The R Journal: article published in 2021, volume 13:2

diproperm: An R Package for the DiProPerm Test
Andrew G. Allmon, J.S. Marron and Michael G. Hudgens , The R Journal (2021) 13:2, pages 266-272.

Abstract High-dimensional low sample size (HDLSS) data sets frequently emerge in many biomedical applications. The direction-projection-permutation (DiProPerm) test is a two-sample hypothesis test for comparing two high-dimensional distributions. The DiProPerm test is exact, i.e., the type I error is guaranteed to be controlled at the nominal level for any sample size, and thus is applicable in the HDLSS setting. This paper discusses the key components of the DiProPerm test, introduces the diproperm R package, and demonstrates the package on a real-world data set.

Received: 2020-10-30; online 2021-08-17, supplementary material, (840 B)
CRAN packages: diproperm, DWDLargeR, Matrix
CRAN Task Views implied by cited CRAN packages: Econometrics, Multivariate, NumericalMathematics

This article and supplementary materials are licensed under a Creative Commons Attribution 4.0 International license.

@article{RJ-2021-072,
  author = {Andrew G. Allmon and J.S. Marron and Michael G. Hudgens},
  title = {{diproperm: An R Package for the DiProPerm Test}},
  year = {2021},
  journal = {{The R Journal}},
  doi = {10.32614/RJ-2021-072},
  url = {https://doi.org/10.32614/RJ-2021-072},
  pages = {266--272},
  volume = {13},
  number = {2}
}