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) <http://jmlr.org/papers/v18/16-382.html>.
| Version: | 1.3 |
| Imports: | stats, utils, graphics, grDevices, mclust, parallel, foreach, doParallel |
| Published: | 2019-09-24 |
| 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 |
| Citation: | otrimle citation info |
| Materials: | ChangeLog |
| In views: | Robust |
| CRAN checks: | otrimle results |
| Reference manual: | otrimle.pdf |
| Package source: | otrimle_1.3.tar.gz |
| Windows binaries: | r-devel: otrimle_1.3.zip, r-release: otrimle_1.3.zip, r-oldrel: otrimle_1.3.zip |
| macOS binaries: | r-release: otrimle_1.3.tgz, r-oldrel: otrimle_1.3.tgz |
| Old sources: | otrimle archive |
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