Package: BCDAG
Title: Bayesian Structure and Causal Learning of Gaussian Directed
        Graphs
Version: 1.0.0
Authors@R: 
    c(person(given = "Federico",
           family = "Castelletti",
           role = "aut",
           email = "federico.castelletti@unicatt.it"),
           person(given = "Alessandro",
           family = "Mascaro",
           role = c("aut", "cre"),
           email = "a.mascaro3@campus.unimib.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) <arXiv:2201.12003>.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
biocViews:
Imports: graphics, gRbase, grDevices, lattice, methods, mvtnorm, stats,
        utils
Suggests: rmarkdown, knitr, testthat (>= 3.0.0)
Config/testthat/edition: 3
VignetteBuilder: knitr
Depends: R (>= 2.10)
NeedsCompilation: no
Packaged: 2022-03-14 17:39:44 UTC; aless
Author: Federico Castelletti [aut],
  Alessandro Mascaro [aut, cre]
Maintainer: Alessandro Mascaro <a.mascaro3@campus.unimib.it>
Repository: CRAN
Date/Publication: 2022-03-15 19:00:02 UTC
Built: R 4.0.5; ; 2022-03-16 10:48:05 UTC; unix
