基于k记录值的极值指数的极大似然估计

IF 1 Q3 STATISTICS & PROBABILITY
Abderrahim Louzaoui, Mohamed El Arrouchi
{"title":"基于k记录值的极值指数的极大似然估计","authors":"Abderrahim Louzaoui, Mohamed El Arrouchi","doi":"10.1155/2020/5497413","DOIUrl":null,"url":null,"abstract":"In this paper, we study the existence and consistency of the maximum likelihood estimator of the extreme value index based on - record values. Following the method used by Drees et al. (2004) and Zhou (2009), we prove that the likelihood equations, in terms of - record values, eventually admit a strongly consistent solution without any restriction on the extreme value index, which is not the case in the aforementioned studies.","PeriodicalId":44760,"journal":{"name":"Journal of Probability and Statistics","volume":" ","pages":"1-9"},"PeriodicalIF":1.0000,"publicationDate":"2020-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1155/2020/5497413","citationCount":"1","resultStr":"{\"title\":\"On the Maximum Likelihood Estimation of Extreme Value Index Based on k-Record Values\",\"authors\":\"Abderrahim Louzaoui, Mohamed El Arrouchi\",\"doi\":\"10.1155/2020/5497413\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, we study the existence and consistency of the maximum likelihood estimator of the extreme value index based on - record values. Following the method used by Drees et al. (2004) and Zhou (2009), we prove that the likelihood equations, in terms of - record values, eventually admit a strongly consistent solution without any restriction on the extreme value index, which is not the case in the aforementioned studies.\",\"PeriodicalId\":44760,\"journal\":{\"name\":\"Journal of Probability and Statistics\",\"volume\":\" \",\"pages\":\"1-9\"},\"PeriodicalIF\":1.0000,\"publicationDate\":\"2020-06-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1155/2020/5497413\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Probability and Statistics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1155/2020/5497413\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"STATISTICS & PROBABILITY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Probability and Statistics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1155/2020/5497413","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"STATISTICS & PROBABILITY","Score":null,"Total":0}
引用次数: 1

摘要

本文研究了基于非记录值的极值指标的极大似然估计的存在性和相合性。根据Drees et al.(2004)和Zhou(2009)的方法,我们证明了在不受极值指标限制的情况下,就-记录值而言,似然方程最终存在强一致解,而上述研究并非如此。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
On the Maximum Likelihood Estimation of Extreme Value Index Based on k-Record Values
In this paper, we study the existence and consistency of the maximum likelihood estimator of the extreme value index based on - record values. Following the method used by Drees et al. (2004) and Zhou (2009), we prove that the likelihood equations, in terms of - record values, eventually admit a strongly consistent solution without any restriction on the extreme value index, which is not the case in the aforementioned studies.
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
Journal of Probability and Statistics
Journal of Probability and Statistics STATISTICS & PROBABILITY-
自引率
0.00%
发文量
14
审稿时长
18 weeks
×
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