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KStwobign Distribution
docs/tutorial:stats:continuous_kstwobign
This is the limiting distribution of the normalized maximum absolute differences between an empirical distribution function, computed from samples or observations, and a comparison (or target) cumulative distribution function. (ksone is the distribution of the unnormalized positive differences, .)
Writing , the normalization factor is , and kstwobign is the limiting distribution of the values as .
Note that , but and are not independent.
kstwobign can also be used with the differences between two empirical distribution functions, for sets of observations with and samples respectively, where and are "big". Writing , where and are the two empirical distribution functions, then kstwobign is also the limiting distribution of the values, as and .
There are no shape parameters, and the support is .
\begin{eqnarray*} F\left(x\right) & = & 1 - 2 \sum_{k=1}^{\infty} (-1)^{k-1} e^{-2k^2 x^2}\\
& = & \frac{\sqrt{2\pi}}{x} \sum_{k=1}^{\infty} e^{-(2k-1)^2 \pi^2/(8x^2)}\\
& = & 1 - \textrm{scipy.special.kolmogorov}(n, x) \\
f\left(x\right) & = & 8x \sum_{k=1}^{\infty} (-1)^{k-1} k^2 e^{-2k^2 x^2} \end{eqnarray*}References
"Kolmogorov-Smirnov test", Wikipedia https://en.wikipedia.org/wiki/Kolmogorov-Smirnov_test
Kolmogoroff, A. "Confidence Limits for an Unknown Distribution Function."" Ann. Math. Statist. 12 (1941), no. 4, 461--463.
Smirnov, N. "On the estimation of the discrepancy between empirical curves of distribution for two independent samples" Bull. Math. Univ. Moscou., 2 (1039), 2-26.
Feller, W. "On the Kolmogorov-Smirnov Limit Theorems for Empirical Distributions." Ann. Math. Statist. 19 (1948), no. 2, 177--189. and "Errata" Ann. Math. Statist. 21 (1950), no. 2, 301--302.
Implementation: scipy.stats.kstwobign