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) <arXiv:1309.6895>.

Version: 1.1
Imports: stats, utils, graphics, grDevices, mclust, parallel, foreach, doParallel
Published: 2017-06-27
Author: Pietro Coretto [aut, cre], Christian Hennig [aut]
Maintainer: Pietro Coretto <pcoretto at unisa.it>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: no
Citation: otrimle citation info
Materials: ChangeLog
CRAN checks: otrimle results


Reference manual: otrimle.pdf
Package source: otrimle_1.1.tar.gz
Windows binaries: r-devel: otrimle_1.1.zip, r-release: otrimle_1.1.zip, r-oldrel: otrimle_1.1.zip
OS X El Capitan binaries: r-release: otrimle_1.1.tgz
OS X Mavericks binaries: r-oldrel: otrimle_1.1.tgz
Old sources: otrimle archive


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