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

M. Stone
Journal of the Royal Statistical Society. Series B (Methodological)
Vol. 39, No. 1 (1977), pp. 44-47
Published by: Wiley for the Royal Statistical Society
Stable URL: http://www.jstor.org/stable/2984877
Page Count: 4
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Since scans are not currently available to screen readers, please contact JSTOR User Support for access. We'll provide a PDF copy for your screen reader.
An Asymptotic Equivalence of Choice of Model by Cross-Validation and Akaike's Criterion
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Abstract

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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