  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 multidimensional distributions. Here we
present the fasano.franceschini.test package, an R implementation of a
multidimensional 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.
