Minimizing the effect of trends on detrended fluctuation analysis of long-range correlated noise

Radhakrishnan Nagarajan and Rajesh G. Kavasseri

Physica A: Statistical Mechanics and its Applications, 2005, vol. 354, issue C, 182-198

Abstract: Detrended fluctuation analysis (DFA) has been proposed as a robust technique to determine possible long-range correlations in power-law processes (Phys. Rev. E 49 (1994) 1685–1989). However, recent studies have reported the susceptibility of DFA to trends [(Phys. Rev. E 64 (2001) 011114–011133)] which give rise to spurious crossovers and prevent reliable estimation of the scaling exponents. Inspired by these reports, we propose a technique based on singular-value decomposition (SVD) of the trajectory matrix to minimize the effect of linear, power-law, periodic and also quasi-periodic trends superimposed on long-range correlated power-law noise. The effectiveness of the technique is demonstrated on publicly available data sets [(Phys. Rev. E 64 (2001) 011114–011133)].

Keywords: Detrended fluctuation analysis; Trends; Embedding; Singular-value decomposition (search for similar items in EconPapers)
Date: 2005
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Citations: View citations in EconPapers (8)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:354:y:2005:i:c:p:182-198

DOI: 10.1016/j.physa.2005.01.041

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