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>.

Version: 1.6
Depends: R (≥ 2.10)
Imports: Rcpp, shiny, pracma, methods, DataVisualizations, plotly
LinkingTo: Rcpp
Suggests: mclust, grid, foreach, dqrng, parallelDist, knitr (≥ 1.12), rmarkdown (≥ 0.9), reshape2, ggplot2
Published: 2024-02-02
DOI: 10.32614/CRAN.package.AdaptGauss
Author: Michael Thrun ORCID iD [aut, cre], Onno Hansen-Goos [aut, rev], Rabea Griese [ctr, ctb], Catharina Lippmann [ctr], Florian Lerch [ctb, rev], Quirin Stier [ctb, rev], Jorn Lotsch [dtc, rev, fnd, ctb], Luca Brinkmann [ctb, rev], Alfred Ultsch [aut, cph, ths]
Maintainer: Michael Thrun <m.thrun at>
License: GPL-3
NeedsCompilation: yes
CRAN checks: AdaptGauss results


Reference manual: AdaptGauss.pdf
Vignettes: Short Intro into Gaussian Mixture Models


Package source: AdaptGauss_1.6.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): AdaptGauss_1.6.tgz, r-oldrel (arm64): AdaptGauss_1.6.tgz, r-release (x86_64): AdaptGauss_1.6.tgz, r-oldrel (x86_64): AdaptGauss_1.6.tgz
Old sources: AdaptGauss archive

Reverse dependencies:

Reverse imports: DistributionOptimization, opGMMassessment, scapGNN, Umatrix


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