Set, retrieve, and retract finding in Bayesian network.

Set, retrieve, and retract finding in Bayesian network. NOTICE: The functions described here are kept only for backward compatibility; please use the corresponding evidence-functions in the future.

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

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, see examples below.

propagate

Should the network be propagated?

Note

NOTICE: The functions described here are kept only for backward compatibility; please use the corresponding evidence-functions in the future:

setEvidence() is an improvement of setFinding() (and as such setFinding is obsolete). Users are recommended to use setEvidence() in the future.

setEvidence() allows to specification of "hard evidence" (specific values for variables) and likelihood evidence (also known as virtual evidence) for variables.

The syntax of setEvidence() may change in the future.

References

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

See also

setEvidence, getEvidence, retractEvidence, pEvidence, querygrain

Author

Søren Højsgaard, sorenh@math.aau.dk

Examples

## setFindings
yn <- c("yes", "no")
a    <- cpt(~asia, values=c(1, 99),levels=yn)
t.a  <- cpt(~tub+asia, values=c(5, 95, 1, 99),levels=yn)
s    <- cpt(~smoke, values=c(5,5), levels=yn)
l.s  <- cpt(~lung+smoke, values=c(1, 9, 1, 99), levels=yn)
b.s  <- cpt(~bronc+smoke, values=c(6, 4, 3, 7), levels=yn)
e.lt <- cpt(~either+lung+tub,values=c(1, 0, 1, 0, 1, 0, 0, 1),levels=yn)
x.e  <- cpt(~xray+either, values=c(98, 2, 5, 95), levels=yn)
d.be <- cpt(~dysp+bronc+either, values=c(9, 1, 7, 3, 8, 2, 1, 9), levels=yn)
chest.cpt <- compileCPT(a, t.a, s, l.s, b.s, e.lt, x.e, d.be)
chest.bn <- grain(chest.cpt)

## These two forms are equivalent
bn1 <- setFinding(chest.bn, nodes=c("chest", "xray"), states=c("yes", "yes"))
bn2 <- setFinding(chest.bn, flist=list(c("chest", "yes"), c("xray", "yes")))

getFinding(bn1)
#>   nodes is_hard hard_state evi_weight
#> 1  xray    TRUE        yes       1, 0
getFinding(bn2)
#>   nodes is_hard hard_state evi_weight
#> 1  xray    TRUE        yes       1, 0

pFinding(bn1)
#> [1] 0.11029
pFinding(bn2)
#> [1] 0.11029

bn1 <- retractFinding(bn1, nodes="asia")
bn2 <- retractFinding(bn2, nodes="asia")

getFinding(bn1)
#>   nodes is_hard hard_state evi_weight
#> 1  xray    TRUE        yes       1, 0
getFinding(bn2)
#>   nodes is_hard hard_state evi_weight
#> 1  xray    TRUE        yes       1, 0

pFinding(bn1)
#> [1] 0.11029
pFinding(bn2)
#> [1] 0.11029