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. Main references on the methods are Mollica and Tardella (2017) <> and Mollica and Tardella (2014) <doi/10.1002/sim.6224>.

Package details

AuthorCristina Mollica [aut, cre], Luca Tardella [aut]
MaintainerCristina Mollica <[email protected]>
LicenseGPL (>= 2)
Package repositoryView on CRAN
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PLMIX documentation built on Sept. 4, 2019, 5:03 p.m.