proportional_covar: Proportional co-variation scheme

In rramsiya/bnsens: Sensitivity analysis for discrete data in Bayesian networks

Description

proportional_covar returns an updated Bayesian network using proportional co-variation scheme.

Usage

proportional_covar(bnfit, node, value_node, value_parents, new_value)

Arguments

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 node.
value_parents	character string. Levels of node's parents. The levels should be defined according to the order of the parents in bnfit[[node]][["parents"]]. If node has no parents, then should be set to NULL.
new_value	numeric value between 0 and 1. Value to which the parameter should be updated.

Details

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

See Also

Other co-variation schemes: orderp_covar, uniform_covar

rramsiya/bnsens documentation built on Sept. 30, 2020, 3:28 p.m.