calcPnetLLike: Calculates the log likelihood for a set of data under a...

In ralmond/PNetica: Parameterized Bayesian Networks Netica Interface

Calculates the log likelihood for a set of data under a Pnet.NeticaBN model

Description

The method calcPnetLLike.NeticaBN calculates the log likelihood for a set of data contained in cases using the current conditional probability tables in a Pnet.NeticaBN. Here cases should be the filename of a Netica case file (see write.CaseFile).

Usage

## S4 method for signature 'NeticaBN'
calcPnetLLike(net, cases)

Arguments

net	A Pnet.NeticaBN object representing a parameterized network.
cases	A character scalar giving the file name of a Netica case file (see write.CaseFile).

Details

This function provides the convergence test for the GEMfit algorithm. The Pnet.NeticaBN represents a model (with parameters set to the value used in the current iteration of the EM algorithm) and cases a set of data. This function gives the log likelihood of the data.

This method expects the cases argument to be a pathname pointing to a Netica cases file containing the training or test data (see write.CaseFile). Also, it expects that there is a nodeset (see NetworkNodesInSet) attached to the network called “onodes” which references the observable variables in the case file.

As Netica does not have an API function to directly calculate the log-likelihood of a set of cases, this method loops through the cases in the case set and calls FindingsProbability(net) for each one. Note that if there are frequencies in the case file, each case is weighted by its frequency.

Value

A numeric scalar giving the log likelihood of the data in the case file.

Author(s)

Russell Almond

References

Almond, R. G. (2015) An IRT-based Parameterization for Conditional Probability Tables. Paper presented at the 2015 Bayesian Application Workshop at the Uncertainty in Artificial Intelligence Conference.

See Also

Pnet, Pnet.NeticaBN, GEMfit, calcExpTables, BuildAllTables, maxAllTableParams NetworkNodesInSet, FindingsProbability, write.CaseFile

Examples

sess <- NeticaSession()
startSession(sess)

irt10.base <- ReadNetworks(system.file("testnets","IRT10.2PL.base.dne",
                          package="PNetica"), session=sess)
irt10.base <- as.Pnet(irt10.base)  ## Flag as Pnet, fields already set.
irt10.theta <- NetworkFindNode(irt10.base,"theta")
irt10.items <- PnetPnodes(irt10.base)
## Flag items as Pnodes
for (i in 1:length(irt10.items)) {
  irt10.items[[i]] <- as.Pnode(irt10.items[[i]])
}
CompileNetwork(irt10.base) ## Netica requirement

casepath <- system.file("testdat","IRT10.2PL.200.items.cas",
                        package="PNetica")
## Record which nodes in the casefile we should pay attention to
NetworkNodesInSet(irt10.base,"onodes") <-
   NetworkNodesInSet(irt10.base,"observables")

llike <- calcPnetLLike(irt10.base,casepath)

DeleteNetwork(irt10.base)
stopSession(sess)

ralmond/PNetica documentation built on Sept. 19, 2023, 8:27 a.m.