| ewi {bnmonitor} | R Documentation |
Edge-weigthed influence
Description
Computation of the edge-weigthed influence in a Bayesian network
Usage
ewi(bnfit, node)
Arguments
bnfit |
object of class |
node |
a node of |
Details
The edge-weigthed influence of a node X_j on an output node X_i in a Bayesian network is
EWI(X_j,X_i)= \sum_{s\in S_{ji}}\left(\prod_{(k,l)\in s}\delta_{kl}\right)^{|s|},
where S_{ji} is the set of active trails between X_j and X_i, \delta_{kl} is the strength of an edge between X_k and X_l, and |s| is the length of the trail s.
Value
A dataframe with the following columns: Nodes - the vertices of the BN; Influence - the edge-weigthed influence of the corresponding node.
References
Leonelli, M., Smith, J. Q., & Wright, S. K. (2024). The diameter of a stochastic matrix: A new measure for sensitivity analysis in Bayesian networks. arXiv preprint arXiv:2407.04667.
See Also
mutual_info, dwi, edge_strength
Examples
ewi(travel, "T")