sdnet (version 2.4.1)

cnFindAIC-method: Find Network by AIC

Description

This is a model selection routine that finds a network in a set of networks using the AIC criteria.

Usage

cnFindAIC(object, numsamples)

Arguments

object

A list of catNetwork objects or catNetworkEvaluate or dagEvaluate

numsamples

an integer

Value

A catNetwork object with optimal AIC value.

Details

The function returns the network with maximal AIC value from a list of networks as obtained from one of the search-functions cnSearchOrder, cnSearchSA and cnSearchSAcluster. The formula used for the AIC is log(Likelihood) - Complexity.

See Also

cnFind, cnFindBIC

Examples

# NOT RUN {
  cnet <- cnRandomCatnet(numnodes=12, maxpars=3, numcats=2)
  psamples <- cnSamples(object=cnet, numsamples=10)
  nodeOrder <- sample(1:12)
  nets <- cnSearchOrder(data=psamples, pert=NULL, 
	maxParentSet=2, maxComplexity=36, nodeOrder)
  aicnet <- cnFindAIC(object=nets)
  aicnet
# }