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: 2022-04-28 12:38:40 UTC; jkuipers
Repository: CRAN
Date/Publication: 2022-04-28 13:10:02 UTC
Built: R 4.6.0; x86_64-apple-darwin20; 2026-04-28 23:47:58 UTC; unix
Archs: Bestie.so.dSYM
