Bayesian information criterion — BIC.fixest • fixest

This function computes the BIC (Bayesian information criterion) from a fixest estimation.

Usage

# S3 method for class 'fixest'
BIC(object, ...)

Arguments

object: A fixest object. Obtained using the functions femlm, feols or feglm.
...: Optionally, more fitted objects.

Value

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

Details

The BIC is computed as follows: $$BIC = -2\times LogLikelihood + \log(nobs)\times nbParams$$ 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 statistics functions: AIC.fixest, logLik.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