Keywords

#akaike_information_criterion

Akaike information criterion

Estimator for quality of a statistical model

The Akaike information criterion (AIC) is an estimator of prediction error and thereby relative quality of statistical models for a given set of data. Given a collection of models for the data, AIC estimates the quality of each model, relative to each of the other models. Thus, AIC provides a means for model selection.

Tue 2nd

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Akaike information criterion Bayesian information criterion Watanabe–Akaike information criterion Hirotugu Akaike Deviance information criterion Hannan–Quinn information criterion Akaike Focused information criterion Model selection Mallows's Cp
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