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.
Package details |
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Author | Quentin Grimonprez [aut, cre], Julien Jacques [aut], Christophe Biernacki [aut] |
Maintainer | Quentin Grimonprez <quentingrim@yahoo.fr> |
License | GPL (>= 2) |
Version | 0.98.0 |
Package repository | View on CRAN |
Installation |
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