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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".
Getting started
Browse package contents
Package details |
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| Author | Yang Ni [aut, cre] (<https://orcid.org/0000-0003-0636-2363>) |
| Maintainer | Yang Ni <yni@stat.tamu.edu> |
| License | MIT + file LICENSE |
| Version | 1.1.2 |
| URL | https://github.com/nySTAT/OrdCD |
| Package repository | View on CRAN |
| Installation |
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