scipy.special.smirnovi

scipy.special.smirnovi(n, p, out=None) = <ufunc 'smirnovi'>

Inverse to smirnov

Returns d such that smirnov(n, d) == p, the critical value corresponding to p.

Parameters
nint

Number of samples

pfloat array_like

Probability

outndarray, optional

Optional output array for the function results

Returns
scalar or ndarray

The value(s) of smirnovi(n, p), the critical values.

See also

smirnov

The Survival Function (SF) for the distribution

scipy.stats.ksone

Provides the functionality as a continuous distribution

kolmogorov, kolmogi

Functions for the two-sided distribution

scipy.stats.kstwobign

Two-sided Kolmogorov-Smirnov distribution, large n

Notes

smirnov is used by stats.kstest in the application of the Kolmogorov-Smirnov Goodness of Fit test. For historial reasons this function is exposed in scpy.special, but the recommended way to achieve the most accurate CDF/SF/PDF/PPF/ISF computations is to use the stats.ksone distribution.

Examples

>>> from scipy.special import smirnovi, smirnov
>>> n = 24
>>> deviations = [0.1, 0.2, 0.3]

Use smirnov to compute the complementary CDF of the Smirnov distribution for the given number of samples and deviations.

>>> p = smirnov(n, deviations)
>>> p
array([0.58105083, 0.12826832, 0.01032231])

The inverse function smirnovi(n, p) returns deviations.

>>> smirnovi(n, p)
array([0.1, 0.2, 0.3])