Abstract
We show that several time series analysis methods that are often used for detecting self-affine fractal scaling and determining Hurst exponents in data sets may lead to spurious results when applied to short discretized data series. We show that irregularities in the series, such as jumps or spikes (as are often found in geophysical data) may lead to spurious scaling and consequently to an incorrect determination of the Hurst exponent. We also illustrate the statistical error in measuring Hurst exponent in series where self-affine fractal scaling does exist. Users should be aware of these caveats when interpreting the results of short time series analysis.
Original language | English (US) |
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Pages (from-to) | 1085-1089 |
Number of pages | 5 |
Journal | Computers and Geosciences |
Volume | 29 |
Issue number | 9 |
DOIs | |
State | Published - Nov 2003 |
Externally published | Yes |
Bibliographical note
Funding Information:The authors wish to thank the Natural Science and Engineering Research Council of Canada and the Ministry of Training, Colleges and Universities of Ontario for financial support.
Copyright:
Copyright 2017 Elsevier B.V., All rights reserved.
Keywords
- Discontinuities
- Jumps
- Power spectrum
- Self-affine fractal scaling
- Spikes