Description Usage Arguments Value Note Author(s) References See Also Examples
Set, update and remove evidence.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 | setEvidence(
object,
nodes = NULL,
states = NULL,
evidence = NULL,
nslist = NULL,
propagate = TRUE,
details = 0
)
retractEvidence(object, nodes = NULL, propagate = TRUE)
absorbEvidence(object, propagate = TRUE)
pEvidence(object)
getEvidence(object)
evidence(object)
## S3 method for class 'grain'
evidence(object)
evidence(object) <- value
## S3 replacement method for class 'grain'
evidence(object) <- value
|
object |
A "grain" object |
nodes |
A vector of nodes; those nodes for which the (conditional) distribution is requested. |
states |
A vector of states (of the nodes given by 'nodes') |
evidence |
An alternative way of specifying findings (evidence), see examples below. |
nslist |
deprecated |
propagate |
Should the network be propagated? |
details |
Debugging information |
value |
The evidence in the form of a named list or an evidence-object. |
A list of tables with potentials.
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is obsolete).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.
Søren Højsgaard, sorenh@math.aau.dk
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/.
setFinding
, getFinding
,
retractFinding
, pFinding
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 | data(chest_cpt)
chest.bn <- grain(compileCPT(chest_cpt))
chest.bn <- compile(chest.bn)
## 1) These two forms are identical
setEvidence(chest.bn, c("asia", "xray"), c("yes", "yes"))
setFinding(chest.bn, c("asia", "xray"), c("yes", "yes"))
## 2) Suppose we do not know with certainty whether a patient has
## recently been to Asia. We can then introduce a new variable
## "guess.asia" with "asia" as its only parent. Suppose
## p(guess.asia=yes|asia=yes)=.8 and p(guess.asia=yes|asia=no)=.1
## If the patient is e.g. unusually tanned we may set
## guess.asia=yes and propagate.
##
## This corresponds to modifying the model by the likelihood (0.8,
## 0.1) as
setEvidence(chest.bn, c("asia", "xray"), list(c(0.8, 0.1), "yes"))
## 3) Hence, the same result as in 1) can be obtained with
setEvidence(chest.bn, c("asia", "xray"), list(c(1, 0), "yes"))
## 4) An alternative specification using evidence is
setEvidence(chest.bn, evidence=list(asia=c(1, 0), xray="yes"))
|
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.