A multidimensional version of the Kolmogorov–Smirnov test

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ID: 302896
1987
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Abstract
We discuss a generalization of the classical Kolmogorov–Smirnov test, which is suitable to analyse random samples defined in two or three dimensions. This test provides some improvements with respect to an earlier version proposed by Peacock. In particular: (i) it is faster, by a factor equal to the sample size, n, and then usable to analyse quite sizeable samples; (ii) it fully takes into account the dependence of the test statistics on the degree of correlation of data points and on the sample size; (iii) it allows for a generalization to the three-dimensional case which is still viable as regards computing time. Supported by a large number of Monte Carlo simulations, we are ensured that this test is sufficiently distribution-free for any practical purposes. We also give a simple analytic expression to make easier the calculation of the critical values of the test probability distribution.
Reference Key
openalex_W2073768640 Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors G. Fasano, A. Franceschini
Journal monthly notices of the royal astronomical society
Year 1987
DOI
10.1093/mnras/225.1.155
URL
https://doi.org/10.1093/mnras/225.1.155
Keywords Keywords not found

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