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Please read my article for the full details of this project (Open Access):
Vargas Sepulveda, Mauricio. 2025. ‘Kendallknight: An R package for efficient implementation of Kendall’s correlation coefficient computation’. PLOS ONE 20 (6): e0326090. https://doi.org/10.1371/journal.pone.0326090.
This package implements a different algorithm from the one implemented in base R, and it reduces the complexity of the Kendall’s correlation coefficient from O(n^2) to O(n log n) resulting in a runtime of nano seconds or minutes instead of minutes or hours. This package is written in C++ and uses cpp11 to export the functions to R. See the vignette for the mathematical details.
If this software is useful to you, please consider donating on Buy Me A Coffee. All donations
will be used to continue improving kendallknight.
You can install the released version of kendallknight from CRAN with:
install.packages("kendallknight")You can install the development version of kendallknight like so:
remotes::install_github("pachadotdev/kendallknight")See the documentation and vignette: https://pacha.dev/kendallknight/.
Please note that the kendallknight project is released with a Contributor Code of Conduct. By contributing to this project, you agree to abide by its terms.
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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