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Robust Statistical Detection of Power-Law Cross-Correlation

Authors
Blythe, Duncan A. J.Nikulin, Vadim V.Mueller, Klaus-Robert
Issue Date
2-6월-2016
Publisher
NATURE PUBLISHING GROUP
Citation
SCIENTIFIC REPORTS, v.6
Indexed
SCIE
SCOPUS
Journal Title
SCIENTIFIC REPORTS
Volume
6
URI
https://scholar.korea.ac.kr/handle/2021.sw.korea/88367
DOI
10.1038/srep27089
ISSN
2045-2322
Abstract
We show that widely used approaches in statistical physics incorrectly indicate the existence of power-law cross-correlations between financial stock market fluctuations measured over several years and the neuronal activity of the human brain lasting for only a few minutes. While such cross-correlations are nonsensical, no current methodology allows them to be reliably discarded, leaving researchers at greater risk when the spurious nature of cross-correlations is not clear from the unrelated origin of the time series and rather requires careful statistical estimation. Here we propose a theory and method (PLCC-test) which allows us to rigorously and robustly test for power-law cross-correlations, correctly detecting genuine and discarding spurious cross-correlations, thus establishing meaningful relationships between processes in complex physical systems. Our method reveals for the first time the presence of power-law cross-correlations between amplitudes of the alpha and beta frequency ranges of the human electroencephalogram.
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