Rankcluster: An R package for clustering multivariate partial rankings - Archive ouverte HAL Access content directly
Journal Articles The R Journal Year : 2014

Rankcluster: An R package for clustering multivariate partial rankings

Abstract

Rankcluster is the first R package dedicated to ranking data. This package proposes modelling and clustering tools for ranking data, potentially multivariate and partial. Ranking data are modelled by the Insertion Sorting Rank (isr) model, which is a meaningful model parametrized by a central ranking and a dispersion parameter. A conditional independence assumption allows to take into account multivariate rankings, and clustering is performed by the mean of mixtures of multivariate isr model. The clusters parameters (central rankings and dispersion parameters) help the practitioners in the interpretation of the clustering. Moreover, the Rankcluster package provides an estimation of the missing ranking positions when rankings are partial. After an overview of the mixture of multivariate isr model, the Rankcluster package is described and its use is illustrated through two real datasets analysis.
Fichier principal
Vignette du fichier
Rankcluster.pdf (177.28 Ko) Télécharger le fichier
Origin Files produced by the author(s)
Loading...

Dates and versions

hal-00840692 , version 1 (02-07-2013)
hal-00840692 , version 2 (20-08-2013)
hal-00840692 , version 3 (27-02-2014)

Identifiers

Cite

Julien Jacques, Quentin Grimonprez, Christophe Biernacki. Rankcluster: An R package for clustering multivariate partial rankings. The R Journal, 2014, 6 (1), pp.10. ⟨10.32614/rj-2014-010⟩. ⟨hal-00840692v3⟩
516 View
1260 Download

Altmetric

Share

Gmail Mastodon Facebook X LinkedIn More