Package: Rankcluster 0.98.0

Quentin Grimonprez

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.

Authors:Quentin Grimonprez [aut, cre], Julien Jacques [aut], Christophe Biernacki [aut]

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Rankcluster.pdf |Rankcluster.html
Rankcluster/json (API)
NEWS

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

Peer review:

Bug tracker:https://github.com/modal-inria/rankcluster/issues

Uses libs:
  • c++– GNU Standard C++ Library v3
Datasets:
  • APA - Rank data: APA
  • big4 - Rank data: big4
  • eurovision - Multidimensional partial rank data: eurovision
  • quiz - Multidimensional rank data: quiz
  • sports - Rank data: sports
  • words - Rank data: words

On CRAN:

clusteringhacktoberfestrank

5.05 score 1 stars 1 packages 37 scripts 399 downloads 14 exports 2 dependencies

Last updated 2 years agofrom:ef9344d9c9. Checks:OK: 9. Indexed: yes.

TargetResultDate
Doc / VignettesOKOct 14 2024
R-4.5-win-x86_64OKOct 14 2024
R-4.5-linux-x86_64OKOct 14 2024
R-4.4-win-x86_64OKOct 14 2024
R-4.4-mac-x86_64OKOct 14 2024
R-4.4-mac-aarch64OKOct 14 2024
R-4.3-win-x86_64OKOct 14 2024
R-4.3-mac-x86_64OKOct 14 2024
R-4.3-mac-aarch64OKOct 14 2024

Exports:convertRankcriteriadistCayleydistHammingdistKendalldistSpearmanfrequencekhi2kullbackprobabilityrankclustsimulISRsummaryunfrequence

Dependencies:RcppRcppEigen

Data Format

Rendered fromdataFormat.Rmdusingknitr::rmarkdownon Oct 14 2024.

Last update: 2020-02-20
Started: 2020-02-20

Using Rankcluster

Rendered fromRankcluster.Rnwusingutils::Sweaveon Oct 14 2024.

Last update: 2020-02-20
Started: 2013-09-12