Aikake's an information criterion — AIC.fixest • fixest

This function computes the AIC (Aikake's, an information criterion) from a fixest estimation.

Usage

# S3 method for class 'fixest'
AIC(object, ..., k = 2)

Arguments

object: A fixest object. Obtained using the functions femlm, feols or feglm.
...: Optionally, more fitted objects.
k: A numeric, the penalty per parameter to be used; the default k = 2 is the classical AIC (i.e. AIC=-2*LL+k*nparams).

Value

It return a numeric vector, with length the same as the number of objects taken as arguments.

Details

The AIC is computed as: $$AIC = -2\times LogLikelihood + k\times nbParams$$ with k the penalty parameter.

You can have more information on this criterion on AIC.

See also

See also the main estimation functions femlm, feols or feglm. Other statictics methods: BIC.fixest, logLik.fixest, nobs.fixest.

Author

Laurent Berge

Examples


# two fitted models with different expl. variables:
res1 = femlm(Sepal.Length ~ Sepal.Width + Petal.Length +
             Petal.Width | Species, iris)
res2 = femlm(Sepal.Length ~ Petal.Width | Species, iris)

AIC(res1, res2)
#> [1] 557.6455 556.9454
BIC(res1, res2)
#> [1] 575.7093 568.9879