KStwobign Distribution#
This is the limiting distribution of the normalized maximum absolute differences between an
empirical distribution function, computed from \(n\) samples or observations,
and a comparison (or target) cumulative distribution function. (ksone is the distribution
of the unnormalized positive differences, \(D_n^+\).)
Writing \(D_n = \sup_t \left|F_{empirical,n}(t) - F_{target}(t)\right|\),
the normalization factor is \(\sqrt{n}\), and kstwobign is the limiting distribution
of the \(\sqrt{n} D_n\) values as \(n\rightarrow\infty\).
Note that \(D_n=\max(D_n^+, D_n^-)\), but \(D_n^+\) and \(D_n^-\) are not independent.
kstwobign can also be used with the differences between two empirical distribution functions,
for sets of observations with \(m\) and \(n\) samples respectively,
where \(m\) and \(n\) are âbigâ.
Writing \(D_{m,n} = \sup_t \left|F_{1,m}(t)-F_{2,n}(t)\right|\), where
\(F_{1,m}\) and \(F_{2,n}\) are the two empirical distribution functions, then
kstwobign is also the limiting distribution of the \(\sqrt{\frac{mn}{m+n}}D_{m,n}\) values,
as \(m,n\rightarrow\infty\) and \(m/n\rightarrow a \ne 0, \infty\).
There are no shape parameters, and the support is \(x\in\left[0,\infty\right)\).
References#
âKolmogorov-Smirnov testâ, Wikipedia https://en.wikipedia.org/wiki/Kolmogorov-Smirnov_test
Kolmogoroff, A. âConfidence Limits for an Unknown Distribution Function.ââ Ann. Math. Statist. 12 (1941), no. 4, 461â463.
Smirnov, N. âOn the estimation of the discrepancy between empirical curves of distribution for two independent samplesâ Bull. Math. Univ. Moscou., 2 (1039), 2-26.
Feller, W. âOn the Kolmogorov-Smirnov Limit Theorems for Empirical Distributions.â Ann. Math. Statist. 19 (1948), no. 2, 177â189. and âErrataâ Ann. Math. Statist. 21 (1950), no. 2, 301â302.
Implementation: scipy.stats.kstwobign