Akaike information criterion

The Akaike Information Criterion (AIC) is a statistical measure used for model selection among a set of models. It is particularly useful when comparing different statistical models fitted to the same dataset. The AIC provides a means to evaluate how well a model explains the data, while also accounting for the complexity of the model to prevent overfitting.