ClusterTree-class {BayesNetBP} | R Documentation |

## An S4 class of the cluster tree.

### Description

The `ClusterTree`

object is the computational object for belief propagation.

### Slots

`cluster`

A

`vector`

storing the name of clusters in the cluster tree.`node`

A

`vector`

storing the name of nodes in the Bayesian network.`graph`

A

`list`

of two graphNEL objects:`$dag`

stores the graph of Bayesian network,`$tree`

stores the graph of the cluster tree.`member`

A named

`list`

of the node cluster membership.`parent`

A named

`vector`

indicating the parent node of a given cluster in the cluster tree.`cluster.class`

A named

`vector`

of logical values indicating whether a cluster is continuous or discrete.`node.class`

A named

`vector`

of logical values indicating whether a node is continuous or discrete.`assignment`

A named

`list`

indicating the assignment of discrete nodes discrete clusters.`propagated`

A

`logical`

value indicating whether the discrete compartment has been propagated.`cpt`

A named

`list`

of the conditional probability tables.`jpt`

A named

`list`

of the joint distribution tables.`lppotential`

A named

`list`

of the linear predictor potentials assigned to each cluster in the lppotential slots.`postbag`

A named

`list`

of the linear predictor potentials assigned to each cluster in the postbag slots.`activeflag`

A named

`vector`

of logical values indicating whether a continuous cluster is active.`absorbed.variables`

A

`vector`

of characters indicating variables observed with hard evidence.`absorbed.values`

A

`list`

indicating the values of the variables observed with hard evidence.`absorbed.soft.variables`

A

`vector`

of characters indicating variables observed with soft or likelihood evidence.`absorbed.soft.values`

A

`list`

of the likelihoods of the soft or likelihood evidence.

*BayesNetBP*version 1.6.1 Index]