Package: Bestie
Type: Package
Title: Bayesian Estimation of Intervention Effects
Version: 0.1.5
Author: Jack Kuipers [aut,cre] and Giusi Moffa [aut]
Maintainer: Jack Kuipers <jack.kuipers@bsse.ethz.ch>
Description: An implementation of intervention effect estimation for
        DAGs (directed acyclic graphs) learned from binary or
        continuous data. First, parameters are estimated or sampled for
        the DAG and then interventions on each node (variable) are
        propagated through the network (do-calculus). Both exact
        computation (for continuous data or for binary data up to
        around 20 variables) and Monte Carlo schemes (for larger binary
        networks) are implemented.
License: GPL-3
Imports: BiDAG (>= 2.0.0), Rcpp (>= 1.0.3), mvtnorm (>= 1.1.0)
LinkingTo: Rcpp
Encoding: UTF-8
RoxygenNote: 7.1.2
NeedsCompilation: yes
Packaged: 2026-10-15 09:28:31 UTC; root
Config/pak/sysreqs: libglpk-dev libxml2-dev zlib1g-dev
Repository: https://jackkuipers.r-universe.dev
Date/Publication: 2022-04-28 12:10:02 UTC
RemoteUrl: https://github.com/cran/Bestie
RemoteRef: HEAD
RemoteSha: 1c4f01c0ed501ae77aec4051cd031c7fe0d42ef2