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贝叶斯分析中有界影响的一个注记AI 解读

Let χ be a single observation from a distribution having unknown location parameter θ. Dawid (1973) provided sufficient conditions for the posterior distribution of θ to approach the prior distribution as χ tends to infinity, so that an outlier has bounded and vanishing influence on the posterior distribution. We present a result closely related to Dawid's theorem. This enables us to consider priors and likelihoods for the location problem which have bounded but nonvanishing…

指数族贝叶斯推断中的后验累积量关系AI 解读

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…