Gaussian Mixture Models (GMM) R package AdaptGauss version 1.6 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>. Software 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 Michael Thrun <m.thrun@gmx.net> Comprehensive R Archive Network (CRAN) Michael Thrun [aut, cre] (ORCID: <https://orcid.org/0000-0001-9542-5543>), 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] GPL-3 2024-02-02 application/tgz https://CRAN.R-project.org/package=AdaptGauss doi:10.32614/CRAN.package.AdaptGauss