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)
|Author||Pietro Coretto [aut, cre], Christian Hennig [aut]|
|Date of publication||2017-06-27 16:15:33 UTC|
|Maintainer||Pietro Coretto <[email protected]>|
|License||GPL (>= 2)|
|Package repository||View on CRAN|
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