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Two partially supervised mixture modeling methods: soft-label and belief-based modeling are implemented. For completeness, we equipped the package also with the functionality of unsupervised, semi- and fully supervised mixture modeling. The package can be applied also to selection of the best-fitting from a set of models with different component numbers or constraints on their structures. For detailed introduction see: Przemyslaw Biecek, Ewa Szczurek, Martin Vingron, Jerzy Tiuryn (2012), The R Package bgmm: Mixture Modeling with Uncertain Knowledge, Journal of Statistical Software <doi:10.18637/jss.v047.i03>.
Version: | 1.8.5 |
Depends: | R (≥ 2.0), mvtnorm, car, lattice, combinat |
Suggests: | testthat |
Published: | 2021-10-10 |
DOI: | 10.32614/CRAN.package.bgmm |
Author: | Przemyslaw Biecek \& Ewa Szczurek |
Maintainer: | Przemyslaw Biecek <Przemyslaw.Biecek at gmail.com> |
License: | GPL-3 |
URL: | http://bgmm.molgen.mpg.de/ |
NeedsCompilation: | no |
Citation: | bgmm citation info |
In views: | Cluster |
CRAN checks: | bgmm results |
Reference manual: | bgmm.pdf |
Package source: | bgmm_1.8.5.tar.gz |
Windows binaries: | r-devel: bgmm_1.8.5.zip, r-release: bgmm_1.8.5.zip, r-oldrel: bgmm_1.8.5.zip |
macOS binaries: | r-release (arm64): bgmm_1.8.5.tgz, r-oldrel (arm64): bgmm_1.8.5.tgz, r-release (x86_64): bgmm_1.8.5.tgz, r-oldrel (x86_64): bgmm_1.8.5.tgz |
Old sources: | bgmm archive |
Reverse imports: | ggrasp |
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.