Bayesian Preference Learning with the Mallows Rank Model


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Documentation for package ‘BayesMallows’ version 0.4.0

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BayesMallows-package BayesMallows: Bayesian Preference Learning with the Mallows Rank Model.
assess_convergence Trace Plots from Metropolis-Hastings Algorithm
assign_cluster Assign Assessors to Clusters
BayesMallows BayesMallows: Bayesian Preference Learning with the Mallows Rank Model.
beach_preferences Beach Preferences
compute_consensus Compute Consensus Ranking
compute_mallows Preference Learning with the Mallows Rank Model
compute_mallows_mixtures Compute Mixtures of Mallows Models
compute_posterior_intervals Compute Posterior Intervals
create_ordering Convert between ranking and ordering.
create_ranking Convert between ranking and ordering.
estimate_partition_function Estimate Partition Function
generate_constraints Generate Constraint Set from Pairwise Comparisons
generate_initial_ranking Generate Initial Ranking
generate_transitive_closure Generate Transitive Closure
label_switching Checking for Label Switching in the Mallows Mixture Model
plot.BayesMallows Plot 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 Result of ranking potatoes by weight, where the assessors were only allowed to inspected the potatoes visually. 12 assessors ranked 20 potatoes.
potato_weighing Result of ranking potatoes by weight, where the assessors were allowed to lift the potatoes. 12 assessors ranked 20 potatoes.
predict_top_k Predict Top-k Rankings with Pairwise Preferences
print.BayesMallows Print Method for BayesMallows Objects
print.BayesMallowsMixtures Print Method for BayesMallowsMixtures Objects
rank_conversion Convert between ranking and ordering.
sample_mallows Random Samples from the Mallows Rank Model
sushi_rankings Sushi Rankings