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Asymptotically pointwise optimal and asymptotically optimal stopping times in the Bayesian inference

机译:贝叶斯推理中的渐近点向最优和渐近最优停止时间

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摘要

The paper deals with the problem of determining asymptotically pointwise optimal and asymptotically optimal stopping times in the Bayesian inference. The sufficient conditions are given for a family of stopping times to be asymptotically pointwise optimal and asymptotically optimal with respect to a continuous time process. As an example a sequential estimation of the intensity of the Poisson process is considered. Under a gamma prior distribution, an asymptotically pointwise optimal and asymptotically optimal rule is given using a LINEX loss function and the cost c per unit time.
机译:本文讨论了在贝叶斯推理中确定渐近点式最优和渐近最优停止时间的问题。给出了足够的条件,以使一系列停止时间相对于连续时间过程渐近地逐点最优和渐近最优。作为示例,考虑了泊松过程强度的顺序估计。在伽玛先验分布下,使用LINEX损失函数和每单位时间的成本c给出了渐近点向最优和渐近最优规则。

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