AIC | R Documentation |
Returns Akaike's information criterion for a set of FLSAM objects
AIC(object, ..., k = 2)
object |
An |
... |
Further |
k |
the _penalty_ per parameter to be used; the default 'k = 2' is the classical AIC. |
The AIC criteria can be used as a basis for comparing model fits in situations where a likelihood ratio test is not appropriate (i.e. the models are not nested). For more information see the help for AIC
in the stats package.
Numeric value
Based on code by Anders Nielsen in SAM. Adapted to FLSAM by Mark R. Payne.
lr.test
, AIC
#Load assessment
library(FLSAM)
data(NSH.sam)
#Extract AIC
AIC(NSH.sam)
#For more an FLSAMs
#data(HERAS.sams)
#plot(AIC(HERAS.sams),pch=16)
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