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.

Version: 1.1.0
Depends: R (≥ 2.10)
Imports: shiny, caTools, mclust, methods
Published: 2015-10-14
Author: Michael Thrun, Onno Hansen-Goos, Rabea Griese, Catharina Lippmann, Jorn Lotsch, Alfred Ultsch
Maintainer: Michael Thrun <mthrun at mathematik.uni-marburg.de>
License: GPL-3
NeedsCompilation: no
CRAN checks: AdaptGauss results

Downloads:

Reference manual: AdaptGauss.pdf
Package source: AdaptGauss_1.1.0.tar.gz
Windows binaries: r-devel: AdaptGauss_1.1.0.zip, r-release: AdaptGauss_1.1.0.zip, r-oldrel: AdaptGauss_1.1.0.zip
OS X Snow Leopard binaries: r-release: AdaptGauss_1.1.0.tgz, r-oldrel: not available
OS X Mavericks binaries: r-release: AdaptGauss_1.1.0.tgz
Old sources: AdaptGauss archive