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An improved empirical Bayes test for positive exponential families

机译:改进的正指数家庭经验贝叶斯检验

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摘要

We exhibit an empirical Bayes test δ*n for a decision problem using a linear error loss in a class of positive exponential families. This empirical Bayes test δ*n possesses the asymptotic optimality, and its associated regret converges to zero with rate n−1(ln n)6 This rate of convergence improves the previous results in the literature in the sense that a faster rate of convergence is achieved under much weaker conditions. Examples are presented to illustrate the performance of the empirical Bayes test δ*n
机译:对于一类正指数族中的线性误差,我们展示了针对决策问题的经验贝叶斯检验δ* n。该经验贝叶斯检验δ* n具有渐近最优性,并且其相关联的后悔以速率n-1(ln n)6收敛至零。在某种意义上,这种收敛速度改善了文献中的先前结果,因为收敛速度更快。在弱得多的条件下实现。举例说明了经验贝叶斯检验δ* n的性能。

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