Pith. sign in

REVIEW

Detecting Long-range Correlations with Detrended Fluctuation Analysis

Not yet reviewed by Pith; the record is open.

Re-run · record.json Download PDF Read on arXiv ↗

This paper has not been read by Pith yet. Machine review is queued; the pith claim, tier, and objections will appear here once it completes.

SPECIMEN: schema-true, not a live event

T0 review · schema-true

One-sentence machine reading of the paper's core claim.

pith:XXXXXXXX · record.json · timestamp

arxiv cond-mat/0102214 v1 pith:GJ4S2BIO submitted 2001-02-12 cond-mat.stat-mech

Jan W. Kantelhardt , Eva Koscielny-Bunde , Henio H. A. Rego , Shlomo Havlin , Armin Bunde This is my paper · ORCID
classification cond-mat.stat-mech
keywords analysiscorrelationsdetrendedfluctuationlong-rangemethodorderstime
verification ladder T0 review T1 audit T2 compute T3 formal
0 comments
read the original 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 that 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.

Discussion (0). Continue with ORCID to comment.

Pith tools