AIC.oglmx {oglmx} | R Documentation |
Calculates the Akaike Information Criterion for objects of class oglmx
. Calculate using the formula -2*loglikelihood + k*npar
where npar
represents the number of parameters in the model and k
is the cost of additional parameters, equal to 2 for the AIC, it is k=\log(n)
with n
the number of observations for the BIC.
## S3 method for class 'oglmx'
AIC(object, ..., k = 2)
object |
object of class |
... |
additional arguments. Currently ignored. |
k |
the penalty per parameter to be used. |
When comparing models by maximium likelihood estimation the smaller the value of the AIC the better.
A numeric value with the AIC.
Nathan Carroll, nathan.carroll@ur.de
AIC
.