Bayesian Estimation of Intervention Effects

An implementation of intervention effect estimation for DAGs (directed acyclic graphs) learned from binary 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 (up to around 20 variables) and Monte Carlo schemes (for larger networks) are implemented.


Reference manual

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0.1.2 by Jack Kuipers, 7 months ago

Browse source code at

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

Documentation:   PDF Manual  

GPL-3 license

Imports BiDAG, Rcpp

Linking to Rcpp

See at CRAN