cnNodeMarginalProb: Probability Calculations
In sdnet: Soft-Discretization-Based Bayesian Network Inference

Description Usage Arguments Details Value Author(s) See Also Examples

Marginal probability of a node, joint probability of a set of nodes or conditional probability of two sets of nodes.

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cnNodeMarginalProb(object, node)
cnJointProb(object, nodes)
cnCondProb(object, x, y)

`object`	a `catNetwork`
`node`	an `integer`, a node index in `object`
`nodes`	a `vector` of node names or indices in `object`
`x,y`	`vector`s of node categories (either characters or indices) named after nodes of `object`

cnJointProb returns a matrix with probability values for each combinations of categories arranged in columns. cnCondProb calculates the value of P(X=x|Y=y).

a numerical or numerical matrix

N. Balov

cnProb

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  cnet <- cnRandomCatnet(numnodes=10, maxpars=3, numcats=2)
  cnNodeMarginalProb(cnet, node=5)
  cnCondProb(cnet, x=c("N1"=1, "N2"=2), y=c("N3"=1, "N4"=2, "N5"=2))