mb {abn} | 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`

.

### 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*version 3.1.1 Index]