# mb: Compute the Markov blanket In abn: Modelling Multivariate Data with Additive Bayesian Networks

 mb R Documentation

## 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`.

Gilles Kratzer

### 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 April 25, 2022, 9:06 a.m.