cnFindAIC-method {sdnet} | R Documentation |
This is a model selection routine that finds a network in a set of networks using the AIC criteria.
cnFindAIC(object, numsamples)
object |
A |
numsamples |
an |
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
.
A catNetwork
object with optimal AIC value.
N. Balov
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