Hypothesis test
Kolmogorov-Smirnov Test
The Kolmogorov-Smirnov (KS) test is a nonparametric goodness-of-fit test that assesses whether a sample comes from a specified theoretical distribution, such as the normal or exponential. First formalised by Andrey Kolmogorov in 1933 and further developed by Nikolai Smirnov in 1948, it compares the empirical cumulative distribution function of the observed data against a target theoretical CDF and quantifies their maximum absolute deviation.
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Sources
- Kolmogorov, A. N. (1933). Sulla determinazione empirica di una legge di distribuzione. Giornale dell'Istituto Italiano degli Attuari, 4, 83–91. link ↗
- Smirnov, N. V. (1948). Table for estimating the goodness of fit of empirical distributions. Annals of Mathematical Statistics, 19(2), 279–281. DOI: 10.1214/aoms/1177730256 ↗
- Massey, F. J. (1951). The Kolmogorov-Smirnov test for goodness of fit. Journal of the American Statistical Association, 46(253), 68–78. DOI: 10.2307/2280095 ↗
- Conover, W. J. (1999). Practical Nonparametric Statistics (3rd ed.). Wiley. ISBN: 978-0471160687