Package: AdaptGauss
Type: Package
Title: Gaussian Mixture Models (GMM)
Version: 1.5.6
Date: 2020-02-02
Authors@R: c(person("Michael", "Thrun", email= "m.thrun@gmx.net",role=c("aut","cre"), comment = c(ORCID = "0000-0001-9542-5543")),person("Onno", "Hansen-Goos",role=c("aut","rev")),person("Rabea", "Griese",role=c("ctr","ctb")),person("Catharina", "Lippmann",role=c("ctr")),person("Florian", "Lerch",role=c("ctb","rev")),person("Jorn", "Lotsch",role=c("dtc","rev","fnd","ctb")),person("Alfred", "Ultsch",role=c("aut","cph","ths")))
Maintainer: Michael Thrun <m.thrun@gmx.net>
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)  <DOI:10.3390/ijms161025897>.
Imports: Rcpp, shiny, pracma, methods, DataVisualizations
Suggests: mclust, grid, foreach, dqrng, parallelDist, knitr (>= 1.12),
        rmarkdown (>= 0.9), reshape2, ggplot2
LinkingTo: Rcpp
Depends: R (>= 2.10)
License: GPL-3
LazyLoad: yes
URL: https://www.uni-marburg.de/fb12/datenbionik/software-en
Encoding: UTF-8
NeedsCompilation: yes
VignetteBuilder: knitr
BugReports: https://github.com/Mthrun/AdaptGauss/issues
Packaged: 2020-02-03 08:42:56 UTC; MT
Author: Michael Thrun [aut, cre] (<https://orcid.org/0000-0001-9542-5543>),
  Onno Hansen-Goos [aut, rev],
  Rabea Griese [ctr, ctb],
  Catharina Lippmann [ctr],
  Florian Lerch [ctb, rev],
  Jorn Lotsch [dtc, rev, fnd, ctb],
  Alfred Ultsch [aut, cph, ths]
Repository: CRAN
Date/Publication: 2020-02-03 10:00:08 UTC
Built: R 4.0.5; x86_64-w64-mingw32; 2022-04-21 10:12:20 UTC; windows
Archs: i386, x64
