OrdCD: Ordinal Causal Discovery (original) (raw)
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 |
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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 |
BugReports: | https://github.com/nySTAT/OrdCD/issues |
License: | MIT + file |
URL: | https://github.com/nySTAT/OrdCD |
NeedsCompilation: | no |
Materials: | README |
CRAN checks: | OrdCD results |
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