Description Usage Arguments Details See Also
KL
returns the Kullback-Leibler divergence between a Bayesian network and its update after parameter variation.
1 2 |
bnfit |
object of class bn.fit |
node |
character string. Node of which the conditional probability distribution is being changed. |
value_node |
character string. Level of |
value_parents |
character string. Levels of |
new_value |
numeric vector with elements between 0 and 1. Values to which the parameter should be updated. It can take a specific value or more than one. In the case in which the user wants to consider more than one value,these should be defined through a vector with an increasing order of the elements. |
covariation |
character string. Covariation scheme to be used for the updated Bayesian network. Can take values |
plot |
boolean value. If |
... |
additional parameters to be added to the plot. |
The Bayesian network on which parameter variation is being conducted should be expressed as a bn.fit object.
The name of the node to be varied, its level and its parent's level should be specified.
The parameter variation specified by the function is:
P ( node
= value_node
| parents = value_parents
) = new_value
Other dissimilarity measures: CD_distance
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