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Discover causality for bivariate categorical data. This package aims to enable users to discover causality for bivariate observational categorical data. See Ni, Y. (2022) <doi:10.48550/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 |
DOI: | 10.32614/CRAN.package.COLP |
Author: | Yang Ni [aut, cre] |
Maintainer: | Yang Ni <yni at stat.tamu.edu> |
BugReports: | https://github.com/nySTAT/COLP/issues |
License: | MIT + file LICENSE |
URL: | https://github.com/nySTAT/COLP |
NeedsCompilation: | no |
CRAN checks: | COLP results |
Reference manual: | COLP.pdf |
Package source: | COLP_1.0.0.tar.gz |
Windows binaries: | r-devel: COLP_1.0.0.zip, r-release: COLP_1.0.0.zip, r-oldrel: COLP_1.0.0.zip |
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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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.