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)".

Version: 1.0.0
Depends: R (≥ 3.5.0)
Imports: MASS, combinat, stats
Published: 2022-09-29
Author: Yang Ni ORCID iD [aut, cre]
Maintainer: Yang Ni <yni at>
License: MIT + file LICENSE
NeedsCompilation: no
CRAN checks: COLP results


Reference manual: COLP.pdf


Package source: COLP_1.0.0.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): COLP_1.0.0.tgz, r-oldrel (arm64): COLP_1.0.0.tgz, r-release (x86_64): COLP_1.0.0.tgz, r-oldrel (x86_64): COLP_1.0.0.tgz


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