0473066 20240103213846.620170316235959.9 85014923760 000399513200015 10.1016/j.cnsns.2017.02.018 Fractal approach towards power-law coherency to measure cross-correlations between time series 8 s. P cav_un_epca*03149331007-5704Communications in Nonlinear Science and Numerical Simulation501 (2017)193-200Elsevier power-law coherency power-law cross-correlations correlations cav_un_auth*0256902 Krištoufek Ladislav Ekonometrie Department of Econometrics E E UTIA-B Department of Econometrics CZ Ústav teorie informace a automatizace AV ČR, v. v. i. http://library.utia.cas.cz/separaty/2017/E/kristoufek-0473066.pdf cav_un_auth*0303546 GP14-11402P GA ČR CZ We focus on power-law coherency as an alternative approach towards studying power law cross-correlations between simultaneously recorded time series. To be able to study empirical data, we introduce three estimators of the power-law coherency parameter Hp based on popular techniques usually utilized for studying power-law cross-correlations detrended cross-correlation analysis (DCCA), detrending moving-average cross-correlation analysis (DMCA) and height cross-correlation analysis (HXA). In the finite sample properties study, we focus on the bias, variance and mean squared error of the estimators. We find that the DMCA-based method is the safest choice among the three. The HXA method is reasonable for long time series with at least 104 observations, which can be easily attainable in some disciplines but problematic in others. The DCCA-based method does not provide favorable properties which even deteriorate with an increasing time series length. The paper opens a new venue towards studying cross-correlations between time series. AH 50000 50200 50202 2018 1 RVO:67985556 http://hdl.handle.net/11104/0271360 S 1 Article Mathematics Applied|Mathematics Interdisciplinary Applications|Mechanics|Physics Fluids Plasmas|Physics Mathematical 1 Article Mathematics Applied|Mathematics Interdisciplinary Applications|Mechanics|Physics Fluids Plasmas|Physics Mathematical 1 Article Mathematics Applied|Mathematics Interdisciplinary Applications|Mechanics|Physics Fluids Plasmas|Physics Mathematical MECHANICS|MATHEMATICS.APPLIED|PHYSICS.MATHEMATICAL|MATHEMATICS.INTERDISCIPLINARYAPPLICATIONS|PHYSICS.FLUIDS&PLASMAS 3.239 1.791 5.2 0.0217 0.859 10779 1.372 2.869 358 Q1 71.568 92.6 Q2 Q1 1.89 Q1 97.421 2017 85014923760 SCOPUS PUBMED 000399513200015 WOS cav_un_epca*0314933 Communications in Nonlinear Science and Numerical Simulation 1007-5704 1878-7274 Roč. 50 č. 1 2017 193 200 Elsevier