Gralha's Alvarezramirez [2 articles]

Abstract

Detrended fluctuation analysis (DFA) is a scaling method commonly used for detecting long-range correlations in nonstationary time series. Applications range from financial time series to physiological data. However, as the removal of trends in DFA is based on discontinuous polynomial fitting, oscillations in the fluctuation function and significant errors in crossover locations can be introduced. To reduce the problems induced by discontinuous fitting, moving average (MA) methods have been proposed previously by Alesio et al. (Eur. J. Phys. B 27 (2002) ...

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 ...