Loading [MathJax]/jax/input/TeX/config.js
scipy 1.10.1 Pypi GitHub Homepage
Other Docs

ParametersReturns
kolmogn(n, x, cdf=True)

The two-sided Kolmogorov-Smirnov distribution has as its CDF Pr(D_n <= x), for a sample of size n drawn from a distribution with CDF F(t), where D_n &= sup_t |F_n(t) - F(t)|, and F_n(t) is the Empirical Cumulative Distribution Function of the sample.

Parameters

n : integer, array_like

the number of samples

x : float, array_like

The K-S statistic, float between 0 and 1

cdf : bool, optional

whether to compute the CDF(default=true) or the SF.

Returns

cdf : ndarray

CDF (or SF it cdf is False) at the specified locations.

The return value has shape the result of numpy broadcasting n and x.

Computes the CDF for the two-sided Kolmogorov-Smirnov distribution.

Examples

See :

Local connectivity graph

Hover to see nodes names; edges to Self not shown, Caped at 50 nodes.

Using a canvas is more power efficient and can get hundred of nodes ; but does not allow hyperlinks; , arrows or text (beyond on hover)

SVG is more flexible but power hungry; and does not scale well to 50 + nodes.

All aboves nodes referred to, (or are referred from) current nodes; Edges from Self to other have been omitted (or all nodes would be connected to the central node "self" which is not useful). Nodes are colored by the library they belong to, and scaled with the number of references pointing them


GitHub : /scipy/stats/_ksstats.py#501
type: <class 'function'>
Commit: