This function computes the Markov blanket of a set of nodes given a DAG (Directed Acyclic Graph).
Arguments
- dag
a matrix or a formula statement (see details for format) defining the network structure, a directed acyclic graph (DAG).
- node
a character vector of the nodes for which the Markov Blanket should be returned.
- data.dists
a named list giving the distribution for each node in the network, see details.
Details
This function returns the Markov Blanket of a set of nodes given a DAG.
The dag can be provided using a formula statement (similar to glm). A typical formula is ~ node1|parent1:parent2 + node2:node3|parent3. The formula statement have to start with ~. In this example, node1 has two parents (parent1 and parent2). node2 and node3 have the same parent3. The parents names have to exactly match those given in name. : is the separtor between either children or parents, | separates children (left side) and parents (right side), + separates terms, . replaces all the variables in name.
Examples
## Defining distribution and dag
dist <- list(a="gaussian", b="gaussian", c="gaussian", d="gaussian",
e="binomial", f="binomial")
dag <- matrix(c(0,1,1,0,1,0,
0,0,1,1,0,1,
0,0,0,0,0,0,
0,0,0,0,0,0,
0,0,0,0,0,1,
0,0,0,0,0,0), nrow = 6L, ncol = 6L, byrow = TRUE)
colnames(dag) <- rownames(dag) <- names(dist)
mb(dag, node = "b")
#> [1] "a" "c" "d" "f" "e"
mb(dag, node = c("b","e"))
#> [1] "a" "c" "d" "f" "e" "b"
mb(~a|b:c:e+b|c:d:f+e|f, node = "e", data.dists = dist)
#> [1] "a" "f" "b" "c"