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Rankcluster: Model-Based Clustering for Multivariate Partial Ranking Data

Implementation of a model-based clustering algorithm for ranking data (C. Biernacki, J. Jacques (2013) <doi:10.1016/j.csda.2012.08.008>). Multivariate rankings as well as partial rankings are taken into account. This algorithm is based on an extension of the Insertion Sorting Rank (ISR) model for ranking data, which is a meaningful and effective model parametrized by a position parameter (the modal ranking, quoted by mu) and a dispersion parameter (quoted by pi). The heterogeneity of the rank population is modelled by a mixture of ISR, whereas conditional independence assumption is considered for multivariate rankings.

Version: 0.98.0
Depends: R (≥ 2.10)
Imports: Rcpp, methods
LinkingTo: Rcpp, RcppEigen
Suggests: knitr, rmarkdown, testthat
Published: 2022-11-12
DOI: 10.32614/CRAN.package.Rankcluster
Author: Quentin Grimonprez [aut, cre], Julien Jacques [aut], Christophe Biernacki [aut]
Maintainer: Quentin Grimonprez <quentingrim at yahoo.fr>
BugReports: https://github.com/modal-inria/Rankcluster/issues/
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
Copyright: Inria - Université de Lille
NeedsCompilation: yes
Citation: Rankcluster citation info
Materials: NEWS
CRAN checks: Rankcluster results

Documentation:

Reference manual: Rankcluster.pdf
Vignettes: Data Format
Using Rankcluster

Downloads:

Package source: Rankcluster_0.98.0.tar.gz
Windows binaries: r-devel: Rankcluster_0.98.0.zip, r-release: Rankcluster_0.98.0.zip, r-oldrel: Rankcluster_0.98.0.zip
macOS binaries: r-release (arm64): Rankcluster_0.98.0.tgz, r-oldrel (arm64): Rankcluster_0.98.0.tgz, r-release (x86_64): Rankcluster_0.98.0.tgz, r-oldrel (x86_64): Rankcluster_0.98.0.tgz
Old sources: Rankcluster archive

Reverse dependencies:

Reverse imports: MSmix

Linking:

Please use the canonical form https://CRAN.R-project.org/package=Rankcluster to link to this page.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.