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>.

Getting started

Package details

AuthorPietro Coretto [aut, cre], Christian Hennig [aut]
MaintainerPietro Coretto <[email protected]>
LicenseGPL (>= 2)
Version1.1
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:
install.packages("otrimle")

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otrimle documentation built on July 4, 2017, 9:24 a.m.