:orphan: # 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 statisic ## Notes The Kolmogorov-Smirnov statistic for a given cumulative distribution function $F(x)$ is ```none 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. ## See Also `PetscProbFunc` ## Level advanced ## Location src/dm/dt/interface/dtprob.c --- [Edit on GitLab](https://gitlab.com/petsc/petsc/-/edit/release/src/dm/dt/interface/dtprob.c) [Index of all DT routines](index.md) [Table of Contents for all manual pages](/manualpages/index.md) [Index of all manual pages](/manualpages/singleindex.md)