components_gather: Compile conditional probability tables / cliques potentials.

In DataSciBurgoon/gRain: Graphical Independence Networks

Description

Compile conditional probability tables / cliques potentials as a preprocessing step for creating a graphical independence network

Usage

compileCPT(x, ..., forceCheck = TRUE)

compilePOT(x, ..., forceCheck = TRUE)

Arguments

x	To compileCPT x is a list of conditional probability tables; to compilePOT, x is a list of clique potentials.
...	Additional arguments; currently not used.
forceCheck	Controls if consistency checks of the probability tables should be made.

Details

* `compileCPT` is relevant for turning a collection of
cptable's into an object from which a network can be built. For
example, when specification of a cpt is made with cptable then
the levels of the node is given but not the levels of the
parents. `compileCPT` checks that the levels of variables in
the cpt's are consistent and also that the specifications
define a dag.

* `compilePOT` is not of direct relevance for the
user for the moment. However, the elements of the input should
be arrays which define a chordal undirected graph and the
arrays should, if multiplied, form a valid probability density.

Value

A list with a class attribute.

Author(s)

Søren Højsgaard, [e-mail]

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

extractCPT, extractPOT, extractMARG

Examples

data(chest_cpt)
x <- compileCPT(chest_cpt)
class(x)
grain(x)

## FIXME: compileCPT/compilePOT examples missing.

DataSciBurgoon/gRain documentation built on March 25, 2020, 12:02 a.m.