kendallknight: Efficient Implementation of Kendall's Correlation Coefficient Computation

The computational complexity of the implemented algorithm for Kendall's correlation is O(n log(n)), which is faster than the base R implementation with a computational complexity of O(n^2). For small vectors (i.e., less than 100 observations), the time difference is negligible. However, for larger vectors, the speed difference can be substantial and the numerical difference is minimal. The references are Knight (1966) <doi:10.2307/2282833>, Abrevaya (1999) <doi:10.1016/S0165-1765(98)00255-9>, Christensen (2005) <doi:10.1007/BF02736122> and Emara (2024) <https://learningcpp.org/>. This implementation is described in Vargas Sepulveda (2024) <doi:10.48550/arXiv.2408.09618>.

Version: 0.4.0
Depends: R (≥ 3.5.0)
Imports: stats
LinkingTo: cpp11
Suggests: knitr, rmarkdown, spelling, testthat (≥ 3.0.0)
Published: 2024-11-21
DOI: 10.32614/CRAN.package.kendallknight
Author: Mauricio Vargas Sepulveda ORCID iD [aut, cre], Loader Catherine [ctb] (original stirlerr implementations in C (2000)), Ross Ihaka [ctb] (original chebyshev_eval, gammafn and lgammacor implementations in C (1998))
Maintainer: Mauricio Vargas Sepulveda <m.sepulveda at mail.utoronto.ca>
BugReports: https://github.com/pachadotdev/capybara/issues
License: Apache License (≥ 2)
URL: https://pacha.dev/capybara/, https://github.com/pachadotdev/capybara
NeedsCompilation: yes
Language: en-US
Materials: README NEWS
CRAN checks: kendallknight results

Documentation:

Reference manual: kendallknight.pdf
Vignettes: details (source, R code)

Downloads:

Package source: kendallknight_0.4.0.tar.gz
Windows binaries: r-devel: kendallknight_0.4.0.zip, r-release: kendallknight_0.4.0.zip, r-oldrel: kendallknight_0.4.0.zip
macOS binaries: r-release (arm64): kendallknight_0.4.0.tgz, r-oldrel (arm64): kendallknight_0.4.0.tgz, r-release (x86_64): kendallknight_0.4.0.tgz, r-oldrel (x86_64): kendallknight_0.4.0.tgz

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