LikelihoodRatio4Mixtures: Likelihood Ratio for Gaussian Mixtures

In AdaptGauss: Gaussian Mixture Models (GMM)

Description

Computes the likelihood ratio for two Gaussian Mixture Models.

Usage

LikelihoodRatio4Mixtures(Data,NullMixture,OneMixture,PlotIt,LowerLimit,UpperLimit)

Arguments

Data	Data points.
NullMixture	A Matrix: cbind(Means0,SDs0,Weights0) or cbind(Means0,SDs0,Weights0,IsLog0). The null model; usually with less Gaussians than the OneMixture
OneMixture	A Matrix: cbind(Means1,SDs1,Weights1) or cbind(Means1,SDs1,Weights1,IsLog1). The alternative model usually with more Gaussians than the OneMixture.
PlotIt	Optional: zero or one. o a Plot of the compared cdf's and the KS-test distribution (Diff)
LowerLimit	Optional: test only for Data >= LowerLimit, Default = min(Data) i.e all Data.
UpperLimit	Optional: test only for Data <= UpperLimit, Default = max(Data) i.e all Data.

Value

List with

Pvalue	the error that we make, if we accept OneMixture as the better Model over the NullMixture
NullLogLikelihood	log likelihood of GMM Null
OneLogLikelihood	log likelihood of GMM One

Author(s)

Alfred Ultsch, Michael Thrun, Catharina Lippmann

Examples

  
  data2=c(rnorm(1000),rnorm(2000)+2,rnorm(1000)*2-1)
  ## Not run: Vals=AdaptGauss(data2,c(-1,0,2),c(2,1,1),c(0.25,0.25,0.5),0.3,-6,6)
  NullMixture=cbind(Vals$Means,Vals$SDs,Vals$Weights)
  
## End(Not run)
  ## Not run: Vals2=AdaptGauss(data2,c(-1,0,2,3),c(2,1,1,1),c(0.25,0.25,0.25,0.25),0.3,-6,6)
  OneMixture=cbind(Vals2$Means,Vals2$SDs,Vals2$Weights)
  
## End(Not run)
  ## Not run: 
  res=LikelihoodRatio4Mixtures(Data,NullMixture,OneMixture,T)
  
## End(Not run)
 

AdaptGauss documentation built on March 26, 2020, 7:57 p.m.