network.AIC {nem} | R Documentation |
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.
network.AIC(network,Pm=NULL,k=2,verbose=TRUE)
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 |
For k = log(n) the BIC (Schwarz criterion) is computed. Usually this function is not called directly but from nemModelSelection
AIC value
Holger Froehlich
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)