PLMIX: Bayesian Analysis of Finite Mixtures of Plackett-Luce Models for Partial Rankings/Orderings

Fit finite mixtures of Plackett-Luce models for partial top rankings/orderings within the Bayesian framework. It provides MAP point estimates via EM algorithm and posterior MCMC simulations via Gibbs Sampling. It also fits MLE as a special case of the noninformative Bayesian analysis with vague priors. In addition to inferential techniques, the package assists other fundamental phases of a model-based analysis for partial rankings/orderings, by including functions for data manipulation, simulation, descriptive summary, model selection and goodness-of-fit evaluation.

Version: 2.0.1
Imports: Rcpp (≥ 0.12.16), abind, foreach, rcdd, MCMCpack, gtools, label.switching, stats
LinkingTo: Rcpp
Suggests: doParallel
Published: 2018-05-02
Author: Cristina Mollica [aut, cre], Luca Tardella [aut]
Maintainer: Cristina Mollica <cristina.mollica at uniroma1.it>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: yes
Citation: PLMIX citation info
Materials: NEWS
CRAN checks: PLMIX results

Downloads:

Reference manual: PLMIX.pdf
Package source: PLMIX_2.0.1.tar.gz
Windows binaries: r-devel: PLMIX_2.0.1.zip, r-release: PLMIX_2.0.1.zip, r-oldrel: PLMIX_2.0.1.zip
OS X binaries: r-release: PLMIX_2.0.1.tgz, r-oldrel: PLMIX_2.0.tgz
Old sources: PLMIX archive

Reverse dependencies:

Reverse suggests: PlackettLuce

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