1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54
|
.. _continuous-kstwobign:
KStwobign Distribution
======================
This is the limiting distribution of the normalized maximum absolute differences between an
empirical distribution function, computed from :math:`n` samples or observations,
and a comparison (or target) cumulative distribution function. (``ksone`` is the distribution
of the unnormalized positive differences, :math:`D_n^+`.)
Writing :math:`D_n = \sup_t \left|F_{empirical,n}(t) - F_{target}(t)\right|`,
the normalization factor is :math:`\sqrt{n}`, and ``kstwobign`` is the limiting distribution
of the :math:`\sqrt{n} D_n` values as :math:`n\rightarrow\infty`.
Note that :math:`D_n=\max(D_n^+, D_n^-)`, but :math:`D_n^+` and :math:`D_n^-` are not independent.
``kstwobign`` can also be used with the differences between two empirical distribution functions,
for sets of observations with :math:`m` and :math:`n` samples respectively,
where :math:`m` and :math:`n` are "big".
Writing :math:`D_{m,n} = \sup_t \left|F_{1,m}(t)-F_{2,n}(t)\right|`, where
:math:`F_{1,m}` and :math:`F_{2,n}` are the two empirical distribution functions, then
``kstwobign`` is also the limiting distribution of the :math:`\sqrt{\left(\frac{mn}{m+n}\right)D_{m,n}}` values,
as :math:`m,n\rightarrow\infty` and :math:`m/n\rightarrow a \ne 0, \infty`.
There are no shape parameters, and the support is :math:`x\in\left[0,\infty\right)`.
.. math::
:nowrap:
\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`
|