edge_entropy: Calculate entropy on model averaging results

In robertness/bninfo: Queries and information theoritic operations on Bayesian networks.

Description

Model averaging results, of the class "bn.learn" provide estimates of the probabilities the true network structure includes a given edge. This function calculates information entropy on those estimates. Entropy for each edge is calculated, then the average over all edges in the model averaging results is return. mean averaging entropy.

Usage

edge_entropy(strength, presence_only = FALSE)

Arguments

strength	The results of model averaging, class bn.strength, see functions boot.strength and custom.strength
presence_only	calculate entropy only for edge presence (either direction),

Value

a modified data frame with the entropy added as a column.

robertness/bninfo documentation built on May 27, 2019, 10:32 a.m.