Compile a graphical independence network (a Bayesian network)

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Description

Compiles a Bayesian network. This means creating a junction tree and establishing clique potentials.

Usage

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## S3 method for class 'grain'
compile(object, propagate = FALSE, root = NULL,
  control = object$control, details = 0, ...)

## S3 method for class 'CPTgrain'
compile(object, propagate = FALSE, root = NULL,
  control = object$control, details = 0, ...)

## S3 method for class 'POTgrain'
compile(object, propagate = FALSE, root = NULL,
  control = object$control, details = 0, ...)

Arguments

object

A grain object.

propagate

If TRUE the network is also propagated meaning that the cliques of the junction tree are calibrated to each other.

root

A set of variables which must be in the root of the junction tree

control

Controlling the compilation process.

details

For debugging info. Do not use.

...

Currently not used.

Value

A compiled Bayesian network; an object of class grain.

Author(s)

Søren Højsgaard, sorenh@math.aau.dk

References

Søren Højsgaard (2012). Graphical Independence Networks with the gRain Package for R. Journal of Statistical Software, 46(10), 1-26. http://www.jstatsoft.org/v46/i10/.

See Also

grain, propagate, triangulate, rip, junctionTree