Aikake's an information criterion
This function computes the AIC (Aikake's, an information criterion) from a fixest estimation.
## S3 method for class 'fixest' AIC(object, ..., k = 2)
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.
It return a numeric vector, with length the same as the number of objects taken as arguments.
Laurent Berge
See also the main estimation functions femlm, feols or feglm. Other statictics methods: BIC.fixest, logLik.fixest, nobs.fixest.
# 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)
BIC(res1, res2)Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.