CRAN/E | bgmm

bgmm

Gaussian Mixture Modeling Algorithms and the Belief-Based Mixture Modeling

Installation

About

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.

Citation bgmm citation info
bgmm.molgen.mpg.de/

Key Metrics

Version 1.8.5
R ≥ 2.0
Published 2021-10-10 928 days ago
Needs compilation? no
License GPL-3
CRAN checks bgmm results

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Maintainer

Maintainer

Przemyslaw Biecek

Przemyslaw.Biecek@gmail.com

Authors

Przemyslaw Biecek \& Ewa Szczurek

Material

Reference manual
Package source

In Views

Cluster

macOS

r-release

arm64

r-oldrel

arm64

r-release

x86_64

r-oldrel

x86_64

Windows

r-devel

x86_64

r-release

x86_64

r-oldrel

x86_64

Old Sources

bgmm archive

Depends

R ≥ 2.0
mvtnorm
car
lattice
combinat

Suggests

testthat

Reverse Imports

ggrasp