Detecting long-range correlations with detrended fluctuation analysis

Jan W Kantelhardt, Eva Koscielny-Bunde, Henio H.A Rego, Shlomo Havlin and Armin Bunde

Physica A: Statistical Mechanics and its Applications, 2001, vol. 295, issue 3, 441-454

Abstract: We examine the detrended fluctuation analysis (DFA), which is a well-established method for the detection of long-range correlations in time series. We show that deviations from scaling which appear at small time scales become stronger in higher orders of DFA, and suggest a modified DFA method to remove them. The improvement is necessary especially for short records that are affected by non-stationarities. Furthermore, we describe how crossovers in the correlation behavior can be detected reliably and determined quantitatively and show how several types of trends in the data affect the different orders of DFA.

Keywords: Time-series analysis; Long-range correlations; Detrending (search for similar items in EconPapers)
Date: 2001
References: View complete reference list from CitEc
Citations: View citations in EconPapers (169)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:295:y:2001:i:3:p:441-454

DOI: 10.1016/S0378-4371(01)00144-3

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