pcalg (version 2.0-3)

dsepTest: Test for d-separation in a DAG

Description

Tests for d-separation of nodes in a DAG. dsepTest() is written to be easily used in skeleton, pc, fci.

Usage

dsepTest(x, y, S=NULL, suffStat)

Arguments

x,y

integer position of variable x and y in the adjacency matrix.

S

integer positions of conditioning variables in the adjacency matrix, possibly empty.

suffStat

a list with two elements, [object Object],[object Object]

Value

• If x and y are d-separated by S in DAG G the result is 1, otherwise it is 0. This is analogous to the p-value of an ideal (without sampling error) conditional independence test on any distribution that is faithful to the DAG G.

Details

The function is based on dsep. For details on d-separation see the reference Lauritzen (2004).

References

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

See Also

gaussCItest, disCItest and binCItest for similar functions for a conditional independence test for gaussian, discrete and binary variables, respectively.

Examples

p <- 8
set.seed(45)
myDAG <- randomDAG(p, prob = 0.3)

if (require(Rgraphviz)) {
## plot the DAG
plot(myDAG, main = "randomDAG(10, prob = 0.2)")
}

## define sufficient statistics (d-separation oracle)
suffStat <- list(g = myDAG, jp = RBGL::johnson.all.pairs.sp(myDAG))

dsepTest(1,6, S= NULL,  suffStat) ## not d-separated
dsepTest(1,6, S= 3,     suffStat) ## not d-separated by node 3
dsepTest(1,6, S= c(3,4),suffStat) ## d-separated by node 3 and 4