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Probabilities, Laws, and Structures
This paper presents a refinement of the Bayesian Information Criterion (BIC). While the original BIC selects models on the basis of complexity and fit, the so-called prior-adapted BIC allows us to choose among statistical models that differ on three scores: fit, complexity, and model size. The prior-adapted BIC can therefore accommodate comparisons among statistical models that differ only in the admissible parameter space, e.g., for choosing among models with different constraints on thedoi:10.1007/978-94-007-3030-4_7 fatcat:q3mbp22xjzh3pgfktn6opebq5a