On limiting posterior distributions

Abstract

In this article, a theorem is developed on limiting posterior distributions of asymptotically pivotal quantities. The theorem, called the posterior limit theorem (PLT), provides a set of sufficient conditions for an asymptotically pivotal quantity to have a limiting posterior distribution coincident with its limiting sampling distribution. It can be applied to the real data analysis without any specified functional form of likelihood. We present various illustrative applications of our theorem.