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.
Package details |
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Author | Connor Dowd [aut, cre] (<https://orcid.org/0000-0002-9782-0931>) |
Maintainer | Connor Dowd <cd@codowd.com> |
License | GPL (>= 2) |
Version | 2.0.1 |
URL | https://twosampletest.com https://github.com/cdowd/twosamples |
Package repository | View on CRAN |
Installation |
Install the latest version of this package by entering the following in R:
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