Bayesian robustness on constrained density band classes

摘要

An interesting class in Bayesian robustness is a ‘band’ of priors: its flexibility allows for different tail behaviours while excluding point masses. In this paper, we consider density band classes of priors with additional constraints modelling different available prior information: quantiles, moments, constraints derived from the probability of observables or from the dependence structure in a multidimensional setting. The proposed techniques allow us to obtain the range of quantities of interest that are not linear or ratio linear functionals. Numerical examples are provi