估计多元正态总体的平均向量的k阶段程序

IF 0.6 4区数学 Q4 STATISTICS & PROBABILITY Sequential Analysis-Design Methods and Applications Pub Date : 2019-07-03 DOI:10.1080/07474946.2019.1648926

Ajit Chaturvedi, Sudeep R. Bapat, Neeraj Joshi

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引用次数: 3

摘要

摘要在本文中，我们使用k阶序列估计程序估计了多元正态总体的平均向量。进行了点估计和置信区间估计。在这两种情况下都得到了二阶近似。在最小风险点估计为的情况下，实现了负后悔。

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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A k-stage procedure for estimating the mean vector of a multivariate normal population

Abstract In this article, we have estimated the mean vector of a multivariate normal population by using a k-stage sequential estimation procedure. Point estimation as well as confidence region estimation is done. Second-order approximations are obtained in both the cases. In case of minimum risk point estimation of , negative regret is achieved.

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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.