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:Yang Ni [aut, cre]

COLP_1.0.0.tar.gz
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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

Datasets:

CatPairs - Categorical Cause-Effect Pairs

On CRAN:

2.70 score 1 stars 145 downloads 1 exports 2 dependencies

Last updated 2 years agofrom:3bd5f55bef. Checks:OK: 3 NOTE: 4. Indexed: yes.

Target	Result	Date
Doc / Vignettes	OK	Oct 23 2024
R-4.5-win	OK	Oct 23 2024
R-4.5-linux	OK	Oct 23 2024
R-4.4-win	NOTE	Oct 23 2024
R-4.4-mac	NOTE	Oct 23 2024
R-4.3-win	NOTE	Oct 23 2024
R-4.3-mac	NOTE	Oct 23 2024