In the context of robust Bayesian analysis, we introduce a new class of prior distributions based on stochastic orders and distortion functions. We provide the new definition, its interpretation and the main properties and we also study the relationship with other classical classes of prior beliefs. We also consider Kolmogorov and Kantorovich metrics to measure the uncertainty induced by such a class, as well as its effect on the set of corresponding Bayes actions. Finally, we conclude the paper with some numerical examples.

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