BayesMallowsSMC20.2.1 package

Nested Sequential Monte Carlo for the Bayesian Mallows Model

compute_sequentially

Compute the Bayesian Mallows model sequentially

plot.BayesMallowsSMC2

Plot Posterior Distributions for BayesMallowsSMC2 Objects

precompute_topological_sorts

Precompute All Topological Sorts

print.BayesMallowsSMC2

Print Method for BayesMallowsSMC2 Objects

print.summary.BayesMallowsSMC2

Print Method for summary.BayesMallowsSMC2 Objects

set_hyperparameters

Set hyperparameters

set_smc_options

Set SMC options

summary.BayesMallowsSMC2

Summary Method for BayesMallowsSMC2 Objects

trace_plot

Create Trace Plots for BayesMallowsSMC2 Objects

Download source packageRead PDF manual

Provides nested sequential Monte Carlo algorithms for performing sequential inference in the Bayesian Mallows model, which is a widely used probability model for rank and preference data. The package implements the SMC2 (Sequential Monte Carlo Squared) algorithm for handling sequentially arriving rankings and pairwise preferences, including support for complete rankings, partial rankings, and pairwise comparisons. The methods are based on Sorensen (2025) <doi:10.1214/25-BA1564>.

  • Maintainer: Oystein Sorensen
  • License: GPL-3
  • Last published: 2026-02-04