Sprecher
Eric-Jan Wagenmakers
Beschreibung
In Bayesian model selection, the Ockham factor is the extent to which the maximum likelihood
needs to be discounted to attain a fair assessment of a model's predictive performance. As a correction for selection, the Ockham factor quantifies the amount of prior mass that was wasted
on parameter values that are undercut by the data. In this talk I will outline several complementary perspectives on the Ockham factor, and suggest that, outside of the domain of physics, its
conceptual benefits have been underappreciated.