Package: RMBC 0.1.0

RMBC: Robust Model Based Clustering

A robust clustering algorithm (Model-Based) similar to Expectation Maximization for finite mixture normal distributions is implemented, its main advantage is that the estimator is resistant to outliers, that means that results of parameter estimation are still correct when there are atypical values in the sample (see Gonzalez, Maronna, Yohai and Zamar (2021) <https://arxiv.org/abs/2102.06851>).

Authors:Juan Domingo Gonzalez [cre, aut], Victor J. Yohai [aut], Ruben H. Zamar [aut] Ricardo Maronna [aut]

RMBC_0.1.0.tar.gz
RMBC_0.1.0.zip(r-4.5)RMBC_0.1.0.zip(r-4.4)RMBC_0.1.0.zip(r-4.3)
RMBC_0.1.0.tgz(r-4.5-any)RMBC_0.1.0.tgz(r-4.4-any)RMBC_0.1.0.tgz(r-4.3-any)
RMBC_0.1.0.tar.gz(r-4.5-noble)RMBC_0.1.0.tar.gz(r-4.4-noble)
RMBC_0.1.0.tgz(r-4.4-emscripten)RMBC_0.1.0.tgz(r-4.3-emscripten)
RMBC.pdf |RMBC.html
RMBC/json (API)

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

Bug tracker:https://github.com/jdgonzalezwork/rmbc/issues

Datasets:

On CRAN:

Conda:

2.70 score 173 downloads 3 exports 46 dependencies

Last updated 4 years agofrom:4fe44a6e77. Checks:3 OK, 6 NOTE. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKMar 21 2025
R-4.5-winNOTEMar 21 2025
R-4.5-macNOTEMar 21 2025
R-4.5-linuxNOTEMar 21 2025
R-4.4-winNOTEMar 21 2025
R-4.4-macNOTEMar 21 2025
R-4.4-linuxNOTEMar 21 2025
R-4.3-winOKMar 21 2025
R-4.3-macOKMar 21 2025

Exports:is_in_grquad_discRMBC

Dependencies:cellWiseclicolorspaceDEoptimRfansifarverggplot2gluegridExtraGSEgtableisobandktaucenterslabelinglatticelifecyclemagrittrMASSMatrixmatrixStatsmgcvmunsellmvtnormnlmepcaPPpillarpkgconfigplyrR6RColorBrewerRcppRcppArmadilloreshape2rlangrobustbaserrcovscalesshapestringistringrsvdtibbleutf8vctrsviridisLitewithr