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otrimle

Robust Model-Based Clustering

Installation

About

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) .

Citation otrimle citation info

Key Metrics

Version 2.0
Published 2021-05-29 1227 days ago
Needs compilation? no
License GPL-2
License GPL-3
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Maintainer

Maintainer

Pietro Coretto

Authors

Pietro Coretto

aut / cre

(Homepage: <https://pietro-coretto.github.io>)

Christian Hennig

aut

(Homepage: <https://www.unibo.it/sitoweb/christian.hennig/en>)

Material

NEWS
Reference manual
Package source

In Views

Robust

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

otrimle archive

Imports

stats
utils
graphics
grDevices
mvtnorm
parallel
foreach
doParallel
robustbase
mclust