Package: OrdCD
Type: Package
Title: Ordinal Causal Discovery
Version: 1.1.2
Date: 2023-05-14
Authors@R: person(given = "Yang", family = "Ni", email = "yni@stat.tamu.edu", role = c("aut", "cre"), comment = c(ORCID = "0000-0003-0636-2363"))
Description: 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".
License: MIT + file LICENSE
Encoding: UTF-8
RoxygenNote: 7.2.3
Imports: gRbase, MASS, bnlearn, igraph, stats, Matrix
URL: https://github.com/nySTAT/OrdCD
BugReports: https://github.com/nySTAT/OrdCD/issues
NeedsCompilation: no
Packaged: 2023-05-17 19:27:50 UTC; yangni
Author: Yang Ni [aut, cre] (<https://orcid.org/0000-0003-0636-2363>)
Maintainer: Yang Ni <yni@stat.tamu.edu>
Repository: CRAN
Date/Publication: 2023-05-17 21:40:11 UTC
Built: R 4.6.0; ; 2026-04-26 04:24:15 UTC; unix
