Second-order approximations of a robust sequential procedure in Bayes sequential estimation

IF 0.6 4区 数学 Q4 STATISTICS & PROBABILITY Sequential Analysis-Design Methods and Applications Pub Date : 2020-10-01 DOI:10.1080/07474946.2020.1826785
Leng-Cheng Hwang
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Abstract

Abstract The problem of sequential estimation of the mean with quadratic loss and fixed cost per observation is considered within the Bayesian framework. A robust sequential procedure, not depending on the distributions of outcome variables and the prior, in the Bayes sequential estimation is investigated. In the present article, the second-order approximations to the expected sample size and the Bayes risk of the robust sequential procedure are obtained for the arbitrary distributions of outcome variables and the prior. The second-order efficiency is further discussed in an example.
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Bayes序列估计中稳健序列过程的二阶近似
摘要在贝叶斯框架下考虑了具有二次损失和每次观测固定成本的均值的序列估计问题。研究了贝叶斯序列估计中不依赖于结果变量和先验分布的稳健序列过程。在本文中,对于结果变量和先验的任意分布,获得了稳健序列过程的预期样本量和贝叶斯风险的二阶近似。在一个例子中进一步讨论了二阶效率。
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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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