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xiacf: Quantifying Nonlinear Dependence and Lead-Lag Dynamics via Chatterjee's Xi
Computes Chatterjee's non-parametric correlation coefficient for time series data. It extends the original metric to time series analysis by providing the Xi-Autocorrelation Function (Xi-ACF) and Xi-Cross-Correlation Function (Xi-CCF). The package allows users to test for non-linear dependence using Iterative Amplitude Adjusted Fourier Transform (IAAFT) surrogate data. Main functions include xi_acf() and xi_ccf() for computation, along with matrix extraction tools. Methodologies are based on Chatterjee (2021) <doi:10.1080/01621459.2020.1758115> and surrogate data testing methods by Schreiber and Schmitz (1996) <doi:10.1103/PhysRevLett.77.635>.
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Package details |
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| Author | Yasunori Watanabe [aut, cre] |
| Maintainer | Yasunori Watanabe <watanabe.yasunori@outlook.com> |
| License | MIT + file LICENSE |
| Version | 0.4.0 |
| Package repository | View on CRAN |
| Installation |
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