An Asymptotic Equivalence of Choice of Model by Cross-Validation and Akaike's Criterion

1977/09/01 by M. Stone · 10 citations
Engineering · Mathematics · #Engineering Applied Research #Akaike information criterion #Equivalence (formal languages) #Bayesian information criterion #Mathematics #Cross-validation #Statistics #Econometrics #Applied mathematics #Pure mathematics

paper · doi:10.1111/j.2517-6161.1977.tb01603.x

openalex publication_date 1977/09/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/05

Abstract

Summary A logarithmic assessment of the performance of a predicting density is found to lead to asymptotic equivalence of choice of model by cross-validation and Akaike's criterion, when maximum likelihood estimation is used within each model.

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