Package: otrimle
Type: Package
Title: Robust Model-Based Clustering
Description: 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) <https://jmlr.org/papers/v18/16-382.html>.
Version: 1.6
Date: 2020-11-24
Author: Pietro Coretto [aut, cre],
  Christian Hennig [aut]
Maintainer: Pietro Coretto <pcoretto@unisa.it>
Authors@R: c(person("Pietro", "Coretto",
                    role = c("aut", "cre"), email = "pcoretto@unisa.it"),
             person("Christian", "Hennig",
	             role = "aut"))
Imports: stats, utils, graphics, grDevices, mclust, parallel, foreach,
        doParallel
License: GPL (>= 2)
LazyData: TRUE
NeedsCompilation: no
Packaged: 2020-11-24 10:35:43 UTC; pietro
Repository: CRAN
Date/Publication: 2020-11-24 10:50:02 UTC
