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Correcting the corrected AIC

Author

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  • DelSole, Timothy
  • Tippett, Michael K.

Abstract

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.

Suggested Citation

  • DelSole, Timothy & Tippett, Michael K., 2021. "Correcting the corrected AIC," Statistics & Probability Letters, Elsevier, vol. 173(C).
    • Handle: RePEc:eee:stapro:v:173:y:2021:i:c:s0167715221000262
    DOI: 10.1016/j.spl.2021.109064
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    References listed on IDEAS

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    1. Saharon Rosset & Ryan J. Tibshirani, 2020. "From Fixed-X to Random-X Regression: Bias-Variance Decompositions, Covariance Penalties, and Prediction Error Estimation," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 115(529), pages 138-151, January.
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