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 <arXiv:2007.01360> or <https://codowd.com/public/DTS.pdf> 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.

Getting started

Package details

AuthorConnor Dowd [aut, cre] (<https://orcid.org/0000-0002-9782-0931>)
MaintainerConnor Dowd <cd@codowd.com>
LicenseGPL (>= 2)
Version2.0.1
URL https://twosampletest.com https://github.com/cdowd/twosamples
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:
install.packages("twosamples")

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twosamples documentation built on July 9, 2023, 7:30 p.m.