Robustness in Bayesian nonparametrics

We consider Bayesian robustness in the context of Bayesian Nonparametrics, and specifically for the Dirichlet Process prior. We show how to find an optimal procedure, based on C-minimax posterior regret (CMPR) for a class of priors C. We consider regret based on squared error loss. The neighborhood classes considered are the density ratio (DR) class and the epsilon-contamination class.