一类纯顺序过程及其在估计、排序和选择问题中的应用

IF 0.6 4区 数学 Q4 STATISTICS & PROBABILITY
Neeraj Joshi, Sudeep R. Bapat
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引用次数: 1

摘要

摘要在本文中,我们发展了一类一般的纯序列过程,并获得了预期样本量和遗憾的相关一阶和二阶渐近性。我们建立了许多估计、排序和选择问题可以在所提出的一类序列过程的帮助下处理。为了支持我们提出的顺序方法的准确性,进行了简短的模拟分析,并包括了环境研究的真实数据集,以证明其实用性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
On a class of purely sequential procedures with applications to estimation and ranking and selection problems
Abstract In this article, we develop a general class of purely sequential procedures and obtain the associated first- and second-order asymptotics for the expected sample size and regret. We establish that many estimation and ranking and selection problems can be handled with the help of the proposed class of sequential procedures. A brief simulation analysis is carried out in support of the accuracy of our proposed sequential methodology and a real data set from environment study is included to demonstrate the practical utility.
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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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