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 (2015) <https://arxiv.org/abs/1406.0808>, and Coretto and Hennig (2016) <https://arxiv.org/abs/1309.6895>.

Version: 0.4
Imports: stats, graphics, grDevices, mclust, prabclus
Published: 2016-11-30
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
CRAN checks: otrimle results


Reference manual: otrimle.pdf
Package source: otrimle_0.4.tar.gz
Windows binaries: r-devel: otrimle_0.4.zip, r-release: otrimle_0.4.zip, r-oldrel: otrimle_0.4.zip
OS X Mavericks binaries: r-release: otrimle_0.4.tgz, r-oldrel: otrimle_0.4.tgz
Old sources: otrimle archive


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