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Rankcluster  

Model-Based Clustering for Multivariate Partial Ranking Data
View on CRAN: Click here


Download and install Rankcluster package within the R console
Install from CRAN:
install.packages("Rankcluster")

Install from Github:
library("remotes")
install_github("cran/Rankcluster")

Install by package version:
library("remotes")
install_version("Rankcluster", "0.98.0")



Attach the package and use:
library("Rankcluster")
Maintained by
Quentin Grimonprez
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2013-08-28
Latest Update: 2022-11-12
Description:
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.
How to cite:
Quentin Grimonprez (2013). Rankcluster: Model-Based Clustering for Multivariate Partial Ranking Data. R package version 0.98.0, https://cran.r-project.org/web/packages/Rankcluster
Previous versions and publish date:
0.89 (2013-08-28 19:16), 0.90.1 (2013-08-30 19:45), 0.90.2 (2013-09-05 09:55), 0.90.3 (2013-09-12 09:19), 0.91.5 (2013-12-05 09:26), 0.91.6 (2013-12-19 12:24), 0.91 (2013-11-03 18:23), 0.92.9 (2014-07-25 16:31), 0.92 (2014-02-12 11:41), 0.93.1 (2016-01-12 22:46), 0.94.1 (2019-08-28 01:40), 0.94.2 (2020-02-20 11:30), 0.94.4 (2020-10-06 17:20), 0.94.5 (2021-01-27 09:40), 0.94 (2016-07-29 00:55)
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