Detrending fluctuation analysis based on high-pass filtering

Eduardo Rodriguez, Juan Carlos Echeverría and Jose Alvarez-Ramirez

Physica A: Statistical Mechanics and its Applications, 2007, vol. 375, issue 2, 699-708

Abstract: Detrended fluctuation analysis (DFA) is a scaling method commonly used for detecting long-range correlations in non-stationary time series. The DFA method uses a trend based on polynomial fitting to extract and quantify fluctuations at different time scales. Basically, such procedure acts as a (non-dynamical) high-pass filter that removes time series components below a given time scale. As an alternative to the polynomial fitting approach, this paper proposes a DFA method based on well-known high-pass filters (e.g., Butterworth, elliptic, etc.). Numerical results show that the proposed DFA approach yields results similar to traditional DFA method. Maybe, the main advantage of the proposed DFA method is that efficient implementations of high-pass filters are available commercially.

Keywords: Fluctuations analysis; DFA; High-pass filtering (search for similar items in EconPapers)
Date: 2007
References: View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:375:y:2007:i:2:p:699-708

DOI: 10.1016/j.physa.2006.10.038

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