Package: rankrate 1.2.1

rankrate: Joint Statistical Models for Preference Learning with Rankings and Ratings

Statistical tools for the Mallows-Binomial model, the first joint statistical model for preference learning for rankings and ratings. This project was supported by the National Science Foundation under Grant No. 2019901.

Authors:Michael Pearce [aut, cre, cph]

rankrate_1.2.1.tar.gz
rankrate_1.2.1.zip(r-4.7)rankrate_1.2.1.zip(r-4.6)rankrate_1.2.1.zip(r-4.5)
rankrate_1.2.1.tgz(r-4.6-any)rankrate_1.2.1.tgz(r-4.5-any)
rankrate_1.2.1.tar.gz(r-4.7-any)rankrate_1.2.1.tar.gz(r-4.6-any)
rankrate_1.2.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
rankrate/json (API)

# Install 'rankrate' in R:
install.packages('rankrate', repos = c('https://pearce790.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/pearce790/rankrate/issues

Pkgdown/docs site:https://pearce790.github.io

Datasets:
  • AIBS - Real peer review data set from the American Institute of Biological Sciences
  • ToyData1 - Toy data set of rankings and ratings demonstrating tie-breaking
  • ToyData2 - Toy data set of rankings and ratings demonstrating decision-making with partial rankings
  • ToyData3 - Toy data set of rankings and ratings when judges express internally inconsistent preferences

On CRAN:

Conda:

4.00 score 7 scripts 230 downloads 14 exports 3 dependencies

Last updated from:85ad316194. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK139
source / vignettesOK240
linux-release-x86_64OK133
macos-release-arm64OK202
macos-oldrel-arm64OK175
windows-develOK132
windows-releaseOK88
windows-oldrelOK75
wasm-releaseOK116

Exports:ASTARci_mbdmalldmbfit_mbFVgetQGreedyGreedyLocalkendallpsirmallrmbto_rankings

Dependencies:gtoolsisotonennls

rankrate: Joint Statistical Models for Preference Learning with Rankings and Ratings
Funding | References
Rendered fromoverview.Rmdusingknitr::rmarkdown

Last update: 2025-03-25
Started: 2023-05-06

Tutorial: Toy Data Set
Exploratory Data Analysis | Visualizing rankings | Visualizing ratings | Estimation | Inference | References
Rendered fromtutorial.Rmdusingknitr::rmarkdown

Last update: 2023-05-07
Started: 2023-05-06