PLMIX - Bayesian Analysis of Finite Mixture of Plackett-Luce Models
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)
<doi.org/10.1007/s11336-016-9530-0> and Mollica and Tardella
(2014) <doi/10.1002/sim.6224>.
