Invariance Properties of Density Ratio Priors

Abstract

Density ratio neighborhoods are classes of probabilities that are used in robust Bayesian inference. These classes are invariant under Bayesian updating and marginalization. This makes them computationally convenient in robust Bayesian inference. We show that this is the unique class of probabilities that has these invariance properties. Aside from its theoretical value, this result has computational implications as well.