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

arXiv: https://arxiv.org/abs/2106.10539 · HTML: https://mlsanity.com/paper/2106.10539/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 19 Jun 2021.

## Built on by (most cited first, 1 of 1)

- [Spectral Regularized Kernel Goodness-of-Fit Tests](https://mlsanity.com/paper/2308.04561/) (2023)

## Abstract (arXiv)

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.