Package: COLP 1.0.0
Yang Ni
COLP: Causal Discovery for Categorical Data with Label Permutation
Discover causality for bivariate categorical data. This package aims to enable users to discover causality for bivariate observational categorical data. See Ni, Y. (2022) <arxiv:2209.08579> "Bivariate Causal Discovery for Categorical Data via Classification with Optimal Label Permutation. Advances in Neural Information Processing Systems 35 (in press)".
Authors:
COLP_1.0.0.tar.gz
COLP_1.0.0.zip(r-4.5)COLP_1.0.0.zip(r-4.4)COLP_1.0.0.zip(r-4.3)
COLP_1.0.0.tgz(r-4.4-any)COLP_1.0.0.tgz(r-4.3-any)
COLP_1.0.0.tar.gz(r-4.5-noble)COLP_1.0.0.tar.gz(r-4.4-noble)
COLP_1.0.0.tgz(r-4.4-emscripten)COLP_1.0.0.tgz(r-4.3-emscripten)
COLP.pdf |COLP.html✨
COLP/json (API)
# Install 'COLP' in R: |
install.packages('COLP', repos = c('https://nystat.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/nystat/colp/issues
- CatPairs - Categorical Cause-Effect Pairs
Last updated 2 years agofrom:3bd5f55bef. Checks:OK: 3 NOTE: 4. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Nov 22 2024 |
R-4.5-win | OK | Nov 22 2024 |
R-4.5-linux | OK | Nov 22 2024 |
R-4.4-win | NOTE | Nov 22 2024 |
R-4.4-mac | NOTE | Nov 22 2024 |
R-4.3-win | NOTE | Nov 22 2024 |
R-4.3-mac | NOTE | Nov 22 2024 |
Exports:COLP
Readme and manuals
Help Manual
Help page | Topics |
---|---|
Categorical Cause-Effect Pairs | CatPairs |
Causal Discovery for Bivariate Cateogrical Data | COLP |