| KL | R Documentation | 
KL returns the Kullback-Leibler divergence between a Bayesian network and its update after parameter variation.
KL(bnfit, node, value_node, value_parents, new_value,
  covariation = "proportional", plot = TRUE, ...)
| 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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