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: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:
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