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)".
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
1.0.0 |
rolling linux/jammy R-4.5 | COLP_1.0.0.tar.gz |
20.3 KiB |
1.0.0 |
rolling linux/noble R-4.5 | COLP_1.0.0.tar.gz |
20.2 KiB |
1.0.0 |
rolling source/ R- | COLP_1.0.0.tar.gz |
8.6 KiB |
1.0.0 |
latest linux/jammy R-4.5 | COLP_1.0.0.tar.gz |
20.3 KiB |
1.0.0 |
latest linux/noble R-4.5 | COLP_1.0.0.tar.gz |
20.2 KiB |
1.0.0 |
latest source/ R- | COLP_1.0.0.tar.gz |
8.6 KiB |
1.0.0 |
2026-04-26 source/ R- | COLP_1.0.0.tar.gz |
8.6 KiB |
1.0.0 |
2026-04-23 source/ R- | COLP_1.0.0.tar.gz |
8.6 KiB |
1.0.0 |
2026-04-09 windows/windows R-4.5 | COLP_1.0.0.zip |
23.6 KiB |
1.0.0 |
2025-04-20 source/ R- | COLP_1.0.0.tar.gz |
8.6 KiB |