gRaven-package {gRaven}

Bayes Nets: 'RHugin' Emulation with 'gRain'

Description

Wrappers for functions in the 'gRain' package to emulate some 'RHugin' functionality, allowing the building of Bayesian networks consisting on discrete chance nodes incrementally, through adding nodes, edges and conditional probability tables, the setting of evidence, both 'hard' (boolean) or 'soft' (likelihoods), querying marginal probabilities and normalizing constants, and generating sets of high-probability configurations. Computations will typically not be so fast as they are with 'RHugin', but this package should assist users without access to 'Hugin' to use code written to use 'RHugin'.

Author(s)

Maintainer: Peter Green <[e-mail]>

Examples

library(gRaven)
rm(list=ls(all=TRUE))

yn <- c("yes","no")
chest<-hugin.domain()

add.node(chest,"asia",states=yn)
add.node(chest,"tub",states=yn)
add.node(chest,"smoke",states=yn)
add.node(chest,"lung",states=yn)
add.node(chest,"bronc",states=yn)
add.node(chest,"either",states=yn)
add.node(chest,"xray",states=yn)
add.node(chest,"dysp",states=yn)

add.edge(chest,"tub","asia")
add.edge(chest,"lung","smoke")
add.edge(chest,"bronc","smoke")
add.edge(chest,"either","lung")
add.edge(chest,"either","tub")
add.edge(chest,"xray","either")
add.edge(chest,"dysp","bronc")
add.edge(chest,"dysp","either")

set.table(chest,"asia",c(0.01,0.99))
set.table(chest,"tub",c(0.05,0.95,0.01,0.99))
set.table(chest,"smoke",c(0.5,0.5))
set.table(chest,"lung",c(0.1,0.9,0.01,0.99))
set.table(chest,"bronc",c(0.6,0.4,0.3,0.7))
set.table(chest,"either",c(1,0,1,0,1,0,0,1))
set.table(chest,"xray",c(0.98,0.02,0.05,0.95))
set.table(chest,"dysp",c(0.9,0.1,0.7,0.3,0.8,0.2,0.1,0.9))

chest
get.nodes(chest)
chest$states
sapply(get.nodes(chest),function(x) get.parents(chest,x))
compile(chest)
chest
get.belief(chest,"asia")
get.belief(chest,"tub")
get.belief(chest,"lung")
get.belief(chest,"bronc")
sapply(get.nodes(chest),function(x) get.belief(chest,x)) 

c2<-clone.domain(chest)

set.finding(chest,"asia","yes")
set.finding(chest,"dysp","yes")
propagate(chest)

get.belief(chest,"asia")
get.belief(chest,"tub")
get.belief(chest,"lung")
get.belief(chest,"bronc")

pEvidence(chest$net)
get.normalization.constant(chest)

pEvidence(c2$net,evidence=list(asia="yes",dysp="yes"))
get.normalization.constant(c2)