Bayesian Preference Learning with the Mallows Rank Model

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Documentation for package ‘BayesMallows’ version 2.2.1

• DESCRIPTION file.
• User guides, package vignettes and other documentation.
• Package NEWS.

Help Pages

assess_convergence	Trace Plots from Metropolis-Hastings Algorithm
assess_convergence.BayesMallows	Trace Plots from Metropolis-Hastings Algorithm
assess_convergence.BayesMallowsMixtures	Trace Plots from Metropolis-Hastings Algorithm
assign_cluster	Assign Assessors to Clusters
beach_preferences	Beach preferences
bernoulli_data	Simulated intransitive pairwise preferences
burnin	See the burnin
burnin.BayesMallows	See the burnin
burnin.BayesMallowsMixtures	See the burnin
burnin.SMCMallows	See the burnin
burnin<-	Set the burnin
burnin<-.BayesMallows	Set the burnin
burnin<-.BayesMallowsMixtures	Set the burnin
cluster_data	Simulated clustering data
compute_consensus	Compute Consensus Ranking
compute_consensus.BayesMallows	Compute Consensus Ranking
compute_consensus.SMCMallows	Compute Consensus Ranking
compute_exact_partition_function	Compute exact partition function
compute_expected_distance	Expected value of metrics under a Mallows rank model
compute_mallows	Preference Learning with the Mallows Rank Model
compute_mallows_mixtures	Compute Mixtures of Mallows Models
compute_mallows_sequentially	Estimate the Bayesian Mallows Model Sequentially
compute_observation_frequency	Frequency distribution of the ranking sequences
compute_posterior_intervals	Compute Posterior Intervals
compute_posterior_intervals.BayesMallows	Compute Posterior Intervals
compute_posterior_intervals.SMCMallows	Compute Posterior Intervals
compute_rank_distance	Distance between a set of rankings and a given rank sequence
create_ordering	Convert between ranking and ordering.
create_ranking	Convert between ranking and ordering.
estimate_partition_function	Estimate Partition Function
get_acceptance_ratios	Get Acceptance Ratios
get_acceptance_ratios.BayesMallows	Get Acceptance Ratios
get_acceptance_ratios.SMCMallows	Get Acceptance Ratios
get_cardinalities	Get cardinalities for each distance
get_mallows_loglik	Likelihood and log-likelihood evaluation for a Mallows mixture model
get_transitive_closure	Get transitive closure
heat_plot	Heat plot of posterior probabilities
plot.BayesMallows	Plot Posterior Distributions
plot.SMCMallows	Plot SMC Posterior Distributions
plot_elbow	Plot Within-Cluster Sum of Distances
plot_top_k	Plot Top-k Rankings with Pairwise Preferences
potato_true_ranking	True ranking of the weights of 20 potatoes.
potato_visual	Potato weights assessed visually
potato_weighing	Potato weights assessed by hand
predict_top_k	Predict Top-k Rankings with Pairwise Preferences
print.BayesMallows	Print Method for BayesMallows Objects
print.BayesMallowsMixtures	Print Method for BayesMallows Objects
print.SMCMallows	Print Method for BayesMallows Objects
sample_mallows	Random Samples from the Mallows Rank Model
sample_prior	Sample from prior distribution
setup_rank_data	Setup rank data
set_compute_options	Specify options for computation
set_initial_values	Set initial values of scale parameter and modal ranking
set_model_options	Set options for Bayesian Mallows model
set_priors	Set prior parameters for Bayesian Mallows model
set_progress_report	Set progress report options for MCMC algorithm
set_smc_options	Set SMC compute options
sushi_rankings	Sushi rankings
update_mallows	Update a Bayesian Mallows model with new users
update_mallows.BayesMallows	Update a Bayesian Mallows model with new users
update_mallows.BayesMallowsPriorSamples	Update a Bayesian Mallows model with new users
update_mallows.SMCMallows	Update a Bayesian Mallows model with new users