边频多边形的一致强相合性和渐近正态率

IF 1.2 4区 数学 Q2 STATISTICS & PROBABILITY
Mengmei Xi, Chunhua Wang, Xuejun Wang
{"title":"边频多边形的一致强相合性和渐近正态率","authors":"Mengmei Xi, Chunhua Wang, Xuejun Wang","doi":"10.1080/02331888.2023.2268314","DOIUrl":null,"url":null,"abstract":"AbstractIn this paper, we primarily focus on the edge frequency polygon estimator of f(x), which represents the probability density function of a sequence of φ-mixing random variables {Xi,i≥1}. We establish the uniformly strong consistency and the convergence rate of asymptotic normality for the edge frequency polygon estimator under suitable conditions. Notably, the convergence rate achieves O(n−1/6), which is more precise compared to the corresponding rate mentioned in the existing literature. Additionally, we present simulation studies to validate the theoretical results.Keywords: Berry–Esseen boundsuniformly strong consistencydensity functionedge frequency polygon estimatorMathematical Subject Classifications: 60E0562G20 AcknowledgementsThe authors are most grateful to the Editor and anonymous referee for carefully reading the manuscript and valuable suggestions which helped in improving an earlier version of this paper.Disclosure statementNo potential conflict of interest was reported by the author(s).Additional informationFundingSupported by the National Social Science Foundation of China (22BTJ059), the National Natural Science Foundation of China (12201600), and the Natural Science Foundation of Anhui Province (2108085MA06), and the Postdoctoral Science Foundation of China (2022M713056).","PeriodicalId":54358,"journal":{"name":"Statistics","volume":"120 1","pages":"0"},"PeriodicalIF":1.2000,"publicationDate":"2023-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Uniformly strong consistency and the rates of asymptotic normality for the edge frequency polygons\",\"authors\":\"Mengmei Xi, Chunhua Wang, Xuejun Wang\",\"doi\":\"10.1080/02331888.2023.2268314\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"AbstractIn this paper, we primarily focus on the edge frequency polygon estimator of f(x), which represents the probability density function of a sequence of φ-mixing random variables {Xi,i≥1}. We establish the uniformly strong consistency and the convergence rate of asymptotic normality for the edge frequency polygon estimator under suitable conditions. Notably, the convergence rate achieves O(n−1/6), which is more precise compared to the corresponding rate mentioned in the existing literature. Additionally, we present simulation studies to validate the theoretical results.Keywords: Berry–Esseen boundsuniformly strong consistencydensity functionedge frequency polygon estimatorMathematical Subject Classifications: 60E0562G20 AcknowledgementsThe authors are most grateful to the Editor and anonymous referee for carefully reading the manuscript and valuable suggestions which helped in improving an earlier version of this paper.Disclosure statementNo potential conflict of interest was reported by the author(s).Additional informationFundingSupported by the National Social Science Foundation of China (22BTJ059), the National Natural Science Foundation of China (12201600), and the Natural Science Foundation of Anhui Province (2108085MA06), and the Postdoctoral Science Foundation of China (2022M713056).\",\"PeriodicalId\":54358,\"journal\":{\"name\":\"Statistics\",\"volume\":\"120 1\",\"pages\":\"0\"},\"PeriodicalIF\":1.2000,\"publicationDate\":\"2023-10-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Statistics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1080/02331888.2023.2268314\",\"RegionNum\":4,\"RegionCategory\":\"数学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"STATISTICS & PROBABILITY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Statistics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1080/02331888.2023.2268314","RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"STATISTICS & PROBABILITY","Score":null,"Total":0}
引用次数: 0

摘要

在适当的条件下,给出了边频多边形估计的一致强相合性和渐近正态性的收敛速度。值得注意的是,收敛速度达到了O(n−1/6),与已有文献中相应的收敛速度相比,收敛速度更加精确。此外,我们提出了仿真研究来验证理论结果。关键词:Berry-Esseen界均匀强一致性密度函数边缘频率多边形估计数学学科分类:60E0562G20致谢作者非常感谢编辑和匿名审稿人仔细阅读稿件并提出宝贵意见,帮助改进了本文的早期版本。披露声明作者未报告潜在的利益冲突。项目资助:国家社会科学基金项目(22BTJ059)、国家自然科学基金项目(12201600)、安徽省自然科学基金项目(2108085MA06)、中国博士后科学基金项目(2022M713056)。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Uniformly strong consistency and the rates of asymptotic normality for the edge frequency polygons
AbstractIn this paper, we primarily focus on the edge frequency polygon estimator of f(x), which represents the probability density function of a sequence of φ-mixing random variables {Xi,i≥1}. We establish the uniformly strong consistency and the convergence rate of asymptotic normality for the edge frequency polygon estimator under suitable conditions. Notably, the convergence rate achieves O(n−1/6), which is more precise compared to the corresponding rate mentioned in the existing literature. Additionally, we present simulation studies to validate the theoretical results.Keywords: Berry–Esseen boundsuniformly strong consistencydensity functionedge frequency polygon estimatorMathematical Subject Classifications: 60E0562G20 AcknowledgementsThe authors are most grateful to the Editor and anonymous referee for carefully reading the manuscript and valuable suggestions which helped in improving an earlier version of this paper.Disclosure statementNo potential conflict of interest was reported by the author(s).Additional informationFundingSupported by the National Social Science Foundation of China (22BTJ059), the National Natural Science Foundation of China (12201600), and the Natural Science Foundation of Anhui Province (2108085MA06), and the Postdoctoral Science Foundation of China (2022M713056).
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
Statistics
Statistics 数学-统计学与概率论
CiteScore
1.00
自引率
0.00%
发文量
59
审稿时长
12 months
期刊介绍: Statistics publishes papers developing and analysing new methods for any active field of statistics, motivated by real-life problems. Papers submitted for consideration should provide interesting and novel contributions to statistical theory and its applications with rigorous mathematical results and proofs. Moreover, numerical simulations and application to real data sets can improve the quality of papers, and should be included where appropriate. Statistics does not publish papers which represent mere application of existing procedures to case studies, and papers are required to contain methodological or theoretical innovation. Topics of interest include, for example, nonparametric statistics, time series, analysis of topological or functional data. Furthermore the journal also welcomes submissions in the field of theoretical econometrics and its links to mathematical statistics.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信