sensitivity: Sensitivity function

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

Description

sensitivity returns the sensitivity function for a probabilistic query of interest with respect to a parameter change defined by the user.

Usage

sensitivity(bnfit, interest_node, interest_node_value,
  evidence_nodes = NULL, evidence_states = NULL, node, value_node,
  value_parents, new_value, covariation = "orderp", plot = TRUE, ...)

Arguments

bnfit	object of class bn.fit
interest_node	character string. Node of the probability query of interest.
interest_node_value	character string. Level of interest_node
evidence_nodes	character string. Evidence nodes. If NULL no evidence is considerated. Set by default to NULL.
evidence_states	character string. Levels of evidence_nodes. If NULL no evidence is considerated. If evidence_nodes="NULL", evidence_states should be set to NULL. Set by default to NULL.
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 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. new_value can also take as value the character string all: in this case a sequence of possible parameter changes ranging from 0.05 to 0.95 will be considered.
covariation	character string. Covariation scheme to be used for the updated Bayesian network. Can take values uniform, proportional, orderp, all.If equal to all, uniform, proportional and order-preserving co-variation schemes will be considered. Set by default to proportional.
plot	boolean value. If TRUE the function returns a plot. If covariation = "all", sensitivity function for uniform (red), proportional (green), order-preserving (blue) co-variation schemes will be plotted. Set by default to TRUE.
...	additional parameters to be added to the plot.

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

and the probabilistic query of interest is:

P ( interest_node = interest_node_value | evidence_nodes = evidence_states )

See Also

Other sensitivity: sensquery

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