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. 2023 Sep 12;19(2):2251830. doi: 10.1080/21645515.2023.2251830

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© 2023 The Author(s). Published with license by Taylor & Francis Group, LLC.

This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial License (http://creativecommons.org/licenses/by-nc/4.0/), which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited. The terms on which this article has been published allow the posting of the Accepted Manuscript in a repository by the author(s) or with their consent.

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Figure 4. — A comparison of error estimate from additive randomization (denoted as “additive”), AIC, BIC, the true prediction error (denoted as “test”), and training error (denoted as “train”) in example 2. Panels a and B shows the results for $β = 0$ and $β = 1,$ respectively as we vary the subset size ( $s)$ . The prediction performance in this example is not able to be tracked by the training error, AIC or BIC.