An implementation of the Bayesian version of the Mallows rank model (Vitelli et al., Journal of Machine Learning Research, 2018 <https://jmlr.org/papers/v18/15-481.html>; Crispino et al., Annals of Applied Statistics, 2019 <doi:10.1214/18-AOAS1203>; Sorensen et al., R Journal, 2020 <doi:10.32614/RJ-2020-026>; Stein, PhD Thesis, 2023 <https://eprints.lancs.ac.uk/id/eprint/195759>). Both Metropolis-Hastings and sequential Monte Carlo algorithms for estimating the models are available. Cayley, footrule, Hamming, Kendall, Spearman, and Ulam distances are supported in the models. The rank data to be analyzed can be in the form of complete rankings, top-k rankings, partially missing rankings, as well as consistent and inconsistent pairwise preferences. Several functions for plotting and studying the posterior distributions of parameters are provided. The package also provides functions for estimating the partition function (normalizing constant) of the Mallows rank model, both with the importance sampling algorithm of Vitelli et al. and asymptotic approximation with the IPFP algorithm (Mukherjee, Annals of Statistics, 2016 <doi:10.1214/15-AOS1389>).
Version: | 2.2.2 |
Depends: | R (≥ 3.5.0) |
Imports: | Rcpp (≥ 1.0.0), ggplot2 (≥ 3.1.0), Rdpack (≥ 1.0), sets (≥ 1.0-18), relations (≥ 0.6-8), rlang (≥ 0.3.1) |
LinkingTo: | Rcpp, RcppArmadillo, testthat |
Suggests: | knitr, testthat (≥ 3.0.0), label.switching (≥ 1.7), rmarkdown, covr, parallel (≥ 3.5.1) |
Published: | 2024-08-17 |
DOI: | 10.32614/CRAN.package.BayesMallows |
Author: | Oystein Sorensen [aut, cre], Waldir Leoncio [aut], Valeria Vitelli [aut], Marta Crispino [aut], Qinghua Liu [aut], Cristina Mollica [aut], Luca Tardella [aut], Anja Stein [aut] |
Maintainer: | Oystein Sorensen <oystein.sorensen.1985 at gmail.com> |
BugReports: | https://github.com/ocbe-uio/BayesMallows/issues |
License: | GPL-3 |
URL: | https://github.com/ocbe-uio/BayesMallows, https://ocbe-uio.github.io/BayesMallows/ |
NeedsCompilation: | yes |
Citation: | BayesMallows citation info |
Materials: | NEWS |
In views: | Bayesian, MissingData |
CRAN checks: | BayesMallows results |
Reference manual: | BayesMallows.pdf |
Vignettes: |
Introduction (source) Sequential Monte Carlo for the Bayesian Mallows model (source) MCMC with Parallel Chains (source) |
Package source: | BayesMallows_2.2.2.tar.gz |
Windows binaries: | r-devel: BayesMallows_2.2.2.zip, r-release: BayesMallows_2.2.2.zip, r-oldrel: BayesMallows_2.2.2.zip |
macOS binaries: | r-release (arm64): BayesMallows_2.2.2.tgz, r-oldrel (arm64): BayesMallows_2.2.2.tgz, r-release (x86_64): BayesMallows_2.2.2.tgz, r-oldrel (x86_64): BayesMallows_2.2.2.tgz |
Old sources: | BayesMallows archive |
Reverse imports: | MSmix |
Reverse suggests: | PlackettLuce |
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