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The standard correction to Akaike’s Information Criterion, AICc, assumes the same predictors for training and verification and therefore underestimates prediction error for random predictors. A corrected AIC for regression models containing a mix of random and fixed predictors is derived.
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DelSole et al. (2021) studied this question.
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