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.
翻译:Kolmogorov-Smirnov (KS) 测试是用于测试单体概率分布差异的非参数统计测试。 KS 测试的多功能性使它成为许多科学学科统计分析的基石。 然而, Kolmogorov 和 Smirnov 提出的测试并不轻易延伸到多维分布。 这里我们展示了 Fasano.franceschini. test 软件包,这是Fasano 和Francschini (1987年) 描述的多维两样KS 测试的R 。 Fasano.franceschini. test 软件包提供了一种计算效率高的测试,适用于任何层面和类型(连续的、离散的或混合的)数据,并且与类似的R 软件包具有竞争性。