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基于信息更丰富样本的单调经验贝叶斯估计AI 解读

An empirical Bayes estimator is constructed for the case of nonidentical components coming from an exponential family of distributions that is closed under convolution. Examples are the normal, Poisson, and binomial distributions. The construction is based on Robbins' approach to empirical Bayes estimation and generalizes results of O'Bryan and Stijnen and Van Houwelingen. The method is elaborated for the normal and Poisson case, and examples are given that show that this…

连续单参数指数族经验贝叶斯检验的渐近行为AI 解读

Several authors have proposed empirical Bayes tests (EBT) for the continuous one-parameter exponential family for the case that the prior distribution is completely unspecified. They investigated the convergence rate of the (unconditional) Bayes risk, and gave upper bounds for this convergence rate. In this paper it is proposed to study the convergence of the conditional Bayes risk. A method is presented which makes it possible to derive the exact convergence rate of the…