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

journal.r-project.org · 5,907 words · saved by 1 readers

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](https://CRAN.R-project.org/package=fasano.franceschini.test) package, an R implementation of a multivariate two-sample KS test described by @ff1987. 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.

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

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