gRain (version 0.6.0)

querygm: Query an independence network

Description

Query an independence network, i.e. obtain the conditional distribution of a set of variables given finding (evidence) on other variables.

Usage

querygm(object, nodes = nodeNames(object), normalize = TRUE, type =
c("marginal", "joint", "conditional"), return="array", trace = 0)

setFinding(object, nodes=NULL, states=NULL, flist=NULL, propagate=TRUE)
retractFinding(object, nodes=NULL, propagate=TRUE)
getFinding(object)
pFinding(object)

Arguments

object

A "grain" object

nodes

A vector of nodes

states

A vector of states (of the nodes given by 'nodes')

flist

An alternative way of specifying findings (evidence), see examples below.

propagate

Should the network be propagated?

normalize

Should the results be normalized to sum to one.

type

Should marginals (for each node), the joint for all nodes, or the conditional of the first node given the rest be returned.

return

If "data.frame" the result is returned as a data frame (or possibly as a list of dataframes).

trace

Debugging information

Value

• A list of tables with potentials

See Also

cptable

Examples

testfile <- system.file("huginex", "chest_clinic.net", package = "gRain")
 chest <- as.grain(loadHuginNet(testfile, trace=1))
 print(class(chest))

 qb <- querygm(chest)
 qb

 lapply(qb, as.numeric) # Safe
 sapply(qb, as.numeric) # Risky