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• W2510186736 abstract "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 $H_{rho}$ 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 $10^4$ 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." @default.
• W2510186736 created "2016-09-16" @default.
• W2510186736 creator A5083821951 @default.
• W2510186736 date "2017-09-01" @default.
• W2510186736 modified "2023-10-16" @default.
• W2510186736 title "Fractal approach towards power-law coherency to measure cross-correlations between time series" @default.
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• W2510186736 doi "https://doi.org/10.1016/j.cnsns.2017.02.018" @default.
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