EnterIntervalFinding {RNetica} | R Documentation |
Sets the finding associate with node to an interval.
EnterIntervalFinding(node, low, high, retractFirst = TRUE)
node |
An active |
low |
Lower bound of interval. |
high |
Upper bound of interval. |
retractFirst |
A logical value. If true, any previous findings will be retracted first. |
The node
must a continuous node that has
been discretized using NodeLevels(node)
. The
probabilities for each state are calculated based on a uniform
distribution with the given low
and high
endpoints.
Return the node
argument invisibly.
The internal Netica function EnterIntervalFinding_bn is not behaving
at all like what I expected. In particular, I expect that it would
behave like a uniform likelihood, but instead it seems to be behaving
as if I typed the expression NodeValue(node)<-low
. I've
queried Norsys about this.
Meanwhile, I've worked around by calling NodeLikelihood
instead of the internal Netica function.
Russell Almond
http://norsys.com/onLineAPIManual/index.html: EnterIntervalFinding_bn()
EnterNegativeFinding()
, EnterFindings()
,
RetractNodeFinding()
, NodeLikelihood()
,
NodeFinding()
, EnterGaussianFinding()
,
NodeValue()
sess <- NeticaSession() startSession(sess) cirt5 <- CreateNetwork("ContinuousIRT5", session=sess) theta <- NewContinuousNode(cirt5,"Theta") NodeLevels(theta) <- c(-5,-2.5,-1.5,-0.5,0.5,1.5,2.5,5) NodeProbs(theta) <- rep(1/NodeNumStates(theta),NodeNumStates(theta)) CompileNetwork(cirt5) ## Ready to enter findings EnterIntervalFinding(theta,-1,1) NodeBeliefs(theta) stopifnot(all(abs(NodeBeliefs(theta)*4-c(0,0,1,2,1,0,0))<.0001)) DeleteNetwork(cirt5) stopSession(sess)