Package: PLMIX
Type: Package
Title: Bayesian Analysis of Finite Mixtures of Plackett-Luce Models for
        Partial Rankings/Orderings
Version: 2.1.1
Date: 2019-09-04
Authors@R: c(person("Cristina", "Mollica", role = c("aut", "cre"), email = "cristina.mollica@uniroma1.it"), person("Luca", "Tardella", role = "aut",email = "luca.tardella@uniroma1.it"))
Description: 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>.
License: GPL (>= 2)
Imports: Rcpp (>= 1.0.0), abind (>= 1.4-5), foreach (>= 1.4.4), ggplot2
        (>= 2.2.1), ggmcmc (>= 1.2), coda (>= 0.19-1), reshape2 (>=
        1.4.3), rcdd (>= 1.2), gridExtra (>= 2.3), MCMCpack (>= 1.4-2),
        gtools (>= 3.8.1), label.switching (>= 1.6), radarchart (>=
        0.3.1), prefmod (>= 0.8-34), rankdist (>= 1.1.3), StatRank (>=
        0.0.6), pmr (>= 1.2.5), PlackettLuce (>= 0.2-3), stats, utils
LinkingTo: Rcpp
RoxygenNote: 6.1.0
Suggests: doParallel
LazyData: true
NeedsCompilation: yes
Packaged: 2019-09-04 11:25:41 UTC; cmollica
Author: Cristina Mollica [aut, cre],
  Luca Tardella [aut]
Maintainer: Cristina Mollica <cristina.mollica@uniroma1.it>
Repository: CRAN
Date/Publication: 2019-09-04 11:50:02 UTC
Built: R 4.3.0; aarch64-apple-darwin20; 2023-07-10 06:25:37 UTC; unix
Archs: PLMIX.so.dSYM
