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 |