Detecting long-range correlations with detrended fluctuation analysis

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

Research output: Contribution to journalArticlepeer-review

1185 Scopus citations

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.

Original languageEnglish
Pages (from-to)441-454
Number of pages14
JournalPhysica A: Statistical Mechanics and its Applications
Volume295
Issue number3-4
DOIs
StatePublished - 15 Jun 2001

Bibliographical note

Funding Information:
This work was supported by the Deutsche Forschungsgemeinschaft and the project “KLIWA” of the Bayerische Landesamt für Wasserwirtschaft.

Keywords

  • Detrending
  • Long-range correlations
  • Time-series analysis

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