Recent Methodological Advances in Robust Bayesian Inference
Larry Wasserman · 1992
Abstract Robust Bayesian inference is an approach to statistics that uses classes of models and priors. To use this approach, we must choose appropriate classes of priors and models, compute bounds on posterior expectations, succinctly summarize inferences and graphically display the results. I will discuss some recent attempts to address these issues.