Thomas Lumley • 7/22/2025

AIC and combined discrete/continuous models

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The article discusses a technical statistical problem: comparing models with discrete vs. continuous likelihoods using Akaike Information Criterion (AIC). It explains that such comparisons are meaningless because probability mass functions and density functions are fundamentally incommensurable, using examples like Beta vs. binomial or Normal vs. binomial models to illustrate the issue.

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#Model Comparison #R #Statistical Modeling
AIC and combined discrete/continuous models

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