Posterior Cumulant Relationships in Bayesian Inference Involving the Exponential Family
涉及指数族的贝叶斯推断中后验累积量的关系
For Bayesian inference in one-parameter contexts where either the likelihood or the prior has an exponential family form, relationships are derived for posterior moments and cumulants of (functions of) both the canonical and the expectation parameters. The identities exhibited generalize the simple relationships well known in the conjugate analysis case. Applications of these results are indicated in the areas of Bayesian robustness and approximation. In particular, results…