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:10.1007/s11336-016-9530-0> and Mollica and Tardella (2014) <doi:10.1002/sim.6224>.
Version: 2.2.0 Imports: Rcpp (≥ 1.0.5), 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), label.switching (≥ 1.6), PlackettLuce (≥ 0.2-3), radarchart (≥ 0.3.1), methods, stats, utils LinkingTo: Rcpp Suggests: doParallel, pmr (≥ 1.2.5), prefmod (≥ 0.8-34), rankdist (≥ 1.1.3), StatRank (≥ 0.0.6), e1071 (≥ 1.7-11) Published: 2025-06-30 DOI: 10.32614/CRAN.package.PLMIX 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: README NEWS In views: Psychometrics CRAN checks: PLMIX results Documentation: Downloads: Reverse dependencies: Linking:Please use the canonical form https://CRAN.R-project.org/package=PLMIX to link to this page.
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