Test for d-separation in a DAG
dsepTest(x, y, S=NULL, suffStat)
x,y |
(integer) position of variable X and Y, respectively, in the adjacency matrix. |
S |
(integer) positions of zero or more conditioning variables in the adjacency matrix. |
suffStat |
a
|
The function is based on dsep. For details on
d-separation see the reference Lauritzen (2004).
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.
Markus Kalisch (kalisch@stat.math.ethz.ch)
S.L. Lauritzen (2004), Graphical Models, Oxford University Press.
dsepAMTest for a similar function for MAGs.
gaussCItest, disCItest and
binCItest for similar functions for a conditional
independence test for gaussian, discrete and
binary variables, respectively.
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 4Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.