AdaptGauss (version 1.2.0)

KStestMixtures: Kolmogorov-Smirnov test

Description

Returns a P value and visualizes for Kolmogorov-Smirnov test of Data versus a given Gauss Mixture Model

Usage

KStestMixtures(Data,Means,SDs,Weights,IsLogDistribution,PlotIt,UpperLimit)

Arguments

Data

vector of data points

Means

vector of Means of Gaussians

SDs

vector of standard deviations, estimated Gaussian Kernels

Weights

vector of relative number of points in Gaussians (prior probabilities)

IsLogDistribution

Optional, if IsLogDistribution(i)==1, then mixture is lognormal, default vector of zeros of length 1:L

PlotIt

Optional, Default: FALSE, do a Plot of the compared cdfs and the KS-test distribution (Diff)

UpperLimit

Optional. test only for Data

Value

• List with
• Pvalue
  Pvalue of a suiting Kolmogorov-Smirnov test, Pvalue ==0 if Pvalue <0.001< description="">
• DataKernels
  such that plot(DataKernels,DataCDF) gives the cdf(Data)
• DataCDF
  such that plot(DataKernels,DataCDF) gives the cdf(Data)
• CDFGaussMixture
  No. of data that should be in bin according to GMM

Details

...

References

Smirnov, N., Table for Estimating the Goodness of Fit of Empirical Distributions. 1948, (2), 279-281.