Package: rankdist 1.1.4
Zhaozhi Qian
rankdist: Distance Based Ranking Models
Implements distance based probability models for ranking data. The supported distance metrics include Kendall distance, Spearman distance, Footrule distance, Hamming distance, Weighted-tau distance and Weighted Kendall distance. Phi-component model and mixture models are also supported.
Authors:
rankdist_1.1.4.tar.gz
rankdist_1.1.4.tar.gz(r-4.5-noble)rankdist_1.1.4.tar.gz(r-4.4-noble)
rankdist_1.1.4.tgz(r-4.4-emscripten)rankdist_1.1.4.tgz(r-4.3-emscripten)
rankdist.pdf |rankdist.html✨
rankdist/json (API)
# Install 'rankdist' in R: |
install.packages('rankdist', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
- apa_obj - American Psychological Association (APA) election data
- apa_partial_obj - American Psychological Association
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 5 years agofrom:5deb852108. Checks:OK: 2. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Dec 06 2024 |
R-4.5-linux-x86_64 | OK | Dec 06 2024 |
Exports:DistanceBlockDistanceMatrixDistancePairGenerateExampleGenerateExampleTopQHashtoRankModelSummaryMomentsEstOrderingToRankingRankDistanceModelRanktoHash