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: |
1.3.3 |
| Depends: |
R (≥ 2.10) |
| Imports: |
shiny, caTools, methods, ggplot2 |
| Suggests: |
mclust, grid |
| Published: |
2017-03-15 |
| Author: |
Michael Thrun, Onno Hansen-Goos, Rabea Griese, Catharina Lippmann, Florian Lerch, Jorn Lotsch, Alfred Ultsch |
| Maintainer: |
Florian Lerch <lerch at mathematik.uni-marburg.de> |
| License: |
GPL-3 |
| URL: |
https://www.uni-marburg.de/fb12/datenbionik/software-en |
| NeedsCompilation: |
no |
| CRAN checks: |
AdaptGauss results |
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