PetscProbComputeKSStatistic#

Compute the Kolmogorov-Smirnov statistic for the empirical distribution for an input vector, compared to an analytic CDF.

Synopsis#

#include "petscdt.h" 
PetscErrorCode PetscProbComputeKSStatistic(Vec v, PetscProbFunc cdf, PetscReal *alpha)

Collective

Input Parameters#

v - The data vector, blocksize is the sample dimension
cdf - The analytic CDF

Output Parameter#

alpha - The KS statistic

Notes#

The Kolmogorov-Smirnov statistic for a given cumulative distribution function \(F(x)\) is

\[ D_n = \sup_x \left| F_n(x) - F(x) \right| \]

where \(\sup_x\) is the supremum of the set of distances, and the empirical distribution function \(F_n(x)\) is discrete, and given by

\[ F_n = # of samples <= x / n \]

The empirical distribution function \(F_n(x)\) is discrete, and thus had a ``stairstep’’ cumulative distribution, making \(n\) the number of stairs. Intuitively, the statistic takes the largest absolute difference between the two distribution functions across all \(x\) values.

Level#

advanced

Location#

src/dm/dt/interface/dtprob.c

Index of all DT routines
Table of Contents for all manual pages
Index of all manual pages