Package: PLMIX 2.1.2

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>.

Authors:Cristina Mollica [aut, cre], Luca Tardella [aut]

PLMIX_2.1.2.tar.gz
PLMIX_2.1.2.zip(r-4.7)PLMIX_2.1.2.zip(r-4.6)PLMIX_2.1.2.zip(r-4.5)
PLMIX_2.1.2.tgz(r-4.6-x86_64)PLMIX_2.1.2.tgz(r-4.6-arm64)PLMIX_2.1.2.tgz(r-4.5-x86_64)PLMIX_2.1.2.tgz(r-4.5-arm64)
PLMIX_2.1.2.tar.gz(r-4.7-arm64)PLMIX_2.1.2.tar.gz(r-4.7-x86_64)PLMIX_2.1.2.tar.gz(r-4.6-arm64)PLMIX_2.1.2.tar.gz(r-4.6-x86_64)
PLMIX_2.1.2.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
PLMIX/json (API)
NEWS

# Install 'PLMIX' in R:
install.packages('PLMIX', repos = c('https://cmollica.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/cmollica/plmix/issues

Uses libs:
  • c++– GNU Standard C++ Library v3
Datasets:

On CRAN:

Conda:

cpp

3.19 score 31 scripts 427 downloads 30 exports 125 dependencies

Last updated from:f1524aed33. Checks:4 NOTE, 2 OK, 7 FAIL. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-arm64NOTE249
linux-devel-x86_64NOTE244
source / vignettesOK273
linux-release-arm64NOTE256
linux-release-x86_64NOTE241
macos-release-arm64FAIL101
macos-release-x86_64FAIL191
macos-oldrel-arm64FAIL107
macos-oldrel-x86_64FAIL261
windows-develFAIL116
windows-releaseFAIL71
windows-oldrelFAIL64
wasm-releaseOK177

Exports:as.top_orderingbicPLMIXbinary_group_indfreq_to_unitgibbsPLMIXgibbsPLMIX_with_normgsPLMIX_to_mcmchowmanyrankedis.top_orderinglabel_switchPLMIXlikPLMIXloglikPLMIXmake_completemake_partialmapPLMIXmapPLMIX_multistartpaired_comparisonsplot.gsPLMIXplot.mpPLMIXppcheckPLMIXppcheckPLMIX_condprint.gsPLMIXprint.mpPLMIXrank_ord_switchrank_summariesrPLMIXselectPLMIXsummary.gsPLMIXsummary.mpPLMIXunit_to_freq

Dependencies:abindbackportsbase64encbslibcachemcheckmateclarabelclicodacodetoolscolorspacecombinatcpp11crayonCVXRdigestdplyrevaluateevdfarverfastmapfontawesomeforcatsforeachFormulafsgenericsGGallyggmcmcggplot2ggstatsgluegmpgnmgridExtragtablegtoolshashhighrhighshmshtmltoolshtmlwidgetsigraphinumisobanditeratorsjquerylibjsonliteknitrlabel.switchinglabelinglatticelibcoinlifecyclelpSolvemagrittrMASSMatrixMatrixModelsmatrixStatsmcmcMCMCpackmemoisemimemvtnormnloptrnnetnumDerivoptimxosqppartykitpatchworkpermutepillarpkgconfigPlackettLuceplyrpmrpracmaprefmodprettyunitsprogresspsychotoolspsychotreepurrrquantregqvcalcR6radarchartrankdistrappdirsrcddRColorBrewerRcppRcppEigenrelimpreshape2rlangrmarkdownrpartRSpectraS7sandwichsassscalesscsslamSparseMStatRankstringistringrsurvivaltibbletidyrtidyselecttinytextruncdistutf8vctrsviridisLitewithrxfunyamlzoo

Readme and manuals

Help Manual

Help pageTopics
Coercion into top-ordering datasetsas.top_ordering
BIC for the MLE of a mixture of Plackett-Luce modelsbicPLMIX
Binary group membership matrixbinary_group_ind
Chi-squared index relying on paired comparisons for observed datachisqmeasureobs
Chi-squared index relying on top1 preferences for observed datachisqmeasureobs1dim
Conditional Chi-squared index relying on paired comparisons for observed datachisqmeasureobscond
Generic term of the conditional Chi-squared index relying on top1 preferences for observed datachisqmeasureobsmatrix1dim
Chi-squared index relying on paired comparisons for replicated datachisqmeasuretheo
Chi-squared index relying on top1 preferences for replicated datachisqmeasuretheo1dim
Conditional Chi-squared index relying on paired comparisons for replicated datachisqmeasuretheocond
Generic term of the conditional Chi-squared index relying on top1 preferences for replicated datachisqmeasuretheomatrix1dim
Multinomial probability computation for the Multinomial full-conditionals of the latent component membershipsCompProbZpartial
Rate parameter computation for the Gamma full-conditionals of the support parametersCompRateP
Rate parameter computation for the Exponential full-conditionals of the quantitative latent variablesCompRateYpartial
American Psychological Association Data (partial orderings)d_apa
Car Configurator Data (partial orderings)d_carconf
Dublin West Data (partial orderings)d_dublinwest
Gaming Platforms Data (complete orderings)d_gaming
German Sample Data (complete orderings)d_german
NASCAR Data (partial orderings)d_nascar
Occupation Data (complete orderings)d_occup
Rice Voting Data (partial orderings)d_rice
Bayesian Analysis of Finite Mixtures of Plackett-Luce Models for Partial Rankings/Orderingsdata PLMIX
E-step in the EM algorithm for MAP estimation of a Bayesian mixture of Plackett-Luce modelsEstep
Individual rankings/orderings from the frequency distributionfreq_to_unit
Gibbs sampling for a Bayesian mixture of Plackett-Luce modelsgibbsPLMIX
gibbsPLMIX_with_normgibbsPLMIX_with_norm
MCMC class objects from the Gibbs sampling simulations of a Bayesian mixture of Plackett-Luce modelsgsPLMIX_to_mcmc
Counts how many items are ranked in a partial ranking matrixhowmanyranked
Top-ordering datasetsis.top_ordering
Label switching adjustment of the Gibbs sampling simulations for Bayesian mixtures of Plackett-Luce modelslabel_switchPLMIX
Likelihood and log-likelihood evaluation for a mixture of Plackett-Luce modelsLikelihood likelihood likPLMIX Loglikelihood loglikelihood loglikPLMIX
Completion of partial rankings/orderingsmake_complete
Censoring of complete rankings/orderingsmake_partial
MAP estimation for a Bayesian mixture of Plackett-Luce modelsmapPLMIX
MAP estimation for a Bayesian mixture of Plackett-Luce models with multiple starting valuesmapPLMIX_multistart
Paired comparison matrix for a partial ordering/ranking datasetpaired_comparisons
Random generation from a finite mixture of Plackett-Luce models and subsequent censoringPLMIXsim
Plot the Gibbs sampling simulations for a Bayesian mixture of Plackett-Luce modelsplot.gsPLMIX
Plot the MAP estimates for a Bayesian mixture of Plackett-Luce modelsplot.mpPLMIX
Posterior predictive check for Bayesian mixtures of Plackett-Luce modelsppcheckPLMIX
Conditional posterior predictive check for Bayesian mixtures of Plackett-Luce modelsppcheckPLMIX_cond
Print of the Gibbs sampling simulation of a Bayesian mixture of Plackett-Luce modelsprint.gsPLMIX
Print of the MAP estimation algorithm for a Bayesian mixture of Plackett-Luce modelsprint.mpPLMIX
Weighted sampling without replacement from a finite urnquickintsample
Switch from orderings to rankings and vice versarank_ord_switch
Descriptive summaries for a partial ordering/ranking datasetrank_summaries
Random sample from a mixture of Plackett-Luce modelsrPLMIX
Bayesian selection criteria for mixtures of Plackett-Luce modelsselectPLMIX
Gibbs sampling of the quantitative latent variablesSimYpsilon
Summary of the Gibbs sampling procedure for a Bayesian mixture of Plackett-Luce modelssummary.gsPLMIX
Summary of the MAP estimation for a Bayesian mixture of Plackett-Luce modelssummary.mpPLMIX
Compute paired comparison matrix for a partial ordering datasettau
Computation top1 frequencies conditionally on the number of ranked itemstop1freq1dim
Binary matrix detailing the items ranked by each sample unitumat
Frequency distribution from the individual rankings/orderingsunit_to_freq
M-step for the support parameters of a Bayesian mixture of Plackett-Luce modelsUpPhetpartial
M-step for the weights of a Bayesian mixture of Plackett-Luce modelsUpWhet