Hurst parameter provides information about the memory range or correlations (long vs. short) of processes (time-series). A new application for the Hurst parameter, real-time event detection, is identified. Hurst estimates using rescaled range, dispersional and bridgedetrended scaled windowed variance analyses of seizure time-series recorded from human subjects reliably detect ...
متن کاملHurst Parameter Estimation Using Artificial Neural Networks
The Hurst parameter captures the amount of long-range dependence (LRD) in a time series. There are several methods to estimate the Hurst parameter, being the most popular: the variance-time plot, the R/S plot, the periodogram, and Whittle’s estimator. The first three are graphical methods, and the estimation accuracy depends on how the plot is interpreted and calculated. In contrast, Whittle’s ...
متن کاملA Practical Guide to Measuring the Hurst Parameter
This paper describes, in detail, techniques for measuring the Hurst parameter. Measurements are given on artificial data both in a raw form and corrupted in various ways to check the robustness of the tools in question. Measurements are also given on real data, both new data sets and well-studied data sets. All data and tools used are freely available for download along with simple “recipes” wh...
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ژورنال
عنوان ژورنال: Statistical Inference for Stochastic Processes
سال: 2007
ISSN: 1387-0874,1572-9311
DOI: 10.1007/s11203-005-0059-6