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AdaptGauss (version 1.6)

Gaussian Mixture Models (GMM)

Description

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) .

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Version

Install

install.packages('AdaptGauss')

Monthly Downloads

489

Version

1.6

License

GPL-3

Maintainer

Michael Thrun

Last Published

February 2nd, 2024

Functions in AdaptGauss (1.6)

Intersect2Mixtures

Intersect of two Gaussians
EMGauss

EM Algorithm for GMM
LikelihoodRatio4Mixtures

Likelihood Ratio for Gaussian Mixtures
RandomLogGMM

Random Number Generator for Log or Gaussian Mixture Model
KStestMixtures

Kolmogorov-Smirnov test
PlotMixtures

Shows GMM
PlotMixturesAndBoundaries

Shows GMM with Boundaries
LogLikelihood4Mixtures

LogLikelihood for Gaussian Mixture Models
Pdf4Mixtures

Calculates pdf for GMM
GMMplot_ggplot2

Plots the Gaussian Mixture Model (GMM) withing ggplot2
Symlognpdf

computes a special case of log normal distribution density
InformationCriteria4GMM

Information Criteria For GMM
QQplotGMM

Quantile Quantile Plot of Data
BayesClassification

BayesClassification
CDFMixtures

cumulative distribution of mixture model
Bayes4Mixtures

Posterioris of Bayes Theorem
BayesFor2GMM

Posterioris of Bayes Theorem for a two group GMM
ClassifyByDecisionBoundaries

Classify Data according to decision Boundaries
AdaptGauss

Adapt Gaussian Mixture Model (GMM)
AdaptGauss-package

tools:::Rd_package_title("AdaptGauss")
Chi2testMixtures

Pearson's chi-squared goodness of fit test
LKWFahrzeitSeehafen2010

Truck driving time seaport 2010
BayesDecisionBoundaries

Decision Boundaries calculated through Bayes Theorem