AI Chat Paper
Note: Please note that the following content is generated by AMiner AI. SciOpen does not take any responsibility related to this content.
{{lang === 'zh_CN' ? '文章概述' : 'Summary'}}
{{lang === 'en_US' ? '中' : 'Eng'}}
Chat more with AI
PDF (262.9 KB)
Collect
Submit Manuscript AI Chat Paper
Show Outline
Outline
Show full outline
Hide outline
Outline
Show full outline
Hide outline
Research Article | Open Access

On moment convergence for some order statistics

Jin-liang Wang1Chang-shou Deng2( )Jiang-feng Li1
Science Department of Jiujiang University, Jiangxi Province, China
Electronic and Information Engineering Department of Jiujiang University, Jiangxi Province, China
Show Author Information

Abstract

By exploring the uniform integrability of a sequence of some order statistics (OSs), we obtain the moment convergence conclusion of the sequence under some weak conditions even when the corresponding population of interest has no moment of any positive order. As an application, we embody the range of applications of a theorem presented in a reference dealing with the approximation of the difference between the moment of a sequence of normalized OSs and the corresponding moment of a standard normal distribution. By the aid of the embodied theorem, we explore the infinitesimal type of the moments of errors when we estimate some population quantiles by relative OSs. Finally, by the obtained conclusion, we can easily get a combination formula which seems hard to be proved in other methods.

CLC number: 62F10, 62G30

References

【1】
【1】
 
 
AIMS Mathematics
Pages 17061-17079

{{item.num}}

Comments on this article

Go to comment

< Back to all reports

Review Status: {{reviewData.commendedNum}} Commended , {{reviewData.revisionRequiredNum}} Revision Required , {{reviewData.notCommendedNum}} Not Commended Under Peer Review

Review Comment

Close
Close
Cite this article:
Wang J-l, Deng C-s, Li J-f. On moment convergence for some order statistics. AIMS Mathematics, 2022, 7(9): 17061-17079. https://doi.org/10.3934/math.2022938

123

Views

2

Downloads

2

Crossref

2

Web of Science

2

Scopus

Received: 25 March 2022
Revised: 26 May 2022
Accepted: 06 June 2022
Published: 15 September 2022
©2022 the Author(s), licensee AIMS Press.

This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0)