This function computes the Markov blanket of a set of nodes given a DAG (Directed Acyclic Graph).
mb(dag, node, data.dists=NULL)
a matrix or a formula statement (see details for format) defining the network structure, a directed acyclic graph (DAG).
a character vector of the nodes for which the Markov Blanket should be returned.
a named list giving the distribution for each node in the network, see details.
This function returns the Markov Blanket of a set of nodes given a DAG.
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
: is the separtor between either children or parents,
| separates children (left side) and parents (right side),
+ separates terms,
. replaces all the variables in
## 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") mb(dag, node = c("b","e")) mb(~a|b:c:e+b|c:d:f+e|f, node = "e", data.dists = dist)
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