 Solution (source code)

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= Solution

For a likelihood $L(\theta)$ with $k$ estimated parameters, the <Akaike information criterion> is
$$
\operatorname{AIC}=-2\log L(\widehat\theta)+2k,
$$
where $\widehat\theta$ is the <maximum-likelihood estimator>. Among likelihoods for the same observed response and reference measure, smaller AIC estimates smaller expected out-of-sample <Kullback-Leibler divergence> up to a model-independent constant.

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