40 Akaike information criterion;41 AIC; It is a measure of the relative quality of a statistical model for a given set of data. As such, AIC provides a means for the selection of the model.AIC is responsible for compensation between the goodness of fit of the model and the complexity of the model. It is based on the theory of information: provides a relative estimation of the information lost when a given model is used to represent the process that generates the data.AIC does not provide proof of a model in the sense of to test a null hypothesis; i.e. AIC can say nothing about the quality of the model in an absolute sense. If all candidates models fit poorly, AIC will not give any notice of this
