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otrimle: Robust Model-Based Clustering

Performs robust cluster analysis allowing for outliers and noise that cannot be fitted by any cluster. The data are modelled by a mixture of Gaussian distributions and a noise component, which is an improper uniform distribution covering the whole Euclidean space. Parameters are estimated by (pseudo) maximum likelihood. This is fitted by a EM-type algorithm. See Coretto and Hennig (2016) <doi:10.1080/01621459.2015.1100996>, and Coretto and Hennig (2017) <https://jmlr.org/papers/v18/16-382.html>.

Version: 2.0
Imports: stats, utils, graphics, grDevices, mvtnorm, parallel, foreach, doParallel, robustbase, mclust
Published: 2021-05-29
Author: Pietro Coretto [aut, cre] (Homepage: <https://pietro-coretto.github.io>), Christian Hennig [aut] (Homepage: <https://www.unibo.it/sitoweb/christian.hennig/en>)
Maintainer: Pietro Coretto <pcoretto at unisa.it>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: no
Citation: otrimle citation info
Materials: NEWS
In views: Cluster, Robust
CRAN checks: otrimle results

Documentation:

Reference manual: otrimle.pdf

Downloads:

Package source: otrimle_2.0.tar.gz
Windows binaries: r-devel: otrimle_2.0.zip, r-release: otrimle_2.0.zip, r-oldrel: otrimle_2.0.zip
macOS binaries: r-release (arm64): otrimle_2.0.tgz, r-oldrel (arm64): otrimle_2.0.tgz, r-release (x86_64): otrimle_2.0.tgz, r-oldrel (x86_64): otrimle_2.0.tgz
Old sources: otrimle archive

Reverse dependencies:

Reverse imports: ICSClust

Linking:

Please use the canonical form https://CRAN.R-project.org/package=otrimle to link to this page.

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.
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