print.summary.BayesMallowsSMC2

Prints a summary of a BayesMallowsSMC2 model.

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>.

Oystein Sorensen

BayesMallowsSMC2

Nested Sequential Monte Carlo for the Bayesian Mallows Model

print.summary.BayesMallowsSMC2 function

<dl><dt>x</dt>
<dd>An object of class <code>summary.BayesMallowsSMC2</code>.</dd>
<dt>...</dt>
<dd>Additional arguments (currently unused).</dd></dl>

Arguments

Print Method for summary.BayesMallowsSMC2 Objects — print.summary.BayesMallowsSMC2

<dl>

<dt>x</dt>
<dd>An object of class <code>summary.BayesMallowsSMC2</code>.</dd>


<dt>...</dt>
<dd>Additional arguments (currently unused).</dd>

</dl>

print.summary.BayesMallowsSMC2: Print Method for summary.BayesMallowsSMC2 Objects

Description

Usage

Value

Arguments