twosamples: Fast Permutation Based Two Sample Tests

Fast randomization based two sample tests. Testing the hypothesis that two samples come from the same distribution using randomization to create p-values. Included tests are: Kolmogorov-Smirnov, Kuiper, Cramer-von Mises, Anderson-Darling, Wasserstein, and DTS. The default test (two_sample) is based on the DTS test statistic, as it is the most powerful, and thus most useful to most users. The DTS test statistic builds on the Wasserstein distance by using a weighting scheme like that of Anderson-Darling. See the companion paper at <doi:10.48550/arXiv.2007.01360> or <> for details of that test statistic, and non-standard uses of the package (parallel for big N, weighted observations, one sample tests, etc). We also include the permutation scheme to make test building simple for others.

Version: 2.0.1
LinkingTo: cpp11
Suggests: testthat (≥ 3.0.0)
Published: 2023-06-23
DOI: 10.32614/CRAN.package.twosamples
Author: Connor Dowd ORCID iD [aut, cre]
Maintainer: Connor Dowd <cd at>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: yes
Materials: README NEWS
CRAN checks: twosamples results


Reference manual: twosamples.pdf


Package source: twosamples_2.0.1.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): twosamples_2.0.1.tgz, r-oldrel (arm64): twosamples_2.0.1.tgz, r-release (x86_64): twosamples_2.0.1.tgz, r-oldrel (x86_64): twosamples_2.0.1.tgz
Old sources: twosamples archive

Reverse dependencies:

Reverse imports: CAST, opdisDownsampling
Reverse suggests: FRESA.CAD, MARVEL, mlr3spatiotempcv


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