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
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
NeedsCompilation: no
Packaged: 2026-06-18 23:33:59 UTC; alessandromascaro
Author: Federico Castelletti [aut],
  Alessandro Mascaro [aut, cre, cph]
Maintainer: Alessandro Mascaro <alessandromascaro@outlook.it>
Repository: CRAN
Date/Publication: 2026-06-21 14:10:40 UTC
Built: R 4.5.2; ; 2026-06-21 15:24:51 UTC; unix
