Become an expert in R — Interactive courses, Cheat Sheets, certificates and more!
Get Started for Free

expected_dist

Expected value of metrics under a Mallows rank model

Description

Compute the expectation of several metrics under the Mallows rank model.

Usage

expected_dist(alpha, n_items, metric)

Arguments

alpha

Non-negative scalar specifying the scale (precision) parameter in the Mallows rank model.
n_items

Integer specifying the number of items.
metric

Character string specifying the distance measure to use. Available options are "kendall", "cayley", "hamming", "ulam" for n_items<=95, "footrule" for n_items<=50 and "spearman" for n_items<=14.

Value

A scalar providing the expected value of the metric under the Mallows rank model with distance specified by the metric argument.

Examples

expected_dist(1,5,metric="kendall")
expected_dist(2,6,metric="cayley")
expected_dist(1.5,7,metric="hamming")
expected_dist(5,30,"ulam")
expected_dist(3.5,45,"footrule")
expected_dist(4,10,"spearman")
BayesMallows

Bayesian Preference Learning with the Mallows Rank Model

v1.0.1
GPL-3
Authors
Oystein Sorensen [aut, cre] (<https://orcid.org/0000-0003-0724-3542>), Valeria Vitelli [aut] (<https://orcid.org/0000-0002-6746-0453>), Marta Crispino [aut], Qinghua Liu [aut], Cristina Mollica [aut], Luca Tardella [aut]
Initial release

We don't support your browser anymore

Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.