Package: otrimle 2.0

Pietro Coretto

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) <https://jmlr.org/papers/v18/16-382.html>.

Authors:Pietro Coretto [aut, cre], Christian Hennig [aut]

otrimle_2.0.tar.gz
otrimle_2.0.tar.gz(r-4.5-noble)otrimle_2.0.tar.gz(r-4.4-noble)
otrimle_2.0.tgz(r-4.4-emscripten)otrimle_2.0.tgz(r-4.3-emscripten)
otrimle.pdf |otrimle.html
otrimle/json (API)
NEWS

# Install 'otrimle' in R:
install.packages('otrimle', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

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This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

1.48 score 1 stars 1 packages 9 scripts 314 downloads 14 exports 8 dependencies

Last updated 4 years agofrom:14c0d74625. Checks:OK: 2. Indexed: yes.

TargetResultDate
Doc / VignettesOKDec 08 2024
R-4.5-linuxOKDec 08 2024

Exports:generator.otrimleInitClustkerndensclusterkerndensmeasurekerndenspkmeanfunksdfunotrimleotrimlegotrimlesimgplot.summary.otrimlesimgdensprint.summary.otrimlesimgdensrimlesummary.otrimlesimgdens

Dependencies:codetoolsDEoptimRdoParallelforeachiteratorsmclustmvtnormrobustbase