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# CITATION file created with {cffr} R package
# See also: https://docs.ropensci.org/cffr/
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cff-version: 1.2.0
message: 'To cite package "kendallknight" in publications use:'
type: software
license: Apache-2.0
title: 'kendallknight: Efficient Implementation of Kendall''s Correlation Coefficient
  Computation'
version: 0.6.0
doi: 10.32614/CRAN.package.kendallknight
abstract: 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) <https://doi.org/10.2307/2282833>, Abrevaya (1999) <https://doi.org/10.1016/S0165-1765(98)00255-9>,
  Christensen (2005) <https://doi.org/10.1007/BF02736122> and Emara (2024) <https://learningcpp.org/>.
  This implementation is described in Vargas Sepulveda (2024) <https://doi.org/10.48550/arXiv.2408.09618>.
authors:
- family-names: Vargas Sepulveda
  given-names: Mauricio
  email: m.sepulveda@mail.utoronto.ca
  orcid: https://orcid.org/0000-0003-1017-7574
repository: https://CRAN.R-project.org/package=kendallknight
repository-code: https://github.com/pachadotdev/kendallknight
url: https://pacha.dev/kendallknight/
date-released: '2025-02-20'
contact:
- family-names: Vargas Sepulveda
  given-names: Mauricio
  email: m.sepulveda@mail.utoronto.ca
  orcid: https://orcid.org/0000-0003-1017-7574