Akaike's information criterion

AIC developed by Hirotsugu Akaike under the name of “An Information Criterion” (AIC) in 1971 and proposed in Akaike (1974), is a measure of the goodness of fit of an estimated statistical model. It is developed in effect offering a relative measure of the information lost when a given model is used to describe reality. The AIC is an operational way of trading off the complexity of an estimated model against how well the model fits the data.

In the general case, the AIC is:

AIC=-2ln(L(x))+2K