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. The package is based on the publication of Ultsch, A., Thrun, M.C., Hansen-Goos, O., Lotsch, J. (2015) <DOI:10.3390/ijms161025897>.

Install the latest version of this package by entering the following in R:
AuthorMichael Thrun, Onno Hansen-Goos, Rabea Griese, Catharina Lippmann, Florian Lerch, Jorn Lotsch, Alfred Ultsch
Date of publication2017-03-15 17:12:21
MaintainerFlorian Lerch <>

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AdaptGauss Man page
AdaptGauss-package Man page
Bayes4Mixtures Man page
BayesDecisionBoundaries Man page
CDFMixtures Man page
Chi2testMixtures Man page
ClassifyByDecisionBoundaries Man page
EMGauss Man page
InformationCriteria4GMM Man page
Intersect2Mixtures Man page
KStestMixtures Man page
LikelihoodRatio4Mixtures Man page
LogLikelihood4Mixtures Man page
MultiModal Man page
MultiModal-package Man page
OptimalNoBins Man page
ParetoDensityEstimation Man page
ParetoRadius Man page
Pdf4Mixtures Man page
PlotMixtures Man page
PlotMixturesAndBoundaries Man page
QQplotGMM Man page
RandomLogGMM Man page

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