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The classic Schwarz Information Criterion, originally derived as an approximation to Bayes posterior probability, is widely used as a standalone likelihood-based measure of model fit. However, selection consistency is compromised when model sets partially include their parameter boundaries and when these in turn are partially shared by different models. This happens, for example, where sets represent...
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