bernoulli_data

<p>Simulated dataset based on the potato_visual data. Based on
the rankings in potato_visual, all n-choose-2 = 190 pairs of items were
sampled from each assessor. With probability .9, the pairwise
preference was in agreement with potato_visual, and with probability .1,
they were in disagreement. Hence, the data generating mechanism was a
Bernoulli error model crispino2019BayesMallows with
\(\theta=0.1\).</p>

datasets

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>;
Sorensen et al., R Journal, 2020 <doi:10.32614/RJ-2020-026>;
Stein, PhD Thesis, 2023 <https://eprints.lancs.ac.uk/id/eprint/195759>). 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

Waldir Leoncio

Valeria Vitelli

Marta Crispino

Qinghua Liu

Cristina Mollica

Luca Tardella

Anja Stein

bernoulli_data function

<p>An object of class <code>data.frame</code> with 2280 rows and 3 columns.</p>

Format

Simulated intransitive pairwise preferences — bernoulli_data

Simulated intransitive pairwise preferences

bernoulli_data: Simulated intransitive pairwise preferences

Description

Usage

Arguments

Format

See Also