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Tempting long-memory : on the interpretation of DFA results

  • We study the inference of long-range correlations by means of Detrended Fluctuation Analysis (DFA) and argue that power-law scaling of the fluctuation function and thus long-memory may not be assumed a priori but have to be established. This requires the investigation of the local slopes. We account for the variability characteristic for stochastic processes by calculating empirical confidence regions. Comparing a long-memory with a short-memory model shows that the inference of long-range correlations from a finite amount of data by means of DFA is not specific. We remark that scaling cannot be concluded from a straight line fit to the fluctuation function in a log-log representation. Furthermore, we show that a local slope larger than alpha=0.5 for large scales does not necessarily imply long memory. We also demonstrate, that it is not valid to conclude from a finite scaling region of the fluctuation function to an equivalent scaling region of the autocoffelation function. Finally, we review DFA results for the Prague temperatureWe study the inference of long-range correlations by means of Detrended Fluctuation Analysis (DFA) and argue that power-law scaling of the fluctuation function and thus long-memory may not be assumed a priori but have to be established. This requires the investigation of the local slopes. We account for the variability characteristic for stochastic processes by calculating empirical confidence regions. Comparing a long-memory with a short-memory model shows that the inference of long-range correlations from a finite amount of data by means of DFA is not specific. We remark that scaling cannot be concluded from a straight line fit to the fluctuation function in a log-log representation. Furthermore, we show that a local slope larger than alpha=0.5 for large scales does not necessarily imply long memory. We also demonstrate, that it is not valid to conclude from a finite scaling region of the fluctuation function to an equivalent scaling region of the autocoffelation function. Finally, we review DFA results for the Prague temperature data set and show that long-range correlations cannot not be concluded unambiguouslyshow moreshow less

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Metadaten
Author details:Douglas Maraun, H. W. Rust, Jens Timmer
ISSN:1023-5809
Publication type:Article
Language:English
Year of first publication:2004
Publication year:2004
Release date:2017/03/24
Source:Nonlinear Processes in Geophysics. - ISSN 1023-5809. - 11 (2004), 4, S. 495 - 503
Organizational units:Mathematisch-Naturwissenschaftliche Fakultät / Institut für Physik und Astronomie
Peer review:Referiert
Publishing method:Open Access
Institution name at the time of the publication:Mathematisch-Naturwissenschaftliche Fakultät / Institut für Physik
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