Package: cia
Title: Learn and Apply Directed Acyclic Graphs for Causal Inference
Version: 1.0.0
Authors@R: c(
    person(given = "Mathew",
           family = "Varidel",
           role = c("aut", "cre", "cph"),
           email = "mathew.varidel@sydney.edu.au",
           comment = c(ORCID = "0000-0002-1648-8317")),
    person(given = "Victor",
           family = "An",
           role = c("ctb"),
           email = "victor.an@sydney.edu.au")
    )
Description: Causal Inference Assistance (CIA) for performing causal inference within the structural causal modelling framework. Structure learning is performed using partition Markov chain Monte Carlo (Kuipers & Moffa, 2017) and several additional functions have been added to help with causal inference. Kuipers and Moffa (2017) <doi:10.1080/01621459.2015.1133426>.
License: MIT + file LICENSE
Encoding: UTF-8
RoxygenNote: 7.3.1
Depends: R (>= 4.4.0)
Imports: bnlearn (>= 4.9), igraph, doParallel, parallel, foreach,
        arrangements, graphics, dplyr, rlang, fastmatch, methods,
        gRain, patchwork, tidyr
Suggests: rmarkdown, knitr, testthat (>= 3.0.0), gtools, gRbase,
        ggplot2, qgraph, dagitty
Config/testthat/edition: 3
URL: https://spaceodyssey.github.io/cia/
BugReports: https://github.com/SpaceOdyssey/cia/issues
NeedsCompilation: no
Packaged: 2024-11-11 21:41:08 UTC; mvar0005
Author: Mathew Varidel [aut, cre, cph]
    (<https://orcid.org/0000-0002-1648-8317>),
  Victor An [ctb]
Maintainer: Mathew Varidel <mathew.varidel@sydney.edu.au>
Repository: CRAN
Date/Publication: 2024-11-13 14:00:07 UTC
Built: R 4.6.0; ; 2026-04-30 08:59:45 UTC; unix
