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>.
| Version: |
0.4.0 |
| Imports: |
dplyr (≥ 1.1.4), doFuture, foreach, future, ggplot2 (≥
4.0.1), latex2exp, progressr, Rcpp (≥ 1.1.0), stats |
| LinkingTo: |
Rcpp, RcppArmadillo |
| Suggests: |
testthat (≥ 3.3.2) |
| Published: |
2026-04-16 |
| DOI: |
10.32614/CRAN.package.xiacf (may not be active yet) |
| Author: |
Yasunori Watanabe [aut, cre] |
| Maintainer: |
Yasunori Watanabe <watanabe.yasunori at outlook.com> |
| License: |
MIT + file LICENSE |
| NeedsCompilation: |
yes |
| Citation: |
xiacf citation info |
| Materials: |
README, NEWS |
| CRAN checks: |
xiacf results |
Documentation:
Downloads:
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