CBM for testing multiple hypotheses with directional alternatives in sequential experiments

IF 0.6 4区数学 Q4 STATISTICS & PROBABILITY

Sequential Analysis-Design Methods and Applications Pub Date : 2020-01-02 DOI:10.1080/07474946.2020.1727166

K. Kachiashvili, J. K. Kachiashvili, I. Prangishvili

引用次数: 2

Abstract

Abstract 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 () 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.

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CBM用于序列实验中具有方向选择的多个假设的检验

摘要本文考虑了用于检验方向性假设的约束贝叶斯方法（CBM）和错误发现率（FDRs）的概念。研究表明，当我们考虑（）组方向假设时，CBM的直接应用使我们能够将一组方向假设和多个情况的FDR控制在所需水平上。当保证对期望水平的限制时，可以应用贝叶斯序列方法，其停止规则是适当的，并且用于做出决策的序列方案强烈地控制混合方向FDR。具体算例的计算结果验证了理论结果的正确性。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Sequential Analysis-Design Methods and Applications STATISTICS & PROBABILITY-

CiteScore

1.40

自引率

12.50%

发文量

期刊介绍： The purpose of Sequential Analysis is to contribute to theoretical and applied aspects of sequential methodologies in all areas of statistical science. Published papers highlight the development of new and important sequential approaches. Interdisciplinary articles that emphasize the methodology of practical value to applied researchers and statistical consultants are highly encouraged. Papers that cover contemporary areas of applications including animal abundance, bioequivalence, communication science, computer simulations, data mining, directional data, disease mapping, environmental sampling, genome, imaging, microarrays, networking, parallel processing, pest management, sonar detection, spatial statistics, tracking, and engineering are deemed especially important. Of particular value are expository review articles that critically synthesize broad-based statistical issues. Papers on case-studies are also considered. All papers are refereed.