AdaptGauss: Gaussian Mixture Models (GMM)

Multimodal distributions can be modelled as a mixture of components. The model is derived using the Pareto Density Estimation (PDE) for an estimation of the pdf. PDE has been designed in particular to identify groups/classes in a dataset. Precise limits for the classes can be calculated using the theorem of Bayes. Verification of the model is possible by QQ plot, Chi-squared test and Kolmogorov-Smirnov test.

Author
Michael Thrun, Onno Hansen-Goos, Rabea Griese, Catharina Lippmann, Jorn Lotsch, Alfred Ultsch
Date of publication
2016-06-30 18:16:06
Maintainer
Michael Thrun <mthrun@mathematik.uni-marburg.de>
License
GPL-3
Version
1.2.4
URLs

View on CRAN

Man pages

AdaptGauss
Adapt Gaussian Mixture Model (GMM)
AdaptGauss-package
AdaptGauss-package
Bayes4Mixtures
Posterioris of Bayes Theorem
BayesDecisionBoundaries
Decision Boundaries calculated through Bayes Theorem
CDFMixtures
cumulative distribution of mixture model
Chi2testMixtures
Pearson's chi-squared goodness of fit test
ClassifyByDecisionBoundaries
Classify Data according to decision Boundaries
EMGauss
EM Algorithm for GMM
InformationCriteria4GMM
Information Criteria For GMM
Intersect2Mixtures
Intersect of two Gaussians
KStestMixtures
Kolmogorov-Smirnov test
LikelihoodRatio4Mixtures
Likelihood Ratio for Gaussian Mixtures
LogLikelihood4Mixtures
LogLikelihood for Gaussian Mixture Models
OptimalNoBins
Optimal Number Of Bins
ParetoDensityEstimation
Pareto Density Estimation
ParetoRadius
ParetoRadius for distributions
Pdf4Mixtures
Calculates pdf for GMM
PlotMixtures
Shows GMM
PlotMixturesAndBoundaries
Shows GMM with Boundaries
qqplotGMM
Quantile Quantile Plot of Data
randomLogGMM
Random Number Generator for Log or Gaussian Mixture Model

Files in this package

AdaptGauss
AdaptGauss/NAMESPACE
AdaptGauss/R
AdaptGauss/R/Chi2testMixtures.R
AdaptGauss/R/KStestMixtures.R
AdaptGauss/R/EMGauss.R
AdaptGauss/R/ParetoDensityEstimation.R
AdaptGauss/R/OptimalNoBins.R
AdaptGauss/R/QQplotGMM.R
AdaptGauss/R/ParetoRadius.R
AdaptGauss/R/Pdf4Mixtures.R
AdaptGauss/R/RandomLogGMM.R
AdaptGauss/R/CDFMixtures.R
AdaptGauss/R/BayesDecisionBoundaries.R
AdaptGauss/R/PlotMixturesAndBoundaries.R
AdaptGauss/R/Intersect2Mixtures.R
AdaptGauss/R/ClassifyByDecisionBoundaries.R
AdaptGauss/R/PlotMixtures.R
AdaptGauss/R/LogLikelihood4Mixtures.R
AdaptGauss/R/LikelihoodRatio4Mixtures.R
AdaptGauss/R/InformationCriteria4GMM.R
AdaptGauss/R/Bayes4Mixtures.R
AdaptGauss/R/AdaptGauss.R
AdaptGauss/MD5
AdaptGauss/DESCRIPTION
AdaptGauss/man
AdaptGauss/man/AdaptGauss.Rd
AdaptGauss/man/InformationCriteria4GMM.Rd
AdaptGauss/man/ParetoDensityEstimation.Rd
AdaptGauss/man/AdaptGauss-package.Rd
AdaptGauss/man/qqplotGMM.Rd
AdaptGauss/man/Chi2testMixtures.Rd
AdaptGauss/man/BayesDecisionBoundaries.Rd
AdaptGauss/man/PlotMixturesAndBoundaries.Rd
AdaptGauss/man/LogLikelihood4Mixtures.Rd
AdaptGauss/man/Pdf4Mixtures.Rd
AdaptGauss/man/CDFMixtures.Rd
AdaptGauss/man/ParetoRadius.Rd
AdaptGauss/man/Bayes4Mixtures.Rd
AdaptGauss/man/randomLogGMM.Rd
AdaptGauss/man/Intersect2Mixtures.Rd
AdaptGauss/man/ClassifyByDecisionBoundaries.Rd
AdaptGauss/man/KStestMixtures.Rd
AdaptGauss/man/OptimalNoBins.Rd
AdaptGauss/man/EMGauss.Rd
AdaptGauss/man/PlotMixtures.Rd
AdaptGauss/man/LikelihoodRatio4Mixtures.Rd