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: | 0.94.5 |
| Depends: | R (≥ 2.10) |
| Imports: | Rcpp, methods |
| LinkingTo: | Rcpp, RcppEigen |
| Suggests: | knitr, rmarkdown |
| Published: | 2021-01-27 |
| 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 |
| CRAN checks: | Rankcluster results |
| Reference manual: | Rankcluster.pdf |
| Vignettes: |
Data Format Using Rankcluster |
| Package source: | Rankcluster_0.94.5.tar.gz |
| Windows binaries: | r-devel: Rankcluster_0.94.5.zip, r-release: Rankcluster_0.94.5.zip, r-oldrel: Rankcluster_0.94.5.zip |
| macOS binaries: | r-release (arm64): Rankcluster_0.94.5.tgz, r-oldrel (arm64): Rankcluster_0.94.5.tgz, r-release (x86_64): Rankcluster_0.94.5.tgz, r-oldrel (x86_64): Rankcluster_0.94.5.tgz |
| Old sources: | Rankcluster archive |
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