dorsal/arxiv
View SchemaEffect of nonstationarities on detrended fluctuation analysis
| Authors | Zhi Chen, Plamen Ch. Ivanov, Kun Hu, H. Eugene Stanley |
|---|---|
| Categories | |
| ArXiv ID | physics/0111103 |
| URL | https://arxiv.org/abs/physics/0111103 |
| DOI | 10.1103/PhysRevE.65.041107 |
| Journal | Phys. Rev. E, 65 (2002) 041107(15) |
Abstract
Detrended fluctuation analysis (DFA) is a scaling analysis method used to quantify long-range power-law correlations in signals. Many physical and biological signals are ``noisy'', heterogeneous and exhibit different types of nonstationarities, which can affect the correlation properties of these signals. We systematically study the effects of three types of nonstationarities often encountered in real data. Specifically, we consider nonstationary sequences formed in three ways: (i) stitching together segments of data obtained from discontinuous experimental recordings, or removing some noisy and unreliable parts from continuous recordings and stitching together the remaining parts -- 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 amplitude, and (iii) generating a signal comprised of segments with different properties -- e.g. different standard deviations or different correlation exponents. We compare the difference between the scaling results obtained for stationary correlated signals and correlated signals with these three types of nonstationarities.
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"abstract": "Detrended fluctuation analysis (DFA) is a scaling analysis method used to\nquantify long-range power-law correlations in signals. Many physical and\nbiological signals are ``noisy\u0027\u0027, heterogeneous and exhibit different types of\nnonstationarities, which can affect the correlation properties of these\nsignals. We systematically study the effects of three types of\nnonstationarities often encountered in real data. Specifically, we consider\nnonstationary sequences formed in three ways: (i) stitching together segments\nof data obtained from discontinuous experimental recordings, or removing some\nnoisy and unreliable parts from continuous recordings and stitching together\nthe remaining parts -- a ``cutting\u0027\u0027 procedure commonly used in preparing data\nprior to signal analysis; (ii) adding to a signal with known correlations a\ntunable concentration of random outliers or spikes with different amplitude,\nand (iii) generating a signal comprised of segments with different properties\n-- e.g. different standard deviations or different correlation exponents. We\ncompare the difference between the scaling results obtained for stationary\ncorrelated signals and correlated signals with these three types of\nnonstationarities.",
"arxiv_id": "physics/0111103",
"authors": [
"Zhi Chen",
"Plamen Ch. Ivanov",
"Kun Hu",
"H. Eugene Stanley"
],
"categories": [
"physics.data-an",
"cond-mat"
],
"doi": "10.1103/PhysRevE.65.041107",
"journal_ref": "Phys. Rev. E, 65 (2002) 041107(15)",
"title": "Effect of nonstationarities on detrended fluctuation analysis",
"url": "https://arxiv.org/abs/physics/0111103"
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