Bayesian Estimation of Intervention Effects

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.


Reference manual

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0.1.3 by Jack Kuipers, 2 months ago

Browse source code at

Authors: Jack Kuipers [aut,cre] and Giusi Moffa [aut]

Documentation:   PDF Manual  

GPL-3 license

Imports BiDAG, Rcpp, mvtnorm

Linking to Rcpp

See at CRAN