mb: Compute the Markov blanket

In abn: Modelling Multivariate Data with Additive Bayesian Networks

Compute the Markov blanket

Description

This function computes the Markov blanket of a set of nodes given a DAG (Directed Acyclic Graph).

Usage

mb(dag, node, data.dists = NULL)

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.

Value

character vector of node names from the Markov blanket.

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")
mb(dag, node = c("b","e"))

mb(~a|b:c:e+b|c:d:f+e|f, node = "e", data.dists = dist)

abn documentation built on Nov. 3, 2023, 5:08 p.m.