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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>.
Getting started
Browse package contents
Package details |
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| 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], Quirin Stier [ctb, rev], Jorn Lotsch [dtc, rev, fnd, ctb], Luca Brinkmann [ctb, rev], Alfred Ultsch [aut, cph, ths] |
| Maintainer | Michael Thrun <m.thrun@gmx.net> |
| License | GPL-3 |
| Version | 1.6 |
| URL | https://www.deepbionics.org |
| Package repository | View on CRAN |
| Installation |
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