## Kolmogorov-Smirnov test

Purpose

Description

Macro Synopsis

Modules

Related Functions

References

### Purpose

Kolmogorov-Smirnov test

### Description

Using the K-S-Test, one can determine whether two data sets
are drawn from the same distribution. The function performs a significance test and compares the cumulative distribution functions of the given signals xA and xB, and calculates the maximum distance D between them.
What makes the K-S-test very useful is its invariance under
reparametrization of x, i.e. the x axis can be locally stretched or
shifted without changing D.

The results of "Kolmogorov-Smirnov test", applied to two signals xA and xB, will appear
in the Dataplore ® message window.
Return parameters of "Kolmogorov-Smirnov test" are:

- the maximum distance D
- the significance
`signif`, i.e. the probability [0..1] of randomly equal distributions, where small values indicate significant differences in the cumulative distribution functions.

### Macro Synopsis

`KSTest([xA,xB],&D,&signif);`

signal xA,xB;

float D,signif;

### Modules

Statistics

### Related Functions

BDS test, Test for different histograms,
Test for different means, Test for different variances,
Test for non-normal-distributed data,
Test for non-white-noise,
Test for the mean of a Gaussian, Test for the variance of a Gaussian,
Wilcoxon test

### References

Hollander/Wolfe [13], Lehmann [36]