fasano.franceschini.test: An Implementation of a Multivariate KS Test in R

Connor Puritz, Elan Ness-Cohn, Rosemary Braun

Research output: Contribution to journalArticlepeer-review

Abstract

The Kolmogorov–Smirnov (KS) test is a nonparametric statistical test used to test for differences between univariate probability distributions. The versatility of the KS test has made it a cornerstone of statistical analysis across many scientific disciplines. However, the test proposed by Kolmogorov and Smirnov does not easily extend to multivariate distributions. Here we present the fasano.franceschini.test package, an R implementation of a multivariate two-sample KS test described by Fasano and Franceschini (1987). The fasano.franceschini.test package provides a test that is computationally efficient, applicable to data of any dimension and type (continuous, discrete, or mixed), and that performs competitively with similar R packages.

Original languageEnglish (US)
Pages (from-to)159-171
Number of pages13
JournalR Journal
Volume15
Issue number3
DOIs
StatePublished - 2023

ASJC Scopus subject areas

  • Statistics and Probability
  • Numerical Analysis
  • Statistics, Probability and Uncertainty

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