AdaptGauss (1.5.4)

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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) .

Maintainer: Michael Thrun
Author(s): Michael Thrun [aut, cre] (<>), Onno Hansen-Goos [aut, rev], Rabea Griese [ctr, ctb], Catharina Lippmann [ctr], Florian Lerch [ctb, rev], Jorn Lotsch [dtc, rev, fnd], Alfred Ultsch [aut, cph, ths]

License: GPL-3

Uses: DataVisualizations, ggplot2, pracma, Rcpp, shiny, mclust, foreach, knitr, rmarkdown, parallelDist, dqrng
Reverse suggests: DatabionicSwarm, DataVisualizations

Released 21 days ago.

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