Adaptation of the Tuning Parameter in General Bayesian Inference with Robust Divergence
Adaptation of the Tuning Parameter in General Bayesian Inference with Robust Divergence
Abstract We introduce a novel methodology for robust Bayesian estimation with robust divergence (e.g., density power divergence or γ-divergence), indexed by tuning parameters. It is well known that the posterior density induced by robust divergence gives highly robust estimators against outliers if the tuning parameter is appropriately and carefully chosen. …