otrimle: Robust Model-Based Clustering
Version 0.4

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) , and Coretto and Hennig (2016) .

Getting started

Package details

AuthorPietro Coretto [aut, cre], Christian Hennig [aut]
Date of publication2016-11-30 14:55:24
MaintainerPietro Coretto <pcoretto@unisa.it>
LicenseGPL (>= 2)
Package repositoryView on CRAN
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otrimle documentation built on May 29, 2017, 12:32 p.m.