A Random Weighting Approach for Posterior Distributions

Abstract

In Bayesian theory, calculating a posterior probability distribution is highly important but usually difficult. Therefore, some methods have been put forward to deal with such problem, among which, the most popular one is the asymptotic expansions for posterior distributions. In this paper, we propose an alternative method, named random weighting method, for scaled posterior distributions, and give an ideal convergence speed, which serves as the theoretical guarantee for methods of numerical simulations.