A key inequality for lower bound formulas for lattice event probabilities

IF 0.6 4区 数学 Q4 STATISTICS & PROBABILITY Sequential Analysis-Design Methods and Applications Pub Date : 2021-10-02 DOI:10.1080/07474946.2021.2010417
B. Levin, C. Leu
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引用次数: 1

Abstract

Abstract We introduce and discuss some key inequalities that underlie the lower bound formula for the probability of lattice events in the Levin-Robbins-Leu family of sequential subset selection procedures for binary outcomes. The present work combines the notion of lattice events—as previously discussed for the nonadaptive member of the family—with the positive cumulative sum property for the adaptive members—as previously discussed for the special lattice event of correct selection, thereby extending the key inequality to its broadest scope.
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晶格事件概率下界公式的一个关键不等式
摘要本文引入并讨论了二元结果序列子集选择程序Levin-Robbins-Leu族中格事件概率下界公式的几个关键不等式。目前的工作结合了晶格事件的概念-如前所述的非适应性家庭成员与适应性成员的正累积和性质-如前所述的正确选择的特殊晶格事件,从而将关键不等式扩展到最广泛的范围。
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来源期刊
CiteScore
1.40
自引率
12.50%
发文量
20
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.
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