Package: BCDAG
Title: Bayesian Structure and Causal Learning of Gaussian Directed
        Graphs
Version: 1.1.4
Authors@R: 
    c(person(given = "Federico",
           family = "Castelletti",
           role = "aut",
           email = "federico.castelletti@unicatt.it"),
           person(given = "Alessandro",
           family = "Mascaro",
           role = c("aut", "cre", "cph"),
           email = "alessandromascaro@outlook.it"))
Description: A collection of functions for structure learning of causal
        networks and estimation of joint causal effects from
        observational Gaussian data. Main algorithm consists of a
        Markov chain Monte Carlo scheme for posterior inference of
        causal structures, parameters and causal effects between
        variables. References: F. Castelletti and A. Mascaro (2021)
        <doi:10.1007/s10260-021-00579-1>, F. Castelletti and A. Mascaro
        (2022) <doi:10.48550/arXiv.2201.12003>, F. Castelletti and A.
        Mascaro (2026) <doi:10.18637/jss.v116.i05>.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Roxygen: list(markdown = TRUE)
RoxygenNote: 7.3.2
biocViews:
Imports: graph, graphics, gRbase, Rgraphviz, grDevices, lattice,
        methods, mvtnorm, stats, utils
Suggests: rmarkdown, knitr, testthat (>= 3.0.0)
Config/testthat/edition: 3
VignetteBuilder: knitr
Depends: R (>= 2.10)
URL: https://github.com/alesmascaro/BCDAG
BugReports: https://github.com/alesmascaro/BCDAG/issues
Config/pak/sysreqs: libglpk-dev libxml2-dev zlib1g-dev
Repository: https://alesmascaro.r-universe.dev
Date/Publication: 2026-06-18 23:27:38 UTC
RemoteUrl: https://github.com/alesmascaro/bcdag
RemoteRef: HEAD
RemoteSha: 8280d0cc5da583daee566a5f33fba60adb1c7220
NeedsCompilation: no
Packaged: 2026-06-19 00:11:31 UTC; root
Author: Federico Castelletti [aut],
  Alessandro Mascaro [aut, cre, cph]
Maintainer: Alessandro Mascaro <alessandromascaro@outlook.it>