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Commentary on Gronau and Wagenmakers
2018
Computational Brain & Behavior
The three examples Gronau and Wagenmakers (Computational Brain and Behavior, 2018; hereafter denoted G&W) use to demonstrate the limitations of Bayesian forms of leave-one-out cross validation (let us term this LOOCV) for model selection have several important properties: The true model instance is among the model classes being compared; the smaller, simpler model is a point hypothesis that in fact generates the data; the larger class contains the smaller. As G&W admit, there is a good deal of
doi:10.1007/s42113-018-0017-1
fatcat:lvtu5vcfmzdz7lt3orrivgnyd4