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Analytical derivation of the reference prior by sequential maximization of Shannon's mutual information in the multi-group parameter case

机译:在多组参数情况下,通过香农互信息的顺序最大化来对参考先验进行解析推导

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We provide an analytical derivation of a non-informative prior by sequential maximization of Shannon's mutual information in the multi-group parameter case assuming reasonable regularity conditions. We show that the derived prior coincides with the reference prior proposed by Berger and Bernardo, and that it can be considered as a useful alternative expression for the calculation of the reference prior. In using this expression we discuss the conditions under which an improper reference prior can be uniquely defined, i.e. when it does not depend on the particular choice of nested sequences of compact subsets of the parameter space needed for its construction. We also present the conditions under which the reference prior coincides with Jeffreys' prior.
机译:我们在合理的规则性条件下,通过在多组参数情况下按顺序最大化香农的互信息,来提供非信息先验的分析推导。我们表明,导出的先验与Berger和Bernardo提出的参考先验相符,并且可以将其视为计算参考先验的有用替代表达式。在使用该表达式时,我们讨论了可以正确定义不正确的引用先验的条件,即何时不依赖于对其构造所需的参数空间的紧凑子集的嵌套序列的特定选择。我们还提出了参考先验与杰弗里斯先验相符的条件。

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