Package: rankrate
Title: Statistical Tools for Preference Learning with Rankings and
        Ratings
Version: 1.0.0
Authors@R: 
    person("Michael", "Pearce", , "pearce790@gmail.com", role = c("aut", "cre", "cph"),
           comment = c(ORCID = "0000-0002-9313-271X"))
Description: An implementation of the statistical methodology proposed by Pearce and Erosheva, 
    "A Unified Statistical Learning Model for Rankings and Scores with Application to Grant Panel Review" (2022),
    which at time of release has been accepted in the Journal of Machine Learning Research. The package provides tools 
    for estimating parameters of a Mallows-Binomial model, the first joint statistical preference
    learning model for rankings and ratings. The package includes functions for simulating rankings and ratings from the model, 
    calculating the density of Mallows-Binomial data, estimating parameters using various exact and approximate algorithms, 
    and for obtaining approximate confidence intervals based on the nonparametric bootstrap.
License: GPL-3
Encoding: UTF-8
RoxygenNote: 7.1.2
Imports: stats, nloptr, gtools, lpSolve
NeedsCompilation: no
Packaged: 2022-06-07 20:54:23 UTC; pearce790
Author: Michael Pearce [aut, cre, cph]
    (<https://orcid.org/0000-0002-9313-271X>)
Maintainer: Michael Pearce <pearce790@gmail.com>
Repository: CRAN
Date/Publication: 2022-06-09 08:20:05 UTC
