Rejoinder: More Limitations of Bayesian Leave-One-Out Cross-Validation
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| Publication date | 03-2019 |
| Journal | Computational Brain & Behavior |
| Volume | Issue number | 2 | 1 |
| Pages (from-to) | 35-47 |
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| Abstract | We recently discussed several limitations of Bayesian leave-one-out cross-validation (LOO) for model selection. Our contribution attracted three thought-provoking commentaries. In this rejoinder, we address each of the commentaries and identify several additional limitations of LOO-based methods such as Bayesian stacking. We focus on differences between LOO-based methods versus approaches that consistently use Bayes’ rule for both parameter estimation and model comparison. We conclude that LOO-based methods do not align satisfactorily with the epistemic goal of mathematical psychology. |
| Document type | Article |
| Note | In special issue: Leave-one-out Cross-Validation, and Issues in Practical Model Selection. |
| Language | English |
| Published at | https://doi.org/10.1007/s42113-018-0022-4 |
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Gronau-Wagenmakers2019_Article_RejoinderMoreLimitationsOfBaye
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