OrdCD: Ordinal Causal Discovery
Algorithms for ordinal causal discovery. This package aims to enable users to discover causality for observational ordinal categorical data with greedy and exhaustive search. See Ni, Y., & Mallick, B. (2022) <https://proceedings.mlr.press/v180/ni22a/ni22a.pdf> "Ordinal Causal Discovery. Proceedings of the 38th Conference on Uncertainty in Artificial Intelligence, (UAI 2022), PMLR 180:1530–1540".
| Version: | 1.1.2 |
| Imports: | gRbase,MASS,bnlearn,igraph, stats,Matrix |
| Published: | 2023-05-17 |
| DOI: | 10.32614/CRAN.package.OrdCD |
| Author: | Yang Ni [aut, cre] |
| Maintainer: | Yang Ni <yni at stat.tamu.edu> |
| BugReports: | https://github.com/nySTAT/OrdCD/issues |
| License: | MIT + fileLICENSE |
| URL: | https://github.com/nySTAT/OrdCD |
| NeedsCompilation: | no |
| Materials: | README |
| CRAN checks: | OrdCD results |
Documentation:
| Reference manual: | OrdCD.html ,OrdCD.pdf |
Downloads:
| Package source: | OrdCD_1.1.2.tar.gz |
| Windows binaries: | r-devel:OrdCD_1.1.2.zip, r-release:OrdCD_1.1.2.zip, r-oldrel:OrdCD_1.1.2.zip |
| macOS binaries: | r-release (arm64):OrdCD_1.1.2.tgz, r-oldrel (arm64):OrdCD_1.1.2.tgz, r-release (x86_64):OrdCD_1.1.2.tgz, r-oldrel (x86_64):OrdCD_1.1.2.tgz |
| Old sources: | OrdCD archive |
Linking:
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