Effect of nonstationarities on detrended fluctuation analysis.pdfVIP

Effect of nonstationarities on detrended fluctuation analysis 1 1,2 1 1 Zhi Chen , Plamen Ch. Ivanov , Kun Hu , H. Eugene Stanley 1 Center for Polymer Studies and Department of Physics, Boston University, Boston, Massachusetts 02215 2 Harvard Medical School, Beth Israel Deaconess Medical Center, Boston, Massachusetts 02215 Detrended fluctuation analysis (DFA) is a scaling analysis method used to quantify long-range 2 power-law correlations in signals. Many physical and biological signals are “noisy”, heterogeneous 0 and exhibit different types of nonstationarities, which can affect the correlation properties of these 0 signals. We systematically study the effects of three types of nonstationarities often encountered 2 in real data. Specifically, we consider nonstationary sequences formed in three ways: (i) stitching r together segments of data obtained from discontinuous experimental recordings, or removing some p noisy and unreliable parts from continuous recordings and stitching together the remaining parts A — a “cutting” procedure commonly used in preparing data prior to signal analysis; (ii) adding to a signal with known correlations a tunable concentration of random outliers or spikes with different 5 amplitude, and (iii) generating a signal comprised of segments with different properties — e.g. 1 different standard deviations or different correlation exponents. We compare the d