Rankcluster: Model-Based Clustering for Multivariate Partial Ranking Data
Version 0.94

Implementation of a model-based clustering algorithm for ranking data. 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.

Package details

AuthorQuentin Grimonprez, Julien Jacques
Date of publication2016-07-29 00:55:17
MaintainerQuentin Grimonprez <quentin.grimonprez@inria.fr>
LicenseGPL (>= 2)
Package repositoryView on CRAN
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Rankcluster documentation built on May 30, 2017, 4:46 a.m.