Detecting and quantifying cross-correlations by analogous multifractal height cross-correlation analysis
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DOI: 10.1016/j.physa.2015.10.096
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Cited by:
- Li, Bao-Gen & Ling, Dian-Yi & Yu, Zu-Guo, 2021. "Multifractal temporally weighted detrended partial cross-correlation analysis of two non-stationary time series affected by common external factors," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 573(C).
- Wang, Fang & Han, Guosheng, 2023. "Coupling correlation adaptive detrended analysis for multiple nonstationary series," Chaos, Solitons & Fractals, Elsevier, vol. 177(C).
- Wang, Fang & Wang, Lin & Chen, Yuming, 2022. "Multi-affine visible height correlation analysis for revealing rich structures of fractal time series," Chaos, Solitons & Fractals, Elsevier, vol. 157(C).
- Zhang, Zehui & Wang, Fang & Shen, Luming & Xie, Qiang, 2022. "Multiscale time-lagged correlation networks for detecting air pollution interaction," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 602(C).
- Wang, Fang & Wang, Lin & Chen, Yuming, 2018. "Quantifying the range of cross-correlated fluctuations using a q–L dependent AHXA coefficient," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 494(C), pages 454-464.
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Keywords
Cross-correlation; Analogous multifractal height cross-correlation analysis; Analogous multifractal height cross-correlation coefficient;All these keywords.
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