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MuMIn (version 0.13.3)

AICc: Second-order Akaike Information Criterion

Description

Calculates second-order Akaike information criterion for one or several fitted model objects (AIC for small samples).

Usage

AICc(object, ..., k = 2)

Arguments

object
a fitted model object
...
optionally more fitted model objects
k
the penalty per parameter to be used; the default k = 2 is the classical AIC

Value

  • If just one object is provided, returns a numeric value with the corresponding AICc; if more than one object are provided, returns a data.frame with rows corresponding to the objects and columns representing the number of parameters in the model (df), AICc and the AIC.

encoding

utf-8

References

Burnham, K. P. and Anderson, D. R (2002) Model selection and multimodel inference: a practical information-theoretic approach. 2nd ed.

See Also

Akaike's An Information Criterion: AIC