network.AIC {nem}R Documentation

AIC criterion for network graph

Description

Calclate AIC for a given network graph (should be transitively closed). The number of free parameters equals the number of unknown edges in the network graph.

Usage

        network.AIC(network,Pm=NULL,k=2,verbose=TRUE)

Arguments

network a nem object (e.g. 'pairwise')
Pm prior over models (n x n matrix). If NULL, then a matrix of 0s is assumed
k penalty per parameter in the AIC calculation. Default = 2 for classical AIC
verbose print out the result

Details

For k = log(n) the BIC (Schwarz criterion) is computed. Usually this function is not called directly but from nemModelSelection

Value

AIC value

Author(s)

Holger Froehlich

See Also

nemModelSelection

Examples

   data("BoutrosRNAi2002") 
   res1 <- nem.greedy(BoutrosRNAiDiscrete[,9:16],para=c(.13,.05))
   network.AIC(res1)
   res2 <- nem.greedy(BoutrosRNAiDiscrete[,9:16],para=c(.13,.05),lambda=10)
   network.AIC(res2)

[Package nem version 2.6.0 Index]