Inadmissibility of the corrected Akaike information criterion

Takeru Matsuda

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arXiv · 2211.09326

Inadmissibility of the corrected Akaike information criterion

Takeru Matsuda

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Abstract

For the multivariate linear regression model with unknown covariance, the corrected Akaike information criterion is the minimum variance unbiased estimator of the expected Kullback--Leibler discrepancy. In this study, based on the loss estimation framework, we show its inadmissibility as an estimator of the Kullback--Leibler discrepancy itself, instead of the expected Kullback--Leibler discrepancy. We provide improved estimators of the Kullback--Leibler discrepancy that work well in reduced-rank situations and examine their performance numerically.

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Takeru Matsuda. 2022-11-17. Inadmissibility of the corrected Akaike information criterion. https://arxiv.org/abs/2211.09326

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