Physics – Data Analysis – Statistics and Probability
Scientific paper
2002-02-27
Physica A 316, 87 (2002)
Physics
Data Analysis, Statistics and Probability
14 pages (RevTex) with 10 figures (eps)
Scientific paper
10.1016/S0378-4371(02)01383-3
We develop a method for the multifractal characterization of nonstationary time series, which is based on a generalization of the detrended fluctuation analysis (DFA). We relate our multifractal DFA method to the standard partition function-based multifractal formalism, and prove that both approaches are equivalent for stationary signals with compact support. By analyzing several examples we show that the new method can reliably determine the multifractal scaling behavior of time series. By comparing the multifractal DFA results for original series to those for shuffled series we can distinguish multifractality due to long-range correlations from multifractality due to a broad probability density function. We also compare our results with the wavelet transform modulus maxima (WTMM) method, and show that the results are equivalent.
Bunde Armin
Havlin Shlomo
Kantelhardt Jan W.
Koscielny-Bunde Eva
Stanley Eugene H.
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