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CBM for testing multiple hypotheses with directional alternatives in sequential experiments
Sequential Analysis ( IF 0.8 ) Pub Date : 2020-05-13
K. J. Kachiashvili, J. K. Kachiashvili, I. A. Prangishvili

Constrained Bayesian methods (CBMs) and the concept of false discovery rates (FDRs) for testing directional hypotheses are considered in this article. It is shown that the direct application of CBM allows us to control FDR on the desired level for both one set of directional hypotheses and a multiple case when we consider m (m>1) sets of directional hypotheses. When guaranteeing restriction on the desired level, a Bayesian sequential method can be applied, the stopping rules of which are proper and the sequential scheme for making a decision strongly controls the mixed directional FDR. Computational results of concrete examples confirm the correctness of the theoretical outcomes.



中文翻译:

CBM用于在顺序实验中测试具有方向性选择的多个假设

本文考虑了约束贝叶斯方法(CBM)和用于测试方向假设的错误发现率(FDR)概念。结果表明,CBM的直接应用使我们能够将FDR控制在一组方向性假设和多种情况下所需的水平上>1个)方向假设集。当保证对期望水平的限制时,可以采用贝叶斯顺序法,其停止规则是适当的,并且用于做出决定的顺序方案强烈地控制了混合方向FDR。具体例子的计算结果证实了理论结果的正确性。

更新日期:2020-05-13
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