Loss Functions for Set Estimations

Approaches to set estimation based on a decision-theoretic formulation have usually used a loss function that is a linear combination of volume and coverage probability. Such loss functions can suffer from paradoxical behavior of the Bayes rules, and thus may not be appropriate. We investigate the behavior of optimal set estimators for different classes of loss functions and study their decision-theoretic properties.