cnFind: Find Network by Complexity

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

Description

This is a model selection routine that finds a network in a set of networks for a given complx.

Usage

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 cnFind(object, complx = 0, alpha=0, factor=1)
 cnFindKL(object, numsamples)

Arguments

object

catNetworkEvaluate or dagEvaluate or list of catNetworks

complx

an integer, target complx

alpha

a character or numeric

factor

a numeric

numsamples

an integer

Details

The complx must be at least the number of nodes of the networks. If no network with the requested complx exists in the list, then the one with the closest complx is returned. Alternatively, one can apply some standard model selection with alpha="BIC" and alpha=AIC.

Value

A catNetwork object.

Author(s)

N. Balov

See Also

cnFindAIC, cnFindBIC

Examples

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  cnet <- cnRandomCatnet(numnodes=10, maxpars=2, numcats=2)
  psamples <- cnSamples(object=cnet, numsamples=100)
  netlist <- cnSearchOrder(data=psamples, maxParentSet=2)
  bnet <- cnFind(object=netlist, complx=cnComplexity(cnet))
  bnet


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