compute_rho_consensus

MAP AND CP consensus ranking estimates

An implementation of the Bayesian version of the Mallows rank model
(Vitelli et al., Journal of Machine Learning Research, 2018 <https://jmlr.org/papers/v18/15-481.html>;
Crispino et al., Annals of Applied Statistics, 2019 <doi:10.1214/18-AOAS1203>). Both Metropolis-Hastings
and sequential Monte Carlo algorithms for estimating the models are available. Cayley, footrule,
Hamming, Kendall, Spearman, and Ulam distances are supported in the models. The rank data to be
analyzed can be in the form of complete rankings, top-k rankings, partially missing rankings, as well
as consistent and inconsistent pairwise preferences. Several functions for plotting and studying the
posterior distributions of parameters are provided. The package also provides functions for estimating
the partition function (normalizing constant) of the Mallows rank model, both with the importance
sampling algorithm of Vitelli et al. and asymptotic approximation with the IPFP algorithm
(Mukherjee, Annals of Statistics, 2016 <doi:10.1214/15-AOS1389>).

Oystein Sorensen

BayesMallows

Bayesian Preference Learning with the Mallows Rank Model

Valeria Vitelli

Marta Crispino

Qinghua Liu

Cristina Mollica

Luca Tardella

Anja Stein

Waldir Leoncio

compute_rho_consensus function

<dl><dt>output</dt>
<dd>input</dd>
<dt>nmc</dt>
<dd>Number of Monte Carlo samples</dd>
<dt>burnin</dt>
<dd>A numeric value specifying the number of iterations
to discard as burn-in.</dd>
<dt>C</dt>
<dd>C</dd>
<dt>type</dt>
<dd>type</dd>
<dt>colnames</dt>
<dd>colnames</dd>
<dt>verbose</dt>
<dd>if <code>TRUE</code>, prints the final output even if the function
is assigned to an object. Defaults to <code>FALSE</code>.</dd></dl>

Arguments

Author

Compute rho consensus — compute_rho_consensus

<dl>

<dt>output</dt>
<dd>input</dd>


<dt>nmc</dt>
<dd>Number of Monte Carlo samples</dd>


<dt>burnin</dt>
<dd>A numeric value specifying the number of iterations
to discard as burn-in.</dd>


<dt>C</dt>
<dd>C</dd>


<dt>type</dt>
<dd>type</dd>


<dt>colnames</dt>
<dd>colnames</dd>


<dt>verbose</dt>
<dd>if <code>TRUE</code>, prints the final output even if the function
is assigned to an object. Defaults to <code>FALSE</code>.</dd>

</dl>

Compute rho consensus

compute_rho_consensus: Compute rho consensus

Description

Usage

Arguments

Author