extractAIC (fit, scale, k = 2, ...) extractAIC.lm (fit, scale = 0, k = 2, ...) extractAIC.glm(fit, scale = 0, k = 2, ...) extractAIC.aov(fit, scale = 0, k = 2, ...) extractAIC.coxph (fit, scale, k = 2, ...) extractAIC.negbin (fit, scale, k = 2, ...) extractAIC.survreg(fit, scale, k = 2, ...)
fit
|
fitted model, usually the result of a fitter like lm .
|
scale
|
optional numeric specifying the scale parameter of the
model, see scale in step .
|
k
|
numeric specifying the ``weight'' of the
equivalent degrees of freedom (=:edf )
part in the AIC formula.
|
...
| further arguments (currently unused in base R). |
fit
, i.e.
AIC = - 2*log L + k * edf,
where L is the likelihood andedf
the equivalent degrees of freedom (i.e., the number of
parameters for usual parametric models) of fit
.lm
,
aov
, and glm
), -2log L is
the deviance, as computed by deviance(fit)
.
k = 2
corresponds to the traditional AIC, using k =
log(n)
provides the BIC (Bayes IC) instead.
For further information, particularly about scale
, see
step
.
edf
|
the ``equivalent degrees of freedom''
of the fitted model fit .
|
AIC
|
the (generalized) Akaike Information Criterion for fit .
|
add1
,
drop1
and step
and that may be their
main use.deviance
, add1
, step
example(glm) extractAIC(glm.D93)#>> 5 15.129