## Likelihood Ratio for Gaussian Mixtures

### 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)
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)