Limitations of “Limitations of Bayesian Leave-one-out Cross-Validation for Model Selection”

26Citations
Citations of this article
128Readers
Mendeley users who have this article in their library.

This article is free to access.

Abstract

In an earlier article in this journal, Gronau and Wagenmakers (2018) discuss some problems with leave-one-out cross-validation (LOO) for Bayesian model selection. However, the variant of LOO that Gronau and Wagenmakers discuss is at odds with a long literature on how to use LOO well. In this discussion, we discuss the use of LOO in practical data analysis, from the perspective that we need to abandon the idea that there is a device that will produce a single-number decision rule.

Cite

CITATION STYLE

APA

Vehtari, A., Simpson, D. P., Yao, Y., & Gelman, A. (2019). Limitations of “Limitations of Bayesian Leave-one-out Cross-Validation for Model Selection.” Computational Brain and Behavior, 2(1), 22–27. https://doi.org/10.1007/s42113-018-0020-6

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free