dsep: Test for d-separation in a DAG

In pcalg: Methods for Graphical Models and Causal Inference

Test for d-separation in a DAG

Description

This function tests for d-separation of nodes in a DAG.

Usage

dsep(a, b, S=NULL, g, john.pairs = NULL)

Arguments

a	Label (sic!) of node A
b	Label (sic!) of node B
S	Labels (sic!) of set of nodes on which it is conditioned, maybe empty
g	The Directed Acyclic Graph (object of class "graph", see graph-class from the package graph)
john.pairs	The shortest path distance matrix for all pairs of nodes as computed (also by default) in johnson.all.pairs.sp from package RBGL.

Details

This function checks separation in the moralized graph as explained in Lauritzen (2004).

Value

TRUE if a and b are d-separated by S in G, otherwise FALSE.

Author(s)

Markus Kalisch ([e-mail])

References

S.L. Lauritzen (2004), Graphical Models, Oxford University Press, Chapter 3.2.2

See Also

dsepTest for a wrapper of this function that can easily be included into skeleton, pc, fci or fciPlus. dsepAM for a similar function for MAGs.

Examples

## generate random DAG
p <- 8
set.seed(45)
myDAG <- randomDAG(p, prob = 0.3)
if (require(Rgraphviz)) {
plot(myDAG)
}

## Examples for d-separation
dsep("1","7",NULL,myDAG)
dsep("4","5",NULL,myDAG)
dsep("4","5","2",myDAG)
dsep("4","5",c("2","3"),myDAG)

## Examples for d-connection
dsep("1","3",NULL,myDAG)
dsep("1","6","3",myDAG)
dsep("4","5","8",myDAG)

pcalg documentation built on Sept. 26, 2023, 9:06 a.m.